INSERT INTO `papers` (`id`, `ano`, `journal`, `titulo`, `autores`, `afiliacao`, `pais`, `citacoes`, `palavra_chave`, `categorias`, `doi`, `pubmed`, `abstract`) VALUES
(87314, 2015, 'plos', 'Pluripotency, Differentiation, and Reprogramming: A Gene Expression Dynamics Model with Epigenetic Feedback Regulation', 'Miyamoto, Tadashi|Furusawa, Chikara|Kaneko, Kunihiko', 'Department of Basic Science, The University of Tokyo, Meguro-ku, Tokyo, Japan.|Quantitative Biology Center (QBiC), RIKEN, Suita, Osaka, Japan.|Department of Basic Science, The University of Tokyo, Meguro-ku, Tokyo, Japan.', 'Japan|Japan|Japan', 30, 'Cell Differentiation|Cellular Reprogramming|Computational Biology|Embryonic Stem Cells|Epigenesis, Genetic|Feedback, Physiological|Gene Expression Regulation|Models, Genetic|Pluripotent Stem Cells', 'Journal Article', '10.1371/journal.pcbi.1004476', '26308610', 'Embryonic stem cells exhibit pluripotency: they can differentiate into all types of somatic cells. Pluripotent genes such as Oct4 and Nanog are activated in the pluripotent state, and their expression decreases during cell differentiation. Inversely, expression of differentiation genes such as Gata6 and Gata4 is promoted during differentiation. The gene regulatory network controlling the expression of these genes has been described, and slower-scale epigenetic modifications have been uncovered. Although the differentiation of pluripotent stem cells is normally irreversible, reprogramming of cells can be experimentally manipulated to regain pluripotency via overexpression of certain genes. Despite these experimental advances, the dynamics and mechanisms of differentiation and reprogramming are not yet fully understood. Based on recent experimental findings, we constructed a simple gene regulatory network including pluripotent and differentiation genes, and we demonstrated the existence of pluripotent and differentiated states from the resultant dynamical-systems model. Two differentiation mechanisms, interaction-induced switching from an expression oscillatory state and noise-assisted transition between bistable stationary states, were tested in the model. The former was found to be relevant to the differentiation process. We also introduced variables representing epigenetic modifications, which controlled the threshold for gene expression. By assuming positive feedback between expression levels and the epigenetic variables, we observed differentiation in expression dynamics. Additionally, with numerical reprogramming experiments for differentiated cells, we showed that pluripotency was recovered in cells by imposing overexpression of two pluripotent genes and external factors to control expression of differentiation genes. Interestingly, these factors were consistent with the four Yamanaka factors, Oct4, Sox2, Klf4, and Myc, which were necessary for the establishment of induced pluripotent stem cells. These results, based on a gene regulatory network and expression dynamics, contribute to our wider understanding of pluripotency, differentiation, and reprogramming of cells, and they provide a fresh viewpoint on robustness and control during development. '),
(87315, 2015, 'plos', 'Prediction of Functionally Important Phospho-Regulatory Events in Xenopus laevis Oocytes', 'Johnson, Jeffrey R|Santos, Silvia D|Johnson, Tasha|Pieper, Ursula|Strumillo, Marta|Wagih, Omar|Sali, Andrej|Krogan, Nevan J|Beltrao, Pedro', 'Department of Cellular and Molecular Pharmacology, University of California, San Francisco, San Francisco, California, United States of America.|Quantitative Cell Biology group, MRC Clinical Sciences Centre, Imperial College, London, United Kingdom.|Department of Cellular and Molecular Pharmacology, University of California, San Francisco, San Francisco, California, United States of America.|Department of Bioengineering and Therapeutic Sciences, California Institute for Quantitative Biosciences, Byers Hall at Mission Bay, University of California, San Francisco, San Francisco, California, United States of America, Department of Pharmaceutical Chemistry, California Institute for Quantitative Biosciences, Byers Hall at Mission Bay, University of California, San Francisco, San Francisco, California, United States of America.|European Molecular Biology Laboratory, Genome Biology Unit, Heidelberg, Germany and European Bioinformatics Institute (EMBL-EBI), Cambridge, United Kingdom.|European Molecular Biology Laboratory, Genome Biology Unit, Heidelberg, Germany and European Bioinformatics Institute (EMBL-EBI), Cambridge, United Kingdom.|Department of Bioengineering and Therapeutic Sciences, California Institute for Quantitative Biosciences, Byers Hall at Mission Bay, University of California, San Francisco, San Francisco, California, United States of America, Department of Pharmaceutical Chemistry, California Institute for Quantitative Biosciences, Byers Hall at Mission Bay, University of California, San Francisco, San Francisco, California, United States of America.|Department of Cellular and Molecular Pharmacology, University of California, San Francisco, San Francisco, California, United States of America, Gladstone Institutes, San Francisco, California, United States of America.|European Molecular Biology Laboratory, Genome Biology Unit, Heidelberg, Germany and European Bioinformatics Institute (EMBL-EBI), Cambridge, United Kingdom, iBiMED and Department of Health Sciences, University of Aveiro, Aveiro, Portugal.', 'United States|United Kingdom|United States|United States|Germany|Germany|United States|United States', 0, 'Animals|Female|Mass Spectrometry|Models, Molecular|Oocytes|Phosphoproteins|Phosphorylation|Protein Interaction Maps|Proteomics|Xenopus laevis', 'Journal Article', '10.1371/journal.pcbi.1004362', '26312481', 'The African clawed frog Xenopus laevis is an important model organism for studies in developmental and cell biology, including cell-signaling. However, our knowledge of X. laevis protein post-translational modifications remains scarce. Here, we used a mass spectrometry-based approach to survey the phosphoproteome of this species, compiling a list of 2636 phosphosites. We used structural information and phosphoproteomic data for 13 other species in order to predict functionally important phospho-regulatory events. We found that the degree of conservation of phosphosites across species is predictive of sites with known molecular function. In addition, we predicted kinase-protein interactions for a set of cell-cycle kinases across all species. The degree of conservation of kinase-protein interactions was found to be predictive of functionally relevant regulatory interactions. Finally, using comparative protein structure models, we find that phosphosites within structured domains tend to be located at positions with high conformational flexibility. Our analysis suggests that a small class of phosphosites occurs in positions that have the potential to regulate protein conformation. '),
(87316, 2015, 'plos', 'Escher: A Web Application for Building, Sharing, and Embedding Data-Rich Visualizations of Biological Pathways', 'King, Zachary A|Dräger, Andreas|Ebrahim, Ali|Sonnenschein, Nikolaus|Lewis, Nathan E|Palsson, Bernhard O', 'Department of Bioengineering, University of California, San Diego, La Jolla, California, United States of America.|Department of Bioengineering, University of California, San Diego, La Jolla, California, United States of America, Center for Bioinformatics Tuebingen (ZBIT), University of Tuebingen, Tübingen, Germany.|Department of Bioengineering, University of California, San Diego, La Jolla, California, United States of America.|Novo Nordisk Foundation Center for Biosustainability, Technical University of Denmark, Lyngby, Denmark.|Department of Pediatrics, University of California, San Diego, La Jolla, California, United States of America.|Department of Bioengineering, University of California, San Diego, La Jolla, California, United States of America, Department of Pediatrics, University of California, San Diego, La Jolla, California, United States of America.', 'United States|Germany|United States|Denmark|United States|United States', 104, 'Computational Biology|Computer Graphics|Image Processing, Computer-Assisted|Internet|Metabolic Networks and Pathways|Models, Biological|Signal Transduction|Software|Transcriptome', 'Journal Article', '10.1371/journal.pcbi.1004321', '26313928', 'Escher is a web application for visualizing data on biological pathways. Three key features make Escher a uniquely effective tool for pathway visualization. First, users can rapidly design new pathway maps. Escher provides pathway suggestions based on user data and genome-scale models, so users can draw pathways in a semi-automated way. Second, users can visualize data related to genes or proteins on the associated reactions and pathways, using rules that define which enzymes catalyze each reaction. Thus, users can identify trends in common genomic data types (e.g. RNA-Seq, proteomics, ChIP)--in conjunction with metabolite- and reaction-oriented data types (e.g. metabolomics, fluxomics). Third, Escher harnesses the strengths of web technologies (SVG, D3, developer tools) so that visualizations can be rapidly adapted, extended, shared, and embedded. This paper provides examples of each of these features and explains how the development approach used for Escher can be used to guide the development of future visualization tools.'),
(87317, 2015, 'plos', 'Discovery of Drug Synergies in Gastric Cancer Cells Predicted by Logical Modeling', 'Flobak, Åsmund|Baudot, Anaïs|Remy, Elisabeth|Thommesen, Liv|Thieffry, Denis|Kuiper, Martin|Lægreid, Astrid', 'Department of Cancer Research and Molecular Medicine, Norwegian University of Science and Technology (NTNU), Trondheim, Norway.|Aix Marseille Université, CNRS, Centrale Marseille, I2M, UMR 7373, Marseille, France.|Aix Marseille Université, CNRS, Centrale Marseille, I2M, UMR 7373, Marseille, France.|Department of Cancer Research and Molecular Medicine, Norwegian University of Science and Technology (NTNU), Trondheim, Norway, Faculty of Technology, Sør-Trøndelag University College, Trondheim, Norway.|Institut de Biologie de lEcole Normale Supérieure (IBENS), Paris, France, CNRS UMR 8197, Paris, France, INSERM U1024, Paris, France.|Department of Biology, Norwegian University of Science and Technology (NTNU), Trondheim, Norway.|Department of Cancer Research and Molecular Medicine, Norwegian University of Science and Technology (NTNU), Trondheim, Norway.', 'Norway|France|France|Norway|France|Norway|Norway', 0, 'Antineoplastic Agents|Cell Line, Tumor|Cell Proliferation|Computational Biology|Computer Simulation|Drug Discovery|Drug Synergism|Humans|Models, Biological|Stomach Neoplasms', 'Journal Article', '10.1371/journal.pcbi.1004426', '26317215', 'Discovery of efficient anti-cancer drug combinations is a major challenge, since experimental testing of all possible combinations is clearly impossible. Recent efforts to computationally predict drug combination responses retain this experimental search space, as model definitions typically rely on extensive drug perturbation data. We developed a dynamical model representing a cell fate decision network in the AGS gastric cancer cell line, relying on background knowledge extracted from literature and databases. We defined a set of logical equations recapitulating AGS data observed in cells in their baseline proliferative state. Using the modeling software GINsim, model reduction and simulation compression techniques were applied to cope with the vast state space of large logical models and enable simulations of pairwise applications of specific signaling inhibitory chemical substances. Our simulations predicted synergistic growth inhibitory action of five combinations from a total of 21 possible pairs. Four of the predicted synergies were confirmed in AGS cell growth real-time assays, including known effects of combined MEK-AKT or MEK-PI3K inhibitions, along with novel synergistic effects of combined TAK1-AKT or TAK1-PI3K inhibitions. Our strategy reduces the dependence on a priori drug perturbation experimentation for well-characterized signaling networks, by demonstrating that a model predictive of combinatorial drug effects can be inferred from background knowledge on unperturbed and proliferating cancer cells. Our modeling approach can thus contribute to preclinical discovery of efficient anticancer drug combinations, and thereby to development of strategies to tailor treatment to individual cancer patients. '),
(87318, 2015, 'plos', 'Analysis of Single Locus Trajectories for Extracting In Vivo Chromatin Tethering Interactions', 'Amitai, Assaf|Toulouze, Mathias|Dubrana, Karine|Holcman, David', 'Institute for Medical Engineering & Science, The Massachusetts Institute of Technology (MIT), Cambridge, Massachusetts, United States of America.|Laboratory of genetic instability and nuclear organization, CEA, Fontenay-aux-Roses, France.|Laboratory of genetic instability and nuclear organization, CEA, Fontenay-aux-Roses, France.|IBENS, Ecole Normale Supérieure, Paris, France and Mathematical Institute, University of Oxford, Oxford, United Kingdom.', 'United States|France|France|France', 23, 'Chromatin|Computational Biology|Computer Simulation|Models, Molecular|Saccharomyces cerevisiae', 'Journal Article', '10.1371/journal.pcbi.1004433', '26317360', 'Is it possible to extract tethering forces applied on chromatin from the statistics of a single locus trajectories imaged in vivo? Chromatin fragments interact with many partners such as the nuclear membrane, other chromosomes or nuclear bodies, but the resulting forces cannot be directly measured in vivo. However, they impact chromatin dynamics and should be reflected in particular in the motion of a single locus. We present here a method based on polymer models and statistics of single trajectories to extract the force characteristics and in particular when they are generated by the gradient of a quadratic potential well. Using numerical simulations of a Rouse polymer and live cell imaging of the MAT-locus located on the yeast Saccharomyces cerevisiae chromosome III, we recover the amplitude and the distance between the observed and the interacting monomer. To conclude, the confined trajectories we observed in vivo reflect local interaction on chromatin. '),
(87319, 2015, 'plos', 'Identifying Driver Genomic Alterations in Cancers by Searching Minimum-Weight, Mutually Exclusive Sets', 'Lu, Songjian|Lu, Kevin N|Cheng, Shi-Yuan|Hu, Bo|Ma, Xiaojun|Nystrom, Nicholas|Lu, Xinghua', 'Department of Biomedical Informatics, University of Pittsburgh, Pittsburgh, Pennsylvania, United States of America.|Department of Biomedical Informatics, University of Pittsburgh, Pittsburgh, Pennsylvania, United States of America.|Department of Neurology, Northwestern Brain Tumor Institute, Center for Genetic Medicine, The Robert H. Lurie Comprehensive Cancer Center, Northwestern University Feinberg School of Medicine, Chicago, Illinois, United States of America.|Department of Neurology, Northwestern Brain Tumor Institute, Center for Genetic Medicine, The Robert H. Lurie Comprehensive Cancer Center, Northwestern University Feinberg School of Medicine, Chicago, Illinois, United States of America.|Department of Biomedical Informatics, University of Pittsburgh, Pittsburgh, Pennsylvania, United States of America.|Pittsburgh Supercomputing Center, Pittsburgh, Pennsylvania, United States of America.|Department of Biomedical Informatics, University of Pittsburgh, Pittsburgh, Pennsylvania, United States of America.', 'United States|United States|United States|United States|United States|United States|United States', 10, 'Algorithms|Computational Biology|Gene Expression Regulation, Neoplastic|Gene Regulatory Networks|Genome|Humans|Mutation|Neoplasms', 'Journal Article', '10.1371/journal.pcbi.1004257', '26317392', 'An important goal of cancer genomic research is to identify the driving pathways underlying disease mechanisms and the heterogeneity of cancers. It is well known that somatic genome alterations (SGAs) affecting the genes that encode the proteins within a common signaling pathway exhibit mutual exclusivity, in which these SGAs usually do not co-occur in a tumor. With some success, this characteristic has been utilized as an objective function to guide the search for driver mutations within a pathway. However, mutual exclusivity alone is not sufficient to indicate that genes affected by such SGAs are in common pathways. Here, we propose a novel, signal-oriented framework for identifying driver SGAs. First, we identify the perturbed cellular signals by mining the gene expression data. Next, we search for a set of SGA events that carries strong information with respect to such perturbed signals while exhibiting mutual exclusivity. Finally, we design and implement an efficient exact algorithm to solve an NP-hard problem encountered in our approach. We apply this framework to the ovarian and glioblastoma tumor data available at the TCGA database, and perform systematic evaluations. Our results indicate that the signal-oriented approach enhances the ability to find informative sets of driver SGAs that likely constitute signaling pathways. '),
(87320, 2015, 'plos', 'Task-Driven Activity Reduces the Cortical Activity Space of the Brain: Experiment and Whole-Brain Modeling', 'Ponce-Alvarez, Adrián|He, Biyu J|Hagmann, Patric|Deco, Gustavo', 'Center for Brain and Cognition, Computational Neuroscience Group, Department of Information and Communication Technologies, Universitat Pompeu Fabra, Barcelona, Spain.|National Institute of Neurological Disorders and Stroke, National Institutes of Health, Bethesda, Maryland, United States of America.|Department of Radiology, Lausanne University Hospital and University of Lausanne (CHUV-UNIL), Lausanne, Switzerland, Signal Processing Lab 5, Ecole Polytechnique Fédérale de Lausanne (EPFL), Lausanne, Switzerland.|Center for Brain and Cognition, Computational Neuroscience Group, Department of Information and Communication Technologies, Universitat Pompeu Fabra, Barcelona, Spain, Institució Catalana de la Recerca i Estudis Avançats (ICREA), Universitat Pompeu Fabra, Barcelona, Spain.', 'Spain|United States|Switzerland|Spain', 0, 'Adolescent|Adult|Cerebral Cortex|Computational Biology|Entropy|Female|Humans|Magnetic Resonance Imaging|Male|Models, Neurological|Rest|Task Performance and Analysis|Young Adult', 'Journal Article', '10.1371/journal.pcbi.1004445', '26317432', 'How a stimulus or a task alters the spontaneous dynamics of the brain remains a fundamental open question in neuroscience. One of the most robust hallmarks of task/stimulus-driven brain dynamics is the decrease of variability with respect to the spontaneous level, an effect seen across multiple experimental conditions and in brain signals observed at different spatiotemporal scales. Recently, it was observed that the trial-to-trial variability and temporal variance of functional magnetic resonance imaging (fMRI) signals decrease in the task-driven activity. Here we examined the dynamics of a large-scale model of the human cortex to provide a mechanistic understanding of these observations. The model allows computing the statistics of synaptic activity in the spontaneous condition and in putative tasks determined by external inputs to a given subset of brain regions. We demonstrated that external inputs decrease the variance, increase the covariances, and decrease the autocovariance of synaptic activity as a consequence of single node and large-scale network dynamics. Altogether, these changes in network statistics imply a reduction of entropy, meaning that the spontaneous synaptic activity outlines a larger multidimensional activity space than does the task-driven activity. We tested this models prediction on fMRI signals from healthy humans acquired during rest and task conditions and found a significant decrease of entropy in the stimulus-driven activity. Altogether, our study proposes a mechanism for increasing the information capacity of brain networks by enlarging the volume of possible activity configurations at rest and reliably settling into a confined stimulus-driven state to allow better transmission of stimulus-related information. '),
(87321, 2015, 'plos', 'An Optimal Free Energy Dissipation Strategy of the MinCDE Oscillator in Regulating Symmetric Bacterial Cell Division', 'Xiong, Liping|Lan, Ganhui', 'Department of Physics, George Washington University, Washington, D.C., United States of America.|Department of Physics, George Washington University, Washington, D.C., United States of America.', 'United States|United States', 0, 'Adenosine Triphosphate|Cell Cycle Proteins|Cell Division|Computational Biology|Computer Simulation|Escherichia coli|Escherichia coli Proteins|Models, Biological|Thermodynamics', 'Journal Article', '10.1371/journal.pcbi.1004351', '26317492', 'Sustained molecular oscillations are ubiquitous in biology. The obtained oscillatory patterns provide vital functions as timekeepers, pacemakers and spacemarkers. Models based on control theory have been introduced to explain how specific oscillatory behaviors stem from protein interaction feedbacks, whereas the energy dissipation through the oscillating processes and its role in the regulatory function remain unexplored. Here we developed a general framework to assess an oscillators regulation performance at different dissipation levels. Using the Escherichia coli MinCDE oscillator as a model system, we showed that a sufficient amount of energy dissipation is needed to switch on the oscillation, which is tightly coupled to the systems regulatory performance. Once the dissipation level is beyond this threshold, unlike stationary regulators monotonic performance-to-cost relation, excess dissipation at certain steps in the oscillating process damages the oscillators regulatory performance. We further discovered that the chemical free energy from ATP hydrolysis has to be strategically assigned to the MinE-aided MinD release and the MinD immobilization steps for optimal performance, and a higher energy budget improves the robustness of the oscillator. These results unfold a novel mode by which living systems trade energy for regulatory function. '),
(87322, 2015, 'plos', 'Modeling and Classification of Kinetic Patterns of Dynamic Metabolic Biomarkers in Physical Activity', 'Breit, Marc|Netzer, Michael|Weinberger, Klaus M|Baumgartner, Christian', 'Research Group for Clinical Bioinformatics, Institute of Electrical and Biomedical Engineering (IEBE), University for Health Sciences, Medical Informatics and Technology (UMIT), Hall in Tirol, Austria.|Research Group for Clinical Bioinformatics, Institute of Electrical and Biomedical Engineering (IEBE), University for Health Sciences, Medical Informatics and Technology (UMIT), Hall in Tirol, Austria.|Research Group for Clinical Bioinformatics, Institute of Electrical and Biomedical Engineering (IEBE), University for Health Sciences, Medical Informatics and Technology (UMIT), Hall in Tirol, Austria, sAnalytiCo Ltd, Belfast, United Kingdom.|Research Group for Clinical Bioinformatics, Institute of Electrical and Biomedical Engineering (IEBE), University for Health Sciences, Medical Informatics and Technology (UMIT), Hall in Tirol, Austria, Institute of Health Care Engineering with European Notified Body of Medical Devices, Graz University of Technology, Graz, Austria.', 'Austria|Austria|Austria|Austria', 7, 'Adult|Algorithms|Biomarkers|Female|Glucose|Humans|Male|Metabolic Networks and Pathways|Metabolome|Metabolomics|Middle Aged|Models, Biological|Motor Activity|Tandem Mass Spectrometry|Young Adult', 'Journal Article', '10.1371/journal.pcbi.1004454', '26317529', 'The objectives of this work were the classification of dynamic metabolic biomarker candidates and the modeling and characterization of kinetic regulatory mechanisms in human metabolism with response to external perturbations by physical activity. Longitudinal metabolic concentration data of 47 individuals from 4 different groups were examined, obtained from a cycle ergometry cohort study. In total, 110 metabolites (within the classes of acylcarnitines, amino acids, and sugars) were measured through a targeted metabolomics approach, combining tandem mass spectrometry (MS/MS) with the concept of stable isotope dilution (SID) for metabolite quantitation. Biomarker candidates were selected by combined analysis of maximum fold changes (MFCs) in concentrations and P-values resulting from statistical hypothesis testing. Characteristic kinetic signatures were identified through a mathematical modeling approach utilizing polynomial fitting. Modeled kinetic signatures were analyzed for groups with similar behavior by applying hierarchical cluster analysis. Kinetic shape templates were characterized, defining different forms of basic kinetic response patterns, such as sustained, early, late, and other forms, that can be used for metabolite classification. Acetylcarnitine (C2), showing a late response pattern and having the highest values in MFC and statistical significance, was classified as late marker and ranked as strong predictor (MFC = 1.97, P < 0.001). In the class of amino acids, highest values were shown for alanine (MFC = 1.42, P < 0.001), classified as late marker and strong predictor. Glucose yields a delayed response pattern, similar to a hockey stick function, being classified as delayed marker and ranked as moderate predictor (MFC = 1.32, P < 0.001). These findings coincide with existing knowledge on central metabolic pathways affected in exercise physiology, such as xcexb2-oxidation of fatty acids, glycolysis, and glycogenolysis. The presented modeling approach demonstrates high potential for dynamic biomarker identification and the investigation of kinetic mechanisms in disease or pharmacodynamics studies using MS data from longitudinal cohort studies. '),
(87323, 2015, 'plos', 'Do Brain Networks Evolve by Maximizing Their Information Flow Capacity?', 'Antonopoulos, Chris G|Srivastava, Shambhavi|Pinto, Sandro E de S|Baptista, Murilo S', 'Department of Physics (ICSMB), University of Aberdeen, Aberdeen, United Kingdom.|Department of Physics (ICSMB), University of Aberdeen, Aberdeen, United Kingdom.|Departamento de Física, Universidade Estadual de Ponta Grossa, Paraná, Brazil.|Department of Physics (ICSMB), University of Aberdeen, Aberdeen, United Kingdom.', 'United Kingdom|United Kingdom|Brazil|United Kingdom', 0, 'Adult|Animals|Brain|Caenorhabditis elegans|Computational Biology|Humans|Learning|Male|Models, Neurological|Nerve Net|Neural Networks (Computer)|Neurons|Young Adult', 'Journal Article', '10.1371/journal.pcbi.1004372', '26317592', 'We propose a working hypothesis supported by numerical simulations that brain networks evolve based on the principle of the maximization of their internal information flow capacity. We find that synchronous behavior and capacity of information flow of the evolved networks reproduce well the same behaviors observed in the brain dynamical networks of Caenorhabditis elegans and humans, networks of Hindmarsh-Rose neurons with graphs given by these brain networks. We make a strong case to verify our hypothesis by showing that the neural networks with the closest graph distance to the brain networks of Caenorhabditis elegans and humans are the Hindmarsh-Rose neural networks evolved with coupling strengths that maximize information flow capacity. Surprisingly, we find that global neural synchronization levels decrease during brain evolution, reflecting on an underlying global no Hebbian-like evolution process, which is driven by no Hebbian-like learning behaviors for some of the clusters during evolution, and Hebbian-like learning rules for clusters where neurons increase their synchronization. '),
(87324, 2015, 'plos', 'Testing Foundations of Biological Scaling Theory Using Automated Measurements of Vascular Networks', 'Newberry, Mitchell G|Ennis, Daniel B|Savage, Van M', 'Department of Biomathematics, David Geffen School of Medicine, University of California Los Angeles, Los Angeles, California, United States of America.|Department of Radiological Sciences, Biomedical Physics, and Bioengineering, University of California, Los Angeles, Los Angeles, California, United States of America.|Department of Biomathematics, David Geffen School of Medicine, University of California Los Angeles, Los Angeles, California, United States of America, Department of Ecology and Evolutionary Biology, University of California, Los Angeles, Los Angeles, California, United States of America, Santa Fe Institute, Santa Fe, New Mexico, United States of America.', 'United States|United States|Mexico', 0, 'Adult|Algorithms|Carotid Artery Diseases|Computational Biology|Humans|Magnetic Resonance Angiography|Models, Cardiovascular|Prospective Studies|Regression Analysis', 'Journal Article', '10.1371/journal.pcbi.1004455', '26317654', 'Scientists have long sought to understand how vascular networks supply blood and oxygen to cells throughout the body. Recent work focuses on principles that constrain how vessel size changes through branching generations from the aorta to capillaries and uses scaling exponents to quantify these changes. Prominent scaling theories predict that combinations of these exponents explain how metabolic, growth, and other biological rates vary with body size. Nevertheless, direct measurements of individual vessel segments have been limited because existing techniques for measuring vasculature are invasive, time consuming, and technically difficult. We developed software that extracts the length, radius, and connectivity of in vivo vessels from contrast-enhanced 3D Magnetic Resonance Angiography. Using data from 20 human subjects, we calculated scaling exponents by four methods-two derived from local properties of branching junctions and two from whole-network properties. Although these methods are often used interchangeably in the literature, we do not find general agreement between these methods, particularly for vessel lengths. Measurements for length of vessels also diverge from theoretical values, but those for radius show stronger agreement. Our results demonstrate that vascular network models cannot ignore certain complexities of real vascular systems and indicate the need to discover new principles regarding vessel lengths. '),
(87325, 2015, 'plos', 'Flexible Modeling of Epidemics with an Empirical Bayes Framework', 'Brooks, Logan C|Farrow, David C|Hyun, Sangwon|Tibshirani, Ryan J|Rosenfeld, Roni', 'School of Computer Science, Carnegie Mellon University, Pittsburgh, Pennsylvania, United States of America.|School of Computer Science, Carnegie Mellon University, Pittsburgh, Pennsylvania, United States of America.|Department of Statistics, Carnegie Mellon University, Pittsburgh, Pennsylvania, United States of America.|Department of Statistics, Carnegie Mellon University, Pittsburgh, Pennsylvania, United States of America.|School of Computer Science, Carnegie Mellon University, Pittsburgh, Pennsylvania, United States of America.', 'United States|United States|United States|United States|United States', 0, 'Bayes Theorem|Centers for Disease Control and Prevention (U.S.)|Computational Biology|Epidemics|Humans|Influenza, Human|Models, Biological|Models, Statistical|Reproducibility of Results|United States', 'Journal Article', '10.1371/journal.pcbi.1004382', '26317693', 'Seasonal influenza epidemics cause consistent, considerable, widespread loss annually in terms of economic burden, morbidity, and mortality. With access to accurate and reliable forecasts of a current or upcoming influenza epidemics behavior, policy makers can design and implement more effective countermeasures. This past year, the Centers for Disease Control and Prevention hosted the Predict the Influenza Season Challenge, with the task of predicting key epidemiological measures for the 2013-2014 U.S. influenza season with the help of digital surveillance data. We developed a framework for in-season forecasts of epidemics using a semiparametric Empirical Bayes framework, and applied it to predict the weekly percentage of outpatient doctors visits for influenza-like illness, and the season onset, duration, peak time, and peak height, with and without using Google Flu Trends data. Previous work on epidemic modeling has focused on developing mechanistic models of disease behavior and applying time series tools to explain historical data. However, tailoring these models to certain types of surveillance data can be challenging, and overly complex models with many parameters can compromise forecasting ability. Our approach instead produces possibilities for the epidemic curve of the season of interest using modified versions of data from previous seasons, allowing for reasonable variations in the timing, pace, and intensity of the seasonal epidemics, as well as noise in observations. Since the framework does not make strict domain-specific assumptions, it can easily be applied to some other diseases with seasonal epidemics. This method produces a complete posterior distribution over epidemic curves, rather than, for example, solely point predictions of forecasting targets. We report prospective influenza-like-illness forecasts made for the 2013-2014 U.S. influenza season, and compare the frameworks cross-validated prediction error on historical data to that of a variety of simpler baseline predictors. '),
(87326, 2015, 'plos', 'Efficient Characterization of Parametric Uncertainty of Complex (Bio)chemical Networks', 'Schillings, Claudia|Sunnåker, Mikael|Stelling, Jörg|Schwab, Christoph', 'Seminar for Applied Mathematics, ETH Zürich, Zürich, Switzerland.|Department of Biosystems Science and Engineering and SIB Swiss Institute of Bioinformatics, ETH Zürich, Zürich, Switzerland.|Department of Biosystems Science and Engineering and SIB Swiss Institute of Bioinformatics, ETH Zürich, Zürich, Switzerland.|Seminar for Applied Mathematics, ETH Zürich, Zürich, Switzerland.', 'Switzerland|Switzerland|Switzerland|Switzerland', 9, 'Algorithms|ErbB Receptors|Glucose|Models, Biological|Monte Carlo Method|Saccharomyces cerevisiae|Signal Transduction|Systems Biology', 'Journal Article', '10.1371/journal.pcbi.1004457', '26317784', 'Parametric uncertainty is a particularly challenging and relevant aspect of systems analysis in domains such as systems biology where, both for inference and for assessing prediction uncertainties, it is essential to characterize the system behavior globally in the parameter space. However, current methods based on local approximations or on Monte-Carlo sampling cope only insufficiently with high-dimensional parameter spaces associated with complex network models. Here, we propose an alternative deterministic methodology that relies on sparse polynomial approximations. We propose a deterministic computational interpolation scheme which identifies most significant expansion coefficients adaptively. We present its performance in kinetic model equations from computational systems biology with several hundred parameters and state variables, leading to numerical approximations of the parametric solution on the entire parameter space. The scheme is based on adaptive Smolyak interpolation of the parametric solution at judiciously and adaptively chosen points in parameter space. As Monte-Carlo sampling, it is non-intrusive and well-suited for massively parallel implementation, but affords higher convergence rates. This opens up new avenues for large-scale dynamic network analysis by enabling scaling for many applications, including parameter estimation, uncertainty quantification, and systems design. '),
(87327, 2015, 'plos', 'Inflow/Outflow Boundary Conditions for Particle-Based Blood Flow Simulations: Application to Arterial Bifurcations and Trees', 'Lykov, Kirill|Li, Xuejin|Lei, Huan|Pivkin, Igor V|Karniadakis, George Em', 'Institute of Computational Science, Faculty of Informatics, University of Lugano, Lugano, Switzerland.|Division of Applied Mathematics, Brown University, Providence, Rhode Island, United States of America.|Pacific Northwest National Laboratory, Richland, Washington, United States of America.|Institute of Computational Science, Faculty of Informatics, University of Lugano, Lugano, Switzerland, Swiss Institute of Bioinformatics, Lausanne, Switzerland.|Division of Applied Mathematics, Brown University, Providence, Rhode Island, United States of America.', 'Switzerland|United States|United States|Switzerland|United States', 0, 'Arteries|Blood Flow Velocity|Computational Biology|Computer Simulation|Erythrocytes|Humans|Imaging, Three-Dimensional|Microcirculation|Models, Cardiovascular', 'Journal Article', '10.1371/journal.pcbi.1004410', '26317829', 'When blood flows through a bifurcation, red blood cells (RBCs) travel into side branches at different hematocrit levels, and it is even possible that all RBCs enter into one branch only, leading to a complete separation of plasma and RBCs. To quantify this phenomenon via particle-based mesoscopic simulations, we developed a general framework for open boundary conditions in multiphase flows that is effective even for high hematocrit levels. The inflow at the inlet is duplicated from a fully developed flow generated in a pilot simulation with periodic boundary conditions. The outflow is controlled by adaptive forces to maintain the flow rate and velocity gradient at fixed values, while the particles leaving the arteriole at the outlet are removed from the system. Upon validation of this approach, we performed systematic 3D simulations to study plasma skimming in arterioles of diameters 20 to 32 microns. For a flow rate ratio 6:1 at the branches, we observed the all-or-nothing phenomenon with plasma only entering the low flow rate branch. We then simulated blood-plasma separation in arteriolar bifurcations with different bifurcation angles and same diameter of the daughter branches. Our simulations predict a significant increase in RBC flux through the main daughter branch as the bifurcation angle is increased. Finally, we demonstrated the effectiveness of the new methodology in simulations of blood flow in vessels with multiple inlets and outlets, constructed using an angiogenesis model. '),
(87328, 2015, 'plos', 'Functional Basis of Microorganism Classification', 'Zhu, Chengsheng|Delmont, Tom O|Vogel, Timothy M|Bromberg, Yana', 'Department of Biochemistry and Microbiology, Rutgers University, New Brunswick, New Jersey, United States of America.|Environmental Microbial Genomics, Laboratoire Ampere, École Centrale de Lyon, Université de Lyon, Ecully, France.|Environmental Microbial Genomics, Laboratoire Ampere, École Centrale de Lyon, Université de Lyon, Ecully, France.|Department of Biochemistry and Microbiology, Rutgers University, New Brunswick, New Jersey, United States of America, Institute for Advanced Study, Technische Universität München, Garching, Germany.', 'Jersey|France|France|Germany', 12, 'Bacteria|Classification|Computational Biology|Genome, Bacterial|Software', 'Journal Article', '10.1371/journal.pcbi.1004472', '26317871', 'Correctly identifying nearest neighbors of a given microorganism is important in industrial and clinical applications where close relationships imply similar treatment. Microbial classification based on similarity of physiological and genetic organism traits (polyphasic similarity) is experimentally difficult and, arguably, subjective. Evolutionary relatedness, inferred from phylogenetic markers, facilitates classification but does not guarantee functional identity between members of the same taxon or lack of similarity between different taxa. Using over thirteen hundred sequenced bacterial genomes, we built a novel function-based microorganism classification scheme, functional-repertoire similarity-based organism network (FuSiON, flattened to fusion). Our scheme is phenetic, based on a network of quantitatively defined organism relationships across the known prokaryotic space. It correlates significantly with the current taxonomy, but the observed discrepancies reveal both (1) the inconsistency of functional diversity levels among different taxa and (2) an (unsurprising) bias towards prioritizing, for classification purposes, relatively minor traits of particular interest to humans. Our dynamic network-based organism classification is independent of the arbitrary pairwise organism similarity cut-offs traditionally applied to establish taxonomic identity. Instead, it reveals natural, functionally defined organism groupings and is thus robust in handling organism diversity. Additionally, fusion can use organism meta-data to highlight the specific environmental factors that drive microbial diversification. Our approach provides a complementary view to cladistic assignments and holds important clues for further exploration of microbial lifestyles. Fusion is a more practical fit for biomedical, industrial, and ecological applications, as many of these rely on understanding the functional capabilities of the microbes in their environment and are less concerned with phylogenetic descent. '),
(87329, 2015, 'plos', 'An Integrated Framework Advancing Membrane Protein Modeling and Design', 'Alford, Rebecca F|Koehler Leman, Julia|Weitzner, Brian D|Duran, Amanda M|Tilley, Drew C|Elazar, Assaf|Gray, Jeffrey J', 'Department of Chemical and Biomolecular Engineering, Johns Hopkins University, Baltimore, Maryland, United States of America, Department of Chemistry, Carnegie Mellon University, Pittsburgh, Pennsylvania, United States of America.|Department of Chemical and Biomolecular Engineering, Johns Hopkins University, Baltimore, Maryland, United States of America.|Department of Chemical and Biomolecular Engineering, Johns Hopkins University, Baltimore, Maryland, United States of America.|Center for Structural Biology, Department of Chemistry, Vanderbilt University, Nashville, Tennessee, United States of America.|Department of Physiology and Membrane Biology, University of California, Davis, Davis, California, United States of America.|Department of Biological Chemistry, Weizmann Institute of Science, Rehovot, Israel.|Department of Chemical and Biomolecular Engineering, Johns Hopkins University, Baltimore, Maryland, United States of America.', 'United States|United States|United States|United States|United States|Israel|United States', 50, 'Computational Biology|Membrane Proteins|Models, Molecular|Protein Conformation|Protein Engineering', 'Journal Article', '10.1371/journal.pcbi.1004398', '26325167', 'Membrane proteins are critical functional molecules in the human body, constituting more than 30% of open reading frames in the human genome. Unfortunately, a myriad of difficulties in overexpression and reconstitution into membrane mimetics severely limit our ability to determine their structures. Computational tools are therefore instrumental to membrane protein structure prediction, consequently increasing our understanding of membrane protein function and their role in disease. Here, we describe a general framework facilitating membrane protein modeling and design that combines the scientific principles for membrane protein modeling with the flexible software architecture of Rosetta3. This new framework, called RosettaMP, provides a general membrane representation that interfaces with scoring, conformational sampling, and mutation routines that can be easily combined to create new protocols. To demonstrate the capabilities of this implementation, we developed four proof-of-concept applications for (1) prediction of free energy changes upon mutation, (2) high-resolution structural refinement, (3) protein-protein docking, and (4) assembly of symmetric protein complexes, all in the membrane environment. Preliminary data show that these algorithms can produce meaningful scores and structures. The data also suggest needed improvements to both sampling routines and score functions. Importantly, the applications collectively demonstrate the potential of combining the flexible nature of RosettaMP with the power of Rosetta algorithms to facilitate membrane protein modeling and design. '),
(87330, 2015, 'plos', 'A Theory of Cheap Control in Embodied Systems', 'Montúfar, Guido|Ghazi-Zahedi, Keyan|Ay, Nihat', 'Max Planck Institute for Mathematics in the Sciences, 04103 Leipzig, Germany.|Max Planck Institute for Mathematics in the Sciences, 04103 Leipzig, Germany.|Max Planck Institute for Mathematics in the Sciences, 04103 Leipzig, Germany, Department of Mathematics and Computer Science, Leipzig University, 04009 Leipzig, Germany, Santa Fe Institute, Santa Fe, New Mexico, United States of America.', 'Germany|Germany|Germany', 8, 'Feedback|Models, Biological|Models, Neurological|Motion|Neural Networks (Computer)|Robotics', 'Journal Article', '10.1371/journal.pcbi.1004427', '26325254', 'We present a framework for designing cheap control architectures of embodied agents. Our derivation is guided by the classical problem of universal approximation, whereby we explore the possibility of exploiting the agents embodiment for a new and more efficient universal approximation of behaviors generated by sensorimotor control. This embodied universal approximation is compared with the classical non-embodied universal approximation. To exemplify our approach, we present a detailed quantitative case study for policy models defined in terms of conditional restricted Boltzmann machines. In contrast to non-embodied universal approximation, which requires an exponential number of parameters, in the embodied setting we are able to generate all possible behaviors with a drastically smaller model, thus obtaining cheap universal approximation. We test and corroborate the theory experimentally with a six-legged walking machine. The experiments indicate that the controller complexity predicted by our theory is close to the minimal sufficient value, which means that the theory has direct practical implications. '),
(87331, 2015, 'plos', 'Analysis of Nearly One Thousand Mammalian Mirtrons Reveals Novel Features of Dicer Substrates', 'Wen, Jiayu|Ladewig, Erik|Shenker, Sol|Mohammed, Jaaved|Lai, Eric C', 'Department of Developmental Biology, Sloan-Kettering Institute, New York, New York, United States of America.|Department of Developmental Biology, Sloan-Kettering Institute, New York, New York, United States of America.|Department of Developmental Biology, Sloan-Kettering Institute, New York, New York, United States of America, Tri-Institutional Program in Computational Biology and Medicine, Weill Cornell Medical College, New York, New York, United States of America.|Department of Developmental Biology, Sloan-Kettering Institute, New York, New York, United States of America, Tri-Institutional Program in Computational Biology and Medicine, Weill Cornell Medical College, New York, New York, United States of America.|Department of Developmental Biology, Sloan-Kettering Institute, New York, New York, United States of America.', 'United States|United States|United States|United States|United States', 0, 'Animals|Computational Biology|Gene Library|Humans|Mice|MicroRNAs|Models, Genetic|Ribonuclease III|Sequence Analysis, RNA', 'Journal Article', '10.1371/journal.pcbi.1004441', '26325366', 'Mirtrons are microRNA (miRNA) substrates that utilize the splicing machinery to bypass the necessity of Drosha cleavage for their biogenesis. Expanding our recent efforts for mammalian mirtron annotation, we use meta-analysis of aggregate datasets to identify ~500 novel mouse and human introns that confidently generate diced small RNA duplexes. These comprise nearly 1000 total loci distributed in four splicing-mediated biogenesis subclasses, with 5-tailed mirtrons as, by far, the dominant subtype. Thus, mirtrons surprisingly comprise a substantial fraction of endogenous Dicer substrates in mammalian genomes. Although mirtron-derived small RNAs exhibit overall expression correlation with their host mRNAs, we observe a subset with substantial differences that suggest regulated processing or accumulation. We identify characteristic sequence, length, and structural features of mirtron loci that distinguish them from bulk introns, and find that mirtrons preferentially emerge from genes with larger numbers of introns. While mirtrons generate miRNA-class regulatory RNAs, we also find that mirtrons exhibit many features that distinguish them from canonical miRNAs. We observe that conventional mirtron hairpins are substantially longer than Drosha-generated pre-miRNAs, indicating that the characteristic length of canonical pre-miRNAs is not a general feature of Dicer substrate hairpins. In addition, mammalian mirtrons exhibit unique patterns of ordered 5 and 3 heterogeneity, which reveal hidden complexity in miRNA processing pathways. These include broad 3-uridylation of mirtron hairpins, atypically heterogeneous 5 termini that may result from exonucleolytic processing, and occasionally robust decapitation of the 5 guanine (G) of mirtron-5p species defined by splicing. Altogether, this study reveals that this extensive class of non-canonical miRNA bears a multitude of characteristic properties, many of which raise general mechanistic questions regarding the processing of endogenous hairpin transcripts. ');
INSERT INTO `papers` (`id`, `ano`, `journal`, `titulo`, `autores`, `afiliacao`, `pais`, `citacoes`, `palavra_chave`, `categorias`, `doi`, `pubmed`, `abstract`) VALUES
(87332, 2015, 'plos', 'Mapping the Conformation Space of Wildtype and Mutant H-Ras with a Memetic, Cellular, and Multiscale Evolutionary Algorithm', 'Clausen, Rudy|Ma, Buyong|Nussinov, Ruth|Shehu, Amarda', 'Department of Computer Science, George Mason University, Fairfax, Virginia, United States of America.|Basic Science Program, Leidos Biomedical Research, Inc. Cancer and Inflammation Program, National Cancer Institute, Frederick, Maryland, United States of America.|Basic Science Program, Leidos Biomedical Research, Inc. Cancer and Inflammation Program, National Cancer Institute, Frederick, Maryland, United States of America, Sackler Institute of Molecular Medicine, Department of Human Genetics and Molecular Medicine, Sackler School of Medicine, Tel Aviv University, Tel Aviv, Israel.|Department of Computer Science, George Mason University, Fairfax, Virginia, United States of America, Department of Biongineering, George Mason University, Fairfax, Virginia, United States of America, School of Systems Biology, George Mason University, Manassas, Virginia, United States of America.', 'United States|United States|Israel|United States', 37, 'Algorithms|Computational Biology|Crystallography|Humans|Models, Molecular|Mutation|Oncogene Protein p21(ras)|Principal Component Analysis|Protein Conformation|Thermodynamics', 'Journal Article', '10.1371/journal.pcbi.1004470', '26325505', 'An important goal in molecular biology is to understand functional changes upon single-point mutations in proteins. Doing so through a detailed characterization of structure spaces and underlying energy landscapes is desirable but continues to challenge methods based on Molecular Dynamics. In this paper we propose a novel algorithm, SIfTER, which is based instead on stochastic optimization to circumvent the computational challenge of exploring the breadth of a proteins structure space. SIfTER is a data-driven evolutionary algorithm, leveraging experimentally-available structures of wildtype and variant sequences of a protein to define a reduced search space from where to efficiently draw samples corresponding to novel structures not directly observed in the wet laboratory. The main advantage of SIfTER is its ability to rapidly generate conformational ensembles, thus allowing mapping and juxtaposing landscapes of variant sequences and relating observed differences to functional changes. We apply SIfTER to variant sequences of the H-Ras catalytic domain, due to the prominent role of the Ras protein in signaling pathways that control cell proliferation, its well-studied conformational switching, and abundance of documented mutations in several human tumors. Many Ras mutations are oncogenic, but detailed energy landscapes have not been reported until now. Analysis of SIfTER-computed energy landscapes for the wildtype and two oncogenic variants, G12V and Q61L, suggests that these mutations cause constitutive activation through two different mechanisms. G12V directly affects binding specificity while leaving the energy landscape largely unchanged, whereas Q61L has pronounced, starker effects on the landscape. An implementation of SIfTER is made available at http://www.cs.gmu.edu/~ashehu/?q=OurTools. We believe SIfTER is useful to the community to answer the question of how sequence mutations affect the function of a protein, when there is an abundance of experimental structures that can be exploited to reconstruct an energy landscape that would be computationally impractical to do via Molecular Dynamics. '),
(87333, 2015, 'plos', 'Scalability of Asynchronous Networks Is Limited by One-to-One Mapping between Effective Connectivity and Correlations', 'van Albada, Sacha Jennifer|Helias, Moritz|Diesmann, Markus', 'Institute of Neuroscience and Medicine (INM-6) and Institute for Advanced Simulation (IAS-6) and JARA BRAIN Institute I, Jülich Research Centre, Jülich, Germany.|Institute of Neuroscience and Medicine (INM-6) and Institute for Advanced Simulation (IAS-6) and JARA BRAIN Institute I, Jülich Research Centre, Jülich, Germany.|Institute of Neuroscience and Medicine (INM-6) and Institute for Advanced Simulation (IAS-6) and JARA BRAIN Institute I, Jülich Research Centre, Jülich, Germany, Department of Psychiatry, Psychotherapy and Psychosomatics, Medical Faculty, RWTH Aachen University, Aachen, Germany, Department of Physics, Faculty 1, RWTH Aachen University, Aachen, Germany.', 'Germany|Germany|Germany', 0, 'Brain|Computational Biology|Humans|Models, Neurological|Nerve Net|Neurons|Synapses', 'Journal Article', '10.1371/journal.pcbi.1004490', '26325661', 'Network models are routinely downscaled compared to nature in terms of numbers of nodes or edges because of a lack of computational resources, often without explicit mention of the limitations this entails. While reliable methods have long existed to adjust parameters such that the first-order statistics of network dynamics are conserved, here we show that limitations already arise if also second-order statistics are to be maintained. The temporal structure of pairwise averaged correlations in the activity of recurrent networks is determined by the effective population-level connectivity. We first show that in general the converse is also true and explicitly mention degenerate cases when this one-to-one relationship does not hold. The one-to-one correspondence between effective connectivity and the temporal structure of pairwise averaged correlations implies that network scalings should preserve the effective connectivity if pairwise averaged correlations are to be held constant. Changes in effective connectivity can even push a network from a linearly stable to an unstable, oscillatory regime and vice versa. On this basis, we derive conditions for the preservation of both mean population-averaged activities and pairwise averaged correlations under a change in numbers of neurons or synapses in the asynchronous regime typical of cortical networks. We find that mean activities and correlation structure can be maintained by an appropriate scaling of the synaptic weights, but only over a range of numbers of synapses that is limited by the variance of external inputs to the network. Our results therefore show that the reducibility of asynchronous networks is fundamentally limited. '),
(87334, 2015, 'plos', 'A Self-Organising Model of Thermoregulatory Huddling', 'Glancy, Jonathan|Groß, Roderich|Stone, James V|Wilson, Stuart P', 'Sheffield Robotics, The University of Sheffield, Sheffield, United Kingdom, Department of Psychology, The University of Sheffield, Sheffield, United Kingdom.|Sheffield Robotics, The University of Sheffield, Sheffield, United Kingdom, Department of Automatic Control and Systems Engineering, The University of Sheffield, Sheffield, United Kingdom.|Sheffield Robotics, The University of Sheffield, Sheffield, United Kingdom, Department of Psychology, The University of Sheffield, Sheffield, United Kingdom.|Sheffield Robotics, The University of Sheffield, Sheffield, United Kingdom, Department of Psychology, The University of Sheffield, Sheffield, United Kingdom.', 'United Kingdom|United Kingdom|United Kingdom|United Kingdom', 0, 'Algorithms|Animals|Behavior, Animal|Body Temperature Regulation|Computational Biology|Mice|Models, Biological|Rats|Thermodynamics', 'Journal Article', '10.1371/journal.pcbi.1004283', '26334993', 'Endotherms such as rats and mice huddle together to keep warm. The huddle is considered to be an example of a self-organising system, because complex properties of the collective group behaviour are thought to emerge spontaneously through simple interactions between individuals. Groups of rodent pups display two such emergent properties. First, huddling undergoes a phase transition, such that pups start to aggregate rapidly as the temperature of the environment falls below a critical temperature. Second, the huddle maintains a constant pup flow, where cooler pups at the periphery continually displace warmer pups at the centre. We set out to test whether these complex group behaviours can emerge spontaneously from local interactions between individuals. We designed a model using a minimal set of assumptions about how individual pups interact, by simply turning towards heat sources, and show in computer simulations that the model reproduces the first emergent property--the phase transition. However, this minimal model tends to produce an unnatural behaviour where several smaller aggregates emerge rather than one large huddle. We found that an extension of the minimal model to include heat exchange between pups allows the group to maintain one large huddle but eradicates the phase transition, whereas inclusion of an additional homeostatic term recovers the phase transition for large huddles. As an unanticipated consequence, the extended model also naturally gave rise to the second observed emergent property--a continuous pup flow. The model therefore serves as a minimal description of huddling as a self-organising system, and as an existence proof that group-level huddling dynamics emerge spontaneously through simple interactions between individuals. We derive a specific testable prediction: Increasing the capacity of the individual to generate or conserve heat will increase the range of ambient temperatures over which adaptive thermoregulatory huddling will emerge.'),
(87335, 2015, 'plos', 'Relating Alpha Power and Phase to Population Firing and Hemodynamic Activity Using a Thalamo-cortical Neural Mass Model', 'Becker, Robert|Knock, Stuart|Ritter, Petra|Jirsa, Viktor', 'Functional Brain Mapping Lab, University of Geneva, Geneva, Switzerland.|Institut de Neurosciences des Systèmes, Aix Marseille Université, Marseille, France.|Minerva Research Group BrainModes, Max Planck Institute for Human Cognitive and Brain Sciences, Leipzig, Germany, Dept. Neurology, Charité & Bernstein Center for Computational Neuroscience-University Medicine, Berlin, Germany, Berlin School of Mind and Brain & Mind and Brain Institute, Humboldt University, Berlin, Germany.|Institut de Neurosciences des Systèmes, Aix Marseille Université, Marseille, France, Inserm, UMR 1106, Aix Marseille Université, Marseille, France.', 'Switzerland|France|Germany|France', 16, 'Alpha Rhythm|Computational Biology|Electroencephalography|Hemodynamics|Humans|Magnetic Resonance Imaging|Models, Neurological|Thalamus|Visual Cortex', 'Journal Article', '10.1371/journal.pcbi.1004352', '26335064', 'Oscillations are ubiquitous phenomena in the animal and human brain. Among them, the alpha rhythm in human EEG is one of the most prominent examples. However, its precise mechanisms of generation are still poorly understood. It was mainly this lack of knowledge that motivated a number of simultaneous electroencephalography (EEG) - functional magnetic resonance imaging (fMRI) studies. This approach revealed how oscillatory neuronal signatures such as the alpha rhythm are paralleled by changes of the blood oxygenation level dependent (BOLD) signal. Several such studies revealed a negative correlation between the alpha rhythm and the hemodynamic BOLD signal in visual cortex and a positive correlation in the thalamus. In this study we explore the potential generative mechanisms that lead to those observations. We use a bursting capable Stefanescu-Jirsa 3D (SJ3D) neural-mass model that reproduces a wide repertoire of prominent features of local neuronal-population dynamics. We construct a thalamo-cortical network of coupled SJ3D nodes considering excitatory and inhibitory directed connections. The model suggests that an inverse correlation between cortical multi-unit activity, i.e. the firing of neuronal populations, and narrow band local field potential oscillations in the alpha band underlies the empirically observed negative correlation between alpha-rhythm power and fMRI signal in visual cortex. Furthermore the model suggests that the interplay between tonic and bursting mode in thalamus and cortex is critical for this relation. This demonstrates how biophysically meaningful modelling can generate precise and testable hypotheses about the underpinnings of large-scale neuroimaging signals. '),
(87336, 2015, 'plos', 'An Emerging Allee Effect Is Critical for Tumor Initiation and Persistence', 'Böttger, Katrin|Hatzikirou, Haralambos|Voss-Böhme, Anja|Cavalcanti-Adam, Elisabetta Ada|Herrero, Miguel A|Deutsch, Andreas', 'Center for Information Services and High Performance Computing, Technische Universität Dresden, Dresden, Germany.|Center for Advancing Electronics, Technische Universität Dresden, Dresden, Germany.|Center for Information Services and High Performance Computing, Technische Universität Dresden, Dresden, Germany, Hochschule für Technik und Wirtschaft Dresden, Dresden, Germany.|Department of Biophysical Chemistry, Institute of Physical Chemistry, University of Heidelberg, Heidelberg, Germany, Max Planck Institute for Intelligent Systems, Stuttgart, Germany.|Departamento de Matemática Aplicada, Facultad de Matemáticas, Universidad Complutense, Madrid, Spain.|Center for Information Services and High Performance Computing, Technische Universität Dresden, Dresden, Germany.', 'Germany|Germany|Germany|Germany|Spain|Germany', 0, 'Cell Count|Cell Movement|Cell Proliferation|Computational Biology|Computer Simulation|Models, Biological|Neoplastic Processes|Tumor Microenvironment', 'Journal Article', '10.1371/journal.pcbi.1004366', '26335202', 'Tumor cells develop different strategies to cope with changing microenvironmental conditions. A prominent example is the adaptive phenotypic switching between cell migration and proliferation. While it has been shown that the migration-proliferation plasticity influences tumor spread, it remains unclear how this particular phenotypic plasticity affects overall tumor growth, in particular initiation and persistence. To address this problem, we formulate and study a mathematical model of spatio-temporal tumor dynamics which incorporates the microenvironmental influence through a local cell density dependence. Our analysis reveals that two dynamic regimes can be distinguished. If cell motility is allowed to increase with local cell density, any tumor cell population will persist in time, irrespective of its initial size. On the contrary, if cell motility is assumed to decrease with respect to local cell density, any tumor population below a certain size threshold will eventually extinguish, a fact usually termed as Allee effect in ecology. These results suggest that strategies aimed at modulating migration are worth to be explored as alternatives to those mainly focused at keeping tumor proliferation under control. '),
(87337, 2015, 'plos', 'Examination of the Effects of Heterogeneous Organization of RyR Clusters, Myofibrils and Mitochondria on Ca2+ Release Patterns in Cardiomyocytes', 'Rajagopal, Vijay|Bass, Gregory|Walker, Cameron G|Crossman, David J|Petzer, Amorita|Hickey, Anthony|Siekmann, Ivo|Hoshijima, Masahiko|Ellisman, Mark H|Crampin, Edmund J|Soeller, Christian', 'Department of Mechanical Engineering, University of Melbourne, Melbourne, Australia, Auckland Bioengineering Institute, University of Auckland, Auckland, New Zealand, Systems Biology Laboratory, Melbourne School of Engineering, University of Melbourne, Melbourne, Australia.|Systems Biology Laboratory, Melbourne School of Engineering, University of Melbourne, Melbourne, Australia.|Department of Engineering Science, University of Auckland, Auckland, New Zealand.|Department of Physiology, University of Auckland, Auckland, New Zealand.|School of Biological Sciences, University of Auckland, Auckland. New Zealand.|School of Biological Sciences, University of Auckland, Auckland. New Zealand.|Department of Mechanical Engineering, University of Melbourne, Melbourne, Australia.|Department of Medicine, University of California San Diego, San Diego, United States of America, National Center for Microscopy and Imaging Research, University of California San Diego, San Diego, United States of America.|National Center for Microscopy and Imaging Research, University of California San Diego, San Diego, United States of America.|Systems Biology Laboratory, Melbourne School of Engineering, University of Melbourne, Melbourne, Australia, School of Mathematics and Statistics, Faculty of Science, University of Melbourne, Melbourne, Australia, School of Medicine, Faculty of Medicine, Dentistry and Health Sciences, University of Melbourne, Melbourne, Australia, ARC Centre of Excellence in Convergent Bio-Nano Science and Technology, University of Melbourne, Melbourne, Australia.|Department of Physiology, University of Auckland, Auckland, New Zealand, Biomedical Physics, University of Exeter, Exeter, United Kingdom.', 'Australia|Australia|New Zealand|New Zealand|New Zealand|New Zealand|Australia|United States|United S', 23, 'Animals|Calcium|Calcium Signaling|Computational Biology|Computer Simulation|Male|Mitochondria|Models, Biological|Myocytes, Cardiac|Myofibrils|Rats|Rats, Wistar|Ryanodine Receptor Calcium Release Channel', 'Journal Article', '10.1371/journal.pcbi.1004417', '26335304', 'Spatio-temporal dynamics of intracellular calcium, [Ca2+]i, regulate the contractile function of cardiac muscle cells. Measuring [Ca2+]i flux is central to the study of mechanisms that underlie both normal cardiac function and calcium-dependent etiologies in heart disease. However, current imaging techniques are limited in the spatial resolution to which changes in [Ca2+]i can be detected. Using spatial point process statistics techniques we developed a novel method to simulate the spatial distribution of RyR clusters, which act as the major mediators of contractile Ca2+ release, upon a physiologically-realistic cellular landscape composed of tightly-packed mitochondria and myofibrils. We applied this method to computationally combine confocal-scale (~ 200 nm) data of RyR clusters with 3D electron microscopy data (~ 30 nm) of myofibrils and mitochondria, both collected from adult rat left ventricular myocytes. Using this hybrid-scale spatial model, we simulated reaction-diffusion of [Ca2+]i during the rising phase of the transient (first 30 ms after initiation). At 30 ms, the average peak of the simulated [Ca2+]i transient and of the simulated fluorescence intensity signal, F/F0, reached values similar to that found in the literature ([Ca2+]i xe2x89x881 xcexbcM, F/F0xe2x89x885.5). However, our model predicted the variation in [Ca2+]i to be between 0.3 and 12.7 xcexbcM (~3 to 100 fold from resting value of 0.1 xcexbcM) and the corresponding F/F0 signal ranging from 3 to 9.5. We demonstrate in this study that: (i) heterogeneities in the [Ca2+]i transient are due not only to heterogeneous distribution and clustering of mitochondria, (ii) but also to heterogeneous local densities of RyR clusters. Further, we show that: (iii) these structure-induced heterogeneities in [Ca2+]i can appear in line scan data. Finally, using our unique method for generating RyR cluster distributions, we demonstrate the robustness in the [Ca2+]i transient to differences in RyR cluster distributions measured between rat and human cardiomyocytes. '),
(87338, 2015, 'plos', 'Self-organization in Balanced State Networks by STDP and Homeostatic Plasticity', 'Effenberger, Felix|Jost, Jürgen|Levina, Anna', 'Max-Planck-Institute for Mathematics in the Sciences, Leipzig, Germany.|Max-Planck-Institute for Mathematics in the Sciences, Leipzig, Germany.|Max-Planck-Institute for Mathematics in the Sciences, Leipzig, Germany, Bernstein Center for Computational Neuroscience Göttingen, Göttingen, Germany.', 'Germany|Germany|Germany', 0, 'Computational Biology|Models, Neurological|Nerve Net|Neuronal Plasticity|Neurons|Synapses', 'Journal Article', '10.1371/journal.pcbi.1004420', '26335425', 'Structural inhomogeneities in synaptic efficacies have a strong impact on population response dynamics of cortical networks and are believed to play an important role in their functioning. However, little is known about how such inhomogeneities could evolve by means of synaptic plasticity. Here we present an adaptive model of a balanced neuronal network that combines two different types of plasticity, STDP and synaptic scaling. The plasticity rules yield both long-tailed distributions of synaptic weights and firing rates. Simultaneously, a highly connected subnetwork of driver neurons with strong synapses emerges. Coincident spiking activity of several driver cells can evoke population bursts and driver cells have similar dynamical properties as leader neurons found experimentally. Our model allows us to observe the delicate interplay between structural and dynamical properties of the emergent inhomogeneities. It is simple, robust to parameter changes and able to explain a multitude of different experimental findings in one basic network. '),
(87339, 2015, 'plos', 'ReproPhylo: An Environment for Reproducible Phylogenomics', 'Szitenberg, Amir|John, Max|Blaxter, Mark L|Lunt, David H', 'Evolutionary Biology Group, School of Biological, Biomedical & Environmental Sciences, The University of Hull, Hull, United Kingdom.|Evolutionary Biology Group, School of Biological, Biomedical & Environmental Sciences, The University of Hull, Hull, United Kingdom.|Institute of Evolutionary Biology, The University of Edinburgh, Edinburgh, United Kingdom.|Evolutionary Biology Group, School of Biological, Biomedical & Environmental Sciences, The University of Hull, Hull, United Kingdom.', 'United Kingdom|United Kingdom|United Kingdom|United Kingdom', 12, 'Genomics|Models, Genetic|Phylogeny|Reproducibility of Results|Sequence Alignment|Software', 'Journal Article', '10.1371/journal.pcbi.1004447', '26335558', 'The reproducibility of experiments is key to the scientific process, and particularly necessary for accurate reporting of analyses in data-rich fields such as phylogenomics. We present ReproPhylo, a phylogenomic analysis environment developed to ensure experimental reproducibility, to facilitate the handling of large-scale data, and to assist methodological experimentation. Reproducibility, and instantaneous repeatability, is built in to the ReproPhylo system and does not require user intervention or configuration because it stores the experimental workflow as a single, serialized Python object containing explicit provenance and environment information. This single file approach ensures the persistence of provenance across iterations of the analysis, with changes automatically managed by the version control program Git. This file, along with a Git repository, are the primary reproducibility outputs of the program. In addition, ReproPhylo produces an extensive human-readable report and generates a comprehensive experimental archive file, both of which are suitable for submission with publications. The system facilitates thorough experimental exploration of both parameters and data. ReproPhylo is a platform independent CC0 Python module and is easily installed as a Docker image or a WinPython self-sufficient package, with a Jupyter Notebook GUI, or as a slimmer version in a Galaxy distribution. '),
(87340, 2015, 'plos', 'Explaining the Timing of Natural Scene Understanding with a Computational Model of Perceptual Categorization', 'Sofer, Imri|Crouzet, Sébastien M|Serre, Thomas', 'Cognitive, Linguistic & Psychological Sciences Department, Brown Institute for Brain Science, Brown University, Providence, Rhode Island, United States of America.|Cognitive, Linguistic & Psychological Sciences Department, Brown Institute for Brain Science, Brown University, Providence, Rhode Island, United States of America.|Cognitive, Linguistic & Psychological Sciences Department, Brown Institute for Brain Science, Brown University, Providence, Rhode Island, United States of America.', 'United States|United States|United States', 0, 'Adult|Algorithms|Computational Biology|Female|Humans|Male|Models, Biological|Pattern Recognition, Visual|Reaction Time|Task Performance and Analysis|Young Adult', 'Journal Article', '10.1371/journal.pcbi.1004456', '26335683', 'Observers can rapidly perform a variety of visual tasks such as categorizing a scene as open, as outdoor, or as a beach. Although we know that different tasks are typically associated with systematic differences in behavioral responses, to date, little is known about the underlying mechanisms. Here, we implemented a single integrated paradigm that links perceptual processes with categorization processes. Using a large image database of natural scenes, we trained machine-learning classifiers to derive quantitative measures of task-specific perceptual discriminability based on the distance between individual images and different categorization boundaries. We showed that the resulting discriminability measure accurately predicts variations in behavioral responses across categorization tasks and stimulus sets. We further used the model to design an experiment, which challenged previous interpretations of the so-called superordinate advantage. Overall, our study suggests that observed differences in behavioral responses across rapid categorization tasks reflect natural variations in perceptual discriminability. '),
(87341, 2015, 'plos', 'Increased Aggregation Is More Frequently Associated to Human Disease-Associated Mutations Than to Neutral Polymorphisms', 'De Baets, Greet|Van Doorn, Loic|Rousseau, Frederic|Schymkowitz, Joost', 'VIB Switch Laboratory, Flanders Institute for Biotechnology (VIB), Leuven, Belgium, Switch Laboratory, Department of Cellular and Molecular Medicine, University of Leuven, Leuven, Belgium.|VIB Switch Laboratory, Flanders Institute for Biotechnology (VIB), Leuven, Belgium, Switch Laboratory, Department of Cellular and Molecular Medicine, University of Leuven, Leuven, Belgium.|VIB Switch Laboratory, Flanders Institute for Biotechnology (VIB), Leuven, Belgium, Switch Laboratory, Department of Cellular and Molecular Medicine, University of Leuven, Leuven, Belgium.|VIB Switch Laboratory, Flanders Institute for Biotechnology (VIB), Leuven, Belgium, Switch Laboratory, Department of Cellular and Molecular Medicine, University of Leuven, Leuven, Belgium.', 'Belgium|Belgium|Belgium|Belgium', 15, 'Computational Biology|Databases, Factual|Genetic Predisposition to Disease|Humans|Mutation|Polymorphism, Genetic|Protein Aggregation, Pathological|Protein Stability', 'Journal Article', '10.1371/journal.pcbi.1004374', '26340370', 'Protein aggregation is a hallmark of over 30 human pathologies. In these diseases, the aggregation of one or a few specific proteins is often toxic, leading to cellular degeneration and/or organ disruption in addition to the loss-of-function resulting from protein misfolding. Although the pathophysiological consequences of these diseases are overt, the molecular dysregulations leading to aggregate toxicity are still unclear and appear to be diverse and multifactorial. The molecular mechanisms of protein aggregation and therefore the biophysical parameters favoring protein aggregation are better understood. Here we perform an in silico survey of the impact of human sequence variation on the aggregation propensity of human proteins. We find that disease-associated variations are statistically significantly enriched in mutations that increase the aggregation potential of human proteins when compared to neutral sequence variations. These findings suggest that protein aggregation might have a broader impact on human disease than generally assumed and that beyond loss-of-function, the aggregation of mutant proteins involved in cancer, immune disorders or inflammation could potentially further contribute to disease by additional burden on cellular protein homeostasis. '),
(87342, 2015, 'plos', 'Metabolic Adaptation Processes That Converge to Optimal Biomass Flux Distributions', 'Altafini, Claudio|Facchetti, Giuseppe', 'Division of Automatic Control, Dept. of Electrical Engineering, Linköping University, Linköping, Sweden.|John Innes Centre, Norwich, United Kingdom.', 'Sweden|United Kingdom', 1, 'Adaptation, Physiological|Algorithms|Biomass|Carbon|Escherichia coli|Metabolic Flux Analysis|Metabolism|Models, Biological|Systems Biology', 'Journal Article', '10.1371/journal.pcbi.1004434', '26340476', 'In simple organisms like E.coli, the metabolic response to an external perturbation passes through a transient phase in which the activation of a number of latent pathways can guarantee survival at the expenses of growth. Growth is gradually recovered as the organism adapts to the new condition. This adaptation can be modeled as a process of repeated metabolic adjustments obtained through the resilencings of the non-essential metabolic reactions, using growth rate as selection probability for the phenotypes obtained. The resulting metabolic adaptation process tends naturally to steer the metabolic fluxes towards high growth phenotypes. Quite remarkably, when applied to the central carbon metabolism of E.coli, it follows that nearly all flux distributions converge to the flux vector representing optimal growth, i.e., the solution of the biomass optimization problem turns out to be the dominant attractor of the metabolic adaptation process. '),
(87343, 2015, 'plos', 'Evolution of Intra-specific Regulatory Networks in a Multipartite Bacterial Genome', 'Galardini, Marco|Brilli, Matteo|Spini, Giulia|Rossi, Matteo|Roncaglia, Bianca|Bani, Alessia|Chiancianesi, Manuela|Moretto, Marco|Engelen, Kristof|Bacci, Giovanni|Pini, Francesco|Biondi, Emanuele G|Bazzicalupo, Marco|Mengoni, Alessio', 'Department of Biology, University of Florence, Florence, Italy.|Department of Genomics and Biology of Fruit Crops, Research and Innovation Centre, Fondazione Edmund Mach (FEM), San Michele allAdige, Italy.|Dipartimento di Biotecnologie Agrarie, Sezione di Microbiologia, University of Florence, Florence, Italy.|Department of Biology, University of Florence, Florence, Italy.|Department of Biology, University of Florence, Florence, Italy.|Department of Biology, University of Florence, Florence, Italy.|Department of Biology, University of Florence, Florence, Italy.|Department of Computational Biology, Research and Innovation Centre, Fondazione Edmund Mach (FEM), San Michele allAdige, Italy.|Department of Computational Biology, Research and Innovation Centre, Fondazione Edmund Mach (FEM), San Michele allAdige, Italy.|Department of Biology, University of Florence, Florence, Italy, Consiglio per la Ricerca e la Sperimentazione in Agricoltura, Centro di Ricerca per lo Studio delle Relazioni tra Pianta e Suolo (CRA-RPS), Rome, Italy.|Interdisciplinary Research Institute USR3078, CNRS-Universit Lille Nord de France, Villeneuve dAscq, France.|Interdisciplinary Research Institute USR3078, CNRS-Universit Lille Nord de France, Villeneuve dAscq, France.|Department of Biology, University of Florence, Florence, Italy.|Department of Biology, University of Florence, Florence, Italy.', 'Italy|Italy|Italy|Italy|Italy|Italy|Italy|Italy|Italy|Italy|France|France|Italy|Italy', 0, 'Computational Biology|Evolution, Molecular|Gene Regulatory Networks|Genome, Bacterial|Models, Genetic|Sinorhizobium meliloti', 'Journal Article', '10.1371/journal.pcbi.1004478', '26340565', 'Reconstruction of the regulatory network is an important step in understanding how organisms control the expression of gene products and therefore phenotypes. Recent studies have pointed out the importance of regulatory network plasticity in bacterial adaptation and evolution. The evolution of such networks within and outside the species boundary is however still obscure. Sinorhizobium meliloti is an ideal species for such study, having three large replicons, many genomes available and a significant knowledge of its transcription factors (TF). Each replicon has a specific functional and evolutionary mark, which might also emerge from the analysis of their regulatory signatures. Here we have studied the plasticity of the regulatory network within and outside the S. meliloti species, looking for the presence of 41 TFs binding motifs in 51 strains and 5 related rhizobial species. We have detected a preference of several TFs for one of the three replicons, and the function of regulated genes was found to be in accordance with the overall replicon functional signature: house-keeping functions for the chromosome, metabolism for the chromid, symbiosis for the megaplasmid. This therefore suggests a replicon-specific wiring of the regulatory network in the S. meliloti species. At the same time a significant part of the predicted regulatory network is shared between the chromosome and the chromid, thus adding an additional layer by which the chromid integrates itself in the core genome. Furthermore, the regulatory network distance was found to be correlated with both promoter regions and accessory genome evolution inside the species, indicating that both pangenome compartments are involved in the regulatory network evolution. We also observed that genes which are not included in the species regulatory network are more likely to belong to the accessory genome, indicating that regulatory interactions should also be considered to predict gene conservation in bacterial pangenomes. '),
(87344, 2015, 'plos', 'A Dynamic Gene Regulatory Network Model That Recovers the Cyclic Behavior of Arabidopsis thaliana Cell Cycle', 'Ortiz-Gutiérrez, Elizabeth|García-Cruz, Karla|Azpeitia, Eugenio|Castillo, Aaron|Sánchez, María de la Paz|Álvarez-Buylla, Elena R', 'Instituto de Ecología, Universidad Nacional Autónoma de México, 3er Circuito Exterior, Junto a Jardín Botánico Exterior, México, D.F. CP 04510, México, Centro de Ciencias de la Complejidad-C3, Universidad Nacional Autónoma de México, Ciudad Universitaria, Apartado Postal 70-275, México, D.F. 04510, México.|Instituto de Ecología, Universidad Nacional Autónoma de México, 3er Circuito Exterior, Junto a Jardín Botánico Exterior, México, D.F. CP 04510, México.|Instituto de Ecología, Universidad Nacional Autónoma de México, 3er Circuito Exterior, Junto a Jardín Botánico Exterior, México, D.F. CP 04510, México, Centro de Ciencias de la Complejidad-C3, Universidad Nacional Autónoma de México, Ciudad Universitaria, Apartado Postal 70-275, México, D.F. 04510, México.|Instituto de Ecología, Universidad Nacional Autónoma de México, 3er Circuito Exterior, Junto a Jardín Botánico Exterior, México, D.F. CP 04510, México, Centro de Ciencias de la Complejidad-C3, Universidad Nacional Autónoma de México, Ciudad Universitaria, Apartado Postal 70-275, México, D.F. 04510, México.|Instituto de Ecología, Universidad Nacional Autónoma de México, 3er Circuito Exterior, Junto a Jardín Botánico Exterior, México, D.F. CP 04510, México.|Instituto de Ecología, Universidad Nacional Autónoma de México, 3er Circuito Exterior, Junto a Jardín Botánico Exterior, México, D.F. CP 04510, México, Centro de Ciencias de la Complejidad-C3, Universidad Nacional Autónoma de México, Ciudad Universitaria, Apartado Postal 70-275, México, D.F. 04510, México.', '-|-|-|-|-|-', 0, 'Arabidopsis|Cell Cycle|Computational Biology|Gene Regulatory Networks|Genes, Plant|Models, Genetic', 'Journal Article', '10.1371/journal.pcbi.1004486', '26340681', 'Cell cycle control is fundamental in eukaryotic development. Several modeling efforts have been used to integrate the complex network of interacting molecular components involved in cell cycle dynamics. In this paper, we aimed at recovering the regulatory logic upstream of previously known components of cell cycle control, with the aim of understanding the mechanisms underlying the emergence of the cyclic behavior of such components. We focus on Arabidopsis thaliana, but given that many components of cell cycle regulation are conserved among eukaryotes, when experimental data for this system was not available, we considered experimental results from yeast and animal systems. We are proposing a Boolean gene regulatory network (GRN) that converges into only one robust limit cycle attractor that closely resembles the cyclic behavior of the key cell-cycle molecular components and other regulators considered here. We validate the model by comparing our in silico configurations with data from loss- and gain-of-function mutants, where the endocyclic behavior also was recovered. Additionally, we approximate a continuous model and recovered the temporal periodic expression profiles of the cell-cycle molecular components involved, thus suggesting that the single limit cycle attractor recovered with the Boolean model is not an artifact of its discrete and synchronous nature, but rather an emergent consequence of the inherent characteristics of the regulatory logic proposed here. This dynamical model, hence provides a novel theoretical framework to address cell cycle regulation in plants, and it can also be used to propose novel predictions regarding cell cycle regulation in other eukaryotes. '),
(87345, 2015, 'plos', 'A Gene Gravity Model for the Evolution of Cancer Genomes: A Study of 3,000 Cancer Genomes across 9 Cancer Types', 'Cheng, Feixiong|Liu, Chuang|Lin, Chen-Ching|Zhao, Junfei|Jia, Peilin|Li, Wen-Hsiung|Zhao, Zhongming', 'Department of Biomedical Informatics, Vanderbilt University School of Medicine, Nashville, Tennessee, United States of America.|Alibaba Research Center for Complexity Sciences, Hangzhou Normal University, Hangzhou, Zhejiang, China.|Department of Biomedical Informatics, Vanderbilt University School of Medicine, Nashville, Tennessee, United States of America.|Department of Biomedical Informatics, Vanderbilt University School of Medicine, Nashville, Tennessee, United States of America.|Department of Biomedical Informatics, Vanderbilt University School of Medicine, Nashville, Tennessee, United States of America, Center for Quantitative Sciences, Vanderbilt University Medical Center, Nashville, Tennessee, United States of America.|Department of Ecology and Evolution, University of Chicago, Chicago, Illinois, United States of America, Biodiversity Research Center and Genomics Research Center, Academia Sinica, Taipei, Taiwan.|Department of Biomedical Informatics, Vanderbilt University School of Medicine, Nashville, Tennessee, United States of America, Center for Quantitative Sciences, Vanderbilt University Medical Center, Nashville, Tennessee, United States of America, Department of Cancer Biology, Vanderbilt University School of Medicine, Nashville, Tennessee, United States of America.', 'United States|China|United States|United States|United States|United States|United States', 38, 'Databases, Genetic|Female|Genome, Human|Genomics|Humans|Male|Models, Genetic|Mutation|Neoplasms', 'Journal Article', '10.1371/journal.pcbi.1004497', '26352260', 'Cancer development and progression result from somatic evolution by an accumulation of genomic alterations. The effects of those alterations on the fitness of somatic cells lead to evolutionary adaptations such as increased cell proliferation, angiogenesis, and altered anticancer drug responses. However, there are few general mathematical models to quantitatively examine how perturbations of a single gene shape subsequent evolution of the cancer genome. In this study, we proposed the gene gravity model to study the evolution of cancer genomes by incorporating the genome-wide transcription and somatic mutation profiles of ~3,000 tumors across 9 cancer types from The Cancer Genome Atlas into a broad gene network. We found that somatic mutations of a cancer driver gene may drive cancer genome evolution by inducing mutations in other genes. This functional consequence is often generated by the combined effect of genetic and epigenetic (e.g., chromatin regulation) alterations. By quantifying cancer genome evolution using the gene gravity model, we identified six putative cancer genes (AHNAK, COL11A1, DDX3X, FAT4, STAG2, and SYNE1). The tumor genomes harboring the nonsynonymous somatic mutations in these genes had a higher mutation density at the genome level compared to the wild-type groups. Furthermore, we provided statistical evidence that hypermutation of cancer driver genes on inactive X chromosomes is a general feature in female cancer genomes. In summary, this study sheds light on the functional consequences and evolutionary characteristics of somatic mutations during tumorigenesis by propelling adaptive cancer genome evolution, which would provide new perspectives for cancer research and therapeutics. '),
(87346, 2015, 'plos', 'Social Feedback and the Emergence of Rank in Animal Society', 'Hobson, Elizabeth A|DeDeo, Simon', 'National Institute for Mathematical and Biological Synthesis, University of Tennessee, Knoxville, Tennessee, United States of America, Department of Biology, New Mexico State University, Las Cruces, New Mexico, United States of America.|Department of Informatics, School of Informatics and Computing, Indiana University, Bloomington, Indiana, United States of America, Santa Fe Institute, Santa Fe, New Mexico, United States of America.', 'Mexico|India', 25, 'Aggression|Algorithms|Animals|Behavior, Animal|Computational Biology|Conflict (Psychology)|Feedback, Psychological|Parakeets|Social Dominance', 'Journal Article', '10.1371/journal.pcbi.1004411', '26355292', 'Dominance hierarchies are group-level properties that emerge from the aggression of individuals. Although individuals can gain critical benefits from their position in a hierarchy, we do not understand how real-world hierarchies form. Nor do we understand what signals and decision-rules individuals use to construct and maintain hierarchies in the absence of simple cues such as size or spatial location. A study of conflict in two groups of captive monk parakeets (Myiopsitta monachus) found that a transition to large-scale order in aggression occurred in newly-formed groups after one week, with individuals thereafter preferring to direct aggression more frequently against those nearby in rank. We consider two cognitive mechanisms underlying the emergence of this order: inference based on overall levels of aggression, or on subsets of the aggression network. Both mechanisms were predictive of individual decisions to aggress, but observed patterns were better explained by rank inference through subsets of the aggression network. Based on these results, we present a new theory, of a feedback loop between knowledge of rank and consequent behavior. This loop explains the transition to strategic aggression and the formation and persistence of dominance hierarchies in groups capable of both social memory and inference. '),
(87347, 2015, 'plos', 'Ten Simple Rules for a Computational Biologists Laboratory Notebook', 'Schnell, Santiago', 'Department of Molecular and Integrative Physiology, University of Michigan Medical School, Ann Arbor, Michigan, United States of America, Department of Computational Medicine and Bioinformatics, University of Michigan Medical School, Ann Arbor, Michigan, United States of America, Brehm Center for Diabetes Research, University of Michigan Medical School, Ann Arbor, Michigan, United States of America.', 'United States', 13, 'Computational Biology|Data Collection|Humans|Information Management', 'Editorial', '10.1371/journal.pcbi.1004385', '26356732', '-'),
(87348, 2015, 'plos', 'Steering Evolution with Sequential Therapy to Prevent the Emergence of Bacterial Antibiotic Resistance', 'Nichol, Daniel|Jeavons, Peter|Fletcher, Alexander G|Bonomo, Robert A|Maini, Philip K|Paul, Jerome L|Gatenby, Robert A|Anderson, Alexander R A|Scott, Jacob G', 'Department of Computer Science, University of Oxford, Oxford, United Kingdom, Department of Integrated Mathematical Oncology, H. Lee Moffitt Cancer Center and Research Institute, Tampa, Florida, United States of America.|Department of Computer Science, University of Oxford, Oxford, United Kingdom.|Wolfson Centre for Mathematical Biology, Mathematical Institute, University of Oxford, Oxford, United Kingdom.|Department of Medicine, Louis Stokes Department of Veterans Affairs Hospital, Cleveland Ohio, United States of America.|Wolfson Centre for Mathematical Biology, Mathematical Institute, University of Oxford, Oxford, United Kingdom.|School of Electrical Engineering and Computing Systems, University of Cincinnati, Cincinnati, Ohio, United States of America.|Department of Integrated Mathematical Oncology, H. Lee Moffitt Cancer Center and Research Institute, Tampa, Florida, United States of America.|Department of Integrated Mathematical Oncology, H. Lee Moffitt Cancer Center and Research Institute, Tampa, Florida, United States of America.|Department of Integrated Mathematical Oncology, H. Lee Moffitt Cancer Center and Research Institute, Tampa, Florida, United States of America, Wolfson Centre for Mathematical Biology, Mathematical Institute, University of Oxford, Oxford, United Kingdom.', 'United Kingdom|United Kingdom|United Kingdom|United States|United Kingdom|United States|United State', 0, 'Anti-Bacterial Agents|Computational Biology|Drug Resistance, Bacterial|Escherichia coli|Escherichia coli Infections|Evolution, Molecular|Genetic Fitness|Humans|Models, Biological|Selection, Genetic', 'Journal Article', '10.1371/journal.pcbi.1004493', '26360300', 'The increasing rate of antibiotic resistance and slowing discovery of novel antibiotic treatments presents a growing threat to public health. Here, we consider a simple model of evolution in asexually reproducing populations which considers adaptation as a biased random walk on a fitness landscape. This model associates the global properties of the fitness landscape with the algebraic properties of a Markov chain transition matrix and allows us to derive general results on the non-commutativity and irreversibility of natural selection as well as antibiotic cycling strategies. Using this formalism, we analyze 15 empirical fitness landscapes of E. coli under selection by different xcexb2-lactam antibiotics and demonstrate that the emergence of resistance to a given antibiotic can be either hindered or promoted by different sequences of drug application. Specifically, we demonstrate that the majority, approximately 70%, of sequential drug treatments with 2-4 drugs promote resistance to the final antibiotic. Further, we derive optimal drug application sequences with which we can probabilistically steer the population through genotype space to avoid the emergence of resistance. This suggests a new strategy in the war against antibiotic-resistant organisms: drug sequencing to shepherd evolution through genotype space to states from which resistance cannot emerge and by which to maximize the chance of successful therapy. '),
(87349, 2015, 'plos', 'The Internal Dynamics of Fibrinogen and Its Implications for Coagulation and Adsorption', 'Köhler, Stephan|Schmid, Friederike|Settanni, Giovanni', 'Institut für Physik, Johannes Gutenberg-Universität Mainz, Mainz, Germany, Graduate School Materials Science in Mainz, Mainz, Germany.|Institut für Physik, Johannes Gutenberg-Universität Mainz, Mainz, Germany.|Institut für Physik, Johannes Gutenberg-Universität Mainz, Mainz, Germany, Max Planck Graduate Center mit der Johannes Gutenberg-Universität Mainz, Mainz, Germany.', 'Germany|Germany|Germany', 27, 'Adsorption|Blood Coagulation|Computational Biology|Fibrinogen|Humans|Molecular Dynamics Simulation|Protein Binding', 'Journal Article', '10.1371/journal.pcbi.1004346', '26366880', 'Fibrinogen is a serum multi-chain protein which, when activated, aggregates to form fibrin, one of the main components of a blood clot. Fibrinolysis controls blood clot dissolution through the action of the enzyme plasmin, which cleaves fibrin at specific locations. Although the main biochemical factors involved in fibrin formation and lysis have been identified, a clear mechanistic picture of how these processes take place is not available yet. This picture would be instrumental, for example, for the design of improved thrombolytic or anti-haemorrhagic strategies, as well as, materials with improved biocompatibility. Here, we present extensive molecular dynamics simulations of fibrinogen which reveal large bending motions centered at a hinge point in the coiled-coil regions of the molecule. This feature, likely conserved across vertebrates according to our analysis, suggests an explanation for the mechanism of exposure to lysis of the plasmin cleavage sites on fibrinogen coiled-coil region. It also explains the conformational variability of fibrinogen observed during its adsorption on inorganic surfaces and it is supposed to play a major role in the determination of the hydrodynamic properties of fibrinogen. In addition the simulations suggest how the dynamics of the D region of fibrinogen may contribute to the allosteric regulation of the blood coagulation cascade through a dynamic coupling between the a- and b-holes, important for fibrin polymerization, and the integrin binding site P1. ');
INSERT INTO `papers` (`id`, `ano`, `journal`, `titulo`, `autores`, `afiliacao`, `pais`, `citacoes`, `palavra_chave`, `categorias`, `doi`, `pubmed`, `abstract`) VALUES
(87350, 2015, 'plos', 'Dynamical Organization of Syntaxin-1A at the Presynaptic Active Zone', 'Ullrich, Alexander|Böhme, Mathias A|Schöneberg, Johannes|Depner, Harald|Sigrist, Stephan J|Noé, Frank', 'Department of Mathematics, Freie Universität Berlin, Berlin, Germany.|Institute for Biology/Genetics, Freie Universität Berlin, Berlin, Germany, NeuroCure Cluster of Excellence, Charité Berlin, Berlin, Germany.|Department of Mathematics, Freie Universität Berlin, Berlin, Germany.|Institute for Biology/Genetics, Freie Universität Berlin, Berlin, Germany.|Institute for Biology/Genetics, Freie Universität Berlin, Berlin, Germany, NeuroCure Cluster of Excellence, Charité Berlin, Berlin, Germany.|Department of Mathematics, Freie Universität Berlin, Berlin, Germany.', 'Germany|Germany|Germany|Germany|Germany|Germany', 34, 'Animals|Computational Biology|Drosophila|Image Processing, Computer-Assisted|Larva|Microscopy|Models, Biological|Synapses|Synaptic Vesicles|Syntaxin 1', 'Journal Article', '10.1371/journal.pcbi.1004407', '26367029', 'Synaptic vesicle fusion is mediated by SNARE proteins forming in between synaptic vesicle (v-SNARE) and plasma membrane (t-SNARE), one of which is Syntaxin-1A. Although exocytosis mainly occurs at active zones, Syntaxin-1A appears to cover the entire neuronal membrane. By using STED super-resolution light microscopy and image analysis of Drosophila neuro-muscular junctions, we show that Syntaxin-1A clusters are more abundant and have an increased size at active zones. A computational particle-based model of syntaxin cluster formation and dynamics is developed. The model is parametrized to reproduce Syntaxin cluster-size distributions found by STED analysis, and successfully reproduces existing FRAP results. The model shows that the neuronal membrane is adjusted in a way to strike a balance between having most syntaxins stored in large clusters, while still keeping a mobile fraction of syntaxins free or in small clusters that can efficiently search the membrane or be traded between clusters. This balance is subtle and can be shifted toward almost no clustering and almost complete clustering by modifying the syntaxin interaction energy on the order of only 1 kBT. This capability appears to be exploited at active zones. The larger active-zone syntaxin clusters are more stable and provide regions of high docking and fusion capability, whereas the smaller clusters outside may serve as flexible reserve pool or sites of spontaneous ectopic release. '),
(87351, 2015, 'plos', 'Diversity Waves in Collapse-Driven Population Dynamics', 'Maslov, Sergei|Sneppen, Kim', 'Department of Bioengineering, University of Illinois Urbana-Champaign, Champaign, Illinois, United States of America, Carl R. Woese Institute for Genomic Biology, University of Illinois Urbana-Champaign, Champaign, Illinois, United States of America, Biological, Environmental and Climate Sciences Department, Brookhaven National Laboratory, Upton, New York, United States of America.|Center for Models of Life, Niels Bohr Institute, University of Copenhagen, Copenhagen, Denmark.', 'United States|Denmark', 4, 'Bacteria|Bacteriophages|Biodiversity|Computational Biology|Economics|Ecosystem|Genetic Speciation|Models, Theoretical|Population Dynamics', 'Journal Article', '10.1371/journal.pcbi.1004440', '26367172', 'Populations of species in ecosystems are often constrained by availability of resources within their environment. In effect this means that a growth of one population, needs to be balanced by comparable reduction in populations of others. In neutral models of biodiversity all populations are assumed to change incrementally due to stochastic births and deaths of individuals. Here we propose and model another redistribution mechanism driven by abrupt and severe reduction in size of the population of a single species freeing up resources for the remaining ones. This mechanism may be relevant e.g. for communities of bacteria, with strain-specific collapses caused e.g. by invading bacteriophages, or for other ecosystems where infectious diseases play an important role. The emergent dynamics of our system is characterized by cyclic diversity waves triggered by collapses of globally dominating populations. The population diversity peaks at the beginning of each wave and exponentially decreases afterwards. Species abundances have bimodal time-aggregated distribution with the lower peak formed by populations of recently collapsed or newly introduced species while the upper peak--species that has not yet collapsed in the current wave. In most waves both upper and lower peaks are composed of several smaller peaks. This self-organized hierarchical peak structure has a long-term memory transmitted across several waves. It gives rise to a scale-free tail of the time-aggregated population distribution with a universal exponent of 1.7. We show that diversity wave dynamics is robust with respect to variations in the rules of our model such as diffusion between multiple environments, species-specific growth and extinction rates, and bet-hedging strategies.'),
(87352, 2015, 'plos', 'Prospective Optimization with Limited Resources', 'Snider, Joseph|Lee, Dongpyo|Poizner, Howard|Gepshtein, Sergei', 'Institute for Neural Computation, University of California at San Diego, La Jolla, California, United States of America.|Institute for Neural Computation, University of California at San Diego, La Jolla, California, United States of America.|Institute for Neural Computation, University of California at San Diego, La Jolla, California, United States of America, Graduate Program in Neurosciences, University of California at San Diego, La Jolla, California, United States of America.|Systems Neurobiology Laboratories, Salk Institute for Biological Studies, La Jolla, California, United States of America.', 'United States|United States|United States|United States', 6, 'Adult|Algorithms|Computational Biology|Decision Making|Female|Humans|Male|Reward|Task Performance and Analysis|Uncertainty|Young Adult', 'Journal Article', '10.1371/journal.pcbi.1004501', '26367309', 'The future is uncertain because some forthcoming events are unpredictable and also because our ability to foresee the myriad consequences of our own actions is limited. Here we studied how humans select actions under such extrinsic and intrinsic uncertainty, in view of an exponentially expanding number of prospects on a branching multivalued visual stimulus. A triangular grid of disks of different sizes scrolled down a touchscreen at a variable speed. The larger disks represented larger rewards. The task was to maximize the cumulative reward by touching one disk at a time in a rapid sequence, forming an upward path across the grid, while every step along the path constrained the part of the grid accessible in the future. This task captured some of the complexity of natural behavior in the risky and dynamic world, where ongoing decisions alter the landscape of future rewards. By comparing human behavior with behavior of ideal actors, we identified the strategies used by humans in terms of how far into the future they looked (their depth of computation) and how often they attempted to incorporate new information about the future rewards (their recalculation period). We found that, for a given task difficulty, humans traded off their depth of computation for the recalculation period. The form of this tradeoff was consistent with a complete, brute-force exploration of all possible paths up to a resource-limited finite depth. A step-by-step analysis of the human behavior revealed that participants took into account very fine distinctions between the future rewards and that they abstained from some simple heuristics in assessment of the alternative paths, such as seeking only the largest disks or avoiding the smaller disks. The participants preferred to reduce their depth of computation or increase the recalculation period rather than sacrifice the precision of computation. '),
(87353, 2015, 'plos', 'Shaping Neuronal Network Activity by Presynaptic Mechanisms', 'Lavi, Ayal|Perez, Omri|Ashery, Uri', 'Department of Neurobiology, Life Sciences Institute, Tel Aviv University, Tel Aviv, Israel, Sagol School of Neuroscience, Tel Aviv University, Tel Aviv, Israel.|Sagol School of Neuroscience, Tel Aviv University, Tel Aviv, Israel, Sackler School of Medicine, Tel Aviv University, Tel Aviv, Israel.|Department of Neurobiology, Life Sciences Institute, Tel Aviv University, Tel Aviv, Israel, Sagol School of Neuroscience, Tel Aviv University, Tel Aviv, Israel.', 'Israel|Israel|Israel', 0, 'Animals|Computational Biology|Computer Simulation|Humans|Models, Neurological|Nerve Net|Neurons|Rats|Synaptic Transmission', 'Journal Article', '10.1371/journal.pcbi.1004438', '26372048', 'Neuronal microcircuits generate oscillatory activity, which has been linked to basic functions such as sleep, learning and sensorimotor gating. Although synaptic release processes are well known for their ability to shape the interaction between neurons in microcircuits, most computational models do not simulate the synaptic transmission process directly and hence cannot explain how changes in synaptic parameters alter neuronal network activity. In this paper, we present a novel neuronal network model that incorporates presynaptic release mechanisms, such as vesicle pool dynamics and calcium-dependent release probability, to model the spontaneous activity of neuronal networks. The model, which is based on modified leaky integrate-and-fire neurons, generates spontaneous network activity patterns, which are similar to experimental data and robust under changes in the models primary gain parameters such as excitatory postsynaptic potential and connectivity ratio. Furthermore, it reliably recreates experimental findings and provides mechanistic explanations for data obtained from microelectrode array recordings, such as network burst termination and the effects of pharmacological and genetic manipulations. The model demonstrates how elevated asynchronous release, but not spontaneous release, synchronizes neuronal network activity and reveals that asynchronous release enhances utilization of the recycling vesicle pool to induce the network effect. The model further predicts a positive correlation between vesicle priming at the single-neuron level and burst frequency at the network level, this prediction is supported by experimental findings. Thus, the model is utilized to reveal how synaptic release processes at the neuronal level govern activity patterns and synchronization at the network level. '),
(87354, 2015, 'plos', 'Structural Bridges through Fold Space', 'Edwards, Hannah|Deane, Charlotte M', 'Department of Statistics, University of Oxford, Oxford, United Kingdom.|Department of Statistics, University of Oxford, Oxford, United Kingdom.', 'United Kingdom|United Kingdom', 7, 'Algorithms|Computational Biology|Protein Conformation|Protein Folding|Proteins', 'Journal Article', '10.1371/journal.pcbi.1004466', '26372166', 'Several protein structure classification schemes exist that partition the protein universe into structural units called folds. Yet these schemes do not discuss how these units sit relative to each other in a global structure space. In this paper we construct networks that describe such global relationships between folds in the form of structural bridges. We generate these networks using four different structural alignment methods across multiple score thresholds. The networks constructed using the different methods remain a similar distance apart regardless of the probability threshold defining a structural bridge. This suggests that at least some structural bridges are method specific and that any attempt to build a picture of structural space should not be reliant on a single structural superposition method. Despite these differences all representations agree on an organisation of fold space into five principal community structures: all-xcexb1, all-xcexb2 sandwiches, all-xcexb2 barrels, xcexb1/xcexb2 and xcexb1 + xcexb2. We project estimated fold ages onto the networks and find that not only are the pairings of unconnected folds associated with higher age differences than bridged folds, but this difference increases with the number of networks displaying an edge. We also examine different centrality measures for folds within the networks and how these relate to fold age. While these measures interpret the central core of fold space in varied ways they all identify the disposition of ancestral folds to fall within this core and that of the more recently evolved structures to provide the peripheral landscape. These findings suggest that evolutionary information is encoded along these structural bridges. Finally, we identify four highly central pivotal folds representing dominant topological features which act as key attractors within our landscapes. '),
(87355, 2015, 'plos', 'The Problem with Phi: A Critique of Integrated Information Theory', 'Cerullo, Michael A', 'Cincinnati Institute for Cognitive Science, Cincinnati, Ohio, United States of America.', 'United States', 0, 'Algorithms|Biomedical Research|Consciousness|Humans|Information Theory|Models, Neurological|Split-Brain Procedure', 'Journal Article', '10.1371/journal.pcbi.1004286', '26378789', '-'),
(87356, 2015, 'plos', 'Bioinformatics in Africa: The Rise of Ghana?', 'Karikari, Thomas K', 'Department of Science Laboratory Technology, School of Applied Science and Technology, Wa Polytechnic, Wa, Ghana.', 'Ghana', 26, 'Computational Biology|Developing Countries|Ghana|Humans', 'Journal Article', '10.1371/journal.pcbi.1004308', '26378921', 'Until recently, bioinformatics, an important discipline in the biological sciences, was largely limited to countries with advanced scientific resources. Nonetheless, several developing countries have lately been making progress in bioinformatics training and applications. In Africa, leading countries in the discipline include South Africa, Nigeria, and Kenya. However, one country that is less known when it comes to bioinformatics is Ghana. Here, I provide a first description of the development of bioinformatics activities in Ghana and how these activities contribute to the overall development of the discipline in Africa. Over the past decade, scientists in Ghana have been involved in publications incorporating bioinformatics analyses, aimed at addressing research questions in biomedical science and agriculture. Scarce research funding and inadequate training opportunities are some of the challenges that need to be addressed for Ghanaian scientists to continue developing their expertise in bioinformatics. '),
(87357, 2015, 'plos', 'An Evolutionary Approach for Identifying Driver Mutations in Colorectal Cancer', 'Foo, Jasmine|Liu, Lin L|Leder, Kevin|Riester, Markus|Iwasa, Yoh|Lengauer, Christoph|Michor, Franziska', 'Department of Mathematics, University of Minnesota Twin Cities, St. Paul, Minnesota, United States of America.|Department of Biostatistics and Computational Biology, Dana-Farber Cancer Institute, and Department of Biostatistics, Harvard T. H. Chan School of Public Health, Boston, Massachusetts, United States of America.|Industrial and Systems Engineering, University of Minnesota Twin Cities, St. Paul, Minnesota, United States of America.|Department of Biostatistics and Computational Biology, Dana-Farber Cancer Institute, and Department of Biostatistics, Harvard T. H. Chan School of Public Health, Boston, Massachusetts, United States of America.|Department of Biology, Kyushu University, Fukuoka, Japan.|Blueprint Medicines, Cambridge, Massachusetts, United States of America.|Department of Biostatistics and Computational Biology, Dana-Farber Cancer Institute, and Department of Biostatistics, Harvard T. H. Chan School of Public Health, Boston, Massachusetts, United States of America.', 'United States|United States|United States|United States|Japan|United States|United States', 0, 'Colorectal Neoplasms|Computational Biology|Cross-Sectional Studies|Evolution, Molecular|Humans|Models, Genetic|Models, Statistical|Mutation|Population Dynamics', 'Journal Article', '10.1371/journal.pcbi.1004350', '26379039', 'The traditional view of cancer as a genetic disease that can successfully be treated with drugs targeting mutant onco-proteins has motivated whole-genome sequencing efforts in many human cancer types. However, only a subset of mutations found within the genomic landscape of cancer is likely to provide a fitness advantage to the cell. Distinguishing such driver mutations from innocuous passenger events is critical for prioritizing the validation of candidate mutations in disease-relevant models. We design a novel statistical index, called the Hitchhiking Index, which reflects the probability that any observed candidate gene is a passenger alteration, given the frequency of alterations in a cross-sectional cancer sample set, and apply it to a mutational data set in colorectal cancer. Our methodology is based upon a population dynamics model of mutation accumulation and selection in colorectal tissue prior to cancer initiation as well as during tumorigenesis. This methodology can be used to aid in the prioritization of candidate mutations for functional validation and contributes to the process of drug discovery. '),
(87358, 2015, 'plos', 'A Method to Constrain Genome-Scale Models with 13C Labeling Data', 'Martín, Héctor García|Kumar, Vinay Satish|Weaver, Daniel|Ghosh, Amit|Chubukov, Victor|Mukhopadhyay, Aindrila|Arkin, Adam|Keasling, Jay D', 'Physical Biosciences Division, Lawrence Berkeley National Laboratory, Berkeley, United States of America, Joint BioEnergy Institute, Emeryville, United States of America.|Physical Biosciences Division, Lawrence Berkeley National Laboratory, Berkeley, United States of America, Joint BioEnergy Institute, Emeryville, United States of America.|Physical Biosciences Division, Lawrence Berkeley National Laboratory, Berkeley, United States of America, Joint BioEnergy Institute, Emeryville, United States of America.|Physical Biosciences Division, Lawrence Berkeley National Laboratory, Berkeley, United States of America, Joint BioEnergy Institute, Emeryville, United States of America.|Physical Biosciences Division, Lawrence Berkeley National Laboratory, Berkeley, United States of America, Joint BioEnergy Institute, Emeryville, United States of America.|Physical Biosciences Division, Lawrence Berkeley National Laboratory, Berkeley, United States of America, Joint BioEnergy Institute, Emeryville, United States of America.|Physical Biosciences Division, Lawrence Berkeley National Laboratory, Berkeley, United States of America, Department of Bioengineering, University of California, Berkeley, Berkely, United States of America.|Physical Biosciences Division, Lawrence Berkeley National Laboratory, Berkeley, United States of America, Joint BioEnergy Institute, Emeryville, United States of America, Department of Bioengineering, University of California, Berkeley, Berkely, United States of America, Department of Chemical Engineering, University of California, Berkeley, Berkeley, United States of America.', 'United States|United States|United States|United States|United States|United States|United States|Un', 36, 'Algorithms|Carbon Isotopes|Escherichia coli|Gene Knockout Techniques|Genome, Bacterial|Metabolic Engineering|Metabolic Flux Analysis|Models, Biological|Systems Biology', 'Journal Article', '10.1371/journal.pcbi.1004363', '26379153', 'Current limitations in quantitatively predicting biological behavior hinder our efforts to engineer biological systems to produce biofuels and other desired chemicals. Here, we present a new method for calculating metabolic fluxes, key targets in metabolic engineering, that incorporates data from 13C labeling experiments and genome-scale models. The data from 13C labeling experiments provide strong flux constraints that eliminate the need to assume an evolutionary optimization principle such as the growth rate optimization assumption used in Flux Balance Analysis (FBA). This effective constraining is achieved by making the simple but biologically relevant assumption that flux flows from core to peripheral metabolism and does not flow back. The new method is significantly more robust than FBA with respect to errors in genome-scale model reconstruction. Furthermore, it can provide a comprehensive picture of metabolite balancing and predictions for unmeasured extracellular fluxes as constrained by 13C labeling data. A comparison shows that the results of this new method are similar to those found through 13C Metabolic Flux Analysis (13C MFA) for central carbon metabolism but, additionally, it provides flux estimates for peripheral metabolism. The extra validation gained by matching 48 relative labeling measurements is used to identify where and why several existing COnstraint Based Reconstruction and Analysis (COBRA) flux prediction algorithms fail. We demonstrate how to use this knowledge to refine these methods and improve their predictive capabilities. This method provides a reliable base upon which to improve the design of biological systems. '),
(87359, 2015, 'plos', 'Model-Based Reasoning in Humans Becomes Automatic with Training', 'Economides, Marcos|Kurth-Nelson, Zeb|Lübbert, Annika|Guitart-Masip, Marc|Dolan, Raymond J', 'Wellcome Trust Centre for Neuroimaging, Institute of Neurology, University College London, London, United Kingdom.|Wellcome Trust Centre for Neuroimaging, Institute of Neurology, University College London, London, United Kingdom, Max Planck Centre for Computational Psychiatry and Ageing, University College London, London, United Kingdom.|Wellcome Trust Centre for Neuroimaging, Institute of Neurology, University College London, London, United Kingdom.|Wellcome Trust Centre for Neuroimaging, Institute of Neurology, University College London, London, United Kingdom, Ageing Research Centre, Karolinska Institute, Stockholm, Sweden.|Wellcome Trust Centre for Neuroimaging, Institute of Neurology, University College London, London, United Kingdom, Max Planck Centre for Computational Psychiatry and Ageing, University College London, London, United Kingdom.', 'United Kingdom|United Kingdom|United Kingdom|United Kingdom|United Kingdom', 0, 'Adolescent|Adult|Algorithms|Computational Biology|Decision Making|Female|Humans|Male|Models, Biological|Reinforcement (Psychology)|Reward|Task Performance and Analysis|Young Adult', 'Journal Article', '10.1371/journal.pcbi.1004463', '26379239', 'Model-based and model-free reinforcement learning (RL) have been suggested as algorithmic realizations of goal-directed and habitual action strategies. Model-based RL is more flexible than model-free but requires sophisticated calculations using a learnt model of the world. This has led model-based RL to be identified with slow, deliberative processing, and model-free RL with fast, automatic processing. In support of this distinction, it has recently been shown that model-based reasoning is impaired by placing subjects under cognitive load--a hallmark of non-automaticity. Here, using the same task, we show that cognitive load does not impair model-based reasoning if subjects receive prior training on the task. This finding is replicated across two studies and a variety of analysis methods. Thus, task familiarity permits use of model-based reasoning in parallel with other cognitive demands. The ability to deploy model-based reasoning in an automatic, parallelizable fashion has widespread theoretical implications, particularly for the learning and execution of complex behaviors. It also suggests a range of important failure modes in psychiatric disorders.'),
(87360, 2015, 'plos', 'Efficient Optimization of Stimuli for Model-Based Design of Experiments to Resolve Dynamical Uncertainty', 'Mdluli, Thembi|Buzzard, Gregery T|Rundell, Ann E', 'Weldon School of Biomedical Engineering, Purdue University, West Lafayette, Indiana, United States of America.|Mathematics Department, Purdue University, West Lafayette, Indiana, United States of America.|Weldon School of Biomedical Engineering, Purdue University, West Lafayette, Indiana, United States of America.', 'India|India|India', 9, 'Algorithms|Models, Biological|Research Design|Systems Biology', 'Journal Article', '10.1371/journal.pcbi.1004488', '26379275', 'This model-based design of experiments (MBDOE) method determines the input magnitudes of an experimental stimuli to apply and the associated measurements that should be taken to optimally constrain the uncertain dynamics of a biological system under study. The ideal global solution for this experiment design problem is generally computationally intractable because of parametric uncertainties in the mathematical model of the biological system. Others have addressed this issue by limiting the solution to a local estimate of the model parameters. Here we present an approach that is independent of the local parameter constraint. This approach is made computationally efficient and tractable by the use of: (1) sparse grid interpolation that approximates the biological system dynamics, (2) representative parameters that uniformly represent the data-consistent dynamical space, and (3) probability weights of the represented experimentally distinguishable dynamics. Our approach identifies data-consistent representative parameters using sparse grid interpolants, constructs the optimal input sequence from a greedy search, and defines the associated optimal measurements using a scenario tree. We explore the optimality of this MBDOE algorithm using a 3-dimensional Hes1 model and a 19-dimensional T-cell receptor model. The 19-dimensional T-cell model also demonstrates the MBDOE algorithms scalability to higher dimensions. In both cases, the dynamical uncertainty region that bounds the trajectories of the target system states were reduced by as much as 86% and 99% respectively after completing the designed experiments in silico. Our results suggest that for resolving dynamical uncertainty, the ability to design an input sequence paired with its associated measurements is particularly important when limited by the number of measurements. '),
(87361, 2015, 'plos', 'Multiscale Mechanical Model of the Pacinian Corpuscle Shows Depth and Anisotropy Contribute to the Receptors Characteristic Response to Indentation', 'Quindlen, Julia C|Lai, Victor K|Barocas, Victor H', 'Department of Biomedical Engineering, University of Minnesota, Minneapolis, Minnesota, United States of America.|Department of Chemical Engineering, University of Minnesota, Duluth, Minnesota, United States of America.|Department of Biomedical Engineering, University of Minnesota, Minneapolis, Minnesota, United States of America.', 'United States|United States|United States', 0, 'Anisotropy|Computational Biology|Humans|Models, Biological|Pacinian Corpuscles', 'Journal Article', '10.1371/journal.pcbi.1004370', '26390130', 'Cutaneous mechanoreceptors transduce different tactile stimuli into neural signals that produce distinct sensations of touch. The Pacinian corpuscle (PC), a cutaneous mechanoreceptor located deep within the dermis of the skin, detects high frequency vibrations that occur within its large receptive field. The PC is comprised of lamellae that surround the nerve fiber at its core. We hypothesized that a layered, anisotropic structure, embedded deep within the skin, would produce the nonlinear strain transmission and low spatial sensitivity characteristic of the PC. A multiscale finite-element model was used to model the equilibrium response of the PC to indentation. The first simulation considered an isolated PC with fiber networks aligned with the PCs surface. The PC was subjected to a 10 xcexbcm indentation by a 250 xcexbcm diameter indenter. The multiscale model captured the nonlinear strain transmission through the PC, predicting decreased compressive strain with proximity to the receptors core, as seen experimentally by others. The second set of simulations considered a single PC embedded epidermally (shallow) or dermally (deep) to model the PCs location within the skin. The embedded models were subjected to 10 xcexbcm indentations at a series of locations on the surface of the skin. Strain along the long axis of the PC was calculated after indentation to simulate stretch along the nerve fiber at the center of the PC. Receptive fields for the epidermis and dermis models were constructed by mapping the long-axis strain after indentation at each point on the surface of the skin mesh. The dermis model resulted in a larger receptive field, as the calculated strain showed less indenter location dependence than in the epidermis model. '),
(87362, 2015, 'plos', 'Automated Identification of Core Regulatory Genes in Human Gene Regulatory Networks', 'Narang, Vipin|Ramli, Muhamad Azfar|Singhal, Amit|Kumar, Pavanish|de Libero, Gennaro|Poidinger, Michael|Monterola, Christopher', 'Singapore Immunology Network, Singapore.|Institute of High Performance Computing, Singapore.|Singapore Immunology Network, Singapore.|Singapore Immunology Network, Singapore.|Singapore Immunology Network, Singapore.|Singapore Immunology Network, Singapore.|Institute of High Performance Computing, Singapore.', 'Singapore|Singapore|Singapore|Singapore|Singapore|Singapore|Singapore', 19, 'Algorithms|Biomarkers, Tumor|Breast Neoplasms|Cell Line, Tumor|Computational Biology|Databases, Genetic|Estrogens|Female|Gene Expression Profiling|Gene Regulatory Networks|Humans', 'Journal Article', '10.1371/journal.pcbi.1004504', '26393364', 'Human gene regulatory networks (GRN) can be difficult to interpret due to a tangle of edges interconnecting thousands of genes. We constructed a general human GRN from extensive transcription factor and microRNA target data obtained from public databases. In a subnetwork of this GRN that is active during estrogen stimulation of MCF-7 breast cancer cells, we benchmarked automated algorithms for identifying core regulatory genes (transcription factors and microRNAs). Among these algorithms, we identified K-core decomposition, pagerank and betweenness centrality algorithms as the most effective for discovering core regulatory genes in the network evaluated based on previously known roles of these genes in MCF-7 biology as well as in their ability to explain the up or down expression status of up to 70% of the remaining genes. Finally, we validated the use of K-core algorithm for organizing the GRN in an easier to interpret layered hierarchy where more influential regulatory genes percolate towards the inner layers. The integrated human gene and miRNA network and software used in this study are provided as supplementary materials (S1 Data) accompanying this manuscript. '),
(87363, 2015, 'plos', 'Systematic Prediction of Scaffold Proteins Reveals New Design Principles in Scaffold-Mediated Signal Transduction', 'Hu, Jianfei|Neiswinger, Johnathan|Zhang, Jin|Zhu, Heng|Qian, Jiang', 'Department of Ophthalmology, Johns Hopkins School of Medicine, Baltimore, Maryland, United States of America.|Department of Pharmacology and Molecular Sciences, Johns Hopkins School of Medicine, Baltimore, Maryland, United States of America.|Department of Pharmacology and Molecular Sciences, Johns Hopkins School of Medicine, Baltimore, Maryland, United States of America, The Sidney Kimmel Comprehensive Cancer Center, Johns Hopkins School of Medicine, Baltimore, Maryland, United States of America, Solomon H. Snyder Department of Neuroscience, Johns Hopkins School of Medicine, Baltimore, Maryland, United States of America.|Department of Pharmacology and Molecular Sciences, Johns Hopkins School of Medicine, Baltimore, Maryland, United States of America, The Sidney Kimmel Comprehensive Cancer Center, Johns Hopkins School of Medicine, Baltimore, Maryland, United States of America, Center for High-Throughput Biology, Johns Hopkins School of Medicine, Baltimore, Maryland, United States of America.|Department of Ophthalmology, Johns Hopkins School of Medicine, Baltimore, Maryland, United States of America, The Sidney Kimmel Comprehensive Cancer Center, Johns Hopkins School of Medicine, Baltimore, Maryland, United States of America.', 'United States|United States|United States|United States|United States', 9, 'Computational Biology|Humans|Models, Biological|Phosphorylation|Protein Interaction Maps|Proteins|Signal Transduction', 'Journal Article', '10.1371/journal.pcbi.1004508', '26393507', 'Scaffold proteins play a crucial role in facilitating signal transduction in eukaryotes by bringing together multiple signaling components. In this study, we performed a systematic analysis of scaffold proteins in signal transduction by integrating protein-protein interaction and kinase-substrate relationship networks. We predicted 212 scaffold proteins that are involved in 605 distinct signaling pathways. The computational prediction was validated using a protein microarray-based approach. The predicted scaffold proteins showed several interesting characteristics, as we expected from the functionality of scaffold proteins. We found that the scaffold proteins are likely to interact with each other, which is consistent with previous finding that scaffold proteins tend to form homodimers and heterodimers. Interestingly, a single scaffold protein can be involved in multiple signaling pathways by interacting with other scaffold protein partners. Furthermore, we propose two possible regulatory mechanisms by which the activity of scaffold proteins is coordinated with their associated pathways through phosphorylation process. '),
(87364, 2015, 'plos', 'The LUX Score: A Metric for Lipidome Homology', 'Marella, Chakravarthy|Torda, Andrew E|Schwudke, Dominik', 'Division of Bioanalytical Chemistry, Research Center Borstel, Leibniz-Center for Medicine and Biosciences, Borstel, SH, Germany, National Centre for Biological Sciences, Tata Institute of Fundamental Research, Bangalore, KA, India.|Centre for Bioinformatics, University of Hamburg, Hamburg, Germany.|Division of Bioanalytical Chemistry, Research Center Borstel, Leibniz-Center for Medicine and Biosciences, Borstel, SH, Germany, National Centre for Biological Sciences, Tata Institute of Fundamental Research, Bangalore, KA, India, Airway Research Center North, German Center for Lung Research, Grosshansdorf, SH, Germany, German Center for Infection Research, TTU-Tb, Borstel, SH, Germany.', 'Germany|Germany|Germany', 0, 'Algorithms|Animals|Computational Biology|Drosophila|Isomerism|Lipids|Models, Biological|Models, Molecular|Organ Specificity', 'Journal Article', '10.1371/journal.pcbi.1004511', '26393792', 'A lipidome is the set of lipids in a given organism, cell or cell compartment and this set reflects the organisms synthetic pathways and interactions with its environment. Recently, lipidomes of biological model organisms and cell lines were published and the number of functional studies of lipids is increasing. In this study we propose a homology metric that can quantify systematic differences in the composition of a lipidome. Algorithms were developed to 1. consistently convert lipids structure into SMILES, 2. determine structural similarity between molecular species and 3. describe a lipidome in a chemical space model. We tested lipid structure conversion and structure similarity metrics, in detail, using sets of isomeric ceramide molecules and chemically related phosphatidylinositols. Template-based SMILES showed the best properties for representing lipid-specific structural diversity. We also show that sequence analysis algorithms are best suited to calculate distances between such template-based SMILES and we adjudged the Levenshtein distance as best choice for quantifying structural changes. When all lipid molecules of the LIPIDMAPS structure database were mapped in chemical space, they automatically formed clusters corresponding to conventional chemical families. Accordingly, we mapped a pair of lipidomes into the same chemical space and determined the degree of overlap by calculating the Hausdorff distance. We named this metric the Lipidome jUXtaposition (LUX) score. First, we tested this approach for estimating the lipidome similarity on four yeast strains with known genetic alteration in fatty acid synthesis. We show that the LUX score reflects the genetic relationship and growth temperature better than conventional methods although the score is based solely on lipid structures. Next, we applied this metric to high-throughput data of larval tissue lipidomes of Drosophila. This showed that the LUX score is sufficient to cluster tissues and determine the impact of nutritional changes in an unbiased manner, despite the limited information on the underlying structural diversity of each lipidome. This study is the first effort to define a lipidome homology metric based on structures that will enrich functional association of lipids in a similar manner to measures used in genetics. Finally, we discuss the significance of the LUX score to perform comparative lipidome studies across species borders. '),
(87365, 2015, 'plos', 'Dynamic Integration of Value Information into a Common Probability Currency as a Theory for Flexible Decision Making', 'Christopoulos, Vassilios|Schrater, Paul R', 'Division of Biology and Biological Engineering, California Institute of Technology, Pasadena, California, United States of America.|Department of Psychology, University of Minnesota, Minneapolis, Minnesota, United States of America, Department of Computer Science & Engineering, University of Minnesota, Minneapolis, Minnesota, United States of America.', 'United States|United States', 14, 'Brain|Computational Biology|Decision Making|Goals|Humans|Models, Theoretical|Psychomotor Performance', 'Journal Article', '10.1371/journal.pcbi.1004402', '26394299', 'Decisions involve two fundamental problems, selecting goals and generating actions to pursue those goals. While simple decisions involve choosing a goal and pursuing it, humans evolved to survive in hostile dynamic environments where goal availability and value can change with time and previous actions, entangling goal decisions with action selection. Recent studies suggest the brain generates concurrent action-plans for competing goals, using online information to bias the competition until a single goal is pursued. This creates a challenging problem of integrating information across diverse types, including both the dynamic value of the goal and the costs of action. We model the computations underlying dynamic decision-making with disparate value types, using the probability of getting the highest pay-off with the least effort as a common currency that supports goal competition. This framework predicts many aspects of decision behavior that have eluded a common explanation. '),
(87366, 2015, 'plos', 'Decoding Structural Properties of a Partially Unfolded Protein Substrate: En Route to Chaperone Binding', 'Nagpal, Suhani|Tiwari, Satyam|Mapa, Koyeli|Thukral, Lipi', 'CSIR-Institute of Genomics and Integrative Biology, New Delhi, India.|CSIR-Institute of Genomics and Integrative Biology, New Delhi, India, Academy of Scientific and Innovative Research (AcSIR), New Delhi, India.|CSIR-Institute of Genomics and Integrative Biology, New Delhi, India, Department of Life Sciences, School of Natural Sciences, Shiv Nadar University, Dadri, Uttar Pradesh, India.|CSIR-Institute of Genomics and Integrative Biology, New Delhi, India.', 'India|India|India|India', 5, 'Computational Biology|Hydrophobic and Hydrophilic Interactions|Molecular Chaperones|Molecular Dynamics Simulation|Protein Binding|Protein Conformation|Protein Folding', 'Journal Article', '10.1371/journal.pcbi.1004496', '26394388', 'Many proteins comprising of complex topologies require molecular chaperones to achieve their unique three-dimensional folded structure. The E.coli chaperone, GroEL binds with a large number of unfolded and partially folded proteins, to facilitate proper folding and prevent misfolding and aggregation. Although the major structural components of GroEL are well defined, scaffolds of the non-native substrates that determine chaperone-mediated folding have been difficult to recognize. Here we performed all-atomistic and replica-exchange molecular dynamics simulations to dissect non-native ensemble of an obligate GroEL folder, DapA. Thermodynamics analyses of unfolding simulations revealed populated intermediates with distinct structural characteristics. We found that surface exposed hydrophobic patches are significantly increased, primarily contributed from native and non-native xcexb2-sheet elements. We validate the structural properties of these conformers using experimental data, including circular dichroism (CD), 1-anilinonaphthalene-8-sulfonic acid (ANS) binding measurements and previously reported hydrogen-deutrium exchange coupled to mass spectrometry (HDX-MS). Further, we constructed network graphs to elucidate long-range intra-protein connectivity of native and intermediate topologies, demonstrating regions that serve as central hubs. Overall, our results implicate that genomic variations (or mutations) in the distinct regions of protein structures might disrupt these topological signatures disabling chaperone-mediated folding, leading to formation of aggregates. '),
(87367, 2015, 'plos', 'Coupling Protein Side-Chain and Backbone Flexibility Improves the Re-design of Protein-Ligand Specificity', 'Ollikainen, Noah|de Jong, René M|Kortemme, Tanja', 'Graduate Program in Bioinformatics, University of California San Francisco, San Francisco, California, United States of America.|DSM Biotechnology Center, Alexander Fleminglaan 1, Delft, The Netherlands.|Graduate Program in Bioinformatics, University of California San Francisco, San Francisco, California, United States of America, California Institute for Quantitative Biosciences (QB3), University of California San Francisco, San Francisco, California, United States of America, Department of Bioengineering and Therapeutic Science, University of California San Francisco, San Francisco, California, United States of America.', 'United States|Netherlands|United States', 0, 'Amino Acid Sequence|Binding Sites|Computational Biology|Ligands|Models, Molecular|Molecular Sequence Data|Pliability|Protein Conformation|Proteins|Substrate Specificity', 'Journal Article', '10.1371/journal.pcbi.1004335', '26397464', 'Interactions between small molecules and proteins play critical roles in regulating and facilitating diverse biological functions, yet our ability to accurately re-engineer the specificity of these interactions using computational approaches has been limited. One main difficulty, in addition to inaccuracies in energy functions, is the exquisite sensitivity of protein-ligand interactions to subtle conformational changes, coupled with the computational problem of sampling the large conformational search space of degrees of freedom of ligands, amino acid side chains, and the protein backbone. Here, we describe two benchmarks for evaluating the accuracy of computational approaches for re-engineering protein-ligand interactions: (i) prediction of enzyme specificity altering mutations and (ii) prediction of sequence tolerance in ligand binding sites. After finding that current state-of-the-art fixed backbone design methods perform poorly on these tests, we develop a new coupled moves design method in the program Rosetta that couples changes to protein sequence with alterations in both protein side-chain and protein backbone conformations, and allows for changes in ligand rigid-body and torsion degrees of freedom. We show significantly increased accuracy in both predicting ligand specificity altering mutations and binding site sequences. These methodological improvements should be useful for many applications of protein-ligand design. The approach also provides insights into the role of subtle conformational adjustments that enable functional changes not only in engineering applications but also in natural protein evolution.'),
(87368, 2015, 'plos', 'You Are Not Working for Me, I Am Working with You', 'Markowetz, Florian', 'University of Cambridge, Cancer Research UK Cambridge Institute, Cambridge, United Kingdom.', 'United Kingdom', 2, 'Communication|Group Processes|Humans|Laboratories|Leadership|Research Design|Workplace', 'Journal Article', '10.1371/journal.pcbi.1004387', '26402330', '-'),
(87369, 2015, 'plos', 'Early Characterization of the Severity and Transmissibility of Pandemic Influenza Using Clinical Episode Data from Multiple Populations', 'Riley, Pete|Ben-Nun, Michal|Linker, Jon A|Cost, Angelia A|Sanchez, Jose L|George, Dylan|Bacon, David P|Riley, Steven', 'Predictive Science Inc., San Diego, California, United States of America.|Predictive Science Inc., San Diego, California, United States of America.|Predictive Science Inc., San Diego, California, United States of America.|Armed Forces Health Surveillance Center, Silver Spring, Maryland, United States of America.|Armed Forces Health Surveillance Center, Silver Spring, Maryland, United States of America.|Biomedical Advanced Research and Development Authority (BARDA), Assistant Secretary for Preparedness and Response (ASPR), Department of Health and Human Services (HHS), Washington, D.C., United States of America.|Leidos, McLean, Virginia, United States of America.|Predictive Science Inc., San Diego, California, United States of America, MRC Centre for Outbreak Analysis and Modelling, Imperial College London, United Kingdom.', 'United States|United States|United States|United States|United States|United States|United States|Un', 3, 'Computational Biology|Databases, Factual|Humans|Influenza, Human|Models, Biological|Pandemics', 'Journal Article', '10.1371/journal.pcbi.1004392', '26402446', 'The potential rapid availability of large-scale clinical episode data during the next influenza pandemic suggests an opportunity for increasing the speed with which novel respiratory pathogens can be characterized. Key intervention decisions will be determined by both the transmissibility of the novel strain (measured by the basic reproductive number R0) and its individual-level severity. The 2009 pandemic illustrated that estimating individual-level severity, as described by the proportion pC of infections that result in clinical cases, can remain uncertain for a prolonged period of time. Here, we use 50 distinct US military populations during 2009 as a retrospective cohort to test the hypothesis that real-time encounter data combined with disease dynamic models can be used to bridge this uncertainty gap. Effectively, we estimated the total number of infections in multiple early-affected communities using the model and divided that number by the known number of clinical cases. Joint estimates of severity and transmissibility clustered within a relatively small region of parameter space, with 40 of the 50 populations bounded by: pC, 0.0133-0.150 and R0, 1.09-2.16. These fits were obtained despite widely varying incidence profiles: some with spring waves, some with fall waves and some with both. To illustrate the benefit of specific pairing of rapidly available data and infectious disease models, we simulated a future moderate pandemic strain with pC approximately ×10 that of 2009, the results demonstrating that even before the peak had passed in the first affected population, R0 and pC could be well estimated. This study provides a clear reference in this two-dimensional space against which future novel respiratory pathogens can be rapidly assessed and compared with previous pandemics. '),
(87370, 2015, 'plos', 'How to Grow a Computational Biology Lab', 'McHardy, Alice Carolyn', 'Helmholtz Centre for Infection Research and Technical University of Braunschweig, Braunschweig, Germany.', 'Germany', 0, 'Biomedical Research|Communication|Computational Biology|Goals|Humans|Laboratories|Leadership|Motivation|Time Management', 'Journal Article', '10.1371/journal.pcbi.1004397', '26402619', '-');
INSERT INTO `papers` (`id`, `ano`, `journal`, `titulo`, `autores`, `afiliacao`, `pais`, `citacoes`, `palavra_chave`, `categorias`, `doi`, `pubmed`, `abstract`) VALUES
(87371, 2015, 'plos', 'miRTex: A Text Mining System for miRNA-Gene Relation Extraction', 'Li, Gang|Ross, Karen E|Arighi, Cecilia N|Peng, Yifan|Wu, Cathy H|Vijay-Shanker, K', 'Department of Computer and Information Sciences, University of Delaware, Newark, Delaware, United States of America.|Department of Biochemistry and Molecular & Cellular Biology, Georgetown University Medical Center, Washington, DC, United States of America, Center for Bioinformatics and Computational Biology, University of Delaware, Newark, Delaware, United States of America.|Center for Bioinformatics and Computational Biology, University of Delaware, Newark, Delaware, United States of America.|Department of Computer and Information Sciences, University of Delaware, Newark, Delaware, United States of America.|Department of Computer and Information Sciences, University of Delaware, Newark, Delaware, United States of America, Department of Biochemistry and Molecular & Cellular Biology, Georgetown University Medical Center, Washington, DC, United States of America, Center for Bioinformatics and Computational Biology, University of Delaware, Newark, Delaware, United States of America.|Department of Computer and Information Sciences, University of Delaware, Newark, Delaware, United States of America.', 'United States|United States|United States|United States|United States|United States', 25, 'Computational Biology|Data Mining|Databases, Genetic|Genes|Humans|MicroRNAs|Models, Genetic|Periodicals as Topic', 'Journal Article', '10.1371/journal.pcbi.1004391', '26407127', 'MicroRNAs (miRNAs) regulate a wide range of cellular and developmental processes through gene expression suppression or mRNA degradation. Experimentally validated miRNA gene targets are often reported in the literature. In this paper, we describe miRTex, a text mining system that extracts miRNA-target relations, as well as miRNA-gene and gene-miRNA regulation relations. The system achieves good precision and recall when evaluated on a literature corpus of 150 abstracts with F-scores close to 0.90 on the three different types of relations. We conducted full-scale text mining using miRTex to process all the Medline abstracts and all the full-length articles in the PubMed Central Open Access Subset. The results for all the Medline abstracts are stored in a database for interactive query and file download via the website at http://proteininformationresource.org/mirtex. Using miRTex, we identified genes potentially regulated by miRNAs in Triple Negative Breast Cancer, as well as miRNA-gene relations that, in conjunction with kinase-substrate relations, regulate the response to abiotic stress in Arabidopsis thaliana. These two use cases demonstrate the usefulness of miRTex text mining in the analysis of miRNA-regulated biological processes. '),
(87372, 2015, 'plos', 'Implicit Value Updating Explains Transitive Inference Performance: The Betasort Model', 'Jensen, Greg|Muñoz, Fabian|Alkan, Yelda|Ferrera, Vincent P|Terrace, Herbert S', 'Department of Neuroscience, Columbia University, New York, New York, United States of America, Department of Psychology, Columbia University, New York, New York, United States of America.|Department of Neuroscience, Columbia University, New York, New York, United States of America.|Department of Neuroscience, Columbia University, New York, New York, United States of America.|Department of Neuroscience, Columbia University, New York, New York, United States of America, Department of Psychiatry, Columbia University, New York, New York, United States of America.|Department of Psychology, Columbia University, New York, New York, United States of America.', 'United States|United States|United States|United States|United States', 9, 'Algorithms|Animals|Computational Biology|Humans|Learning|Macaca mulatta|Machine Learning|Male|Models, Neurological|Models, Statistical|Reward', 'Journal Article', '10.1371/journal.pcbi.1004523', '26407227', 'Transitive inference (the ability to infer that B > D given that B > C and C > D) is a widespread characteristic of serial learning, observed in dozens of species. Despite these robust behavioral effects, reinforcement learning models reliant on reward prediction error or associative strength routinely fail to perform these inferences. We propose an algorithm called betasort, inspired by cognitive processes, which performs transitive inference at low computational cost. This is accomplished by (1) representing stimulus positions along a unit span using beta distributions, (2) treating positive and negative feedback asymmetrically, and (3) updating the position of every stimulus during every trial, whether that stimulus was visible or not. Performance was compared for rhesus macaques, humans, and the betasort algorithm, as well as Q-learning, an established reward-prediction error (RPE) model. Of these, only Q-learning failed to respond above chance during critical test trials. Betasorts success (when compared to RPE models) and its computational efficiency (when compared to full Markov decision process implementations) suggests that the study of reinforcement learning in organisms will be best served by a feature-driven approach to comparing formal models. '),
(87373, 2015, 'plos', 'Predicting Anticancer Drug Responses Using a Dual-Layer Integrated Cell Line-Drug Network Model', 'Zhang, Naiqian|Wang, Haiyun|Fang, Yun|Wang, Jun|Zheng, Xiaoqi|Liu, X Shirley', 'Department of Mathematics, Shanghai Normal University, Shanghai, China.|Department of Bioinformatics, School of Life Science and Technology, Tongji University, Shanghai, China.|Department of Mathematics, Shanghai Normal University, Shanghai, China.|Department of Mathematics, Shanghai Normal University, Shanghai, China.|Department of Mathematics, Shanghai Normal University, Shanghai, China.|Department of Biostatistics and Computational Biology, Dana-Farber Cancer Institute and Harvard School of Public Health, Boston, Massachusetts, United States of America, Center for Functional Cancer Epigenetics, Dana-Farber Cancer Institute, Boston, Massachusetts, United States of America.', 'China|China|China|China|China|United States', 62, 'Antineoplastic Agents|Cell Line, Tumor|Computational Biology|Humans|Models, Biological|Models, Statistical', 'Journal Article', '10.1371/journal.pcbi.1004498', '26418249', 'The ability to predict the response of a cancer patient to a therapeutic agent is a major goal in modern oncology that should ultimately lead to personalized treatment. Existing approaches to predicting drug sensitivity rely primarily on profiling of cancer cell line panels that have been treated with different drugs and selecting genomic or functional genomic features to regress or classify the drug response. Here, we propose a dual-layer integrated cell line-drug network model, which uses both cell line similarity network (CSN) data and drug similarity network (DSN) data to predict the drug response of a given cell line using a weighted model. Using the Cancer Cell Line Encyclopedia (CCLE) and Cancer Genome Project (CGP) studies as benchmark datasets, our single-layer model with CSN or DSN and only a single parameter achieved a prediction performance comparable to the previously generated elastic net model. When using the dual-layer model integrating both CSN and DSN, our predicted response reached a 0.6 Pearson correlation coefficient with observed responses for most drugs, which is significantly better than the previous results using the elastic net model. We have also applied the dual-layer cell line-drug integrated network model to fill in the missing drug response values in the CGP dataset. Even though the dual-layer integrated cell line-drug network model does not specifically model mutation information, it correctly predicted that BRAF mutant cell lines would be more sensitive than BRAF wild-type cell lines to three MEK1/2 inhibitors tested. '),
(87374, 2015, 'plos', 'Ten Simple Rules for Protecting Research Integrity', 'Shaw, David M|Erren, Thomas C', 'Institute for Biomedical Ethics, University of Basel, Basel, Switzerland.|Institute and Policlinic for Occupational Medicine, Environmental Medicine and Prevention Research, University Hospital of Cologne, Cologne, Germany.', 'Switzerland|Germany', 10, 'Algorithms|Disclosure|Guideline Adherence|Guidelines as Topic|Quality Control|Research|Scientific Misconduct', 'Editorial', '10.1371/journal.pcbi.1004388', '26426757', '-'),
(87375, 2015, 'plos', 'Implications of Heterogeneous Biting Exposure and Animal Hosts on Trypanosomiasis brucei gambiense Transmission and Control', 'Stone, Chris M|Chitnis, Nakul', 'Department of Epidemiology and Public Health, Swiss Tropical and Public Health Institute, Basel, Switzerland, University of Basel, Basel, Switzerland.|Department of Epidemiology and Public Health, Swiss Tropical and Public Health Institute, Basel, Switzerland, University of Basel, Basel, Switzerland.', 'Switzerland|Switzerland', 0, 'Animals|Computer Simulation|Disease Reservoirs|Host-Pathogen Interactions|Humans|Insect Bites and Stings|Models, Statistical|Risk Assessment|Trypanosoma brucei gambiense|Trypanosomiasis, African|Tsetse Flies', 'Journal Article', '10.1371/journal.pcbi.1004514', '26426854', 'The gambiense form of sleeping sickness is a neglected tropical disease, which is presumed to be anthroponotic. However, the parasite persists in human populations at levels of considerable rarity and as such the existence of animal reservoirs has been posited. Clarifying the impact of animal host reservoirs on the feasibility of interrupting sleeping sickness transmission through interventions is a matter of urgency. We developed a mathematical model allowing for heterogeneous exposure of humans to tsetse, with animal populations that differed in their ability to transmit infections, to investigate the effectiveness of two established techniques, screening and treatment of at-risk populations, and vector control. Importantly, under both assumptions, an integrated approach of human screening and vector control was supported in high transmission areas. However, increasing the intensity of vector control was more likely to eliminate transmission, while increasing the intensity of human screening reduced the time to elimination. Non-human animal hosts played important, but different roles in HAT transmission, depending on whether or not they contributed as reservoirs. If they did not serve as reservoirs, sensitivity analyses suggested their attractiveness may instead function as a sink for tsetse bites. These outcomes highlight the importance of understanding the ecological and environmental context of sleeping sickness in optimizing integrated interventions, particularly for moderate and low transmission intensity settings. '),
(87376, 2015, 'plos', 'Biofilm Formation Mechanisms of Pseudomonas aeruginosa Predicted via Genome-Scale Kinetic Models of Bacterial Metabolism', 'Vital-Lopez, Francisco G|Reifman, Jaques|Wallqvist, Anders', 'Department of Defense Biotechnology High Performance Computing Software Applications Institute, Telemedicine and Advanced Technology Research Center, U.S. Army Medical Research and Materiel Command, Fort Detrick, Maryland, United States of America.|Department of Defense Biotechnology High Performance Computing Software Applications Institute, Telemedicine and Advanced Technology Research Center, U.S. Army Medical Research and Materiel Command, Fort Detrick, Maryland, United States of America.|Department of Defense Biotechnology High Performance Computing Software Applications Institute, Telemedicine and Advanced Technology Research Center, U.S. Army Medical Research and Materiel Command, Fort Detrick, Maryland, United States of America.', 'United States|United States|United States', 25, 'Bacterial Proteins|Biofilms|Computer Simulation|Genome, Bacterial|Kinetics|Metabolome|Models, Biological|Proteome|Pseudomonas aeruginosa', 'Journal Article', '10.1371/journal.pcbi.1004452', '26431398', 'A hallmark of Pseudomonas aeruginosa is its ability to establish biofilm-based infections that are difficult to eradicate. Biofilms are less susceptible to host inflammatory and immune responses and have higher antibiotic tolerance than free-living planktonic cells. Developing treatments against biofilms requires an understanding of bacterial biofilm-specific physiological traits. Research efforts have started to elucidate the intricate mechanisms underlying biofilm development. However, many aspects of these mechanisms are still poorly understood. Here, we addressed questions regarding biofilm metabolism using a genome-scale kinetic model of the P. aeruginosa metabolic network and gene expression profiles. Specifically, we computed metabolite concentration differences between known mutants with altered biofilm formation and the wild-type strain to predict drug targets against P. aeruginosa biofilms. We also simulated the altered metabolism driven by gene expression changes between biofilm and stationary growth-phase planktonic cultures. Our analysis suggests that the synthesis of important biofilm-related molecules, such as the quorum-sensing molecule Pseudomonas quinolone signal and the exopolysaccharide Psl, is regulated not only through the expression of genes in their own synthesis pathway, but also through the biofilm-specific expression of genes in pathways competing for precursors to these molecules. Finally, we investigated why mutants defective in anthranilate degradation have an impaired ability to form biofilms. Alternative to a previous hypothesis that this biofilm reduction is caused by a decrease in energy production, we proposed that the dysregulation of the synthesis of secondary metabolites derived from anthranilate and chorismate is what impaired the biofilms of these mutants. Notably, these insights generated through our kinetic model-based approach are not accessible from previous constraint-based model analyses of P. aeruginosa biofilm metabolism. Our simulation results showed that plausible, non-intuitive explanations of difficult-to-interpret experimental observations could be generated by integrating genome-scale kinetic models with gene expression profiles. '),
(87377, 2015, 'plos', 'Correction: When Less Is More: Non-monotonic Spike Sequence Processing in Neurons', 'PLOS Computational Biology Staff', 'Department of Defense Biotechnology High Performance Computing Software Applications Institute, Telemedicine and Advanced Technology Research Center, U.S. Army Medical Research and Materiel Command, Fort Detrick, Maryland, United States of America.', 'United States', 0, '-', 'Published Erratum', '10.1371/journal.pcbi.1004380', '26436417', '-'),
(87378, 2015, 'plos', 'SubClonal Hierarchy Inference from Somatic Mutations: Automatic Reconstruction of Cancer Evolutionary Trees from Multi-region Next Generation Sequencing', 'Niknafs, Noushin|Beleva-Guthrie, Violeta|Naiman, Daniel Q|Karchin, Rachel', 'Department of Biomedical Engineering and Institute for Computational Medicine, Johns Hopkins University, Baltimore, Maryland, United States of America.|Department of Biomedical Engineering and Institute for Computational Medicine, Johns Hopkins University, Baltimore, Maryland, United States of America.|Department of Applied Math and Statistics, Johns Hopkins University, Baltimore, Maryland, United States of America.|Department of Biomedical Engineering and Institute for Computational Medicine, Johns Hopkins University, Baltimore, Maryland, United States of America, Department of Oncology, Johns Hopkins Medical Institutions, Baltimore, Maryland, United States of America.', 'United States|United States|United States|United States', 0, 'Algorithms|Animals|Base Sequence|Clonal Evolution|DNA Mutational Analysis|DNA, Neoplasm|Evolution, Molecular|High-Throughput Nucleotide Sequencing|Mice|Molecular Sequence Data|Mutation|Neoplasms|Pattern Recognition, Automated|Single-Cell Analysis', 'Journal Article', '10.1371/journal.pcbi.1004416', '26436540', 'Recent improvements in next-generation sequencing of tumor samples and the ability to identify somatic mutations at low allelic fractions have opened the way for new approaches to model the evolution of individual cancers. The power and utility of these models is increased when tumor samples from multiple sites are sequenced. Temporal ordering of the samples may provide insight into the etiology of both primary and metastatic lesions and rationalizations for tumor recurrence and therapeutic failures. Additional insights may be provided by temporal ordering of evolving subclones--cellular subpopulations with unique mutational profiles. Current methods for subclone hierarchy inference tightly couple the problem of temporal ordering with that of estimating the fraction of cancer cells harboring each mutation. We present a new framework that includes a rigorous statistical hypothesis test and a collection of tools that make it possible to decouple these problems, which we believe will enable substantial progress in the field of subclone hierarchy inference. The methods presented here can be flexibly combined with methods developed by others addressing either of these problems. We provide tools to interpret hypothesis test results, which inform phylogenetic tree construction, and we introduce the first genetic algorithm designed for this purpose. The utility of our framework is systematically demonstrated in simulations. For most tested combinations of tumor purity, sequencing coverage, and tree complexity, good power (xe2x89xa5 0.8) can be achieved and Type 1 error is well controlled when at least three tumor samples are available from a patient. Using data from three published multi-region tumor sequencing studies of (murine) small cell lung cancer, acute myeloid leukemia, and chronic lymphocytic leukemia, in which the authors reconstructed subclonal phylogenetic trees by manual expert curation, we show how different configurations of our tools can identify either a single tree in agreement with the authors, or a small set of trees, which include the authors preferred tree. Our results have implications for improved modeling of tumor evolution and the importance of multi-region tumor sequencing.'),
(87379, 2015, 'plos', 'Genome-Wide Detection and Analysis of Multifunctional Genes', 'Pritykin, Yuri|Ghersi, Dario|Singh, Mona', 'Department of Computer Science, Princeton University, Princeton, New Jersey, United States of America, Lewis-Sigler Institute for Integrative Genomics, Princeton University, Princeton, New Jersey, United States of America.|Lewis-Sigler Institute for Integrative Genomics, Princeton University, Princeton, New Jersey, United States of America, School of Interdisciplinary Informatics, University of Nebraska at Omaha, Omaha, Nebraska, United States of America.|Department of Computer Science, Princeton University, Princeton, New Jersey, United States of America, Lewis-Sigler Institute for Integrative Genomics, Princeton University, Princeton, New Jersey, United States of America.', 'Jersey|Jersey|Jersey', 23, 'Animals|Chromosome Mapping|Data Mining|Drosophila Proteins|Drosophila melanogaster|Genome|Genome-Wide Association Study|Humans|Multigene Family|Natural Language Processing|Proteome|Saccharomyces cerevisiae|Saccharomyces cerevisiae Proteins|Species Specificity', 'Journal Article', '10.1371/journal.pcbi.1004467', '26436655', 'Many genes can play a role in multiple biological processes or molecular functions. Identifying multifunctional genes at the genome-wide level and studying their properties can shed light upon the complexity of molecular events that underpin cellular functioning, thereby leading to a better understanding of the functional landscape of the cell. However, to date, genome-wide analysis of multifunctional genes (and the proteins they encode) has been limited. Here we introduce a computational approach that uses known functional annotations to extract genes playing a role in at least two distinct biological processes. We leverage functional genomics data sets for three organisms--H. sapiens, D. melanogaster, and S. cerevisiae--and show that, as compared to other annotated genes, genes involved in multiple biological processes possess distinct physicochemical properties, are more broadly expressed, tend to be more central in protein interaction networks, tend to be more evolutionarily conserved, and are more likely to be essential. We also find that multifunctional genes are significantly more likely to be involved in human disorders. These same features also hold when multifunctionality is defined with respect to molecular functions instead of biological processes. Our analysis uncovers key features about multifunctional genes, and is a step towards a better genome-wide understanding of gene multifunctionality.'),
(87380, 2015, 'plos', 'Cortical Composition Hierarchy Driven by Spine Proportion Economical Maximization or Wire Volume Minimization', 'Karbowski, Jan', 'Institute of Applied Mathematics and Mechanics, University of Warsaw, Warsaw, Poland.', 'Poland', 6, 'Animals|Axons|Capillaries|Cerebral Cortex|Computer Simulation|Connectome|Dendritic Spines|Humans|Models, Anatomic|Models, Neurological|Neuroglia|Organ Size|Species Specificity', 'Journal Article', '10.1371/journal.pcbi.1004532', '26436731', 'The structure and quantitative composition of the cerebral cortex are interrelated with its computational capacity. Empirical data analyzed here indicate a certain hierarchy in local cortical composition. Specifically, neural wire, i.e., axons and dendrites take each about 1/3 of cortical space, spines and glia/astrocytes occupy each about (1/3)(2), and capillaries around (1/3)(4). Moreover, data analysis across species reveals that these fractions are roughly brain size independent, which suggests that they could be in some sense optimal and thus important for brain function. Is there any principle that sets them in this invariant way? This study first builds a model of local circuit in which neural wire, spines, astrocytes, and capillaries are mutually coupled elements and are treated within a single mathematical framework. Next, various forms of wire minimization rule (wire length, surface area, volume, or conduction delays) are analyzed, of which, only minimization of wire volume provides realistic results that are very close to the empirical cortical fractions. As an alternative, a new principle called spine economy maximization is proposed and investigated, which is associated with maximization of spine proportion in the cortex per spine size that yields equally good but more robust results. Additionally, a combination of wire cost and spine economy notions is considered as a meta-principle, and it is found that this proposition gives only marginally better results than either pure wire volume minimization or pure spine economy maximization, but only if spine economy component dominates. However, such a combined meta-principle yields much better results than the constraints related solely to minimization of wire length, wire surface area, and conduction delays. Interestingly, the type of spine size distribution also plays a role, and better agreement with the data is achieved for distributions with long tails. In sum, these results suggest that for the efficiency of local circuits wire volume may be more primary variable than wire length or temporal delays, and moreover, the new spine economy principle may be important for brain evolutionary design in a broader context.'),
(87381, 2015, 'plos', 'Cell Invasion Dynamics into a Three Dimensional Extracellular Matrix Fibre Network', 'Kim, Min-Cheol|Whisler, Jordan|Silberberg, Yaron R|Kamm, Roger D|Asada, H Harry', 'BioSystems and Micromechanics IRG, Singapore MIT Alliance for Research and Technology, Singapore, Department of Mechanical Engineering, Massachusetts Institute of Technology, Cambridge, Massachusetts, United States of America.|Department of Mechanical Engineering, Massachusetts Institute of Technology, Cambridge, Massachusetts, United States of America.|BioSystems and Micromechanics IRG, Singapore MIT Alliance for Research and Technology, Singapore, Department of Mechanical Engineering, Massachusetts Institute of Technology, Cambridge, Massachusetts, United States of America.|BioSystems and Micromechanics IRG, Singapore MIT Alliance for Research and Technology, Singapore, Department of Mechanical Engineering, Massachusetts Institute of Technology, Cambridge, Massachusetts, United States of America, Department of Biological Engineering, Massachusetts Institute of Technology, Cambridge, Massachusetts, United States of America.|BioSystems and Micromechanics IRG, Singapore MIT Alliance for Research and Technology, Singapore, Department of Mechanical Engineering, Massachusetts Institute of Technology, Cambridge, Massachusetts, United States of America.', 'Singapore|United States|Singapore|Singapore|Singapore', 40, 'Animals|Cell Adhesion|Cell Movement|Computer Simulation|Elastic Modulus|Extracellular Matrix|Humans|Mechanotransduction, Cellular|Models, Biological|Pseudopodia|Stress, Mechanical', 'Journal Article', '10.1371/journal.pcbi.1004535', '26436883', 'The dynamics of filopodia interacting with the surrounding extracellular matrix (ECM) play a key role in various cell-ECM interactions, but their mechanisms of interaction with the ECM in 3D environment remain poorly understood. Based on first principles, here we construct an individual-based, force-based computational model integrating four modules of 1) filopodia penetration dynamics, 2) intracellular mechanics of cellular and nuclear membranes, contractile actin stress fibers, and focal adhesion dynamics, 3) structural mechanics of ECM fiber networks, and 4) reaction-diffusion mass transfers of seven biochemical concentrations in related with chemotaxis, proteolysis, haptotaxis, and degradation in ECM to predict dynamic behaviors of filopodia that penetrate into a 3D ECM fiber network. The tip of each filopodium crawls along ECM fibers, tugs the surrounding fibers, and contracts or retracts depending on the strength of the binding and the ECM stiffness and pore size. This filopodium-ECM interaction is modeled as a stochastic process based on binding kinetics between integrins along the filopodial shaft and the ligands on the surrounding ECM fibers. This filopodia stochastic model is integrated into migratory dynamics of a whole cell in order to predict the cell invasion into 3D ECM in response to chemotaxis, haptotaxis, and durotaxis cues. Predicted average filopodia speed and that of the cell membrane advance agreed with experiments of 3D HUVEC migration at r(2) > 0.95 for diverse ECMs with different pore sizes and stiffness.'),
(87382, 2015, 'plos', 'Reconciling Estimates of Cell Proliferation from Stable Isotope Labeling Experiments', 'Ahmed, Raya|Westera, Liset|Drylewicz, Julia|Elemans, Marjet|Zhang, Yan|Kelly, Elizabeth|Reljic, Rajko|Tesselaar, Kiki|de Boer, Rob J|Macallan, Derek C|Borghans, José A M|Asquith, Becca', 'Institute for Infection and Immunity, St. Georges, University of London, London, United Kingdom.|Laboratory of Translational Immunology, Department of Immunology, University Medical Center Utrecht, Utrecht, The Netherlands.|Laboratory of Translational Immunology, Department of Immunology, University Medical Center Utrecht, Utrecht, The Netherlands, Theoretical Biology & Bioinformatics, Utrecht University, The Netherlands.|Department of Medicine, Imperial College, London, United Kingdom.|Institute for Infection and Immunity, St. Georges, University of London, London, United Kingdom.|Institute for Infection and Immunity, St. Georges, University of London, London, United Kingdom.|Institute for Infection and Immunity, St. Georges, University of London, London, United Kingdom.|Laboratory of Translational Immunology, Department of Immunology, University Medical Center Utrecht, Utrecht, The Netherlands.|Theoretical Biology & Bioinformatics, Utrecht University, The Netherlands.|Institute for Infection and Immunity, St. Georges, University of London, London, United Kingdom.|Laboratory of Translational Immunology, Department of Immunology, University Medical Center Utrecht, Utrecht, The Netherlands.|Department of Medicine, Imperial College, London, United Kingdom.', 'United Kingdom|Netherlands|Netherlands|United Kingdom|United Kingdom|United Kingdom|United Kingdom|N', 11, 'Algorithms|Cell Proliferation|Deuterium|Deuterium Oxide|Glucose|Humans|Isotope Labeling|Lymphocyte Count|Lymphocytes|Radioisotope Dilution Technique|Radiopharmaceuticals|Reproducibility of Results|Sensitivity and Specificity', 'Journal Article', '10.1371/journal.pcbi.1004355', '26437372', 'Stable isotope labeling is the state of the art technique for in vivo quantification of lymphocyte kinetics in humans. It has been central to a number of seminal studies, particularly in the context of HIV-1 and leukemia. However, there is a significant discrepancy between lymphocyte proliferation rates estimated in different studies. Notably, deuterated (2)H2-glucose (D2-glucose) labeling studies consistently yield higher estimates of proliferation than deuterated water (D2O) labeling studies. This hampers our understanding of immune function and undermines our confidence in this important technique. Whether these differences are caused by fundamental biochemical differences between the two compounds and/or by methodological differences in the studies is unknown. D2-glucose and D2O labeling experiments have never been performed by the same group under the same experimental conditions, consequently a direct comparison of these two techniques has not been possible. We sought to address this problem. We performed both in vitro and murine in vivo labeling experiments using identical protocols with both D2-glucose and D2O. This showed that intrinsic differences between the two compounds do not cause differences in the proliferation rate estimates, but that estimates made using D2-glucose in vivo were susceptible to difficulties in normalization due to highly variable blood glucose enrichment. Analysis of three published human studies made using D2-glucose and D2O confirmed this problem, particularly in the case of short term D2-glucose labeling. Correcting for these inaccuracies in normalization decreased proliferation rate estimates made using D2-glucose and slightly increased estimates made using D2O, thus bringing the estimates from the two methods significantly closer and highlighting the importance of reliable normalization when using this technique.'),
(87383, 2015, 'plos', 'Detecting Horizontal Gene Transfer between Closely Related Taxa', 'Adato, Orit|Ninyo, Noga|Gophna, Uri|Snir, Sagi', 'Department of Evolutionary Biology, University of Haifa, Haifa, Israel.|Department of Evolutionary Biology, University of Haifa, Haifa, Israel.|Department of Molecular Microbiology and Biotechnology Tel Aviv University, Tel-Aviv, Israel.|Department of Evolutionary Biology, University of Haifa, Haifa, Israel.', 'Israel|Israel|Israel|Israel', 18, 'Algorithms|Chromosome Mapping|Escherichia coli|Evolution, Molecular|Gene Transfer, Horizontal|Genome, Bacterial|Models, Genetic|Phylogeny|Synteny', 'Journal Article', '10.1371/journal.pcbi.1004408', '26439115', 'Horizontal gene transfer (HGT), the transfer of genetic material between organisms, is crucial for genetic innovation and the evolution of genome architecture. Existing HGT detection algorithms rely on a strong phylogenetic signal distinguishing the transferred sequence from ancestral (vertically derived) genes in its recipient genome. Detecting HGT between closely related species or strains is challenging, as the phylogenetic signal is usually weak and the nucleotide composition is normally nearly identical. Nevertheless, there is a great importance in detecting HGT between congeneric species or strains, especially in clinical microbiology, where understanding the emergence of new virulent and drug-resistant strains is crucial, and often time-sensitive. We developed a novel, self-contained technique named Near HGT, based on the synteny index, to measure the divergence of a gene from its native genomic environment and used it to identify candidate HGT events between closely related strains. The method confirms candidate transferred genes based on the constant relative mutability (CRM). Using CRM, the algorithm assigns a confidence score based on unusual sequence divergence. A gene exhibiting exceptional deviations according to both synteny and mutability criteria, is considered a validated HGT product. We first employed the technique to a set of three E. coli strains and detected several highly probable horizontally acquired genes. We then compared the method to existing HGT detection tools using a larger strain data set. When combined with additional approaches our new algorithm provides richer picture and brings us closer to the goal of detecting all newly acquired genes in a particular strain. '),
(87384, 2015, 'plos', 'A Generative Statistical Algorithm for Automatic Detection of Complex Postures', 'Nagy, Stanislav|Goessling, Marc|Amit, Yali|Biron, David', 'The Institute for Biophysical Dynamics, The University of Chicago, Chicago, Illinois, United States of America.|Department of Statistics, The University of Chicago, Chicago, Illinois, United States of America.|Department of Statistics, The University of Chicago, Chicago, Illinois, United States of America, Department of Computer Science, The University of Chicago, Chicago, Illinois, United States of America.|The Institute for Biophysical Dynamics, The University of Chicago, Chicago, Illinois, United States of America, Department of Physics and the James Franck Institute, The University of Chicago, Chicago, Illinois, United States of America.', 'United States|United States|United States|United States', 6, 'Algorithms|Animals|Caenorhabditis elegans|Computer Simulation|Data Interpretation, Statistical|Image Interpretation, Computer-Assisted|Locomotion|Models, Statistical|Pattern Recognition, Automated|Posture|Reproducibility of Results|Sensitivity and Specificity|Whole Body Imaging', 'Journal Article', '10.1371/journal.pcbi.1004517', '26439258', 'This paper presents a method for automated detection of complex (non-self-avoiding) postures of the nematode Caenorhabditis elegans and its application to analyses of locomotion defects. Our approach is based on progressively detailed statistical models that enable detection of the head and the body even in cases of severe coilers, where data from traditional trackers is limited. We restrict the input available to the algorithm to a single digitized frame, such that manual initialization is not required and the detection problem becomes embarrassingly parallel. Consequently, the proposed algorithm does not propagate detection errors and naturally integrates in a big data workflow used for large-scale analyses. Using this framework, we analyzed the dynamics of postures and locomotion of wild-type animals and mutants that exhibit severe coiling phenotypes. Our approach can readily be extended to additional automated tracking tasks such as tracking pairs of animals (e.g., for mating assays) or different species. '),
(87385, 2015, 'plos', 'Analyzing and Quantifying the Gain-of-Function Enhancement of IP3 Receptor Gating by Familial Alzheimers Disease-Causing Mutants in Presenilins', 'Mak, Don-On Daniel|Cheung, King-Ho|Toglia, Patrick|Foskett, J Kevin|Ullah, Ghanim', 'Department of Physiology, University of Pennsylvania, Philadelphia, Pennsylvania, United States of America.|Department of Physiology, The University of Hong Kong, Pok Fu Lam, Hong Kong.|Department of Physics, University of South Florida, Tampa, Florida, United States of America.|Department of Physiology, University of Pennsylvania, Philadelphia, Pennsylvania, United States of America, Department of Cell and Developmental Biology, University of Pennsylvania, Philadelphia, Pennsylvania, United States of America.|Department of Physics, University of South Florida, Tampa, Florida, United States of America.', 'United States|Hong Kong|United States|United States|United States', 16, 'Alzheimer Disease|Animals|Calcium|Calcium Signaling|Computer Simulation|Humans|Inositol 1,4,5-Trisphosphate Receptors|Insecta|Ion Channel Gating|Models, Biological|Models, Chemical|Presenilins', 'Journal Article', '10.1371/journal.pcbi.1004529', '26439382', 'Familial Alzheimers disease (FAD)-causing mutant presenilins (PS) interact with inositol 1,4,5-trisphosphate (IP3) receptor (IP3R) Ca(2+) release channels resulting in enhanced IP3R channel gating in an amyloid beta (Axcexb2) production-independent manner. This gain-of-function enhancement of IP3R activity is considered to be the main reason behind the upregulation of intracellular Ca(2+) signaling in the presence of optimal and suboptimal stimuli and spontaneous Ca(2+) signals observed in cells expressing mutant PS. In this paper, we employed computational modeling of single IP3R channel activity records obtained under optimal Ca(2+) and multiple IP3 concentrations to gain deeper insights into the enhancement of IP3R function. We found that in addition to the high occupancy of the high-activity (H) mode and the low occupancy of the low-activity (L) mode, IP3R in FAD-causing mutant PS-expressing cells exhibits significantly longer mean life-time for the H mode and shorter life-time for the L mode, leading to shorter mean close-time and hence high open probability of the channel in comparison to IP3R in cells expressing wild-type PS. The model is then used to extrapolate the behavior of the channel to a wide range of IP3 and Ca(2+) concentrations and quantify the sensitivity of IP3R to its two ligands. We show that the gain-of-function enhancement is sensitive to both IP3 and Ca(2+) and that very small amount of IP3 is required to stimulate IP3R channels in the presence of FAD-causing mutant PS to the same level of activity as channels in control cells stimulated by significantly higher IP3 concentrations. We further demonstrate with simulations that the relatively longer time spent by IP3R in the H mode leads to the observed higher frequency of local Ca(2+) signals, which can account for the more frequent global Ca(2+) signals observed, while the enhanced activity of the channel at extremely low ligand concentrations will lead to spontaneous Ca(2+) signals in cells expressing FAD-causing mutant PS.'),
(87386, 2015, 'plos', 'Primary Visual Cortex as a Saliency Map: A Parameter-Free Prediction and Its Test by Behavioral Data', 'Zhaoping, Li|Zhe, Li', 'University College London, London, United Kingdom.|Tsinghua University, Beijing, China.', 'United Kingdom|China', 12, 'Attention|Brain Mapping|Computer Simulation|Female|Humans|Male|Models, Neurological|Nerve Net|Reaction Time|Space Perception|Visual Cortex|Visual Fields|Visual Perception', 'Journal Article', '10.1371/journal.pcbi.1004375', '26441341', 'It has been hypothesized that neural activities in the primary visual cortex (V1) represent a saliency map of the visual field to exogenously guide attention. This hypothesis has so far provided only qualitative predictions and their confirmations. We report this hypothesis first quantitative prediction, derived without free parameters, and its confirmation by human behavioral data. The hypothesis provides a direct link between V1 neural responses to a visual location and the saliency of that location to guide attention exogenously. In a visual input containing many bars, one of them saliently different from all the other bars which are identical to each other, saliency at the singletons location can be measured by the shortness of the reaction time in a visual search for singletons. The hypothesis predicts quantitatively the whole distribution of the reaction times to find a singleton unique in color, orientation, and motion direction from the reaction times to find other types of singletons. The prediction matches human reaction time data. A requirement for this successful prediction is a data-motivated assumption that V1 lacks neurons tuned simultaneously to color, orientation, and motion direction of visual inputs. Since evidence suggests that extrastriate cortices do have such neurons, we discuss the possibility that the extrastriate cortices play no role in guiding exogenous attention so that they can be devoted to other functions like visual decoding and endogenous attention. '),
(87387, 2015, 'plos', 'Ligand Discovery for the Alanine-Serine-Cysteine Transporter (ASCT2, SLC1A5) from Homology Modeling and Virtual Screening', 'Colas, Claire|Grewer, Christof|Otte, Nicholas James|Gameiro, Armanda|Albers, Thomas|Singh, Kurnvir|Shere, Helen|Bonomi, Massimiliano|Holst, Jeff|Schlessinger, Avner', 'Department of Pharmacology and Systems Therapeutics, Tisch Cancer Institute, Icahn School of Medicine at Mount Sinai, New York, New York, United States of America.|Department of Chemistry, Binghamton University, Binghamton, New York, United States of America.|Origins of Cancer Laboratory Centenary Program, Camperdown, Australia, Sydney Medical School, University of Sydney, Sydney, Australia.|Department of Chemistry, Binghamton University, Binghamton, New York, United States of America.|Department of Chemistry, Binghamton University, Binghamton, New York, United States of America.|Department of Chemistry, Binghamton University, Binghamton, New York, United States of America.|Department of Pharmacology and Systems Therapeutics, Tisch Cancer Institute, Icahn School of Medicine at Mount Sinai, New York, New York, United States of America.|Department of Chemistry, University of Cambridge, Cambridge, United Kingdom.|Origins of Cancer Laboratory Centenary Program, Camperdown, Australia, Sydney Medical School, University of Sydney, Sydney, Australia.|Department of Pharmacology and Systems Therapeutics, Tisch Cancer Institute, Icahn School of Medicine at Mount Sinai, New York, New York, United States of America.', 'United States|United States|Australia|United States|United States|United States|United States|United', 40, 'Algorithms|Amino Acid Sequence|Amino Acid Transport System ASC|Binding Sites|Drug Evaluation, Preclinical|Minor Histocompatibility Antigens|Models, Chemical|Molecular Docking Simulation|Molecular Sequence Data|Protein Binding|Protein Interaction Mapping|Sequence Analysis, Protein|Sequence Homology, Amino Acid', 'Journal Article', '10.1371/journal.pcbi.1004477', '26444490', 'The Alanine-Serine-Cysteine transporter ASCT2 (SLC1A5) is a membrane protein that transports neutral amino acids into cells in exchange for outward movement of intracellular amino acids. ASCT2 is highly expressed in peripheral tissues such as the lung and intestines where it contributes to the homeostasis of intracellular concentrations of neutral amino acids. ASCT2 also plays an important role in the development of a variety of cancers such as melanoma by transporting amino acid nutrients such as glutamine into the proliferating tumors. Therefore, ASCT2 is a key drug target with potentially great pharmacological importance. Here, we identify seven ASCT2 ligands by computational modeling and experimental testing. In particular, we construct homology models based on crystallographic structures of the aspartate transporter GltPh in two different conformations. Optimization of the models binding sites for protein-ligand complementarity reveals new putative pockets that can be targeted via structure-based drug design. Virtual screening of drugs, metabolites, fragments-like, and lead-like molecules from the ZINC database, followed by experimental testing of 14 top hits with functional measurements using electrophysiological methods reveals seven ligands, including five activators and two inhibitors. For example, aminooxetane-3-carboxylate is a more efficient activator than any other known ASCT2 natural or unnatural substrate. Furthermore, two of the hits inhibited ASCT2 mediated glutamine uptake and proliferation of a melanoma cancer cell line. Our results improve our understanding of how substrate specificity is determined in amino acid transporters, as well as provide novel scaffolds for developing chemical tools targeting ASCT2, an emerging therapeutic target for cancer and neurological disorders. '),
(87388, 2015, 'plos', 'Ten Simple Rules for Establishing International Research Collaborations', 'de Grijs, Richard', 'Kavli Institute for Astronomy and Astrophysics, Peking University, Beijing, China, East Asian Regional Office of Astronomy for Development (EA-ROAD), International Astronomical Union.', 'China', 5, 'Algorithms|Cooperative Behavior|Interinstitutional Relations|International Cooperation|Models, Organizational|Research|Science', 'Editorial', '10.1371/journal.pcbi.1004311', '26447799', '-'),
(87389, 2015, 'plos', 'TRANSIT--A Software Tool for Himar1 TnSeq Analysis', 'DeJesus, Michael A|Ambadipudi, Chaitra|Baker, Richard|Sassetti, Christopher|Ioerger, Thomas R', 'Department of Computer Science, Texas A&M University, College Station, Texas, United States of America.|Department of Computer Science, Texas A&M University, College Station, Texas, United States of America.|Department of Microbiology and Physiological Systems, University of Massachusetts Medical School, Worcester, Massachusetts, United States of America.|Department of Microbiology and Physiological Systems, University of Massachusetts Medical School, Worcester, Massachusetts, United States of America.|Department of Computer Science, Texas A&M University, College Station, Texas, United States of America.', 'United States|United States|United States|United States|United States', 48, 'Algorithms|Base Sequence|Chromosome Mapping|DNA Transposable Elements|Genome, Bacterial|Molecular Sequence Data|Pattern Recognition, Automated|Programming Languages|Sequence Analysis, DNA|Software', 'Journal Article', '10.1371/journal.pcbi.1004401', '26447887', 'TnSeq has become a popular technique for determining the essentiality of genomic regions in bacterial organisms. Several methods have been developed to analyze the wealth of data that has been obtained through TnSeq experiments. We developed a tool for analyzing Himar1 TnSeq data called TRANSIT. TRANSIT provides a graphical interface to three different statistical methods for analyzing TnSeq data. These methods cover a variety of approaches capable of identifying essential genes in individual datasets as well as comparative analysis between conditions. We demonstrate the utility of this software by analyzing TnSeq datasets of M. tuberculosis grown on glycerol and cholesterol. We show that TRANSIT can be used to discover genes which have been previously implicated for growth on these carbon sources. TRANSIT is written in Python, and thus can be run on Windows, OSX and Linux platforms. The source code is distributed under the GNU GPL v3 license and can be obtained from the following GitHub repository: https://github.com/mad-lab/transit. '),
(87390, 2015, 'plos', 'An Adapting Auditory-motor Feedback Loop Can Contribute to Generating Vocal Repetition', 'Wittenbach, Jason D|Bouchard, Kristofer E|Brainard, Michael S|Jin, Dezhe Z', 'Department of Physics and Center for Neural Engineering, the Pennsylvania State University, University Park, Pennsylvania, United States of America.|Department of Physiology and Center for Integrative Neuroscience, University of California at San Francisco, San Francisco, California, United States of America, Department of Neurosurgery and Center for Neural Engineering and Prosthesis, University of California at San Francisco, San Francisco, California, United States of America.|Department of Physiology and Center for Integrative Neuroscience, University of California at San Francisco, San Francisco, California, United States of America, Howard Hughes Medical Institute, San Francisco, California, United States of America.|Department of Physics and Center for Neural Engineering, the Pennsylvania State University, University Park, Pennsylvania, United States of America.', 'United States|United States|United States|United States', 0, 'Adaptation, Physiological|Animals|Auditory Cortex|Auditory Pathways|Computer Simulation|Efferent Pathways|Feedback, Physiological|Male|Models, Neurological|Motor Cortex|Movement|Songbirds|Vocalization, Animal', 'Journal Article', '10.1371/journal.pcbi.1004471', '26448054', 'Consecutive repetition of actions is common in behavioral sequences. Although integration of sensory feedback with internal motor programs is important for sequence generation, if and how feedback contributes to repetitive actions is poorly understood. Here we study how auditory feedback contributes to generating repetitive syllable sequences in songbirds. We propose that auditory signals provide positive feedback to ongoing motor commands, but this influence decays as feedback weakens from response adaptation during syllable repetitions. Computational models show that this mechanism explains repeat distributions observed in Bengalese finch song. We experimentally confirmed two predictions of this mechanism in Bengalese finches: removal of auditory feedback by deafening reduces syllable repetitions, and neural responses to auditory playback of repeated syllable sequences gradually adapt in sensory-motor nucleus HVC. Together, our results implicate a positive auditory-feedback loop with adaptation in generating repetitive vocalizations, and suggest sensory adaptation is important for feedback control of motor sequences. ');
INSERT INTO `papers` (`id`, `ano`, `journal`, `titulo`, `autores`, `afiliacao`, `pais`, `citacoes`, `palavra_chave`, `categorias`, `doi`, `pubmed`, `abstract`) VALUES
(87391, 2015, 'plos', 'Ten Simple Rules for Writing a Reply Paper', 'Simmons, Mark P', 'Department of Biology, Colorado State University, Fort Collins, Colorado, United States of America.', 'United States', 1, 'Algorithms|Information Dissemination|Medical Writing|Peer Review, Research|Periodicals as Topic|Publishing', 'Editorial', '10.1371/journal.pcbi.1004536', '26448197', '-'),
(87392, 2015, 'plos', 'Antagonistic Coevolution Drives Whack-a-Mole Sensitivity in Gene Regulatory Networks', 'Shin, Jeewoen|MacCarthy, Thomas', 'Department of Applied Mathematics and Statistics, Stony Brook University, Stony Brook, New York, United States of America.|Department of Applied Mathematics and Statistics, Stony Brook University, Stony Brook, New York, United States of America, Laufer Center for Physical and Quantitative Biology, Stony Brook University, Stony Brook, New York, United States of America.', 'United States|United States', 2, 'Animals|Evolution, Molecular|Feedback, Physiological|Game Theory|Gene Expression Regulation|Gene Regulatory Networks|Models, Genetic|Mutation|Predatory Behavior|Selection, Genetic', 'Journal Article', '10.1371/journal.pcbi.1004432', '26451700', 'Robustness, defined as tolerance to perturbations such as mutations and environmental fluctuations, is pervasive in biological systems. However, robustness often coexists with its counterpart, evolvability--the ability of perturbations to generate new phenotypes. Previous models of gene regulatory network evolution have shown that robustness evolves under stabilizing selection, but it is unclear how robustness and evolvability will emerge in common coevolutionary scenarios. We consider a two-species model of coevolution involving one host and one parasite population. By using two interacting species, key model parameters that determine the fitness landscapes become emergent properties of the model, avoiding the need to impose these parameters externally. In our study, parasites are modeled on species such as cuckoos where mimicry of the host phenotype confers high fitness to the parasite but lower fitness to the host. Here, frequent phenotype changes are favored as each population continually adapts to the other population. Sensitivity evolves at the network level such that point mutations can induce large phenotype changes. Crucially, the sensitive points of the network are broadly distributed throughout the network and continually relocate. Each time sensitive points in the network are mutated, new ones appear to take their place. We have therefore named this phenomenon whack-a-mole sensitivity, after a popular fun park game. We predict that this type of sensitivity will evolve under conditions of strong directional selection, an observation that helps interpret existing experimental evidence, for example, during the emergence of bacterial antibiotic resistance.'),
(87393, 2015, 'plos', 'Connectivity Homology Enables Inter-Species Network Models of Synthetic Lethality', 'Jacunski, Alexandra|Dixon, Scott J|Tatonetti, Nicholas P', 'Integrated Program in Cellular, Molecular, and Biomedical Studies, Columbia University, New York, New York, United States of America, Department of Systems Biology, Columbia University, New York, New York, United States of America.|Department of Biological Sciences, Columbia University, New York, New York, United States of America.|Department of Systems Biology, Columbia University, New York, New York, United States of America, Department of Biomedical Informatics, Columbia University, New York, New York, United States of America, Department of Medicine, Columbia University, New York, New York, United States of America.', 'United States|United States|United States', 11, 'Algorithms|Cell Survival|Computer Simulation|Fungal Proteins|Genes, Lethal|Models, Genetic|Protein Biosynthesis|RNA, Small Interfering|Saccharomyces|Sequence Homology, Nucleic Acid|Species Specificity', 'Journal Article', '10.1371/journal.pcbi.1004506', '26451775', 'Synthetic lethality is a genetic interaction wherein two otherwise nonessential genes cause cellular inviability when knocked out simultaneously. Drugs can mimic genetic knock-out effects, therefore, our understanding of promiscuous drugs, polypharmacology-related adverse drug reactions, and multi-drug therapies, especially cancer combination therapy, may be informed by a deeper understanding of synthetic lethality. However, the colossal experimental burden in humans necessitates in silico methods to guide the identification of synthetic lethal pairs. Here, we present SINaTRA (Species-INdependent TRAnslation), a network-based methodology that discovers genome-wide synthetic lethality in translation between species. SINaTRA uses connectivity homology, defined as biological connectivity patterns that persist across species, to identify synthetic lethal pairs. Importantly, our approach does not rely on genetic homology or structural and functional similarity, and it significantly outperforms models utilizing these data. We validate SINaTRA by predicting synthetic lethality in S. pombe using S. cerevisiae data, then identify over one million putative human synthetic lethal pairs to guide experimental approaches. We highlight the translational applications of our algorithm for drug discovery by identifying clusters of genes significantly enriched for single- and multi-drug cancer therapies. '),
(87394, 2015, 'plos', 'Modelling Odor Decoding in the Antennal Lobe by Combining Sequential Firing Rate Models with Bayesian Inference', 'Cuevas Rivera, Dario|Bitzer, Sebastian|Kiebel, Stefan J', 'Department of Psychology, Technische Universität, Dresden, Germany, Biomagnetic Centre, Department of Neurology, University Hospital Jena, Jena, Germany.|Department of Psychology, Technische Universität, Dresden, Germany, Department of Neurology, Max Planck Institute for Human Cognitive and Brain Sciences, Leipzig, Germany.|Department of Psychology, Technische Universität, Dresden, Germany, Biomagnetic Centre, Department of Neurology, University Hospital Jena, Jena, Germany, Department of Neurology, Max Planck Institute for Human Cognitive and Brain Sciences, Leipzig, Germany.', 'Germany|Germany|Germany', 3, 'Action Potentials|Animals|Arthropod Antennae|Bayes Theorem|Computer Simulation|Insecta|Models, Neurological|Models, Statistical|Nerve Net|Odorants|Olfactory Perception|Olfactory Receptor Neurons', 'Journal Article', '10.1371/journal.pcbi.1004528', '26451888', 'The olfactory information that is received by the insect brain is encoded in the form of spatiotemporal patterns in the projection neurons of the antennal lobe. These dense and overlapping patterns are transformed into a sparse code in Kenyon cells in the mushroom body. Although it is clear that this sparse code is the basis for rapid categorization of odors, it is yet unclear how the sparse code in Kenyon cells is computed and what information it represents. Here we show that this computation can be modeled by sequential firing rate patterns using Lotka-Volterra equations and Bayesian online inference. This new model can be understood as an intelligent coincidence detector, which robustly and dynamically encodes the presence of specific odor features. We found that the model is able to qualitatively reproduce experimentally observed activity in both the projection neurons and the Kenyon cells. In particular, the model explains mechanistically how sparse activity in the Kenyon cells arises from the dense code in the projection neurons. The odor classification performance of the model proved to be robust against noise and time jitter in the observed input sequences. As in recent experimental results, we found that recognition of an odor happened very early during stimulus presentation in the model. Critically, by using the model, we found surprising but simple computational explanations for several experimental phenomena. '),
(87395, 2015, 'plos', 'Discrete Element Framework for Modelling Extracellular Matrix, Deformable Cells and Subcellular Components', 'Gardiner, Bruce S|Wong, Kelvin K L|Joldes, Grand R|Rich, Addison J|Tan, Chin Wee|Burgess, Antony W|Smith, David W', 'School of Engineering and Information Technology, Murdoch University, Perth, Australia.|Engineering Computational Biology, School of Computer Science and Software Engineering, The University of Western Australia, Perth, Australia.|Intelligent Systems for Medicine Laboratory, School of Mechanical and Chemical Engineering, The University of Western Australia, Perth, Australia.|Engineering Computational Biology, School of Computer Science and Software Engineering, The University of Western Australia, Perth, Australia.|Structural Biology Division, The Walter and Eliza Hall Institute of Medical Research, Parkville, Victoria, Australia, Department of Medical Biology, University of Melbourne, Melbourne, Victoria, Australia.|Structural Biology Division, The Walter and Eliza Hall Institute of Medical Research, Parkville, Victoria, Australia, Department of Medical Biology, University of Melbourne, Melbourne, Victoria, Australia, Department of Surgery, Royal Melbourne Hospital, Melbourne, Victoria, Australia.|Engineering Computational Biology, School of Computer Science and Software Engineering, The University of Western Australia, Perth, Australia.', 'Australia|Australia|Australia|Australia|Australia|Australia|Australia', 17, 'Animals|Cell Physiological Phenomena|Computer Simulation|Extracellular Matrix|Humans|Mechanotransduction, Cellular|Models, Biological|Models, Statistical|Subcellular Fractions', 'Journal Article', '10.1371/journal.pcbi.1004544', '26452000', 'This paper presents a framework for modelling biological tissues based on discrete particles. Cell components (e.g. cell membranes, cell cytoskeleton, cell nucleus) and extracellular matrix (e.g. collagen) are represented using collections of particles. Simple particle to particle interaction laws are used to simulate and control complex physical interaction types (e.g. cell-cell adhesion via cadherins, integrin basement membrane attachment, cytoskeletal mechanical properties). Particles may be given the capacity to change their properties and behaviours in response to changes in the cellular microenvironment (e.g., in response to cell-cell signalling or mechanical loadings). Each particle is in effect an agent, meaning that the agent can sense local environmental information and respond according to pre-determined or stochastic events. The behaviour of the proposed framework is exemplified through several biological problems of ongoing interest. These examples illustrate how the modelling framework allows enormous flexibility for representing the mechanical behaviour of different tissues, and we argue this is a more intuitive approach than perhaps offered by traditional continuum methods. Because of this flexibility, we believe the discrete modelling framework provides an avenue for biologists and bioengineers to explore the behaviour of tissue systems in a computational laboratory. '),
(87396, 2015, 'plos', 'Comprehensive Meta-analysis of Ontology Annotated 16S rRNA Profiles Identifies Beta Diversity Clusters of Environmental Bacterial Communities', 'Henschel, Andreas|Anwar, Muhammad Zohaib|Manohar, Vimitha', 'Department of Electrical Engineering and Computer Science/Institute Center Smart Infrastructure (iSmart), Masdar Institute, Abu Dhabi, UAE.|Department of Electrical Engineering and Computer Science/Institute Center Smart Infrastructure (iSmart), Masdar Institute, Abu Dhabi, UAE.|Department of Electrical Engineering and Computer Science/Institute Center Smart Infrastructure (iSmart), Masdar Institute, Abu Dhabi, UAE.', '-|-|-', 17, 'Chromosome Mapping|Data Mining|Databases, Genetic|Ecosystem|Genetic Variation|Genome, Bacterial|Metagenome|Microbiota|RNA, Ribosomal, 16S', 'Journal Article', '10.1371/journal.pcbi.1004468', '26458130', 'Comprehensive mapping of environmental microbiomes in terms of their compositional features remains a great challenge in understanding the microbial biosphere of the Earth. It bears promise to identify the driving forces behind the observed community patterns and whether community assembly happens deterministically. Advances in Next Generation Sequencing allow large community profiling studies, exceeding sequencing data output of conventional methods in scale by orders of magnitude. However, appropriate collection systems are still in a nascent state. We here present a database of 20,427 diverse environmental 16S rRNA profiles from 2,426 independent studies, which forms the foundation of our meta-analysis. We conducted a sample size adaptive all-against-all beta diversity comparison while also respecting phylogenetic relationships of Operational Taxonomic Units(OTUs). After conventional hierarchical clustering we systematically test for enrichment of Environmental Ontology terms and their abstractions in all possible clusters. This post-hoc algorithm provides a novel formalism that quantifies to what extend compositional and semantic similarity of microbial community samples coincide. We automatically visualize significantly enriched subclusters on a comprehensive dendrogram of microbial communities. As a result we obtain the hitherto most differentiated and comprehensive view on global patterns of microbial community diversity. We observe strong clusterability of microbial communities in ecosystems such as human/mammal-associated, geothermal, fresh water, plant-associated, soils and rhizosphere microbiomes, whereas hypersaline and anthropogenic samples are less homogeneous. Moreover, saline samples appear less cohesive in terms of compositional properties than previously reported. '),
(87397, 2015, 'plos', 'Feed-Forward versus Feedback Inhibition in a Basic Olfactory Circuit', 'Kee, Tiffany|Sanda, Pavel|Gupta, Nitin|Stopfer, Mark|Bazhenov, Maxim', 'Department of Cell Biology and Neuroscience, University of California, Riverside, Riverside, California, United States of America.|Department of Cell Biology and Neuroscience, University of California, Riverside, Riverside, California, United States of America.|Department of Biological Sciences and Bioengineering, Indian Institute of Technology Kanpur, Kanpur, India.|US National Institutes of Health, National Institute of Child Health and Human Development, Bethesda, Maryland, United States of America.|Department of Cell Biology and Neuroscience, University of California, Riverside, Riverside, California, United States of America.', 'United States|United States|India|United States|United States', 19, 'Action Potentials|Animals|Computer Simulation|Excitatory Postsynaptic Potentials|Feedback, Physiological|Grasshoppers|Models, Neurological|Mushroom Bodies|Nerve Net|Neural Inhibition|Olfactory Pathways|Smell|Synaptic Transmission', 'Journal Article', '10.1371/journal.pcbi.1004531', '26458212', 'Inhibitory interneurons play critical roles in shaping the firing patterns of principal neurons in many brain systems. Despite difference in the anatomy or functions of neuronal circuits containing inhibition, two basic motifs repeatedly emerge: feed-forward and feedback. In the locust, it was proposed that a subset of lateral horn interneurons (LHNs), provide feed-forward inhibition onto Kenyon cells (KCs) to maintain their sparse firing--a property critical for olfactory learning and memory. But recently it was established that a single inhibitory cell, the giant GABAergic neuron (GGN), is the main and perhaps sole source of inhibition in the mushroom body, and that inhibition from this cell is mediated by a feedback (FB) loop including KCs and the GGN. To clarify basic differences in the effects of feedback vs. feed-forward inhibition in circuit dynamics we here use a model of the locust olfactory system. We found both inhibitory motifs were able to maintain sparse KCs responses and provide optimal odor discrimination. However, we further found that only FB inhibition could create a phase response consistent with data recorded in vivo. These findings describe general rules for feed-forward versus feedback inhibition and suggest GGN is potentially capable of providing the primary source of inhibition to the KCs. A better understanding of how inhibitory motifs impact post-synaptic neuronal activity could be used to reveal unknown inhibitory structures within biological networks.'),
(87398, 2015, 'plos', 'A Common Mechanism Underlying Food Choice and Social Decisions', 'Krajbich, Ian|Hare, Todd|Bartling, Björn|Morishima, Yosuke|Fehr, Ernst', 'Department of Economics, University of Zurich, Zurich, Switzerland, Department of Psychology, The Ohio State University, Columbus, Ohio, United States of America, Department of Economics, The Ohio State University, Columbus, Ohio, United States of America.|Department of Economics, University of Zurich, Zurich, Switzerland.|Department of Economics, University of Zurich, Zurich, Switzerland.|Department of Economics, University of Zurich, Zurich, Switzerland, Translational Research Center, University Hospital of Psychiatry, University of Bern, Bern, Switzerland, Japan Science and Technology Agency, PRESTO, Saitama, Japan.|Department of Economics, University of Zurich, Zurich, Switzerland.', 'Switzerland|Switzerland|Switzerland|Switzerland|Switzerland', 35, 'Choice Behavior|Computer Simulation|Decision Support Techniques|Feeding Behavior|Food Preferences|Game Theory|Humans|Models, Biological|Social Behavior', 'Journal Article', '10.1371/journal.pcbi.1004371', '26460812', 'People make numerous decisions every day including perceptual decisions such as walking through a crowd, decisions over primary rewards such as what to eat, and social decisions that require balancing own and others benefits. The unifying principles behind choices in various domains are, however, still not well understood. Mathematical models that describe choice behavior in specific contexts have provided important insights into the computations that may underlie decision making in the brain. However, a critical and largely unanswered question is whether these models generalize from one choice context to another. Here we show that a model adapted from the perceptual decision-making domain and estimated on choices over food rewards accurately predicts choices and reaction times in four independent sets of subjects making social decisions. The robustness of the model across domains provides behavioral evidence for a common decision-making process in perceptual, primary reward, and social decision making. '),
(87399, 2015, 'plos', 'Efficient Shotgun Inference of Neural Connectivity from Highly Sub-sampled Activity Data', 'Soudry, Daniel|Keshri, Suraj|Stinson, Patrick|Oh, Min-Hwan|Iyengar, Garud|Paninski, Liam', 'Department of Statistics, Department of Neuroscience, the Center for Theoretical Neuroscience, the Grossman Center for the Statistics of Mind, the Kavli Institute for Brain Science, and the NeuroTechnology Center, Columbia University, New York, New York, United States of America.|Department of Industrial Engineering and Operations Research, Columbia University, New York, New York, United States of America.|Department of Statistics, Department of Neuroscience, the Center for Theoretical Neuroscience, the Grossman Center for the Statistics of Mind, the Kavli Institute for Brain Science, and the NeuroTechnology Center, Columbia University, New York, New York, United States of America.|Department of Industrial Engineering and Operations Research, Columbia University, New York, New York, United States of America.|Department of Industrial Engineering and Operations Research, Columbia University, New York, New York, United States of America.|Department of Statistics, Department of Neuroscience, the Center for Theoretical Neuroscience, the Grossman Center for the Statistics of Mind, the Kavli Institute for Brain Science, and the NeuroTechnology Center, Columbia University, New York, New York, United States of America.', 'United States|United States|United States|United States|United States|United States', 20, 'Algorithms|Animals|Computer Simulation|Connectome|Data Interpretation, Statistical|Humans|Models, Neurological|Models, Statistical|Nerve Net|Neurons|Sample Size|Synaptic Transmission', 'Journal Article', '10.1371/journal.pcbi.1004464', '26465147', 'Inferring connectivity in neuronal networks remains a key challenge in statistical neuroscience. The common input problem presents a major roadblock: it is difficult to reliably distinguish causal connections between pairs of observed neurons versus correlations induced by common input from unobserved neurons. Available techniques allow us to simultaneously record, with sufficient temporal resolution, only a small fraction of the network. Consequently, naive connectivity estimators that neglect these common input effects are highly biased. This work proposes a shotgun experimental design, in which we observe multiple sub-networks briefly, in a serial manner. Thus, while the full network cannot be observed simultaneously at any given time, we may be able to observe much larger subsets of the network over the course of the entire experiment, thus ameliorating the common input problem. Using a generalized linear model for a spiking recurrent neural network, we develop a scalable approximate expected loglikelihood-based Bayesian method to perform network inference given this type of data, in which only a small fraction of the network is observed in each time bin. We demonstrate in simulation that the shotgun experimental design can eliminate the biases induced by common input effects. Networks with thousands of neurons, in which only a small fraction of the neurons is observed in each time bin, can be quickly and accurately estimated, achieving orders of magnitude speed up over previous approaches. '),
(87400, 2015, 'plos', 'The Mass-Longevity Triangle: Pareto Optimality and the Geometry of Life-History Trait Space', 'Szekely, Pablo|Korem, Yael|Moran, Uri|Mayo, Avi|Alon, Uri', 'Department of Molecular Cell Biology, The Weizmann Institute of Science, Rehovot, Israel.|Department of Molecular Cell Biology, The Weizmann Institute of Science, Rehovot, Israel.|Department of Plant Science, The Weizmann Institute of Science, Rehovot, Israel.|Department of Molecular Cell Biology, The Weizmann Institute of Science, Rehovot, Israel.|Department of Molecular Cell Biology, The Weizmann Institute of Science, Rehovot, Israel.', 'Israel|Israel|Israel|Israel|Israel', 0, 'Algorithms|Animals|Body Weight|Computer Simulation|Game Theory|Longevity|Models, Biological|Models, Statistical', 'Journal Article', '10.1371/journal.pcbi.1004524', '26465336', 'When organisms need to perform multiple tasks they face a fundamental tradeoff: no phenotype can be optimal at all tasks. This situation was recently analyzed using Pareto optimality, showing that tradeoffs between tasks lead to phenotypes distributed on low dimensional polygons in trait space. The vertices of these polygons are archetypes--phenotypes optimal at a single task. This theory was applied to examples from animal morphology and gene expression. Here we ask whether Pareto optimality theory can apply to life history traits, which include longevity, fecundity and mass. To comprehensively explore the geometry of life history trait space, we analyze a dataset of life history traits of 2105 endothermic species. We find that, to a first approximation, life history traits fall on a triangle in log-mass log-longevity space. The vertices of the triangle suggest three archetypal strategies, exemplified by bats, shrews and whales, with specialists near the vertices and generalists in the middle of the triangle. To a second approximation, the data lies in a tetrahedron, whose extra vertex above the mass-longevity triangle suggests a fourth strategy related to carnivory. Each animal species can thus be placed in a coordinate system according to its distance from the archetypes, which may be useful for genome-scale comparative studies of mammalian aging and other biological aspects. We further demonstrate that Pareto optimality can explain a range of previous studies which found animal and plant phenotypes which lie in triangles in trait space. This study demonstrates the applicability of multi-objective optimization principles to understand life history traits and to infer archetypal strategies that suggest why some mammalian species live much longer than others of similar mass.'),
(87401, 2015, 'plos', 'Establishing a Statistical Link between Network Oscillations and Neural Synchrony', 'Zhou, Pengcheng|Burton, Shawn D|Snyder, Adam C|Smith, Matthew A|Urban, Nathaniel N|Kass, Robert E', 'Program for Neural Computation, Carnegie Mellon University, Pittsburgh, Pennsylvania, United States of America, Center for the Neural Basis of Cognition, Pittsburgh, Pennsylvania, United States of America.|Center for the Neural Basis of Cognition, Pittsburgh, Pennsylvania, United States of America, Department of Biological Sciences, Carnegie Mellon University, Pittsburgh, Pennsylvania, United States of America.|Center for the Neural Basis of Cognition, Pittsburgh, Pennsylvania, United States of America, Department of Ophthalmology, University of Pittsburgh, Pittsburgh, Pennsylvania, United States of America.|Center for the Neural Basis of Cognition, Pittsburgh, Pennsylvania, United States of America, Department of Ophthalmology, University of Pittsburgh, Pittsburgh, Pennsylvania, United States of America.|Center for the Neural Basis of Cognition, Pittsburgh, Pennsylvania, United States of America, Department of Biological Sciences, Carnegie Mellon University, Pittsburgh, Pennsylvania, United States of America, Department of Neurobiology, University of Pittsburgh, Pittsburgh, Pennsylvania, United States of America.|Center for the Neural Basis of Cognition, Pittsburgh, Pennsylvania, United States of America, Department of Statistics, Carnegie Mellon University, Pittsburgh, Pennsylvania, United States of America, Department of Machine Learning, Carnegie Mellon University, Pittsburgh, Pennsylvania, United States of America.', 'United States|United States|United States|United States|United States|United States', 9, 'Action Potentials|Animals|Biological Clocks|Cells, Cultured|Computer Simulation|Cortical Synchronization|Feedback, Physiological|Humans|Macaca mulatta|Male|Mice|Models, Neurological|Models, Statistical|Nerve Net|Synaptic Transmission', 'Journal Article', '10.1371/journal.pcbi.1004549', '26465621', 'Pairs of active neurons frequently fire action potentials or spikes nearly synchronously (i.e., within 5 ms of each other). This spike synchrony may occur by chance, based solely on the neurons fluctuating firing patterns, or it may occur too frequently to be explicable by chance alone. When spike synchrony above chances levels is present, it may subserve computation for a specific cognitive process, or it could be an irrelevant byproduct of such computation. Either way, spike synchrony is a feature of neural data that should be explained. A point process regression framework has been developed previously for this purpose, using generalized linear models (GLMs). In this framework, the observed number of synchronous spikes is compared to the number predicted by chance under varying assumptions about the factors that affect each of the individual neurons firing-rate functions. An important possible source of spike synchrony is network-wide oscillations, which may provide an essential mechanism of network information flow. To establish the statistical link between spike synchrony and network-wide oscillations, we have integrated oscillatory field potentials into our point process regression framework. We first extended a previously-published model of spike-field association and showed that we could recover phase relationships between oscillatory field potentials and firing rates. We then used this new framework to demonstrate the statistical relationship between oscillatory field potentials and spike synchrony in: 1) simulated neurons, 2) in vitro recordings of hippocampal CA1 pyramidal cells, and 3) in vivo recordings of neocortical V4 neurons. Our results provide a rigorous method for establishing a statistical link between network oscillations and neural synchrony. '),
(87402, 2015, 'plos', 'Gene Prioritization by Compressive Data Fusion and Chaining', 'Žitnik, Marinka|Nam, Edward A|Dinh, Christopher|Kuspa, Adam|Shaulsky, Gad|Zupan, Blaž', 'Faculty of Computer and Information Science, University of Ljubljana, Ljubljana, Slovenia.|Department of Molecular and Human Genetics, Baylor College of Medicine, Houston, Texas, United States of America.|Department of Biochemistry and Molecular Biology, Baylor College of Medicine, Houston, Texas, United States of America.|Department of Molecular and Human Genetics, Baylor College of Medicine, Houston, Texas, United States of America, Department of Biochemistry and Molecular Biology, Baylor College of Medicine, Houston, Texas, United States of America.|Department of Molecular and Human Genetics, Baylor College of Medicine, Houston, Texas, United States of America.|Faculty of Computer and Information Science, University of Ljubljana, Ljubljana, Slovenia, Department of Molecular and Human Genetics, Baylor College of Medicine, Houston, Texas, United States of America.', 'Slovenia|United States|United States|United States|United States|Slovenia', 0, 'Cell Proliferation|Data Compression|Data Mining|Databases, Genetic|Dictyostelium|Gram-Negative Bacteria|Protozoan Proteins', 'Journal Article', '10.1371/journal.pcbi.1004552', '26465776', 'Data integration procedures combine heterogeneous data sets into predictive models, but they are limited to data explicitly related to the target object type, such as genes. Collage is a new data fusion approach to gene prioritization. It considers data sets of various association levels with the prediction task, utilizes collective matrix factorization to compress the data, and chaining to relate different object types contained in a data compendium. Collage prioritizes genes based on their similarity to several seed genes. We tested Collage by prioritizing bacterial response genes in Dictyostelium as a novel model system for prokaryote-eukaryote interactions. Using 4 seed genes and 14 data sets, only one of which was directly related to the bacterial response, Collage proposed 8 candidate genes that were readily validated as necessary for the response of Dictyostelium to Gram-negative bacteria. These findings establish Collage as a method for inferring biological knowledge from the integration of heterogeneous and coarsely related data sets. '),
(87403, 2015, 'plos', 'A Neutrophil Phenotype Model for Extracorporeal Treatment of Sepsis', 'Malkin, Alexander D|Sheehan, Robert P|Mathew, Shibin|Federspiel, William J|Redl, Heinz|Clermont, Gilles', 'McGowan Institute for Regenerative Medicine, University of Pittsburgh, Pittsburgh, Pennsylvania, United States of America, Department of Bioengineering, University of Pittsburgh, Pittsburgh, Pennsylvania, United States of America.|Department of Computational and Systems Biology, University of Pittsburgh, Pittsburgh, Pennsylvania, United States of America.|Department of Chemical and Petroleum Engineering, University of Pittsburgh, Pittsburgh, Pennsylvania, United States of America.|McGowan Institute for Regenerative Medicine, University of Pittsburgh, Pittsburgh, Pennsylvania, United States of America, Department of Bioengineering, University of Pittsburgh, Pittsburgh, Pennsylvania, United States of America, Department of Chemical and Petroleum Engineering, University of Pittsburgh, Pittsburgh, Pennsylvania, United States of America, Department of Surgery, University of Pittsburgh, Pittsburgh, Pennsylvania, United States of America.|Ludwig Boltzmann Institute for Experimental and Clinical Traumatology in AUVA center, Vienna, Austria.|CRISMA Center, Department of Critical Care Medicine, University of Pittsburgh, Pittsburgh, Pennsylvania, United States of America.', 'United States|United States|United States|United States|Austria|United States', 0, 'Animals|Blood Component Removal|Computer Simulation|Extracorporeal Circulation|Models, Immunological|Neutrophils|Papio|Prognosis|Receptors, CXCR|Receptors, Interleukin-8A|Receptors, Interleukin-8B|Sepsis|Survival Rate|Treatment Outcome', 'Journal Article', '10.1371/journal.pcbi.1004314', '26468651', 'Neutrophils play a central role in eliminating bacterial pathogens, but may also contribute to end-organ damage in sepsis. Interleukin-8 (IL-8), a key modulator of neutrophil function, signals through neutrophil specific surface receptors CXCR-1 and CXCR-2. In this study a mechanistic computational model was used to evaluate and deploy an extracorporeal sepsis treatment which modulates CXCR-1/2 levels. First, a simplified mechanistic computational model of IL-8 mediated activation of CXCR-1/2 receptors was developed, containing 16 ODEs and 43 parameters. Receptor level dynamics and systemic parameters were coupled with multiple neutrophil phenotypes to generate dynamic populations of activated neutrophils which reduce pathogen load, and/or primed neutrophils which cause adverse tissue damage when misdirected. The mathematical model was calibrated using experimental data from baboons administered a two-hour infusion of E coli and followed for a maximum of 28 days. Ensembles of parameters were generated using a Bayesian parallel tempering approach to produce model fits that could recreate experimental outcomes. Stepwise logistic regression identified seven model parameters as key determinants of mortality. Sensitivity analysis showed that parameters controlling the level of killer cell neutrophils affected the overall systemic damage of individuals. To evaluate rescue strategies and provide probabilistic predictions of their impact on mortality, time of onset, duration, and capture efficacy of an extracorporeal device that modulated neutrophil phenotype were explored. Our findings suggest that interventions aiming to modulate phenotypic composition are time sensitive. When introduced between 3-6 hours of infection for a 72 hour duration, the survivor population increased from 31% to 40-80%. Treatment efficacy quickly diminishes if not introduced within 15 hours of infection. Significant harm is possible with treatment durations ranging from 5-24 hours, which may reduce survival to 13%. In severe sepsis, an extracorporeal treatment which modulates CXCR-1/2 levels has therapeutic potential, but also potential for harm. Further development of the computational model will help guide optimal device development and determine which patient populations should be targeted by treatment. '),
(87404, 2015, 'plos', 'PF2fit: Polar Fast Fourier Matched Alignment of Atomistic Structures with 3D Electron Microscopy Maps', 'Bettadapura, Radhakrishna|Rasheed, Muhibur|Vollrath, Antje|Bajaj, Chandrajit', 'Radhakrishna Bettadapura Computational Visualization Center/Department of Mechanical Engineering, University of Texas at Austin, Austin, Texas, United States of America.|Muhibur Rasheed Computational Visualization Center/Department of Mechanical Engineering, University of Texas at Austin, Austin, Texas, United States of America.|Antje Vollrath Institut Computational Mathematics, Technische Universität Braunschweig, Braunschweig, Germany.|Chandrajit Bajaj Computational Visualization Center/Institute of Computational Engineering & Sciences/Department of Computer Science, University of Texas at Austin, Austin, Texas, United States of America.', 'United States|United States|Germany|United States', 2, 'Algorithms|Crystallography|Fourier Analysis|Image Interpretation, Computer-Assisted|Imaging, Three-Dimensional|Microscopy, Electron|Programming Languages|Protein Conformation|Proteins|Software|Subtraction Technique', 'Journal Article', '10.1371/journal.pcbi.1004289', '26469938', 'There continue to be increasing occurrences of both atomistic structure models in the PDB (possibly reconstructed from X-ray diffraction or NMR data), and 3D reconstructed cryo-electron microscopy (3D EM) maps (albeit at coarser resolution) of the same or homologous molecule or molecular assembly, deposited in the EMDB. To obtain the best possible structural model of the molecule at the best achievable resolution, and without any missing gaps, one typically aligns (match and fits) the atomistic structure model with the 3D EM map. We discuss a new algorithm and generalized framework, named PF(2) fit (Polar Fast Fourier Fitting) for the best possible structural alignment of atomistic structures with 3D EM. While PF(2) fit enables only a rigid, six dimensional (6D) alignment method, it augments prior work on 6D X-ray structure and 3D EM alignment in multiple ways: Scoring. PF(2) fit includes a new scoring scheme that, in addition to rewarding overlaps between the volumes occupied by the atomistic structure and 3D EM map, rewards overlaps between the volumes complementary to them. We quantitatively demonstrate how this new complementary scoring scheme improves upon existing approaches. PF(2) fit also includes two scoring functions, the non-uniform exterior penalty and the skeleton-secondary structure score, and implements the scattering potential score as an alternative to traditional Gaussian blurring. Search. PF(2) fit utilizes a fast polar Fourier search scheme, whose main advantage is the ability to search over uniformly and adaptively sampled subsets of the space of rigid-body motions. PF(2) fit also implements a new reranking search and scoring methodology that considerably improves alignment metrics in results obtained from the initial search.'),
(87405, 2015, 'plos', 'Quantitative Live Imaging of Human Embryonic Stem Cell Derived Neural Rosettes Reveals Structure-Function Dynamics Coupled to Cortical Development', 'Ziv, Omer|Zaritsky, Assaf|Yaffe, Yakey|Mutukula, Naresh|Edri, Reuven|Elkabetz, Yechiel', 'Department of Cell and Developmental Biology, Sackler School of Medicine, Tel Aviv University, Ramat Aviv, Tel Aviv, Israel.|Department of Cell Biology, UT Southwestern Medical Center, Dallas, Texas, United States of America, The Blavatnik School of Computer Science, Tel Aviv University, Ramat Aviv, Tel Aviv, Israel.|Department of Cell and Developmental Biology, Sackler School of Medicine, Tel Aviv University, Ramat Aviv, Tel Aviv, Israel.|Department of Cell and Developmental Biology, Sackler School of Medicine, Tel Aviv University, Ramat Aviv, Tel Aviv, Israel.|Department of Cell and Developmental Biology, Sackler School of Medicine, Tel Aviv University, Ramat Aviv, Tel Aviv, Israel.|Department of Cell and Developmental Biology, Sackler School of Medicine, Tel Aviv University, Ramat Aviv, Tel Aviv, Israel.', 'Israel|Israel|Israel|Israel|Israel|Israel', 0, 'Cell Differentiation|Cell Tracking|Cells, Cultured|Cerebral Cortex|Embryonic Stem Cells|Humans|Intravital Microscopy|Neural Stem Cells|Neurogenesis|Structure-Activity Relationship', 'Journal Article', '10.1371/journal.pcbi.1004453', '26473351', 'Neural stem cells (NSCs) are progenitor cells for brain development, where cellular spatial composition (cytoarchitecture) and dynamics are hypothesized to be linked to critical NSC capabilities. However, understanding cytoarchitectural dynamics of this process has been limited by the difficulty to quantitatively image brain development in vivo. Here, we study NSC dynamics within Neural Rosettes--highly organized multicellular structures derived from human pluripotent stem cells. Neural rosettes contain NSCs with strong epithelial polarity and are expected to perform apical-basal interkinetic nuclear migration (INM)--a hallmark of cortical radial glial cell development. We developed a quantitative live imaging framework to characterize INM dynamics within rosettes. We first show that the tendency of cells to follow the INM orientation--a phenomenon we referred to as radial organization, is associated with rosette size, presumably via mechanical constraints of the confining structure. Second, early forming rosettes, which are abundant with founder NSCs and correspond to the early proliferative developing cortex, show fast motions and enhanced radial organization. In contrast, later derived rosettes, which are characterized by reduced NSC capacity and elevated numbers of differentiated neurons, and thus correspond to neurogenesis mode in the developing cortex, exhibit slower motions and decreased radial organization. Third, later derived rosettes are characterized by temporal instability in INM measures, in agreement with progressive loss in rosette integrity at later developmental stages. Finally, molecular perturbations of INM by inhibition of actin or non-muscle myosin-II (NMII) reduced INM measures. Our framework enables quantification of cytoarchitecture NSC dynamics and may have implications in functional molecular studies, drug screening, and iPS cell-based platforms for disease modeling.'),
(87406, 2015, 'plos', 'Bridging between NMA and Elastic Network Models: Preserving All-Atom Accuracy in Coarse-Grained Models', 'Na, Hyuntae|Jernigan, Robert L|Song, Guang', 'Department of Computer Science, Iowa State University, Ames, Iowa, United States of America.|Department of Biochemistry, Biophysics and Molecular Biology, Iowa State University, Ames, Iowa, United States of America, Program of Bioinformatics and Computational Biology, Iowa State University, Ames, Iowa, United States of America, L. H. Baker Center for Bioinformatics and Biological Statistics, Iowa State University, Ames, Iowa, United States of America.|Department of Computer Science, Iowa State University, Ames, Iowa, United States of America, Program of Bioinformatics and Computational Biology, Iowa State University, Ames, Iowa, United States of America, L. H. Baker Center for Bioinformatics and Biological Statistics, Iowa State University, Ames, Iowa, United States of America.', 'United States|United States|United States', 0, 'Binding Sites|Chaperonin 10|Chaperonin 60|Elastic Modulus|Models, Chemical|Molecular Docking Simulation|Motion|Protein Binding|Protein Conformation|Protein Interaction Mapping', 'Journal Article', '10.1371/journal.pcbi.1004542', '26473491', 'Dynamics can provide deep insights into the functional mechanisms of proteins and protein complexes. For large protein complexes such as GroEL/GroES with more than 8,000 residues, obtaining a fine-grained all-atom description of its normal mode motions can be computationally prohibitive and is often unnecessary. For this reason, coarse-grained models have been used successfully. However, most existing coarse-grained models use extremely simple potentials to represent the interactions within the coarse-grained structures and as a result, the dynamics obtained for the coarse-grained structures may not always be fully realistic. There is a gap between the quality of the dynamics of the coarse-grained structures given by all-atom models and that by coarse-grained models. In this work, we resolve an important question in protein dynamics computations--how can we efficiently construct coarse-grained models whose description of the dynamics of the coarse-grained structures remains as accurate as that given by all-atom models? Our method takes advantage of the sparseness of the Hessian matrix and achieves a high efficiency with a novel iterative matrix projection approach. The result is highly significant since it can provide descriptions of normal mode motions at an all-atom level of accuracy even for the largest biomolecular complexes. The application of our method to GroEL/GroES offers new insights into the mechanism of this biologically important chaperonin, such as that the conformational transitions of this protein complex in its functional cycle are even more strongly connected to the first few lowest frequency modes than with other coarse-grained models.'),
(87407, 2015, 'plos', 'The Structural Basis for Activation and Inhibition of ZAP-70 Kinase Domain', 'Huber, Roland G|Fan, Hao|Bond, Peter J', 'Bioinformatics Institute (BII), Agency for Science, Technology and Research (A*STAR), Singapore.|Bioinformatics Institute (BII), Agency for Science, Technology and Research (A*STAR), Singapore, Department of Biological Sciences, National University of Singapore, Singapore.|Bioinformatics Institute (BII), Agency for Science, Technology and Research (A*STAR), Singapore, Department of Biological Sciences, National University of Singapore, Singapore.', 'Singapore|Singapore|Singapore', 4, 'Binding Sites|Enzyme Activation|Enzyme Stability|Models, Chemical|Molecular Dynamics Simulation|Phosphotransferases|Protein Binding|Protein Conformation|Protein Structure, Tertiary|Structure-Activity Relationship|Substrate Specificity|ZAP-70 Protein-Tyrosine Kinase', 'Journal Article', '10.1371/journal.pcbi.1004560', '26473606', 'ZAP-70 (Zeta-chain-associated protein kinase 70) is a tyrosine kinase that interacts directly with the activated T-cell receptor to transduce downstream signals, and is hence a major player in the regulation of the adaptive immune response. Dysfunction of ZAP-70 causes selective T cell deficiency that in turn results in persistent infections. ZAP-70 is activated by a variety of signals including phosphorylation of the kinase domain (KD), and binding of its regulatory tandem Src homology 2 (SH2) domains to the T cell receptor. The present study investigates molecular mechanisms of activation and inhibition of ZAP-70 via atomically detailed molecular dynamics simulation approaches. We report microsecond timescale simulations of five distinct states of the ZAP-70 KD, comprising apo, inhibited and three phosphorylated variants. Extensive analysis of local flexibility and correlated motions reveal crucial transitions between the states, thus elucidating crucial steps in the activation mechanism of the ZAP-70 KD. Furthermore, we rationalize previously observed staurosporine-bound crystal structures, suggesting that whilst the KD superficially resembles an active-like conformation, the inhibitor modulates the underlying protein dynamics and restricts it in a compact, rigid state inaccessible to ligands or cofactors. Finally, our analysis reveals a novel, potentially druggable pocket in close proximity to the activation loop of the kinase, and we subsequently use its structure in fragment-based virtual screening to develop a pharmacophore model. The pocket is distinct from classical type I or type II kinase pockets, and its discovery offers promise in future design of specific kinase inhibitors, whilst mutations in residues associated with this pocket are implicated in immunodeficiency in humans. '),
(87408, 2015, 'plos', 'Transcriptional Bursting in Gene Expression: Analytical Results for General Stochastic Models', 'Kumar, Niraj|Singh, Abhyudai|Kulkarni, Rahul V', 'Department of Physics, University of Massachusetts Boston, Boston, Massachusetts, United States of America.|Department of Electrical and Computer Engineering, University of Delaware, Newark, Delaware, United States of America.|Department of Physics, University of Massachusetts Boston, Boston, Massachusetts, United States of America.', 'United States|United States|United States', 50, 'Animals|Computer Simulation|Gene Expression Regulation|Humans|Models, Genetic|Models, Statistical|Protein Biosynthesis|RNA, Messenger|Stochastic Processes|Transcriptional Activation', 'Journal Article', '10.1371/journal.pcbi.1004292', '26474290', 'Gene expression in individual cells is highly variable and sporadic, often resulting in the synthesis of mRNAs and proteins in bursts. Such bursting has important consequences for cell-fate decisions in diverse processes ranging from HIV-1 viral infections to stem-cell differentiation. It is generally assumed that bursts are geometrically distributed and that they arrive according to a Poisson process. On the other hand, recent single-cell experiments provide evidence for complex burst arrival processes, highlighting the need for analysis of more general stochastic models. To address this issue, we invoke a mapping between general stochastic models of gene expression and systems studied in queueing theory to derive exact analytical expressions for the moments associated with mRNA/protein steady-state distributions. These results are then used to derive noise signatures, i.e. explicit conditions based entirely on experimentally measurable quantities, that determine if the burst distributions deviate from the geometric distribution or if burst arrival deviates from a Poisson process. For non-Poisson arrivals, we develop approaches for accurate estimation of burst parameters. The proposed approaches can lead to new insights into transcriptional bursting based on measurements of steady-state mRNA/protein distributions. ');
INSERT INTO `papers` (`id`, `ano`, `journal`, `titulo`, `autores`, `afiliacao`, `pais`, `citacoes`, `palavra_chave`, `categorias`, `doi`, `pubmed`, `abstract`) VALUES
(87409, 2015, 'plos', 'Electrosensory Midbrain Neurons Display Feature Invariant Responses to Natural Communication Stimuli', 'Aumentado-Armstrong, Tristan|Metzen, Michael G|Sproule, Michael K J|Chacron, Maurice J', 'School of Computer Science, McGill University, Montreal, Quebec, Canada.|Department of Physiology, McGill University, Montreal, Quebec, Canada.|Department of Physiology, McGill University, Montreal, Quebec, Canada.|Department of Physiology, McGill University, Montreal, Quebec, Canada.', 'Canada|Canada|Canada|Canada', 20, 'Action Potentials|Animal Communication|Animals|Computer Simulation|Electric Fish|Electric Organ|Mesencephalon|Models, Neurological|Sense Organs|Sensory Receptor Cells', 'Journal Article', '10.1371/journal.pcbi.1004430', '26474395', 'Neurons that respond selectively but in an invariant manner to a given feature of natural stimuli have been observed across species and systems. Such responses emerge in higher brain areas, thereby suggesting that they occur by integrating afferent input. However, the mechanisms by which such integration occurs are poorly understood. Here we show that midbrain electrosensory neurons can respond selectively and in an invariant manner to heterogeneity in behaviorally relevant stimulus waveforms. Such invariant responses were not seen in hindbrain electrosensory neurons providing afferent input to these midbrain neurons, suggesting that response invariance results from nonlinear integration of such input. To test this hypothesis, we built a model based on the Hodgkin-Huxley formalism that received realistic afferent input. We found that multiple combinations of parameter values could give rise to invariant responses matching those seen experimentally. Our model thus shows that there are multiple solutions towards achieving invariant responses and reveals how subthreshold membrane conductances help promote robust and invariant firing in response to heterogeneous stimulus waveforms associated with behaviorally relevant stimuli. We discuss the implications of our findings for the electrosensory and other systems. '),
(87410, 2015, 'plos', 'The Impact of Different Sources of Fluctuations on Mutual Information in Biochemical Networks', 'Chevalier, Michael|Venturelli, Ophelia|El-Samad, Hana', 'Department of Biochemistry and Biophysics, California Institute for Quantitative Biosciences, University of California San Francisco, San Francisco, California, United States of America.|Department of Bioengineering, University of California, Berkeley, Berkeley, California, United States of America.|Department of Biochemistry and Biophysics, California Institute for Quantitative Biosciences, University of California San Francisco, San Francisco, California, United States of America.', 'United States|United States|United States', 0, 'Animals|Computer Simulation|Gene Expression Regulation|Humans|Models, Biological|Models, Statistical|Proteome|Signal Transduction|Stochastic Processes', 'Journal Article', '10.1371/journal.pcbi.1004462', '26484538', 'Stochastic fluctuations in signaling and gene expression limit the ability of cells to sense the state of their environment, transfer this information along cellular pathways, and respond to it with high precision. Mutual information is now often used to quantify the fidelity with which information is transmitted along a cellular pathway. Mutual information calculations from experimental data have mostly generated low values, suggesting that cells might have relatively low signal transmission fidelity. In this work, we demonstrate that mutual information calculations might be artificially lowered by cell-to-cell variability in both initial conditions and slowly fluctuating global factors across the population. We carry out our analysis computationally using a simple signaling pathway and demonstrate that in the presence of slow global fluctuations, every cell might have its own high information transmission capacity but that population averaging underestimates this value. We also construct a simple synthetic transcriptional network and demonstrate using experimental measurements coupled to computational modeling that its operation is dominated by slow global variability, and hence that its mutual information is underestimated by a population averaged calculation. '),
(87411, 2015, 'plos', 'The Shape of an Auxin Pulse, and What It Tells Us about the Transport Mechanism', 'Mitchison, Graeme', 'Sainsbury Laboratory, Cambridge University, Cambridge, United Kingdom.', 'United Kingdom', 6, 'Biological Transport, Active|Carrier Proteins|Computer Simulation|Cotyledon|Diffusion|Indoleacetic Acids|Models, Biological|Models, Chemical|Plant Proteins|Plant Stems', 'Journal Article', '10.1371/journal.pcbi.1004487', '26484661', 'Auxin underlies many processes in plant development and physiology, and this makes it of prime importance to understand its movements through plant tissues. In stems and coleoptiles, classic experiments showed that the peak region of a pulse of radio-labelled auxin moves at a roughly constant velocity down a stem or coleoptile segment. As the pulse moves it becomes broader, at a roughly constant rate. It is shown here that this spreading rate is larger than can be accounted for by a single channel model, but can be explained by coupling of channels with differing polar transport rates. An extreme case is where strongly polar channels are coupled to completely apolar channels, in which case auxin in the apolar part is dragged along by the polar part in a somewhat diffuse distribution. The behaviour of this model is explored, together with others that can account for the experimentally observed spreading rates. It is also shown that saturation of carriers involved in lateral transport can explain the characteristic shape of pulses that result from uptake of large amounts of auxin. '),
(87412, 2015, 'plos', 'Perm-seq: Mapping Protein-DNA Interactions in Segmental Duplication and Highly Repetitive Regions of Genomes with Prior-Enhanced Read Mapping', 'Zeng, Xin|Li, Bo|Welch, Rene|Rojo, Constanza|Zheng, Ye|Dewey, Colin N|Kelexc5x9f, Sxc3xbcndxc3xbcz', 'Department of Statistics, University of Wisconsin, Madison, Wisconsin, United States of America.|California Institute for Quantitative Biosciences, University of California, Berkeley, California, United States of America.|Department of Statistics, University of Wisconsin, Madison, Wisconsin, United States of America.|Department of Statistics, University of Wisconsin, Madison, Wisconsin, United States of America.|Department of Statistics, University of Wisconsin, Madison, Wisconsin, United States of America.|Department of Biostatistics and Medical Informatics, University of Wisconsin, Madison, Wisconsin, United States of America.|Department of Statistics, University of Wisconsin, Madison, Wisconsin, United States of America, Department of Biostatistics and Medical Informatics, University of Wisconsin, Madison, Wisconsin, United States of America.', 'United States|United States|United States|United States|United States|United States|United States', 0, 'Algorithms|Base Sequence|Chromatin Immunoprecipitation|Chromosome Mapping|DNA|DNA-Binding Proteins|High-Throughput Nucleotide Sequencing|Humans|K562 Cells|Molecular Sequence Data|Protein Interaction Mapping|Repetitive Sequences, Nucleic Acid|Segmental Duplications, Genomic', 'Journal Article', '10.1371/journal.pcbi.1004491', '26484757', 'Segmental duplications and other highly repetitive regions of genomes contribute significantly to cells regulatory programs. Advancements in next generation sequencing enabled genome-wide profiling of protein-DNA interactions by chromatin immunoprecipitation followed by high throughput sequencing (ChIP-seq). However, interactions in highly repetitive regions of genomes have proven difficult to map since short reads of 50-100 base pairs (bps) from these regions map to multiple locations in reference genomes. Standard analytical methods discard such multi-mapping reads and the few that can accommodate them are prone to large false positive and negative rates. We developed Perm-seq, a prior-enhanced read allocation method for ChIP-seq experiments, that can allocate multi-mapping reads in highly repetitive regions of the genomes with high accuracy. We comprehensively evaluated Perm-seq, and found that our prior-enhanced approach significantly improves multi-read allocation accuracy over approaches that do not utilize additional data types. The statistical formalism underlying our approach facilitates supervising of multi-read allocation with a variety of data sources including histone ChIP-seq. We applied Perm-seq to 64 ENCODE ChIP-seq datasets from GM12878 and K562 cells and identified many novel protein-DNA interactions in segmental duplication regions. Our analysis reveals that although the protein-DNA interactions sites are evolutionarily less conserved in repetitive regions, they share the overall sequence characteristics of the protein-DNA interactions in non-repetitive regions. '),
(87413, 2015, 'plos', 'At the Edge of Chaos: How Cerebellar Granular Layer Network Dynamics Can Provide the Basis for Temporal Filters', 'Rössert, Christian|Dean, Paul|Porrill, John', 'Department of Psychology, The University of Sheffield, Sheffield, United Kingdom.|Department of Psychology, The University of Sheffield, Sheffield, United Kingdom.|Department of Psychology, The University of Sheffield, Sheffield, United Kingdom.', 'United Kingdom|United Kingdom|United Kingdom', 0, 'Action Potentials|Animals|Cerebellum|Computer Simulation|Humans|Models, Neurological|Models, Statistical|Nerve Net|Neural Inhibition|Neurons|Nonlinear Dynamics', 'Journal Article', '10.1371/journal.pcbi.1004515', '26484859', 'Models of the cerebellar microcircuit often assume that input signals from the mossy-fibers are expanded and recoded to provide a foundation from which the Purkinje cells can synthesize output filters to implement specific input-signal transformations. Details of this process are however unclear. While previous work has shown that recurrent granule cell inhibition could in principle generate a wide variety of random outputs suitable for coding signal onsets, the more general application for temporally varying signals has yet to be demonstrated. Here we show for the first time that using a mechanism very similar to reservoir computing enables random neuronal networks in the granule cell layer to provide the necessary signal separation and extension from which Purkinje cells could construct basis filters of various time-constants. The main requirement for this is that the network operates in a state of criticality close to the edge of random chaotic behavior. We further show that the lack of recurrent excitation in the granular layer as commonly required in traditional reservoir networks can be circumvented by considering other inherent granular layer features such as inverted input signals or mGluR2 inhibition of Golgi cells. Other properties that facilitate filter construction are direct mossy fiber excitation of Golgi cells, variability of synaptic weights or input signals and output-feedback via the nucleocortical pathway. Our findings are well supported by previous experimental and theoretical work and will help to bridge the gap between system-level models and detailed models of the granular layer network. '),
(87414, 2015, 'plos', 'A Pan-Cancer Catalogue of Cancer Driver Protein Interaction Interfaces', 'Porta-Pardo, Eduard|Garcia-Alonso, Luz|Hrabe, Thomas|Dopazo, Joaquin|Godzik, Adam', 'Bioinformatics and Systems Biology Program, Sanford-Burnham Medical Research Institute, La Jolla, California, United States of America.|European Bioinformatics Institute (EMBL-EBI), Wellcome Trust Genome Campus, Cambridge, United Kingdom.|Bioinformatics and Systems Biology Program, Sanford-Burnham Medical Research Institute, La Jolla, California, United States of America.|Computational Genomics Department, Centro de Investigación Príncipe Felipe (CIPF), Valencia, Spain, Functional Genomics Node, (INB) at CIPF, Valencia, Spain, Bioinformatics of Rare Diseases (BIER), CIBER de Enfermedades Raras (CIBERER), Valencia, Spain.|Bioinformatics and Systems Biology Program, Sanford-Burnham Medical Research Institute, La Jolla, California, United States of America.', 'United States|United Kingdom|United States|Spain|United States', 51, 'Animals|Base Sequence|Biomarkers, Tumor|Catalogs as Topic|Chromosome Mapping|Computer Simulation|DNA Mutational Analysis|Genetic Predisposition to Disease|Humans|Models, Genetic|Molecular Sequence Data|Mutation|Neoplasm Proteins|Neoplasms|Polymorphism, Single Nucleotide|Protein Interaction Mapping|Signal Transduction', 'Journal Article', '10.1371/journal.pcbi.1004518', '26485003', 'Despite their importance in maintaining the integrity of all cellular pathways, the role of mutations on protein-protein interaction (PPI) interfaces as cancer drivers has not been systematically studied. Here we analyzed the mutation patterns of the PPI interfaces from 10,028 proteins in a pan-cancer cohort of 5,989 tumors from 23 projects of The Cancer Genome Atlas (TCGA) to find interfaces enriched in somatic missense mutations. To that end we use e-Driver, an algorithm to analyze the mutation distribution of specific protein functional regions. We identified 103 PPI interfaces enriched in somatic cancer mutations. 32 of these interfaces are found in proteins coded by known cancer driver genes. The remaining 71 interfaces are found in proteins that have not been previously identified as cancer drivers even that, in most cases, there is an extensive literature suggesting they play an important role in cancer. Finally, we integrate these findings with clinical information to show how tumors apparently driven by the same gene have different behaviors, including patient outcomes, depending on which specific interfaces are mutated. '),
(87415, 2015, 'plos', 'Established Microbial Colonies Can Survive Type VI Secretion Assault', 'Borenstein, David Bruce|Ringel, Peter|Basler, Marek|Wingreen, Ned S', 'Princeton University, Lewis-Sigler Institute for Integrative Genomics, Princeton, New Jersey, United States of America.|Universität Basel, Biozentrum, Basel, Switzerland.|Universität Basel, Biozentrum, Basel, Switzerland.|Princeton University, Lewis-Sigler Institute for Integrative Genomics, Princeton, New Jersey, United States of America, Princeton University, Department of Molecular Biology, Princeton, New Jersey, United States of America.', 'Jersey|Switzerland|Switzerland|Jersey', 0, 'Cell Communication|Cell Survival|Computer Simulation|Escherichia coli|Microbiota|Models, Biological|Type VI Secretion Systems|Vibrio cholerae', 'Journal Article', '10.1371/journal.pcbi.1004520', '26485125', 'Type VI secretion (T6S) is a cell-to-cell injection system that can be used as a microbial weapon. T6S kills vulnerable cells, and is present in close to 25% of sequenced Gram-negative bacteria. To examine the ecological role of T6S among bacteria, we competed self-immune T6S+ cells and T6S-sensitive cells in simulated range expansions. As killing takes place only at the interface between sensitive and T6S+ strains, while growth takes place everywhere, sufficiently large domains of sensitive cells can achieve net growth in the face of attack. Indeed T6S-sensitive cells can often outgrow their T6S+ competitors. We validated these findings through in vivo competition experiments between T6S+ Vibrio cholerae and T6S-sensitive Escherichia coli. We found that E. coli can survive and even dominate so long as they have an adequate opportunity to form microcolonies at the outset of the competition. Finally, in simulated competitions between two equivalent and mutually sensitive T6S+ strains, the more numerous strain has an advantage that increases with the T6S attack rate. We conclude that sufficiently large domains of T6S-sensitive individuals can survive attack and potentially outcompete self-immune T6S+ bacteria. '),
(87416, 2015, 'plos', 'Refinement of the Central Steps of Substrate Transport by the Aspartate Transporter GltPh: Elucidating the Role of the Na2 Sodium Binding Site', 'Venkatesan, SanthoshKannan|Saha, Kusumika|Sohail, Azmat|Sandtner, Walter|Freissmuth, Michael|Ecker, Gerhard F|Sitte, Harald H|Stockner, Thomas', 'Institute of Pharmacology, Center for Physiology and Pharmacology, Medical University of Vienna, Vienna, Austria.|Institute of Pharmacology, Center for Physiology and Pharmacology, Medical University of Vienna, Vienna, Austria.|Institute of Pharmacology, Center for Physiology and Pharmacology, Medical University of Vienna, Vienna, Austria.|Institute of Pharmacology, Center for Physiology and Pharmacology, Medical University of Vienna, Vienna, Austria.|Institute of Pharmacology, Center for Physiology and Pharmacology, Medical University of Vienna, Vienna, Austria.|Division of Drug Design & Medicinal Chemistry, Department of Pharmaceutical Chemistry, University of Vienna, Vienna, Austria.|Institute of Pharmacology, Center for Physiology and Pharmacology, Medical University of Vienna, Vienna, Austria.|Institute of Pharmacology, Center for Physiology and Pharmacology, Medical University of Vienna, Vienna, Austria.', 'Austria|Austria|Austria|Austria|Austria|Austria|Austria|Austria', 0, 'Amino Acid Transport Systems|Aspartic Acid|Binding Sites|Diffusion|Models, Chemical|Molecular Docking Simulation|Protein Binding|Protein Conformation|Sodium', 'Journal Article', '10.1371/journal.pcbi.1004551', '26485255', 'Glutamate homeostasis in the brain is maintained by glutamate transporter mediated accumulation. Impaired transport is associated with several neurological disorders, including stroke and amyotrophic lateral sclerosis. Crystal structures of the homolog transporter GltPh from Pyrococcus horikoshii revealed large structural changes. Substrate uptake at the atomic level and the mechanism of ion gradient conversion into directional transport remained enigmatic. We observed in repeated simulations that two local structural changes regulated transport. The first change led to formation of the transient Na2 sodium binding site, triggered by side chain rotation of T308. The second change destabilized cytoplasmic ionic interactions. We found that sodium binding to the transiently formed Na2 site energized substrate uptake through reshaping of the energy hypersurface. Uptake experiments in reconstituted proteoliposomes confirmed the proposed mechanism. We reproduced the results in the human glutamate transporter EAAT3 indicating a conserved mechanics from archaea to humans. '),
(87417, 2015, 'plos', 'Integrative Genomics-Based Discovery of Novel Regulators of the Innate Antiviral Response', 'van der Lee, Robin|Feng, Qian|Langereis, Martijn A|Ter Horst, Rob|Szklarczyk, Radek|Netea, Mihai G|Andeweg, Arno C|van Kuppeveld, Frank J M|Huynen, Martijn A', 'Centre for Molecular and Biomolecular Informatics, Radboud Institute for Molecular Life Sciences, Radboud university medical center, Nijmegen, The Netherlands.|Virology Division, Department of Infectious Diseases and Immunology, Faculty of Veterinary Medicine, University of Utrecht, Utrecht, The Netherlands.|Virology Division, Department of Infectious Diseases and Immunology, Faculty of Veterinary Medicine, University of Utrecht, Utrecht, The Netherlands.|Centre for Molecular and Biomolecular Informatics, Radboud Institute for Molecular Life Sciences, Radboud university medical center, Nijmegen, The Netherlands.|Centre for Molecular and Biomolecular Informatics, Radboud Institute for Molecular Life Sciences, Radboud university medical center, Nijmegen, The Netherlands.|Department of Internal Medicine and Radboud Center for Infectious Diseases, Radboud university medical center, Nijmegen, The Netherlands.|Department of Viroscience, Erasmus Medical Center, Rotterdam, The Netherlands.|Virology Division, Department of Infectious Diseases and Immunology, Faculty of Veterinary Medicine, University of Utrecht, Utrecht, The Netherlands.|Centre for Molecular and Biomolecular Informatics, Radboud Institute for Molecular Life Sciences, Radboud university medical center, Nijmegen, The Netherlands.', 'Netherlands|Netherlands|Netherlands|Netherlands|Netherlands|Netherlands|Netherlands|Netherlands|Neth', 0, 'Cytokines|DEAD Box Protein 58|DEAD-box RNA Helicases|Gene Expression Profiling|Gene Expression Regulation, Viral|Genomics|Immunity, Innate|RNA, Viral|Systems Integration|Virus Integration|Viruses', 'Journal Article', '10.1371/journal.pcbi.1004553', '26485378', 'The RIG-I-like receptor (RLR) pathway is essential for detecting cytosolic viral RNA to trigger the production of type I interferons (IFNxcexb1/xcexb2) that initiate an innate antiviral response. Through systematic assessment of a wide variety of genomics data, we discovered 10 molecular signatures of known RLR pathway components that collectively predict novel members. We demonstrate that RLR pathway genes, among others, tend to evolve rapidly, interact with viral proteins, contain a limited set of protein domains, are regulated by specific transcription factors, and form a tightly connected interaction network. Using a Bayesian approach to integrate these signatures, we propose likely novel RLR regulators. RNAi knockdown experiments revealed a high prediction accuracy, identifying 94 genes among 187 candidates tested (~50%) that affected viral RNA-induced production of IFNxcexb2. The discovered antiviral regulators may participate in a wide range of processes that highlight the complexity of antiviral defense (e.g. MAP3K11, CDK11B, PSMA3, TRIM14, HSPA9B, CDC37, NUP98, G3BP1), and include uncharacterized factors (DDX17, C6orf58, C16orf57, PKN2, SNW1). Our validated RLR pathway list (http://rlr.cmbi.umcn.nl/), obtained using a combination of integrative genomics and experiments, is a new resource for innate antiviral immunity research. '),
(87418, 2015, 'plos', 'Ten Simple Rules for Experiments Provenance', 'Kazic, Toni', 'Dept. of Computer Science Missouri Maize Center, Missouri Informatics Institute, and Interdisciplinary Plant Group, University of Missouri, Columbia, Missouri, United States of America.', 'United States', 7, 'Algorithms|Data Accuracy|Databases, Factual|Documentation|Guidelines as Topic|Information Storage and Retrieval|Ownership|Research Design|Terminology as Topic', 'Editorial', '10.1371/journal.pcbi.1004384', '26485673', '-'),
(87419, 2015, 'plos', 'Crawling and Gliding: A Computational Model for Shape-Driven Cell Migration', 'Niculescu, Ioana|Textor, Johannes|de Boer, Rob J', 'Theoretical Biology & Bioinformatics, Utrecht University, The Netherlands.|Theoretical Biology & Bioinformatics, Utrecht University, The Netherlands.|Theoretical Biology & Bioinformatics, Utrecht University, The Netherlands.', 'Netherlands|Netherlands|Netherlands', 18, 'Actins|Amoeba|Animals|Cell Adhesion|Cell Movement|Cell Size|Computer Simulation|Humans|Models, Biological|Molecular Motor Proteins', 'Journal Article', '10.1371/journal.pcbi.1004280', '26488304', 'Cell migration is a complex process involving many intracellular and extracellular factors, with different cell types adopting sometimes strikingly different morphologies. Modeling realistically behaving cells in tissues is computationally challenging because it implies dealing with multiple levels of complexity. We extend the Cellular Potts Model with an actin-inspired feedback mechanism that allows small stochastic cell rufflings to expand to cell protrusions. This simple phenomenological model produces realistically crawling and deforming amoeboid cells, and gliding half-moon shaped keratocyte-like cells. Both cell types can migrate randomly or follow directional cues. They can squeeze in between other cells in densely populated environments or migrate collectively. The model is computationally light, which allows the study of large, dense and heterogeneous tissues containing cells with realistic shapes and migratory properties. '),
(87420, 2015, 'plos', 'Path Similarity Analysis: A Method for Quantifying Macromolecular Pathways', 'Seyler, Sean L|Kumar, Avishek|Thorpe, M F|Beckstein, Oliver', 'Department of Physics and Center for Biological Physics, Arizona State University, Tempe, Arizona, United States of America.|Department of Physics and Center for Biological Physics, Arizona State University, Tempe, Arizona, United States of America.|Department of Physics and Center for Biological Physics, Arizona State University, Tempe, Arizona, United States of America, Rudolf Peierls Centre for Theoretical Physics, University of Oxford, Oxford, United Kingdom.|Department of Physics and Center for Biological Physics, Arizona State University, Tempe, Arizona, United States of America.', 'United States|United States|United Kingdom|United States', 0, 'Algorithms|Computer Simulation|Models, Chemical|Models, Molecular|Motion|Multiprotein Complexes|Protein Conformation|Proteins', 'Journal Article', '10.1371/journal.pcbi.1004568', '26488417', 'Diverse classes of proteins function through large-scale conformational changes and various sophisticated computational algorithms have been proposed to enhance sampling of these macromolecular transition paths. Because such paths are curves in a high-dimensional space, it has been difficult to quantitatively compare multiple paths, a necessary prerequisite to, for instance, assess the quality of different algorithms. We introduce a method named Path Similarity Analysis (PSA) that enables us to quantify the similarity between two arbitrary paths and extract the atomic-scale determinants responsible for their differences. PSA utilizes the full information available in 3N-dimensional configuration space trajectories by employing the Hausdorff or Fréchet metrics (adopted from computational geometry) to quantify the degree of similarity between piecewise-linear curves. It thus completely avoids relying on projections into low dimensional spaces, as used in traditional approaches. To elucidate the principles of PSA, we quantified the effect of path roughness induced by thermal fluctuations using a toy model system. Using, as an example, the closed-to-open transitions of the enzyme adenylate kinase (AdK) in its substrate-free form, we compared a range of protein transition path-generating algorithms. Molecular dynamics-based dynamic importance sampling (DIMS) MD and targeted MD (TMD) and the purely geometric FRODA (Framework Rigidity Optimized Dynamics Algorithm) were tested along with seven other methods publicly available on servers, including several based on the popular elastic network model (ENM). PSA with clustering revealed that paths produced by a given method are more similar to each other than to those from another method and, for instance, that the ENM-based methods produced relatively similar paths. PSA applied to ensembles of DIMS MD and FRODA trajectories of the conformational transition of diphtheria toxin, a particularly challenging example. For the AdK transition, the new concept of a Hausdorff-pair map enabled us to extract the molecular structural determinants responsible for differences in pathways, namely a set of conserved salt bridges whose charge-charge interactions are fully modelled in DIMS MD but not in FRODA. PSA has the potential to enhance our understanding of transition path sampling methods, validate them, and to provide a new approach to analyzing conformational transitions.'),
(87421, 2015, 'plos', 'Laminar Neural Field Model of Laterally Propagating Waves of Orientation Selectivity', 'Bressloff, Paul C|Carroll, Samuel R', 'Department of Mathematics, University of Utah, Salt Lake City, Utah, United States of America.|Department of Mathematics, University of Utah, Salt Lake City, Utah, United States of America.', 'United States|United States', 9, 'Action Potentials|Animals|Biological Clocks|Computer Simulation|Humans|Models, Neurological|Nerve Net|Orientation|Photic Stimulation|Space Perception|Spatial Processing|Visual Cortex', 'Journal Article', '10.1371/journal.pcbi.1004545', '26491877', 'We construct a laminar neural-field model of primary visual cortex (V1) consisting of a superficial layer of neurons that encode the spatial location and orientation of a local visual stimulus coupled to a deep layer of neurons that only encode spatial location. The spatially-structured connections in the deep layer support the propagation of a traveling front, which then drives propagating orientation-dependent activity in the superficial layer. Using a combination of mathematical analysis and numerical simulations, we establish that the existence of a coherent orientation-selective wave relies on the presence of weak, long-range connections in the superficial layer that couple cells of similar orientation preference. Moreover, the wave persists in the presence of feedback from the superficial layer to the deep layer. Our results are consistent with recent experimental studies that indicate that deep and superficial layers work in tandem to determine the patterns of cortical activity observed in vivo. '),
(87422, 2015, 'plos', 'Intracellular Information Processing through Encoding and Decoding of Dynamic Signaling Features', 'Makadia, Hirenkumar K|Schwaber, James S|Vadigepalli, Rajanikanth', 'Daniel Baugh Institute for Functional Genomics and Computational Biology, Department of Pathology, Anatomy and Cell Biology, Sidney Kimmel Medical College, Thomas Jefferson University, Philadelphia, Pennsylvania, United States of America.|Daniel Baugh Institute for Functional Genomics and Computational Biology, Department of Pathology, Anatomy and Cell Biology, Sidney Kimmel Medical College, Thomas Jefferson University, Philadelphia, Pennsylvania, United States of America.|Daniel Baugh Institute for Functional Genomics and Computational Biology, Department of Pathology, Anatomy and Cell Biology, Sidney Kimmel Medical College, Thomas Jefferson University, Philadelphia, Pennsylvania, United States of America.', 'United States|United States|United States', 9, 'Computer Simulation|Gene Expression Regulation|Models, Biological|Signal Transduction|Transcription Factors|Transcription, Genetic', 'Journal Article', '10.1371/journal.pcbi.1004563', '26491963', 'Cell signaling dynamics and transcriptional regulatory activities are variable within specific cell types responding to an identical stimulus. In addition to studying the network interactions, there is much interest in utilizing single cell scale data to elucidate the non-random aspects of the variability involved in cellular decision making. Previous studies have considered the information transfer between the signaling and transcriptional domains based on an instantaneous relationship between the molecular activities. These studies predict a limited binary on/off encoding mechanism which underestimates the complexity of biological information processing, and hence the utility of single cell resolution data. Here we pursue a novel strategy that reformulates the information transfer problem as involving dynamic features of signaling rather than molecular abundances. We pursue a computational approach to test if and how the transcriptional regulatory activity patterns can be informative of the temporal history of signaling. Our analysis reveals (1) the dynamic features of signaling that significantly alter transcriptional regulatory patterns (encoding), and (2) the temporal history of signaling that can be inferred from single cell scale snapshots of transcriptional activity (decoding). Immediate early gene expression patterns were informative of signaling peak retention kinetics, whereas transcription factor activity patterns were informative of activation and deactivation kinetics of signaling. Moreover, the information processing aspects varied across the network, with each component encoding a selective subset of the dynamic signaling features. We developed novel sensitivity and information transfer maps to unravel the dynamic multiplexing of signaling features at each of these network components. Unsupervised clustering of the maps revealed two groups that aligned with network motifs distinguished by transcriptional feedforward vs feedback interactions. Our new computational methodology impacts the single cell scale experiments by identifying downstream snapshot measures required for inferring specific dynamical features of upstream signals involved in the regulation of cellular responses. '),
(87423, 2015, 'plos', 'Qualitative and Quantitative Protein Complex Prediction Through Proteome-Wide Simulations', 'Rizzetto, Simone|Priami, Corrado|Csikász-Nagy, Attila', 'The Microsoft Research-University of Trento Centre for Computational Systems Biology, Rovereto, Italy.|The Microsoft Research-University of Trento Centre for Computational Systems Biology, Rovereto, Italy, Department of Mathematics, University of Trento, Povo (TN), Italy.|Department of Computational Biology, Research and Innovation Centre, Fondazione Edmund Mach, San Michele allAdige, Italy, Randall Division of Cell and Molecular Biophysics and Institute for Mathematical and Molecular Biomedicine, Kings College London, London, United Kingdom.', 'Italy|Italy|United Kingdom', 0, 'Algorithms|Binding Sites|Humans|Models, Chemical|Molecular Docking Simulation|Protein Binding|Protein Interaction Mapping|Proteins|Structure-Activity Relationship', 'Journal Article', '10.1371/journal.pcbi.1004424', '26492574', 'Despite recent progress in proteomics most protein complexes are still unknown. Identification of these complexes will help us understand cellular regulatory mechanisms and support development of new drugs. Therefore it is really important to establish detailed information about the composition and the abundance of protein complexes but existing algorithms can only give qualitative predictions. Herein, we propose a new approach based on stochastic simulations of protein complex formation that integrates multi-source data--such as protein abundances, domain-domain interactions and functional annotations--to predict alternative forms of protein complexes together with their abundances. This method, called SiComPre (Simulation based Complex Prediction), achieves better qualitative prediction of yeast and human protein complexes than existing methods and is the first to predict protein complex abundances. Furthermore, we show that SiComPre can be used to predict complexome changes upon drug treatment with the example of bortezomib. SiComPre is the first method to produce quantitative predictions on the abundance of molecular complexes while performing the best qualitative predictions. With new data on tissue specific protein complexes becoming available SiComPre will be able to predict qualitative and quantitative differences in the complexome in various tissue types and under various conditions.'),
(87424, 2015, 'plos', 'Ten Simple Rules for Creating a Good Data Management Plan', 'Michener, William K', 'College of University Libraries & Learning Sciences, University of New Mexico, Albuquerque, New Mexico, United States of America.', 'Mexico', 42, 'Algorithms|Data Accuracy|Database Management Systems|Databases, Factual|Guidelines as Topic|Information Storage and Retrieval|Research Design', 'Journal Article', '10.1371/journal.pcbi.1004525', '26492633', '-'),
(87425, 2015, 'plos', 'An Exploration of the Universe of Polyglutamine Structures', 'Gómez-Sicilia, Àngel|Sikora, Mateusz|Cieplak, Marek|Carrión-Vázquez, Mariano', 'Intituto Cajal/CSIC, Madrid, Spain, Instituto Madrileño de Estudios Avanzados en Nanociencia (IMDEA-Nanociencia),Madrid, Spain.|Institute of Science and Technology Austria, Klosterneuburg, Austria.|Instytut Fizyki PAN, Warsaw, Poland.|Intituto Cajal/CSIC, Madrid, Spain, Instituto Madrileño de Estudios Avanzados en Nanociencia (IMDEA-Nanociencia),Madrid, Spain.', 'Spain|Austria|Poland|Spain', 0, 'Models, Chemical|Molecular Dynamics Simulation|Peptides|Protein Conformation|Protein Folding', 'Journal Article', '10.1371/journal.pcbi.1004541', '26495838', 'Deposits of misfolded proteins in the human brain are associated with the development of many neurodegenerative diseases. Recent studies show that these proteins have common traits even at the monomer level. Among them, a polyglutamine region that is present in huntingtin is known to exhibit a correlation between the length of the chain and the severity as well as the earliness of the onset of Huntington disease. Here, we apply bias exchange molecular dynamics to generate structures of polyglutamine expansions of several lengths and characterize the resulting independent conformations. We compare the properties of these conformations to those of the standard proteins, as well as to other homopolymeric tracts. We find that, similar to the previously studied polyvaline chains, the set of possible transient folds is much broader than the set of known-to-date folds, although the conformations have different structures. We show that the mechanical stability is not related to any simple geometrical characteristics of the structures. We demonstrate that long polyglutamine expansions result in higher mechanical stability than the shorter ones. They also have a longer life span and are substantially more prone to form knotted structures. The knotted region has an average length of 35 residues, similar to the typical threshold for most polyglutamine-related diseases. Similarly, changes in shape and mechanical stability appear once the total length of the peptide exceeds this threshold of 35 glutamine residues. We suggest that knotted conformers may also harm the cellular machinery and thus lead to disease. '),
(87426, 2015, 'plos', 'Modeling the Evolution of Beliefs Using an Attentional Focus Mechanism', 'Markovixc4x87, Dimitrije|Glxc3xa4scher, Jan|Bossaerts, Peter|ODoherty, John|Kiebel, Stefan J', 'Department of Psychology, Technical University Dresden, Dresden, Germany, Max Planck Institute for Human Cognitive and Brain Sciences, Leipzig, Germany.|Institute for Systems Neuroscience, University Medical Center Hamburg-Eppendorf, Hamburg, Germany, Division of Humanities and Social Sciences, California Institute of Technology, Pasadena, California, United States of America.|Division of Humanities and Social Sciences, California Institute of Technology, Pasadena, California, United States of America, Department of Finance, University of Utah, Salt Lake City, United States of America, Computation and Neural Systems, California Institute of Technology, Pasadena, California, United States of America.|Division of Humanities and Social Sciences, California Institute of Technology, Pasadena, California, United States of America, Computation and Neural Systems, California Institute of Technology, Pasadena, California, United States of America, Trinity College Institute of Neuroscience, Trinity College Dublin, Dublin, Ireland.|Department of Psychology, Technical University Dresden, Dresden, Germany, Max Planck Institute for Human Cognitive and Brain Sciences, Leipzig, Germany.', 'Germany|Germany|United States|Ireland|Germany', 5, 'Attention|Choice Behavior|Culture|Decision Making|Decision Support Techniques|Environment|Humans|Models, Neurological|Models, Statistical|Visual Perception', 'Journal Article', '10.1371/journal.pcbi.1004558', '26495984', 'For making decisions in everyday life we often have first to infer the set of environmental features that are relevant for the current task. Here we investigated the computational mechanisms underlying the evolution of beliefs about the relevance of environmental features in a dynamical and noisy environment. For this purpose we designed a probabilistic Wisconsin card sorting task (WCST) with belief solicitation, in which subjects were presented with stimuli composed of multiple visual features. At each moment in time a particular feature was relevant for obtaining reward, and participants had to infer which feature was relevant and report their beliefs accordingly. To test the hypothesis that attentional focus modulates the belief update process, we derived and fitted several probabilistic and non-probabilistic behavioral models, which either incorporate a dynamical model of attentional focus, in the form of a hierarchical winner-take-all neuronal network, or a diffusive model, without attention-like features. We used Bayesian model selection to identify the most likely generative model of subjects behavior and found that attention-like features in the behavioral model are essential for explaining subjects responses. Furthermore, we demonstrate a method for integrating both connectionist and Bayesian models of decision making within a single framework that allowed us to infer hidden belief processes of human subjects. '),
(87427, 2015, 'plos', 'Signaling and Adaptation Modulate the Dynamics of the Photosensoric Complex of Natronomonas pharaonis', 'Orekhov, Philipp S|Klose, Daniel|Mulkidjanian, Armen Y|Shaitan, Konstantin V|Engelhard, Martin|Klare, Johann P|Steinhoff, Heinz-Jürgen', 'Department of Physics, University of Osnabrueck, Osnabrueck, Germany, Department of Biology, Lomonosov Moscow State University, Moscow, Russia.|Department of Physics, University of Osnabrueck, Osnabrueck, Germany.|Department of Physics, University of Osnabrueck, Osnabrueck, Germany, Department of Bioengineering and Bioinformatics and A. N. Belozersky Institute of Physico-Chemical Biology, Lomonosov Moscow State University, Moscow, Russia.|Department of Biology, Lomonosov Moscow State University, Moscow, Russia.|Max-Planck-Institute for Molecular Physiology, Dortmund, Germany.|Department of Physics, University of Osnabrueck, Osnabrueck, Germany.|Department of Physics, University of Osnabrueck, Osnabrueck, Germany.', 'Germany|Germany|Germany|-|Germany|Germany|Germany', 3, 'Adaptation, Ocular|Archaeal Proteins|Carotenoids|Computer Simulation|Halobacteriaceae|Light|Models, Biological|Models, Chemical|Molecular Dynamics Simulation|Photic Stimulation|Photoreceptors, Microbial|Protein Conformation|Radiation Dosage', 'Journal Article', '10.1371/journal.pcbi.1004561', '26496122', 'Motile bacteria and archaea respond to chemical and physical stimuli seeking optimal conditions for survival. To this end transmembrane chemo- and photoreceptors organized in large arrays initiate signaling cascades and ultimately regulate the rotation of flagellar motors. To unravel the molecular mechanism of signaling in an archaeal phototaxis complex we performed coarse-grained molecular dynamics simulations of a trimer of receptor/transducer dimers, namely NpSRII/NpHtrII from Natronomonas pharaonis. Signaling is regulated by a reversible methylation mechanism called adaptation, which also influences the level of basal receptor activation. Mimicking two extreme methylation states in our simulations we found conformational changes for the transmembrane region of NpSRII/NpHtrII which resemble experimentally observed light-induced changes. Further downstream in the cytoplasmic domain of the transducer the signal propagates via distinct changes in the dynamics of HAMP1, HAMP2, the adaptation domain and the binding region for the kinase CheA, where conformational rearrangements were found to be subtle. Overall these observations suggest a signaling mechanism based on dynamic allostery resembling models previously proposed for E. coli chemoreceptors, indicating similar properties of signal transduction for archaeal photoreceptors and bacterial chemoreceptors. '),
(87428, 2015, 'plos', 'Automatic Prediction of Protein 3D Structures by Probabilistic Multi-template Homology Modeling', 'Meier, Armin|Söding, Johannes', 'Quantitative and Computational Biology, Max Planck Institute for Biophysical Chemistry, Göttingen, Germany, Gene Center, Ludwig-Maximilians-Universität München Munich, Munich, Germany.|Quantitative and Computational Biology, Max Planck Institute for Biophysical Chemistry, Göttingen, Germany, Gene Center, Ludwig-Maximilians-Universität München Munich, Munich, Germany.', 'Germany|Germany', 51, 'Algorithms|Amino Acid Sequence|Computer Simulation|Models, Chemical|Models, Molecular|Models, Statistical|Molecular Sequence Data|Programming Languages|Protein Conformation|Proteins|Sequence Alignment|Sequence Analysis, Protein|Sequence Homology, Amino Acid|Software', 'Journal Article', '10.1371/journal.pcbi.1004343', '26496371', 'Homology modeling predicts the 3D structure of a query protein based on the sequence alignment with one or more template proteins of known structure. Its great importance for biological research is owed to its speed, simplicity, reliability and wide applicability, covering more than half of the residues in protein sequence space. Although multiple templates have been shown to generally increase model quality over single templates, the information from multiple templates has so far been combined using empirically motivated, heuristic approaches. We present here a rigorous statistical framework for multi-template homology modeling. First, we find that the query proteins atomic distance restraints can be accurately described by two-component Gaussian mixtures. This insight allowed us to apply the standard laws of probability theory to combine restraints from multiple templates. Second, we derive theoretically optimal weights to correct for the redundancy among related templates. Third, a heuristic template selection strategy is proposed. We improve the average GDT-ha model quality score by 11% over single template modeling and by 6.5% over a conventional multi-template approach on a set of 1000 query proteins. Robustness with respect to wrong constraints is likewise improved. We have integrated our multi-template modeling approach with the popular MODELLER homology modeling software in our free HHpred server http://toolkit.tuebingen.mpg.de/hhpred and also offer open source software for running MODELLER with the new restraints at https://bitbucket.org/soedinglab/hh-suite. '),
(87429, 2015, 'plos', 'The Invariance Hypothesis Implies Domain-Specific Regions in Visual Cortex', 'Leibo, Joel Z|Liao, Qianli|Anselmi, Fabio|Poggio, Tomaso', 'Center for Brains, Minds, and Machines, MIT, Cambridge, Massachusetts, United States of America, McGovern Institute for Brain Research, MIT, Cambridge, Massachusetts, United States of America.|Center for Brains, Minds, and Machines, MIT, Cambridge, Massachusetts, United States of America, McGovern Institute for Brain Research, MIT, Cambridge, Massachusetts, United States of America.|Center for Brains, Minds, and Machines, MIT, Cambridge, Massachusetts, United States of America, McGovern Institute for Brain Research, MIT, Cambridge, Massachusetts, United States of America, Istituto Italiano di Tecnologia, Genova, Italy.|Center for Brains, Minds, and Machines, MIT, Cambridge, Massachusetts, United States of America, McGovern Institute for Brain Research, MIT, Cambridge, Massachusetts, United States of America, Istituto Italiano di Tecnologia, Genova, Italy.', 'United States|United States|Italy|Italy', 0, 'Animals|Computer Simulation|Humans|Models, Neurological|Nerve Net|Pattern Recognition, Visual|Recognition (Psychology)|Visual Cortex|Visual Pathways', 'Journal Article', '10.1371/journal.pcbi.1004390', '26496457', 'Is visual cortex made up of general-purpose information processing machinery, or does it consist of a collection of specialized modules? If prior knowledge, acquired from learning a set of objects is only transferable to new objects that share properties with the old, then the recognition systems optimal organization must be one containing specialized modules for different object classes. Our analysis starts from a premise we call the invariance hypothesis: that the computational goal of the ventral stream is to compute an invariant-to-transformations and discriminative signature for recognition. The key condition enabling approximate transfer of invariance without sacrificing discriminability turns out to be that the learned and novel objects transform similarly. This implies that the optimal recognition system must contain subsystems trained only with data from similarly-transforming objects and suggests a novel interpretation of domain-specific regions like the fusiform face area (FFA). Furthermore, we can define an index of transformation-compatibility, computable from videos, that can be combined with information about the statistics of natural vision to yield predictions for which object categories ought to have domain-specific regions in agreement with the available data. The result is a unifying account linking the large literature on view-based recognition with the wealth of experimental evidence concerning domain-specific regions. ');
INSERT INTO `papers` (`id`, `ano`, `journal`, `titulo`, `autores`, `afiliacao`, `pais`, `citacoes`, `palavra_chave`, `categorias`, `doi`, `pubmed`, `abstract`) VALUES
(87430, 2015, 'plos', 'Reinforcement Learning of Linking and Tracing Contours in Recurrent Neural Networks', 'Brosch, Tobias|Neumann, Heiko|Roelfsema, Pieter R', 'University of Ulm, Institute of Neural Information Processing, Ulm, Germany.|University of Ulm, Institute of Neural Information Processing, Ulm, Germany.|Department of Vision & Cognition, Netherlands Institute for Neuroscience (KNAW), Amsterdam, The Netherlands, Department of Integrative Neurophysiology, Center for Neurogenomics and Cognitive Research, VU University, Amsterdam, The Netherlands, Psychiatry Department, Academic Medical Center, Amsterdam, The Netherlands.', 'Germany|Germany|Netherlands', 15, 'Animals|Computer Simulation|Feedback, Physiological|Macaca|Memory|Models, Neurological|Nerve Net|Reinforcement (Psychology)|Visual Cortex|Visual Perception', 'Journal Article', '10.1371/journal.pcbi.1004489', '26496502', 'The processing of a visual stimulus can be subdivided into a number of stages. Upon stimulus presentation there is an early phase of feedforward processing where the visual information is propagated from lower to higher visual areas for the extraction of basic and complex stimulus features. This is followed by a later phase where horizontal connections within areas and feedback connections from higher areas back to lower areas come into play. In this later phase, image elements that are behaviorally relevant are grouped by Gestalt grouping rules and are labeled in the cortex with enhanced neuronal activity (object-based attention in psychology). Recent neurophysiological studies revealed that reward-based learning influences these recurrent grouping processes, but it is not well understood how rewards train recurrent circuits for perceptual organization. This paper examines the mechanisms for reward-based learning of new grouping rules. We derive a learning rule that can explain how rewards influence the information flow through feedforward, horizontal and feedback connections. We illustrate the efficiency with two tasks that have been used to study the neuronal correlates of perceptual organization in early visual cortex. The first task is called contour-integration and demands the integration of collinear contour elements into an elongated curve. We show how reward-based learning causes an enhancement of the representation of the to-be-grouped elements at early levels of a recurrent neural network, just as is observed in the visual cortex of monkeys. The second task is curve-tracing where the aim is to determine the endpoint of an elongated curve composed of connected image elements. If trained with the new learning rule, neural networks learn to propagate enhanced activity over the curve, in accordance with neurophysiological data. We close the paper with a number of model predictions that can be tested in future neurophysiological and computational studies. '),
(87431, 2015, 'plos', 'Critical Roles of the Direct GABAergic Pallido-cortical Pathway in Controlling Absence Seizures', 'Chen, Mingming|Guo, Daqing|Li, Min|Ma, Tao|Wu, Shengdun|Ma, Jingling|Cui, Yan|Xia, Yang|Xu, Peng|Yao, Dezhong', 'Key Laboratory for NeuroInformation of Ministry of Education, School of Life Science and Technology, University of Electronic Science and Technology of China, Chengdu 610054, Peoples Republic of China.|Key Laboratory for NeuroInformation of Ministry of Education, School of Life Science and Technology, University of Electronic Science and Technology of China, Chengdu 610054, Peoples Republic of China, Center for Information in Medicine, University of Electronic Science and Technology of China, Chengdu 610054, Peoples Republic of China.|Key Laboratory for NeuroInformation of Ministry of Education, School of Life Science and Technology, University of Electronic Science and Technology of China, Chengdu 610054, Peoples Republic of China.|Key Laboratory for NeuroInformation of Ministry of Education, School of Life Science and Technology, University of Electronic Science and Technology of China, Chengdu 610054, Peoples Republic of China.|Key Laboratory for NeuroInformation of Ministry of Education, School of Life Science and Technology, University of Electronic Science and Technology of China, Chengdu 610054, Peoples Republic of China.|Key Laboratory for NeuroInformation of Ministry of Education, School of Life Science and Technology, University of Electronic Science and Technology of China, Chengdu 610054, Peoples Republic of China.|Key Laboratory for NeuroInformation of Ministry of Education, School of Life Science and Technology, University of Electronic Science and Technology of China, Chengdu 610054, Peoples Republic of China.|Key Laboratory for NeuroInformation of Ministry of Education, School of Life Science and Technology, University of Electronic Science and Technology of China, Chengdu 610054, Peoples Republic of China, Center for Information in Medicine, University of Electronic Science and Technology of China, Chengdu 610054, Peoples Republic of China.|Key Laboratory for NeuroInformation of Ministry of Education, School of Life Science and Technology, University of Electronic Science and Technology of China, Chengdu 610054, Peoples Republic of China, Center for Information in Medicine, University of Electronic Science and Technology of China, Chengdu 610054, Peoples Republic of China.|Key Laboratory for NeuroInformation of Ministry of Education, School of Life Science and Technology, University of Electronic Science and Technology of China, Chengdu 610054, Peoples Republic of China, Center for Information in Medicine, University of Electronic Science and Technology of China, Chengdu 610054, Peoples Republic of China.', 'China|China|China|China|China|China|China|China|China|China', 0, 'Biological Clocks|Cerebral Cortex|Computer Simulation|Epilepsy, Absence|Feedback, Physiological|GABAergic Neurons|Globus Pallidus|Humans|Models, Neurological|Nerve Net|Neural Pathways|gamma-Aminobutyric Acid', 'Journal Article', '10.1371/journal.pcbi.1004539', '26496656', 'The basal ganglia (BG), serving as an intermediate bridge between the cerebral cortex and thalamus, are believed to play crucial roles in controlling absence seizure activities generated by the pathological corticothalamic system. Inspired by recent experiments, here we systematically investigate the contribution of a novel identified GABAergic pallido-cortical pathway, projecting from the globus pallidus externa (GPe) in the BG to the cerebral cortex, to the control of absence seizures. By computational modelling, we find that both increasing the activation of GPe neurons and enhancing the coupling strength of the inhibitory pallido-cortical pathway can suppress the bilaterally synchronous 2-4 Hz spike and wave discharges (SWDs) during absence seizures. Appropriate tuning of several GPe-related pathways may also trigger the SWD suppression, through modulating the activation level of GPe neurons. Furthermore, we show that the previously discovered bidirectional control of absence seizures due to the competition between other two BG output pathways also exists in our established model. Importantly, such bidirectional control is shaped by the coupling strength of this direct GABAergic pallido-cortical pathway. Our work suggests that the novel identified pallido-cortical pathway has a functional role in controlling absence seizures and the presented results might provide testable hypotheses for future experimental studies. '),
(87432, 2015, 'plos', 'Sensorimotor Model of Obstacle Avoidance in Echolocating Bats', 'Vanderelst, Dieter|Holderied, Marc W|Peremans, Herbert', 'Active Perception Lab, University of Antwerp, Antwerp, Belgium, School of Biological Sciences, University of Bristol, Bristol, United Kingdom.|School of Biological Sciences, University of Bristol, Bristol, United Kingdom.|Active Perception Lab, University of Antwerp, Antwerp, Belgium.', 'Belgium|United Kingdom|Belgium', 0, 'Animals|Chiroptera|Computer Simulation|Cues|Echolocation|Feedback, Sensory|Models, Neurological|Space Perception|Spatial Navigation', 'Journal Article', '10.1371/journal.pcbi.1004484', '26502063', 'Bat echolocation is an ability consisting of many subtasks such as navigation, prey detection and object recognition. Understanding the echolocation capabilities of bats comes down to isolating the minimal set of acoustic cues needed to complete each task. For some tasks, the minimal cues have already been identified. However, while a number of possible cues have been suggested, little is known about the minimal cues supporting obstacle avoidance in echolocating bats. In this paper, we propose that the Interaural Intensity Difference (IID) and travel time of the first millisecond of the echo train are sufficient cues for obstacle avoidance. We describe a simple control algorithm based on the use of these cues in combination with alternating ear positions modeled after the constant frequency bat Rhinolophus rouxii. Using spatial simulations (2D and 3D), we show that simple phonotaxis can steer a bat clear from obstacles without performing a reconstruction of the 3D layout of the scene. As such, this paper presents the first computationally explicit explanation for obstacle avoidance validated in complex simulated environments. Based on additional simulations modelling the FM bat Phyllostomus discolor, we conjecture that the proposed cues can be exploited by constant frequency (CF) bats and frequency modulated (FM) bats alike. We hypothesize that using a low level yet robust cue for obstacle avoidance allows bats to comply with the hard real-time constraints of this basic behaviour. '),
(87433, 2015, 'plos', 'Structural Refinement of Proteins by Restrained Molecular Dynamics Simulations with Non-interacting Molecular Fragments', 'Shen, Rong|Han, Wei|Fiorin, Giacomo|Islam, Shahidul M|Schulten, Klaus|Roux, Benoît', 'Department of Biochemistry and Molecular Biology, Gordon Center for Integrative Science, University of Chicago, Chicago, Illinois, United States of America.|Beckman Institute, University of Illinois at Urbana-Champaign, Urbana, Illinois, United States of America.|Institute for Computational Molecular Science, Temple University, Philadelphia, Pennsylvania, United States of America.|Department of Biochemistry and Molecular Biology, Gordon Center for Integrative Science, University of Chicago, Chicago, Illinois, United States of America.|Beckman Institute, University of Illinois at Urbana-Champaign, Urbana, Illinois, United States of America.|Department of Biochemistry and Molecular Biology, Gordon Center for Integrative Science, University of Chicago, Chicago, Illinois, United States of America.', 'United States|United States|United States|United States|United States|United States', 14, 'Algorithms|Membrane Transport Proteins|Models, Chemical|Molecular Dynamics Simulation|Protein Binding|Protein Conformation|Protein Structure, Tertiary', 'Journal Article', '10.1371/journal.pcbi.1004368', '26505197', 'The knowledge of multiple conformational states is a prerequisite to understand the function of membrane transport proteins. Unfortunately, the determination of detailed atomic structures for all these functionally important conformational states with conventional high-resolution approaches is often difficult and unsuccessful. In some cases, biophysical and biochemical approaches can provide important complementary structural information that can be exploited with the help of advanced computational methods to derive structural models of specific conformational states. In particular, functional and spectroscopic measurements in combination with site-directed mutations constitute one important source of information to obtain these mixed-resolution structural models. A very common problem with this strategy, however, is the difficulty to simultaneously integrate all the information from multiple independent experiments involving different mutations or chemical labels to derive a unique structural model consistent with the data. To resolve this issue, a novel restrained molecular dynamics structural refinement method is developed to simultaneously incorporate multiple experimentally determined constraints (e.g., engineered metal bridges or spin-labels), each treated as an individual molecular fragment with all atomic details. The internal structure of each of the molecular fragments is treated realistically, while there is no interaction between different molecular fragments to avoid unphysical steric clashes. The information from all the molecular fragments is exploited simultaneously to constrain the backbone to refine a three-dimensional model of the conformational state of the protein. The method is illustrated by refining the structure of the voltage-sensing domain (VSD) of the Kv1.2 potassium channel in the resting state and by exploring the distance histograms between spin-labels attached to T4 lysozyme. The resulting VSD structures are in good agreement with the consensus model of the resting state VSD and the spin-spin distance histograms from ESR/DEER experiments on T4 lysozyme are accurately reproduced. '),
(87434, 2015, 'plos', 'Multi-scale Visualization of Molecular Architecture Using Real-Time Ambient Occlusion in Sculptor', 'Wahle, Manuel|Wriggers, Willy', 'School of Biomedical Informatics, University of Texas Health Science Center at Houston, Houston, Texas, United States of America.|Department of Mechanical and Aerospace Engineering, Old Dominion University, Norfolk, Virginia, United States of America.', 'United States|United States', 0, 'Algorithms|Computer Graphics|Computer Systems|Imaging, Three-Dimensional|Models, Chemical|Molecular Dynamics Simulation|Protein Conformation|Proteins|Software|User-Computer Interface', 'Journal Article', '10.1371/journal.pcbi.1004516', '26505203', 'The modeling of large biomolecular assemblies relies on an efficient rendering of their hierarchical architecture across a wide range of spatial level of detail. We describe a paradigm shift currently under way in computer graphics towards the use of more realistic global illumination models, and we apply the so-called ambient occlusion approach to our open-source multi-scale modeling program, Sculptor. While there are many other higher quality global illumination approaches going all the way up to full GPU-accelerated ray tracing, they do not provide size-specificity of the features they shade. Ambient occlusion is an aspect of global lighting that offers great visual benefits and powerful user customization. By estimating how other molecular shape features affect the reception of light at some surface point, it effectively simulates indirect shadowing. This effect occurs between molecular surfaces that are close to each other, or in pockets such as protein or ligand binding sites. By adding ambient occlusion, large macromolecular systems look much more natural, and the perception of characteristic surface features is strongly enhanced. In this work, we present a real-time implementation of screen space ambient occlusion that delivers realistic cues about tunable spatial scale characteristics of macromolecular architecture. Heretofore, the visualization of large biomolecular systems, comprising e.g. hundreds of thousands of atoms or Mega-Dalton size electron microscopy maps, did not take into account the length scales of interest or the spatial resolution of the data. Our approach has been uniquely customized with shading that is tuned for pockets and cavities of a user-defined size, making it useful for visualizing molecular features at multiple scales of interest. This is a feature that none of the conventional ambient occlusion approaches provide. Actual Sculptor screen shots illustrate how our implementation supports the size-dependent rendering of molecular surface features. '),
(87435, 2015, 'plos', 'Computational Methods for Exploration and Analysis of Macromolecular Structure and Dynamics', 'Shehu, Amarda|Nussinov, Ruth', 'Department of Computer Science, George Mason University, Fairfax, Virginia, United States of America, Department of Bioengineering, George Mason University, Fairfax, Virginia, United States of America, School of Systems Biology, George Mason University, Fairfax, Virginia, United States of America.|Cancer and Inflammation Program, Leidos Biomedical Research, Inc., Frederick National Laboratory for Cancer Research National Cancer Institute, Frederick, Maryland, United States of America, Sackler Institute of Molecular Medicine, Department of Human Genetics and Molecular Medicine, Sackler School of Medicine, Tel Aviv University, Tel Aviv, Israel.', 'United States|Israel', 9, 'Computer Simulation|Kinetics|Macromolecular Substances|Models, Chemical|Models, Molecular|Molecular Conformation', 'Editorial', '10.1371/journal.pcbi.1004585', '26505479', '-'),
(87436, 2015, 'plos', 'Multiscale Estimation of Binding Kinetics Using Brownian Dynamics, Molecular Dynamics and Milestoning', 'Votapka, Lane W|Amaro, Rommie E', 'Department of Chemistry and Biochemistry and National Biomedical Computation Resource, University of California, San Diego, San Diego, California, United States of America.|Department of Chemistry and Biochemistry and National Biomedical Computation Resource, University of California, San Diego, San Diego, California, United States of America.', 'United States|United States', 33, 'Algorithms|Binding Sites|Diffusion|Kinetics|Models, Chemical|Models, Statistical|Molecular Dynamics Simulation|Protein Binding|Protein Conformation|Proteins', 'Journal Article', '10.1371/journal.pcbi.1004381', '26505480', 'The kinetic rate constants of binding were estimated for four biochemically relevant molecular systems by a method that uses milestoning theory to combine Brownian dynamics simulations with more detailed molecular dynamics simulations. The rate constants found using this method agreed well with experimentally and theoretically obtained values. We predicted the association rate of a small charged molecule toward both a charged and an uncharged spherical receptor and verified the estimated value with Smoluchowski theory. We also calculated the kon rate constant for superoxide dismutase with its natural substrate, O2-, in a validation of a previous experiment using similar methods but with a number of important improvements. We also calculated the kon for a new system: the N-terminal domain of Troponin C with its natural substrate Ca2+. The kon calculated for the latter two systems closely resemble experimentally obtained values. This novel multiscale approach is computationally cheaper and more parallelizable when compared to other methods of similar accuracy. We anticipate that this methodology will be useful for predicting kinetic rate constants and for understanding the process of binding between a small molecule and a protein receptor. '),
(87437, 2015, 'plos', 'ENCORE: Software for Quantitative Ensemble Comparison', 'Tiberti, Matteo|Papaleo, Elena|Bengtsen, Tone|Boomsma, Wouter|Lindorff-Larsen, Kresten', 'Department of Biotechnology and Biosciences, University of Milano-Bicocca, Milan, Italy, Structural Biology and NMR Laboratory, Department of Biology, University of Copenhagen, Copenhagen, Denmark.|Structural Biology and NMR Laboratory, Department of Biology, University of Copenhagen, Copenhagen, Denmark.|Structural Biology and NMR Laboratory, Department of Biology, University of Copenhagen, Copenhagen, Denmark.|Structural Biology and NMR Laboratory, Department of Biology, University of Copenhagen, Copenhagen, Denmark.|Structural Biology and NMR Laboratory, Department of Biology, University of Copenhagen, Copenhagen, Denmark.', 'Denmark|Denmark|Denmark|Denmark|Denmark', 27, 'Algorithms|Molecular Dynamics Simulation|Pattern Recognition, Automated|Programming Languages|Protein Conformation|Proteins|Software|Software Validation', 'Comparative Study', '10.1371/journal.pcbi.1004415', '26505632', 'There is increasing evidence that protein dynamics and conformational changes can play an important role in modulating biological function. As a result, experimental and computational methods are being developed, often synergistically, to study the dynamical heterogeneity of a protein or other macromolecules in solution. Thus, methods such as molecular dynamics simulations or ensemble refinement approaches have provided conformational ensembles that can be used to understand protein function and biophysics. These developments have in turn created a need for algorithms and software that can be used to compare structural ensembles in the same way as the root-mean-square-deviation is often used to compare static structures. Although a few such approaches have been proposed, these can be difficult to implement efficiently, hindering a broader applications and further developments. Here, we present an easily accessible software toolkit, called ENCORE, which can be used to compare conformational ensembles generated either from simulations alone or synergistically with experiments. ENCORE implements three previously described methods for ensemble comparison, that each can be used to quantify the similarity between conformational ensembles by estimating the overlap between the probability distributions that underlie them. We demonstrate the kinds of insights that can be obtained by providing examples of three typical use-cases: comparing ensembles generated with different molecular force fields, assessing convergence in molecular simulations, and calculating differences and similarities in structural ensembles refined with various sources of experimental data. We also demonstrate efficient computational scaling for typical analyses, and robustness against both the size and sampling of the ensembles. ENCORE is freely available and extendable, integrates with the established MDAnalysis software package, reads ensemble data in many common formats, and can work with large trajectory files. '),
(87438, 2015, 'plos', 'Mapping the Protein Fold Universe Using the CamTube Force Field in Molecular Dynamics Simulations', 'Kukic, Predrag|Kannan, Arvind|Dijkstra, Maurits J J|Abeln, Sanne|Camilloni, Carlo|Vendruscolo, Michele', 'Department of Chemistry, University of Cambridge, Cambridge, United Kingdom.|Department of Chemistry, University of Cambridge, Cambridge, United Kingdom, Departments of Bioengineering, Stanford University, Stanford, California, United States of America.|Department of Chemistry, University of Cambridge, Cambridge, United Kingdom, Department of Computer Science, Vrije Universiteit, Amsterdam, The Netherlands.|Department of Computer Science, Vrije Universiteit, Amsterdam, The Netherlands.|Department of Chemistry, University of Cambridge, Cambridge, United Kingdom.|Department of Chemistry, University of Cambridge, Cambridge, United Kingdom.', 'United Kingdom|United Kingdom|United Kingdom|Netherlands|United Kingdom|United Kingdom', 0, 'Algorithms|Models, Chemical|Molecular Dynamics Simulation|Programming Languages|Protein Conformation|Protein Folding|Proteins|Software|Stress, Mechanical', 'Journal Article', '10.1371/journal.pcbi.1004435', '26505754', 'It has been recently shown that the coarse-graining of the structures of polypeptide chains as self-avoiding tubes can provide an effective representation of the conformational space of proteins. In order to fully exploit the opportunities offered by such a tube model approach, we present here a strategy to combine it with molecular dynamics simulations. This strategy is based on the incorporation of the CamTube force field into the Gromacs molecular dynamics package. By considering the case of a 60-residue polyvaline chain, we show that CamTube molecular dynamics simulations can comprehensively explore the conformational space of proteins. We obtain this result by a 20 xcexbcs metadynamics simulation of the polyvaline chain that recapitulates the currently known protein fold universe. We further show that, if residue-specific interaction potentials are added to the CamTube force field, it is possible to fold a protein into a topology close to that of its native state. These results illustrate how the CamTube force field can be used to explore efficiently the universe of protein folds with good accuracy and very limited computational cost.'),
(87439, 2015, 'plos', 'Parsimonious Model of Vascular Patterning Links Transverse Hormone Fluxes to Lateral Root Initiation: Auxin Leads the Way, while Cytokinin Levels Out', 'el-Showk, Sedeer|Help-Rinta-Rahko, Hanna|Blomster, Tiina|Siligato, Riccardo|Marée, Athanasius F M|Mähönen, Ari Pekka|Grieneisen, Verônica A', 'Institute of Biotechnology, University of Helsinki, Helsinki, Finland, Computational and Systems Biology, John Innes Centre, Norwich United Kingdom, Department of Biosciences, Viikki Plant Science Centre, University of Helsinki, Helsinki, Finland.|Institute of Biotechnology, University of Helsinki, Helsinki, Finland, Department of Biosciences, Viikki Plant Science Centre, University of Helsinki, Helsinki, Finland.|Institute of Biotechnology, University of Helsinki, Helsinki, Finland, Department of Biosciences, Viikki Plant Science Centre, University of Helsinki, Helsinki, Finland.|Institute of Biotechnology, University of Helsinki, Helsinki, Finland, Department of Biosciences, Viikki Plant Science Centre, University of Helsinki, Helsinki, Finland.|Computational and Systems Biology, John Innes Centre, Norwich United Kingdom.|Institute of Biotechnology, University of Helsinki, Helsinki, Finland, Department of Biosciences, Viikki Plant Science Centre, University of Helsinki, Helsinki, Finland.|Computational and Systems Biology, John Innes Centre, Norwich United Kingdom.', 'Finland|Finland|Finland|Finland|United Kingdom|Finland|United Kingdom', 0, 'Arabidopsis|Arabidopsis Proteins|Computer Simulation|Cytokinins|Indoleacetic Acids|Membrane Transport Proteins|Models, Biological|Plant Growth Regulators|Plant Roots|Plant Vascular Bundle', 'Journal Article', '10.1371/journal.pcbi.1004450', '26505899', 'An auxin maximum is positioned along the xylem axis of the Arabidopsis root tip. The pattern depends on mutual feedback between auxin and cytokinins mediated by the PIN class of auxin efflux transporters and AHP6, an inhibitor of cytokinin signalling. This interaction has been proposed to regulate the size and the position of the hormones respective signalling domains and specify distinct boundaries between them. To understand the dynamics of this regulatory network, we implemented a parsimonious computational model of auxin transport that considers hormonal regulation of the auxin transporters within a spatial context, explicitly taking into account cell shape and polarity and the presence of cell walls. Our analysis reveals that an informative spatial pattern in cytokinin levels generated by diffusion is a theoretically unlikely scenario. Furthermore, our model shows that such a pattern is not required for correct and robust auxin patterning. Instead, auxin-dependent modifications of cytokinin response, rather than variations in cytokinin levels, allow for the necessary feedbacks, which can amplify and stabilise the auxin maximum. Our simulations demonstrate the importance of hormonal regulation of auxin efflux for pattern robustness. While involvement of the PIN proteins in vascular patterning is well established, we predict and experimentally verify a role of AUX1 and LAX1/2 auxin influx transporters in this process. Furthermore, we show that polar localisation of PIN1 generates an auxin flux circuit that not only stabilises the accumulation of auxin within the xylem axis, but also provides a mechanism for auxin to accumulate specifically in the xylem-pole pericycle cells, an important early step in lateral root initiation. The model also revealed that pericycle cells on opposite xylem poles compete for auxin accumulation, consistent with the observation that lateral roots are not initiated opposite to each other. '),
(87440, 2015, 'plos', 'DynaFace: Discrimination between Obligatory and Non-obligatory Protein-Protein Interactions Based on the Complexs Dynamics', 'Soner, Seren|Ozbek, Pemra|Garzon, Jose Ignacio|Ben-Tal, Nir|Haliloglu, Turkan', 'Department of Computer Engineering and Polymer Research Center, Bogazici University, Istanbul, Turkey.|Department of Bioengineering, Marmara University, Istanbul, Turkey.|Departments of Biochemistry and Molecular Biophysics and Systems Biology and Howard Hughes Medical Institute, Columbia University, New York, New York, United States of America.|Department of Biochemistry and Molecular Biology, George S. Wise Faculty of Life Sciences, Tel Aviv University, Tel Aviv, Israel.|Department of Chemical Engineering and Polymer Research Center, Bogazici University, Istanbul, Turkey.', 'Turkey|Turkey|United States|Israel|Turkey', 5, 'Algorithms|Binding Sites|Kinetics|Models, Chemical|Molecular Dynamics Simulation|Multiprotein Complexes|Protein Binding|Protein Conformation|Protein Interaction Mapping|Proteins|Software', 'Journal Article', '10.1371/journal.pcbi.1004461', '26506003', 'Protein-protein interfaces have been evolutionarily-designed to enable transduction between the interacting proteins. Thus, we hypothesize that analysis of the dynamics of the complex can reveal details about the nature of the interaction, and in particular whether it is obligatory, i.e., persists throughout the entire lifetime of the proteins, or not. Indeed, normal mode analysis, using the Gaussian network model, shows that for the most part obligatory and non-obligatory complexes differ in their decomposition into dynamic domains, i.e., the mobile elements of the protein complex. The dynamic domains of obligatory complexes often mix segments from the interacting chains, and the hinges between them do not overlap with the interface between the chains. In contrast, in non-obligatory complexes the interface often hinges between dynamic domains, held together through few anchor residues on one side of the interface that interact with their counterpart grooves in the other end. In automatic analysis, 117 of 139 obligatory (84.2%) and 203 of 246 non-obligatory (82.5%) complexes are correctly classified by our method: DynaFace. We further use DynaFace to predict obligatory and non-obligatory interactions among a set of 300 putative protein complexes. DynaFace is available at: http://safir.prc.boun.edu.tr/dynaface. '),
(87441, 2015, 'plos', 'pMD-Membrane: A Method for Ligand Binding Site Identification in Membrane-Bound Proteins', 'Prakash, Priyanka|Sayyed-Ahmad, Abdallah|Gorfe, Alemayehu A', 'University of Texas Health Science Center at Houston, Department of Integrative Biology and Pharmacology, Houston, Texas, United States of America.|University of Texas Health Science Center at Houston, Department of Integrative Biology and Pharmacology, Houston, Texas, United States of America.|University of Texas Health Science Center at Houston, Department of Integrative Biology and Pharmacology, Houston, Texas, United States of America.', 'United States|United States|United States', 0, 'Algorithms|Binding Sites|Cell Membrane|Lipid Bilayers|Models, Chemical|Molecular Dynamics Simulation|Protein Binding|Protein Conformation|Protein Interaction Mapping|Software|ras Proteins', 'Journal Article', '10.1371/journal.pcbi.1004469', '26506102', 'Probe-based or mixed solvent molecular dynamics simulation is a useful approach for the identification and characterization of druggable sites in drug targets. However, thus far the method has been applied only to soluble proteins. A major reason for this is the potential effect of the probe molecules on membrane structure. We have developed a technique to overcome this limitation that entails modification of force field parameters to reduce a few pairwise non-bonded interactions between selected atoms of the probe molecules and bilayer lipids. We used the resulting technique, termed pMD-membrane, to identify allosteric ligand binding sites on the G12D and G13D oncogenic mutants of the K-Ras protein bound to a negatively charged lipid bilayer. In addition, we show that differences in probe occupancy can be used to quantify changes in the accessibility of druggable sites due to conformational changes induced by membrane binding or mutation. '),
(87442, 2015, 'plos', 'A Virtual Mixture Approach to the Study of Multistate Equilibrium: Application to Constant pH Simulation in Explicit Water', 'Wu, Xiongwu|Brooks, Bernard R', 'Laboratory of Computational Biology, National Heart, Lung, and Blood Institute (NHLBI), National Institutes of Health (NIH), Bethesda, Maryland, United States of America.|Laboratory of Computational Biology, National Heart, Lung, and Blood Institute (NHLBI), National Institutes of Health (NIH), Bethesda, Maryland, United States of America.', 'United States|United States', 12, 'Algorithms|Complex Mixtures|Computer Simulation|Energy Transfer|Hydrogen-Ion Concentration|Models, Chemical|Peptides|Solvents|Thermodynamics|Water', 'Journal Article', '10.1371/journal.pcbi.1004480', '26506245', 'Chemical and thermodynamic equilibrium of multiple states is a fundamental phenomenon in biology systems and has been the focus of many experimental and computational studies. This work presents a simulation method to directly study the equilibrium of multiple states. This method constructs a virtual mixture of multiple states (VMMS) to sample the conformational space of all chemical states simultaneously. The VMMS system consists of multiple subsystems, one for each state. The subsystem contains a solute and a solvent environment. The solute molecules in all subsystems share the same conformation but have their own solvent environments. Transition between states is implicated by the change of their molar fractions. Simulation of a VMMS system allows efficient calculation of relative free energies of all states, which in turn determine their equilibrium molar fractions. For systems with a large number of state transition sites, an implicit site approximation is introduced to minimize the cost of simulation. A direct application of the VMMS method is for constant pH simulation to study protonation equilibrium. Applying the VMMS method to a heptapeptide of 3 ionizable residues, we calculated the pKas of those residues both with all explicit states and with implicit sites and obtained consistent results. For mouse epidermal growth factor of 9 ionizable groups, our VMMS simulations with implicit sites produced pKas of all 9 ionizable groups and the results agree qualitatively with NMR measurement. This example demonstrates the VMMS method can be applied to systems of a large number of ionizable groups and the computational cost scales linearly with the number of ionizable groups. For one of the most challenging systems in constant pH calculation, SNase xcex94+PHS/V66K, our VMMS simulation shows that it is the state-dependent water penetration that causes the large deviation in lysine66s pKa. '),
(87443, 2015, 'plos', 'Broad CTL Response in Early HIV Infection Drives Multiple Concurrent CTL Escapes', 'Leviyang, Sivan|Ganusov, Vitaly V', 'Department of Mathematics and Statistics, Georgetown University, Washington, DC, United States of America.|Department of Microbiology, University of Tennessee, Knoxville, Tennessee, United States of America.', 'United States|United States', 0, 'HIV|HIV Infections|Humans|Immune Evasion|Models, Genetic|Models, Immunological|Mutation|T-Lymphocytes, Cytotoxic|Virus Replication', 'Journal Article', '10.1371/journal.pcbi.1004492', '26506433', 'Recent studies have highlighted the ability of HIV to escape from cytotoxic T lymphocyte (CTL) responses that concurrently target multiple viral epitopes. Yet, the viral dynamics involved in such escape are incompletely understood. Previous analyses have made several strong assumptions regarding HIV escape from CTL responses such as independent or non-concurrent escape from individual CTL responses. Using experimental data from evolution of HIV half genomes in four patients we observe concurrent viral escape from multiple CTL responses during early infection (first 100 days of infection), providing confirmation of a recent result found in a study of one HIV-infected patient. We show that current methods of estimating CTL escape rates, based on the assumption of independent escapes, are biased and perform poorly when CTL escape proceeds concurrently at multiple epitopes. We propose a new method for analyzing longitudinal sequence data to estimate the rate of CTL escape across multiple epitopes, this method involves few parameters and performs well in simulation studies. By applying our novel method to experimental data, we find that concurrent multiple escapes occur at rates between 0.03 and 0.4 day(-1), a relatively broad range that reflects uncertainty due to sparse sampling and wide ranges of parameter values. However, we show that concurrent escape at rates 0.1-0.2 day(-1) across multiple epitopes is consistent with our patient datasets.'),
(87444, 2015, 'plos', 'Conformational Dynamics and Binding Free Energies of Inhibitors of BACE-1: From the Perspective of Protonation Equilibria', 'Kim, M Olivia|Blachly, Patrick G|McCammon, J Andrew', 'Department of Chemistry and Biochemistry, University of California San Diego, La Jolla, California, United States of America.|Department of Chemistry and Biochemistry, University of California San Diego, La Jolla, California, United States of America.|Department of Chemistry and Biochemistry, University of California San Diego, La Jolla, California, United States of America, Department of Pharmacology, University of California San Diego, La Jolla, California, United States of America, Howard Hughes Medical Institute, University of California San Diego, La Jolla, California, United States of America, National Biomedical Computation Resource, University of California San Diego, La Jolla, California, United States of America.', 'United States|United States|United States', 0, 'Amyloid Precursor Protein Secretases|Aspartic Acid Endopeptidases|Binding Sites|Energy Transfer|Enzyme Inhibitors|Models, Chemical|Molecular Dynamics Simulation|Protein Binding|Protein Conformation|Protons|Structure-Activity Relationship|Thermodynamics', 'Journal Article', '10.1371/journal.pcbi.1004341', '26506513', 'BACE-1 is the xcexb2-secretase responsible for the initial amyloidogenesis in Alzheimers disease, catalyzing hydrolytic cleavage of substrate in a pH-sensitive manner. The catalytic mechanism of BACE-1 requires water-mediated proton transfer from aspartyl dyad to the substrate, as well as structural flexibility in the flap region. Thus, the coupling of protonation and conformational equilibria is essential to a full in silico characterization of BACE-1. In this work, we perform constant pH replica exchange molecular dynamics simulations on both apo BACE-1 and five BACE-1-inhibitor complexes to examine the effect of pH on dynamics and inhibitor binding properties of BACE-1. In our simulations, we find that solution pH controls the conformational flexibility of apo BACE-1, whereas bound inhibitors largely limit the motions of the holo enzyme at all levels of pH. The microscopic pKa values of titratable residues in BACE-1 including its aspartyl dyad are computed and compared between apo and inhibitor-bound states. Changes in protonation between the apo and holo forms suggest a thermodynamic linkage between binding of inhibitors and protons localized at the dyad. Utilizing our recently developed computational protocol applying the binding polynomial formalism to the constant pH molecular dynamics (CpHMD) framework, we are able to obtain the pH-dependent binding free energy profiles for various BACE-1-inhibitor complexes. Our results highlight the importance of correctly addressing the binding-induced protonation changes in protein-ligand systems where binding accompanies a net proton transfer. This work comprises the first application of our CpHMD-based free energy computational method to protein-ligand complexes and illustrates the value of CpHMD as an all-purpose tool for obtaining pH-dependent dynamics and binding free energies of biological systems. '),
(87445, 2015, 'plos', 'Predicting the Effect of Mutations on Protein-Protein Binding Interactions through Structure-Based Interface Profiles', 'Brender, Jeffrey R|Zhang, Yang', 'Department of Computational Medicine and Bioinformatics, University of Michigan, Ann Arbor, Michigan, United States of America.|Department of Computational Medicine and Bioinformatics, University of Michigan, Ann Arbor, Michigan, United States of America, Department of Biological Chemistry, University of Michigan, Ann Arbor, Michigan, United States of America.', 'United States|United States', 65, 'Amino Acid Sequence|Binding Sites|Models, Chemical|Models, Genetic|Models, Molecular|Molecular Sequence Data|Mutation|Protein Binding|Protein Conformation|Protein Interaction Mapping|Proteins|Sequence Analysis, Protein|Structure-Activity Relationship', 'Journal Article', '10.1371/journal.pcbi.1004494', '26506533', 'The formation of protein-protein complexes is essential for proteins to perform their physiological functions in the cell. Mutations that prevent the proper formation of the correct complexes can have serious consequences for the associated cellular processes. Since experimental determination of protein-protein binding affinity remains difficult when performed on a large scale, computational methods for predicting the consequences of mutations on binding affinity are highly desirable. We show that a scoring function based on interface structure profiles collected from analogous protein-protein interactions in the PDB is a powerful predictor of protein binding affinity changes upon mutation. As a standalone feature, the differences between the interface profile score of the mutant and wild-type proteins has an accuracy equivalent to the best all-atom potentials, despite being two orders of magnitude faster once the profile has been constructed. Due to its unique sensitivity in collecting the evolutionary profiles of analogous binding interactions and the high speed of calculation, the interface profile score has additional advantages as a complementary feature to combine with physics-based potentials for improving the accuracy of composite scoring approaches. By incorporating the sequence-derived and residue-level coarse-grained potentials with the interface structure profile score, a composite model was constructed through the random forest training, which generates a Pearson correlation coefficient >0.8 between the predicted and observed binding free-energy changes upon mutation. This accuracy is comparable to, or outperforms in most cases, the current best methods, but does not require high-resolution full-atomic models of the mutant structures. The binding interface profiling approach should find useful application in human-disease mutation recognition and protein interface design studies. '),
(87446, 2015, 'plos', 'ApoE4-specific Misfolded Intermediate Identified by Molecular Dynamics Simulations', 'Williams, Benfeard|Convertino, Marino|Das, Jhuma|Dokholyan, Nikolay V', 'Biochemistry and Biophysics Department, University of North Carolina, Chapel Hill, Chapel Hill, North Carolina, United States of America.|Biochemistry and Biophysics Department, University of North Carolina, Chapel Hill, Chapel Hill, North Carolina, United States of America.|Biochemistry and Biophysics Department, University of North Carolina, Chapel Hill, Chapel Hill, North Carolina, United States of America.|Biochemistry and Biophysics Department, University of North Carolina, Chapel Hill, Chapel Hill, North Carolina, United States of America.', 'United States|United States|United States|United States', 0, 'Apolipoprotein E4|Models, Chemical|Molecular Dynamics Simulation|Protein Conformation|Protein Denaturation|Protein Folding|Thermodynamics', 'Journal Article', '10.1371/journal.pcbi.1004359', '26506597', 'The increased risk of developing Alzheimers disease (AD) is associated with the APOE gene, which encodes for three variants of Apolipoprotein E, namely E2, E3, E4, differing only by two amino acids at positions 112 and 158. ApoE4 is known to be the strongest risk factor for AD onset, while ApoE3 and ApoE2 are considered to be the AD-neutral and AD-protective isoforms, respectively. It has been hypothesized that the ApoE isoforms may contribute to the development of AD by modifying the homeostasis of ApoE physiological partners and AD-related proteins in an isoform-specific fashion. Here we find that, despite the high sequence similarity among the three ApoE variants, only ApoE4 exhibits a misfolded intermediate state characterized by isoform-specific domain-domain interactions in molecular dynamics simulations. The existence of an ApoE4-specific intermediate state can contribute to the onset of AD by altering multiple cellular pathways involved in ApoE-dependent lipid transport efficiency or in AD-related protein aggregation and clearance. We present what we believe to be the first structural model of an ApoE4 misfolded intermediate state, which may serve to elucidate the molecular mechanism underlying the role of ApoE4 in AD pathogenesis. The knowledge of the structure for the ApoE4 folding intermediate provides a new platform for the rational design of alternative therapeutic strategies to fight AD. '),
(87447, 2015, 'plos', 'Exposing Hidden Alternative Backbone Conformations in X-ray Crystallography Using qFit', 'Keedy, Daniel A|Fraser, James S|van den Bedem, Henry', 'Department of Bioengineering and Therapeutic Sciences, University of California, San Francisco, San Francisco, California, United States of America.|Department of Bioengineering and Therapeutic Sciences, University of California, San Francisco, San Francisco, California, United States of America.|Division of Biosciences, SLAC National Accelerator Laboratory, Stanford University, California, United States of America.', 'United States|United States|United States', 0, 'Algorithms|Computer Simulation|Crystallography, X-Ray|Models, Chemical|Models, Molecular|Protein Conformation|Proteins|Software', 'Journal Article', '10.1371/journal.pcbi.1004507', '26506617', 'Proteins must move between different conformations of their native ensemble to perform their functions. Crystal structures obtained from high-resolution X-ray diffraction data reflect this heterogeneity as a spatial and temporal conformational average. Although movement between natively populated alternative conformations can be critical for characterizing molecular mechanisms, it is challenging to identify these conformations within electron density maps. Alternative side chain conformations are generally well separated into distinct rotameric conformations, but alternative backbone conformations can overlap at several atomic positions. Our model building program qFit uses mixed integer quadratic programming (MIQP) to evaluate an extremely large number of combinations of sidechain conformers and backbone fragments to locally explain the electron density. Here, we describe two major modeling enhancements to qFit: peptide flips and alternative glycine conformations. We find that peptide flips fall into four stereotypical clusters and are enriched in glycine residues at the n+1 position. The potential for insights uncovered by new peptide flips and glycine conformations is exemplified by HIV protease, where different inhibitors are associated with peptide flips in the flap regions adjacent to the inhibitor binding site. Our results paint a picture of peptide flips as conformational switches, often enabled by glycine flexibility, that result in dramatic local rearrangements. Our results furthermore demonstrate the power of large-scale computational analysis to provide new insights into conformational heterogeneity. Overall, improved modeling of backbone heterogeneity with high-resolution X-ray data will connect dynamics to the structure-function relationship and help drive new design strategies for inhibitors of biomedically important systems. ');
INSERT INTO `papers` (`id`, `ano`, `journal`, `titulo`, `autores`, `afiliacao`, `pais`, `citacoes`, `palavra_chave`, `categorias`, `doi`, `pubmed`, `abstract`) VALUES
(87448, 2015, 'plos', 'Extracting Diffusive States of Rho GTPase in Live Cells: Towards In Vivo Biochemistry', 'Koo, Peter K|Weitzman, Matthew|Sabanaygam, Chandran R|van Golen, Kenneth L|Mochrie, Simon G J', 'Department of Physics, Yale University, New Haven, Connecticut, United States of America.|Department of Biological Sciences, University of Delaware, Newark, Delaware, United States of America.|Delaware Biotechnology Institute, Bioimaging Center, Newark, Delaware, United States of America.|Department of Biological Sciences, University of Delaware, Newark, Delaware, United States of America.|Department of Biological Sciences, University of Delaware, Newark, Delaware, United States of America, Department of Applied Physics, Yale University, New Haven, Connecticut, United States of America.', 'United States|United States|United States|United States|United States', 9, 'Computer Simulation|Diffusion|Machine Learning|Models, Biological|Models, Chemical|Models, Statistical|Molecular Imaging|Subcellular Fractions|rho GTP-Binding Proteins', 'Journal Article', '10.1371/journal.pcbi.1004297', '26512894', 'Resolving distinct biochemical interaction states when analyzing the trajectories of diffusing proteins in live cells on an individual basis remains challenging because of the limited statistics provided by the relatively short trajectories available experimentally. Here, we introduce a novel, machine-learning based classification methodology, which we call perturbation expectation-maximization (pEM), that simultaneously analyzes a population of protein trajectories to uncover the system of diffusive behaviors which collectively result from distinct biochemical interactions. We validate the performance of pEM in silico and demonstrate that pEM is capable of uncovering the proper number of underlying diffusive states with an accurate characterization of their diffusion properties. We then apply pEM to experimental protein trajectories of Rho GTPases, an integral regulator of cytoskeletal dynamics and cellular homeostasis, in vivo via single particle tracking photo-activated localization microscopy. Remarkably, pEM uncovers 6 distinct diffusive states conserved across various Rho GTPase family members. The variability across family members in the propensities for each diffusive state reveals non-redundant roles in the activation states of RhoA and RhoC. In a resting cell, our results support a model where RhoA is constantly cycling between activation states, with an imbalance of rates favoring an inactive state. RhoC, on the other hand, remains predominantly inactive.'),
(87449, 2015, 'plos', 'The Trigger Factor Chaperone Encapsulates and Stabilizes Partial Folds of Substrate Proteins', 'Singhal, Kushagra|Vreede, Jocelyne|Mashaghi, Alireza|Tans, Sander J|Bolhuis, Peter G', 'van t Hoff Institute for Molecular Sciences, University of Amsterdam, Amsterdam, The Netherlands.|van t Hoff Institute for Molecular Sciences, University of Amsterdam, Amsterdam, The Netherlands.|Department of Systems Biophysics, FOM Institute AMOLF, Amsterdam, The Netherlands.|Department of Systems Biophysics, FOM Institute AMOLF, Amsterdam, The Netherlands.|van t Hoff Institute for Molecular Sciences, University of Amsterdam, Amsterdam, The Netherlands.', 'Netherlands|Netherlands|Netherlands|Netherlands|Netherlands', 0, 'Binding Sites|Computer Simulation|Enzyme Activation|Escherichia coli Proteins|Models, Chemical|Molecular Chaperones|Molecular Dynamics Simulation|Peptidylprolyl Isomerase|Protein Binding|Protein Conformation|Protein Folding|Substrate Specificity', 'Journal Article', '10.1371/journal.pcbi.1004444', '26512985', 'How chaperones interact with protein chains to assist in their folding is a central open question in biology. Obtaining atomistic insight is challenging in particular, given the transient nature of the chaperone-substrate complexes and the large system sizes. Recent single-molecule experiments have shown that the chaperone Trigger Factor (TF) not only binds unfolded protein chains, but can also guide protein chains to their native state by interacting with partially folded structures. Here, we used all-atom MD simulations to provide atomistic insights into how Trigger Factor achieves this chaperone function. Our results indicate a crucial role for the tips of the finger-like appendages of TF in the early interactions with both unfolded chains and partially folded structures. Unfolded chains are kinetically trapped when bound to TF, which suppresses the formation of transient, non-native end-to-end contacts. Mechanical flexibility allows TF to hold partially folded structures with two tips (in a pinching configuration), and to stabilize them by wrapping around its appendages. This encapsulation mechanism is distinct from that of chaperones such as GroEL, and allows folded structures of diverse size and composition to be protected from aggregation and misfolding interactions. The results suggest that an ATP cycle is not required to enable both encapsulation and liberation. '),
(87450, 2015, 'plos', 'Dendritic Pooling of Noisy Threshold Processes Can Explain Many Properties of a Collision-Sensitive Visual Neuron', 'Keil, Matthias S', 'Basic Psychology Department, University of Barcelona, Barcelona, Spain, Institute of Brain, Bahaviour and Cognition (I3C), University of Barcelona, Barcelona, Spain.', 'Spain', 1, 'Animals|Computer Simulation|Dendrites|Differential Threshold|Grasshoppers|Models, Neurological|Models, Statistical|Motion Perception|Neurons, Afferent|Sensory Thresholds|Signal-To-Noise Ratio|Synapses', 'Journal Article', '10.1371/journal.pcbi.1004479', '26513150', 'Power laws describe brain functions at many levels (from biophysics to psychophysics). It is therefore possible that they are generated by similar underlying mechanisms. Previously, the response properties of a collision-sensitive neuron were reproduced by a model which used a power law for scaling its inhibitory input. A common characteristic of such neurons is that they integrate information across a large part of the visual field. Here we present a biophysically plausible model of collision-sensitive neurons with xcexb7-like response properties, in which we assume that each information channel is noisy and has a response threshold. Then, an approximative power law is obtained as a result of pooling these channels. We show that with this mechanism one can successfully predict many response characteristics of the Lobula Giant Movement Detector Neuron (LGMD). Moreover, the results depend critically on noise in the inhibitory pathway, but they are fairly robust against noise in the excitatory pathway. '),
(87451, 2015, 'plos', 'Combining Search, Social Media, and Traditional Data Sources to Improve Influenza Surveillance', 'Santillana, Mauricio|Nguyen, André T|Dredze, Mark|Paul, Michael J|Nsoesie, Elaine O|Brownstein, John S', 'Harvard School of Engineering and Applied Sciences, Cambridge, Massachusetts, United States of America, Boston Childrens Hospital Informatics Program, Boston, Massachusetts, United States of America, Harvard Medical School, Boston, Massachusetts, United States of America.|Harvard School of Engineering and Applied Sciences, Cambridge, Massachusetts, United States of America.|Department of Computer Science, Johns Hopkins University, Baltimore, Maryland, United States of America.|Department of Information Science, University of Colorado, Boulder, Colorado, United States of America.|Department of Global Health, University of Washington, Seattle, Washington, United States of America, Institute for Health Metrics and Evaluation, Seattle, Washington, United States of America.|Boston Childrens Hospital Informatics Program, Boston, Massachusetts, United States of America, Harvard Medical School, Boston, Massachusetts, United States of America.', 'United States|United States|United States|United States|United States|United States', 162, 'Data Mining|Database Management Systems|Databases, Factual|Humans|Influenza, Human|Machine Learning|Natural Language Processing|Pattern Recognition, Automated|Population Surveillance|Prevalence|Risk Assessment|Search Engine|Seasons|Social Media|United States|Vocabulary, Controlled', 'Journal Article', '10.1371/journal.pcbi.1004513', '26513245', 'We present a machine learning-based methodology capable of providing real-time (nowcast) and forecast estimates of influenza activity in the US by leveraging data from multiple data sources including: Google searches, Twitter microblogs, nearly real-time hospital visit records, and data from a participatory surveillance system. Our main contribution consists of combining multiple influenza-like illnesses (ILI) activity estimates, generated independently with each data source, into a single prediction of ILI utilizing machine learning ensemble approaches. Our methodology exploits the information in each data source and produces accurate weekly ILI predictions for up to four weeks ahead of the release of CDCs ILI reports. We evaluate the predictive ability of our ensemble approach during the 2013-2014 (retrospective) and 2014-2015 (live) flu seasons for each of the four weekly time horizons. Our ensemble approach demonstrates several advantages: (1) our ensemble methods predictions outperform every prediction using each data source independently, (2) our methodology can produce predictions one week ahead of GFTs real-time estimates with comparable accuracy, and (3) our two and three week forecast estimates have comparable accuracy to real-time predictions using an autoregressive model. Moreover, our results show that considerable insight is gained from incorporating disparate data streams, in the form of social media and crowd sourced data, into influenza predictions in all time horizons. '),
(87452, 2015, 'plos', 'Comparisons of Allergenic and Metazoan Parasite Proteins: Allergy the Price of Immunity', 'Tyagi, Nidhi|Farnell, Edward J|Fitzsimmons, Colin M|Ryan, Stephanie|Tukahebwa, Edridah|Maizels, Rick M|Dunne, David W|Thornton, Janet M|Furnham, Nicholas', 'The EMBL-European Bioinformatics Institute, Wellcome Trust Genome Campus, Hinxton, Cambridge, United Kingdom.|Department of Pathology, University of Cambridge, Cambridge, United Kingdom.|Department of Pathology, University of Cambridge, Cambridge, United Kingdom.|Institute of Immunology and Infection Research, University of Edinburgh, Edinburgh, United Kingdom.|Vector Control Division, Ministry of Health, Kampala, Uganda.|Institute of Immunology and Infection Research, University of Edinburgh, Edinburgh, United Kingdom.|Department of Pathology, University of Cambridge, Cambridge, United Kingdom.|The EMBL-European Bioinformatics Institute, Wellcome Trust Genome Campus, Hinxton, Cambridge, United Kingdom.|London School of Hygiene and Tropical Medicine, London, United Kingdom.', 'United Kingdom|United Kingdom|United Kingdom|United Kingdom|Uganda|United Kingdom|United Kingdom|Uni', 0, 'Allergens|Animals|Antigens, Helminth|Evolution, Molecular|Helminth Proteins|Helminths|Humans|Hypersensitivity|Immunity, Innate|Immunoglobulin E', 'Journal Article', '10.1371/journal.pcbi.1004546', '26513360', 'Allergic reactions can be considered as maladaptive IgE immune responses towards environmental antigens. Intriguingly, these mechanisms are observed to be very similar to those implicated in the acquisition of an important degree of immunity against metazoan parasites (helminths and arthropods) in mammalian hosts. Based on the hypothesis that IgE-mediated immune responses evolved in mammals to provide extra protection against metazoan parasites rather than to cause allergy, we predict that the environmental allergens will share key properties with the metazoan parasite antigens that are specifically targeted by IgE in infected human populations. We seek to test this prediction by examining if significant similarity exists between molecular features of allergens and helminth proteins that induce an IgE response in the human host. By employing various computational approaches, 2712 unique protein molecules that are known IgE antigens were searched against a dataset of proteins from helminths and parasitic arthropods, resulting in a comprehensive list of 2445 parasite proteins that show significant similarity through sequence and structure with allergenic proteins. Nearly half of these parasite proteins from 31 species fall within the 10 most abundant allergenic protein domain families (EF-hand, Tropomyosin, CAP, Profilin, Lipocalin, Trypsin-like serine protease, Cupin, BetV1, Expansin and Prolamin). We identified epitopic-like regions in 206 parasite proteins and present the first example of a plant protein (BetV1) that is the commonest allergen in pollen in a worm, and confirming it as the target of IgE in schistosomiasis infected humans. The identification of significant similarity, inclusive of the epitopic regions, between allergens and helminth proteins against which IgE is an observed marker of protective immunity explains the off-target effects of the IgE-mediated immune system in allergy. All these findings can impact the discovery and design of molecules used in immunotherapy of allergic conditions. '),
(87453, 2015, 'plos', 'Structural Insights into Separase Architecture and Substrate Recognition through Computational Modelling of Caspase-Like and Death Domains', 'Winter, Anja|Schmid, Ralf|Bayliss, Richard', 'Department of Biochemistry, University of Leicester, Leicester, United Kingdom.|Department of Biochemistry, University of Leicester, Leicester, United Kingdom.|Department of Biochemistry, University of Leicester, Leicester, United Kingdom.', 'United Kingdom|United Kingdom|United Kingdom', 13, 'Adhesins, Bacterial|Amino Acid Sequence|Binding Sites|Caspases|Cysteine Endopeptidases|Enzyme Activation|Models, Chemical|Molecular Docking Simulation|Molecular Sequence Data|Protein Binding|Protein Structure, Tertiary|Receptors, Death Domain|Separase|Structure-Activity Relationship|Substrate Specificity', 'Journal Article', '10.1371/journal.pcbi.1004548', '26513470', 'Separases are large proteins that mediate sister chromatid disjunction in all eukaryotes. They belong to clan CD of cysteine peptidases and contain a well-conserved C-terminal catalytic protease domain similar to caspases and gingipains. However, unlike other well-characterized groups of clan CD peptidases, there are no high-resolution structures of separases and the details of their regulation and substrate recognition are poorly understood. Here we undertook an in-depth bioinformatical analysis of separases from different species with respect to their similarity in amino acid sequence and protein fold in comparison to caspases, MALT-1 proteins (mucosa-associated lymphoidtissue lymphoma translocation protein 1) and gingipain-R. A comparative model of the single C-terminal caspase-like domain in separase from C. elegans suggests similar binding modes of substrate peptides between these protein subfamilies, and enables differences in substrate specificity of separase proteins to be rationalised. We also modelled a newly identified putative death domain, located N-terminal to the caspase-like domain. The surface features of this domain identify potential sites of protein-protein interactions. Notably, we identified a novel conserved region with the consensus sequence WWxxRxxLD predicted to be exposed on the surface of the death domain, which we termed the WR motif. We envisage that findings from our study will guide structural and functional studies of this important protein family. '),
(87454, 2015, 'plos', 'Relating Cortical Atrophy in Temporal Lobe Epilepsy with Graph Diffusion-Based Network Models', 'Abdelnour, Farras|Mueller, Susanne|Raj, Ashish', 'Radiology, Weill Cornell Medical College, New York, New York, United States of America.|Radiology, University of California San Francisco, San Francisco, California, United States of America.|Radiology, Weill Cornell Medical College, New York, New York, United States of America.', 'United States|United States|United States', 12, 'Atrophy|Computer Simulation|Connectome|Epilepsy, Temporal Lobe|Female|Hippocampus|Humans|Magnetic Resonance Imaging|Male|Models, Neurological|Nerve Net', 'Journal Article', '10.1371/journal.pcbi.1004564', '26513579', 'Mesial temporal lobe epilepsy (TLE) is characterized by stereotyped origination and spread pattern of epileptogenic activity, which is reflected in stereotyped topographic distribution of neuronal atrophy on magnetic resonance imaging (MRI). Both epileptogenic activity and atrophy spread appear to follow white matter connections. We model the networked spread of activity and atrophy in TLE from first principles via two simple first order network diffusion models. Atrophy distribution is modeled as a simple consequence of the propagation of epileptogenic activity in one model, and as a progressive degenerative process in the other. We show that the network models closely reproduce the regional volumetric gray matter atrophy distribution of two epilepsy cohorts: 29 TLE subjects with medial temporal sclerosis (TLE-MTS), and 50 TLE subjects with normal appearance on MRI (TLE-no). Statistical validation at the group level suggests high correlation with measured atrophy (R = 0.586 for TLE-MTS, R = 0.283 for TLE-no). We conclude that atrophy spread model out-performs the hyperactivity spread model. These results pave the way for future clinical application of the proposed model on individual patients, including estimating future spread of atrophy, identification of seizure onset zones and surgical planning. '),
(87455, 2015, 'plos', 'Emergence of Shared Intentionality Is Coupled to the Advance of Cumulative Culture', 'Angus, Simon D|Newton, Jonathan', 'Department of Economics, Monash University, Victoria, Australia.|School of Economics, University of Sydney, New South Wales, Australia.', 'Australia|Australia', 13, 'Computer Simulation|Cooperative Behavior|Cultural Evolution|Decision Making|Ecosystem|Game Theory|Humans|Intention|Models, Statistical', 'Journal Article', '10.1371/journal.pcbi.1004587', '26516775', 'There is evidence that the sharing of intentions was an important factor in the evolution of humans unique cognitive abilities. Here, for the first time, we formally model the coevolution of jointly intentional behavior and cumulative culture, showing that rapid techno-cultural advance goes hand in hand with the emergence of the ability to participate in jointly intentional behavior. Conversely, in the absence of opportunities for significant techno-cultural improvement, the ability to undertake jointly intentional behavior is selected against. Thus, we provide a unified mechanism for the suppression or emergence of shared intentions and collaborative behavior in humans, as well as a potential cause of inter-species diversity in the prevalence of such behavior. '),
(87456, 2015, 'plos', 'Deconstructing Interocular Suppression: Attention and Divisive Normalization', 'Li, Hsin-Hung|Carrasco, Marisa|Heeger, David J', 'Department of Psychology, New York University, New York, New York, United States of America.|Department of Psychology, New York University, New York, New York, United States of America, Center for Neural Science, New York University, New York, New York, United States of America.|Department of Psychology, New York University, New York, New York, United States of America, Center for Neural Science, New York University, New York, New York, United States of America.', 'United States|United States|United States', 14, 'Attention|Computer Simulation|Cues|Dominance, Ocular|Female|Humans|Inhibition (Psychology)|Male|Models, Neurological|Nerve Net|Perceptual Masking|Photic Stimulation|Vision Disparity|Vision, Binocular|Visual Cortex|Visual Fields|Visual Perception', 'Journal Article', '10.1371/journal.pcbi.1004510', '26517321', 'In interocular suppression, a suprathreshold monocular target can be rendered invisible by a salient competitor stimulus presented in the other eye. Despite decades of research on interocular suppression and related phenomena (e.g., binocular rivalry, flash suppression, continuous flash suppression), the neural processing underlying interocular suppression is still unknown. We developed and tested a computational model of interocular suppression. The model included two processes that contributed to the strength of interocular suppression: divisive normalization and attentional modulation. According to the model, the salient competitor induced a stimulus-driven attentional modulation selective for the location and orientation of the competitor, thereby increasing the gain of neural responses to the competitor and reducing the gain of neural responses to the target. Additional suppression was induced by divisive normalization in the model, similar to other forms of visual masking. To test the model, we conducted psychophysics experiments in which both the size and the eye-of-origin of the competitor were manipulated. For small and medium competitors, behavioral performance was consonant with a change in the response gain of neurons that responded to the target. But large competitors induced a contrast-gain change, even when the competitor was split between the two eyes. The model correctly predicted these results and outperformed an alternative model in which the attentional modulation was eye specific. We conclude that both stimulus-driven attention (selective for location and feature) and divisive normalization contribute to interocular suppression. '),
(87457, 2015, 'plos', 'Doubly Bayesian Analysis of Confidence in Perceptual Decision-Making', 'Aitchison, Laurence|Bang, Dan|Bahrami, Bahador|Latham, Peter E', 'Gatsby Computational Neuroscience Unit, University College London, London, United Kingdom.|Department of Experimental Psychology, University of Oxford, Oxford, United Kingdom, Calleva Research Centre for Evolution and Human Sciences, Magdalen College, University of Oxford, Oxford, United Kingdom, Interacting Minds Centre, Aarhus University, Aarhus, Denmark.|Interacting Minds Centre, Aarhus University, Aarhus, Denmark, Institute of Cognitive Neuroscience, University College London, London, United Kingdom.|Gatsby Computational Neuroscience Unit, University College London, London, United Kingdom.', 'United Kingdom|Denmark|Denmark|United Kingdom', 28, 'Bayes Theorem|Choice Behavior|Computer Simulation|Decision Support Techniques|Heuristics|Humans|Models, Statistical|Visual Perception', 'Journal Article', '10.1371/journal.pcbi.1004519', '26517475', 'Humans stand out from other animals in that they are able to explicitly report on the reliability of their internal operations. This ability, which is known as metacognition, is typically studied by asking people to report their confidence in the correctness of some decision. However, the computations underlying confidence reports remain unclear. In this paper, we present a fully Bayesian method for directly comparing models of confidence. Using a visual two-interval forced-choice task, we tested whether confidence reports reflect heuristic computations (e.g. the magnitude of sensory data) or Bayes optimal ones (i.e. how likely a decision is to be correct given the sensory data). In a standard design in which subjects were first asked to make a decision, and only then gave their confidence, subjects were mostly Bayes optimal. In contrast, in a less-commonly used design in which subjects indicated their confidence and decision simultaneously, they were roughly equally likely to use the Bayes optimal strategy or to use a heuristic but suboptimal strategy. Our results suggest that, while peoples confidence reports can reflect Bayes optimal computations, even a small unusual twist or additional element of complexity can prevent optimality. '),
(87458, 2015, 'plos', 'Membrane Mechanics of Endocytosis in Cells with Turgor', 'Dmitrieff, Serge|Nédélec, François', 'Cell Biology and Biophysics Unit, European Molecular Biology Laboratory, Heidelberg, Germany.|Cell Biology and Biophysics Unit, European Molecular Biology Laboratory, Heidelberg, Germany.', 'Germany|Germany', 33, 'Actins|Cell Membrane|Cell Size|Computer Simulation|Elastic Modulus|Endocytosis|Mechanotransduction, Cellular|Membrane Fluidity|Models, Biological|Pressure', 'Journal Article', '10.1371/journal.pcbi.1004538', '26517669', 'Endocytosis is an essential process by which cells internalize a piece of plasma membrane and material from the outside. In cells with turgor, pressure opposes membrane deformations, and increases the amount of force that has to be generated by the endocytic machinery. To determine this force, and calculate the shape of the membrane, we used physical theory to model an elastic surface under pressure. Accurate fits of experimental profiles are obtained assuming that the coated membrane is highly rigid and preferentially curved at the endocytic site. The forces required from the actin machinery peaks at the onset of deformation, indicating that once invagination has been initiated, endocytosis is unlikely to stall before completion. Coat proteins do not lower the initiation force but may affect the process by the curvature they induce. In the presence of isotropic curvature inducers, pulling the tip of the invagination can trigger the formation of a neck at the base of the invagination. Hence direct neck constriction by actin may not be required, while its pulling role is essential. Finally, the theory shows that anisotropic curvature effectors stabilize membrane invaginations, and the loss of crescent-shaped BAR domain proteins such as Rvs167 could therefore trigger membrane scission. '),
(87459, 2015, 'plos', 'Oxygen-Driven Tumour Growth Model: A Pathology-Relevant Mathematical Approach', 'Delgado-SanMartin, Juan A|Hare, Jennifer I|de Moura, Alessandro P S|Yates, James W T', 'Modelling & Simulation Oncology DMPK, AstraZeneca, Cambridge, United Kingdom, Physics Department, University of Aberdeen, Aberdeen, United Kingdom.|In vivo bioscience, AstraZeneca, Macclesfield, United Kingdom.|Physics Department, University of Aberdeen, Aberdeen, United Kingdom.|Modelling & Simulation Oncology DMPK, AstraZeneca, Cambridge, United Kingdom.', 'United Kingdom|United Kingdom|United Kingdom|United Kingdom', 4, 'Animals|Cell Hypoxia|Cell Line, Tumor|Cell Proliferation|Computer Simulation|Humans|Models, Biological|Neoplasms|Oxidative Stress|Oxygen|Oxygen Consumption', 'Journal Article', '10.1371/journal.pcbi.1004550', '26517813', 'Xenografts--as simplified animal models of cancer-differ substantially in vasculature and stromal architecture when compared to clinical tumours. This makes mathematical model-based predictions of clinical outcome challenging. Our objective is to further understand differences in tumour progression and physiology between animal models and the clinic. To achieve that, we propose a mathematical model based upon tumour pathophysiology, where oxygen--as a surrogate for endocrine delivery--is our main focus. The Oxygen-Driven Model (ODM), using oxygen diffusion equations, describes tumour growth, hypoxia and necrosis. The ODM describes two key physiological parameters. Apparent oxygen uptake rate (kR) represents the amount of oxygen cells seem to need to proliferate. The more oxygen they appear to need, the more the oxygen transport. kR gathers variability from the vasculature, stroma and tumour morphology. Proliferating rate (kp) deals with cell line specific factors to promote growth. The KH,KN describe the switch of hypoxia and necrosis. Retrospectively, using archived data, we looked at longitudinal tumour volume datasets for 38 xenografted cell lines and 5 patient-derived xenograft-like models. Exploration of the parameter space allows us to distinguish 2 groups of parameters. Group 1 of cell lines shows a spread in values of kR and lower kp, indicating that tumours are poorly perfused and slow growing. Group 2 share the value of the oxygen uptake rate (kR) and vary greatly in kp, which we interpret as having similar oxygen transport, but more tumour intrinsic variability in growth. However, the ODM has some limitations when tested in explant-like animal models, whose complex tumour-stromal morphology may not be captured in the current version of the model. Incorporation of stroma in the ODM will help explain these discrepancies. We have provided an example. The ODM is a very simple -and versatile- model suitable for the design of preclinical experiments, which can be modified and enhanced whilst maintaining confidence in its predictions.'),
(87460, 2015, 'plos', 'Temporal Gillespie Algorithm: Fast Simulation of Contagion Processes on Time-Varying Networks', 'Vestergaard, Christian L|Génois, Mathieu', 'Aix Marseille Université, Université de Toulon, CNRS, CPT, UMR 7332, Marseille, France.|Aix Marseille Université, Université de Toulon, CNRS, CPT, UMR 7332, Marseille, France.', 'France|France', 32, 'Algorithms|Computer Simulation|Contact Tracing|Disease Transmission, Infectious|Epidemics|Humans|Models, Statistical|Risk Assessment|Spatio-Temporal Analysis|Stochastic Processes', 'Journal Article', '10.1371/journal.pcbi.1004579', '26517860', 'Stochastic simulations are one of the cornerstones of the analysis of dynamical processes on complex networks, and are often the only accessible way to explore their behavior. The development of fast algorithms is paramount to allow large-scale simulations. The Gillespie algorithm can be used for fast simulation of stochastic processes, and variants of it have been applied to simulate dynamical processes on static networks. However, its adaptation to temporal networks remains non-trivial. We here present a temporal Gillespie algorithm that solves this problem. Our method is applicable to general Poisson (constant-rate) processes on temporal networks, stochastically exact, and up to multiple orders of magnitude faster than traditional simulation schemes based on rejection sampling. We also show how it can be extended to simulate non-Markovian processes. The algorithm is easily applicable in practice, and as an illustration we detail how to simulate both Poissonian and non-Markovian models of epidemic spreading. Namely, we provide pseudocode and its implementation in C++ for simulating the paradigmatic Susceptible-Infected-Susceptible and Susceptible-Infected-Recovered models and a Susceptible-Infected-Recovered model with non-constant recovery rates. For empirical networks, the temporal Gillespie algorithm is here typically from 10 to 100 times faster than rejection sampling. '),
(87461, 2015, 'plos', 'Mathematical Modelling of Molecular Pathways Enabling Tumour Cell Invasion and Migration', 'Cohen, David P A|Martignetti, Loredana|Robine, Sylvie|Barillot, Emmanuel|Zinovyev, Andrei|Calzone, Laurence', 'Institut Curie, Paris, France, INSERM, U900, Paris, France, Mines ParisTech, Fontainebleau, Paris, France.|Institut Curie, Paris, France, INSERM, U900, Paris, France, Mines ParisTech, Fontainebleau, Paris, France.|Institut Curie, Paris, France, CNRS UMR144, Paris, France.|Institut Curie, Paris, France, INSERM, U900, Paris, France, Mines ParisTech, Fontainebleau, Paris, France.|Institut Curie, Paris, France, INSERM, U900, Paris, France, Mines ParisTech, Fontainebleau, Paris, France.|Institut Curie, Paris, France, INSERM, U900, Paris, France, Mines ParisTech, Fontainebleau, Paris, France.', 'France|France|France|France|France|France', 45, 'Animals|Colonic Neoplasms|Computational Biology|Databases, Genetic|Epithelial-Mesenchymal Transition|Humans|Mice|Mice, Transgenic|Models, Biological|Mutation|Neoplasm Invasiveness|Neoplasm Metastasis', 'Journal Article', '10.1371/journal.pcbi.1004571', '26528548', 'Understanding the etiology of metastasis is very important in clinical perspective, since it is estimated that metastasis accounts for 90% of cancer patient mortality. Metastasis results from a sequence of multiple steps including invasion and migration. The early stages of metastasis are tightly controlled in normal cells and can be drastically affected by malignant mutations, therefore, they might constitute the principal determinants of the overall metastatic rate even if the later stages take long to occur. To elucidate the role of individual mutations or their combinations affecting the metastatic development, a logical model has been constructed that recapitulates published experimental results of known gene perturbations on local invasion and migration processes, and predict the effect of not yet experimentally assessed mutations. The model has been validated using experimental data on transcriptome dynamics following TGF-xcexb2-dependent induction of Epithelial to Mesenchymal Transition in lung cancer cell lines. A method to associate gene expression profiles with different stable state solutions of the logical model has been developed for that purpose. In addition, we have systematically predicted alleviating (masking) and synergistic pairwise genetic interactions between the genes composing the model with respect to the probability of acquiring the metastatic phenotype. We focused on several unexpected synergistic genetic interactions leading to theoretically very high metastasis probability. Among them, the synergistic combination of Notch overexpression and p53 deletion shows one of the strongest effects, which is in agreement with a recent published experiment in a mouse model of gut cancer. The mathematical model can recapitulate experimental mutations in both cell line and mouse models. Furthermore, the model predicts new gene perturbations that affect the early steps of metastasis underlying potential intervention points for innovative therapeutic strategies in oncology. '),
(87462, 2015, 'plos', 'Parallel Representation of Value-Based and Finite State-Based Strategies in the Ventral and Dorsal Striatum', 'Ito, Makoto|Doya, Kenji', 'Okinawa Institute of Science and Technology Graduate University, Onna-son Okinawa, Japan.|Okinawa Institute of Science and Technology Graduate University, Onna-son Okinawa, Japan.', 'Japan|Japan', 0, 'Algorithms|Animals|Choice Behavior|Computational Biology|Corpus Striatum|Learning|Male|Markov Chains|Models, Neurological|Neurons|Rats|Rats, Long-Evans', 'Journal Article', '10.1371/journal.pcbi.1004540', '26529522', 'Previous theoretical studies of animal and human behavioral learning have focused on the dichotomy of the value-based strategy using action value functions to predict rewards and the model-based strategy using internal models to predict environmental states. However, animals and humans often take simple procedural behaviors, such as the win-stay, lose-switch strategy without explicit prediction of rewards or states. Here we consider another strategy, the finite state-based strategy, in which a subject selects an action depending on its discrete internal state and updates the state depending on the action chosen and the reward outcome. By analyzing choice behavior of rats in a free-choice task, we found that the finite state-based strategy fitted their behavioral choices more accurately than value-based and model-based strategies did. When fitted models were run autonomously with the same task, only the finite state-based strategy could reproduce the key feature of choice sequences. Analyses of neural activity recorded from the dorsolateral striatum (DLS), the dorsomedial striatum (DMS), and the ventral striatum (VS) identified significant fractions of neurons in all three subareas for which activities were correlated with individual states of the finite state-based strategy. The signal of internal states at the time of choice was found in DMS, and for clusters of states was found in VS. In addition, action values and state values of the value-based strategy were encoded in DMS and VS, respectively. These results suggest that both the value-based strategy and the finite state-based strategy are implemented in the striatum. '),
(87463, 2015, 'plos', 'FireProt: Energy- and Evolution-Based Computational Design of Thermostable Multiple-Point Mutants', 'Bednar, David|Beerens, Koen|Sebestova, Eva|Bendl, Jaroslav|Khare, Sagar|Chaloupkova, Radka|Prokop, Zbynek|Brezovsky, Jan|Baker, David|Damborsky, Jiri', 'Loschmidt Laboratories, Department of Experimental Biology and Research Centre for Toxic Compounds in the Environment RECETOX, Masaryk University, Brno, Czech Republic, International Clinical Research Center, St. Annes University Hospital Brno, Brno, Czech Republic.|Loschmidt Laboratories, Department of Experimental Biology and Research Centre for Toxic Compounds in the Environment RECETOX, Masaryk University, Brno, Czech Republic.|Loschmidt Laboratories, Department of Experimental Biology and Research Centre for Toxic Compounds in the Environment RECETOX, Masaryk University, Brno, Czech Republic.|Loschmidt Laboratories, Department of Experimental Biology and Research Centre for Toxic Compounds in the Environment RECETOX, Masaryk University, Brno, Czech Republic, International Clinical Research Center, St. Annes University Hospital Brno, Brno, Czech Republic, Department of Information Systems, Faculty of Information Technology, Brno University of Technology, Brno, Czech Republic.|Department of Chemistry and Chemical Biology, Rutgers University, Piscataway, New Jersey, United States of America.|Loschmidt Laboratories, Department of Experimental Biology and Research Centre for Toxic Compounds in the Environment RECETOX, Masaryk University, Brno, Czech Republic.|Loschmidt Laboratories, Department of Experimental Biology and Research Centre for Toxic Compounds in the Environment RECETOX, Masaryk University, Brno, Czech Republic, International Clinical Research Center, St. Annes University Hospital Brno, Brno, Czech Republic, Enantis, Ltd., Brno, Czech Republic.|Loschmidt Laboratories, Department of Experimental Biology and Research Centre for Toxic Compounds in the Environment RECETOX, Masaryk University, Brno, Czech Republic, International Clinical Research Center, St. Annes University Hospital Brno, Brno, Czech Republic.|Department of Biochemistry, University of Washington, Seattle, Washington, United States of America.|Loschmidt Laboratories, Department of Experimental Biology and Research Centre for Toxic Compounds in the Environment RECETOX, Masaryk University, Brno, Czech Republic, International Clinical Research Center, St. Annes University Hospital Brno, Brno, Czech Republic, Enantis, Ltd., Brno, Czech Republic.', '-|-|-|-|Jersey|-|-|-|United States|-', 59, 'Computational Biology|Computer Simulation|Databases, Genetic|Enzyme Stability|Lyases|Models, Molecular|Point Mutation|Protein Engineering|Temperature', 'Journal Article', '10.1371/journal.pcbi.1004556', '26529612', 'There is great interest in increasing proteins stability to enhance their utility as biocatalysts, therapeutics, diagnostics and nanomaterials. Directed evolution is a powerful, but experimentally strenuous approach. Computational methods offer attractive alternatives. However, due to the limited reliability of predictions and potentially antagonistic effects of substitutions, only single-point mutations are usually predicted in silico, experimentally verified and then recombined in multiple-point mutants. Thus, substantial screening is still required. Here we present FireProt, a robust computational strategy for predicting highly stable multiple-point mutants that combines energy- and evolution-based approaches with smart filtering to identify additive stabilizing mutations. FireProts reliability and applicability was demonstrated by validating its predictions against 656 mutations from the ProTherm database. We demonstrate that thermostability of the model enzymes haloalkane dehalogenase DhaA and xcexb3-hexachlorocyclohexane dehydrochlorinase LinA can be substantially increased (xcex94Tm = 24xc2xb0C and 21xc2xb0C) by constructing and characterizing only a handful of multiple-point mutants. FireProt can be applied to any protein for which a tertiary structure and homologous sequences are available, and will facilitate the rapid development of robust proteins for biomedical and biotechnological applications. '),
(87464, 2015, 'plos', 'A Unifying Probabilistic View of Associative Learning', 'Gershman, Samuel J', 'Department of Psychology and Center for Brain Science, Harvard University, Cambridge, Massachusetts, United States of America.', 'United States', 33, 'Algorithms|Animals|Association Learning|Bayes Theorem|Computational Biology|Humans|Models, Neurological', 'Journal Article', '10.1371/journal.pcbi.1004567', '26535896', 'Two important ideas about associative learning have emerged in recent decades: (1) Animals are Bayesian learners, tracking their uncertainty about associations, and (2) animals acquire long-term reward predictions through reinforcement learning. Both of these ideas are normative, in the sense that they are derived from rational design principles. They are also descriptive, capturing a wide range of empirical phenomena that troubled earlier theories. This article describes a unifying framework encompassing Bayesian and reinforcement learning theories of associative learning. Each perspective captures a different aspect of associative learning, and their synthesis offers insight into phenomena that neither perspective can explain on its own. '),
(87465, 2015, 'plos', 'Neural Sequence Generation Using Spatiotemporal Patterns of Inhibition', 'Cannon, Jonathan|Kopell, Nancy|Gardner, Timothy|Markowitz, Jeffrey', 'Department of Mathematics, Boston University, Boston, Massachusetts, United States of America.|Department of Mathematics, Boston University, Boston, Massachusetts, United States of America.|Department of Biology, Boston University, Boston, Massachusetts, United States of America.|Department of Biology, Boston University, Boston, Massachusetts, United States of America.', 'United States|United States|United States|United States', 8, 'Animals|Birds|Computational Biology|Computer Simulation|Feedback, Physiological|Humans|Models, Neurological|Motor Cortex|Neural Inhibition', 'Journal Article', '10.1371/journal.pcbi.1004581', '26536029', 'Stereotyped sequences of neural activity are thought to underlie reproducible behaviors and cognitive processes ranging from memory recall to arm movement. One of the most prominent theoretical models of neural sequence generation is the synfire chain, in which pulses of synchronized spiking activity propagate robustly along a chain of cells connected by highly redundant feedforward excitation. But recent experimental observations in the avian song production pathway during song generation have shown excitatory activity interacting strongly with the firing patterns of inhibitory neurons, suggesting a process of sequence generation more complex than feedforward excitation. Here we propose a model of sequence generation inspired by these observations in which a pulse travels along a spatially recurrent excitatory chain, passing repeatedly through zones of local feedback inhibition. In this model, synchrony and robust timing are maintained not through redundant excitatory connections, but rather through the interaction between the pulse and the spatiotemporal pattern of inhibition that it creates as it circulates the network. These results suggest that spatially and temporally structured inhibition may play a key role in sequence generation. '),
(87466, 2015, 'plos', 'Direct Measurements of Local Coupling between Myosin Molecules Are Consistent with a Model of Muscle Activation', 'Walcott, Sam|Kad, Neil M', 'Mathematics, University of California at Davis, Davis, California, United States of America.|School of Biosciences, University of Kent, Canterbury, Kent, United Kingdom.', 'United States|United Kingdom', 4, 'Algorithms|Computational Biology|Computer Simulation|Fluorescent Dyes|Green Fluorescent Proteins|Humans|Kymography|Models, Biological|Muscle, Skeletal|Myosins|Protein Binding', 'Journal Article', '10.1371/journal.pcbi.1004599', '26536123', 'Muscle contracts due to ATP-dependent interactions of myosin motors with thin filaments composed of the proteins actin, troponin, and tropomyosin. Contraction is initiated when calcium binds to troponin, which changes conformation and displaces tropomyosin, a filamentous protein that wraps around the actin filament, thereby exposing myosin binding sites on actin. Myosin motors interact with each other indirectly via tropomyosin, since myosin binding to actin locally displaces tropomyosin and thereby facilitates binding of nearby myosin. Defining and modeling this local coupling between myosin motors is an open problem in muscle modeling and, more broadly, a requirement to understanding the connection between muscle contraction at the molecular and macro scale. It is challenging to directly observe this coupling, and such measurements have only recently been made. Analysis of these data suggests that two myosin heads are required to activate the thin filament. This result contrasts with a theoretical model, which reproduces several indirect measurements of coupling between myosin, that assumes a single myosin head can activate the thin filament. To understand this apparent discrepancy, we incorporated the model into stochastic simulations of the experiments, which generated simulated data that were then analyzed identically to the experimental measurements. By varying a single parameter, good agreement between simulation and experiment was established. The conclusion that two myosin molecules are required to activate the thin filament arises from an assumption, made during data analysis, that the intensity of the fluorescent tags attached to myosin varies depending on experimental condition. We provide an alternative explanation that reconciles theory and experiment without assuming that the intensity of the fluorescent tags varies. '),
(87467, 2015, 'plos', 'Bayesian Estimation of Conditional Independence Graphs Improves Functional Connectivity Estimates', 'Hinne, Max|Janssen, Ronald J|Heskes, Tom|van Gerven, Marcel A J', 'Radboud University, Institute for Computing and Information Sciences, Nijmegen, the Netherlands.|Radboud University, Donders Institute for Brain, Cognition and Behaviour, Nijmegen, the Netherlands.|Radboud University, Institute for Computing and Information Sciences, Nijmegen, the Netherlands.|Radboud University, Donders Institute for Brain, Cognition and Behaviour, Nijmegen, the Netherlands.', 'Netherlands|Netherlands|Netherlands|Netherlands', 0, 'Bayes Theorem|Brain|Computational Biology|Connectome|Humans|Magnetic Resonance Imaging|Models, Neurological|Nerve Net', 'Journal Article', '10.1371/journal.pcbi.1004534', '26540089', 'Functional connectivity concerns the correlated activity between neuronal populations in spatially segregated regions of the brain, which may be studied using functional magnetic resonance imaging (fMRI). This coupled activity is conveniently expressed using covariance, but this measure fails to distinguish between direct and indirect effects. A popular alternative that addresses this issue is partial correlation, which regresses out the signal of potentially confounding variables, resulting in a measure that reveals only direct connections. Importantly, provided the data are normally distributed, if two variables are conditionally independent given all other variables, their respective partial correlation is zero. In this paper, we propose a probabilistic generative model that allows us to estimate functional connectivity in terms of both partial correlations and a graph representing conditional independencies. Simulation results show that this methodology is able to outperform the graphical LASSO, which is the de facto standard for estimating partial correlations. Furthermore, we apply the model to estimate functional connectivity for twenty subjects using resting-state fMRI data. Results show that our model provides a richer representation of functional connectivity as compared to considering partial correlations alone. Finally, we demonstrate how our approach can be extended in several ways, for instance to achieve data fusion by informing the conditional independence graph with data from probabilistic tractography. As our Bayesian formulation of functional connectivity provides access to the posterior distribution instead of only to point estimates, we are able to quantify the uncertainty associated with our results. This reveals that while we are able to infer a clear backbone of connectivity in our empirical results, the data are not accurately described by simply looking at the mode of the distribution over connectivity. The implication of this is that deterministic alternatives may misjudge connectivity results by drawing conclusions from noisy and limited data. ');
INSERT INTO `papers` (`id`, `ano`, `journal`, `titulo`, `autores`, `afiliacao`, `pais`, `citacoes`, `palavra_chave`, `categorias`, `doi`, `pubmed`, `abstract`) VALUES
(87468, 2015, 'plos', 'Learning to Estimate Dynamical State with Probabilistic Population Codes', 'Makin, Joseph G|Dichter, Benjamin K|Sabes, Philip N', 'Center for Integrative Neuroscience, University of California, San Francisco, San Francisco, California, United States of America.|Center for Integrative Neuroscience, University of California, San Francisco, San Francisco, California, United States of America.|Center for Integrative Neuroscience, University of California, San Francisco, San Francisco, California, United States of America.', 'United States|United States|United States', 6, 'Algorithms|Computational Biology|Computer Simulation|Humans|Models, Neurological|Models, Statistical|Neural Networks (Computer)|Proprioception', 'Journal Article', '10.1371/journal.pcbi.1004554', '26540152', 'Tracking moving objects, including ones own body, is a fundamental ability of higher organisms, playing a central role in many perceptual and motor tasks. While it is unknown how the brain learns to follow and predict the dynamics of objects, it is known that this process of state estimation can be learned purely from the statistics of noisy observations. When the dynamics are simply linear with additive Gaussian noise, the optimal solution is the well known Kalman filter (KF), the parameters of which can be learned via latent-variable density estimation (the EM algorithm). The brain does not, however, directly manipulate matrices and vectors, but instead appears to represent probability distributions with the firing rates of population of neurons, probabilistic population codes. We show that a recurrent neural network-a modified form of an exponential family harmonium (EFH)-that takes a linear probabilistic population code as input can learn, without supervision, to estimate the state of a linear dynamical system. After observing a series of population responses (spike counts) to the position of a moving object, the network learns to represent the velocity of the object and forms nearly optimal predictions about the position at the next time-step. This result builds on our previous work showing that a similar network can learn to perform multisensory integration and coordinate transformations for static stimuli. The receptive fields of the trained network also make qualitative predictions about the developing and learning brain: tuning gradually emerges for higher-order dynamical states not explicitly present in the inputs, appearing as delayed tuning for the lower-order states. '),
(87469, 2015, 'plos', 'A Voltage-Based STDP Rule Combined with Fast BCM-Like Metaplasticity Accounts for LTP and Concurrent Heterosynaptic LTD in the Dentate Gyrus In Vivo', 'Jedlicka, Peter|Benuskova, Lubica|Abraham, Wickliffe C', 'Institute of Clinical Neuroanatomy, Neuroscience Center, Goethe University Frankfurt, Frankfurt, Germany.|Department of Computer Science, University of Otago, Dunedin, New Zealand.|Brain Health Research Centre and Brain Research New Zealand, University of Otago, Dunedin, New Zealand.', 'Germany|New Zealand|New Zealand', 18, 'Action Potentials|Animals|Computational Biology|Dentate Gyrus|Long-Term Potentiation|Long-Term Synaptic Depression|Models, Neurological|Neuronal Plasticity|Rats|Synapses', 'Journal Article', '10.1371/journal.pcbi.1004588', '26544038', 'Long-term potentiation (LTP) and long-term depression (LTD) are widely accepted to be synaptic mechanisms involved in learning and memory. It remains uncertain, however, which particular activity rules are utilized by hippocampal neurons to induce LTP and LTD in behaving animals. Recent experiments in the dentate gyrus of freely moving rats revealed an unexpected pattern of LTP and LTD from high-frequency perforant path stimulation. While 400 Hz theta-burst stimulation (400-TBS) and 400 Hz delta-burst stimulation (400-DBS) elicited substantial LTP of the tetanized medial path input and, concurrently, LTD of the non-tetanized lateral path input, 100 Hz theta-burst stimulation (100-TBS, a normally efficient LTP protocol for in vitro preparations) produced only weak LTP and concurrent LTD. Here we show in a biophysically realistic compartmental granule cell model that this pattern of results can be accounted for by a voltage-based spike-timing-dependent plasticity (STDP) rule combined with a relatively fast Bienenstock-Cooper-Munro (BCM)-like homeostatic metaplasticity rule, all on a background of ongoing spontaneous activity in the input fibers. Our results suggest that, at least for dentate granule cells, the interplay of STDP-BCM plasticity rules and ongoing pre- and postsynaptic background activity determines not only the degree of input-specific LTP elicited by various plasticity-inducing protocols, but also the degree of associated LTD in neighboring non-tetanized inputs, as generated by the ongoing constitutive activity at these synapses. '),
(87470, 2015, 'plos', 'Mechanism of Focal Adhesion Kinase Mechanosensing', 'Zhou, Jing|Aponte-Santamaría, Camilo|Sturm, Sebastian|Bullerjahn, Jakob Tómas|Bronowska, Agnieszka|Gräter, Frauke', 'Heidelberg Institute for Theoretical Studies, Heidelberg, Germany.|Heidelberg Institute for Theoretical Studies, Heidelberg, Germany.|Leipzig University, Institute for Theoretical Physics, Leipzig, Germany.|Leipzig University, Institute for Theoretical Physics, Leipzig, Germany.|Heidelberg Institute for Theoretical Studies, Heidelberg, Germany.|Heidelberg Institute for Theoretical Studies, Heidelberg, Germany.', 'Germany|Germany|Germany|Germany|Germany|Germany', 0, 'Computational Biology|Cytoskeletal Proteins|Cytoskeleton|Focal Adhesion Protein-Tyrosine Kinases|Focal Adhesions|Mechanotransduction, Cellular|Membrane Proteins|Models, Biological|Molecular Dynamics Simulation', 'Journal Article', '10.1371/journal.pcbi.1004593', '26544178', 'Mechanosensing at focal adhesions regulates vital cellular processes. Here, we present results from molecular dynamics (MD) and mechano-biochemical network simulations that suggest a direct role of Focal Adhesion Kinase (FAK) as a mechano-sensor. Tensile forces, propagating from the membrane through the PIP2 binding site of the FERM domain and from the cytoskeleton-anchored FAT domain, activate FAK by unlocking its central phosphorylation site (Tyr576/577) from the autoinhibitory FERM domain. Varying loading rates, pulling directions, and membrane PIP2 concentrations corroborate the specific opening of the FERM-kinase domain interface, due to its remarkably lower mechanical stability compared to the individual alpha-helical domains and the PIP2-FERM link. Analyzing downstream signaling networks provides further evidence for an intrinsic mechano-signaling role of FAK in broadcasting force signals through Ras to the nucleus. This distinguishes FAK from hitherto identified focal adhesion mechano-responsive molecules, allowing a new interpretation of cell stretching experiments. '),
(87471, 2015, 'plos', 'A Quantitative Model of the GIRK1/2 Channel Reveals That Its Basal and Evoked Activities Are Controlled by Unequal Stoichiometry of Gxcexb1 and Gxcexb2xcexb3', 'Yakubovich, Daniel|Berlin, Shai|Kahanovitch, Uri|Rubinstein, Moran|Farhy-Tselnicker, Isabella|Styr, Boaz|Keren-Raifman, Tal|Dessauer, Carmen W|Dascal, Nathan', 'Department of Physiology and Pharmacology and Sagol School of Neuroscience, Tel Aviv University, Tel Aviv, Israel.|Department of Physiology and Pharmacology and Sagol School of Neuroscience, Tel Aviv University, Tel Aviv, Israel.|Department of Physiology and Pharmacology and Sagol School of Neuroscience, Tel Aviv University, Tel Aviv, Israel.|Department of Physiology and Pharmacology and Sagol School of Neuroscience, Tel Aviv University, Tel Aviv, Israel.|Department of Physiology and Pharmacology and Sagol School of Neuroscience, Tel Aviv University, Tel Aviv, Israel.|Department of Physiology and Pharmacology and Sagol School of Neuroscience, Tel Aviv University, Tel Aviv, Israel.|Department of Physiology and Pharmacology and Sagol School of Neuroscience, Tel Aviv University, Tel Aviv, Israel.|Department of Integrative Biology and Pharmacology, University of Texas Health Science Center, Houston, Texas, United States of America.|Department of Physiology and Pharmacology and Sagol School of Neuroscience, Tel Aviv University, Tel Aviv, Israel.', 'Israel|Israel|Israel|Israel|Israel|Israel|Israel|United States|Israel', 7, 'Animals|Computational Biology|Female|G Protein-Coupled Inwardly-Rectifying Potassium Channels|GTP-Binding Protein alpha Subunits|GTP-Binding Protein beta Subunits|HEK293 Cells|Humans|Models, Biological|Oocytes|Xenopus laevis', 'Journal Article', '10.1371/journal.pcbi.1004598', '26544551', 'G protein-gated K+ channels (GIRK, Kir3), activated by Gxcexb2xcexb3 subunits derived from Gi/o proteins, regulate heartbeat and neuronal excitability and plasticity. Both neurotransmitter-evoked (Ievoked) and neurotransmitter-independent basal (Ibasal) GIRK activities are physiologically important, but mechanisms of Ibasal and its relation to Ievoked are unclear. We have previously shown for heterologously expressed neuronal GIRK1/2, and now show for native GIRK in hippocampal neurons, that Ibasal and Ievoked are interrelated: the extent of activation by neurotransmitter (activation index, Ra) is inversely related to Ibasal. To unveil the underlying mechanisms, we have developed a quantitative model of GIRK1/2 function. We characterized single-channel and macroscopic GIRK1/2 currents, and surface densities of GIRK1/2 and Gxcexb2xcexb3 expressed in Xenopus oocytes. Based on experimental results, we constructed a mathematical model of GIRK1/2 activity under steady-state conditions before and after activation by neurotransmitter. Our model accurately recapitulates Ibasal and Ievoked in Xenopus oocytes, HEK293 cells and hippocampal neurons, correctly predicts the dose-dependent activation of GIRK1/2 by coexpressed Gxcexb2xcexb3 and fully accounts for the inverse Ibasal-Ra correlation. Modeling indicates that, under all conditions and at different channel expression levels, between 3 and 4 Gxcexb2xcexb3 dimers are available for each GIRK1/2 channel. In contrast, available Gxcexb1i/o decreases from ~2 to less than one Gxcexb1 per channel as GIRK1/2s density increases. The persistent Gxcexb2xcexb3/channel (but not Gxcexb1/channel) ratio support a strong association of GIRK1/2 with Gxcexb2xcexb3, consistent with recruitment to the cell surface of Gxcexb2xcexb3, but not Gxcexb1, by GIRK1/2. Our analysis suggests a maximal stoichiometry of 4 Gxcexb2xcexb3 but only 2 Gxcexb1i/o per one GIRK1/2 channel. The unique, unequal association of GIRK1/2 with G protein subunits, and the cooperative nature of GIRK gating by Gxcexb2xcexb3, underlie the complex pattern of basal and agonist-evoked activities and allow GIRK1/2 to act as a sensitive bidirectional detector of both Gxcexb2xcexb3 and Gxcexb1. '),
(87472, 2015, 'plos', 'Lévy Walks Suboptimal under Predation Risk', 'Abe, Masato S|Shimada, Masakazu', 'Department of General Systems Studies, Graduate School of Arts and Sciences, The University of Tokyo, Tokyo, Japan.|Department of General Systems Studies, Graduate School of Arts and Sciences, The University of Tokyo, Tokyo, Japan.', 'Japan|Japan', 7, 'Algorithms|Animals|Computational Biology|Computer Simulation|Models, Biological|Movement|Predatory Behavior|Risk', 'Journal Article', '10.1371/journal.pcbi.1004601', '26544687', 'A key challenge in movement ecology is to understand how animals move in nature. Previous studies have predicted that animals should perform a special class of random walks, called Lévy walk, to obtain more targets. However, some empirical studies did not support this hypothesis, and the relationship between search strategy and ecological factors is still unclear. We focused on ecological factors, such as predation risk, and analyzed whether Lévy walk may not be favored. It was remarkable that the ecological factors often altered an optimal search strategy from Lévy walk to Brownian walk, depending on the speed of the predators movement, density of predators, etc. This occurred because higher target encounter rates simultaneously led searchers to higher predation risks. Our findings indicate that animals may not perform Lévy walks often, and we suggest that it is crucial to consider the ecological context for evaluating the search strategy performed by animals in the field. '),
(87473, 2015, 'plos', 'Regulated CRISPR Modules Exploit a Dual Defense Strategy of Restriction and Abortive Infection in a Model of Prokaryote-Phage Coevolution', 'Kumar, M Senthil|Plotkin, Joshua B|Hannenhalli, Sridhar', 'Graduate Program in Bioinformatics, University of Maryland, College Park, Maryland, United States of America.|Department of Biology, University of Pennsylvania, Philadelphia, Pennsylvania, United States of America.|Center for Bioinformatics and Computational Biology, University of Maryland, College Park, Maryland, United States of America.', 'United States|United States|United States', 7, 'Bacteria|Bacteriophages|Biological Evolution|CRISPR-Cas Systems|Computational Biology', 'Journal Article', '10.1371/journal.pcbi.1004603', '26544847', 'CRISPRs offer adaptive immunity in prokaryotes by acquiring genomic fragments from infecting phage and subsequently exploiting them for phage restriction via an RNAi-like mechanism. Here, we develop and analyze a dynamical model of CRISPR-mediated prokaryote-phage coevolution that incorporates classical CRISPR kinetics along with the recently discovered infection-induced activation and autoimmunity side effects. Our analyses reveal two striking characteristics of the CRISPR defense strategy: that both restriction and abortive infections operate during coevolution with phages, driving phages to much lower densities than possible with restriction alone, and that CRISPR maintenance is determined by a key dimensionless combination of parameters, which upper bounds the activation level of CRISPRs in uninfected populations. We contrast these qualitative observations with experimental data on CRISPR kinetics, which offer insight into the spacer deletion mechanism and the observed low CRISPR prevalence in clinical isolates. More generally, we exploit numerical simulations to delineate four regimes of CRISPR dynamics in terms of its host, kinetic, and regulatory parameters. '),
(87474, 2015, 'plos', 'Deciphering Transcriptional Dynamics In Vivo by Counting Nascent RNA Molecules', 'Choubey, Sandeep|Kondev, Jane|Sanchez, Alvaro', 'Department of Physics, Brandeis University, Waltham, Massachusetts, United States of America.|Department of Physics, Brandeis University, Waltham, Massachusetts, United States of America.|Rowland Institute at Harvard, Harvard University, Cambridge, Massachusetts, United States of America.', 'United States|United States|United States', 11, 'Algorithms|Computational Biology|Cytoplasm|DNA-Directed RNA Polymerases|Models, Genetic|RNA|Transcription, Genetic|Yeasts', 'Journal Article', '10.1371/journal.pcbi.1004345', '26544860', 'Deciphering how the regulatory DNA sequence of a gene dictates its expression in response to intra and extracellular cues is one of the leading challenges in modern genomics. The development of novel single-cell sequencing and imaging techniques, as well as a better exploitation of currently available single-molecule imaging techniques, provides an avenue to interrogate the process of transcription and its dynamics in cells by quantifying the number of RNA polymerases engaged in the transcription of a gene (or equivalently the number of nascent RNAs) at a given moment in time. In this paper, we propose that measurements of the cell-to-cell variability in the number of nascent RNAs provide a mostly unexplored method for deciphering mechanisms of transcription initiation in cells. We propose a simple kinetic model of transcription initiation and elongation from which we calculate nascent RNA copy-number fluctuations. To demonstrate the usefulness of this approach, we test our theory against published nascent RNA data for twelve constitutively expressed yeast genes. Rather than transcription being initiated through a single rate limiting step, as it had been previously proposed, our single-cell analysis reveals the presence of at least two rate limiting steps. Surprisingly, half of the genes analyzed have nearly identical rates of transcription initiation, suggesting a common mechanism. Our analytical framework can be used to extract quantitative information about dynamics of transcription from single-cell sequencing data, as well as from single-molecule imaging and electron micrographs of fixed cells, and provides the mathematical means to exploit the quantitative power of these technologies. '),
(87475, 2015, 'plos', 'Most Undirected Random Graphs Are Amplifiers of Selection for Birth-Death Dynamics, but Suppressors of Selection for Death-Birth Dynamics', 'Hindersin, Laura|Traulsen, Arne', 'Department of Evolutionary Theory, Max Planck Institute for Evolutionary Biology, Plön, Germany.|Department of Evolutionary Theory, Max Planck Institute for Evolutionary Biology, Plön, Germany.', 'Germany|Germany', 0, 'Algorithms|Biological Evolution|Computational Biology|Models, Biological|Mutation|Population Dynamics|Population Growth', 'Journal Article', '10.1371/journal.pcbi.1004437', '26544962', 'We analyze evolutionary dynamics on graphs, where the nodes represent individuals of a population. The links of a node describe which other individuals can be displaced by the offspring of the individual on that node. Amplifiers of selection are graphs for which the fixation probability is increased for advantageous mutants and decreased for disadvantageous mutants. A few examples of such amplifiers have been developed, but so far it is unclear how many such structures exist and how to construct them. Here, we show that almost any undirected random graph is an amplifier of selection for Birth-death updating, where an individual is selected to reproduce with probability proportional to its fitness and one of its neighbors is replaced by that offspring at random. If we instead focus on death-Birth updating, in which a random individual is removed and its neighbors compete for the empty spot, then the same ensemble of graphs consists of almost only suppressors of selection for which the fixation probability is decreased for advantageous mutants and increased for disadvantageous mutants. Thus, the impact of population structure on evolutionary dynamics is a subtle issue that will depend on seemingly minor details of the underlying evolutionary process. '),
(87476, 2015, 'plos', 'Network Plasticity as Bayesian Inference', 'Kappel, David|Habenschuss, Stefan|Legenstein, Robert|Maass, Wolfgang', 'Institute for Theoretical Computer Science, Graz University of Technology, A-8010 Graz, Austria.|Institute for Theoretical Computer Science, Graz University of Technology, A-8010 Graz, Austria.|Institute for Theoretical Computer Science, Graz University of Technology, A-8010 Graz, Austria.|Institute for Theoretical Computer Science, Graz University of Technology, A-8010 Graz, Austria.', 'Austria|Austria|Austria|Austria', 39, 'Action Potentials|Bayes Theorem|Computational Biology|Computer Simulation|Models, Neurological|Nerve Net|Neuronal Plasticity|Neurons', 'Journal Article', '10.1371/journal.pcbi.1004485', '26545099', 'General results from statistical learning theory suggest to understand not only brain computations, but also brain plasticity as probabilistic inference. But a model for that has been missing. We propose that inherently stochastic features of synaptic plasticity and spine motility enable cortical networks of neurons to carry out probabilistic inference by sampling from a posterior distribution of network configurations. This model provides a viable alternative to existing models that propose convergence of parameters to maximum likelihood values. It explains how priors on weight distributions and connection probabilities can be merged optimally with learned experience, how cortical networks can generalize learned information so well to novel experiences, and how they can compensate continuously for unforeseen disturbances of the network. The resulting new theory of network plasticity explains from a functional perspective a number of experimental data on stochastic aspects of synaptic plasticity that previously appeared to be quite puzzling. '),
(87477, 2015, 'plos', 'On the Adjacency Matrix of RyR2 Cluster Structures', 'Walker, Mark A|Kohl, Tobias|Lehnart, Stephan E|Greenstein, Joseph L|Lederer, W J|Winslow, Raimond L', 'Institute for Computational Medicine, Department of Biomedical Engineering, Johns Hopkins University, Baltimore, Maryland, United States of America.|Heart Research Center Gxc3xb6ttingen, Clinic of Cardiology and Pulmonology, University Medical Center Gxc3xb6ttingen, Gxc3xb6ttingen, Germany.|Heart Research Center Gxc3xb6ttingen, Clinic of Cardiology and Pulmonology, University Medical Center Gxc3xb6ttingen, Gxc3xb6ttingen, Germany.|Institute for Computational Medicine, Department of Biomedical Engineering, Johns Hopkins University, Baltimore, Maryland, United States of America.|Center for Biomedical Engineering and Technology, University of Maryland School of Medicine, Baltimore, Maryland, United States of America.|Institute for Computational Medicine, Department of Biomedical Engineering, Johns Hopkins University, Baltimore, Maryland, United States of America.', 'United States|Germany|Germany|United States|United States|United States', 0, 'Animals|Calcium|Calcium Signaling|Mice|Models, Biological|Myocardial Contraction|Myocytes, Cardiac|Ryanodine Receptor Calcium Release Channel|Systems Biology', 'Journal Article', '10.1371/journal.pcbi.1004521', '26545234', 'In the heart, electrical stimulation of cardiac myocytes increases the open probability of sarcolemmal voltage-sensitive Ca2+ channels and flux of Ca2+ into the cells. This increases Ca2+ binding to ligand-gated channels known as ryanodine receptors (RyR2). Their openings cause cell-wide release of Ca2+, which in turn causes muscle contraction and the generation of the mechanical force required to pump blood. In resting myocytes, RyR2s can also open spontaneously giving rise to spatially-confined Ca2+ release events known as sparks. RyR2s are organized in a lattice to form clusters in the junctional sarcoplasmic reticulum membrane. Our recent work has shown that the spatial arrangement of RyR2s within clusters strongly influences the frequency of Ca2+ sparks. We showed that the probability of a Ca2+ spark occurring when a single RyR2 in the cluster opens spontaneously can be predicted from the precise spatial arrangements of the RyR2s. Thus, function follows from structure. This probability is related to the maximum eigenvalue (xcexbb1) of the adjacency matrix of the RyR2 cluster lattice. In this work, we develop a theoretical framework for understanding this relationship. We present a stochastic contact network model of the Ca2+ spark initiation process. We show that xcexbb1 determines a stability threshold for the formation of Ca2+ sparks in terms of the RyR2 gating transition rates. We recapitulate these results by applying the model to realistic RyR2 cluster structures informed by super-resolution stimulated emission depletion (STED) microscopy. Eigendecomposition of the linearized mean-field contact network model reveals functional subdomains within RyR2 clusters with distinct sensitivities to Ca2+. This work provides novel perspectives on the cardiac Ca2+ release process and a general method for inferring the functional properties of transmembrane receptor clusters from their structure. '),
(87478, 2015, 'plos', 'A Kinetic Platform to Determine the Fate of Hydrogen Peroxide in Escherichia coli', 'Adolfsen, Kristin J|Brynildsen, Mark P', 'Department of Chemical and Biological Engineering, Princeton University, Princeton, New Jersey, United States of America.|Department of Chemical and Biological Engineering, Princeton University, Princeton, New Jersey, United States of America.', 'Jersey|Jersey', 13, 'Computational Biology|Escherichia coli|Hydrogen Peroxide|Kinetics|Metabolic Networks and Pathways|Oxidative Stress', 'Journal Article', '10.1371/journal.pcbi.1004562', '26545295', 'Hydrogen peroxide (H2O2) is used by phagocytic cells of the innate immune response to kill engulfed bacteria. H2O2 diffuses freely into bacteria, where it can wreak havoc on sensitive biomolecules if it is not rapidly detoxified. Accordingly, bacteria have evolved numerous systems to defend themselves against H2O2, and the importance of these systems to pathogenesis has been substantiated by the many bacteria that require them to establish or sustain infections. The kinetic competition for H2O2 within bacteria is complex, which suggests that quantitative models will improve interpretation and prediction of network behavior. To date, such models have been of limited scope, and this inspired us to construct a quantitative, systems-level model of H2O2 detoxification in Escherichia coli that includes detoxification enzymes, H2O2-dependent transcriptional regulation, enzyme degradation, the Fenton reaction and damage caused by •OH, oxidation of biomolecules by H2O2, and repair processes. After using an iterative computational and experimental procedure to train the model, we leveraged it to predict how H2O2 detoxification would change in response to an environmental perturbation that pathogens encounter within host phagosomes, carbon source deprivation, which leads to translational inhibition and limited availability of NADH. We found that the model accurately predicted that NADH depletion would delay clearance at low H2O2 concentrations and that detoxification at higher concentrations would resemble that of carbon-replete conditions. These results suggest that protein synthesis during bolus H2O2 stress does not affect clearance dynamics and that access to catabolites only matters at low H2O2 concentrations. We anticipate that this model will serve as a computational tool for the quantitative exploration and dissection of oxidative stress in bacteria, and that the model and methods used to develop it will provide important templates for the generation of comparable models for other bacterial species. '),
(87479, 2015, 'plos', 'Non-canonical Activation of Akt in Serum-Stimulated Fibroblasts, Revealed by Comparative Modeling of Pathway Dynamics', 'Nim, Tri Hieu|Luo, Le|White, Jacob K|Clément, Marie-Véronique|Tucker-Kellogg, Lisa', 'Computational Systems Biology Programme, Singapore-MIT Alliance, Singapore.|Department of Biochemistry, Yong Loo Lin School of Medicine, National University of Singapore, Singapore.|Computational Systems Biology Programme, Singapore-MIT Alliance, Singapore.|Systems Biology Institute (SBI), Clayton, Victoria, Australia.|Computational Systems Biology Programme, Singapore-MIT Alliance, Singapore.', 'Singapore|Singapore|Singapore|Australia|Singapore', 6, 'Animals|Cell Line|Computational Biology|Fibroblasts|Mice|Models, Biological|Phosphatidylinositol Phosphates|Proto-Oncogene Proteins c-akt|Signal Transduction', 'Journal Article', '10.1371/journal.pcbi.1004505', '26554359', 'The dynamic behaviors of signaling pathways can provide clues to pathway mechanisms. In cancer cells, excessive phosphorylation and activation of the Akt pathway is responsible for cell survival advantages. In normal cells, serum stimulation causes brief peaks of extremely high Akt phosphorylation before reaching a moderate steady-state. Previous modeling assumed this peak and decline behavior (i.e., overshoot) was due to receptor internalization. In this work, we modeled the dynamics of the overshoot as a tool for gaining insight into Akt pathway function. We built an ordinary differential equation (ODE) model describing pathway activation immediately upstream of Akt phosphorylation at Thr308 (Aktp308). The model was fit to experimental measurements of Aktp308, total Akt, and phosphatidylinositol (3,4,5)-trisphosphate (PIP3), from mouse embryonic fibroblasts with serum stimulation. The canonical Akt activation model (the null hypothesis) was unable to recapitulate the observed delay between the peak of PIP3 (at 2 minutes), and the peak of Aktp308 (at 30-60 minutes). From this we conclude that the peak and decline behavior of Aktp308 is not caused by PIP3 dynamics. Models for alternative hypotheses were constructed by allowing an arbitrary dynamic curve to perturb each of 5 steps of the pathway. All 5 of the alternative models could reproduce the observed delay. To distinguish among the alternatives, simulations suggested which species and timepoints would show strong differences. Time-series experiments with membrane fractionation and PI3K inhibition were performed, and incompatible hypotheses were excluded. We conclude that the peak and decline behavior of Aktp308 is caused by a non-canonical effect that retains Akt at the membrane, and not by receptor internalization. Furthermore, we provide a novel spline-based method for simulating the network implications of an unknown effect, and we demonstrate a process of hypothesis management for guiding efficient experiments. '),
(87480, 2015, 'plos', 'An Ovol2-Zeb1 Mutual Inhibitory Circuit Governs Bidirectional and Multi-step Transition between Epithelial and Mesenchymal States', 'Hong, Tian|Watanabe, Kazuhide|Ta, Catherine Ha|Villarreal-Ponce, Alvaro|Nie, Qing|Dai, Xing', 'Department of Mathematics, University of California, Irvine, Irvine, California, United States of America.|Center for Complex Biological Systems, University of California, Irvine, Irvine, California, United States of America.|Department of Mathematics, University of California, Irvine, Irvine, California, United States of America.|Center for Complex Biological Systems, University of California, Irvine, Irvine, California, United States of America.|Department of Mathematics, University of California, Irvine, Irvine, California, United States of America.|Center for Complex Biological Systems, University of California, Irvine, Irvine, California, United States of America.', 'United States|United States|United States|United States|United States|United States', 0, 'Animals|Cell Line|Cell Line, Tumor|Computational Biology|Epithelial-Mesenchymal Transition|Feedback, Physiological|Homeodomain Proteins|Humans|Mice|Transcription Factors|Zinc Fingers', 'Journal Article', '10.1371/journal.pcbi.1004569', '26554584', 'Reversible epithelial-to-mesenchymal transition (EMT) is central to tissue development, epithelial stemness, and cancer metastasis. While many regulatory elements have been identified to induce EMT, the complex process underlying such cellular plasticity remains poorly understood. Utilizing a systems biology approach integrating modeling and experiments, we found multiple intermediate states contributing to EMT and that the robustness of the transitions is modulated by transcriptional factor Ovol2. In particular, we obtained evidence for a mutual inhibition relationship between Ovol2 and EMT inducer Zeb1, and observed that adding this regulation generates a novel four-state system consisting of two distinct intermediate phenotypes that differ in differentiation propensities and are favored in different environmental conditions. We identified epithelial cells that naturally exist in an intermediate state with bidirectional differentiation potential, and found the balance between EMT-promoting and -inhibiting factors to be critical in achieving and selecting between intermediate states. Our analysis suggests a new design principle in controlling cellular plasticity through multiple intermediate cell fates and underscores the critical involvement of Ovol2 and its associated molecular regulations. '),
(87481, 2015, 'plos', 'From Sensory Signals to Modality-Independent Conceptual Representations: A Probabilistic Language of Thought Approach', 'Erdogan, Goker|Yildirim, Ilker|Jacobs, Robert A', 'Department of Brain & Cognitive Sciences, University of Rochester, Rochester, New York, United States of America.|Department of Brain & Cognitive Sciences, Massachusetts Institute of Technology, Cambridge, Massachusetts, United States of America.|Department of Brain & Cognitive Sciences, University of Rochester, Rochester, New York, United States of America.', 'United States|United States|United States', 0, 'Algorithms|Computational Biology|Computer Simulation|Humans|Models, Neurological|Perception|Photic Stimulation|Touch', 'Journal Article', '10.1371/journal.pcbi.1004610', '26554704', 'People learn modality-independent, conceptual representations from modality-specific sensory signals. Here, we hypothesize that any system that accomplishes this feat will include three components: a representational language for characterizing modality-independent representations, a set of sensory-specific forward models for mapping from modality-independent representations to sensory signals, and an inference algorithm for inverting forward models-that is, an algorithm for using sensory signals to infer modality-independent representations. To evaluate this hypothesis, we instantiate it in the form of a computational model that learns object shape representations from visual and/or haptic signals. The model uses a probabilistic grammar to characterize modality-independent representations of object shape, uses a computer graphics toolkit and a human hand simulator to map from object representations to visual and haptic features, respectively, and uses a Bayesian inference algorithm to infer modality-independent object representations from visual and/or haptic signals. Simulation results show that the model infers identical object representations when an object is viewed, grasped, or both. That is, the models percepts are modality invariant. We also report the results of an experiment in which different subjects rated the similarity of pairs of objects in different sensory conditions, and show that the model provides a very accurate account of subjects ratings. Conceptually, this research significantly contributes to our understanding of modality invariance, an important type of perceptual constancy, by demonstrating how modality-independent representations can be acquired and used. Methodologically, it provides an important contribution to cognitive modeling, particularly an emerging probabilistic language-of-thought approach, by showing how symbolic and statistical approaches can be combined in order to understand aspects of human perception. '),
(87482, 2015, 'plos', 'The Elementary Operations of Human Vision Are Not Reducible to Template-Matching', 'Neri, Peter', 'Laboratoire des Systèmes Perceptifs, CNRS UMR 8248, 29 rue dUlm, 75005 Paris, France.', 'France', 6, 'Computational Biology|Humans|Models, Neurological|Nonlinear Dynamics|Vision, Ocular|Visual Cortex', 'Journal Article', '10.1371/journal.pcbi.1004499', '26556758', 'It is generally acknowledged that biological vision presents nonlinear characteristics, yet linear filtering accounts of visual processing are ubiquitous. The template-matching operation implemented by the linear-nonlinear cascade (linear filter followed by static nonlinearity) is the most widely adopted computational tool in systems neuroscience. This simple model achieves remarkable explanatory power while retaining analytical tractability, potentially extending its reach to a wide range of systems and levels in sensory processing. The extent of its applicability to human behaviour, however, remains unclear. Because sensory stimuli possess multiple attributes (e.g. position, orientation, size), the issue of applicability may be asked by considering each attribute one at a time in relation to a family of linear-nonlinear models, or by considering all attributes collectively in relation to a specified implementation of the linear-nonlinear cascade. We demonstrate that human visual processing can operate under conditions that are indistinguishable from linear-nonlinear transduction with respect to substantially different stimulus attributes of a uniquely specified target signal with associated behavioural task. However, no specific implementation of a linear-nonlinear cascade is able to account for the entire collection of results across attributes, a satisfactory account at this level requires the introduction of a small gain-control circuit, resulting in a model that no longer belongs to the linear-nonlinear family. Our results inform and constrain efforts at obtaining and interpreting comprehensive characterizations of the human sensory process by demonstrating its inescapably nonlinear nature, even under conditions that have been painstakingly fine-tuned to facilitate template-matching behaviour and to produce results that, at some level of inspection, do conform to linear filtering predictions. They also suggest that compliance with linear transduction may be the targeted outcome of carefully crafted nonlinear circuits, rather than default behaviour exhibited by basic components. '),
(87483, 2015, 'plos', 'The Encoding of Decision Difficulty and Movement Time in the Primate Premotor Cortex', 'Martinez-Garcia, Marina|Insabato, Andrea|Pannunzi, Mario|Pardo-Vazquez, Jose L|Acuña, Carlos|Deco, Gustavo', 'Universitat Pompeu Fabra, Theoretical and Computational Neuroscience Center for Brain and Cognition, Barcelona, Spain.|Universitat Pompeu Fabra, Theoretical and Computational Neuroscience Center for Brain and Cognition, Barcelona, Spain.|Universitat Pompeu Fabra, Theoretical and Computational Neuroscience Center for Brain and Cognition, Barcelona, Spain.|Circuit Dynamics & Computation Laboratory, Champalimaud Neuroscience Programme, Lisboa, Portugal.|Departamento de Fisiología, Facultad de Medicina, Universidad de Santiago de Compostela, Santiago de Compostela, Spain.|Universitat Pompeu Fabra, Theoretical and Computational Neuroscience Center for Brain and Cognition, Barcelona, Spain.', 'Spain|Spain|Spain|Portugal|Spain|Spain', 0, 'Algorithms|Animals|Computational Biology|Decision Making|Macaca mulatta|Male|Models, Neurological|Motor Cortex|Psychomotor Performance|Time Factors', 'Journal Article', '10.1371/journal.pcbi.1004502', '26556807', 'Estimating the difficulty of a decision is a fundamental process to elaborate complex and adaptive behaviour. In this paper, we show that the movement time of behaving monkeys performing a decision-making task is correlated with decision difficulty and that the activity of a population of neurons in ventral Premotor cortex correlates with the movement time. Moreover, we found another population of neurons that encodes the discriminability of the stimulus, thereby supplying another source of information about the difficulty of the decision. The activity of neurons encoding the difficulty can be produced by very different computations. Therefore, we show that decision difficulty can be encoded through three different mechanisms: 1. Switch time coding, 2. rate coding and 3. binary coding. This rich representation reflects the basis of different functional aspects of difficulty in the making of a decision and the possible role of difficulty estimation in complex decision scenarios. '),
(87484, 2015, 'plos', 'Network Events on Multiple Space and Time Scales in Cultured Neural Networks and in a Stochastic Rate Model', 'Gigante, Guido|Deco, Gustavo|Marom, Shimon|Del Giudice, Paolo', 'Italian Institute of Health, Rome, Italy.|Center for Brain and Cognition, Computational Neuroscience Group, Department of Information and Communication Technologies, Universitat Pompeu Fabra, Barcelona, Spain.|Technion - Israel Institute of Technology, Haifa Israel.|Italian Institute of Health, Rome, Italy.', 'Italy|Spain|Israel|Italy', 17, 'Action Potentials|Animals|Animals, Newborn|Cell Culture Techniques|Cells, Cultured|Cerebral Cortex|Computational Biology|Computer Simulation|Electrodes|Models, Neurological|Nerve Net|Neurons|Rats', 'Journal Article', '10.1371/journal.pcbi.1004547', '26558616', 'Cortical networks, in-vitro as well as in-vivo, can spontaneously generate a variety of collective dynamical events such as network spikes, UP and DOWN states, global oscillations, and avalanches. Though each of them has been variously recognized in previous works as expression of the excitability of the cortical tissue and the associated nonlinear dynamics, a unified picture of the determinant factors (dynamical and architectural) is desirable and not yet available. Progress has also been partially hindered by the use of a variety of statistical measures to define the network events of interest. We propose here a common probabilistic definition of network events that, applied to the firing activity of cultured neural networks, highlights the co-occurrence of network spikes, power-law distributed avalanches, and exponentially distributed quasi-orbits, which offer a third type of collective behavior. A rate model, including synaptic excitation and inhibition with no imposed topology, synaptic short-term depression, and finite-size noise, accounts for all these different, coexisting phenomena. We find that their emergence is largely regulated by the proximity to an oscillatory instability of the dynamics, where the non-linear excitable behavior leads to a self-amplification of activity fluctuations over a wide range of scales in space and time. In this sense, the cultured network dynamics is compatible with an excitation-inhibition balance corresponding to a slightly sub-critical regime. Finally, we propose and test a method to infer the characteristic time of the fatigue process, from the observed time course of the networks firing rate. Unlike the model, possessing a single fatigue mechanism, the cultured network appears to show multiple time scales, signalling the possible coexistence of different fatigue mechanisms. '),
(87485, 2015, 'plos', 'Regulation of Spatiotemporal Patterns by Biological Variability: General Principles and Applications to Dictyostelium discoideum', 'Grace, Miriam|Hütt, Marc-Thorsten', 'School of Engineering and Science, Jacobs University Bremen, Bremen, Germany.|School of Engineering and Science, Jacobs University Bremen, Bremen, Germany.', 'Germany|Germany', 4, 'Algorithms|Dictyostelium|Models, Biological|Signal Transduction|Spatio-Temporal Analysis|Systems Biology', 'Journal Article', '10.1371/journal.pcbi.1004367', '26562406', 'Spatiotemporal patterns often emerge from local interactions in a self-organizing fashion. In biology, the resulting patterns are also subject to the influence of the systematic differences between the systems constituents (biological variability). This regulation of spatiotemporal patterns by biological variability is the topic of our review. We discuss several examples of correlations between cell properties and the self-organized spatiotemporal patterns, together with their relevance for biology. Our guiding, illustrative example will be spiral waves of cAMP in a colony of Dictyostelium discoideum cells. Analogous processes take place in diverse situations (such as cardiac tissue, where spiral waves occur in potentially fatal ventricular fibrillation) so a deeper understanding of this additional layer of self-organized pattern formation would be beneficial to a wide range of applications. One of the most striking differences between pattern-forming systems in physics or chemistry and those in biology is the potential importance of variability. In the former, system components are essentially identical with random fluctuations determining the details of the self-organization process and the resulting patterns. In biology, due to variability, the properties of potentially very few cells can have a driving influence on the resulting asymptotic collective state of the colony. Variability is one means of implementing a few-element control on the collective mode. Regulatory architectures, parameters of signaling cascades, and properties of structure formation processes can be reverse-engineered from observed spatiotemporal patterns, as different types of regulation and forms of interactions between the constituents can lead to markedly different correlations. The power of this biology-inspired view of pattern formation lies in building a bridge between two scales: the patterns as a collective state of a very large number of cells on the one hand, and the internal parameters of the single cells on the other. '),
(87486, 2015, 'plos', 'Neuromechanistic Model of Auditory Bistability', 'Rankin, James|Sussman, Elyse|Rinzel, John', 'Center for Neural Science, New York University, New York, New York, United States of America.|Dominick P. Purpura Department of Neuroscience, Albert Einstein College of Medicine, Bronx, New York, United States of America.|Center for Neural Science, New York University, New York, New York, United States of America.', 'United States|United States|United States', 22, 'Acoustic Stimulation|Adult|Auditory Cortex|Auditory Perception|Computational Biology|Female|Humans|Male|Models, Neurological|Young Adult', 'Journal Article', '10.1371/journal.pcbi.1004555', '26562507', 'Sequences of higher frequency A and lower frequency B tones repeating in an ABA- triplet pattern are widely used to study auditory streaming. One may experience either an integrated percept, a single ABA-ABA- stream, or a segregated percept, separate but simultaneous streams A-A-A-A- and -B---B--. During minutes-long presentations, subjects may report irregular alternations between these interpretations. We combine neuromechanistic modeling and psychoacoustic experiments to study these persistent alternations and to characterize the effects of manipulating stimulus parameters. Unlike many phenomenological models with abstract, percept-specific competition and fixed inputs, our network model comprises neuronal units with sensory feature dependent inputs that mimic the pulsatile-like A1 responses to tones in the ABA- triplets. It embodies a neuronal computation for percept competition thought to occur beyond primary auditory cortex (A1). Mutual inhibition, adaptation and noise are implemented. We include slow NDMA recurrent excitation for local temporal memory that enables linkage across sound gaps from one triplet to the next. Percepts in our model are identified in the firing patterns of the neuronal units. We predict with the model that manipulations of the frequency difference between tones A and B should affect the dominance durations of the stronger percept, the one dominant a larger fraction of time, more than those of the weaker percept-a property that has been previously established and generalized across several visual bistable paradigms. We confirm the qualitative prediction with our psychoacoustic experiments and use the behavioral data to further constrain and improve the model, achieving quantitative agreement between experimental and modeling results. Our work and model provide a platform that can be extended to consider other stimulus conditions, including the effects of context and volition. '),
(87487, 2015, 'plos', 'Dynamic Redox Regulation of IL-4 Signaling', 'Dwivedi, Gaurav|Gran, Margaret A|Bagchi, Pritha|Kemp, Melissa L', 'Wallace H. Coulter Department of Biomedical Engineering, Georgia Institute of Technology and Emory University, Atlanta, Georgia, United States of America.|Wallace H. Coulter Department of Biomedical Engineering, Georgia Institute of Technology and Emory University, Atlanta, Georgia, United States of America.|Wallace H. Coulter Department of Biomedical Engineering, Georgia Institute of Technology and Emory University, Atlanta, Georgia, United States of America.|Wallace H. Coulter Department of Biomedical Engineering, Georgia Institute of Technology and Emory University, Atlanta, Georgia, United States of America.', 'Georgia|Georgia|Georgia|Georgia', 0, 'Algorithms|Humans|Interleukin-4|Jurkat Cells|Models, Biological|Oxidation-Reduction|Protein Tyrosine Phosphatases|Signal Transduction|Systems Biology', 'Journal Article', '10.1371/journal.pcbi.1004582', '26562652', 'Quantifying the magnitude and dynamics of protein oxidation during cell signaling is technically challenging. Computational modeling provides tractable, quantitative methods to test hypotheses of redox mechanisms that may be simultaneously operative during signal transduction. The interleukin-4 (IL-4) pathway, which has previously been reported to induce reactive oxygen species and oxidation of PTP1B, may be controlled by several other putative mechanisms of redox regulation, widespread proteomic thiol oxidation observed via 2D redox differential gel electrophoresis upon IL-4 treatment suggests more than one redox-sensitive protein implicated in this pathway. Through computational modeling and a model selection strategy that relied on characteristic STAT6 phosphorylation dynamics of IL-4 signaling, we identified reversible protein tyrosine phosphatase (PTP) oxidation as the primary redox regulatory mechanism in the pathway. A systems-level model of IL-4 signaling was developed that integrates synchronous pan-PTP oxidation with ROS-independent mechanisms. The model quantitatively predicts the dynamics of IL-4 signaling over a broad range of new redox conditions, offers novel hypotheses about regulation of JAK/STAT signaling, and provides a framework for interrogating putative mechanisms involving receptor-initiated oxidation. ');
