INSERT INTO `papers` (`id`, `ano`, `journal`, `titulo`, `autores`, `afiliacao`, `pais`, `citacoes`, `palavra_chave`, `categorias`, `doi`, `pubmed`, `abstract`) VALUES
(89271, 2018, 'plos', 'Ten quick tips for getting the most scientific value out of numerical data', 'Schwen, Lars Ole|Rueschenbaum, Sabrina', 'Fraunhofer MEVIS, Am Fallturm 1, Bremen, Germany.|Department of Internal Medicine 1, University Hospital Frankfurt, Goethe University, Theodor-Stern-Kai 7, Frankfurt (Main), Germany.', 'Germany|Germany', 0, 'Biomedical Research|Data Analysis|Humans|Research Design', 'Editorial', '10.1371/journal.pcbi.1006141', '30307934', 'Most studies in the life sciences and other disciplines involve generating and analyzing numerical data of some type as the foundation for scientific findings. Working with numerical data involves multiple challenges. These include reproducible data acquisition, appropriate data storage, computationally correct data analysis, appropriate reporting and presentation of the results, and suitable data interpretation. Finding and correcting mistakes when analyzing and interpreting data can be frustrating and time-consuming. Presenting or publishing incorrect results is embarrassing but not uncommon. Particular sources of errors are inappropriate use of statistical methods and incorrect interpretation of data by software. To detect mistakes as early as possible, one should frequently check intermediate and final results for plausibility. Clearly documenting how quantities and results were obtained facilitates correcting mistakes. Properly understanding data is indispensable for reaching well-founded conclusions from experimental results. Units are needed to make sense of numbers, and uncertainty should be estimated to know how meaningful results are. Descriptive statistics and significance testing are useful tools for interpreting numerical results if applied correctly. However, blindly trusting in computed numbers can also be misleading, so it is worth thinking about how data should be summarized quantitatively to properly answer the question at hand. Finally, a suitable form of presentation is needed so that the data can properly support the interpretation and findings. By additionally sharing the relevant data, others can access, understand, and ultimately make use of the results. These quick tips are intended to provide guidelines for correctly interpreting, efficiently analyzing, and presenting numerical data in a useful way.'),
(89272, 2018, 'plos', 'Seizure pathways: A model-based investigation', 'Karoly, Philippa J|Kuhlmann, Levin|Soudry, Daniel|Grayden, David B|Cook, Mark J|Freestone, Dean R', 'Department of Biomedical Engineering, The University of Melbourne, Parkville, Australia.|Brain Dynamics Lab, Swinburne University of Technology, Hawthorn, Australia.|Department of Electrical Engineering, Technion, Haifa, Israel.|Department of Biomedical Engineering, The University of Melbourne, Parkville, Australia.|Department of Medicine, St Vincents Hospital, The University of Melbourne, Fitzroy, Australia.|Department of Medicine, St Vincents Hospital, The University of Melbourne, Fitzroy, Australia.', 'Australia|Australia|Israel|Australia|Australia|Australia', 10, 'Algorithms|Computational Biology|Databases, Factual|Electrocorticography|Humans|Models, Neurological|Seizures|Signal Processing, Computer-Assisted', 'Journal Article', '10.1371/journal.pcbi.1006403', '30307937', 'We present the results of a model inversion algorithm for electrocorticography (ECoG) data recorded during epileptic seizures. The states and parameters of neural mass models were tracked during a total of over 3000 seizures from twelve patients with focal epilepsy. These models provide an estimate of the effective connectivity within intracortical circuits over the time course of seizures. Observing the dynamics of effective connectivity provides insight into mechanisms of seizures. Estimation of patients seizure dynamics revealed: 1) a highly stereotyped pattern of evolution for each patient, 2) distinct sub-groups of onset mechanisms amongst patients, and 3) different offset mechanisms for long and short seizures. Stereotypical dynamics suggest that, once initiated, seizures follow a deterministic path through the parameter space of a neural model. Furthermore, distinct sub-populations of patients were identified based on characteristic motifs in the dynamics at seizure onset. There were also distinct patterns between long and short duration seizures that were related to seizure offset. Understanding how these different patterns of seizure evolution arise may provide new insights into brain function and guide treatment for epilepsy, since specific therapies may have preferential effects on the various parameters that could potentially be individualized. Methods that unite computational models with data provide a powerful means to generate testable hypotheses for further experimental research. This work provides a demonstration that the hidden connectivity parameters of a neural mass model can be dynamically inferred from data. Our results underscore the power of theoretical models to inform epilepsy management. It is our hope that this work guides further efforts to apply computational models to clinical data.'),
(89273, 2018, 'plos', 'Ten simple rules for developing good reading habits during graduate school and beyond', 'Méndez, Marcos', 'Area of Biodiversity and Conservation, Universidad Rey Juan Carlos, Móstoles, Madrid, Spain.', 'Spain', 0, 'Habits|Humans|Reading', 'Editorial', '10.1371/journal.pcbi.1006467', '30307941', '-'),
(89274, 2018, 'plos', 'Self-organized traffic via priority rules in leaf-cutting ants', 'Strömbom, Daniel|Dussutour, Audrey', 'Department of Mathematics, Uppsala University, Uppsala, Sweden.|Centre de Recherches sur la Cognition Animale (CRCA), Centre de Biologie Intégrative (CBI), Université de Toulouse, CNRS, UPS, Toulouse, France.', 'Sweden|France', 3, 'Animals|Ants|Appetitive Behavior|Computational Biology|Models, Theoretical|Social Behavior|Spatial Behavior', 'Journal Article', '10.1371/journal.pcbi.1006523', '30307942', 'Ants, termites and humans often form well-organized and highly efficient trails between different locations. Yet the microscopic traffic rules responsible for this organization and efficiency are not fully understood. In previous experimental studies with leaf-cutting ants (Atta colombica), a set of local priority rules were isolated and it was proposed that these rules govern the temporal and spatial organization of the traffic on the trails. Here we introduce a model based on these priority rules to investigate whether they are sufficient to produce traffic similar to that observed in the experiments on both a narrow and a wider trail. We establish that the model is able to reproduce key characteristics of the traffic on the trails. In particular, we show that the proposed priority rules induce de-synchronization into clusters of inbound and outbound ants on a narrow trail, and that priority-type dependent segregated traffic emerges on a wider trail. Due to the generic nature of the proposed priority rules we speculate that they may be used to model traffic organization in a variety of other ant species.'),
(89275, 2018, 'plos', 'Precision in a rush: Trade-offs between reproducibility and steepness of the hunchback expression pattern', 'Tran, Huy|Desponds, Jonathan|Perez Romero, Carmina Angelica|Coppey, Mathieu|Fradin, Cecile|Dostatni, Nathalie|Walczak, Aleksandra M', 'Ecole Normale Supérieure, PSL Research University, CNRS, Sorbonne Université, Laboratoire de Physique Théorique, Paris, France.|Department of Physics, University of California, San Diego, La Jolla, California, United States of America.|Department of Physics and Astronomy, McMaster University, Hamilton, Canada.|Institut Curie, PSL Research University, CNRS, Sorbonne Université, Physico Chimie, Paris, France.|Department of Physics and Astronomy, McMaster University, Hamilton, Canada.|Institut Curie, PSL Research University, CNRS, Sorbonne Université, Nuclear Dynamics, Paris, France.|Ecole Normale Supérieure, PSL Research University, CNRS, Sorbonne Université, Laboratoire de Physique Théorique, Paris, France.', 'France|United States|Canada|France|Canada|France|France', 0, 'Animals|DNA-Binding Proteins|Drosophila Proteins|Drosophila melanogaster|Gene Expression Regulation, Developmental|Homeodomain Proteins|Larva|Models, Genetic|Trans-Activators|Transcription Factors', 'Journal Article', '10.1371/journal.pcbi.1006513', '30307984', 'Fly development amazes us by the precision and reproducibility of gene expression, especially since the initial expression patterns are established during very short nuclear cycles. Recent live imaging of hunchback promoter dynamics shows a stable steep binary expression pattern established within the three minute interphase of nuclear cycle 11. Considering expression models of different complexity, we explore the trade-off between the ability of a regulatory system to produce a steep boundary and minimize expression variability between different nuclei. We show how a limited readout time imposed by short developmental cycles affects the genes ability to read positional information along the embryos anterior posterior axis and express reliably. Comparing our theoretical results to real-time monitoring of the hunchback transcription dynamics in live flies, we discuss possible regulatory strategies, suggesting an important role for additional binding sites, gradients or non-equilibrium binding and modified transcription factor search strategies.'),
(89276, 2018, 'plos', 'What to know before forecasting the flu', 'Chakraborty, Prithwish|Lewis, Bryan|Eubank, Stephen|Brownstein, John S|Marathe, Madhav|Ramakrishnan, Naren', 'Discovery Analytics Center, Virginia Tech, Blacksburg, Virginia, United States of America.|Biocomplexity Institute, University of Virginia, Charlottesville, Virginia, United States of America.|Network Dynamics and Simulation Science Laboratory, Biocomplexity Institute, Virginia Tech, Blacksburg, Virginia, United States of America.|Childrens Hospital Informatics Program, Boston Childrens Hospital, Massachusetts, United States of America.|Biocomplexity Institute, University of Virginia, Charlottesville, Virginia, United States of America.|Discovery Analytics Center, Virginia Tech, Blacksburg, Virginia, United States of America.', 'United States|United States|United States|United States|United States|United States', 2, 'Forecasting|Humans|Influenza, Human|Public Health Surveillance', 'Journal Article', '10.1371/journal.pcbi.1005964', '30312305', '-'),
(89277, 2018, 'plos', 'State dependence of stimulus-induced variability tuning in macaque MT', 'Lombardo, Joseph A|Macellaio, Matthew V|Liu, Bing|Palmer, Stephanie E|Osborne, Leslie C', 'Computational Neuroscience Graduate Program, University of Chicago, Chicago, Illinois, United States of America.|Neurobiology Graduate Program, University of Chicago, Chicago, Illinois, United States of America.|Department of Neurobiology, University of Chicago, Chicago, Illinois, United States of America.|Department of Organismal Biology and Anatomy, University of Chicago, Chicago, Illinois, United States of America.|Department of Organismal Biology and Anatomy, University of Chicago, Chicago, Illinois, United States of America.', 'United States|United States|United States|United States|United States', 0, 'Action Potentials|Animals|Computational Biology|Macaca|Models, Neurological|Neurons|Temporal Lobe', 'Journal Article', '10.1371/journal.pcbi.1006527', '30312315', 'Behavioral states marked by varying levels of arousal and attention modulate some properties of cortical responses (e.g. average firing rates or pairwise correlations), yet it is not fully understood what drives these response changes and how they might affect downstream stimulus decoding. Here we show that changes in state modulate the tuning of response variance-to-mean ratios (Fano factors) in a fashion that is neither predicted by a Poisson spiking model nor changes in the mean firing rate, with a substantial effect on stimulus discriminability. We recorded motion-sensitive neurons in middle temporal cortex (MT) in two states: alert fixation and light, opioid anesthesia. Anesthesia tended to lower average spike counts, without decreasing trial-to-trial variability compared to the alert state. Under anesthesia, within-trial fluctuations in excitability were correlated over longer time scales compared to the alert state, creating supra-Poisson Fano factors. In contrast, alert-state MT neurons have higher mean firing rates and largely sub-Poisson variability that is stimulus-dependent and cannot be explained by firing rate differences alone. The absence of such stimulus-induced variability tuning in the anesthetized state suggests different sources of variability between states. A simple model explains state-dependent shifts in the distribution of observed Fano factors via a suppression in the variance of gain fluctuations in the alert state. A population model with stimulus-induced variability tuning and behaviorally constrained information-limiting correlations explores the potential enhancement in stimulus discriminability by the cortical population in the alert state.'),
(89278, 2018, 'plos', 'Internal but not external noise frees working memory resources', 'Tomixc4x87, Ivan|Bays, Paul M', 'Faculty of Humanities and Social Sciences, Department of Psychology, University of Zagreb, Zagreb, Croatia.|Department of Psychology, University of Cambridge, Cambridge, United Kingdom.', 'Croatia|United Kingdom', 0, 'Adolescent|Adult|Computational Biology|Female|Humans|Male|Memory, Short-Term|Models, Neurological|Noise|Reproducibility of Results|Young Adult', 'Journal Article', '10.1371/journal.pcbi.1006488', '30321172', 'The precision with which visual information can be recalled from working memory declines as the number of items in memory increases. This finding has been explained in terms of the distribution of a limited representational resource between items. Here we investigated how the sensory strength of memoranda affects resource allocation. We manipulated signal strength of an orientation stimulus in two ways: we varied the internal (sensory) noise by adjusting stimulus contrast, and varied the external (stimulus) noise by altering the within-stimulus variability. Both manipulations had similar effects on the precision with which the orientation could be recalled, but differed in their impact on memory for other stimuli. These results indicate that increasing internal noise released resources that could be used to store other stimuli more precisely, increasing external noise had no such effect. We show that these observations can be captured by a simple neural model of working memory encoding, in which spiking activity takes on the role of the limited resource.'),
(89279, 2018, 'plos', 'Correction: Elucidation of molecular kinetic schemes from macroscopic traces using system identification', 'Fribourg, Miguel|Logothetis, Diomedes E|González-Maeso, Javier|Sealfon, Stuart C|Galocha-Iragüen, Belén|Las-Heras Andrés, Fernando|Brezina, Vladimir', 'Department of Psychology, University of Cambridge, Cambridge, United Kingdom.|Department of Psychology, University of Cambridge, Cambridge, United Kingdom.|Department of Psychology, University of Cambridge, Cambridge, United Kingdom.|Department of Psychology, University of Cambridge, Cambridge, United Kingdom.|Department of Psychology, University of Cambridge, Cambridge, United Kingdom.|Department of Psychology, University of Cambridge, Cambridge, United Kingdom.|Department of Psychology, University of Cambridge, Cambridge, United Kingdom.', 'United Kingdom|United Kingdom|United Kingdom|United Kingdom|United Kingdom|United Kingdom|United Kin', 0, '-', 'Journal Article', '10.1371/journal.pcbi.1006539', '30325915', '[This corrects the article DOI: 10.1371/journal.pcbi.1005376.].'),
(89280, 2018, 'plos', 'Genomic data integration systematically biases interactome mapping', 'Skinnider, Michael A|Stacey, R Greg|Foster, Leonard J', 'Michael Smith Laboratories, University of British Columbia, Vancouver, Canada.|Michael Smith Laboratories, University of British Columbia, Vancouver, Canada.|Michael Smith Laboratories, University of British Columbia, Vancouver, Canada.', 'Canada|Canada|Canada', 0, 'Animals|Databases, Genetic|Genomics|Humans|Mice|Protein Interaction Mapping', 'Journal Article', '10.1371/journal.pcbi.1006474', '30332399', 'Elucidating the complete network of protein-protein interactions, or interactome, is a fundamental goal of the post-genomic era, yet existing interactome maps are far from complete. To increase the throughput and resolution of interactome mapping, methods for protein-protein interaction discovery by co-migration have been introduced. However, accurate identification of interacting protein pairs within the resulting large-scale proteomic datasets is challenging. Consequently, most computational pipelines for co-migration data analysis incorporate external genomic datasets to distinguish interacting from non-interacting protein pairs. The effect of this procedure on interactome mapping is poorly understood. Here, we conduct a rigorous analysis of genomic data integration for interactome recovery across a large number of co-migration datasets, spanning diverse experimental and computational methods. We find that genomic data integration leads to an increase in the functional coherence of the resulting interactome maps, but this comes at the expense of a decrease in power to discover novel interactions. Importantly, putative novel interactions predicted by genomic data integration are no more likely to later be experimentally discovered than those predicted from co-migration data alone. Our results reveal a widespread and unappreciated limitation in a methodology that has been widely used to map the interactome of humans and model organisms.'),
(89281, 2018, 'plos', 'Predicting B cell receptor substitution profiles using public repertoire data', 'Dhar, Amrit|Davidsen, Kristian|Matsen, Frederick A|Minin, Vladimir N', 'Department of Statistics, University of Washington, Seattle, Washington, United States of America.|Computational Biology, Fred Hutchinson Cancer Research Center, Seattle, Washington, United States of America.|Computational Biology, Fred Hutchinson Cancer Research Center, Seattle, Washington, United States of America.|Department of Statistics, University of California, Irvine, California, United States of America.', 'United States|United States|United States|United States', 0, 'Amino Acid Substitution|Amino Acids|Animals|B-Lymphocytes|Clone Cells|Computational Biology|Databases, Protein|Humans|Models, Immunological|Receptors, Antigen, B-Cell|Recombinant Proteins', 'Journal Article', '10.1371/journal.pcbi.1006388', '30332400', 'B cells develop high affinity receptors during the course of affinity maturation, a cyclic process of mutation and selection. At the end of affinity maturation, a number of cells sharing the same ancestor (i.e. in the same clonal family) are released from the germinal center, their amino acid frequency profile reflects the allowed and disallowed substitutions at each position. These clonal-family-specific frequency profiles, called substitution profiles, are useful for studying the course of affinity maturation as well as for antibody engineering purposes. However, most often only a single sequence is recovered from each clonal family in a sequencing experiment, making it impossible to construct a clonal-family-specific substitution profile. Given the public release of many high-quality large B cell receptor datasets, one may ask whether it is possible to use such data in a prediction model for clonal-family-specific substitution profiles. In this paper, we present the method Substitution Profiles Using Related Families (SPURF), a penalized tensor regression framework that integrates information from a rich assemblage of datasets to predict the clonal-family-specific substitution profile for any single input sequence. Using this framework, we show that substitution profiles from similar clonal families can be leveraged together with simulated substitution profiles and germline gene sequence information to improve prediction. We fit this model on a large public dataset and validate the robustness of our approach on two external datasets. Furthermore, we provide a command-line tool in an open-source software package (https://github.com/krdav/SPURF) implementing these ideas and providing easy prediction using our pre-fit models.'),
(89282, 2018, 'plos', 'Data-driven brain network models differentiate variability across language tasks', 'Bansal, Kanika|Medaglia, John D|Bassett, Danielle S|Vettel, Jean M|Muldoon, Sarah F', 'Department of Mathematics, University at Buffalo - SUNY, Buffalo, New York, United States of America.|Department of Psychology, Drexel University, Philadelphia, Pennsylvania, United States of America.|Department of Biomedical Engineering, University of Pennsylvania, Philadelphia, Pennsylvania, United States of America.|Human Research and Engineering Directorate, U.S. Army Research Laboratory, Aberdeen Proving Ground, Maryland, United States of America.|Department of Mathematics, University at Buffalo - SUNY, Buffalo, New York, United States of America.', 'United States|United States|United States|United States|United States', 0, 'Adult|Brain|Computational Biology|Female|Humans|Language|Male|Models, Neurological|Nerve Net|Speech Perception|Task Performance and Analysis|Young Adult', 'Journal Article', '10.1371/journal.pcbi.1006487', '30332401', 'The relationship between brain structure and function has been probed using a variety of approaches, but how the underlying structural connectivity of the human brain drives behavior is far from understood. To investigate the effect of anatomical brain organization on human task performance, we use a data-driven computational modeling approach and explore the functional effects of naturally occurring structural differences in brain networks. We construct personalized brain network models by combining anatomical connectivity estimated from diffusion spectrum imaging of individual subjects with a nonlinear model of brain dynamics. By performing computational experiments in which we measure the excitability of the global brain network and spread of synchronization following a targeted computational stimulation, we quantify how individual variation in the underlying connectivity impacts both local and global brain dynamics. We further relate the computational results to individual variability in the subjects performance of three language-demanding tasks both before and after transcranial magnetic stimulation to the left-inferior frontal gyrus. Our results show that task performance correlates with either local or global measures of functional activity, depending on the complexity of the task. By emphasizing differences in the underlying structural connectivity, our model serves as a powerful tool to assess individual differences in task performances, to dissociate the effect of targeted stimulation in tasks that differ in cognitive demand, and to pave the way for the development of personalized therapeutics.'),
(89283, 2018, 'plos', 'Virus and CTL dynamics in the extrafollicular and follicular tissue compartments in SIV-infected macaques', 'Wodarz, Dominik|Skinner, Pamela J|Levy, David N|Connick, Elizabeth', 'Department of Ecology and Evolutionary Biology, Department of Mathematics, University of California, Irvine, Irvine, California, United States of America.|Department of Veterinary and Biomedical Sciences, University of Minnesota, St. Paul, Minnesota, United States of America.|Department of Basic Science, New York University College of Dentistry, New York, New York, United States of America.|Division of Infectious Diseases, University of Arizona, Tucson, Arizona, United States of America.', 'United States|United States|United States|United States', 2, 'Animals|Computational Biology|Host-Pathogen Interactions|Macaca|Models, Immunological|Simian Acquired Immunodeficiency Syndrome|Simian Immunodeficiency Virus|T-Lymphocytes, Cytotoxic', 'Journal Article', '10.1371/journal.pcbi.1006461', '30335747', 'Data from SIV-infected macaques indicate that virus-specific cytotoxic T lymphocytes (CTL) are mostly present in the extrafollicular (EF) compartment of the lymphoid tissue, with reduced homing to the follicular (F) site. This contributes to the majority of the virus being present in the follicle and represents a barrier to virus control. Using mathematical models, we investigate these dynamics. Two models are analyzed. The first assumes that CTL can only become stimulated and expand in the extrafollicular compartment, with migration accounting for the presence of CTL in the follicle. In the second model, follicular CTL can also undergo antigen-induced expansion. Consistent with experimental data, both models predict increased virus compartmentalization in the presence of stronger CTL responses and lower virus loads, and a more pronounced rise of extrafollicular compared to follicular virus during CD8 cell depletion experiments. The models, however, differ in other aspects. The follicular expansion model results in dynamics that promote the clearance of productive infection in the extrafollicular site, with any productively infected cells found being the result of immigration from the follicle. This is not observed in the model without follicular CTL expansion. The models further predict different consequences of introducing engineered, follicular-homing CTL, which has been proposed as a therapeutic means to improve virus control. Without follicular CTL expansion, this is predicted to result in a reduction of virus load in both compartments. The follicular CTL expansion model, however, makes the counter-intuitive prediction that addition of F-homing CTL not only results in a reduction of follicular virus load, but also in an increase in extrafollicular virus replication. These predictions remain to be experimentally tested, which will be relevant for distinguishing between models and for understanding how therapeutic introduction of F-homing CTL might impact the overall dynamics of the infection.'),
(89284, 2018, 'plos', 'A multi-scale layer-resolved spiking network model of resting-state dynamics in macaque visual cortical areas', 'Schmidt, Maximilian|Bakker, Rembrandt|Shen, Kelly|Bezgin, Gleb|Diesmann, Markus|van Albada, Sacha Jennifer', 'Laboratory for Neural Coding and Brain Computing, RIKEN Center for Brain Science, Wako-Shi, Saitama, Japan.|Institute of Neuroscience and Medicine (INM-6) and Institute for Advanced Simulation (IAS-6) and JARA Institute Brain Structure-Function Relationships (INM-10), Jülich Research Centre, Jülich, Germany.|Rotman Research Institute, Baycrest, Toronto, Ontario, Canada.|McConnell Brain Imaging Centre, Montreal Neurological Institute, McGill University, Montreal, Canada.|Institute of Neuroscience and Medicine (INM-6) and Institute for Advanced Simulation (IAS-6) and JARA Institute Brain Structure-Function Relationships (INM-10), Jülich Research Centre, Jülich, Germany.|Institute of Neuroscience and Medicine (INM-6) and Institute for Advanced Simulation (IAS-6) and JARA Institute Brain Structure-Function Relationships (INM-10), Jülich Research Centre, Jülich, Germany.', 'Japan|Germany|Canada|Canada|Germany|Germany', 8, 'Action Potentials|Algorithms|Animals|Computational Biology|Electroencephalography|Implantable Neurostimulators|Macaca|Male|Models, Neurological|Neurons|Photic Stimulation|Sleep|Visual Cortex', 'Journal Article', '10.1371/journal.pcbi.1006359', '30335761', 'Cortical activity has distinct features across scales, from the spiking statistics of individual cells to global resting-state networks. We here describe the first full-density multi-area spiking network model of cortex, using macaque visual cortex as a test system. The model represents each area by a microcircuit with area-specific architecture and features layer- and population-resolved connectivity between areas. Simulations reveal a structured asynchronous irregular ground state. In a metastable regime, the network reproduces spiking statistics from electrophysiological recordings and cortico-cortical interaction patterns in fMRI functional connectivity under resting-state conditions. Stable inter-area propagation is supported by cortico-cortical synapses that are moderately strong onto excitatory neurons and stronger onto inhibitory neurons. Causal interactions depend on both cortical structure and the dynamical state of populations. Activity propagates mainly in the feedback direction, similar to experimental results associated with visual imagery and sleep. The model unifies local and large-scale accounts of cortex, and clarifies how the detailed connectivity of cortex shapes its dynamics on multiple scales. Based on our simulations, we hypothesize that in the spontaneous condition the brain operates in a metastable regime where cortico-cortical projections target excitatory and inhibitory populations in a balanced manner that produces substantial inter-area interactions while maintaining global stability.'),
(89285, 2018, 'plos', 'Modeling large fluctuations of thousands of clones during hematopoiesis: The role of stem cell self-renewal and bursty progenitor dynamics in rhesus macaque', 'Xu, Song|Kim, Sanggu|Chen, Irvin S Y|Chou, Tom', 'Center for Biomedical Informatics Research, Department of Medicine, Stanford University, Stanford, California, United States of America.|Department of Veterinary Biosciences, The Ohio State University, Columbus, Ohio, United States of America.|UCLA AIDS Institute and Department of Microbiology, Immunology, and Molecular Genetics, University of California, Los Angeles, Los Angeles, California, United States of America.|Center for Biomedical Informatics Research, Department of Medicine, Stanford University, Stanford, California, United States of America.', 'United States|United States|United States|United States', 0, 'Animals|Cell Differentiation|Cell Tracking|Clone Cells|Computational Biology|Hematopoiesis|Hematopoietic Stem Cells|Macaca mulatta|Models, Biological', 'Journal Article', '10.1371/journal.pcbi.1006489', '30335762', 'In a recent clone-tracking experiment, millions of uniquely tagged hematopoietic stem cells (HSCs) and progenitor cells were autologously transplanted into rhesus macaques and peripheral blood containing thousands of tags were sampled and sequenced over 14 years to quantify the abundance of hundreds to thousands of tags or clones. Two major puzzles of the data have been observed: consistent differences and massive temporal fluctuations of clone populations. The large sample-to-sample variability can lead clones to occasionally go extinct but resurrect themselves in subsequent samples. Although heterogeneity in HSC differentiation rates, potentially due to tagging, and random sampling of the animals blood and cellular demographic stochasticity might be invoked to explain these features, we show that random sampling cannot explain the magnitude of the temporal fluctuations. Moreover, we show through simpler neutral mechanistic and statistical models of hematopoiesis of tagged cells that a broad distribution in clone sizes can arise from stochastic HSC self-renewal instead of tag-induced heterogeneity. The very large clone population fluctuations that often lead to extinctions and resurrections can be naturally explained by a generation-limited proliferation constraint on the progenitor cells. This constraint leads to bursty cell population dynamics underlying the large temporal fluctuations. We analyzed experimental clone abundance data using a new statistic that counts clonal disappearances and provided least-squares estimates of two key model parameters in our model, the total HSC differentiation rate and the maximum number of progenitor-cell divisions.'),
(89286, 2018, 'plos', 'RAVEN 20: A versatile toolbox for metabolic network reconstruction and a case study on Streptomyces coelicolor', 'Wang, Hao|Marcišauskas, Simonas|Sánchez, Benjamín J|Domenzain, Iván|Hermansson, Daniel|Agren, Rasmus|Nielsen, Jens|Kerkhoven, Eduard J', 'Department of Biology and Biological Engineering, Chalmers University of Technology, Gothenburg, Sweden.|Department of Biology and Biological Engineering, Chalmers University of Technology, Gothenburg, Sweden.|Department of Biology and Biological Engineering, Chalmers University of Technology, Gothenburg, Sweden.|Department of Biology and Biological Engineering, Chalmers University of Technology, Gothenburg, Sweden.|Department of Biology and Biological Engineering, Chalmers University of Technology, Gothenburg, Sweden.|Department of Biology and Biological Engineering, National Bioinformatics Infrastructure Sweden, Science for Life Laboratory, Chalmers University of Technology, Gothenburg, Sweden.|Department of Biology and Biological Engineering, Chalmers University of Technology, Gothenburg, Sweden.|Department of Biology and Biological Engineering, Chalmers University of Technology, Gothenburg, Sweden.', 'Sweden|Sweden|Sweden|Sweden|Sweden|Sweden|Sweden|Sweden', 31, 'Computational Biology|Computer Simulation|Databases, Genetic|Gene Editing|Metabolic Networks and Pathways|Models, Genetic|Software|Streptomyces coelicolor', 'Journal Article', '10.1371/journal.pcbi.1006541', '30335785', 'RAVEN is a commonly used MATLAB toolbox for genome-scale metabolic model (GEM) reconstruction, curation and constraint-based modelling and simulation. Here we present RAVEN Toolbox 2.0 with major enhancements, including: (i) de novo reconstruction of GEMs based on the MetaCyc pathway database, (ii) a redesigned KEGG-based reconstruction pipeline, (iii) convergence of reconstructions from various sources, (iv) improved performance, usability, and compatibility with the COBRA Toolbox. Capabilities of RAVEN 2.0 are here illustrated through de novo reconstruction of GEMs for the antibiotic-producing bacterium Streptomyces coelicolor. Comparison of the automated de novo reconstructions with the iMK1208 model, a previously published high-quality S. coelicolor GEM, exemplifies that RAVEN 2.0 can capture most of the manually curated model. The generated de novo reconstruction is subsequently used to curate iMK1208 resulting in Sco4, the most comprehensive GEM of S. coelicolor, with increased coverage of both primary and secondary metabolism. This increased coverage allows the use of Sco4 to predict novel genome editing targets for optimized secondary metabolites production. As such, we demonstrate that RAVEN 2.0 can be used not only for de novo GEM reconstruction, but also for curating existing models based on up-to-date databases. Both RAVEN 2.0 and Sco4 are distributed through GitHub to facilitate usage and further development by the community (https://github.com/SysBioChalmers/RAVEN and https://github.com/SysBioChalmers/Streptomyces_coelicolor-GEM).'),
(89287, 2018, 'plos', 'Predicting how and when hidden neurons skew measured synaptic interactions', 'Brinkman, Braden A W|Rieke, Fred|Shea-Brown, Eric|Buice, Michael A', 'Department of Applied Mathematics, University of Washington, Seattle, Washington, United States of America.|Department of Physiology and Biophysics, University of Washington, Seattle, Washington, United States of America.|Department of Applied Mathematics, University of Washington, Seattle, Washington, United States of America.|Department of Applied Mathematics, University of Washington, Seattle, Washington, United States of America.', 'United States|United States|United States|United States', 7, 'Computational Biology|Models, Neurological|Models, Statistical|Neurons|Synapses', 'Journal Article', '10.1371/journal.pcbi.1006490', '30346943', 'A major obstacle to understanding neural coding and computation is the fact that experimental recordings typically sample only a small fraction of the neurons in a circuit. Measured neural properties are skewed by interactions between recorded neurons and the hidden portion of the network. To properly interpret neural data and determine how biological structure gives rise to neural circuit function, we thus need a better understanding of the relationships between measured effective neural properties and the true underlying physiological properties. Here, we focus on how the effective spatiotemporal dynamics of the synaptic interactions between neurons are reshaped by coupling to unobserved neurons. We find that the effective interactions from a pre-synaptic neuron r to a post-synaptic neuron r can be decomposed into a sum of the true interaction from r to r plus corrections from every directed path from r to r through unobserved neurons. Importantly, the resulting formula reveals when the hidden units have-or do not have-major effects on reshaping the interactions among observed neurons. As a particular example of interest, we derive a formula for the impact of hidden units in random networks with strong coupling-connection weights that scale with [Formula: see text], where N is the network size, precisely the scaling observed in recent experiments. With this quantitative relationship between measured and true interactions, we can study how network properties shape effective interactions, which properties are relevant for neural computations, and how to manipulate effective interactions.'),
(89288, 2018, 'plos', 'A k-mer-based method for the identification of phenotype-associated genomic biomarkers and predicting phenotypes of sequenced bacteria', 'Aun, Erki|Brauer, Age|Kisand, Veljo|Tenson, Tanel|Remm, Maido', 'Department of Bioinformatics, Institute of Molecular and Cell Biology, University of Tartu, Tartu, Estonia.|Department of Bioinformatics, Institute of Molecular and Cell Biology, University of Tartu, Tartu, Estonia.|Institute of Technology, University of Tartu, Tartu, Estonia.|Institute of Technology, University of Tartu, Tartu, Estonia.|Department of Bioinformatics, Institute of Molecular and Cell Biology, University of Tartu, Tartu, Estonia.', 'Estonia|Estonia|Estonia|Estonia|Estonia', 2, 'Algorithms|Bacteria|DNA, Bacterial|Genetic Markers|Genome, Bacterial|Genomics|Phenotype|Sequence Alignment|Sequence Analysis, DNA|Software', 'Journal Article', '10.1371/journal.pcbi.1006434', '30346947', 'We have developed an easy-to-use and memory-efficient method called PhenotypeSeeker that (a) identifies phenotype-specific k-mers, (b) generates a k-mer-based statistical model for predicting a given phenotype and (c) predicts the phenotype from the sequencing data of a given bacterial isolate. The method was validated on 167 Klebsiella pneumoniae isolates (virulence), 200 Pseudomonas aeruginosa isolates (ciprofloxacin resistance) and 459 Clostridium difficile isolates (azithromycin resistance). The phenotype prediction models trained from these datasets obtained the F1-measure of 0.88 on the K. pneumoniae test set, 0.88 on the P. aeruginosa test set and 0.97 on the C. difficile test set. The F1-measures were the same for assembled sequences and raw sequencing data, however, building the model from assembled genomes is significantly faster. On these datasets, the model building on a mid-range Linux server takes approximately 3 to 5 hours per phenotype if assembled genomes are used and 10 hours per phenotype if raw sequencing data are used. The phenotype prediction from assembled genomes takes less than one second per isolate. Thus, PhenotypeSeeker should be well-suited for predicting phenotypes from large sequencing datasets. PhenotypeSeeker is implemented in Python programming language, is open-source software and is available at GitHub (https://github.com/bioinfo-ut/PhenotypeSeeker/).'),
(89289, 2018, 'plos', 'Computationally-guided drug repurposing enables the discovery of kinase targets and inhibitors as new schistosomicidal agents', 'Giuliani, Sandra|Silva, Arthur C|Borba, Joyce V V B|Ramos, Pablo I P|Paveley, Ross A|Muratov, Eugene N|Andrade, Carolina Horta|Furnham, Nicholas', 'Department of Pathogen Molecular Biology, London School of Hygiene and Tropical Medicine, London, United Kingdom.|LabMol - Laboratory for Molecular Modeling and Drug Design, Faculdade de Farmácia, Universidade Federal de Goiás - UFG, Goiânia, Goiás, Brazil.|LabMol - Laboratory for Molecular Modeling and Drug Design, Faculdade de Farmácia, Universidade Federal de Goiás - UFG, Goiânia, Goiás, Brazil.|Instituto Gonçalo Moniz, Fundação Oswaldo Cruz (FIOCRUZ), Salvador, Bahia, Brazil.|Department of Pathogen Molecular Biology, London School of Hygiene and Tropical Medicine, London, United Kingdom.|Laboratory for Molecular Modeling, Division of Chemical Biology and Medicinal Chemistry, University of North Carolina, Chapel Hill, North Carolina, United States of America.|LabMol - Laboratory for Molecular Modeling and Drug Design, Faculdade de Farmácia, Universidade Federal de Goiás - UFG, Goiânia, Goiás, Brazil.|Department of Pathogen Molecular Biology, London School of Hygiene and Tropical Medicine, London, United Kingdom.', 'United Kingdom|Brazil|Brazil|Brazil|United Kingdom|United States|Brazil|United Kingdom', 1, 'Animals|Computational Biology|Databases, Protein|Drug Repositioning|Protein Kinase Inhibitors|Reproducibility of Results|Schistosoma|Schistosomicides', 'Journal Article', '10.1371/journal.pcbi.1006515', '30346968', 'The development of novel therapeutics is urgently required for diseases where existing treatments are failing due to the emergence of resistance. This is particularly pertinent for parasitic infections of the tropics and sub-tropics, referred to collectively as neglected tropical diseases, where the commercial incentives to develop new drugs are weak. One such disease is schistosomiasis, a highly prevalent acute and chronic condition caused by a parasitic helminth infection, with three species of the genus Schistosoma infecting humans. Currently, a single 40-year old drug, praziquantel, is available to treat all infective species, but its use in mass drug administration is leading to signs of drug-resistance emerging. To meet the challenge of developing new therapeutics against this disease, we developed an innovative computational drug repurposing pipeline supported by phenotypic screening. The approach highlighted several protein kinases as interesting new biological targets for schistosomiasis as they play an essential role in many parasites biological processes. Focusing on this target class, we also report the first elucidation of the kinome of Schistosoma japonicum, as well as updated kinomes of S. mansoni and S. haematobium. In comparison with the human kinome, we explored these kinomes to identify potential targets of existing inhibitors which are unique to Schistosoma species, allowing us to identify novel targets and suggest approved drugs that might inhibit them. These include previously suggested schistosomicidal agents such as bosutinib, dasatinib, and imatinib as well as new inhibitors such as vandetanib, saracatinib, tideglusib, alvocidib, dinaciclib, and 22 newly identified targets such as CHK1, CDC2, WEE, PAKA, MEK1. Additionally, the primary and secondary targets in Schistosoma of those approved drugs are also suggested, allowing for the development of novel therapeutics against this important yet neglected disease.'),
(89290, 2018, 'plos', 'An agent-based model for drug-radiation interactions in the tumour microenvironment: Hypoxia-activated prodrug SN30000 in multicellular tumour spheroids', 'Mao, Xinjian|McManaway, Sarah|Jaiswal, Jagdish K|Patel, Priyanka B|Wilson, William R|Hicks, Kevin O|Bogle, Gib', 'Auckland Cancer Society Research Centre, School of Medical Sciences, University of Auckland, Auckland, New Zealand.|Auckland Cancer Society Research Centre, School of Medical Sciences, University of Auckland, Auckland, New Zealand.|Auckland Cancer Society Research Centre, School of Medical Sciences, University of Auckland, Auckland, New Zealand.|Auckland Cancer Society Research Centre, School of Medical Sciences, University of Auckland, Auckland, New Zealand.|Auckland Cancer Society Research Centre, School of Medical Sciences, University of Auckland, Auckland, New Zealand.|Auckland Cancer Society Research Centre, School of Medical Sciences, University of Auckland, Auckland, New Zealand.|Maurice Wilkins Centre for Molecular Biodiscovery, University of Auckland, Auckland, New Zealand.', 'New Zealand|New Zealand|New Zealand|New Zealand|New Zealand|New Zealand|New Zealand', 7, 'Antineoplastic Agents|Cell Hypoxia|Cyclic N-Oxides|HCT116 Cells|Humans|Models, Biological|Prodrugs|Radiotherapy|Triazines|Tumor Microenvironment', 'Journal Article', '10.1371/journal.pcbi.1006469', '30356233', 'Multicellular tumour spheroids capture many characteristics of human tumour microenvironments, including hypoxia, and represent an experimentally tractable in vitro model for studying interactions between radiotherapy and anticancer drugs. However, interpreting spheroid data is challenging because of limited ability to observe cell fate within spheroids dynamically. To overcome this limitation, we have developed a hybrid continuum/agent-based model (ABM) for HCT116 tumour spheroids, parameterised using experimental models (monolayers and multilayers) in which reaction and diffusion can be measured directly. In the ABM, cell fate is simulated as a function of local oxygen, glucose and drug concentrations, determined by solving diffusion equations and intracellular reactions. The model is lattice-based, with cells occupying discrete locations on a 3D grid embedded within a coarser grid that encompasses the culture medium, separate solvers are employed for each grid. The generated concentration fields account for depletion in the medium and specify concentration-time profiles within the spheroid. Cell growth and survival are determined by intracellular oxygen and glucose concentrations, the latter based on direct measurement of glucose diffusion/reaction (in multilayers) for the first time. The ABM reproduces known features of spheroids including overall growth rate, its oxygen and glucose dependence, peripheral cell proliferation, central hypoxia and necrosis. We extended the ABM to describe in detail the hypoxia-dependent interaction between ionising radiation and a hypoxia-activated prodrug (SN30000), again using experimentally determined parameters, the model accurately simulated clonogenic cell killing in spheroids, while inclusion of reversible cell cycle delay was required to account for the marked spheroid growth delay after combined radiation and SN30000. This ABM of spheroid growth and response exemplifies the utility of integrating computational and experimental tools for investigating radiation/drug interactions, and highlights the critical importance of understanding oxygen, glucose and drug concentration gradients in interpreting activity of therapeutic agents in spheroid models.'),
(89291, 2018, 'plos', 'Dilution and titration of cell-cycle regulators may control cell size in budding yeast', 'Heldt, Frank S|Lunstone, Reece|Tyson, John J|Novák, Béla', 'Department of Biochemistry, University of Oxford, Oxford,United Kingdom.|Department of Biochemistry, University of Oxford, Oxford,United Kingdom.|Department of Biological Sciences, Virginia Tech, Blacksburg, VA, United States of America.|Department of Biochemistry, University of Oxford, Oxford,United Kingdom.', 'United Kingdom|United Kingdom|United States|United Kingdom', 0, 'Binding Sites|Cell Cycle|Cell Proliferation|Cell Size|Computational Biology|Genome, Fungal|Models, Biological|Saccharomyces cerevisiae|Saccharomycetales|Transcription Factors', 'Journal Article', '10.1371/journal.pcbi.1006548', '30356259', 'The size of a cell sets the scale for all biochemical processes within it, thereby affecting cellular fitness and survival. Hence, cell size needs to be kept within certain limits and relatively constant over multiple generations. However, how cells measure their size and use this information to regulate growth and division remains controversial. Here, we present two mechanistic mathematical models of the budding yeast (S. cerevisiae) cell cycle to investigate competing hypotheses on size control: inhibitor dilution and titration of nuclear sites. Our results suggest that an inhibitor-dilution mechanism, in which cell growth dilutes the transcriptional inhibitor Whi5 against the constant activator Cln3, can facilitate size homeostasis. This is achieved by utilising a positive feedback loop to establish a fixed size threshold for the Start transition, which efficiently couples cell growth to cell cycle progression. Yet, we show that inhibitor dilution cannot reproduce the size of mutants that alter the cells overall ploidy and WHI5 gene copy number. By contrast, size control through titration of Cln3 against a constant number of genomic binding sites for the transcription factor SBF recapitulates both size homeostasis and the size of these mutant strains. Moreover, this model produces an imperfect sizer behaviour in G1 and a timer in S/G2/M, which combine to yield an adder over the whole cell cycle, an observation recently made in experiments. Hence, our model connects these phenomenological data with the molecular details of the cell cycle, providing a systems-level perspective of budding yeast size control.');
INSERT INTO `papers` (`id`, `ano`, `journal`, `titulo`, `autores`, `afiliacao`, `pais`, `citacoes`, `palavra_chave`, `categorias`, `doi`, `pubmed`, `abstract`) VALUES
(89292, 2018, 'plos', 'Quantum chemistry reveals thermodynamic principles of redox biochemistry', 'Jinich, Adrian|Flamholz, Avi|Ren, Haniu|Kim, Sung-Jin|Sanchez-Lengeling, Benjamin|Cotton, Charles A R|Noor, Elad|Aspuru-Guzik, Alán|Bar-Even, Arren', 'Department of Chemistry and Chemical Biology, Harvard University, Cambridge, Massachusetts, United States of America.|Department of Molecular and Cellular Biology, University of California, Berkeley, Berkeley, California, United States of America.|Department of Chemistry and Chemical Biology, Harvard University, Cambridge, Massachusetts, United States of America.|Center for Systems Biology, Massachusetts General Hospital, Boston, Massachusetts, United States of America.|Department of Chemistry and Chemical Biology, Harvard University, Cambridge, Massachusetts, United States of America.|Max Planck Institute of Molecular Plant Physiology, Potsdam-Golm, Germany.|Institute of Molecular Systems Biology, ETH Zurich, Zürich, Switzerland.|Department of Chemistry and Department of Computer Science, University of Toronto, Ontario, Canada.|Max Planck Institute of Molecular Plant Physiology, Potsdam-Golm, Germany.', 'United States|United States|United States|United States|United States|Germany|Switzerland|Canada|Ger', 4, 'Biochemical Phenomena|Linear Models|Models, Chemical|NAD|NADP|Oxidation-Reduction|Thermodynamics', 'Journal Article', '10.1371/journal.pcbi.1006471', '30356318', 'Thermodynamics dictates the structure and function of metabolism. Redox reactions drive cellular energy and material flow. Hence, accurately quantifying the thermodynamics of redox reactions should reveal design principles that shape cellular metabolism. However, only few redox potentials have been measured, and mostly with inconsistent experimental setups. Here, we develop a quantum chemistry approach to calculate redox potentials of biochemical reactions and demonstrate our method predicts experimentally measured potentials with unparalleled accuracy. We then calculate the potentials of all redox pairs that can be generated from biochemically relevant compounds and highlight fundamental trends in redox biochemistry. We further address the question of why NAD/NADP are used as primary electron carriers, demonstrating how their physiological potential range fits the reactions of central metabolism and minimizes the concentration of reactive carbonyls. The use of quantum chemistry can revolutionize our understanding of biochemical phenomena by enabling fast and accurate calculation of thermodynamic values.'),
(89293, 2018, 'plos', 'Modeling sensory-motor decisions in natural behavior', 'Zhang, Ruohan|Zhang, Shun|Tong, Matthew H|Cui, Yuchen|Rothkopf, Constantin A|Ballard, Dana H|Hayhoe, Mary M', 'Department of Computer Science, The University of Texas at Austin, Austin, TX, USA.|Computer Science and Engineering, University of Michigan, Ann Arbor, MI, USA.|Center for Perceptual Systems, The University of Texas at Austin, Austin, TX, USA.|Department of Computer Science, The University of Texas at Austin, Austin, TX, USA.|Cognitive Science Center and Institute of Psychology, Technical University Darmstadt, Darmstadt, Germany.|Department of Computer Science, The University of Texas at Austin, Austin, TX, USA.|Center for Perceptual Systems, The University of Texas at Austin, Austin, TX, USA.', 'United States|United States|United States|United States|Germany|United States|United States', 0, 'Algorithms|Computational Biology|Decision Making|Humans|Models, Biological|Psychomotor Performance|Reinforcement (Psychology)|Reward', 'Journal Article', '10.1371/journal.pcbi.1006518', '30359364', 'Although a standard reinforcement learning model can capture many aspects of reward-seeking behaviors, it may not be practical for modeling human natural behaviors because of the richness of dynamic environments and limitations in cognitive resources. We propose a modular reinforcement learning model that addresses these factors. Based on this model, a modular inverse reinforcement learning algorithm is developed to estimate both the rewards and discount factors from human behavioral data, which allows predictions of human navigation behaviors in virtual reality with high accuracy across different subjects and with different tasks. Complex human navigation trajectories in novel environments can be reproduced by an artificial agent that is based on the modular model. This model provides a strategy for estimating the subjective value of actions and how they influence sensory-motor decisions in natural behavior.'),
(89294, 2018, 'plos', 'Representations of regular and irregular shapes by deep Convolutional Neural Networks, monkey inferotemporal neurons and human judgments', 'Kalfas, Ioannis|Vinken, Kasper|Vogels, Rufin', 'Laboratorium voor Neuro- en Psychofysiologie, Department of Neurosciences, KU Leuven, Leuven, Belgium.|Laboratorium voor Neuro- en Psychofysiologie, Department of Neurosciences, KU Leuven, Leuven, Belgium.|Laboratorium voor Neuro- en Psychofysiologie, Department of Neurosciences, KU Leuven, Leuven, Belgium.', 'Belgium|Belgium|Belgium', 0, 'Adult|Algorithms|Animals|Computational Biology|Humans|Macaca|Magnetic Resonance Imaging|Male|Neural Networks (Computer)|Neurons|Temporal Lobe', 'Journal Article', '10.1371/journal.pcbi.1006557', '30365485', 'Recent studies suggest that deep Convolutional Neural Network (CNN) models show higher representational similarity, compared to any other existing object recognition models, with macaque inferior temporal (IT) cortical responses, human ventral stream fMRI activations and human object recognition. These studies employed natural images of objects. A long research tradition employed abstract shapes to probe the selectivity of IT neurons. If CNN models provide a realistic model of IT responses, then they should capture the IT selectivity for such shapes. Here, we compare the activations of CNN units to a stimulus set of 2D regular and irregular shapes with the response selectivity of macaque IT neurons and with human similarity judgements. The shape set consisted of regular shapes that differed in nonaccidental properties, and irregular, asymmetrical shapes with curved or straight boundaries. We found that deep CNNs (Alexnet, VGG-16 and VGG-19) that were trained to classify natural images show response modulations to these shapes that were similar to those of IT neurons. Untrained CNNs with the same architecture than trained CNNs, but with random weights, demonstrated a poorer similarity than CNNs trained in classification. The difference between the trained and untrained CNNs emerged at the deep convolutional layers, where the similarity between the shape-related response modulations of IT neurons and the trained CNNs was high. Unlike IT neurons, human similarity judgements of the same shapes correlated best with the last layers of the trained CNNs. In particular, these deepest layers showed an enhanced sensitivity for straight versus curved irregular shapes, similar to that shown in human shape judgments. In conclusion, the representations of abstract shape similarity are highly comparable between macaque IT neurons and deep convolutional layers of CNNs that were trained to classify natural images, while human shape similarity judgments correlate better with the deepest layers.'),
(89295, 2018, 'plos', 'Structural and dynamic basis of substrate permissiveness in hydroxycinnamoyltransferase (HCT)', 'Chiang, Ying-Chih|Levsh, Olesya|Lam, Chun Kei|Weng, Jing-Ke|Wang, Yi', 'Department of Physics, The Chinese University of Hong Kong, Shatin, Hong Kong.|Whitehead Institute for Biomedical Research, Cambridge, Massachusetts, United States of America.|Department of Physics, The Chinese University of Hong Kong, Shatin, Hong Kong.|Whitehead Institute for Biomedical Research, Cambridge, Massachusetts, United States of America.|Department of Physics, The Chinese University of Hong Kong, Shatin, Hong Kong.', 'Hong Kong|United States|Hong Kong|United States|Hong Kong', 0, 'Acetophenones|Acyltransferases|Computational Biology|Crystallography, X-Ray|Plant Proteins|Selaginellaceae|Substrate Specificity', 'Journal Article', '10.1371/journal.pcbi.1006511', '30365487', 'Substrate permissiveness has long been regarded as the raw materials for the evolution of new enzymatic functions. In land plants, hydroxycinnamoyltransferase (HCT) is an essential enzyme of the phenylpropanoid metabolism. Although essential enzymes are normally associated with high substrate specificity, HCT can utilize a variety of non-native substrates. To examine the structural and dynamic basis of substrate permissiveness in this enzyme, we report the crystal structure of HCT from Selaginella moellendorffii and molecular dynamics (MD) simulations performed on five orthologous HCTs from several major lineages of land plants. Through altogether 17-xcexbcs MD simulations, we demonstrate the prevalent swing motion of an arginine handle on a submicrosecond timescale across all five HCTs, which plays a key role in native substrate recognition by these intrinsically promiscuous enzymes. Our simulations further reveal how a non-native substrate of HCT engages a binding site different from that of the native substrate and diffuses to reach the catalytic center and its co-substrate. By numerically solving the Smoluchowski equation, we show that the presence of such an alternative binding site, even when it is distant from the catalytic center, always increases the reaction rate of a given substrate. However, this increase is only significant for enzyme-substrate reactions heavily influenced by diffusion. In these cases, binding non-native substrates off-center provides an effective rationale to develop substrate permissiveness while maintaining the native functions of promiscuous enzymes.'),
(89296, 2018, 'plos', 'Computational discovery of dynamic cell line specific Boolean networks from multiplex time-course data', 'Razzaq, Misbah|Paulevé, Loïc|Siegel, Anne|Saez-Rodriguez, Julio|Bourdon, Jérémie|Guziolowski, Carito', 'Université de Nantes, Centrale Nantes, CNRS, Laboratoire des Sciences du Numérique de Nantes (LS2N UMR 6004), F-44000, Nantes, France.|LRI UMR8623, Université Paris-Sud, CNRS, Université Paris-Saclay, F-91400 Orsay, France.|Institut de Recherche en Informatique et Systèmes Aléatoires, Rennes, France.|RWTH-Aachen University, Faculty of Medicine, Joint Research Center for Computational Biomedicine, Aachen, Germany.|Université de Nantes, Centrale Nantes, CNRS, Laboratoire des Sciences du Numérique de Nantes (LS2N UMR 6004), F-44000, Nantes, France.|Université de Nantes, Centrale Nantes, CNRS, Laboratoire des Sciences du Numérique de Nantes (LS2N UMR 6004), F-44000, Nantes, France.', 'France|France|France|Germany|France|France', 2, 'Algorithms|Cell Line, Tumor|Humans|Models, Biological|Neoplasms|Phosphoproteins|Protein Interaction Maps|Proteomics|Signal Transduction', 'Journal Article', '10.1371/journal.pcbi.1006538', '30372442', 'Protein signaling networks are static views of dynamic processes where proteins go through many biochemical modifications such as ubiquitination and phosphorylation to propagate signals that regulate cells and can act as feed-back systems. Understanding the precise mechanisms underlying protein interactions can elucidate how signaling and cell cycle progression occur within cells in different diseases such as cancer. Large-scale protein signaling networks contain an important number of experimentally verified protein relations but lack the capability to predict the outcomes of the system, and therefore to be trained with respect to experimental measurements. Boolean Networks (BNs) are a simple yet powerful framework to study and model the dynamics of the protein signaling networks. While many BN approaches exist to model biological systems, they focus mainly on system properties, and few exist to integrate experimental data in them. In this work, we show an application of a method conceived to integrate time series phosphoproteomic data into protein signaling networks. We use a large-scale real case study from the HPN-DREAM Breast Cancer challenge. Our efficient and parameter-free method combines logic programming and model-checking to infer a family of BNs from multiple perturbation time series data of four breast cancer cell lines given a prior protein signaling network. Because each predicted BN family is cell line specific, our method highlights commonalities and discrepancies between the four cell lines. Our models have a Root Mean Square Error (RMSE) of 0.31 with respect to the testing data, while the best performant method of this HPN-DREAM challenge had a RMSE of 0.47. To further validate our results, BNs are compared with the canonical mTOR pathway showing a comparable AUROC score (0.77) to the top performing HPN-DREAM teams. In addition, our approach can also be used as a complementary method to identify erroneous experiments. These results prove our methodology as an efficient dynamic model discovery method in multiple perturbation time course experimental data of large-scale signaling networks. The software and data are publicly available at https://github.com/misbahch6/caspo-ts.'),
(89297, 2018, 'plos', 'Predicting bioprocess targets of chemical compounds through integration of chemical-genetic and genetic interactions', 'Simpkins, Scott W|Nelson, Justin|Deshpande, Raamesh|Li, Sheena C|Piotrowski, Jeff S|Wilson, Erin H|Gebre, Abraham A|Safizadeh, Hamid|Okamoto, Reika|Yoshimura, Mami|Costanzo, Michael|Yashiroda, Yoko|Ohya, Yoshikazu|Osada, Hiroyuki|Yoshida, Minoru|Boone, Charles|Myers, Chad L', 'University of Minnesota-Twin Cities, Bioinformatics and Computational Biology Graduate Program, Minneapolis, Minnesota, United States of America.|University of Minnesota-Twin Cities, Bioinformatics and Computational Biology Graduate Program, Minneapolis, Minnesota, United States of America.|University of Minnesota-Twin Cities, Department of Computer Science and Engineering, Minneapolis, Minnesota, United States of America.|RIKEN Center for Sustainable Resource Science, Wako, Saitama, Japan.|RIKEN Center for Sustainable Resource Science, Wako, Saitama, Japan.|University of Minnesota-Twin Cities, Department of Computer Science and Engineering, Minneapolis, Minnesota, United States of America.|University of Tokyo, Department of Integrated Biosciences, Graduate School of Frontier Sciences, Kashiwa, Chiba, Japan.|University of Minnesota-Twin Cities, Department of Computer Science and Engineering, Minneapolis, Minnesota, United States of America.|RIKEN Center for Sustainable Resource Science, Wako, Saitama, Japan.|RIKEN Center for Sustainable Resource Science, Wako, Saitama, Japan.|University of Toronto, Donnelly Centre, Toronto, Ontario, Canada.|RIKEN Center for Sustainable Resource Science, Wako, Saitama, Japan.|University of Tokyo, Department of Integrated Biosciences, Graduate School of Frontier Sciences, Kashiwa, Chiba, Japan.|RIKEN Center for Sustainable Resource Science, Wako, Saitama, Japan.|RIKEN Center for Sustainable Resource Science, Wako, Saitama, Japan.|RIKEN Center for Sustainable Resource Science, Wako, Saitama, Japan.|University of Minnesota-Twin Cities, Bioinformatics and Computational Biology Graduate Program, Minneapolis, Minnesota, United States of America.', 'United States|United States|United States|Japan|Japan|United States|Japan|United States|Japan|Japan|', 0, 'Cell Cycle|Colchicine|Drug Discovery|Gene Regulatory Networks|Protein Multimerization|Reproducibility of Results|Small Molecule Libraries|Systems Biology|Tubulin|Tubulin Modulators|Yeasts', 'Journal Article', '10.1371/journal.pcbi.1006532', '30376562', 'Chemical-genetic interactions-observed when the treatment of mutant cells with chemical compounds reveals unexpected phenotypes-contain rich functional information linking compounds to their cellular modes of action. To systematically identify these interactions, an array of mutants is challenged with a compound and monitored for fitness defects, generating a chemical-genetic interaction profile that provides a quantitative, unbiased description of the cellular function(s) perturbed by the compound. Genetic interactions, obtained from genome-wide double-mutant screens, provide a key for interpreting the functional information contained in chemical-genetic interaction profiles. Despite the utility of this approach, integrative analyses of genetic and chemical-genetic interaction networks have not been systematically evaluated. We developed a method, called CG-TARGET (Chemical Genetic Translation via A Reference Genetic nETwork), that integrates large-scale chemical-genetic interaction screening data with a genetic interaction network to predict the biological processes perturbed by compounds. In a recent publication, we applied CG-TARGET to a screen of nearly 14,000 chemical compounds in Saccharomyces cerevisiae, integrating this dataset with the global S. cerevisiae genetic interaction network to prioritize over 1500 compounds with high-confidence biological process predictions for further study. We present here a formal description and rigorous benchmarking of the CG-TARGET method, showing that, compared to alternative enrichment-based approaches, it achieves similar or better accuracy while substantially improving the ability to control the false discovery rate of biological process predictions. Additional investigation of the compatibility of chemical-genetic and genetic interaction profiles revealed that one-third of observed chemical-genetic interactions contributed to the highest-confidence biological process predictions and that negative chemical-genetic interactions overwhelmingly formed the basis of these predictions. We also present experimental validations of CG-TARGET-predicted tubulin polymerization and cell cycle progression inhibitors. Our approach successfully demonstrates the use of genetic interaction networks in the high-throughput functional annotation of compounds to biological processes.'),
(89298, 2018, 'plos', 'Modeling and subtleties of K-Ras and Calmodulin interaction', 'Garrido, Eduardo|Lxc3xa1zaro, Juan|Jaumot, Montserrat|Agell, Neus|Rubio-Martinez, Jaime', 'Department of Materials Science and Physical Chemistry, Universitat de Barcelona, Institut de Recerca en Quxc3xadmica Texc3xb2rica i Computacional (IQTCUB), Barcelona, Spain.|Department de Biomedicina, Facultat de Medicina i Cixc3xa8ncies de la Salut, Universitat de Barcelona, IDIBAPS, Barcelona, Spain.|Department de Biomedicina, Facultat de Medicina i Cixc3xa8ncies de la Salut, Universitat de Barcelona, IDIBAPS, Barcelona, Spain.|Department de Biomedicina, Facultat de Medicina i Cixc3xa8ncies de la Salut, Universitat de Barcelona, IDIBAPS, Barcelona, Spain.|Department of Materials Science and Physical Chemistry, Universitat de Barcelona, Institut de Recerca en Quxc3xadmica Texc3xb2rica i Computacional (IQTCUB), Barcelona, Spain.', 'Spain|Spain|Spain|Spain|Spain', 4, 'Calmodulin|Humans|Molecular Dynamics Simulation|Protein Binding|Proto-Oncogene Proteins p21(ras)|Recombinant Proteins|Signal Transduction', 'Journal Article', '10.1371/journal.pcbi.1006552', '30376570', 'K-Ras, one of the most common small GTPases of the cell, still presents many riddles, despite the intense efforts to unveil its mysteries. Such is the case of its interaction with Calmodulin, a small acidic protein known for its role as a calcium ion sensor. Although the interaction between these two proteins and its biological implications have been widely studied, a model of their interaction has not been performed. In the present work we analyse this intriguing interaction by computational means. To do so, both conventional molecular dynamics and scaled molecular dynamics have been used. Our simulations suggest a model in which Calmodulin would interact with both the hypervariable region and the globular domain of K-Ras, using a lobe to interact with each of them. According to the presented model, the interface of helixes xcexb14 and xcexb15 of the globular domain of K-Ras would be relevant for the interaction with a lobe of Calmodulin. These results were also obtained when bringing the proteins together in a step wise manner with the umbrella sampling methodology. The computational results have been validated using SPR to determine the relevance of certain residues. Our results demonstrate that, when mutating residues of the xcexb14-xcexb15 interface described to be relevant for the interaction with Calmodulin, the interaction of the globular domain of K-Ras with Calmodulin diminishes. However, it is to be considered that our simulations indicate that the bulk of the interaction would fall on the hypervariable region of K-Ras, as many more interactions are identified in said region. All in all our simulations present a suitable model in which K-Ras could interact with Calmodulin at membrane level using both its globular domain and its hypervariable region to stablish an interaction that leads to an altered signalling.'),
(89299, 2018, 'plos', 'Suboptimal community growth mediated through metabolite crossfeeding promotes species diversity in the gut microbiota', 'Henson, Michael A|Phalak, Poonam', 'Department of Chemical Engineering, University of Massachusetts, Amherst, Massachusetts, USA.|Department of Chemical Engineering, University of Massachusetts, Amherst, Massachusetts, USA.', 'United States|United States', 6, 'Bacteria|Computational Biology|Gastrointestinal Microbiome|Humans|Models, Biological', 'Journal Article', '10.1371/journal.pcbi.1006558', '30376571', 'The gut microbiota represent a highly complex ecosystem comprised of approximately 1000 species that forms a mutualistic relationship with the human host. A critical attribute of the microbiota is high species diversity, which provides system robustness through overlapping and redundant metabolic capabilities. The gradual loss of bacterial diversity has been associated with a broad array of gut pathologies and diseases including malnutrition, obesity, diabetes and inflammatory bowel disease. We formulated an in silico community model of the gut microbiota by combining genome-scale metabolic reconstructions of 28 representative species to explore the relationship between species diversity and community growth. While the individual species offered a broad range of metabolic capabilities, communities optimized for maximal growth on simulated Western and high-fiber diets had low diversities and imbalances in short-chain fatty acid (SCFA) synthesis characterized by acetate overproduction. Community flux variability analysis performed with the 28-species model and a reduced 20-species model suggested that enhanced species diversity and more balanced SCFA production were achievable at suboptimal growth rates. We developed a simple method for constraining species abundances to sample the growth-diversity tradeoff and used the 20-species model to show that tradeoff curves for Western and high-fiber diets resembled Pareto-optimal surfaces. Compared to maximal growth solutions, suboptimal growth solutions were characterized by higher species diversity, more balanced SCFA synthesis and lower exchange rates of crossfed metabolites between more species. We hypothesized that modulation of crossfeeding relationships through host-microbiota interactions could be an important means for maintaining species diversity and suggest that community metabolic modeling approaches that allow multiobjective optimization of growth and diversity are needed for more realistic simulation of complex communities.'),
(89300, 2018, 'plos', 'Steered molecular dynamics simulations reveal critical residues for (un)binding of substrates, inhibitors and a product to the malarial M1 aminopeptidase', 'Moore, Daniel S|Brines, Conor|Jewhurst, Heather|Dalton, John P|Tikhonova, Irina G', 'School of Pharmacy, Medical Biology Centre, Queens University Belfast, Belfast, Northern Ireland, United Kingdom.|School of Biological Sciences, Medical Biology Centre, Queens University Belfast, Belfast, Northern Ireland, United Kingdom.|School of Biological Sciences, Medical Biology Centre, Queens University Belfast, Belfast, Northern Ireland, United Kingdom.|School of Biological Sciences, Medical Biology Centre, Queens University Belfast, Belfast, Northern Ireland, United Kingdom.|School of Pharmacy, Medical Biology Centre, Queens University Belfast, Belfast, Northern Ireland, United Kingdom.', 'United Kingdom|United Kingdom|United Kingdom|United Kingdom|United Kingdom', 0, 'Aminopeptidases|Catalytic Domain|Computational Biology|Molecular Dynamics Simulation|Plasmodium falciparum|Protozoan Proteins', 'Journal Article', '10.1371/journal.pcbi.1006525', '30379805', 'Malaria is a life-threatening disease spread by mosquitoes. Plasmodium falciparum M1 alanyl aminopeptidase (PfM1-AAP) is a promising target for the treatment of malaria. The recently solved crystal structures of PfM1-AAP revealed that the buried active site can be accessed through two channel openings: a short N-terminal channel with the length of 8 Å and a long C-terminal channel with the length of 30 Å. It is unclear, however, how substrates and inhibitors migrate to the active site and a product of cleavage leaves. Here, we study the molecular mechanism of substrate and inhibitor migration to the active site and the product release using steered molecular dynamics simulations. We identified a stepwise passage of substrates and inhibitors in the C-terminal channel of PfM1-AAP, involving (I) ligand recognition at the opening of the channel, (II) ionic translation to the water reservoir, (III) ligand reorientation in the water reservoir and (IV) passage in a suitable conformation into the active site. Endorsed by enzymatic analysis of functional recombinant PfM1-AAP and mutagenesis studies, our novel ligand-residue binding network analysis has identified the functional residues controlling ligand migration within the C-terminal channel of PfM1-AAP. Furthermore, from unbinding simulations of the Arg product we propose a charge repulsion as the driving force to expel the product out from the N-terminal channel of PfM1-AAP. Our work paves the way towards the design of a novel class of PfM1-AAP inhibitors based on preventing substrate entry to the active site.'),
(89301, 2018, 'plos', 'A Pareto approach to resolve the conflict between information gain and experimental costs: Multiple-criteria design of carbon labeling experiments', 'Nöh, Katharina|Niedenführ, Sebastian|Beyß, Martin|Wiechert, Wolfgang', 'Institute of Bio- and Geosciences, IBG-1: Biotechnology, Forschungszentrum Jülich GmbH, Jülich, Germany.|Institute of Bio- and Geosciences, IBG-1: Biotechnology, Forschungszentrum Jülich GmbH, Jülich, Germany.|Institute of Bio- and Geosciences, IBG-1: Biotechnology, Forschungszentrum Jülich GmbH, Jülich, Germany.|Institute of Bio- and Geosciences, IBG-1: Biotechnology, Forschungszentrum Jülich GmbH, Jülich, Germany.', 'Germany|Germany|Germany|Germany', 4, 'Algorithms|Carbon|Computational Biology|Metabolic Flux Analysis|Models, Biological|Models, Statistical|Penicillium chrysogenum|Research Design|Tandem Mass Spectrometry', 'Journal Article', '10.1371/journal.pcbi.1006533', '30379837', 'Science revolves around the best way of conducting an experiment to obtain insightful results. Experiments with maximal information content can be found by computational experimental design (ED) strategies that identify optimal conditions under which to perform the experiment. Several criteria have been proposed to measure the information content, each emphasizing different aspects of the design goal, i.e., reduction of uncertainty. Where experiments are complex or expensive, second sight is at the budget governing the achievable amount of information. In this context, the design objectives cost and information gain are often incommensurable, though dependent. By casting the ED task into a multiple-criteria optimization problem, a set of trade-off designs is derived that approximates the Pareto-frontier which is instrumental for exploring preferable designs. In this work, we present a computational methodology for multiple-criteria ED of information-rich experiments that accounts for virtually any set of design criteria. The methodology is implemented for the case of 13C metabolic flux analysis (MFA), which is arguably the most expensive type among the omics technologies, featuring dozens of design parameters (tracer composition, analytical platform, measurement selection etc.). Supported by an innovative visualization scheme, we demonstrate with two realistic showcases that the use of multiple criteria reveals deep insights into the conflicting interplay between information carriers and cost factors that are not amendable to single-objective ED. For instance, tandem mass spectrometry turns out as best-in-class with respect to information gain, while it delivers this information quality cheaper than the other, routinely applied analytical technologies. Therewith, our Pareto approach to ED offers the investigator great flexibilities in the conception phase of a study to balance costs and benefits.'),
(89302, 2018, 'plos', 'Molecular characterization of breast and lung tumors by integration of multiple data types with functional sparse-factor analysis', 'Bismeijer, Tycho|Canisius, Sander|Wessels, Lodewyk F A', 'Division of Molecular Carcinogenesis, Oncode Institute, The Netherlands Cancer Institute, Amsterdam, The Netherlands.|Division of Molecular Carcinogenesis, Oncode Institute, The Netherlands Cancer Institute, Amsterdam, The Netherlands.|Division of Molecular Carcinogenesis, Oncode Institute, The Netherlands Cancer Institute, Amsterdam, The Netherlands.', 'Netherlands|Netherlands|Netherlands', 1, 'Algorithms|Breast Neoplasms|Cluster Analysis|Computational Biology|Databases, Factual|Epithelial-Mesenchymal Transition|Female|Gene Expression Profiling|Humans|Lung Neoplasms', 'Journal Article', '10.1371/journal.pcbi.1006520', '30379847', 'Effective cancer treatment is crucially dependent on the identification of the biological processes that drive a tumor. However, multiple processes may be active simultaneously in a tumor. Clustering is inherently unsuitable to this task as it assigns a tumor to a single cluster. In addition, the wide availability of multiple data types per tumor provides the opportunity to profile the processes driving a tumor more comprehensively. Here we introduce Functional Sparse-Factor Analysis (funcSFA) to address these challenges. FuncSFA integrates multiple data types to define a lower dimensional space capturing the relevant variation. A tailor-made module associates biological processes with these factors. FuncSFA is inspired by iCluster, which we improve in several key aspects. First, we increase the convergence efficiency significantly, allowing the analysis of multiple molecular datasets that have not been pre-matched to contain only concordant features. Second, FuncSFA does not assign tumors to discrete clusters, but identifies the dominant driver processes active in each tumor. This is achieved by a regression of the factors on the RNA expression data followed by a functional enrichment analysis and manual curation step. We apply FuncSFA to the TCGA breast and lung datasets. We identify EMT and Immune processes common to both cancer types. In the breast cancer dataset we recover the known intrinsic subtypes and identify additional processes. These include immune infiltration and EMT, and processes driven by copy number gains on the 8q chromosome arm. In lung cancer we recover the major types (adenocarcinoma and squamous cell carcinoma) and processes active in both of these types. These include EMT, two immune processes, and the activity of the NFE2L2 transcription factor. We validate the breast cancer findings on the METABRIC set and demonstrate the translatability of the TCGA breast cancer factors to METABRIC. In summary, FuncSFA is a robust method to perform discovery of key driver processes in a collection of tumors through unsupervised integration of multiple molecular data types and functional annotation.'),
(89303, 2018, 'plos', 'Active dendrites regulate the spatiotemporal spread of signaling microdomains', 'Basak, Reshma|Narayanan, Rishikesh', 'Cellular Neurophysiology Laboratory, Molecular Biophysics Unit, Indian Institute of Science, Bangalore, India.|Cellular Neurophysiology Laboratory, Molecular Biophysics Unit, Indian Institute of Science, Bangalore, India.', 'India|India', 0, 'Action Potentials|Animals|Calcium Channels, T-Type|Calcium-Calmodulin-Dependent Protein Kinase Type 2|Dendrites|Humans|Ion Channel Gating|Phosphorylation|Potassium Channels|Protein Domains|Protein Phosphatase 1|Pyramidal Cells|Receptors, N-Methyl-D-Aspartate|Signal Transduction|Synapses', 'Journal Article', '10.1371/journal.pcbi.1006485', '30383745', 'Microdomains that emerge from spatially constricted spread of biochemical signaling components play a central role in several neuronal computations. Although dendrites, endowed with several voltage-gated ion channels, form a prominent structural substrate for microdomain physiology, it is not known if these channels regulate the spatiotemporal spread of signaling microdomains. Here, we employed a multiscale, morphologically realistic, conductance-based model of the hippocampal pyramidal neuron that accounted for experimental details of electrical and calcium-dependent biochemical signaling. We activated synaptic N-Methyl-d-Aspartate receptors through theta-burst stimulation (TBS) or pairing (TBP) and assessed microdomain propagation along a signaling pathway that included calmodulin, calcium/calmodulin-dependent protein kinase II (CaMKII) and protein phosphatase 1. We found that the spatiotemporal spread of the TBS-evoked microdomain in phosphorylated CaMKII (pCaMKII) was amplified in comparison to that of the corresponding calcium microdomain. Next, we assessed the role of two dendritically expressed inactivating channels, one restorative (A-type potassium) and another regenerative (T-type calcium), by systematically varying their conductances. Whereas A-type potassium channels suppressed the spread of pCaMKII microdomains by altering the voltage response to TBS, T-type calcium channels enhanced this spread by modulating TBS-induced calcium influx without changing the voltage. Finally, we explored cross-dependencies of these channels with other model components, and demonstrated the heavy mutual interdependence of several biophysical and biochemical properties in regulating microdomains and their spread. Our conclusions unveil a pivotal role for dendritic voltage-gated ion channels in actively amplifying or suppressing biochemical signals and their spatiotemporal spread, with critical implications for clustered synaptic plasticity, robust information transfer and efficient neural coding.'),
(89304, 2018, 'plos', 'Efficient pedigree recording for fast population genetics simulation', 'Kelleher, Jerome|Thornton, Kevin R|Ashander, Jaime|Ralph, Peter L', 'Big Data Institute, University of Oxford, Oxford, United Kingdom.|Ecology and Evolutionary Biology, University of California, Irvine, Irvine, California, United States of America.|Ecology and Evolutionary Biology, University of California, Los Angeles, Los Angeles, United States of America.|Institute for Ecology and Evolution, University of Oregon, Eugene, Oregon, United States of America.', 'United Kingdom|United States|United States|United States', 22, 'Algorithms|Computational Biology|Computer Simulation|Gene Frequency|Genetic Variation|Genetics, Population|Genome|Genotype|Humans|Models, Genetic|Pedigree|Polymorphism, Genetic|Software', 'Journal Article', '10.1371/journal.pcbi.1006581', '30383757', 'In this paper we describe how to efficiently record the entire genetic history of a population in forwards-time, individual-based population genetics simulations with arbitrary breeding models, population structure and demography. This approach dramatically reduces the computational burden of tracking individual genomes by allowing us to simulate only those loci that may affect reproduction (those having non-neutral variants). The genetic history of the population is recorded as a succinct tree sequence as introduced in the software package msprime, on which neutral mutations can be quickly placed afterwards. Recording the results of each breeding event requires storage that grows linearly with time, but there is a great deal of redundancy in this information. We solve this storage problem by providing an algorithm to quickly simplify a tree sequence by removing this irrelevant history for a given set of genomes. By periodically simplifying the history with respect to the extant population, we show that the total storage space required is modest and overall large efficiency gains can be made over classical forward-time simulations. We implement a general-purpose framework for recording and simplifying genealogical data, which can be used to make simulations of any population model more efficient. We modify two popular forwards-time simulation frameworks to use this new approach and observe efficiency gains in large, whole-genome simulations of one to two orders of magnitude. In addition to speed, our method for recording pedigrees has several advantages: (1) All marginal genealogies of the simulated individuals are recorded, rather than just genotypes. (2) A population of N individuals with M polymorphic sites can be stored in O(N log N + M) space, making it feasible to store a simulations entire final generation as well as its history. (3) A simulation can easily be initialized with a more efficient coalescent simulation of deep history. The software for recording and processing tree sequences is named tskit.'),
(89305, 2018, 'plos', 'Motif-Aware PRALINE: Improving the alignment of motif regions', 'Dijkstra, Maurits|Bawono, Punto|Abeln, Sanne|Feenstra, K Anton|Fokkink, Wan|Heringa, Jaap', 'Department of Computer Science, Vrije Universiteit Amsterdam, Amsterdam, The Netherlands.|Department of Computer Science, Vrije Universiteit Amsterdam, Amsterdam, The Netherlands.|Department of Computer Science, Vrije Universiteit Amsterdam, Amsterdam, The Netherlands.|Department of Computer Science, Vrije Universiteit Amsterdam, Amsterdam, The Netherlands.|Department of Computer Science, Vrije Universiteit Amsterdam, Amsterdam, The Netherlands.|Department of Computer Science, Vrije Universiteit Amsterdam, Amsterdam, The Netherlands.', 'Netherlands|Netherlands|Netherlands|Netherlands|Netherlands|Netherlands', 0, 'Algorithms|Amino Acid Motifs|Amino Acid Sequence|Conserved Sequence|DNA|HIV-1|Proteins|Sequence Alignment|Sequence Homology, Amino Acid|env Gene Products, Human Immunodeficiency Virus', 'Journal Article', '10.1371/journal.pcbi.1006547', '30383764', 'Protein or DNA motifs are sequence regions which possess biological importance. These regions are often highly conserved among homologous sequences. The generation of multiple sequence alignments (MSAs) with a correct alignment of the conserved sequence motifs is still difficult to achieve, due to the fact that the contribution of these typically short fragments is overshadowed by the rest of the sequence. Here we extended the PRALINE multiple sequence alignment program with a novel motif-aware MSA algorithm in order to address this shortcoming. This method can incorporate explicit information about the presence of externally provided sequence motifs, which is then used in the dynamic programming step by boosting the amino acid substitution matrix towards the motif. The strength of the boost is controlled by a parameter, xcexb1. Using a benchmark set of alignments we confirm that a good compromise can be found that improves the matching of motif regions while not significantly reducing the overall alignment quality. By estimating xcexb1 on an unrelated set of reference alignments we find there is indeed a strong conservation signal for motifs. A number of typical but difficult MSA use cases are explored to exemplify the problems in correctly aligning functional sequence motifs and how the motif-aware alignment method can be employed to alleviate these problems.'),
(89306, 2018, 'plos', 'Demonstrating aspects of multiscale modeling by studying the permeation pathway of the human ZnT2 zinc transporter', 'Golan, Yarden|Alhadeff, Raphael|Glaser, Fabian|Ganoth, Assaf|Warshel, Arieh|Assaraf, Yehuda G', 'The Fred Wyszkowski Cancer Research Laboratory, Dept. of Biology, Technion-Israel Institute of Technology, Haifa, Israel.|Department of Chemistry, University of Southern California, Los Angeles, CA, United States of America.|Lorry I. Lokey Interdisciplinary Center for Life Sciences and Engineering, Technion-Israel Institute of Technology, Haifa, Israel.|The Interdisciplinary Center (IDC), Herzliya, Israel.|Department of Chemistry, University of Southern California, Los Angeles, CA, United States of America.|The Fred Wyszkowski Cancer Research Laboratory, Dept. of Biology, Technion-Israel Institute of Technology, Haifa, Israel.', 'Israel|United States|Israel|Israel|United States|Israel', 0, 'Cation Transport Proteins|Computational Biology|Deficiency Diseases|Homeostasis|Humans|Models, Theoretical|Monte Carlo Method|Mutagenesis, Site-Directed|Permeability|Zinc', 'Journal Article', '10.1371/journal.pcbi.1006503', '30388104', 'Multiscale modeling provides a very powerful means of studying complex biological systems. An important component of this strategy involves coarse-grained (CG) simplifications of regions of the system, which allow effective exploration of complex systems. Here we studied aspects of CG modeling of the human zinc transporter ZnT2. Zinc is an essential trace element with 10% of the proteins in the human proteome capable of zinc binding. Thus, zinc deficiency or impairment of zinc homeostasis disrupt key cellular functions. Mammalian zinc transport proceeds via two transporter families: ZnT and ZIP, however, little is known about the zinc permeation pathway through these transporters. As a step towards this end, we herein undertook comprehensive computational analyses employing multiscale techniques, focusing on the human zinc transporter ZnT2 and its bacterial homologue, YiiP. Energy calculations revealed a favorable pathway for zinc translocation via alternating access. We then identified key residues presumably involved in the passage of zinc ions through ZnT2 and YiiP, and functionally validated their role in zinc transport using site-directed mutagenesis of ZnT2 residues. Finally, we use a CG Monte Carlo simulation approach to sample the transition between the inward-facing and the outward-facing states. We present our structural models of the inward- and outward-facing conformations of ZnT2 as a blueprint prototype of the transporter conformations, including the putative permeation pathway and participating residues. The insights gained from this study may facilitate the delineation of the pathways of other zinc transporters, laying the foundations for the molecular basis underlying ion permeation. This may possibly facilitate the development of therapeutic interventions in pathological states associated with zinc deficiency and other disorders based on loss-of-function mutations in solute carriers.'),
(89307, 2018, 'plos', 'Modeling driver cells in developing neuronal networks', 'Luccioli, Stefano|Angulo-Garcia, David|Cossart, Rosa|Malvache, Arnaud|Módol, Laura|Sousa, Vitor Hugo|Bonifazi, Paolo|Torcini, Alessandro', 'CNR - Consiglio Nazionale delle Ricerche - Istituto dei Sistemi Complessi, Sesto Fiorentino, Italy.|Grupo de Modelado Computacional - Dinámica y Complejidad de Sistemas, Instituto de Matemáticas Aplicadas, Universidad de Cartagena, Cartagena de Indias, Colombia.|Aix Marseille Univ, INSERM, INMED, Marseille, France.|Aix Marseille Univ, INSERM, INMED, Marseille, France.|Aix Marseille Univ, INSERM, INMED, Marseille, France.|Aix Marseille Univ, INSERM, INMED, Marseille, France.|Biocruces Health Research Institute, Bilbao, Vizcaya, Spain.|CNR - Consiglio Nazionale delle Ricerche - Istituto dei Sistemi Complessi, Sesto Fiorentino, Italy.', 'Italy|Colombia|France|France|France|France|Spain|Italy', 2, 'Brain|Humans|Models, Neurological|Nerve Net|Neurogenesis|Neurons|Synapses', 'Journal Article', '10.1371/journal.pcbi.1006551', '30388120', 'Spontaneous emergence of synchronized population activity is a characteristic feature of developing brain circuits. Recent experiments in the developing neo-cortex showed the existence of driver cells able to impact the synchronization dynamics when single-handedly stimulated. We have developed a spiking network model capable to reproduce the experimental results, thus identifying two classes of driver cells: functional hubs and low functionally connected (LC) neurons. The functional hubs arranged in a clique orchestrated the synchronization build-up, while the LC drivers were lately or not at all recruited in the synchronization process. Notwithstanding, they were able to alter the network state when stimulated by modifying the temporal activation of the functional clique or even its composition. LC drivers can lead either to higher population synchrony or even to the arrest of population dynamics, upon stimulation. Noticeably, some LC driver can display both effects depending on the received stimulus. We show that in the model the presence of inhibitory neurons together with the assumption that younger cells are more excitable and less connected is crucial for the emergence of LC drivers. These results provide a further understanding of the structural-functional mechanisms underlying synchronized firings in developing circuits possibly related to the coordinated activity of cell assemblies in the adult brain.'),
(89308, 2018, 'plos', 'Prediction and classification in equation-free collective motion dynamics', 'Fujii, Keisuke|Kawasaki, Takeshi|Inaba, Yuki|Kawahara, Yoshinobu', 'Center for Advanced Intelligence Project, Institute of Physical and Chemical Research (RIKEN), Osaka, JAPAN.|Department of Physics, Nagoya University, Nagoya, Aichi, JAPAN.|Japan Institute of Sports Sciences, Tokyo, JAPAN.|Center for Advanced Intelligence Project, Institute of Physical and Chemical Research (RIKEN), Osaka, JAPAN.', '-|-|Japan|-', 0, 'Algorithms|Group Processes|Humans|Models, Biological|Motion|Nonlinear Dynamics|Sports', 'Journal Article', '10.1371/journal.pcbi.1006545', '30395600', 'Modeling the complex collective behavior is a challenging issue in several material and life sciences. The collective motion has been usually modeled by simple interaction rules and explained by global statistics. However, it remains difficult to bridge the gap between the dynamic properties of the complex interaction and the emerging group-level functions. Here we introduce decomposition methods to directly extract and classify the latent global dynamics of nonlinear dynamical systems in an equation-free manner, even including complex interaction in few data dimensions. We first verified that the basic decomposition method can extract and discriminate the dynamics of a well-known rule-based fish-schooling (or bird-flocking) model. The method extracted different temporal frequency modes with spatial interaction coherence among three distinct emergent motions, whereas these wave properties in multiple spatiotemporal scales showed similar dispersion relations. Second, we extended the basic method to map high-dimensional feature space for application to actual small-dimensional systems complexly changing the interaction rules. Using group sports human data, we classified the dynamics and predicted the group objective achievement. Our methods have a potential for classifying collective motions in various domains which obey in non-trivial dominance law known as active matters.');
INSERT INTO `papers` (`id`, `ano`, `journal`, `titulo`, `autores`, `afiliacao`, `pais`, `citacoes`, `palavra_chave`, `categorias`, `doi`, `pubmed`, `abstract`) VALUES
(89309, 2018, 'plos', 'Synthetic protein alignments by CCMgen quantify noise in residue-residue contact prediction', 'Vorberg, Susann|Seemayer, Stefan|Söding, Johannes', 'Quantitative and Computational Biology Group, Max-Planck Institute for Biophysical Chemistry, Göttingen, Germany.|Quantitative and Computational Biology Group, Max-Planck Institute for Biophysical Chemistry, Göttingen, Germany.|Quantitative and Computational Biology Group, Max-Planck Institute for Biophysical Chemistry, Göttingen, Germany.', 'Germany|Germany|Germany', 2, 'Algorithms|Amino Acid Sequence|Binding Sites|Entropy|Noise|Proteins|Sequence Alignment|Sequence Homology, Amino Acid', 'Journal Article', '10.1371/journal.pcbi.1006526', '30395601', 'Compensatory mutations between protein residues in physical contact can manifest themselves as statistical couplings between the corresponding columns in a multiple sequence alignment (MSA) of the protein family. Conversely, large coupling coefficients predict residue contacts. Methods for de-novo protein structure prediction based on this approach are becoming increasingly reliable. Their main limitation is the strong systematic and statistical noise in the estimation of coupling coefficients, which has so far limited their application to very large protein families. While most research has focused on improving predictions by adding external information, little progress has been made to improve the statistical procedure at the core, because our lack of understanding of the sources of noise poses a major obstacle. First, we show theoretically that the expectation value of the coupling score assuming no coupling is proportional to the product of the square roots of the column entropies, and we propose a simple entropy bias correction (EntC) that subtracts out this expectation value. Second, we show that the average product correction (APC) includes the correction of the entropy bias, partly explaining its success. Third, we have developed CCMgen, the first method for simulating protein evolution and generating realistic synthetic MSAs with pairwise statistical residue couplings. Fourth, to learn exact statistical models that reliably reproduce observed alignment statistics, we developed CCMpredPy, an implementation of the persistent contrastive divergence (PCD) method for exact inference. Fifth, we demonstrate how CCMgen and CCMpredPy can facilitate the development of contact prediction methods by analysing the systematic noise contributions from phylogeny and entropy. Using the entropy bias correction, we can disentangle both sources of noise and find that entropy contributes roughly twice as much noise as phylogeny.'),
(89310, 2018, 'plos', 'Chromatin remodelers couple inchworm motion with twist-defect formation to slide nucleosomal DNA', 'Brandani, Giovanni B|Takada, Shoji', 'Department of Biophysics, Graduate School of Science, Kyoto University, Kyoto, Japan.|Department of Biophysics, Graduate School of Science, Kyoto University, Kyoto, Japan.', 'Japan|Japan', 0, 'Adenosine Triphosphatases|Adenosine Triphosphate|Chromatin Assembly and Disassembly|DNA|Molecular Dynamics Simulation|Mutation|Nucleosomes|Saccharomyces cerevisiae Proteins|Static Electricity|Transcription Factors', 'Journal Article', '10.1371/journal.pcbi.1006512', '30395604', 'ATP-dependent chromatin remodelers are molecular machines that control genome organization by repositioning, ejecting, or editing nucleosomes, activities that confer them essential regulatory roles on gene expression and DNA replication. Here, we investigate the molecular mechanism of active nucleosome sliding by means of molecular dynamics simulations of the Snf2 remodeler translocase in complex with a nucleosome. During its inchworm motion driven by ATP consumption, the translocase overwrites the original nucleosome energy landscape via steric and electrostatic interactions to induce sliding of nucleosomal DNA unidirectionally. The sliding is initiated at the remodeler binding location via the generation of a pair of twist defects, which then spontaneously propagate to complete sliding throughout the entire nucleosome. We also reveal how remodeler mutations and DNA sequence control active nucleosome repositioning, explaining several past experimental observations. These results offer a detailed mechanistic picture of remodeling important for the complete understanding of these key biological processes.'),
(89311, 2018, 'plos', 'Modulation of voltage-dependent K+ conductances in photoreceptors trades off investment in contrast gain for bandwidth', 'Heras, Francisco J H|Vähäsöyrinki, Mikko|Niven, Jeremy E', 'Department of Zoology, University of Cambridge, Cambridge, UK.|Sensapex Ltd, Oulu, Finland.|School of Life Sciences, University of Sussex, Falmer, Brighton, UK.', 'United Kingdom|Finland|United Kingdom', 1, 'Action Potentials|Animals|Computer Simulation|Drosophila melanogaster|Ion Transport|Light|Membrane Potentials|Models, Neurological|Neurons|Photons|Photoreceptor Cells, Invertebrate|Potassium Channels', 'Journal Article', '10.1371/journal.pcbi.1006566', '30399147', 'Modulation is essential for adjusting neurons to prevailing conditions and differing demands. Yet understanding how modulators adjust neuronal properties to alter information processing remains unclear, as is the impact of neuromodulation on energy consumption. Here we combine two computational models, one Hodgkin-Huxley type and the other analytic, to investigate the effects of neuromodulation upon Drosophila melanogaster photoreceptors. Voltage-dependent K+ conductances in these photoreceptors: (i) activate upon depolarisation to reduce membrane resistance and adjust bandwidth to functional requirements, (ii) produce negative feedback to increase bandwidth in an energy efficient way, (iii) produce shunt-peaking thereby increasing the membrane gain bandwidth product, and (iv) inactivate to amplify low frequencies. Through their effects on the voltage-dependent K+ conductances, three modulators, serotonin, calmodulin and PIP2, trade-off contrast gain against membrane bandwidth. Serotonin shifts the photoreceptor performance towards higher contrast gains and lower membrane bandwidths, whereas PIP2 and calmodulin shift performance towards lower contrast gains and higher membrane bandwidths. These neuromodulators have little effect upon the overall energy consumed by photoreceptors, instead they redistribute the energy invested in gain versus bandwidth. This demonstrates how modulators can shift neuronal information processing within the limitations of biophysics and energy consumption.'),
(89312, 2018, 'plos', 'A computational analysis of dynamic, multi-organ inflammatory crosstalk induced by endotoxin in mice', 'Zamora, Ruben|Korff, Sebastian|Mi, Qi|Barclay, Derek|Schimunek, Lukas|Zucca, Riccardo|Arsiwalla, Xerxes D|Simmons, Richard L|Verschure, Paul|Billiar, Timothy R|Vodovotz, Yoram', 'Department of Surgery, University of Pittsburgh, Pittsburgh, Pennsylvania, United States of America.|Department of Surgery, University of Pittsburgh, Pittsburgh, Pennsylvania, United States of America.|Center for Inflammation and Regenerative Modeling, McGowan Institute for Regenerative Medicine, University of Pittsburgh, Pittsburgh, Pennsylvania, United States of America.|Department of Surgery, University of Pittsburgh, Pittsburgh, Pennsylvania, United States of America.|Department of Surgery, University of Pittsburgh, Pittsburgh, Pennsylvania, United States of America.|SPECS, ETIC, Universitat Pompeu Fabra, Barcelona, Spain.|SPECS, ETIC, Universitat Pompeu Fabra, Barcelona, Spain.|Department of Surgery, University of Pittsburgh, Pittsburgh, Pennsylvania, United States of America.|SPECS, ETIC, Universitat Pompeu Fabra, Barcelona, Spain.|Department of Surgery, University of Pittsburgh, Pittsburgh, Pennsylvania, United States of America.|Department of Surgery, University of Pittsburgh, Pittsburgh, Pennsylvania, United States of America.', 'United States|United States|United States|United States|United States|Spain|Spain|United States|Spai', 1, 'Animals|Computational Biology|Cytokines|Endotoxins|Inflammation|Lipopolysaccharides|Liver|Male|Mice|Mice, Inbred C57BL|Mice, Knockout|Principal Component Analysis|Signal Transduction|Toll-Like Receptor 4|Tumor Necrosis Factor-alpha', 'Journal Article', '10.1371/journal.pcbi.1006582', '30399158', 'Bacterial lipopolysaccharide (LPS) induces an acute inflammatory response across multiple organs, primarily via Toll-like receptor 4 (TLR4). We sought to define novel aspects of the complex spatiotemporal dynamics of LPS-induced inflammation using computational modeling, with a special focus on the timing of pathological systemic spillover. An analysis of principal drivers of LPS-induced inflammation in the heart, gut, lung, liver, spleen, and kidney to assess organ-specific dynamics, as well as in the plasma (as an assessment of systemic spillover), was carried out using data on 20 protein-level inflammatory mediators measured over 0-48h in both C57BL/6 and TLR4-null mice. Using a suite of computational techniques, including a time-interval variant of Principal Component Analysis, we confirm key roles for cytokines such as tumor necrosis factor-xcexb1 and interleukin-17A, define a temporal hierarchy of organ-localized inflammation, and infer the point at which organ-localized inflammation spills over systemically. Thus, by employing a systems biology approach, we obtain a novel perspective on the time- and organ-specific components in the propagation of acute systemic inflammation.'),
(89313, 2018, 'plos', 'Putting benchmarks in their rightful place: The heart of computational biology', 'Peters, Bjoern|Brenner, Steven E|Wang, Edwin|Slonim, Donna|Kann, Maricel G', 'La Jolla Institute for Allergy and Immunology, La Jolla, California, United States of America.|Department of Plant and Microbial Biology, University of California, Berkeley, California, United States of America.|Cumming School of Medicine, University of Calgary, Calgary, Alberta, Canada.|Department of Computer Science and Genetics, Tufts University, Medford, Massachusetts, United States of America.|Department of Biological Sciences, University of Maryland, College Park, Maryland, United States of America.', 'United States|United States|Canada|United States|United States', 0, 'Algorithms|Area Under Curve|Computational Biology|Publications', 'Editorial', '10.1371/journal.pcbi.1006494', '30408027', 'Research in computational biology has given rise to a vast number of methods developed to solve scientific problems. For areas in which many approaches exist, researchers have a hard time deciding which tool to select to address a scientific challenge, as essentially all publications introducing a new method will claim better performance than all others. Not all of these claims can be correct. Equally, for this same reason, developers struggle to demonstrate convincingly that they created a new and superior algorithm or implementation. Moreover, the developer community often has difficulty discerning which new approaches constitute true scientific advances for the field. The obvious answer to this conundrum is to develop benchmarks-meaning standard points of reference that facilitate evaluating the performance of different tools-allowing both users and developers to compare multiple tools in an unbiased fashion.'),
(89314, 2018, 'plos', 'The Cultural Brain Hypothesis: How culture drives brain expansion, sociality, and life history', 'Muthukrishna, Michael|Doebeli, Michael|Chudek, Maciej|Henrich, Joseph', 'Department of Psychological and Behavioural Science, London School of Economics and Political Science, London, United Kingdom.|Department of Zoology / Department of Mathematics, University of British Columbia, Vancouver, British Columbia, Canada.|School of Human Evolution and Social Change, Arizona State University, Tempe, Arizona, United States of America.|Department of Human Evolutionary Biology, Harvard University, Cambridge, Massachusetts, United States of America.', 'United Kingdom|Canada|United States|United States', 13, 'Brain|Cultural Evolution|Humans|Learning|Models, Theoretical|Phylogeny|Social Behavior', 'Journal Article', '10.1371/journal.pcbi.1006504', '30408028', 'In the last few million years, the hominin brain more than tripled in size. Comparisons across evolutionary lineages suggest that this expansion may be part of a broader trend toward larger, more complex brains in many taxa. Efforts to understand the evolutionary forces driving brain expansion have focused on climatic, ecological, and social factors. Here, building on existing research on learning, we analytically and computationally model the predictions of two closely related hypotheses: The Cultural Brain Hypothesis and the Cumulative Cultural Brain Hypothesis. The Cultural Brain Hypothesis posits that brains have been selected for their ability to store and manage information, acquired through asocial or social learning. The model of the Cultural Brain Hypothesis reveals relationships between brain size, group size, innovation, social learning, mating structures, and the length of the juvenile period that are supported by the existing empirical literature. From this model, we derive a set of predictions-the Cumulative Cultural Brain Hypothesis-for the conditions that favor an autocatalytic take-off characteristic of human evolution. This narrow evolutionary pathway, created by cumulative cultural evolution, may help explain the rapid expansion of human brains and other aspects of our species life history and psychology.'),
(89315, 2018, 'plos', 'A benchmark driven guide to binding site comparison: An exhaustive evaluation using tailor-made data sets (ProSPECCTs)', 'Ehrt, Christiane|Brinkjost, Tobias|Koch, Oliver', 'Faculty of Chemistry and Chemical Biology, TU Dortmund University, Dortmund, Germany.|Faculty of Chemistry and Chemical Biology, TU Dortmund University, Dortmund, Germany.|Faculty of Chemistry and Chemical Biology, TU Dortmund University, Dortmund, Germany.', 'Germany|Germany|Germany', 8, 'Algorithms|Automation|Binding Sites|Datasets as Topic|Molecular Dynamics Simulation|Nuclear Magnetic Resonance, Biomolecular|Proteins', 'Comparative Study', '10.1371/journal.pcbi.1006483', '30408032', 'The automated comparison of protein-ligand binding sites provides useful insights into yet unexplored site similarities. Various stages of computational and chemical biology research can benefit from this knowledge. The search for putative off-targets and the establishment of polypharmacological effects by comparing binding sites led to promising results for numerous projects. Although many cavity comparison methods are available, a comprehensive analysis to guide the choice of a tool for a specific application is wanting. Moreover, the broad variety of binding site modeling approaches, comparison algorithms, and scoring metrics impedes this choice. Herein, we aim to elucidate strengths and weaknesses of binding site comparison methodologies. A detailed benchmark study is the only possibility to rationalize the selection of appropriate tools for different scenarios. Specific evaluation data sets were developed to shed light on multiple aspects of binding site comparison. An assembly of all applied benchmark sets (ProSPECCTs-Protein Site Pairs for the Evaluation of Cavity Comparison Tools) is made available for the evaluation and optimization of further and still emerging methods. The results indicate the importance of such analyses to facilitate the choice of a methodology that complies with the requirements of a specific scientific challenge.'),
(89316, 2018, 'plos', 'Systematically benchmarking peptide-MHC binding predictors: From synthetic to naturally processed epitopes', 'Zhao, Weilong|Sher, Xinwei', 'Global Research IT, Merck & Co., Inc., Boston, MA, United States of America.|Global Research IT, Merck & Co., Inc., Boston, MA, United States of America.', 'United States|United States', 27, 'Algorithms|Alleles|Cancer Vaccines|Datasets as Topic|Epitopes, T-Lymphocyte|Histocompatibility Antigens Class I|Histocompatibility Antigens Class II|Humans|Immunogenicity, Vaccine|Ligands|Machine Learning|Major Histocompatibility Complex|Peptides|Protein Binding|Reproducibility of Results|T-Lymphocytes', 'Journal Article', '10.1371/journal.pcbi.1006457', '30408041', 'A number of machine learning-based predictors have been developed for identifying immunogenic T-cell epitopes based on major histocompatibility complex (MHC) class I and II binding affinities. Rationally selecting the most appropriate tool has been complicated by the evolving training data and machine learning methods. Despite the recent advances made in generating high-quality MHC-eluted, naturally processed ligandome, the reliability of new predictors on these epitopes has yet to be evaluated. This study reports the latest benchmarking on an extensive set of MHC-binding predictors by using newly available, untested data of both synthetic and naturally processed epitopes. 32 human leukocyte antigen (HLA) class I and 24 HLA class II alleles are included in the blind test set. Artificial neural network (ANN)-based approaches demonstrated better performance than regression-based machine learning and structural modeling. Among the 18 predictors benchmarked, ANN-based mhcflurry and nn_align perform the best for MHC class I 9-mer and class II 15-mer predictions, respectively, on binding/non-binding classification (Area Under Curves = 0.911). NetMHCpan4 also demonstrated comparable predictive power. Our customization of mhcflurry to a pan-HLA predictor has achieved similar accuracy to NetMHCpan. The overall accuracy of these methods are comparable between 9-mer and 10-mer testing data. However, the top methods deliver low correlations between the predicted versus the experimental affinities for strong MHC binders. When used on naturally processed MHC-ligands, tools that have been trained on elution data (NetMHCpan4 and MixMHCpred) shows better accuracy than pure binding affinity predictor. The variability of false prediction rate is considerable among HLA types and datasets. Finally, structure-based predictor of Rosetta FlexPepDock is less optimal compared to the machine learning approaches. With our benchmarking of MHC-binding and MHC-elution predictors using a comprehensive metrics, a unbiased view for establishing best practice of T-cell epitope predictions is presented, facilitating future development of methods in immunogenomics.'),
(89317, 2018, 'plos', 'Correction: Assessment of ab initio models of protein complexes by molecular dynamics', 'PLOS Computational Biology Staff', 'Global Research IT, Merck & Co., Inc., Boston, MA, United States of America.', 'United States', 0, '-', 'Journal Article', '10.1371/journal.pcbi.1006598', '30412574', '[This corrects the article DOI: 10.1371/journal.pcbi.1006182.].'),
(89318, 2018, 'plos', 'Comparative structural dynamic analysis of GTPases', 'Li, Hongyang|Yao, Xin-Qiu|Grant, Barry J', 'Department of Computational Medicine and Bioinformatics, University of Michigan, Ann Arbor, MI, United States of America.|Department of Chemistry, Georgia State University, Atlanta, GA, United States of America.|Division of Biological Sciences, Section of Molecular Biology, University of California, San Diego, La Jolla, CA, United States of America.', 'United States|Georgia|United States', 6, 'Binding Sites|Crystallography, X-Ray|GTP Phosphohydrolases|Guanosine Diphosphate|Guanosine Triphosphate|Molecular Dynamics Simulation|Mutation|Nucleotides|Peptide Elongation Factor Tu|Principal Component Analysis|Protein Binding|Protein Conformation|Protein Domains|Signal Transduction|Transducin|ras Proteins', 'Comparative Study', '10.1371/journal.pcbi.1006364', '30412578', 'GTPases regulate a multitude of essential cellular processes ranging from movement and division to differentiation and neuronal activity. These ubiquitous enzymes operate by hydrolyzing GTP to GDP with associated conformational changes that modulate affinity for family-specific binding partners. There are three major GTPase superfamilies: Ras-like GTPases, heterotrimeric G proteins and protein-synthesizing GTPases. Although they contain similar nucleotide-binding sites, the detailed mechanisms by which these structurally and functionally diverse superfamilies operate remain unclear. Here we compare and contrast the structural dynamic mechanisms of each superfamily using extensive molecular dynamics (MD) simulations and subsequent network analysis approaches. In particular, dissection of the cross-correlations of atomic displacements in both the GTP and GDP-bound states of Ras, transducin and elongation factor EF-Tu reveals analogous dynamic features. This includes similar dynamic communities and subdomain structures (termed lobes). For all three proteins the GTP-bound state has stronger couplings between equivalent lobes. Network analysis further identifies common and family-specific residues mediating the state-specific coupling of distal functional sites. Mutational simulations demonstrate how disrupting these couplings leads to distal dynamic effects at the nucleotide-binding site of each family. Collectively our studies extend current understanding of GTPase allosteric mechanisms and highlight previously unappreciated similarities across functionally diverse families.'),
(89319, 2018, 'plos', 'Visual physiology of the layer 4 cortical circuit in silico', 'Arkhipov, Anton|Gouwens, Nathan W|Billeh, Yazan N|Gratiy, Sergey|Iyer, Ramakrishnan|Wei, Ziqiang|Xu, Zihao|Abbasi-Asl, Reza|Berg, Jim|Buice, Michael|Cain, Nicholas|da Costa, Nuno|de Vries, Saskia|Denman, Daniel|Durand, Severine|Feng, David|Jarsky, Tim|Lecoq, Jérôme|Lee, Brian|Li, Lu|Mihalas, Stefan|Ocker, Gabriel K|Olsen, Shawn R|Reid, R Clay|Soler-Llavina, Gilberto|Sorensen, Staci A|Wang, Quanxin|Waters, Jack|Scanziani, Massimo|Koch, Christof', 'Allen Institute for Brain Science, Seattle, Washington, United States of America.|Allen Institute for Brain Science, Seattle, Washington, United States of America.|Allen Institute for Brain Science, Seattle, Washington, United States of America.|Allen Institute for Brain Science, Seattle, Washington, United States of America.|Allen Institute for Brain Science, Seattle, Washington, United States of America.|Janelia Research Campus, Howard Hughes Medical Institute, Ashburn, Virginia, United States of America.|University of California San Diego, La Jolla, CA, United States of America.|Allen Institute for Brain Science, Seattle, Washington, United States of America.|Allen Institute for Brain Science, Seattle, Washington, United States of America.|Allen Institute for Brain Science, Seattle, Washington, United States of America.|Allen Institute for Brain Science, Seattle, Washington, United States of America.|Allen Institute for Brain Science, Seattle, Washington, United States of America.|Allen Institute for Brain Science, Seattle, Washington, United States of America.|Allen Institute for Brain Science, Seattle, Washington, United States of America.|Allen Institute for Brain Science, Seattle, Washington, United States of America.|Allen Institute for Brain Science, Seattle, Washington, United States of America.|Allen Institute for Brain Science, Seattle, Washington, United States of America.|Allen Institute for Brain Science, Seattle, Washington, United States of America.|Allen Institute for Brain Science, Seattle, Washington, United States of America.|Allen Institute for Brain Science, Seattle, Washington, United States of America.|Allen Institute for Brain Science, Seattle, Washington, United States of America.|Allen Institute for Brain Science, Seattle, Washington, United States of America.|Allen Institute for Brain Science, Seattle, Washington, United States of America.|Allen Institute for Brain Science, Seattle, Washington, United States of America.|Novartis Institutes for BioMedical Research, Cambridge, MA, United States of America.|Allen Institute for Brain Science, Seattle, Washington, United States of America.|Allen Institute for Brain Science, Seattle, Washington, United States of America.|Allen Institute for Brain Science, Seattle, Washington, United States of America.|Howard Hughes Medical Institute and Department of Physiology, University of California San Francisco, San Francisco, California, United States of America.|Allen Institute for Brain Science, Seattle, Washington, United States of America.', 'United States|United States|United States|United States|United States|United States|United States|Un', 16, 'Animals|Computer Simulation|Mice|Models, Neurological|Neurons|Synapses|Thalamus|Visual Cortex', 'Journal Article', '10.1371/journal.pcbi.1006535', '30419013', 'Despite advances in experimental techniques and accumulation of large datasets concerning the composition and properties of the cortex, quantitative modeling of cortical circuits under in-vivo-like conditions remains challenging. Here we report and publicly release a biophysically detailed circuit model of layer 4 in the mouse primary visual cortex, receiving thalamo-cortical visual inputs. The 45,000-neuron model was subjected to a battery of visual stimuli, and results were compared to published work and new in vivo experiments. Simulations reproduced a variety of observations, including effects of optogenetic perturbations. Critical to the agreement between responses in silico and in vivo were the rules of functional synaptic connectivity between neurons. Interestingly, after extreme simplification the model still performed satisfactorily on many measurements, although quantitative agreement with experiments suffered. These results emphasize the importance of functional rules of cortical wiring and enable a next generation of data-driven models of in vivo neural activity and computations.'),
(89320, 2018, 'plos', 'Functional mechanisms underlie the emergence of a diverse range of plasticity phenomena', 'Henderson, James A|Gong, Pulin', 'School of Physics, The University of Sydney, Sydney, NSW, Australia.|School of Physics, The University of Sydney, Sydney, NSW, Australia.', 'Australia|Australia', 2, 'Action Potentials|Algorithms|Animals|Cerebral Cortex|Computer Simulation|Excitatory Postsynaptic Potentials|Homeostasis|Humans|Learning|Mice|Models, Neurological|Nerve Net|Neural Networks (Computer)|Neuronal Plasticity|Neurons|Rats|Synapses', 'Journal Article', '10.1371/journal.pcbi.1006590', '30419014', 'Diverse plasticity mechanisms are orchestrated to shape the spatiotemporal dynamics underlying brain functions. However, why these plasticity rules emerge and how their dynamics interact with neural activity to give rise to complex neural circuit dynamics remains largely unknown. Here we show that both Hebbian and homeostatic plasticity rules emerge from a functional perspective of neuronal dynamics whereby each neuron learns to encode its own activity in the population activity, so that the activity of the presynaptic neuron can be decoded from the activity of its postsynaptic neurons. We explain how a range of experimentally observed plasticity phenomena with widely separated time scales emerge from learning this encoding function, including STDP and its frequency dependence, and metaplasticity. We show that when implemented in neural circuits, these plasticity rules naturally give rise to essential neural response properties, including variable neural dynamics with balanced excitation and inhibition, and approximately log-normal distributions of synaptic strengths, while simultaneously encoding a complex real-world visual stimulus. These findings establish a novel function-based account of diverse plasticity mechanisms, providing a unifying framework relating plasticity, dynamics and neural computation.'),
(89321, 2018, 'plos', 'Oscillations in working memory and neural binding: A mechanism for multiple memories and their interactions', 'Pina, Jason E|Bodner, Mark|Ermentrout, Bard', 'Department of Mathematics, University of Pittsburgh, Pittsburgh, Pennsylvania, United States of America.|MIND Research Institute, Irvine, California, United States of America.|Department of Mathematics, University of Pittsburgh, Pittsburgh, Pennsylvania, United States of America.', 'United States|United States|United States', 6, 'Brain|Cognition|Electroencephalography|Humans|Memory, Short-Term|Models, Neurological|Neurons', 'Journal Article', '10.1371/journal.pcbi.1006517', '30419015', 'Neural oscillations have been recorded and implicated in many different basic brain and cognitive processes. For example, oscillatory neural activity has been suggested to play a role in binding and in the maintenance of information in working memory. With respect to the latter, the majority of work has focused primarily on oscillations in terms of providing a code in working memory. However, oscillations may additionally play a fundamental role by enabling or facilitating essential properties and behaviors that neuronal networks must exhibit in order to produce functional working memory and the processes it supports, such as combining items in memory into bound objects or separating bound objects into distinct items. In the present work, we present a biologically plausible working memory model and demonstrate that specific types of stable oscillatory dynamics that arise may play critical roles in providing mechanisms for working memory and the cognitive functions that it supports. Specifically, these roles include (1) enabling a range of different types of binding, (2) both enabling and limiting capacities of bound and distinct items held active in working memory, and (3) facilitating transitions between active working memory states as required in cognitive function. Several key results arise within the examinations, such as the occurrence of different network capacities for working memory and binding, differences in processing times for transitions in working memory states, and the emergence of a combinatorially rich and complex range of oscillatory states that are sufficient to map onto a wide range of cognitive operations supported by working memory, such as variable binding, reasoning, and language. In particular, we show that these oscillatory states and their transitions can provide a specific instantiation of current established connectionist models in representing these functions. Finally, we further characterize the dependence of the relevant oscillatory solutions on certain critical parameters, including mutual inhibition and synaptic timescales.'),
(89322, 2018, 'plos', 'A regularity index for dendrites - local statistics of a neurons input space', 'Anton-Sanchez, Laura|Effenberger, Felix|Bielza, Concha|Larrañaga, Pedro|Cuntz, Hermann', 'Departamento de Inteligencia Artificial, Universidad Politécnica de Madrid, Madrid, Spain.|Ernst Strüngmann Institute (ESI) for Neuroscience in Cooperation with Max Planck Society, Frankfurt/Main, Germany.|Departamento de Inteligencia Artificial, Universidad Politécnica de Madrid, Madrid, Spain.|Departamento de Inteligencia Artificial, Universidad Politécnica de Madrid, Madrid, Spain.|Ernst Strüngmann Institute (ESI) for Neuroscience in Cooperation with Max Planck Society, Frankfurt/Main, Germany.', 'Spain|Germany|Spain|Spain|Germany', 0, 'Animals|Cell Size|Computational Biology|Computer Simulation|Connectome|Dendrites|Diptera|Image Processing, Computer-Assisted|Models, Neurological|Neuronal Plasticity|Neurons|Pattern Recognition, Automated|Software|Synapses', 'Journal Article', '10.1371/journal.pcbi.1006593', '30419016', 'Neurons collect their inputs from other neurons by sending out arborized dendritic structures. However, the relationship between the shape of dendrites and the precise organization of synaptic inputs in the neural tissue remains unclear. Inputs could be distributed in tight clusters, entirely randomly or else in a regular grid-like manner. Here, we analyze dendritic branching structures using a regularity index R, based on average nearest neighbor distances between branch and termination points, characterizing their spatial distribution. We find that the distributions of these points depend strongly on cell types, indicating possible fundamental differences in synaptic input organization. Moreover, R is independent of cell size and we find that it is only weakly correlated with other branching statistics, suggesting that it might reflect features of dendritic morphology that are not captured by commonly studied branching statistics. We then use morphological models based on optimal wiring principles to study the relation between input distributions and dendritic branching structures. Using our models, we find that branch point distributions correlate more closely with the input distributions while termination points in dendrites are generally spread out more randomly with a close to uniform distribution. We validate these model predictions with connectome data. Finally, we find that in spatial input distributions with increasing regularity, characteristic scaling relationships between branching features are altered significantly. In summary, we conclude that local statistics of input distributions and dendrite morphology depend on each other leading to potentially cell type specific branching features.'),
(89323, 2018, 'plos', 'Invasion and effective size of graph-structured populations', 'Giaimo, Stefano|Arranz, Jordi|Traulsen, Arne', 'Evolutionary Theory Department, Max Planck Institute for Evolutionary Biology, Plön, Germany.|Evolutionary Theory Department, Max Planck Institute for Evolutionary Biology, Plön, Germany.|Evolutionary Theory Department, Max Planck Institute for Evolutionary Biology, Plön, Germany.', 'Germany|Germany|Germany', 2, 'Biological Evolution|Computer Simulation|Models, Biological|Population Dynamics|Probability', 'Journal Article', '10.1371/journal.pcbi.1006559', '30419017', 'Population structure can strongly affect evolutionary dynamics. The most general way to describe population structures are graphs. An important observable on evolutionary graphs is the probability that a novel mutation spreads through the entire population. But what drives this spread of a mutation towards fixation? Here, we propose a novel way to understand the forces driving fixation by borrowing techniques from evolutionary demography to quantify the invasion fitness and the effective population size for different graphs. Our method is very general and even applies to weighted graphs with node dependent fitness. However, we focus on analytical results for undirected graphs with node independent fitness. The method will allow to conceptually integrate evolutionary graph theory with theoretical genetics of structured populations.'),
(89324, 2018, 'plos', 'Comparing Bayesian and non-Bayesian accounts of human confidence reports', 'Adler, William T|Ma, Wei Ji', 'Center for Neural Science, New York University, New York, NY, United States of America.|Center for Neural Science, New York University, New York, NY, United States of America.', 'United States|United States', 10, 'Adult|Bayes Theorem|Behavior|Decision Making|Female|Humans|Male|Models, Statistical|Normal Distribution|Observer Variation|Poisson Distribution|Probability|Uncertainty|Young Adult', 'Comparative Study', '10.1371/journal.pcbi.1006572', '30422974', 'Humans can meaningfully report their confidence in a perceptual or cognitive decision. It is widely believed that these reports reflect the Bayesian probability that the decision is correct, but this hypothesis has not been rigorously tested against non-Bayesian alternatives. We use two perceptual categorization tasks in which Bayesian confidence reporting requires subjects to take sensory uncertainty into account in a specific way. We find that subjects do take sensory uncertainty into account when reporting confidence, suggesting that brain areas involved in reporting confidence can access low-level representations of sensory uncertainty, a prerequisite of Bayesian inference. However, behavior is not fully consistent with the Bayesian hypothesis and is better described by simple heuristic models that use uncertainty in a non-Bayesian way. Both conclusions are robust to changes in the uncertainty manipulation, task, response modality, model comparison metric, and additional flexibility in the Bayesian model. Our results suggest that adhering to a rational account of confidence behavior may require incorporating implementational constraints.'),
(89325, 2018, 'plos', 'Moth olfactory receptor neurons adjust their encoding efficiency to temporal statistics of pheromone fluctuations', 'Levakova, Marie|Kostal, Lubomir|Monsempès, Christelle|Jacob, Vincent|Lucas, Philippe', 'Institute of Physiology of the Czech Academy of Sciences, Prague, Czech Republic.|Institute of Physiology of the Czech Academy of Sciences, Prague, Czech Republic.|Institute of Ecology and Environmental Sciences, INRA, Versailles, France.|Institute of Ecology and Environmental Sciences, INRA, Versailles, France.|Institute of Ecology and Environmental Sciences, INRA, Versailles, France.', '-|-|France|France|France', 2, 'Animals|Arthropod Antennae|Electrophysiological Phenomena|Male|Models, Statistical|Moths|Neurons, Afferent|Olfactory Pathways|Olfactory Receptor Neurons|Pheromones|Probability|Reproducibility of Results', 'Journal Article', '10.1371/journal.pcbi.1006586', '30422975', 'The efficient coding hypothesis predicts that sensory neurons adjust their coding resources to optimally represent the stimulus statistics of their environment. To test this prediction in the moth olfactory system, we have developed a stimulation protocol that mimics the natural temporal structure within a turbulent pheromone plume. We report that responses of antennal olfactory receptor neurons to pheromone encounters follow the temporal fluctuations in such a way that the most frequent stimulus timescales are encoded with maximum accuracy. We also observe that the average coding precision of the neurons adjusted to the stimulus-timescale statistics at a given distance from the pheromone source is higher than if the same encoding model is applied at a shorter, non-matching, distance. Finally, the coding accuracy profile and the stimulus-timescale distribution are related in the manner predicted by the information theory for the many-to-one convergence scenario of the moth peripheral sensory system.'),
(89326, 2018, 'plos', 'Inferring interaction partners from protein sequences using mutual information', 'Bitbol, Anne-Florence', 'Sorbonne Université, CNRS, Laboratoire Jean Perrin (UMR 8237), F-75005 Paris, France.', 'France', 8, 'Algorithms|Amino Acid Sequence|Computational Biology|Entropy|Evolution, Molecular|Models, Statistical|Protein Binding|Protein Conformation|Proteins|Sequence Alignment', 'Journal Article', '10.1371/journal.pcbi.1006401', '30422978', 'Functional protein-protein interactions are crucial in most cellular processes. They enable multi-protein complexes to assemble and to remain stable, and they allow signal transduction in various pathways. Functional interactions between proteins result in coevolution between the interacting partners, and thus in correlations between their sequences. Pairwise maximum-entropy based models have enabled successful inference of pairs of amino-acid residues that are in contact in the three-dimensional structure of multi-protein complexes, starting from the correlations in the sequence data of known interaction partners. Recently, algorithms inspired by these methods have been developed to identify which proteins are functional interaction partners among the paralogous proteins of two families, starting from sequence data alone. Here, we demonstrate that a slightly higher performance for partner identification can be reached by an approximate maximization of the mutual information between the sequence alignments of the two protein families. Our mutual information-based method also provides signatures of the existence of interactions between protein families. These results stand in contrast with structure prediction of proteins and of multi-protein complexes from sequence data, where pairwise maximum-entropy based global statistical models substantially improve performance compared to mutual information. Our findings entail that the statistical dependences allowing interaction partner prediction from sequence data are not restricted to the residue pairs that are in direct contact at the interface between the partner proteins.'),
(89327, 2018, 'plos', 'Bayesian phylodynamic inference with complex models', 'Volz, Erik M|Siveroni, Igor', 'Department of Infectious Disease Epidemiology and the MRC Centre for Global Infectious Disease Analysis, Imperial College London, London, United Kingdom.|Department of Infectious Disease Epidemiology and the MRC Centre for Global Infectious Disease Analysis, Imperial College London, London, United Kingdom.', 'United Kingdom|United Kingdom', 6, 'Africa, Western|Bayes Theorem|Computer Simulation|Epidemics|Genetics, Population|Hemorrhagic Fever, Ebola|Humans|Influenza, Human|Models, Theoretical|Phylogeny|Population Surveillance|Seasons|Software Design', 'Journal Article', '10.1371/journal.pcbi.1006546', '30422979', 'Population genetic modeling can enhance Bayesian phylogenetic inference by providing a realistic prior on the distribution of branch lengths and times of common ancestry. The parameters of a population genetic model may also have intrinsic importance, and simultaneous estimation of a phylogeny and model parameters has enabled phylodynamic inference of population growth rates, reproduction numbers, and effective population size through time. Phylodynamic inference based on pathogen genetic sequence data has emerged as useful supplement to epidemic surveillance, however commonly-used mechanistic models that are typically fitted to non-genetic surveillance data are rarely fitted to pathogen genetic data due to a dearth of software tools, and the theory required to conduct such inference has been developed only recently. We present a framework for coalescent-based phylogenetic and phylodynamic inference which enables highly-flexible modeling of demographic and epidemiological processes. This approach builds upon previous structured coalescent approaches and includes enhancements for computational speed, accuracy, and stability. A flexible markup language is described for translating parametric demographic or epidemiological models into a structured coalescent model enabling simultaneous estimation of demographic or epidemiological parameters and time-scaled phylogenies. We demonstrate the utility of these approaches by fitting compartmental epidemiological models to Ebola virus and Influenza A virus sequence data, demonstrating how important features of these epidemics, such as the reproduction number and epidemic curves, can be gleaned from genetic data. These approaches are provided as an open-source package PhyDyn for the BEAST2 phylogenetics platform.'),
(89328, 2018, 'plos', 'Cytoplasmic flows in starfish oocytes are fully determined by cortical contractions', 'Klughammer, Nils|Bischof, Johanna|Schnellbächer, Nikolas D|Callegari, Andrea|Lénárt, Péter|Schwarz, Ulrich S', 'Institute for Theoretical Physics and BioQuant, Heidelberg University, Heidelberg, Germany.|Cell Biology and Biophysics Unit, European Molecular Biology Laboratory (EMBL), Heidelberg, Germany.|Institute for Theoretical Physics and BioQuant, Heidelberg University, Heidelberg, Germany.|Cell Biology and Biophysics Unit, European Molecular Biology Laboratory (EMBL), Heidelberg, Germany.|Cell Biology and Biophysics Unit, European Molecular Biology Laboratory (EMBL), Heidelberg, Germany.|Institute for Theoretical Physics and BioQuant, Heidelberg University, Heidelberg, Germany.', 'Germany|Germany|Germany|Germany|Germany|Germany', 3, 'Actins|Algorithms|Animals|Cytoplasm|Heterocyclic Compounds, 4 or More Rings|Imaging, Three-Dimensional|Models, Theoretical|Myosin Type II|Normal Distribution|Oocytes|Polar Bodies|Rotation|Seawater|Starfish|Surface Properties', 'Journal Article', '10.1371/journal.pcbi.1006588', '30439934', 'Cytoplasmic flows are an ubiquitous feature of biological systems, in particular in large cells, such as oocytes and eggs in early animal development. Here we show that cytoplasmic flows in starfish oocytes, which can be imaged well with transmission light microscopy, are fully determined by the cortical dynamics during surface contraction waves. We first show that the dynamics of the oocyte surface is highly symmetric around the animal-vegetal axis. We then mathematically solve the Stokes equation for flows inside a deforming sphere using the measured surface displacements as boundary conditions. Our theoretical predictions agree very well with the intracellular flows quantified by particle image velocimetry, proving that during this stage the starfish cytoplasm behaves as a simple Newtonian fluid on the micrometer scale. We calculate the pressure field inside the oocyte and find that its gradient is too small as to explain polar body extrusion, in contrast to earlier suggestions. Myosin II inhibition by blebbistatin confirms this conclusion, because it diminishes cell shape changes and hydrodynamic flow, but does not abolish polar body formation.'),
(89329, 2018, 'plos', 'Ten simple rules for delivering live distance training in bioinformatics across the globe using webinars', 'Carvalho-Silva, Denise|Garcia, Leyla|Morgan, Sarah L|Brooksbank, Cath|Dunham, Ian', 'European Molecular Biology Laboratory, European Bioinformatics Institute (EMBL-EBI), Wellcome Genome Campus, Hinxton, Cambridgeshire, United Kingdom.|European Molecular Biology Laboratory, European Bioinformatics Institute (EMBL-EBI), Wellcome Genome Campus, Hinxton, Cambridgeshire, United Kingdom.|European Molecular Biology Laboratory, European Bioinformatics Institute (EMBL-EBI), Wellcome Genome Campus, Hinxton, Cambridgeshire, United Kingdom.|European Molecular Biology Laboratory, European Bioinformatics Institute (EMBL-EBI), Wellcome Genome Campus, Hinxton, Cambridgeshire, United Kingdom.|European Molecular Biology Laboratory, European Bioinformatics Institute (EMBL-EBI), Wellcome Genome Campus, Hinxton, Cambridgeshire, United Kingdom.', 'United Kingdom|United Kingdom|United Kingdom|United Kingdom|United Kingdom', 2, 'Communication|Computational Biology|Curriculum|Education|Education, Distance|Humans|Internet|Teaching|Videoconferencing|Webcasts as Topic', 'Editorial', '10.1371/journal.pcbi.1006419', '30439935', '-'),
(89330, 2018, 'plos', 'Ten simple rules for collaboratively writing a multi-authored paper', 'Frassl, Marieke A|Hamilton, David P|Denfeld, Blaize A|de Eyto, Elvira|Hampton, Stephanie E|Keller, Philipp S|Sharma, Sapna|Lewis, Abigail S L|Weyhenmeyer, Gesa A|OReilly, Catherine M|Lofton, Mary E|Catalán, Núria', 'Australian Rivers Institute, Griffith University, Nathan, Queensland, Australia.|Australian Rivers Institute, Griffith University, Nathan, Queensland, Australia.|Department of Ecology and Environmental Science, Umeå University, Umeå, Sweden.|Marine Institute, Furnace, Newport, Co. Mayo, Ireland.|Center for Environmental Research, Education and Outreach, Washington State University, Pullman, Washington, United States of America.|UFZ, Helmholtz Centre for Environmental Research, Department of Lake Research, Magdeburg, Germany.|Department of Biology, York University, Toronto, Ontario, Canada.|Department of Biology, Pomona College, Claremont, California, United States of America.|Department of Ecology and Genetics/Limnology, Uppsala University, Uppsala, Sweden.|Department of Geography, Geology, and the Environment, Illinois State University, Normal, Illinois, United States of America.|Department of Biological Sciences, Virginia Tech, Blacksburg, Virginia, United States of America.|Catalan Institute for Water Research (ICRA), Girona, Spain.', 'Australia|Australia|Sweden|Ireland|United States|Germany|Canada|United States|Sweden|United States|U', 0, 'Communication|Cooperative Behavior|Ecology|Ethics, Research|Humans|Leadership|Publications|Publishing|Science|Social Behavior|Writing', 'Editorial', '10.1371/journal.pcbi.1006508', '30439938', '-');
INSERT INTO `papers` (`id`, `ano`, `journal`, `titulo`, `autores`, `afiliacao`, `pais`, `citacoes`, `palavra_chave`, `categorias`, `doi`, `pubmed`, `abstract`) VALUES
(89331, 2018, 'plos', 'Patterning the insect eye: From stochastic to deterministic mechanisms', 'Ebadi, Haleh|Perry, Michael|Short, Keith|Klemm, Konstantin|Desplan, Claude|Stadler, Peter F|Mehta, Anita', 'Bioinformatics, Institute for Computer Science, Leipzig University, Leipzig, Germany.|Department of Biology, New York University, New York, New York, United States of America.|Department of Biology, New York University, New York, New York, United States of America.|Department of Computer Science, School of Science and Technology, Nazarbayev University, Astana, Republic of Kazakhstan.|Department of Biology, New York University, New York, New York, United States of America.|Bioinformatics, Institute for Computer Science, Leipzig University, Leipzig, Germany.|Max Planck Institute for Mathematics in the Sciences, Leipzig, Germany.', 'Germany|United States|United States|Kazakhstan|United States|Germany|Germany', 4, 'Animals|Body Patterning|Drosophila|Drosophila Proteins|Eye|Models, Theoretical|Photoreceptor Cells, Invertebrate|Probability|Stochastic Processes', 'Journal Article', '10.1371/journal.pcbi.1006363', '30439954', 'While most processes in biology are highly deterministic, stochastic mechanisms are sometimes used to increase cellular diversity. In human and Drosophila eyes, photoreceptors sensitive to different wavelengths of light are distributed in stochastic patterns, and one such patterning system has been analyzed in detail in the Drosophila retina. Interestingly, some species in the dipteran family Dolichopodidae (the long legged flies, or Doli) instead exhibit highly orderly deterministic eye patterns. In these species, alternating columns of ommatidia (unit eyes) produce corneal lenses of different colors. Occasional perturbations in some individuals disrupt the regular columns in a way that suggests that patterning occurs via a posterior-to-anterior signaling relay during development, and that specification follows a local, cellular-automaton-like rule. We hypothesize that the regulatory mechanisms that pattern the eye are largely conserved among flies and that the difference between unordered Drosophila and ordered dolichopodid eyes can be explained in terms of relative strengths of signaling interactions rather than a rewiring of the regulatory network itself. We present a simple stochastic model that is capable of explaining both the stochastic Drosophila eye and the striped pattern of Dolichopodidae eyes and thereby characterize the least number of underlying developmental rules necessary to produce both stochastic and deterministic patterns. We show that only small changes to model parameters are needed to also reproduce intermediate, semi-random patterns observed in another Doli species, and quantification of ommatidial distributions in these eyes suggests that their patterning follows similar rules.'),
(89332, 2018, 'plos', 'Metabolic models and gene essentiality data reveal essential and conserved metabolism in prokaryotes', 'Xavier, Joana C|Patil, Kiran Raosaheb|Rocha, Isabel', 'Department of Biological Engineering, University of Minho, Campus de Gualtar, Braga, Portugal.|European Molecular Biology Laboratory, Heidelberg, Germany.|Department of Biological Engineering, University of Minho, Campus de Gualtar, Braga, Portugal.', 'Portugal|Germany|Portugal', 0, 'Archaea|Bacteria|Energy Metabolism|Genes, Essential|Genome|Metabolic Networks and Pathways|Models, Biological|Phylogeny|RNA, Transfer', 'Journal Article', '10.1371/journal.pcbi.1006556', '30444863', 'Essential metabolic reactions are shaping constituents of metabolic networks, enabling viable and distinct phenotypes across diverse life forms. Here we analyse and compare modelling predictions of essential metabolic functions with experimental data and thereby identify core metabolic pathways in prokaryotes. Simulations of 15 manually curated genome-scale metabolic models were integrated with 36 large-scale gene essentiality datasets encompassing a wide variety of species of bacteria and archaea. Conservation of metabolic genes was estimated by analysing 79 representative genomes from all the branches of the prokaryotic tree of life. We find that essentiality patterns reflect phylogenetic relations both for modelling and experimental data, which correlate highly at the pathway level. Genes that are essential for several species tend to be highly conserved as opposed to non-essential genes which may be conserved or not. The tRNA-charging module is highlighted as ancestral and with high centrality in the networks, followed closely by cofactor metabolism, pointing to an early information processing system supplied by organic cofactors. The results, which point to model improvements and also indicate faults in the experimental data, should be relevant to the study of centrality in metabolic networks and ancient metabolism but also to metabolic engineering with prokaryotes.'),
(89333, 2018, 'plos', 'Towards a molecular basis of ubiquitin signaling: A dual-scale simulation study of ubiquitin dimers', 'Berg, Andrej|Kukharenko, Oleksandra|Scheffner, Martin|Peter, Christine', 'Department of Chemistry, University of Konstanz, Konstanz, Germany.|Department of Chemistry, University of Konstanz, Konstanz, Germany.|Department of Biology, University of Konstanz, Konstanz, Germany.|Department of Chemistry, University of Konstanz, Konstanz, Germany.', 'Germany|Germany|Germany|Germany', 0, 'Algorithms|Computer Simulation|Databases, Protein|Models, Molecular|Molecular Dynamics Simulation|Protein Binding|Protein Interaction Mapping|Protein Multimerization|Protein Processing, Post-Translational|Signal Transduction|Ubiquitin|Ubiquitination', 'Journal Article', '10.1371/journal.pcbi.1006589', '30444864', 'Covalent modification of proteins by ubiquitin or ubiquitin chains is one of the most prevalent post-translational modifications in eukaryotes. Different types of ubiquitin chains are assumed to selectively signal respectively modified proteins for different fates. In support of this hypothesis, structural studies have shown that the eight possible ubiquitin dimers adopt different conformations. However, at least in some cases, these structures cannot sufficiently explain the molecular basis of the selective signaling mechanisms. This indicates that the available structures represent only a few distinct conformations within the entire conformational space adopted by a ubiquitin dimer. Here, molecular simulations on different levels of resolution can complement the structural information. We have combined exhaustive coarse grained and atomistic simulations of all eight possible ubiquitin dimers with a suitable dimensionality reduction technique and a new method to characterize protein-protein interfaces and the conformational landscape of protein conjugates. We found that ubiquitin dimers exhibit characteristic linkage type-dependent properties in solution, such as interface stability and the character of contacts between the subunits, which can be directly correlated with experimentally observed linkage-specific properties.'),
(89334, 2018, 'plos', 'Rosetta FunFolDes - A general framework for the computational design of functional proteins', 'Bonet, Jaume|Wehrle, Sarah|Schriever, Karen|Yang, Che|Billet, Anne|Sesterhenn, Fabian|Scheck, Andreas|Sverrisson, Freyr|Veselkova, Barbora|Vollers, Sabrina|Lourman, Roxanne|Villard, Mélanie|Rosset, Stéphane|Krey, Thomas|Correia, Bruno E', 'Institute of Bioengineering, École Polytechnique Fédérale de Lausanne, Lausanne, Switzerland.|Institute of Bioengineering, École Polytechnique Fédérale de Lausanne, Lausanne, Switzerland.|Institute of Bioengineering, École Polytechnique Fédérale de Lausanne, Lausanne, Switzerland.|Institute of Bioengineering, École Polytechnique Fédérale de Lausanne, Lausanne, Switzerland.|Institute of Bioengineering, École Polytechnique Fédérale de Lausanne, Lausanne, Switzerland.|Institute of Bioengineering, École Polytechnique Fédérale de Lausanne, Lausanne, Switzerland.|Institute of Bioengineering, École Polytechnique Fédérale de Lausanne, Lausanne, Switzerland.|Institute of Bioengineering, École Polytechnique Fédérale de Lausanne, Lausanne, Switzerland.|Institute of Virology, Hannover Medical School, Hannover, Germany.|Institute of Bioengineering, École Polytechnique Fédérale de Lausanne, Lausanne, Switzerland.|Institute of Bioengineering, École Polytechnique Fédérale de Lausanne, Lausanne, Switzerland.|Institute of Bioengineering, École Polytechnique Fédérale de Lausanne, Lausanne, Switzerland.|Institute of Bioengineering, École Polytechnique Fédérale de Lausanne, Lausanne, Switzerland.|Institute of Virology, Hannover Medical School, Hannover, Germany.|Institute of Bioengineering, École Polytechnique Fédérale de Lausanne, Lausanne, Switzerland.', 'Switzerland|Switzerland|Switzerland|Switzerland|Switzerland|Switzerland|Switzerland|Switzerland|Germ', 2, 'Amino Acid Motifs|Antibodies, Monoclonal|Catalysis|Computational Biology|Epitopes|Humans|Models, Molecular|Protein Binding|Protein Engineering|Protein Folding|Proteins|Software', 'Journal Article', '10.1371/journal.pcbi.1006623', '30452434', 'The robust computational design of functional proteins has the potential to deeply impact translational research and broaden our understanding of the determinants of protein function and stability. The low success rates of computational design protocols and the extensive in vitro optimization often required, highlight the challenge of designing proteins that perform essential biochemical functions, such as binding or catalysis. One of the most simplistic approaches for the design of function is to adopt functional motifs in naturally occurring proteins and transplant them to computationally designed proteins. The structural complexity of the functional motif largely determines how readily one can find host protein structures that are designable, meaning that are likely to present the functional motif in the desired conformation. One promising route to enhance the designability of protein structures is to allow backbone flexibility. Here, we present a computational approach that couples conformational folding with sequence design to embed functional motifs into heterologous proteins-Rosetta Functional Folding and Design (FunFolDes). We performed extensive computational benchmarks, where we observed that the enforcement of functional requirements resulted in designs distant from the global energetic minimum of the protein. An observation consistent with several experimental studies that have revealed function-stability tradeoffs. To test the design capabilities of FunFolDes we transplanted two viral epitopes into distant structural templates including one de novo functionless fold, which represent two typical challenges where the designability problem arises. The designed proteins were experimentally characterized showing high binding affinities to monoclonal antibodies, making them valuable candidates for vaccine design endeavors. Overall, we present an accessible strategy to repurpose old protein folds for new functions. This may lead to important improvements on the computational design of proteins, with structurally complex functional sites, that can perform elaborate biochemical functions related to binding and catalysis.'),
(89335, 2018, 'plos', 'Simulations of blood as a suspension predicts a depth dependent hematocrit in the circulation throughout the cerebral cortex', 'Hartung, Grant|Vesel, Claudia|Morley, Ryan|Alaraj, Ali|Sled, John|Kleinfeld, David|Linninger, Andreas', 'Department of Bioengineering, University of Illinois at Chicago, Chicago, IL, United States of America.|Department of Bioengineering, University of Illinois at Chicago, Chicago, IL, United States of America.|Department of Bioengineering, University of Illinois at Chicago, Chicago, IL, United States of America.|Department of Bioengineering, University of Illinois at Chicago, Chicago, IL, United States of America.|Department of Medical Biophysics, University of Toronto, Toronto, Canada.|Department of Physics, University of California, San Diego, La Jolla, CA, United States of America.|Department of Bioengineering, University of Illinois at Chicago, Chicago, IL, United States of America.', 'United States|United States|United States|United States|Canada|United States|United States', 2, 'Animals|Blood|Cerebral Cortex|Cerebrovascular Circulation|Erythrocyte Count|Hematocrit|Hemodynamics|Mice|Microcirculation|Models, Biological|Neuroglia|Neuroimaging|Neurons|Oxygen|Probability', 'Journal Article', '10.1371/journal.pcbi.1006549', '30452440', 'Recent advances in modeling oxygen supply to cortical brain tissue have begun to elucidate the functional mechanisms of neurovascular coupling. While the principal mechanisms of blood flow regulation after neuronal firing are generally known, mechanistic hemodynamic simulations cannot yet pinpoint the exact spatial and temporal coordination between the network of arteries, arterioles, capillaries and veins for the entire brain. Because of the potential significance of blood flow and oxygen supply simulations for illuminating spatiotemporal regulation inside the cortical microanatomy, there is a need to create mathematical models of the entire cerebral circulation with realistic anatomical detail. Our hypothesis is that an anatomically accurate reconstruction of the cerebrocirculatory architecture will inform about possible regulatory mechanisms of the neurovascular interface. In this article, we introduce large-scale networks of the murine cerebral circulation spanning the Circle of Willis, main cerebral arteries connected to the pial network down to the microcirculation in the capillary bed. Several multiscale models were generated from state-of-the-art neuroimaging data. Using a vascular network construction algorithm, the entire circulation of the middle cerebral artery was synthesized. Blood flow simulations indicate a consistent trend of higher hematocrit in deeper cortical layers, while surface layers with shorter vascular path lengths seem to carry comparatively lower red blood cell (RBC) concentrations. Moreover, the variability of RBC flux decreases with cortical depth. These results support the notion that plasma skimming serves a self-regulating function for maintaining uniform oxygen perfusion to neurons irrespective of their location in the blood supply hierarchy. Our computations also demonstrate the practicality of simulating blood flow for large portions of the mouse brain with existing computer resources. The efficient simulation of blood flow throughout the entire middle cerebral artery (MCA) territory is a promising milestone towards the final aim of predicting blood flow patterns for the entire brain.'),
(89336, 2018, 'plos', 'Adaptive feature detection from differential processing in parallel retinal pathways', 'Ozuysal, Yusuf|Kastner, David B|Baccus, Stephen A', 'Department of Electrical Engineering, Stanford University, Stanford, CA, United States of America.|Neuroscience Program, Stanford University, Stanford, CA, United States of America.|Department of Neurobiology, Stanford University, Stanford, CA, United States of America.', 'United States|United States|United States', 3, 'Animals|Electrophysiological Phenomena|Medical Informatics|Neural Networks (Computer)|Neural Pathways|Nonlinear Dynamics|Pattern Recognition, Automated|Photic Stimulation|Retina|Retinal Ganglion Cells|Signal Processing, Computer-Assisted|Synapses|Urodela|Vision, Ocular|Visual Pathways', 'Journal Article', '10.1371/journal.pcbi.1006560', '30457994', 'To transmit information efficiently in a changing environment, the retina adapts to visual contrast by adjusting its gain, latency and mean response. Additionally, the temporal frequency selectivity, or bandwidth changes to encode the absolute intensity when the stimulus environment is noisy, and intensity differences when noise is low. We show that the On pathway of On-Off retinal amacrine and ganglion cells is required to change temporal bandwidth but not other adaptive properties. This remarkably specific adaptive mechanism arises from differential effects of contrast on the On and Off pathways. We analyzed a biophysical model fit only to a cells membrane potential, and verified pharmacologically that it accurately revealed the two pathways. We conclude that changes in bandwidth arise mostly from differences in synaptic threshold in the two pathways, rather than synaptic release dynamics as has previously been proposed to underlie contrast adaptation. Different efficient codes are selected by different thresholds in two independently adapting neural pathways.'),
(89337, 2018, 'plos', 'Deepbinner: Demultiplexing barcoded Oxford Nanopore reads with deep convolutional neural networks', 'Wick, Ryan R|Judd, Louise M|Holt, Kathryn E', 'Department of Biochemistry and Molecular Biology, Bio21 Molecular Science and Biotechnology Institute, University of Melbourne, Parkville, Victoria, Australia.|Department of Biochemistry and Molecular Biology, Bio21 Molecular Science and Biotechnology Institute, University of Melbourne, Parkville, Victoria, Australia.|Department of Biochemistry and Molecular Biology, Bio21 Molecular Science and Biotechnology Institute, University of Melbourne, Parkville, Victoria, Australia.', 'Australia|Australia|Australia', 0, 'Algorithms|Bacteria|Computational Biology|DNA|DNA Barcoding, Taxonomic|Electronic Data Processing|Gene Library|Genome|High-Throughput Nucleotide Sequencing|Nanopores|Nanotechnology|Neural Networks (Computer)|Reproducibility of Results|Software', 'Journal Article', '10.1371/journal.pcbi.1006583', '30458005', 'Multiplexing, the simultaneous sequencing of multiple barcoded DNA samples on a single flow cell, has made Oxford Nanopore sequencing cost-effective for small genomes. However, it depends on the ability to sort the resulting sequencing reads by barcode, and current demultiplexing tools fail to classify many reads. Here we present Deepbinner, a tool for Oxford Nanopore demultiplexing that uses a deep neural network to classify reads based on the raw electrical read signal. This signal-space approach allows for greater accuracy than existing base-space tools (Albacore and Porechop) for which signals must first be converted to DNA base calls, itself a complex problem that can introduce noise into the barcode sequence. To assess Deepbinner and existing tools, we performed multiplex sequencing on 12 amplicons chosen for their distinguishability. This allowed us to establish a ground truth classification for each read based on internal sequence alone. Deepbinner had the lowest rate of unclassified reads (7.8%) and the highest demultiplexing precision (98.5% of classified reads were correctly assigned). It can be used alone (to maximise the number of classified reads) or in conjunction with other demultiplexers (to maximise precision and minimise false positive classifications). We also found cross-sample chimeric reads (0.3%) and evidence of barcode switching (0.3%) in our dataset, which likely arise during library preparation and may be detrimental for quantitative studies that use multiplexing. Deepbinner is open source (GPLv3) and available at https://github.com/rrwick/Deepbinner.'),
(89338, 2018, 'plos', 'Binding of the general anesthetic sevoflurane to ion channels', 'Stock, Letícia|Hosoume, Juliana|Cirqueira, Leonardo|Treptow, Werner', 'Laboratório de Biologia Teórica e Computacional (LBTC), Universidade de Brasília DF, Brasil.|Laboratório de Biologia Teórica e Computacional (LBTC), Universidade de Brasília DF, Brasil.|Laboratório de Biologia Teórica e Computacional (LBTC), Universidade de Brasília DF, Brasil.|Laboratório de Biologia Teórica e Computacional (LBTC), Universidade de Brasília DF, Brasil.', '-|-|-|-', 0, 'Algorithms|Anesthetics, General|Anesthetics, Inhalation|Animals|Binding Sites|Computational Biology|Ion Channel Gating|Ion Channels|Kv1.2 Potassium Channel|Ligands|Molecular Conformation|Molecular Dynamics Simulation|Probability|Protein Binding|Protein Domains|Sevoflurane|Software', 'Journal Article', '10.1371/journal.pcbi.1006605', '30475796', 'The direct-site hypothesis assumes general anesthetics bind ion channels to impact protein equilibrium and function, inducing anesthesia. Despite advancements in the field, a first principle all-atom demonstration of this structure-function premise is still missing. We focus on the clinically used sevoflurane interaction to anesthetic-sensitive Kv1.2 mammalian channel to resolve if sevoflurane binds proteins well-characterized open and closed structures in a conformation-dependent manner to shift channel equilibrium. We employ an innovative approach relying on extensive docking calculations and free-energy perturbation of all potential binding sites revealed by the latter, and find sevoflurane binds open and closed structures at multiple sites under complex saturation and concentration effects. Results point to a non-trivial interplay of site and conformation-dependent modes of action involving distinct binding sites that increase channel open-probability at diluted ligand concentrations. Given the challenge in exploring more complex processes potentially impacting channel-anesthetic interaction, the result is revealing as it demonstrates the process of multiple anesthetic binding events alone may account for open-probability shifts recorded in measurements.'),
(89339, 2018, 'plos', 'Comprehensive computational modelling of the development of mammalian cortical connectivity underlying an architectonic type principle', 'Beul, Sarah F|Goulas, Alexandros|Hilgetag, Claus C', 'Institute of Computational Neuroscience, University Medical Center Hamburg-Eppendorf, Hamburg, Germany.|Institute of Computational Neuroscience, University Medical Center Hamburg-Eppendorf, Hamburg, Germany.|Institute of Computational Neuroscience, University Medical Center Hamburg-Eppendorf, Hamburg, Germany.', 'Germany|Germany|Germany', 3, 'Animals|Brain Mapping|Cerebral Cortex|Computer Simulation|Connectome|Humans|Mammals|Neurogenesis', 'Journal Article', '10.1371/journal.pcbi.1006550', '30475798', 'The architectonic type principle relates patterns of cortico-cortical connectivity to the relative architectonic differentiation of cortical regions. One mechanism through which the observed close relation between cortical architecture and connectivity may be established is the joint development of cortical areas and their connections in developmental time windows. Here, we describe a theoretical exploration of the possible mechanistic underpinnings of the architectonic type principle, by performing systematic computational simulations of cortical development. The main component of our in silico model was a developing two-dimensional cortical sheet, which was gradually populated by neurons that formed cortico-cortical connections. To assess different explanatory mechanisms, we varied the spatiotemporal trajectory of the simulated neurogenesis. By keeping the rules governing axon outgrowth and connection formation constant across all variants of simulated development, we were able to create model variants which differed exclusively by the specifics of when and where neurons were generated. Thus, all differences in the resulting connectivity were due to the variations in spatiotemporal growth trajectories. Our results demonstrated that a prescribed targeting of interareal connection sites was not necessary for obtaining a realistic replication of the experimentally observed relation between connection patterns and architectonic differentiation. Instead, we found that spatiotemporal interactions within the forming cortical sheet were sufficient if a small number of empirically well-grounded assumptions were met, namely planar, expansive growth of the cortical sheet around two points of origin as neurogenesis progressed, stronger architectonic differentiation of cortical areas for later neurogenetic time windows, and stochastic connection formation. Thus, our study highlights a potential mechanism of how relative architectonic differentiation and cortical connectivity become linked during development. We successfully predicted connectivity in two species, cat and macaque, from simulated cortico-cortical connection networks, which further underscored the general applicability of mechanisms through which the architectonic type principle can explain cortical connectivity in terms of the relative architectonic differentiation of cortical regions.'),
(89340, 2018, 'plos', 'Determinants of early afterdepolarization properties in ventricular myocyte models', 'Huang, Xiaodong|Song, Zhen|Qu, Zhilin', 'Department of Physics, South China University of Technology, Guangzhou, China.|Department of Medicine, David Geffen School of Medicine, University of California, Los Angeles, California, United States of America.|Department of Medicine, David Geffen School of Medicine, University of California, Los Angeles, California, United States of America.', 'China|United States|United States', 0, 'Action Potentials|Computer Simulation|Heart Ventricles|Humans|Ion Transport|Models, Biological|Myocytes, Cardiac', 'Journal Article', '10.1371/journal.pcbi.1006382', '30475801', 'Early afterdepolarizations (EADs) are spontaneous depolarizations during the repolarization phase of an action potential in cardiac myocytes. It is widely known that EADs are promoted by increasing inward currents and/or decreasing outward currents, a condition called reduced repolarization reserve. Recent studies based on bifurcation theories show that EADs are caused by a dual Hopf-homoclinic bifurcation, bringing in further mechanistic insights into the genesis and dynamics of EADs. In this study, we investigated the EAD properties, such as the EAD amplitude, the inter-EAD interval, and the latency of the first EAD, and their major determinants. We first made predictions based on the bifurcation theory and then validated them in physiologically more detailed action potential models. These properties were investigated by varying one parameter at a time or using parameter sets randomly drawn from assigned intervals. The theoretical and simulation results were compared with experimental data from the literature. Our major findings are that the EAD amplitude and takeoff potential exhibit a negative linear correlation, the inter-EAD interval is insensitive to the maximum ionic current conductance but mainly determined by the kinetics of ICa,L and the dual Hopf-homoclinic bifurcation, and both inter-EAD interval and latency vary largely from model to model. Most of the model results generally agree with experimental observations in isolated ventricular myocytes. However, a major discrepancy between modeling results and experimental observations is that the inter-EAD intervals observed in experiments are mainly between 200 and 500 ms, irrespective of species, while those of the mathematical models exhibit a much wider range with some models exhibiting inter-EAD intervals less than 100 ms. Our simulations show that the cause of this discrepancy is likely due to the difference in ICa,L recovery properties in different mathematical models, which needs to be addressed in future action potential model development.'),
(89341, 2018, 'plos', 'Modeling craniofacial development reveals spatiotemporal constraints on robust patterning of the mandibular arch', 'Meinecke, Lina|Sharma, Praveer P|Du, Huijing|Zhang, Lei|Nie, Qing|Schilling, Thomas F', 'Department of Mathematics, University of California, Irvine, CA, United States of America.|Center for Complex Biological Systems, University of California, Irvine, CA, United States of America.|Department of Mathematics, University of Nebraska, Lincoln, NE, United States of America.|Beijing International Center for Mathematical Research, Peking University, Beijing, China.|Department of Mathematics, University of California, Irvine, CA, United States of America.|Center for Complex Biological Systems, University of California, Irvine, CA, United States of America.', 'United States|United States|United States|China|United States|United States', 7, 'Animals|Body Patterning|Bone Morphogenetic Proteins|Branchial Region|Cell Adhesion|Computer Simulation|Gene Expression Regulation|Gene Expression Regulation, Developmental|Green Fluorescent Proteins|Mandible|Reproducibility of Results|Signal Transduction|Stochastic Processes|Transgenes|Zebrafish|Zebrafish Proteins', 'Journal Article', '10.1371/journal.pcbi.1006569', '30481168', 'How does pattern formation occur accurately when confronted with tissue growth and stochastic fluctuations (noise) in gene expression? Dorso-ventral (D-V) patterning of the mandibular arch specifies upper versus lower jaw skeletal elements through a combination of Bone morphogenetic protein (Bmp), Endothelin-1 (Edn1), and Notch signaling, and this system is highly robust. We combine NanoString experiments of early D-V gene expression with live imaging of arch development in zebrafish to construct a computational model of the D-V mandibular patterning network. The model recapitulates published genetic perturbations in arch development. Patterning is most sensitive to changes in Bmp signaling, and the temporal order of gene expression modulates the response of the patterning network to noise. Thus, our integrated systems biology approach reveals non-intuitive features of the complex signaling system crucial for craniofacial development, including novel insights into roles of gene expression timing and stochasticity in signaling and gene regulation.'),
(89342, 2018, 'plos', 'A Bayesian mixture modelling approach for spatial proteomics', 'Crook, Oliver M|Mulvey, Claire M|Kirk, Paul D W|Lilley, Kathryn S|Gatto, Laurent', 'Computational Proteomics Unit, Department of Biochemistry, University of Cambridge, Cambridge, UK.|Cambridge Centre for Proteomics, Department of Biochemistry, University of Cambridge, Cambridge, UK.|MRC Biostatistics Unit, Cambridge Institute for Public Health, Cambridge, UK.|Cambridge Centre for Proteomics, Department of Biochemistry, University of Cambridge, Cambridge, UK.|Computational Proteomics Unit, Department of Biochemistry, University of Cambridge, Cambridge, UK.', 'United Kingdom|United Kingdom|United Kingdom|United Kingdom|United Kingdom', 6, 'Algorithms|Animals|Bayes Theorem|Embryonic Stem Cells|Machine Learning|Mice|Models, Theoretical|Proteomics|Reproducibility of Results|Subcellular Fractions|Uncertainty', 'Journal Article', '10.1371/journal.pcbi.1006516', '30481170', 'Analysis of the spatial sub-cellular distribution of proteins is of vital importance to fully understand context specific protein function. Some proteins can be found with a single location within a cell, but up to half of proteins may reside in multiple locations, can dynamically re-localise, or reside within an unknown functional compartment. These considerations lead to uncertainty in associating a protein to a single location. Currently, mass spectrometry (MS) based spatial proteomics relies on supervised machine learning algorithms to assign proteins to sub-cellular locations based on common gradient profiles. However, such methods fail to quantify uncertainty associated with sub-cellular class assignment. Here we reformulate the framework on which we perform statistical analysis. We propose a Bayesian generative classifier based on Gaussian mixture models to assign proteins probabilistically to sub-cellular niches, thus proteins have a probability distribution over sub-cellular locations, with Bayesian computation performed using the expectation-maximisation (EM) algorithm, as well as Markov-chain Monte-Carlo (MCMC). Our methodology allows proteome-wide uncertainty quantification, thus adding a further layer to the analysis of spatial proteomics. Our framework is flexible, allowing many different systems to be analysed and reveals new modelling opportunities for spatial proteomics. We find our methods perform competitively with current state-of-the art machine learning methods, whilst simultaneously providing more information. We highlight several examples where classification based on the support vector machine is unable to make any conclusions, while uncertainty quantification using our approach provides biologically intriguing results. To our knowledge this is the first Bayesian model of MS-based spatial proteomics data.'),
(89343, 2018, 'plos', 'RNA3DCNN: Local and global quality assessments of RNA 3D structures using 3D deep convolutional neural networks', 'Li, Jun|Zhu, Wei|Wang, Jun|Li, Wenfei|Gong, Sheng|Zhang, Jian|Wang, Wei', 'National Laboratory of Solid State Microstructures, School of Physics, Collaborative Innovation Center of Advanced Microstructures, Nanjing University, Nanjing, China.|National Laboratory of Solid State Microstructures, School of Physics, Collaborative Innovation Center of Advanced Microstructures, Nanjing University, Nanjing, China.|National Laboratory of Solid State Microstructures, School of Physics, Collaborative Innovation Center of Advanced Microstructures, Nanjing University, Nanjing, China.|National Laboratory of Solid State Microstructures, School of Physics, Collaborative Innovation Center of Advanced Microstructures, Nanjing University, Nanjing, China.|Department of Pharmaceutics, Nanjing General Hospital, Nanjing University Medical School, Nanjing, China.|National Laboratory of Solid State Microstructures, School of Physics, Collaborative Innovation Center of Advanced Microstructures, Nanjing University, Nanjing, China.|National Laboratory of Solid State Microstructures, School of Physics, Collaborative Innovation Center of Advanced Microstructures, Nanjing University, Nanjing, China.', 'China|China|China|China|China|China|China', 0, 'Datasets as Topic|Hot Temperature|Molecular Dynamics Simulation|Monte Carlo Method|Neural Networks (Computer)|Nucleic Acid Conformation|RNA', 'Journal Article', '10.1371/journal.pcbi.1006514', '30481171', 'Quality assessment is essential for the computational prediction and design of RNA tertiary structures. To date, several knowledge-based statistical potentials have been proposed and proved to be effective in identifying native and near-native RNA structures. All these potentials are based on the inverse Boltzmann formula, while differing in the choice of the geometrical descriptor, reference state, and training dataset. Via an approach that diverges completely from the conventional statistical potentials, our work explored the power of a 3D convolutional neural network (CNN)-based approach as a quality evaluator for RNA 3D structures, which used a 3D grid representation of the structure as input without extracting features manually. The RNA structures were evaluated by examining each nucleotide, so our method can also provide local quality assessment. Two sets of training samples were built. The first one included 1 million samples generated by high-temperature molecular dynamics (MD) simulations and the second one included 1 million samples generated by Monte Carlo (MC) structure prediction. Both MD and MC procedures were performed for a non-redundant set of 414 RNAs. For two training datasets (one including only MD training samples and the other including both MD and MC training samples), we trained two neural networks, named RNA3DCNN_MD and RNA3DCNN_MDMC, respectively. The former is suitable for assessing near-native structures, while the latter is suitable for assessing structures covering large structural space. We tested the performance of our method and made comparisons with four other traditional scoring functions. On two of three test datasets, our method performed similarly to the state-of-the-art traditional scoring function, and on the third test dataset, our method was far superior to other scoring functions. Our method can be downloaded from https://github.com/lijunRNA/RNA3DCNN.'),
(89344, 2018, 'plos', 'powerTCR: A model-based approach to comparative analysis of the clone size distribution of the T cell receptor repertoire', 'Koch, Hillary|Starenki, Dmytro|Cooper, Sara J|Myers, Richard M|Li, Qunhua', 'Department of Statistics, Pennsylvania State University, University Park, Pennsylvania, United States of America.|HudsonAlpha Institute for Biotechnology, Huntsville, Alabama, United States of America.|HudsonAlpha Institute for Biotechnology, Huntsville, Alabama, United States of America.|HudsonAlpha Institute for Biotechnology, Huntsville, Alabama, United States of America.|Department of Statistics, Pennsylvania State University, University Park, Pennsylvania, United States of America.', 'United States|United States|United States|United States|United States', 2, 'Alternative Splicing|Animals|Brain Neoplasms|CD4-Positive T-Lymphocytes|Clone Cells|Cluster Analysis|Computer Simulation|Glioblastoma|High-Throughput Nucleotide Sequencing|Humans|Immune System|Likelihood Functions|Lung|Mice|Programming Languages|Receptors, Antigen, T-Cell|Sarcoidosis|Software', 'Journal Article', '10.1371/journal.pcbi.1006571', '30485278', 'Sequencing of the T cell receptor (TCR) repertoire is a powerful tool for deeper study of immune response, but the unique structure of this type of data makes its meaningful quantification challenging. We introduce a new method, the Gamma-GPD spliced threshold model, to address this difficulty. This biologically interpretable model captures the distribution of the TCR repertoire, demonstrates stability across varying sequencing depths, and permits comparative analysis across any number of sampled individuals. We apply our method to several datasets and obtain insights regarding the differentiating features in the T cell receptor repertoire among sampled individuals across conditions. We have implemented our method in the open-source R package powerTCR.'),
(89345, 2018, 'plos', 'Strategies and opportunities for promoting bioinformatics in Zimbabwe', 'Shoko, Ryman|Manasa, Justen|Maphosa, Mcebisi|Mbanga, Joshua|Mudziwapasi, Reagan|Nembaware, Victoria|Sanyika, Walter T|Tinago, Tawanda|Chikwambi, Zedias|Mawere, Cephas|Matimba, Alice|Mugumbate, Grace|Mufandaedza, Jonathan|Mulder, Nicola|Patterton, Hugh', 'Department of Biology, School of Natural Science and Mathematics, Chinhoyi University of Technology, Chinhoyi, Zimbabwe.|African Institute of Biomedical Science & Technology, Harare, Zimbabwe.|Department of Crop and Soil Science, School of Agricultural Sciences, Lupane State University, Lupane, Zimbabwe.|Department of Applied Biology and Biochemistry, Faculty of Applied Sciences, National University of Science and Technology, Bulawayo, Zimbabwe.|Department of Crop and Soil Science, School of Agricultural Sciences, Lupane State University, Lupane, Zimbabwe.|Computational Biology Division, Department of Integrative Biomedical Sciences, Institute of Infectious Disease and Molecular Medicine, Faculty of Health Sciences, University of Cape Town, Cape Town, South Africa.|Department of Biotechnology, School of Agricultural Sciences and Technology, Chinhoyi University of Technology, Chinhoyi, Zimbabwe.|Department of Biology, School of Natural Science and Mathematics, Chinhoyi University of Technology, Chinhoyi, Zimbabwe.|Department of Biotechnology, School of Agricultural Sciences and Technology, Chinhoyi University of Technology, Chinhoyi, Zimbabwe.|Department of Biotechnology, School of Industrial Science and Technology, Harare Institute of Technology, Harare, Zimbabwe.|Department of Clinical Pharmacology, College of Health Sciences, University of Zimbabwe, Harare, Zimbabwe.|Department of Chemistry, School of Natural Science and Mathematics, Chinhoyi University of Technology, Chinhoyi, Zimbabwe.|National Biotechnology Authority, Harare, Zimbabwe.|Computational Biology Division, Department of Integrative Biomedical Sciences, Institute of Infectious Disease and Molecular Medicine, Faculty of Health Sciences, University of Cape Town, Cape Town, South Africa.|Centre for Bioinformatics and Computational Biology, Stellenbosch University, Stellenbosch, South Africa.', 'Zimbabwe|Zimbabwe|Zimbabwe|Zimbabwe|Zimbabwe|South Africa|Zimbabwe|Zimbabwe|Zimbabwe|Zimbabwe|Zimbab', 2, 'Computational Biology|Food Supply|Health Status Indicators|Humans|Interprofessional Relations|Metagenomics|Zimbabwe', 'Journal Article', '10.1371/journal.pcbi.1006480', '30496170', '-'),
(89346, 2018, 'plos', 'Atlases of cognition with large-scale human brain mapping', 'Varoquaux, Gaël|Schwartz, Yannick|Poldrack, Russell A|Gauthier, Baptiste|Bzdok, Danilo|Poline, Jean-Baptiste|Thirion, Bertrand', 'Parietal, Inria, Saclay, France.|Parietal, Inria, Saclay, France.|Psychology department, Stanford University, Stanford, CA 94305, USA.|Neurospin, CEA, Gif sur Yvette, France.|Parietal, Inria, Saclay, France.|Montreal neurological Institute and Hospital, McGill University, Montreal, Canada.|Parietal, Inria, Saclay, France.', 'France|France|United States|France|France|Canada|France', 0, 'Area Under Curve|Bayes Theorem|Brain|Brain Mapping|Cognition|Databases, Factual|Functional Neuroimaging|Hearing|Humans|Magnetic Resonance Imaging|Motor Skills|Neuroimaging|ROC Curve|Reproducibility of Results', 'Journal Article', '10.1371/journal.pcbi.1006565', '30496171', 'To map the neural substrate of mental function, cognitive neuroimaging relies on controlled psychological manipulations that engage brain systems associated with specific cognitive processes. In order to build comprehensive atlases of cognitive function in the brain, it must assemble maps for many different cognitive processes, which often evoke overlapping patterns of activation. Such data aggregation faces contrasting goals: on the one hand finding correspondences across vastly different cognitive experiments, while on the other hand precisely describing the function of any given brain region. Here we introduce a new analysis framework that tackles these difficulties and thereby enables the generation of brain atlases for cognitive function. The approach leverages ontologies of cognitive concepts and multi-label brain decoding to map the neural substrate of these concepts. We demonstrate the approach by building an atlas of functional brain organization based on 30 diverse functional neuroimaging studies, totaling 196 different experimental conditions. Unlike conventional brain mapping, this functional atlas supports robust reverse inference: predicting the mental processes from brain activity in the regions delineated by the atlas. To establish that this reverse inference is indeed governed by the corresponding concepts, and not idiosyncrasies of experimental designs, we show that it can accurately decode the cognitive concepts recruited in new tasks. These results demonstrate that aggregating independent task-fMRI studies can provide a more precise global atlas of selective associations between brain and cognition.'),
(89347, 2018, 'plos', 'Coevolving residues inform protein dynamics profiles and disease susceptibility of nSNVs', 'Butler, Brandon M|Kazan, I Can|Kumar, Avishek|Ozkan, S Banu', 'Department of Physics and Center for Biological Physics, Arizona State University, Tempe, AZ, United States of America.|Department of Physics and Center for Biological Physics, Arizona State University, Tempe, AZ, United States of America.|Department of Physics and Center for Biological Physics, Arizona State University, Tempe, AZ, United States of America.|Department of Physics and Center for Biological Physics, Arizona State University, Tempe, AZ, United States of America.', 'United States|United States|United States|United States', 0, 'Acyl-CoA Dehydrogenase|Animals|Computational Biology|Computer Simulation|Cytochrome Reductases|Disease Susceptibility|Genomics|Humans|Imaging, Three-Dimensional|Molecular Conformation|Muramidase|Neurons|Normal Distribution|Phenotype|Protein Conformation|Protein Isoforms|Proteins|ROC Curve|Rats', 'Journal Article', '10.1371/journal.pcbi.1006626', '30496278', 'The conformational dynamics of proteins is rarely used in methodologies used to predict the impact of genetic mutations due to the paucity of three-dimensional protein structures as compared to the vast number of available sequences. Until now a three-dimensional (3D) structure has been required to predict the conformational dynamics of a protein. We introduce an approach that estimates the conformational dynamics of a protein, without relying on structural information. This de novo approach utilizes coevolving residues identified from a multiple sequence alignment (MSA) using Potts models. These coevolving residues are used as contacts in a Gaussian network model (GNM) to obtain protein dynamics. B-factors calculated using sequence-based GNM (Seq-GNM) are in agreement with crystallographic B-factors as well as theoretical B-factors from the original GNM that utilizes the 3D structure. Moreover, we demonstrate the ability of the calculated B-factors from the Seq-GNM approach to discriminate genomic variants according to their phenotypes for a wide range of proteins. These results suggest that protein dynamics can be approximated based on sequence information alone, making it possible to assess the phenotypes of nSNVs in cases where a 3D structure is unknown. We hope this work will promote the use of dynamics information in genetic disease prediction at scale by circumventing the need for 3D structures.'),
(89348, 2018, 'plos', 'Deterministic response strategies in a trial-and-error learning task', 'Mohr, Holger|Zwosta, Katharina|Markovic, Dimitrije|Bitzer, Sebastian|Wolfensteller, Uta|Ruge, Hannes', 'Department of Psychology, Technische Universität Dresden, Dresden, Germany.|Department of Psychology, Technische Universität Dresden, Dresden, Germany.|Department of Psychology, Technische Universität Dresden, Dresden, Germany.|Department of Psychology, Technische Universität Dresden, Dresden, Germany.|Department of Psychology, Technische Universität Dresden, Dresden, Germany.|Department of Psychology, Technische Universität Dresden, Dresden, Germany.', 'Germany|Germany|Germany|Germany|Germany|Germany', 2, 'Adolescent|Adult|Cognition|Computational Biology|Female|Humans|Learning|Learning Curve|Likelihood Functions|Male|Memory|Probability|Reaction Time|Reinforcement (Psychology)|Reproducibility of Results|Software|Young Adult', 'Journal Article', '10.1371/journal.pcbi.1006621', '30496285', 'Trial-and-error learning is a universal strategy for establishing which actions are beneficial or harmful in new environments. However, learning stimulus-response associations solely via trial-and-error is often suboptimal, as in many settings dependencies among stimuli and responses can be exploited to increase learning efficiency. Previous studies have shown that in settings featuring such dependencies, humans typically engage high-level cognitive processes and employ advanced learning strategies to improve their learning efficiency. Here we analyze in detail the initial learning phase of a sample of human subjects (N = 85) performing a trial-and-error learning task with deterministic feedback and hidden stimulus-response dependencies. Using computational modeling, we find that the standard Q-learning model cannot sufficiently explain human learning strategies in this setting. Instead, newly introduced deterministic response models, which are theoretically optimal and transform stimulus sequences unambiguously into response sequences, provide the best explanation for 50.6% of the subjects. Most of the remaining subjects either show a tendency towards generic optimal learning (21.2%) or at least partially exploit stimulus-response dependencies (22.3%), while a few subjects (5.9%) show no clear preference for any of the employed models. After the initial learning phase, asymptotic learning performance during the subsequent practice phase is best explained by the standard Q-learning model. Our results show that human learning strategies in the presented trial-and-error learning task go beyond merely associating stimuli and responses via incremental reinforcement. Specifically during initial learning, high-level cognitive processes support sophisticated learning strategies that increase learning efficiency while keeping memory demands and computational efforts bounded. The good asymptotic fit of the Q-learning model indicates that these cognitive processes are successively replaced by the formation of stimulus-response associations over the course of learning.');
INSERT INTO `papers` (`id`, `ano`, `journal`, `titulo`, `autores`, `afiliacao`, `pais`, `citacoes`, `palavra_chave`, `categorias`, `doi`, `pubmed`, `abstract`) VALUES
(89349, 2018, 'plos', 'How pupil responses track value-based decision-making during and after reinforcement learning', 'Van Slooten, Joanne C|Jahfari, Sara|Knapen, Tomas|Theeuwes, Jan', 'Department of Experimental and Applied Psychology, Vrije Universiteit, Amsterdam, Noord-Holland, The Netherlands.|Spinoza Centre for Neuroimaging, Royal Academy of Sciences, Amsterdam, Noord-Holland, The Netherlands.|Department of Experimental and Applied Psychology, Vrije Universiteit, Amsterdam, Noord-Holland, The Netherlands.|Department of Experimental and Applied Psychology, Vrije Universiteit, Amsterdam, Noord-Holland, The Netherlands.', 'Netherlands|Netherlands|Netherlands|Netherlands', 1, 'Adolescent|Adult|Bayes Theorem|Choice Behavior|Cognition|Computational Biology|Computer Simulation|Decision Making|Female|Humans|Learning|Male|Probability|Pupil|Reinforcement (Psychology)|Reproducibility of Results|Reward|Uncertainty|Young Adult', 'Journal Article', '10.1371/journal.pcbi.1006632', '30500813', 'Cognition can reveal itself in the pupil, as latent cognitive processes map onto specific pupil responses. For instance, the pupil dilates when we make decisions and these pupil size fluctuations reflect decision-making computations during and after a choice. Surprisingly little is known, however, about how pupil responses relate to decisions driven by the learned value of stimuli. This understanding is important, as most real-life decisions are guided by the outcomes of earlier choices. The goal of this study was to investigate which cognitive processes the pupil reflects during value-based decision-making. We used a reinforcement learning task to study pupil responses during value-based decisions and subsequent decision evaluations, employing computational modeling to quantitatively describe the underlying cognitive processes. We found that the pupil closely tracks reinforcement learning processes independently across participants and across trials. Prior to choice, the pupil dilated as a function of trial-by-trial fluctuations in value beliefs about the to-be chosen option and predicted an individuals tendency to exploit high value options. After feedback a biphasic pupil response was observed, the amplitude of which correlated with participants learning rates. Furthermore, across trials, early feedback-related dilation scaled with value uncertainty, whereas later constriction scaled with signed reward prediction errors. These findings show that pupil size fluctuations can provide detailed information about the computations underlying value-based decisions and the subsequent updating of value beliefs. As these processes are affected in a host of psychiatric disorders, our results indicate that pupillometry can be used as an accessible tool to non-invasively study the processes underlying ongoing reinforcement learning in the clinic.'),
(89350, 2018, 'plos', 'Mechanistic insight into spontaneous transition from cellular alternans to arrhythmia-A simulation study', 'Wang, Wei|Zhang, Shanzhuo|Ni, Haibo|Garratt, Clifford J|Boyett, Mark R|Hancox, Jules C|Zhang, Henggui', 'Biological Physics Group, School of Physics & Astronomy, The University of Manchester, Manchester, United Kingdom.|School of Computer Science and Technology, Harbin Institute of Technology, Harbin, China.|Biological Physics Group, School of Physics & Astronomy, The University of Manchester, Manchester, United Kingdom.|Manchester Heart Centre, Manchester Royal Infirmary, Manchester, United Kingdom.|Manchester Heart Centre, Manchester Royal Infirmary, Manchester, United Kingdom.|Biological Physics Group, School of Physics & Astronomy, The University of Manchester, Manchester, United Kingdom.|Biological Physics Group, School of Physics & Astronomy, The University of Manchester, Manchester, United Kingdom.', 'United Kingdom|China|United Kingdom|United Kingdom|United Kingdom|United Kingdom|United Kingdom', 6, 'Action Potentials|Algorithms|Animals|Anisotropy|Arrhythmias, Cardiac|Biomarkers|Computational Biology|Computer Simulation|Electrocardiography|Heart|Heart Atria|Heart Conduction System|Heart Rate|Heart Ventricles|Humans|Image Processing, Computer-Assisted|Models, Cardiovascular|Rabbits', 'Journal Article', '10.1371/journal.pcbi.1006594', '30500818', 'Cardiac electrical alternans (CEA), manifested as T-wave alternans in ECG, is a clinical biomarker for predicting cardiac arrhythmias and sudden death. However, the mechanism underlying the spontaneous transition from CEA to arrhythmias remains incompletely elucidated. In this study, multiscale rabbit ventricular models were used to study the transition and a potential role of INa in perpetuating such a transition. It was shown CEA evolved into either concordant or discordant action potential (AP) conduction alternans in a homogeneous one-dimensional tissue model, depending on tissue AP duration and conduction velocity (CV) restitution properties. Discordant alternans was able to cause conduction failure in the model, which was promoted by impaired sodium channel with either a reduced or increased channel current. In a two-dimensional homogeneous tissue model, a combined effect of rate- and curvature-dependent CV broke-up alternating wavefronts at localised points, facilitating a spontaneous transition from CEA to re-entry. Tissue inhomogeneity or anisotropy further promoted break-up of re-entry, leading to multiple wavelets. Similar observations have also been seen in human atrial cellular and tissue models. In conclusion, our results identify a mechanism by which CEA spontaneously evolves into re-entry without a requirement for premature ventricular complexes or pre-existing tissue heterogeneities, and demonstrated the important pro-arrhythmic role of impaired sodium channel activity. These findings are model-independent and have potential human relevance.'),
(89351, 2018, 'plos', 'Tox_(R)CNN: Deep learning-based nuclei profiling tool for drug toxicity screening', 'Jimenez-Carretero, Daniel|Abrishami, Vahid|Fernández-de-Manuel, Laura|Palacios, Irene|Quílez-Álvarez, Antonio|Díez-Sánchez, Alberto|Del Pozo, Miguel A|Montoya, María C', 'Cellomics Unit, Cell & Developmental Biology Area, Centro Nacional de Investigaciones Cardiovasculares (CNIC), Madrid, Spain.|Cellomics Unit, Cell & Developmental Biology Area, Centro Nacional de Investigaciones Cardiovasculares (CNIC), Madrid, Spain.|Cellomics Unit, Cell & Developmental Biology Area, Centro Nacional de Investigaciones Cardiovasculares (CNIC), Madrid, Spain.|Cellomics Unit, Cell & Developmental Biology Area, Centro Nacional de Investigaciones Cardiovasculares (CNIC), Madrid, Spain.|Cellomics Unit, Cell & Developmental Biology Area, Centro Nacional de Investigaciones Cardiovasculares (CNIC), Madrid, Spain.|Mechanoadaptation and Caveolae biology, Cell & Developmental Biology Area, Centro Nacional de Investigaciones Cardiovasculares (CNIC), Madrid, Spain.|Mechanoadaptation and Caveolae biology, Cell & Developmental Biology Area, Centro Nacional de Investigaciones Cardiovasculares (CNIC), Madrid, Spain.|Cellomics Unit, Cell & Developmental Biology Area, Centro Nacional de Investigaciones Cardiovasculares (CNIC), Madrid, Spain.', 'Spain|Spain|Spain|Spain|Spain|Spain|Spain|Spain', 5, 'Algorithms|Automation|Cell Nucleus|Deep Learning|Drug-Related Side Effects and Adverse Reactions|Fluorescent Dyes|Image Interpretation, Computer-Assisted|Indoles|Neural Networks (Computer)', 'Journal Article', '10.1371/journal.pcbi.1006238', '30500821', 'Toxicity is an important factor in failed drug development, and its efficient identification and prediction is a major challenge in drug discovery. We have explored the potential of microscopy images of fluorescently labeled nuclei for the prediction of toxicity based on nucleus pattern recognition. Deep learning algorithms obtain abstract representations of images through an automated process, allowing them to efficiently classify complex patterns, and have become the state-of-the art in machine learning for computer vision. Here, deep convolutional neural networks (CNN) were trained to predict toxicity from images of DAPI-stained cells pre-treated with a set of drugs with differing toxicity mechanisms. Different cropping strategies were used for training CNN models, the nuclei-cropping-based Tox_CNN model outperformed other models classifying cells according to health status. Tox_CNN allowed automated extraction of feature maps that clustered compounds according to mechanism of action. Moreover, fully automated region-based CNNs (RCNN) were implemented to detect and classify nuclei, providing per-cell toxicity prediction from raw screening images. We validated both Tox_(R)CNN models for detection of pre-lethal toxicity from nuclei images, which proved to be more sensitive and have broader specificity than established toxicity readouts. These models predicted toxicity of drugs with mechanisms of action other than those they had been trained for and were successfully transferred to other cell assays. The Tox_(R)CNN models thus provide robust, sensitive, and cost-effective tools for in vitro screening of drug-induced toxicity. These models can be adopted for compound prioritization in drug screening campaigns, and could thereby increase the efficiency of drug discovery.'),
(89352, 2018, 'plos', 'Chain organization of human interphase chromosome determines the spatiotemporal dynamics of chromatin loci', 'Liu, Lei|Shi, Guang|Thirumalai, D|Hyeon, Changbong', 'Korea Institute for Advanced Study, Seoul, Korea.|Biophysics Program, Institute for Physical Science and Technology, University of Maryland, College Park, MD, USA.|Department of Chemistry, The University of Texas at Austin, Austin, TX, USA.|Korea Institute for Advanced Study, Seoul, Korea.', 'United States|United States|United States|United States', 0, 'Algorithms|Chromatin|Chromosomes, Human|Chromosomes, Human, Pair 10|Computational Biology|Computer Simulation|Euchromatin|Heterochromatin|Humans|Interphase|Lymphocytes|Models, Genetic|Molecular Conformation', 'Journal Article', '10.1371/journal.pcbi.1006617', '30507936', 'We investigate spatiotemporal dynamics of human interphase chromosomes by employing a heteropolymer model that incorporates the information of human chromosomes inferred from Hi-C data. Despite considerable heterogeneities in the chromosome structures generated from our model, chromatins are organized into crumpled globules with space-filling (SF) statistics characterized by a single universal scaling exponent (xcexbd = 1/3), and this exponent alone can offer a quantitative account of experimentally observed, many different features of chromosome dynamics. The local chromosome structures, whose scale corresponds to that of topologically associated domains (xe2x88xbc 0.1 - 1 Mb), display dynamics with a fast relaxation time (xe2x89xb2 1 - 10 sec), in contrast, the long-range spatial reorganization of the entire chromatin ([Formula: see text] Mb) occurs on a much slower time scale (xe2x89xb3 hour), providing the dynamic basis of cell-to-cell variability and glass-like behavior of chromosomes. Biological activities, modeled using stronger isotropic white noises added to active loci, accelerate the relaxation dynamics of chromatin domains associated with the low frequency modes and induce phase segregation between the active and inactive loci. Surprisingly, however, they do not significantly change the dynamics at local scales from those obtained under passive conditions. Our study underscores the role of chain organization of chromosome in determining the spatiotemporal dynamics of chromatin loci.'),
(89353, 2018, 'plos', 'Detection and analysis of spatiotemporal patterns in brain activity', 'Townsend, Rory G|Gong, Pulin', 'School of Physics, The University of Sydney, NSW, Australia.|School of Physics, The University of Sydney, NSW, Australia.', 'Australia|Australia', 0, 'Animals|Brain|Brain Mapping|Callithrix|Computational Biology|Computer Simulation|Evoked Potentials, Visual|Male|Mice|Models, Neurological|Nerve Net|Optogenetics|Software|Visual Cortex', 'Journal Article', '10.1371/journal.pcbi.1006643', '30507937', 'There is growing evidence that population-level brain activity is often organized into propagating waves that are structured in both space and time. Such spatiotemporal patterns have been linked to brain function and observed across multiple recording methodologies and scales. The ability to detect and analyze these patterns is thus essential for understanding the working mechanisms of neural circuits. Here we present a mathematical and computational framework for the identification and analysis of multiple classes of wave patterns in neural population-level recordings. By drawing a conceptual link between spatiotemporal patterns found in the brain and coherent structures such as vortices found in turbulent flows, we introduce velocity vector fields to characterize neural population activity. These vector fields are calculated for both phase and amplitude of oscillatory neural signals by adapting optical flow estimation methods from the field of computer vision. Based on these velocity vector fields, we then introduce order parameters and critical point analysis to detect and characterize a diverse range of propagating wave patterns, including planar waves, sources, sinks, spiral waves, and saddle patterns. We also introduce a novel vector field decomposition method that extracts the dominant spatiotemporal structures in a recording. This enables neural data to be represented by the activity of a small number of independent spatiotemporal modes, providing an alternative to existing dimensionality reduction techniques which separate space and time components. We demonstrate the capabilities of the framework and toolbox with simulated data, local field potentials from marmoset visual cortex and optical voltage recordings from whole mouse cortex, and we show that pattern dynamics are non-random and are modulated by the presence of visual stimuli. These methods are implemented in a MATLAB toolbox, which is freely available under an open-source licensing agreement.'),
(89354, 2018, 'plos', 'TAMMiCol: Tool for analysis of the morphology of microbial colonies', 'Tronnolone, Hayden|Gardner, Jennifer M|Sundstrom, Joanna F|Jiranek, Vladimir|Oliver, Stephen G|Binder, Benjamin J', 'School of Mathematical Sciences, University of Adelaide, Adelaide, Australia.|Department of Wine and Food Science, University of Adelaide, Adelaide, Australia.|Department of Wine and Food Science, University of Adelaide, Adelaide, Australia.|Department of Wine and Food Science, University of Adelaide, Adelaide, Australia.|Cambridge Systems Biology Centre and Department of Biochemistry, University of Cambridge, Cambridge, United Kingdom.|School of Mathematical Sciences, University of Adelaide, Adelaide, Australia.', 'Australia|Australia|Australia|Australia|United Kingdom|Australia', 1, 'Ammonium Sulfate|Bacillus subtilis|Biofilms|Computational Biology|Culture Media|Databases, Factual|Image Processing, Computer-Assisted|Microbiota|Saccharomyces cerevisiae|Software', 'Journal Article', '10.1371/journal.pcbi.1006629', '30507938', 'Many microbes are studied by examining colony morphology via two-dimensional top-down images. The quantification of such images typically requires each pixel to be labelled as belonging to either the colony or background, producing a binary image. While this may be achieved manually for a single colony, this process is infeasible for large datasets containing thousands of images. The software Tool for Analysis of the Morphology of Microbial Colonies (TAMMiCol) has been developed to efficiently and automatically convert colony images to binary. TAMMiCol exploits the structure of the images to choose a thresholding tolerance and produce a binary image of the colony. The images produced are shown to compare favourably with images processed manually, while TAMMiCol is shown to outperform standard segmentation methods. Multiple images may be imported together for batch processing, while the binary data may be exported as a CSV or MATLAB MAT file for quantification, or analysed using statistics built into the software. Using the in-built statistics, it is found that images produced by TAMMiCol yield values close to those computed from binary images processed manually. Analysis of a new large dataset using TAMMiCol shows that colonies of Saccharomyces cerevisiae reach a maximum level of filamentous growth once the concentration of ammonium sulfate is reduced to 200 xcexbcM. TAMMiCol is accessed through a graphical user interface, making it easy to use for those without specialist knowledge of image processing, statistical methods or coding.'),
(89355, 2018, 'plos', 'A stochastic framework to model axon interactions within growing neuronal populations', 'Razetti, Agustina|Medioni, Caroline|Malandain, Grégoire|Besse, Florence|Descombes, Xavier', 'Université Côte dAzur, INRIA, CNRS, I3S, Nice, France.|Université Côte dAzur, CNRS, Inserm, iBV, Nice, France.|Université Côte dAzur, INRIA, CNRS, I3S, Nice, France.|Université Côte dAzur, CNRS, Inserm, iBV, Nice, France.|Université Côte dAzur, INRIA, CNRS, I3S, Nice, France.', 'France|France|France|France|France', 2, 'Algorithms|Animals|Axons|Brain|Computational Biology|Computer Simulation|Drosophila melanogaster|Imaging, Three-Dimensional|Models, Neurological|Mushroom Bodies|Mutation|Nerve Regeneration|Neurogenesis|Neurons|Phenotype|Stochastic Processes', 'Journal Article', '10.1371/journal.pcbi.1006627', '30507939', 'The confined and crowded environment of developing brains imposes spatial constraints on neuronal cells that have evolved individual and collective strategies to optimize their growth. These include organizing neurons into populations extending their axons to common target territories. How individual axons interact with each other within such populations to optimize innervation is currently unclear and difficult to analyze experimentally in vivo. Here, we developed a stochastic model of 3D axon growth that takes into account spatial environmental constraints, physical interactions between neighboring axons, and branch formation. This general, predictive and robust model, when fed with parameters estimated on real neurons from the Drosophila brain, enabled the study of the mechanistic principles underlying the growth of axonal populations. First, it provided a novel explanation for the diversity of growth and branching patterns observed in vivo within populations of genetically identical neurons. Second, it uncovered that axon branching could be a strategy optimizing the overall growth of axons competing with others in contexts of high axonal density. The flexibility of this framework will make it possible to investigate the rules underlying axon growth and regeneration in the context of various neuronal populations.'),
(89356, 2018, 'plos', 'Performance of convolutional neural networks for identification of bacteria in 3D microscopy datasets', 'Hay, Edouard A|Parthasarathy, Raghuveer', 'Department of Physics, Institute of Molecular Biology, Materials Science Institute, University of Oregon, Eugene, Oregon, United States of America.|Department of Physics, Institute of Molecular Biology, Materials Science Institute, University of Oregon, Eugene, Oregon, United States of America.', 'United States|United States', 0, 'Algorithms|Animals|Bacteria|Computational Biology|Databases, Factual|Humans|Imaging, Three-Dimensional|Intestines|Microscopy, Fluorescence|Neural Networks (Computer)|Pseudomonas|Support Vector Machine|Vibrio|Zebrafish', 'Journal Article', '10.1371/journal.pcbi.1006628', '30507940', 'Three-dimensional microscopy is increasingly prevalent in biology due to the development of techniques such as multiphoton, spinning disk confocal, and light sheet fluorescence microscopies. These methods enable unprecedented studies of life at the microscale, but bring with them larger and more complex datasets. New image processing techniques are therefore called for to analyze the resulting images in an accurate and efficient manner. Convolutional neural networks are becoming the standard for classification of objects within images due to their accuracy and generalizability compared to traditional techniques. Their application to data derived from 3D imaging, however, is relatively new and has mostly been in areas of magnetic resonance imaging and computer tomography. It remains unclear, for images of discrete cells in variable backgrounds as are commonly encountered in fluorescence microscopy, whether convolutional neural networks provide sufficient performance to warrant their adoption, especially given the challenges of human comprehension of their classification criteria and their requirements of large training datasets. We therefore applied a 3D convolutional neural network to distinguish bacteria and non-bacterial objects in 3D light sheet fluorescence microscopy images of larval zebrafish intestines. We find that the neural network is as accurate as human experts, outperforms random forest and support vector machine classifiers, and generalizes well to a different bacterial species through the use of transfer learning. We also discuss network design considerations, and describe the dependence of accuracy on dataset size and data augmentation. We provide source code, labeled data, and descriptions of our analysis pipeline to facilitate adoption of convolutional neural network analysis for three-dimensional microscopy data.'),
(89357, 2018, 'plos', 'A comprehensive ensemble model for comparing the allosteric effect of ordered and disordered proteins', 'Zhang, Luhao|Li, Maodong|Liu, Zhirong', 'College of Chemistry and Molecular Engineering, Peking University, Beijing, China.|Center for Quantitative Biology, Peking University, Beijing, China.|College of Chemistry and Molecular Engineering, Peking University, Beijing, China.', 'China|China|China', 6, 'Allosteric Regulation|Amino Acids|Entropy|Intrinsically Disordered Proteins|Models, Molecular|Molecular Dynamics Simulation|Probability|Protein Conformation|Proteins|Thermodynamics', 'Journal Article', '10.1371/journal.pcbi.1006393', '30507941', 'Intrinsically disordered proteins/regions (IDPs/IDRs) are prevalent in allosteric regulation. It was previously thought that intrinsic disorder is favorable for maximizing the allosteric coupling. Here, we propose a comprehensive ensemble model to compare the roles of both order-order transition and disorder-order transition in allosteric effect. It is revealed that the MWC pathway (order-order transition) has a higher probability than the EAM pathway (disorder-order transition) in allostery, suggesting a complicated role of IDPs/IDRs in regulatory proteins. In addition, an analytic formula for the maximal allosteric coupling response is obtained, which shows that too stable or too unstable state is unfavorable to endow allostery, and is thus helpful for rational design of allosteric drugs.'),
(89358, 2018, 'plos', 'Regulation of harvester ant foraging as a closed-loop excitable system', 'Pagliara, Renato|Gordon, Deborah M|Leonard, Naomi Ehrich', 'Department of Mechanical and Aerospace Engineering, Princeton University, Princeton, New Jersey, United States of America.|Department of Biology, Stanford University, Stanford, California, United States of America.|Department of Mechanical and Aerospace Engineering, Princeton University, Princeton, New Jersey, United States of America.', 'Jersey|United States|Jersey', 0, 'Animal Communication|Animals|Ants|Behavior, Animal|Computer Simulation|Feeding Behavior|Humidity|Models, Biological|Social Behavior|Temperature', 'Journal Article', '10.1371/journal.pcbi.1006200', '30513076', 'Ant colonies regulate activity in response to changing conditions without using centralized control. Desert harvester ant colonies forage for seeds, and regulate foraging to manage a tradeoff between spending and obtaining water. Foragers lose water while outside in the dry air, but ants obtain water by metabolizing the fats in the seeds they eat. Previous work shows that the rate at which an outgoing forager leaves the nest depends on its recent rate of brief antennal contacts with incoming foragers carrying food. We examine how this process can yield foraging rates that are robust to uncertainty and responsive to temperature and humidity across minute-to-hour timescales. To explore possible mechanisms, we develop a low-dimensional analytical model with a small number of parameters that captures observed foraging behavior. The model uses excitability dynamics to represent response to interactions inside the nest and a random delay distribution to represent foraging time outside the nest. We show how feedback from outgoing foragers returning to the nest stabilizes the incoming and outgoing foraging rates to a common value determined by the volatility of available foragers. The model exhibits a critical volatility above which there is sustained foraging at a constant rate and below which foraging stops. To explain how foraging rates adjust to temperature and humidity, we propose that foragers modify their volatility after they leave the nest and become exposed to the environment. Our study highlights the importance of feedback in the regulation of foraging activity and shows how modulation of volatility can explain how foraging activity responds to conditions and varies across colonies. Our model elucidates the role of feedback across many timescales in collective behavior, and may be generalized to other systems driven by excitable dynamics, such as neuronal networks.'),
(89359, 2018, 'plos', 'The empirical characteristics of human pattern vision defy theoretically-driven expectations', 'Neri, Peter', 'Laboratoire des Systèmes Perceptifs, Département détudes cognitives, École normale supérieure, PSL University, CNRS, 75005 Paris, France.', 'France', 0, 'Computational Biology|Computer Simulation|Humans|Models, Neurological|Neurons|Nonlinear Dynamics|Pattern Recognition, Visual|Vision, Ocular|Visual Perception', 'Journal Article', '10.1371/journal.pcbi.1006585', '30513091', 'Contrast is the most fundamental property of images. Consequently, any comprehensive model of biological vision must incorporate this attribute and provide a veritable description of its impact on visual perception. Current theoretical and computational models predict that vision should modify its characteristics at low contrast: for example, it should become broader (more lowpass) to protect from noise, as often demonstrated by individual neurons. We find that the opposite is true for human discrimination of elementary image elements: vision becomes sharper, not broader, as contrast approaches threshold levels. Furthermore, it suffers from increased internal variability at low contrast and it transitions from a surprisingly linear regime at high contrast to a markedly nonlinear processing mode in the low-contrast range. These characteristics are hard-wired in that they happen on a single trial without memory or expectation. Overall, the empirical results urge caution when attempting to interpret human vision from the standpoint of optimality and related theoretical constructs. Direct measurements of this phenomenon indicate that the actual constraints derive from intrinsic architectural features, such as the co-existence of complex-cell-like and simple-cell-like components. Small circuits built around these elements can indeed account for the empirical results, but do not appear to operate in a manner that conforms to optimality even approximately. More generally, our results provide a compelling demonstration of how far we still are from securing an adequate computational account of the most basic operations carried out by human vision.'),
(89360, 2018, 'plos', 'Insights on the impact of mitochondrial organisation on bioenergetics in high-resolution computational models of cardiac cell architecture', 'Ghosh, Shouryadipta|Tran, Kenneth|Delbridge, Lea M D|Hickey, Anthony J R|Hanssen, Eric|Crampin, Edmund J|Rajagopal, Vijay', 'Cell Structure and Mechanobiology Group, Dept. of Biomedical Engineering, Melbourne School of Engineering, University of Melbourne, Melbourne, Australia.|Auckland Bioengineering Institute, University of Auckland, Auckland New Zealand.|Department of Physiology, University of Melbourne, Parkville, Australia.|School of Biological Sciences, University of Auckland, Auckland, New Zealand.|Advanced Microscopy Facility, Bio21 Molecular Science and Biotechnology Institute, The University of Melbourne, Melbourne, Australia.|Systems Biology Laboratory, School of Mathematics and Statistics, and Melbourne School of Engineering, University of Melbourne, Melbourne, Australia.|Cell Structure and Mechanobiology Group, Dept. of Biomedical Engineering, Melbourne School of Engineering, University of Melbourne, Melbourne, Australia.', 'Australia|New Zealand|Australia|New Zealand|Australia|Australia|Australia', 3, 'Adenosine Diphosphate|Adenosine Triphosphate|Animals|Biological Transport, Active|Computational Biology|Computer Simulation|Creatine|Creatine Kinase|Diabetic Cardiomyopathies|Energy Metabolism|Male|Microscopy, Electron, Transmission|Mitochondria, Heart|Models, Cardiovascular|Myocytes, Cardiac|Oxygen Consumption|Phosphocreatine|Rats|Rats, Sprague-Dawley', 'Journal Article', '10.1371/journal.pcbi.1006640', '30517098', 'Recent electron microscopy data have revealed that cardiac mitochondria are not arranged in crystalline columns but are organised with several mitochondria aggregated into columns of varying sizes spanning the cell cross-section. This raises the question-how does the mitochondrial arrangement affect the metabolite distributions within cardiomyocytes and what is its impact on force dynamics? Here, we address this question by employing finite element modeling of cardiac bioenergetics on computational meshes derived from electron microscope images. Our results indicate that heterogeneous mitochondrial distributions can lead to significant spatial variation across the cell in concentrations of inorganic phosphate, creatine (Cr) and creatine phosphate (PCr). However, our model predicts that sufficient activity of the creatine kinase (CK) system, coupled with rapid diffusion of Cr and PCr, maintains near uniform ATP and ADP ratios across the cell cross sections. This homogenous distribution of ATP and ADP should also evenly distribute force production and twitch duration with contraction. These results suggest that the PCr shuttle and associated enzymatic reactions act to maintain uniform force dynamics in the cell despite the heterogeneous mitochondrial organization. However, our model also predicts that under hypoxia activity of mitochondrial CK enzymes and diffusion of high-energy phosphate compounds may be insufficient to sustain uniform ATP/ADP distribution and hence force generation.'),
(89361, 2018, 'plos', 'Bayesian adaptive dual control of deep brain stimulation in a computational model of Parkinsons disease', 'Grado, Logan L|Johnson, Matthew D|Netoff, Theoden I', 'Department of Biomedical Engineering, University of Minnesota, Minneapolis, Minnesota, United States of America.|Department of Biomedical Engineering, University of Minnesota, Minneapolis, Minnesota, United States of America.|Department of Biomedical Engineering, University of Minnesota, Minneapolis, Minnesota, United States of America.', 'United States|United States|United States', 5, 'Algorithms|Bayes Theorem|Computer Simulation|Deep Brain Stimulation|Feedback|Humans|Models, Neurological|Neurons|Parkinson Disease|Thalamus', 'Journal Article', '10.1371/journal.pcbi.1006606', '30521519', 'In this paper, we present a novel Bayesian adaptive dual controller (ADC) for autonomously programming deep brain stimulation devices. We evaluated the Bayesian ADCs performance in the context of reducing beta power in a computational model of Parkinsons disease, in which it was tasked with finding the set of stimulation parameters which optimally reduced beta power as fast as possible. Here, the Bayesian ADC has dual goals: (a) to minimize beta power by exploiting the best parameters found so far, and (b) to explore the space to find better parameters, thus allowing for better control in the future. The Bayesian ADC is composed of two parts: an inner parameterized feedback stimulator and an outer parameter adjustment loop. The inner loop operates on a short time scale, delivering stimulus based upon the phase and power of the beta oscillation. The outer loop operates on a long time scale, observing the effects of the stimulation parameters and using Bayesian optimization to intelligently select new parameters to minimize the beta power. We show that the Bayesian ADC can efficiently optimize stimulation parameters, and is superior to other optimization algorithms. The Bayesian ADC provides a robust and general framework for tuning stimulation parameters, can be adapted to use any feedback signal, and is applicable across diseases and stimulator designs.'),
(89362, 2018, 'plos', 'Molecular basis for the increased affinity of an RNA recognition motif with re-engineered specificity: A molecular dynamics and enhanced sampling simulations study', 'Bochicchio, Anna|Krepl, Miroslav|Yang, Fan|Varani, Gabriele|Sponer, Jiri|Carloni, Paolo', 'Computational Biomedicine, Institute for Advanced Simulation IAS-5 and Institute of Neuroscience and Medicine INM-9, Forschungszentrum Jülich, Jülich, Germany.|Institute of Biophysics of the Czech Academy of Sciences, Brno, Czech Republic.|Department of Chemistry, University of Washington, Seattle, Washington, United States of America.|Department of Chemistry, University of Washington, Seattle, Washington, United States of America.|Institute of Biophysics of the Czech Academy of Sciences, Brno, Czech Republic.|Computational Biomedicine, Institute for Advanced Simulation IAS-5 and Institute of Neuroscience and Medicine INM-9, Forschungszentrum Jülich, Jülich, Germany.', 'Germany|-|United States|United States|-|Germany', 0, 'Amino Acid Sequence|Binding Sites|Computational Biology|Humans|MicroRNAs|Models, Molecular|Molecular Dynamics Simulation|Nuclear Magnetic Resonance, Biomolecular|Nucleic Acid Conformation|Protein Binding|Protein Engineering|RNA|RNA Recognition Motif|RNA Stability|RNA-Binding Proteins', 'Journal Article', '10.1371/journal.pcbi.1006642', '30521520', 'The RNA recognition motif (RRM) is the most common RNA binding domain across eukaryotic proteins. It is therefore of great value to engineer its specificity to target RNAs of arbitrary sequence. This was recently achieved for the RRM in Rbfox protein, where four mutations R118D, E147R, N151S, and E152T were designed to target the precursor to the oncogenic miRNA 21. Here, we used a variety of molecular dynamics-based approaches to predict specific interactions at the binding interface. Overall, we have run approximately 50 microseconds of enhanced sampling and plain molecular dynamics simulations on the engineered complex as well as on the wild-type Rbfox·pre-miRNA 20b from which the mutated systems were designed. Comparison with the available NMR data on the wild type molecules (protein, RNA, and their complex) served to establish the accuracy of the calculations. Free energy calculations suggest that further improvements in affinity and selectivity are achieved by the S151T replacement.'),
(89363, 2018, 'plos', 'Function and energy consumption constrain neuronal biophysics in a canonical computation: Coincidence detection', 'Remme, Michiel W H|Rinzel, John|Schreiber, Susanne', 'Institute for Theoretical Biology, Department of Biology, Humboldt-Universität zu Berlin, Berlin, Germany.|Center for Neural Science, New York University, New York, New York, United States of America.|Institute for Theoretical Biology, Department of Biology, Humboldt-Universität zu Berlin, Berlin, Germany.', 'Germany|United States|Germany', 0, 'Action Potentials|Animals|Auditory Pathways|Biophysical Phenomena|Computational Biology|Computer Simulation|Energy Metabolism|Evoked Potentials, Auditory|Gerbillinae|Humans|Models, Neurological|Neural Conduction|Neurons|Superior Olivary Complex|Synaptic Transmission', 'Journal Article', '10.1371/journal.pcbi.1006612', '30521528', 'Neural morphology and membrane properties vary greatly between cell types in the nervous system. The computations and local circuit connectivity that neurons support are thought to be the key factors constraining the cells biophysical properties. Nevertheless, additional constraints can be expected to further shape neuronal design. Here, we focus on a particularly energy-intense system (as indicated by metabolic markers): principal neurons in the medial superior olive (MSO) nucleus of the auditory brainstem. Based on a modeling approach, we show that a trade-off between the level of performance of a functionally relevant computation and energy consumption predicts optimal ranges for cell morphology and membrane properties. The biophysical parameters appear most strongly constrained by functional needs, while energy use is minimized as long as function can be maintained. The key factors that determine model performance and energy consumption are 1) the saturation of the synaptic conductance input and 2) the temporal resolution of the postsynaptic signals as they reach the soma, which is largely determined by active membrane properties. MSO cells seem to operate close to pareto optimality, i.e., the trade-off boundary between performance and energy consumption that is formed by the set of optimal models. Good performance for drastically lower costs could in theory be achieved by small neurons without dendrites, as seen in the avian auditory system, pointing to additional constraints for mammalian MSO cells, including their circuit connectivity.'),
(89364, 2018, 'plos', 'Coherency of circadian rhythms in the SCN is governed by the interplay of two coupling factors', 'Tokuda, Isao T|Ono, Daisuke|Honma, Sato|Honma, Ken-Ichi|Herzel, Hanspeter', 'Department of Mechanical Engineering, Ritsumeikan University, Shiga, Japan.|Photonic Bioimaging Section, Research Center for Cooperative Projects, Hokkaido University Graduate School of Medicine, Sapporo, Japan.|Department of Chronomedicine, Hokkaido University Graduate School of Medicine, Sapporo, Japan.|Department of Chronomedicine, Hokkaido University Graduate School of Medicine, Sapporo, Japan.|Institute for Theoretical Biology, Charité and Humboldt University of Berlin, Berlin, Germany.', 'Japan|Japan|Japan|Japan|Germany', 0, 'Animals|Arginine Vasopressin|Circadian Clocks|Circadian Rhythm|Mice|Mice, Inbred C57BL|Mice, Knockout|Neurons|Neuropeptides|Period Circadian Proteins|Signal Transduction|Suprachiasmatic Nucleus|Vasoactive Intestinal Peptide', 'Journal Article', '10.1371/journal.pcbi.1006607', '30532130', 'Circadian clocks are autonomous oscillators driving daily rhythms in physiology and behavior. In mammals, a network of coupled neurons in the suprachiasmatic nucleus (SCN) is entrained to environmental light-dark cycles and orchestrates the timing of peripheral organs. In each neuron, transcriptional feedbacks generate noisy oscillations. Coupling mediated by neuropeptides such as VIP and AVP lends precision and robustness to circadian rhythms. The detailed coupling mechanisms between SCN neurons are debated. We analyze organotypic SCN slices from neonatal and adult mice in wild-type and multiple knockout conditions. Different degrees of rhythmicity are quantified by pixel-level analysis of bioluminescence data. We use empirical orthogonal functions (EOFs) to characterize spatio-temporal patterns. Simulations of coupled stochastic single cell oscillators can reproduce the diversity of observed patterns. Our combination of data analysis and modeling provides deeper insight into the enormous complexity of the data: (1) Neonatal slices are typically stronger oscillators than adult slices pointing to developmental changes of coupling. (2) Wild-type slices are completely synchronized and exhibit specific spatio-temporal patterns of phases. (3) Some slices of Cry double knockouts obey impaired synchrony that can lead to co-existing rhythms (splitting). (4) The loss of VIP-coupling leads to desynchronized rhythms with few residual local clusters. Additional information was extracted from co-culturing slices with rhythmic neonatal wild-type SCNs. These co-culturing experiments were simulated using external forcing terms representing VIP and AVP signaling. The rescue of rhythmicity via co-culturing lead to surprising results, since a cocktail of AVP-antagonists improved synchrony. Our modeling suggests that these counter-intuitive observations are pointing to an antagonistic action of VIP and AVP coupling. Our systematic theoretical and experimental study shows that dual coupling mechanisms can explain the astonishing complexity of spatio-temporal patterns in SCN slices.'),
(89365, 2018, 'plos', 'Odorant mixtures elicit less variable and faster responses than pure odorants', 'Chan, Ho Ka|Hersperger, Fabian|Marachlian, Emiliano|Smith, Brian H|Locatelli, Fernando|Szyszka, Paul|Nowotny, Thomas', 'Sussex Neuroscience, School of Engineering and Informatics, University of Sussex, Falmer, Brighton, United Kingdom.|Department of Neuroscience, University of Konstanz, Konstanz, Germany.|Instituto de Fisiología, Biología Molecular y Neurociencias (IFIBYNE-UBA-CONICET) and Departamento de Fisiología, Biología Molecular y Celular, Facultad de Ciencias Exactas y Naturales, Universidad de Buenos Aires, Ciudad Universitaria, Buenos Aires, Argentina.|School of Life Sciences, Arizona State University, Tempe, Arizona, United States of America.|Instituto de Fisiología, Biología Molecular y Neurociencias (IFIBYNE-UBA-CONICET) and Departamento de Fisiología, Biología Molecular y Celular, Facultad de Ciencias Exactas y Naturales, Universidad de Buenos Aires, Ciudad Universitaria, Buenos Aires, Argentina.|Department of Neuroscience, University of Konstanz, Konstanz, Germany.|Sussex Neuroscience, School of Engineering and Informatics, University of Sussex, Falmer, Brighton, United Kingdom.', 'United Kingdom|Germany|Argentina|United States|Argentina|Germany|United Kingdom', 7, 'Animals|Bees|Complex Mixtures|Insecta|Models, Theoretical|Odorants|Olfactory Bulb|Olfactory Receptor Neurons|Receptors, Odorant|Smell', 'Journal Article', '10.1371/journal.pcbi.1006536', '30532147', 'In natural environments, odors are typically mixtures of several different chemical compounds. However, the implications of mixtures for odor processing have not been fully investigated. We have extended a standard olfactory receptor model to mixtures and found through its mathematical analysis that odorant-evoked activity patterns are more stable across concentrations and first-spike latencies of receptor neurons are shorter for mixtures than for pure odorants. Shorter first-spike latencies arise from the nonlinear dependence of binding rate on odorant concentration, commonly described by the Hill coefficient, while the more stable activity patterns result from the competition between different ligands for receptor sites. These results are consistent with observations from numerical simulations and physiological recordings in the olfactory system of insects. Our results suggest that mixtures allow faster and more reliable olfactory coding, which could be one of the reasons why animals often use mixtures in chemical signaling.'),
(89366, 2018, 'plos', 'Identifying (un)controllable dynamical behavior in complex networks', 'Rozum, Jordan C|Albert, Réka', 'Department of Physics, The Pennsylvania State University, University Park, PA, USA.|Department of Physics, The Pennsylvania State University, University Park, PA, USA.', 'United States|United States', 0, 'Algorithms|Animals|Body Patterning|Computational Biology|Drosophila melanogaster|Gene Regulatory Networks|Humans|Models, Biological|Receptors, Antigen, T-Cell|Signal Transduction|Systems Biology|T-Lymphocytes', 'Journal Article', '10.1371/journal.pcbi.1006630', '30532150', 'We present a technique applicable in any dynamical framework to identify control-robust subsets of an interacting system. These robust subsystems, which we call stable modules, are characterized by constraints on the variables that make up the subsystem. They are robust in the sense that if the defining constraints are satisfied at a given time, they remain satisfied for all later times, regardless of what happens in the rest of the system, and can only be broken if the constrained variables are externally manipulated. We identify stable modules as graph structures in an expanded network, which represents causal links between variable constraints. A stable module represents a system decision point, or trap subspace. Using the expanded network, small stable modules can be composed sequentially to form larger stable modules that describe dynamics on the system level. Collections of large, mutually exclusive stable modules describe the systems repertoire of long-term behaviors. We implement this technique in a broad class of dynamical systems and illustrate its practical utility via examples and algorithmic analysis of two published biological network models. In the segment polarity gene network of Drosophila melanogaster, we obtain a state-space visualization that reproduces by novel means the four possible cell fates and predicts the outcome of cell transplant experiments. In the T-cell signaling network, we identify six signaling elements that determine the high-signal response and show that control of an element connected to them cannot disrupt this response.'),
(89367, 2018, 'plos', 'Projecting social contact matrices to different demographic structures', 'Arregui, Sergio|Aleta, Alberto|Sanz, Joaquín|Moreno, Yamir', 'Institute for Biocomputation and Physics of Complex Systems (BIFI), University of Zargoza, Zargoza, Spain.|Institute for Biocomputation and Physics of Complex Systems (BIFI), University of Zargoza, Zargoza, Spain.|Department of Genetics. Saint-Justine Hospital Research Center, Montreal, Canada.|Institute for Biocomputation and Physics of Complex Systems (BIFI), University of Zargoza, Zargoza, Spain.', 'Spain|Spain|Canada|Spain', 0, 'Bias|Computational Biology|Contact Tracing|Demography|Epidemics|Humans|Models, Statistical|Social Behavior', 'Journal Article', '10.1371/journal.pcbi.1006638', '30532206', 'The modeling of large-scale communicable epidemics has greatly benefited in the last years from the increasing availability of highly detailed data. Particullarly, in order to achieve quantitative descriptions of the evolution of epidemics, contact networks and mixing patterns are key. These heterogeneous patterns depend on several factors such as location, socioeconomic conditions, time, and age. This last factor has been shown to encapsulate a large fraction of the observed inter-individual variation in contact patterns, an observation validated by different measurements of age-dependent contact matrices. Recently, several works have studied how to project those matrices to areas where empirical data are not available. However, the dependence of contact matrices on demographic structures and their time evolution has been largely neglected. In this work, we tackle the problem of how to transform an empirical contact matrix that has been obtained for a given demographic structure into a different contact matrix that is compatible with a different demography. The methodology discussed here allows to extrapolate a contact structure measured in a particular area to any other whose demographic structure is known, as well as to obtain the time evolution of contact matrices as a function of the demographic dynamics of the populations they refer to. To quantify the effect of considering time-dynamics of contact patterns on disease modeling, we implemented a Susceptible-Exposed-Infected-Recovered (SEIR) model on 16 different countries and regions and evaluated the impact of neglecting the temporal evolution of mixing patterns. Our results show that simulated disease incidence rates, both at the aggregated and age-specific levels, are significantly dependent on contact structures variation driven by demographic evolution. The present work opens the path to eliminate technical biases from model-based impact evaluations of future epidemic threats and warns against the use of contact matrices to model diseases without correcting for demographic evolution or geographic variations.');
INSERT INTO `papers` (`id`, `ano`, `journal`, `titulo`, `autores`, `afiliacao`, `pais`, `citacoes`, `palavra_chave`, `categorias`, `doi`, `pubmed`, `abstract`) VALUES
(89368, 2018, 'plos', 'Multi-scale computational study of the Warburg effect, reverse Warburg effect and glutamine addiction in solid tumors', 'Shan, Mengrou|Dai, David|Vudem, Arunodai|Varner, Jeffrey D|Stroock, Abraham D', 'Robert Frederick Smith School of Chemical and Biomolecular Engineering, Cornell University, Ithaca, New York, United States of America.|Robert Frederick Smith School of Chemical and Biomolecular Engineering, Cornell University, Ithaca, New York, United States of America.|Robert Frederick Smith School of Chemical and Biomolecular Engineering, Cornell University, Ithaca, New York, United States of America.|Robert Frederick Smith School of Chemical and Biomolecular Engineering, Cornell University, Ithaca, New York, United States of America.|Robert Frederick Smith School of Chemical and Biomolecular Engineering, Cornell University, Ithaca, New York, United States of America.', 'United States|United States|United States|United States|United States', 2, 'Cell Line, Tumor|Cell Proliferation|Citric Acid Cycle|Glucose|Glutamine|Glycolysis|Humans|Kinetics|Lactic Acid|Metabolic Networks and Pathways|Metabolome|Neoplasms|Oxygen|Tumor Microenvironment', 'Journal Article', '10.1371/journal.pcbi.1006584', '30532226', 'Cancer metabolism has received renewed interest as a potential target for cancer therapy. In this study, we use a multi-scale modeling approach to interrogate the implications of three metabolic scenarios of potential clinical relevance: the Warburg effect, the reverse Warburg effect and glutamine addiction. At the intracellular level, we construct a network of central metabolism and perform flux balance analysis (FBA) to estimate metabolic fluxes, at the cellular level, we exploit this metabolic network to calculate parameters for a coarse-grained description of cellular growth kinetics, and at the multicellular level, we incorporate these kinetic schemes into the cellular automata of an agent-based model (ABM), iDynoMiCS. This ABM evaluates the reaction-diffusion of the metabolites, cellular division and motion over a simulation domain. Our multi-scale simulations suggest that the Warburg effect provides a growth advantage to the tumor cells under resource limitation. However, we identify a non-monotonic dependence of growth rate on the strength of glycolytic pathway. On the other hand, the reverse Warburg scenario provides an initial growth advantage in tumors that originate deeper in the tissue. The metabolic profile of stromal cells considered in this scenario allows more oxygen to reach the tumor cells in the deeper tissue and thus promotes tumor growth at earlier stages. Lastly, we suggest that glutamine addiction does not confer a selective advantage to tumor growth with glutamine acting as a carbon source in the tricarboxylic acid (TCA) cycle, any advantage of glutamine uptake must come through other pathways not included in our model (e.g., as a nitrogen donor). Our analysis illustrates the importance of accounting explicitly for spatial and temporal evolution of tumor microenvironment in the interpretation of metabolic scenarios and hence provides a basis for further studies, including evaluation of specific therapeutic strategies that target metabolism.'),
(89369, 2018, 'plos', 'Enzymatic and non-enzymatic pathways of kynurenines dimerization: the molecular factors for oxidative stress development', 'Zhuravlev, Aleksandr V|Vetrovoy, Oleg V|Savvateeva-Popova, Elena V', 'Laboratory of Neurogenetics, Pavlov Institute of Physiology, Russian Academy of Sciences, Saint-Petersburg, Russia.|Laboratory of Regulation of the Brain Neuronal Functions, Pavlov Institute of Physiology, Russian Academy of Sciences, Saint-Petersburg, Russia.|Laboratory of Neurogenetics, Pavlov Institute of Physiology, Russian Academy of Sciences, Saint-Petersburg, Russia.', '-|-|-', 0, 'Aminophenols|Animals|Antioxidants|Computational Biology|Dimerization|Drosophila Proteins|Drosophila melanogaster|Humans|Kynurenine|Metabolic Networks and Pathways|Models, Biological|Models, Molecular|Molecular Conformation|Neurotoxicity Syndromes|Oxidation-Reduction|Oxidative Stress|Oxidoreductases|Oxygen|Reactive Oxygen Species|Thermodynamics|Tryptophan', 'Journal Article', '10.1371/journal.pcbi.1006672', '30532237', 'Kynurenines, the products of tryptophan oxidative degradation, are involved in multiple neuropathologies, such as Huntingtons chorea, Parkinsons disease, senile dementia, etc. The major cause for hydroxykynureniness neurotoxicity is the oxidative stress induced by the reactive oxygen species (ROS), the by-products of L-3-hydroxykynurenine (L-3HOK) and 3-hydroxyanthranilic acid (3HAA) oxidative self-dimerization. 2-aminophenol (2AP), a structural precursor of L-3HOK and 3HAA, undergoes the oxidative conjugation to form 2-aminophenoxazinone. There are several modes of 2AP dimerization, including both enzymatic and non-enzymatic stages. In this study, the free energies for 2AP, L-3HOK and 3HAA dimerization stages have been calculated at B3LYP/6-311G(d,p)//6-311+(O)+G(d) level, both in the gas phase and in heptane or water solution. For the intermediates, ionization potentials and electron affinities were calculated, as well as free energy and kinetics of molecular oxygen interaction with several non-enzymatically formed dimers. H-atom donating power of the intermediates increases upon the progress of the oxidation, making possible generation of hydroperoxyl radical or hydrogen peroxide from O2 at the last stages. Among the dimerization intermediates, 2-aminophenoxazinole derivatives have the lowest ionization potential and can reduce O2 to superoxide anion. The rate for O-H homolytic bond dissociation is significantly higher than that for C-H bond in non-enzymatic quinoneimine conjugate. However, the last reaction passes irreversibly, reducing O2 to hydroperoxyl radical. The inorganic ferrous iron and the heme group of Drosophila phenoxazinone synthase significantly reduce the energy cost of 2AP H-atom abstraction by O2. We have also shown experimentally that total antioxidant capacity decreases in Drosophila mutant cardinal with L-3HOK excess relative to the wild type Canton-S, and lipid peroxidation decreases in aged cardinal. Taken together, our data supports the conception of hydroxykynurenines dual role in neurotoxicity: serving as antioxidants themselves, blocking lipid peroxidation by H-atom donation, they also can easily generate ROS upon dimerization, leading to the oxidative stress development.'),
(89370, 2018, 'plos', 'PathFX provides mechanistic insights into drug efficacy and safety for regulatory review and therapeutic development', 'Wilson, Jennifer L|Racz, Rebecca|Liu, Tianyun|Adeniyi, Oluseyi|Sun, Jielin|Ramamoorthy, Anuradha|Pacanowski, Michael|Altman, Russ', 'Department of Bioengineering, Stanford University, Palo Alto California, United States of America.|Division of Applied Regulatory Science, US Food and Drug Administration, Silver Spring Maryland, United States of America.|Department of Bioengineering, Stanford University, Palo Alto California, United States of America.|Office of Clinical Pharmacology, Office of Translational Sciences, Center for Drug Evaluation and Research, US Food and Drug Administration, Silver Spring Maryland, United States of America.|Office of Clinical Pharmacology, Office of Translational Sciences, Center for Drug Evaluation and Research, US Food and Drug Administration, Silver Spring Maryland, United States of America.|Office of Clinical Pharmacology, Office of Translational Sciences, Center for Drug Evaluation and Research, US Food and Drug Administration, Silver Spring Maryland, United States of America.|Office of Clinical Pharmacology, Office of Translational Sciences, Center for Drug Evaluation and Research, US Food and Drug Administration, Silver Spring Maryland, United States of America.|Department of Bioengineering, Stanford University, Palo Alto California, United States of America.', 'United States|United States|United States|United States|United States|United States|United States|Un', 3, 'Algorithms|Computational Biology|Databases, Pharmaceutical|Decision Making|Drug Approval|Drug Development|Drug Discovery|Drug Interactions|Drug Repositioning|Drug and Narcotic Control|Drug-Related Side Effects and Adverse Reactions|Humans|Safety|Treatment Outcome|United States|United States Food and Drug Administration', 'Journal Article', '10.1371/journal.pcbi.1006614', '30532240', 'Failure to demonstrate efficacy and safety issues are important reasons that drugs do not reach the market. An incomplete understanding of how drugs exert their effects hinders regulatory and pharmaceutical industry projections of a drugs benefits and risks. Signaling pathways mediate drug response and while many signaling molecules have been characterized for their contribution to disease or their role in drug side effects, our knowledge of these pathways is incomplete. To better understand all signaling molecules involved in drug response and the phenotype associations of these molecules, we created a novel method, PathFX, a non-commercial entity, to identify these pathways and drug-related phenotypes. We benchmarked PathFX by identifying drugs marketed disease indications and reported a sensitivity of 41%, a 2.7-fold improvement over similar approaches. We then used PathFX to strengthen signals for drug-adverse event pairs occurring in the FDA Adverse Event Reporting System (FAERS) and also identified opportunities for drug repurposing for new diseases based on interaction paths that associated a marketed drug to that disease. By discovering molecular interaction pathways, PathFX improved our understanding of drug associations to safety and efficacy phenotypes. The algorithm may provide a new means to improve regulatory and therapeutic development decisions.'),
(89371, 2018, 'plos', 'Predicting protein targets for drug-like compounds using transcriptomics', 'Pabon, Nicolas A|Xia, Yan|Estabrooks, Samuel K|Ye, Zhaofeng|Herbrand, Amanda K|Süß, Evelyn|Biondi, Ricardo M|Assimon, Victoria A|Gestwicki, Jason E|Brodsky, Jeffrey L|Camacho, Carlos J|Bar-Joseph, Ziv', 'Department of Computational and Systems Biology, University of Pittsburgh, Pittsburgh, Pennsylvania, United States of America.|Machine Learning Department, School of Computer Science, Carnegie Mellon University, Pittsburgh, Pennsylvania, United States of America.|Department of Biological Sciences, University of Pittsburgh, Pittsburgh, Pennsylvania, United States of America.|School of Medicine, Tsinghua University, Beijing, China.|Department of Internal Medicine I, Universitätsklinikum Frankfurt, Frankfurt, Germany.|Department of Internal Medicine I, Universitätsklinikum Frankfurt, Frankfurt, Germany.|Department of Internal Medicine I, Universitätsklinikum Frankfurt, Frankfurt, Germany.|Department of Pharmaceutical Chemistry, University of California, San Francisco, San Francisco, California, United States of America.|Department of Pharmaceutical Chemistry, University of California, San Francisco, San Francisco, California, United States of America.|Department of Biological Sciences, University of Pittsburgh, Pittsburgh, Pennsylvania, United States of America.|Department of Computational and Systems Biology, University of Pittsburgh, Pittsburgh, Pennsylvania, United States of America.|Machine Learning Department, School of Computer Science, Carnegie Mellon University, Pittsburgh, Pennsylvania, United States of America.', 'United States|United States|United States|China|Germany|Germany|Germany|United States|United States|', 0, 'Cell Line|Computational Biology|Computer Simulation|Databases, Nucleic Acid|Drug Discovery|Drug Evaluation, Preclinical|Gene Expression Profiling|Gene Knockdown Techniques|Gene Ontology|Gene Regulatory Networks|Humans|Models, Molecular|Molecular Docking Simulation|Protein Kinase Inhibitors|Proteins|Ubiquitin-Protein Ligases|Wortmannin|ras Proteins', 'Journal Article', '10.1371/journal.pcbi.1006651', '30532261', 'An expanded chemical space is essential for improved identification of small molecules for emerging therapeutic targets. However, the identification of targets for novel compounds is biased towards the synthesis of known scaffolds that bind familiar protein families, limiting the exploration of chemical space. To change this paradigm, we validated a new pipeline that identifies small molecule-protein interactions and works even for compounds lacking similarity to known drugs. Based on differential mRNA profiles in multiple cell types exposed to drugs and in which gene knockdowns (KD) were conducted, we showed that drugs induce gene regulatory networks that correlate with those produced after silencing protein-coding genes. Next, we applied supervised machine learning to exploit drug-KD signature correlations and enriched our predictions using an orthogonal structure-based screen. As a proof-of-principle for this regimen, top-10/top-100 target prediction accuracies of 26% and 41%, respectively, were achieved on a validation of set 152 FDA-approved drugs and 3104 potential targets. We then predicted targets for 1680 compounds and validated chemical interactors with four targets that have proven difficult to chemically modulate, including non-covalent inhibitors of HRAS and KRAS. Importantly, drug-target interactions manifest as gene expression correlations between drug treatment and both target gene KD and KD of genes that act up- or down-stream of the target, even for relatively weak binders. These correlations provide new insights on the cellular response of disrupting protein interactions and highlight the complex genetic phenotypes of drug treatment. With further refinement, our pipeline may accelerate the identification and development of novel chemical classes by screening compound-target interactions.'),
(89372, 2018, 'plos', 'Deep convolutional networks do not classify based on global object shape', 'Baker, Nicholas|Lu, Hongjing|Erlikhman, Gennady|Kellman, Philip J', 'Department of Psychology, University of California, Los Angeles, Los Angeles, California, United States of America.|Department of Psychology, University of California, Los Angeles, Los Angeles, California, United States of America.|University of Nevada, Reno, Nevada, United States of America.|Department of Psychology, University of California, Los Angeles, Los Angeles, California, United States of America.', 'United States|United States|United States|United States', 29, 'Animals|Computational Biology|Deep Learning|Form Perception|Humans|Neural Networks (Computer)|Pattern Recognition, Automated|Pattern Recognition, Visual|Photic Stimulation', 'Journal Article', '10.1371/journal.pcbi.1006613', '30532273', 'Deep convolutional networks (DCNNs) are achieving previously unseen performance in object classification, raising questions about whether DCNNs operate similarly to human vision. In biological vision, shape is arguably the most important cue for recognition. We tested the role of shape information in DCNNs trained to recognize objects. In Experiment 1, we presented a trained DCNN with object silhouettes that preserved overall shape but were filled with surface texture taken from other objects. Shape cues appeared to play some role in the classification of artifacts, but little or none for animals. In Experiments 2-4, DCNNs showed no ability to classify glass figurines or outlines but correctly classified some silhouettes. Aspects of these results led us to hypothesize that DCNNs do not distinguish objects bounding contours from other edges, and that DCNNs access some local shape features, but not global shape. In Experiment 5, we tested this hypothesis with displays that preserved local features but disrupted global shape, and vice versa. With disrupted global shape, which reduced human accuracy to 28%, DCNNs gave the same classification labels as with ordinary shapes. Conversely, local contour changes eliminated accurate DCNN classification but caused no difficulty for human observers. These results provide evidence that DCNNs have access to some local shape information in the form of local edge relations, but they have no access to global object shapes.'),
(89373, 2018, 'plos', 'SFPEL-LPI: Sequence-based feature projection ensemble learning for predicting LncRNA-protein interactions', 'Zhang, Wen|Yue, Xiang|Tang, Guifeng|Wu, Wenjian|Huang, Feng|Zhang, Xining', 'College of Informatics, Huazhong Agricultural University, Wuhan, China.|Department of Computer Science and Engineering, The Ohio State University, Columbus, United States of America.|School of Computer Science, Wuhan University, Wuhan, China.|Electronic Information School, Wuhan University, Wuhan, China.|School of Computer Science, Wuhan University, Wuhan, China.|School of Computer Science, Wuhan University, Wuhan, China.', 'China|United States|China|China|China|China', 0, 'Algorithms|Amino Acid Sequence|Base Sequence|Computational Biology|Databases, Nucleic Acid|Databases, Protein|Humans|Machine Learning|Protein Binding|RNA Processing, Post-Transcriptional|RNA, Long Noncoding|RNA-Binding Proteins', 'Journal Article', '10.1371/journal.pcbi.1006616', '30533006', 'LncRNA-protein interactions play important roles in post-transcriptional gene regulation, poly-adenylation, splicing and translation. Identification of lncRNA-protein interactions helps to understand lncRNA-related activities. Existing computational methods utilize multiple lncRNA features or multiple protein features to predict lncRNA-protein interactions, but features are not available for all lncRNAs or proteins, most of existing methods are not capable of predicting interacting proteins (or lncRNAs) for new lncRNAs (or proteins), which dont have known interactions. In this paper, we propose the sequence-based feature projection ensemble learning method, SFPEL-LPI, to predict lncRNA-protein interactions. First, SFPEL-LPI extracts lncRNA sequence-based features and protein sequence-based features. Second, SFPEL-LPI calculates multiple lncRNA-lncRNA similarities and protein-protein similarities by using lncRNA sequences, protein sequences and known lncRNA-protein interactions. Then, SFPEL-LPI combines multiple similarities and multiple features with a feature projection ensemble learning frame. In computational experiments, SFPEL-LPI accurately predicts lncRNA-protein associations and outperforms other state-of-the-art methods. More importantly, SFPEL-LPI can be applied to new lncRNAs (or proteins). The case studies demonstrate that our method can find out novel lncRNA-protein interactions, which are confirmed by literature. Finally, we construct a user-friendly web server, available at http://www.bioinfotech.cn/SFPEL-LPI/.'),
(89374, 2018, 'plos', 'PremPDI estimates and interprets the effects of missense mutations on protein-DNA interactions', 'Zhang, Ning|Chen, Yuting|Zhao, Feiyang|Yang, Qing|Simonetti, Franco L|Li, Minghui', 'School of Biology and Basic Medical Sciences, Soochow University, Suzhou, China.|School of Biology and Basic Medical Sciences, Soochow University, Suzhou, China.|School of Biology and Basic Medical Sciences, Soochow University, Suzhou, China.|School of Biology and Basic Medical Sciences, Soochow University, Suzhou, China.|Institute Leloir Foundation, Buenos Aires, Argentina.|School of Biology and Basic Medical Sciences, Soochow University, Suzhou, China.', 'China|China|China|China|Argentina|China', 6, 'Algorithms|Amino Acid Substitution|Computational Biology|DNA|DNA-Binding Proteins|Databases, Genetic|Humans|Linear Models|Molecular Dynamics Simulation|Mutation, Missense|Protein Binding|Thermodynamics', 'Evaluation Studies', '10.1371/journal.pcbi.1006615', '30533007', 'Protein-DNA interactions play important roles in regulations of many vital cellular processes, including transcription, translation, DNA replication and recombination. Sequence variants occurring in these DNA binding proteins that alter protein-DNA interactions may cause significant perturbations or complete abolishment of function, potentially leading to diseases. Developing a mechanistic understanding of impacts of variants on protein-DNA interactions becomes a persistent need. To address this need we introduce a new computational method PremPDI that predicts the effect of single missense mutation in the protein on the protein-DNA interaction and calculates the quantitative binding affinity change. The PremPDI method is based on molecular mechanics force fields and fast side-chain optimization algorithms with parameters optimized on experimental sets of 219 mutations from 49 protein-DNA complexes. PremPDI yields a very good agreement between predicted and experimental values with Pearson correlation coefficient of 0.71 and root-mean-square error of 0.86 kcal mol-1. The PremPDI server could map mutations on a structural protein-DNA complex, calculate the associated changes in binding affinity, determine the deleterious effect of a mutation, and produce a mutant structural model for download. PremPDI can be applied to many tasks, such as determination of potential damaging mutations in cancer and other diseases. PremPDI is available at http://lilab.jysw.suda.edu.cn/research/PremPDI/.'),
(89375, 2018, 'plos', 'Eleven quick tips to build a usable REST API for life sciences', 'Tarkowska, Aleksandra|Carvalho-Silva, Denise|Cook, Charles E|Turner, Edd|Finn, Robert D|Yates, Andrew D', 'European Molecular Biology Laboratory, European Bioinformatics Institute (EMBL-EBI), Wellcome Genome Campus, Hinxton, Cambridge, United Kingdom.|European Molecular Biology Laboratory, European Bioinformatics Institute (EMBL-EBI), Wellcome Genome Campus, Hinxton, Cambridge, United Kingdom.|European Molecular Biology Laboratory, European Bioinformatics Institute (EMBL-EBI), Wellcome Genome Campus, Hinxton, Cambridge, United Kingdom.|European Molecular Biology Laboratory, European Bioinformatics Institute (EMBL-EBI), Wellcome Genome Campus, Hinxton, Cambridge, United Kingdom.|European Molecular Biology Laboratory, European Bioinformatics Institute (EMBL-EBI), Wellcome Genome Campus, Hinxton, Cambridge, United Kingdom.|European Molecular Biology Laboratory, European Bioinformatics Institute (EMBL-EBI), Wellcome Genome Campus, Hinxton, Cambridge, United Kingdom.', 'United Kingdom|United Kingdom|United Kingdom|United Kingdom|United Kingdom|United Kingdom', 2, 'Biological Science Disciplines|Computational Biology|Databases, Factual|Databases, Genetic|Genomics|Humans|Information Storage and Retrieval|Software|User-Computer Interface', 'Journal Article', '10.1371/journal.pcbi.1006542', '30543619', '-'),
(89376, 2018, 'plos', 'Full-Length Envelope Analyzer (FLEA): A tool for longitudinal analysis of viral amplicons', 'Eren, Kemal|Weaver, Steven|Ketteringham, Robert|Valentyn, Morné|Laird Smith, Melissa|Kumar, Venkatesh|Mohan, Sanjay|Kosakovsky Pond, Sergei L|Murrell, Ben', 'Bioinformatics and Systems Biology, University of California San Diego, La Jolla, CA, USA.|Department of Biology and Institute for Genomics and Evolutionary Medicine, Temple University, Philadelphia, PA, USA.|Division of Medical Virology, Department of Pathology, Institute of Infectious Diseases and Molecular Medicine, University of Cape Town, Cape Town, Western Cape, South Africa.|Division of Medical Virology, Department of Pathology, Institute of Infectious Diseases and Molecular Medicine, University of Cape Town, Cape Town, Western Cape, South Africa.|Department of Genetics and Genomic Sciences, Icahn School of Medicine at Mount Sinai, New York, NY, USA.|Division of Infectious Diseases and Global Public Health, Department of Medicine, University of California San Diego, La Jolla, CA, USA.|Division of Infectious Diseases and Global Public Health, Department of Medicine, University of California San Diego, La Jolla, CA, USA.|Department of Biology and Institute for Genomics and Evolutionary Medicine, Temple University, Philadelphia, PA, USA.|Division of Infectious Diseases and Global Public Health, Department of Medicine, University of California San Diego, La Jolla, CA, USA.', 'United States|United States|South Africa|South Africa|United States|United States|United States|United States|United States', 1, 'High-Throughput Nucleotide Sequencing|Phylogeny|Sequence Alignment|Sequence Analysis, DNA|Software|Viruses', 'Journal Article', '10.1371/journal.pcbi.1006498', '30543621', 'Next generation sequencing of viral populations has advanced our understanding of viral population dynamics, the development of drug resistance, and escape from host immune responses. Many applications require complete gene sequences, which can be impossible to reconstruct from short reads. HIV env, the protein of interest for HIV vaccine studies, is exceptionally challenging for long-read sequencing and analysis due to its length, high substitution rate, and extensive indel variation. While long-read sequencing is attractive in this setting, the analysis of such data is not well handled by existing methods. To address this, we introduce FLEA (Full-Length Envelope Analyzer), which performs end-to-end analysis and visualization of long-read sequencing data. FLEA consists of both a pipeline (optionally run on a high-performance cluster), and a client-side web application that provides interactive results. The pipeline transforms FASTQ reads into high-quality consensus sequences (HQCSs) and uses them to build a codon-aware multiple sequence alignment. The resulting alignment is then used to infer phylogenies, selection pressure, and evolutionary dynamics. The web application provides publication-quality plots and interactive visualizations, including an annotated viral alignment browser, time series plots of evolutionary dynamics, visualizations of gene-wide selective pressures (such as dN/dS) across time and across protein structure, and a phylogenetic tree browser. We demonstrate how FLEA may be used to process Pacific Biosciences HIV env data and describe recent examples of its use. Simulations show how FLEA dramatically reduces the error rate of this sequencing platform, providing an accurate portrait of complex and variable HIV env populations. A public instance of FLEA is hosted at http://flea.datamonkey.org. The Python source code for the FLEA pipeline can be found at https://github.com/veg/flea-pipeline. The client-side application is available at https://github.com/veg/flea-web-app. A live demo of the P018 results can be found at http://flea.murrell.group/view/P018.'),
(89377, 2018, 'plos', 'G-quadruplex forming sequences in the genome of all known human viruses: A comprehensive guide', 'Lavezzo, Enrico|Berselli, Michele|Frasson, Ilaria|Perrone, Rosalba|Palù, Giorgio|Brazzale, Alessandra R|Richter, Sara N|Toppo, Stefano', 'Department of Molecular Medicine, University of Padova, Padova, Italy.|Department of Molecular Medicine, University of Padova, Padova, Italy.|Department of Molecular Medicine, University of Padova, Padova, Italy.|Department of Molecular Medicine, University of Padova, Padova, Italy.|Department of Molecular Medicine, University of Padova, Padova, Italy.|Department of Statistical Sciences, University of Padova, Padova, Italy.|Department of Molecular Medicine, University of Padova, Padova, Italy.|Department of Molecular Medicine, University of Padova, Padova, Italy.', 'Italy|Italy|Italy|Italy|Italy|Italy|Italy|Italy', 22, 'Computational Biology|Computer Simulation|DNA, Viral|Databases, Genetic|G-Quadruplexes|Genome, Viral|Humans|Models, Genetic|RNA, Viral|Virus Diseases|Viruses', 'Journal Article', '10.1371/journal.pcbi.1006675', '30543627', 'G-quadruplexes are non-canonical nucleic-acid structures that control transcription, replication, and recombination in organisms. G-quadruplexes are present in eukaryotes, prokaryotes, and viruses. In the latter, mounting evidence indicates their key biological activity. Since data on viruses are scattered, we here present a comprehensive analysis of potential quadruplex-forming sequences (PQS) in the genome of all known viruses that can infect humans. We show that occurrence and location of PQSs are features characteristic of each virus class and family. Our statistical analysis proves that their presence within the viral genome is orderly arranged, as indicated by the possibility to correctly assign up to two-thirds of viruses to their exact class based on the PQS classification. For each virus we provide: i) the list of all PQS present in the genome (positive and negative strands), ii) their position in the viral genome, iii) the degree of conservation among strains of each PQS in its genome context, iv) the statistical significance of PQS abundance. This information is accessible from a database to allow the easy navigation of the results: http://www.medcomp.medicina.unipd.it/main_site/doku.php?id=g4virus. The availability of these data will greatly expedite research on G-quadruplex in viruses, with the possibility to accelerate finding therapeutic opportunities to numerous and some fearsome human diseases.'),
(89378, 2018, 'plos', 'Coherent chaos in a recurrent neural network with structured connectivity', 'Landau, Itamar Daniel|Sompolinsky, Haim', 'Edmond and Lily Safra Center for Brain Sciences, The Hebrew University of Jerusalem, Jerusalem, Israel.|Edmond and Lily Safra Center for Brain Sciences, The Hebrew University of Jerusalem, Jerusalem, Israel.', 'Israel|Israel', 0, 'Computer Simulation|Models, Neurological|Neural Networks (Computer)|Neurons|Nonlinear Dynamics', 'Journal Article', '10.1371/journal.pcbi.1006309', '30543634', 'We present a simple model for coherent, spatially correlated chaos in a recurrent neural network. Networks of randomly connected neurons exhibit chaotic fluctuations and have been studied as a model for capturing the temporal variability of cortical activity. The dynamics generated by such networks, however, are spatially uncorrelated and do not generate coherent fluctuations, which are commonly observed across spatial scales of the neocortex. In our model we introduce a structured component of connectivity, in addition to random connections, which effectively embeds a feedforward structure via unidirectional coupling between a pair of orthogonal modes. Local fluctuations driven by the random connectivity are summed by an output mode and drive coherent activity along an input mode. The orthogonality between input and output mode preserves chaotic fluctuations by preventing feedback loops. In the regime of weak structured connectivity we apply a perturbative approach to solve the dynamic mean-field equations, showing that in this regime coherent fluctuations are driven passively by the chaos of local residual fluctuations. When we introduce a row balance constraint on the random connectivity, stronger structured connectivity puts the network in a distinct dynamical regime of self-tuned coherent chaos. In this regime the coherent component of the dynamics self-adjusts intermittently to yield periods of slow, highly coherent chaos. The dynamics display longer time-scales and switching-like activity. We show how in this regime the dynamics depend qualitatively on the particular realization of the connectivity matrix: a complex leading eigenvalue can yield coherent oscillatory chaos while a real leading eigenvalue can yield chaos with broken symmetry. The level of coherence grows with increasing strength of structured connectivity until the dynamics are almost entirely constrained to a single spatial mode. We examine the effects of network-size scaling and show that these results are not finite-size effects. Finally, we show that in the regime of weak structured connectivity, coherent chaos emerges also for a generalized structured connectivity with multiple input-output modes.'),
(89379, 2018, 'plos', 'Prediction of antibiotic resistance in Escherichia coli from large-scale pan-genome data', 'Moradigaravand, Danesh|Palm, Martin|Farewell, Anne|Mustonen, Ville|Warringer, Jonas|Parts, Leopold', 'Wellcome Sanger Institute, Wellcome Genome Campus, Hinxton, Cambridgeshire, United Kingdom.|Department for Chemistry and Molecular Biology, University of Gothenburg, Gothenburg, Sweden.|Department for Chemistry and Molecular Biology, University of Gothenburg, Gothenburg, Sweden.|Organismal and Evolutionary Biology Research Programme, Department of Computer Science, Institute of Biotechnology, University of Helsinki, Helsinki, Finland.|Department for Chemistry and Molecular Biology, University of Gothenburg, Gothenburg, Sweden.|Wellcome Sanger Institute, Wellcome Genome Campus, Hinxton, Cambridgeshire, United Kingdom.', 'United Kingdom|Sweden|Sweden|Finland|Sweden|United Kingdom', 24, 'Anti-Bacterial Agents|DNA, Bacterial|Drug Resistance, Bacterial|Drug Resistance, Multiple, Bacterial|Escherichia coli|Escherichia coli Infections|Forecasting|Genome|Genome, Bacterial|Humans|Microbial Sensitivity Tests|Sequence Analysis, DNA', 'Journal Article', '10.1371/journal.pcbi.1006258', '30550564', 'The emergence of microbial antibiotic resistance is a global health threat. In clinical settings, the key to controlling spread of resistant strains is accurate and rapid detection. As traditional culture-based methods are time consuming, genetic approaches have recently been developed for this task. The detection of antibiotic resistance is typically made by measuring a few known determinants previously identified from genome sequencing, and thus requires the prior knowledge of its biological mechanisms. To overcome this limitation, we employed machine learning models to predict resistance to 11 compounds across four classes of antibiotics from existing and novel whole genome sequences of 1936 E. coli strains. We considered a range of methods, and examined population structure, isolation year, gene content, and polymorphism information as predictors. Gradient boosted decision trees consistently outperformed alternative models with an average accuracy of 0.91 on held-out data (range 0.81-0.97). While the best models most frequently employed gene content, an average accuracy score of 0.79 could be obtained using population structure information alone. Single nucleotide variation data were less useful, and significantly improved prediction only for two antibiotics, including ciprofloxacin. These results demonstrate that antibiotic resistance in E. coli can be accurately predicted from whole genome sequences without a priori knowledge of mechanisms, and that both genomic and epidemiological data can be informative. This paves way to integrating machine learning approaches into diagnostic tools in the clinic.'),
(89380, 2018, 'plos', 'Multiscale computational model of Achilles tendon wound healing: Untangling the effects of repair and loading', 'Chen, Kellen|Hu, Xiao|Blemker, Silvia S|Holmes, Jeffrey W', 'Department of Biomedical Engineering, University of Virginia, Charlottesville, VA, United States of America.|Department of Biomedical Engineering, University of Virginia, Charlottesville, VA, United States of America.|Department of Biomedical Engineering, University of Virginia, Charlottesville, VA, United States of America.|Department of Biomedical Engineering, University of Virginia, Charlottesville, VA, United States of America.', 'United States|United States|United States|United States', 4, 'Achilles Tendon|Animals|Biomechanical Phenomena|Cicatrix|Collagen|Computational Biology|Computer Simulation|Disease Models, Animal|Humans|Models, Biological|Rats|Rupture|Tendon Injuries|Weight-Bearing|Wound Healing', 'Journal Article', '10.1371/journal.pcbi.1006652', '30550566', 'Mechanical stimulation of the healing tendon is thought to regulate scar anisotropy and strength and is relatively easy to modulate through physical therapy. However, in vivo studies of various loading protocols in animal models have produced mixed results. To integrate and better understand the available data, we developed a multiscale model of rat Achilles tendon healing that incorporates the effect of changes in the mechanical environment on fibroblast behavior, collagen deposition, and scar formation. We modified an OpenSim model of the rat right hindlimb to estimate physiologic strains in the lateral/medial gastrocnemius and soleus musculo-tendon units during loading and unloading conditions. We used the tendon strains as inputs to a thermodynamic model of stress fiber dynamics that predicts fibroblast alignment, and to determine local collagen synthesis rates according to a response curve derived from in vitro studies. We then used an agent-based model (ABM) of scar formation to integrate these cell-level responses and predict tissue-level collagen alignment and content. We compared our model predictions to experimental data from ten different studies. We found that a single set of cellular response curves can explain features of observed tendon healing across a wide array of reported experiments in rats-including the paradoxical finding that repairing transected tendon reverses the effect of loading on alignment-without fitting model parameters to any data from those experiments. The key to these successful predictions was simulating the specific loading and surgical protocols to predict tissue-level strains, which then guided cellular behaviors according to response curves based on in vitro experiments. Our model results provide a potential explanation for the highly variable responses to mechanical loading reported in the tendon healing literature and may be useful in guiding the design of future experiments and interventions.'),
(89381, 2018, 'plos', 'A graph-based evidence synthesis approach to detecting outbreak clusters: An application to dog rabies', 'Cori, Anne|Nouvellet, Pierre|Garske, Tini|Bourhy, Hervé|Nakouné, Emmanuel|Jombart, Thibaut', 'MRC Centre for Outbreak Analysis and Modelling, Department of Infectious Disease Epidemiology, School of Public Health, Imperial College London, London, United Kingdom.|MRC Centre for Outbreak Analysis and Modelling, Department of Infectious Disease Epidemiology, School of Public Health, Imperial College London, London, United Kingdom.|MRC Centre for Outbreak Analysis and Modelling, Department of Infectious Disease Epidemiology, School of Public Health, Imperial College London, London, United Kingdom.|Unit Lyssavirus Dynamics and Host Adaptation, WHO Collaborating Centre for Reference and Research on Rabies, Institut Pasteur, Paris, France.|Département fièvres hémorragiques virales, Institut Pasteur de Bangui, Bangui, République Centrafricaine.|MRC Centre for Outbreak Analysis and Modelling, Department of Infectious Disease Epidemiology, School of Public Health, Imperial College London, London, United Kingdom.', 'United Kingdom|United Kingdom|United Kingdom|France|-|United Kingdom', 6, 'Animals|Cluster Analysis|Communicable Diseases|Disease Outbreaks|Dogs|Rabies|Time', 'Journal Article', '10.1371/journal.pcbi.1006554', '30557340', 'Early assessment of infectious disease outbreaks is key to implementing timely and effective control measures. In particular, rapidly recognising whether infected individuals stem from a single outbreak sustained by local transmission, or from repeated introductions, is crucial to adopt effective interventions. In this study, we introduce a new framework for combining several data streams, e.g. temporal, spatial and genetic data, to identify clusters of related cases of an infectious disease. Our method explicitly accounts for underreporting, and allows incorporating preexisting information about the disease, such as its serial interval, spatial kernel, and mutation rate. We define, for each data stream, a graph connecting all cases, with edges weighted by the corresponding pairwise distance between cases. Each graph is then pruned by removing distances greater than a given cutoff, defined based on preexisting information on the disease and assumptions on the reporting rate. The pruned graphs corresponding to different data streams are then merged by intersection to combine all data types, connected components define clusters of cases related for all types of data. Estimates of the reproduction number (the average number of secondary cases infected by an infectious individual in a large population), and the rate of importation of the disease into the population, are also derived. We test our approach on simulated data and illustrate it using data on dog rabies in Central African Republic. We show that the outbreak clusters identified using our method are consistent with structures previously identified by more complex, computationally intensive approaches.'),
(89382, 2018, 'plos', 'Bayesian inference of protein conformational ensembles from limited structural data', 'Potrzebowski, Wojciech|Trewhella, Jill|Andre, Ingemar', 'Data Management and Software Centre, European Spallation Source ERIC, Copenhagen, Denmark.|School of Life and Environmental Sciences, The University of Sydney, Sydney, Australia.|Biochemistry and Structural Biology, University of Lund, Lund, Sweden.', 'Denmark|Australia|Sweden', 7, 'Animals|Bayes Theorem|Calmodulin|Carrier Proteins|Computational Biology|Computer Simulation|Humans|Models, Molecular|Molecular Dynamics Simulation|Monte Carlo Method|Nuclear Magnetic Resonance, Biomolecular|Protein Conformation|Protein Domains|Protein Folding|Proteins|Scattering, Small Angle|X-Ray Diffraction', 'Journal Article', '10.1371/journal.pcbi.1006641', '30557358', 'Many proteins consist of folded domains connected by regions with higher flexibility. The details of the resulting conformational ensemble play a central role in controlling interactions between domains and with binding partners. Small-Angle Scattering (SAS) is well-suited to study the conformational states adopted by proteins in solution. However, analysis is complicated by the limited information content in SAS data and care must be taken to avoid constructing overly complex ensemble models and fitting to noise in the experimental data. To address these challenges, we developed a method based on Bayesian statistics that infers conformational ensembles from a structural library generated by all-atom Monte Carlo simulations. The first stage of the method involves a fast model selection based on variational Bayesian inference that maximizes the model evidence of the selected ensemble. This is followed by a complete Bayesian inference of population weights in the selected ensemble. Experiments with simulated ensembles demonstrate that model evidence is capable of identifying the correct ensemble and that correct number of ensemble members can be recovered up to high level of noise. Using experimental data, we demonstrate how the method can be extended to include data from Nuclear Magnetic Resonance (NMR) and structural energies of conformers extracted from the all-atom energy functions. We show that the data from SAXS, NMR chemical shifts and energies calculated from conformers can work synergistically to improve the definition of the conformational ensemble.'),
(89383, 2018, 'plos', 'Local epigenomic state cannot discriminate interacting and non-interacting enhancer-promoter pairs with high accuracy', 'Xi, Wang|Beer, Michael A', 'Department of Biomedical Engineering John Hopkins, Baltimore, MD, United States of America.|Department of Biomedical Engineering John Hopkins, Baltimore, MD, United States of America.', 'United States|United States', 0, 'Cell Line|Computational Biology|Enhancer Elements, Genetic|Epigenesis, Genetic|Humans|K562 Cells|Machine Learning|Models, Genetic|Promoter Regions, Genetic|Support Vector Machine', 'Journal Article', '10.1371/journal.pcbi.1006625', '30562350', 'We report an experimental design issue in recent machine learning formulations of the enhancer-promoter interaction problem arising from the fact that many enhancer-promoter pairs share features. Cross-fold validation schemes which do not correctly separate these feature sharing enhancer-promoter pairs into one test set report high accuracy, which is actually arising from high training set accuracy and a failure to properly evaluate generalization performance. Cross-fold validation schemes which properly segregate pairs with shared features show markedly reduced ability to predict enhancer-promoter interactions from epigenomic state. Parameter scans with multiple models indicate that local epigenomic features of individual pairs of enhancers and promoters cannot distinguish those pairs that interact from those which do with high accuracy, suggesting that additional information is required to predict enhancer-promoter interactions.'),
(89384, 2018, 'plos', 'Ten simple rules for documenting scientific software', 'Lee, Benjamin D', 'School of Engineering and Applied Sciences, Harvard University, Cambridge, Massachusetts, United States of America.', 'United States', 2, 'Computational Biology|Research|Research Design|Software', 'Editorial', '10.1371/journal.pcbi.1006561', '30571677', '-'),
(89385, 2018, 'plos', 'Dynamical anchoring of distant arrhythmia sources by fibrotic regions via restructuring of the activation pattern', 'Vandersickel, Nele|Watanabe, Masaya|Tao, Qian|Fostier, Jan|Zeppenfeld, Katja|Panfilov, Alexander V', 'Department of Physics and Astronomy, Ghent University, Belgium.|Department of Cardiology, Leiden University Medical Center, Leiden, the Netherlands.|Department of Radiology, Division of Image Processing, Leiden University Medical Centre, Leiden, the Netherlands.|Department of Information Technology (INTEC), IDLab, Ghent University - imec, Ghent, Belgium.|Department of Cardiology, Leiden University Medical Center, Leiden, the Netherlands.|Department of Physics and Astronomy, Ghent University, Belgium.', 'Belgium|Netherlands|Netherlands|Belgium|Netherlands|Belgium', 4, 'Action Potentials|Arrhythmias, Cardiac|Catheter Ablation|Computational Biology|Computer Simulation|Electrocardiography|Electrophysiological Phenomena|Fibrosis|Heart Conduction System|Heart Ventricles|Humans|Magnetic Resonance Imaging|Models, Cardiovascular|Myocardial Infarction', 'Journal Article', '10.1371/journal.pcbi.1006637', '30571689', 'Rotors are functional reentry sources identified in clinically relevant cardiac arrhythmias, such as ventricular and atrial fibrillation. Ablation targeting rotor sites has resulted in arrhythmia termination. Recent clinical, experimental and modelling studies demonstrate that rotors are often anchored around fibrotic scars or regions with increased fibrosis. However, the mechanisms leading to abundance of rotors at these locations are not clear. The current study explores the hypothesis whether fibrotic scars just serve as anchoring sites for the rotors or whether there are other active processes which drive the rotors to these fibrotic regions. Rotors were induced at different distances from fibrotic scars of various sizes and degree of fibrosis. Simulations were performed in a 2D model of human ventricular tissue and in a patient-specific model of the left ventricle of a patient with remote myocardial infarction. In both the 2D and the patient-specific model we found that without fibrotic scars, the rotors were stable at the site of their initiation. However, in the presence of a scar, rotors were eventually dynamically anchored from large distances by the fibrotic scar via a process of dynamical reorganization of the excitation pattern. This process coalesces with a change from polymorphic to monomorphic ventricular tachycardia.'),
(89386, 2018, 'plos', 'One thousand simple rules', 'Bourne, Philip E|Lewitter, Fran|Markel, Scott|Papin, Jason A', 'Data Science Institute, University of Virginia, Charlottesville, VA, United States of America.|Bioinformatics and Research Computing, Whitehead Institute, Cambridge, MA, United States of America.|Dassault Systèmes BIOVIA, San Diego, CA, United States of America.|Department of Biomedical Engineering, University of Virginia, Charlottesville, VA, United States of America.', 'United States|United States|United States|United States', 0, 'Computational Biology|Publishing|Research Report|Surveys and Questionnaires|Writing', 'Editorial', '10.1371/journal.pcbi.1006670', '30571692', '-');
INSERT INTO `papers` (`id`, `ano`, `journal`, `titulo`, `autores`, `afiliacao`, `pais`, `citacoes`, `palavra_chave`, `categorias`, `doi`, `pubmed`, `abstract`) VALUES
(89387, 2018, 'plos', 'Determinants of drug-target interactions at the single cell level', 'Elgart, Vlad|Lin, Jia-Ren|Loscalzo, Joseph', 'Laboratory for Systems Pharmacology, Harvard Medical School, Boston, Massachusetts, United States of America.|Laboratory for Systems Pharmacology, Harvard Medical School, Boston, Massachusetts, United States of America.|Laboratory for Systems Pharmacology, Harvard Medical School, Boston, Massachusetts, United States of America.', 'United States|United States|United States', 6, 'Cell Culture Techniques|Cell Nucleus|Computer Simulation|Cytoplasm|Diffusion|Doxorubicin|Drug Delivery Systems|Drug Interactions|Humans|Kinetics|Models, Biological|Single-Cell Analysis', 'Journal Article', '10.1371/journal.pcbi.1006601', '30571695', 'The physiochemical determinants of drug-target interactions in the microenvironment of the cell are complex and generally not defined by simple diffusion and intrinsic chemical reactivity. Non-specific interactions of drugs and macromolecules in cells are rarely considered formally in assessing pharmacodynamics. Here, we demonstrate that non-specific interactions lead to very slow incorporation kinetics of DNA binding drugs. We observe a rate of drug incorporation in cell nuclei three orders of magnitude slower than in vitro due to anomalous drug diffusion within cells. This slow diffusion, however, has an advantageous consequence: it leads to virtually irreversible binding of the drug to specific DNA targets in cells. We show that non-specific interactions drive slow drug diffusion manifesting as slow reaction front propagation. We study the effect of non-specific interactions in different cellular compartments by permeabilization of plasma and nuclear membranes in order to pinpoint differential compartment effects on variability in intracellular drug kinetics. These results provide the basis for a comprehensive model of the determinants of intracellular diffusion of small-molecule drugs, their target-seeking trajectories, and the consequences of these processes on the apparent kinetics of drug-target interactions.'),
(89388, 2018, 'plos', 'Movement and conformity interact to establish local behavioural traditions in animal populations', 'Somveille, Marius|Firth, Josh A|Aplin, Lucy M|Farine, Damien R|Sheldon, Ben C|Thompson, Robin N', 'Edward Grey Institute, Department of Zoology, University of Oxford, Oxford, United Kingdom.|Edward Grey Institute, Department of Zoology, University of Oxford, Oxford, United Kingdom.|Edward Grey Institute, Department of Zoology, University of Oxford, Oxford, United Kingdom.|Edward Grey Institute, Department of Zoology, University of Oxford, Oxford, United Kingdom.|Edward Grey Institute, Department of Zoology, University of Oxford, Oxford, United Kingdom.|Department of Zoology, University of Oxford, Oxford, United Kingdom.', 'United Kingdom|United Kingdom|United Kingdom|United Kingdom|United Kingdom|United Kingdom', 2, 'Animals|Behavior, Animal|Computational Biology|Ecosystem|England|Learning|Models, Biological|Models, Psychological|Passeriformes|Population Dynamics|Social Behavior', 'Journal Article', '10.1371/journal.pcbi.1006647', '30571696', 'The social transmission of information is critical to the emergence of animal culture. Two processes are predicted to play key roles in how socially-transmitted information spreads in animal populations: the movement of individuals across the landscape and conformist social learning. We develop a model that, for the first time, explicitly integrates these processes to investigate their impacts on the spread of behavioural preferences. Our results reveal a strong interplay between movement and conformity in determining whether locally-variable traditions establish across a landscape or whether a single preference dominates the whole population. The model is able to replicate a real-world cultural diffusion experiment in great tits Parus major, but also allows for a range of predictions for the emergence of animal culture under various initial conditions, habitat structure and strength of conformist bias to be made. Integrating social behaviour with ecological variation will be important for understanding the stability and diversity of culture in animals.'),
(89389, 2018, 'plos', 'Hosts mobility and spatial spread of Rickettsia rickettsii', 'Polo, Gina|Mera Acosta, Carlos|Labruna, Marcelo B|Ferreira, Fernando|Brockmann, Dirk', 'Laboratory of Epidemiology and Biostatistics. Department of Preventive Veterinary Medicine and Animal Health. University of São Paulo, São Paulo, Brazil.|Physics Institute, University of São Paulo, São Paulo, Brazil.|Laboratory of Parasitic Diseases. Department of Preventive Veterinary Medicine and Animal Health. University of São Paulo, São Paulo, Brazil.|Laboratory of Epidemiology and Biostatistics. Department of Preventive Veterinary Medicine and Animal Health. University of São Paulo, São Paulo, Brazil.|Robert Koch-Institute, Berlin, Germany.', 'Brazil|Brazil|Brazil|Brazil|Germany', 6, 'Animals|Arachnid Vectors|Brazil|Computational Biology|Computer Simulation|Conservation of Natural Resources|Host Microbial Interactions|Humans|Ixodidae|Models, Biological|Rickettsia rickettsii|Rocky Mountain Spotted Fever|Rodentia|Stochastic Processes|Zoonoses', 'Journal Article', '10.1371/journal.pcbi.1006636', '30586381', 'There are a huge number of pathogens with multi-component transmission cycles, involving amplifier hosts, vectors or complex pathogen life cycles. These complex systems present challenges in terms of modeling and policy development. A lethal tick-borne infectious disease, the Brazilian Spotted Fever (BSF), is a relevant example of that. The current increase of human cases of BSF has been associated with the presence and expansion of the capybara Hydrochoerus hydrochaeris, amplifier host for the agent Rickettsia rickettsii and primary host for the tick vector Amblyomma sculptum. We introduce a stochastic dynamical model that captures the spatial distribution of capybaras and ticks to gain a better understanding of the spatial spread of the R. rickettsii and potentially predict future epidemic outcomes. We implemented a reaction-diffusion process in which individuals were divided into classes denoting their state with respect to the disease. The model considered bidirectional movements between base and destination locations limited by the carrying capacity of the environment. We performed systematic stochastic simulations and numerical analysis of the model and investigate the impact of potential interventions to mitigate the spatial spread of the disease. The mobility of capybaras and their attached ticks was significantly influenced by the birth rate of capybaras and therefore, disease propagation velocity was higher in places with higher carrying capacity. Some geographical barriers, generated for example by riparian reforesting, can impede the spatial spread of BSF. The results of this work will allow the formulation of public actions focused on the prevention of BSF human cases.'),
(89390, 2018, 'plos', 'A likelihood approach to testing hypotheses on the co-evolution of epigenome and genome', 'Lu, Jia|Cao, Xiaoyi|Zhong, Sheng', '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.|Department of Bioengineering, University of California San Diego, La Jolla, California, United States of America.', 'United States|United States|United States', 2, 'Algorithms|Animals|Computational Biology|Computer Simulation|Databases, Genetic|Epigenesis, Genetic|Evolution, Molecular|Genetic Variation|Genome|Histone Code|Histones|Humans|INDEL Mutation|Likelihood Functions|Macaca mulatta|Male|Mice|Models, Genetic|Models, Statistical', 'Journal Article', '10.1371/journal.pcbi.1006673', '30586383', 'Central questions to epigenome evolution include whether interspecies changes of histone modifications are independent of evolutionary changes of DNA, and if there is dependence whether they depend on any specific types of DNA sequence changes. Here, we present a likelihood approach for testing hypotheses on the co-evolution of genome and histone modifications. The gist of this approach is to convert evolutionary biology hypotheses into probabilistic forms, by explicitly expressing the joint probability of multispecies DNA sequences and histone modifications, which we refer to as a class of Joint Evolutionary Model for the Genome and the Epigenome (JEMGE). JEMGE can be summarized as a mixture model of four components representing four evolutionary hypotheses, namely dependence and independence of interspecies epigenomic variations to underlying sequence substitutions and to underlying sequence insertions and deletions (indels). We implemented a maximum likelihood method to fit the models to the data. Based on comparison of likelihoods, we inferred whether interspecies epigenomic variations depended on substitution or indels in local genomic sequences based on DNase hypersensitivity and spermatid H3K4me3 ChIP-seq data from human and rhesus macaque. Approximately 5.5% of homologous regions in the genomes exhibited H3K4me3 modification in either species, among which approximately 67% homologous regions exhibited local-sequence-dependent interspecies H3K4me3 variations. Substitutions accounted for less local-sequence-dependent H3K4me3 variations than indels. Among transposon-mediated indels, ERV1 insertions and L1 insertions were most strongly associated with H3K4me3 gains and losses, respectively. By initiating probabilistic formulation on the co-evolution of genomes and epigenomes, JEMGE helps to bring evolutionary biology principles to comparative epigenomic studies.'),
(89391, 2018, 'plos', 'On variational solutions for whole brain serial-section histology using a Sobolev prior in the computational anatomy random orbit model', 'Lee, Brian C|Tward, Daniel J|Mitra, Partha P|Miller, Michael I', 'Center for Imaging Science, Department of Biomedical Engineering, Johns Hopkins University, Baltimore, MD, USA.|Center for Imaging Science, Department of Biomedical Engineering, Johns Hopkins University, Baltimore, MD, USA.|Cold Spring Harbor Laboratory, Cold Spring Harbor, NY, USA.|Center for Imaging Science, Department of Biomedical Engineering, Johns Hopkins University, Baltimore, MD, USA.', 'United States|United States|United States|United States', 6, 'Algorithms|Animals|Brain|Brain Mapping|Computational Biology|Computer Simulation|Histological Techniques|Humans|Imaging, Three-Dimensional|Likelihood Functions|Mice|Models, Anatomic|Models, Neurological|Phantoms, Imaging|Software', 'Journal Article', '10.1371/journal.pcbi.1006610', '30586384', 'This paper presents a variational framework for dense diffeomorphic atlas-mapping onto high-throughput histology stacks at the 20 xcexbcm meso-scale. The observed sections are modelled as Gaussian random fields conditioned on a sequence of unknown section by section rigid motions and unknown diffeomorphic transformation of a three-dimensional atlas. To regularize over the high-dimensionality of our parameter space (which is a product space of the rigid motion dimensions and the diffeomorphism dimensions), the histology stacks are modelled as arising from a first order Sobolev space smoothness prior. We show that the joint maximum a-posteriori, penalized-likelihood estimator of our high dimensional parameter space emerges as a joint optimization interleaving rigid motion estimation for histology restacking and large deformation diffeomorphic metric mapping to atlas coordinates. We show that joint optimization in this parameter space solves the classical curvature non-identifiability of the histology stacking problem. The algorithms are demonstrated on a collection of whole-brain histological image stacks from the Mouse Brain Architecture Project.'),
(89392, 2018, 'plos', 'Conventional analysis of trial-by-trial adaptation is biased: Empirical and theoretical support using a Bayesian estimator', 'Blustein, Daniel|Shehata, Ahmed|Englehart, Kevin|Sensinger, Jonathon', 'Institute of Biomedical Engineering, University of New Brunswick, Fredericton, New Brunswick, Canada.|Department of Medicine, Faculty of Medicine and Dentistry, University of Alberta, Edmonton, Alberta, Canada.|Institute of Biomedical Engineering, University of New Brunswick, Fredericton, New Brunswick, Canada.|Institute of Biomedical Engineering, University of New Brunswick, Fredericton, New Brunswick, Canada.', 'Canada|Canada|Canada|Canada', 3, 'Adaptation, Physiological|Adult|Bayes Theorem|Female|Humans|Learning|Male|Middle Aged|Movement|Psychomotor Performance', 'Journal Article', '10.1371/journal.pcbi.1006501', '30586387', 'Research on human motor adaptation has often focused on how people adapt to self-generated or externally-influenced errors. Trial-by-trial adaptation is a persons response to self-generated errors. Externally-influenced errors applied as catch-trial perturbations are used to calculate a persons perturbation adaptation rate. Although these adaptation rates are sometimes compared to one another, we show through simulation and empirical data that the two metrics are distinct. We demonstrate that the trial-by-trial adaptation rate, often calculated as a coefficient in a linear regression, is biased under typical conditions. We tested 12 able-bodied subjects moving a cursor on a screen using a computer mouse. Statistically different adaptation rates arise when sub-sets of trials from different phases of learning are analyzed from within a sequence of movement results. We propose a new approach to identify when a persons learning has stabilized in order to identify steady-state movement trials from which to calculate a more reliable trial-by-trial adaptation rate. Using a Bayesian model of human movement, we show that this analysis approach is more consistent and provides a more confident estimate than alternative approaches. Constraining analyses to steady-state conditions will allow researchers to better decouple the multiple concurrent learning processes that occur while a person makes goal-directed movements. Streamlining this analysis may help broaden the impact of motor adaptation studies, perhaps even enhancing their clinical usefulness.'),
(89393, 2018, 'plos', 'Harnessing formal concepts of biological mechanism to analyze human disease', 'Darden, Lindley|Kundu, Kunal|Pal, Lipika R|Moult, John', 'Department of Philosophy, University of Maryland College Park, College Park, Maryland, United States of America.|Institute for Bioscience and Biotechnology Research, University of Maryland, Rockville, Maryland, United States of America.|Institute for Bioscience and Biotechnology Research, University of Maryland, Rockville, Maryland, United States of America.|Institute for Bioscience and Biotechnology Research, University of Maryland, Rockville, Maryland, United States of America.', 'United States|United States|United States|United States', 0, 'Biological Phenomena|Biomedical Research|Classification|Computational Biology|Databases, Factual|Disease|Humans|Physiological Phenomena', 'Editorial', '10.1371/journal.pcbi.1006540', '30586388', 'Mechanism is a widely used concept in biology. In 2017, more than 10% of PubMed abstracts used the term. Therefore, searching for and reasoning about mechanisms is fundamental to much of biomedical research, but until now there has been almost no computational infrastructure for this purpose. Recent work in the philosophy of science has explored the central role that the search for mechanistic accounts of biological phenomena plays in biomedical research, providing a conceptual basis for representing and analyzing biological mechanism. The foundational categories for components of mechanisms-entities and activities-guide the development of general, abstract types of biological mechanism parts. Building on that analysis, we have developed a formal framework for describing and representing biological mechanism, MecCog, and applied it to describing mechanisms underlying human genetic disease. Mechanisms are depicted using a graphical notation. Key features are assignment of mechanism components to stages of biological organization and classes, visual representation of uncertainty, ignorance, and ambiguity, and tight integration with literature sources. The MecCog framework facilitates analysis of many aspects of disease mechanism, including the prioritization of future experiments, probing of gene-drug and gene-environment interactions, identification of possible new drug targets, personalized drug choice, analysis of nonlinear interactions between relevant genetic loci, and classification of diseases based on mechanism.'),
(89394, 2018, 'plos', 'Trajectory-based training enables protein simulations with accurate folding and Boltzmann ensembles in cpu-hours', 'Jumper, John M|Faruk, Nabil F|Freed, Karl F|Sosnick, Tobin R', 'Department of Biochemistry and Molecular Biology, University of Chicago, Chicago, Illinois, USA.|Graduate Program in Biophysical Sciences, University of Chicago, Chicago, Illinois, USA.|Department of Chemistry, and The James Franck Institute, University of Chicago, Chicago, Illinois, USA.|Department of Biochemistry and Molecular Biology, University of Chicago, Chicago, Illinois, USA.', 'United States|United States|United States|United States', 4, 'Bayes Theorem|Computational Biology|Computer Simulation|Machine Learning|Molecular Dynamics Simulation|Protein Conformation|Protein Folding|Proteins|Software|Thermodynamics', 'Journal Article', '10.1371/journal.pcbi.1006578', '30589834', 'An ongoing challenge in protein chemistry is to identify the underlying interaction energies that capture protein dynamics. The traditional trade-off in biomolecular simulation between accuracy and computational efficiency is predicated on the assumption that detailed force fields are typically well-parameterized, obtaining a significant fraction of possible accuracy. We re-examine this trade-off in the more realistic regime in which parameterization is a greater source of error than the level of detail in the force field. To address parameterization of coarse-grained force fields, we use the contrastive divergence technique from machine learning to train from simulations of 450 proteins. In our procedure, the computational efficiency of the model enables high accuracy through the precise tuning of the Boltzmann ensemble. This method is applied to our recently developed Upside model, where the free energy for side chains is rapidly calculated at every time-step, allowing for a smooth energy landscape without steric rattling of the side chains. After this contrastive divergence training, the model is able to de novo fold proteins up to 100 residues on a single core in days. This improved Upside model provides a starting point both for investigation of folding dynamics and as an inexpensive Bayesian prior for protein physics that can be integrated with additional experimental or bioinformatic data.'),
(89395, 2018, 'plos', 'Ten quick tips for sharing open genomic data', 'Brown, Anne V|Campbell, Jacqueline D|Assefa, Teshale|Grant, David|Nelson, Rex T|Weeks, Nathan T|Cannon, Steven B', 'USDA-ARS, Corn Insects and Crop Genetics Research Unit, Ames, Iowa, United States of America.|Department of Computer Science, Iowa State University, Ames, Iowa, United States of America.|ORISE Fellow, USDA-ARS, Corn Insects and Crop Genetics Research Unit, Ames, Iowa, United States of America.|USDA-ARS, Corn Insects and Crop Genetics Research Unit, Ames, Iowa, United States of America.|USDA-ARS, Corn Insects and Crop Genetics Research Unit, Ames, Iowa, United States of America.|USDA-ARS, Corn Insects and Crop Genetics Research Unit, Ames, Iowa, United States of America.|USDA-ARS, Corn Insects and Crop Genetics Research Unit, Ames, Iowa, United States of America.', 'United States|United States|United States|United States|United States|United States|United States', 1, 'Databases, Factual|Databases, Genetic|Genomics|Information Dissemination|Information Storage and Retrieval|Software|User-Computer Interface', 'Journal Article', '10.1371/journal.pcbi.1006472', '30589835', 'As sequencing prices drop, genomic data accumulates-seemingly at a steadily increasing pace. Most genomic data potentially have value beyond the initial purpose-but only if shared with the scientific community. This, of course, is often easier said than done. Some of the challenges in sharing genomic data include data volume (raw file sizes and number of files), complexities, formats, nomenclatures, metadata descriptions, and the choice of a repository. In this paper, we describe 10 quick tips for sharing open genomic data.'),
(89396, 2018, 'plos', 'Chirality provides a direct fitness advantage and facilitates intermixing in cellular aggregates', 'B George, Ashish|Korolev, Kirill S', 'Department of Physics, Boston University, Boston, Massachusetts, United States of America.|Department of Physics and Graduate Program in Bioinformatics, Boston University, Boston, Massachusetts, United States of America.', 'United States|United States', 0, 'Cell Aggregation|Cell Movement|Cell Polarity|Cell Proliferation|Cell Shape|Computational Biology|Computer Simulation|Humans|Microbiota|Models, Biological|Neoplasm Invasiveness|Neoplasms|Stochastic Processes', 'Journal Article', '10.1371/journal.pcbi.1006645', '30589836', 'Chirality in shape and motility can evolve rapidly in microbes and cancer cells. To determine how chirality affects cell fitness, we developed a model of chiral growth in compact aggregates such as microbial colonies and solid tumors. Our model recapitulates previous experimental findings and shows that mutant cells can invade by increasing their chirality or switching their handedness. The invasion results either in a takeover or stable coexistence between the mutant and the ancestor depending on their relative chirality. For large chiralities, the coexistence is accompanied by strong intermixing between the cells, while spatial segregation occurs otherwise. We show that the competition within the aggregate is mediated by bulges in regions where the cells with different chiralities meet. The two-way coupling between aggregate shape and natural selection is described by the chiral Kardar-Parisi-Zhang equation coupled to the Burgers equation with multiplicative noise. We solve for the key features of this theory to explain the origin of selection on chirality. Overall, our work suggests that chirality could be an important ecological trait that mediates competition, invasion, and spatial structure in cellular populations.'),
(89397, 2018, 'plos', 'Active degradation of MarA controls coordination of its downstream targets', 'Rossi, Nicholas A|Mora, Thierry|Walczak, Aleksandra M|Dunlop, Mary J', 'Molecular Biology, Cell Biology & Biochemistry Program, Boston University, Boston, Massachusetts, United States of America.|Laboratoire de Physique Statistique, CNRS, Sorbonne Université, Université Paris-Diderot, and École Normale Supérieure (PSL), Paris, France.|Laboratoire de Physique Théorique, CNRS, Sorbonne Université, and École Normale Supérieure (PSL), Paris, France.|Molecular Biology, Cell Biology & Biochemistry Program, Boston University, Boston, Massachusetts, United States of America.', 'United States|France|France|United States', 0, 'Computational Biology|DNA-Binding Proteins|Escherichia coli|Escherichia coli Proteins|Gene Expression Regulation, Bacterial|Gene Knockdown Techniques|Genes, Bacterial|Half-Life|Models, Biological|Protease La|Proteolysis|Stochastic Processes', 'Journal Article', '10.1371/journal.pcbi.1006634', '30589845', 'Several key transcription factors have unusually short half-lives compared to other cellular proteins. Here, we explore the utility of active degradation in shaping how the multiple antibiotic resistance activator MarA coordinates its downstream targets. MarA controls a variety of stress response genes in Escherichia coli. We modify its half-life either by knocking down the protease that targets it via CRISPRi or by engineering MarA to protect it from degradation. Our experimental and analytical results indicate that active degradation can impact both the rate of coordination and the maximum coordination that downstream genes can achieve. In the context of multi-gene regulation, trade-offs between these properties show that perfect information fidelity and instantaneous coordination cannot coexist.'),
(89398, 2018, 'plos', 'Accurate calculation of side chain packing and free energy with applications to protein molecular dynamics', 'Jumper, John M|Faruk, Nabil F|Freed, Karl F|Sosnick, Tobin R', 'Department of Biochemistry and Molecular Biology, University of Chicago, Chicago, Illinois, United States of America.|Graduate Program in Biophysical Sciences, University of Chicago, Chicago, Illinois, United States of America.|Department of Chemistry, and The James Franck Institute, University of Chicago, Chicago, Illinois, United States of America.|Department of Biochemistry and Molecular Biology, University of Chicago, Chicago, Illinois, United States of America.', 'United States|United States|United States|United States', 0, 'Amino Acids|Entropy|Models, Molecular|Molecular Dynamics Simulation|Probability|Protein Conformation|Proteins|Thermodynamics', 'Journal Article', '10.1371/journal.pcbi.1006342', '30589846', 'To address the large gap between time scales that can be easily reached by molecular simulations and those required to understand protein dynamics, we present a rapid self-consistent approximation of the side chain free energy at every integration step. In analogy with the adiabatic Born-Oppenheimer approximation for electronic structure, the protein backbone dynamics are simulated as preceding according to the dictates of the free energy of an instantaneously-equilibrated side chain potential. The side chain free energy is computed on the fly, allowing the protein backbone dynamics to traverse a greatly smoothed energetic landscape. This computation results in extremely rapid equilibration and sampling of the Boltzmann distribution. Our method, termed Upside, employs a reduced model involving the three backbone atoms, along with the carbonyl oxygen and amide proton, and a single (oriented) side chain bead having multiple locations reflecting the conformational diversity of the side chains rotameric states. We also introduce a novel, maximum-likelihood method to parameterize the side chain interactions using protein structures. We demonstrate state-of-the-art accuracy for predicting xcfx871 rotamer states while consuming only milliseconds of CPU time. Our method enables rapidly equilibrating coarse-grained simulations that can nonetheless contain significant molecular detail. We also show that the resulting free energies of the side chains are sufficiently accurate for de novo folding of some proteins.'),
(89399, 2018, 'plos', 'Exploring chromatin hierarchical organization via Markov State Modelling', 'Tan, Zhen Wah|Guarnera, Enrico|Berezovsky, Igor N', 'Bioinformatics Institute (BII), Agency for Science, Technology and Research (A*STAR), Matrix, Singapore.|Bioinformatics Institute (BII), Agency for Science, Technology and Research (A*STAR), Matrix, Singapore.|Bioinformatics Institute (BII), Agency for Science, Technology and Research (A*STAR), Matrix, Singapore.', 'Singapore|Singapore|Singapore', 1, 'Algorithms|CCCTC-Binding Factor|Cell Cycle Proteins|Cell Line|Chromatin|Chromatin Assembly and Disassembly|Chromosomal Proteins, Non-Histone|Chromosomes, Human, Pair 17|Computational Biology|DNA|DNA-Directed RNA Polymerases|Epigenesis, Genetic|Gene Expression Regulation|Gene Regulatory Networks|Genome, Human|Histone Code|Humans|Markov Chains|Models, Genetic', 'Journal Article', '10.1371/journal.pcbi.1006686', '30596637', 'We propose a new computational method for exploring chromatin structural organization based on Markov State Modelling of Hi-C data represented as an interaction network between genomic loci. A Markov process describes the random walk of a traveling probe in the corresponding energy landscape, mimicking the motion of a biomolecule involved in chromatin function. By studying the metastability of the associated Markov State Model upon annealing, the hierarchical structure of individual chromosomes is observed, and corresponding set of structural partitions is identified at each level of hierarchy. Then, the notion of effective interaction between partitions is derived, delineating the overall topology and architecture of chromosomes. Mapping epigenetic data on the graphs of intra-chromosomal effective interactions helps in understanding how chromosome organization facilitates its function. A sketch of whole-genome interactions obtained from the analysis of 539 partitions from all 23 chromosomes, complemented by distributions of gene expression regulators and epigenetic factors, sheds light on the structure-function relationships in chromatin, delineating chromosomal territories, as well as structural partitions analogous to topologically associating domains and active / passive epigenomic compartments. In addition to the overall genome architecture shown by effective interactions, the affinity between partitions of different chromosomes was analyzed as an indicator of the degree of association between partitions in functionally relevant genomic interactions. The overall static picture of whole-genome interactions obtained with the method presented in this work provides a foundation for chromatin structural reconstruction, for the modelling of chromatin dynamics, and for exploring the regulation of genome function. The algorithms used in this study are implemented in a freely available Python package ChromaWalker (https://bitbucket.org/ZhenWahTan/chromawalker).'),
(89400, 2018, 'plos', 'Change, stability, and instability in the Pavlovian guidance of behaviour from adolescence to young adulthood', 'Moutoussis, Michael|Bullmore, Edward T|Goodyer, Ian M|Fonagy, Peter|Jones, Peter B|Dolan, Raymond J|Dayan, Peter|Neuroscience in Psychiatry Network Research Consortium', 'Wellcome Centre for Human Neuroimaging, University College London, London, United Kingdom.|Department of Psychiatry, University of Cambridge, Cambridge, United Kingdom.|Department of Psychiatry, University of Cambridge, Cambridge, United Kingdom.|Research Department of Clinical, Educational and Health Psychology, University College London, London, United Kingdom.|Department of Psychiatry, University of Cambridge, Cambridge, United Kingdom.|Wellcome Centre for Human Neuroimaging, University College London, London, United Kingdom.|Max Planck Institute of Biological Cybernetics, Tübingen, Germany.|Max Planck Institute of Biological Cybernetics, Tübingen, Germany.', 'United Kingdom|United Kingdom|United Kingdom|United Kingdom|United Kingdom|United Kingdom|Germany|Ge', 9, 'Adolescent|Adolescent Behavior|Affect|Choice Behavior|Computational Biology|Decision Making|Female|Humans|Intelligence|Longitudinal Studies|Male|Models, Psychological|Psychometrics|Task Performance and Analysis|Young Adult', 'Journal Article', '10.1371/journal.pcbi.1006679', '30596638', 'Pavlovian influences are important in guiding decision-making across health and psychopathology. There is an increasing interest in using concise computational tasks to parametrise such influences in large populations, and especially to track their evolution during development and changes in mental health. However, the developmental course of Pavlovian influences is uncertain, a problem compounded by the unclear psychometric properties of the relevant measurements. We assessed Pavlovian influences in a longitudinal sample using a well characterised and widely used Go-NoGo task. We hypothesized that the strength of Pavlovian influences and other psychomarkers guiding decision-making would behave like traits. As reliance on Pavlovian influence is not as profitable as precise instrumental decision-making in this Go-NoGo task, we expected this influence to decrease with higher IQ and age. Additionally, we hypothesized it would correlate with expressions of psychopathology. We found that Pavlovian effects had weak temporal stability, while model-fit was more stable. In terms of external validity, Pavlovian effects decreased with increasing IQ and experience within the task, in line with normative expectations. However, Pavlovian effects were poorly correlated with age or psychopathology. Thus, although this computational construct did correlate with important aspects of development, it does not meet conventional requirements for tracking individual development. We suggest measures that might improve psychometric properties of task-derived Pavlovian measures for future studies.'),
(89401, 2018, 'plos', 'Statistical investigations of protein residue direct couplings', 'Neuwald, Andrew F|Altschul, Stephen F', 'Institute for Genome Sciences and Department of Biochemistry & Molecular Biology, University of Maryland School of Medicine, Baltimore, Maryland, United States of America.|Computational Biology Branch, National Center for Biotechnology Information, National Library of Medicine, National Institutes of Health, Bethesda, Maryland, United States of America.', 'United States|United States', 0, 'Algorithms|Binding Sites|Models, Molecular|Protein Conformation|Protein Interaction Domains and Motifs|Protein Structural Elements|Proteins|Sequence Alignment|Sequence Analysis, Protein', 'Journal Article', '10.1371/journal.pcbi.1006237', '30596639', 'Protein Direct Coupling Analysis (DCA), which predicts residue-residue contacts based on covarying positions within a multiple sequence alignment, has been remarkably effective. This suggests that there is more to learn from sequence correlations than is generally assumed, and calls for deeper investigations into DCA and perhaps into other types of correlations. Here we describe an approach that enables such investigations by measuring, as an estimated p-value, the statistical significance of the association between residue-residue covariance and structural interactions, either internal or homodimeric. Its application to thirty protein superfamilies confirms that direct coupling (DC) scores correlate with 3D pairwise contacts with very high significance. This method also permits quantitative assessment of the relative performance of alternative DCA methods, and of the degree to which they detect direct versus indirect couplings. We illustrate its use to assess, for a given protein, the biological relevance of alternative conformational states, to investigate the possible mechanistic implications of differences between these states, and to characterize subtle aspects of direct couplings. Our analysis indicates that direct pairwise correlations may be largely distinct from correlated patterns associated with functional specialization, and that the joint analysis of both types of correlations can yield greater power. Data, programs, and source code are freely available at http://evaldca.igs.umaryland.edu.'),
(89402, 2018, 'plos', 'Chemogenomic model identifies synergistic drug combinations robust to the pathogen microenvironment', 'Cokol, Murat|Li, Chen|Chandrasekaran, Sriram', 'Axcella Health, Cambridge, Massachusetts, United States of America.|Department of Biomedical Engineering, University of Michigan, Ann Arbor, Michigan, United States of America.|Department of Biomedical Engineering, University of Michigan, Ann Arbor, Michigan, United States of America.', 'United States|United States|United States', 0, 'Acinetobacter baumannii|Anti-Bacterial Agents|Computational Biology|Drug Interactions|Drug Resistance, Multiple, Bacterial|Drug Synergism|Drug Therapy, Combination|Escherichia coli|Genes, Bacterial|Glycolysis|Glyoxylates|Host Microbial Interactions|Humans|Metabolic Networks and Pathways|Microbial Sensitivity Tests|Models, Biological|Pharmacogenomic Testing|Software|Systems Biology', 'Journal Article', '10.1371/journal.pcbi.1006677', '30596642', 'Antibiotics need to be effective in diverse environments in vivo. However, the pathogen microenvironment can have a significant impact on antibiotic potency. Further, antibiotics are increasingly used in combinations to combat resistance, yet, the effect of microenvironments on drug-combination efficacy is unknown. To exhaustively explore the impact of diverse microenvironments on drug-combinations, here we develop a computational framework-Metabolism And GENomics-based Tailoring of Antibiotic regimens (MAGENTA). MAGENTA uses chemogenomic profiles of individual drugs and metabolic perturbations to predict synergistic or antagonistic drug-interactions in different microenvironments. We uncovered antibiotic combinations with robust synergy across nine distinct environments against both E. coli and A. baumannii by searching through 2556 drug-combinations of 72 drugs. MAGENTA also accurately predicted the change in efficacy of bacteriostatic and bactericidal drug-combinations during growth in glycerol media, which we confirmed experimentally in both microbes. Our approach identified genes in glycolysis and glyoxylate pathway as top predictors of synergy and antagonism respectively. Our systems approach enables tailoring of antibiotic therapies based on the pathogen microenvironment.'),
(89403, 2018, 'plos', 'Scene complexity modulates degree of feedback activity during object detection in natural scenes', 'Groen, Iris I A|Jahfari, Sara|Seijdel, Noor|Ghebreab, Sennay|Lamme, Victor A F|Scholte, H Steven', 'New York University, Department of Psychology, New York, New York, United States of America.|Spinoza Centre for Neuroimaging, Royal Netherlands Academy of Arts and Sciences (KNAW), Amsterdam, The Netherlands.|University of Amsterdam, Department of Psychology, Section Brain and Cognition, Amsterdam, The Netherlands.|University of Amsterdam, Department of Psychology, Section Brain and Cognition, Amsterdam, The Netherlands.|University of Amsterdam, Department of Psychology, Section Brain and Cognition, Amsterdam, The Netherlands.|University of Amsterdam, Department of Psychology, Section Brain and Cognition, Amsterdam, The Netherlands.', 'United States|Netherlands|Netherlands|Netherlands|Netherlands|Netherlands', 3, 'Adult|Animals|Brain|Brain Mapping|Computational Biology|Electroencephalography|Evoked Potentials|Feedback, Physiological|Feedback, Psychological|Female|Humans|Magnetic Resonance Imaging|Male|Models, Neurological|Models, Psychological|Pattern Recognition, Visual|Photic Stimulation|Reaction Time|Visual Cortex|Young Adult', 'Journal Article', '10.1371/journal.pcbi.1006690', '30596644', 'Selective brain responses to objects arise within a few hundreds of milliseconds of neural processing, suggesting that visual object recognition is mediated by rapid feed-forward activations. Yet disruption of neural responses in early visual cortex beyond feed-forward processing stages affects object recognition performance. Here, we unite these discrepant findings by reporting that object recognition involves enhanced feedback activity (recurrent processing within early visual cortex) when target objects are embedded in natural scenes that are characterized by high complexity. Human participants performed an animal target detection task on natural scenes with low, medium or high complexity as determined by a computational model of low-level contrast statistics. Three converging lines of evidence indicate that feedback was selectively enhanced for high complexity scenes. First, functional magnetic resonance imaging (fMRI) activity in early visual cortex (V1) was enhanced for target objects in scenes with high, but not low or medium complexity. Second, event-related potentials (ERPs) evoked by target objects were selectively enhanced at feedback stages of visual processing (from ~220 ms onwards) for high complexity scenes only. Third, behavioral performance for high complexity scenes deteriorated when participants were pressed for time and thus less able to incorporate the feedback activity. Modeling of the reaction time distributions using drift diffusion revealed that object information accumulated more slowly for high complexity scenes, with evidence accumulation being coupled to trial-to-trial variation in the EEG feedback response. Together, these results suggest that while feed-forward activity may suffice to recognize isolated objects, the brain employs recurrent processing more adaptively in naturalistic settings, using minimal feedback for simple scenes and increasing feedback for complex scenes.'),
(89404, 2019, 'plos', 'Context-explorer: Analysis of spatially organized protein expression in high-throughput screens', 'Ostblom, Joel|Nazareth, Emanuel J P|Tewary, Mukul|Zandstra, Peter W', 'Institute of Biomaterials and Biomedical Engineering, University of Toronto, Toronto, ON, Canada.|Institute of Biomaterials and Biomedical Engineering, University of Toronto, Toronto, ON, Canada.|Institute of Biomaterials and Biomedical Engineering, University of Toronto, Toronto, ON, Canada.|Institute of Biomaterials and Biomedical Engineering, University of Toronto, Toronto, ON, Canada.', 'Canada|Canada|Canada|Canada', 2, 'Algorithms|Animals|Cells, Cultured|Cellular Microenvironment|Computational Biology|Cytological Techniques|High-Throughput Screening Assays|Humans|Image Processing, Computer-Assisted|Mice|Pluripotent Stem Cells|Proteins|Software', 'Journal Article', '10.1371/journal.pcbi.1006384', '30601802', 'A growing body of evidence highlights the importance of the cellular microenvironment as a regulator of phenotypic and functional cellular responses to perturbations. We have previously developed cell patterning techniques to control population context parameters, and here we demonstrate context-explorer (CE), a software tool to improve investigation cell fate acquisitions through community level analyses. We demonstrate the capabilities of CE in the analysis of human and mouse pluripotent stem cells (hPSCs, mPSCs) patterned in colonies of defined geometries in multi-well plates. CE employs a density-based clustering algorithm to identify cell colonies. Using this automatic colony classification methodology, we reach accuracies comparable to manual colony counts in a fraction of the time, both in micropatterned and unpatterned wells. Classifying cells according to their relative position within a colony enables statistical analysis of spatial organization in protein expression within colonies. When applied to colonies of hPSCs, our analysis reveals a radial gradient in the expression of the transcription factors SOX2 and OCT4. We extend these analyses to colonies of different sizes and shapes and demonstrate how the metrics derived by CE can be used to asses the patterning fidelity of micropatterned plates. We have incorporated a number of features to enhance the usability and utility of CE. To appeal to a broad scientific community, all of the softwares functionality is accessible from a graphical user interface, and convenience functions for several common data operations are included. CE is compatible with existing image analysis programs such as CellProfiler and extends the analytical capabilities already provided by these tools. Taken together, CE facilitates investigation of spatially heterogeneous cell populations for fundamental research and drug development validation programs.'),
(89405, 2019, 'plos', 'Global analysis of N6-methyladenosine functions and its disease association using deep learning and network-based methods', 'Zhang, Song-Yao|Zhang, Shao-Wu|Fan, Xiao-Nan|Meng, Jia|Chen, Yidong|Gao, Shou-Jiang|Huang, Yufei', 'Key Laboratory of Information Fusion Technology of Ministry of Education, School of Automation, Northwestern Polytechnical University, Xian, China.|Key Laboratory of Information Fusion Technology of Ministry of Education, School of Automation, Northwestern Polytechnical University, Xian, China.|Key Laboratory of Information Fusion Technology of Ministry of Education, School of Automation, Northwestern Polytechnical University, Xian, China.|Department of Biological Sciences, HRINU, SUERI, Xian Jiaotong-Liverpool University, Suzhou, Jiangsu, China.|Department of Epidemiology and Biostatistics, University of Texas Health San Antonio, San Antonio, Texas, United States of America.|UPMC Hillman Cancer Center and Department of Microbiology and Molecular Genetics, University of Pittsburgh, Pittsburgh, Pennsylvania, United States of America.|Department of Electrical and Computer Engineering, University of Texas at San Antonio, San Antonio, Texas, United States of America.', 'China|China|China|China|United States|United States|United States', 15, 'Adenosine|Algorithms|Computational Biology|Deep Learning|Genetic Markers|Humans|Neoplasms|Protein Interaction Maps|Software', 'Journal Article', '10.1371/journal.pcbi.1006663', '30601803', 'N6-methyladenosine (m6A) is the most abundant methylation, existing in >25% of human mRNAs. Exciting recent discoveries indicate the close involvement of m6A in regulating many different aspects of mRNA metabolism and diseases like cancer. However, our current knowledge about how m6A levels are controlled and whether and how regulation of m6A levels of a specific gene can play a role in cancer and other diseases is mostly elusive. We propose in this paper a computational scheme for predicting m6A-regulated genes and m6A-associated disease, which includes Deep-m6A, the first model for detecting condition-specific m6A sites from MeRIP-Seq data with a single base resolution using deep learning and Hot-m6A, a new network-based pipeline that prioritizes functional significant m6A genes and its associated diseases using the Protein-Protein Interaction (PPI) and gene-disease heterogeneous networks. We applied Deep-m6A and this pipeline to 75 MeRIP-seq human samples, which produced a compact set of 709 functionally significant m6A-regulated genes and nine functionally enriched subnetworks. The functional enrichment analysis of these genes and networks reveal that m6A targets key genes of many critical biological processes including transcription, cell organization and transport, and cell proliferation and cancer-related pathways such as Wnt pathway. The m6A-associated disease analysis prioritized five significantly associated diseases including leukemia and renal cell carcinoma. These results demonstrate the power of our proposed computational scheme and provide new leads for understanding m6A regulatory functions and its roles in diseases.');
INSERT INTO `papers` (`id`, `ano`, `journal`, `titulo`, `autores`, `afiliacao`, `pais`, `citacoes`, `palavra_chave`, `categorias`, `doi`, `pubmed`, `abstract`) VALUES
(89406, 2019, 'plos', 'Short-term synaptic depression can increase the rate of information transfer at a release site', 'Salmasi, Mehrdad|Loebel, Alex|Glasauer, Stefan|Stemmler, Martin', 'Graduate School of Systemic Neurosciences, Ludwig-Maximilians-Universität, Munich, Germany.|Bernstein Center for Computational Neuroscience, Munich, Germany.|Bernstein Center for Computational Neuroscience, Munich, Germany.|Bernstein Center for Computational Neuroscience, Munich, Germany.', 'Germany|Germany|Germany|Germany', 4, 'Action Potentials|Animals|Computational Biology|Dopamine|Hippocampus|Memory|Models, Neurological|Neurotransmitter Agents|Nucleus Accumbens|Synapses', 'Journal Article', '10.1371/journal.pcbi.1006666', '30601804', 'The release of neurotransmitters from synapses obeys complex and stochastic dynamics. Depending on the recent history of synaptic activation, many synapses depress the probability of releasing more neurotransmitter, which is known as synaptic depression. Our understanding of how synaptic depression affects the information efficacy, however, is limited. Here we propose a mathematically tractable model of both synchronous spike-evoked release and asynchronous release that permits us to quantify the information conveyed by a synapse. The model transits between discrete states of a communication channel, with the present state depending on many past time steps, emulating the gradual depression and exponential recovery of the synapse. Asynchronous and spontaneous releases play a critical role in shaping the information efficacy of the synapse. We prove that depression can enhance both the information rate and the information rate per unit energy expended, provided that synchronous spike-evoked release depresses less (or recovers faster) than asynchronous release. Furthermore, we explore the theoretical implications of short-term synaptic depression adapting on longer time scales, as part of the phenomenon of metaplasticity. In particular, we show that a synapse can adjust its energy expenditure by changing the dynamics of short-term synaptic depression without affecting the net information conveyed by each successful release. Moreover, the optimal input spike rate is independent of the amplitude or time constant of synaptic depression. We analyze the information efficacy of three types of synapses for which the short-term dynamics of both synchronous and asynchronous release have been experimentally measured. In hippocampal autaptic synapses, the persistence of asynchronous release during depression cannot compensate for the reduction of synchronous release, so that the rate of information transmission declines with synaptic depression. In the calyx of Held, the information rate per release remains constant despite large variations in the measured asynchronous release rate. Lastly, we show that dopamine, by controlling asynchronous release in corticostriatal synapses, increases the synaptic information efficacy in nucleus accumbens.'),
(89407, 2019, 'plos', 'Locus Coeruleus tracking of prediction errors optimises cognitive flexibility: An Active Inference model', 'Sales, Anna C|Friston, Karl J|Jones, Matthew W|Pickering, Anthony E|Moran, Rosalyn J', 'School of Physiology, Pharmacology and Neuroscience, University of Bristol, Bristol, United Kingdom.|Wellcome Trust Centre for Neuroimaging, UCL, London, United Kingdom.|School of Physiology, Pharmacology and Neuroscience, University of Bristol, Bristol, United Kingdom.|School of Physiology, Pharmacology and Neuroscience, University of Bristol, Bristol, United Kingdom.|School of Physiology, Pharmacology and Neuroscience, University of Bristol, Bristol, United Kingdom.', 'United Kingdom|United Kingdom|United Kingdom|United Kingdom|United Kingdom', 0, 'Animals|Cognition|Computational Biology|Learning|Locus Coeruleus|Models, Neurological|Norepinephrine|Reward', 'Journal Article', '10.1371/journal.pcbi.1006267', '30608922', 'The locus coeruleus (LC) in the pons is the major source of noradrenaline (NA) in the brain. Two modes of LC firing have been associated with distinct cognitive states: changes in tonic rates of firing are correlated with global levels of arousal and behavioural flexibility, whilst phasic LC responses are evoked by salient stimuli. Here, we unify these two modes of firing by modelling the response of the LC as a correlate of a prediction error when inferring states for action planning under Active Inference (AI). We simulate a classic Go/No-go reward learning task and a three-arm explore/exploit task and show that, if LC activity is considered to reflect the magnitude of high level state-action prediction errors, then both tonic and phasic modes of firing are emergent features of belief updating. We also demonstrate that when contingencies change, AI agents can update their internal models more quickly by feeding back this state-action prediction error-reflected in LC firing and noradrenaline release-to optimise learning rate, enabling large adjustments over short timescales. We propose that such prediction errors are mediated by cortico-LC connections, whilst ascending input from LC to cortex modulates belief updating in anterior cingulate cortex (ACC). In short, we characterise the LC/ NA system within a general theory of brain function. In doing so, we show that contrasting, behaviour-dependent firing patterns are an emergent property of the LC that translates state-action prediction errors into an optimal balance between plasticity and stability.'),
(89408, 2019, 'plos', 'A computational model to understand mouse iron physiology and disease', 'Parmar, Jignesh H|Mendes, Pedro', 'Center for Quantitative Medicine and Department of Cell Biology, University of Connecticut School of Medicine, Farmington, Connecticut, United States of America.|Center for Quantitative Medicine and Department of Cell Biology, University of Connecticut School of Medicine, Farmington, Connecticut, United States of America.', 'United States|United States', 0, 'Animals|Computational Biology|Iron|Iron Metabolism Disorders|Liver|Mice|Models, Biological|Transferrin|beta-Thalassemia', 'Journal Article', '10.1371/journal.pcbi.1006680', '30608934', 'It is well known that iron is an essential element for life but is toxic when in excess or in certain forms. Accordingly there are many diseases that result directly from either lack or excess of iron. Yet many molecular and physiological aspects of iron regulation have only been discovered recently and others are still elusive. There is still no good quantitative and dynamic description of iron absorption, distribution, storage and mobilization that agrees with the wide array of phenotypes presented in several iron-related diseases. The present work addresses this issue by developing a mathematical model of iron distribution in mice calibrated with ferrokinetic data and subsequently validated against data from mouse models of iron disorders, such as hemochromatosis, xcexb2-thalassemia, atransferrinemia and anemia of inflammation. To adequately fit the ferrokinetic data required inclusion of the following mechanisms: a) transferrin-mediated iron delivery to tissues, b) induction of hepcidin by transferrin-bound iron, c) ferroportin-dependent iron export regulated by hepcidin, d) erythropoietin regulation of erythropoiesis, and e) liver uptake of NTBI. The utility of the model to simulate disease interventions was demonstrated by using it to investigate the outcome of different schedules of transferrin treatment in xcexb2-thalassemia.'),
(89409, 2019, 'plos', 'Protein-protein binding supersites', 'Viswanathan, Raji|Fajardo, Eduardo|Steinberg, Gabriel|Haller, Matthew|Fiser, Andras', 'Department of Chemistry, Yeshiva University, New York, NY, United States of America.|Departments of Systems & Computational Biology, and Biochemistry, Albert Einstein College of Medicine, Bronx, NY, United States of America.|Department of Chemistry, Yeshiva University, New York, NY, United States of America.|Department of Chemistry, Yeshiva University, New York, NY, United States of America.|Departments of Systems & Computational Biology, and Biochemistry, Albert Einstein College of Medicine, Bronx, NY, United States of America.', 'United States|United States|United States|United States|United States', 0, 'Algorithms|Binding Sites|Computational Biology|Databases, Protein|Molecular Docking Simulation|Protein Binding|Protein Conformation|Proteins|ROC Curve', 'Journal Article', '10.1371/journal.pcbi.1006704', '30615604', 'The lack of a deep understanding of how proteins interact remains an important roadblock in advancing efforts to identify binding partners and uncover the corresponding regulatory mechanisms of the functions they mediate. Understanding protein-protein interactions is also essential for designing specific chemical modifications to develop new reagents and therapeutics. We explored the hypothesis of whether protein interaction sites serve as generic biding sites for non-cognate protein ligands, just as it has been observed for small-molecule-binding sites in the past. Using extensive computational docking experiments on a test set of 241 protein complexes, we found that indeed there is a strong preference for non-cognate ligands to bind to the cognate binding site of a receptor. This observation appears to be robust to variations in docking programs, types of non-cognate protein probes, sizes of binding patches, relative sizes of binding patches and full-length proteins, and the exploration of obligate and non-obligate complexes. The accuracy of the docking scoring function appears to play a role in defining the correct site. The frequency of interaction of unrelated probes recognizing the binding interface was utilized in a simple prediction algorithm that showed accuracy competitive with other state of the art methods.'),
(89410, 2019, 'plos', 'Calcium phosphate precipitation inhibits mitochondrial energy metabolism', 'Malyala, Sathyavani|Zhang, Yizhu|Strubbe, Jasiel O|Bazil, Jason N', 'Department of Physiology, Michigan State University, East Lansing, MI, United States of America.|Department of Physiology, Michigan State University, East Lansing, MI, United States of America.|Department of Physiology, Michigan State University, East Lansing, MI, United States of America.|Department of Physiology, Michigan State University, East Lansing, MI, United States of America.', 'United States|United States|United States|United States', 6, 'Animals|Calcium|Calcium Phosphates|Cell Membrane Permeability|Computational Biology|Energy Metabolism|Guinea Pigs|Membrane Potential, Mitochondrial|Mitochondria, Heart|Models, Biological', 'Journal Article', '10.1371/journal.pcbi.1006719', '30615608', 'Early studies have shown that moderate levels of calcium overload can cause lower oxidative phosphorylation rates. However, the mechanistic interpretations of these findings were inadequate. And while the effect of excessive calcium overload on mitochondrial function is well appreciated, there has been little to no reports on the consequences of low to moderate calcium overload. To resolve this inadequacy, mitochondrial function from guinea pig hearts was quantified using several well-established methods including high-resolution respirometry and spectrofluorimetry and analyzed using mathematical modeling. We measured key mitochondrial variables such as respiration, mitochondrial membrane potential, buffer calcium, and substrate effects for a range of mitochondrial calcium loads from near zero to levels approaching mitochondrial permeability transition. In addition, we developed a computer model closely mimicking the experimental conditions and used this model to design experiments capable of eliminating many hypotheses generated from the data analysis. We subsequently performed those experiments and determined why mitochondrial ADP-stimulated respiration is significantly lowered during calcium overload. We found that when calcium phosphate levels, not matrix free calcium, reached sufficient levels, complex I activity is inhibited, and the rate of ATP synthesis is reduced. Our findings suggest that calcium phosphate granules form physical barriers that isolate complex I from NADH, disrupt complex I activity, or destabilize cristae and inhibit NADH-dependent respiration.'),
(89411, 2019, 'plos', 'Mutation, drift and selection in single-driver hematologic malignancy: Example of secondary myelodysplastic syndrome following treatment of inherited neutropenia', 'Wojdyla, Tomasz|Mehta, Hrishikesh|Glaubach, Taly|Bertolusso, Roberto|Iwanaszko, Marta|Braun, Rosemary|Corey, Seth J|Kimmel, Marek', 'Systems Engineering Group, Silesian University of Technology, Gliwice, Poland.|Department of Pediatrics, Cleveland Clinic, Cleveland, OH, United States of America.|Clinical Pediatrics, Division of Hospital Medicine, Stony Brook Childrens Hospital, Stony Brook, New York.|Department of Statistics, Rice University, Houston, TX, United States of America.|Systems Engineering Group, Silesian University of Technology, Gliwice, Poland.|Department of Preventive Medicine-Division of Biostatistics, Northwestern University, Chicago, IL United States of America.|Department of Pediatrics, Cleveland Clinic, Cleveland, OH, United States of America.|Systems Engineering Group, Silesian University of Technology, Gliwice, Poland.', 'Poland|United States|-|United States|Poland|United States|United States|Poland', 0, 'Cell Cycle|Computational Biology|Hematologic Neoplasms|Humans|Leukocyte Elastase|Models, Genetic|Mutation|Mutation Rate|Myelodysplastic Syndromes|Neutropenia|Receptors, Colony-Stimulating Factor|Selection, Genetic', 'Journal Article', '10.1371/journal.pcbi.1006664', '30615612', 'Cancer development is driven by series of events involving mutations, which may become fixed in a tumor via genetic drift and selection. This process usually includes a limited number of driver (advantageous) mutations and a greater number of passenger (neutral or mildly deleterious) mutations. We focus on a real-world leukemia model evolving on the background of a germline mutation. Severe congenital neutropenia (SCN) evolves to secondary myelodysplastic syndrome (sMDS) and/or secondary acute myeloid leukemia (sAML) in 30-40%. The majority of SCN cases are due to a germline ELANE mutation. Acquired mutations in CSF3R occur in >70% sMDS/sAML associated with SCN. Hypotheses underlying our model are: an ELANE mutation causes SCN, CSF3R mutations occur spontaneously at a low rate, in fetal life, hematopoietic stem and progenitor cells expands quickly, resulting in a high probability of several tens to several hundreds of cells with CSF3R truncation mutations, therapeutic granulocyte colony-stimulating factor (G-CSF) administration early in life exerts a strong selective pressure, providing mutants with a growth advantage. Applying population genetics theory, we propose a novel two-phase model of disease development from SCN to sMDS. In Phase 1, hematopoietic tissues expand and produce tens to hundreds of stem cells with the CSF3R truncation mutation. Phase 2 occurs postnatally through adult stages with bone marrow production of granulocyte precursors and positive selection of mutants due to chronic G-CSF therapy to reverse the severe neutropenia. We predict the existence of the pool of cells with the mutated truncated receptor before G-CSF treatment begins. The model does not require increase in mutation rate under G-CSF treatment and agrees with age distribution of sMDS onset and clinical sequencing data.'),
(89412, 2019, 'plos', 'Sour grapes and sweet victories: How actions shape preferences', 'Vinckier, Fabien|Rigoux, Lionel|Kurniawan, Irma T|Hu, Chen|Bourgeois-Gironde, Sacha|Daunizeau, Jean|Pessiglione, Mathias', 'Motivation, Brain & Behavior (MBB) lab, Institut du Cerveau et de la Moelle épinière (ICM), Hôpital de la Pitié-Salpêtrière, Paris, France.|Translational Neurocircuitry Group, Max Planck Institute for Metabolism Research, Cologne, Germany.|Motivation, Brain & Behavior (MBB) lab, Institut du Cerveau et de la Moelle épinière (ICM), Hôpital de la Pitié-Salpêtrière, Paris, France.|Motivation, Brain & Behavior (MBB) lab, Institut du Cerveau et de la Moelle épinière (ICM), Hôpital de la Pitié-Salpêtrière, Paris, France.|Laboratoire dÉconomie Mathématique et de Microéconomie Appliquée (LEMMA), Université Panthéon-Assas, Paris, France.|Motivation, Brain & Behavior (MBB) lab, Institut du Cerveau et de la Moelle épinière (ICM), Hôpital de la Pitié-Salpêtrière, Paris, France.|Motivation, Brain & Behavior (MBB) lab, Institut du Cerveau et de la Moelle épinière (ICM), Hôpital de la Pitié-Salpêtrière, Paris, France.', 'France|Germany|France|France|France|France|France', 4, 'Adult|Bayes Theorem|Choice Behavior|Computational Biology|Decision Making|Decision Theory|Female|Hand Strength|Humans|Male|Task Performance and Analysis|Young Adult', 'Journal Article', '10.1371/journal.pcbi.1006499', '30615615', 'Classical decision theory postulates that choices proceed from subjective values assigned to the probable outcomes of alternative actions. Some authors have argued that opposite causality should also be envisaged, with choices influencing subsequent values expressed in desirability ratings. The idea is that agents may increase their ratings of items that they have chosen in the first place, which has been typically explained by the need to reduce cognitive dissonance. However, evidence in favor of this reverse causality has been the topic of intense debates that have not reached consensus so far. Here, we take a novel approach using Bayesian techniques to compare models in which choices arise from stable (but noisy) underlying values (one-way causality) versus models in which values are in turn influenced by choices (two-way causality). Moreover, we examined whether in addition to choices, other components of previous actions, such as the effort invested and the eventual action outcome (success or failure), could also impact subsequent values. Finally, we assessed whether the putative changes in values were only expressed in explicit ratings, or whether they would also affect other value-related behaviors such as subsequent choices. Behavioral data were obtained from healthy participants in a rating-choice-rating-choice-rating paradigm, where the choice task involves deciding whether or not to exert a given physical effort to obtain a particular food item. Bayesian selection favored two-way causality models, where changes in value due to previous actions affected subsequent ratings, choices and action outcomes. Altogether, these findings may help explain how values and actions drift when several decisions are made successively, hence highlighting some shortcomings of classical decision theory.'),
(89413, 2019, 'plos', 'Using the drug-protein interactome to identify anti-ageing compounds for humans', 'Fuentealba, Matxc3xadas|Dxc3xb6nertaxc5x9f, Handan Melike|Williams, Rhianna|Labbadia, Johnathan|Thornton, Janet M|Partridge, Linda', 'Institute of Healthy Ageing, Department of Genetics, Evolution and Environment, University College London, London, United Kingdom.|European Molecular Biology Laboratory, European Bioinformatics Institute, Wellcome Genome Campus, Hinxton, Cambridge, United Kingdom.|Institute of Healthy Ageing, Department of Genetics, Evolution and Environment, University College London, London, United Kingdom.|Institute of Healthy Ageing, Department of Genetics, Evolution and Environment, University College London, London, United Kingdom.|European Molecular Biology Laboratory, European Bioinformatics Institute, Wellcome Genome Campus, Hinxton, Cambridge, United Kingdom.|Institute of Healthy Ageing, Department of Genetics, Evolution and Environment, University College London, London, United Kingdom.', 'United Kingdom|United Kingdom|United Kingdom|United Kingdom|United Kingdom|United Kingdom', 8, 'Aging|Animals|Caenorhabditis elegans|Caenorhabditis elegans Proteins|Computational Biology|Drug Discovery|Drug Interactions|Humans|Longevity|Protective Agents|Protein Binding', 'Journal Article', '10.1371/journal.pcbi.1006639', '30625143', 'Advancing age is the dominant risk factor for most of the major killer diseases in developed countries. Hence, ameliorating the effects of ageing may prevent multiple diseases simultaneously. Drugs licensed for human use against specific diseases have proved to be effective in extending lifespan and healthspan in animal models, suggesting that there is scope for drug repurposing in humans. New bioinformatic methods to identify and prioritise potential anti-ageing compounds for humans are therefore of interest. In this study, we first used drug-protein interaction information, to rank 1,147 drugs by their likelihood of targeting ageing-related gene products in humans. Among 19 statistically significant drugs, 6 have already been shown to have pro-longevity properties in animal models (p < 0.001). Using the targets of each drug, we established their association with ageing at multiple levels of biological action including pathways, functions and protein interactions. Finally, combining all the data, we calculated a ranked list of drugs that identified tanespimycin, an inhibitor of HSP-90, as the top-ranked novel anti-ageing candidate. We experimentally validated the pro-longevity effect of tanespimycin through its HSP-90 target in Caenorhabditis elegans.'),
(89414, 2019, 'plos', 'A computational knowledge-base elucidates the response of Staphylococcus aureus to different media types', 'Seif, Yara|Monk, Jonathan M|Mih, Nathan|Tsunemoto, Hannah|Poudel, Saugat|Zuniga, Cristal|Broddrick, Jared|Zengler, Karsten|Palsson, Bernhard O', 'Department of Bioengineering, University of California, San Diego, La Jolla, CA, United States of America.|Department of Bioengineering, University of California, San Diego, La Jolla, CA, United States of America.|Department of Bioengineering, University of California, San Diego, La Jolla, CA, United States of America.|Division of Biological Sciences, University of California San Diego, La Jolla, CA, United States of America.|Department of Bioengineering, University of California, San Diego, La Jolla, CA, United States of America.|Department of Bioengineering, University of California, San Diego, La Jolla, CA, United States of America.|Department of Bioengineering, University of California, San Diego, La Jolla, CA, United States of America.|Department of Bioengineering, University of California, San Diego, La Jolla, CA, United States of America.|Department of Bioengineering, University of California, San Diego, La Jolla, CA, United States of America.', 'United States|United States|United States|United States|United States|United States|United States|Un', 7, 'Culture Media|Gene Expression Regulation, Bacterial|Genome, Bacterial|Knowledge Bases|Metabolic Networks and Pathways|Metabolome|Metabolomics|Models, Biological|Staphylococcus aureus|Systems Biology', 'Journal Article', '10.1371/journal.pcbi.1006644', '30625152', 'S. aureus is classified as a serious threat pathogen and is a priority that guides the discovery and development of new antibiotics. Despite growing knowledge of S. aureus metabolic capabilities, our understanding of its systems-level responses to different media types remains incomplete. Here, we develop a manually reconstructed genome-scale model (GEM-PRO) of metabolism with 3D protein structures for S. aureus USA300 str. JE2 containing 854 genes, 1,440 reactions, 1,327 metabolites and 673 3-dimensional protein structures. Computations were in 85% agreement with gene essentiality data from random barcode transposon site sequencing (RB-TnSeq) and 68% agreement with experimental physiological data. Comparisons of computational predictions with experimental observations highlight: 1) cases of non-essential biomass precursors, 2) metabolic genes subject to transcriptional regulation involved in Staphyloxanthin biosynthesis, 3) the essentiality of purine and amino acid biosynthesis in synthetic physiological media, and 4) a switch to aerobic fermentation upon exposure to extracellular glucose elucidated as a result of integrating time-course of quantitative exo-metabolomics data. An up-to-date GEM-PRO thus serves as a knowledge-based platform to elucidate S. aureus metabolic response to its environment.'),
(89415, 2019, 'plos', 'Whole genomes define concordance of matched primary, xenograft, and organoid models of pancreas cancer', 'Gendoo, Deena M A|Denroche, Robert E|Zhang, Amy|Radulovich, Nikolina|Jang, Gun Ho|Lemire, Mathieu|Fischer, Sandra|Chadwick, Dianne|Lungu, Ilinca M|Ibrahimov, Emin|Cao, Ping-Jiang|Stein, Lincoln D|Wilson, Julie M|Bartlett, John M S|Tsao, Ming-Sound|Dhani, Neesha|Hedley, David|Gallinger, Steven|Haibe-Kains, Benjamin', 'Centre for Computational Biology, Institute of Cancer and Genomic Sciences, University of Birmingham, Birmingham, United Kingdom.|PanCuRx Translational Research Initiative, Ontario Institute of Cancer Research (OICR), Toronto, Ontario, Canada.|PanCuRx Translational Research Initiative, Ontario Institute of Cancer Research (OICR), Toronto, Ontario, Canada.|Princess Margaret Living Biobank Core, University Health Network, Toronto, Ontario, Canada.|PanCuRx Translational Research Initiative, Ontario Institute of Cancer Research (OICR), Toronto, Ontario, Canada.|PanCuRx Translational Research Initiative, Ontario Institute of Cancer Research (OICR), Toronto, Ontario, Canada.|Department of Pathology, University Health Network, University of Toronto, Toronto, Ontario, Canada.|UHN Program in BioSpecimen Sciences, Department of Pathology, University Health Network, Toronto, Ontario, Canada.|Transformative Pathology, Ontario Institute for Cancer Research, Toronto, Ontario, Canada.|Princess Margaret Living Biobank Core, University Health Network, Toronto, Ontario, Canada.|Division of Medical Oncology, Princess Margaret Cancer Centre, Toronto, Ontario, Canada.|Informatics and Bio-computing Program, Ontario Institute for Cancer Research, Toronto, Ontario, Canada.|PanCuRx Translational Research Initiative, Ontario Institute of Cancer Research (OICR), Toronto, Ontario, Canada.|Transformative Pathology, Ontario Institute for Cancer Research, Toronto, Ontario, Canada.|Princess Margaret Living Biobank Core, University Health Network, Toronto, Ontario, Canada.|Division of Medical Oncology, Princess Margaret Cancer Centre, Toronto, Ontario, Canada.|Division of Medical Oncology, Princess Margaret Cancer Centre, Toronto, Ontario, Canada.|PanCuRx Translational Research Initiative, Ontario Institute of Cancer Research (OICR), Toronto, Ontario, Canada.|PanCuRx Translational Research Initiative, Ontario Institute of Cancer Research (OICR), Toronto, Ontario, Canada.', 'United Kingdom|Canada|Canada|Canada|Canada|Canada|Canada|Canada|Canada|Canada|Canada|Canada|Canada|C', 0, 'Animals|Biomedical Research|Carcinoma, Pancreatic Ductal|Genome|Humans|Models, Biological|Neoplasms, Experimental|Pancreas|Pancreatic Neoplasms', 'Journal Article', '10.1371/journal.pcbi.1006596', '30629588', 'Pancreatic ductal adenocarcinoma (PDAC) has the worst prognosis among solid malignancies and improved therapeutic strategies are needed to improve outcomes. Patient-derived xenografts (PDX) and patient-derived organoids (PDO) serve as promising tools to identify new drugs with therapeutic potential in PDAC. For these preclinical disease models to be effective, they should both recapitulate the molecular heterogeneity of PDAC and validate patient-specific therapeutic sensitivities. To date however, deep characterization of the molecular heterogeneity of PDAC PDX and PDO models and comparison with matched human tumour remains largely unaddressed at the whole genome level. We conducted a comprehensive assessment of the genetic landscape of 16 whole-genome pairs of tumours and matched PDX, from primary PDAC and liver metastasis, including a unique cohort of 5 trios of matched primary tumour, PDX, and PDO. We developed a pipeline to score concordance between PDAC models and their paired human tumours for genomic events, including mutations, structural variations, and copy number variations. Tumour-model comparisons of mutations displayed single-gene concordance across major PDAC driver genes, but relatively poor agreement across the greater mutational load. Genome-wide and chromosome-centric analysis of structural variation (SV) events highlights previously unrecognized concordance across chromosomes that demonstrate clustered SV events. We found that polyploidy presented a major challenge when assessing copy number changes, however, ploidy-corrected copy number states suggest good agreement between donor-model pairs. Collectively, our investigations highlight that while PDXs and PDOs may serve as tractable and transplantable systems for probing the molecular properties of PDAC, these models may best serve selective analyses across different levels of genomic complexity.'),
(89416, 2019, 'plos', 'Computational translation of genomic responses from experimental model systems to humans', 'Brubaker, Douglas K|Proctor, Elizabeth A|Haigis, Kevin M|Lauffenburger, Douglas A', 'Department of Biological Engineering, Massachusetts Institute of Technology, Cambridge, MA, United States of America.|Department of Biological Engineering, Massachusetts Institute of Technology, Cambridge, MA, United States of America.|Cancer Research Institute, Beth Israel Deaconess Cancer Center and Department of Medicine, Harvard University Medical School, Boston, MA, United States of America.|Department of Biological Engineering, Massachusetts Institute of Technology, Cambridge, MA, United States of America.', 'United States|United States|Israel|United States', 8, 'Animals|Disease Models, Animal|Gene Expression Profiling|Genomics|Humans|Inflammation|Mice|Neural Networks (Computer)|Supervised Machine Learning|Transcriptome|Translational Medical Research', 'Journal Article', '10.1371/journal.pcbi.1006286', '30629591', 'The high failure rate of therapeutics showing promise in mouse models to translate to patients is a pressing challenge in biomedical science. Though retrospective studies have examined the fidelity of mouse models to their respective human conditions, approaches for prospective translation of insights from mouse models to patients remain relatively unexplored. Here, we develop a semi-supervised learning approach for inference of disease-associated human differentially expressed genes and pathways from mouse model experiments. We examined 36 transcriptomic case studies where comparable phenotypes were available for mouse and human inflammatory diseases and assessed multiple computational approaches for inferring human biology from mouse datasets. We found that semi-supervised training of a neural network identified significantly more true human biological associations than interpreting mouse experiments directly. Evaluating the experimental design of mouse experiments where our model was most successful revealed principles of experimental design that may improve translational performance. Our study shows that when prospectively evaluating biological associations in mouse studies, semi-supervised learning approaches, combining mouse and human data for biological inference, provide the most accurate assessment of human in vivo disease processes. Finally, we proffer a delineation of four categories of model system-to-human Translation Problems defined by the resolution and coverage of the datasets available for molecular insight translation and suggest that the task of translating insights from model systems to human disease contexts may be better accomplished by a combination of translation-minded experimental design and computational approaches.'),
(89417, 2019, 'plos', 'Correction: clusterExperiment and RSEC: A Bioconductor package and framework for clustering of single-cell and other large gene expression datasets', 'PLOS Computational Biology Staff', 'Department of Biological Engineering, Massachusetts Institute of Technology, Cambridge, MA, United States of America.', 'United States', 0, '-', 'Journal Article', '10.1371/journal.pcbi.1006727', '30633740', '[This corrects the article DOI: 10.1371/journal.pcbi.1006378.].'),
(89418, 2019, 'plos', 'PAIRUP-MS: Pathway analysis and imputation to relate unknowns in profiles from mass spectrometry-based metabolite data', 'Hsu, Yu-Han H|Churchhouse, Claire|Pers, Tune H|Mercader, Josep M|Metspalu, Andres|Fischer, Krista|Fortney, Kristen|Morgen, Eric K|Gonzalez, Clicerio|Gonzalez, Maria E|Esko, Tonu|Hirschhorn, Joel N', 'Department of Genetics, Harvard Medical School, Boston, Massachusetts, United States of America.|Stanley Center for Psychiatric Research, Broad Institute of Harvard and MIT, Cambridge, Massachusetts, United States of America.|Novo Nordisk Foundation Centre for Basic Metabolic Research, University of Copenhagen, Copenhagen, Denmark.|Programs in Metabolism and Medical & Population Genetics, Broad Institute of Harvard and MIT, Cambridge, Massachusetts, United States of America.|Estonian Genome Center, Institute of Genomics, University of Tartu, Tartu, Estonia.|Estonian Genome Center, Institute of Genomics, University of Tartu, Tartu, Estonia.|BioAge Labs, Richmond, CA, United States of America.|BioAge Labs, Richmond, CA, United States of America.|Instituto Nacional de Salud Publica, Cuernavaca, Morelos, Mexico.|Instituto Nacional de Salud Publica, Cuernavaca, Morelos, Mexico.|Programs in Metabolism and Medical & Population Genetics, Broad Institute of Harvard and MIT, Cambridge, Massachusetts, United States of America.|Department of Genetics, Harvard Medical School, Boston, Massachusetts, United States of America.', 'United States|United States|Denmark|United States|Estonia|Estonia|United States|United States|Mexico', 4, 'Aged|Aged, 80 and over|Biomarkers|Computational Biology|Databases, Factual|Humans|Mass Spectrometry|Metabolic Networks and Pathways|Metabolome|Metabolomics', 'Journal Article', '10.1371/journal.pcbi.1006734', '30640898', 'Metabolomics is a powerful approach for discovering biomarkers and for characterizing the biochemical consequences of genetic variation. While untargeted metabolite profiling can measure thousands of signals in a single experiment, many biologically meaningful signals cannot be readily identified as known metabolites nor compared across datasets, making it difficult to infer biology and to conduct well-powered meta-analyses across studies. To overcome these challenges, we developed a suite of computational methods, PAIRUP-MS, to match metabolite signals across mass spectrometry-based profiling datasets and to generate metabolic pathway annotations for these signals. To pair up signals measured in different datasets, where retention times (RT) are often not comparable or even available, we implemented an imputation-based approach that only requires mass-to-charge ratios (m/z). As validation, we treated each shared known metabolite as an unmatched signal and showed that PAIRUP-MS correctly matched 70-88% of these metabolites from among thousands of signals, equaling or outperforming a standard m/z- and RT-based approach. We performed further validation using genetic data: the most stringent set of matched signals and shared knowns showed comparable consistency of genetic associations across datasets. Next, we developed a pathway reconstitution method to annotate unknown signals using curated metabolic pathways containing known metabolites. We performed genetic validation for the generated annotations, showing that annotated signals associated with gene variants were more likely to be enriched for pathways functionally related to the genes compared to random expectation. Finally, we applied PAIRUP-MS to study associations between metabolites and genetic variants or body mass index (BMI) across multiple datasets, identifying up to ~6 times more significant signals and many more BMI-associated pathways compared to the standard practice of only analyzing known metabolites. These results demonstrate that PAIRUP-MS enables analysis of unknown signals in a robust, biologically meaningful manner and provides a path to more comprehensive, well-powered studies of untargeted metabolomics data.'),
(89419, 2019, 'plos', 'Deep image reconstruction from human brain activity', 'Shen, Guohua|Horikawa, Tomoyasu|Majima, Kei|Kamitani, Yukiyasu', 'Computational Neuroscience Laboratories, Advanced Telecommunications Research Institute International, Kyoto, Japan.|Computational Neuroscience Laboratories, Advanced Telecommunications Research Institute International, Kyoto, Japan.|Graduate school of Informatics, Kyoto University, Kyoto, Japan.|Computational Neuroscience Laboratories, Advanced Telecommunications Research Institute International, Kyoto, Japan.', 'Japan|Japan|Japan|Japan', 17, 'Adult|Algorithms|Brain|Deep Learning|Female|Humans|Image Processing, Computer-Assisted|Imagination|Magnetic Resonance Imaging|Male|Photic Stimulation|Signal Processing, Computer-Assisted|Young Adult', 'Journal Article', '10.1371/journal.pcbi.1006633', '30640910', 'The mental contents of perception and imagery are thought to be encoded in hierarchical representations in the brain, but previous attempts to visualize perceptual contents have failed to capitalize on multiple levels of the hierarchy, leaving it challenging to reconstruct internal imagery. Recent work showed that visual cortical activity measured by functional magnetic resonance imaging (fMRI) can be decoded (translated) into the hierarchical features of a pre-trained deep neural network (DNN) for the same input image, providing a way to make use of the information from hierarchical visual features. Here, we present a novel image reconstruction method, in which the pixel values of an image are optimized to make its DNN features similar to those decoded from human brain activity at multiple layers. We found that our method was able to reliably produce reconstructions that resembled the viewed natural images. A natural image prior introduced by a deep generator neural network effectively rendered semantically meaningful details to the reconstructions. Human judgment of the reconstructions supported the effectiveness of combining multiple DNN layers to enhance the visual quality of generated images. While our model was solely trained with natural images, it successfully generalized to artificial shapes, indicating that our model was not simply matching to exemplars. The same analysis applied to mental imagery demonstrated rudimentary reconstructions of the subjective content. Our results suggest that our method can effectively combine hierarchical neural representations to reconstruct perceptual and subjective images, providing a new window into the internal contents of the brain.'),
(89420, 2019, 'plos', 'The finite state projection based Fisher information matrix approach to estimate information and optimize single-cell experiments', 'Fox, Zachary R|Munsky, Brian', 'Keck Scholars, School of Biomedical Engineering, Colorado State University, Fort Collins, CO, USA.|Keck Scholars, School of Biomedical Engineering, Colorado State University, Fort Collins, CO, USA.', 'United States|United States', 0, 'Computer Simulation|Models, Statistical|Monte Carlo Method|Optical Imaging|Research Design|Single-Cell Analysis|Systems Biology', 'Journal Article', '10.1371/journal.pcbi.1006365', '30645589', 'Modern optical imaging experiments not only measure single-cell and single-molecule dynamics with high precision, but they can also perturb the cellular environment in myriad controlled and novel settings. Techniques, such as single-molecule fluorescence in-situ hybridization, microfluidics, and optogenetics, have opened the door to a large number of potential experiments, which begs the question of how to choose the best possible experiment. The Fisher information matrix (FIM) estimates how well potential experiments will constrain model parameters and can be used to design optimal experiments. Here, we introduce the finite state projection (FSP) based FIM, which uses the formalism of the chemical master equation to derive and compute the FIM. The FSP-FIM makes no assumptions about the distribution shapes of single-cell data, and it does not require precise measurements of higher order moments of such distributions. We validate the FSP-FIM against well-known Fisher information results for the simple case of constitutive gene expression. We then use numerical simulations to demonstrate the use of the FSP-FIM to optimize the timing of single-cell experiments with more complex, non-Gaussian fluctuations. We validate optimal simulated experiments determined using the FSP-FIM with Monte-Carlo approaches and contrast these to experiment designs chosen by traditional analyses that assume Gaussian fluctuations or use the central limit theorem. By systematically designing experiments to use all of the measurable fluctuations, our method enables a key step to improve co-design of experiments and quantitative models.'),
(89421, 2019, 'plos', 'On identifying collective displacements in apo-proteins that reveal eventual binding pathways', 'Dube, Dheeraj|Ahalawat, Navjeet|Khandelia, Himanshu|Mondal, Jagannath|Sengupta, Surajit', 'Tata Institute of Fundamental Research, Center for Interdisciplinary Sciences, Hyderabad, India.|Tata Institute of Fundamental Research, Center for Interdisciplinary Sciences, Hyderabad, India.|MEMPHYS, Center for Biomembrane Physics, Department of Physics, Chemistry and Pharmacy, University of Southern Denmark, Odense, Denmark.|Tata Institute of Fundamental Research, Center for Interdisciplinary Sciences, Hyderabad, India.|Tata Institute of Fundamental Research, Center for Interdisciplinary Sciences, Hyderabad, India.', 'India|India|Denmark|India|India', 4, 'Animals|Computational Biology|Ligands|Molecular Dynamics Simulation|Protein Binding|Protein Conformation|Proteins', 'Journal Article', '10.1371/journal.pcbi.1006665', '30645590', 'Binding of small molecules to proteins often involves large conformational changes in the latter, which open up pathways to the binding site. Observing and pinpointing these rare events in large scale, all-atom, computations of specific protein-ligand complexes, is expensive and to a great extent serendipitous. Further, relevant collective variables which characterise specific binding or un-binding scenarios are still difficult to identify despite the large body of work on the subject. Here, we show that possible primary and secondary binding pathways can be discovered from short simulations of the apo-protein without waiting for an actual binding event to occur. We use a projection formalism, introduced earlier to study deformation in solids, to analyse local atomic displacements into two mutually orthogonal subspaces-those which are affine i.e. expressible as a homogeneous deformation of the native structure, and those which are not. The susceptibility to non-affine displacements among the various residues in the apo- protein is then shown to correlate with typical binding pathways and sites crucial for allosteric modifications. We validate our observation with all-atom computations of three proteins, T4-Lysozyme, Src kinase and Cytochrome P450.'),
(89422, 2019, 'plos', 'Ten simple rules on how to create open access and reproducible molecular simulations of biological systems', 'Elofsson, Arne|Hess, Berk|Lindahl, Erik|Onufriev, Alexey|van der Spoel, David|Wallqvist, Anders', 'Department of Biochemistry and Biophysics, Science for life Laboratory, Stockholm University, Solna, Sweden.|Department of Physics, Swedish e-Science Research Center, KTH Royal Institute of Technology, Stockholm, Sweden.|Department of Biochemistry and Biophysics, Science for life Laboratory, Stockholm University, Solna, Sweden.|Departments of Computer Science and Physics, Center for Soft Matter and Biological Physics, Virginia Tech, Blacksburg, Virginia, United States of America.|Uppsala Centre for Computational Chemistry, Science for Life Laboratory, Department of Cell and Molecular Biology, Uppsala University, Uppsala, Sweden.|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.', 'Sweden|Sweden|Sweden|United States|Sweden|United States', 0, 'Access to Information|Databases, Factual|Humans|Information Dissemination|Molecular Docking Simulation|Molecular Dynamics Simulation|Monte Carlo Method|Software', 'Editorial', '10.1371/journal.pcbi.1006649', '30653494', '-'),
(89423, 2019, 'plos', 'Thermodynamic model of gene regulation for the Or59b olfactory receptor in Drosophila', 'González, Alejandra|Jafari, Shadi|Zenere, Alberto|Alenius, Mattias|Altafini, Claudio', 'Department of Electrical Engineering, Linköping University, Linköping, Sweden.|Department of Clinical and Experimental Medicine, Linköping University, Linköping, Sweden.|Department of Electrical Engineering, Linköping University, Linköping, Sweden.|Department of Clinical and Experimental Medicine, Linköping University, Linköping, Sweden.|Department of Electrical Engineering, Linköping University, Linköping, Sweden.', 'Sweden|Sweden|Sweden|Sweden|Sweden', 0, 'Animals|Chromatin|DNA-Directed RNA Polymerases|Drosophila|Drosophila Proteins|Female|Gene Expression Regulation|Male|Mutation|Promoter Regions, Genetic|Receptors, Odorant|Systems Biology|Thermodynamics', 'Journal Article', '10.1371/journal.pcbi.1006709', '30653495', 'Complex eukaryotic promoters normally contain multiple cis-regulatory sequences for different transcription factors (TFs). The binding patterns of the TFs to these sites, as well as the way the TFs interact with each other and with the RNA polymerase (RNAp), lead to combinatorial problems rarely understood in detail, especially under varying epigenetic conditions. The aim of this paper is to build a model describing how the main regulatory cluster of the olfactory receptor Or59b drives transcription of this gene in Drosophila. The cluster-driven expression of this gene is represented as the equilibrium probability of RNAp being bound to the promoter region, using a statistical thermodynamic approach. The RNAp equilibrium probability is computed in terms of the occupancy probabilities of the single TFs of the cluster to the corresponding binding sites, and of the interaction rules among TFs and RNAp, using experimental data of Or59b expression to tune the model parameters. The model reproduces correctly the changes in RNAp binding probability induced by various mutation of specific sites and epigenetic modifications. Some of its predictions have also been validated in novel experiments.');
INSERT INTO `papers` (`id`, `ano`, `journal`, `titulo`, `autores`, `afiliacao`, `pais`, `citacoes`, `palavra_chave`, `categorias`, `doi`, `pubmed`, `abstract`) VALUES
(89424, 2019, 'plos', 'STRFs in primary auditory cortex emerge from masking-based statistics of natural sounds', 'Sheikh, Abdul-Saboor|Harper, Nicol S|Drefs, Jakob|Singer, Yosef|Dai, Zhenwen|Turner, Richard E|Lücke, Jörg', 'Research Center Neurosensory Science, Cluster of Excellence Hearing4all, Department of Medical Physics and Acoustics, University of Oldenburg, Oldenburg, Germany.|Institute of Biomedical Engineering, Department of Engineering Science, University of Oxford, Oxford, United Kingdom.|Research Center Neurosensory Science, Cluster of Excellence Hearing4all, Department of Medical Physics and Acoustics, University of Oldenburg, Oldenburg, Germany.|Department of Physiology, Anatomy and Genetics, University of Oxford, Oxford, United Kingdom.|Department of Computer Science, University of Sheffield, Sheffield, United Kingdom.|Department of Engineering, University of Cambridge, Cambridge, United Kingdom.|Research Center Neurosensory Science, Cluster of Excellence Hearing4all, Department of Medical Physics and Acoustics, University of Oldenburg, Oldenburg, Germany.', 'Germany|United Kingdom|Germany|United Kingdom|United Kingdom|United Kingdom|Germany', 1, 'Acoustic Stimulation|Algorithms|Animals|Auditory Cortex|Cochlea|Female|Ferrets|Hearing Tests|Humans|Male|Models, Neurological|Models, Statistical|Signal Processing, Computer-Assisted', 'Journal Article', '10.1371/journal.pcbi.1006595', '30653497', 'We investigate how the neural processing in auditory cortex is shaped by the statistics of natural sounds. Hypothesising that auditory cortex (A1) represents the structural primitives out of which sounds are composed, we employ a statistical model to extract such components. The input to the model are cochleagrams which approximate the non-linear transformations a sound undergoes from the outer ear, through the cochlea to the auditory nerve. Cochleagram components do not superimpose linearly, but rather according to a rule which can be approximated using the max function. This is a consequence of the compression inherent in the cochleagram and the sparsity of natural sounds. Furthermore, cochleagrams do not have negative values. Cochleagrams are therefore not matched well by the assumptions of standard linear approaches such as sparse coding or ICA. We therefore consider a new encoding approach for natural sounds, which combines a model of early auditory processing with maximal causes analysis (MCA), a sparse coding model which captures both the non-linear combination rule and non-negativity of the data. An efficient truncated EM algorithm is used to fit the MCA model to cochleagram data. We characterize the generative fields (GFs) inferred by MCA with respect to in vivo neural responses in A1 by applying reverse correlation to estimate spectro-temporal receptive fields (STRFs) implied by the learned GFs. Despite the GFs being non-negative, the STRF estimates are found to contain both positive and negative subfields, where the negative subfields can be attributed to explaining away effects as captured by the applied inference method. A direct comparison with ferret A1 shows many similar forms, and the spectral and temporal modulation tuning of both ferret and model STRFs show similar ranges over the population. In summary, our model represents an alternative to linear approaches for biological auditory encoding while it captures salient data properties and links inhibitory subfields to explaining away effects.'),
(89425, 2019, 'plos', 'Modeling cell line-specific recruitment of signaling proteins to the insulin-like growth factor 1 receptor', 'Erickson, Keesha E|Rukhlenko, Oleksii S|Shahinuzzaman, Md|Slavkova, Kalina P|Lin, Yen Ting|Suderman, Ryan|Stites, Edward C|Anghel, Marian|Posner, Richard G|Barua, Dipak|Kholodenko, Boris N|Hlavacek, William S', 'Theoretical Biology and Biophysics Group, Theoretical Division, Los Alamos National Laboratory, Los Alamos, New Mexico, United States of America.|Systems Biology Ireland, University College Dublin, Belfield, Dublin, Ireland.|Department of Chemical and Biochemical Engineering, University of Missouri Science and Technology, Rolla, Missouri, United States of America.|Theoretical Biology and Biophysics Group, Theoretical Division, Los Alamos National Laboratory, Los Alamos, New Mexico, United States of America.|Theoretical Biology and Biophysics Group, Theoretical Division, Los Alamos National Laboratory, Los Alamos, New Mexico, United States of America.|Theoretical Biology and Biophysics Group, Theoretical Division, Los Alamos National Laboratory, Los Alamos, New Mexico, United States of America.|The Salk Institute for Biological Studies, La Jolla, California, United States of America.|Information Sciences Group, Computer, Computational and Statistical Sciences Division, Los Alamos National Laboratory, Los Alamos, New Mexico, United States of America.|Department of Biological Sciences, Northern Arizona University, Flagstaff, Arizona, United States of America.|Department of Chemical and Biochemical Engineering, University of Missouri Science and Technology, Rolla, Missouri, United States of America.|Systems Biology Ireland, University College Dublin, Belfield, Dublin, Ireland.|Theoretical Biology and Biophysics Group, Theoretical Division, Los Alamos National Laboratory, Los Alamos, New Mexico, United States of America.', 'Mexico|Ireland|United States|Mexico|Mexico|Mexico|United States|Mexico|United States|United States|I', 0, 'Animals|Binding Sites|Cell Line|Cluster Analysis|Computational Biology|Humans|Mice|Models, Biological|Phosphorylation|Protein Binding|Proteins|Receptor, IGF Type 1|Signal Transduction|src Homology Domains', 'Journal Article', '10.1371/journal.pcbi.1006706', '30653502', 'Receptor tyrosine kinases (RTKs) typically contain multiple autophosphorylation sites in their cytoplasmic domains. Once activated, these autophosphorylation sites can recruit downstream signaling proteins containing Src homology 2 (SH2) and phosphotyrosine-binding (PTB) domains, which recognize phosphotyrosine-containing short linear motifs (SLiMs). These domains and SLiMs have polyspecific or promiscuous binding activities. Thus, multiple signaling proteins may compete for binding to a common SLiM and vice versa. To investigate the effects of competition on RTK signaling, we used a rule-based modeling approach to develop and analyze models for ligand-induced recruitment of SH2/PTB domain-containing proteins to autophosphorylation sites in the insulin-like growth factor 1 (IGF1) receptor (IGF1R). Models were parameterized using published datasets reporting protein copy numbers and site-specific binding affinities. Simulations were facilitated by a novel application of model restructuration, to reduce redundancy in rule-derived equations. We compare predictions obtained via numerical simulation of the model to those obtained through simple prediction methods, such as through an analytical approximation, or ranking by copy number and/or KD value, and find that the simple methods are unable to recapitulate the predictions of numerical simulations. We created 45 cell line-specific models that demonstrate how early events in IGF1R signaling depend on the protein abundance profile of a cell. Simulations, facilitated by model restructuration, identified pairs of IGF1R binding partners that are recruited in anti-correlated and correlated fashions, despite no inclusion of cooperativity in our models. This work shows that the outcome of competition depends on the physicochemical parameters that characterize pairwise interactions, as well as network properties, including network connectivity and the relative abundances of competitors.'),
(89426, 2019, 'plos', 'Sequential infection experiments for quantifying innate and adaptive immunity during influenza infection', 'Yan, Ada W C|Zaloumis, Sophie G|Simpson, Julie A|McCaw, James M', 'School of Mathematics and Statistics, The University of Melbourne, Parkville, Victoria, Australia.|Centre for Epidemiology and Biostatistics, Melbourne School of Population and Global Health, The University of Melbourne, Parkville, Victoria, Australia.|Centre for Epidemiology and Biostatistics, Melbourne School of Population and Global Health, The University of Melbourne, Parkville, Victoria, Australia.|School of Mathematics and Statistics, The University of Melbourne, Parkville, Victoria, Australia.', 'Australia|Australia|Australia|Australia', 2, 'Adaptive Immunity|Animals|Computational Biology|Ferrets|Immunity, Innate|Influenza A virus|Models, Immunological|Orthomyxoviridae Infections', 'Journal Article', '10.1371/journal.pcbi.1006568', '30653522', 'Laboratory models are often used to understand the interaction of related pathogens via host immunity. For example, recent experiments where ferrets were exposed to two influenza strains within a short period of time have shown how the effects of cross-immunity vary with the time between exposures and the specific strains used. On the other hand, studies of the workings of different arms of the immune response, and their relative importance, typically use experiments involving a single infection. However, inferring the relative importance of different immune components from this type of data is challenging. Using simulations and mathematical modelling, here we investigate whether the sequential infection experiment design can be used not only to determine immune components contributing to cross-protection, but also to gain insight into the immune response during a single infection. We show that virological data from sequential infection experiments can be used to accurately extract the timing and extent of cross-protection. Moreover, the broad immune components responsible for such cross-protection can be determined. Such data can also be used to infer the timing and strength of some immune components in controlling a primary infection, even in the absence of serological data. By contrast, single infection data cannot be used to reliably recover this information. Hence, sequential infection data enhances our understanding of the mechanisms underlying the control and resolution of infection, and generates new insight into how previous exposure influences the time course of a subsequent infection.'),
(89427, 2019, 'plos', 'Ten Simple Rules for avoiding and resolving conflicts with your colleagues', 'Lewitter, Fran|Bourne, Philip E|Attwood, Teresa K', 'Whitehead Institute for Biomedical Research, Cambridge, Massachusetts, United States of America.|Data Science Institute & Department of Biomedical Engineering, University of Virginia, Charlottesville, Virginia, United States of America.|School of Computer Science, The University of Manchester, Manchester, United Kingdom.', 'United States|United States|United Kingdom', 0, 'Communication|Conflict (Psychology)|Humans|Negotiating|Workplace', 'Editorial', '10.1371/journal.pcbi.1006708', '30657752', '-'),
(89428, 2019, 'plos', 'OpenCASA: A new open-source and scalable tool for sperm quality analysis', 'Alquézar-Baeta, Carlos|Gimeno-Martos, Silvia|Miguel-Jiménez, Sara|Santolaria, Pilar|Yániz, Jesús|Palacín, Inmaculada|Casao, Adriana|Cebrián-Pérez, José Álvaro|Muiño-Blanco, Teresa|Pérez-Pé, Rosaura', 'Department of Biochemistry and Molecular and Cellular Biology-Institute of Research in Environmental Sciences of Aragon (IUCA), Veterinary Faculty, University of Zaragoza, Zaragoza, Spain.|Department of Biochemistry and Molecular and Cellular Biology-Institute of Research in Environmental Sciences of Aragon (IUCA), Veterinary Faculty, University of Zaragoza, Zaragoza, Spain.|Department of Biochemistry and Molecular and Cellular Biology-Institute of Research in Environmental Sciences of Aragon (IUCA), Veterinary Faculty, University of Zaragoza, Zaragoza, Spain.|TECNOGAM Research Group, Institute of Research in Environmental Sciences of Aragon (IUCA), Higher Polytechnic School of Huesca, University of Zaragoza, Huesca, Spain.|TECNOGAM Research Group, Institute of Research in Environmental Sciences of Aragon (IUCA), Higher Polytechnic School of Huesca, University of Zaragoza, Huesca, Spain.|TECNOGAM Research Group, Institute of Research in Environmental Sciences of Aragon (IUCA), Higher Polytechnic School of Huesca, University of Zaragoza, Huesca, Spain.|Department of Biochemistry and Molecular and Cellular Biology-Institute of Research in Environmental Sciences of Aragon (IUCA), Veterinary Faculty, University of Zaragoza, Zaragoza, Spain.|Department of Biochemistry and Molecular and Cellular Biology-Institute of Research in Environmental Sciences of Aragon (IUCA), Veterinary Faculty, University of Zaragoza, Zaragoza, Spain.|Department of Biochemistry and Molecular and Cellular Biology-Institute of Research in Environmental Sciences of Aragon (IUCA), Veterinary Faculty, University of Zaragoza, Zaragoza, Spain.|Department of Biochemistry and Molecular and Cellular Biology-Institute of Research in Environmental Sciences of Aragon (IUCA), Veterinary Faculty, University of Zaragoza, Zaragoza, Spain.', 'Spain|Spain|Spain|Spain|Spain|Spain|Spain|Spain|Spain|Spain', 1, 'Animals|Image Processing, Computer-Assisted|Male|Microscopy, Fluorescence|Reproducibility of Results|Semen Analysis|Sheep|Software|Sperm Motility|Spermatozoa', 'Journal Article', '10.1371/journal.pcbi.1006691', '30657753', 'In the field of assisted reproductive techniques (ART), computer-assisted sperm analysis (CASA) systems have proved their utility and potential for assessing sperm quality, improving the prediction of the fertility potential of a seminal dose. Although most laboratories and scientific centers use commercial systems, in the recent years certain free and open-source alternatives have emerged that can reduce the costs that research groups have to face. However, these open-source alternatives cannot analyze sperm kinetic responses to different stimuli, such as chemotaxis, thermotaxis or rheotaxis. In addition, the programs released to date have not usually been designed to encourage the scalability and the continuity of software development. We have developed an open-source CASA software, called OpenCASA, which allows users to study three classical sperm quality parameters: motility, morphometry and membrane integrity (viability) and offers the possibility of analyzing the guided movement response of spermatozoa to different stimuli (useful for chemotaxis, thermotaxis or rheotaxis studies) or different motile cells such as bacteria, using a single software. This software has been released in a Version Control System at Github. This platform will allow researchers not only to download the software but also to be involved in and contribute to further developments. Additionally, a Google group has been created to allow the research community to interact and discuss OpenCASA. For validation of the OpenCASA software, we analysed different simulated sperm populations (for chemotaxis module) and evaluated 36 ejaculates obtained from 12 fertile rams using other sperm analysis systems (for motility, membrane integrity and morphology modules). The results were compared with those obtained by Open-CASA using the Pearsons correlation and Bland-Altman tests, obtaining a high level of correlation in all parameters and a good agreement between the different used methods and the OpenCASA. With this work, we propose an open-source project oriented to the development of a new software application for sperm quality analysis. This proposed software will use a minimally centralized infrastructure to allow the continued development of its modules by the research community.'),
(89429, 2019, 'plos', 'Generalizing clusters of similar species as a signature of coexistence under competition', 'DAndrea, Rafael|Riolo, Maria|Ostling, Annette M', 'Ecology and Evolutionary Biology, University of Michigan, Ann Arbor, Michigan, United States of America.|Ecology and Evolutionary Biology, University of Michigan, Ann Arbor, Michigan, United States of America.|Ecology and Evolutionary Biology, University of Michigan, Ann Arbor, Michigan, United States of America.', 'United States|United States|United States', 5, 'Animals|Biological Evolution|Cluster Analysis|Computational Biology|Ecosystem|Models, Biological', 'Journal Article', '10.1371/journal.pcbi.1006688', '30668562', 'Patterns of trait distribution among competing species can potentially reveal the processes that allow them to coexist. It has been recently proposed that competition may drive the spontaneous emergence of niches comprising clusters of similar species, in contrast with the dominant paradigm of greater-than-chance species differences. However, current clustering theory relies largely on heuristic rather than mechanistic models. Furthermore, studies of models incorporating demographic stochasticity and immigration, two key players in community assembly, did not observe clusters. Here we demonstrate clustering under partitioning of resources, partitioning of environmental gradients, and a competition-colonization tradeoff. We show that clusters are robust to demographic stochasticity, and can persist under immigration. While immigration may sustain clusters that are otherwise transient, too much dilutes the pattern. In order to detect and quantify clusters in nature, we introduce and validate metrics which have no free parameters nor require arbitrary trait binning, and weigh species by their abundances rather than relying on a presence-absence count. By generalizing beyond the circumstances where clusters have been observed, our study contributes to establishing them as an update to classical trait patterning theory.'),
(89430, 2019, 'plos', 'Top-down inputs drive neuronal network rewiring and context-enhanced sensory processing in olfaction', 'Adams, Wayne|Graham, James N|Han, Xuchen|Riecke, Hermann', 'Engineering Sciences and Applied Mathematics, Northwestern University, Evanston, IL, USA.|Engineering Sciences and Applied Mathematics, Northwestern University, Evanston, IL, USA.|Mathematics, Northwestern University, Evanston, IL, USA.|Engineering Sciences and Applied Mathematics, Northwestern University, Evanston, IL, USA.', 'United States|United States|United States|United States', 1, 'Adult|Computational Biology|Humans|Models, Neurological|Nerve Net|Neurogenesis|Neuronal Plasticity|Olfactory Bulb|Olfactory Pathways|Olfactory Perception|Smell|Synapses', 'Journal Article', '10.1371/journal.pcbi.1006611', '30668563', 'Much of the computational power of the mammalian brain arises from its extensive top-down projections. To enable neuron-specific information processing these projections have to be precisely targeted. How such a specific connectivity emerges and what functions it supports is still poorly understood. We addressed these questions in silico in the context of the profound structural plasticity of the olfactory system. At the core of this plasticity are the granule cells of the olfactory bulb, which integrate bottom-up sensory inputs and top-down inputs delivered by vast top-down projections from cortical and other brain areas. We developed a biophysically supported computational model for the rewiring of the top-down projections and the intra-bulbar network via adult neurogenesis. The model captures various previous physiological and behavioral observations and makes specific predictions for the cortico-bulbar network connectivity that is learned by odor exposure and environmental contexts. Specifically, it predicts that-after learning-the granule-cell receptive fields with respect to sensory and with respect to cortical inputs are highly correlated. This enables cortical cells that respond to a learned odor to enact disynaptic inhibitory control specifically of bulbar principal cells that respond to that odor. For this the reciprocal nature of the granule cell synapses with the principal cells is essential. Functionally, the model predicts context-enhanced stimulus discrimination in cluttered environments (olfactory cocktail parties) and the ability of the system to adapt to its tasks by rapidly switching between different odor-processing modes. These predictions are experimentally testable. At the same time they provide guidance for future experiments aimed at unraveling the cortico-bulbar connectivity.'),
(89431, 2019, 'plos', 'A Gestalt inference model for auditory scene segregation', 'Chakrabarty, Debmalya|Elhilali, Mounya', 'Laboratory for Computational Audio Processing, Center for Speech and Language Processing, Department of Electrical and Computer Engineering, Johns Hopkins University, Baltimore, MD, USA.|Laboratory for Computational Audio Processing, Center for Speech and Language Processing, Department of Electrical and Computer Engineering, Johns Hopkins University, Baltimore, MD, USA.', 'United States|United States', 0, 'Acoustic Stimulation|Auditory Cortex|Auditory Perception|Cluster Analysis|Databases, Factual|Female|Gestalt Theory|Humans|Male|Models, Psychological|Music|Pattern Recognition, Physiological|Psychophysics|Speech', 'Journal Article', '10.1371/journal.pcbi.1006711', '30668568', 'Our current understanding of how the brain segregates auditory scenes into meaningful objects is in line with a Gestaltism framework. These Gestalt principles suggest a theory of how different attributes of the soundscape are extracted then bound together into separate groups that reflect different objects or streams present in the scene. These cues are thought to reflect the underlying statistical structure of natural sounds in a similar way that statistics of natural images are closely linked to the principles that guide figure-ground segregation and object segmentation in vision. In the present study, we leverage inference in stochastic neural networks to learn emergent grouping cues directly from natural soundscapes including speech, music and sounds in nature. The model learns a hierarchy of local and global spectro-temporal attributes reminiscent of simultaneous and sequential Gestalt cues that underlie the organization of auditory scenes. These mappings operate at multiple time scales to analyze an incoming complex scene and are then fused using a Hebbian network that binds together coherent features into perceptually-segregated auditory objects. The proposed architecture successfully emulates a wide range of well established auditory scene segregation phenomena and quantifies the complimentary role of segregation and binding cues in driving auditory scene segregation.'),
(89432, 2019, 'plos', 'Differential mobility and local variation in infection attack rate', 'Haw, David J|Cummings, Derek A T|Lessler, Justin|Salje, Henrik|Read, Jonathan M|Riley, Steven', 'MRC Centre for Global Infectious Disease Analysis, Department of Infectious Disease Epidemiology, School of Public Health, Imperial College London, London, United Kingdom.|Department of Biology, University of Florida, Gainesville, Florida, United States of America.|Department of Epidemiology, Johns Hopkins University, Baltimore, Maryland, United States of America.|Department of Epidemiology, Johns Hopkins University, Baltimore, Maryland, United States of America.|Centre for Health Informatics Computing and Statistics, Lancaster Medical School, Lancaster University, Lancaster, United Kingdom.|MRC Centre for Global Infectious Disease Analysis, Department of Infectious Disease Epidemiology, School of Public Health, Imperial College London, London, United Kingdom.', 'United Kingdom|United States|United States|United States|United Kingdom|United Kingdom', 0, 'Algorithms|China|Computational Biology|Disease Susceptibility|Humans|Incidence|Influenza, Human|Models, Biological|Models, Statistical|Pandemics|Population Density', 'Journal Article', '10.1371/journal.pcbi.1006600', '30668575', 'Infectious disease transmission is an inherently spatial process in which a hosts home location and their social mixing patterns are important, with the mixing of infectious individuals often different to that of susceptible individuals. Although incidence data for humans have traditionally been aggregated into low-resolution data sets, modern representative surveillance systems such as electronic hospital records generate high volume case data with precise home locations. Here, we use a gridded spatial transmission model of arbitrary resolution to investigate the theoretical relationship between population density, differential population movement and local variability in incidence. We show analytically that a uniform local attack rate is typically only possible for individual pixels in the grid if susceptible and infectious individuals move in the same way. Using a population in Guangdong, China, for which a robust quantitative description of movement is available (a travel kernel), and a natural history consistent with pandemic influenza, we show that local cumulative incidence is positively correlated with population density when susceptible individuals are more connected in space than infectious individuals. Conversely, under the less intuitively likely scenario, when infectious individuals are more connected, local cumulative incidence is negatively correlated with population density. The strength and direction of correlation changes sign for other kernel parameter values. We show that simulation models in which it is assumed implicitly that only infectious individuals move are assuming a slightly unusual specific correlation between population density and attack rate. However, we also show that this potential structural bias can be corrected by using the appropriate non-isotropic kernel that maps infectious-only code onto the isotropic dual-mobility kernel. These results describe a precise relationship between the spatio-social mixing of infectious and susceptible individuals and local variability in attack rates. More generally, these results suggest a genuine risk that mechanistic models of high-resolution attack rate data may reach spurious conclusions if the precise implications of spatial force-of-infection assumptions are not first fully characterized, prior to models being fit to data.'),
(89433, 2019, 'plos', 'Erratum: Notice of Republication: Simulating Cortical Development as a Self Constructing Process: A Novel Multi-Scale Approach Combining Molecular and Physical Aspects', 'PLOS Computational Biology Staff', 'MRC Centre for Global Infectious Disease Analysis, Department of Infectious Disease Epidemiology, School of Public Health, Imperial College London, London, United Kingdom.', 'United Kingdom', 0, '-', 'Journal Article', '10.1371/journal.pcbi.1006747', '30673692', '[This corrects the article DOI: 10.1371/journal.pcbi.1003173.].'),
(89434, 2019, 'plos', 'Epithelial stratification shapes infection dynamics', 'Murall, Carmen Lía|Jackson, Robert|Zehbe, Ingeborg|Boulle, Nathalie|Segondy, Michel|Alizon, Samuel', 'Laboratoire MIVEGEC (UMR CNRS 5290, IRD, UM), Montpellier, France.|Probe Development and Biomarker Exploration, Thunder Bay Regional Health Research Institute, Thunder Bay, Ontario, Canada.|Probe Development and Biomarker Exploration, Thunder Bay Regional Health Research Institute, Thunder Bay, Ontario, Canada.|Pathogenesis and Control of Chronic Infections, INSERM, EFS, Université de Montpellier, Montpellier, France.|Pathogenesis and Control of Chronic Infections, INSERM, EFS, Université de Montpellier, Montpellier, France.|Laboratoire MIVEGEC (UMR CNRS 5290, IRD, UM), Montpellier, France.', 'France|Canada|Canada|France|France|France', 0, 'Cell Culture Techniques|Chlamydia Infections|Chlamydia trachomatis|Epithelium|Female|Host-Pathogen Interactions|Humans|Models, Biological|Papillomaviridae|Papillomavirus Infections|Vagina', 'Journal Article', '10.1371/journal.pcbi.1006646', '30673699', 'Infections of stratified epithelia contribute to a large group of common diseases, such as dermatological conditions and sexually transmitted diseases. To investigate how epithelial structure affects infection dynamics, we develop a general ecology-inspired model for stratified epithelia. Our model allows us to simulate infections, explore new hypotheses and estimate parameters that are difficult to measure with tissue cell cultures. We focus on two contrasting pathogens: Chlamydia trachomatis and Human papillomaviruses (HPV). Using cervicovaginal parameter estimates, we find that key infection symptoms can be explained by differential interactions with the layers, while clearance and pathogen burden appear to be bottom-up processes. Cell protective responses to infections (e.g. mucus trapping) generally lowered pathogen load but there were specific effects based on infection strategies. Our modeling approach opens new perspectives for 3D tissue culture experimental systems of infections and, more generally, for developing and testing hypotheses related to infections of stratified epithelia.'),
(89435, 2019, 'plos', 'Cellular determinants of metabolite concentration ranges', 'Küken, Anika|Eloundou-Mbebi, Jeanne M O|Basler, Georg|Nikoloski, Zoran', 'System Biology and Mathematical Modeling Group, Max Planck Institute of Molecular Plant Physiology, Potsdam-Golm, Germany.|System Biology and Mathematical Modeling Group, Max Planck Institute of Molecular Plant Physiology, Potsdam-Golm, Germany.|System Biology and Mathematical Modeling Group, Max Planck Institute of Molecular Plant Physiology, Potsdam-Golm, Germany.|System Biology and Mathematical Modeling Group, Max Planck Institute of Molecular Plant Physiology, Potsdam-Golm, Germany.', 'Germany|Germany|Germany|Germany', 3, 'Escherichia coli|Kinetics|Metabolic Networks and Pathways|Metabolome|Models, Biological|Systems Biology', 'Journal Article', '10.1371/journal.pcbi.1006687', '30677015', 'Cellular functions are shaped by reaction networks whose dynamics are determined by the concentrations of underlying components. However, cellular mechanisms ensuring that a components concentration resides in a given range remain elusive. We present network properties which suffice to identify components whose concentration ranges can be efficiently computed in mass-action metabolic networks. We show that the derived ranges are in excellent agreement with simulations from a detailed kinetic metabolic model of Escherichia coli. We demonstrate that the approach can be used with genome-scale metabolic models to arrive at predictions concordant with measurements from Escherichia coli under different growth scenarios. By application to 14 genome-scale metabolic models from diverse species, our approach specifies the cellular determinants of concentration ranges that can be effectively employed to make predictions for a variety of biotechnological and medical applications.'),
(89436, 2019, 'plos', 'Kinetic and thermodynamic insights into sodium ion translocation through the xcexbc-opioid receptor from molecular dynamics and machine learning analysis', 'Hu, Xiaohu|Wang, Yibo|Hunkele, Amanda|Provasi, Davide|Pasternak, Gavril W|Filizola, Marta', 'Department of Pharmacological Sciences, Icahn School of Medicine at Mount Sinai, New York, New York, United States of America.|Department of Pharmacological Sciences, Icahn School of Medicine at Mount Sinai, New York, New York, United States of America.|Department of Neurology and Molecular Pharmacology Program, Memorial Sloan Kettering Cancer Center, New York, New York, United States of America.|Department of Pharmacological Sciences, Icahn School of Medicine at Mount Sinai, New York, New York, United States of America.|Department of Neurology and Molecular Pharmacology Program, Memorial Sloan Kettering Cancer Center, New York, New York, United States of America.|Department of Pharmacological Sciences, Icahn School of Medicine at Mount Sinai, New York, New York, United States of America.', 'United States|United States|United States|United States|United States|United States', 0, 'Animals|Kinetics|Machine Learning|Markov Chains|Mice|Molecular Dynamics Simulation|Protein Binding|Receptors, Opioid, mu|Sodium|Thermodynamics', 'Journal Article', '10.1371/journal.pcbi.1006689', '30677023', 'The differential modulation of agonist and antagonist binding to opioid receptors (ORs) by sodium (Na+) has been known for decades. To shed light on the molecular determinants, thermodynamics, and kinetics of Na+ translocation through the xcexbc-OR (MOR), we used a multi-ensemble Markov model framework combining equilibrium and non-equilibrium atomistic molecular dynamics simulations of Na+ binding to MOR active or inactive crystal structures embedded in an explicit lipid bilayer. We identify an energetically favorable, continuous ion pathway through the MOR active conformation only, and provide, for the first time: i) estimates of the energy differences and required timescales of Na+ translocation in inactive and active MORs, ii) estimates of Na+-induced changes to agonist binding validated by radioligand measurements, and iii) testable hypotheses of molecular determinants and correlated motions involved in this translocation, which are likely to play a key role in MOR signaling.'),
(89437, 2019, 'plos', 'Systems biology reveals how altered TGFxcexb2 signalling with age reduces protection against pro-inflammatory stimuli', 'Hodgson, David|Rowan, Andrew D|Falciani, Francesco|Proctor, Carole J', 'Institute of Cellular Medicine, Ageing Research Laboratories, Campus for Ageing and Vitality, Newcastle University, Newcastle upon Tyne, United Kingdom.|MRC/Arthritis Research UK Centre for Musculoskeletal Ageing (CIMA), United Kingdom.|MRC/Arthritis Research UK Centre for Musculoskeletal Ageing (CIMA), United Kingdom.|Institute of Cellular Medicine, Ageing Research Laboratories, Campus for Ageing and Vitality, Newcastle University, Newcastle upon Tyne, United Kingdom.', 'United Kingdom|United Kingdom|United Kingdom|United Kingdom', 3, 'Aging|Cell Line|Chondrocytes|Gene Expression Profiling|Humans|Osteoarthritis|Signal Transduction|Systems Biology|Transforming Growth Factor beta', 'Journal Article', '10.1371/journal.pcbi.1006685', '30677026', 'Osteoarthritis (OA) is a degenerative condition caused by dysregulation of multiple molecular signalling pathways. Such dysregulation results in damage to cartilage, a smooth and protective tissue that enables low friction articulation of synovial joints. Matrix metalloproteinases (MMPs), especially MMP-13, are key enzymes in the cleavage of type II collagen which is a vital component for cartilage integrity. Transforming growth factor beta (TGFxcexb2) can protect against pro-inflammatory cytokine-mediated MMP expression. With age there is a change in the ratio of two TGFxcexb2 type I receptors (Alk1/Alk5), a shift that results in TGFxcexb2 losing its protective role in cartilage homeostasis. Instead, TGFxcexb2 promotes cartilage degradation which correlates with the spontaneous development of OA in murine models. However, the mechanism by which TGFxcexb2 protects against pro-inflammatory responses and how this changes with age has not been extensively studied. As TGFxcexb2 signalling is complex, we used systems biology to combine experimental and computational outputs to examine how the system changes with age. Experiments showed that the repressive effect of TGFxcexb2 on chondrocytes treated with a pro-inflammatory stimulus required Alk5. Computational modelling revealed two independent mechanisms were needed to explain the crosstalk between TGFxcexb2 and pro-inflammatory signalling pathways. A novel meta-analysis of microarray data from OA patient tissue was used to create a Cytoscape network representative of human OA and revealed the importance of inflammation. Combining the modelled genes with the microarray network provided a global overview into the crosstalk between the different signalling pathways involved in OA development. Our results provide further insights into the mechanisms that cause TGFxcexb2 signalling to change from a protective to a detrimental pathway in cartilage with ageing. Moreover, such a systems biology approach may enable restoration of the protective role of TGFxcexb2 as a potential therapy to prevent age-related loss of cartilage and the development of OA.'),
(89438, 2019, 'plos', 'A diurnal flux balance model of Synechocystis sp PCC 6803 metabolism', 'Sarkar, Debolina|Mueller, Thomas J|Liu, Deng|Pakrasi, Himadri B|Maranas, Costas D', 'Department of Chemical Engineering, Pennsylvania State University, University Park, Pennsylvania, United States of America.|Department of Chemical Engineering, Pennsylvania State University, University Park, Pennsylvania, United States of America.|Department of Biology, Washington University, St. Louis, Missouri, United States of America.|Department of Biology, Washington University, St. Louis, Missouri, United States of America.|Department of Chemical Engineering, Pennsylvania State University, University Park, Pennsylvania, United States of America.', 'United States|United States|United States|United States|United States', 8, 'Algorithms|Biomass|Carotenoids|Circadian Rhythm|Computational Biology|Glycogen|Metabolic Flux Analysis|Models, Biological|Photosynthesis|Synechocystis', 'Journal Article', '10.1371/journal.pcbi.1006692', '30677028', 'Phototrophic organisms such as cyanobacteria utilize the suns energy to convert atmospheric carbon dioxide into organic carbon, resulting in diurnal variations in the cells metabolism. Flux balance analysis is a widely accepted constraint-based optimization tool for analyzing growth and metabolism, but it is generally used in a time-invariant manner with no provisions for sequestering different biomass components at different time periods. Here we present CycleSyn, a periodic model of Synechocystis sp. PCC 6803 metabolism that spans a 12-hr light/12-hr dark cycle by segmenting it into 12 Time Point Models (TPMs) with a uniform duration of two hours. The developed framework allows for the flow of metabolites across TPMs while inventorying metabolite levels and only allowing for the utilization of currently or previously produced compounds. The 12 TPMs allow for the incorporation of time-dependent constraints that capture the cyclic nature of cellular processes. Imposing bounds on reactions informed by temporally-segmented transcriptomic data enables simulation of phototrophic growth as a single linear programming (LP) problem. The solution provides the time varying reaction fluxes over a 24-hour cycle and the accumulation/consumption of metabolites. The diurnal rhythm of metabolic gene expression driven by the circadian clock and its metabolic consequences is explored. Predicted flux and metabolite pools are in line with published studies regarding the temporal organization of phototrophic growth in Synechocystis PCC 6803 paving the way for constructing time-resolved genome-scale models (GSMs) for organisms with a circadian clock. In addition, the metabolic reorganization that would be required to enable Synechocystis PCC 6803 to temporally separate photosynthesis from oxygen-sensitive nitrogen fixation is also explored using the developed model formalism.'),
(89439, 2019, 'plos', 'Ten simple rules for writing statistical book reviews', 'Lortie, Christopher J', 'Department of Biology, York University, Toronto, ON, Canada.', 'Canada', 0, 'Books|Computational Biology|Humans|Reading|Statistics as Topic|Writing', 'Editorial', '10.1371/journal.pcbi.1006562', '30677035', 'Statistical books can provide deep insights into statistics and software. There are, however, many resources available to the practitioner. Book reviews have the capacity to function as a critical mechanism for the learner to assess the merits of engaging in part, in full, or at all with a book. The ten simple rules format, pioneered in computational biology, was applied here to writing effective book reviews for statistics because of the wide breadth of offerings in this domain, including topical introductions, computational solutions, and theory. Learning by doing is a popular paradigm in statistics and computation, but there is still a niche for books in the pedagogy of self-taught and instruction-based learning. Primarily, these rules ensure that book reviews function as a form of short syntheses to inform and guide readers in deciding to use a specific book relative to other options for resolving statistical challenges.'),
(89440, 2019, 'plos', 'Multi-study inference of regulatory networks for more accurate models of gene regulation', 'Castro, Dayanne M|de Veaux, Nicholas R|Miraldi, Emily R|Bonneau, Richard', 'New York University, New York, NY 10003, USA.|Center for Computational Biology, Flatiron Institute, New York, NY 10010, USA.|Department of Pediatrics, University of Cincinnati College of Medicine, Cincinnati, OH 45229, USA.|New York University, New York, NY 10003, USA.', 'United States|United States|United States|United States', 11, 'Bacillus subtilis|Computational Biology|Databases, Genetic|Gene Expression Regulation|Gene Regulatory Networks|Models, Genetic|Saccharomyces cerevisiae', 'Journal Article', '10.1371/journal.pcbi.1006591', '30677040', 'Gene regulatory networks are composed of sub-networks that are often shared across biological processes, cell-types, and organisms. Leveraging multiple sources of information, such as publicly available gene expression datasets, could therefore be helpful when learning a network of interest. Integrating data across different studies, however, raises numerous technical concerns. Hence, a common approach in network inference, and broadly in genomics research, is to separately learn models from each dataset and combine the results. Individual models, however, often suffer from under-sampling, poor generalization and limited network recovery. In this study, we explore previous integration strategies, such as batch-correction and model ensembles, and introduce a new multitask learning approach for joint network inference across several datasets. Our method initially estimates the activities of transcription factors, and subsequently, infers the relevant network topology. As regulatory interactions are context-dependent, we estimate model coefficients as a combination of both dataset-specific and conserved components. In addition, adaptive penalties may be used to favor models that include interactions derived from multiple sources of prior knowledge including orthogonal genomics experiments. We evaluate generalization and network recovery using examples from Bacillus subtilis and Saccharomyces cerevisiae, and show that sharing information across models improves network reconstruction. Finally, we demonstrate robustness to both false positives in the prior information and heterogeneity among datasets.'),
(89441, 2019, 'plos', 'Spatial synchronization codes from coupled rate-phase neurons', 'Monaco, Joseph D|De Guzman, Rose M|Blair, Hugh T|Zhang, Kechen', 'Biomedical Engineering Department, Johns Hopkins University School of Medicine, Baltimore, MD, USA.|Psychology Department, University of California, Los Angeles, Los Angeles, CA, USA.|Psychology Department, University of California, Los Angeles, Los Angeles, CA, USA.|Biomedical Engineering Department, Johns Hopkins University School of Medicine, Baltimore, MD, USA.', 'United States|United States|United States|United States', 5, 'Animals|Computational Biology|Cortical Synchronization|Hippocampus|Male|Models, Neurological|Neurons|Rats|Rats, Long-Evans|Spatial Navigation|Theta Rhythm', 'Journal Article', '10.1371/journal.pcbi.1006741', '30682012', 'During spatial navigation, the frequency and timing of spikes from spatial neurons including place cells in hippocampus and grid cells in medial entorhinal cortex are temporally organized by continuous theta oscillations (6-11 Hz). The theta rhythm is regulated by subcortical structures including the medial septum, but it is unclear how spatial information from place cells may reciprocally organize subcortical theta-rhythmic activity. Here we recorded single-unit spiking from a constellation of subcortical and hippocampal sites to study spatial modulation of rhythmic spike timing in rats freely exploring an open environment. Our analysis revealed a novel class of neurons that we termed phaser cells, characterized by a symmetric coupling between firing rate and spike theta-phase. Phaser cells encoded space by assigning distinct phases to allocentric isocontour levels of each cells spatial firing pattern. In our dataset, phaser cells were predominantly located in the lateral septum, but also the hippocampus, anteroventral thalamus, lateral hypothalamus, and nucleus accumbens. Unlike the unidirectional late-to-early phase precession of place cells, bidirectional phase modulation acted to return phaser cells to the same theta-phase along a given spatial isocontour, including cells that characteristically shifted to later phases at higher firing rates. Our dynamical models of intrinsic theta-bursting neurons demonstrated that experience-independent temporal coding mechanisms can qualitatively explain (1) the spatial rate-phase relationships of phaser cells and (2) the observed temporal segregation of phaser cells according to phase-shift direction. In open-field phaser cell simulations, competitive learning embedded phase-code entrainment maps into the weights of downstream targets, including path integration networks. Bayesian phase decoding revealed error correction capable of resetting path integration at subsecond timescales. Our findings suggest that phaser cells may instantiate a subcortical theta-rhythmic loop of spatial feedback. We outline a framework in which location-dependent synchrony reconciles internal idiothetic processes with the allothetic reference points of sensory experience.'),
(89442, 2019, 'plos', 'Designing and running an advanced Bioinformatics and genome analyses course in Tunisia', 'Guerfali, Fatma Z|Laouini, Dhafer|Boudabous, Abdellatif|Tekaia, Fredj', 'Université Tunis El Manar, Tunis, Tunisia.|Université Tunis El Manar, Tunis, Tunisia.|Université Tunis El Manar, Faculté des Sciences de Tunis, Laboratoire Microorganisme et Biomolécules Actives, Campus Universitaire Farhat Heched, El Manar, Tunis, Tunisia.|Institut Pasteur Paris, 28 rue du Dr Roux, 75724 Paris cedex 15, France.', 'Tunisia|Tunisia|Tunisia|France', 0, 'Academies and Institutes|Computational Biology|Curriculum|Developing Countries|Humans|Models, Educational|Students|Tunisia', 'Journal Article', '10.1371/journal.pcbi.1006373', '30689625', 'Genome data, with underlying new knowledge, are accumulating at exponential rate thanks to ever-improving sequencing technologies and the parallel development of dedicated efficient Bioinformatics methods and tools. Advanced Education in Bioinformatics and Genome Analyses is to a large extent not accessible to students in developing countries where endeavors to set up Bioinformatics courses concern most often only basic levels. Here, we report a pioneering pilot experience concerning the design and implementation, from scratch, of a three-months advanced and extensive course in Bioinformatics and Genome Analyses in the Institut Pasteur de Tunis. Most significantly the outcome of the course was upgrading the participants skills in Bioinformatics and Genome Analyses to recognized international standards. Here we detail the different steps involved in the implementation of this course as well as the topics covered in the program. The description of this pilot experience might be helpful for the implementation of other similar educational projects, notably in developing countries, aiming to go beyond basics and providing young researchers with high-level skills.'),
(89443, 2019, 'plos', 'A low-threshold potassium current enhances sparseness and reliability in a model of avian auditory cortex', 'Bjoring, Margot C|Meliza, C Daniel', 'Department of Psychology, University of Virginia, Charlottesville, VA, USA.|Department of Psychology, University of Virginia, Charlottesville, VA, USA.', 'United States|United States', 2, 'Animals|Auditory Cortex|Computational Biology|Evoked Potentials, Auditory|Finches|Male|Models, Neurological|Potassium|Reproducibility of Results|Vocalization, Animal', 'Journal Article', '10.1371/journal.pcbi.1006723', '30689626', 'Birdsong is a complex vocal communication signal, and like humans, birds need to discriminate between similar sequences of sound with different meanings. The caudal mesopallium (CM) is a cortical-level auditory area implicated in song discrimination. CM neurons respond sparsely to conspecific song and are tolerant of production variability. Intracellular recordings in CM have identified a diversity of intrinsic membrane dynamics, which could contribute to the emergence of these higher-order functional properties. We investigated this hypothesis using a novel linear-dynamical cascade model that incorporated detailed biophysical dynamics to simulate auditory responses to birdsong. Neuron models that included a low-threshold potassium current present in a subset of CM neurons showed increased selectivity and coding efficiency relative to models without this current. These results demonstrate the impact of intrinsic dynamics on sensory coding and the importance of including the biophysical characteristics of neural populations in simulation studies.');
