INSERT INTO `papers` (`id`, `ano`, `journal`, `titulo`, `autores`, `afiliacao`, `pais`, `citacoes`, `palavra_chave`, `categorias`, `doi`, `pubmed`, `abstract`) VALUES
(87671, 2016, 'plos', 'Quantifying Transmission Investment in Malaria Parasites', 'Greischar, Megan A|Mideo, Nicole|Read, Andrew F|Bjørnstad, Ottar N', 'Department of Entomology and the Center For Infectious Disease Dynamics, The Pennsylvania State University, University Park, Pennsylvania, United States of America.|Department of Ecology & Evolutionary Biology, University of Toronto, Toronto, Ontario, Canada.|Department of Entomology and the Center For Infectious Disease Dynamics, The Pennsylvania State University, University Park, Pennsylvania, United States of America.|Department of Entomology and the Center For Infectious Disease Dynamics, The Pennsylvania State University, University Park, Pennsylvania, United States of America.', 'United States|Canada|United States|United States', 10, 'Animals|Computational Biology|Erythrocytes|Female|Life Cycle Stages|Malaria|Male|Mice|Models, Biological|Plasmodium chabaudi', 'Journal Article', '10.1371/journal.pcbi.1004718', '26890485', 'Many microparasites infect new hosts with specialized life stages, requiring a subset of the parasite population to forgo proliferation and develop into transmission forms. Transmission stage production influences infectivity, host exploitation, and the impact of medical interventions like drug treatment. Predicting how parasites will respond to public health efforts on both epidemiological and evolutionary timescales requires understanding transmission strategies. These strategies can rarely be observed directly and must typically be inferred from infection dynamics. Using malaria as a case study, we test previously described methods for inferring transmission stage investment against simulated data generated with a model of within-host infection dynamics, where the true transmission investment is known. We show that existing methods are inadequate and potentially very misleading. The key difficulty lies in separating transmission stages produced by different generations of parasites. We develop a new approach that performs much better on simulated data. Applying this approach to real data from mice infected with a single Plasmodium chabaudi strain, we estimate that transmission investment varies from zero to 20%, with evidence for variable investment over time in some hosts, but not others. These patterns suggest that, even in experimental infections where host genetics and other environmental factors are controlled, parasites may exhibit remarkably different patterns of transmission investment. '),
(87672, 2016, 'plos', 'A Feedback Model of Attention Explains the Diverse Effects of Attention on Neural Firing Rates and Receptive Field Structure', 'Miconi, Thomas|VanRullen, Rufin', 'Centre de Recherche Cerveau et Cognition (CerCo), CNRS & Université Paul Sabatier, Pavillon Baudot CHU Purpan, Toulouse Cedex, France.|Centre de Recherche Cerveau et Cognition (CerCo), CNRS & Université Paul Sabatier, Pavillon Baudot CHU Purpan, Toulouse Cedex, France.', 'France|France', 0, 'Attention|Computational Biology|Feedback, Sensory|Models, Neurological|Neurons|Visual Cortex', 'Journal Article', '10.1371/journal.pcbi.1004770', '26890584', 'Visual attention has many effects on neural responses, producing complex changes in firing rates, as well as modifying the structure and size of receptive fields, both in topological and feature space. Several existing models of attention suggest that these effects arise from selective modulation of neural inputs. However, anatomical and physiological observations suggest that attentional modulation targets higher levels of the visual system (such as V4 or MT) rather than input areas (such as V1). Here we propose a simple mechanism that explains how a top-down attentional modulation, falling on higher visual areas, can produce the observed effects of attention on neural responses. Our model requires only the existence of modulatory feedback connections between areas, and short-range lateral inhibition within each area. Feedback connections redistribute the top-down modulation to lower areas, which in turn alters the inputs of other higher-area cells, including those that did not receive the initial modulation. This produces firing rate modulations and receptive field shifts. Simultaneously, short-range lateral inhibition between neighboring cells produce competitive effects that are automatically scaled to receptive field size in any given area. Our model reproduces the observed attentional effects on response rates (response gain, input gain, biased competition automatically scaled to receptive field size) and receptive field structure (shifts and resizing of receptive fields both spatially and in complex feature space), without modifying model parameters. Our model also makes the novel prediction that attentional effects on response curves should shift from response gain to contrast gain as the spatial focus of attention drifts away from the studied cell. '),
(87673, 2016, 'plos', 'Correction: Rich RNA Structure Landscapes Revealed by Mutate-and-Map Analysis', 'PLOS Computational Biology Staff', 'Centre de Recherche Cerveau et Cognition (CerCo), CNRS & Université Paul Sabatier, Pavillon Baudot CHU Purpan, Toulouse Cedex, France.', 'France', 0, '-', 'Published Erratum', '10.1371/journal.pcbi.1004783', '26890727', '-'),
(87674, 2016, 'plos', 'Inferring Neuronal Dynamics from Calcium Imaging Data Using Biophysical Models and Bayesian Inference', 'Rahmati, Vahid|Kirmse, Knut|Markovixc4x87, Dimitrije|Holthoff, Knut|Kiebel, Stefan J', 'Department of Psychology, Technische Universitxc3xa4t Dresden, Dresden, Germany.|Hans-Berger Department of Neurology, University Hospital Jena, Jena, Germany.|Department of Psychology, Technische Universitxc3xa4t Dresden, Dresden, Germany.|Hans-Berger Department of Neurology, University Hospital Jena, Jena, Germany.|Department of Psychology, Technische Universitxc3xa4t Dresden, Dresden, Germany.', 'Germany|Germany|Germany|Germany|Germany', 8, 'Action Potentials|Animals|Bayes Theorem|CA3 Region, Hippocampal|Calcium|Calcium Signaling|Cells, Cultured|Computational Biology|Mice|Mice, Inbred C57BL|Models, Neurological|Molecular Imaging|Neurons', 'Journal Article', '10.1371/journal.pcbi.1004736', '26894748', 'Calcium imaging has been used as a promising technique to monitor the dynamic activity of neuronal populations. However, the calcium trace is temporally smeared which restricts the extraction of quantities of interest such as spike trains of individual neurons. To address this issue, spike reconstruction algorithms have been introduced. One limitation of such reconstructions is that the underlying models are not informed about the biophysics of spike and burst generations. Such existing prior knowledge might be useful for constraining the possible solutions of spikes. Here we describe, in a novel Bayesian approach, how principled knowledge about neuronal dynamics can be employed to infer biophysical variables and parameters from fluorescence traces. By using both synthetic and in vitro recorded fluorescence traces, we demonstrate that the new approach is able to reconstruct different repetitive spiking and/or bursting patterns with accurate single spike resolution. Furthermore, we show that the high inference precision of the new approach is preserved even if the fluorescence trace is rather noisy or if the fluorescence transients show slow rise kinetics lasting several hundred milliseconds, and inhomogeneous rise and decay times. In addition, we discuss the use of the new approach for inferring parameter changes, e.g. due to a pharmacological intervention, as well as for inferring complex characteristics of immature neuronal circuits. '),
(87675, 2016, 'plos', 'Phenotypic Heterogeneity and the Evolution of Bacterial Life Cycles', 'van Gestel, Jordi|Nowak, Martin A', 'Program for Evolutionary Dynamics, Departments of Organismic and Evolutionary Biology and Mathematics, Harvard University, Boston, Massachusetts, United States of America.|Program for Evolutionary Dynamics, Departments of Organismic and Evolutionary Biology and Mathematics, Harvard University, Boston, Massachusetts, United States of America.', 'United States|United States', 9, 'Bacterial Physiological Phenomena|Biological Evolution|Computational Biology|Computer Simulation|Phenotype', 'Journal Article', '10.1371/journal.pcbi.1004764', '26894881', 'Most bacteria live in colonies, where they often express different cell types. The ecological significance of these cell types and their evolutionary origin are often unknown. Here, we study the evolution of cell differentiation in the context of surface colonization. We particularly focus on the evolution of a sticky cell type that is required for surface attachment, but is costly to express. The sticky cells not only facilitate their own attachment, but also that of non-sticky cells. Using individual-based simulations, we show that surface colonization rapidly evolves and in most cases leads to phenotypic heterogeneity, in which sticky and non-sticky cells occur side by side on the surface. In the presence of regulation, cell differentiation leads to a remarkable set of bacterial life cycles, in which cells alternate between living in the liquid and living on the surface. The dominant life stage is formed by the surface-attached colony that shows many complex features: colonies reproduce via fission and by producing migratory propagules, cells inside the colony divide labour, and colonies can produce filaments to facilitate expansion. Overall, our model illustrates how the evolution of an adhesive cell type goes hand in hand with the evolution of complex bacterial life cycles. '),
(87676, 2016, 'plos', 'BinPacker: Packing-Based De Novo Transcriptome Assembly from RNA-seq Data', 'Liu, Juntao|Li, Guojun|Chang, Zheng|Yu, Ting|Liu, Bingqiang|McMullen, Rick|Chen, Pengyin|Huang, Xiuzhen', 'School of Mathematics, Shandong University, Jinan, China.|School of Mathematics, Shandong University, Jinan, China.|School of Mathematics, Shandong University, Jinan, China.|School of Mathematics, Shandong University, Jinan, China.|School of Mathematics, Shandong University, Jinan, China.|High Performance Computing Center, University of Arkansas, Fayetteville, Arkansas, United States of America.|Crop, Soil, and Environmental Sciences, University of Arkansas, Fayetteville, Arkansas, United States of America.|Department of Computer Science, Arkansas State University, Jonesboro, Arkansas, United States of America.', 'China|China|China|China|China|United States|United States|United States', 57, 'Algorithms|Animals|Computational Biology|Dogs|Gene Expression Profiling|High-Throughput Nucleotide Sequencing|Humans|Mice|RNA, Messenger|Sequence Analysis, RNA|Transcriptome', 'Journal Article', '10.1371/journal.pcbi.1004772', '26894997', 'High-throughput RNA-seq technology has provided an unprecedented opportunity to reveal the very complex structures of transcriptomes. However, it is an important and highly challenging task to assemble vast amounts of short RNA-seq reads into transcriptomes with alternative splicing isoforms. In this study, we present a novel de novo assembler, BinPacker, by modeling the transcriptome assembly problem as tracking a set of trajectories of items with their sizes representing coverage of their corresponding isoforms by solving a series of bin-packing problems. This approach, which subtly integrates coverage information into the procedure, has two exclusive features: 1) only splicing junctions are involved in the assembling procedure, 2) massive pell-mell reads are assembled seemingly by moving a comb along junction edges on a splicing graph. Being tested on both real and simulated RNA-seq datasets, it outperforms almost all the existing de novo assemblers on all the tested datasets, and even outperforms those ab initio assemblers on the real dog dataset. In addition, it runs substantially faster and requires less memory space than most of the assemblers. BinPacker is published under GNU GENERAL PUBLIC LICENSE and the source is available from: http://sourceforge.net/projects/transcriptomeassembly/files/BinPacker_1.0.tar.gz/download. Quick installation version is available from: http://sourceforge.net/projects/transcriptomeassembly/files/BinPacker_binary.tar.gz/download. '),
(87677, 2016, 'plos', 'Non-monotonic Response to Monotonic Stimulus: Regulation of Glyoxylate Shunt Gene-Expression Dynamics in Mycobacterium tuberculosis', 'Ascensao, Joao A|Datta, Pratik|Hancioglu, Baris|Sontag, Eduardo|Gennaro, Maria L|Igoshin, Oleg A', 'Department of Bioengineering and Center for Theoretical Biological Physics, Rice University, Houston, Texas, United States of America.|Public Health Research Institute, New Jersey Medical School, Rutgers University, Newark, New Jersey, United States of America.|Department of Bioengineering and Center for Theoretical Biological Physics, Rice University, Houston, Texas, United States of America.|Department of Mathematics and Center for Quantitative Biology, Rutgers University, Piscataway, New Jersey, United States of America.|Public Health Research Institute, New Jersey Medical School, Rutgers University, Newark, New Jersey, United States of America.|Department of Bioengineering and Center for Theoretical Biological Physics, Rice University, Houston, Texas, United States of America.', 'United States|Jersey|United States|Jersey|Jersey|United States', 9, 'Bacterial Proteins|Gene Expression Regulation, Bacterial|Glyoxylates|Metabolic Networks and Pathways|Models, Genetic|Mycobacterium tuberculosis|Systems Biology|Transcription Factors', 'Journal Article', '10.1371/journal.pcbi.1004741', '26900694', 'Understanding how dynamical responses of biological networks are constrained by underlying network topology is one of the fundamental goals of systems biology. Here we employ monotone systems theory to formulate a theorem stating necessary conditions for non-monotonic time-response of a biochemical network to a monotonic stimulus. We apply this theorem to analyze the non-monotonic dynamics of the xcfx83B-regulated glyoxylate shunt gene expression in Mycobacterium tuberculosis cells exposed to hypoxia. We first demonstrate that the known network structure is inconsistent with observed dynamics. To resolve this inconsistency we employ the formulated theorem, modeling simulations and optimization along with follow-up dynamic experimental measurements. We show a requirement for post-translational modulation of xcfx83B activity in order to reconcile the network dynamics with its topology. The results of this analysis make testable experimental predictions and demonstrate wider applicability of the developed methodology to a wide class of biological systems. '),
(87678, 2016, 'plos', 'Model-Driven Understanding of Palmitoylation Dynamics: Regulated Acylation of the Endoplasmic Reticulum Chaperone Calnexin', 'Dallavilla, Tiziano|Abrami, Laurence|Sandoz, Patrick A|Savoglidis, Georgios|Hatzimanikatis, Vassily|van der Goot, F Gisou', 'Laboratory of Computational Systems Biotechnology, Ecole Polytechnique Fédérale de Lausanne (EPFL), Lausanne, Switzerland.|Global Health Institute, Ecole Polytechnique Fédérale de Lausanne (EPFL), Lausanne, Switzerland.|Global Health Institute, Ecole Polytechnique Fédérale de Lausanne (EPFL), Lausanne, Switzerland.|Laboratory of Computational Systems Biotechnology, Ecole Polytechnique Fédérale de Lausanne (EPFL), Lausanne, Switzerland.|Laboratory of Computational Systems Biotechnology, Ecole Polytechnique Fédérale de Lausanne (EPFL), Lausanne, Switzerland.|Global Health Institute, Ecole Polytechnique Fédérale de Lausanne (EPFL), Lausanne, Switzerland.', 'Switzerland|Switzerland|Switzerland|Switzerland|Switzerland|Switzerland', 16, 'Acylation|Calnexin|Computational Biology|Computer Simulation|Endoplasmic Reticulum|HeLa Cells|Humans|Lipoylation|Models, Biological|RNA Interference', 'Journal Article', '10.1371/journal.pcbi.1004774', '26900856', 'Cellular functions are largely regulated by reversible post-translational modifications of proteins which act as switches. Amongst these, S-palmitoylation is unique in that it confers hydrophobicity. Due to technical difficulties, the understanding of this modification has lagged behind. To investigate principles underlying dynamics and regulation of palmitoylation, we have here studied a key cellular protein, the ER chaperone calnexin, which requires dual palmitoylation for function. Apprehending the complex inter-conversion between single-, double- and non-palmitoylated species required combining experimental determination of kinetic parameters with extensive mathematical modelling. We found that calnexin, due to the presence of two cooperative sites, becomes stably acylated, which not only confers function but also a remarkable increase in stability. Unexpectedly, stochastic simulations revealed that palmitoylation does not occur soon after synthesis, but many hours later. This prediction guided us to find that phosphorylation actively delays calnexin palmitoylation in resting cells. Altogether this study reveals that cells synthesize 5 times more calnexin than needed under resting condition, most of which is degraded. This unused pool can be mobilized by preventing phosphorylation or increasing the activity of the palmitoyltransferase DHHC6.'),
(87679, 2016, 'plos', 'Control of xcexb2AR- and N-methyl-D-aspartate (NMDA) Receptor-Dependent cAMP Dynamics in Hippocampal Neurons', 'Chay, Andrew|Zamparo, Ilaria|Koschinski, Andreas|Zaccolo, Manuela|Blackwell, Kim T', 'Molecular Neuroscience Department, Krasnow Institute, George Mason University, Fairfax, Virginia, United States of America.|Venetian Institute of Molecular Medicine, Padova, Italy.|Department of Physiology, Anatomy and Genetics, Oxford University, Oxford, United Kingdom.|Department of Physiology, Anatomy and Genetics, Oxford University, Oxford, United Kingdom.|Molecular Neuroscience Department, Krasnow Institute, George Mason University, Fairfax, Virginia, United States of America.', 'United States|Italy|United Kingdom|United Kingdom|United States', 8, 'Animals|Calcium|Computational Biology|Cyclic AMP|Cyclic AMP-Dependent Protein Kinases|Cyclic Nucleotide Phosphodiesterases, Type 4|Fluorescence Resonance Energy Transfer|Hippocampus|Isoproterenol|Molecular Imaging|N-Methylaspartate|Neurons|Rats|Rats, Sprague-Dawley|Receptors, Adrenergic, beta', 'Journal Article', '10.1371/journal.pcbi.1004735', '26901880', 'Norepinephrine, a neuromodulator that activates xcexb2-adrenergic receptors (xcexb2ARs), facilitates learning and memory as well as the induction of synaptic plasticity in the hippocampus. Several forms of long-term potentiation (LTP) at the Schaffer collateral CA1 synapse require stimulation of both xcexb2ARs and N-methyl-D-aspartate receptors (NMDARs). To understand the mechanisms mediating the interactions between xcexb2AR and NMDAR signaling pathways, we combined FRET imaging of cAMP in hippocampal neuron cultures with spatial mechanistic modeling of signaling pathways in the CA1 pyramidal neuron. Previous work implied that cAMP is synergistically produced in the presence of the xcexb2AR agonist isoproterenol and intracellular calcium. In contrast, we show that when application of isoproterenol precedes application of NMDA by several minutes, as is typical of xcexb2AR-facilitated LTP experiments, the average amplitude of the cAMP response to NMDA is attenuated compared with the response to NMDA alone. Models simulations suggest that, although the negative feedback loop formed by cAMP, cAMP-dependent protein kinase (PKA), and type 4 phosphodiesterase may be involved in attenuating the cAMP response to NMDA, it is insufficient to explain the range of experimental observations. Instead, attenuation of the cAMP response requires mechanisms upstream of adenylyl cyclase. Our model demonstrates that Gs-to-Gi switching due to PKA phosphorylation of xcexb2ARs as well as Gi inhibition of type 1 adenylyl cyclase may underlie the experimental observations. This suggests that signaling by xcexb2-adrenergic receptors depends on temporal pattern of stimulation, and that switching may represent a novel mechanism for recruiting kinases involved in synaptic plasticity and memory. '),
(87680, 2016, 'plos', 'Enhanced Sensitivity to Rapid Input Fluctuations by Nonlinear Threshold Dynamics in Neocortical Pyramidal Neurons', 'Mensi, Skander|Hagens, Olivier|Gerstner, Wulfram|Pozzorini, Christian', 'Laboratory of Computational Neuroscience (LCN), Brain Mind Institute, School of Computer and Communication Sciences and School of Life Sciences, École Polytechnique Fédérale de Lausanne, Lausanne, Switzerland.|Laboratory of Neural Microcircuitry (LNMC), Brain Mind Institute, School of Life Sciences, École Polytechnique Fédérale de Lausanne, Lausanne, Switzerland.|Laboratory of Computational Neuroscience (LCN), Brain Mind Institute, School of Computer and Communication Sciences and School of Life Sciences, École Polytechnique Fédérale de Lausanne, Lausanne, Switzerland.|Laboratory of Computational Neuroscience (LCN), Brain Mind Institute, School of Computer and Communication Sciences and School of Life Sciences, École Polytechnique Fédérale de Lausanne, Lausanne, Switzerland.', 'Switzerland|Switzerland|Switzerland|Switzerland', 16, 'Action Potentials|Animals|Computational Biology|Male|Mice|Mice, Inbred C57BL|Models, Neurological|Neocortex|Nonlinear Dynamics|Pyramidal Cells', 'Journal Article', '10.1371/journal.pcbi.1004761', '26907675', 'The way in which single neurons transform input into output spike trains has fundamental consequences for network coding. Theories and modeling studies based on standard Integrate-and-Fire models implicitly assume that, in response to increasingly strong inputs, neurons modify their coding strategy by progressively reducing their selective sensitivity to rapid input fluctuations. Combining mathematical modeling with in vitro experiments, we demonstrate that, in L5 pyramidal neurons, the firing threshold dynamics adaptively adjust the effective timescale of somatic integration in order to preserve sensitivity to rapid signals over a broad range of input statistics. For that, a new Generalized Integrate-and-Fire model featuring nonlinear firing threshold dynamics and conductance-based adaptation is introduced that outperforms state-of-the-art neuron models in predicting the spiking activity of neurons responding to a variety of in vivo-like fluctuating currents. Our model allows for efficient parameter extraction and can be analytically mapped to a Generalized Linear Model in which both the input filter--describing somatic integration--and the spike-history filter--accounting for spike-frequency adaptation--dynamically adapt to the input statistics, as experimentally observed. Overall, our results provide new insights on the computational role of different biophysical processes known to underlie adaptive coding in single neurons and support previous theoretical findings indicating that the nonlinear dynamics of the firing threshold due to Na+-channel inactivation regulate the sensitivity to rapid input fluctuations.'),
(87681, 2016, 'plos', 'The 2015 Bioinformatics Open Source Conference (BOSC 2015)', 'Harris, Nomi L|Cock, Peter J A|Lapp, Hilmar|Chapman, Brad|Davey, Rob|Fields, Christopher|Hokamp, Karsten|Munoz-Torres, Monica', 'Lawrence Berkeley National Laboratory, Berkeley, California, United States of America.|The James Hutton Institute, Dundee, United Kingdom.|Center for Genomic and Computational Biology, Duke University, Durham, North Carolina, United States of America.|Bioinformatics Core, Harvard School of Public Health, Boston, Massachusetts, United States of America.|The Genome Analysis Centre, Norwich, United Kingdom.|National Center for Supercomputing Applications, University of Illinois Urbana-Champaign, Urbana, Illinois, United States of America.|Smurfit Institute of Genetics, Trinity College Dublin, Dublin, Ireland.|Lawrence Berkeley National Laboratory, Berkeley, California, United States of America.', 'United States|United Kingdom|United States|United States|United Kingdom|United States|Ireland|United', 0, 'Computational Biology|Congresses as Topic|Humans|Ireland', 'Journal Article', '10.1371/journal.pcbi.1004691', '26914653', 'The Bioinformatics Open Source Conference (BOSC) is organized by the Open Bioinformatics Foundation (OBF), a nonprofit group dedicated to promoting the practice and philosophy of open source software development and open science within the biological research community. Since its inception in 2000, BOSC has provided bioinformatics developers with a forum for communicating the results of their latest efforts to the wider research community. BOSC offers a focused environment for developers and users to interact and share ideas about standards, software development practices, practical techniques for solving bioinformatics problems, and approaches that promote open science and sharing of data, results, and software. BOSC is run as a two-day special interest group (SIG) before the annual Intelligent Systems in Molecular Biology (ISMB) conference. BOSC 2015 took place in Dublin, Ireland, and was attended by over 125 people, about half of whom were first-time attendees. Session topics included Data Science, Standards and Interoperability, Open Science and Reproducibility, Translational Bioinformatics, Visualization, and Bioinformatics Open Source Project Updates. In addition to two keynote talks and dozens of shorter talks chosen from submitted abstracts, BOSC 2015 included a panel, titled Open Source, Open Door: Increasing Diversity in the Bioinformatics Open Source Community, that provided an opportunity for open discussion about ways to increase the diversity of participants in BOSC in particular, and in open source bioinformatics in general. The complete program of BOSC 2015 is available online at http://www.open-bio.org/wiki/BOSC_2015_Schedule. '),
(87682, 2016, 'plos', 'A Sensory-Driven Trade-Off between Coordinated Motion in Social Prey and a Predators Visual Confusion', 'Lemasson, Bertrand H|Tanner, Colby J|Dimperio, Eric', 'Environmental Laboratory, U.S. Army Engineer Research & Development Center (ERDC), Santa Barbara, California, United States of America.|Department of Ecology, Université de Lausanne, Switzerland.|Environmental Laboratory, U.S. Army Engineer Research & Development Center (ERDC), Santa Barbara, California, United States of America.', 'United States|Switzerland|United States', 6, 'Adult|Animals|Computational Biology|Computer Simulation|Confusion|Humans|Models, Biological|Movement|Predatory Behavior|Social Behavior', 'Journal Article', '10.1371/journal.pcbi.1004708', '26914768', 'Social animals are capable of enhancing their awareness by paying attention to their neighbors, and prey found in groups can also confuse their predators. Both sides of these sensory benefits have long been appreciated, yet less is known of how the perception of events from the perspectives of both prey and predator can interact to influence their encounters. Here we examined how a visual sensory mechanism impacts the collective motion of prey and, subsequently, how their resulting movements influenced predator confusion and capture ability. We presented virtual prey to human players in a targeting game and measured the speed and accuracy with which participants caught designated prey. As prey paid more attention to neighbor movements their collective coordination increased, yet increases in prey coordination were positively associated with increases in the speed and accuracy of attacks. However, while attack speed was unaffected by the initial state of the prey, accuracy dropped significantly if the prey were already organized at the start of the attack, rather than in the process of self-organizing. By repeating attack scenarios and masking the targeted preys neighbors we were able to visually isolate them and conclusively demonstrate how visual confusion impacted capture ability. Delays in capture caused by decreased coordination amongst the prey depended upon the collection motion of neighboring prey, while it was primarily the motion of the targets themselves that determined capture accuracy. Interestingly, while a complete loss of coordination in the prey (e.g., a flash expansion) caused the greatest delay in capture, such behavior had little effect on capture accuracy. Lastly, while increases in collective coordination in prey enhanced personal risk, traveling in coordinated groups was still better than appearing alone. These findings demonstrate a trade-off between the sensory mechanisms that can enhance the collective properties that emerge in social animals and the individual group members predation risk during an attack. '),
(87683, 2016, 'plos', 'Cortical Resonance Frequencies Emerge from Network Size and Connectivity', 'Lea-Carnall, Caroline A|Montemurro, Marcelo A|Trujillo-Barreto, Nelson J|Parkes, Laura M|El-Deredy, Wael', 'Faculty of Medical and Human Sciences, University of Manchester, Manchester, United Kingdom.|Faculty of Life Sciences, University of Manchester, Manchester, United Kingdom.|Faculty of Medical and Human Sciences, University of Manchester, Manchester, United Kingdom.|Faculty of Medical and Human Sciences, University of Manchester, Manchester, United Kingdom.|Faculty of Medical and Human Sciences, University of Manchester, Manchester, United Kingdom.', 'United Kingdom|United Kingdom|United Kingdom|United Kingdom|United Kingdom', 0, 'Computational Biology|Computer Simulation|Evoked Potentials, Visual|Humans|Models, Neurological|Nerve Net|Visual Cortex', 'Journal Article', '10.1371/journal.pcbi.1004740', '26914905', 'Neural oscillations occur within a wide frequency range with different brain regions exhibiting resonance-like characteristics at specific points in the spectrum. At the microscopic scale, single neurons possess intrinsic oscillatory properties, such that is not yet known whether cortical resonance is consequential to neural oscillations or an emergent property of the networks that interconnect them. Using a network model of loosely-coupled Wilson-Cowan oscillators to simulate a patch of cortical sheet, we demonstrate that the size of the activated network is inversely related to its resonance frequency. Further analysis of the parameter space indicated that the number of excitatory and inhibitory connections, as well as the average transmission delay between units, determined the resonance frequency. The model predicted that if an activated network within the visual cortex increased in size, the resonance frequency of the network would decrease. We tested this prediction experimentally using the steady-state visual evoked potential where we stimulated the visual cortex with different size stimuli at a range of driving frequencies. We demonstrate that the frequency corresponding to peak steady-state response inversely correlated with the size of the network. We conclude that although individual neurons possess resonance properties, oscillatory activity at the macroscopic level is strongly influenced by network interactions, and that the steady-state response can be used to investigate functional networks. '),
(87684, 2016, 'plos', 'Cell Assembly Dynamics of Sparsely-Connected Inhibitory Networks: A Simple Model for the Collective Activity of Striatal Projection Neurons', 'Angulo-Garcia, David|Berke, Joshua D|Torcini, Alessandro', 'CNR - Consiglio Nazionale delle Ricerche - Istituto dei Sistemi Complessi, Sesto Fiorentino, Italy.|Department of Psychology and Biomedical Engineering, University of Michigan, Ann Arbor, Michigan, United States of America.|CNR - Consiglio Nazionale delle Ricerche - Istituto dei Sistemi Complessi, Sesto Fiorentino, Italy.', 'Italy|United States|Italy', 0, 'Algorithms|Animals|Computational Biology|Corpus Striatum|Mice|Models, Neurological|Nerve Net|Neurons', 'Journal Article', '10.1371/journal.pcbi.1004778', '26915024', 'Striatal projection neurons form a sparsely-connected inhibitory network, and this arrangement may be essential for the appropriate temporal organization of behavior. Here we show that a simplified, sparse inhibitory network of Leaky-Integrate-and-Fire neurons can reproduce some key features of striatal population activity, as observed in brain slices. In particular we develop a new metric to determine the conditions under which sparse inhibitory networks form anti-correlated cell assemblies with time-varying activity of individual cells. We find that under these conditions the network displays an input-specific sequence of cell assembly switching, that effectively discriminates similar inputs. Our results support the proposal that GABAergic connections between striatal projection neurons allow stimulus-selective, temporally-extended sequential activation of cell assemblies. Furthermore, we help to show how altered intrastriatal GABAergic signaling may produce aberrant network-level information processing in disorders such as Parkinsons and Huntingtons diseases. '),
(87685, 2016, 'plos', 'Oligomers of Heat-Shock Proteins: Structures That Dont Imply Function', 'Jacobs, William M|Knowles, Tuomas P J|Frenkel, Daan', 'Department of Chemistry, University of Cambridge, Cambridge, United Kingdom.|Department of Chemistry, University of Cambridge, Cambridge, United Kingdom.|Department of Chemistry, University of Cambridge, Cambridge, United Kingdom.', 'United Kingdom|United Kingdom|United Kingdom', 0, 'Computational Biology|Heat-Shock Proteins|Models, Molecular|Multiprotein Complexes|Thermodynamics', 'Journal Article', '10.1371/journal.pcbi.1004756', '26928170', 'Most proteins must remain soluble in the cytosol in order to perform their biological functions. To protect against undesired protein aggregation, living cells maintain a population of molecular chaperones that ensure the solubility of the proteome. Here we report simulations of a lattice model of interacting proteins to understand how low concentrations of passive molecular chaperones, such as small heat-shock proteins, suppress thermodynamic instabilities in protein solutions. Given fixed concentrations of chaperones and client proteins, the solubility of the proteome can be increased by tuning the chaperone-client binding strength. Surprisingly, we find that the binding strength that optimizes solubility while preventing irreversible chaperone binding also promotes the formation of weakly bound chaperone oligomers, although the presence of these oligomers does not significantly affect the thermodynamic stability of the solution. Such oligomers are commonly observed in experiments on small heat-shock proteins, but their connection to the biological function of these chaperones has remained unclear. Our simulations suggest that this clustering may not have any essential biological function, but rather emerges as a natural side-effect of optimizing the thermodynamic stability of the proteome. '),
(87686, 2016, 'plos', 'A Multi-Method Approach for Proteomic Network Inference in 11 Human Cancers', 'xc5x9eenbabaoxc4x9flu, Yasin|Sxc3xbcmer, Selxc3xa7uk Onur|Sxc3xa1nchez-Vega, Francisco|Bemis, Debra|Ciriello, Giovanni|Schultz, Nikolaus|Sander, Chris', 'Computational Biology Program, Memorial Sloan Kettering Cancer Center, New York, New York, United States of America.|Computational Biology Program, Memorial Sloan Kettering Cancer Center, New York, New York, United States of America.|Computational Biology Program, Memorial Sloan Kettering Cancer Center, New York, New York, United States of America.|Computational Biology Program, Memorial Sloan Kettering Cancer Center, New York, New York, United States of America.|Computational Biology Program, Memorial Sloan Kettering Cancer Center, New York, New York, United States of America.|Department of Epidemiology and Biostatistics, Memorial Sloan Kettering Cancer Center, New York, New York, United States of America.|Computational Biology Program, Memorial Sloan Kettering Cancer Center, New York, New York, United States of America.', 'United States|United States|United States|United States|United States|United States|United States', 15, 'Cluster Analysis|Databases, Protein|Gene Expression Profiling|Humans|Neoplasm Proteins|Neoplasms|Principal Component Analysis|Protein Interaction Maps|Proteomics|Software', 'Journal Article', '10.1371/journal.pcbi.1004765', '26928298', 'Protein expression and post-translational modification levels are tightly regulated in neoplastic cells to maintain cellular processes known as cancer hallmarks. The first Pan-Cancer initiative of The Cancer Genome Atlas (TCGA) Research Network has aggregated protein expression profiles for 3,467 patient samples from 11 tumor types using the antibody based reverse phase protein array (RPPA) technology. The resultant proteomic data can be utilized to computationally infer protein-protein interaction (PPI) networks and to study the commonalities and differences across tumor types. In this study, we compare the performance of 13 established network inference methods in their capacity to retrieve the curated Pathway Commons interactions from RPPA data. We observe that no single method has the best performance in all tumor types, but a group of six methods, including diverse techniques such as correlation, mutual information, and regression, consistently rank highly among the tested methods. We utilize the high performing methods to obtain a consensus network, and identify four robust and densely connected modules that reveal biological processes as well as suggest antibody-related technical biases. Mapping the consensus network interactions to Reactome gene lists confirms the pan-cancer importance of signal transduction pathways, innate and adaptive immune signaling, cell cycle, metabolism, and DNA repair, and also suggests several biological processes that may be specific to a subset of tumor types. Our results illustrate the utility of the RPPA platform as a tool to study proteomic networks in cancer. '),
(87687, 2016, 'plos', 'Evolution of Cooperation in Social Dilemmas on Complex Networks', 'Iyer, Swami|Killingback, Timothy', 'Computer Science Department, University of Massachusetts, Boston, Massachusetts, United States of America.|Mathematics Department, University of Massachusetts, Boston, Massachusetts, United States of America.', 'United States|United States', 0, 'Altruism|Biological Evolution|Computational Biology|Computer Simulation|Cooperative Behavior|Games, Experimental|Humans|Models, Biological', 'Journal Article', '10.1371/journal.pcbi.1004779', '26928428', 'Cooperation in social dilemmas is essential for the functioning of systems at multiple levels of complexity, from the simplest biological organisms to the most sophisticated human societies. Cooperation, although widespread, is fundamentally challenging to explain evolutionarily, since natural selection typically favors selfish behavior which is not socially optimal. Here we study the evolution of cooperation in three exemplars of key social dilemmas, representing the prisoners dilemma, hawk-dove and coordination classes of games, in structured populations defined by complex networks. Using individual-based simulations of the games on model and empirical networks, we give a detailed comparative study of the effects of the structural properties of a network, such as its average degree, variance in degree distribution, clustering coefficient, and assortativity coefficient, on the promotion of cooperative behavior in all three classes of games. '),
(87688, 2016, 'plos', 'Feedbacks, Bifurcations, and Cell Fate Decision-Making in the p53 System', 'Hat, Beata|Kochaxc5x84czyk, Marek|Bogdaxc5x82, Marta N|Lipniacki, Tomasz', 'Institute of Fundamental Technological Research, Polish Academy of Sciences, Warsaw, Poland.|Institute of Fundamental Technological Research, Polish Academy of Sciences, Warsaw, Poland.|Institute of Fundamental Technological Research, Polish Academy of Sciences, Warsaw, Poland.|Institute of Fundamental Technological Research, Polish Academy of Sciences, Warsaw, Poland.', 'Poland|Poland|Poland|Poland', 22, 'Apoptosis|Cell Cycle Checkpoints|Feedback, Physiological|Gene Expression Regulation, Neoplastic|Humans|Models, Biological|Signal Transduction|Tumor Suppressor Protein p53', 'Journal Article', '10.1371/journal.pcbi.1004787', '26928575', 'The p53 transcription factor is a regulator of key cellular processes including DNA repair, cell cycle arrest, and apoptosis. In this theoretical study, we investigate how the complex circuitry of the p53 network allows for stochastic yet unambiguous cell fate decision-making. The proposed Markov chain model consists of the regulatory core and two subordinated bistable modules responsible for cell cycle arrest and apoptosis. The regulatory core is controlled by two negative feedback loops (regulated by Mdm2 and Wip1) responsible for oscillations, and two antagonistic positive feedback loops (regulated by phosphatases Wip1 and PTEN) responsible for bistability. By means of bifurcation analysis of the deterministic approximation we capture the recurrent solutions (i.e., steady states and limit cycles) that delineate temporal responses of the stochastic system. Direct switching from the limit-cycle oscillations to the apoptotic steady state is enabled by the existence of a subcritical Neimark-Sacker bifurcation in which the limit cycle loses its stability by merging with an unstable invariant torus. Our analysis provides an explanation why cancer cell lines known to have vastly diverse expression levels of Wip1 and PTEN exhibit a broad spectrum of responses to DNA damage: from a fast transition to a high level of p53 killer (a p53 phosphoform which promotes commitment to apoptosis) in cells characterized by high PTEN and low Wip1 levels to long-lasting p53 level oscillations in cells having PTEN promoter methylated (as in, e.g., MCF-7 cell line). '),
(87689, 2016, 'plos', 'Training Excitatory-Inhibitory Recurrent Neural Networks for Cognitive Tasks: A Simple and Flexible Framework', 'Song, H Francis|Yang, Guangyu R|Wang, Xiao-Jing', 'Center for Neural Science, New York University, New York, New York, United States of America.|Center for Neural Science, New York University, New York, New York, United States of America.|Center for Neural Science, New York University, New York, New York, United States of America.', 'United States|United States|United States', 53, 'Algorithms|Animals|Cognition|Computational Biology|Computer Simulation|Haplorhini|Models, Neurological|Neurons', 'Journal Article', '10.1371/journal.pcbi.1004792', '26928718', 'The ability to simultaneously record from large numbers of neurons in behaving animals has ushered in a new era for the study of the neural circuit mechanisms underlying cognitive functions. One promising approach to uncovering the dynamical and computational principles governing population responses is to analyze model recurrent neural networks (RNNs) that have been optimized to perform the same tasks as behaving animals. Because the optimization of network parameters specifies the desired output but not the manner in which to achieve this output, trained networks serve as a source of mechanistic hypotheses and a testing ground for data analyses that link neural computation to behavior. Complete access to the activity and connectivity of the circuit, and the ability to manipulate them arbitrarily, make trained networks a convenient proxy for biological circuits and a valuable platform for theoretical investigation. However, existing RNNs lack basic biological features such as the distinction between excitatory and inhibitory units (Dales principle), which are essential if RNNs are to provide insights into the operation of biological circuits. Moreover, trained networks can achieve the same behavioral performance but differ substantially in their structure and dynamics, highlighting the need for a simple and flexible framework for the exploratory training of RNNs. Here, we describe a framework for gradient descent-based training of excitatory-inhibitory RNNs that can incorporate a variety of biological knowledge. We provide an implementation based on the machine learning library Theano, whose automatic differentiation capabilities facilitate modifications and extensions. We validate this framework by applying it to well-known experimental paradigms such as perceptual decision-making, context-dependent integration, multisensory integration, parametric working memory, and motor sequence generation. Our results demonstrate the wide range of neural activity patterns and behavior that can be modeled, and suggest a unified setting in which diverse cognitive computations and mechanisms can be studied. '),
(87690, 2016, 'plos', 'Correction: ClassTR: Classifying Within-Host Heterogeneity Based on Tandem Repeats with Application to Mycobacterium tuberculosis Infections', 'PLOS Computational Biology Staff', 'Center for Neural Science, New York University, New York, New York, United States of America.', 'United States', 0, '-', 'Published Erratum', '10.1371/journal.pcbi.1004806', '26928849', '-'),
(87691, 2016, 'plos', 'Genetic Correlations Greatly Increase Mutational Robustness and Can Both Reduce and Enhance Evolvability', 'Greenbury, Sam F|Schaper, Steffen|Ahnert, Sebastian E|Louis, Ard A', 'Theory of Condensed Matter Group, Cavendish Laboratory, University of Cambridge, Cambridge, United Kingdom.|Rudolf Peierls Centre for Theoretical Physics, University of Oxford, Oxford, United Kingdom.|Theory of Condensed Matter Group, Cavendish Laboratory, University of Cambridge, Cambridge, United Kingdom.|Rudolf Peierls Centre for Theoretical Physics, University of Oxford, Oxford, United Kingdom.', 'United Kingdom|United Kingdom|United Kingdom|United Kingdom', 22, 'Animals|Computer Simulation|Evolution, Molecular|Genetics, Population|Genotype|Humans|Models, Genetic|Models, Statistical|Mutation|Proteome', 'Journal Article', '10.1371/journal.pcbi.1004773', '26937652', 'Mutational neighbourhoods in genotype-phenotype (GP) maps are widely believed to be more likely to share characteristics than expected from random chance. Such genetic correlations should strongly influence evolutionary dynamics. We explore and quantify these intuitions by comparing three GP maps-a model for RNA secondary structure, the HP model for protein tertiary structure, and the Polyomino model for protein quaternary structure-to a simple random null model that maintains the number of genotypes mapping to each phenotype, but assigns genotypes randomly. The mutational neighbourhood of a genotype in these GP maps is much more likely to contain genotypes mapping to the same phenotype than in the random null model. Such neutral correlations can be quantified by the robustness to mutations, which can be many orders of magnitude larger than that of the null model, and crucially, above the critical threshold for the formation of large neutral networks of mutationally connected genotypes which enhance the capacity for the exploration of phenotypic novelty. Thus neutral correlations increase evolvability. We also study non-neutral correlations: Compared to the null model, i) If a particular (non-neutral) phenotype is found once in the 1-mutation neighbourhood of a genotype, then the chance of finding that phenotype multiple times in this neighbourhood is larger than expected, ii) If two genotypes are connected by a single neutral mutation, then their respective non-neutral 1-mutation neighbourhoods are more likely to be similar, iii) If a genotype maps to a folding or self-assembling phenotype, then its non-neutral neighbours are less likely to be a potentially deleterious non-folding or non-assembling phenotype. Non-neutral correlations of type i) and ii) reduce the rate at which new phenotypes can be found by neutral exploration, and so may diminish evolvability, while non-neutral correlations of type iii) may instead facilitate evolutionary exploration and so increase evolvability. ');
INSERT INTO `papers` (`id`, `ano`, `journal`, `titulo`, `autores`, `afiliacao`, `pais`, `citacoes`, `palavra_chave`, `categorias`, `doi`, `pubmed`, `abstract`) VALUES
(87692, 2016, 'plos', 'Power-Law Dynamics of Membrane Conductances Increase Spiking Diversity in a Hodgkin-Huxley Model', 'Teka, Wondimu|Stockton, David|Santamaria, Fidel', 'UTSA Neurosciences Institute, The University of Texas at San Antonio, San Antonio, Texas, United States of America.|Biomedical Engineering Program, The University of Texas at San Antonio, San Antonio, Texas, United States of America.|UTSA Neurosciences Institute, The University of Texas at San Antonio, San Antonio, Texas, United States of America.', 'United States|United States|United States', 20, 'Action Potentials|Animals|Cell Membrane|Computer Simulation|Electric Conductivity|Humans|Ion Channel Gating|Membrane Potentials|Models, Neurological|Potassium Channels|Sodium Channels', 'Journal Article', '10.1371/journal.pcbi.1004776', '26937967', 'We studied the effects of non-Markovian power-law voltage dependent conductances on the generation of action potentials and spiking patterns in a Hodgkin-Huxley model. To implement slow-adapting power-law dynamics of the gating variables of the potassium, n, and sodium, m and h, conductances we used fractional derivatives of order xcexb7xe2x89xa41. The fractional derivatives were used to solve the kinetic equations of each gate. We systematically classified the properties of each gate as a function of xcexb7. We then tested if the full model could generate action potentials with the different power-law behaving gates. Finally, we studied the patterns of action potential that emerged in each case. Our results show the model produces a wide range of action potential shapes and spiking patterns in response to constant current stimulation as a function of xcexb7. In comparison with the classical model, the action potential shapes for power-law behaving potassium conductance (n gate) showed a longer peak and shallow hyperpolarization, for power-law activation of the sodium conductance (m gate), the action potentials had a sharp rise time, and for power-law inactivation of the sodium conductance (h gate) the spikes had wider peak that for low values of xcexb7 replicated pituitary- and cardiac-type action potentials. With all physiological parameters fixed a wide range of spiking patterns emerged as a function of the value of the constant input current and xcexb7, such as square wave bursting, mixed mode oscillations, and pseudo-plateau potentials. Our analyses show that the intrinsic memory trace of the fractional derivative provides a negative feedback mechanism between the voltage trace and the activity of the power-law behaving gate variable. As a consequence, power-law behaving conductances result in an increase in the number of spiking patterns a neuron can generate and, we propose, expand the computational capacity of the neuron. '),
(87693, 2016, 'plos', '4C-ker: A Method to Reproducibly Identify Genome-Wide Interactions Captured by 4C-Seq Experiments', 'Raviram, Ramya|Rocha, Pedro P|Müller, Christian L|Miraldi, Emily R|Badri, Sana|Fu, Yi|Swanzey, Emily|Proudhon, Charlotte|Snetkova, Valentina|Bonneau, Richard|Skok, Jane A', 'Department of Pathology, New York University School of Medicine, New York, New York, United States of America.|Department of Pathology, New York University School of Medicine, New York, New York, United States of America.|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 Pathology, New York University School of Medicine, New York, New York, United States of America.|Department of Pathology, New York University School of Medicine, New York, New York, United States of America.|Skirball Institute, New York University School of Medicine, New York, New York, United States of America.|Department of Pathology, New York University School of Medicine, New York, New York, United States of America.|Department of Pathology, New York University School of Medicine, New York, New York, United States of America.|Department of Biology, New York University, New York, New York, United States of America.|Department of Pathology, New York University School of Medicine, New York, New York, United States of America.', 'United States|United States|United States|United States|United States|United States|United States|Un', 34, 'Algorithms|Base Sequence|Binding Sites|DNA, Catalytic|Genome|Molecular Sequence Data|Protein Binding|Restriction Mapping|Sequence Analysis, DNA|Software', 'Journal Article', '10.1371/journal.pcbi.1004780', '26938081', '4C-Seq has proven to be a powerful technique to identify genome-wide interactions with a single locus of interest (or bait) that can be important for gene regulation. However, analysis of 4C-Seq data is complicated by the many biases inherent to the technique. An important consideration when dealing with 4C-Seq data is the differences in resolution of signal across the genome that result from differences in 3D distance separation from the bait. This leads to the highest signal in the region immediately surrounding the bait and increasingly lower signals in far-cis and trans. Another important aspect of 4C-Seq experiments is the resolution, which is greatly influenced by the choice of restriction enzyme and the frequency at which it can cut the genome. Thus, it is important that a 4C-Seq analysis method is flexible enough to analyze data generated using different enzymes and to identify interactions across the entire genome. Current methods for 4C-Seq analysis only identify interactions in regions near the bait or in regions located in far-cis and trans, but no method comprehensively analyzes 4C signals of different length scales. In addition, some methods also fail in experiments where chromatin fragments are generated using frequent cutter restriction enzymes. Here, we describe 4C-ker, a Hidden-Markov Model based pipeline that identifies regions throughout the genome that interact with the 4C bait locus. In addition, we incorporate methods for the identification of differential interactions in multiple 4C-seq datasets collected from different genotypes or experimental conditions. Adaptive window sizes are used to correct for differences in signal coverage in near-bait regions, far-cis and trans chromosomes. Using several datasets, we demonstrate that 4C-ker outperforms all existing 4C-Seq pipelines in its ability to reproducibly identify interaction domains at all genomic ranges with different resolution enzymes. '),
(87694, 2016, 'plos', 'Quantifying and Mitigating the Effect of Preferential Sampling on Phylodynamic Inference', 'Karcher, Michael D|Palacios, Julia A|Bedford, Trevor|Suchard, Marc A|Minin, Vladimir N', 'Department of Statistics, University of Washington, Seattle, Washington, United States of America.|Department of Organismic and Evolutionary Biology, Harvard University, Cambridge, Massachusetts, United States of America.|Vaccine and Infectious Disease Division, Fred Hutchinson Cancer Research Center, Seattle, Washington, United States of America.|Department of Human Genetics, David Geffen School of Medicine at UCLA, University of California, Los Angeles, Los Angeles, CA, United States of America.|Department of Statistics, University of Washington, Seattle, Washington, United States of America.', 'United States|United States|United States|United States|United States', 11, 'Biological Evolution|Computer Simulation|Data Interpretation, Statistical|Genetic Variation|Genetics, Population|Hemagglutinins|Influenza A Virus, H3N2 Subtype|Models, Genetic|Models, Statistical|Phylogeny|Sample Size', 'Journal Article', '10.1371/journal.pcbi.1004789', '26938243', 'Phylodynamics seeks to estimate effective population size fluctuations from molecular sequences of individuals sampled from a population of interest. One way to accomplish this task formulates an observed sequence data likelihood exploiting a coalescent model for the sampled individuals genealogy and then integrating over all possible genealogies via Monte Carlo or, less efficiently, by conditioning on one genealogy estimated from the sequence data. However, when analyzing sequences sampled serially through time, current methods implicitly assume either that sampling times are fixed deterministically by the data collection protocol or that their distribution does not depend on the size of the population. Through simulation, we first show that, when sampling times do probabilistically depend on effective population size, estimation methods may be systematically biased. To correct for this deficiency, we propose a new model that explicitly accounts for preferential sampling by modeling the sampling times as an inhomogeneous Poisson process dependent on effective population size. We demonstrate that in the presence of preferential sampling our new model not only reduces bias, but also improves estimation precision. Finally, we compare the performance of the currently used phylodynamic methods with our proposed model through clinically-relevant, seasonal human influenza examples. '),
(87695, 2016, 'plos', 'Extracting Behaviorally Relevant Traits from Natural Stimuli: Benefits of Combinatorial Representations at the Accessory Olfactory Bulb', 'Kahan, Anat|Ben-Shaul, Yoram', 'Department of Medical Neurobiology, Hebrew University Medical School, Jerusalem, Israel.|Department of Medical Neurobiology, Hebrew University Medical School, Jerusalem, Israel.', 'Israel|Israel', 7, 'Animals|Computer Simulation|Estrus|Female|Genetic Background|Mating Preference, Animal|Mice|Mice, Inbred BALB C|Mice, Inbred C57BL|Models, Neurological|Nerve Net|Odorants|Olfactory Bulb|Olfactory Perception|Sex Characteristics', 'Journal Article', '10.1371/journal.pcbi.1004798', '26938460', 'For many animals, chemosensation is essential for guiding social behavior. However, because multiple factors can modulate levels of individual chemical cues, deriving information about other individuals via natural chemical stimuli involves considerable challenges. How social information is extracted despite these sources of variability is poorly understood. The vomeronasal system provides an excellent opportunity to study this topic due to its role in detecting socially relevant traits. Here, we focus on two such traits: a female mouses strain and reproductive state. In particular, we measure stimulus-induced neuronal activity in the accessory olfactory bulb (AOB) in response to various dilutions of urine, vaginal secretions, and saliva, from estrus and non-estrus female mice from two different strains. We first show that all tested secretions provide information about a females receptivity and genotype. Next, we investigate how these traits can be decoded from neuronal activity despite multiple sources of variability. We show that individual neurons are limited in their capacity to allow trait classification across multiple sources of variability. However, simple linear classifiers sampling neuronal activity from small neuronal ensembles can provide a substantial improvement over that attained with individual units. Furthermore, we show that some traits are more efficiently detected than others, and that particular secretions may be optimized for conveying information about specific traits. Across all tested stimulus sources, discrimination between strains is more accurate than discrimination of receptivity, and detection of receptivity is more accurate with vaginal secretions than with urine. Our findings highlight the challenges of chemosensory processing of natural stimuli, and suggest that downstream readout stages decode multiple behaviorally relevant traits by sampling information from distinct but overlapping populations of AOB neurons. '),
(87696, 2016, 'plos', 'Structure-Based Statistical Mechanical Model Accounts for the Causality and Energetics of Allosteric Communication', 'Guarnera, Enrico|Berezovsky, Igor N', 'Bioinformatics Institute (BII), Agency for Science, Technology and Research (ASTAR), Singapore.|Bioinformatics Institute (BII), Agency for Science, Technology and Research (ASTAR), Singapore.', 'Singapore|Singapore', 43, 'Allosteric Regulation|Allosteric Site|Amino Acid Sequence|Computer Simulation|Energy Transfer|Enzyme Activation|Enzymes|Models, Chemical|Models, Molecular|Models, Statistical|Molecular Sequence Data|Protein Binding|Protein Conformation|Structure-Activity Relationship|Thermodynamics', 'Journal Article', '10.1371/journal.pcbi.1004678', '26939022', 'Allostery is one of the pervasive mechanisms through which proteins in living systems carry out enzymatic activity, cell signaling, and metabolism control. Effective modeling of the protein function regulation requires a synthesis of the thermodynamic and structural views of allostery. We present here a structure-based statistical mechanical model of allostery, allowing one to observe causality of communication between regulatory and functional sites, and to estimate per residue free energy changes. Based on the consideration of ligand free and ligand bound systems in the context of a harmonic model, corresponding sets of characteristic normal modes are obtained and used as inputs for an allosteric potential. This potential quantifies the mean work exerted on a residue due to the local motion of its neighbors. Subsequently, in a statistical mechanical framework the entropic contribution to allosteric free energy of a residue is directly calculated from the comparison of conformational ensembles in the ligand free and ligand bound systems. As a result, this method provides a systematic approach for analyzing the energetics of allosteric communication based on a single structure. The feasibility of the approach was tested on a variety of allosteric proteins, heterogeneous in terms of size, topology and degree of oligomerization. The allosteric free energy calculations show the diversity of ways and complexity of scenarios existing in the phenomenology of allosteric causality and communication. The presented model is a step forward in developing the computational techniques aimed at detecting allosteric sites and obtaining the discriminative power between agonistic and antagonistic effectors, which are among the major goals in allosteric drug design. '),
(87697, 2016, 'plos', 'Stability and Competition in Multi-spike Models of Spike-Timing Dependent Plasticity', 'Babadi, Baktash|Abbott, L F', 'Center for Theoretical Neuroscience, Department of Neuroscience, Columbia University, New York, New York, United States of America.|Center for Theoretical Neuroscience, Department of Neuroscience, Columbia University, New York, New York, United States of America.', 'United States|United States', 12, 'Action Potentials|Computer Simulation|Humans|Models, Neurological|Models, Statistical|Nerve Net|Neural Inhibition|Neuronal Plasticity|Neurons|Synaptic Transmission', 'Journal Article', '10.1371/journal.pcbi.1004750', '26939080', 'Spike-timing dependent plasticity (STDP) is a widespread plasticity mechanism in the nervous system. The simplest description of STDP only takes into account pairs of pre- and postsynaptic spikes, with potentiation of the synapse when a presynaptic spike precedes a postsynaptic spike and depression otherwise. In light of experiments that explored a variety of spike patterns, the pair-based STDP model has been augmented to account for multiple pre- and postsynaptic spike interactions. As a result, a number of different multi-spike STDP models have been proposed based on different experimental observations. The behavior of these models at the population level is crucial for understanding mechanisms of learning and memory. The challenging balance between the stability of a population of synapses and their competitive modification is well studied for pair-based models, but it has not yet been fully analyzed for multi-spike models. Here, we address this issue through numerical simulations of an integrate-and-fire model neuron with excitatory synapses subject to STDP described by three different proposed multi-spike models. We also analytically calculate average synaptic changes and fluctuations about these averages. Our results indicate that the different multi-spike models behave quite differently at the population level. Although each model can produce synaptic competition in certain parameter regions, none of them induces synaptic competition with its originally fitted parameters. The dichotomy between synaptic stability and Hebbian competition, which is well characterized for pair-based STDP models, persists in multi-spike models. However, anti-Hebbian competition can coexist with synaptic stability in some models. We propose that the collective behavior of synaptic plasticity models at the population level should be used as an additional guideline in applying phenomenological models based on observations of single synapses. '),
(87698, 2016, 'plos', 'Annealed Importance Sampling for Neural Mass Models', 'Penny, Will|Sengupta, Biswa', 'Wellcome Trust Centre for Neuroimaging, University College London, London, United Kingdom.|Wellcome Trust Centre for Neuroimaging, University College London, London, United Kingdom.', 'United Kingdom|United Kingdom', 4, 'Action Potentials|Brain|Computer Simulation|Connectome|Models, Neurological|Models, Statistical|Nerve Net|Neurons|Sample Size', 'Journal Article', '10.1371/journal.pcbi.1004797', '26942606', 'Neural Mass Models provide a compact description of the dynamical activity of cell populations in neocortical regions. Moreover, models of regional activity can be connected together into networks, and inferences made about the strength of connections, using M/EEG data and Bayesian inference. To date, however, Bayesian methods have been largely restricted to the Variational Laplace (VL) algorithm which assumes that the posterior distribution is Gaussian and finds model parameters that are only locally optimal. This paper explores the use of Annealed Importance Sampling (AIS) to address these restrictions. We implement AIS using proposals derived from Langevin Monte Carlo (LMC) which uses local gradient and curvature information for efficient exploration of parameter space. In terms of the estimation of Bayes factors, VL and AIS agree about which model is best but report different degrees of belief. Additionally, AIS finds better model parameters and we find evidence of non-Gaussianity in their posterior distribution. '),
(87699, 2016, 'plos', 'Reconstruction of Tissue-Specific Metabolic Networks Using CORDA', 'Schultz, André|Qutub, Amina A', 'Department of Bioengineering, Rice University, Houston, Texas, United States of America.|Department of Bioengineering, Rice University, Houston, Texas, United States of America.', 'United States|United States', 44, 'Algorithms|Computer Simulation|Humans|Metabolome|Metabolomics|Models, Biological|Neoplasm Proteins|Neoplasms|Organ Specificity|Proteome|Signal Transduction', 'Journal Article', '10.1371/journal.pcbi.1004808', '26942765', 'Human metabolism involves thousands of reactions and metabolites. To interpret this complexity, computational modeling becomes an essential experimental tool. One of the most popular techniques to study human metabolism as a whole is genome scale modeling. A key challenge to applying genome scale modeling is identifying critical metabolic reactions across diverse human tissues. Here we introduce a novel algorithm called Cost Optimization Reaction Dependency Assessment (CORDA) to build genome scale models in a tissue-specific manner. CORDA performs more efficiently computationally, shows better agreement to experimental data, and displays better model functionality and capacity when compared to previous algorithms. CORDA also returns reaction associations that can greatly assist in any manual curation to be performed following the automated reconstruction process. Using CORDA, we developed a library of 76 healthy and 20 cancer tissue-specific reconstructions. These reconstructions identified which metabolic pathways are shared across diverse human tissues. Moreover, we identified changes in reactions and pathways that are differentially included and present different capacity profiles in cancer compared to healthy tissues, including up-regulation of folate metabolism, the down-regulation of thiamine metabolism, and tight regulation of oxidative phosphorylation. '),
(87700, 2016, 'plos', 'Correction: Plasticity-Driven Self-Organization under Topological Constraints Accounts for Non-random Features of Cortical Synaptic Wiring', 'PLOS Computational Biology Staff', 'Department of Bioengineering, Rice University, Houston, Texas, United States of America.', 'United States', 0, '-', 'Published Erratum', '10.1371/journal.pcbi.1004810', '26942937', '-'),
(87701, 2016, 'plos', 'Correction: A Systematic Computational Analysis of Biosynthetic Gene Cluster Evolution: Lessons for Engineering Biosynthesis', 'PLOS Computational Biology Staff', 'Department of Bioengineering, Rice University, Houston, Texas, United States of America.', 'United States', 0, '-', 'Published Erratum', '10.1371/journal.pcbi.1004767', '26953826', '-'),
(87702, 2016, 'plos', 'BIITE: A Tool to Determine HLA Class II Epitopes from T Cell ELISpot Data', 'Boelen, Lies|ONeill, Patrick K|Quigley, Kathryn J|Reynolds, Catherine J|Maillere, Bernard|Robinson, John H|Lertmemongkolchai, Ganjana|Altmann, Daniel M|Boyton, Rosemary J|Asquith, Becca', 'Section of Immunology, Wright-Fleming Institute, School of Medicine, Imperial College London, London, United Kingdom.|Department of Biological Sciences, University of Maryland Baltimore County (UMBC), Baltimore, Maryland, United States of America.|Lung Immunology Group, Section of Infectious Diseases and Immunity, Hammersmith Hospital, Department of Medicine, Imperial College London, London, United Kingdom.|Lung Immunology Group, Section of Infectious Diseases and Immunity, Hammersmith Hospital, Department of Medicine, Imperial College London, London, United Kingdom.|CEA-Saclay, Institute of Biology and Technologies, SIMOPRO, Labex LERMIT, Labex VRI, Gif Sur Yvette, France.|Institute of Cellular Medicine, Newcastle University, Newcastle upon Tyne, United Kingdom.|Centre for Research and Development of Medical Diagnostic Laboratories, Faculty of Associated Medical Sciences, Khon Kaen University, Khon Kaen, Thailand.|Lung Immunology Group, Section of Infectious Diseases and Immunity, Hammersmith Hospital, Department of Medicine, Imperial College London, London, United Kingdom.|Lung Immunology Group, Section of Infectious Diseases and Immunity, Hammersmith Hospital, Department of Medicine, Imperial College London, London, United Kingdom.|Section of Immunology, Wright-Fleming Institute, School of Medicine, Imperial College London, London, United Kingdom.', 'United Kingdom|United States|United Kingdom|United Kingdom|France|United Kingdom|Thailand|United Kin', 3, 'Algorithms|Burkholderia pseudomallei|Computational Biology|Computer Simulation|Databases, Factual|Enzyme-Linked Immunospot Assay|Epitopes, T-Lymphocyte|Histocompatibility Antigens Class II|Humans|Melioidosis|Models, Immunological|Peptides|Software', 'Journal Article', '10.1371/journal.pcbi.1004796', '26953935', 'Activation of CD4+ T cells requires the recognition of peptides that are presented by HLA class II molecules and can be assessed experimentally using the ELISpot assay. However, even given an individuals HLA class II genotype, identifying which class II molecule is responsible for a positive ELISpot response to a given peptide is not trivial. The two main difficulties are the number of HLA class II molecules that can potentially be formed in a single individual (3-14) and the lack of clear peptide binding motifs for class II molecules. Here, we present a Bayesian framework to interpret ELISpot data (BIITE: Bayesian Immunogenicity Inference Tool for ELISpot), specifically BIITE identifies which HLA-II:peptide combination(s) are immunogenic based on cohort ELISpot data. We apply BIITE to two ELISpot datasets and explore the expected performance using simulations. We show this method can reach high accuracies, depending on the cohort size and the success rate of the ELISpot assay within the cohort. '),
(87703, 2016, 'plos', 'Dynamical Allocation of Cellular Resources as an Optimal Control Problem: Novel Insights into Microbial Growth Strategies', 'Giordano, Nils|Mairet, Francis|Gouzé, Jean-Luc|Geiselmann, Johannes|de Jong, Hidde', 'Université Grenoble Alpes, Laboratoire Interdisciplinaire de Physique (CNRS UMR 5588), Saint Martin dHères, France.|Inria, Sophia-Antipolis Méditerranée research centre, Sophia-Antipolis Cedex, France.|Inria, Sophia-Antipolis Méditerranée research centre, Sophia-Antipolis Cedex, France.|Université Grenoble Alpes, Laboratoire Interdisciplinaire de Physique (CNRS UMR 5588), Saint Martin dHères, France.|Inria, Grenoble - Rhône-Alpes research centre, Montbonnot, Saint Ismier Cedex, France.', 'France|France|France|France|France', 30, 'Adaptation, Physiological|Cell Proliferation|Computer Simulation|Escherichia coli|Escherichia coli Proteins|Gene Expression Regulation, Bacterial|Models, Biological|Protein Biosynthesis|Pyrophosphatases|Ribosomes', 'Journal Article', '10.1371/journal.pcbi.1004802', '26958858', 'Microbial physiology exhibits growth laws that relate the macromolecular composition of the cell to the growth rate. Recent work has shown that these empirical regularities can be derived from coarse-grained models of resource allocation. While these studies focus on steady-state growth, such conditions are rarely found in natural habitats, where microorganisms are continually challenged by environmental fluctuations. The aim of this paper is to extend the study of microbial growth strategies to dynamical environments, using a self-replicator model. We formulate dynamical growth maximization as an optimal control problem that can be solved using Pontryagins Maximum Principle. We compare this theoretical gold standard with different possible implementations of growth control in bacterial cells. We find that simple control strategies enabling growth-rate maximization at steady state are suboptimal for transitions from one growth regime to another, for example when shifting bacterial cells to a medium supporting a higher growth rate. A near-optimal control strategy in dynamical conditions is shown to require information on several, rather than a single physiological variable. Interestingly, this strategy has structural analogies with the regulation of ribosomal protein synthesis by ppGpp in the enterobacterium Escherichia coli. It involves sensing a mismatch between precursor and ribosome concentrations, as well as the adjustment of ribosome synthesis in a switch-like manner. Our results show how the capability of regulatory systems to integrate information about several physiological variables is critical for optimizing growth in a changing environment. '),
(87704, 2016, 'plos', 'Pathway-Based Genomics Prediction using Generalized Elastic Net', 'Sokolov, Artem|Carlin, Daniel E|Paull, Evan O|Baertsch, Robert|Stuart, Joshua M', 'Department of Biomolecular Engineering and Center for Biomolecular Science and Engineering, University of California Santa Cruz, Santa Cruz, California, United States of America.|Department of Biomolecular Engineering and Center for Biomolecular Science and Engineering, University of California Santa Cruz, Santa Cruz, California, United States of America.|Department of Biomolecular Engineering and Center for Biomolecular Science and Engineering, University of California Santa Cruz, Santa Cruz, California, United States of America.|Department of Biomolecular Engineering and Center for Biomolecular Science and Engineering, University of California Santa Cruz, Santa Cruz, California, United States of America.|Department of Biomolecular Engineering and Center for Biomolecular Science and Engineering, University of California Santa Cruz, Santa Cruz, California, United States of America.', 'United States|United States|United States|United States|United States', 40, 'Animals|Chromosome Mapping|Computer Simulation|Humans|Models, Genetic|Pattern Recognition, Automated|Protein Interaction Mapping|Proteome|Signal Transduction', 'Journal Article', '10.1371/journal.pcbi.1004790', '26960204', 'We present a novel regularization scheme called The Generalized Elastic Net (GELnet) that incorporates gene pathway information into feature selection. The proposed formulation is applicable to a wide variety of problems in which the interpretation of predictive features using known molecular interactions is desired. The method naturally steers solutions toward sets of mechanistically interlinked genes. Using experiments on synthetic data, we demonstrate that pathway-guided results maintain, and often improve, the accuracy of predictors even in cases where the full gene network is unknown. We apply the method to predict the drug response of breast cancer cell lines. GELnet is able to reveal genetic determinants of sensitivity and resistance for several compounds. In particular, for an EGFR/HER2 inhibitor, it finds a possible trans-differentiation resistance mechanism missed by the corresponding pathway agnostic approach. '),
(87705, 2016, 'plos', 'Integrating Transgenic Vector Manipulation with Clinical Interventions to Manage Vector-Borne Diseases', 'Okamoto, Kenichi W|Gould, Fred|Lloyd, Alun L', 'Department of Entomology, North Carolina State University, Raleigh, North Carolina, United States of America.|Department of Entomology, North Carolina State University, Raleigh, North Carolina, United States of America.|Fogarty International Center, National Institutes of Health, Bethesda, Maryland, United States of America.', 'United States|United States|United States', 0, 'Animals|Combined Modality Therapy|Communicable Diseases|Computer Simulation|Genetic Engineering|Humans|Insect Vectors|Models, Genetic|Treatment Outcome', 'Journal Article', '10.1371/journal.pcbi.1004695', '26962871', 'Many vector-borne diseases lack effective vaccines and medications, and the limitations of traditional vector control have inspired novel approaches based on using genetic engineering to manipulate vector populations and thereby reduce transmission. Yet both the short- and long-term epidemiological effects of these transgenic strategies are highly uncertain. If neither vaccines, medications, nor transgenic strategies can by themselves suffice for managing vector-borne diseases, integrating these approaches becomes key. Here we develop a framework to evaluate how clinical interventions (i.e., vaccination and medication) can be integrated with transgenic vector manipulation strategies to prevent disease invasion and reduce disease incidence. We show that the ability of clinical interventions to accelerate disease suppression can depend on the nature of the transgenic manipulation deployed (e.g., whether vector population reduction or replacement is attempted). We find that making a specific, individual strategy highly effective may not be necessary for attaining public-health objectives, provided suitable combinations can be adopted. However, we show how combining only partially effective antimicrobial drugs or vaccination with transgenic vector manipulations that merely temporarily lower vector competence can amplify disease resurgence following transient suppression. Thus, transgenic vector manipulation that cannot be sustained can have adverse consequences-consequences which ineffective clinical interventions can at best only mitigate, and at worst temporarily exacerbate. This result, which arises from differences between the time scale on which the interventions affect disease dynamics and the time scale of host population dynamics, highlights the importance of accounting for the potential delay in the effects of deploying public health strategies on long-term disease incidence. We find that for systems at the disease-endemic equilibrium, even modest perturbations induced by weak interventions can exhibit strong, albeit transient, epidemiological effects. This, together with our finding that under some conditions combining strategies could have transient adverse epidemiological effects suggests that a relatively long time horizon may be necessary to discern the efficacy of alternative intervention strategies. '),
(87706, 2016, 'plos', 'Understanding Genotype-Phenotype Effects in Cancer via Network Approaches', 'Kim, Yoo-Ah|Cho, Dong-Yeon|Przytycka, Teresa M', 'National Center for Biotechnology Information, National Library of Medicine, National Institutes of Health, Bethesda, Maryland, United States of America.|National Center for Biotechnology Information, National Library of Medicine, National Institutes of Health, Bethesda, Maryland, United States of America.|National Center for Biotechnology Information, National Library of Medicine, National Institutes of Health, Bethesda, Maryland, United States of America.', 'United States|United States|United States', 22, 'Animals|Computer Simulation|Genetic Predisposition to Disease|Genotype|Humans|Models, Biological|Neoplasm Proteins|Neoplasms|Phenotype|Protein Interaction Mapping|Signal Transduction', 'Journal Article', '10.1371/journal.pcbi.1004747', '26963104', 'Cancer is now increasingly studied from the perspective of dysregulated pathways, rather than as a disease resulting from mutations of individual genes. A pathway-centric view acknowledges the heterogeneity between genomic profiles from different cancer patients while assuming that the mutated genes are likely to belong to the same pathway and cause similar disease phenotypes. Indeed, network-centric approaches have proven to be helpful for finding genotypic causes of diseases, classifying disease subtypes, and identifying drug targets. In this review, we discuss how networks can be used to help understand patient-to-patient variations and how one can leverage this variability to elucidate interactions between cancer drivers. '),
(87707, 2016, 'plos', 'Systems Approaches to the Eukaryotic Stress Response', 'Vogel, Christine', 'Center for Genomics and Systems Biology, Department of Biology, New York University, New York, United States of America.', 'United States', 0, 'Animals|Computer Simulation|Eukaryotic Cells|Heat-Shock Proteins|Heat-Shock Response|Humans|Laboratories|Models, Biological|Proteomics|Research|Systems Biology', 'Journal Article', '10.1371/journal.pcbi.1004757', '26963258', '-'),
(87708, 2016, 'plos', 'SMOG 2: A Versatile Software Package for Generating Structure-Based Models', 'Noel, Jeffrey K|Levi, Mariana|Raghunathan, Mohit|Lammert, Heiko|Hayes, Ryan L|Onuchic, José N|Whitford, Paul C', 'Center for Theoretical Biological Physics, Rice University, Houston, Texas, United States of America.|Department of Physics, Northeastern University, Boston, Massachusetts, United States of America.|Center for Theoretical Biological Physics, Rice University, Houston, Texas, United States of America.|Center for Theoretical Biological Physics, Rice University, Houston, Texas, United States of America.|Center for Theoretical Biological Physics, Rice University, Houston, Texas, United States of America.|Center for Theoretical Biological Physics, Rice University, Houston, Texas, United States of America.|Department of Physics, Northeastern University, Boston, Massachusetts, United States of America.', 'United States|United States|United States|United States|United States|United States|United States', 0, 'Algorithms|Models, Chemical|Molecular Dynamics Simulation|Protein Conformation|Proteins|Software|Software Design|Software Validation', 'Journal Article', '10.1371/journal.pcbi.1004794', '26963394', 'Molecular dynamics simulations with coarse-grained or simplified Hamiltonians have proven to be an effective means of capturing the functionally important long-time and large-length scale motions of proteins and RNAs. Originally developed in the context of protein folding, structure-based models (SBMs) have since been extended to probe a diverse range of biomolecular processes, spanning from protein and RNA folding to functional transitions in molecular machines. The hallmark feature of a structure-based model is that part, or all, of the potential energy function is defined by a known structure. Within this general class of models, there exist many possible variations in resolution and energetic composition. SMOG 2 is a downloadable software package that reads user-designated structural information and user-defined energy definitions, in order to produce the files necessary to use SBMs with high performance molecular dynamics packages: GROMACS and NAMD. SMOG 2 is bundled with XML-formatted template files that define commonly used SBMs, and it can process template files that are altered according to the needs of each user. This computational infrastructure also allows for experimental or bioinformatics-derived restraints or novel structural features to be included, e.g. novel ligands, prosthetic groups and post-translational/transcriptional modifications. The code and user guide can be downloaded at http://smog-server.org/smog2. '),
(87709, 2016, 'plos', 'Stability of Ensemble Models Predicts Productivity of Enzymatic Systems', 'Theisen, Matthew K|Lafontaine Rivera, Jimmy G|Liao, James C', 'Department of Bioengineering, University of California, Los Angeles, Los Angeles, California, United States of America.|Department of Chemical and Biomolecular Engineering, University of California, Los Angeles, Los Angeles, California, United States of America.|Department of Bioengineering, University of California, Los Angeles, Los Angeles, California, United States of America.', 'United States|United States|United States', 15, 'Animals|Computer Simulation|Enzyme Stability|Humans|Metabolome|Models, Biological|Models, Statistical|Multienzyme Complexes|Proteome|Signal Transduction', 'Journal Article', '10.1371/journal.pcbi.1004800', '26963521', 'Stability in a metabolic system may not be obtained if incorrect amounts of enzymes are used. Without stability, some metabolites may accumulate or deplete leading to the irreversible loss of the desired operating point. Even if initial enzyme amounts achieve a stable steady state, changes in enzyme amount due to stochastic variations or environmental changes may move the system to the unstable region and lose the steady-state or quasi-steady-state flux. This situation is distinct from the phenomenon characterized by typical sensitivity analysis, which focuses on the smooth change before loss of stability. Here we show that metabolic networks differ significantly in their intrinsic ability to attain stability due to the network structure and kinetic forms, and that after achieving stability, some enzymes are prone to cause instability upon changes in enzyme amounts. We use Ensemble Modelling for Robustness Analysis (EMRA) to analyze stability in four cell-free enzymatic systems when enzyme amounts are changed. Loss of stability in continuous systems can lead to lower production even when the system is tested experimentally in batch experiments. The predictions of instability by EMRA are supported by the lower productivity in batch experimental tests. The EMRA method incorporates properties of network structure, including stoichiometry and kinetic form, but does not require specific parameter values of the enzymes. '),
(87710, 2016, 'plos', 'NMR Methods to Study Dynamic Allostery', 'Grutsch, Sarina|Brüschweiler, Sven|Tollinger, Martin', 'Institute of Organic Chemistry, Center for Molecular Biosciences Innsbruck (CMBI), University of Innsbruck, Innsbruck, Austria.|Department of Computational & Structural Biology, Max F. Perutz Laboratories, Campus Vienna Biocenter 5, Vienna, Austria.|Institute of Organic Chemistry, Center for Molecular Biosciences Innsbruck (CMBI), University of Innsbruck, Innsbruck, Austria.', 'Austria|Austria|Austria', 0, 'Allosteric Regulation|Allosteric Site|Amino Acid Sequence|Enzyme Activation|Enzymes|Magnetic Resonance Spectroscopy|Models, Chemical|Molecular Dynamics Simulation|Molecular Sequence Data|Protein Binding|Sequence Analysis, Protein', 'Journal Article', '10.1371/journal.pcbi.1004620', '26964042', 'Nuclear magnetic resonance (NMR) spectroscopy provides a unique toolbox of experimental probes for studying dynamic processes on a wide range of timescales, ranging from picoseconds to milliseconds and beyond. Along with NMR hardware developments, recent methodological advancements have enabled the characterization of allosteric proteins at unprecedented detail, revealing intriguing aspects of allosteric mechanisms and increasing the proportion of the conformational ensemble that can be observed by experiment. Here, we present an overview of NMR spectroscopic methods for characterizing equilibrium fluctuations in free and bound states of allosteric proteins that have been most influential in the field. By combining NMR experimental approaches with molecular simulations, atomistic-level descriptions of the mechanisms by which allosteric phenomena take place are now within reach. '),
(87711, 2016, 'plos', 'Motor Demands Constrain Cognitive Rule Structures', 'Collins, Anne Gabrielle Eva|Frank, Michael Joshua', 'Department of Cognitive, Linguistic and Psychological Sciences, Brown Institute for Brain Science, Brown University, Providence, Rhode Island, United States of America.|Department of Cognitive, Linguistic and Psychological Sciences, Brown Institute for Brain Science, Brown University, Providence, Rhode Island, United States of America.', 'United States|United States', 7, 'Algorithms|Cognition|Computer Simulation|Executive Function|Humans|Learning|Models, Neurological|Motor Cortex|Movement|Psychomotor Performance', 'Journal Article', '10.1371/journal.pcbi.1004785', '26966909', 'Study of human executive function focuses on our ability to represent cognitive rules independently of stimulus or response modality. However, recent findings suggest that executive functions cannot be modularized separately from perceptual and motor systems, and that they instead scaffold on top of motor action selection. Here we investigate whether patterns of motor demands influence how participants choose to implement abstract rule structures. In a learning task that requires integrating two stimulus dimensions for determining appropriate responses, subjects typically structure the problem hierarchically, using one dimension to cue the task-set and the other to cue the response given the task-set. However, the choice of which dimension to use at each level can be arbitrary. We hypothesized that the specific structure subjects adopt would be constrained by the motor patterns afforded within each rule. Across four independent data-sets, we show that subjects create rule structures that afford motor clustering, preferring structures in which adjacent motor actions are valid within each task-set. In a fifth data-set using instructed rules, this bias was strong enough to counteract the well-known task switch-cost when instructions were incongruent with motor clustering. Computational simulations confirm that observed biases can be explained by leveraging overlap in cortical motor representations to improve outcome prediction and hence infer the structure to be learned. These results highlight the importance of sensorimotor constraints in abstract rule formation and shed light on why humans have strong biases to invent structure even when it does not exist. '),
(87712, 2016, 'plos', 'H3 Histone Tail Conformation within the Nucleosome and the Impact of K14 Acetylation Studied Using Enhanced Sampling Simulation', 'Ikebe, Jinzen|Sakuraba, Shun|Kono, Hidetoshi', 'Molecular Modeling and Simulation Group, Japan Atomic Energy Agency, Kizugawa, Japan.|Graduate School of Frontier Sciences, The University of Tokyo, Kashiwa-shi, Japan.|Molecular Modeling and Simulation Group, Japan Atomic Energy Agency, Kizugawa, Japan.', 'Japan|Japan|Japan', 19, 'Acetylation|Algorithms|Binding Sites|Histones|Models, Chemical|Molecular Dynamics Simulation|Nucleosomes|Protein Binding|Protein Conformation', 'Journal Article', '10.1371/journal.pcbi.1004788', '26967163', 'Acetylation of lysine residues in histone tails is associated with gene transcription. Because histone tails are structurally flexible and intrinsically disordered, it is difficult to experimentally determine the tail conformations and the impact of acetylation. In this work, we performed simulations to sample H3 tail conformations with and without acetylation. The results show that irrespective of the presence or absence of the acetylation, the H3 tail remains in contact with the DNA and assumes an xcexb1-helix structure in some regions. Acetylation slightly weakened the interaction between the tail and DNA and enhanced xcexb1-helix formation, resulting in a more compact tail conformation. We inferred that this compaction induces unwrapping and exposure of the linker DNA, enabling DNA-binding proteins (e.g., transcription factors) to bind to their target sequences. In addition, our simulation also showed that acetylated lysine was more often exposed to the solvent, which is consistent with the fact that acetylation functions as a post-translational modification recognition site marker. '),
(87713, 2016, 'plos', 'Dynamic Modelling Reveals Hotspots on the Pathway to Enzyme-Substrate Complex Formation', 'Gordon, Shane E|Weber, Daniel K|Downton, Matthew T|Wagner, John|Perugini, Matthew A', 'Department of Biochemistry and Genetics, La Trobe Institute for Molecular Science, La Trobe University, Melbourne, Victoria, Australia.|Computational Biophysics, IBM Research - Australia, Carlton, Victoria, Australia.|Computational Biophysics, IBM Research - Australia, Carlton, Victoria, Australia.|Computational Biophysics, IBM Research - Australia, Carlton, Victoria, Australia.|Department of Biochemistry and Genetics, La Trobe Institute for Molecular Science, La Trobe University, Melbourne, Victoria, Australia.', 'Australia|Australia|Australia|Australia|Australia', 8, 'Binding Sites|Catalysis|Enzyme Activation|Enzyme Stability|Hydro-Lyases|Kinetics|Models, Chemical|Molecular Dynamics Simulation|Protein Binding|Protein Conformation|Pyruvic Acid|Staphylococcus|Substrate Specificity', 'Journal Article', '10.1371/journal.pcbi.1004811', '26967332', 'Dihydrodipicolinate synthase (DHDPS) catalyzes the first committed step in the diaminopimelate pathway of bacteria, yielding amino acids required for cell wall and protein biosyntheses. The essentiality of the enzyme to bacteria, coupled with its absence in humans, validates DHDPS as an antibacterial drug target. Conventional drug design efforts have thus far been unsuccessful in identifying potent DHDPS inhibitors. Here, we make use of contemporary molecular dynamics simulation and Markov state models to explore the interactions between DHDPS from the human pathogen Staphylococcus aureus and its cognate substrate, pyruvate. Our simulations recover the crystallographic DHDPS-pyruvate complex without a priori knowledge of the final bound structure. The highly conserved residue Arg140 was found to have a pivotal role in coordinating the entry of pyruvate into the active site from bulk solvent, consistent with previous kinetic reports, indicating an indirect role for the residue in DHDPS catalysis. A metastable binding intermediate characterized by multiple points of intermolecular interaction between pyruvate and key DHDPS residue Arg140 was found to be a highly conserved feature of the binding trajectory when comparing alternative binding pathways. By means of umbrella sampling we show that these binding intermediates are thermodynamically metastable, consistent with both the available experimental data and the substrate binding model presented in this study. Our results provide insight into an important enzyme-substrate interaction in atomistic detail that offers the potential to be exploited for the discovery of more effective DHDPS inhibitors and, in a broader sense, dynamic protein-drug interactions. ');
INSERT INTO `papers` (`id`, `ano`, `journal`, `titulo`, `autores`, `afiliacao`, `pais`, `citacoes`, `palavra_chave`, `categorias`, `doi`, `pubmed`, `abstract`) VALUES
(87714, 2016, 'plos', 'The Role of Adherence and Retreatment in De Novo Emergence of MDR-TB', 'Cadosch, Dominique|Abel Zur Wiesch, Pia|Kouyos, Roger|Bonhoeffer, Sebastian', 'Institute for Integrative Biology, ETH Zurich, Switzerland.|Division of Epidemiology of Microbial Diseases, Yale School of Public Health, New Haven, Connecticut, United States of America.|Division of Infectious Diseases and Hospital Epidemiology, University Hospital Zurich, University of Zurich, Switzerland & Institute of Medical Virology, Swiss National Center for Retroviruses, University of Zurich, Zurich, Switzerland.|Institute for Integrative Biology, ETH Zurich, Switzerland.', 'Switzerland|United States|Switzerland|Switzerland', 8, 'Antitubercular Agents|Computer Simulation|Humans|Medication Adherence|Models, Biological|Models, Statistical|Mycobacterium tuberculosis|Risk Assessment|Treatment Outcome|Tuberculosis, Multidrug-Resistant|Tuberculosis, Pulmonary', 'Journal Article', '10.1371/journal.pcbi.1004749', '26967493', 'Treatment failure after therapy of pulmonary tuberculosis (TB) infections is an important challenge, especially when it coincides with de novo emergence of multi-drug-resistant TB (MDR-TB). We seek to explore possible causes why MDR-TB has been found to occur much more often in patients with a history of previous treatment. We develop a mathematical model of the replication of Mycobacterium tuberculosis within a patient reflecting the compartments of macrophages, granulomas, and open cavities as well as parameterizing the effects of drugs on the pathogen dynamics in these compartments. We use this model to study the influence of patient adherence to therapy and of common retreatment regimens on treatment outcome. As expected, the simulations show that treatment success increases with increasing adherence. However, treatment occasionally fails even under perfect adherence due to interpatient variability in pharmacological parameters. The risk of generating MDR de novo is highest between 40% and 80% adherence. Importantly, our simulations highlight the double-edged effect of retreatment: On the one hand, the recommended retreatment regimen increases the overall success rate compared to re-treating with the initial regimen. On the other hand, it increases the probability to accumulate more resistant genotypes. We conclude that treatment adherence is a key factor for a positive outcome, and that screening for resistant strains is advisable after treatment failure or relapse. '),
(87715, 2016, 'plos', 'Incomplete Lineage Sorting and Hybridization Statistics for Large-Scale Retroposon Insertion Data', 'Kuritzin, Andrej|Kischka, Tabea|Schmitz, Jürgen|Churakov, Gennady', 'Department of System Analysis, Saint Petersburg State Institute of Technology, St. Petersburg, Russia.|Institute of Experimental Pathology (ZMBE), University of Münster, Münster, Germany.|Institute of Experimental Pathology (ZMBE), University of Münster, Münster, Germany.|Institute of Experimental Pathology (ZMBE), University of Münster, Münster, Germany.', '-|Germany|Germany|Germany', 15, 'Algorithms|Base Sequence|Computer Simulation|DNA Transposable Elements|High-Throughput Nucleotide Sequencing|Hybridization, Genetic|Models, Genetic|Models, Statistical|Molecular Sequence Data|Mutagenesis, Insertional|Retroelements|Software', 'Journal Article', '10.1371/journal.pcbi.1004812', '26967525', 'Ancient retroposon insertions can be used as virtually homoplasy-free markers to reconstruct the phylogenetic history of species. Inherited, orthologous insertions in related species offer reliable signals of a common origin of the given species. One prerequisite for such a phylogenetically informative insertion is that the inserted element was fixed in the ancestral population before speciation, if not, polymorphically inserted elements may lead to random distributions of presence/absence states during speciation and possibly to apparently conflicting reconstructions of their ancestry. Fortunately, such misleading fixed cases are relatively rare but nevertheless, need to be considered. Here, we present novel, comprehensive statistical models applicable for (1) analyzing any pattern of rare genomic changes, (2) testing and differentiating conflicting phylogenetic reconstructions based on rare genomic changes caused by incomplete lineage sorting or/and ancestral hybridization, and (3) differentiating between search strategies involving genome information from one or several lineages. When the new statistics are applied, in non-conflicting cases a minimum of three elements present in both of two species and absent in a third group are considered significant support (p<0.05) for the branching of the third from the other two, if all three of the given species are screened equally for genome or experimental data. Five elements are necessary for significant support (p<0.05) if a diagnostic locus derived from only one of three species is screened, and no conflicting markers are detected. Most potentially conflicting patterns can be evaluated for their significance and ancestral hybridization can be distinguished from incomplete lineage sorting by considering symmetric or asymmetric distribution of rare genomic changes among possible tree configurations. Additionally, we provide an R-application to make the new KKSC insertion significance test available for the scientific community at http://retrogenomics.uni-muenster.de:3838/KKSC_significance_test/. '),
(87716, 2016, 'plos', 'Simulation and Theory of Antibody Binding to Crowded Antigen-Covered Surfaces', 'De Michele, Cristiano|De Los Rios, Paolo|Foffi, Giuseppe|Piazza, Francesco', 'Dipartimento di Fisica, Sapienza Università di Roma, Roma, Italy.|Institute of Theoretical Physics, Ecole Polytechnique Fédérale de Lausanne, Lausanne, Switzerland.|Laboratoire de Physique des Solides (LPS), UMR8502, Université Paris sud, Orsay, France.|Université dOrléans, Centre de Biophysique Moléculaire, CNRS-UPR4301, Orléans, France.', 'Italy|Switzerland|France|France', 21, 'Antigen-Antibody Complex|Antigen-Antibody Reactions|Binding Sites, Antibody|Computer Simulation|Immunoglobulin G|Models, Chemical|Models, Immunological|Protein Binding', 'Journal Article', '10.1371/journal.pcbi.1004752', '26967624', 'In this paper we introduce a fully flexible coarse-grained model of immunoglobulin G (IgG) antibodies parametrized directly on cryo-EM data and simulate the binding dynamics of many IgGs to antigens adsorbed on a surface at increasing densities. Moreover, we work out a theoretical model that allows to explain all the features observed in the simulations. Our combined computational and theoretical framework is in excellent agreement with surface-plasmon resonance data and allows us to establish a number of important results. (i) Internal flexibility is key to maximize bivalent binding, flexible IgGs being able to explore the surface with their second arm in search for an available hapten. This is made clear by the strongly reduced ability to bind with both arms displayed by artificial IgGs designed to rigidly keep a prescribed shape. (ii) The large size of IgGs is instrumental to keep neighboring molecules at a certain distance (surface repulsion), which essentially makes antigens within reach of the second Fab always unoccupied on average. (iii) One needs to account independently for the thermodynamic and geometric factors that regulate the binding equilibrium. The key geometrical parameters, besides excluded-volume repulsion, describe the screening of free haptens by neighboring bound antibodies. We prove that the thermodynamic parameters govern the low-antigen-concentration regime, while the surface screening and repulsion only affect the binding at high hapten densities. Importantly, we prove that screening effects are concealed in relative measures, such as the fraction of bivalently bound antibodies. Overall, our model provides a valuable, accurate theoretical paradigm beyond existing frameworks to interpret experimental profiles of antibodies binding to multi-valent surfaces of different sorts in many contexts. '),
(87717, 2016, 'plos', 'Correction: Antenna Mechanism of Length Control of Actin Cables', 'PLOS Computational Biology Staff', 'Université dOrléans, Centre de Biophysique Moléculaire, CNRS-UPR4301, Orléans, France.', 'France', 0, '-', 'Published Erratum', '10.1371/journal.pcbi.1004830', '26967653', '-'),
(87718, 2016, 'plos', 'Causal Inference for Spatial Constancy across Saccades', 'Atsma, Jeroen|Maij, Femke|Koppen, Mathieu|Irwin, David E|Medendorp, W Pieter', 'Radboud University, Donders Institute for Brain, Cognition and Behaviour, Nijmegen, The Netherlands.|Radboud University, Donders Institute for Brain, Cognition and Behaviour, Nijmegen, The Netherlands.|Radboud University, Donders Institute for Brain, Cognition and Behaviour, Nijmegen, The Netherlands.|University of Illinois at Urbana-Champaign, Department of Psychology, Champaign, Illinois, United States of America.|Radboud University, Donders Institute for Brain, Cognition and Behaviour, Nijmegen, The Netherlands.', 'Netherlands|Netherlands|Netherlands|United States|Netherlands', 19, 'Computer Simulation|Fixation, Ocular|Humans|Memory|Models, Neurological|Models, Statistical|Motion Perception|Pattern Recognition, Visual|Saccades|Spatio-Temporal Analysis', 'Journal Article', '10.1371/journal.pcbi.1004766', '26967730', 'Our ability to interact with the environment hinges on creating a stable visual world despite the continuous changes in retinal input. To achieve visual stability, the brain must distinguish the retinal image shifts caused by eye movements and shifts due to movements of the visual scene. This process appears not to be flawless: during saccades, we often fail to detect whether visual objects remain stable or move, which is called saccadic suppression of displacement (SSD). How does the brain evaluate the memorized information of the presaccadic scene and the actual visual feedback of the postsaccadic visual scene in the computations for visual stability? Using a SSD task, we test how participants localize the presaccadic position of the fixation target, the saccade target or a peripheral non-foveated target that was displaced parallel or orthogonal during a horizontal saccade, and subsequently viewed for three different durations. Results showed different localization errors of the three targets, depending on the viewing time of the postsaccadic stimulus and its spatial separation from the presaccadic location. We modeled the data through a Bayesian causal inference mechanism, in which at the trial level an optimal mixing of two possible strategies, integration vs. separation of the presaccadic memory and the postsaccadic sensory signals, is applied. Fits of this model generally outperformed other plausible decision strategies for producing SSD. Our findings suggest that humans exploit a Bayesian inference process with two causal structures to mediate visual stability. '),
(87719, 2016, 'plos', 'Correction: Inferring Neuronal Dynamics from Calcium Imaging Data Using Biophysical Models and Bayesian Inference', 'PLOS Computational Biology Staff', 'Radboud University, Donders Institute for Brain, Cognition and Behaviour, Nijmegen, The Netherlands.', 'Netherlands', 0, '-', 'Published Erratum', '10.1371/journal.pcbi.1004835', '26967739', '-'),
(87720, 2016, 'plos', 'Distinguishing Antimicrobial Models with Different Resistance Mechanisms via Population Pharmacodynamic Modeling', 'Jacobs, Matthieu|Grégoire, Nicolas|Couet, William|Bulitta, Jurgen B', 'INSERM U1070, Poitiers, France.|INSERM U1070, Poitiers, France.|INSERM U1070, Poitiers, France.|Center for Pharmacometrics and Systems Pharmacology, Department of Pharmaceutics, College of Pharmacy, University of Florida, Gainesville, Florida, United States of America.', 'France|France|France|United States', 18, 'Anti-Bacterial Agents|Bacteria|Computer Simulation|Dose-Response Relationship, Drug|Drug Resistance, Bacterial|Models, Biological|Models, Statistical|Pharmacokinetics', 'Comparative Study', '10.1371/journal.pcbi.1004782', '26967893', 'Semi-mechanistic pharmacokinetic-pharmacodynamic (PK-PD) modeling is increasingly used for antimicrobial drug development and optimization of dosage regimens, but systematic simulation-estimation studies to distinguish between competing PD models are lacking. This study compared the ability of static and dynamic in vitro infection models to distinguish between models with different resistance mechanisms and support accurate and precise parameter estimation. Monte Carlo simulations (MCS) were performed for models with one susceptible bacterial population without (M1) or with a resting stage (M2), a one population model with adaptive resistance (M5), models with pre-existing susceptible and resistant populations without (M3) or with (M4) inter-conversion, and a model with two pre-existing populations with adaptive resistance (M6). For each model, 200 datasets of the total bacterial population were simulated over 24h using static antibiotic concentrations (256-fold concentration range) or over 48h under dynamic conditions (dosing every 12h, elimination half-life: 1h). Twelve-hundred random datasets (each containing 20 curves for static or four curves for dynamic conditions) were generated by bootstrapping. Each dataset was estimated by all six models via population PD modeling to compare bias and precision. For M1 and M3, most parameter estimates were unbiased (<10%) and had good imprecision (<30%). However, parameters for adaptive resistance and inter-conversion for M2, M4, M5 and M6 had poor bias and large imprecision under static and dynamic conditions. For datasets that only contained viable counts of the total population, common statistical criteria and diagnostic plots did not support sound identification of the true resistance mechanism. Therefore, it seems advisable to quantify resistant bacteria and characterize their MICs and resistance mechanisms to support extended simulations and translate from in vitro experiments to animal infection models and ultimately patients. '),
(87721, 2016, 'plos', 'Elucidation of Genetic Interactions in the Yeast GATA-Factor Network Using Bayesian Model Selection', 'Milias-Argeitis, Andreas|Oliveira, Ana Paula|Gerosa, Luca|Falter, Laura|Sauer, Uwe|Lygeros, John', 'Department of Biosystems Science and Engineering, ETH Zurich, Basel, Switzerland.|Institute of Molecular Systems Biology, ETH Zurich, Zurich, Switzerland.|Institute of Molecular Systems Biology, ETH Zurich, Zurich, Switzerland.|Institute of Molecular Systems Biology, ETH Zurich, Zurich, Switzerland.|Institute of Molecular Systems Biology, ETH Zurich, Zurich, Switzerland.|Automatic Control Laboratory, ETH Zurich, Zurich, Switzerland.', 'Switzerland|Switzerland|Switzerland|Switzerland|Switzerland|Switzerland', 0, 'Bayes Theorem|Computer Simulation|GATA Transcription Factors|Gene Expression Regulation, Fungal|Models, Genetic|Models, Statistical|Nitrogen|Saccharomyces cerevisiae|Saccharomyces cerevisiae Proteins|Signal Transduction', 'Journal Article', '10.1371/journal.pcbi.1004784', '26967983', 'Understanding the structure and function of complex gene regulatory networks using classical genetic assays is an error-prone procedure that frequently generates ambiguous outcomes. Even some of the best-characterized gene networks contain interactions whose validity is not conclusively proven. Founded on dynamic experimental data, mechanistic mathematical models are able to offer detailed insights that would otherwise require prohibitively large numbers of genetic experiments. Here we attempt mechanistic modeling of the transcriptional network formed by the four GATA-factor proteins, a well-studied system of central importance for nitrogen-source regulation of transcription in the yeast Saccharomyces cerevisiae. To resolve ambiguities in the network organization, we encoded a set of five interactions hypothesized in the literature into a set of 32 mathematical models, and employed Bayesian model selection to identify the most plausible set of interactions based on dynamic gene expression data. The top-ranking model was validated on newly generated GFP reporter dynamic data and was subsequently used to gain a better understanding of how yeast cells organize their transcriptional response to dynamic changes of nitrogen sources. Our work constitutes a necessary and important step towards obtaining a holistic view of the yeast nitrogen regulation mechanisms, on the computational side, it provides a demonstration of how powerful Monte Carlo techniques can be creatively combined and used to address the great challenges of large-scale dynamical system inference. '),
(87722, 2016, 'plos', 'Estimation of Directed Effective Connectivity from fMRI Functional Connectivity Hints at Asymmetries of Cortical Connectome', 'Gilson, Matthieu|Moreno-Bote, Ruben|Ponce-Alvarez, Adrián|Ritter, Petra|Deco, Gustavo', 'Center for Brain Cognition, Dept of Technology and Information, Universitat Pompeu Fabra, Barcelona, Spain.|Research Unit, Parc Sanitari Sant Joan de Déu and Universitat de Barcelona, Esplugues de Llobregat, Barcelona, Spain.|Center for Brain Cognition, Dept of Technology and Information, Universitat Pompeu Fabra, Barcelona, Spain.|Minerva Research Group Brain Modes, Max Planck Institute for Human Cognitive and Brain Sciences, Leipzig, Germany.|Center for Brain Cognition, Dept of Technology and Information, Universitat Pompeu Fabra, Barcelona, Spain.', 'Spain|Spain|Spain|Germany|Spain', 48, 'Brain|Computer Simulation|Connectome|Humans|Image Interpretation, Computer-Assisted|Magnetic Resonance Imaging|Models, Neurological|Models, Statistical|Nerve Net|Spatio-Temporal Analysis', 'Journal Article', '10.1371/journal.pcbi.1004762', '26982185', 'The brain exhibits complex spatio-temporal patterns of activity. This phenomenon is governed by an interplay between the internal neural dynamics of cortical areas and their connectivity. Uncovering this complex relationship has raised much interest, both for theory and the interpretation of experimental data (e.g., fMRI recordings) using dynamical models. Here we focus on the so-called inverse problem: the inference of network parameters in a cortical model to reproduce empirically observed activity. Although it has received a lot of interest, recovering directed connectivity for large networks has been rather unsuccessful so far. The present study specifically addresses this point for a noise-diffusion network model. We develop a Lyapunov optimization that iteratively tunes the network connectivity in order to reproduce second-order moments of the node activity, or functional connectivity. We show theoretically and numerically that the use of covariances with both zero and non-zero time shifts is the key to infer directed connectivity. The first main theoretical finding is that an accurate estimation of the underlying network connectivity requires that the time shift for covariances is matched with the time constant of the dynamical system. In addition to the network connectivity, we also adjust the intrinsic noise received by each network node. The framework is applied to experimental fMRI data recorded for subjects at rest. Diffusion-weighted MRI data provide an estimate of anatomical connections, which is incorporated to constrain the cortical model. The empirical covariance structure is reproduced faithfully, especially its temporal component (i.e., time-shifted covariances) in addition to the spatial component that is usually the focus of studies. We find that the cortical interactions, referred to as effective connectivity, in the tuned model are not reciprocal. In particular, hubs are either receptors or feeders: they do not exhibit both strong incoming and outgoing connections. Our results sets a quantitative ground to explore the propagation of activity in the cortex. '),
(87723, 2016, 'plos', 'A Sensorimotor Model for Computing Intended Reach Trajectories', 'Üstün, Cevat', 'Division of Biology, California Institute of Technology, Pasadena, California, United States of America.', 'United States', 0, 'Anticipation, Psychological|Arm|Attention|Computer Simulation|Feedback, Sensory|Humans|Intention|Models, Neurological|Movement|Parietal Lobe|Psychomotor Performance|Sensorimotor Cortex', 'Journal Article', '10.1371/journal.pcbi.1004734', '26985662', 'The presumed role of the primate sensorimotor system is to transform reach targets from retinotopic to joint coordinates for producing motor output. However, the interpretation of neurophysiological data within this framework is ambiguous, and has led to the view that the underlying neural computation may lack a well-defined structure. Here, I consider a model of sensorimotor computation in which temporal as well as spatial transformations generate representations of desired limb trajectories, in visual coordinates. This computation is suggested by behavioral experiments, and its modular implementation makes predictions that are consistent with those observed in monkey posterior parietal cortex (PPC). In particular, the model provides a simple explanation for why PPC encodes reach targets in reference frames intermediate between the eye and hand, and further explains why these reference frames shift during movement. Representations in PPC are thus consistent with the orderly processing of information, provided we adopt the view that sensorimotor computation manipulates desired movement trajectories, and not desired movement endpoints. '),
(87724, 2016, 'plos', 'Systems Pharmacology and Rational Polypharmacy: Nitric Oxide-Cyclic GMP Signaling Pathway as an Illustrative Example and Derivation of the General Case', 'Garmaroudi, Farshid S|Handy, Diane E|Liu, Yang-Yu|Loscalzo, Joseph', 'Cardiovascular Division, Department of Medicine, Brigham and Womens Hospital and Harvard Medical School, Boston, Massachusetts, United States of America.|Cardiovascular Division, Department of Medicine, Brigham and Womens Hospital and Harvard Medical School, Boston, Massachusetts, United States of America.|Channing Division of Network Medicine, Department of Medicine, Brigham and Womens Hospital and Harvard Medical School, Boston, Massachusetts, United States of America.|Cardiovascular Division, Department of Medicine, Brigham and Womens Hospital and Harvard Medical School, Boston, Massachusetts, United States of America.', 'United States|United States|United States|United States', 7, 'Animals|Computer Simulation|Cyclic GMP|Dose-Response Relationship, Drug|Drug Evaluation, Preclinical|Drug Therapy, Computer-Assisted|Humans|Models, Biological|Nitric Oxide|Phosphodiesterase Inhibitors|Phosphoric Diester Hydrolases|Polypharmacy|Signal Transduction', 'Journal Article', '10.1371/journal.pcbi.1004822', '26985825', 'Impaired nitric oxide (NOxcbx99)-cyclic guanosine 3, 5-monophosphate (cGMP) signaling has been observed in many cardiovascular disorders, including heart failure and pulmonary arterial hypertension. There are several enzymatic determinants of cGMP levels in this pathway, including soluble guanylyl cyclase (sGC) itself, the NOxcbx99-activated form of sGC, and phosphodiesterase(s) (PDE). Therapies for some of these disorders with PDE inhibitors have been successful at increasing cGMP levels in both cardiac and vascular tissues. However, at the systems level, it is not clear whether perturbation of PDE alone, under oxidative stress, is the best approach for increasing cGMP levels as compared with perturbation of other potential pathway targets, either alone or in combination. Here, we develop a model-based approach to perturbing this pathway, focusing on single reactions, pairs of reactions, or trios of reactions as targets, then monitoring the theoretical effects of these interventions on cGMP levels. Single perturbations of all reaction steps within this pathway demonstrated that three reaction steps, including the oxidation of sGC, NOxcbx99 dissociation from sGC, and cGMP degradation by PDE, exerted a dominant influence on cGMP accumulation relative to other reaction steps. Furthermore, among all possible single, paired, and triple perturbations of this pathway, the combined perturbations of these three reaction steps had the greatest impact on cGMP accumulation. These computational findings were confirmed in cell-based experiments. We conclude that a combined perturbation of the oxidatively-impaired NOxcbx99-cGMP signaling pathway is a better approach to the restoration of cGMP levels as compared with corresponding individual perturbations. This approach may also yield improved therapeutic responses in other complex pharmacologically amenable pathways. '),
(87725, 2016, 'plos', 'Feedback, Lineages and Self-Organizing Morphogenesis', 'Kunche, Sameeran|Yan, Huaming|Calof, Anne L|Lowengrub, John S|Lander, Arthur D', 'Department of Biomedical Engineering, University of California, Irvine, Irvine, California, United States of America.|Center for Complex Biological Systems, University of California, Irvine, Irvine, California, United States of America.|Center for Complex Biological Systems, University of California, Irvine, Irvine, California, United States of America.|Department of Biomedical Engineering, University of California, Irvine, Irvine, California, United States of America.|Department of Biomedical Engineering, University of California, Irvine, Irvine, California, United States of America.', 'United States|United States|United States|United States|United States', 0, 'Animals|Cell Cycle Proteins|Cell Differentiation|Cell Lineage|Computer Simulation|Feedback, Physiological|Gene Expression Regulation, Developmental|Humans|Models, Biological|Morphogenesis|Signal Transduction|Stem Cells', 'Journal Article', '10.1371/journal.pcbi.1004814', '26989903', 'Feedback regulation of cell lineage progression plays an important role in tissue size homeostasis, but whether such feedback also plays an important role in tissue morphogenesis has yet to be explored. Here we use mathematical modeling to show that a particular feedback architecture in which both positive and negative diffusible signals act on stem and/or progenitor cells leads to the appearance of bistable or bi-modal growth behaviors, ultrasensitivity to external growth cues, local growth-driven budding, self-sustaining elongation, and the triggering of self-organization in the form of lamellar fingers. Such behaviors arise not through regulation of cell cycle speeds, but through the control of stem or progenitor self-renewal. Even though the spatial patterns that arise in this setting are the result of interactions between diffusible factors with antagonistic effects, morphogenesis is not the consequence of Turing-type instabilities. '),
(87726, 2016, 'plos', 'Persistence and Adaptation in Immunity: T Cells Balance the Extent and Thoroughness of Search', 'Fricke, G Matthew|Letendre, Kenneth A|Moses, Melanie E|Cannon, Judy L', 'Department of Computer Science, The University of New Mexico, Albuquerque, New Mexico, United States of America.|Department of Biology, The University of New Mexico, Albuquerque, New Mexico, United States of America.|Department of Computer Science, The University of New Mexico, Albuquerque, New Mexico, United States of America.|Department of Molecular Genetics and Microbiology, The University of New Mexico School of Medicine, Albuquerque, New Mexico, United States of America.', 'Mexico|Mexico|Mexico|Mexico', 24, 'Adaptation, Psychological|Adaptive Immunity|Animals|Cell Movement|Computer Simulation|Humans|Immunity, Innate|Lymph Nodes|Models, Immunological|Models, Statistical|T-Lymphocytes', 'Journal Article', '10.1371/journal.pcbi.1004818', '26990103', 'Effective search strategies have evolved in many biological systems, including the immune system. T cells are key effectors of the immune response, required for clearance of pathogenic infection. T cell activation requires that T cells encounter antigen-bearing dendritic cells within lymph nodes, thus, T cell search patterns within lymph nodes may be a crucial determinant of how quickly a T cell immune response can be initiated. Previous work suggests that T cell motion in the lymph node is similar to a Brownian random walk, however, no detailed analysis has definitively shown whether T cell movement is consistent with Brownian motion. Here, we provide a precise description of T cell motility in lymph nodes and a computational model that demonstrates how motility impacts T cell search efficiency. We find that both Brownian and Lévy walks fail to capture the complexity of T cell motion. Instead, T cell movement is better described as a correlated random walk with a heavy-tailed distribution of step lengths. Using computer simulations, we identify three distinct factors that contribute to increasing T cell search efficiency: 1) a lognormal distribution of step lengths, 2) motion that is directionally persistent over short time scales, and 3) heterogeneity in movement patterns. Furthermore, we show that T cells move differently in specific frequently visited locations that we call hotspots within lymph nodes, suggesting that T cells change their movement in response to the lymph node environment. Our results show that like foraging animals, T cells adapt to environmental cues, suggesting that adaption is a fundamental feature of biological search. '),
(87727, 2016, 'plos', 'Early Transcriptome Signatures from Immunized Mouse Dendritic Cells Predict Late Vaccine-Induced T-Cell Responses', 'Dérian, Nicolas|Bellier, Bertrand|Pham, Hang Phuong|Tsitoura, Eliza|Kazazi, Dorothea|Huret, Christophe|Mavromara, Penelope|Klatzmann, David|Six, Adrien', 'Sorbonne Universités, UPMC Univ Paris 06, UMRS 959, Immunology, Immunopathology, Immunotherapy, Paris, France.|Sorbonne Universités, UPMC Univ Paris 06, UMRS 959, Immunology, Immunopathology, Immunotherapy, Paris, France.|Sorbonne Universités, UPMC Univ Paris 06, UMRS 959, Immunology, Immunopathology, Immunotherapy, Paris, France.|Molecular Virology Laboratory, Hellenic Pasteur Institute, Athens, Greece.|Molecular Virology Laboratory, Hellenic Pasteur Institute, Athens, Greece.|Sorbonne Universités, UPMC Univ Paris 06, UMRS 959, Immunology, Immunopathology, Immunotherapy, Paris, France.|Molecular Virology Laboratory, Hellenic Pasteur Institute, Athens, Greece.|Sorbonne Universités, UPMC Univ Paris 06, UMRS 959, Immunology, Immunopathology, Immunotherapy, Paris, France.|Sorbonne Universités, UPMC Univ Paris 06, UMRS 959, Immunology, Immunopathology, Immunotherapy, Paris, France.', 'France|France|France|Greece|Greece|France|Greece|France|France', 0, 'Animals|Cells, Cultured|Dendritic Cells|Female|Immunity, Innate|Immunization|Lymphocyte Activation|Mice|Mice, Inbred C57BL|T-Lymphocytes|Transcriptome|Viral Vaccines', 'Journal Article', '10.1371/journal.pcbi.1004801', '26998760', 'Systems biology offers promising approaches for identifying response-specific signatures to vaccination and assessing their predictive value. Here, we designed a modelling strategy aiming to predict the quality of late T-cell responses after vaccination from early transcriptome analysis of dendritic cells. Using standardized staining with tetramer, we first quantified antigen-specific T-cell expansion 5 to 10 days after vaccination with one of a set of 41 different vaccine vectors all expressing the same antigen. Hierarchical clustering of the responses defined sets of high and low T cell response inducers. We then compared these responses with the transcriptome of splenic dendritic cells obtained 6 hours after vaccination with the same vectors and produced a random forest model capable of predicting the quality of the later antigen-specific T-cell expansion. The model also successfully predicted vector classification as low or strong T-cell response inducers of a novel set of vaccine vectors, based on the early transcriptome results obtained from spleen dendritic cells, whole spleen and even peripheral blood mononuclear cells. Finally, our model developed with mouse datasets also accurately predicted vaccine efficacy from literature-mined human datasets. '),
(87728, 2016, 'plos', 'Quantitative Analysis of Axonal Branch Dynamics in the Developing Nervous System', 'Chalmers, Kelsey|Kita, Elizabeth M|Scott, Ethan K|Goodhill, Geoffrey J', 'Queensland Brain Institute, The University of Queensland, Brisbane, Queensland, Australia.|Queensland Brain Institute, The University of Queensland, Brisbane, Queensland, Australia.|School of Biomedical Sciences, The University of Queensland, Brisbane, Queensland, Australia.|Queensland Brain Institute, The University of Queensland, Brisbane, Queensland, Australia.', 'Australia|Australia|Australia|Australia', 0, 'Animals|Computer Simulation|Connectome|Image Interpretation, Computer-Assisted|Models, Anatomic|Models, Neurological|Neurogenesis|Superior Colliculi|Time-Lapse Imaging|Zebrafish', 'Journal Article', '10.1371/journal.pcbi.1004813', '26998842', 'Branching is an important mechanism by which axons navigate to their targets during neural development. For instance, in the developing zebrafish retinotectal system, selective branching plays a critical role during both initial pathfinding and subsequent arborisation once the target zone has been reached. Here we show how quantitative methods can help extract new information from time-lapse imaging about the nature of the underlying branch dynamics. First, we introduce Dynamic Time Warping to this domain as a method for automatically matching branches between frames, replacing the effort required for manual matching. Second, we model branch dynamics as a birth-death process, i.e. a special case of a continuous-time Markov process. This reveals that the birth rate for branches from zebrafish retinotectal axons, as they navigate across the tectum, increased over time. We observed no significant change in the death rate for branches over this time period. However, blocking neuronal activity with TTX slightly increased the death rate, without a detectable change in the birth rate. Third, we show how the extraction of these rates allows computational simulations of branch dynamics whose statistics closely match the data. Together these results reveal new aspects of the biology of retinotectal pathfinding, and introduce computational techniques which are applicable to the study of axon branching more generally. '),
(87729, 2016, 'plos', 'A New Fiji-Based Algorithm That Systematically Quantifies Nine Synaptic Parameters Provides Insights into Drosophila NMJ Morphometry', 'Nijhof, Bonnie|Castells-Nobau, Anna|Wolf, Louis|Scheffer-de Gooyert, Jolanda M|Monedero, Ignacio|Torroja, Laura|Coromina, Lluis|van der Laak, Jeroen A W M|Schenck, Annette', 'Department of Human Genetics, Donders Institute for Brain, Cognition and Behaviour, Radboud University Medical Center, Nijmegen, the Netherlands.|Department of Human Genetics, Donders Institute for Brain, Cognition and Behaviour, Radboud University Medical Center, Nijmegen, the Netherlands.|Microscopical Imaging Centre (MIC), Radboud University Medical Center, Nijmegen, the Netherlands.|Department of Human Genetics, Donders Institute for Brain, Cognition and Behaviour, Radboud University Medical Center, Nijmegen, the Netherlands.|Department of Biology, Universidad Autónoma de Madrid, Madrid, Spain.|Department of Biology, Universidad Autónoma de Madrid, Madrid, Spain.|Research Group on Statistics, Econometrics and Health (GRECS) and CIBER of Epidemiology and Public Health (CIBERESP), University of Girona, Girona, Spain.|Department of Pathology, Radboud University Medical Center, Nijmegen, the Netherlands.|Department of Human Genetics, Donders Institute for Brain, Cognition and Behaviour, Radboud University Medical Center, Nijmegen, the Netherlands.', 'Netherlands|Netherlands|Netherlands|Netherlands|Spain|Spain|Spain|Netherlands|Netherlands', 11, 'Algorithms|Animals|Data Mining|Databases, Factual|Drosophila|Image Interpretation, Computer-Assisted|Models, Anatomic|Models, Neurological|Neuromuscular Junction', 'Journal Article', '10.1371/journal.pcbi.1004823', '26998933', 'The morphology of synapses is of central interest in neuroscience because of the intimate relation with synaptic efficacy. Two decades of gene manipulation studies in different animal models have revealed a repertoire of molecules that contribute to synapse development. However, since such studies often assessed only one, or at best a few, morphological features at a given synapse, it remained unaddressed how different structural aspects relate to one another. Furthermore, such focused and sometimes only qualitative approaches likely left many of the more subtle players unnoticed. Here, we present the image analysis algorithm Drosophila_NMJ_Morphometrics, available as a Fiji-compatible macro, for quantitative, accurate and objective synapse morphometry of the Drosophila larval neuromuscular junction (NMJ), a well-established glutamatergic model synapse. We developed this methodology for semi-automated multiparametric analyses of NMJ terminals immunolabeled for the commonly used markers Dlg1 and Brp and showed that it also works for Hrp, Csp and Syt. We demonstrate that gender, genetic background and identity of abdominal body segment consistently and significantly contribute to variability in our data, suggesting that controlling for these parameters is important to minimize variability in quantitative analyses. Correlation and principal component analyses (PCA) were performed to investigate which morphometric parameters are inter-dependent and which ones are regulated rather independently. Based on nine acquired parameters, we identified five morphometric groups: NMJ size, geometry, muscle size, number of NMJ islands and number of active zones. Based on our finding that the parameters of the first two principal components hardly correlated with each other, we suggest that different molecular processes underlie these two morphometric groups. Our study sets the stage for systems morphometry approaches at the well-studied Drosophila NMJ. '),
(87730, 2016, 'plos', 'Application of Rigidity Theory to the Thermostabilization of Lipase A from Bacillus subtilis', 'Rathi, Prakash Chandra|Fulton, Alexander|Jaeger, Karl-Erich|Gohlke, Holger', 'Institute for Pharmaceutical and Medicinal Chemistry, Department of Mathematics and Natural Sciences, Heinrich-Heine-University, Düsseldorf, Germany.|Institute of Molecular Enzyme Technology, Heinrich-Heine-University, Düsseldorf, Germany.|Institute of Molecular Enzyme Technology, Heinrich-Heine-University, Düsseldorf, Germany.|Institute for Pharmaceutical and Medicinal Chemistry, Department of Mathematics and Natural Sciences, Heinrich-Heine-University, Düsseldorf, Germany.', 'Germany|Germany|Germany|Germany', 0, 'Allosteric Site|Amino Acid Sequence|Amino Acid Substitution|Bacillus subtilis|Enzyme Activation|Enzyme Stability|Models, Chemical|Molecular Dynamics Simulation|Molecular Sequence Data|Protein Binding|Sterol Esterase|Temperature', 'Journal Article', '10.1371/journal.pcbi.1004754', '27003415', 'Protein thermostability is a crucial factor for biotechnological enzyme applications. Protein engineering studies aimed at improving thermostability have successfully applied both directed evolution and rational design. However, for rational approaches, the major challenge remains the prediction of mutation sites and optimal amino acid substitutions. Recently, we showed that such mutation sites can be identified as structural weak spots by rigidity theory-based thermal unfolding simulations of proteins. Here, we describe and validate a unique, ensemble-based, yet highly efficient strategy to predict optimal amino acid substitutions at structural weak spots for improving a proteins thermostability. For this, we exploit the fact that in the majority of cases an increased structural rigidity of the folded state has been found as the cause for thermostability. When applied prospectively to lipase A from Bacillus subtilis, we achieved both a high success rate (25% over all experimentally tested mutations, which raises to 60% if small-to-large residue mutations and mutations in the active site are excluded) in predicting significantly thermostabilized lipase variants and a remarkably large increase in those variants thermostability (up to 6.6°C) based on single amino acid mutations. When considering negative controls in addition and evaluating the performance of our approach as a binary classifier, the accuracy is 63% and increases to 83% if small-to-large residue mutations and mutations in the active site are excluded. The gain in precision (predictive value for increased thermostability) over random classification is 1.6-fold (2.4-fold). Furthermore, an increase in thermostability predicted by our approach significantly points to increased experimental thermostability (p < 0.05). These results suggest that our strategy is a valuable complement to existing methods for rational protein design aimed at improving thermostability. '),
(87731, 2016, 'plos', 'Inhibition as a Binary Switch for Excitatory Plasticity in Pyramidal Neurons', 'Wilmes, Katharina A|Sprekeler, Henning|Schreiber, Susanne', 'Department of Biology, Institute for Theoretical Biology, Humboldt-Universität zu Berlin, Berlin, Germany.|Bernstein Center for Computational Neuroscience, Berlin, Germany.|Department of Biology, Institute for Theoretical Biology, Humboldt-Universität zu Berlin, Berlin, Germany.', 'Germany|Germany|Germany', 0, 'Action Potentials|Animals|Calcium Signaling|Computer Simulation|Excitatory Postsynaptic Potentials|Humans|Models, Neurological|Nerve Net|Neural Inhibition|Pyramidal Cells', 'Journal Article', '10.1371/journal.pcbi.1004768', '27003565', 'Synaptic plasticity is thought to induce memory traces in the brain that are the foundation of learning. To ensure the stability of these traces in the presence of further learning, however, a regulation of plasticity appears beneficial. Here, we take up the recent suggestion that dendritic inhibition can switch plasticity of excitatory synapses on and off by gating backpropagating action potentials (bAPs) and calcium spikes, i.e., by gating the coincidence signals required for Hebbian forms of plasticity. We analyze temporal and spatial constraints of such a gating and investigate whether it is possible to suppress bAPs without a simultaneous annihilation of the forward-directed information flow via excitatory postsynaptic potentials (EPSPs). In a computational analysis of conductance-based multi-compartmental models, we demonstrate that a robust control of bAPs and calcium spikes is possible in an all-or-none manner, enabling a binary switch of coincidence signals and plasticity. The position of inhibitory synapses on the dendritic tree determines the spatial extent of the effect and allows a pathway-specific regulation of plasticity. With appropriate timing, EPSPs can still trigger somatic action potentials, although backpropagating signals are abolished. An annihilation of bAPs requires precisely timed inhibition, while the timing constraints are less stringent for distal calcium spikes. We further show that a wide-spread motif of local circuits-feedforward inhibition-is well suited to provide the temporal precision needed for the control of bAPs. Altogether, our model provides experimentally testable predictions and demonstrates that the inhibitory switch of plasticity can be a robust and attractive mechanism, hence assigning an additional function to the inhibitory elements of neuronal microcircuits beyond modulation of excitability. '),
(87732, 2016, 'plos', 'Noise Expands the Response Range of the Bacillus subtilis Competence Circuit', 'Mugler, Andrew|Kittisopikul, Mark|Hayden, Luke|Liu, Jintao|Wiggins, Chris H|Süel, Gürol M|Walczak, Aleksandra M', 'Department of Physics and Astronomy, Purdue University, West Lafayette, Indiana, United States of America.|Department of Biophysics, University of Texas Southwestern Medical Center, Dallas, Texas, United States of America.|Department of Physics and Astronomy, Purdue University, West Lafayette, Indiana, United States of America.|Division of Biological Sciences, University of California San Diego, California, United States of America.|Department of Applied Physics and Applied Mathematics, Columbia University, New York, New York, United States of America.|Division of Biological Sciences, University of California San Diego, California, United States of America.|Laboratoire de Physique Théorique, CNRS, Université Pierre et Marie Curie and École Normale Supérieure, Paris, France.', 'India|United States|India|United States|United States|United States|France', 0, 'Adaptation, Physiological|Bacillus subtilis|Bacterial Proteins|Computer Simulation|Gene Regulatory Networks|Genetic Fitness|Models, Genetic|Models, Statistical|Signal-To-Noise Ratio|Stress, Physiological', 'Journal Article', '10.1371/journal.pcbi.1004793', '27003682', 'Gene regulatory circuits must contend with intrinsic noise that arises due to finite numbers of proteins. While some circuits act to reduce this noise, others appear to exploit it. A striking example is the competence circuit in Bacillus subtilis, which exhibits much larger noise in the duration of its competence events than a synthetically constructed analog that performs the same function. Here, using stochastic modeling and fluorescence microscopy, we show that this larger noise allows cells to exit terminal phenotypic states, which expands the range of stress levels to which cells are responsive and leads to phenotypic heterogeneity at the population level. This is an important example of how noise confers a functional benefit in a genetic decision-making circuit. '),
(87733, 2016, 'plos', 'Correction: A Voltage-Based STDP Rule Combined with Fast BCM-Like Metaplasticity Accounts for LTP and Concurrent Heterosynaptic LTD in the Dentate Gyrus In Vivo', 'PLOS Computational Biology Staff', 'Laboratoire de Physique Théorique, CNRS, Université Pierre et Marie Curie and École Normale Supérieure, Paris, France.', 'France', 0, '-', 'Published Erratum', '10.1371/journal.pcbi.1004854', '27003803', '-'),
(87734, 2016, 'plos', 'Evolutionary Conserved Positions Define Protein Conformational Diversity', 'Saldaxc3xb1o, Tadeo E|Monzon, Alexander M|Parisi, Gustavo|Fernandez-Alberti, Sebastian', 'Universidad Nacional de Quilmes, Bernal, Argentina.|Universidad Nacional de Quilmes, Bernal, Argentina.|Universidad Nacional de Quilmes, Bernal, Argentina.|Universidad Nacional de Quilmes, Bernal, Argentina.', 'Argentina|Argentina|Argentina|Argentina', 13, 'Amino Acid Sequence|Amino Acid Substitution|Base Sequence|Binding Sites|Computer Simulation|Conserved Sequence|Evolution, Molecular|Genetic Variation|Models, Chemical|Models, Genetic|Models, Molecular|Molecular Sequence Data|Point Mutation|Protein Binding|Proteins|Sequence Analysis|Structure-Activity Relationship', 'Journal Article', '10.1371/journal.pcbi.1004775', '27008419', 'Conformational diversity of the native state plays a central role in modulating protein function. The selection paradigm sustains that different ligands shift the conformational equilibrium through their binding to highest-affinity conformers. Intramolecular vibrational dynamics associated to each conformation should guarantee conformational transitions, which due to its importance, could possibly be associated with evolutionary conserved traits. Normal mode analysis, based on a coarse-grained model of the protein, can provide the required information to explore these features. Herein, we present a novel procedure to identify key positions sustaining the conformational diversity associated to ligand binding. The method is applied to an adequate refined dataset of 188 paired protein structures in their bound and unbound forms. Firstly, normal modes most involved in the conformational change are selected according to their corresponding overlap with structural distortions introduced by ligand binding. The subspace defined by these modes is used to analyze the effect of simulated point mutations on preserving the conformational diversity of the protein. We find a negative correlation between the effects of mutations on these normal mode subspaces associated to ligand-binding and position-specific evolutionary conservations obtained from multiple sequence-structure alignments. Positions whose mutations are found to alter the most these subspaces are defined as key positions, that is, dynamically important residues that mediate the ligand-binding conformational change. These positions are shown to be evolutionary conserved, mostly buried aliphatic residues localized in regular structural regions of the protein like xcexb2-sheets and xcexb1-helix. ');
INSERT INTO `papers` (`id`, `ano`, `journal`, `titulo`, `autores`, `afiliacao`, `pais`, `citacoes`, `palavra_chave`, `categorias`, `doi`, `pubmed`, `abstract`) VALUES
(87735, 2016, 'plos', 'Revealing the True Incidence of Pandemic A(H1N1)pdm09 Influenza in Finland during the First Two Seasons - An Analysis Based on a Dynamic Transmission Model', 'Shubin, Mikhail|Lebedev, Artem|Lyytikäinen, Outi|Auranen, Kari', 'University of Helsinki, Helsinki, Finland.|Rybinsk State Aviation Technical University, Rybinsk, Russia.|National Institute for Health and Welfare, Helsinki, Finland.|National Institute for Health and Welfare, Helsinki, Finland.', 'Finland|-|Finland|Finland', 0, 'Adolescent|Adult|Age Distribution|Aged|Aged, 80 and over|Child|Child, Preschool|Computer Simulation|Data Interpretation, Statistical|Female|Finland|Humans|Incidence|Infant|Infant, Newborn|Influenza Vaccines|Influenza, Human|Male|Mass Vaccination|Middle Aged|Models, Statistical|Pandemics|Reproducibility of Results|Risk Assessment|Seasons|Sensitivity and Specificity|Sex Distribution|Young Adult', 'Journal Article', '10.1371/journal.pcbi.1004803', '27010206', 'The threat of the new pandemic influenza A(H1N1)pdm09 imposed a heavy burden on the public health system in Finland in 2009-2010. An extensive vaccination campaign was set up in the middle of the first pandemic season. However, the true number of infected individuals remains uncertain as the surveillance missed a large portion of mild infections. We constructed a transmission model to simulate the spread of influenza in the Finnish population. We used the model to analyse the two first years (2009-2011) of A(H1N1)pdm09 in Finland. Using data from the national surveillance of influenza and data on close person-to-person (social) contacts in the population, we estimated that 6% (90% credible interval 5.1 - 6.7%) of the population was infected with A(H1N1)pdm09 in the first pandemic season (2009/2010) and an additional 3% (2.5 - 3.5%) in the second season (2010/2011). Vaccination had a substantial impact in mitigating the second season. The dynamic approach allowed us to discover how the proportion of detected cases changed over the course of the epidemic. The role of time-varying reproduction number, capturing the effects of weather and changes in behaviour, was important in shaping the epidemic. '),
(87736, 2016, 'plos', 'Impaired Air Conditioning within the Nasal Cavity in Flat-Faced Homo', 'Nishimura, Takeshi|Mori, Futoshi|Hanida, Sho|Kumahata, Kiyoshi|Ishikawa, Shigeru|Samarat, Kaouthar|Miyabe-Nishiwaki, Takako|Hayashi, Misato|Tomonaga, Masaki|Suzuki, Juri|Matsuzawa, Tetsuro|Matsuzawa, Teruo', 'Primate Research Institute, Kyoto University, Inuyama, Aichi, Japan.|Institute for Biomedical Sciences, Iwate Medical University, Yahaba, Iwate, Japan.|Kanazawa Institute of Technology, Nonoichi, Ishikawa, Japan.|RIKEN Advanced Institute for Computational Science, Kobe, Hyogo, Japan.|Kanazawa Municipal Hospital, Kanazawa, Ishikawa, Japan.|Japan Advanced Institute of Science and Technology, Nomi, Ishikawa, Japan.|Primate Research Institute, Kyoto University, Inuyama, Aichi, Japan.|Primate Research Institute, Kyoto University, Inuyama, Aichi, Japan.|Primate Research Institute, Kyoto University, Inuyama, Aichi, Japan.|Primate Research Institute, Kyoto University, Inuyama, Aichi, Japan.|Primate Research Institute, Kyoto University, Inuyama, Aichi, Japan.|Japan Advanced Institute of Science and Technology, Nomi, Ishikawa, Japan.', 'Japan|Japan|Japan|Japan|Japan|Japan|Japan|Japan|Japan|Japan|Japan|Japan', 0, 'Air|Air Conditioning|Animals|Hominidae|Humans|Humidity|Inhalation|Macaca|Nasal Cavity|Pan troglodytes|Rheology|Species Specificity|Temperature', 'Comparative Study', '10.1371/journal.pcbi.1004807', '27010321', 'We are flat-faced hominins with an external nose that protrudes from the face. This feature was derived in the genus Homo, along with facial flattening and reorientation to form a high nasal cavity. The nasal passage conditions the inhaled air in terms of temperature and humidity to match the conditions required in the lung, and its anatomical variation is believed to be evolutionarily sensitive to the ambient atmospheric conditions of a given habitat. In this study, we used computational fluid dynamics (CFD) with three-dimensional topology models of the nasal passage under the same simulation conditions, to investigate air-conditioning performance in humans, chimpanzees, and macaques. The CFD simulation showed a horizontal straight flow of inhaled air in chimpanzees and macaques, contrasting with the upward and curved flow in humans. The inhaled air is conditioned poorly in humans compared with nonhuman primates. Virtual modifications to the human external nose topology, in which the nasal vestibule and valve are modified to resemble those of chimpanzees, change the airflow to be horizontal, but have little influence on the air-conditioning performance in humans. These findings suggest that morphological variation of the nasal passage topology was only weakly sensitive to the ambient atmosphere conditions, rather, the high nasal cavity in humans was formed simply by evolutionary facial reorganization in the divergence of Homo from the other hominin lineages, impairing the air-conditioning performance. Even though the inhaled air is not adjusted well within the nasal cavity in humans, it can be fully conditioned subsequently in the pharyngeal cavity, which is lengthened in the flat-faced Homo. Thus, the air-conditioning faculty in the nasal passages was probably impaired in early Homo members, although they have survived successfully under the fluctuating climate of the Plio-Pleistocene, and then they moved Out of Africa to explore the more severe climates of Eurasia. '),
(87737, 2016, 'plos', 'ISCBs Initial Reaction to The New England Journal of Medicine Editorial on Data Sharing', 'Berger, Bonnie|Gaasterland, Terry|Lengauer, Thomas|Orengo, Christine|Gaeta, Bruno|Markel, Scott|Valencia, Alfonso', 'International Society for Computational Biology, Inc. (ISCB).|International Society for Computational Biology, Inc. (ISCB).|International Society for Computational Biology, Inc. (ISCB).|International Society for Computational Biology, Inc. (ISCB).|International Society for Computational Biology, Inc. (ISCB).|International Society for Computational Biology, Inc. (ISCB).|International Society for Computational Biology, Inc. (ISCB).', '-|-|-|-|-|-|-', 0, 'Clinical Trials as Topic|Editorial Policies|Information Dissemination|New England|Periodicals as Topic', 'Journal Article', '10.1371/journal.pcbi.1004816', '27010398', '-'),
(87738, 2016, 'plos', 'Cellular Growth Arrest and Persistence from Enzyme Saturation', 'Ray, J Christian J|Wickersheim, Michelle L|Jalihal, Ameya P|Adeshina, Yusuf O|Cooper, Tim F|Balázsi, Gábor', 'The University of Texas MD Anderson Cancer Center, Department of Systems Biology, Houston, Texas, United States of America.|Department of Molecular Biosciences, University of Kansas, Lawrence, Kansas, United States of America.|Center for Computational Biology, University of Kansas, Lawrence, Kansas, United States of America.|Center for Computational Biology, University of Kansas, Lawrence, Kansas, United States of America.|Department of Biology and Biochemistry, University of Houston, Houston, Texas, United States of America.|The University of Texas MD Anderson Cancer Center, Department of Systems Biology, Houston, Texas, United States of America.', 'United States|United States|United States|United States|United States|United States', 7, 'Cell Cycle Checkpoints|Cell Proliferation|Computer Simulation|Enzyme Activation|Enzymes|Escherichia coli|Escherichia coli Proteins|Metabolic Clearance Rate|Models, Biological|Monosaccharide Transport Proteins|Symporters|beta-Galactosidase', 'Journal Article', '10.1371/journal.pcbi.1004825', '27010473', 'Metabolic efficiency depends on the balance between supply and demand of metabolites, which is sensitive to environmental and physiological fluctuations, or noise, causing shortages or surpluses in the metabolic pipeline. How cells can reliably optimize biomass production in the presence of metabolic fluctuations is a fundamental question that has not been fully answered. Here we use mathematical models to predict that enzyme saturation creates distinct regimes of cellular growth, including a phase of growth arrest resulting from toxicity of the metabolic process. Noise can drive entry of single cells into growth arrest while a fast-growing majority sustains the population. We confirmed these predictions by measuring the growth dynamics of Escherichia coli utilizing lactose as a sole carbon source. The predicted heterogeneous growth emerged at high lactose concentrations, and was associated with cell death and production of antibiotic-tolerant persister cells. These results suggest how metabolic networks may balance costs and benefits, with important implications for drug tolerance. '),
(87739, 2016, 'plos', 'Dynamic Allostery Mediated by a Conserved Tryptophan in the Tec Family Kinases', 'Chopra, Nikita|Wales, Thomas E|Joseph, Raji E|Boyken, Scott E|Engen, John R|Jernigan, Robert L|Andreotti, Amy H', 'Roy J. Carver Department of Biochemistry, Biophysics and Molecular Biology, Iowa State University, Ames, Iowa, United States of America.|Department of Chemistry and Chemical Biology, Northeastern University, Boston, Massachusetts, United States of America.|Roy J. Carver Department of Biochemistry, Biophysics and Molecular Biology, Iowa State University, Ames, Iowa, United States of America.|Department of Biochemistry, University of Washington, Seattle, Washington, United States of America.|Department of Chemistry and Chemical Biology, Northeastern University, Boston, Massachusetts, United States of America.|Roy J. Carver Department of Biochemistry, Biophysics and Molecular Biology, Iowa State University, Ames, Iowa, United States of America.|Roy J. Carver Department of Biochemistry, Biophysics and Molecular Biology, Iowa State University, Ames, Iowa, United States of America.', 'United States|United States|United States|United States|United States|United States|United States', 13, 'Agammaglobulinaemia Tyrosine Kinase|Allosteric Regulation|Allosteric Site|Amino Acid Sequence|Conserved Sequence|Enzyme Activation|Models, Chemical|Molecular Dynamics Simulation|Molecular Sequence Data|Motion|Protein Binding|Protein Conformation|Protein Structure, Tertiary|Protein-Tyrosine Kinases|Structure-Activity Relationship|Tryptophan', 'Journal Article', '10.1371/journal.pcbi.1004826', '27010561', 'Brutons tyrosine kinase (Btk) is a Tec family non-receptor tyrosine kinase that plays a critical role in immune signaling and is associated with the immunological disorder X-linked agammaglobulinemia (XLA). Our previous findings showed that the Tec kinases are allosterically activated by the adjacent N-terminal linker. A single tryptophan residue in the N-terminal 17-residue linker mediates allosteric activation, and its mutation to alanine leads to the complete loss of activity. Guided by hydrogen/deuterium exchange mass spectrometry results, we have employed Molecular Dynamics simulations, Principal Component Analysis, Community Analysis and measures of node centrality to understand the details of how a single tryptophan mediates allostery in Btk. A specific tryptophan side chain rotamer promotes the functional dynamic allostery by inducing coordinated motions that spread across the kinase domain. Either a shift in the rotamer population, or a loss of the tryptophan side chain by mutation, drastically changes the coordinated motions and dynamically isolates catalytically important regions of the kinase domain. This work also identifies a new set of residues in the Btk kinase domain with high node centrality values indicating their importance in transmission of dynamics essential for kinase activation. Structurally, these node residues appear in both lobes of the kinase domain. In the N-lobe, high centrality residues wrap around the ATP binding pocket connecting previously described Catalytic-spine residues. In the C-lobe, two high centrality node residues connect the base of the R- and C-spines on the xcexb1F-helix. We suggest that the bridging residues that connect the catalytic and regulatory architecture within the kinase domain may be a crucial element in transmitting information about regulatory spine assembly to the catalytic machinery of the catalytic spine and active site. '),
(87740, 2016, 'plos', 'Similarity in Shape Dictates Signature Intrinsic Dynamics Despite No Functional Conservation in TIM Barrel Enzymes', 'Tiwari, Sandhya P|Reuter, Nathalie', 'Department of Molecular Biology, University of Bergen, Pb. 7803, Bergen, Norway.|Department of Molecular Biology, University of Bergen, Pb. 7803, Bergen, Norway.', 'Norway|Norway', 0, 'Allosteric Regulation|Allosteric Site|Amino Acid Sequence|Catalysis|Computer Simulation|Conserved Sequence|Enzyme Activation|Models, Chemical|Models, Molecular|Molecular Sequence Data|Protein Binding|Sequence Analysis, Protein|Structure-Activity Relationship|Triose-Phosphate Isomerase', 'Journal Article', '10.1371/journal.pcbi.1004834', '27015412', 'The conservation of the intrinsic dynamics of proteins emerges as we attempt to understand the relationship between sequence, structure and functional conservation. We characterise the conservation of such dynamics in a case where the structure is conserved but function differs greatly. The triosephosphate isomerase barrel fold (TBF), renowned for its 8 xcexb2-strand-xcexb1-helix repeats that close to form a barrel, is one of the most diverse and abundant folds found in known protein structures. Proteins with this fold have diverse enzymatic functions spanning five of six Enzyme Commission classes, and we have picked five different superfamily candidates for our analysis using elastic network models. We find that the overall shape is a large determinant in the similarity of the intrinsic dynamics, regardless of function. In particular, the xcexb2-barrel core is highly rigid, while the xcexb1-helices that flank the xcexb2-strands have greater relative mobility, allowing for the many possibilities for placement of catalytic residues. We find that these elements correlate with each other via the loops that link them, as opposed to being directly correlated. We are also able to analyse the types of motions encoded by the normal mode vectors of the xcexb1-helices. We suggest that the global conservation of the intrinsic dynamics in the TBF contributes greatly to its success as an enzymatic scaffold both through evolution and enzyme design. '),
(87741, 2016, 'plos', 'Modeling the Excess Cell Surface Stored in a Complex Morphology of Bleb-Like Protrusions', 'Kapustina, Maryna|Tsygankov, Denis|Zhao, Jia|Wessler, Timothy|Yang, Xiaofeng|Chen, Alex|Roach, Nathan|Elston, Timothy C|Wang, Qi|Jacobson, Ken|Forest, M Gregory', 'Department of Cell Biology and Physiology, University of North Carolina School of Medicine, Chapel Hill, North Carolina, United States of America.|Wallace H. Coulter Department of Biomedical Engineering at Georgia Institute of Technology and Emory University, Atlanta, Georgia, United States of America.|Department of Mathematics, University of South Carolina, Columbia, South Carolina, United States of America.|Department of Mathematics, University of North Carolina at Chapel Hill, Chapel Hill, North Carolina, United States of America.|Department of Mathematics, University of South Carolina, Columbia, South Carolina, United States of America.|Department of Mathematics, University of North Carolina at Chapel Hill, Chapel Hill, North Carolina, United States of America.|Department of Cell Biology and Physiology, University of North Carolina School of Medicine, Chapel Hill, North Carolina, United States of America.|Department of Pharmacology, University of North Carolina School of Medicine, Chapel Hill, North Carolina, United States of America.|Department of Mathematics, University of South Carolina, Columbia, South Carolina, United States of America.|Department of Cell Biology and Physiology, University of North Carolina School of Medicine, Chapel Hill, North Carolina, United States of America.|Department of Mathematics, University of North Carolina at Chapel Hill, Chapel Hill, North Carolina, United States of America.', 'United States|Georgia|United States|United States|United States|United States|United States|United S', 17, 'Animals|CHO Cells|Cell Size|Cell Surface Extensions|Computer Simulation|Cricetulus|Membrane Fluidity|Models, Chemical|Models, Molecular', 'Journal Article', '10.1371/journal.pcbi.1004841', '27015526', 'Cells transition from spread to rounded morphologies in diverse physiological contexts including mitosis and mesenchymal-to-amoeboid transitions. When these drastic shape changes occur rapidly, cell volume and surface area are approximately conserved. Consequently, the rounded cells are suddenly presented with a several-fold excess of cell surface whose area far exceeds that of a smooth sphere enclosing the cell volume. This excess is stored in a population of bleb-like protrusions (BLiPs), whose size distribution is shown by electron micrographs to be skewed. We introduce three complementary models of rounded cell morphologies with a prescribed excess surface area. A 2D Hamiltonian model provides a mechanistic description of how discrete attachment points between the cell surface and cortex together with surface bending energy can generate a morphology that satisfies a prescribed excess area and BLiP number density. A 3D random seed-and-growth model simulates efficient packing of BLiPs over a primary rounded shape, demonstrating a pathway for skewed BLiP size distributions that recapitulate 3D morphologies. Finally, a phase field model (2D and 3D) posits energy-based constitutive laws for the cell membrane, nematic F-actin cortex, interior cytosol, and external aqueous medium. The cell surface is equipped with a spontaneous curvature function, a proxy for the cell surface-cortex couple, that is a priori unknown, which the model learns from the thin section transmission electron micrograph image (2D) or the seed and growth model image (3D). Converged phase field simulations predict self-consistent amplitudes and spatial localization of pressure and stress throughout the cell for any posited stationary morphology target and cell compartment constitutive properties. The models form a general framework for future studies of cell morphological dynamics in a variety of biological contexts. '),
(87742, 2016, 'plos', 'Deep Learning for Population Genetic Inference', 'Sheehan, Sara|Song, Yun S', 'Department of Computer Science, Smith College, Northampton, Massachusetts, United States of America.|Computer Science Division, UC Berkeley, Berkeley, California, United States of America.', 'United States|United States', 0, 'Animals|Drosophila melanogaster|Genetics, Population|Genomics|Machine Learning|Models, Genetic', 'Journal Article', '10.1371/journal.pcbi.1004845', '27018908', 'Given genomic variation data from multiple individuals, computing the likelihood of complex population genetic models is often infeasible. To circumvent this problem, we introduce a novel likelihood-free inference framework by applying deep learning, a powerful modern technique in machine learning. Deep learning makes use of multilayer neural networks to learn a feature-based function from the input (e.g., hundreds of correlated summary statistics of data) to the output (e.g., population genetic parameters of interest). We demonstrate that deep learning can be effectively employed for population genetic inference and learning informative features of data. As a concrete application, we focus on the challenging problem of jointly inferring natural selection and demography (in the form of a population size change history). Our method is able to separate the global nature of demography from the local nature of selection, without sequential steps for these two factors. Studying demography and selection jointly is motivated by Drosophila, where pervasive selection confounds demographic analysis. We apply our method to 197 African Drosophila melanogaster genomes from Zambia to infer both their overall demography, and regions of their genome under selection. We find many regions of the genome that have experienced hard sweeps, and fewer under selection on standing variation (soft sweep) or balancing selection. Interestingly, we find that soft sweeps and balancing selection occur more frequently closer to the centromere of each chromosome. In addition, our demographic inference suggests that previously estimated bottlenecks for African Drosophila melanogaster are too extreme. '),
(87743, 2016, 'plos', 'Structure-Based Sequence Alignment of the Transmembrane Domains of All Human GPCRs: Phylogenetic, Structural and Functional Implications', 'Cvicek, Vaclav|Goddard, William A|Abrol, Ravinder', 'Materials and Process Simulation Center, California Institute of Technology, Pasadena, California, United States of America.|Materials and Process Simulation Center, California Institute of Technology, Pasadena, California, United States of America.|Materials and Process Simulation Center, California Institute of Technology, Pasadena, California, United States of America.', 'United States|United States|United States', 0, 'Algorithms|Amino Acid Sequence|Computational Biology|Databases, Protein|Humans|Models, Molecular|Phylogeny|Protein Structure, Tertiary|Receptors, G-Protein-Coupled|Sequence Alignment|Sequence Analysis, Protein', 'Journal Article', '10.1371/journal.pcbi.1004805', '27028541', 'The understanding of G-protein coupled receptors (GPCRs) is undergoing a revolution due to increased information about their signaling and the experimental determination of structures for more than 25 receptors. The availability of at least one receptor structure for each of the GPCR classes, well separated in sequence space, enables an integrated superfamily-wide analysis to identify signatures involving the role of conserved residues, conserved contacts, and downstream signaling in the context of receptor structures. In this study, we align the transmembrane (TM) domains of all experimental GPCR structures to maximize the conserved inter-helical contacts. The resulting superfamily-wide GpcR Sequence-Structure (GRoSS) alignment of the TM domains for all human GPCR sequences is sufficient to generate a phylogenetic tree that correctly distinguishes all different GPCR classes, suggesting that the class-level differences in the GPCR superfamily are encoded at least partly in the TM domains. The inter-helical contacts conserved across all GPCR classes describe the evolutionarily conserved GPCR structural fold. The corresponding structural alignment of the inactive and active conformations, available for a few GPCRs, identifies activation hot-spot residues in the TM domains that get rewired upon activation. Many GPCR mutations, known to alter receptor signaling and cause disease, are located at these conserved contact and activation hot-spot residue positions. The GRoSS alignment places the chemosensory receptor subfamilies for bitter taste (TAS2R) and pheromones (Vomeronasal, VN1R) in the rhodopsin family, known to contain the chemosensory olfactory receptor subfamily. The GRoSS alignment also enables the quantification of the structural variability in the TM regions of experimental structures, useful for homology modeling and structure prediction of receptors. Furthermore, this alignment identifies structurally and functionally important residues in all human GPCRs. These residues can be used to make testable hypotheses about the structural basis of receptor function and about the molecular basis of disease-associated single nucleotide polymorphisms. '),
(87744, 2016, 'plos', 'Assessing Concordance of Drug-Induced Transcriptional Response in Rodent Liver and Cultured Hepatocytes', 'Sutherland, Jeffrey J|Jolly, Robert A|Goldstein, Keith M|Stevens, James L', 'Lilly Research Laboratories, Eli Lilly and Company, Indianapolis, Indiana, United States of America.|Lilly Research Laboratories, Eli Lilly and Company, Indianapolis, Indiana, United States of America.|Lilly Research Laboratories, Eli Lilly and Company, Indianapolis, Indiana, United States of America.|Lilly Research Laboratories, Eli Lilly and Company, Indianapolis, Indiana, United States of America.', 'India|India|India|India', 0, 'Animals|Azathioprine|Cells, Cultured|Gene Expression|Gene Expression Profiling|Hepatocytes|Liver|Male|Mice|Rats|Rats, Sprague-Dawley', 'Journal Article', '10.1371/journal.pcbi.1004847', '27028627', 'The effect of drugs, disease and other perturbations on mRNA levels are studied using gene expression microarrays or RNA-seq, with the goal of understanding molecular effects arising from the perturbation. Previous comparisons of reproducibility across laboratories have been limited in scale and focused on a single model. The use of model systems, such as cultured primary cells or cancer cell lines, assumes that mechanistic insights derived from the models would have been observed via in vivo studies. We examined the concordance of compound-induced transcriptional changes using data from several sources: rat liver and rat primary hepatocytes (RPH) from Drug Matrix (DM) and open TG-GATEs (TG), human primary hepatocytes (HPH) from TG, and mouse liver/HepG2 results from the Gene Expression Omnibus (GEO) repository. Gene expression changes for treatments were normalized to controls and analyzed with three methods: 1) gene level for 9071 high expression genes in rat liver, 2) gene set analysis (GSA) using canonical pathways and gene ontology sets, 3) weighted gene co-expression network analysis (WGCNA). Co-expression networks performed better than genes or GSA when comparing treatment effects within rat liver and rat vs. mouse liver. Genes and modules performed similarly at Connectivity Map-style analyses, where success at identifying similar treatments among a collection of reference profiles is the goal. Comparisons between rat liver and RPH, and those between RPH, HPH and HepG2 cells reveal lower concordance for all methods. We observe that the baseline state of untreated cultured cells relative to untreated rat liver shows striking similarity with toxicant-exposed cells in vivo, indicating that gross systems level perturbation in the underlying networks in culture may contribute to the low concordance.'),
(87745, 2016, 'plos', 'A Simple and Accurate Model to Predict Responses to Multi-electrode Stimulation in the Retina', 'Maturana, Matias I|Apollo, Nicholas V|Hadjinicolaou, Alex E|Garrett, David J|Cloherty, Shaun L|Kameneva, Tatiana|Grayden, David B|Ibbotson, Michael R|Meffin, Hamish', 'National Vision Research Institute, Australian College of Optometry, Carlton, Victoria, Australia.|Department of Physics, University of Melbourne, Parkville, Victoria, Australia.|National Vision Research Institute, Australian College of Optometry, Carlton, Victoria, Australia.|Department of Physics, University of Melbourne, Parkville, Victoria, Australia.|National Vision Research Institute, Australian College of Optometry, Carlton, Victoria, Australia.|Department of Electrical and Electronic Engineering, NeuroEngineering Laboratory, University of Melbourne, Parkville, Victoria, Australia.|Department of Electrical and Electronic Engineering, NeuroEngineering Laboratory, University of Melbourne, Parkville, Victoria, Australia.|National Vision Research Institute, Australian College of Optometry, Carlton, Victoria, Australia.|National Vision Research Institute, Australian College of Optometry, Carlton, Victoria, Australia.', 'Australia|Australia|Australia|Australia|Australia|Australia|Australia|Australia|Australia', 18, 'Action Potentials|Animals|Computational Biology|In Vitro Techniques|Linear Models|Models, Neurological|Neural Prostheses|Nonlinear Dynamics|Principal Component Analysis|Prosthesis Design|Rats|Rats, Long-Evans|Retina|Retinal Ganglion Cells', 'Journal Article', '10.1371/journal.pcbi.1004849', '27035143', 'Implantable electrode arrays are widely used in therapeutic stimulation of the nervous system (e.g. cochlear, retinal, and cortical implants). Currently, most neural prostheses use serial stimulation (i.e. one electrode at a time) despite this severely limiting the repertoire of stimuli that can be applied. Methods to reliably predict the outcome of multi-electrode stimulation have not been available. Here, we demonstrate that a linear-nonlinear model accurately predicts neural responses to arbitrary patterns of stimulation using in vitro recordings from single retinal ganglion cells (RGCs) stimulated with a subretinal multi-electrode array. In the model, the stimulus is projected onto a low-dimensional subspace and then undergoes a nonlinear transformation to produce an estimate of spiking probability. The low-dimensional subspace is estimated using principal components analysis, which gives the neurons electrical receptive field (ERF), i.e. the electrodes to which the neuron is most sensitive. Our model suggests that stimulation proportional to the ERF yields a higher efficacy given a fixed amount of power when compared to equal amplitude stimulation on up to three electrodes. We find that the model captures the responses of all the cells recorded in the study, suggesting that it will generalize to most cell types in the retina. The model is computationally efficient to evaluate and, therefore, appropriate for future real-time applications including stimulation strategies that make use of recorded neural activity to improve the stimulation strategy. '),
(87746, 2016, 'plos', 'A Well-Defined Readily Releasable Pool with Fixed Capacity for Storing Vesicles at Calyx of Held', 'Mahfooz, Kashif|Singh, Mahendra|Renden, Robert|Wesseling, John F', 'Department Neurociencias (CIMA), Universidad de Navarra, Pamplona, Spain.|Department of Physiology & Cell Biology, University of Nevada School of Medicine, Reno, Nevada, United States of America.|Department of Physiology & Cell Biology, University of Nevada School of Medicine, Reno, Nevada, United States of America.|Department Neurociencias (CIMA), Universidad de Navarra, Pamplona, Spain.', 'Spain|United States|United States|Spain', 8, 'Animals|Auditory Pathways|Calcium|Cochlear Nucleus|Computational Biology|Computer Simulation|Electric Stimulation|Excitatory Postsynaptic Potentials|Female|Male|Mice|Mice, Inbred C57BL|Models, Neurological|Neuronal Plasticity|Presynaptic Terminals|Synaptic Vesicles|Trapezoid Body', 'Journal Article', '10.1371/journal.pcbi.1004855', '27035349', 'The readily releasable pool (RRP) of vesicles is a core concept in studies of presynaptic function. However, operating principles lack consensus definition and the utility for quantitative analysis has been questioned. Here we confirm that RRPs at calyces of Held from 14 to 21 day old mice have a fixed capacity for storing vesicles that is not modulated by Ca2+. Discrepancies with previous studies are explained by a dynamic flow-through pool, established during heavy use, containing vesicles that are released with low probability despite being immediately releasable. Quantitative analysis ruled out a posteriori explanations for the vesicles with low release probability, such as Ca2+-channel inactivation, and established unexpected boundary conditions for remaining alternatives. Vesicles in the flow-through pool could be incompletely primed, in which case the full sequence of priming steps downstream of recruitment to the RRP would have an average unitary rate of at least 9/s during heavy use. Alternatively, vesicles with low and high release probability could be recruited to distinct types of release sites, in this case the timing of recruitment would be similar at the two types, and the downstream transition from recruited to fully primed would be much faster. In either case, further analysis showed that activity accelerates the upstream step where vesicles are initially recruited to the RRP. Overall, our results show that the RRP can be well defined in the mathematical sense, and support the concept that the defining mechanism is a stable group of autonomous release sites. '),
(87747, 2016, 'plos', 'Exploiting Gene-Expression Deconvolution to Probe the Genetics of the Immune System', 'Steuerman, Yael|Gat-Viks, Irit', 'Department of Cell Research and Immunology, George S. Wise Faculty of Life Sciences, Tel Aviv University, Tel Aviv, Israel.|Department of Cell Research and Immunology, George S. Wise Faculty of Life Sciences, Tel Aviv University, Tel Aviv, Israel.', 'Israel|Israel', 5, 'Algorithms|Animals|Computational Biology|Gene Expression|Genetic Markers|Genotype|Humans|Immune System|Killer Cells, Natural|Lung|Mice|Models, Genetic|Models, Immunological|Quantitative Trait Loci|Transcriptome', 'Journal Article', '10.1371/journal.pcbi.1004856', '27035464', 'Sequence variation can affect the physiological state of the immune system. Major experimental efforts targeted at understanding the genetic control of the abundance of immune cell subpopulations. However, these studies are typically focused on a limited number of immune cell types, mainly due to the use of relatively low throughput cell-sorting technologies. Here we present an algorithm that can reveal the genetic basis of inter-individual variation in the abundance of immune cell types using only gene expression and genotyping measurements as input. Our algorithm predicts the abundance of immune cell subpopulations based on the RNA levels of informative marker genes within a complex tissue, and then provides the genetic control on these predicted immune traits as output. A key feature of the approach is the integration of predictions from various sets of marker genes and refinement of these sets to avoid spurious signals. Our evaluation of both synthetic and real biological data shows the significant benefits of the new approach. Our method, VoCAL, is implemented in the freely available R package ComICS. '),
(87748, 2016, 'plos', 'Sensory Agreement Guides Kinetic Energy Optimization of Arm Movements during Object Manipulation', 'Farshchiansadegh, Ali|Melendez-Calderon, Alejandro|Ranganathan, Rajiv|Murphey, Todd D|Mussa-Ivaldi, Ferdinando A', 'Sensory Motor Performance Program, Rehabilitation Institute of Chicago, Chicago, Illinois, United States of America.|Sensory Motor Performance Program, Rehabilitation Institute of Chicago, Chicago, Illinois, United States of America.|Department of Kinesiology, Michigan State University, East Lansing, Michigan, United States of America.|Department of Mechanical Engineering, Northwestern University, Evanston, Illinois, United States of America.|Sensory Motor Performance Program, Rehabilitation Institute of Chicago, Chicago, Illinois, United States of America.', 'United States|United States|United States|United States|United States', 11, 'Arm|Biomechanical Phenomena|Computational Biology|Energy Metabolism|Feedback, Physiological|Female|Humans|Kinetics|Male|Movement|Psychomotor Performance|User-Computer Interface', 'Journal Article', '10.1371/journal.pcbi.1004861', '27035587', 'The laws of physics establish the energetic efficiency of our movements. In some cases, like locomotion, the mechanics of the body dominate in determining the energetically optimal course of action. In other tasks, such as manipulation, energetic costs depend critically upon the variable properties of objects in the environment. Can the brain identify and follow energy-optimal motions when these motions require moving along unfamiliar trajectories? What feedback information is required for such optimal behavior to occur? To answer these questions, we asked participants to move their dominant hand between different positions while holding a virtual mechanical system with complex dynamics (a planar double pendulum). In this task, trajectories of minimum kinetic energy were along curvilinear paths. Our findings demonstrate that participants were capable of finding the energy-optimal paths, but only when provided with veridical visual and haptic information pertaining to the object, lacking which the trajectories were executed along rectilinear paths. '),
(87749, 2016, 'plos', 'Robust Brain-Machine Interface Design Using Optimal Feedback Control Modeling and Adaptive Point Process Filtering', 'Shanechi, Maryam M|Orsborn, Amy L|Carmena, Jose M', 'Department of Electrical Engineering, Viterbi School of Engineering, University of Southern California, Los Angeles, California, United States of America.|University of California, Berkeley-University of California, San Francisco Graduate Group in Bioengineering, San Francisco, California, United States of America.|Department of Electrical Engineering and Computer Sciences, University of California, Berkeley, Berkeley, California, United States of America.', 'United States|United States|United States', 52, 'Action Potentials|Adaptation, Physiological|Animals|Behavior, Animal|Biomechanical Phenomena|Brain-Computer Interfaces|Computational Biology|Computer Simulation|Feedback, Sensory|Humans|Macaca mulatta|Male|Models, Neurological|Motor Cortex|Software Design|Task Performance and Analysis', 'Journal Article', '10.1371/journal.pcbi.1004730', '27035820', 'Much progress has been made in brain-machine interfaces (BMI) using decoders such as Kalman filters and finding their parameters with closed-loop decoder adaptation (CLDA). However, current decoders do not model the spikes directly, and hence may limit the processing time-scale of BMI control and adaptation. Moreover, while specialized CLDA techniques for intention estimation and assisted training exist, a unified and systematic CLDA framework that generalizes across different setups is lacking. Here we develop a novel closed-loop BMI training architecture that allows for processing, control, and adaptation using spike events, enables robust control and extends to various tasks. Moreover, we develop a unified control-theoretic CLDA framework within which intention estimation, assisted training, and adaptation are performed. The architecture incorporates an infinite-horizon optimal feedback-control (OFC) model of the brains behavior in closed-loop BMI control, and a point process model of spikes. The OFC model infers the users motor intention during CLDA-a process termed intention estimation. OFC is also used to design an autonomous and dynamic assisted training technique. The point process model allows for neural processing, control and decoder adaptation with every spike event and at a faster time-scale than current decoders, it also enables dynamic spike-event-based parameter adaptation unlike current CLDA methods that use batch-based adaptation on much slower adaptation time-scales. We conducted closed-loop experiments in a non-human primate over tens of days to dissociate the effects of these novel CLDA components. The OFC intention estimation improved BMI performance compared with current intention estimation techniques. OFC assisted training allowed the subject to consistently achieve proficient control. Spike-event-based adaptation resulted in faster and more consistent performance convergence compared with batch-based methods, and was robust to parameter initialization. Finally, the architecture extended control to tasks beyond those used for CLDA training. These results have significant implications towards the development of clinically-viable neuroprosthetics. '),
(87750, 2016, 'plos', 'HER2+ Cancer Cell Dependence on PI3K vs MAPK Signaling Axes Is Determined by Expression of EGFR, ERBB3 and CDKN1B', 'Kirouac, Daniel C|Du, Jinyan|Lahdenranta, Johanna|Onsum, Matthew D|Nielsen, Ulrik B|Schoeberl, Birgit|McDonagh, Charlotte F', 'Discovery, Merrimack Pharmaceuticals, Cambridge, Massachusetts, United States of America.|Discovery, Merrimack Pharmaceuticals, Cambridge, Massachusetts, United States of America.|Discovery, Merrimack Pharmaceuticals, Cambridge, Massachusetts, United States of America.|Discovery, Merrimack Pharmaceuticals, Cambridge, Massachusetts, United States of America.|Discovery, Merrimack Pharmaceuticals, Cambridge, Massachusetts, United States of America.|Discovery, Merrimack Pharmaceuticals, Cambridge, Massachusetts, United States of America.|Discovery, Merrimack Pharmaceuticals, Cambridge, Massachusetts, United States of America.', 'United States|United States|United States|United States|United States|United States|United States', 14, 'Biomarkers, Tumor|Breast Neoplasms|Cell Line, Tumor|Computational Biology|Cyclin-Dependent Kinase Inhibitor p27|ErbB Receptors|Female|Gene Knockdown Techniques|Genes, erbB-2|Humans|MAP Kinase Signaling System|Mutation|Neoplasms|Phosphatidylinositol 3-Kinases|RNA, Messenger|RNA, Neoplasm|Receptor, ErbB-2|Receptor, ErbB-3', 'Journal Article', '10.1371/journal.pcbi.1004827', '27035903', 'Understanding the molecular pathways by which oncogenes drive cancerous cell growth, and how dependence on such pathways varies between tumors could be highly valuable for the design of anti-cancer treatment strategies. In this work we study how dependence upon the canonical PI3K and MAPK cascades varies across HER2+ cancers, and define biomarkers predictive of pathway dependencies. A panel of 18 HER2+ (ERBB2-amplified) cell lines representing a variety of indications was used to characterize the functional and molecular diversity within this oncogene-defined cancer. PI3K and MAPK-pathway dependencies were quantified by measuring in vitro cell growth responses to combinations of AKT (MK2206) and MEK (GSK1120212, trametinib) inhibitors, in the presence and absence of the ERBB3 ligand heregulin (NRG1). A combination of three protein measurements comprising the receptors EGFR, ERBB3 (HER3), and the cyclin-dependent kinase inhibitor p27 (CDKN1B) was found to accurately predict dependence on PI3K/AKT vs. MAPK/ERK signaling axes. Notably, this multivariate classifier outperformed the more intuitive and clinically employed metrics, such as expression of phospho-AKT and phospho-ERK, and PI3K pathway mutations (PIK3CA, PTEN, and PIK3R1). In both cell lines and primary patient samples, we observed consistent expression patterns of these biomarkers varies by cancer indication, such that ERBB3 and CDKN1B expression are relatively high in breast tumors while EGFR expression is relatively high in other indications. The predictability of the three protein biomarkers for differentiating PI3K/AKT vs. MAPK dependence in HER2+ cancers was confirmed using external datasets (Project Achilles and GDSC), again out-performing clinically used genetic markers. Measurement of this minimal set of three protein biomarkers could thus inform treatment, and predict mechanisms of drug resistance in HER2+ cancers. More generally, our results show a single oncogenic transformation can have differing effects on cell signaling and growth, contingent upon the molecular and cellular context. '),
(87751, 2016, 'plos', 'Identifying Malaria Transmission Foci for Elimination Using Human Mobility Data', 'Ruktanonchai, Nick W|DeLeenheer, Patrick|Tatem, Andrew J|Alegana, Victor A|Caughlin, T Trevor|Zu Erbach-Schoenberg, Elisabeth|Lourenço, Christopher|Ruktanonchai, Corrine W|Smith, David L', 'WorldPop Project, Geography and Environment, University of Southampton, Southampton, United Kingdom.|Department of Mathematics, Oregon State University, Corvallis, Oregon, United States of America.|WorldPop Project, Geography and Environment, University of Southampton, Southampton, United Kingdom.|WorldPop Project, Geography and Environment, University of Southampton, Southampton, United Kingdom.|School of Forest Resources and Conservation, Gainesville, Florida, United States of America.|WorldPop Project, Geography and Environment, University of Southampton, Southampton, United Kingdom.|WorldPop Project, Geography and Environment, University of Southampton, Southampton, United Kingdom.|WorldPop Project, Geography and Environment, University of Southampton, Southampton, United Kingdom.|Institute for Health Metrics and Evaluation, University of Washington, Seattle, Washington, United States of America.', 'United Kingdom|United States|United Kingdom|United Kingdom|United States|United Kingdom|United Kingd', 55, 'Cell Phone|Computational Biology|Data Interpretation, Statistical|Human Migration|Humans|Malaria|Models, Biological|Namibia|Prevalence', 'Journal Article', '10.1371/journal.pcbi.1004846', '27043913', 'Humans move frequently and tend to carry parasites among areas with endemic malaria and into areas where local transmission is unsustainable. Human-mediated parasite mobility can thus sustain parasite populations in areas where they would otherwise be absent. Data describing human mobility and malaria epidemiology can help classify landscapes into parasite demographic sources and sinks, ecological concepts that have parallels in malaria control discussions of transmission foci. By linking transmission to parasite flow, it is possible to stratify landscapes for malaria control and elimination, as sources are disproportionately important to the regional persistence of malaria parasites. Here, we identify putative malaria sources and sinks for pre-elimination Namibia using malaria parasite rate (PR) maps and call data records from mobile phones, using a steady-state analysis of a malaria transmission model to infer where infections most likely occurred. We also examined how the landscape of transmission and burden changed from the pre-elimination setting by comparing the location and extent of predicted pre-elimination transmission foci with modeled incidence for 2009. This comparison suggests that while transmission was spatially focal pre-elimination, the spatial distribution of cases changed as burden declined. The changing spatial distribution of burden could be due to importation, with cases focused around importation hotspots, or due to heterogeneous application of elimination effort. While this framework is an important step towards understanding progressive changes in malaria distribution and the role of subnational transmission dynamics in a policy-relevant way, future work should account for international parasite movement, utilize real time surveillance data, and relax the steady state assumption required by the presented model. '),
(87752, 2016, 'plos', 'Detecting Presymptomatic Infection Is Necessary to Forecast Major Epidemics in the Earliest Stages of Infectious Disease Outbreaks', 'Thompson, Robin N|Gilligan, Christopher A|Cunniffe, Nik J', 'Department of Plant Sciences, University of Cambridge, Cambridge, United Kingdom.|Department of Plant Sciences, University of Cambridge, Cambridge, United Kingdom.|Department of Plant Sciences, University of Cambridge, Cambridge, United Kingdom.', 'United Kingdom|United Kingdom|United Kingdom', 30, 'Communicable Diseases, Emerging|Computational Biology|Diagnostic Tests, Routine|Disease Outbreaks|Early Diagnosis|Epidemics|Forecasting|Hemorrhagic Fever, Ebola|Humans|Models, Biological|Models, Statistical|Probability|Stochastic Processes', 'Journal Article', '10.1371/journal.pcbi.1004836', '27046030', 'We assess how presymptomatic infection affects predictability of infectious disease epidemics. We focus on whether or not a major outbreak (i.e. an epidemic that will go on to infect a large number of individuals) can be predicted reliably soon after initial cases of disease have appeared within a population. For emerging epidemics, significant time and effort is spent recording symptomatic cases. Scientific attention has often focused on improving statistical methodologies to estimate disease transmission parameters from these data. Here we show that, even if symptomatic cases are recorded perfectly, and disease spread parameters are estimated exactly, it is impossible to estimate the probability of a major outbreak without ambiguity. Our results therefore provide an upper bound on the accuracy of forecasts of major outbreaks that are constructed using data on symptomatic cases alone. Accurate prediction of whether or not an epidemic will occur requires records of symptomatic individuals to be supplemented with data concerning the true infection status of apparently uninfected individuals. To forecast likely future behavior in the earliest stages of an emerging outbreak, it is therefore vital to develop and deploy accurate diagnostic tests that can determine whether asymptomatic individuals are actually uninfected, or instead are infected but just do not yet show detectable symptoms. ');
INSERT INTO `papers` (`id`, `ano`, `journal`, `titulo`, `autores`, `afiliacao`, `pais`, `citacoes`, `palavra_chave`, `categorias`, `doi`, `pubmed`, `abstract`) VALUES
(87753, 2016, 'plos', 'Learning Pitch with STDP: A Computational Model of Place and Temporal Pitch Perception Using Spiking Neural Networks', 'Erfanian Saeedi, Nafise|Blamey, Peter J|Burkitt, Anthony N|Grayden, David B', 'NeuroEngineering Laboratory, Department of Electrical and Electronic Engineering, University of Melbourne, Melbourne, Victoria, Australia.|The Bionics Institute, East Melbourne, Victoria, Australia.|NeuroEngineering Laboratory, Department of Electrical and Electronic Engineering, University of Melbourne, Melbourne, Victoria, Australia.|NeuroEngineering Laboratory, Department of Electrical and Electronic Engineering, University of Melbourne, Melbourne, Victoria, Australia.', 'Australia|Australia|Australia|Australia', 8, 'Acoustic Stimulation|Action Potentials|Auditory Pathways|Biophysical Phenomena|Cochlear Implants|Computational Biology|Computer Simulation|Humans|Learning|Models, Neurological|Nerve Net|Neural Networks (Computer)|Pitch Perception|Time Perception', 'Journal Article', '10.1371/journal.pcbi.1004860', '27049657', 'Pitch perception is important for understanding speech prosody, music perception, recognizing tones in tonal languages, and perceiving speech in noisy environments. The two principal pitch perception theories consider the place of maximum neural excitation along the auditory nerve and the temporal pattern of the auditory neurons action potentials (spikes) as pitch cues. This paper describes a biophysical mechanism by which fine-structure temporal information can be extracted from the spikes generated at the auditory periphery. Deriving meaningful pitch-related information from spike times requires neural structures specialized in capturing synchronous or correlated activity from amongst neural events. The emergence of such pitch-processing neural mechanisms is described through a computational model of auditory processing. Simulation results show that a correlation-based, unsupervised, spike-based form of Hebbian learning can explain the development of neural structures required for recognizing the pitch of simple and complex tones, with or without the fundamental frequency. The temporal code is robust to variations in the spectral shape of the signal and thus can explain the phenomenon of pitch constancy. '),
(87754, 2016, 'plos', 'Cache Domains That are Homologous to, but Different from PAS Domains Comprise the Largest Superfamily of Extracellular Sensors in Prokaryotes', 'Upadhyay, Amit A|Fleetwood, Aaron D|Adebali, Ogun|Finn, Robert D|Zhulin, Igor B', 'Genome Science and Technology Graduate Program, University of Tennessee-Oak Ridge National Laboratory, Knoxville, Tennessee, United States of America.|Department of Microbiology, University of Tennessee, Knoxville, Tennessee, United States of America.|Genome Science and Technology Graduate Program, University of Tennessee-Oak Ridge National Laboratory, Knoxville, Tennessee, United States of America.|European Molecular Biology Laboratory, European Bioinformatics Institute, Wellcome Trust Genome Campus, Hinxton, Cambridge, United Kingdom.|Genome Science and Technology Graduate Program, University of Tennessee-Oak Ridge National Laboratory, Knoxville, Tennessee, United States of America.', 'United States|United States|United States|United Kingdom|United States', 54, 'Algorithms|Archaeal Proteins|Bacterial Proteins|Computational Biology|Evolution, Molecular|Markov Chains|Models, Molecular|Phylogeny|Prokaryotic Cells|Protein Structure, Tertiary|Receptors, Cell Surface|Signal Transduction', 'Journal Article', '10.1371/journal.pcbi.1004862', '27049771', 'Cellular receptors usually contain a designated sensory domain that recognizes the signal. Per/Arnt/Sim (PAS) domains are ubiquitous sensors in thousands of species ranging from bacteria to humans. Although PAS domains were described as intracellular sensors, recent structural studies revealed PAS-like domains in extracytoplasmic regions in several transmembrane receptors. However, these structurally defined extracellular PAS-like domains do not match sequence-derived PAS domain models, and thus their distribution across the genomic landscape remains largely unknown. Here we show that structurally defined extracellular PAS-like domains belong to the Cache superfamily, which is homologous to, but distinct from the PAS superfamily. Our newly built computational models enabled identification of Cache domains in tens of thousands of signal transduction proteins including those from important pathogens and model organisms. Furthermore, we show that Cache domains comprise the dominant mode of extracellular sensing in prokaryotes. '),
(87755, 2016, 'plos', 'A Theoretical Model of Jigsaw-Puzzle Pattern Formation by Plant Leaf Epidermal Cells', 'Higaki, Takumi|Kutsuna, Natsumaro|Akita, Kae|Takigawa-Imamura, Hisako|Yoshimura, Kenji|Miura, Takashi', 'Department of Integrated Biosciences, Graduate School of Frontier Sciences, The University of Tokyo, Tokyo, Japan.|Department of Integrated Biosciences, Graduate School of Frontier Sciences, The University of Tokyo, Tokyo, Japan.|Department of Integrated Biosciences, Graduate School of Frontier Sciences, The University of Tokyo, Tokyo, Japan.|Department of Anatomy and Cell Biology, Graduate School of Medical Sciences, Kyushu University, Fukuoka, Japan.|Department of Neurology, Osaka City General Hospital, Osaka, Japan.|Department of Anatomy and Cell Biology, Graduate School of Medical Sciences, Kyushu University, Fukuoka, Japan.', 'Japan|Japan|Japan|Japan|Japan|Japan', 12, 'Arabidopsis|Arabidopsis Proteins|Body Patterning|Cell Wall|Computational Biology|GTP-Binding Proteins|Microscopy, Electron, Transmission|Models, Biological|Monomeric GTP-Binding Proteins|Plant Epidermis|Plant Leaves|Time-Lapse Imaging', 'Journal Article', '10.1371/journal.pcbi.1004833', '27054467', 'Plant leaf epidermal cells exhibit a jigsaw puzzle-like pattern that is generated by interdigitation of the cell wall during leaf development. The contribution of two ROP GTPases, ROP2 and ROP6, to the cytoskeletal dynamics that regulate epidermal cell wall interdigitation has already been examined, however, how interactions between these molecules result in pattern formation remains to be elucidated. Here, we propose a simple interface equation model that incorporates both the cell wall remodeling activity of ROP GTPases and the diffusible signaling molecules by which they are regulated. This model successfully reproduces pattern formation observed in vivo, and explains the counterintuitive experimental results of decreased cellulose production and increased thickness. Our model also reproduces the dynamics of three-way cell wall junctions. Therefore, this model provides a possible mechanism for cell wall interdigitation formation in vivo. '),
(87756, 2016, 'plos', 'A Knowledge-Based System for Display and Prediction of O-Glycosylation Network Behaviour in Response to Enzyme Knockouts', 'McDonald, Andrew G|Tipton, Keith F|Davey, Gavin P', 'School of Biochemistry and Immunology, Trinity College Dublin, Dublin, Ireland.|School of Biochemistry and Immunology, Trinity College Dublin, Dublin, Ireland.|School of Biochemistry and Immunology, Trinity College Dublin, Dublin, Ireland.', 'Ireland|Ireland|Ireland', 12, 'Animals|CHO Cells|Computational Biology|Computer Simulation|Cricetulus|Gene Knockout Techniques|Genetic Engineering|Glycosylation|Glycosyltransferases|Humans|Knowledge Bases|Metabolic Networks and Pathways|Models, Biological|Mucins|Polysaccharides|Protein Processing, Post-Translational|Terminology as Topic', 'Journal Article', '10.1371/journal.pcbi.1004844', '27054587', 'O-linked glycosylation is an important post-translational modification of mucin-type protein, changes to which are important biomarkers of cancer. For this study of the enzymes of O-glycosylation, we developed a shorthand notation for representing GalNAc-linked oligosaccharides, a method for their graphical interpretation, and a pattern-matching algorithm that generates networks of enzyme-catalysed reactions. Software for generating glycans from the enzyme activities is presented, and is also available online. The degree distributions of the resulting enzyme-reaction networks were found to be Poisson in nature. Simple graph-theoretic measures were used to characterise the resulting reaction networks. From a study of in-silico single-enzyme knockouts of each of 25 enzymes known to be involved in mucin O-glycan biosynthesis, six of them, xcexb2-1,4-galactosyltransferase (xcexb24Gal-T4), four glycosyltransferases and one sulfotransferase, play the dominant role in determining O-glycan heterogeneity. In the absence of xcexb24Gal-T4, all Lewis X, sialyl-Lewis X, Lewis Y and Sda/Cad glycoforms were eliminated, in contrast to knockouts of the N-acetylglucosaminyltransferases, which did not affect the relative abundances of O-glycans expressing these epitopes. A set of 244 experimentally determined mucin-type O-glycans obtained from the literature was used to validate the method, which was able to predict up to 98% of the most common structures obtained from human and engineered CHO cell glycoforms. '),
(87757, 2016, 'plos', 'Hypercycle', 'Szostak, Natalia|Wasik, Szymon|Blazewicz, Jacek', 'Institute of Computing Science, Poznan University of Technology, Poznan, Poland.|Institute of Computing Science, Poznan University of Technology, Poznan, Poland.|Institute of Computing Science, Poznan University of Technology, Poznan, Poland.', 'Poland|Poland|Poland', 18, 'Catalysis|Computational Biology|Evolution, Molecular|Feedback, Physiological|Macromolecular Substances|Models, Biological|Models, Molecular|Nucleic Acids|Origin of Life|Peptides|Protein Biosynthesis|RNA, Catalytic', 'Journal Article', '10.1371/journal.pcbi.1004853', '27054759', '-'),
(87758, 2016, 'plos', 'Dynamics of Cell Ensembles on Adhesive Micropatterns: Bridging the Gap between Single Cell Spreading and Collective Cell Migration', 'Albert, Philipp J|Schwarz, Ulrich S', 'Institute for Theoretical Physics and BioQuant, Heidelberg University, Heidelberg, Germany.|Institute for Theoretical Physics and BioQuant, Heidelberg University, Heidelberg, Germany.', 'Germany|Germany', 39, 'Animals|Biomechanical Phenomena|Cell Adhesion|Cell Communication|Cell Division|Cell Line|Cell Movement|Cell Polarity|Cell Shape|Computational Biology|Computer Simulation|Extracellular Matrix|Humans|Models, Biological|Video Recording', 'Journal Article', '10.1371/journal.pcbi.1004863', '27054883', 'The collective dynamics of multicellular systems arise from the interplay of a few fundamental elements: growth, division and apoptosis of single cells, their mechanical and adhesive interactions with neighboring cells and the extracellular matrix, and the tendency of polarized cells to move. Micropatterned substrates are increasingly used to dissect the relative roles of these fundamental processes and to control the resulting dynamics. Here we show that a unifying computational framework based on the cellular Potts model can describe the experimentally observed cell dynamics over all relevant length scales. For single cells, the model correctly predicts the statistical distribution of the orientation of the cell division axis as well as the final organisation of the two daughters on a large range of micropatterns, including those situations in which a stable configuration is not achieved and rotation ensues. Large ensembles migrating in heterogeneous environments form non-adhesive regions of inward-curved arcs like in epithelial bridge formation. Collective migration leads to swirl formation with variations in cell area as observed experimentally. In each case, we also use our model to predict cell dynamics on patterns that have not been studied before. '),
(87759, 2016, 'plos', 'Computational and Empirical Studies Predict Mycobacterium tuberculosis-Specific T Cells as a Biomarker for Infection Outcome', 'Marino, Simeone|Gideon, Hannah P|Gong, Chang|Mankad, Shawn|McCrone, John T|Lin, Philana Ling|Linderman, Jennifer J|Flynn, JoAnne L|Kirschner, Denise E', 'Department of Microbiology and Immunology, University of Michigan Medical School, Ann Arbor, Michigan, United States of America.|Department of Microbiology and Molecular Genetics, University of Pittsburgh, Pittsburgh, Pennsylvania, United States of America.|Department of Microbiology and Immunology, University of Michigan Medical School, Ann Arbor, Michigan, United States of America.|Robert H. Smith School of Business, University of Maryland, College Park, Maryland, United States of America.|Department of Microbiology and Immunology, University of Michigan Medical School, Ann Arbor, Michigan, United States of America.|Department of Pediatrics, Childrens Hospital of the University of Pittsburgh of UPMC, Pittsburgh, Pennsylvania, United States of America.|Department of Chemical Engineering, University of Michigan, Ann Arbor, Michigan, United States of America.|Department of Microbiology and Molecular Genetics, University of Pittsburgh, Pittsburgh, Pennsylvania, United States of America.|Department of Microbiology and Immunology, University of Michigan Medical School, Ann Arbor, Michigan, United States of America.', 'United States|United States|United States|United States|United States|United States|United States|Un', 25, 'Algorithms|Animals|Biomarkers|CD4-Positive T-Lymphocytes|CD8-Positive T-Lymphocytes|Computational Biology|Computer Simulation|Cytokines|Databases, Factual|Humans|Lung|Macaca fascicularis|Models, Immunological|Mycobacterium tuberculosis|T-Lymphocytes|Tuberculosis, Pulmonary', 'Journal Article', '10.1371/journal.pcbi.1004804', '27065304', 'Identifying biomarkers for tuberculosis (TB) is an ongoing challenge in developing immunological correlates of infection outcome and protection. Biomarker discovery is also necessary for aiding design and testing of new treatments and vaccines. To effectively predict biomarkers for infection progression in any disease, including TB, large amounts of experimental data are required to reach statistical power and make accurate predictions. We took a two-pronged approach using both experimental and computational modeling to address this problem. We first collected 200 blood samples over a 2- year period from 28 non-human primates (NHP) infected with a low dose of Mycobacterium tuberculosis. We identified T cells and the cytokines that they were producing (single and multiple) from each sample along with monkey status and infection progression data. Machine learning techniques were used to interrogate the experimental NHP datasets without identifying any potential TB biomarker. In parallel, we used our extensive novel NHP datasets to build and calibrate a multi-organ computational model that combines what is occurring at the site of infection (e.g., lung) at a single granuloma scale with blood level readouts that can be tracked in monkeys and humans. We then generated a large in silico repository of in silico granulomas coupled to lymph node and blood dynamics and developed an in silico tool to scale granuloma level results to a full host scale to identify what best predicts Mycobacterium tuberculosis (Mtb) infection outcomes. The analysis of in silico blood measures identifies Mtb-specific frequencies of effector T cell phenotypes at various time points post infection as promising indicators of infection outcome. We emphasize that pairing wetlab and computational approaches holds great promise to accelerate TB biomarker discovery. '),
(87760, 2016, 'plos', 'A Robust Feedforward Model of the Olfactory System', 'Zhang, Yilun|Sharpee, Tatyana O', 'Computational Neurobiology Laboratory, The Salk Institute for Biological Studies, La Jolla, California, United States of America.|Computational Neurobiology Laboratory, The Salk Institute for Biological Studies, La Jolla, California, United States of America.', 'United States|United States', 10, 'Algorithms|Animals|Computational Biology|Feedback, Physiological|Humans|Models, Neurological|Odorants|Olfactory Bulb|Olfactory Pathways|Olfactory Receptor Neurons|Receptors, Odorant|Smell', 'Journal Article', '10.1371/journal.pcbi.1004850', '27065441', 'Most natural odors have sparse molecular composition. This makes the principles of compressed sensing potentially relevant to the structure of the olfactory code. Yet, the largely feedforward organization of the olfactory system precludes reconstruction using standard compressed sensing algorithms. To resolve this problem, recent theoretical work has shown that signal reconstruction could take place as a result of a low dimensional dynamical system converging to one of its attractor states. However, the dynamical aspects of optimization slowed down odor recognition and were also found to be susceptible to noise. Here we describe a feedforward model of the olfactory system that achieves both strong compression and fast reconstruction that is also robust to noise. A key feature of the proposed model is a specific relationship between how odors are represented at the glomeruli stage, which corresponds to a compression, and the connections from glomeruli to third-order neurons (neurons in the olfactory cortex of vertebrates or Kenyon cells in the mushroom body of insects), which in the model corresponds to reconstruction. We show that should this specific relationship hold true, the reconstruction will be both fast and robust to noise, and in particular to the false activation of glomeruli. The predicted connectivity rate from glomeruli to third-order neurons can be tested experimentally. '),
(87761, 2016, 'plos', 'Fast and Accurate Learning When Making Discrete Numerical Estimates', 'Sanborn, Adam N|Beierholm, Ulrik R', 'Department of Psychology, University of Warwick, Coventry, United Kingdom.|Department of Psychology, Durham University, Durham, United Kingdom.', 'United Kingdom|United Kingdom', 7, 'Bayes Theorem|Computational Biology|Decision Theory|Discriminant Analysis|Humans|Learning|Likelihood Functions|Mathematical Concepts|Models, Statistical|Normal Distribution|Statistics as Topic', 'Journal Article', '10.1371/journal.pcbi.1004859', '27070155', 'Many everyday estimation tasks have an inherently discrete nature, whether the task is counting objects (e.g., a number of paint buckets) or estimating discretized continuous variables (e.g., the number of paint buckets needed to paint a room). While Bayesian inference is often used for modeling estimates made along continuous scales, discrete numerical estimates have not received as much attention, despite their common everyday occurrence. Using two tasks, a numerosity task and an area estimation task, we invoke Bayesian decision theory to characterize how people learn discrete numerical distributions and make numerical estimates. Across three experiments with novel stimulus distributions we found that participants fell between two common decision functions for converting their uncertain representation into a response: drawing a sample from their posterior distribution and taking the maximum of their posterior distribution. While this was consistent with the decision function found in previous work using continuous estimation tasks, surprisingly the prior distributions learned by participants in our experiments were much more adaptive: When making continuous estimates, participants have required thousands of trials to learn bimodal priors, but in our tasks participants learned discrete bimodal and even discrete quadrimodal priors within a few hundred trials. This makes discrete numerical estimation tasks good testbeds for investigating how people learn and make estimates. '),
(87762, 2016, 'plos', 'Molecular Infectious Disease Epidemiology: Survival Analysis and Algorithms Linking Phylogenies to Transmission Trees', 'Kenah, Eben|Britton, Tom|Halloran, M Elizabeth|Longini, Ira M', 'Biostatistics Department and Emerging Pathogens Institute, University of Florida, Gainesville, Florida, United States of America.|Department of Mathematics, Stockholm University, Stockholm, Sweden.|Center for Inference and Dynamics of Infectious Diseases, Fred Hutchinson Cancer Research Center, Seattle, Washington, United States of America.|Biostatistics Department and Emerging Pathogens Institute, University of Florida, Gainesville, Florida, United States of America.', 'United States|Sweden|United States|United States', 18, 'Algorithms|Animals|Communicable Diseases|Computational Biology|Computer Simulation|Disease Transmission, Infectious|Foot-and-Mouth Disease|Foot-and-Mouth Disease Virus|Humans|Models, Statistical|Molecular Epidemiology|Phylogeny|Stochastic Processes|Survival Analysis', 'Journal Article', '10.1371/journal.pcbi.1004869', '27070316', 'Recent work has attempted to use whole-genome sequence data from pathogens to reconstruct the transmission trees linking infectors and infectees in outbreaks. However, transmission trees from one outbreak do not generalize to future outbreaks. Reconstruction of transmission trees is most useful to public health if it leads to generalizable scientific insights about disease transmission. In a survival analysis framework, estimation of transmission parameters is based on sums or averages over the possible transmission trees. A phylogeny can increase the precision of these estimates by providing partial information about who infected whom. The leaves of the phylogeny represent sampled pathogens, which have known hosts. The interior nodes represent common ancestors of sampled pathogens, which have unknown hosts. Starting from assumptions about disease biology and epidemiologic study design, we prove that there is a one-to-one correspondence between the possible assignments of interior node hosts and the transmission trees simultaneously consistent with the phylogeny and the epidemiologic data on person, place, and time. We develop algorithms to enumerate these transmission trees and show these can be used to calculate likelihoods that incorporate both epidemiologic data and a phylogeny. A simulation study confirms that this leads to more efficient estimates of hazard ratios for infectiousness and baseline hazards of infectious contact, and we use these methods to analyze data from a foot-and-mouth disease virus outbreak in the United Kingdom in 2001. These results demonstrate the importance of data on individuals who escape infection, which is often overlooked. The combination of survival analysis and algorithms linking phylogenies to transmission trees is a rigorous but flexible statistical foundation for molecular infectious disease epidemiology. '),
(87763, 2016, 'plos', 'Quorum Sensing Desynchronization Leads to Bimodality and Patterned Behaviors', 'Quan, David N|Tsao, Chen-Yu|Wu, Hsuan-Chen|Bentley, William E', 'Fischell Department of Bioengineering, University of Maryland, College Park, Maryland, United States of America.|Fischell Department of Bioengineering, University of Maryland, College Park, Maryland, United States of America.|Fischell Department of Bioengineering, University of Maryland, College Park, Maryland, United States of America.|Fischell Department of Bioengineering, University of Maryland, College Park, Maryland, United States of America.', 'United States|United States|United States|United States', 16, 'Bacterial Physiological Phenomena|Computational Biology|Computer Simulation|Models, Biological|Quorum Sensing', 'Journal Article', '10.1371/journal.pcbi.1004781', '27071007', 'Quorum Sensing (QS) drives coordinated phenotypic outcomes among bacterial populations. Its role in mediating infectious disease has led to the elucidation of numerous autoinducers and their corresponding QS signaling pathways. Among them, the Lsr (LuxS-regulated) QS system is conserved in scores of bacteria, and its signal molecule, autoinducer-2 (AI-2), is synthesized as a product of 1-carbon metabolism. Lsr signal transduction processes, therefore, may help organize population scale activities in numerous bacterial consortia. Conceptions of how Lsr QS organizes population scale behaviors remain limited, however. Using mathematical simulations, we examined how desynchronized Lsr QS activation, arising from cell-to-cell population heterogeneity, could lead to bimodal Lsr signaling and fractional activation. This has been previously observed experimentally. Governing these processes are an asynchronous AI-2 uptake, where positive intracellular feedback in Lsr expression is combined with negative feedback between cells. The resulting activation patterns differ from that of the more widely studied LuxIR system, the topology of which consists of only positive feedback. To elucidate differences, both QS systems were simulated in 2D, where cell populations grow and signal each other via traditional growth and diffusion equations. Our results demonstrate that the LuxIR QS system produces an outward wave of autoinduction, and the Lsr QS system yields dispersed autoinduction from spatially-localized secretion and uptake profiles. In both cases, our simulations mirror previously demonstrated experimental results. As a whole, these models inform QS observations and synthetic biology designs. '),
(87764, 2016, 'plos', 'Traveling Pulses for a Two-Species Chemotaxis Model', 'Emako, Casimir|Gayrard, Charlène|Buguin, Axel|Neves de Almeida, Luís|Vauchelet, Nicolas', 'Sorbonne Universités, UPMC Univ Paris 06, CNRS, INRIA, UMR 7598, Laboratoire Jacques-Louis Lions, Equipe MAMBA, Paris, France.|Institut Jacques Monod - UMR 7592, CNRS Université Denis Diderot, Paris, France.|Laboratoire Physico-chimie Curie, Institut Curie, PSL Research University, UPMC Univ. Paris 6, CNRS UMR 168, Paris, France.|CNRS, Sorbonne Universités, UPMC Univ Paris 06, INRIA, UMR 7598, Laboratoire Jacques-Louis Lions, Equipe MAMBA, Paris, France.|Sorbonne Universités, UPMC Univ Paris 06, CNRS, INRIA, UMR 7598, Laboratoire Jacques-Louis Lions, Equipe MAMBA, Paris, France.', 'France|France|France|France|France', 14, 'Bacterial Physiological Phenomena|Chemotaxis|Computational Biology|Computer Simulation|Escherichia coli|Kinetics|Microscopy, Video|Models, Biological', 'Journal Article', '10.1371/journal.pcbi.1004843', '27071058', 'Mathematical models have been widely used to describe the collective movement of bacteria by chemotaxis. In particular, bacterial concentration waves traveling in a narrow channel have been experimentally observed and can be precisely described thanks to a mathematical model at the macroscopic scale. Such model was derived in [1] using a kinetic model based on an accurate description of the mesoscopic run-and-tumble process. We extend this approach to study the behavior of the interaction between two populations of E. Coli. Separately, each population travels with its own speed in the channel. When put together, a synchronization of the speed of the traveling pulses can be observed. We show that this synchronization depends on the fraction of the fast population. Our approach is based on mathematical analysis of a macroscopic model of partial differential equations. Numerical simulations in comparison with experimental observations show qualitative agreement. '),
(87765, 2016, 'plos', 'Mechanical Stress Induces Remodeling of Vascular Networks in Growing Leaves', 'Bar-Sinai, Yohai|Julien, Jean-Daniel|Sharon, Eran|Armon, Shahaf|Nakayama, Naomi|Adda-Bedia, Mokhtar|Boudaoud, Arezki', 'Department of Chemical Physics, Weizmann Institute of Science, Rehovot, Israel.|Laboratoire de Physique, ENS Lyon, CNRS, UCB Lyon I, Université de Lyon, Lyon, France.|Racah Institute of Physics, The Hebrew University, Jerusalem, Israel.|Racah Institute of Physics, The Hebrew University, Jerusalem, Israel.|Institute of Molecular Plant Sciences, University of Edinburgh, Edinburgh, United Kingdom.|Laboratoire de Physique Statistique, Ecole Normale Supérieure, CNRS, Université Paris VI, Université Paris VII, Paris, France.|Laboratoire Reproduction et Développement des Plantes, Univ Lyon, ENS de Lyon, UCB Lyon 1, CNRS, INRA, Lyon, France.', 'Israel|France|Israel|Israel|United Kingdom|France|France', 11, 'Anisotropy|Arabidopsis|Biomechanical Phenomena|Body Patterning|Computational Biology|Computer Simulation|Models, Biological|Plant Leaves|Plant Vascular Bundle|Stress, Mechanical', 'Journal Article', '10.1371/journal.pcbi.1004819', '27074136', 'Differentiation into well-defined patterns and tissue growth are recognized as key processes in organismal development. However, it is unclear whether patterns are passively, homogeneously dilated by growth or whether they remodel during tissue expansion. Leaf vascular networks are well-fitted to investigate this issue, since leaves are approximately two-dimensional and grow manyfold in size. Here we study experimentally and computationally how vein patterns affect growth. We first model the growing vasculature as a network of viscoelastic rods and consider its response to external mechanical stress. We use the so-called texture tensor to quantify the local network geometry and reveal that growth is heterogeneous, resembling non-affine deformations in composite materials. We then apply mechanical forces to growing leaves after veins have differentiated, which respond by anisotropic growth and reorientation of the network in the direction of external stress. External mechanical stress appears to make growth more homogeneous, in contrast with the model with viscoelastic rods. However, we reconcile the model with experimental data by incorporating randomness in rod thickness and a threshold in the rod growth law, making the rods viscoelastoplastic. Altogether, we show that the higher stiffness of veins leads to their reorientation along external forces, along with a reduction in growth heterogeneity. This process may lead to the reinforcement of leaves against mechanical stress. More generally, our work contributes to a framework whereby growth and patterns are coordinated through the differences in mechanical properties between cell types. '),
(87766, 2016, 'plos', 'Problem Solving as Probabilistic Inference with Subgoaling: Explaining Human Successes and Pitfalls in the Tower of Hanoi', 'Donnarumma, Francesco|Maisto, Domenico|Pezzulo, Giovanni', 'Institute of Cognitive Sciences and Technologies, National Research Council, Rome, Italy.|Institute for High Performance Computing and Networking, National Research Council, Naples, Italy.|Institute of Cognitive Sciences and Technologies, National Research Council, Rome, Italy.', 'Italy|Italy|Italy', 25, 'Algorithms|Cognition|Computational Biology|Computer Simulation|Decision Making|Humans|Models, Psychological|Models, Statistical|Neuropsychological Tests|Problem Solving', 'Journal Article', '10.1371/journal.pcbi.1004864', '27074140', 'How do humans and other animals face novel problems for which predefined solutions are not available? Human problem solving links to flexible reasoning and inference rather than to slow trial-and-error learning. It has received considerable attention since the early days of cognitive science, giving rise to well known cognitive architectures such as SOAR and ACT-R, but its computational and brain mechanisms remain incompletely known. Furthermore, it is still unclear whether problem solving is a specialized domain or module of cognition, in the sense that it requires computations that are fundamentally different from those supporting perception and action systems. Here we advance a novel view of human problem solving as probabilistic inference with subgoaling. In this perspective, key insights from cognitive architectures are retained such as the importance of using subgoals to split problems into subproblems. However, here the underlying computations use probabilistic inference methods analogous to those that are increasingly popular in the study of perception and action systems. To test our model we focus on the widely used Tower of Hanoi (ToH) task, and show that our proposed method can reproduce characteristic idiosyncrasies of human problem solvers: their sensitivity to the community structure of the ToH and their difficulties in executing so-called counterintuitive movements. Our analysis reveals that subgoals have two key roles in probabilistic inference and problem solving. First, prior beliefs on (likely) useful subgoals carve the problem space and define an implicit metric for the problem at hand-a metric to which humans are sensitive. Second, subgoals are used as waypoints in the probabilistic problem solving inference and permit to find effective solutions that, when unavailable, lead to problem solving deficits. Our study thus suggests that a probabilistic inference scheme enhanced with subgoals provides a comprehensive framework to study problem solving and its deficits. '),
(87767, 2016, 'plos', 'Maximum-Entropy Models of Sequenced Immune Repertoires Predict Antigen-Antibody Affinity', 'Asti, Lorenzo|Uguzzoni, Guido|Marcatili, Paolo|Pagnani, Andrea', 'Dipartimento di Scienze di Base e Applicate per lIngegneria, Sapienza University of Roma, Roma, Italy.|Human Genetics Foundation, Molecular Biotechnology Center, Torino, Italy.|Center for Biological Sequence Analysis, Department of Systems Biology, Technical University of Denmark, Lyngby, Denmark.|Human Genetics Foundation, Molecular Biotechnology Center, Torino, Italy.', 'Italy|Italy|Denmark|Italy', 11, 'Antibodies, Neutralizing|Antibody Affinity|Antigen-Antibody Reactions|B-Lymphocytes|Binding Sites, Antibody|Cluster Analysis|Computational Biology|Computer Simulation|Entropy|Evolution, Molecular|HIV Antibodies|HIV Infections|HIV-1|Humans|Models, Immunological|Models, Molecular|Mutation|Normal Distribution|Sequence Alignment', 'Journal Article', '10.1371/journal.pcbi.1004870', '27074145', 'The immune system has developed a number of distinct complex mechanisms to shape and control the antibody repertoire. One of these mechanisms, the affinity maturation process, works in an evolutionary-like fashion: after binding to a foreign molecule, the antibody-producing B-cells exhibit a high-frequency mutation rate in the genome region that codes for the antibody active site. Eventually, cells that produce antibodies with higher affinity for their cognate antigen are selected and clonally expanded. Here, we propose a new statistical approach based on maximum entropy modeling in which a scoring function related to the binding affinity of antibodies against a specific antigen is inferred from a sample of sequences of the immune repertoire of an individual. We use our inference strategy to infer a statistical model on a data set obtained by sequencing a fairly large portion of the immune repertoire of an HIV-1 infected patient. The Pearson correlation coefficient between our scoring function and the IC50 neutralization titer measured on 30 different antibodies of known sequence is as high as 0.77 (p-value 10-6), outperforming other sequence- and structure-based models. '),
(87768, 2016, 'plos', 'A Predictive Model for Yeast Cell Polarization in Pheromone Gradients', 'Muller, Nicolas|Piel, Matthieu|Calvez, Vincent|Voituriez, Raphaxc3xabl|Gonxc3xa7alves-Sxc3xa1, Joana|Guo, Chin-Lin|Jiang, Xingyu|Murray, Andrew|Meunier, Nicolas', 'MAP5, CNRS UMR 8145, Universitxc3xa9 Paris Descartes, Paris, France.|Institut Curie, CNRS UMR 144, Paris, France.|Unitxc3xa9 de Mathxc3xa9matiques Pures et Appliquxc3xa9es, CNRS UMR 5669 and xc3xa9quipe-projet INRIA NUMED, xc3x89cole Normale Supxc3xa9rieure de Lyon, Lyon, France.|Laboratoire Jean Perrin and Laboratoire de Physique Thxc3xa9orique de la Matixc3xa8re Condensxc3xa9e, UMR 7600 CNRS /UPMC, Paris, France.|Molecular and Cell Biology and FAS Center for Systems Biology, Harvard University, Cambridge, Massachusetts, United States of America.|Molecular and Cell Biology and FAS Center for Systems Biology, Harvard University, Cambridge, Massachusetts, United States of America.|Department of Chemistry and Chemical Biology, Harvard University, Cambridge, Massachusetts, United States of America.|Molecular and Cell Biology and FAS Center for Systems Biology, Harvard University, Cambridge, Massachusetts, United States of America.|MAP5, CNRS UMR 8145, Universitxc3xa9 Paris Descartes, Paris, France.', 'France|France|France|France|United States|United States|United States|United States|France', 13, 'Cell Polarity|Computational Biology|Models, Biological|Pheromones|Quorum Sensing|Saccharomyces cerevisiae|Saccharomyces cerevisiae Proteins|Signal Transduction', 'Journal Article', '10.1371/journal.pcbi.1004795', '27077831', 'Budding yeast cells exist in two mating types, a and xcexb1, which use peptide pheromones to communicate with each other during mating. Mating depends on the ability of cells to polarize up pheromone gradients, but cells also respond to spatially uniform fields of pheromone by polarizing along a single axis. We used quantitative measurements of the response of a cells to xcexb1-factor to produce a predictive model of yeast polarization towards a pheromone gradient. We found that cells make a sharp transition between budding cycles and mating induced polarization and that they detect pheromone gradients accurately only over a narrow range of pheromone concentrations corresponding to this transition. We fit all the parameters of the mathematical model by using quantitative data on spontaneous polarization in uniform pheromone concentration. Once these parameters have been computed, and without any further fit, our model quantitatively predicts the yeast cell response to pheromone gradient providing an important step toward understanding how cells communicate with each other. '),
(87769, 2016, 'plos', 'Computational Reconstruction of NFxcexbaB Pathway Interaction Mechanisms during Prostate Cancer', 'Bxc3xb6rnigen, Daniela|Tyekucheva, Svitlana|Wang, Xiaodong|Rider, Jennifer R|Lee, Gwo-Shu|Mucci, Lorelei A|Sweeney, Christopher|Huttenhower, Curtis', 'Department of Biostatistics, Harvard T.H. Chan School of Public Health, Harvard University, Boston, Massachusetts, United States of America.|Department of Biostatistics and Computational Biology, Dana-Farber Cancer Institute, Boston, Massachusetts, United States of America.|Department of Medical Oncology, Dana-Farber Cancer Institute, Harvard Medical School, Boston, Massachusetts, United States of America.|Department of Epidemiology, Harvard T.H. Chan School of Public Health, Harvard University, Boston, Massachusetts, United States of America.|Department of Medical Oncology, Dana-Farber Cancer Institute, Harvard Medical School, Boston, Massachusetts, United States of America.|Department of Epidemiology, Harvard T.H. Chan School of Public Health, Harvard University, Boston, Massachusetts, United States of America.|Department of Medical Oncology, Dana-Farber Cancer Institute, Harvard Medical School, Boston, Massachusetts, United States of America.|Department of Biostatistics, Harvard T.H. Chan School of Public Health, Harvard University, Boston, Massachusetts, United States of America.', 'United States|United States|United States|United States|United States|United States|United States|Un', 8, 'Adaptor Proteins, Signal Transducing|Bayes Theorem|Cell Line, Tumor|Cell Proliferation|Computational Biology|Databases, Genetic|Gene Expression Profiling|Gene Knockdown Techniques|Gene Ontology|Gene Regulatory Networks|Humans|Immunoprecipitation|Male|Models, Biological|NF-kappa B|Phosphoproteins|Prostatic Neoplasms|Signal Transduction|Tristetraprolin', 'Journal Article', '10.1371/journal.pcbi.1004820', '27078000', 'Molecular research in cancer is one of the largest areas of bioinformatic investigation, but it remains a challenge to understand biomolecular mechanisms in cancer-related pathways from high-throughput genomic data. This includes the Nuclear-factor-kappa-B (NFxcexbaB) pathway, which is central to the inflammatory response and cell proliferation in prostate cancer development and progression. Despite close scrutiny and a deep understanding of many of its members biomolecular activities, the current list of pathway members and a systems-level understanding of their interactions remains incomplete. Here, we provide the first steps toward computational reconstruction of interaction mechanisms of the NFxcexbaB pathway in prostate cancer. We identified novel roles for ATF3, CXCL2, DUSP5, JUNB, NEDD9, SELE, TRIB1, and ZFP36 in this pathway, in addition to new mechanistic interactions between these genes and 10 known NFxcexbaB pathway members. A newly predicted interaction between NEDD9 and ZFP36 in particular was validated by co-immunoprecipitation, as was NEDD9s potential biological role in prostate cancer cell growth regulation. We combined 651 gene expression datasets with 1.4M gene product interactions to predict the inclusion of 40 additional genes in the pathway. Molecular mechanisms of interaction among pathway members were inferred using recent advances in Bayesian data integration to simultaneously provide information specific to biological contexts and individual biomolecular activities, resulting in a total of 112 interactions in the fully reconstructed NFxcexbaB pathway: 13 (11%) previously known, 29 (26%) supported by existing literature, and 70 (63%) novel. This method is generalizable to other tissue types, cancers, and organisms, and this new information about the NFxcexbaB pathway will allow us to further understand prostate cancer and to develop more effective prevention and treatment strategies. '),
(87770, 2016, 'plos', 'Ups and Downs of Poised RNA Polymerase II in B-Cells', 'Dao, Phuong|Wojtowicz, Damian|Nelson, Steevenson|Levens, David|Przytycka, Teresa M', 'National Center for Biotechnology Information, National Library of Medicine, National Institutes of Health, Bethesda, Maryland, United States of America.|National Center for Biotechnology Information, National Library of Medicine, National Institutes of Health, Bethesda, Maryland, United States of America.|Laboratory of Molecular Immunogenetics, National Institute of Arthritis and Musculoskeletal and Skin Diseases, National Institutes of Health, Bethesda, Maryland, United States of America.|Laboratory of Pathology, Center for Cancer Research, National Cancer Institute, National Institutes of Health, Bethesda, Maryland, United States of America.|National Center for Biotechnology Information, National Library of Medicine, National Institutes of Health, Bethesda, Maryland, United States of America.', 'United States|United States|United States|United States|United States', 1, 'Animals|B-Lymphocytes|Computational Biology|G-Quadruplexes|Gene Expression Regulation|Genes, Immediate-Early|Lymphocyte Activation|Mice|Mice, Inbred C57BL|Promoter Regions, Genetic|RNA Polymerase II|Transcription Elongation, Genetic|Transcription Initiation Site', 'Journal Article', '10.1371/journal.pcbi.1004821', '27078128', 'Recent genome-wide analyses have uncovered a high accumulation of RNA polymerase II (Pol II) at the 5 end of genes. This elevated Pol II presence at promoters, referred to here as Poll II poising, is mainly (but not exclusively) attributed to temporal pausing of transcription during early elongation which, in turn, has been proposed to be a regulatory step for processes that need to be activated on demand. Yet, the full genome-wide regulatory role of Pol II poising is yet to be delineated. To elucidate the role of Pol II poising in B cell activation, we compared Pol II profiles in resting and activated B cells. We found that while Pol II poised genes generally overlap functionally among different B cell states and correspond to the functional groups previously identified for other cell types, non-poised genes are B cell state specific. Focusing on the changes in transcription activity upon B cell activation, we found that the majority of such changes were from poised to non-poised state. The genes showing this type of transition were functionally enriched in translation, RNA processing and mRNA metabolic process. Interestingly, we also observed a transition from non-poised to poised state. Within this set of genes we identified several Immediate Early Genes (IEG), which were highly expressed in resting B cell and shifted from non-poised to poised state after B cell activation. Thus Pol II poising does not only mark genes for rapid expression in the future, but it is also associated with genes that are silenced after a burst of their expression. Finally, we performed comparative analysis of the presence of G4 motifs in the context of poised versus non-poised but active genes. Interestingly we observed a differential enrichment of these motifs upstream versus downstream of TSS depending on poising status. The enrichment of G4 sequence motifs upstream of TSS of non-poised active genes suggests a potential role of quadruplexes in expression regulation. '),
(87771, 2016, 'plos', 'Mathematical Model for Length Control by the Timing of Substrate Switching in the Type III Secretion System', 'Nariya, Maulik K|Israeli, Johnny|Shi, Jack J|Deeds, Eric J', 'Department of Physics and Astronomy, University of Kansas, Lawrence, Kansas, United States of America.|Department of Physics and Astronomy, University of Kansas, Lawrence, Kansas, United States of America.|Department of Physics and Astronomy, University of Kansas, Lawrence, Kansas, United States of America.|Center for Computational Biology, University of Kansas, Lawrence, Kansas, United States of America.', 'United States|United States|United States|United States', 2, 'Bacterial Proteins|Computational Biology|Computer Simulation|Host-Pathogen Interactions|Models, Biological|Models, Molecular|Protein Binding|Proteolysis|Salmonella typhimurium|Stochastic Processes|Type III Secretion Systems|Virulence|Virulence Factors', 'Journal Article', '10.1371/journal.pcbi.1004851', '27078235', 'Type III Secretion Systems (T3SS) are complex bacterial structures that provide gram-negative pathogens with a unique virulence mechanism whereby they grow a needle-like structure in order to inject bacterial effector proteins into the cytoplasm of a host cell. Numerous experiments have been performed to understand the structural details of this nanomachine during the past decade. Despite the concerted efforts of molecular and structural biologists, several crucial aspects of the assembly of this structure, such as the regulation of the length of the needle itself, remain unclear. In this work, we used a combination of mathematical and computational techniques to better understand length control based on the timing of substrate switching, which is a possible mechanism for how bacteria ensure that the T3SS needles are neither too short nor too long. In particular, we predicted the form of the needle length distribution based on this mechanism, and found excellent agreement with available experimental data from Salmonella typhimurium with only a single free parameter. Although our findings provide preliminary evidence in support of the substrate switching model, they also make a set of quantitative predictions that, if tested experimentally, would assist in efforts to unambiguously characterize the regulatory mechanisms that control the growth of this crucial virulence factor. '),
(87772, 2016, 'plos', 'Integrating Antimicrobial Therapy with Host Immunity to Fight Drug-Resistant Infections: Classical vs Adaptive Treatment', 'Gjini, Erida|Brito, Patricia H', 'Instituto Gulbenkian de Ciência, Oeiras, Portugal.|Instituto Gulbenkian de Ciência, Oeiras, Portugal.', 'Portugal|Portugal', 29, 'Anti-Infective Agents|Computational Biology|Computer Simulation|Drug Resistance, Microbial|Host-Pathogen Interactions|Humans|Infection|Models, Immunological', 'Journal Article', '10.1371/journal.pcbi.1004857', '27078624', 'Antimicrobial resistance of infectious agents is a growing problem worldwide. To prevent the continuing selection and spread of drug resistance, rational design of antibiotic treatment is needed, and the question of aggressive vs. moderate therapies is currently heatedly debated. Host immunity is an important, but often-overlooked factor in the clearance of drug-resistant infections. In this work, we compare aggressive and moderate antibiotic treatment, accounting for host immunity effects. We use mathematical modelling of within-host infection dynamics to study the interplay between pathogen-dependent host immune responses and antibiotic treatment. We compare classical (fixed dose and duration) and adaptive (coupled to pathogen load) treatment regimes, exploring systematically infection outcomes such as time to clearance, immunopathology, host immunization, and selection of resistant bacteria. Our analysis and simulations uncover effective treatment strategies that promote synergy between the host immune system and the antimicrobial drug in clearing infection. Both in classical and adaptive treatment, we quantify how treatment timing and the strength of the immune response determine the success of moderate therapies. We explain key parameters and dimensions, where an adaptive regime differs from classical treatment, bringing new insight into the ongoing debate of resistance management. Emphasizing the sensitivity of treatment outcomes to the balance between external antibiotic intervention and endogenous natural defenses, our study calls for more empirical attention to host immunity processes. ');
INSERT INTO `papers` (`id`, `ano`, `journal`, `titulo`, `autores`, `afiliacao`, `pais`, `citacoes`, `palavra_chave`, `categorias`, `doi`, `pubmed`, `abstract`) VALUES
(87773, 2016, 'plos', 'The Development of Audio-Visual Integration for Temporal Judgements', 'Adams, Wendy J', 'Psychology, University of Southampton, Southampton, Hampshire, United Kingdom.', 'United Kingdom', 0, 'Acoustic Stimulation|Adolescent|Adult|Aging|Auditory Perception|Child|Child, Preschool|Computational Biology|Female|Humans|Judgment|Male|Models, Psychological|Photic Stimulation|Visual Perception|Young Adult', 'Journal Article', '10.1371/journal.pcbi.1004865', '27078834', 'Adults combine information from different sensory modalities to estimate object properties such as size or location. This process is optimal in that (i) sensory information is weighted according to relative reliability: more reliable estimates have more influence on the combined estimate and (ii) the combined estimate is more reliable than the component uni-modal estimates. Previous studies suggest that optimal sensory integration does not emerge until around 10 years of age. Younger children rely on a single modality or combine information using inappropriate sensory weights. Children aged 4-11 and adults completed a simple audio-visual task in which they reported either the number of beeps or the number of flashes in uni-modal and bi-modal conditions. In bi-modal trials, beeps and flashes differed in number by 0, 1 or 2. Mutual interactions between the sensory signals were evident at all ages: the reported number of flashes was influenced by the number of simultaneously presented beeps and vice versa. Furthermore, for all ages, the relative strength of these interactions was predicted by the relative reliabilities of the two modalities, in other words, all observers weighted the signals appropriately. The degree of cross-modal interaction decreased with age: the youngest observers could not ignore the task-irrelevant modality-they fully combined vision and audition such that they perceived equal numbers of flashes and beeps for bi-modal stimuli. Older observers showed much smaller effects of the task-irrelevant modality. Do these interactions reflect optimal integration? Full or partial cross-modal integration predicts improved reliability in bi-modal conditions. In contrast, switching between modalities reduces reliability. Model comparison suggests that older observers employed partial integration, whereas younger observers (up to around 8 years) did not integrate, but followed a sub-optimal switching strategy, responding according to either visual or auditory information on each trial. '),
(87774, 2016, 'plos', 'Visualization of Metabolic Interaction Networks in Microbial Communities Using VisANT 50', 'Granger, Brian R|Chang, Yi-Chien|Wang, Yan|DeLisi, Charles|Segrè, Daniel|Hu, Zhenjun', 'Bioinformatics Program, Boston University, Boston, Massachusetts, United States of America.|Bioinformatics Program, Boston University, Boston, Massachusetts, United States of America.|Bioinformatics Program, Boston University, Boston, Massachusetts, United States of America.|Bioinformatics Program, Boston University, Boston, Massachusetts, United States of America.|Bioinformatics Program, Boston University, Boston, Massachusetts, United States of America.|Center for Advanced Genomic Technology, Boston University, Boston, Massachusetts, United States of America.', 'United States|United States|United States|United States|United States|United States', 11, 'Computational Biology|Computer Graphics|Computer Simulation|Humans|Metabolic Networks and Pathways|Microbial Consortia|Microbiota|Models, Biological|Software|Systems Biology', 'Journal Article', '10.1371/journal.pcbi.1004875', '27081850', 'The complexity of metabolic networks in microbial communities poses an unresolved visualization and interpretation challenge. We address this challenge in the newly expanded version of a software tool for the analysis of biological networks, VisANT 5.0. We focus in particular on facilitating the visual exploration of metabolic interaction between microbes in a community, e.g. as predicted by COMETS (Computation of Microbial Ecosystems in Time and Space), a dynamic stoichiometric modeling framework. Using VisANTs unique metagraph implementation, we show how one can use VisANT 5.0 to explore different time-dependent ecosystem-level metabolic networks. In particular, we analyze the metabolic interaction network between two bacteria previously shown to display an obligate cross-feeding interdependency. In addition, we illustrate how a putative minimal gut microbiome community could be represented in our framework, making it possible to highlight interactions across multiple coexisting species. We envisage that the symbiotic layout of VisANT can be employed as a general tool for the analysis of metabolism in complex microbial communities as well as heterogeneous human tissues. VisANT is freely available at: http://visant.bu.edu and COMETS at http://comets.bu.edu. '),
(87775, 2016, 'plos', 'Oscillations via Spike-Timing Dependent Plasticity in a Feed-Forward Model', 'Luz, Yotam|Shamir, Maoz', 'Department of Physiology and Cell Biology Faculty of Health Sciences, Ben-Gurion University of the Negev, Beer-Sheva, Israel.|Department of Physiology and Cell Biology Faculty of Health Sciences, Ben-Gurion University of the Negev, Beer-Sheva, Israel.', 'Israel|Israel', 2, 'Action Potentials|Algorithms|Animals|Brain|Computational Biology|Computer Simulation|Feedback, Physiological|Humans|Learning|Models, Neurological|Neuronal Plasticity|Presynaptic Terminals', 'Journal Article', '10.1371/journal.pcbi.1004878', '27082118', 'Neuronal oscillatory activity has been reported in relation to a wide range of cognitive processes including the encoding of external stimuli, attention, and learning. Although the specific role of these oscillations has yet to be determined, it is clear that neuronal oscillations are abundant in the central nervous system. This raises the question of the origin of these oscillations: are the mechanisms for generating these oscillations genetically hard-wired or can they be acquired via a learning process? Here, we study the conditions under which oscillatory activity emerges through a process of spike timing dependent plasticity (STDP) in a feed-forward architecture. First, we analyze the effect of oscillations on STDP-driven synaptic dynamics of a single synapse, and study how the parameters that characterize the STDP rule and the oscillations affect the resultant synaptic weight. Next, we analyze STDP-driven synaptic dynamics of a pre-synaptic population of neurons onto a single post-synaptic cell. The pre-synaptic neural population is assumed to be oscillating at the same frequency, albeit with different phases, such that the net activity of the pre-synaptic population is constant in time. Thus, in the homogeneous case in which all synapses are equal, the post-synaptic neuron receives constant input and hence does not oscillate. To investigate the transition to oscillatory activity, we develop a mean-field Fokker-Planck approximation of the synaptic dynamics. We analyze the conditions causing the homogeneous solution to lose its stability. The findings show that oscillatory activity appears through a mechanism of spontaneous symmetry breaking. However, in the general case the homogeneous solution is unstable, and the synaptic dynamics does not converge to a different fixed point, but rather to a limit cycle. We show how the temporal structure of the STDP rule determines the stability of the homogeneous solution and the drift velocity of the limit cycle. '),
(87776, 2016, 'plos', 'AuPairWise: A Method to Estimate RNA-Seq Replicability through Co-expression', 'Ballouz, Sara|Gillis, Jesse', 'Stanley Institute for Cognitive Genomics, Cold Spring Harbor Laboratory, Cold Spring Harbor, New York, United States of America.|Stanley Institute for Cognitive Genomics, Cold Spring Harbor Laboratory, Cold Spring Harbor, New York, United States of America.', 'United States|United States', 6, 'Computational Biology|Databases, Nucleic Acid|Gene Expression|Humans|Models, Statistical|Quality Control|Reproducibility of Results|Sequence Analysis, RNA|Signal-To-Noise Ratio', 'Journal Article', '10.1371/journal.pcbi.1004868', '27082953', 'In addition to detecting novel transcripts and higher dynamic range, a principal claim for RNA-sequencing has been greater replicability, typically measured in sample-sample correlations of gene expression levels. Through a re-analysis of ENCODE data, we show that replicability of transcript abundances will provide misleading estimates of the replicability of conditional variation in transcript abundances (i.e., most expression experiments). Heuristics which implicitly address this problem have emerged in quality control measures to obtain good differential expression results. However, these methods involve strict filters such as discarding low expressing genes or using technical replicates to remove discordant transcripts, and are costly or simply ad hoc. As an alternative, we model gene-level replicability of differential activity using co-expressing genes. We find that sets of housekeeping interactions provide a sensitive means of estimating the replicability of expression changes, where the co-expressing pair can be regarded as pseudo-replicates of one another. We model the effects of noise that perturbs a genes expression within its usual distribution of values and show that perturbing expression by only 5% within that range is readily detectable (AUROC~0.73). We have made our method available as a set of easily implemented R scripts. '),
(87777, 2016, 'plos', 'APP Is a Context-Sensitive Regulator of the Hippocampal Presynaptic Active Zone', 'Laxc3x9fek, Melanie|Weingarten, Jens|Wegner, Martin|Mueller, Benjamin F|Rohmer, Marion|Baeumlisberger, Dominic|Arrey, Tabiwang N|Hick, Meike|Ackermann, Jxc3xb6rg|Acker-Palmer, Amparo|Koch, Ina|Mxc3xbcller, Ulrike|Karas, Michael|Volknandt, Walter', 'Institute for Cell Biology and Neuroscience, Biologicum, Johann Wolfgang Goethe-University, Frankfurt am Main, Germany.|Institute for Cell Biology and Neuroscience, Biologicum, Johann Wolfgang Goethe-University, Frankfurt am Main, Germany.|Institute for Molecular Bioinformatics, Johann Wolfgang Goethe-University, Frankfurt am Main, Germany.|Institute of Pharmaceutical Chemistry, Cluster of Excellence Macromolecular Complexes, Johann Wolfgang Goethe-University, Frankfurt am Main, Germany.|Institute of Pharmaceutical Chemistry, Cluster of Excellence Macromolecular Complexes, Johann Wolfgang Goethe-University, Frankfurt am Main, Germany.|SunChrom Wissenschaftliche Gerxc3xa4te GmbH, Friedrichsdorf, Germany.|Thermo Fisher Scientific, Bremen, Germany.|Department of Pharmacy and Molecular Biotechnology, University Heidelberg, Heidelberg Germany.|Institute for Molecular Bioinformatics, Johann Wolfgang Goethe-University, Frankfurt am Main, Germany.|Institute for Cell Biology and Neuroscience, Biologicum, Johann Wolfgang Goethe-University, Frankfurt am Main, Germany.|Institute for Molecular Bioinformatics, Johann Wolfgang Goethe-University, Frankfurt am Main, Germany.|Department of Pharmacy and Molecular Biotechnology, University Heidelberg, Heidelberg Germany.|Institute of Pharmaceutical Chemistry, Cluster of Excellence Macromolecular Complexes, Johann Wolfgang Goethe-University, Frankfurt am Main, Germany.|Institute for Cell Biology and Neuroscience, Biologicum, Johann Wolfgang Goethe-University, Frankfurt am Main, Germany.', 'Germany|Germany|Germany|Germany|Germany|Germany|Germany|Germany|Germany|Germany|Germany|Germany|Germ', 0, 'Alzheimer Disease|Amyloid beta-Protein Precursor|Animals|Computational Biology|Hippocampus|Humans|Mice|Mice, Inbred C57BL|Mice, Knockout|Presynaptic Terminals|Protein Interaction Maps|Proteome|Synapses', 'Journal Article', '10.1371/journal.pcbi.1004832', '27092780', 'The hallmarks of Alzheimers disease (AD) are characterized by cognitive decline and behavioral changes. The most prominent brain region affected by the progression of AD is the hippocampal formation. The pathogenesis involves a successive loss of hippocampal neurons accompanied by a decline in learning and memory consolidation mainly attributed to an accumulation of senile plaques. The amyloid precursor protein (APP) has been identified as precursor of Axcexb2-peptides, the main constituents of senile plaques. Until now, little is known about the physiological function of APP within the central nervous system. The allocation of APP to the proteome of the highly dynamic presynaptic active zone (PAZ) highlights APP as a yet unknown player in neuronal communication and signaling. In this study, we analyze the impact of APP deletion on the hippocampal PAZ proteome. The native hippocampal PAZ derived from APP mouse mutants (APP-KOs and NexCreAPP/APLP2-cDKOs) was isolated by subcellular fractionation and immunopurification. Subsequently, an isobaric labeling was performed using TMT6 for protein identification and quantification by high-resolution mass spectrometry. We combine bioinformatics tools and biochemical approaches to address the proteomics dataset and to understand the role of individual proteins. The impact of APP deletion on the hippocampal PAZ proteome was visualized by creating protein-protein interaction (PPI) networks that incorporated APP into the synaptic vesicle cycle, cytoskeletal organization, and calcium-homeostasis. The combination of subcellular fractionation, immunopurification, proteomic analysis, and bioinformatics allowed us to identify APP as structural and functional regulator in a context-sensitive manner within the hippocampal active zone network. '),
(87778, 2016, 'plos', 'Rapid Prediction of Bacterial Heterotrophic Fluxomics Using Machine Learning and Constraint Programming', 'Wu, Stephen Gang|Wang, Yuxuan|Jiang, Wu|Oyetunde, Tolutola|Yao, Ruilian|Zhang, Xuehong|Shimizu, Kazuyuki|Tang, Yinjie J|Bao, Forrest Sheng', 'Department of Energy, Environmental and Chemical Engineering, Washington University in St. Louis, St. Louis, Missouri, United States of America.|Department of Computer Science and Engineering, Ohio State University, Columbus, Ohio, United States of America.|Boxed Wholesale, Edison, New Jersey, United States of America.|Department of Energy, Environmental and Chemical Engineering, Washington University in St. Louis, St. Louis, Missouri, United States of America.|State Key Laboratory of Microbial Metabolism, School of Life Sciences and Biotechnology, Shanghai Jiao Tong University, Peoples Republic of China.|State Key Laboratory of Microbial Metabolism, School of Life Sciences and Biotechnology, Shanghai Jiao Tong University, Peoples Republic of China.|Institute of Advanced Biosciences, Keio University, Tsuruoka, Yamagata, Japan.|Department of Energy, Environmental and Chemical Engineering, Washington University in St. Louis, St. Louis, Missouri, United States of America.|Department of Electrical and Computer Engineering, University of Akron, Akron, Ohio, United States of America.', 'United States|United States|Jersey|United States|China|China|Japan|United States|United States', 0, 'Algorithms|Bacteria|Carbon Isotopes|Computational Biology|Decision Trees|Machine Learning|Metabolic Flux Analysis|Metabolic Networks and Pathways|Models, Biological|Support Vector Machine|Systems Biology', 'Comparative Study', '10.1371/journal.pcbi.1004838', '27092947', '13C metabolic flux analysis (13C-MFA) has been widely used to measure in vivo enzyme reaction rates (i.e., metabolic flux) in microorganisms. Mining the relationship between environmental and genetic factors and metabolic fluxes hidden in existing fluxomic data will lead to predictive models that can significantly accelerate flux quantification. In this paper, we present a web-based platform MFlux (http://mflux.org) that predicts the bacterial central metabolism via machine learning, leveraging data from approximately 100 13C-MFA papers on heterotrophic bacterial metabolisms. Three machine learning methods, namely Support Vector Machine (SVM), k-Nearest Neighbors (k-NN), and Decision Tree, were employed to study the sophisticated relationship between influential factors and metabolic fluxes. We performed a grid search of the best parameter set for each algorithm and verified their performance through 10-fold cross validations. SVM yields the highest accuracy among all three algorithms. Further, we employed quadratic programming to adjust flux profiles to satisfy stoichiometric constraints. Multiple case studies have shown that MFlux can reasonably predict fluxomes as a function of bacterial species, substrate types, growth rate, oxygen conditions, and cultivation methods. Due to the interest of studying model organism under particular carbon sources, bias of fluxome in the dataset may limit the applicability of machine learning models. This problem can be resolved after more papers on 13C-MFA are published for non-model species. '),
(87779, 2016, 'plos', 'Hippocampal CA1 Ripples as Inhibitory Transients', 'Malerba, Paola|Krishnan, Giri P|Fellous, Jean-Marc|Bazhenov, Maxim', 'Department of Cell Biology and Neuroscience, University of California Riverside, Riverside, California, United States of America.|Department of Cell Biology and Neuroscience, University of California Riverside, Riverside, California, United States of America.|Department of Psychology, University of Arizona, Tucson, Arizona, United States of America.|Department of Cell Biology and Neuroscience, University of California Riverside, Riverside, California, United States of America.', 'United States|United States|United States|United States', 14, 'Animals|CA1 Region, Hippocampal|CA3 Region, Hippocampal|Cerebral Cortex|Computational Biology|Humans|Interneurons|Memory Consolidation|Models, Animal|Models, Neurological|Models, Psychological|Nerve Net|Pyramidal Cells|Rats|Rats, Inbred BN|Sleep', 'Journal Article', '10.1371/journal.pcbi.1004880', '27093059', 'Memories are stored and consolidated as a result of a dialogue between the hippocampus and cortex during sleep. Neurons active during behavior reactivate in both structures during sleep, in conjunction with characteristic brain oscillations that may form the neural substrate of memory consolidation. In the hippocampus, replay occurs within sharp wave-ripples: short bouts of high-frequency activity in area CA1 caused by excitatory activation from area CA3. In this work, we develop a computational model of ripple generation, motivated by in vivo rat data showing that ripples have a broad frequency distribution, exponential inter-arrival times and yet highly non-variable durations. Our study predicts that ripples are not persistent oscillations but result from a transient network behavior, induced by input from CA3, in which the high frequency synchronous firing of perisomatic interneurons does not depend on the time scale of synaptic inhibition. We found that noise-induced loss of synchrony among CA1 interneurons dynamically constrains individual ripple duration. Our study proposes a novel mechanism of hippocampal ripple generation consistent with a broad range of experimental data, and highlights the role of noise in regulating the duration of input-driven oscillatory spiking in an inhibitory network. '),
(87780, 2016, 'plos', 'Effective Design of Multifunctional Peptides by Combining Compatible Functions', 'Diener, Christian|Garza Ramos Martínez, Georgina|Moreno Blas, Daniel|Castillo González, David A|Corzo, Gerardo|Castro-Obregon, Susana|Del Rio, Gabriel', 'Department of Biochemistry and Structural Biology, Institute of Cellular Physiology, Universidad Nacional Autónoma de México, Mexico City, Mexico.|Department of Biochemistry, Facultad de Medicina, Universidad Nacional Autónoma de México, Mexico City, Mexico.|Department of Neurodevelopment and Physiology, Institute of Cellular Physiology, Universidad Nacional Autónoma de México, Mexico City, Mexico.|Department of Biochemistry and Structural Biology, Institute of Cellular Physiology, Universidad Nacional Autónoma de México, Mexico City, Mexico.|Department of Molecular Medicine and Bioprocesses, Institute of Biotechnology, Universidad Nacional Autónoma de México, Cuernavaca Morelos, México.|Department of Neurodevelopment and Physiology, Institute of Cellular Physiology, Universidad Nacional Autónoma de México, Mexico City, Mexico.|Department of Biochemistry and Structural Biology, Institute of Cellular Physiology, Universidad Nacional Autónoma de México, Mexico City, Mexico.', 'Mexico|Mexico|Mexico|Mexico|-|Mexico|Mexico', 0, 'Algorithms|Amino Acid Sequence|Animals|Antimicrobial Cationic Peptides|Cell-Penetrating Peptides|Cells, Cultured|Computational Biology|DNA-Binding Proteins|Drug Design|Escherichia coli|Machine Learning|Mice|Models, Statistical|Molecular Sequence Data|Nuclear Localization Signals|Peptides|Protein Binding|Protein Engineering|Protein Structure, Secondary', 'Journal Article', '10.1371/journal.pcbi.1004786', '27096600', 'Multifunctionality is a common trait of many natural proteins and peptides, yet the rules to generate such multifunctionality remain unclear. We propose that the rules defining some protein/peptide functions are compatible. To explore this hypothesis, we trained a computational method to predict cell-penetrating peptides at the sequence level and learned that antimicrobial peptides and DNA-binding proteins are compatible with the rules of our predictor. Based on this finding, we expected that designing peptides for CPP activity may render AMP and DNA-binding activities. To test this prediction, we designed peptides that embedded two independent functional domains (nuclear localization and yeast pheromone activity), linked by optimizing their composition to fit the rules characterizing cell-penetrating peptides. These peptides presented effective cell penetration, DNA-binding, pheromone and antimicrobial activities, thus confirming the effectiveness of our computational approach to design multifunctional peptides with potential therapeutic uses. Our computational implementation is available at http://bis.ifc.unam.mx/en/software/dcf. '),
(87781, 2016, 'plos', 'A Computational Model of the Rainbow Trout Hypothalamus-Pituitary-Ovary-Liver Axis', 'Gillies, Kendall|Krone, Stephen M|Nagler, James J|Schultz, Irvin R', 'Battelle, Pacific Northwest National Laboratory, Marine Sciences Laboratory, Sequim, Washington, United States of America.|University of Idaho, Department of Mathematics, Moscow, Idaho, United States of America.|University of Idaho, Department of Biological Sciences and Center for Reproductive Biology, Moscow, Idaho, United States of America.|Battelle, Pacific Northwest National Laboratory, Marine Sciences Laboratory, Sequim, Washington, United States of America.', 'United States|United States|United States|United States', 14, 'Animals|Computational Biology|Computer Simulation|Female|Hormones|Hypothalamo-Hypophyseal System|Liver|Models, Biological|Oncorhynchus mykiss|Oocytes|Ovary|Reproduction|Signal Transduction|Systems Biology', 'Journal Article', '10.1371/journal.pcbi.1004874', '27096735', 'Reproduction in fishes and other vertebrates represents the timely coordination of many endocrine factors that culminate in the production of mature, viable gametes. In recent years there has been rapid growth in understanding fish reproductive biology, which has been motivated in part by recognition of the potential effects that climate change, habitat destruction and contaminant exposure can have on natural and cultured fish populations. New approaches to understanding the impacts of these stressors are being developed that require a systems biology approach with more biologically accurate and detailed mathematical models. We have developed a multi-scale mathematical model of the female rainbow trout hypothalamus-pituitary-ovary-liver axis to use as a tool to help understand the functioning of the system and for extrapolation of laboratory findings of stressor impacts on specific components of the axis. The model describes the essential endocrine components of the female rainbow trout reproductive axis. The model also describes the stage specific growth of maturing oocytes within the ovary and permits the presence of sub-populations of oocytes at different stages of development. Model formulation and parametrization was largely based on previously published in vivo and in vitro data in rainbow trout and new data on the synthesis of gonadotropins in the pituitary. Model predictions were validated against several previously published data sets for annual changes in gonadotropins and estradiol in rainbow trout. Estimates of select model parameters can be obtained from in vitro assays using either quantitative (direct estimation of rate constants) or qualitative (relative change from control values) approaches. This is an important aspect of mathematical models as in vitro, cell-based assays are expected to provide the bulk of experimental data for future risk assessments and will require quantitative physiological models to extrapolate across biological scales. '),
(87782, 2016, 'plos', 'Network-Based Interpretation of Diverse High-Throughput Datasets through the Omics Integrator Software Package', 'Tuncbag, Nurcan|Gosline, Sara J C|Kedaigle, Amanda|Soltis, Anthony R|Gitter, Anthony|Fraenkel, Ernest', 'Department of Biological Engineering, Massachusetts Institute of Technology, Cambridge, Massachusetts, United States of America.|Department of Biological Engineering, Massachusetts Institute of Technology, Cambridge, Massachusetts, United States of America.|Department of Biological Engineering, Massachusetts Institute of Technology, Cambridge, Massachusetts, United States of America.|Department of Biological Engineering, Massachusetts Institute of Technology, Cambridge, Massachusetts, United States of America.|Department of Biological Engineering, Massachusetts Institute of Technology, Cambridge, Massachusetts, United States of America.|Department of Biological Engineering, Massachusetts Institute of Technology, Cambridge, Massachusetts, United States of America.', 'United States|United States|United States|United States|United States|United States', 0, 'Algorithms|Computational Biology|Databases, Genetic|Epigenesis, Genetic|Gene Expression Profiling|Gene Regulatory Networks|High-Throughput Nucleotide Sequencing|Humans|Lung Neoplasms|Protein Interaction Maps|Software|Transcription Factors', 'Journal Article', '10.1371/journal.pcbi.1004879', '27096930', 'High-throughput, omic methods provide sensitive measures of biological responses to perturbations. However, inherent biases in high-throughput assays make it difficult to interpret experiments in which more than one type of data is collected. In this work, we introduce Omics Integrator, a software package that takes a variety of omic data as input and identifies putative underlying molecular pathways. The approach applies advanced network optimization algorithms to a network of thousands of molecular interactions to find high-confidence, interpretable subnetworks that best explain the data. These subnetworks connect changes observed in gene expression, protein abundance or other global assays to proteins that may not have been measured in the screens due to inherent bias or noise in measurement. This approach reveals unannotated molecular pathways that would not be detectable by searching pathway databases. Omics Integrator also provides an elegant framework to incorporate not only positive data, but also negative evidence. Incorporating negative evidence allows Omics Integrator to avoid unexpressed genes and avoid being biased toward highly-studied hub proteins, except when they are strongly implicated by the data. The software is comprised of two individual tools, Garnet and Forest, that can be run together or independently to allow a user to perform advanced integration of multiple types of high-throughput data as well as create condition-specific subnetworks of protein interactions that best connect the observed changes in various datasets. It is available at http://fraenkel.mit.edu/omicsintegrator and on GitHub at https://github.com/fraenkel-lab/OmicsIntegrator. '),
(87783, 2016, 'plos', 'CNVkit: Genome-Wide Copy Number Detection and Visualization from Targeted DNA Sequencing', 'Talevich, Eric|Shain, A Hunter|Botton, Thomas|Bastian, Boris C', 'Department of Dermatology, University of California, San Francisco, San Francisco, California, United States of America.|Department of Dermatology, University of California, San Francisco, San Francisco, California, United States of America.|Department of Dermatology, University of California, San Francisco, San Francisco, California, United States of America.|Department of Dermatology, University of California, San Francisco, San Francisco, California, United States of America.', 'United States|United States|United States|United States', 313, 'Comparative Genomic Hybridization|Computational Biology|DNA Copy Number Variations|Genome, Human|Genome-Wide Association Study|High-Throughput Nucleotide Sequencing|Humans|In Situ Hybridization, Fluorescence|Sequence Analysis, DNA|Software', 'Journal Article', '10.1371/journal.pcbi.1004873', '27100738', 'Germline copy number variants (CNVs) and somatic copy number alterations (SCNAs) are of significant importance in syndromic conditions and cancer. Massively parallel sequencing is increasingly used to infer copy number information from variations in the read depth in sequencing data. However, this approach has limitations in the case of targeted re-sequencing, which leaves gaps in coverage between the regions chosen for enrichment and introduces biases related to the efficiency of target capture and library preparation. We present a method for copy number detection, implemented in the software package CNVkit, that uses both the targeted reads and the nonspecifically captured off-target reads to infer copy number evenly across the genome. This combination achieves both exon-level resolution in targeted regions and sufficient resolution in the larger intronic and intergenic regions to identify copy number changes. In particular, we successfully inferred copy number at equivalent to 100-kilobase resolution genome-wide from a platform targeting as few as 293 genes. After normalizing read counts to a pooled reference, we evaluated and corrected for three sources of bias that explain most of the extraneous variability in the sequencing read depth: GC content, target footprint size and spacing, and repetitive sequences. We compared the performance of CNVkit to copy number changes identified by array comparative genomic hybridization. We packaged the components of CNVkit so that it is straightforward to use and provides visualizations, detailed reporting of significant features, and export options for integration into existing analysis pipelines. CNVkit is freely available from https://github.com/etal/cnvkit. '),
(87784, 2016, 'plos', 'Single-Cell Co-expression Analysis Reveals Distinct Functional Modules, Co-regulation Mechanisms and Clinical Outcomes', 'Wang, Jie|Xia, Shuli|Arand, Brian|Zhu, Heng|Machiraju, Raghu|Huang, Kun|Ji, Hongkai|Qian, Jiang', 'The Wilmer Eye Institute, Johns Hopkins University School of Medicine, Baltimore, Maryland, United States of America.|Department of Neurology, Johns Hopkins University School of Medicine, Baltimore, Maryland, United States of America.|Department of Computer Science and Engineering, the Ohio State University, Columbus, Ohio, United States of America.|The Sidney Kimmel Comprehensive Cancer Center, Johns Hopkins University School of Medicine, Baltimore, Maryland, United States of America.|Department of Computer Science and Engineering, the Ohio State University, Columbus, Ohio, United States of America.|Department of Computer Science and Engineering, the Ohio State University, Columbus, Ohio, United States of America.|Department of Biostatistics, Johns Hopkins University Bloomberg School of Public Health, Baltimore, Maryland, United States of America.|The Wilmer Eye Institute, Johns Hopkins University School of Medicine, Baltimore, Maryland, United States of America.', 'United States|United States|United States|United States|United States|United States|United States|Un', 6, 'Brain Neoplasms|Computational Biology|Computer Simulation|Glioblastoma|Humans|Male|Models, Genetic|Multigene Family|Prognosis|Prostatic Neoplasms|Protein Interaction Maps|Single-Cell Analysis|Transcriptome', 'Journal Article', '10.1371/journal.pcbi.1004892', '27100869', 'Co-expression analysis has been employed to predict gene function, identify functional modules, and determine tumor subtypes. Previous co-expression analysis was mainly conducted at bulk tissue level. It is unclear whether co-expression analysis at the single-cell level will provide novel insights into transcriptional regulation. Here we developed a computational approach to compare glioblastoma expression profiles at the single-cell level with those obtained from bulk tumors. We found that the co-expressed genes observed in single cells and bulk tumors have little overlap and show distinct characteristics. The co-expressed genes identified in bulk tumors tend to have similar biological functions, and are enriched for intrachromosomal interactions with synchronized promoter activity. In contrast, single-cell co-expressed genes are enriched for known protein-protein interactions, and are regulated through interchromosomal interactions. Moreover, gene members of some protein complexes are co-expressed only at the bulk level, while those of other complexes are co-expressed at both single-cell and bulk levels. Finally, we identified a set of co-expressed genes that can predict the survival of glioblastoma patients. Our study highlights that comparative analyses of single-cell and bulk gene expression profiles enable us to identify functional modules that are regulated at different levels and hold great translational potential. '),
(87785, 2016, 'plos', 'Modularity Induced Gating and Delays in Neuronal Networks', 'Shein-Idelson, Mark|Cohen, Gilad|Ben-Jacob, Eshel|Hanein, Yael', 'School of Electrical Engineering, Tel Aviv University, Tel Aviv, Israel.|School of Electrical Engineering, Tel Aviv University, Tel Aviv, Israel.|Tel Aviv University Center for Nanoscience and Nanotechnology, Tel Aviv, Israel.|School of Electrical Engineering, Tel Aviv University, Tel Aviv, Israel.', 'Israel|Israel|Israel|Israel', 0, 'Animals|Bioengineering|Cell Communication|Cells, Cultured|Computational Biology|Computer Simulation|Electrophysiological Phenomena|In Vitro Techniques|Models, Neurological|Nerve Net|Neurons|Rats|Synaptic Transmission', 'Journal Article', '10.1371/journal.pcbi.1004883', '27104350', 'Neural networks, despite their highly interconnected nature, exhibit distinctly localized and gated activation. Modularity, a distinctive feature of neural networks, has been recently proposed as an important parameter determining the manner by which networks support activity propagation. Here we use an engineered biological model, consisting of engineered rat cortical neurons, to study the role of modular topology in gating the activity between cell populations. We show that pairs of connected modules support conditional propagation (transmitting stronger bursts with higher probability), long delays and propagation asymmetry. Moreover, large modular networks manifest diverse patterns of both local and global activation. Blocking inhibition decreased activity diversity and replaced it with highly consistent transmission patterns. By independently controlling modularity and disinhibition, experimentally and in a model, we pose that modular topology is an important parameter affecting activation localization and is instrumental for population-level gating by disinhibition. '),
(87786, 2016, 'plos', 'The Role of Genome Accessibility in Transcription Factor Binding in Bacteria', 'Gomes, Antonio L C|Wang, Harris H', 'Department of Systems Biology, Columbia University, New York, New York, United States of America.|Department of Systems Biology, Columbia University, New York, New York, United States of America.', 'United States|United States', 2, 'Bacteria|Biophysical Phenomena|Chromatin Immunoprecipitation|Computational Biology|Gene Regulatory Networks|Genome, Bacterial|Linear Models|Models, Biological|Mycobacterium tuberculosis|Protein Binding|Sequence Analysis, DNA|Systems Biology|Thermodynamics|Transcription Factors', 'Journal Article', '10.1371/journal.pcbi.1004891', '27104615', 'ChIP-seq enables genome-scale identification of regulatory regions that govern gene expression. However, the biological insights generated from ChIP-seq analysis have been limited to predictions of binding sites and cooperative interactions. Furthermore, ChIP-seq data often poorly correlate with in vitro measurements or predicted motifs, highlighting that binding affinity alone is insufficient to explain transcription factor (TF)-binding in vivo. One possibility is that binding sites are not equally accessible across the genome. A more comprehensive biophysical representation of TF-binding is required to improve our ability to understand, predict, and alter gene expression. Here, we show that genome accessibility is a key parameter that impacts TF-binding in bacteria. We developed a thermodynamic model that parameterizes ChIP-seq coverage in terms of genome accessibility and binding affinity. The role of genome accessibility is validated using a large-scale ChIP-seq dataset of the M. tuberculosis regulatory network. We find that accounting for genome accessibility led to a model that explains 63% of the ChIP-seq profile variance, while a model based in motif score alone explains only 35% of the variance. Moreover, our framework enables de novo ChIP-seq peak prediction and is useful for inferring TF-binding peaks in new experimental conditions by reducing the need for additional experiments. We observe that the genome is more accessible in intergenic regions, and that increased accessibility is positively correlated with gene expression and anti-correlated with distance to the origin of replication. Our biophysically motivated model provides a more comprehensive description of TF-binding in vivo from first principles towards a better representation of gene regulation in silico, with promising applications in systems biology. '),
(87787, 2016, 'plos', 'Bulk Genotyping of Biopsies Can Create Spurious Evidence for Hetereogeneity in Mutation Content', 'Kostadinov, Rumen|Maley, Carlo C|Kuhner, Mary K', 'Pediatric Oncology, Johns Hopkins School of Medicine, Baltimore, Maryland, United States of America.|Center for Evolution and Cancer, University of California, San Francisco, San Francisco, California, United States of America.|Department of Genome Sciences, University of Washington, Seattle, Washington, United States of America.', 'United States|United States|United States', 14, 'Barrett Esophagus|Biopsy|Computational Biology|Computer Simulation|DNA Mutational Analysis|DNA, Neoplasm|Genotype|Humans|Models, Genetic|Mutation|Neoplasms|Selection, Genetic', 'Journal Article', '10.1371/journal.pcbi.1004413', '27105344', 'When multiple samples are taken from the neoplastic tissues of a single patient, it is natural to compare their mutation content. This is often done by bulk genotyping of whole biopsies, but the chance that a mutation will be detected in bulk genotyping depends on its local frequency in the sample. When the underlying mutation count per cell is equal, homogenous biopsies will have more high-frequency mutations, and thus more detectable mutations, than heterogeneous ones. Using simulations, we show that bulk genotyping of data simulated under a neutral model of somatic evolution generates strong spurious evidence for non-neutrality, because the pattern of tissue growth systematically generates differences in biopsy heterogeneity. Any experiment which compares mutation content across bulk-genotyped biopsies may therefore suggest mutation rate or selection intensity variation even when these forces are absent. We discuss computational and experimental approaches for resolving this problem. '),
(87788, 2016, 'plos', 'Reconstruction of Cell Surface Densities of Ion Pumps, Exchangers, and Channels from mRNA Expression, Conductance Kinetics, Whole-Cell Calcium, and Current-Clamp Voltage Recordings, with an Application to Human Uterine Smooth Muscle Cells', 'Atia, Jolene|McCloskey, Conor|Shmygol, Anatoly S|Rand, David A|van den Berg, Hugo A|Blanks, Andrew M', 'Division of Reproductive Health, Warwick Medical School, University of Warwick, Coventry, United Kingdom.|Division of Reproductive Health, Warwick Medical School, University of Warwick, Coventry, United Kingdom.|Division of Reproductive Health, Warwick Medical School, University of Warwick, Coventry, United Kingdom.|University of Warwick, Coventry, United Kingdom.|University of Warwick, Coventry, United Kingdom.|Division of Reproductive Health, Warwick Medical School, University of Warwick, Coventry, United Kingdom.', 'United Kingdom|United Kingdom|United Kingdom|United Kingdom|United Kingdom|United Kingdom', 10, 'Action Potentials|Biophysical Phenomena|Calcium|Cell Membrane|Computational Biology|Computer Simulation|Female|Gene Expression Profiling|Humans|Ion Channel Gating|Ion Channels|Ion Pumps|Ion Transport|Kinetics|Membrane Potentials|Models, Biological|Myocytes, Smooth Muscle|Myometrium|Patch-Clamp Techniques|RNA, Messenger', 'Journal Article', '10.1371/journal.pcbi.1004828', '27105427', 'Uterine smooth muscle cells remain quiescent throughout most of gestation, only generating spontaneous action potentials immediately prior to, and during, labor. This study presents a method that combines transcriptomics with biophysical recordings to characterise the conductance repertoire of these cells, the conductance repertoire being the total complement of ion channels and transporters expressed by an electrically active cell. Transcriptomic analysis provides a set of potential electrogenic entities, of which the conductance repertoire is a subset. Each entity within the conductance repertoire was modeled independently and its gating parameter values were fixed using the available biophysical data. The only remaining free parameters were the surface densities for each entity. We characterise the space of combinations of surface densities (density vectors) consistent with experimentally observed membrane potential and calcium waveforms. This yields insights on the functional redundancy of the system as well as its behavioral versatility. Our approach couples high-throughput transcriptomic data with physiological behaviors in health and disease, and provides a formal method to link genotype to phenotype in excitable systems. We accurately predict current densities and chart functional redundancy. For example, we find that to evoke the observed voltage waveform, the BK channel is functionally redundant whereas hERG is essential. Furthermore, our analysis suggests that activation of calcium-activated chloride conductances by intracellular calcium release is the key factor underlying spontaneous depolarisations. '),
(87789, 2016, 'plos', 'A Geometrically-Constrained Mathematical Model of Mammary Gland Ductal Elongation Reveals Novel Cellular Dynamics within the Terminal End Bud', 'Paine, Ingrid|Chauviere, Arnaud|Landua, John|Sreekumar, Amulya|Cristini, Vittorio|Rosen, Jeffrey|Lewis, Michael T', 'Lester and Sue Smith Breast Center, Baylor College of Medicine, Houston, Texas, United States of America.|University Grenoble Alpes, TIMC-IMAG (DyCTiM), Grenoble, France.|Lester and Sue Smith Breast Center, Baylor College of Medicine, Houston, Texas, United States of America.|Department of Molecular and Cellular Biology, Baylor College of Medicine, Houston, Texas, United States of America.|Department of NanoMedicine and Biomedical Engineering, University of Texas Medical School at Houston, Houston, Texas, United States of America.|Department of Molecular and Cellular Biology, Baylor College of Medicine, Houston, Texas, United States of America.|Lester and Sue Smith Breast Center, Baylor College of Medicine, Houston, Texas, United States of America.', 'United States|France|United States|United States|United States|United States|United States', 25, 'Animals|Apoptosis|Body Patterning|Cell Cycle|Cell Proliferation|Cell Size|Computational Biology|Female|Kinetics|Mammary Glands, Animal|Mice|Mice, Inbred BALB C|Mice, Transgenic|Models, Anatomic|Models, Biological|Sexual Maturation', 'Journal Article', '10.1371/journal.pcbi.1004839', '27115287', 'Mathematics is often used to model biological systems. In mammary gland development, mathematical modeling has been limited to acinar and branching morphogenesis and breast cancer, without reference to normal duct formation. We present a model of ductal elongation that exploits the geometrically-constrained shape of the terminal end bud (TEB), the growing tip of the duct, and incorporates morphometrics, region-specific proliferation and apoptosis rates. Iterative model refinement and behavior analysis, compared with biological data, indicated that the traditional metric of nipple to the ductal front distance, or percent fat pad filled to evaluate ductal elongation rate can be misleading, as it disregards branching events that can reduce its magnitude. Further, model driven investigations of the fates of specific TEB cell types confirmed migration of cap cells into the body cell layer, but showed their subsequent preferential elimination by apoptosis, thus minimizing their contribution to the luminal lineage and the mature duct. '),
(87790, 2016, 'plos', 'Constraints on Biological Mechanism from Disease Comorbidity Using Electronic Medical Records and Database of Genetic Variants', 'Bagley, Steven C|Sirota, Marina|Chen, Richard|Butte, Atul J|Altman, Russ B', 'Department of Genetics, Stanford University, Stanford, California, United States of America.|UCSF Institute for Computational Health Sciences, San Francisco, California, United States of America.|Personalis, Inc., Menlo Park, California, United States of America.|UCSF Institute for Computational Health Sciences, San Francisco, California, United States of America.|Department of Genetics, Stanford University, Stanford, California, United States of America.', 'United States|United States|United States|United States|United States', 12, 'Age Factors|Cluster Analysis|Comorbidity|Computational Biology|Databases, Genetic|Electronic Health Records|Genetic Variation|Humans|Models, Statistical', 'Journal Article', '10.1371/journal.pcbi.1004885', '27115429', 'Patterns of disease co-occurrence that deviate from statistical independence may represent important constraints on biological mechanism, which sometimes can be explained by shared genetics. In this work we study the relationship between disease co-occurrence and commonly shared genetic architecture of disease. Records of pairs of diseases were combined from two different electronic medical systems (Columbia, Stanford), and compared to a large database of published disease-associated genetic variants (VARIMED), data on 35 disorders were available across all three sources, which include medical records for over 1.2 million patients and variants from over 17,000 publications. Based on the sources in which they appeared, disease pairs were categorized as having predominant clinical, genetic, or both kinds of manifestations. Confounding effects of age on disease incidence were controlled for by only comparing diseases when they fall in the same cluster of similarly shaped incidence patterns. We find that disease pairs that are overrepresented in both electronic medical record systems and in VARIMED come from two main disease classes, autoimmune and neuropsychiatric. We furthermore identify specific genes that are shared within these disease groups. ');
INSERT INTO `papers` (`id`, `ano`, `journal`, `titulo`, `autores`, `afiliacao`, `pais`, `citacoes`, `palavra_chave`, `categorias`, `doi`, `pubmed`, `abstract`) VALUES
(87791, 2016, 'plos', 'Rigid Residue Scan Simulations Systematically Reveal Residue Entropic Roles in Protein Allostery', 'Kalescky, Robert|Zhou, Hongyu|Liu, Jin|Tao, Peng', 'Department of Chemistry, Center for Drug Discovery, Design, and Delivery (CD4), Center for Scientific Computation, Southern Methodist University, Dallas, Texas, United States of America.|Department of Chemistry, Center for Drug Discovery, Design, and Delivery (CD4), Center for Scientific Computation, Southern Methodist University, Dallas, Texas, United States of America.|Department of Chemistry, Center for Drug Discovery, Design, and Delivery (CD4), Center for Scientific Computation, Southern Methodist University, Dallas, Texas, United States of America.|Department of Chemistry, Center for Drug Discovery, Design, and Delivery (CD4), Center for Scientific Computation, Southern Methodist University, Dallas, Texas, United States of America.', 'United States|United States|United States|United States', 18, 'Allosteric Regulation|Computational Biology|Computer Simulation|Entropy|Humans|Ligands|Models, Molecular|Molecular Dynamics Simulation|Nuclear Magnetic Resonance, Biomolecular|PDZ Domains|Principal Component Analysis|Protein Binding|Protein Tyrosine Phosphatase, Non-Receptor Type 13|Proteins', 'Journal Article', '10.1371/journal.pcbi.1004893', '27115535', 'Intra-protein information is transmitted over distances via allosteric processes. This ubiquitous protein process allows for protein function changes due to ligand binding events. Understanding protein allostery is essential to understanding protein functions. In this study, allostery in the second PDZ domain (PDZ2) in the human PTP1E protein is examined as model system to advance a recently developed rigid residue scan method combining with configurational entropy calculation and principal component analysis. The contributions from individual residues to whole-protein dynamics and allostery were systematically assessed via rigid body simulations of both unbound and ligand-bound states of the protein. The entropic contributions of individual residues to whole-protein dynamics were evaluated based on covariance-based correlation analysis of all simulations. The changes of overall protein entropy when individual residues being held rigid support that the rigidity/flexibility equilibrium in protein structure is governed by the La Châteliers principle of chemical equilibrium. Key residues of PDZ2 allostery were identified with good agreement with NMR studies of the same protein bound to the same peptide. On the other hand, the change of entropic contribution from each residue upon perturbation revealed intrinsic differences among all the residues. The quasi-harmonic and principal component analyses of simulations without rigid residue perturbation showed a coherent allosteric mode from unbound and bound states, respectively. The projection of simulations with rigid residue perturbation onto coherent allosteric modes demonstrated the intrinsic shifting of ensemble distributions supporting the population-shift theory of protein allostery. Overall, the study presented here provides a robust and systematic approach to estimate the contribution of individual residue internal motion to overall protein dynamics and allostery. '),
(87792, 2016, 'plos', 'An Electrostatic Funnel in the GABA-Binding Pathway', 'Carpenter, Timothy S|Lightstone, Felice C', 'Biosciences and Biotechnology Division, Physical and Life Sciences Directorate, Lawrence Livermore National Laboratory, Livermore, California, United States of America.|Biosciences and Biotechnology Division, Physical and Life Sciences Directorate, Lawrence Livermore National Laboratory, Livermore, California, United States of America.', 'United States|United States', 4, 'Animals|Binding Sites|Computational Biology|Computer Simulation|Humans|Ion Channel Gating|Ligands|Models, Molecular|Molecular Dynamics Simulation|Protein Interaction Domains and Motifs|Protein Subunits|Receptors, GABA-A|Static Electricity|gamma-Aminobutyric Acid', 'Journal Article', '10.1371/journal.pcbi.1004831', '27119953', 'The xcexb3-aminobutyric acid type A receptor (GABAA-R) is a major inhibitory neuroreceptor that is activated by the binding of GABA. The structure of the GABAA-R is well characterized, and many of the binding site residues have been identified. However, most of these residues are obscured behind the C-loop that acts as a cover to the binding site. Thus, the mechanism by which the GABA molecule recognizes the binding site, and the pathway it takes to enter the binding site are both unclear. Through the completion and detailed analysis of 100 short, unbiased, independent molecular dynamics simulations, we have investigated this phenomenon of GABA entering the binding site. In each system, GABA was placed quasi-randomly near the binding site of a GABAA-R homology model, and atomistic simulations were carried out to observe the behavior of the GABA molecules. GABA fully entered the binding site in 19 of the 100 simulations. The pathway taken by these molecules was consistent and non-random, the GABA molecules approach the binding site from below, before passing up behind the C-loop and into the binding site. This binding pathway is driven by long-range electrostatic interactions, whereby the electrostatic field acts as a funnel that sweeps the GABA molecules towards the binding site, at which point more specific atomic interactions take over. These findings define a nuanced mechanism whereby the GABAA-R uses the general zwitterionic features of the GABA molecule to identify a potential ligand some 2 nm away from the binding site. '),
(87793, 2016, 'plos', 'The Evolution of Quorum Sensing as a Mechanism to Infer Kinship', 'Schluter, Jonas|Schoech, Armin P|Foster, Kevin R|Mitri, Sara', 'Computational Biology Program, Sloan-Kettering Institute, Memorial Sloan-Kettering Cancer Center, New York, New York, United States of America.|Department of Systems Biology, Harvard Medical School, Boston, Massachusetts, United States of America.|Department of Zoology, University of Oxford, Oxford, United Kingdom.|Department of Fundamental Microbiology, University of Lausanne, Switzerland.', 'United States|United States|United Kingdom|Switzerland', 24, 'Bacteria|Bacterial Physiological Phenomena|Biological Evolution|Computer Simulation|Microbial Consortia|Models, Biological|Quorum Sensing', 'Journal Article', '10.1371/journal.pcbi.1004848', '27120081', 'Bacteria regulate many phenotypes via quorum sensing systems. Quorum sensing is typically thought to evolve because the regulated cooperative phenotypes are only beneficial at certain cell densities. However, quorum sensing systems are also threatened by non-cooperative cheaters that may exploit quorum-sensing regulated cooperation, which begs the question of how quorum sensing systems are maintained in nature. Here we study the evolution of quorum sensing using an individual-based model that captures the natural ecology and population structuring of microbial communities. We first recapitulate the two existing observations on quorum sensing evolution: density-dependent benefits favor quorum sensing but competition and cheating will destabilize it. We then model quorum sensing in a dense community like a biofilm, which reveals a novel benefit to quorum sensing that is intrinsically evolutionarily stable. In these communities, competing microbial genotypes gradually segregate over time leading to positive correlation between density and genetic similarity between neighboring cells (relatedness). This enables quorum sensing to track genetic relatedness and ensures that costly cooperative traits are only activated once a cell is safely surrounded by clonemates. We hypothesize that under similar natural conditions, the benefits of quorum sensing will not result from an assessment of density but from the ability to infer kinship.'),
(87794, 2016, 'plos', 'MEDYAN: Mechanochemical Simulations of Contraction and Polarity Alignment in Actomyosin Networks', 'Popov, Konstantin|Komianos, James|Papoian, Garegin A', 'Department of Chemistry and Biochemistry, University of Maryland, College Park, Maryland, United States of America.|Department of Chemistry and Biochemistry, University of Maryland, College Park, Maryland, United States of America.|Department of Chemistry and Biochemistry, University of Maryland, College Park, Maryland, United States of America.', 'United States|United States|United States', 26, 'Actomyosin|Animals|Biomechanical Phenomena|Computational Biology|Computer Simulation|Cytoskeleton|Humans|Models, Biological|Models, Molecular|Muscle Contraction|Nonlinear Dynamics|Software|Stochastic Processes|Systems Biology', 'Journal Article', '10.1371/journal.pcbi.1004877', '27120189', 'Active matter systems, and in particular the cell cytoskeleton, exhibit complex mechanochemical dynamics that are still not well understood. While prior computational models of cytoskeletal dynamics have lead to many conceptual insights, an important niche still needs to be filled with a high-resolution structural modeling framework, which includes a minimally-complete set of cytoskeletal chemistries, stochastically treats reaction and diffusion processes in three spatial dimensions, accurately and efficiently describes mechanical deformations of the filamentous network under stresses generated by molecular motors, and deeply couples mechanics and chemistry at high spatial resolution. To address this need, we propose a novel reactive coarse-grained force field, as well as a publicly available software package, named the Mechanochemical Dynamics of Active Networks (MEDYAN), for simulating active network evolution and dynamics (available at www.medyan.org). This model can be used to study the non-linear, far from equilibrium processes in active matter systems, in particular, comprised of interacting semi-flexible polymers embedded in a solution with complex reaction-diffusion processes. In this work, we applied MEDYAN to investigate a contractile actomyosin network consisting of actin filaments, alpha-actinin cross-linking proteins, and non-muscle myosin IIA mini-filaments. We found that these systems undergo a switch-like transition in simulations from a random network to ordered, bundled structures when cross-linker concentration is increased above a threshold value, inducing contraction driven by myosin II mini-filaments. Our simulations also show how myosin II mini-filaments, in tandem with cross-linkers, can produce a range of actin filament polarity distributions and alignment, which is crucially dependent on the rate of actin filament turnover and the actin filaments resulting super-diffusive behavior in the actomyosin-cross-linker system. We discuss the biological implications of these findings for the arc formation in lamellipodium-to-lamellum architectural remodeling. Lastly, our simulations produce force-dependent accumulation of myosin II, which is thought to be responsible for their mechanosensation ability, also spontaneously generating myosin II concentration gradients in the solution phase of the simulation volume. '),
(87795, 2016, 'plos', 'Parasites Sustain and Enhance RNA-Like Replicators through Spatial Self-Organisation', 'Colizzi, Enrico Sandro|Hogeweg, Paulien', 'Theoretical Biology and Bioinformatics, Utrecht University, Utrecht, The Netherlands.|Theoretical Biology and Bioinformatics, Utrecht University, Utrecht, The Netherlands.', 'Netherlands|Netherlands', 7, 'Animals|Computational Biology|Evolution, Molecular|Genetic Speciation|Models, Biological|Origin of Life|Parasites|RNA', 'Journal Article', '10.1371/journal.pcbi.1004902', '27120344', 'In a prebiotic RNA world, parasitic behaviour may be favoured because template dependent replication happens in trans, thus being altruistic. Spatially extended systems are known to reduce harmful effects of parasites. Here we present a spatial system to show that evolution of replication is (indirectly) enhanced by strong parasites, and we characterise the phase transition that leads to this mode of evolution. Building on the insights of this analysis, we identify two scenarios, namely periodic disruptions and longer replication time-span, in which speciation occurs and an evolved parasite-like lineage enables the evolutionary increase of replication rates in replicators. Finally, we show that parasites co-evolving with replicators are selected to become weaker, i.e. worse templates for replication when the duration of replication is increased. We conclude that parasites may not be considered a problem for evolution in a prebiotic system, but a degree of freedom that can be exploited by evolution to enhance the evolvability of replicators, by means of emergent levels of selection. '),
(87796, 2016, 'plos', 'Principles and Overview of Sampling Methods for Modeling Macromolecular Structure and Dynamics', 'Maximova, Tatiana|Moffatt, Ryan|Ma, Buyong|Nussinov, Ruth|Shehu, Amarda', 'Department of Computer Science, George Mason University, Fairfax, Virginia, United States of America.|Department of Computer Science, George Mason University, Fairfax, Virginia, United States of America.|Basic Science Program, Leidos Biomedical Research, Inc. Cancer and Inflammation Program, National Cancer Institute, Frederick, Maryland, United States of America.|Basic Science Program, Leidos Biomedical Research, Inc. Cancer and Inflammation Program, National Cancer Institute, Frederick, Maryland, United States of America.|Department of Computer Science, George Mason University, Fairfax, Virginia, United States of America.', 'United States|United States|United States|United States|United States', 106, 'Algorithms|Computational Biology|Computer Simulation|Macromolecular Substances|Models, Molecular|Molecular Dynamics Simulation|Molecular Structure|Monte Carlo Method|Nucleic Acids|Protein Folding|Protein Interaction Domains and Motifs', 'Journal Article', '10.1371/journal.pcbi.1004619', '27124275', 'Investigation of macromolecular structure and dynamics is fundamental to understanding how macromolecules carry out their functions in the cell. Significant advances have been made toward this end in silico, with a growing number of computational methods proposed yearly to study and simulate various aspects of macromolecular structure and dynamics. This review aims to provide an overview of recent advances, focusing primarily on methods proposed for exploring the structure space of macromolecules in isolation and in assemblies for the purpose of characterizing equilibrium structure and dynamics. In addition to surveying recent applications that showcase current capabilities of computational methods, this review highlights state-of-the-art algorithmic techniques proposed to overcome challenges posed in silico by the disparate spatial and time scales accessed by dynamic macromolecules. This review is not meant to be exhaustive, as such an endeavor is impossible, but rather aims to balance breadth and depth of strategies for modeling macromolecular structure and dynamics for a broad audience of novices and experts.'),
(87797, 2016, 'plos', 'A Drug-Centric View of Drug Development: How Drugs Spread from Disease to Disease', 'Rodriguez-Esteban, Raul', 'Roche Pharmaceutical Research and Early Development, pRED Informatics, Roche Innovation Center, Basel, Switzerland.', 'Switzerland', 10, 'Clinical Trials as Topic|Computational Biology|Databases, Pharmaceutical|Disease|Drug Discovery|Drug Therapy|Humans|Models, Biological', 'Journal Article', '10.1371/journal.pcbi.1004852', '27124390', 'Drugs are often seen as ancillary to the purpose of fighting diseases. Here an alternative view is proposed in which they occupy a spearheading role. In this view, drugs are technologies with an inherent therapeutic potential. Once created, they can spread from disease to disease independently of the drug creators original intentions. Through the analysis of extensive literature and clinical trial records, it can be observed that successful drugs follow a life cycle in which they are studied at an increasing rate, and for the treatment of an increasing number of diseases, leading to clinical advancement. Such initial growth, following a power law on average, has a degree of momentum, but eventually decelerates, leading to stagnation and decay. A network model can describe the propagation of drugs from disease to disease in which diseases communicate with each other by receiving and sending drugs. Within this model, some diseases appear more prone to influence other diseases than be influenced, and vice versa. Diseases can also be organized into a drug-centric disease taxonomy based on the drugs that each adopts. This taxonomy reflects not only biological similarities across diseases, but also the level of differentiation of existing therapies. In sum, this study shows that drugs can become contagious technologies playing a driving role in the fight against disease. By better understanding such dynamics, pharmaceutical developers may be able to manage drug projects more effectively.'),
(87798, 2016, 'plos', 'A Network Biology Approach Identifies Molecular Cross-Talk between Normal Prostate Epithelial and Prostate Carcinoma Cells', 'Trevino, Victor|Cassese, Alberto|Nagy, Zsuzsanna|Zhuang, Xiaodong|Herbert, John|Antczak, Philipp|Clarke, Kim|Davies, Nicholas|Rahman, Ayesha|Campbell, Moray J|Guindani, Michele|Bicknell, Roy|Vannucci, Marina|Falciani, Francesco', 'Catedra de Bioinformatica, Escuela de Medicina, Tecnologico de Monterrey, Monterrey, Nuevo Leon, Mexico.|Department of Methodology and Statistics, Maastricht University, Maastricht, Netherlands.|School of Experimental and Clinical Medicine, University of Birmingham, Edgbaston, Birmingham, United Kingdom.|School of Immunity and Infection, University of Birmingham, Edgbaston, Birmingham, United Kingdom.|Institute of Integrative Biology, University of Liverpool, Liverpool, United Kingdom.|Institute of Integrative Biology, University of Liverpool, Liverpool, United Kingdom.|Institute of Integrative Biology, University of Liverpool, Liverpool, United Kingdom.|School of Cancer Sciences, College of Medicine and Dentistry, University of Birmingham, Edgbaston, Birmingham, United Kingdom.|School of Pharmacy, Faculty of Science and Engineering, University of Wolverhampton, Wolverhampton, United Kingdom.|Department of Pharmacology and Therapeutics, Roswell Park Cancer Institute, Buffalo, New York, United States of America.|Department of Biostatistics, University of Texas MD Anderson Cancer Center, Houston, Texas, United States of America.|School of Immunity and Infection, University of Birmingham, Edgbaston, Birmingham, United Kingdom.|Department of Statistics, Rice University, Houston, Texas, United States of America.|Institute of Integrative Biology, University of Liverpool, Liverpool, United Kingdom.', 'Mexico|Netherlands|United Kingdom|United Kingdom|United Kingdom|United Kingdom|United Kingdom|United', 3, 'Bayes Theorem|Cell Communication|Cell Line|Cell Line, Tumor|Coculture Techniques|Computational Biology|Epithelial Cells|Gene Expression Profiling|Gene Regulatory Networks|Humans|Male|Models, Biological|Prostate|Prostatic Neoplasms|Signal Transduction', 'Journal Article', '10.1371/journal.pcbi.1004884', '27124473', 'The advent of functional genomics has enabled the genome-wide characterization of the molecular state of cells and tissues, virtually at every level of biological organization. The difficulty in organizing and mining this unprecedented amount of information has stimulated the development of computational methods designed to infer the underlying structure of regulatory networks from observational data. These important developments had a profound impact in biological sciences since they triggered the development of a novel data-driven investigative approach. In cancer research, this strategy has been particularly successful. It has contributed to the identification of novel biomarkers, to a better characterization of disease heterogeneity and to a more in depth understanding of cancer pathophysiology. However, so far these approaches have not explicitly addressed the challenge of identifying networks representing the interaction of different cell types in a complex tissue. Since these interactions represent an essential part of the biology of both diseased and healthy tissues, it is of paramount importance that this challenge is addressed. Here we report the definition of a network reverse engineering strategy designed to infer directional signals linking adjacent cell types within a complex tissue. The application of this inference strategy to prostate cancer genome-wide expression profiling data validated the approach and revealed that normal epithelial cells exert an anti-tumour activity on prostate carcinoma cells. Moreover, by using a Bayesian hierarchical model integrating genetics and gene expression data and combining this with survival analysis, we show that the expression of putative cell communication genes related to focal adhesion and secretion is affected by epistatic gene copy number variation and it is predictive of patient survival. Ultimately, this study represents a generalizable approach to the challenge of deciphering cell communication networks in a wide spectrum of biological systems.'),
(87799, 2016, 'plos', 'Nucleosome Presence at AML-1 Binding Sites Inversely Correlates with Ly49 Expression: Revelations from an Informatics Analysis of Nucleosomes and Immune Cell Transcription Factors', 'Wight, Andrew|Yang, Doo|Ioshikhes, Ilya|Makrigiannis, Andrew P', 'Department of Biochemistry, Microbiology and Immunology, University of Ottawa, Ottawa, Ontario, Canada.|Department of Biochemistry, Microbiology and Immunology, University of Ottawa, Ottawa, Ontario, Canada.|Department of Biochemistry, Microbiology and Immunology, University of Ottawa, Ottawa, Ontario, Canada.|Department of Biochemistry, Microbiology and Immunology, University of Ottawa, Ottawa, Ontario, Canada.', 'Canada|Canada|Canada|Canada', 2, 'Animals|Binding Sites|Cell Line|Chromosome Mapping|Computational Biology|Core Binding Factor Alpha 2 Subunit|Gene Expression Regulation|Killer Cells, Natural|Mice|Multigene Family|NK Cell Lectin-Like Receptor Subfamily A|Nucleosomes|Promoter Regions, Genetic|Protein Binding|Transcription Factors', 'Journal Article', '10.1371/journal.pcbi.1004894', '27124577', 'Beyond its role in genomic organization and compaction, the nucleosome is believed to participate in the regulation of gene transcription. Here, we report a computational method to evaluate the nucleosome sensitivity for a transcription factor over a given stretch of the genome. Sensitive factors are predicted to be those with binding sites preferentially contained within nucleosome boundaries and lacking 10 bp periodicity. Based on these criteria, the Acute Myeloid Leukemia-1a (AML-1a) transcription factor, a regulator of immune gene expression, was identified as potentially sensitive to nucleosomal regulation within the mouse Ly49 gene family. This result was confirmed in RMA, a cell line with natural expression of Ly49, using MNase-Seq to generate a nucleosome map of chromosome 6, where the Ly49 gene family is located. Analysis of this map revealed a specific depletion of nucleosomes at AML-1a binding sites in the expressed Ly49A when compared to the other, silent Ly49 genes. Our data suggest that nucleosome-based regulation contributes to the expression of Ly49 genes, and we propose that this method of predicting nucleosome sensitivity could aid in dissecting the regulatory role of nucleosomes in general.'),
(87800, 2016, 'plos', 'Deep Neural Networks as a Computational Model for Human Shape Sensitivity', 'Kubilius, Jonas|Bracci, Stefania|Op de Beeck, Hans P', 'Brain and Cognition, University of Leuven (KU Leuven), Leuven, Belgium.|Brain and Cognition, University of Leuven (KU Leuven), Leuven, Belgium.|Brain and Cognition, University of Leuven (KU Leuven), Leuven, Belgium.', 'Belgium|Belgium|Belgium', 0, 'Computational Biology|Humans|Models, Neurological|Neural Networks (Computer)|Pattern Recognition, Visual', 'Journal Article', '10.1371/journal.pcbi.1004896', '27124699', 'Theories of object recognition agree that shape is of primordial importance, but there is no consensus about how shape might be represented, and so far attempts to implement a model of shape perception that would work with realistic stimuli have largely failed. Recent studies suggest that state-of-the-art convolutional deep neural networks (DNNs) capture important aspects of human object perception. We hypothesized that these successes might be partially related to a human-like representation of object shape. Here we demonstrate that sensitivity for shape features, characteristic to human and primate vision, emerges in DNNs when trained for generic object recognition from natural photographs. We show that these models explain human shape judgments for several benchmark behavioral and neural stimulus sets on which earlier models mostly failed. In particular, although never explicitly trained for such stimuli, DNNs develop acute sensitivity to minute variations in shape and to non-accidental properties that have long been implicated to form the basis for object recognition. Even more strikingly, when tested with a challenging stimulus set in which shape and category membership are dissociated, the most complex model architectures capture human shape sensitivity as well as some aspects of the category structure that emerges from human judgments. As a whole, these results indicate that convolutional neural networks not only learn physically correct representations of object categories but also develop perceptually accurate representational spaces of shapes. An even more complete model of human object representations might be in sight by training deep architectures for multiple tasks, which is so characteristic in human development.'),
(87801, 2016, 'plos', 'HepatoDyn: A Dynamic Model of Hepatocyte Metabolism That Integrates 13C Isotopomer Data', 'Foguet, Carles|Marin, Silvia|Selivanov, Vitaly A|Fanchon, Eric|Lee, Wai-Nang Paul|Guinovart, Joan J|de Atauri, Pedro|Cascante, Marta', 'Department of Biochemistry and Molecular Biomedicine, Faculty of Biology, Universitat de Barcelona, Barcelona, Spain.|Department of Biochemistry and Molecular Biomedicine, Faculty of Biology, Universitat de Barcelona, Barcelona, Spain.|Department of Biochemistry and Molecular Biomedicine, Faculty of Biology, Universitat de Barcelona, Barcelona, Spain.|UGA - CNRS, TIMC-IMAG UMR 5525, Grenoble, France.|Department of Pediatrics, Los Angeles Biomedical Research Institute, Torrance, California, United States of America.|Department of Biochemistry and Molecular Biomedicine, Faculty of Biology, Universitat de Barcelona, Barcelona, Spain.|Department of Biochemistry and Molecular Biomedicine, Faculty of Biology, Universitat de Barcelona, Barcelona, Spain.|Department of Biochemistry and Molecular Biomedicine, Faculty of Biology, Universitat de Barcelona, Barcelona, Spain.', 'Spain|Spain|Spain|France|United States|Spain|Spain|Spain', 11, 'Animals|Carbon Isotopes|Computational Biology|Computer Simulation|Fructose|Glucose|Hepatocytes|In Vitro Techniques|Kinetics|Male|Metabolic Networks and Pathways|Models, Biological|Rats|Rats, Wistar', 'Journal Article', '10.1371/journal.pcbi.1004899', '27124774', 'The liver performs many essential metabolic functions, which can be studied using computational models of hepatocytes. Here we present HepatoDyn, a highly detailed dynamic model of hepatocyte metabolism. HepatoDyn includes a large metabolic network, highly detailed kinetic laws, and is capable of dynamically simulating the redox and energy metabolism of hepatocytes. Furthermore, the model was coupled to the module for isotopic label propagation of the software package IsoDyn, allowing HepatoDyn to integrate data derived from 13C based experiments. As an example of dynamical simulations applied to hepatocytes, we studied the effects of high fructose concentrations on hepatocyte metabolism by integrating data from experiments in which rat hepatocytes were incubated with 20 mM glucose supplemented with either 3 mM or 20 mM fructose. These experiments showed that glycogen accumulation was significantly lower in hepatocytes incubated with medium supplemented with 20 mM fructose than in hepatocytes incubated with medium supplemented with 3 mM fructose. Through the integration of extracellular fluxes and 13C enrichment measurements, HepatoDyn predicted that this phenomenon can be attributed to a depletion of cytosolic ATP and phosphate induced by high fructose concentrations in the medium.'),
(87802, 2016, 'plos', 'The Interaction between Vector Life History and Short Vector Life in Vector-Borne Disease Transmission and Control', 'Brand, Samuel P C|Rock, Kat S|Keeling, Matt J', 'School of Life Sciences, University of Warwick, Coventry, United Kingdom.|School of Life Sciences, University of Warwick, Coventry, United Kingdom.|School of Life Sciences, University of Warwick, Coventry, United Kingdom.', 'United Kingdom|United Kingdom|United Kingdom', 10, 'Animals|Basic Reproduction Number|Bluetongue|Bluetongue virus|Ceratopogonidae|Communicable Diseases|Computational Biology|Disease Transmission, Infectious|Humans|Insect Bites and Stings|Insect Vectors|Life Cycle Stages|Models, Biological', 'Journal Article', '10.1371/journal.pcbi.1004837', '27128163', 'Epidemiological modelling has a vital role to play in policy planning and prediction for the control of vectors, and hence the subsequent control of vector-borne diseases. To decide between competing policies requires models that can generate accurate predictions, which in turn requires accurate knowledge of vector natural histories. Here we highlight the importance of the distribution of times between life-history events, using short-lived midge species as an example. In particular we focus on the distribution of the extrinsic incubation period (EIP) which determines the time between infection and becoming infectious, and the distribution of the length of the gonotrophic cycle which determines the time between successful bites. We show how different assumptions for these periods can radically change the basic reproductive ratio (R0) of an infection and additionally the impact of vector control on the infection. These findings highlight the need for detailed entomological data, based on laboratory experiments and field data, to correctly construct the next-generation of policy-informing models.'),
(87803, 2016, 'plos', 'Quorum-Sensing Synchronization of Synthetic Toggle Switches: A Design Based on Monotone Dynamical Systems Theory', 'Nikolaev, Evgeni V|Sontag, Eduardo D', 'Department of Mathematics and Center for Quantitative Biology, Rutgers, The State University of New Jersey, Piscataway, New Jersy, United States of America.|Department of Mathematics and Center for Quantitative Biology, Rutgers, The State University of New Jersey, Piscataway, New Jersy, United States of America.', 'Jersey|Jersey', 13, 'Computational Biology|Genes, Bacterial|Models, Biological|Pseudomonas aeruginosa|Quorum Sensing|Rhizobium leguminosarum|Synthetic Biology|Systems Theory', 'Journal Article', '10.1371/journal.pcbi.1004881', '27128344', 'Synthetic constructs in biotechnology, biocomputing, and modern gene therapy interventions are often based on plasmids or transfected circuits which implement some form of on-off switch. For example, the expression of a protein used for therapeutic purposes might be triggered by the recognition of a specific combination of inducers (e.g., antigens), and memory of this event should be maintained across a cell population until a specific stimulus commands a coordinated shut-off. The robustness of such a design is hampered by molecular (intrinsic) or environmental (extrinsic) noise, which may lead to spontaneous changes of state in a subset of the population and is reflected in the bimodality of protein expression, as measured for example using flow cytometry. In this context, a majority-vote correction circuit, which brings deviant cells back into the required state, is highly desirable, and quorum-sensing has been suggested as a way for cells to broadcast their states to the population as a whole so as to facilitate consensus. In this paper, we propose what we believe is the first such a design that has mathematically guaranteed properties of stability and auto-correction under certain conditions. Our approach is guided by concepts and theory from the field of monotone dynamical systems developed by M. Hirsch, H. Smith, and others. We benchmark our design by comparing it to an existing design which has been the subject of experimental and theoretical studies, illustrating its superiority in stability and self-correction of synchronization errors. Our stability analysis, based on dynamical systems theory, guarantees global convergence to steady states, ruling out unpredictable (chaotic) behaviors and even sustained oscillations in the limit of convergence. These results are valid no matter what are the values of parameters, and are based only on the wiring diagram. The theory is complemented by extensive computational bifurcation analysis, performed for a biochemically-detailed and biologically-relevant model that we developed. Another novel feature of our approach is that our theorems on exponential stability of steady states for homogeneous or mixed populations are valid independently of the number N of cells in the population, which is usually very large (N xe2x89xab 1) and unknown. We prove that the exponential stability depends on relative proportions of each type of state only. While monotone systems theory has been used previously for systems biology analysis, the current work illustrates its power for synthetic biology design, and thus has wider significance well beyond the application to the important problem of coordination of toggle switches.'),
(87804, 2016, 'plos', 'Canonical Cortical Circuit Model Explains Rivalry, Intermittent Rivalry, and Rivalry Memory', 'Vattikuti, Shashaank|Thangaraj, Phyllis|Xie, Hua W|Gotts, Stephen J|Martin, Alex|Chow, Carson C', 'Mathematical Biology Section, Laboratory of Biological Modeling, National Institutes of Diabetes and Digestive and Kidney Disease, National Institutes of Health, Bethesda, Maryland, United States of America.|Mathematical Biology Section, Laboratory of Biological Modeling, National Institutes of Diabetes and Digestive and Kidney Disease, National Institutes of Health, Bethesda, Maryland, United States of America.|Mathematical Biology Section, Laboratory of Biological Modeling, National Institutes of Diabetes and Digestive and Kidney Disease, National Institutes of Health, Bethesda, Maryland, United States of America.|Cognitive Neuropsychology Section, Laboratory of Brain and Cognition, National Institute of Mental Health, National Institutes of Health, Bethesda, Maryland, United States of America.|Cognitive Neuropsychology Section, Laboratory of Brain and Cognition, National Institute of Mental Health, National Institutes of Health, Bethesda, Maryland, United States of America.|Mathematical Biology Section, Laboratory of Biological Modeling, National Institutes of Diabetes and Digestive and Kidney Disease, National Institutes of Health, Bethesda, Maryland, United States of America.', 'United States|United States|United States|United States|United States|United States', 10, 'Adult|Asthenopia|Computational Biology|Humans|Male|Memory, Short-Term|Models, Neurological|Nerve Net|Optical Illusions|Photic Stimulation|Visual Cortex|Visual Perception', 'Journal Article', '10.1371/journal.pcbi.1004903', '27138214', 'It has been shown that the same canonical cortical circuit model with mutual inhibition and a fatigue process can explain perceptual rivalry and other neurophysiological responses to a range of static stimuli. However, it has been proposed that this model cannot explain responses to dynamic inputs such as found in intermittent rivalry and rivalry memory, where maintenance of a percept when the stimulus is absent is required. This challenges the universality of the basic canonical cortical circuit. Here, we show that by including an overlooked realistic small nonspecific background neural activity, the same basic model can reproduce intermittent rivalry and rivalry memory without compromising static rivalry and other cortical phenomena. The background activity induces a mutual-inhibition mechanism for short-term memory, which is robust to noise and where fine-tuning of recurrent excitation or inclusion of sub-threshold currents or synaptic facilitation is unnecessary. We prove existence conditions for the mechanism and show that it can explain experimental results from the quartet apparent motion illusion, which is a prototypical intermittent rivalry stimulus.'),
(87805, 2016, 'plos', 'A MAPK-Driven Feedback Loop Suppresses Rac Activity to Promote RhoA-Driven Cancer Cell Invasion', 'Hetmanski, Joseph H R|Zindy, Egor|Schwartz, Jean-Marc|Caswell, Patrick T', 'Wellcome Trust Centre for Cell-Matrix Research, Faculty of Life Sciences, University of Manchester, Manchester, United Kingdom.|Wellcome Trust Centre for Cell-Matrix Research, Faculty of Life Sciences, University of Manchester, Manchester, United Kingdom.|Wellcome Trust Centre for Cell-Matrix Research, Faculty of Life Sciences, University of Manchester, Manchester, United Kingdom.|Wellcome Trust Centre for Cell-Matrix Research, Faculty of Life Sciences, University of Manchester, Manchester, United Kingdom.', 'United Kingdom|United Kingdom|United Kingdom|United Kingdom', 25, 'Adaptor Proteins, Signal Transducing|Cell Line, Tumor|Cell Movement|Computational Biology|Computer Simulation|ErbB Receptors|Feedback, Physiological|Humans|Imaging, Three-Dimensional|MAP Kinase Signaling System|Models, Biological|Neoplasm Invasiveness|Pseudopodia|Tumor Microenvironment|rac1 GTP-Binding Protein|rhoA GTP-Binding Protein', 'Journal Article', '10.1371/journal.pcbi.1004909', '27138333', 'Cell migration in 3D microenvironments is fundamental to development, homeostasis and the pathobiology of diseases such as cancer. Rab-coupling protein (RCP) dependent co-trafficking of xcexb15xcexb21 and EGFR1 promotes cancer cell invasion into fibronectin (FN) containing extracellular matrix (ECM), by potentiating EGFR1 signalling at the front of invasive cells. This promotes a switch in RhoGTPase signalling to inhibit Rac1 and activate a RhoA-ROCK-Formin homology domain-containing 3 (FHOD3) pathway and generate filopodial actin-spike protrusions which drive invasion. To further understand the signalling network that drives RCP-driven invasive migration, we generated a Boolean logical model based on existing network pathways/models, where each node can be interrogated by computational simulation. The model predicted an unanticipated feedback loop, whereby Raf/MEK/ERK signalling maintains suppression of Rac1 by inhibiting the Rac-activating Sos1-Eps8-Abi1 complex, allowing RhoA activity to predominate in invasive protrusions. MEK inhibition was sufficient to promote lamellipodia formation and oppose filopodial actin-spike formation, and led to activation of Rac and inactivation of RhoA at the leading edge of cells moving in 3D matrix. Furthermore, MEK inhibition abrogated RCP/xcexb15xcexb21/EGFR1-driven invasive migration. However, upon knockdown of Eps8 (to suppress the Sos1-Abi1-Eps8 complex), MEK inhibition had no effect on RhoGTPase activity and did not oppose invasive migration, suggesting that MEK-ERK signalling suppresses the Rac-activating Sos1-Abi1-Eps8 complex to maintain RhoA activity and promote filopodial actin-spike formation and invasive migration. Our study highlights the predictive potential of mathematical modelling approaches, and demonstrates that a simple intervention (MEK-inhibition) could be of therapeutic benefit in preventing invasive migration and metastasis.'),
(87806, 2016, 'plos', 'Efficient Coalescent Simulation and Genealogical Analysis for Large Sample Sizes', 'Kelleher, Jerome|Etheridge, Alison M|McVean, Gilean', 'Wellcome Trust Centre for Human Genetics, University of Oxford, Oxford, United Kingdom.|Department of Statistics, University of Oxford, Oxford, United Kingdom.|Wellcome Trust Centre for Human Genetics, University of Oxford, Oxford, United Kingdom.', 'United Kingdom|United Kingdom|United Kingdom', 110, 'Algorithms|Computational Biology|Computer Simulation|Evolution, Molecular|Genetic Variation|Genetics, Population|Humans|Models, Genetic|Pedigree|Recombination, Genetic|Sample Size', 'Journal Article', '10.1371/journal.pcbi.1004842', '27145223', 'A central challenge in the analysis of genetic variation is to provide realistic genome simulation across millions of samples. Present day coalescent simulations do not scale well, or use approximations that fail to capture important long-range linkage properties. Analysing the results of simulations also presents a substantial challenge, as current methods to store genealogies consume a great deal of space, are slow to parse and do not take advantage of shared structure in correlated trees. We solve these problems by introducing sparse trees and coalescence records as the key units of genealogical analysis. Using these tools, exact simulation of the coalescent with recombination for chromosome-sized regions over hundreds of thousands of samples is possible, and substantially faster than present-day approximate methods. We can also analyse the results orders of magnitude more quickly than with existing methods.'),
(87807, 2016, 'plos', 'Identifying Network Perturbation in Cancer', 'Grechkin, Maxim|Logsdon, Benjamin A|Gentles, Andrew J|Lee, Su-In', 'Department of Computer Science & Engineering, University of Washington, Seattle, Washington, United States of America.|Sage Bionetworks, Seattle, Washington, United States of America.|Center for Cancer Systems Biology, Department of Radiology, Stanford University, Stanford, California, United States of America.|Department of Computer Science & Engineering, University of Washington, Seattle, Washington, United States of America.', 'United States|United States|United States|United States', 17, 'Breast Neoplasms|Computational Biology|Computer Simulation|Databases, Genetic|Epigenesis, Genetic|Female|Gene Expression Regulation, Neoplastic|Gene Regulatory Networks|Humans|Leukemia, Myeloid, Acute|Likelihood Functions|Lung Neoplasms|Models, Genetic|Neoplasms|Prognosis', 'Journal Article', '10.1371/journal.pcbi.1004888', '27145341', 'We present a computational framework, called DISCERN (DIfferential SparsE Regulatory Network), to identify informative topological changes in gene-regulator dependence networks inferred on the basis of mRNA expression datasets within distinct biological states. DISCERN takes two expression datasets as input: an expression dataset of diseased tissues from patients with a disease of interest and another expression dataset from matching normal tissues. DISCERN estimates the extent to which each gene is perturbed-having distinct regulator connectivity in the inferred gene-regulator dependencies between the disease and normal conditions. This approach has distinct advantages over existing methods. First, DISCERN infers conditional dependencies between candidate regulators and genes, where conditional dependence relationships discriminate the evidence for direct interactions from indirect interactions more precisely than pairwise correlation. Second, DISCERN uses a new likelihood-based scoring function to alleviate concerns about accuracy of the specific edges inferred in a particular network. DISCERN identifies perturbed genes more accurately in synthetic data than existing methods to identify perturbed genes between distinct states. In expression datasets from patients with acute myeloid leukemia (AML), breast cancer and lung cancer, genes with high DISCERN scores in each cancer are enriched for known tumor drivers, genes associated with the biological processes known to be important in the disease, and genes associated with patient prognosis, in the respective cancer. Finally, we show that DISCERN can uncover potential mechanisms underlying network perturbation by explaining observed epigenomic activity patterns in cancer and normal tissue types more accurately than alternative methods, based on the available epigenomic data from the ENCODE project.'),
(87808, 2016, 'plos', 'Optimal Current Transfer in Dendrites', 'Bird, Alex D|Cuntz, Hermann', 'Warwick Systems Biology Centre, University of Warwick, Coventry, United Kingdom.|Ernst Strüngmann Institute (ESI) for Neuroscience in Cooperation with Max Planck Society, Frankfurt-am-Main, Germany.', 'United Kingdom|Germany', 9, 'Algorithms|Animals|Brain|Computational Biology|Computer Simulation|Dendrites|Models, Neurological|Neurons|Synaptic Transmission', 'Journal Article', '10.1371/journal.pcbi.1004897', '27145441', 'Integration of synaptic currents across an extensive dendritic tree is a prerequisite for computation in the brain. Dendritic tapering away from the soma has been suggested to both equalise contributions from synapses at different locations and maximise the current transfer to the soma. To find out how this is achieved precisely, an analytical solution for the current transfer in dendrites with arbitrary taper is required. We derive here an asymptotic approximation that accurately matches results from numerical simulations. From this we then determine the diameter profile that maximises the current transfer to the soma. We find a simple quadratic form that matches diameters obtained experimentally, indicating a fundamental architectural principle of the brain that links dendritic diameters to signal transmission.'),
(87809, 2016, 'plos', 'To Cooperate or Not to Cooperate: Why Behavioural Mechanisms Matter', 'Bernard, Arthur|André, Jean-Baptiste|Bredeche, Nicolas', 'Sorbonne Universités, UPMC Univ Paris 06, CNRS, Institute of Intelligent Systems and Robotics (ISIR), Paris, France.|Institut des Sciences de lEvolution, Université de Montpellier, CNRS, IRD, EPHE, CC065, Pl. E. Bataillon, Montpellier, France.|Sorbonne Universités, UPMC Univ Paris 06, CNRS, Institute of Intelligent Systems and Robotics (ISIR), Paris, France.', 'France|France|France', 7, 'Algorithms|Animals|Biological Evolution|Computational Biology|Computer Simulation|Cooperative Behavior|Female|Game Theory|Genetic Phenomena|Humans|Male|Models, Psychological|Neural Networks (Computer)|Predatory Behavior|Robotics', 'Journal Article', '10.1371/journal.pcbi.1004886', '27148874', 'Mutualistic cooperation often requires multiple individuals to behave in a coordinated fashion. Hence, while the evolutionary stability of mutualistic cooperation poses no particular theoretical difficulty, its evolutionary emergence faces a chicken and egg problem: an individual cannot benefit from cooperating unless other individuals already do so. Here, we use evolutionary robotic simulations to study the consequences of this problem for the evolution of cooperation. In contrast with standard game-theoretic results, we find that the transition from solitary to cooperative strategies is very unlikely, whether interacting individuals are genetically related (cooperation evolves in 20% of all simulations) or unrelated (only 3% of all simulations). We also observe that successful cooperation between individuals requires the evolution of a specific and rather complex behaviour. This behavioural complexity creates a large fitness valley between solitary and cooperative strategies, making the evolutionary transition difficult. These results reveal the need for research on biological mechanisms which may facilitate this transition.');
INSERT INTO `papers` (`id`, `ano`, `journal`, `titulo`, `autores`, `afiliacao`, `pais`, `citacoes`, `palavra_chave`, `categorias`, `doi`, `pubmed`, `abstract`) VALUES
(87810, 2016, 'plos', 'A Model for an Angular Velocity-Tuned Motion Detector Accounting for Deviations in the Corridor-Centering Response of the Bee', 'Cope, Alex J|Sabo, Chelsea|Gurney, Kevin|Vasilaki, Eleni|Marshall, James A R', 'Department of Computer Science, University of Sheffield, Sheffield, South Yorkshire, United Kingdom.|Department of Computer Science, University of Sheffield, Sheffield, South Yorkshire, United Kingdom.|Sheffield Robotics, Sheffield, South Yorkshire, United Kingdom.|Department of Computer Science, University of Sheffield, Sheffield, South Yorkshire, United Kingdom.|Department of Computer Science, University of Sheffield, Sheffield, South Yorkshire, United Kingdom.', 'United Kingdom|United Kingdom|United Kingdom|United Kingdom|United Kingdom', 15, 'Algorithms|Animals|Bees|Brain|Computational Biology|Computer Simulation|Flight, Animal|Models, Neurological|Motion Perception|User-Computer Interface', 'Journal Article', '10.1371/journal.pcbi.1004887', '27148968', 'We present a novel neurally based model for estimating angular velocity (AV) in the bee brain, capable of quantitatively reproducing experimental observations of visual odometry and corridor-centering in free-flying honeybees, including previously unaccounted for manipulations of behaviour. The model is fitted using electrophysiological data, and tested using behavioural data. Based on our model we suggest that the AV response can be considered as an evolutionary extension to the optomotor response. The detector is tested behaviourally in silico with the corridor-centering paradigm, where bees navigate down a corridor with gratings (square wave or sinusoidal) on the walls. When combined with an existing flight control algorithm the detector reproduces the invariance of the average flight path to the spatial frequency and contrast of the gratings, including deviations from perfect centering behaviour as found in the real bees behaviour. In addition, the summed response of the detector to a unit distance movement along the corridor is constant for a large range of grating spatial frequencies, demonstrating that the detector can be used as a visual odometer.'),
(87811, 2016, 'plos', 'Conflicting Selection Pressures Will Constrain Viral Escape from Interfering Particles: Principles for Designing Resistance-Proof Antivirals', 'Rast, Luke I|Rouzine, Igor M|Rozhnova, Ganna|Bishop, Lisa|Weinberger, Ariel D|Weinberger, Leor S', 'Gladstone Institutes (Virology and Immunology), San Francisco, California, United States of America.|Gladstone Institutes (Virology and Immunology), San Francisco, California, United States of America.|Gladstone Institutes (Virology and Immunology), San Francisco, California, United States of America.|Gladstone Institutes (Virology and Immunology), San Francisco, California, United States of America.|Wyss Institute for Biologically Inspired Engineering, Harvard University, Boston, Massachusetts, United States of America.|Gladstone Institutes (Virology and Immunology), San Francisco, California, United States of America.', 'United States|United States|United States|United States|United States|United States', 8, 'Anti-HIV Agents|Computational Biology|Defective Viruses|Drug Design|Drug Resistance, Viral|Evolution, Molecular|HIV|HIV Infections|Humans|Models, Biological|Mutation|Selection, Genetic|Viral Load|Virus Replication', 'Journal Article', '10.1371/journal.pcbi.1004799', '27152856', 'The rapid evolution of RNA-encoded viruses such as HIV presents a major barrier to infectious disease control using conventional pharmaceuticals and vaccines. Previously, it was proposed that defective interfering particles could be developed to indefinitely control the HIV/AIDS pandemic, in individual patients, these engineered molecular parasites were further predicted to be refractory to HIVs mutational escape (i.e., be resistance-proof). However, an outstanding question has been whether these engineered interfering particles-termed Therapeutic Interfering Particles (TIPs)-would remain resistance-proof at the population-scale, where TIP-resistant HIV mutants may transmit more efficiently by reaching higher viral loads in the TIP-treated subpopulation. Here, we develop a multi-scale model to test whether TIPs will maintain indefinite control of HIV at the population-scale, as HIV (unilaterally) evolves toward TIP resistance by limiting the production of viral proteins available for TIPs to parasitize. Model results capture the existence of two intrinsic evolutionary tradeoffs that collectively prevent the spread of TIP-resistant HIV mutants in a population. First, despite their increased transmission rates in TIP-treated sub-populations, unilateral TIP-resistant mutants are shown to have reduced transmission rates in TIP-untreated sub-populations. Second, these TIP-resistant mutants are shown to have reduced growth rates (i.e., replicative fitness) in both TIP-treated and TIP-untreated individuals. As a result of these tradeoffs, the model finds that TIP-susceptible HIV strains continually outcompete TIP-resistant HIV mutants at both patient and population scales when TIPs are engineered to express >3-fold more genomic RNA than HIV expresses. Thus, the results provide design constraints for engineering population-scale therapies that may be refractory to the acquisition of antiviral resistance.'),
(87812, 2016, 'plos', 'A Model for Direction Sensing in Dictyostelium discoideum: Ras Activity and Symmetry Breaking Driven by a Gxcexb2xcexb3-Mediated, Gxcexb12-Ric8 -- Dependent Signal Transduction Network', 'Cheng, Yougan|Othmer, Hans', 'School of Mathematics, University of Minnesota, Minneapolis, Minnesota, United States of America.|School of Mathematics, University of Minnesota, Minneapolis, Minnesota, United States of America.', 'United States|United States', 0, 'Animals|Chemotaxis|Computational Biology|Cyclic AMP|Dictyostelium|GTP-Binding Proteins|Gene Knockout Techniques|Guanine Nucleotide Exchange Factors|Kinetics|Models, Biological|Protozoan Proteins|Receptors, G-Protein-Coupled|Signal Transduction|ras Proteins', 'Journal Article', '10.1371/journal.pcbi.1004900', '27152956', 'Chemotaxis is a dynamic cellular process, comprised of direction sensing, polarization and locomotion, that leads to the directed movement of eukaryotic cells along extracellular gradients. As a primary step in the response of an individual cell to a spatial stimulus, direction sensing has attracted numerous theoretical treatments aimed at explaining experimental observations in a variety of cell types. Here we propose a new model of direction sensing based on experiments using Dictyostelium discoideum (Dicty). The model is built around a reaction-diffusion-translocation system that involves three main component processes: a signal detection step based on G-protein-coupled receptors (GPCR) for cyclic AMP (cAMP), a transduction step based on a heterotrimetic G protein Gxcexb12xcexb2xcexb3, and an activation step of a monomeric G-protein Ras. The model can predict the experimentally-observed response of cells treated with latrunculin A, which removes feedback from downstream processes, under a variety of stimulus protocols. We show that [Formula: see text] cycling modulated by Ric8, a nonreceptor guanine exchange factor for [Formula: see text] in Dicty, drives multiple phases of Ras activation and leads to direction sensing and signal amplification in cAMP gradients. The model predicts that both [Formula: see text] and Gxcexb2xcexb3 are essential for direction sensing, in that membrane-localized [Formula: see text], the activated GTP-bearing form of [Formula: see text], leads to asymmetrical recruitment of RasGEF and Ric8, while globally-diffusing Gxcexb2xcexb3 mediates their activation. We show that the predicted response at the level of Ras activation encodes sufficient memory to eliminate the back-of-the wave problem, and the effects of diffusion and cell shape on direction sensing are also investigated. In contrast with existing LEGI models of chemotaxis, the results do not require a disparity between the diffusion coefficients of the Ras activator GEF and the Ras inhibitor GAP. Since the signal pathways we study are highly conserved between Dicty and mammalian leukocytes, the model can serve as a generic one for direction sensing.'),
(87813, 2016, 'plos', 'Effect of Interaction between Chromatin Loops on Cell-to-Cell Variability in Gene Expression', 'Liu, Tuoqi|Zhang, Jiajun|Zhou, Tianshou', 'School of Mathematics and Computational Science, Sun Yat-Sen University, Guangzhou, Peoples Republic of China.|School of Mathematics and Computational Science, Sun Yat-Sen University, Guangzhou, Peoples Republic of China.|School of Mathematics and Computational Science, Sun Yat-Sen University, Guangzhou, Peoples Republic of China.', 'China|China|China', 6, 'Animals|Chromatin|Computational Biology|Drosophila melanogaster|Enhancer Elements, Genetic|Escherichia coli|Gene Expression|Models, Genetic|Promoter Regions, Genetic|RNA, Messenger', 'Journal Article', '10.1371/journal.pcbi.1004917', '27153118', 'According to recent experimental evidence, the interaction between chromatin loops, which can be characterized by three factors-connection pattern, distance between regulatory elements, and communication form, play an important role in determining the level of cell-to-cell variability in gene expression. These quantitative experiments call for a corresponding modeling effect that addresses the question of how changes in these factors affect variability at the expression level in a systematic rather than case-by-case fashion. Here we make such an effort, based on a mechanic model that maps three fundamental patterns for two interacting DNA loops into a 4-state model of stochastic transcription. We first show that in contrast to side-by-side loops, nested loops enhance mRNA expression and reduce expression noise whereas alternating loops have just opposite effects. Then, we compare effects of facilitated tracking and direct looping on gene expression. We find that the former performs better than the latter in controlling mean expression and in tuning expression noise, but this control or tuning is distance-dependent, remarkable for moderate loop lengths, and there is a limit loop length such that the difference in effect between two communication forms almost disappears. Our analysis and results justify the facilitated chromatin-looping hypothesis.'),
(87814, 2016, 'plos', 'High-Degree Neurons Feed Cortical Computations', 'Timme, Nicholas M|Ito, Shinya|Myroshnychenko, Maxym|Nigam, Sunny|Shimono, Masanori|Yeh, Fang-Chin|Hottowy, Pawel|Litke, Alan M|Beggs, John M', 'Department of Physics, Indiana University, Bloomington, Indiana, United States of America.|Santa Cruz Institute for Particle Physics, University of California at Santa Cruz, Santa Cruz, California, United States of America.|Program in Neuroscience, Indiana University, Bloomington, Indiana, United States of America.|Department of Physics, Indiana University, Bloomington, Indiana, United States of America.|MGH/HST Athinoula A. Martinos Center, Harvard Medical School, Charlestown, Massachusetts, United States of America.|Department of Neuroscience and Behavioral Disorders, Duke-NUS Graduate Medical School, Singapore.|Physics and Applied Computer Science, AGH University of Science and Technology, Krakow, Poland.|Santa Cruz Institute for Particle Physics, University of California at Santa Cruz, Santa Cruz, California, United States of America.|Department of Physics, Indiana University, Bloomington, Indiana, United States of America.', 'India|United States|India|India|United States|Singapore|Poland|United States|India', 37, 'Action Potentials|Animals|Cerebral Cortex|Computational Biology|Feedback, Physiological|Hippocampus|Information Theory|Mice|Mice, Inbred C57BL|Models, Neurological|Multivariate Analysis|Nerve Net|Neurons|Synaptic Transmission', 'Journal Article', '10.1371/journal.pcbi.1004858', '27159884', 'Recent work has shown that functional connectivity among cortical neurons is highly varied, with a small percentage of neurons having many more connections than others. Also, recent theoretical developments now make it possible to quantify how neurons modify information from the connections they receive. Therefore, it is now possible to investigate how information modification, or computation, depends on the number of connections a neuron receives (in-degree) or sends out (out-degree). To do this, we recorded the simultaneous spiking activity of hundreds of neurons in cortico-hippocampal slice cultures using a high-density 512-electrode array. This preparation and recording method combination produced large numbers of neurons recorded at temporal and spatial resolutions that are not currently available in any in vivo recording system. We utilized transfer entropy (a well-established method for detecting linear and nonlinear interactions in time series) and the partial information decomposition (a powerful, recently developed tool for dissecting multivariate information processing into distinct parts) to quantify computation between neurons where information flows converged. We found that computations did not occur equally in all neurons throughout the networks. Surprisingly, neurons that computed large amounts of information tended to receive connections from high out-degree neurons. However, the in-degree of a neuron was not related to the amount of information it computed. To gain insight into these findings, we developed a simple feedforward network model. We found that a degree-modified Hebbian wiring rule best reproduced the pattern of computation and degree correlation results seen in the real data. Interestingly, this rule also maximized signal propagation in the presence of network-wide correlations, suggesting a mechanism by which cortex could deal with common random background input. These are the first results to show that the extent to which a neuron modifies incoming information streams depends on its topological location in the surrounding functional network.'),
(87815, 2016, 'plos', 'Enzyme Sequestration as a Tuning Point in Controlling Response Dynamics of Signalling Networks', 'Feng, Song|Ollivier, Julien F|Soyer, Orkun S', 'School of Life Sciences, University of Warwick, Coventry, United Kingdom.|Biojazz Research, Montreal, Quebec, Canada.|School of Life Sciences, University of Warwick, Coventry, United Kingdom.', 'United Kingdom|Canada|United Kingdom', 0, 'Algorithms|Allosteric Regulation|Biological Evolution|Computational Biology|Computer Simulation|Enzymes|Kinetics|Models, Biological|Proteins|Signal Transduction|Synthetic Biology', 'Journal Article', '10.1371/journal.pcbi.1004918', '27163612', 'Signalling networks result from combinatorial interactions among many enzymes and scaffolding proteins. These complex systems generate response dynamics that are often essential for correct decision-making in cells. Uncovering biochemical design principles that underpin such response dynamics is a prerequisite to understand evolved signalling networks and to design synthetic ones. Here, we use in silico evolution to explore the possible biochemical design space for signalling networks displaying ultrasensitive and adaptive response dynamics. By running evolutionary simulations mimicking different biochemical scenarios, we find that enzyme sequestration emerges as a key mechanism for enabling such dynamics. Inspired by these findings, and to test the role of sequestration, we design a generic, minimalist model of a signalling cycle, featuring two enzymes and a single scaffolding protein. We show that this simple system is capable of displaying both ultrasensitive and adaptive response dynamics. Furthermore, we find that tuning the concentration or kinetics of the sequestering protein can shift system dynamics between these two response types. These empirical results suggest that enzyme sequestration through scaffolding proteins is exploited by evolution to generate diverse response dynamics in signalling networks and could provide an engineering point in synthetic biology applications.'),
(87816, 2016, 'plos', 'Structural Determinants of Misfolding in Multidomain Proteins', 'Tian, Pengfei|Best, Robert B', 'Laboratory of Chemical Physics, National Institute of Diabetes and Digestive and Kidney Diseases, National Institutes of Health, Bethesda, Maryland, United States of America.|Laboratory of Chemical Physics, National Institute of Diabetes and Digestive and Kidney Diseases, National Institutes of Health, Bethesda, Maryland, United States of America.', 'United States|United States', 12, 'Computational Biology|Computer Simulation|Fluorescence Resonance Energy Transfer|Kinetics|Microscopy, Atomic Force|Models, Molecular|Molecular Dynamics Simulation|Protein Domains|Protein Folding|Protein Stability|Proteins|Tandem Repeat Sequences', 'Journal Article', '10.1371/journal.pcbi.1004933', '27163669', 'Recent single molecule experiments, using either atomic force microscopy (AFM) or Förster resonance energy transfer (FRET) have shown that multidomain proteins containing tandem repeats may form stable misfolded structures. Topology-based simulation models have been used successfully to generate models for these structures with domain-swapped features, fully consistent with the available data. However, it is also known that some multidomain protein folds exhibit no evidence for misfolding, even when adjacent domains have identical sequences. Here we pose the question: what factors influence the propensity of a given fold to undergo domain-swapped misfolding? Using a coarse-grained simulation model, we can reproduce the known propensities of multidomain proteins to form domain-swapped misfolds, where data is available. Contrary to what might be naively expected based on the previously described misfolding mechanism, we find that the extent of misfolding is not determined by the relative folding rates or barrier heights for forming the domains present in the initial intermediates leading to folded or misfolded structures. Instead, it appears that the propensity is more closely related to the relative stability of the domains present in folded and misfolded intermediates. We show that these findings can be rationalized if the folded and misfolded domains are part of the same folding funnel, with commitment to one structure or the other occurring only at a relatively late stage of folding. Nonetheless, the results are still fully consistent with the kinetic models previously proposed to explain misfolding, with a specific interpretation of the observed rate coefficients. Finally, we investigate the relation between interdomain linker length and misfolding, and propose a simple alchemical model to predict the propensity for domain-swapped misfolding of multidomain proteins.'),
(87817, 2016, 'plos', 'A Molecular Clock Infers Heterogeneous Tissue Age Among Patients with Barretts Esophagus', 'Curtius, Kit|Wong, Chao-Jen|Hazelton, William D|Kaz, Andrew M|Chak, Amitabh|Willis, Joseph E|Grady, William M|Luebeck, E Georg', 'Division of Gastroenterology, University of Washington School of Medicine, Seattle, Washington, United States of America.|Program in Computational Biology, Fred Hutchinson Cancer Research Center, Seattle, Washington, United States of America.|Program in Computational Biology, Fred Hutchinson Cancer Research Center, Seattle, Washington, United States of America.|Division of Gastroenterology, University of Washington School of Medicine, Seattle, Washington, United States of America.|University Hospitals Case Medical Center, Case Western Reserve University School of Medicine, Cleveland, Ohio, United States of America.|University Hospitals Case Medical Center, Case Western Reserve University School of Medicine, Cleveland, Ohio, United States of America.|Division of Gastroenterology, University of Washington School of Medicine, Seattle, Washington, United States of America.|Program in Computational Biology, Fred Hutchinson Cancer Research Center, Seattle, Washington, United States of America.', 'United States|United States|United States|United States|United States|United States|United States|Un', 0, 'Adenocarcinoma|Adult|Aged|Aged, 80 and over|Aging|Barrett Esophagus|Bayes Theorem|Biological Clocks|Computational Biology|CpG Islands|DNA Methylation|Disease Progression|Esophageal Neoplasms|Female|Genetic Markers|Humans|Longitudinal Studies|Male|Middle Aged|Models, Genetic|Risk Factors', 'Journal Article', '10.1371/journal.pcbi.1004919', '27168458', 'Biomarkers that drift differentially with age between normal and premalignant tissues, such as Barretts esophagus (BE), have the potential to improve the assessment of a patients cancer risk by providing quantitative information about how long a patient has lived with the precursor (i.e., dwell time). In the case of BE, which is a metaplastic precursor to esophageal adenocarcinoma (EAC), such biomarkers would be particularly useful because EAC risk may change with BE dwell time and it is generally not known how long a patient has lived with BE when a patient is first diagnosed with this condition. In this study we first describe a statistical analysis of DNA methylation data (both cross-sectional and longitudinal) derived from tissue samples from 50 BE patients to identify and validate a set of 67 CpG dinucleotides in 51 CpG islands that undergo age-related methylomic drift. Next, we describe how this information can be used to estimate a patients BE dwell time. We introduce a Bayesian model that incorporates longitudinal methylomic drift rates, patient age, and methylation data from individually paired BE and normal squamous tissue samples to estimate patient-specific BE onset times. Our application of the model to 30 sporadic BE patients methylomic profiles first exposes a wide heterogeneity in patient-specific BE onset times. Furthermore, independent application of this method to a cohort of 22 familial BE (FBE) patients reveals significantly earlier mean BE onset times. Our analysis supports the conjecture that differential methylomic drift occurs in BE (relative to normal squamous tissue) and hence allows quantitative estimation of the time that a BE patient has lived with BE.'),
(87818, 2016, 'plos', 'Towards Increasing the Clinical Relevance of In Silico Methods to Predict Pathogenic Missense Variants', 'Masica, David L|Karchin, Rachel', 'Department of Biomedical Engineering and The Institute for Computational Medicine, The Johns Hopkins University, Baltimore, Maryland, United States of America.|Department of Biomedical Engineering and The Institute for Computational Medicine, The Johns Hopkins University, Baltimore, Maryland, United States of America.', 'United States|United States', 0, 'Amino Acid Substitution|Computational Biology|Computer Simulation|Cystic Fibrosis|Cystic Fibrosis Transmembrane Conductance Regulator|Endophenotypes|Genetic Association Studies|Genetic Predisposition to Disease|Genetic Variation|Humans|Models, Genetic|Mutation, Missense|Receptors, LDL', 'Journal Article', '10.1371/journal.pcbi.1004725', '27171182', '-'),
(87819, 2016, 'plos', 'Inferring Contacting Residues within and between Proteins: What Do the Probabilities Mean?', 'van Nimwegen, Erik', 'Biozentrum, University of Basel, Basel, Switzerland.', 'Switzerland', 12, 'Computational Biology|Entropy|Models, Chemical|Models, Statistical|Protein Interaction Domains and Motifs|Proteins|Sequence Alignment', 'Journal Article', '10.1371/journal.pcbi.1004726', '27171220', '-'),
(87820, 2016, 'plos', 'The Maximum Entropy Fallacy Redux?', 'Aurell, Erik', 'Department of Computational Biology, ACCESS Linnaeus Centre and Centre for Quantum Materials, KTH-Royal Institute of Technology, Stockholm, Sweden.', 'Sweden', 0, 'Chemical Phenomena|Computational Biology|Computer Simulation|Entropy|Models, Molecular|Models, Statistical|Proteins|Sequence Alignment', 'Journal Article', '10.1371/journal.pcbi.1004777', '27171259', '-'),
(87821, 2016, 'plos', 'Human Leg Model Predicts Muscle Forces, States, and Energetics during Walking', 'Markowitz, Jared|Herr, Hugh', 'MIT Media Lab, Massachusetts Institute of Technology, Cambridge, Massachusetts, United States of America.|MIT Media Lab, Massachusetts Institute of Technology, Cambridge, Massachusetts, United States of America.', 'United States|United States', 9, 'Adult|Algorithms|Bayes Theorem|Biomechanical Phenomena|Computational Biology|Computer Simulation|Energy Metabolism|Gait|Humans|Leg|Male|Models, Biological|Muscle Contraction|Muscle, Skeletal|Tendons|Torque|Walking|Young Adult', 'Journal Article', '10.1371/journal.pcbi.1004912', '27175486', 'Humans employ a high degree of redundancy in joint actuation, with different combinations of muscle and tendon action providing the same net joint torque. Both the resolution of these redundancies and the energetics of such systems depend on the dynamic properties of muscles and tendons, particularly their force-length relations. Current walking models that use stock parameters when simulating muscle-tendon dynamics tend to significantly overestimate metabolic consumption, perhaps because they do not adequately consider the role of elasticity. As an alternative, we posit that the muscle-tendon morphology of the human leg has evolved to maximize the metabolic efficiency of walking at self-selected speed. We use a data-driven approach to evaluate this hypothesis, utilizing kinematic, kinetic, electromyographic (EMG), and metabolic data taken from five participants walking at self-selected speed. The kinematic and kinetic data are used to estimate muscle-tendon lengths, muscle moment arms, and joint moments while the EMG data are used to estimate muscle activations. For each subject we perform an optimization using prescribed skeletal kinematics, varying the parameters that govern the force-length curve of each tendon as well as the strength and optimal fiber length of each muscle while seeking to simultaneously minimize metabolic cost and maximize agreement with the estimated joint moments. We find that the metabolic cost of transport (MCOT) values of our participants may be correctly matched (on average 0.36±0.02 predicted, 0.35±0.02 measured) with acceptable joint torque fidelity through application of a single constraint to the muscle metabolic budget. The associated optimal muscle-tendon parameter sets allow us to estimate the forces and states of individual muscles, resolving redundancies in joint actuation and lending insight into the potential roles and control objectives of the muscles of the leg throughout the gait cycle.'),
(87822, 2016, 'plos', 'Learning from Heterogeneous Data Sources: An Application in Spatial Proteomics', 'Breckels, Lisa M|Holden, Sean B|Wojnar, David|Mulvey, Claire M|Christoforou, Andy|Groen, Arnoud|Trotter, Matthew W B|Kohlbacher, Oliver|Lilley, Kathryn S|Gatto, Laurent', 'Computational Proteomics Unit, Department of Biochemistry, University of Cambridge, Cambridge, United Kingdom.|Computer Laboratory, University of Cambridge, Cambridge, United Kingdom.|Quantitative Biology Center, Universität Tübingen, Tübingen, Germany.|Cambridge Centre for Proteomics, Department of Biochemistry, University of Cambridge, Cambridge, United Kingdom.|Cambridge Centre for Proteomics, Department of Biochemistry, University of Cambridge, Cambridge, United Kingdom.|Cambridge Centre for Proteomics, Department of Biochemistry, University of Cambridge, Cambridge, United Kingdom.|Celgene Institute for Translational Research Europe (CITRE), Sevilla, Spain.|Quantitative Biology Center, Universität Tübingen, Tübingen, Germany.|Cambridge Centre for Proteomics, Department of Biochemistry, University of Cambridge, Cambridge, United Kingdom.|Computational Proteomics Unit, Department of Biochemistry, University of Cambridge, Cambridge, United Kingdom.', 'United Kingdom|United Kingdom|Germany|United Kingdom|United Kingdom|United Kingdom|Spain|Germany|Uni', 21, 'Algorithms|Animals|Arabidopsis|Computational Biology|Data Interpretation, Statistical|Drosophila|Embryonic Stem Cells|Humans|Information Storage and Retrieval|Mass Spectrometry|Mice|Proteome|Proteomics|Software|Subcellular Fractions|Support Vector Machine', 'Journal Article', '10.1371/journal.pcbi.1004920', '27175778', 'Sub-cellular localisation of proteins is an essential post-translational regulatory mechanism that can be assayed using high-throughput mass spectrometry (MS). These MS-based spatial proteomics experiments enable us to pinpoint the sub-cellular distribution of thousands of proteins in a specific system under controlled conditions. Recent advances in high-throughput MS methods have yielded a plethora of experimental spatial proteomics data for the cell biology community. Yet, there are many third-party data sources, such as immunofluorescence microscopy or protein annotations and sequences, which represent a rich and vast source of complementary information. We present a unique transfer learning classification framework that utilises a nearest-neighbour or support vector machine system, to integrate heterogeneous data sources to considerably improve on the quantity and quality of sub-cellular protein assignment. We demonstrate the utility of our algorithms through evaluation of five experimental datasets, from four different species in conjunction with four different auxiliary data sources to classify proteins to tens of sub-cellular compartments with high generalisation accuracy. We further apply the method to an experiment on pluripotent mouse embryonic stem cells to classify a set of previously unknown proteins, and validate our findings against a recent high resolution map of the mouse stem cell proteome. The methodology is distributed as part of the open-source Bioconductor pRoloc suite for spatial proteomics data analysis.'),
(87823, 2016, 'plos', 'Molecular Dynamics of Fuzzy Transcriptional Activator-Coactivator Interactions', 'Scholes, Natalie S|Weinzierl, Robert O J', 'Imperial College London, Department of Life Sciences, London, United Kingdom.|Imperial College London, Department of Life Sciences, London, United Kingdom.', 'United Kingdom|United Kingdom', 0, 'Amino Acid Sequence|Basic-Leucine Zipper Transcription Factors|Computational Biology|Fuzzy Logic|Mediator Complex|Molecular Dynamics Simulation|Protein Interaction Domains and Motifs|Protein Structure, Secondary|Saccharomyces cerevisiae Proteins|Transcription Factors|Transcriptional Activation', 'Journal Article', '10.1371/journal.pcbi.1004935', '27175900', 'Transcriptional activation domains (ADs) are generally thought to be intrinsically unstructured, but capable of adopting limited secondary structure upon interaction with a coactivator surface. The indeterminate nature of this interface made it hitherto difficult to study structure/function relationships of such contacts. Here we used atomistic accelerated molecular dynamics (aMD) simulations to study the conformational changes of the GCN4 AD and variants thereof, either free in solution, or bound to the GAL11 coactivator surface. We show that the AD-coactivator interactions are highly dynamic while obeying distinct rules. The data provide insights into the constant and variable aspects of orientation of ADs relative to the coactivator, changes in secondary structure and energetic contributions stabilizing the various conformers at different time points. We also demonstrate that a prediction of xcexb1-helical propensity correlates directly with the experimentally measured transactivation potential of a large set of mutagenized ADs. The link between xcexb1-helical propensity and the stimulatory activity of ADs has fundamental practical and theoretical implications concerning the recruitment of ADs to coactivators.'),
(87824, 2016, 'plos', 'Applying, Evaluating and Refining Bioinformatics Core Competencies (An Update from the Curriculum Task Force of ISCBs Education Committee)', 'Welch, Lonnie|Brooksbank, Cath|Schwartz, Russell|Morgan, Sarah L|Gaeta, Bruno|Kilpatrick, Alastair M|Mietchen, Daniel|Moore, Benjamin L|Mulder, Nicola|Pauley, Mark|Pearson, William|Radivojac, Predrag|Rosenberg, Naomi|Rosenwald, Anne|Rustici, Gabriella|Warnow, Tandy', 'School of Electrical Engineering and Computer Science, Ohio University, Athens, Ohio, United States of America.|European Molecular Biology Laboratory, European Bioinformatics Institute, Wellcome Genome Campus, Hinxton, Cambridge, United Kingdom.|Department of Biological Sciences and Computational Biology Department, Carnegie Mellon University, Pittsburgh, Pennsylvania, United States of America.|European Molecular Biology Laboratory, European Bioinformatics Institute, Wellcome Genome Campus, Hinxton, Cambridge, United Kingdom.|School of Computer Science and Engineering, UNSW, Sydney, New South Wales, Australia.|Department of Pediatrics, University of California San Diego, La Jolla, California, United States of America.|National Institutes of Health, Bethesda, Maryland, United States of America.|MRC Institute of Genetics and Molecular Medicine, University of Edinburgh, Edinburgh, United Kingdom.|Computational Biology group, Department of Integrative Biomedical Sciences, IDM, University of Cape Town, Cape Town, South Africa.|School of Interdisciplinary Informatics, University of Nebraska at Omaha, Omaha, Nebraska, United States of America.|Department of Biochemistry and Molecular Genetics, School of Medicine, University of Virginia, Charlottesville, Virginia, United States of America.|School of Informatics and Computing, Indiana University, Bloomington, Indiana, United States of America.|Tufts University School of Medicine, Boston, Massachusetts, United States of America.|Department of Biology, Georgetown University, Washington, D.C., United States of America.|School of the Biological Sciences, University of Cambridge, Cambridge Systems Biology Centre, Cambridge, United Kingdom.|Departments of Computer Science and Bioengineering, University of Illinois, Urbana, Illinois, United States of America.', 'United States|United Kingdom|United States|United Kingdom|Australia|United States|United States|Unit', 14, 'Advisory Committees|Computational Biology|Curriculum|Humans|Professional Competence|Program Development|Societies, Scientific', 'Journal Article', '10.1371/journal.pcbi.1004943', '27175996', '-'),
(87825, 2016, 'plos', 'Fast Bayesian Inference of Copy Number Variants using Hidden Markov Models with Wavelet Compression', 'Wiedenhoeft, John|Brugel, Eric|Schliep, Alexander', 'Department of Computer Science, Rutgers University, Piscataway, New Jersey, United States of America.|Department of Computer Science, Rutgers University, Piscataway, New Jersey, United States of America.|Department of Computer Science, Rutgers University, Piscataway, New Jersey, United States of America.', 'Jersey|Jersey|Jersey', 4, 'Bayes Theorem|Breast Neoplasms|Cell Line|Comparative Genomic Hybridization|Computational Biology|Computer Simulation|DNA Copy Number Variations|Data Compression|Female|Genome, Human|Humans|Markov Chains|Models, Genetic|Software', 'Journal Article', '10.1371/journal.pcbi.1004871', '27177143', 'By integrating Haar wavelets with Hidden Markov Models, we achieve drastically reduced running times for Bayesian inference using Forward-Backward Gibbs sampling. We show that this improves detection of genomic copy number variants (CNV) in array CGH experiments compared to the state-of-the-art, including standard Gibbs sampling. The method concentrates computational effort on chromosomal segments which are difficult to call, by dynamically and adaptively recomputing consecutive blocks of observations likely to share a copy number. This makes routine diagnostic use and re-analysis of legacy data collections feasible, to this end, we also propose an effective automatic prior. An open source software implementation of our method is available at http://schlieplab.org/Software/HaMMLET/ (DOI: 10.5281/zenodo.46262). This paper was selected for oral presentation at RECOMB 2016, and an abstract is published in the conference proceedings.'),
(87826, 2016, 'plos', 'Estimating Time of Infection Using Prior Serological and Individual Information Can Greatly Improve Incidence Estimation of Human and Wildlife Infections', 'Borremans, Benny|Hens, Niel|Beutels, Philippe|Leirs, Herwig|Reijniers, Jonas', 'Evolutionary Ecology Group, University of Antwerp, Antwerp, Belgium.|Centre for Health Economics Research & Modelling Infectious Diseases (CHERMID), Vaccine & Infectious Disease Institute (VAXINFECTIO), University of Antwerp, Antwerp, Belgium.|Centre for Health Economics Research & Modelling Infectious Diseases (CHERMID), Vaccine & Infectious Disease Institute (VAXINFECTIO), University of Antwerp, Antwerp, Belgium.|Evolutionary Ecology Group, University of Antwerp, Antwerp, Belgium.|Evolutionary Ecology Group, University of Antwerp, Antwerp, Belgium.', 'Belgium|Belgium|Belgium|Belgium|Belgium', 0, 'Animals|Animals, Wild|Bayes Theorem|Computational Biology|Computer Simulation|Humans|Incidence|Infection|Mice|Models, Biological|Models, Statistical|Seroconversion|Time Factors', 'Journal Article', '10.1371/journal.pcbi.1004882', '27177244', 'Diseases of humans and wildlife are typically tracked and studied through incidence, the number of new infections per time unit. Estimating incidence is not without difficulties, as asymptomatic infections, low sampling intervals and low sample sizes can introduce large estimation errors. After infection, biomarkers such as antibodies or pathogens often change predictably over time, and this temporal pattern can contain information about the time since infection that could improve incidence estimation. Antibody level and avidity have been used to estimate time since infection and to recreate incidence, but the errors on these estimates using currently existing methods are generally large. Using a semi-parametric model in a Bayesian framework, we introduce a method that allows the use of multiple sources of information (such as antibody level, pathogen presence in different organs, individual age, season) for estimating individual time since infection. When sufficient background data are available, this method can greatly improve incidence estimation, which we show using arenavirus infection in multimammate mice as a test case. The method performs well, especially compared to the situation in which seroconversion events between sampling sessions are the main data source. The possibility to implement several sources of information allows the use of data that are in many cases already available, which means that existing incidence data can be improved without the need for additional sampling efforts or laboratory assays.'),
(87827, 2016, 'plos', 'Benchmarking Inverse Statistical Approaches for Protein Structure and Design with Exactly Solvable Models', 'Jacquin, Hugo|Gilson, Amy|Shakhnovich, Eugene|Cocco, Simona|Monasson, Rémi', 'Laboratory of Statistical Physics, Ecole Normale Supérieure, CNRS, PSL Research University, Sorbonne Universités UPMC, Paris, France.|Department of Chemistry and Chemical Biology, Harvard University, Cambridge, Massachusetts, United States of America.|Department of Chemistry and Chemical Biology, Harvard University, Cambridge, Massachusetts, United States of America.|Laboratory of Statistical Physics, Ecole Normale Supérieure, CNRS, PSL Research University, Sorbonne Universités UPMC, Paris, France.|Laboratory of Theoretical Physics, Ecole Normale Supérieure, CNRS, PSL Research University, Sorbonne Universités UPMC, Paris, France.', 'France|United States|United States|France|France', 25, 'Amino Acid Sequence|Benchmarking|Computational Biology|Computer Simulation|Models, Molecular|Models, Statistical|Protein Conformation|Protein Folding|Proteins|Sequence Alignment', 'Journal Article', '10.1371/journal.pcbi.1004889', '27177270', 'Inverse statistical approaches to determine protein structure and function from Multiple Sequence Alignments (MSA) are emerging as powerful tools in computational biology. However the underlying assumptions of the relationship between the inferred effective Potts Hamiltonian and real protein structure and energetics remain untested so far. Here we use lattice protein model (LP) to benchmark those inverse statistical approaches. We build MSA of highly stable sequences in target LP structures, and infer the effective pairwise Potts Hamiltonians from those MSA. We find that inferred Potts Hamiltonians reproduce many important aspects of true LP structures and energetics. Careful analysis reveals that effective pairwise couplings in inferred Potts Hamiltonians depend not only on the energetics of the native structure but also on competing folds, in particular, the coupling values reflect both positive design (stabilization of native conformation) and negative design (destabilization of competing folds). In addition to providing detailed structural information, the inferred Potts models used as protein Hamiltonian for design of new sequences are able to generate with high probability completely new sequences with the desired folds, which is not possible using independent-site models. Those are remarkable results as the effective LP Hamiltonians used to generate MSA are not simple pairwise models due to the competition between the folds. Our findings elucidate the reasons for the success of inverse approaches to the modelling of proteins from sequence data, and their limitations.'),
(87828, 2016, 'plos', 'Bridging Mechanistic and Phenomenological Models of Complex Biological Systems', 'Transtrum, Mark K|Qiu, Peng', 'Department of Physics and Astronomy, Brigham Young University, Provo, Utah, United States of America.|Department of Biomedical Engineering, Georgia Tech and Emory University, Atlanta, Georgia, United States of America.', 'United States|Georgia', 17, 'Adaptation, Physiological|Computational Biology|ErbB Receptors|Feedback, Physiological|Kinetics|MAP Kinase Signaling System|Models, Biological|Systems Biology', 'Journal Article', '10.1371/journal.pcbi.1004915', '27187545', 'The inherent complexity of biological systems gives rise to complicated mechanistic models with a large number of parameters. On the other hand, the collective behavior of these systems can often be characterized by a relatively small number of phenomenological parameters. We use the Manifold Boundary Approximation Method (MBAM) as a tool for deriving simple phenomenological models from complicated mechanistic models. The resulting models are not black boxes, but remain expressed in terms of the microscopic parameters. In this way, we explicitly connect the macroscopic and microscopic descriptions, characterize the equivalence class of distinct systems exhibiting the same range of collective behavior, and identify the combinations of components that function as tunable control knobs for the behavior. We demonstrate the procedure for adaptation behavior exhibited by the EGFR pathway. From a 48 parameter mechanistic model, the system can be effectively described by a single adaptation parameter xcfx84 characterizing the ratio of time scales for the initial response and recovery time of the system which can in turn be expressed as a combination of microscopic reaction rates, Michaelis-Menten constants, and biochemical concentrations. The situation is not unlike modeling in physics in which microscopically complex processes can often be renormalized into simple phenomenological models with only a few effective parameters. The proposed method additionally provides a mechanistic explanation for non-universal features of the behavior.'),
(87829, 2016, 'plos', 'Effects of Darwinian Selection and Mutability on Rate of Broadly Neutralizing Antibody Evolution during HIV-1 Infection', 'Sheng, Zizhang|Schramm, Chaim A|Connors, Mark|Morris, Lynn|Mascola, John R|Kwong, Peter D|Shapiro, Lawrence', 'Department of Biochemistry and Molecular Biophysics and Department of Systems Biology, Columbia University, New York, New York, United States of America.|Department of Biochemistry and Molecular Biophysics and Department of Systems Biology, Columbia University, New York, New York, United States of America.|Laboratory of Immunoregulation, National Institute of Allergy and Infectious Diseases, National Institutes of Health, Bethesda, Maryland, United States of America.|Center for HIV and STIs, National Institute for Communicable Diseases of the National Health Laboratory Service, Johannesburg, South Africa.|Vaccine Research Center, National Institute of Allergy and Infectious Diseases, National Institutes of Health, Bethesda, Maryland, United States of America.|Vaccine Research Center, National Institute of Allergy and Infectious Diseases, National Institutes of Health, Bethesda, Maryland, United States of America.|Department of Biochemistry and Molecular Biophysics and Department of Systems Biology, Columbia University, New York, New York, United States of America.', 'United States|United States|United States|South Africa|United States|United States|United States', 19, 'Antibodies, Neutralizing|Antibody Affinity|Complementarity Determining Regions|Computational Biology|Evolution, Molecular|Genes, Immunoglobulin|HIV Antibodies|HIV Infections|HIV-1|High-Throughput Nucleotide Sequencing|Humans|Immunoglobulin Variable Region|Longitudinal Studies|Models, Genetic|Models, Immunological|Mutation|Selection, Genetic|Somatic Hypermutation, Immunoglobulin', 'Journal Article', '10.1371/journal.pcbi.1004940', '27191167', 'Accumulation of somatic mutations in antibody variable regions is critical for antibody affinity maturation, with HIV-1 broadly neutralizing antibodies (bnAbs) generally requiring years to develop. We recently found that the rate at which mutations accumulate decreases over time, but the mechanism governing this slowing is unclear. In this study, we investigated whether natural selection and/or mutability of the antibody variable region contributed significantly to observed decrease in rate. We used longitudinally sampled sequences of immunoglobulin transcripts of single lineages from each of 3 donors, as determined by next generation sequencing. We estimated the evolutionary rates of the complementarity determining regions (CDRs), which are most significant for functional selection, and found they evolved about 1.5- to 2- fold faster than the framework regions. We also analyzed the presence of AID hotspots and coldspots at different points in lineage development and observed an average decrease in mutability of less than 10 percent over time. Altogether, the correlation between Darwinian selection strength and evolutionary rate trended toward significance, especially for CDRs, but cannot fully explain the observed changes in evolutionary rate. The mutability modulated by AID hotspots and coldspots changes correlated only weakly with evolutionary rates. The combined effects of Darwinian selection and mutability contribute substantially to, but do not fully explain, evolutionary rate change for HIV-1-targeting bnAb lineages.');
INSERT INTO `papers` (`id`, `ano`, `journal`, `titulo`, `autores`, `afiliacao`, `pais`, `citacoes`, `palavra_chave`, `categorias`, `doi`, `pubmed`, `abstract`) VALUES
(87830, 2016, 'plos', 'Neuroprosthetic Decoder Training as Imitation Learning', 'Merel, Josh|Carlson, David|Paninski, Liam|Cunningham, John P', 'Neurobiology and Behavior program, Columbia University, New York, New York, United States of America.|Department of Statistics, Columbia University, New York, New York, United States of America.|Neurobiology and Behavior program, Columbia University, New York, New York, United States of America.|Neurobiology and Behavior program, Columbia University, New York, New York, United States of America.', 'United States|United States|United States|United States', 4, 'Algorithms|Arm|Brain-Computer Interfaces|Computational Biology|Computer Simulation|Humans|Learning|Robotics|Supervised Machine Learning|Task Performance and Analysis', 'Journal Article', '10.1371/journal.pcbi.1004948', '27191387', 'Neuroprosthetic brain-computer interfaces function via an algorithm which decodes neural activity of the user into movements of an end effector, such as a cursor or robotic arm. In practice, the decoder is often learned by updating its parameters while the user performs a task. When the users intention is not directly observable, recent methods have demonstrated value in training the decoder against a surrogate for the users intended movement. Here we show that training a decoder in this way is a novel variant of an imitation learning problem, where an oracle or expert is employed for supervised training in lieu of direct observations, which are not available. Specifically, we describe how a generic imitation learning meta-algorithm, dataset aggregation (DAgger), can be adapted to train a generic brain-computer interface. By deriving existing learning algorithms for brain-computer interfaces in this framework, we provide a novel analysis of regret (an important metric of learning efficacy) for brain-computer interfaces. This analysis allows us to characterize the space of algorithmic variants and bounds on their regret rates. Existing approaches for decoder learning have been performed in the cursor control setting, but the available design principles for these decoders are such that it has been impossible to scale them to naturalistic settings. Leveraging our findings, we then offer an algorithm that combines imitation learning with optimal control, which should allow for training of arbitrary effectors for which optimal control can generate goal-oriented control. We demonstrate this novel and general BCI algorithm with simulated neuroprosthetic control of a 26 degree-of-freedom model of an arm, a sophisticated and realistic end effector.'),
(87831, 2016, 'plos', 'Bayesian Top-Down Protein Sequence Alignment with Inferred Position-Specific Gap Penalties', '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.|National Center for Biotechnology Information, National Library of Medicine, National Institutes of Health, Bethesda, Maryland, United States of America.', 'United States|United States', 9, 'Algorithms|Bayes Theorem|Computational Biology|Databases, Protein|Markov Chains|Monte Carlo Method|Proteins|Sequence Alignment|Software', 'Journal Article', '10.1371/journal.pcbi.1004936', '27192614', 'We describe a Bayesian Markov chain Monte Carlo (MCMC) sampler for protein multiple sequence alignment (MSA) that, as implemented in the program GISMO and applied to large numbers of diverse sequences, is more accurate than the popular MSA programs MUSCLE, MAFFT, Clustal-xcexa9 and Kalign. Features of GISMO central to its performance are: (i) It employs a top-down strategy with a favorable asymptotic time complexity that first identifies regions generally shared by all the input sequences, and then realigns closely related subgroups in tandem. (ii) It infers position-specific gap penalties that favor insertions or deletions (indels) within each sequence at alignment positions in which indels are invoked in other sequences. This favors the placement of insertions between conserved blocks, which can be understood as making up the proteins structural core. (iii) It uses a Bayesian statistical measure of alignment quality based on the minimum description length principle and on Dirichlet mixture priors. Consequently, GISMO aligns sequence regions only when statistically justified. This is unlike methods based on the ad hoc, but widely used, sum-of-the-pairs scoring system, which will align random sequences. (iv) It defines a system for exploring alignment space that provides natural avenues for further experimentation through the development of new sampling strategies for more efficiently escaping from suboptimal traps. GISMOs superior performance is illustrated using 408 protein sets containing, on average, 235 sequences. These sets correspond to NCBI Conserved Domain Database alignments, which have been manually curated in the light of available crystal structures, and thus provide a means to assess alignment accuracy. GISMO fills a different niche than other MSA programs, namely identifying and aligning a conserved domain present within a large, diverse set of full length sequences. The GISMO program is available at http://gismo.igs.umaryland.edu/.'),
(87832, 2016, 'plos', 'A Single Mechanism Can Account for Human Perception of Depth in Mixed Correlation Random Dot Stereograms', 'Henriksen, Sid|Cumming, Bruce G|Read, Jenny C A', 'Laboratory of Sensorimotor Research, National Eye Institute, National Institutes of Health, Bethesda, Maryland, United States of America.|Laboratory of Sensorimotor Research, National Eye Institute, National Institutes of Health, Bethesda, Maryland, United States of America.|Institute of Neuroscience, Newcastle University, Newcastle upon Tyne, United Kingdom.', 'United States|United States|United Kingdom', 9, 'Computational Biology|Computer Simulation|Decision Support Techniques|Depth Perception|Humans|Models, Neurological|Models, Psychological|Neurons|Photic Stimulation|Psychophysics|Vision Disparity|Vision, Binocular|Visual Cortex', 'Journal Article', '10.1371/journal.pcbi.1004906', '27196696', 'In order to extract retinal disparity from a visual scene, the brain must match corresponding points in the left and right retinae. This computationally demanding task is known as the stereo correspondence problem. The initial stage of the solution to the correspondence problem is generally thought to consist of a correlation-based computation. However, recent work by Doi et al suggests that human observers can see depth in a class of stimuli where the mean binocular correlation is 0 (half-matched random dot stereograms). Half-matched random dot stereograms are made up of an equal number of correlated and anticorrelated dots, and the binocular energy model-a well-known model of V1 binocular complex cells-fails to signal disparity here. This has led to the proposition that a second, match-based computation must be extracting disparity in these stimuli. Here we show that a straightforward modification to the binocular energy model-adding a point output nonlinearity-is by itself sufficient to produce cells that are disparity-tuned to half-matched random dot stereograms. We then show that a simple decision model using this single mechanism can reproduce psychometric functions generated by human observers, including reduced performance to large disparities and rapidly updating dot patterns. The model makes predictions about how performance should change with dot size in half-matched stereograms and temporal alternation in correlation, which we test in human observers. We conclude that a single correlation-based computation, based directly on already-known properties of V1 neurons, can account for the literature on mixed correlation random dot stereograms.'),
(87833, 2016, 'plos', 'Cellular Architecture Regulates Collective Calcium Signaling and Cell Contractility', 'Sun, Jian|Hoying, James B|Deymier, Pierre A|Zhang, Donna D|Wong, Pak Kin', 'Department of Mechanical Science and Engineering, University of Illinois at Urbana-Champaign, Urbana, Illinois, United States of America.|Cardiovascular Innovation Institute, University of Louisville & Jewish Hospital, Louisville, Kentucky, United States of America.|Material Science and Engineering Department, The University of Arizona, Tucson, Arizona, United States of America.|Department of Pharmacology and Toxicology, The University of Arizona, Tucson, Arizona, United States of America.|Department of Aerospace and Mechanical Engineering, The University of Arizona, Tucson, Arizona, United States of America.', 'United States|United States|United States|United States|United States', 5, 'Actin Cytoskeleton|Calcium Signaling|Cell Communication|Cell Movement|Cellular Microenvironment|Computational Biology|Computer Simulation|Endothelial Cells|Gap Junctions|Histamine|Human Umbilical Vein Endothelial Cells|Humans|Models, Biological', 'Journal Article', '10.1371/journal.pcbi.1004955', '27196735', 'A key feature of multicellular systems is the ability of cells to function collectively in response to external stimuli. However, the mechanisms of intercellular cell signaling and their functional implications in diverse vascular structures are poorly understood. Using a combination of computational modeling and plasma lithography micropatterning, we investigate the roles of structural arrangement of endothelial cells in collective calcium signaling and cell contractility. Under histamine stimulation, endothelial cells in self-assembled and microengineered networks, but not individual cells and monolayers, exhibit calcium oscillations. Micropatterning, pharmacological inhibition, and computational modeling reveal that the calcium oscillation depends on the number of neighboring cells coupled via gap junctional intercellular communication, providing a mechanistic basis of the architecture-dependent calcium signaling. Furthermore, the calcium oscillation attenuates the histamine-induced cytoskeletal reorganization and cell contraction, resulting in differential cell responses in an architecture-dependent manner. Taken together, our results suggest that endothelial cells can sense and respond to chemical stimuli according to the vascular architecture via collective calcium signaling.'),
(87834, 2016, 'plos', 'Computational Identification of Genomic Features That Influence 3D Chromatin Domain Formation', 'Mourad, Raphaël|Cuvier, Olivier', 'Laboratoire de Biologie Moléculaire Eucaryote (LBME), CNRS, Université Paul Sabatier (UPS), Toulouse, France.|Laboratoire de Biologie Moléculaire Eucaryote (LBME), CNRS, Université Paul Sabatier (UPS), Toulouse, France.', 'France|France', 16, 'Animals|CCCTC-Binding Factor|Chromatin|Computational Biology|Computer Simulation|Drosophila Proteins|Drosophila melanogaster|Genome, Human|Genome, Insect|High-Throughput Nucleotide Sequencing|Humans|Imaging, Three-Dimensional|Logistic Models|Models, Genetic|Polymorphism, Single Nucleotide|Repressor Proteins|Sequence Analysis, DNA', 'Journal Article', '10.1371/journal.pcbi.1004908', '27203237', 'Recent advances in long-range Hi-C contact mapping have revealed the importance of the 3D structure of chromosomes in gene expression. A current challenge is to identify the key molecular drivers of this 3D structure. Several genomic features, such as architectural proteins and functional elements, were shown to be enriched at topological domain borders using classical enrichment tests. Here we propose multiple logistic regression to identify those genomic features that positively or negatively influence domain border establishment or maintenance. The model is flexible, and can account for statistical interactions among multiple genomic features. Using both simulated and real data, we show that our model outperforms enrichment test and non-parametric models, such as random forests, for the identification of genomic features that influence domain borders. Using Drosophila Hi-C data at a very high resolution of 1 kb, our model suggests that, among architectural proteins, BEAF-32 and CP190 are the main positive drivers of 3D domain borders. In humans, our model identifies well-known architectural proteins CTCF and cohesin, as well as ZNF143 and Polycomb group proteins as positive drivers of domain borders. The model also reveals the existence of several negative drivers that counteract the presence of domain borders including P300, RXRA, BCL11A and ELK1.'),
(87835, 2016, 'plos', 'Biophysical Network Modelling of the dLGN Circuit: Different Effects of Triadic and Axonal Inhibition on Visual Responses of Relay Cells', 'Heiberg, Thomas|Hagen, Espen|Halnes, Geir|Einevoll, Gaute T', 'Department of Mathematical Sciences and Technology, Norwegian University of Life Sciences, Ås, Norway.|Department of Mathematical Sciences and Technology, Norwegian University of Life Sciences, Ås, Norway.|Department of Mathematical Sciences and Technology, Norwegian University of Life Sciences, Ås, Norway.|Department of Mathematical Sciences and Technology, Norwegian University of Life Sciences, Ås, Norway.', 'Norway|Norway|Norway|Norway', 3, 'Animals|Axons|Biophysical Phenomena|Cats|Computational Biology|Computer Simulation|Evoked Potentials, Visual|Geniculate Bodies|Interneurons|Models, Neurological|Photic Stimulation|Retinal Ganglion Cells|Visual Cortex|Visual Pathways', 'Journal Article', '10.1371/journal.pcbi.1004929', '27203421', 'Despite its prominent placement between the retina and primary visual cortex in the early visual pathway, the role of the dorsal lateral geniculate nucleus (dLGN) in molding and regulating the visual signals entering the brain is still poorly understood. A striking feature of the dLGN circuit is that relay cells (RCs) and interneurons (INs) form so-called triadic synapses, where an IN dendritic terminal can be simultaneously postsynaptic to a retinal ganglion cell (GC) input and presynaptic to an RC dendrite, allowing for so-called triadic inhibition. Taking advantage of a recently developed biophysically detailed multicompartmental model for an IN, we here investigate putative effects of these different inhibitory actions of INs, i.e., triadic inhibition and standard axonal inhibition, on the response properties of RCs. We compute and investigate so-called area-response curves, that is, trial-averaged visual spike responses vs. spot size, for circular flashing spots in a network of RCs and INs. The model parameters are grossly tuned to give results in qualitative accordance with previous in vivo data of responses to such stimuli for cat GCs and RCs. We particularly investigate how the model ingredients affect salient response properties such as the receptive-field center size of RCs and INs, maximal responses and center-surround antagonisms. For example, while triadic inhibition not involving firing of IN action potentials was found to provide only a non-linear gain control of the conversion of input spikes to output spikes by RCs, axonal inhibition was in contrast found to substantially affect the receptive-field center size: the larger the inhibition, the more the RC center size shrinks compared to the GC providing the feedforward excitation. Thus, a possible role of the different inhibitory actions from INs to RCs in the dLGN circuit is to provide separate mechanisms for overall gain control (direct triadic inhibition) and regulation of spatial resolution (axonal inhibition) of visual signals sent to cortex.'),
(87836, 2016, 'plos', 'A Detailed Data-Driven Network Model of Prefrontal Cortex Reproduces Key Features of In Vivo Activity', 'Hass, Joachim|Hertäg, Loreen|Durstewitz, Daniel', 'Department of Theoretical Neuroscience, Bernstein-Center for Computational Neuroscience, Central Institute of Mental Health, Medical Faculty Mannheim of Heidelberg University, Mannheim, Germany.|Modelling of Cognitive Processes, Berlin Institute of Technology and Bernstein Center for Computational Neuroscience Berlin, Germany.|Department of Theoretical Neuroscience, Bernstein-Center for Computational Neuroscience, Central Institute of Mental Health, Medical Faculty Mannheim of Heidelberg University, Mannheim, Germany.', 'Germany|Germany|Germany', 0, 'Action Potentials|Animals|Cognition|Computational Biology|Computer Simulation|Electrophysiological Phenomena|Humans|Mice|Models, Neurological|Models, Psychological|Nerve Net|Neural Networks (Computer)|Neuronal Plasticity|Neurons|Prefrontal Cortex|Rats', 'Journal Article', '10.1371/journal.pcbi.1004930', '27203563', 'The prefrontal cortex is centrally involved in a wide range of cognitive functions and their impairment in psychiatric disorders. Yet, the computational principles that govern the dynamics of prefrontal neural networks, and link their physiological, biochemical and anatomical properties to cognitive functions, are not well understood. Computational models can help to bridge the gap between these different levels of description, provided they are sufficiently constrained by experimental data and capable of predicting key properties of the intact cortex. Here, we present a detailed network model of the prefrontal cortex, based on a simple computationally efficient single neuron model (simpAdEx), with all parameters derived from in vitro electrophysiological and anatomical data. Without additional tuning, this model could be shown to quantitatively reproduce a wide range of measures from in vivo electrophysiological recordings, to a degree where simulated and experimentally observed activities were statistically indistinguishable. These measures include spike train statistics, membrane potential fluctuations, local field potentials, and the transmission of transient stimulus information across layers. We further demonstrate that model predictions are robust against moderate changes in key parameters, and that synaptic heterogeneity is a crucial ingredient to the quantitative reproduction of in vivo-like electrophysiological behavior. Thus, we have produced a physiologically highly valid, in a quantitative sense, yet computationally efficient PFC network model, which helped to identify key properties underlying spike time dynamics as observed in vivo, and can be harvested for in-depth investigation of the links between physiology and cognition.'),
(87837, 2016, 'plos', 'Reactome from a WikiPathways Perspective', 'Bohler, Anwesha|Wu, Guanming|Kutmon, Martina|Pradhana, Leontius Adhika|Coort, Susan L|Hanspers, Kristina|Haw, Robin|Pico, Alexander R|Evelo, Chris T', 'Department of Bioinformatics-BiGCaT, Maastricht University, Maastricht, The Netherlands.|Ontario Institute for Cancer Research, MaRS Centre, Toronto, Ontario, Canada.|Department of Bioinformatics-BiGCaT, Maastricht University, Maastricht, The Netherlands.|Department of Pharmacy, Faculty of Science, National University of Singapore, Singapore, Republic of Singapore.|Department of Bioinformatics-BiGCaT, Maastricht University, Maastricht, The Netherlands.|Gladstone Institutes, San Francisco, California, United States of America.|Ontario Institute for Cancer Research, MaRS Centre, Toronto, Ontario, Canada.|Gladstone Institutes, San Francisco, California, United States of America.|Department of Bioinformatics-BiGCaT, Maastricht University, Maastricht, The Netherlands.', 'Netherlands|Canada|Netherlands|Singapore|Netherlands|United States|Canada|United States|Netherlands', 15, 'Computational Biology|Computer Graphics|Databases, Factual|Gene Ontology|Humans|Internet|Knowledge Bases|Metabolic Networks and Pathways|Models, Biological|Software', 'Journal Article', '10.1371/journal.pcbi.1004941', '27203685', 'Reactome and WikiPathways are two of the most popular freely available databases for biological pathways. Reactome pathways are centrally curated with periodic input from selected domain experts. WikiPathways is a community-based platform where pathways are created and continually curated by any interested party. The nascent collaboration between WikiPathways and Reactome illustrates the mutual benefits of combining these two approaches. We created a format converter that converts Reactome pathways to the GPML format used in WikiPathways. In addition, we developed the ComplexViz plugin for PathVisio which simplifies looking up complex components. The plugin can also score the complexes on a pathway based on a user defined criterion. This score can then be visualized on the complex nodes using the visualization options provided by the plugin. Using the merged collection of curated and converted Reactome pathways, we demonstrate improved pathway coverage of relevant biological processes for the analysis of a previously described polycystic ovary syndrome gene expression dataset. Additionally, this conversion allows researchers to visualize their data on Reactome pathways using PathVisios advanced data visualization functionalities. WikiPathways benefits from the dedicated focus and attention provided to the content converted from Reactome and the wealth of semantic information about interactions. Reactome in turn benefits from the continuous community curation available on WikiPathways. The research community at large benefits from the availability of a larger set of pathways for analysis in PathVisio and Cytoscape. The pathway statistics results obtained from PathVisio are significantly better when using a larger set of candidate pathways for analysis. The conversion serves as a general model for integration of multiple pathway resources developed using different approaches.'),
(87838, 2016, 'plos', 'Correction: Measuring Fisher Information Accurately in Correlated Neural Populations', 'PLOS Computational Biology Staff', 'Department of Bioinformatics-BiGCaT, Maastricht University, Maastricht, The Netherlands.', 'Netherlands', 0, '-', 'Published Erratum', '10.1371/journal.pcbi.1004945', '27203712', '[This corrects the article DOI: 10.1371/journal.pcbi.1004218.].'),
(87839, 2016, 'plos', 'Evaluation of the Phase-Dependent Rhythm Control of Human Walking Using Phase Response Curves', 'Funato, Tetsuro|Yamamoto, Yuki|Aoi, Shinya|Imai, Takashi|Aoyagi, Toshio|Tomita, Nozomi|Tsuchiya, Kazuo', 'Department of Mechanical Engineering and Intelligent Systems, The University of Electro-communications, Chofu, Tokyo, Japan.|Department of Energy and Mechanical Engineering, Doshisha University, Kyotanabe-shi, Kyoto, Japan.|Japan Science and Technology Agency (JST), CREST, Chiyoda-ku, Tokyo, Japan.|Department of Applied Analysis and Complex Dynamical Systems, Kyoto University, Sakyo-ku, Kyoto, Japan.|Japan Science and Technology Agency (JST), CREST, Chiyoda-ku, Tokyo, Japan.|Japan Science and Technology Agency (JST), CREST, Chiyoda-ku, Tokyo, Japan.|Japan Science and Technology Agency (JST), CREST, Chiyoda-ku, Tokyo, Japan.', 'Japan|Japan|Japan|Japan|Japan|Japan|Japan', 0, 'Acceleration|Biomechanical Phenomena|Computational Biology|Gait|Humans|Leg|Male|Models, Biological|Muscle, Skeletal|Periodicity|Walking|Young Adult', 'Journal Article', '10.1371/journal.pcbi.1004950', '27203839', 'Humans and animals control their walking rhythms to maintain motion in a variable environment. The neural mechanism for controlling rhythm has been investigated in many studies using mechanical and electrical stimulation. However, quantitative evaluation of rhythm variation in response to perturbation at various timings has rarely been investigated. Such a characteristic of rhythm is described by the phase response curve (PRC). Dynamical simulations of human skeletal models with changing walking rhythms (phase reset) described a relation between the effective phase reset on stability and PRC, and phase reset around touch-down was shown to improve stability. A PRC of human walking was estimated by pulling the swing leg, but such perturbations hardly influenced the stance leg, so the relation between the PRC and walking events was difficult to discuss. This research thus examines human response to variations in floor velocity. Such perturbation yields another problem, in that the swing leg is indirectly (and weakly) perturbed, so the precision of PRC decreases. To solve this problem, this research adopts the weighted spike-triggered average (WSTA) method. In the WSTA method, a sequential pulsed perturbation is used for stimulation. This is in contrast with the conventional impulse method, which applies an intermittent impulsive perturbation. The WSTA method can be used to analyze responses to a large number of perturbations for each sequence. In the experiment, perturbations are applied to walking subjects by rapidly accelerating and decelerating a treadmill belt, and measured data are analyzed by the WSTA and impulse methods. The PRC obtained by the WSTA method had clear and stable waveforms with a higher temporal resolution than those obtained by the impulse method. By investigation of the rhythm transition for each phase of walking using the obtained PRC, a rhythm change that extends the touch-down and mid-single support phases is found to occur.'),
(87840, 2016, 'plos', 'From Binding-Induced Dynamic Effects in SH3 Structures to Evolutionary Conserved Sectors', 'Zafra Ruano, Ana|Cilia, Elisa|Couceiro, José R|Ruiz Sanz, Javier|Schymkowitz, Joost|Rousseau, Frederic|Luque, Irene|Lenaerts, Tom', 'Department of Physical Chemistry and Institute of Biotechnology, University of Granada, Campus Fuentenueva s/n, Granada, Spain.|MLG, Départment dInformatique, Université Libre de Bruxelles, Brussels, Belgium.|VIB SWITCH Laboratory, Leuven, Belgium.|Department of Physical Chemistry and Institute of Biotechnology, University of Granada, Campus Fuentenueva s/n, Granada, Spain.|VIB SWITCH Laboratory, Leuven, Belgium.|VIB SWITCH Laboratory, Leuven, Belgium.|Department of Physical Chemistry and Institute of Biotechnology, University of Granada, Campus Fuentenueva s/n, Granada, Spain.|MLG, Départment dInformatique, Université Libre de Bruxelles, Brussels, Belgium.', 'Spain|Belgium|Belgium|Spain|Belgium|Belgium|Spain|Belgium', 3, 'Amino Acid Sequence|Animals|Computational Biology|Computer Simulation|Evolution, Molecular|Humans|Ligands|Models, Molecular|Mutation|Protein Binding|Sequence Alignment|Thermodynamics|src Homology Domains', 'Journal Article', '10.1371/journal.pcbi.1004938', '27213566', 'Src Homology 3 domains are ubiquitous small interaction modules known to act as docking sites and regulatory elements in a wide range of proteins. Prior experimental NMR work on the SH3 domain of Src showed that ligand binding induces long-range dynamic changes consistent with an induced fit mechanism. The identification of the residues that participate in this mechanism produces a chart that allows for the exploration of the regulatory role of such domains in the activity of the encompassing protein. Here we show that a computational approach focusing on the changes in side chain dynamics through ligand binding identifies equivalent long-range effects in the Src SH3 domain. Mutation of a subset of the predicted residues elicits long-range effects on the binding energetics, emphasizing the relevance of these positions in the definition of intramolecular cooperative networks of signal transduction in this domain. We find further support for this mechanism through the analysis of seven other publically available SH3 domain structures of which the sequences represent diverse SH3 classes. By comparing the eight predictions, we find that, in addition to a dynamic pathway that is relatively conserved throughout all SH3 domains, there are dynamic aspects specific to each domain and homologous subgroups. Our work shows for the first time from a structural perspective, which transduction mechanisms are common between a subset of closely related and distal SH3 domains, while at the same time highlighting the differences in signal transduction that make each family member unique. These results resolve the missing link between structural predictions of dynamic changes and the domain sectors recently identified for SH3 domains through sequence analysis.'),
(87841, 2016, 'plos', 'Modelling Virus and Antibody Dynamics during Dengue Virus Infection Suggests a Role for Antibody in Virus Clearance', 'Clapham, Hannah E|Quyen, Than Ha|Kien, Duong Thi Hue|Dorigatti, Ilaria|Simmons, Cameron P|Ferguson, Neil M', 'MRC Centre for Outbreak Analysis and Modelling, DIDE, Imperial College, London, United Kingdom.|Oxford University Clinical Research Unit-Wellcome Trust Major Overseas Programme, Ho Chi Minh City, Vietnam.|Oxford University Clinical Research Unit-Wellcome Trust Major Overseas Programme, Ho Chi Minh City, Vietnam.|MRC Centre for Outbreak Analysis and Modelling, DIDE, Imperial College, London, United Kingdom.|Oxford University Clinical Research Unit-Wellcome Trust Major Overseas Programme, Ho Chi Minh City, Vietnam.|MRC Centre for Outbreak Analysis and Modelling, DIDE, Imperial College, London, United Kingdom.', 'United Kingdom|-|-|United Kingdom|-|United Kingdom', 17, 'Antibodies, Neutralizing|Antibodies, Viral|Antibody-Dependent Cell Cytotoxicity|Computational Biology|Dengue|Dengue Virus|Host-Pathogen Interactions|Humans|Kinetics|Models, Biological|Models, Immunological|RNA, Viral|Viral Load|Virus Replication', 'Journal Article', '10.1371/journal.pcbi.1004951', '27213681', 'Dengue is an infection of increasing global importance, yet uncertainty remains regarding critical aspects of its virology, immunology and epidemiology. One unanswered question is how infection is controlled and cleared during a dengue infection. Antibody is thought to play a role, but little past work has examined the kinetics of both virus and antibody during natural infections. We present data on multiple virus and antibody titres measurements recorded sequentially during infection from 53 Vietnamese dengue patients. We fit mechanistic mathematical models of the dynamics of viral replication and the host immune response to these data. These models fit the data well. The model with antibody removing virus fits the data best, but with a role suggested for ADCC or other infected cell clearance mechanisms. Our analysis therefore shows that the observed viral and antibody kinetics are consistent with antibody playing a key role in controlling viral replication. This work gives quantitative insight into the relationship between antibody levels and the efficiency of viral clearance. It will inform the future development of mechanistic models of how vaccines and antivirals might modify the course of natural dengue infection.'),
(87842, 2016, 'plos', 'Spike-Based Bayesian-Hebbian Learning of Temporal Sequences', 'Tully, Philip J|Lindén, Henrik|Hennig, Matthias H|Lansner, Anders', 'Department of Computational Science and Technology, Royal Institute of Technology (KTH), Stockholm, Sweden.|Department of Computational Science and Technology, Royal Institute of Technology (KTH), Stockholm, Sweden.|Institute for Adaptive and Neural Computation, School of Informatics, University of Edinburgh, Edinburgh, United Kingdom.|Department of Computational Science and Technology, Royal Institute of Technology (KTH), Stockholm, Sweden.', 'Sweden|Sweden|United Kingdom|Sweden', 15, 'Action Potentials|Animals|Bayes Theorem|Computational Biology|Humans|Learning|Models, Neurological|N-Methylaspartate|Neocortex|Neural Networks (Computer)|Neuronal Plasticity|alpha-Amino-3-hydroxy-5-methyl-4-isoxazolepropionic Acid', 'Journal Article', '10.1371/journal.pcbi.1004954', '27213810', 'Many cognitive and motor functions are enabled by the temporal representation and processing of stimuli, but it remains an open issue how neocortical microcircuits can reliably encode and replay such sequences of information. To better understand this, a modular attractor memory network is proposed in which meta-stable sequential attractor transitions are learned through changes to synaptic weights and intrinsic excitabilities via the spike-based Bayesian Confidence Propagation Neural Network (BCPNN) learning rule. We find that the formation of distributed memories, embodied by increased periods of firing in pools of excitatory neurons, together with asymmetrical associations between these distinct network states, can be acquired through plasticity. The models feasibility is demonstrated using simulations of adaptive exponential integrate-and-fire model neurons (AdEx). We show that the learning and speed of sequence replay depends on a confluence of biophysically relevant parameters including stimulus duration, level of background noise, ratio of synaptic currents, and strengths of short-term depression and adaptation. Moreover, sequence elements are shown to flexibly participate multiple times in the sequence, suggesting that spiking attractor networks of this type can support an efficient combinatorial code. The model provides a principled approach towards understanding how multiple interacting plasticity mechanisms can coordinate hetero-associative learning in unison.'),
(87843, 2016, 'plos', 'The Influence of Hydroxylation on Maintaining CpG Methylation Patterns: A Hidden Markov Model Approach', 'Giehr, Pascal|Kyriakopoulos, Charalampos|Ficz, Gabriella|Wolf, Verena|Walter, Jörn', 'Department of Biological Sciences, UdS, Saarbrücken, Saarland, Germany.|Computer Science Department, UdS, Saarbrücken, Saarland, Germany.|Barts Cancer Institute, Queen Mary University, London, United Kingdom.|Computer Science Department, UdS, Saarbrücken, Saarland, Germany.|Department of Biological Sciences, UdS, Saarbrücken, Saarland, Germany.', 'Germany|Germany|United Kingdom|Germany|Germany', 10, '5-Methylcytosine|Animals|Cell Division|Computational Biology|CpG Islands|DNA Methylation|DNA Replication|Embryonic Stem Cells|Hydroxylation|Markov Chains|Mice|Models, Biological|Stochastic Processes|Sulfites', 'Journal Article', '10.1371/journal.pcbi.1004905', '27224554', 'DNA methylation and demethylation are opposing processes that when in balance create stable patterns of epigenetic memory. The control of DNA methylation pattern formation by replication dependent and independent demethylation processes has been suggested to be influenced by Tet mediated oxidation of 5mC. Several alternative mechanisms have been proposed suggesting that 5hmC influences either replication dependent maintenance of DNA methylation or replication independent processes of active demethylation. Using high resolution hairpin oxidative bisulfite sequencing data, we precisely determine the amount of 5mC and 5hmC and model the contribution of 5hmC to processes of demethylation in mouse ESCs. We develop an extended hidden Markov model capable of accurately describing the regional contribution of 5hmC to demethylation dynamics. Our analysis shows that 5hmC has a strong impact on replication dependent demethylation, mainly by impairing methylation maintenance.'),
(87844, 2016, 'plos', 'Tuning Curves for Arm Posture Control in Motor Cortex Are Consistent with Random Connectivity', 'Lalazar, Hagai|Abbott, L F|Vaadia, Eilon', 'Center for Theoretical Neuroscience, Columbia University, New York, New York, United States of America.|Center for Theoretical Neuroscience, Columbia University, New York, New York, United States of America.|Edmond and Lily Safra Center for Brain Sciences, Hebrew University, Jerusalem, Israel.', 'United States|United States|Israel', 3, 'Animals|Arm|Computational Biology|Electromyography|Feedback, Sensory|Female|Macaca fascicularis|Male|Models, Neurological|Motor Cortex|Movement|Neural Networks (Computer)|Neurons|Posture|User-Computer Interface', 'Journal Article', '10.1371/journal.pcbi.1004910', '27224735', 'Neuronal responses characterized by regular tuning curves are typically assumed to arise from structured synaptic connectivity. However, many responses exhibit both regular and irregular components. To address the relationship between tuning curve properties and underlying circuitry, we analyzed neuronal activity recorded from primary motor cortex (M1) of monkeys performing a 3D arm posture control task and compared the results with a neural network model. Posture control is well suited for examining M1 neuronal tuning because it avoids the dynamic complexity of time-varying movements. As a function of hand position, the neuronal responses have a linear component, as has previously been described, as well as heterogeneous and highly irregular nonlinearities. These nonlinear components involve high spatial frequencies and therefore do not support explicit encoding of movement parameters. Yet both the linear and nonlinear components contribute to the decoding of EMG of major muscles used in the task. Remarkably, despite the presence of a strong linear component, a feedforward neural network model with entirely random connectivity can replicate the data, including both the mean and distributions of the linear and nonlinear components as well as several other features of the neuronal responses. This result shows that smoothness provided by the regularity in the inputs to M1 can impose apparent structure on neural responses, in this case a strong linear (also known as cosine) tuning component, even in the absence of ordered synaptic connectivity.'),
(87845, 2016, 'plos', 'PEPIS: A Pipeline for Estimating Epistatic Effects in Quantitative Trait Locus Mapping and Genome-Wide Association Studies', 'Zhang, Wenchao|Dai, Xinbin|Wang, Qishan|Xu, Shizhong|Zhao, Patrick X', 'Plant Biology Division, Samuel Roberts Noble Foundation, Ardmore, Oklahoma, United States of America.|Plant Biology Division, Samuel Roberts Noble Foundation, Ardmore, Oklahoma, United States of America.|School of Agriculture and Biology, Shanghai Jiao Tong University, Shanghai, Peoples Republic of China.|Department of Botany and Plant Sciences, University of California, Riverside, Riverside, California, United States of America.|Plant Biology Division, Samuel Roberts Noble Foundation, Ardmore, Oklahoma, United States of America.', 'United States|United States|China|United States|United States', 13, 'Chromosome Mapping|Computational Biology|Computer Simulation|Epistasis, Genetic|Genome-Wide Association Study|Hybridization, Genetic|Linear Models|Oryza|Programming Languages|Quantitative Trait Loci|Software', 'Journal Article', '10.1371/journal.pcbi.1004925', '27224861', 'The term epistasis refers to interactions between multiple genetic loci. Genetic epistasis is important in regulating biological function and is considered to explain part of the missing heritability, which involves marginal genetic effects that cannot be accounted for in genome-wide association studies. Thus, the study of epistasis is of great interest to geneticists. However, estimating epistatic effects for quantitative traits is challenging due to the large number of interaction effects that must be estimated, thus significantly increasing computing demands. Here, we present a new web server-based tool, the Pipeline for estimating EPIStatic genetic effects (PEPIS), for analyzing polygenic epistatic effects. The PEPIS software package is based on a new linear mixed model that has been used to predict the performance of hybrid rice. The PEPIS includes two main sub-pipelines: the first for kinship matrix calculation, and the second for polygenic component analyses and genome scanning for main and epistatic effects. To accommodate the demand for high-performance computation, the PEPIS utilizes C/C++ for mathematical matrix computing. In addition, the modules for kinship matrix calculations and main and epistatic-effect genome scanning employ parallel computing technology that effectively utilizes multiple computer nodes across our networked cluster, thus significantly improving the computational speed. For example, when analyzing the same immortalized F2 rice population genotypic data examined in a previous study, the PEPIS returned identical results at each analysis step with the original prototype R code, but the computational time was reduced from more than one month to about five minutes. These advances will help overcome the bottleneck frequently encountered in genome wide epistatic genetic effect analysis and enable accommodation of the high computational demand. The PEPIS is publically available at http://bioinfo.noble.org/PolyGenic_QTL/.'),
(87846, 2016, 'plos', 'PredictSNP2: A Unified Platform for Accurately Evaluating SNP Effects by Exploiting the Different Characteristics of Variants in Distinct Genomic Regions', 'Bendl, Jaroslav|Musil, Miloxc5xa1|xc5xa0touraxc4x8d, Jan|Zendulka, Jaroslav|Damborskxc3xbd, Jixc5x99xc3xad|Brezovskxc3xbd, Jan', 'Loschmidt Laboratories, Department of Experimental Biology and Research Centre for Toxic Compounds in the Environment RECETOX, Masaryk University, Brno, Czech Republic.|Loschmidt Laboratories, Department of Experimental Biology and Research Centre for Toxic Compounds in the Environment RECETOX, Masaryk University, Brno, Czech Republic.|Loschmidt Laboratories, Department of Experimental Biology and Research Centre for Toxic Compounds in the Environment RECETOX, Masaryk University, Brno, Czech Republic.|Department of Information Systems, Faculty of Information Technology, Brno University of Technology, Brno, Czech Republic.|Loschmidt Laboratories, Department of Experimental Biology and Research Centre for Toxic Compounds in the Environment RECETOX, Masaryk University, Brno, Czech Republic.|Loschmidt Laboratories, Department of Experimental Biology and Research Centre for Toxic Compounds in the Environment RECETOX, Masaryk University, Brno, Czech Republic.', '-|-|-|-|-|-', 64, 'Computational Biology|Databases, Nucleic Acid|Databases, Protein|Genetic Variation|Genome, Human|Genomics|Humans|Polymorphism, Single Nucleotide|Software', 'Journal Article', '10.1371/journal.pcbi.1004962', '27224906', 'An important message taken from human genome sequencing projects is that the human population exhibits approximately 99.9% genetic similarity. Variations in the remaining parts of the genome determine our identity, trace our history and reveal our heritage. The precise delineation of phenotypically causal variants plays a key role in providing accurate personalized diagnosis, prognosis, and treatment of inherited diseases. Several computational methods for achieving such delineation have been reported recently. However, their ability to pinpoint potentially deleterious variants is limited by the fact that their mechanisms of prediction do not account for the existence of different categories of variants. Consequently, their output is biased towards the variant categories that are most strongly represented in the variant databases. Moreover, most such methods provide numeric scores but not binary predictions of the deleteriousness of variants or confidence scores that would be more easily understood by users. We have constructed three datasets covering different types of disease-related variants, which were divided across five categories: (i) regulatory, (ii) splicing, (iii) missense, (iv) synonymous, and (v) nonsense variants. These datasets were used to develop category-optimal decision thresholds and to evaluate six tools for variant prioritization: CADD, DANN, FATHMM, FitCons, FunSeq2 and GWAVA. This evaluation revealed some important advantages of the category-based approach. The results obtained with the five best-performing tools were then combined into a consensus score. Additional comparative analyses showed that in the case of missense variations, protein-based predictors perform better than DNA sequence-based predictors. A user-friendly web interface was developed that provides easy access to the five tools predictions, and their consensus scores, in a user-understandable format tailored to the specific features of different categories of variations. To enable comprehensive evaluation of variants, the predictions are complemented with annotations from eight databases. The web server is freely available to the community at http://loschmidt.chemi.muni.cz/predictsnp2.'),
(87847, 2016, 'plos', 'Control of Ca2+ Influx and Calmodulin Activation by SK-Channels in Dendritic Spines', 'Griffith, Thom|Tsaneva-Atanasova, Krasimira|Mellor, Jack R', 'Department of Engineering Mathematics, University of Bristol, Bristol, United Kingdom.|Department of Mathematics, College of Engineering, Mathematics and Physical Sciences, University of Exeter, Exeter, United Kingdom.|Centre for Synaptic Plasticity, School of Physiology, Pharmacology and Neuroscience, University of Bristol, Bristol, United Kingdom.', 'United Kingdom|United Kingdom|United Kingdom', 11, 'Animals|Calcium Channels, L-Type|Calcium Signaling|Calmodulin|Computational Biology|Dendritic Spines|Excitatory Postsynaptic Potentials|Imaging, Three-Dimensional|Long-Term Potentiation|Long-Term Synaptic Depression|Models, Neurological|Neuronal Plasticity|Receptors, N-Methyl-D-Aspartate|Small-Conductance Calcium-Activated Potassium Channels', 'Journal Article', '10.1371/journal.pcbi.1004949', '27232631', 'The key trigger for Hebbian synaptic plasticity is influx of Ca2+ into postsynaptic dendritic spines. The magnitude of [Ca2+] increase caused by NMDA-receptor (NMDAR) and voltage-gated Ca2+ -channel (VGCC) activation is thought to determine both the amplitude and direction of synaptic plasticity by differential activation of Ca2+ -sensitive enzymes such as calmodulin. Ca2+ influx is negatively regulated by Ca2+ -activated K+ channels (SK-channels) which are in turn inhibited by neuromodulators such as acetylcholine. However, the precise mechanisms by which SK-channels control the induction of synaptic plasticity remain unclear. Using a 3-dimensional model of Ca2+ and calmodulin dynamics within an idealised, but biophysically-plausible, dendritic spine, we show that SK-channels regulate calmodulin activation specifically during neuron-firing patterns associated with induction of spike timing-dependent plasticity. SK-channel activation and the subsequent reduction in Ca2+ influx through NMDARs and L-type VGCCs results in an order of magnitude decrease in calmodulin (CaM) activation, providing a mechanism for the effective gating of synaptic plasticity induction. This provides a common mechanism for the regulation of synaptic plasticity by neuromodulators.'),
(87848, 2016, 'plos', 'Validated Predictions of Metabolic Energy Consumption for Submaximal Effort Movement', 'Tsianos, George A|MacFadden, Lisa N', 'L-3 Applied Technologies, Inc., HEM Division, San Diego, California, United States of America.|L-3 Applied Technologies, Inc., HEM Division, San Diego, California, United States of America.', 'United States|United States', 2, 'Algorithms|Biomechanical Phenomena|Computational Biology|Computer Simulation|Energy Metabolism|Humans|Knee Joint|Models, Biological|Movement|Muscle Contraction|Muscle, Skeletal|Oxygen Consumption', 'Journal Article', '10.1371/journal.pcbi.1004911', '27248429', 'Physical performance emerges from complex interactions among many physiological systems that are largely driven by the metabolic energy demanded. Quantifying metabolic demand is an essential step for revealing the many mechanisms of physical performance decrement, but accurate predictive models do not exist. The goal of this study was to investigate if a recently developed model of muscle energetics and force could be extended to reproduce the kinematics, kinetics, and metabolic demand of submaximal effort movement. Upright dynamic knee extension against various levels of ergometer load was simulated. Task energetics were estimated by combining the model of muscle contraction with validated models of lower limb musculotendon paths and segment dynamics. A genetic algorithm was used to compute the muscle excitations that reproduced the movement with the lowest energetic cost, which was determined to be an appropriate criterion for this task. Model predictions of oxygen uptake rate (VO2) were well within experimental variability for the range over which the model parameters were confidently known. The models accurate estimates of metabolic demand make it useful for assessing the likelihood and severity of physical performance decrement for a given task as well as investigating underlying physiologic mechanisms.');
