INSERT INTO `papers` (`id`, `ano`, `journal`, `titulo`, `autores`, `afiliacao`, `pais`, `citacoes`, `palavra_chave`, `categorias`, `doi`, `pubmed`, `abstract`) VALUES
(87153, 2015, 'plos', 'An Exclusion Zone for Ca2+ Channels around Docked Vesicles Explains Release Control by Multiple Channels at a CNS Synapse', 'Keller, Daniel|Babai, Norbert|Kochubey, Olexiy|Han, Yunyun|Markram, Henry|Schürmann, Felix|Schneggenburger, Ralf', 'Blue Brain Project, École Polytechnique Fédérale de Lausanne (EPFL), Lausanne, Switzerland.|Laboratory of Synaptic Mechanisms, Brain Mind Institute, École Polytechnique Fédérale de Lausanne (EPFL), Lausanne, Switzerland.|Laboratory of Synaptic Mechanisms, Brain Mind Institute, École Polytechnique Fédérale de Lausanne (EPFL), Lausanne, Switzerland.|Laboratory of Synaptic Mechanisms, Brain Mind Institute, École Polytechnique Fédérale de Lausanne (EPFL), Lausanne, Switzerland.|Blue Brain Project, École Polytechnique Fédérale de Lausanne (EPFL), Lausanne, Switzerland.|Blue Brain Project, École Polytechnique Fédérale de Lausanne (EPFL), Lausanne, Switzerland.|Laboratory of Synaptic Mechanisms, Brain Mind Institute, École Polytechnique Fédérale de Lausanne (EPFL), Lausanne, Switzerland.', 'Switzerland|Switzerland|Switzerland|Switzerland|Switzerland|Switzerland|Switzerland', 0, 'Animals|Calcium Channels|Calcium Chelating Agents|Computational Biology|Computer Simulation|Egtazic Acid|In Vitro Techniques|Kinetics|Mice|Mice, Inbred C57BL|Models, Neurological|Stochastic Processes|Synapses|Synaptic Vesicles|Trapezoid Body', 'Journal Article', '10.1371/journal.pcbi.1004253', '25951120', 'The spatial arrangement of Ca2+ channels and vesicles remains unknown for most CNS synapses, despite of the crucial importance of this geometrical parameter for the Ca2+ control of transmitter release. At a large model synapse, the calyx of Held, transmitter release is controlled by several Ca2+ channels in a domain overlap mode, at least in young animals. To study the geometrical constraints of Ca2+ channel placement in domain overlap control of release, we used stochastic MCell modelling, at active zones for which the position of docked vesicles was derived from electron microscopy (EM). We found that random placement of Ca2+ channels was unable to produce high slope values between release and presynaptic Ca2+ entry, a hallmark of domain overlap, and yielded excessively large release probabilities. The simple assumption that Ca2+ channels can be located anywhere at active zones, except below a critical distance of ~ 30 nm away from docked vesicles (exclusion zone), rescued high slope values and low release probabilities. Alternatively, high slope values can also be obtained by placing all Ca2+ channels into a single supercluster, which however results in significantly higher heterogeneity of release probabilities. We also show experimentally that high slope values, and the sensitivity to the slow Ca2+ chelator EGTA-AM, are maintained with developmental maturation of the calyx synapse. Taken together, domain overlap control of release represents a highly organized active zone architecture in which Ca2+ channels must obey a certain distance to docked vesicles. Furthermore, domain overlap can be employed by near-mature, fast-releasing synapses. '),
(87154, 2015, 'plos', 'Power Law Scaling in Human and Empty Room MEG Recordings', 'Kitzbichler, Manfred G|Bullmore, Edward T', 'Behavioural & Clinical Neuroscience Institute, University of Cambridge, Cambridge, United Kingdom.|Behavioural & Clinical Neuroscience Institute, University of Cambridge, Cambridge, United Kingdom.', 'United Kingdom|United Kingdom', 0, 'Action Potentials|Animals|Biological Clocks|Brain|Cortical Synchronization|Humans|Models, Neurological|Nerve Net|Synaptic Transmission', 'Journal Article', '10.1371/journal.pcbi.1004175', '25954803', '-'),
(87155, 2015, 'plos', 'Modelling the Effects of Electrical Coupling between Unmyelinated Axons of Brainstem Neurons Controlling Rhythmic Activity', 'Hull, Michael J|Soffe, Stephen R|Willshaw, David J|Roberts, Alan', 'Institute for Adaptive and Neural Computation, University of Edinburgh, Edinburgh, United Kingdom, School of Biological Sciences, University of Bristol, Bristol, United Kingdom.|School of Biological Sciences, University of Bristol, Bristol, United Kingdom.|Institute for Adaptive and Neural Computation, University of Edinburgh, Edinburgh, United Kingdom.|School of Biological Sciences, University of Bristol, Bristol, United Kingdom.', 'United Kingdom|United Kingdom|United Kingdom|United Kingdom', 11, 'Action Potentials|Animals|Axons|Brain Stem|Computational Biology|Electrophysiological Phenomena|Gap Junctions|Larva|Models, Neurological|Nerve Fibers, Unmyelinated|Patch-Clamp Techniques|Swimming|Xenopus laevis', 'Journal Article', '10.1371/journal.pcbi.1004240', '25954930', 'Gap junctions between fine unmyelinated axons can electrically couple groups of brain neurons to synchronise xefxacx81ring and contribute to rhythmic activity. To explore the distribution and significance of electrical coupling, we modelled a well analysed, small population of brainstem neurons which drive swimming in young frog tadpoles. A passive network of 30 multicompartmental neurons with unmyelinated axons was used to infer that: axon-axon gap junctions close to the soma gave the best match to experimentally measured coupling coefxefxacx81cients, axon diameter had a strong inxefxacx82uence on coupling, most neurons were coupled indirectly via the axons of other neurons. When active channels were added, gap junctions could make action potential propagation along the thin axons unreliable. Increased sodium and decreased potassium channel densities in the initial axon segment improved action potential propagation. Modelling suggested that the single spike xefxacx81ring to step current injection observed in whole-cell recordings is not a cellular property but a dynamic consequence of shunting resulting from electrical coupling. Without electrical coupling, firing of the population during depolarising current was unsynchronised, with coupling, the population showed synchronous recruitment and rhythmic firing. When activated instead by increasing levels of modelled sensory pathway input, the population without electrical coupling was recruited incrementally to unpatterned activity. However, when coupled, the population was recruited all-or-none at threshold into a rhythmic swimming pattern: the tadpole decided to swim. Modelling emphasises uncertainties about fine unmyelinated axon physiology but, when informed by biological data, makes general predictions about gap junctions: locations close to the soma, relatively small numbers, many indirect connections between neurons, cause of action potential propagation failure in fine axons, misleading alteration of intrinsic firing properties. Modelling also indicates that electrical coupling within a population can synchronize recruitment of neurons and their pacemaker firing during rhythmic activity. '),
(87156, 2015, 'plos', 'Memory storage fidelity in the hippocampal circuit: the role of subregions and input statistics', 'Neher, Torsten|Cheng, Sen|Wiskott, Laurenz', 'International Graduate School Neuroscience, Ruhr-University Bochum, Bochum, Germany, Institute for Neural Computation, Ruhr-University Bochum, Bochum, Germany.|International Graduate School Neuroscience, Ruhr-University Bochum, Bochum, Germany, Mercator Research Group Structure of Memory, Department of Psychology, Ruhr-University Bochum, Bochum, Germany.|International Graduate School Neuroscience, Ruhr-University Bochum, Bochum, Germany, Institute for Neural Computation, Ruhr-University Bochum, Bochum, Germany.', 'Germany|Germany|Germany', 13, 'Animals|CA1 Region, Hippocampal|CA3 Region, Hippocampal|Computational Biology|Dentate Gyrus|Entorhinal Cortex|Hippocampus|Humans|Learning|Memory|Mental Recall|Models, Neurological|Models, Psychological', 'Comparative Study', '10.1371/journal.pcbi.1004250', '25954996', 'In the last decades a standard model regarding the function of the hippocampus in memory formation has been established and tested computationally. It has been argued that the CA3 region works as an auto-associative memory and that its recurrent fibers are the actual storing place of the memories. Furthermore, to work properly CA3 requires memory patterns that are mutually uncorrelated. It has been suggested that the dentate gyrus orthogonalizes the patterns before storage, a process known as pattern separation. In this study we review the model when random input patterns are presented for storage and investigate whether it is capable of storing patterns of more realistic entorhinal grid cell input. Surprisingly, we find that an auto-associative CA3 net is redundant for random inputs up to moderate noise levels and is only beneficial at high noise levels. When grid cell input is presented, auto-association is even harmful for memory performance at all levels. Furthermore, we find that Hebbian learning in the dentate gyrus does not support its function as a pattern separator. These findings challenge the standard framework and support an alternative view where the simpler EC-CA1-EC network is sufficient for memory storage. '),
(87157, 2015, 'plos', 'Understanding Voltage Gating of Providencia stuartii Porins at Atomic Level', 'Song, Wanling|Bajaj, Harsha|Nasrallah, Chady|Jiang, Hualiang|Winterhalter, Mathias|Colletier, Jacques-Philippe|Xu, Yechun', 'CAS Key Laboratory of Receptor Research, Drug Discovery and Design Centre, Shanghai Institute of Materia Medica, Chinese Academy of Sciences (CAS), Shanghai, China.|School of Engineering and Sciences, Jacobs University Bremen, Bremen, Germany.|University Grenoble Alpes, Institut de Biologie Structurale (IBS), Grenoble, France, CNRS, Institut de Biologie Structurale (IBS), Grenoble, France, CEA, Institut de Biologie Structurale (IBS), Grenoble, France.|CAS Key Laboratory of Receptor Research, Drug Discovery and Design Centre, Shanghai Institute of Materia Medica, Chinese Academy of Sciences (CAS), Shanghai, China.|School of Engineering and Sciences, Jacobs University Bremen, Bremen, Germany.|University Grenoble Alpes, Institut de Biologie Structurale (IBS), Grenoble, France, CNRS, Institut de Biologie Structurale (IBS), Grenoble, France, CEA, Institut de Biologie Structurale (IBS), Grenoble, France.|CAS Key Laboratory of Receptor Research, Drug Discovery and Design Centre, Shanghai Institute of Materia Medica, Chinese Academy of Sciences (CAS), Shanghai, China.', 'China|Germany|France|China|Germany|France|China', 6, 'Bacterial Outer Membrane Proteins|Bacterial Proteins|Binding Sites|Computational Biology|Computer Simulation|Hydrogen Bonding|Ion Channel Gating|Models, Biological|Models, Molecular|Molecular Dynamics Simulation|Porins|Providencia|Static Electricity', 'Journal Article', '10.1371/journal.pcbi.1004255', '25955156', 'Bacterial porins are water-filled xcexb2-barrel channels that allow translocation of solutes across the outer membrane. They feature a constriction zone, contributed by the plunging of extracellular loop 3 (L3) into the channel lumen. Porins are generally in the open state, but undergo gating in response to external voltages. To date the underlying mechanism is unclear. Here we report results from molecular dynamics simulations on the two porins of Providenica stuartii, Omp-Pst1 and Omp-Pst2, which display distinct voltage sensitivities. Voltage gating was observed in Omp-Pst2, where the binding of cations in-between L3 and the barrel wall results in exposing a conserved aromatic residue in the channel lumen, thereby halting ion permeation. Comparison of Omp-Pst1 and Omp-Pst2 structures and trajectories suggests that their sensitivity to voltage is encoded in the hydrogen-bonding network anchoring L3 onto the barrel wall, as we observed that it is the strength of this network that governs the probability of cations binding behind L3. That Omp-Pst2 gating is observed only when ions flow against the electrostatic potential gradient of the channel furthermore suggests a possible role for this porin in the regulation of charge distribution across the outer membrane and bacterial homeostasis. '),
(87158, 2015, 'plos', 'Structural Conversion of Axcexb217-42 Peptides from Disordered Oligomers to U-Shape Protofilaments via Multiple Kinetic Pathways', 'Cheon, Mookyung|Hall, Carol K|Chang, Iksoo', 'Center for Proteome Biophysics, Department of Brain & Cognitive Sciences, Daegu Gyeongbuk Institute of Science and Technology (DGIST), Daegu, Korea.|Department of Chemical and Biomolecular Engineering, North Carolina State University, Raleigh, North Carolina, United States of America.|Center for Proteome Biophysics, Department of Brain & Cognitive Sciences, Daegu Gyeongbuk Institute of Science and Technology (DGIST), Daegu, Korea.', '-|United States|-', 0, 'Algorithms|Alzheimer Disease|Amyloid beta-Peptides|Computational Biology|Computer Simulation|Humans|Hydrophobic and Hydrophilic Interactions|Kinetics|Molecular Dynamics Simulation|Peptide Fragments|Protein Folding|Protein Structure, Secondary|Protein Structure, Tertiary|Software|Temperature', 'Journal Article', '10.1371/journal.pcbi.1004258', '25955249', 'Discovering the mechanisms by which proteins aggregate into fibrils is an essential first step in understanding the molecular level processes underlying neurodegenerative diseases such as Alzheimers and Parkinsons. The goal of this work is to provide insights into the structural changes that characterize the kinetic pathways by which amyloid-xcexb2 peptides convert from monomers to oligomers to fibrils. By applying discontinuous molecular dynamics simulations to PRIME20, a force field designed to capture the chemical and physical aspects of protein aggregation, we have been able to trace out the entire aggregation process for a system containing 8 Axcexb217-42 peptides. We uncovered two fibrillization mechanisms that govern the structural conversion of Axcexb217-42 peptides from disordered oligomers into protofilaments. The first mechanism is monomeric conversion templated by a U-shape oligomeric nucleus into U-shape protofilament. The second mechanism involves a long-lived and on-pathway metastable oligomer with S-shape chains, having a C-terminal turn, en route to the final U-shape protofilament. Oligomers with this C-terminal turn have been regarded in recent experiments as a major contributing element to cell toxicity in Alzheimers disease. The internal structures of the U-shape protofilaments from our PRIME20/DMD simulation agree well with those from solid state NMR experiments. The approach presented here offers a simple molecular-level framework to describe protein aggregation in general and to visualize the kinetic evolution of a putative toxic element in Alzheimers disease in particular. '),
(87159, 2015, 'plos', 'Extensive decoupling of metabolic genes in cancer', 'Reznik, Ed|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.', 'United States|United States', 0, 'Breast Neoplasms|Carcinoma, Renal Cell|Cell Transformation, Neoplastic|Computational Biology|Electron Transport|Female|Gene Expression Profiling|Genes, Mitochondrial|Humans|Kidney Neoplasms|Metabolic Networks and Pathways|Models, Biological|Multigene Family|Neoplasms', 'Journal Article', '10.1371/journal.pcbi.1004176', '25961905', 'Tumorigenesis requires the re-organization of metabolism to support malignant proliferation. We examine how the altered metabolism of cancer cells is reflected in the rewiring of co-expression patterns among metabolic genes. Focusing on breast and clear-cell kidney tumors, we report the existence of key metabolic genes which act as hubs of differential co-expression, showing significantly different co-regulation patterns between normal and tumor states. We compare our findings to those from classical differential expression analysis, and counterintuitively observe that the extent of a genes differential co-expression only weakly correlates with its differential expression, suggesting that the two measures probe different features of metabolism. Focusing on this discrepancy, we use changes in co-expression patterns to highlight the apparent loss of regulation by the transcription factor HNF4A in clear cell renal cell carcinoma, despite no differential expression of HNF4A. Finally, we aggregate the results of differential co-expression analysis into a Pan-Cancer analysis across seven distinct cancer types to identify pairs of metabolic genes which may be recurrently dysregulated. Among our results is a cluster of four genes, all components of the mitochondrial electron transport chain, which show significant loss of co-expression in tumor tissue, pointing to potential mitochondrial dysfunction in these tumor types. '),
(87160, 2015, 'plos', 'Hi-C Chromatin Interaction Networks Predict Co-expression in the Mouse Cortex', 'Babaei, Sepideh|Mahfouz, Ahmed|Hulsman, Marc|Lelieveldt, Boudewijn P F|de Ridder, Jeroen|Reinders, Marcel', 'Delft Bioinformatics Lab, Delft University of Technology, Delft, The Netherlands.|Delft Bioinformatics Lab, Delft University of Technology, Delft, The Netherlands, Division of Image Processing, Department of Radiology, Leiden University Medical Center, Leiden, The Netherlands.|Delft Bioinformatics Lab, Delft University of Technology, Delft, The Netherlands, Department of Clinical Genetics, VU University Medical Center, Amsterdam, The Netherlands.|Division of Image Processing, Department of Radiology, Leiden University Medical Center, Leiden, The Netherlands, Department of Intelligent Systems, Delft University of Technology, Delft, The Netherlands.|Delft Bioinformatics Lab, Delft University of Technology, Delft, The Netherlands.|Delft Bioinformatics Lab, Delft University of Technology, Delft, The Netherlands.', 'Netherlands|Netherlands|Netherlands|Netherlands|Netherlands|Netherlands', 20, 'Animals|Cell Nucleus|Cerebral Cortex|Chromatin|Chromosomes|Gene Expression Regulation|Genome|Male|Mice|Mice, Inbred C57BL|Models, Genetic|Structure-Activity Relationship', 'Journal Article', '10.1371/journal.pcbi.1004221', '25965262', 'The three dimensional conformation of the genome in the cell nucleus influences important biological processes such as gene expression regulation. Recent studies have shown a strong correlation between chromatin interactions and gene co-expression. However, predicting gene co-expression from frequent long-range chromatin interactions remains challenging. We address this by characterizing the topology of the cortical chromatin interaction network using scale-aware topological measures. We demonstrate that based on these characterizations it is possible to accurately predict spatial co-expression between genes in the mouse cortex. Consistent with previous findings, we find that the chromatin interaction profile of a gene-pair is a good predictor of their spatial co-expression. However, the accuracy of the prediction can be substantially improved when chromatin interactions are described using scale-aware topological measures of the multi-resolution chromatin interaction network. We conclude that, for co-expression prediction, it is necessary to take into account different levels of chromatin interactions ranging from direct interaction between genes (i.e. small-scale) to chromatin compartment interactions (i.e. large-scale). '),
(87161, 2015, 'plos', 'Convex clustering: an attractive alternative to hierarchical clustering', 'Chen, Gary K|Chi, Eric C|Ranola, John Michael O|Lange, Kenneth', 'Department of Preventive Medicine ,Biostatistics Division, University of Southern California, Los Angeles, California, United States of America.|Department of Electrical and Computer Engineering, Rice University, Houston, Texas, United States of America.|Department of Statistics, University of Washington, Seattle, Washington, United States of America.|Department of Biomathematics, University of California, Los Angeles, Los Angeles, California, United States of America, Department of Human Genetics, University of California, Los Angeles, Los Angeles, California, United States of America, Department of Statistics, University of California, Los Angeles, Los Angeles, California, United States of America.', 'United States|United States|United States|United States', 0, 'Algorithms|Cluster Analysis|Computational Biology|Databases, Genetic|Gene Expression Profiling|Humans|Pattern Recognition, Automated|Software', 'Journal Article', '10.1371/journal.pcbi.1004228', '25965340', 'The primary goal in cluster analysis is to discover natural groupings of objects. The field of cluster analysis is crowded with diverse methods that make special assumptions about data and address different scientific aims. Despite its shortcomings in accuracy, hierarchical clustering is the dominant clustering method in bioinformatics. Biologists find the trees constructed by hierarchical clustering visually appealing and in tune with their evolutionary perspective. Hierarchical clustering operates on multiple scales simultaneously. This is essential, for instance, in transcriptome data, where one may be interested in making qualitative inferences about how lower-order relationships like gene modules lead to higher-order relationships like pathways or biological processes. The recently developed method of convex clustering preserves the visual appeal of hierarchical clustering while ameliorating its propensity to make false inferences in the presence of outliers and noise. The solution paths generated by convex clustering reveal relationships between clusters that are hidden by static methods such as k-means clustering. The current paper derives and tests a novel proximal distance algorithm for minimizing the objective function of convex clustering. The algorithm separates parameters, accommodates missing data, and supports prior information on relationships. Our program CONVEXCLUSTER incorporating the algorithm is implemented on ATI and nVidia graphics processing units (GPUs) for maximal speed. Several biological examples illustrate the strengths of convex clustering and the ability of the proximal distance algorithm to handle high-dimensional problems. CONVEXCLUSTER can be freely downloaded from the UCLA Human Genetics web site at http://www.genetics.ucla.edu/software/. '),
(87162, 2015, 'plos', 'Optimal census by quorum sensing', 'Taillefumier, Thibaud|Wingreen, Ned S', 'Lewis-Sigler Institute for Integrative Genomics, Princeton University, Princeton, New Jersey, United States of America.|Lewis-Sigler Institute for Integrative Genomics, Princeton University, Princeton, New Jersey, United States of America, Department of Molecular Biology, Princeton University, Princeton, New Jersey, United States of America.', 'Jersey|Jersey', 12, 'Bacterial Physiological Phenomena|Censuses|Gene Expression Regulation, Bacterial|Information Theory|Models, Biological|Quorum Sensing', 'Journal Article', '10.1371/journal.pcbi.1004238', '25965377', 'Quorum sensing is the regulation of gene expression in response to changes in cell density. To measure their cell density, bacterial populations produce and detect diffusible molecules called autoinducers. Individual bacteria internally represent the external concentration of autoinducers via the level of monitor proteins. In turn, these monitor proteins typically regulate both their own production and the production of autoinducers, thereby establishing internal and external feedbacks. Here, we ask whether feedbacks can increase the information available to cells about their local density. We quantify available information as the mutual information between the abundance of a monitor protein and the local cell density for biologically relevant models of quorum sensing. Using variational methods, we demonstrate that feedbacks can increase information transmission, allowing bacteria to resolve up to two additional ranges of cell density when compared with bistable quorum-sensing systems. Our analysis is relevant to multi-agent systems that track an external driver implicitly via an endogenously generated signal. '),
(87163, 2015, 'plos', 'Computational modeling of seizure dynamics using coupled neuronal networks: factors shaping epileptiform activity', 'Naze, Sebastien|Bernard, Christophe|Jirsa, Viktor', 'UMR1106 Inserm, Institut de Neurosciences des Systèmes, Marseille, France, Aix-Marseille University, Marseille, France.|UMR1106 Inserm, Institut de Neurosciences des Systèmes, Marseille, France, Aix-Marseille University, Marseille, France.|UMR1106 Inserm, Institut de Neurosciences des Systèmes, Marseille, France, Aix-Marseille University, Marseille, France.', 'France|France|France', 27, 'Animals|Computer Simulation|Epilepsy|Male|Models, Neurological|Neurons|Rats|Rats, Wistar', 'Journal Article', '10.1371/journal.pcbi.1004209', '25970348', 'Epileptic seizure dynamics span multiple scales in space and time. Understanding seizure mechanisms requires identifying the relations between seizure components within and across these scales, together with the analysis of their dynamical repertoire. Mathematical models have been developed to reproduce seizure dynamics across scales ranging from the single neuron to the neural population. In this study, we develop a network model of spiking neurons and systematically investigate the conditions, under which the network displays the emergent dynamic behaviors known from the Epileptor, which is a well-investigated abstract model of epileptic neural activity. This approach allows us to study the biophysical parameters and variables leading to epileptiform discharges at cellular and network levels. Our network model is composed of two neuronal populations, characterized by fast excitatory bursting neurons and regular spiking inhibitory neurons, embedded in a common extracellular environment represented by a slow variable. By systematically analyzing the parameter landscape offered by the simulation framework, we reproduce typical sequences of neural activity observed during status epilepticus. We find that exogenous fluctuations from extracellular environment and electro-tonic couplings play a major role in the progression of the seizure, which supports previous studies and further validates our model. We also investigate the influence of chemical synaptic coupling in the generation of spontaneous seizure-like events. Our results argue towards a temporal shift of typical spike waves with fast discharges as synaptic strengths are varied. We demonstrate that spike waves, including interictal spikes, are generated primarily by inhibitory neurons, whereas fast discharges during the wave part are due to excitatory neurons. Simulated traces are compared with in vivo experimental data from rodents at different stages of the disorder. We draw the conclusion that slow variations of global excitability, due to exogenous fluctuations from extracellular environment, and gap junction communication push the system into paroxysmal regimes. We discuss potential mechanisms underlying such machinery and the relevance of our approach, supporting previous detailed modeling studies and reflecting on the limitations of our methodology. '),
(87164, 2015, 'plos', 'Sharing and Specificity of Co-expression Networks across 35 Human Tissues', 'Pierson, Emma|GTEx Consortium|Koller, Daphne|Battle, Alexis|Mostafavi, Sara|Ardlie, Kristin G|Getz, Gad|Wright, Fred A|Kellis, Manolis|Volpi, Simona|Dermitzakis, Emmanouil T', 'Department of Computer Science, Stanford University, Stanford, California, United States of America.|Department of Computer Science, Stanford University, Stanford, California, United States of America.|Department of Computer Science, Stanford University, Stanford, California, United States of America.|Department of Computer Science, Stanford University, Stanford, California, United States of America.|Department of Computer Science, Stanford University, Stanford, California, United States of America.|Department of Computer Science, Stanford University, Stanford, California, United States of America.|Department of Computer Science, Stanford University, Stanford, California, United States of America.|Department of Computer Science, Stanford University, Stanford, California, United States of America.|Department of Computer Science, Stanford University, Stanford, California, United States of America.|Department of Computer Science, Stanford University, Stanford, California, United States of America.|Department of Computer Science, Stanford University, Stanford, California, United States of America.', 'United States|United States|United States|United States|United States|United States|United States|Un', 65, 'Algorithms|Base Sequence|Gene Expression Regulation|Gene Regulatory Networks|Humans|Models, Genetic|Organ Specificity', 'Journal Article', '10.1371/journal.pcbi.1004220', '25970446', 'To understand the regulation of tissue-specific gene expression, the GTEx Consortium generated RNA-seq expression data for more than thirty distinct human tissues. This data provides an opportunity for deriving shared and tissue specific gene regulatory networks on the basis of co-expression between genes. However, a small number of samples are available for a majority of the tissues, and therefore statistical inference of networks in this setting is highly underpowered. To address this problem, we infer tissue-specific gene co-expression networks for 35 tissues in the GTEx dataset using a novel algorithm, GNAT, that uses a hierarchy of tissues to share data between related tissues. We show that this transfer learning approach increases the accuracy with which networks are learned. Analysis of these networks reveals that tissue-specific transcription factors are hubs that preferentially connect to genes with tissue specific functions. Additionally, we observe that genes with tissue-specific functions lie at the peripheries of our networks. We identify numerous modules enriched for Gene Ontology functions, and show that modules conserved across tissues are especially likely to have functions common to all tissues, while modules that are upregulated in a particular tissue are often instrumental to tissue-specific function. Finally, we provide a web tool, available at mostafavilab.stat.ubc.ca/GNAT, which allows exploration of gene function and regulation in a tissue-specific manner. '),
(87165, 2015, 'plos', 'Mechanisms of left-right coordination in mammalian locomotor pattern generation circuits: a mathematical modeling view', 'Molkov, Yaroslav I|Bacak, Bartholomew J|Talpalar, Adolfo E|Rybak, Ilya A', 'Department of Mathematical Sciences, Indiana University-Purdue University, Indianapolis, Indiana, United States of America.|Department of Neurobiology and Anatomy, Drexel University College of Medicine, Philadelphia, Pennsylvania, United States of America.|Department of Neuroscience, Karolinska Institute, Stockholm, Sweden.|Department of Neurobiology and Anatomy, Drexel University College of Medicine, Philadelphia, Pennsylvania, United States of America.', 'India|United States|Sweden|United States', 0, 'Algorithms|Animals|Computer Simulation|Gait|Interneurons|Locomotion|Mice|Mice, Knockout|Models, Statistical|Motor Activity|N-Methylaspartate|Neurons|Pattern Recognition, Automated|Spinal Cord', 'Journal Article', '10.1371/journal.pcbi.1004270', '25970489', 'The locomotor gait in limbed animals is defined by the left-right leg coordination and locomotor speed. Coordination between left and right neural activities in the spinal cord controlling left and right legs is provided by commissural interneurons (CINs). Several CIN types have been genetically identified, including the excitatory V3 and excitatory and inhibitory V0 types. Recent studies demonstrated that genetic elimination of all V0 CINs caused switching from a normal left-right alternating activity to a left-right synchronized hopping pattern. Furthermore, ablation of only the inhibitory V0 CINs (V0D subtype) resulted in a lack of left-right alternation at low locomotor frequencies and retaining this alternation at high frequencies, whereas selective ablation of the excitatory V0 neurons (V0V subtype) maintained the left-right alternation at low frequencies and switched to a hopping pattern at high frequencies. To analyze these findings, we developed a simplified mathematical model of neural circuits consisting of four pacemaker neurons representing left and right, flexor and extensor rhythm-generating centers interacting via commissural pathways representing V3, V0D, and V0V CINs. The locomotor frequency was controlled by a parameter defining the excitation of neurons and commissural pathways mimicking the effects of N-methyl-D-aspartate on locomotor frequency in isolated rodent spinal cord preparations. The model demonstrated a typical left-right alternating pattern under control conditions, switching to a hopping activity at any frequency after removing both V0 connections, a synchronized pattern at low frequencies with alternation at high frequencies after removing only V0D connections, and an alternating pattern at low frequencies with hopping at high frequencies after removing only V0V connections. We used bifurcation theory and fast-slow decomposition methods to analyze network behavior in the above regimes and transitions between them. The model reproduced, and suggested explanation for, a series of experimental phenomena and generated predictions available for experimental testing. '),
(87166, 2015, 'plos', 'The Effect of Incentives and Meta-incentives on the Evolution of Cooperation', 'Okada, Isamu|Yamamoto, Hitoshi|Toriumi, Fujio|Sasaki, Tatsuya', 'Department of Business Administration, Soka University, Tokyo, Japan, Department of Information Systems and Operations, Vienna University of Economics and Business, Vienna, Austria.|Department of Business Administration, Rissho University, Tokyo, Japan.|Department of Systems Innovations, University of Tokyo, Tokyo, Japan.|Faculty of Mathematics, University of Vienna, Vienna, Austria.', 'Austria|Japan|Japan|Austria', 16, 'Cooperative Behavior|Cultural Evolution|Game Theory|Models, Theoretical|Motivation|Reward', 'Journal Article', '10.1371/journal.pcbi.1004232', '25974684', 'Although positive incentives for cooperators and/or negative incentives for free-riders in social dilemmas play an important role in maintaining cooperation, there is still the outstanding issue of who should pay the cost of incentives. The second-order free-rider problem, in which players who do not provide the incentives dominate in a game, is a well-known academic challenge. In order to meet this challenge, we devise and analyze a meta-incentive game that integrates positive incentives (rewards) and negative incentives (punishments) with second-order incentives, which are incentives for other players incentives. The critical assumption of our model is that players who tend to provide incentives to other players for their cooperative or non-cooperative behavior also tend to provide incentives to their incentive behaviors. In this paper, we solve the replicator dynamics for a simple version of the game and analytically categorize the game types into four groups. We find that the second-order free-rider problem is completely resolved without any third-order or higher (meta) incentive under the assumption. To do so, a second-order costly incentive, which is given individually (peer-to-peer) after playing donation games, is needed. The paper concludes that (1) second-order incentives for first-order reward are necessary for cooperative regimes, (2) a system without first-order rewards cannot maintain a cooperative regime, (3) a system with first-order rewards and no incentives for rewards is the worst because it never reaches cooperation, and (4) a system with rewards for incentives is more likely to be a cooperative regime than a system with punishments for incentives when the cost-effect ratio of incentives is sufficiently large. This solution is general and strong in the sense that the game does not need any centralized institution or proactive system for incentives. '),
(87167, 2015, 'plos', 'Forecasting the 2013-2014 influenza season using Wikipedia', 'Hickmann, Kyle S|Fairchild, Geoffrey|Priedhorsky, Reid|Generous, Nicholas|Hyman, James M|Deshpande, Alina|Del Valle, Sara Y', 'Theoretical Division Los Alamos National Laboratory, Los Alamos, New Mexico, United States of America.|Defense Systems Analysis Division Los Alamos National Laboratory, Los Alamos, New Mexico, United States of America.|High Performance Computing Division Los Alamos National Laboratory, Los Alamos, New Mexico, United States of America.|Defense Systems Analysis Division Los Alamos National Laboratory, Los Alamos, New Mexico, United States of America.|Department of Mathematics, Tulane University, New Orleans, Louisiana, United States of America.|Defense Systems Analysis Division Los Alamos National Laboratory, Los Alamos, New Mexico, United States of America.|Defense Systems Analysis Division Los Alamos National Laboratory, Los Alamos, New Mexico, United States of America.', 'Mexico|Mexico|Mexico|Mexico|United States|Mexico|Mexico', 66, 'Centers for Disease Control and Prevention (U.S.)|Computational Biology|Epidemiological Monitoring|Forecasting|History, 21st Century|Humans|Influenza, Human|Internet|Models, Statistical|Seasons|United States', 'Evaluation Studies', '10.1371/journal.pcbi.1004239', '25974758', 'Infectious diseases are one of the leading causes of morbidity and mortality around the world, thus, forecasting their impact is crucial for planning an effective response strategy. According to the Centers for Disease Control and Prevention (CDC), seasonal influenza affects 5% to 20% of the U.S. population and causes major economic impacts resulting from hospitalization and absenteeism. Understanding influenza dynamics and forecasting its impact is fundamental for developing prevention and mitigation strategies. We combine modern data assimilation methods with Wikipedia access logs and CDC influenza-like illness (ILI) reports to create a weekly forecast for seasonal influenza. The methods are applied to the 2013-2014 influenza season but are sufficiently general to forecast any disease outbreak, given incidence or case count data. We adjust the initialization and parametrization of a disease model and show that this allows us to determine systematic model bias. In addition, we provide a way to determine where the model diverges from observation and evaluate forecast accuracy. Wikipedia article access logs are shown to be highly correlated with historical ILI records and allow for accurate prediction of ILI data several weeks before it becomes available. The results show that prior to the peak of the flu season, our forecasting method produced 50% and 95% credible intervals for the 2013-2014 ILI observations that contained the actual observations for most weeks in the forecast. However, since our model does not account for re-infection or multiple strains of influenza, the tail of the epidemic is not predicted well after the peak of flu season has passed. '),
(87168, 2015, 'plos', 'Correction: GOBLET: The Global Organisation for Bioinformatics Learning, Education and Training', 'Attwood, Teresa K|Bongcam-Rudloff, Erik|Brazas, Michelle E|Corpas, Manuel|Gaudet, Pascale|Lewitter, Fran|Mulder, Nicola|Palagi, Patricia M|Schneider, Maria Victoria|van Gelder, Celia W G|GOBLET Consortium', 'Defense Systems Analysis Division Los Alamos National Laboratory, Los Alamos, New Mexico, United States of America.|Defense Systems Analysis Division Los Alamos National Laboratory, Los Alamos, New Mexico, United States of America.|Defense Systems Analysis Division Los Alamos National Laboratory, Los Alamos, New Mexico, United States of America.|Defense Systems Analysis Division Los Alamos National Laboratory, Los Alamos, New Mexico, United States of America.|Defense Systems Analysis Division Los Alamos National Laboratory, Los Alamos, New Mexico, United States of America.|Defense Systems Analysis Division Los Alamos National Laboratory, Los Alamos, New Mexico, United States of America.|Defense Systems Analysis Division Los Alamos National Laboratory, Los Alamos, New Mexico, United States of America.|Defense Systems Analysis Division Los Alamos National Laboratory, Los Alamos, New Mexico, United States of America.|Defense Systems Analysis Division Los Alamos National Laboratory, Los Alamos, New Mexico, United States of America.|Defense Systems Analysis Division Los Alamos National Laboratory, Los Alamos, New Mexico, United States of America.|Defense Systems Analysis Division Los Alamos National Laboratory, Los Alamos, New Mexico, United States of America.', 'Mexico|Mexico|Mexico|Mexico|Mexico|Mexico|Mexico|Mexico|Mexico|Mexico|Mexico', 3, '-', 'Published Erratum', '10.1371/journal.pcbi.1004281', '25974841', '-'),
(87169, 2015, 'plos', 'Distal spike initiation zone location estimation by morphological simulation of ionic current filtering demonstrated in a novel model of an identified Drosophila motoneuron', 'Gxc3xbcnay, Cengiz|Sieling, Fred H|Dharmar, Logesh|Lin, Wei-Hsiang|Wolfram, Verena|Marley, Richard|Baines, Richard A|Prinz, Astrid A', 'Department of Biology, Emory University, Atlanta, Georgia, United States of America.|Department of Biology, Emory University, Atlanta, Georgia, United States of America, Faculty of Life Sciences, University of Manchester, Manchester, United Kingdom.|Department of Biology, Emory University, Atlanta, Georgia, United States of America.|Department of Biomedical Engineering, Georgia Institute of Technology and Emory University, Atlanta, Georgia, United States.|Department of Biomedical Engineering, Georgia Institute of Technology and Emory University, Atlanta, Georgia, United States.|Department of Biomedical Engineering, Georgia Institute of Technology and Emory University, Atlanta, Georgia, United States.|Department of Biomedical Engineering, Georgia Institute of Technology and Emory University, Atlanta, Georgia, United States.|Department of Biology, Emory University, Atlanta, Georgia, United States of America.', 'Georgia|United Kingdom|Georgia|Georgia|Georgia|Georgia|Georgia|Georgia', 0, 'Action Potentials|Animals|Biophysical Phenomena|Computational Biology|Computer Simulation|Drosophila melanogaster|Electrophysiological Phenomena|Ion Channels|Models, Neurological|Motor Neurons|Patch-Clamp Techniques', 'Journal Article', '10.1371/journal.pcbi.1004189', '25978332', 'Studying ion channel currents generated distally from the recording site is difficult because of artifacts caused by poor space clamp and membrane filtering. A computational model can quantify artifact parameters for correction by simulating the currents only if their exact anatomical location is known. We propose that the same artifacts that confound current recordings can help pinpoint the source of those currents by providing a signature of the neurons morphology. This method can improve the recording quality of currents initiated at the spike initiation zone (SIZ) that are often distal to the soma in invertebrate neurons. Drosophila being a valuable tool for characterizing ion currents, we estimated the SIZ location and quantified artifacts in an identified motoneuron, aCC/MN1-Ib, by constructing a novel multicompartmental model. Initial simulation of the measured biophysical channel properties in an isopotential Hodgkin-Huxley type neuron model partially replicated firing characteristics. Adding a second distal compartment, which contained spike-generating Na+ and K+ currents, was sufficient to simulate aCCs in vivo activity signature. Matching this signature using a reconstructed morphology predicted that the SIZ is on aCCs primary axon, 70 xcexbcm after the most distal dendritic branching point. From SIZ to soma, we observed and quantified selective morphological filtering of fast activating currents. Non-inactivating K+ currents are filtered xe2x88xbc3 times less and despite their large magnitude at the soma they could be as distal as Na+ currents. The peak of transient component (NaT) of the voltage-activated Na+ current is also filtered more than the magnitude of slower persistent component (NaP), which can contribute to seizures. The corrected NaP/NaT ratio explains the previously observed discrepancy when the same channel is expressed in different cells. In summary, we used an in vivo signature to estimate ion channel location and recording artifacts, which can be applied to other neurons. '),
(87170, 2015, 'plos', 'Modelling circulating tumour cells for personalised survival prediction in metastatic breast cancer', 'Ascolani, Gianluca|Occhipinti, Annalisa|Liò, Pietro', 'University of Cambridge, Computer Laboratory, Cambridge, United Kingdom.|University of Cambridge, Computer Laboratory, Cambridge, United Kingdom.|University of Cambridge, Computer Laboratory, Cambridge, United Kingdom.', 'United Kingdom|United Kingdom|United Kingdom', 5, 'Biomarkers, Tumor|Breast Neoplasms|Carcinoma, Ductal, Breast|Computer Simulation|Disease Progression|Female|Gene Expression Profiling|Humans|Kaplan-Meier Estimate|Models, Biological|Neoplastic Cells, Circulating|Survival Rate|Transforming Growth Factor beta', 'Journal Article', '10.1371/journal.pcbi.1004199', '25978366', 'Ductal carcinoma is one of the most common cancers among women, and the main cause of death is the formation of metastases. The development of metastases is caused by cancer cells that migrate from the primary tumour site (the mammary duct) through the blood vessels and extravasating they initiate metastasis. Here, we propose a multi-compartment model which mimics the dynamics of tumoural cells in the mammary duct, in the circulatory system and in the bone. Through a branching process model, we describe the relation between the survival times and the four markers mainly involved in metastatic breast cancer (EPCAM, CD47, CD44 and MET). In particular, the model takes into account the gene expression profile of circulating tumour cells to predict personalised survival probability. We also include the administration of drugs as bisphosphonates, which reduce the formation of circulating tumour cells and their survival in the blood vessels, in order to analyse the dynamic changes induced by the therapy. We analyse the effects of circulating tumour cells on the progression of the disease providing a quantitative measure of the cell driver mutations needed for invading the bone tissue. Our model allows to design intervention scenarios that alter the patient-specific survival probability by modifying the populations of circulating tumour cells and it could be extended to other cancer metastasis dynamics. '),
(87171, 2015, 'plos', 'Model-Free RNA Sequence and Structure Alignment Informed by SHAPE Probing Reveals a Conserved Alternate Secondary Structure for 16S rRNA', 'Lavender, Christopher A|Lorenz, Ronny|Zhang, Ge|Tamayo, Rita|Hofacker, Ivo L|Weeks, Kevin M', 'Department of Chemistry, University of North Carolina, Chapel Hill, Chapel Hill, North Carolina, United States of America.|Institute for Theoretical Chemistry, University of Vienna, Vienna, Austria, Bioinformatics Group, Department of Computer Science, University of Leipzig, Leipzig, Germany.|Department of Chemistry, University of North Carolina, Chapel Hill, Chapel Hill, North Carolina, United States of America.|Department of Microbiology and Immunology, University of North Carolina, Chapel Hill, Chapel Hill, North Carolina, United States of America.|Institute for Theoretical Chemistry, University of Vienna, Vienna, Austria, Bioinformatics and Computational Biology, University of Vienna, Vienna, Austria.|Department of Chemistry, University of North Carolina, Chapel Hill, Chapel Hill, North Carolina, United States of America.', 'United States|Austria|United States|United States|Austria|United States', 0, 'Base Sequence|Clostridium difficile|Computational Biology|Escherichia coli|Haloferax volcanii|High-Throughput Nucleotide Sequencing|Models, Molecular|Molecular Sequence Data|Nucleic Acid Conformation|RNA, Archaeal|RNA, Bacterial|RNA, Ribosomal, 16S|Sequence Alignment|Sequence Analysis, RNA', 'Journal Article', '10.1371/journal.pcbi.1004126', '25992778', 'Discovery and characterization of functional RNA structures remains challenging due to deficiencies in de novo secondary structure modeling. Here we describe a dynamic programming approach for model-free sequence comparison that incorporates high-throughput chemical probing data. Based on SHAPE probing data alone, ribosomal RNAs (rRNAs) from three diverse organisms--the eubacteria E. coli and C. difficile and the archeon H. volcanii--could be aligned with accuracies comparable to alignments based on actual sequence identity. When both base sequence identity and chemical probing reactivities were considered together, accuracies improved further. Derived sequence alignments and chemical probing data from protein-free RNAs were then used as pseudo-free energy constraints to model consensus secondary structures for the 16S and 23S rRNAs. There are critical differences between these experimentally-informed models and currently accepted models, including in the functionally important neck and decoding regions of the 16S rRNA. We infer that the 16S rRNA has evolved to undergo large-scale changes in base pairing as part of ribosome function. As high-quality RNA probing data become widely available, structurally-informed sequence alignment will become broadly useful for de novo motif and function discovery.');
INSERT INTO `papers` (`id`, `ano`, `journal`, `titulo`, `autores`, `afiliacao`, `pais`, `citacoes`, `palavra_chave`, `categorias`, `doi`, `pubmed`, `abstract`) VALUES
(87172, 2015, 'plos', 'Structure-Based Alignment and Consensus Secondary Structures for Three HIV-Related RNA Genomes', 'Lavender, Christopher A|Gorelick, Robert J|Weeks, Kevin M', 'Department of Chemistry, University of North Carolina, Chapel Hill, Chapel Hill, North Carolina, United States of America.|AIDS and Cancer Virus Program, Leidos Biomedical Research, Inc., Frederick National Laboratory for Cancer Research, Frederick, Maryland, United States of America.|Department of Chemistry, University of North Carolina, Chapel Hill, Chapel Hill, North Carolina, United States of America.', 'United States|United States|United States', 22, 'Animals|Base Sequence|Conserved Sequence|Genetic Structures|Genome, Viral|HIV-1|Molecular Sequence Data|Nucleic Acid Conformation|Nucleotide Motifs|RNA, Viral|Sequence Alignment|Structure-Activity Relationship', 'Journal Article', '10.1371/journal.pcbi.1004230', '25992893', 'HIV and related primate lentiviruses possess single-stranded RNA genomes. Multiple regions of these genomes participate in critical steps in the viral replication cycle, and the functions of many RNA elements are dependent on the formation of defined structures. The structures of these elements are still not fully understood, and additional functional elements likely exist that have not been identified. In this work, we compared three full-length HIV-related viral genomes: HIV-1NL4-3, SIVcpz, and SIVmac (the latter two strains are progenitors for all HIV-1 and HIV-2 strains, respectively). Model-free RNA structure comparisons were performed using whole-genome structure information experimentally derived from nucleotide-resolution SHAPE reactivities. Consensus secondary structures were constructed for strongly correlated regions by taking into account both SHAPE probing structural data and nucleotide covariation information from structure-based alignments. In these consensus models, all known functional RNA elements were recapitulated with high accuracy. In addition, we identified multiple previously unannotated structural elements in the HIV-1 genome likely to function in translation, splicing and other replication cycle processes, these are compelling targets for future functional analyses. The structure-informed alignment strategy developed here will be broadly useful for efficient RNA motif discovery. '),
(87173, 2015, 'plos', 'Metapopulation persistence in random fragmented landscapes', 'Grilli, Jacopo|Barabás, György|Allesina, Stefano', 'Department of Physics and Astronomy G. Galilei, Università di Padova, Padova, Italy.|Department of Ecology & Evolution, University of Chicago, Chicago, Illinois, United States of America.|Department of Ecology & Evolution, University of Chicago, Chicago, Illinois, United States of America, Computation Institute, University of Chicago, Chicago, Illinois, United States of America.', 'Italy|United States|United States', 0, 'Animals|Computational Biology|Ecosystem|Extinction, Biological|Humans|Markov Chains|Models, Biological|Population Density|Population Dynamics', 'Journal Article', '10.1371/journal.pcbi.1004251', '25993004', 'Habitat destruction and land use change are making the world in which natural populations live increasingly fragmented, often leading to local extinctions. Although local populations might undergo extinction, a metapopulation may still be viable as long as patches of suitable habitat are connected by dispersal, so that empty patches can be recolonized. Thus far, metapopulations models have either taken a mean-field approach, or have modeled empirically-based, realistic landscapes. Here we show that an intermediate level of complexity between these two extremes is to consider random landscapes, in which the patches of suitable habitat are randomly arranged in an area (or volume). Using methods borrowed from the mathematics of Random Geometric Graphs and Euclidean Random Matrices, we derive a simple, analytic criterion for the persistence of the metapopulation in random fragmented landscapes. Our results show how the density of patches, the variability in their value, the shape of the dispersal kernel, and the dimensionality of the landscape all contribute to determining the fate of the metapopulation. Using this framework, we derive sufficient conditions for the population to be spatially localized, such that spatially confined clusters of patches act as a source of dispersal for the whole landscape. Finally, we show that a regular arrangement of the patches is always detrimental for persistence, compared to the random arrangement of the patches. Given the strong parallel between metapopulation models and contact processes, our results are also applicable to models of disease spread on spatial networks. '),
(87174, 2015, 'plos', 'Regulators associated with clinical outcomes revealed by DNA methylation data in breast cancer', 'Ung, Matthew H|Varn, Frederick S|Lou, Shaoke|Cheng, Chao', 'Department of Genetics, Geisel School of Medicine at Dartmouth, Hanover, New Hampshire, United States of America.|Department of Genetics, Geisel School of Medicine at Dartmouth, Hanover, New Hampshire, United States of America.|Department of Genetics, Geisel School of Medicine at Dartmouth, Hanover, New Hampshire, United States of America.|Department of Genetics, Geisel School of Medicine at Dartmouth, Hanover, New Hampshire, United States of America, Institute for Quantitative Biomedical Sciences, Geisel School of Medicine at Dartmouth, Lebanon, New Hampshire, United States of America, Norris Cotton Cancer Center, Geisel School of Medicine at Dartmouth, Lebanon, New Hampshire, United States of America.', 'United States|United States|United States|Lebanon', 0, 'Amino Acid Motifs|Binding Sites|Breast Neoplasms|Cluster Analysis|CpG Islands|DNA Methylation|DNA, Neoplasm|Female|Gene Expression Profiling|Gene Expression Regulation, Neoplastic|Humans|Prognosis|Receptors, Estrogen|Transcription Factors|Treatment Outcome|Tumor Suppressor Protein p53', 'Journal Article', '10.1371/journal.pcbi.1004269', '25996148', 'The regulatory architecture of breast cancer is extraordinarily complex and gene misregulation can occur at many levels, with transcriptional malfunction being a major cause. This dysfunctional process typically involves additional regulatory modulators including DNA methylation. Thus, the interplay between transcription factor (TF) binding and DNA methylation are two components of a cancer regulatory interactome presumed to display correlated signals. As proof of concept, we performed a systematic motif-based in silico analysis to infer all potential TFs that are involved in breast cancer prognosis through an association with DNA methylation changes. Using breast cancer DNA methylation and clinical data derived from The Cancer Genome Atlas (TCGA), we carried out a systematic inference of TFs whose misregulation underlie different clinical subtypes of breast cancer. Our analysis identified TFs known to be associated with clinical outcomes of p53 and ER (estrogen receptor) subtypes of breast cancer, while also predicting new TFs that may also be involved. Furthermore, our results suggest that misregulation in breast cancer can be caused by the binding of alternative factors to the binding sites of TFs whose activity has been ablated. Overall, this study provides a comprehensive analysis that links DNA methylation to TF binding to patient prognosis. '),
(87175, 2015, 'plos', 'The opponent channel population code of sound location is an efficient representation of natural binaural sounds', 'Mxc5x82ynarski, Wiktor', 'Max-Planck Institute for Mathematics in the Sciences, Leipzig, Germany. wiktor.mlynarski@gmail.com', 'Germany', 11, 'Acoustic Stimulation|Algorithms|Animals|Auditory Cortex|Auditory Pathways|Computer Simulation|Ear|Female|Hearing|Humans|Learning|Models, Biological|Neurons|Sound|Sound Localization|Time Factors', 'Journal Article', '10.1371/journal.pcbi.1004294', '25996373', 'In mammalian auditory cortex, sound source position is represented by a population of broadly tuned neurons whose firing is modulated by sounds located at all positions surrounding the animal. Peaks of their tuning curves are concentrated at lateral position, while their slopes are steepest at the interaural midline, allowing for the maximum localization accuracy in that area. These experimental observations contradict initial assumptions that the auditory space is represented as a topographic cortical map. It has been suggested that a panoramic code has evolved to match specific demands of the sound localization task. This work provides evidence suggesting that properties of spatial auditory neurons identified experimentally follow from a general design principle- learning a sparse, efficient representation of natural stimuli. Natural binaural sounds were recorded and served as input to a hierarchical sparse-coding model. In the first layer, left and right ear sounds were separately encoded by a population of complex-valued basis functions which separated phase and amplitude. Both parameters are known to carry information relevant for spatial hearing. Monaural input converged in the second layer, which learned a joint representation of amplitude and interaural phase difference. Spatial selectivity of each second-layer unit was measured by exposing the model to natural sound sources recorded at different positions. Obtained tuning curves match well tuning characteristics of neurons in the mammalian auditory cortex. This study connects neuronal coding of the auditory space with natural stimulus statistics and generates new experimental predictions. Moreover, results presented here suggest that cortical regions with seemingly different functions may implement the same computational strategy-efficient coding. '),
(87176, 2015, 'plos', 'Context-Dependent Role of Mitochondrial Fusion-Fission in Clonal Expansion of mtDNA Mutations', 'Tam, Zhi Yang|Gruber, Jan|Halliwell, Barry|Gunawan, Rudiyanto', 'Lee Kong Chian School of Medicine, Nanyang Technological University, Singapore.|Department of Biochemistry, Centre for Life Sciences, National University of Singapore, Singapore, Yale-NUS College, Science Division, National University of Singapore, Singapore.|Department of Biochemistry, Centre for Life Sciences, National University of Singapore, Singapore.|Institute for Chemical and Bioengineering, ETH Zurich, Zurich, Switzerland, Swiss Institute of Bioinformatics, Lausanne, Switzerland.', 'Singapore|Singapore|Singapore|Switzerland', 25, 'Aging|Animals|Computational Biology|Computer Simulation|DNA, Mitochondrial|Humans|Mitochondrial Degradation|Mitochondrial Dynamics|Models, Biological|Mutation', 'Journal Article', '10.1371/journal.pcbi.1004183', '25996936', 'The accumulation of mutant mitochondrial DNA (mtDNA) molecules in aged cells has been associated with mitochondrial dysfunction, age-related diseases and the ageing process itself. This accumulation has been shown to often occur clonally, where mutant mtDNA grow in number and overpopulate the wild-type mtDNA. However, the cell possesses quality control (QC) mechanisms that maintain mitochondrial function, in which dysfunctional mitochondria are isolated and removed by selective fusion and mitochondrial autophagy (mitophagy), respectively. The aim of this study is to elucidate the circumstances related to mitochondrial QC that allow the expansion of mutant mtDNA molecules. For the purpose of the study, we have developed a mathematical model of mitochondrial QC process by extending our previous validated model of mitochondrial turnover and fusion-fission. A global sensitivity analysis of the model suggested that the selectivity of mitophagy and fusion is the most critical QC parameter for clearing de novo mutant mtDNA molecules. We further simulated several scenarios involving perturbations of key QC parameters to gain a better understanding of their dynamic and synergistic interactions. Our model simulations showed that a higher frequency of mitochondrial fusion-fission can provide a faster clearance of mutant mtDNA, but only when mutant-rich mitochondria that are transiently created are efficiently prevented from re-fusing with other mitochondria and selectively removed. Otherwise, faster fusion-fission quickens the accumulation of mutant mtDNA. Finally, we used the insights gained from model simulations and analysis to propose a possible circumstance involving deterioration of mitochondrial QC that permits mutant mtDNA to expand with age. '),
(87177, 2015, 'plos', 'The hydrophobic temperature dependence of amino acids directly calculated from protein structures', 'van Dijk, Erik|Hoogeveen, Arlo|Abeln, Sanne', 'Computer Science Department, Centre for Integrative Bioinformatics (IBIVU), VU University, Amsterdam, Netherlands.|Computer Science Department, Centre for Integrative Bioinformatics (IBIVU), VU University, Amsterdam, Netherlands.|Computer Science Department, Centre for Integrative Bioinformatics (IBIVU), VU University, Amsterdam, Netherlands.', 'Netherlands|Netherlands|Netherlands', 0, 'Algorithms|Amino Acids|Computational Biology|Crystallography, X-Ray|Databases, Protein|Hydrophobic and Hydrophilic Interactions|Magnetic Resonance Spectroscopy|Models, Statistical|Protein Denaturation|Protein Folding|Proteins|Solvents|Temperature|Water', 'Journal Article', '10.1371/journal.pcbi.1004277', '26000449', 'The hydrophobic effect is the main driving force in protein folding. One can estimate the relative strength of this hydrophobic effect for each amino acid by mining a large set of experimentally determined protein structures. However, the hydrophobic force is known to be strongly temperature dependent. This temperature dependence is thought to explain the denaturation of proteins at low temperatures. Here we investigate if it is possible to extract this temperature dependence directly from a large set of protein structures determined at different temperatures. Using NMR structures filtered for sequence identity, we were able to extract hydrophobicity propensities for all amino acids at five different temperature ranges (spanning 265-340 K). These propensities show that the hydrophobicity becomes weaker at lower temperatures, in line with current theory. Alternatively, one can conclude that the temperature dependence of the hydrophobic effect has a measurable influence on protein structures. Moreover, this work provides a method for probing the individual temperature dependence of the different amino acid types, which is difficult to obtain by direct experiment. '),
(87178, 2015, 'plos', 'Improving 3D Genome Reconstructions Using Orthologous and Functional Constraints', 'Diament, Alon|Tuller, Tamir', 'Dept. of Biomedical Engineering, Tel Aviv University, Tel Aviv, Israel.|Dept. of Biomedical Engineering, Tel Aviv University, Tel Aviv, Israel, The Sagol School of Neuroscience, Tel Aviv University, Tel Aviv, Israel.', 'Israel|Israel', 0, 'Algorithms|Chromosomes|Cluster Analysis|Computational Biology|Computer Simulation|Databases, Genetic|Genes, Fungal|Genome, Fungal|Genomics|Image Processing, Computer-Assisted|Imaging, Three-Dimensional|Open Reading Frames|Saccharomyces cerevisiae|Schizosaccharomyces|Signal Processing, Computer-Assisted', 'Journal Article', '10.1371/journal.pcbi.1004298', '26000633', 'The study of the 3D architecture of chromosomes has been advancing rapidly in recent years. While a number of methods for 3D reconstruction of genomic models based on Hi-C data were proposed, most of the analyses in the field have been performed on different 3D representation forms (such as graphs). Here, we reproduce most of the previous results on the 3D genomic organization of the eukaryote Saccharomyces cerevisiae using analysis of 3D reconstructions. We show that many of these results can be reproduced in sparse reconstructions, generated from a small fraction of the experimental data (5% of the data), and study the properties of such models. Finally, we propose for the first time a novel approach for improving the accuracy of 3D reconstructions by introducing additional predicted physical interactions to the model, based on orthologous interactions in an evolutionary-related organism and based on predicted functional interactions between genes. We demonstrate that this approach indeed leads to the reconstruction of improved models. '),
(87179, 2015, 'plos', 'Metabolic Needs and Capabilities of Toxoplasma gondii through Combined Computational and Experimental Analysis', 'Tymoshenko, Stepan|Oppenheim, Rebecca D|Agren, Rasmus|Nielsen, Jens|Soldati-Favre, Dominique|Hatzimanikatis, Vassily', 'Laboratory of Computational Systems Biotechnology, École Polytechnique Fédérale de Lausanne, EPFL, Lausanne, Switzerland, Department of Microbiology and Molecular Medicine, Faculty of Medicine, University of Geneva, CMU, Geneva, Switzerland, Swiss Institute of Bioinformatics, Quartier Sorge, Batiment Genopode, Lausanne, Switzerland.|Department of Microbiology and Molecular Medicine, Faculty of Medicine, University of Geneva, CMU, Geneva, Switzerland.|Department of Chemical and Biological Engineering, Chalmers University of Technology, Gothenburg, Sweden.|Department of Chemical and Biological Engineering, Chalmers University of Technology, Gothenburg, Sweden.|Department of Microbiology and Molecular Medicine, Faculty of Medicine, University of Geneva, CMU, Geneva, Switzerland.|Department of Microbiology and Molecular Medicine, Faculty of Medicine, University of Geneva, CMU, Geneva, Switzerland, Swiss Institute of Bioinformatics, Quartier Sorge, Batiment Genopode, Lausanne, Switzerland.', 'Switzerland|Switzerland|Sweden|Sweden|Switzerland|Switzerland', 0, 'Acetyl Coenzyme A|Algorithms|Automation|Cloning, Molecular|Computational Biology|Computer Simulation|DNA|Gene Deletion|Genes, Protozoan|Genome|Host-Parasite Interactions|Humans|Metabolic Networks and Pathways|Open Reading Frames|Phenotype|Protozoan Proteins|Toxoplasma|Toxoplasmosis', 'Journal Article', '10.1371/journal.pcbi.1004261', '26001086', 'Toxoplasma gondii is a human pathogen prevalent worldwide that poses a challenging and unmet need for novel treatment of toxoplasmosis. Using a semi-automated reconstruction algorithm, we reconstructed a genome-scale metabolic model, ToxoNet1. The reconstruction process and flux-balance analysis of the model offer a systematic overview of the metabolic capabilities of this parasite. Using ToxoNet1 we have identified significant gaps in the current knowledge of Toxoplasma metabolic pathways and have clarified its minimal nutritional requirements for replication. By probing the model via metabolic tasks, we have further defined sets of alternative precursors necessary for parasite growth. Within a human host cell environment, ToxoNet1 predicts a minimal set of 53 enzyme-coding genes and 76 reactions to be essential for parasite replication. Double-gene-essentiality analysis identified 20 pairs of genes for which simultaneous deletion is deleterious. To validate several predictions of ToxoNet1 we have performed experimental analyses of cytosolic acetyl-CoA biosynthesis. ATP-citrate lyase and acetyl-CoA synthase were localised and their corresponding genes disrupted, establishing that each of these enzymes is dispensable for the growth of T. gondii, however together they make a synthetic lethal pair. '),
(87180, 2015, 'plos', 'A Multiscale Model Evaluates Screening for Neoplasia in Barretts Esophagus', 'Curtius, Kit|Hazelton, William D|Jeon, Jihyoun|Luebeck, E Georg', 'Department of Applied Mathematics, University of Washington, Seattle, Washington, United States of America.|Program in Computational Biology, Fred Hutchinson Cancer Research Center, Seattle, Washington, United States of America.|Program in Biostatistics and Biomathematics, 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.', 'United States|United States|United States|United States', 14, 'Adenocarcinoma|Algorithms|Barrett Esophagus|Biopsy|Calibration|Computer Simulation|Esophageal Neoplasms|Gastroesophageal Reflux|Humans|Incidence|Mass Screening|Models, Theoretical|Prevalence|Probability|Reproducibility of Results|Stochastic Processes', 'Journal Article', '10.1371/journal.pcbi.1004272', '26001209', 'Barretts esophagus (BE) patients are routinely screened for high grade dysplasia (HGD) and esophageal adenocarcinoma (EAC) through endoscopic screening, during which multiple esophageal tissue samples are removed for histological analysis. We propose a computational method called the multistage clonal expansion for EAC (MSCE-EAC) screening model that is used for screening BE patients in silico to evaluate the effects of biopsy sampling, diagnostic sensitivity, and treatment on disease burden. Our framework seamlessly integrates relevant cell-level processes during EAC development with a spatial screening process to provide a clinically relevant model for detecting dysplastic and malignant clones within the crypt-structured BE tissue. With this computational approach, we retain spatio-temporal information about small, unobserved tissue lesions in BE that may remain undetected during biopsy-based screening but could be detected with high-resolution imaging. This allows evaluation of the efficacy and sensitivity of current screening protocols to detect neoplasia (dysplasia and early preclinical EAC) in the esophageal lining. We demonstrate the clinical utility of this model by predicting three important clinical outcomes: (1) the probability that small cancers are missed during biopsy-based screening, (2) the potential gains in neoplasia detection probabilities if screening occurred via high-resolution tomographic imaging, and (3) the efficacy of ablative treatments that result in the curative depletion of metaplastic and neoplastic cell populations in BE in terms of the long-term impact on reducing EAC incidence. '),
(87181, 2015, 'plos', 'Geometrical and mechanical properties control actin filament organization', 'Letort, Gaëlle|Politi, Antonio Z|Ennomani, Hajer|Théry, Manuel|Nedelec, Francois|Blanchoin, Laurent', 'Laboratoire de Physiologie Cellulaire et Végétale, Institut de Recherches en Technologies et Sciences pour le Vivant, iRTSV, CNRS/CEA/UGA, Grenoble, France, Laboratoire dImagerie et Systèmes dAcquisition, CEA, LETI, MINATEC Campus, Grenoble, France, Univ. Grenoble-Alpes, Grenoble, France.|Cell Biology and Biophysics Unit, EMBL, Heidelberg, Germany.|Laboratoire de Physiologie Cellulaire et Végétale, Institut de Recherches en Technologies et Sciences pour le Vivant, iRTSV, CNRS/CEA/UGA, Grenoble, France.|Laboratoire de Physiologie Cellulaire et Végétale, Institut de Recherches en Technologies et Sciences pour le Vivant, iRTSV, CNRS/CEA/UGA, Grenoble, France.|Cell Biology and Biophysics Unit, EMBL, Heidelberg, Germany.|Laboratoire de Physiologie Cellulaire et Végétale, Institut de Recherches en Technologies et Sciences pour le Vivant, iRTSV, CNRS/CEA/UGA, Grenoble, France.', 'France|Germany|France|France|Germany|France', 0, 'Actin Cytoskeleton|Animals|Biomechanical Phenomena|Computational Biology|Computer Simulation|Humans|In Vitro Techniques|Models, Molecular|Protein Multimerization', 'Journal Article', '10.1371/journal.pcbi.1004245', '26016478', 'The different actin structures governing eukaryotic cell shape and movement are not only determined by the properties of the actin filaments and associated proteins, but also by geometrical constraints. We recently demonstrated that limiting nucleation to specific regions was sufficient to obtain actin networks with different organization. To further investigate how spatially constrained actin nucleation determines the emergent actin organization, we performed detailed simulations of the actin filament system using Cytosim. We first calibrated the steric interaction between filaments, by matching, in simulations and experiments, the bundled actin organization observed with a rectangular bar of nucleating factor. We then studied the overall organization of actin filaments generated by more complex pattern geometries used experimentally. We found that the fraction of parallel versus antiparallel bundles is determined by the mechanical properties of actin filament or bundles and the efficiency of nucleation. Thus nucleation geometry, actin filaments local interactions, bundle rigidity, and nucleation efficiency are the key parameters controlling the emergent actin architecture. We finally simulated more complex nucleation patterns and performed the corresponding experiments to confirm the predictive capabilities of the model. '),
(87182, 2015, 'plos', 'Native contact density and nonnative hydrophobic effects in the folding of bacterial immunity proteins', 'Chen, Tao|Chan, Hue Sun', 'Departments of Biochemistry, of Molecular Genetics, and of Physics, University of Toronto, Toronto, Ontario M5S 1A8, Canada.|Departments of Biochemistry, of Molecular Genetics, and of Physics, University of Toronto, Toronto, Ontario M5S 1A8, Canada.', 'Canada|Canada', 26, 'Bacterial Proteins|Colicins|Computational Biology|Computer Simulation|Diffusion|Hydrogen-Ion Concentration|Hydrophobic and Hydrophilic Interactions|Kinetics|Models, Molecular|Models, Statistical|Mutation|Protein Conformation|Protein Denaturation|Protein Folding|Protein Structure, Secondary|Temperature|Thermodynamics', 'Journal Article', '10.1371/journal.pcbi.1004260', '26016652', 'The bacterial colicin-immunity proteins Im7 and Im9 fold by different mechanisms. Experimentally, at pH 7.0 and 10°C, Im7 folds in a three-state manner via an intermediate but Im9 folding is two-state-like. Accordingly, Im7 exhibits a chevron rollover, whereas the chevron arm for Im9 folding is linear. Here we address the biophysical basis of their different behaviors by using native-centric models with and without additional transferrable, sequence-dependent energies. The Im7 chevron rollover is not captured by either a pure native-centric model or a model augmented by nonnative hydrophobic interactions with a uniform strength irrespective of residue type. By contrast, a more realistic nonnative interaction scheme that accounts for the difference in hydrophobicity among residues leads simultaneously to a chevron rollover for Im7 and an essentially linear folding chevron arm for Im9. Hydrophobic residues identified by published experiments to be involved in nonnative interactions during Im7 folding are found to participate in the strongest nonnative contacts in this model. Thus our observations support the experimental perspective that the Im7 folding intermediate is largely underpinned by nonnative interactions involving large hydrophobics. Our simulation suggests further that nonnative effects in Im7 are facilitated by a lower local native contact density relative to that of Im9. In a one-dimensional diffusion picture of Im7 folding with a coordinate- and stability-dependent diffusion coefficient, a significant chevron rollover is consistent with a diffusion coefficient that depends strongly on native stability at the conformational position of the folding intermediate. '),
(87183, 2015, 'plos', 'SeqGL Identifies Context-Dependent Binding Signals in Genome-Wide Regulatory Element Maps', 'Setty, Manu|Leslie, Christina S', '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.', 'United States|United States', 34, 'Algorithms|Amino Acid Motifs|Binding Sites|Cell Line, Tumor|Chromatin|Chromatin Immunoprecipitation|Chromosome Mapping|Cluster Analysis|Computational Biology|Deoxyribonucleases|Genome|High-Throughput Nucleotide Sequencing|Humans|Models, Statistical|Protein Binding|ROC Curve|Regulatory Sequences, Nucleic Acid|Reproducibility of Results|Transcription Factors', 'Journal Article', '10.1371/journal.pcbi.1004271', '26016777', 'Genome-wide maps of transcription factor (TF) occupancy and regions of open chromatin implicitly contain DNA sequence signals for multiple factors. We present SeqGL, a novel de novo motif discovery algorithm to identify multiple TF sequence signals from ChIP-, DNase-, and ATAC-seq profiles. SeqGL trains a discriminative model using a k-mer feature representation together with group lasso regularization to extract a collection of sequence signals that distinguish peak sequences from flanking regions. Benchmarked on over 100 ChIP-seq experiments, SeqGL outperformed traditional motif discovery tools in discriminative accuracy. Furthermore, SeqGL can be naturally used with multitask learning to identify genomic and cell-type context determinants of TF binding. SeqGL successfully scales to the large multiplicity of sequence signals in DNase- or ATAC-seq maps. In particular, SeqGL was able to identify a number of ChIP-seq validated sequence signals that were not found by traditional motif discovery algorithms. Thus compared to widely used motif discovery algorithms, SeqGL demonstrates both greater discriminative accuracy and higher sensitivity for detecting the DNA sequence signals underlying regulatory element maps. SeqGL is available at http://cbio.mskcc.org/public/Leslie/SeqGL/. '),
(87184, 2015, 'plos', 'Integrated Stochastic Model of DNA Damage Repair by Non-homologous End Joining and p53/p21-Mediated Early Senescence Signalling', 'Dolan, David W P|Zupanic, Anze|Nelson, Glyn|Hall, Philip|Miwa, Satomi|Kirkwood, Thomas B L|Shanley, Daryl P', 'School of Biological and Biomedical Biosciences, Durham University, Durham, United Kingdom, Centre for Integrative Systems Biology of Ageing and Nutrition, Newcastle University Institute for Ageing, Newcastle University, Newcastle upon Tyne, United Kingdom.|Centre for Integrative Systems Biology of Ageing and Nutrition, Newcastle University Institute for Ageing, Newcastle University, Newcastle upon Tyne, United Kingdom, Eawag-Swiss Federal Institute of Aquatic Science and Technology, Dübendorf, Switzerland.|Centre for Integrative Systems Biology of Ageing and Nutrition, Newcastle University Institute for Ageing, Newcastle University, Newcastle upon Tyne, United Kingdom.|Centre for Integrative Systems Biology of Ageing and Nutrition, Newcastle University Institute for Ageing, Newcastle University, Newcastle upon Tyne, United Kingdom.|Centre for Integrative Systems Biology of Ageing and Nutrition, Newcastle University Institute for Ageing, Newcastle University, Newcastle upon Tyne, United Kingdom.|Centre for Integrative Systems Biology of Ageing and Nutrition, Newcastle University Institute for Ageing, Newcastle University, Newcastle upon Tyne, United Kingdom.|Centre for Integrative Systems Biology of Ageing and Nutrition, Newcastle University Institute for Ageing, Newcastle University, Newcastle upon Tyne, United Kingdom.', 'United Kingdom|Switzerland|United Kingdom|United Kingdom|United Kingdom|United Kingdom|United Kingdo', 0, 'Cell Line|Cellular Senescence|Computational Biology|Computer Simulation|Cyclin-Dependent Kinase Inhibitor p21|DNA Damage|DNA End-Joining Repair|Humans|Models, Biological|Signal Transduction|Stochastic Processes|Tumor Suppressor Protein p53', 'Journal Article', '10.1371/journal.pcbi.1004246', '26020242', 'Unrepaired or inaccurately repaired DNA damage can lead to a range of cell fates, such as apoptosis, cellular senescence or cancer, depending on the efficiency and accuracy of DNA damage repair and on the downstream DNA damage signalling. DNA damage repair and signalling have been studied and modelled in detail separately, but it is not yet clear how they integrate with one another to control cell fate. In this study, we have created an integrated stochastic model of DNA damage repair by non-homologous end joining and of gamma irradiation-induced cellular senescence in human cells that are not apoptosis-prone. The integrated model successfully explains the changes that occur in the dynamics of DNA damage repair after irradiation. Simulations of p53/p21 dynamics after irradiation agree well with previously published experimental studies, further validating the model. Additionally, the model predicts, and we offer some experimental support, that low-dose fractionated irradiation of cells leads to temporal patterns in p53/p21 that lead to significant cellular senescence. The integrated model is valuable for studying the processes of DNA damage induced cell fate and predicting the effectiveness of DNA damage related medical interventions at the cellular level. '),
(87185, 2015, 'plos', 'Experimental and computational analysis of a large protein network that controls fat storage reveals the design principles of a signaling network', 'Al-Anzi, Bader|Arpp, Patrick|Gerges, Sherif|Ormerod, Christopher|Olsman, Noah|Zinn, Kai', 'Division of Biology and Biological Engineering, California Institute of Technology, Pasadena, California, United States of America.|Division of Biology and Biological Engineering, California Institute of Technology, Pasadena, California, United States of America.|Department of Molecular Biology, Princeton University, Princeton, New Jersey, United States of America.|Division of Physics, Mathematics, and Astronomy, California Institute of Technology, Pasadena, California, United States of America.|Control and Dynamical Systems Option, Division of Engineering and Applied Sciences, California Institute of Technology, Pasadena, California, United States of America.|Division of Biology and Biological Engineering, California Institute of Technology, Pasadena, California, United States of America.', 'United States|United States|Jersey|United States|United States|United States', 5, 'Algorithms|Cluster Analysis|Computational Biology|Computer Simulation|Fatty Acids|Gene Deletion|MAP Kinase Signaling System|Models, Genetic|Models, Theoretical|Mutation|Phenotype|Proteins|Proteome|Reproducibility of Results|Saccharomyces cerevisiae|Sirolimus|Software|Systems Biology', 'Journal Article', '10.1371/journal.pcbi.1004264', '26020510', 'An approach combining genetic, proteomic, computational, and physiological analysis was used to define a protein network that regulates fat storage in budding yeast (Saccharomyces cerevisiae). A computational analysis of this network shows that it is not scale-free, and is best approximated by the Watts-Strogatz model, which generates small-world networks with high clustering and short path lengths. The network is also modular, containing energy level sensing proteins that connect to four output processes: autophagy, fatty acid synthesis, mRNA processing, and MAP kinase signaling. The importance of each protein to network function is dependent on its Katz centrality score, which is related both to the proteins position within a module and to the modules relationship to the network as a whole. The network is also divisible into subnetworks that span modular boundaries and regulate different aspects of fat metabolism. We used a combination of genetics and pharmacology to simultaneously block output from multiple network nodes. The phenotypic results of this blockage define patterns of communication among distant network nodes, and these patterns are consistent with the Watts-Strogatz model. '),
(87186, 2015, 'plos', 'Predicting cortical dark/bright asymmetries from natural image statistics and early visual transforms', 'Cooper, Emily A|Norcia, Anthony M', 'Department of Psychology, Stanford University, Stanford, California, United States of America.|Department of Psychology, Stanford University, Stanford, California, United States of America.', 'United States|United States', 0, 'Animals|Calibration|Computer Simulation|Databases, Factual|Humans|Image Processing, Computer-Assisted|Models, Neurological|Models, Statistical|Neurons|Normal Distribution|Pattern Recognition, Automated|Photic Stimulation|Probability|Retina|Retinal Ganglion Cells|Vision, Ocular|Visual Cortex|Visual Pathways|Visual Perception', 'Journal Article', '10.1371/journal.pcbi.1004268', '26020624', 'The nervous system has evolved in an environment with structure and predictability. One of the ubiquitous principles of sensory systems is the creation of circuits that capitalize on this predictability. Previous work has identified predictable non-uniformities in the distributions of basic visual features in natural images that are relevant to the encoding tasks of the visual system. Here, we report that the well-established statistical distributions of visual features--such as visual contrast, spatial scale, and depth--differ between bright and dark image components. Following this analysis, we go on to trace how these differences in natural images translate into different patterns of cortical input that arise from the separate bright (ON) and dark (OFF) pathways originating in the retina. We use models of these early visual pathways to transform natural images into statistical patterns of cortical input. The models include the receptive fields and non-linear response properties of the magnocellular (M) and parvocellular (P) pathways, with their ON and OFF pathway divisions. The results indicate that there are regularities in visual cortical input beyond those that have previously been appreciated from the direct analysis of natural images. In particular, several dark/bright asymmetries provide a potential account for recently discovered asymmetries in how the brain processes visual features, such as violations of classic energy-type models. On the basis of our analysis, we expect that the dark/bright dichotomy in natural images plays a key role in the generation of both cortical and perceptual asymmetries.'),
(87187, 2015, 'plos', 'Inferring horizontal gene transfer', 'Ravenhall, Matt|Škunca, Nives|Lassalle, Florent|Dessimoz, Christophe', 'University College London, London, United Kingdom.|ETH Zurich, Zurich, Switzerland, Swiss Institute of Bioinformatics, Zurich, Switzerland.|University College London, London, United Kingdom.|University College London, London, United Kingdom, European Molecular Biology Laboratory, European Bioinformatics Institute, Wellcome Trust Genome Campus, Hinxton, Cambridge, United Kingdom.', 'United Kingdom|Switzerland|United Kingdom|United Kingdom', 0, 'Base Composition|Computational Biology|Computer Simulation|DNA, Bacterial|Databases, Genetic|Drug Resistance, Bacterial|Evolution, Molecular|Gene Transfer, Horizontal|Genomics|Humans|Models, Genetic|Models, Statistical|Phylogeny', 'Journal Article', '10.1371/journal.pcbi.1004095', '26020646', 'Horizontal or Lateral Gene Transfer (HGT or LGT) is the transmission of portions of genomic DNA between organisms through a process decoupled from vertical inheritance. In the presence of HGT events, different fragments of the genome are the result of different evolutionary histories. This can therefore complicate the investigations of evolutionary relatedness of lineages and species. Also, as HGT can bring into genomes radically different genotypes from distant lineages, or even new genes bearing new functions, it is a major source of phenotypic innovation and a mechanism of niche adaptation. For example, of particular relevance to human health is the lateral transfer of antibiotic resistance and pathogenicity determinants, leading to the emergence of pathogenic lineages. Computational identification of HGT events relies upon the investigation of sequence composition or evolutionary history of genes. Sequence composition-based (parametric) methods search for deviations from the genomic average, whereas evolutionary history-based (phylogenetic) approaches identify genes whose evolutionary history significantly differs from that of the host species. The evaluation and benchmarking of HGT inference methods typically rely upon simulated genomes, for which the true history is known. On real data, different methods tend to infer different HGT events, and as a result it can be difficult to ascertain all but simple and clear-cut HGT events.'),
(87188, 2015, 'plos', 'Causal Modeling of Cancer-Stromal Communication Identifies PAPPA as a Novel Stroma-Secreted Factor Activating NFxcexbaB Signaling in Hepatocellular Carcinoma', 'Engelmann, Julia C|Amann, Thomas|Ott-Rxc3xb6tzer, Birgitta|Nxc3xbctzel, Margit|Reinders, Yvonne|Reinders, Jxc3xb6rg|Thasler, Wolfgang E|Kristl, Theresa|Teufel, Andreas|Huber, Christian G|Oefner, Peter J|Spang, Rainer|Hellerbrand, Claus', 'Department of Statistical Bioinformatics, University of Regensburg, Regensburg, Germany.|Department of Internal Medicine I, University Hospital Regensburg, Regensburg, Germany.|Department of Internal Medicine I, University Hospital Regensburg, Regensburg, Germany.|Department of Internal Medicine I, University Hospital Regensburg, Regensburg, Germany.|Institute of Functional Genomics, University of Regensburg, Regensburg, Germany.|Institute of Functional Genomics, University of Regensburg, Regensburg, Germany.|Biobank under the authority of Human Tissue and Cell Research (HTCR) and Center for Liver Cell Research, Department of General, Visceral, Transplantation, Vascular and Thoracic Surgery, Hospital of Ludwig-Maximilians-University of Munich, Munich, Germany.|Department of Molecular Biology, Division of Chemistry and Bioanalytics, University of Salzburg, Salzburg, Austria.|Department of Internal Medicine I, University Hospital Regensburg, Regensburg, Germany.|Department of Molecular Biology, Division of Chemistry and Bioanalytics, University of Salzburg, Salzburg, Austria.|Institute of Functional Genomics, University of Regensburg, Regensburg, Germany.|Department of Statistical Bioinformatics, University of Regensburg, Regensburg, Germany.|Department of Internal Medicine I, University Hospital Regensburg, Regensburg, Germany.', 'Germany|Germany|Germany|Germany|Germany|Germany|Germany|Austria|Germany|Austria|Germany|Germany|Germ', 11, 'Carcinoma, Hepatocellular|Cell Adhesion Molecules|Cell Communication|Cell Line, Tumor|Computational Biology|Drug Design|Gene Expression Profiling|Gene Expression Regulation, Neoplastic|Hep G2 Cells|Hepatic Stellate Cells|Humans|Liver|Liver Neoplasms|NF-kappa B|Oligonucleotide Array Sequence Analysis|Placenta Growth Factor|Pregnancy Proteins|Pregnancy-Associated Plasma Protein-A|Proteomics|Signal Transduction|Transcriptome', 'Journal Article', '10.1371/journal.pcbi.1004293', '26020769', 'Inter-cellular communication with stromal cells is vital for cancer cells. Molecules involved in the communication are potential drug targets. To identify them systematically, we applied a systems level analysis that combined reverse network engineering with causal effect estimation. Using only observational transcriptome profiles we searched for paracrine factors sending messages from activated hepatic stellate cells (HSC) to hepatocellular carcinoma (HCC) cells. We condensed these messages to predict ten proteins that, acting in concert, cause the majority of the gene expression changes observed in HCC cells. Among the 10 paracrine factors were both known and unknown cancer promoting stromal factors, the former including Placental Growth Factor (PGF) and Periostin (POSTN), while Pregnancy-Associated Plasma Protein A (PAPPA) was among the latter. Further support for the predicted effect of PAPPA on HCC cells came from both in vitro studies that showed PAPPA to contribute to the activation of NFxcexbaB signaling, and clinical data, which linked higher expression levels of PAPPA to advanced stage HCC. In summary, this study demonstrates the potential of causal modeling in combination with a condensation step borrowed from gene set analysis [Model-based Gene Set Analysis (MGSA)] in the identification of stromal signaling molecules influencing the cancer phenotype. '),
(87189, 2015, 'plos', 'Summary of the DREAM8 Parameter Estimation Challenge: Toward Parameter Identification for Whole-Cell Models', 'Karr, Jonathan R|Williams, Alex H|Zucker, Jeremy D|Raue, Andreas|Steiert, Bernhard|Timmer, Jens|Kreutz, Clemens|DREAM8 Parameter Estimation Challenge Consortium|Wilkinson, Simon|Allgood, Brandon A|Bot, Brian M|Hoff, Bruce R|Kellen, Michael R|Covert, Markus W|Stolovitzky, Gustavo A|Meyer, Pablo', 'Graduate Program in Biophysics, Stanford University, Stanford, California, United States of America.|Department of Biology, Brandeis University, Waltham, Massachusetts, United States of America, Volen Center for Complex Systems, Brandeis University, Waltham, Massachusetts, United States of America.|Broad Institute of MIT and Harvard, Cambridge, Massachusetts, United States of America.|Institute for Physics, University of Freiburg, Freiburg, Germany, Freiburg Center for Systems Biology (ZBSA), University of Freiburg, Freiburg, Germany.|Institute for Physics, University of Freiburg, Freiburg, Germany, Freiburg Center for Systems Biology (ZBSA), University of Freiburg, Freiburg, Germany.|Institute for Physics, University of Freiburg, Freiburg, Germany, Freiburg Center for Systems Biology (ZBSA), University of Freiburg, Freiburg, Germany, Freiburg Institute for Advanced Studies (FRIAS), University of Freiburg, Freiburg, Germany, BIOSS Centre for Biological Signalling Studies, University of Freiburg, Freiburg, Germany.|Institute for Physics, University of Freiburg, Freiburg, Germany, Freiburg Center for Systems Biology (ZBSA), University of Freiburg, Freiburg, Germany.|Institute for Physics, University of Freiburg, Freiburg, Germany, Freiburg Center for Systems Biology (ZBSA), University of Freiburg, Freiburg, Germany.|Numerate Inc., San Bruno, California, United States of America.|Numerate Inc., San Bruno, California, United States of America.|Sage Bionetworks, Seattle, Washington, United States of America.|Sage Bionetworks, Seattle, Washington, United States of America.|Sage Bionetworks, Seattle, Washington, United States of America.|Department of Bioengineering, Stanford University, Stanford, California, United States of America.|IBM Thomas J. Watson Research Center, Yorktown Heights, New York, United States of America.|IBM Thomas J. Watson Research Center, Yorktown Heights, New York, United States of America.', 'United States|United States|United States|Germany|Germany|Germany|Germany|Germany|United States|Unit', 0, 'Algorithms|Bacteria|Bioengineering|Cells|Cloud Computing|Computational Biology|Computer Simulation|Genetic Association Studies|Models, Biological|Mutation|Mycoplasma genitalium', 'Journal Article', '10.1371/journal.pcbi.1004096', '26020786', 'Whole-cell models that explicitly represent all cellular components at the molecular level have the potential to predict phenotype from genotype. However, even for simple bacteria, whole-cell models will contain thousands of parameters, many of which are poorly characterized or unknown. New algorithms are needed to estimate these parameters and enable researchers to build increasingly comprehensive models. We organized the Dialogue for Reverse Engineering Assessments and Methods (DREAM) 8 Whole-Cell Parameter Estimation Challenge to develop new parameter estimation algorithms for whole-cell models. We asked participants to identify a subset of parameters of a whole-cell model given the models structure and in silico experimental data. Here we describe the challenge, the best performing methods, and new insights into the identifiability of whole-cell models. We also describe several valuable lessons we learned toward improving future challenges. Going forward, we believe that collaborative efforts supported by inexpensive cloud computing have the potential to solve whole-cell model parameter estimation. ');
INSERT INTO `papers` (`id`, `ano`, `journal`, `titulo`, `autores`, `afiliacao`, `pais`, `citacoes`, `palavra_chave`, `categorias`, `doi`, `pubmed`, `abstract`) VALUES
(87190, 2015, 'plos', 'Predicted Role of NAD Utilization in the Control of Circadian Rhythms during DNA Damage Response', 'Luna, Augustin|McFadden, Geoffrey B|Aladjem, Mirit I|Kohn, Kurt W', 'Laboratory of Molecular Pharmacology, National Cancer Institute, Bethesda, Maryland, United States of America, Department of Bioinformatics, Boston University, Boston, Massachusetts, United States of America.|Applied and Computational Mathematics Division, National Institute of Standards and Technology, Gaithersburg, Maryland, United States of America.|Laboratory of Molecular Pharmacology, National Cancer Institute, Bethesda, Maryland, United States of America.|Laboratory of Molecular Pharmacology, National Cancer Institute, Bethesda, Maryland, United States of America.', 'United States|United States|United States|United States', 0, 'ARNTL Transcription Factors|Animals|Apraxia, Ideomotor|CLOCK Proteins|Circadian Rhythm|Circadian Rhythm Signaling Peptides and Proteins|Computational Biology|Computer Simulation|DNA Damage|Humans|Models, Biological|NAD|Period Circadian Proteins|Poly(ADP-ribose) Polymerases|Sirtuin 1', 'Journal Article', '10.1371/journal.pcbi.1004144', '26020938', 'The circadian clock is a set of regulatory steps that oscillate with a period of approximately 24 hours influencing many biological processes. These oscillations are robust to external stresses, and in the case of genotoxic stress (i.e. DNA damage), the circadian clock responds through phase shifting with primarily phase advancements. The effect of DNA damage on the circadian clock and the mechanism through which this effect operates remains to be thoroughly investigated. Here we build an in silico model to examine damage-induced circadian phase shifts by investigating a possible mechanism linking circadian rhythms to metabolism. The proposed model involves two DNA damage response proteins, SIRT1 and PARP1, that are each consumers of nicotinamide adenine dinucleotide (NAD), a metabolite involved in oxidation-reduction reactions and in ATP synthesis. This model builds on two key findings: 1) that SIRT1 (a protein deacetylase) is involved in both the positive (i.e. transcriptional activation) and negative (i.e. transcriptional repression) arms of the circadian regulation and 2) that PARP1 is a major consumer of NAD during the DNA damage response. In our simulations, we observe that increased PARP1 activity may be able to trigger SIRT1-induced circadian phase advancements by decreasing SIRT1 activity through competition for NAD supplies. We show how this competitive inhibition may operate through protein acetylation in conjunction with phosphorylation, consistent with reported observations. These findings suggest a possible mechanism through which multiple perturbations, each dominant during different points of the circadian cycle, may result in the phase advancement of the circadian clock seen during DNA damage. '),
(87191, 2015, 'plos', 'Synaptic Homeostasis and Restructuring across the Sleep-Wake Cycle', 'Blanco, Wilfredo|Pereira, Catia M|Cota, Vinicius R|Souza, Annie C|Rennxc3xb3-Costa, Cxc3xa9sar|Santos, Sharlene|Dias, Gabriella|Guerreiro, Ana M G|Tort, Adriano B L|Neto, Adrixc3xa3o D|Ribeiro, Sidarta', 'Brain Institute, Federal University of Rio Grande do Norte, Natal, Rio Grande do Norte, Brazil, Department of Computer and Automation, Federal University of Rio Grande do Norte, Natal, Rio Grande do Norte, Brazil, Department of Computer Science, State University of Rio Grande do Norte, Natal, Rio Grande do Norte, Brazil.|Edmond and Lily Safra International Institute of Neuroscience of Natal (ELS-IINN), Natal, Rio Grande do Norte, Brazil.|Brain Institute, Federal University of Rio Grande do Norte, Natal, Rio Grande do Norte, Brazil, Laboratory of Neuroengineerging and Neuroscience, Federal University of Sxc3xa3o Joxc3xa3o Del-Rei, Sxc3xa3o Joxc3xa3o Del-Rei, Minas Gerais, Brazil.|Brain Institute, Federal University of Rio Grande do Norte, Natal, Rio Grande do Norte, Brazil.|Brain Institute, Federal University of Rio Grande do Norte, Natal, Rio Grande do Norte, Brazil.|Brain Institute, Federal University of Rio Grande do Norte, Natal, Rio Grande do Norte, Brazil.|Brain Institute, Federal University of Rio Grande do Norte, Natal, Rio Grande do Norte, Brazil.|Department of Biomedical Engineering, Federal University of Rio Grande do Norte, Natal, Rio Grande do Norte, Brazil.|Brain Institute, Federal University of Rio Grande do Norte, Natal, Rio Grande do Norte, Brazil.|Department of Computer and Automation, Federal University of Rio Grande do Norte, Natal, Rio Grande do Norte, Brazil.|Brain Institute, Federal University of Rio Grande do Norte, Natal, Rio Grande do Norte, Brazil.', 'Brazil|Brazil|Brazil|Brazil|Brazil|Brazil|Brazil|Brazil|Brazil|Brazil|Brazil', 25, 'Action Potentials|Animals|Calcium-Calmodulin-Dependent Protein Kinase Type 2|Electrophysiological Phenomena|Hippocampus|Homeostasis|Long-Term Potentiation|Male|Memory Consolidation|Models, Neurological|Models, Psychological|Neuronal Plasticity|Rats|Rats, Wistar|Sleep|Sleep, REM|Wakefulness', 'Journal Article', '10.1371/journal.pcbi.1004241', '26020963', 'Sleep is critical for hippocampus-dependent memory consolidation. However, the underlying mechanisms of synaptic plasticity are poorly understood. The central controversy is on whether long-term potentiation (LTP) takes a role during sleep and which would be its specific effect on memory. To address this question, we used immunohistochemistry to measure phosphorylation of Ca2+/calmodulin-dependent protein kinase II (pCaMKIIxcexb1) in the rat hippocampus immediately after specific sleep-wake states were interrupted. Control animals not exposed to novel objects during waking (WK) showed stable pCaMKIIxcexb1 levels across the sleep-wake cycle, but animals exposed to novel objects showed a decrease during subsequent slow-wave sleep (SWS) followed by a rebound during rapid-eye-movement sleep (REM). The levels of pCaMKIIxcexb1 during REM were proportional to cortical spindles near SWS/REM transitions. Based on these results, we modeled sleep-dependent LTP on a network of fully connected excitatory neurons fed with spikes recorded from the rat hippocampus across WK, SWS and REM. Sleep without LTP orderly rescaled synaptic weights to a narrow range of intermediate values. In contrast, LTP triggered near the SWS/REM transition led to marked swaps in synaptic weight ranking. To better understand the interaction between rescaling and restructuring during sleep, we implemented synaptic homeostasis and embossing in a detailed hippocampal-cortical model with both excitatory and inhibitory neurons. Synaptic homeostasis was implemented by weakening potentiation and strengthening depression, while synaptic embossing was simulated by evoking LTP on selected synapses. We observed that synaptic homeostasis facilitates controlled synaptic restructuring. The results imply a mechanism for a cognitive synergy between SWS and REM, and suggest that LTP at the SWS/REM transition critically influences the effect of sleep: Its lack determines synaptic homeostasis, its presence causes synaptic restructuring. '),
(87192, 2015, 'plos', 'Maintaining homeostasis by decision-making', 'Korn, Christoph W|Bach, Dominik R', 'Department of Psychiatry, Psychotherapy, and Psychosomatics, University of Zurich, Zurich, Switzerland.|Department of Psychiatry, Psychotherapy, and Psychosomatics, University of Zurich, Zurich, Switzerland, Wellcome Trust Centre for Neuroimaging, University College London, London, United Kingdom.', 'Switzerland|Switzerland', 0, 'Adult|Algorithms|Bayes Theorem|Choice Behavior|Decision Making|Female|Gambling|Game Theory|Homeostasis|Humans|Male|Models, Biological|Probability|Software|Young Adult', 'Journal Article', '10.1371/journal.pcbi.1004301', '26024504', 'Living organisms need to maintain energetic homeostasis. For many species, this implies taking actions with delayed consequences. For example, humans may have to decide between foraging for high-calorie but hard-to-get, and low-calorie but easy-to-get food, under threat of starvation. Homeostatic principles prescribe decisions that maximize the probability of sustaining appropriate energy levels across the entire foraging trajectory. Here, predictions from biological principles contrast with predictions from economic decision-making models based on maximizing the utility of the endpoint outcome of a choice. To empirically arbitrate between the predictions of biological and economic models for individual human decision-making, we devised a virtual foraging task in which players chose repeatedly between two foraging environments, lost energy by the passage of time, and gained energy probabilistically according to the statistics of the environment they chose. Reaching zero energy was framed as starvation. We used the mathematics of random walks to derive endpoint outcome distributions of the choices. This also furnished equivalent lotteries, presented in a purely economic, casino-like frame, in which starvation corresponded to winning nothing. Bayesian model comparison showed that--in both the foraging and the casino frames--participants choices depended jointly on the probability of starvation and the expected endpoint value of the outcome, but could not be explained by economic models based on combinations of statistical moments or on rank-dependent utility. This implies that under precisely defined constraints biological principles are better suited to explain human decision-making than economic models based on endpoint utility maximization.'),
(87193, 2015, 'plos', 'Encoder-decoder optimization for brain-computer interfaces', 'Merel, Josh|Pianto, Donald M|Cunningham, John P|Paninski, Liam', 'Neurobiology and Behavior Program, Columbia University, New York, New York, United States of America.|Statistics Department, Columbia University, New York, New York, United States of America, Statistics Department, University of Brasília, Brasília, Distrito Federal, Brazil.|Statistics Department, Columbia University, New York, New York, United States of America.|Statistics Department, Columbia University, New York, New York, United States of America.', 'United States|Brazil|United States|United States', 14, 'Algorithms|Brain-Computer Interfaces|Computational Biology|Computer Simulation|Humans|Models, Neurological|Neural Prostheses|Psychophysics|Signal Processing, Computer-Assisted', 'Journal Article', '10.1371/journal.pcbi.1004288', '26029919', 'Neuroprosthetic brain-computer interfaces are systems that decode neural activity into useful control signals for effectors, such as a cursor on a computer screen. It has long been recognized that both the user and decoding system can adapt to increase the accuracy of the end effector. Co-adaptation is the process whereby a user learns to control the system in conjunction with the decoder adapting to learn the users neural patterns. We provide a mathematical framework for co-adaptation and relate co-adaptation to the joint optimization of the users control scheme (encoding model) and the decoding algorithms parameters. When the assumptions of that framework are respected, co-adaptation cannot yield better performance than that obtainable by an optimal initial choice of fixed decoder, coupled with optimal user learning. For a specific case, we provide numerical methods to obtain such an optimized decoder. We demonstrate our approach in a model brain-computer interface system using an online prosthesis simulator, a simple human-in-the-loop pyschophysics setup which provides a non-invasive simulation of the BCI setting. These experiments support two claims: that users can learn encoders matched to fixed, optimal decoders and that, once learned, our approach yields expected performance advantages. '),
(87194, 2015, 'plos', 'Differential chromosome conformations as hallmarks of cellular identity revealed by mathematical polymer modeling', 'Lassadi, Imen|Kamgouxc3xa9, Alain|Goiffon, Isabelle|Tanguy-le-Gac, Nicolas|Bystricky, Kerstin', 'University of Toulouse, UPS, Toulouse, France, Laboratoire de Biologie Molxc3xa9culaire Eucaryote, CNRS, LBME, Toulouse, France.|University of Toulouse, UPS, Toulouse, France, Laboratoire de Biologie Molxc3xa9culaire Eucaryote, CNRS, LBME, Toulouse, France.|University of Toulouse, UPS, Toulouse, France, Laboratoire de Biologie Molxc3xa9culaire Eucaryote, CNRS, LBME, Toulouse, France.|University of Toulouse, UPS, Toulouse, France, Laboratoire de Biologie Molxc3xa9culaire Eucaryote, CNRS, LBME, Toulouse, France.|University of Toulouse, UPS, Toulouse, France, Laboratoire de Biologie Molxc3xa9culaire Eucaryote, CNRS, LBME, Toulouse, France.', 'France|France|France|France|France', 0, 'Chromosome Structures|Chromosomes, Fungal|Computational Biology|Computer Simulation|Genetic Loci|Models, Genetic|Molecular Conformation|Saccharomyces cerevisiae', 'Journal Article', '10.1371/journal.pcbi.1004306', '26030148', 'Inherently dynamic, chromosomes adopt many different conformations in response to DNA metabolism. Models of chromosome organization in the yeast nucleus obtained from genome-wide chromosome conformation data or biophysical simulations provide important insights into the average behavior but fail to reveal features from dynamic or transient events that are only visible in a fraction of cells at any given moment. We developed a method to determine chromosome conformation from relative positions of three fluorescently tagged DNA in living cells imaged in 3D. Cell type specific chromosome folding properties could be assigned based on positional combinations between three loci on yeast chromosome 3. We determined that the shorter left arm of chromosome 3 is extended in MATxcexb1 cells, but can be crumpled in MATa cells. Furthermore, we implemented a new mathematical model that provides for the first time an estimate of the relative physical constraint of three linked loci related to cellular identity. Variations in this estimate allowed us to predict functional consequences from chromatin structural alterations in asf1 and recombination enhancer deletion mutant cells. The computational method is applicable to identify and characterize dynamic chromosome conformations in any cell type.'),
(87195, 2015, 'plos', 'Detailed Per-residue Energetic Analysis Explains the Driving Force for Microtubule Disassembly', 'Ayoub, Ahmed T|Klobukowski, Mariusz|Tuszynski, Jack A', 'Department of Chemistry, University of Alberta, Edmonton, Alberta, Canada.|Department of Chemistry, University of Alberta, Edmonton, Alberta, Canada.|Department of Oncology, University of Alberta, Edmonton, Alberta, Canada, Department of Physics, University of Alberta, Edmonton, Alberta, Canada.', 'Canada|Canada|Canada', 12, 'Energy Metabolism|Guanosine Diphosphate|Guanosine Triphosphate|Microtubules|Molecular Dynamics Simulation|Tubulin', 'Journal Article', '10.1371/journal.pcbi.1004313', '26030285', 'Microtubules are long filamentous hollow cylinders whose surfaces form lattice structures of xcexb1xcexb2-tubulin heterodimers. They perform multiple physiological roles in eukaryotic cells and are targets for therapeutic interventions. In our study, we carried out all-atom molecular dynamics simulations for arbitrarily long microtubules that have either GDP or GTP molecules in the E-site of xcexb2-tubulin. A detailed energy balance of the MM/GBSA inter-dimer interaction energy per residue contributing to the overall lateral and longitudinal structural stability was performed. The obtained results identified the key residues and tubulin domains according to their energetic contributions. They also identified the molecular forces that drive microtubule disassembly. At the tip of the plus end of the microtubule, the uneven distribution of longitudinal interaction energies within a protofilament generates a torque that bends tubulin outwardly with respect to the cylinders axis causing disassembly. In the presence of GTP, this torque is opposed by lateral interactions that prevent outward curling, thus stabilizing the whole microtubule. Once GTP hydrolysis reaches the tip of the microtubule (lateral cap), lateral interactions become much weaker, allowing tubulin dimers to bend outwards, causing disassembly. The role of magnesium in the process of outward curling has also been demonstrated. This study also showed that the microtubule seam is the most energetically labile inter-dimer interface and could serve as a trigger point for disassembly. Based on a detailed balance of the energetic contributions per amino acid residue in the microtubule, numerous other analyses could be performed to give additional insights into the properties of microtubule dynamic instability. '),
(87196, 2015, 'plos', 'Measuring Fisher information accurately in correlated neural populations', 'Kanitscheider, Ingmar|Coen-Cagli, Ruben|Kohn, Adam|Pouget, Alexandre', 'Department of Basic Neuroscience, University of Geneva, Geneva, Switzerland, Center of Learning and Memory and Department of Neuroscience, The University of Texas at Austin, Austin, Texas, United States of America.|Department of Basic Neuroscience, University of Geneva, Geneva, Switzerland.|Dominick Purpura Department of Neuroscience Albert Einstein College of Medicine, Bronx, New York, United States of America, Department of Ophthalmology and Visual Sciences, Albert Einstein College of Medicine, Bronx, New York, United States of America.|Department of Basic Neuroscience, University of Geneva, Geneva, Switzerland, Department of Brain and Cognitive Sciences, University of Rochester, Rochester, New York, United States of America, Gatsby Computational Neuroscience Unit, London, United Kingdom.', 'Switzerland|Switzerland|United States|Switzerland', 0, 'Animals|Computational Biology|Computer Simulation|Macaca|Male|Models, Neurological|Models, Statistical|Neurons|Visual Cortex', 'Journal Article', '10.1371/journal.pcbi.1004218', '26030735', 'Neural responses are known to be variable. In order to understand how this neural variability constrains behavioral performance, we need to be able to measure the reliability with which a sensory stimulus is encoded in a given population. However, such measures are challenging for two reasons: First, they must take into account noise correlations which can have a large influence on reliability. Second, they need to be as efficient as possible, since the number of trials available in a set of neural recording is usually limited by experimental constraints. Traditionally, cross-validated decoding has been used as a reliability measure, but it only provides a lower bound on reliability and underestimates reliability substantially in small datasets. We show that, if the number of trials per condition is larger than the number of neurons, there is an alternative, direct estimate of reliability which consistently leads to smaller errors and is much faster to compute. The superior performance of the direct estimator is evident both for simulated data and for neuronal population recordings from macaque primary visual cortex. Furthermore we propose generalizations of the direct estimator which measure changes in stimulus encoding across conditions and the impact of correlations on encoding and decoding, typically denoted by Ishuffle and Idiag respectively. '),
(87197, 2015, 'plos', 'Accurate encoding and decoding by single cells: amplitude versus frequency modulation', 'Micali, Gabriele|Aquino, Gerardo|Richards, David M|Endres, Robert G', 'Department of Life Sciences, Imperial College, London, United Kingdom, Centre for Integrative Systems Biology and Bioinformatics, Imperial College, London, United Kingdom, Dipartimento di Fisica, Università degli Studi di Milano, Milano, Italy.|Department of Life Sciences, Imperial College, London, United Kingdom, Centre for Integrative Systems Biology and Bioinformatics, Imperial College, London, United Kingdom.|Department of Life Sciences, Imperial College, London, United Kingdom, Centre for Integrative Systems Biology and Bioinformatics, Imperial College, London, United Kingdom.|Department of Life Sciences, Imperial College, London, United Kingdom, Centre for Integrative Systems Biology and Bioinformatics, Imperial College, London, United Kingdom.', 'United Kingdom|United Kingdom|United Kingdom|United Kingdom', 14, 'Cell Communication|Computational Biology|Ion Channels|Models, Biological|Receptors, Cytoplasmic and Nuclear', 'Journal Article', '10.1371/journal.pcbi.1004222', '26030820', 'Cells sense external concentrations and, via biochemical signaling, respond by regulating the expression of target proteins. Both in signaling networks and gene regulation there are two main mechanisms by which the concentration can be encoded internally: amplitude modulation (AM), where the absolute concentration of an internal signaling molecule encodes the stimulus, and frequency modulation (FM), where the period between successive bursts represents the stimulus. Although both mechanisms have been observed in biological systems, the question of when it is beneficial for cells to use either AM or FM is largely unanswered. Here, we first consider a simple model for a single receptor (or ion channel), which can either signal continuously whenever a ligand is bound, or produce a burst in signaling molecule upon receptor binding. We find that bursty signaling is more accurate than continuous signaling only for sufficiently fast dynamics. This suggests that modulation based on bursts may be more common in signaling networks than in gene regulation. We then extend our model to multiple receptors, where continuous and bursty signaling are equivalent to AM and FM respectively, finding that AM is always more accurate. This implies that the reason some cells use FM is related to factors other than accuracy, such as the ability to coordinate expression of multiple genes or to implement threshold crossing mechanisms. '),
(87198, 2015, 'plos', 'Inferring regulatory networks from experimental morphological phenotypes: a computational method reverse-engineers planarian regeneration', 'Lobo, Daniel|Levin, Michael', 'Center for Regenerative and Developmental Biology, Department of Biology, Tufts University, Medford, Massachusetts, United States of America.|Center for Regenerative and Developmental Biology, Department of Biology, Tufts University, Medford, Massachusetts, United States of America.', 'United States|United States', 49, 'Animals|Computational Biology|Gene Regulatory Networks|Models, Biological|Phenotype|Planarians|Regeneration', 'Journal Article', '10.1371/journal.pcbi.1004295', '26042810', 'Transformative applications in biomedicine require the discovery of complex regulatory networks that explain the development and regeneration of anatomical structures, and reveal what external signals will trigger desired changes of large-scale pattern. Despite recent advances in bioinformatics, extracting mechanistic pathway models from experimental morphological data is a key open challenge that has resisted automation. The fundamental difficulty of manually predicting emergent behavior of even simple networks has limited the models invented by human scientists to pathway diagrams that show necessary subunit interactions but do not reveal the dynamics that are sufficient for complex, self-regulating pattern to emerge. To finally bridge the gap between high-resolution genetic data and the ability to understand and control patterning, it is critical to develop computational tools to efficiently extract regulatory pathways from the resultant experimental shape phenotypes. For example, planarian regeneration has been studied for over a century, but despite increasing insight into the pathways that control its stem cells, no constructive, mechanistic model has yet been found by human scientists that explains more than one or two key features of its remarkable ability to regenerate its correct anatomical pattern after drastic perturbations. We present a method to infer the molecular products, topology, and spatial and temporal non-linear dynamics of regulatory networks recapitulating in silico the rich dataset of morphological phenotypes resulting from genetic, surgical, and pharmacological experiments. We demonstrated our approach by inferring complete regulatory networks explaining the outcomes of the main functional regeneration experiments in the planarian literature, By analyzing all the datasets together, our system inferred the first systems-biology comprehensive dynamical model explaining patterning in planarian regeneration. This method provides an automated, highly generalizable framework for identifying the underlying control mechanisms responsible for the dynamic regulation of growth and form. '),
(87199, 2015, 'plos', 'Particle Simulation of Oxidation Induced Band 3 Clustering in Human Erythrocytes', 'Shimo, Hanae|Arjunan, Satya Nanda Vel|Machiyama, Hiroaki|Nishino, Taiko|Suematsu, Makoto|Fujita, Hideaki|Tomita, Masaru|Takahashi, Koichi', 'Laboratory for Biochemical Simulation, RIKEN Quantitative Biology Center, Osaka, Japan, Department of Biochemistry, School of Medicine, Keio University, Shinjuku, Tokyo, Japan.|Laboratory for Biochemical Simulation, RIKEN Quantitative Biology Center, Osaka, Japan.|Laboratory for Biochemical Simulation, RIKEN Quantitative Biology Center, Osaka, Japan, Immunology Frontier Research Center, Osaka University, Osaka, Japan.|Institute for Advanced Biosciences, Keio University, Tsuruoka, Yamagata, Japan.|Department of Biochemistry, School of Medicine, Keio University, Shinjuku, Tokyo, Japan, Institute for Advanced Biosciences, Keio University, Tsuruoka, Yamagata, Japan.|Laboratory for Biochemical Simulation, RIKEN Quantitative Biology Center, Osaka, Japan, Immunology Frontier Research Center, Osaka University, Osaka, Japan.|Institute for Advanced Biosciences, Keio University, Tsuruoka, Yamagata, Japan, Department of Environment and Information Studies, Keio University, Fujisawa, Kanagawa, Japan.|Laboratory for Biochemical Simulation, RIKEN Quantitative Biology Center, Osaka, Japan, Institute for Advanced Biosciences, Keio University, Tsuruoka, Yamagata, Japan.', 'Japan|Japan|Japan|Japan|Japan|Japan|Japan|Japan', 0, 'Anion Exchange Protein 1, Erythrocyte|Computational Biology|Erythrocyte Membrane|Erythrocytes|Humans|Models, Biological|Oxidation-Reduction', 'Journal Article', '10.1371/journal.pcbi.1004210', '26046580', 'Oxidative stress mediated clustering of membrane protein band 3 plays an essential role in the clearance of damaged and aged red blood cells (RBCs) from the circulation. While a number of previous experimental studies have observed changes in band 3 distribution after oxidative treatment, the details of how these clusters are formed and how their properties change under different conditions have remained poorly understood. To address these issues, a framework that enables the simultaneous monitoring of the temporal and spatial changes following oxidation is needed. In this study, we established a novel simulation strategy that incorporates deterministic and stochastic reactions with particle reaction-diffusion processes, to model band 3 cluster formation at single molecule resolution. By integrating a kinetic model of RBC antioxidant metabolism with a model of band 3 diffusion, we developed a model that reproduces the time-dependent changes of glutathione and clustered band 3 levels, as well as band 3 distribution during oxidative treatment, observed in prior studies. We predicted that cluster formation is largely dependent on fast reverse reaction rates, strong affinity between clustering molecules, and irreversible hemichrome binding. We further predicted that under repeated oxidative perturbations, clusters tended to progressively grow and shift towards an irreversible state. Application of our model to simulate oxidation in RBCs with cytoskeletal deficiency also suggested that oxidation leads to more enhanced clustering compared to healthy RBCs. Taken together, our model enables the prediction of band 3 spatio-temporal profiles under various situations, thus providing valuable insights to potentially aid understanding mechanisms for removing senescent and premature RBCs. '),
(87200, 2015, 'plos', 'Large-Scale Conformational Transitions and Dimerization Are Encoded in the Amino-Acid Sequences of Hsp70 Chaperones', 'Malinverni, Duccio|Marsili, Simone|Barducci, Alessandro|De Los Rios, Paolo', 'Laboratoire de Biophysique Statistique, École Polytechnique Fédérale de Lausanne, Faculté de Sciences de Base, Lausanne, Switzerland.|Structural Computational Biology Group, Spanish National Cancer Research Centre (CNIO), Madrid, Spain.|Laboratoire de Biophysique Statistique, École Polytechnique Fédérale de Lausanne, Faculté de Sciences de Base, Lausanne, Switzerland.|Laboratoire de Biophysique Statistique, École Polytechnique Fédérale de Lausanne, Faculté de Sciences de Base, Lausanne, Switzerland.', 'Switzerland|Spain|Switzerland|Switzerland', 0, 'Amino Acid Sequence|Animals|Cattle|Dimerization|Fungal Proteins|HSP70 Heat-Shock Proteins|Humans|Models, Molecular|Sequence Alignment', 'Journal Article', '10.1371/journal.pcbi.1004262', '26046683', 'Hsp70s are a class of ubiquitous and highly conserved molecular chaperones playing a central role in the regulation of proteostasis in the cell. Hsp70s assist a myriad of cellular processes by binding unfolded or misfolded substrates during a complex biochemical cycle involving large-scale structural rearrangements. Here we show that an analysis of coevolution at the residue level fully captures the characteristic large-scale conformational transitions of this protein family, and predicts an evolutionary conserved-and thus functional-homo-dimeric arrangement. Furthermore, we highlight that the features encoding the Hsp70 dimer are more conserved in bacterial than in eukaryotic sequences, suggesting that the known Hsp70/Hsp110 hetero-dimer is a eukaryotic specialization built on a pre-existing template. '),
(87201, 2015, 'plos', 'Energy Efficient Sparse Connectivity from Imbalanced Synaptic Plasticity Rules', 'Sacramento, João|Wichert, Andreas|van Rossum, Mark C W', 'INESC-ID & Instituto Superior Técnico, Universidade de Lisboa, Porto Salvo, Portugal.|INESC-ID & Instituto Superior Técnico, Universidade de Lisboa, Porto Salvo, Portugal.|Institute for Adaptive and Neural Computation, School of Informatics, University of Edinburgh, Edinburgh, United Kingdom.', 'Portugal|Portugal|United Kingdom', 0, 'Cerebellum|Humans|Models, Neurological|Nerve Net|Neuronal Plasticity|Neurons', 'Journal Article', '10.1371/journal.pcbi.1004265', '26046817', 'It is believed that energy efficiency is an important constraint in brain evolution. As synaptic transmission dominates energy consumption, energy can be saved by ensuring that only a few synapses are active. It is therefore likely that the formation of sparse codes and sparse connectivity are fundamental objectives of synaptic plasticity. In this work we study how sparse connectivity can result from a synaptic learning rule of excitatory synapses. Information is maximised when potentiation and depression are balanced according to the mean presynaptic activity level and the resulting fraction of zero-weight synapses is around 50%. However, an imbalance towards depression increases the fraction of zero-weight synapses without significantly affecting performance. We show that imbalanced plasticity corresponds to imposing a regularising constraint on the L1-norm of the synaptic weight vector, a procedure that is well-known to induce sparseness. Imbalanced plasticity is biophysically plausible and leads to more efficient synaptic configurations than a previously suggested approach that prunes synapses after learning. Our framework gives a novel interpretation to the high fraction of silent synapses found in brain regions like the cerebellum. '),
(87202, 2015, 'plos', 'Elucidation of Ligand-Dependent Modulation of Disorder-Order Transitions in the Oncoprotein MDM2', 'Bueren-Calabuig, Juan A|Michel, Julien', 'EaStCHEM School of Chemistry, the University of Edinburgh, Edinburgh, United Kingdom.|EaStCHEM School of Chemistry, the University of Edinburgh, Edinburgh, United Kingdom.', 'United Kingdom|United Kingdom', 9, 'Humans|Hydrophobic and Hydrophilic Interactions|Ligands|Molecular Dynamics Simulation|Protein Binding|Protein Conformation|Proto-Oncogene Proteins c-mdm2|Tumor Suppressor Protein p53', 'Journal Article', '10.1371/journal.pcbi.1004282', '26046940', 'Numerous biomolecular interactions involve unstructured protein regions, but how to exploit such interactions to enhance the affinity of a lead molecule in the context of rational drug design remains uncertain. Here clarification was sought for cases where interactions of different ligands with the same disordered protein region yield qualitatively different results. Specifically, conformational ensembles for the disordered lid region of the N-terminal domain of the oncoprotein MDM2 in the presence of different ligands were computed by means of a novel combination of accelerated molecular dynamics, umbrella sampling, and variational free energy profile methodologies. The resulting conformational ensembles for MDM2, free and bound to p53 TAD (17-29) peptide identify lid states compatible with previous NMR measurements. Remarkably, the MDM2 lid region is shown to adopt distinct conformational states in the presence of different small-molecule ligands. Detailed analyses of small-molecule bound ensembles reveal that the ca. 25-fold affinity improvement of the piperidinone family of inhibitors for MDM2 constructs that include the full lid correlates with interactions between ligand hydrophobic groups and the C-terminal lid region that is already partially ordered in apo MDM2. By contrast, Nutlin or benzodiazepinedione inhibitors, that bind with similar affinity to full lid and lid-truncated MDM2 constructs, interact additionally through their solubilizing groups with N-terminal lid residues that are more disordered in apo MDM2. '),
(87203, 2015, 'plos', 'Disease Interventions Can Interfere with One Another through Disease-Behaviour Interactions', 'Andrews, Michael A|Bauch, Chris T', 'Department of Mathematics and Statistics, University of Guelph, Guelph, Ontario, Canada.|Department of Mathematics and Statistics, University of Guelph, Guelph, Ontario, Canada, Department of Applied Mathematics, University of Waterloo, Waterloo, Ontario, Canada.', 'Canada|Canada', 0, 'Computational Biology|Disease Outbreaks|Health Behavior|Humans|Influenza Vaccines|Influenza, Human|Models, Biological|Models, Statistical|Vaccination', 'Journal Article', '10.1371/journal.pcbi.1004291', '26047028', 'Theoretical models of disease dynamics on networks can aid our understanding of how infectious diseases spread through a population. Models that incorporate decision-making mechanisms can furthermore capture how behaviour-driven aspects of transmission such as vaccination choices and the use of non-pharmaceutical interventions (NPIs) interact with disease dynamics. However, these two interventions are usually modelled separately. Here, we construct a simulation model of influenza transmission through a contact network, where individuals can choose whether to become vaccinated and/or practice NPIs. These decisions are based on previous experience with the disease, the current state of infection amongst ones contacts, and the personal and social impacts of the choices they make. We find that the interventions interfere with one another: because of negative feedback between intervention uptake and infection prevalence, it is difficult to simultaneously increase uptake of all interventions by changing utilities or perceived risks. However, on account of vaccine efficacy being higher than NPI efficacy, measures to expand NPI practice have only a small net impact on influenza incidence due to strongly mitigating feedback from vaccinating behaviour, whereas expanding vaccine uptake causes a significant net reduction in influenza incidence, despite the reduction of NPI practice in response. As a result, measures that support expansion of only vaccination (such as reducing vaccine cost), or measures that simultaneously support vaccination and NPIs (such as emphasizing harms of influenza infection, or satisfaction from preventing infection in others through both interventions) can significantly reduce influenza incidence, whereas measures that only support expansion of NPI practice (such as making hand sanitizers more available) have little net impact on influenza incidence. (However, measures that improve NPI efficacy may fare better.) We conclude that the impact of interference on programs relying on multiple interventions should be more carefully studied, for both influenza and other infectious diseases. '),
(87204, 2015, 'plos', 'Monte Carlo Planning Method Estimates Planning Horizons during Interactive Social Exchange', 'Hula, Andreas|Montague, P Read|Dayan, Peter', 'Wellcome Trust Centre for Neuroimaging, University College London, London, United Kingdom.|Wellcome Trust Centre for Neuroimaging, University College London, London, United Kingdom, Human Neuroimaging Laboratory, Virginia Tech Carilion Research Institute, Roanoke, Virginia, United States of America, Department of Physics, Virginia Polytechnic Institute and State University, Blacksburg, Virginia, United States of America.|Gatsby Computational Neuroscience Unit, University College London, London, United Kingdom.', 'United Kingdom|United Kingdom|United Kingdom', 0, 'Algorithms|Computational Biology|Decision Making|Humans|Interpersonal Relations|Markov Chains|Models, Biological|Monte Carlo Method|Psychological Theory|Reward|Trust', 'Journal Article', '10.1371/journal.pcbi.1004254', '26053429', 'Reciprocating interactions represent a central feature of all human exchanges. They have been the target of various recent experiments, with healthy participants and psychiatric populations engaging as dyads in multi-round exchanges such as a repeated trust task. Behaviour in such exchanges involves complexities related to each agents preference for equity with their partner, beliefs about the partners appetite for equity, beliefs about the partners model of their partner, and so on. Agents may also plan different numbers of steps into the future. Providing a computationally precise account of the behaviour is an essential step towards understanding what underlies choices. A natural framework for this is that of an interactive partially observable Markov decision process (IPOMDP). However, the various complexities make IPOMDPs inordinately computationally challenging. Here, we show how to approximate the solution for the multi-round trust task using a variant of the Monte-Carlo tree search algorithm. We demonstrate that the algorithm is efficient and effective, and therefore can be used to invert observations of behavioural choices. We use generated behaviour to elucidate the richness and sophistication of interactive inference. '),
(87205, 2015, 'plos', 'Alternatively Spliced Homologous Exons Have Ancient Origins and Are Highly Expressed at the Protein Level', 'Abascal, Federico|Ezkurdia, Iakes|Rodriguez-Rivas, Juan|Rodriguez, Jose Manuel|del Pozo, Angela|Vázquez, Jesús|Valencia, Alfonso|Tress, Michael L', 'Structural Biology and Bioinformatics Programme, Spanish National Cancer Research Centre (CNIO), Madrid, Spain.|Unidad de Proteómica, Centro Nacional de Investigaciones Cardiovasculares (CNIC), Madrid, Spain.|Structural Biology and Bioinformatics Programme, Spanish National Cancer Research Centre (CNIO), Madrid, Spain.|National Bioinformatics Institute (INB), Spanish National Cancer Research Centre (CNIO), Madrid, Spain.|Instituto de Genetica Medica y Molecular, Hospital Universitario La Paz, Madrid, Spain.|Laboratorio de Proteómica Cardiovascular, Centro Nacional de Investigaciones Cardiovasculares (CNIC) Madrid, Spain.|Structural Biology and Bioinformatics Programme, Spanish National Cancer Research Centre (CNIO), Madrid, Spain, National Bioinformatics Institute (INB), Spanish National Cancer Research Centre (CNIO), Madrid, Spain.|Structural Biology and Bioinformatics Programme, Spanish National Cancer Research Centre (CNIO), Madrid, Spain.', 'Spain|Spain|Spain|Spain|Spain|Spain|Spain|Spain', 28, 'Alternative Splicing|Amino Acid Sequence|Animals|Computational Biology|Databases, Genetic|Exons|Humans|Mice|Models, Molecular|Molecular Sequence Data|Organ Specificity|Peptides|Protein Conformation|Protein Isoforms|Sequence Alignment|Sequence Analysis, DNA', 'Journal Article', '10.1371/journal.pcbi.1004325', '26061177', 'Alternative splicing of messenger RNA can generate a wide variety of mature RNA transcripts, and these transcripts may produce protein isoforms with diverse cellular functions. While there is much supporting evidence for the expression of alternative transcripts, the same is not true for the alternatively spliced protein products. Large-scale mass spectroscopy experiments have identified evidence of alternative splicing at the protein level, but with conflicting results. Here we carried out a rigorous analysis of the peptide evidence from eight large-scale proteomics experiments to assess the scale of alternative splicing that is detectable by high-resolution mass spectroscopy. We find fewer splice events than would be expected: we identified peptides for almost 64% of human protein coding genes, but detected just 282 splice events. This data suggests that most genes have a single dominant isoform at the protein level. Many of the alternative isoforms that we could identify were only subtly different from the main splice isoform. Very few of the splice events identified at the protein level disrupted functional domains, in stark contrast to the two thirds of splice events annotated in the human genome that would lead to the loss or damage of functional domains. The most striking result was that more than 20% of the splice isoforms we identified were generated by substituting one homologous exon for another. This is significantly more than would be expected from the frequency of these events in the genome. These homologous exon substitution events were remarkably conserved--all the homologous exons we identified evolved over 460 million years ago--and eight of the fourteen tissue-specific splice isoforms we identified were generated from homologous exons. The combination of proteomics evidence, ancient origin and tissue-specific splicing indicates that isoforms generated from homologous exons may have important cellular roles.'),
(87206, 2015, 'plos', 'Site-Specific Phosphorylation of VEGFR2 Is Mediated by Receptor Trafficking: Insights from a Computational Model', 'Clegg, Lindsay Wendel|Mac Gabhann, Feilim', 'Institute for Computational Medicine and Department of Biomedical Engineering, Johns Hopkins University, Baltimore, Maryland, United States of America.|Institute for Computational Medicine and Department of Biomedical Engineering, Johns Hopkins University, Baltimore, Maryland, United States of America, Department of Materials Science and Engineering, Johns Hopkins University, Baltimore, Maryland, United States of America.', 'United States|United States', 38, 'Animals|Biological Transport|Computational Biology|Endosomes|Humans|Mice|Models, Biological|Neuropilin-1|Phosphorylation|Vascular Endothelial Growth Factor A', 'Journal Article', '10.1371/journal.pcbi.1004158', '26067165', 'Matrix-binding isoforms and non-matrix-binding isoforms of vascular endothelial growth factor (VEGF) are both capable of stimulating vascular remodeling, but the resulting blood vessel networks are structurally and functionally different. Here, we develop and validate a computational model of the binding of soluble and immobilized ligands to VEGF receptor 2 (VEGFR2), the endosomal trafficking of VEGFR2, and site-specific VEGFR2 tyrosine phosphorylation to study differences in induced signaling between these VEGF isoforms. In capturing essential features of VEGFR2 signaling and trafficking, our model suggests that VEGFR2 trafficking parameters are largely consistent across multiple endothelial cell lines. Simulations demonstrate distinct localization of VEGFR2 phosphorylated on Y1175 and Y1214. This is the first model to clearly show that differences in site-specific VEGFR2 activation when stimulated with immobilized VEGF compared to soluble VEGF can be accounted for by altered trafficking of VEGFR2 without an intrinsic difference in receptor activation. The model predicts that Neuropilin-1 can induce differences in the surface-to-internal distribution of VEGFR2. Simulations also show that ligated VEGFR2 and phosphorylated VEGFR2 levels diverge over time following stimulation. Using this model, we identify multiple key levers that alter how VEGF binding to VEGFR2 results in different coordinated patterns of multiple downstream signaling pathways. Specifically, simulations predict that VEGF immobilization, interactions with Neuropilin-1, perturbations of VEGFR2 trafficking, and changes in expression or activity of phosphatases acting on VEGFR2 all affect the magnitude, duration, and relative strength of VEGFR2 phosphorylation on tyrosines 1175 and 1214, and they do so predictably within our single consistent model framework. '),
(87207, 2015, 'plos', 'Cooperative DNA Recognition Modulated by an Interplay between Protein-Protein Interactions and DNA-Mediated Allostery', 'Merino, Felipe|Bouvier, Benjamin|Cojocaru, Vlad', 'Computational Structural Biology Group, Department of Cell and Developmental Biology, Max Planck Institute for Molecular Biomedicine, Münster, Germany, Center for Multiscale Theory and Computation, Westfälische Wilhelms University, Münster, Germany.|Bioinformatics: Structures and Interactions, Bases Moléculaires et Structurales des Systèmes Infectieux, Univ. Lyon I/CNRS UMR5086, IBCP, Lyon, France.|Computational Structural Biology Group, Department of Cell and Developmental Biology, Max Planck Institute for Molecular Biomedicine, Münster, Germany, Center for Multiscale Theory and Computation, Westfälische Wilhelms University, Münster, Germany.', 'Germany|France|Germany', 16, 'Allosteric Regulation|DNA|Molecular Dynamics Simulation|Octamer Transcription Factor-3|Pluripotent Stem Cells|Protein Binding|SOXB1 Transcription Factors', 'Journal Article', '10.1371/journal.pcbi.1004287', '26067358', 'Highly specific transcriptional regulation depends on the cooperative association of transcription factors into enhanceosomes. Usually, their DNA-binding cooperativity originates from either direct interactions or DNA-mediated allostery. Here, we performed unbiased molecular simulations followed by simulations of protein-DNA unbinding and free energy profiling to study the cooperative DNA recognition by OCT4 and SOX2, key components of enhanceosomes in pluripotent cells. We found that SOX2 influences the orientation and dynamics of the DNA-bound configuration of OCT4. In addition SOX2 modifies the unbinding free energy profiles of both DNA-binding domains of OCT4, the POU specific and POU homeodomain, despite interacting directly only with the first. Thus, we demonstrate that the OCT4-SOX2 cooperativity is modulated by an interplay between protein-protein interactions and DNA-mediated allostery. Further, we estimated the change in OCT4-DNA binding free energy due to the cooperativity with SOX2, observed a good agreement with experimental measurements, and found that SOX2 affects the relative DNA-binding strength of the two OCT4 domains. Based on these findings, we propose that available interaction partners in different biological contexts modulate the DNA exploration routes of multi-domain transcription factors such as OCT4. We consider the OCT4-SOX2 cooperativity as a paradigm of how specificity of transcriptional regulation is achieved through concerted modulation of protein-DNA recognition by different types of interactions. ');
INSERT INTO `papers` (`id`, `ano`, `journal`, `titulo`, `autores`, `afiliacao`, `pais`, `citacoes`, `palavra_chave`, `categorias`, `doi`, `pubmed`, `abstract`) VALUES
(87208, 2015, 'plos', 'Behavioural Contagion Explains Group Cohesion in a Social Crustacean', 'Broly, Pierre|Deneubourg, Jean-Louis', 'Unité dEcologie Sociale, Université Libre de Bruxelles, Campus de la Plaine, Bruxelles, Belgium, Laboratoire Ecologie et Biodiversité, Faculté de Gestion, Economie & Science, UCLILLE, Université Lille Nord de France, Lille, France.|Unité dEcologie Sociale, Université Libre de Bruxelles, Campus de la Plaine, Bruxelles, Belgium.', 'Belgium|Belgium', 8, 'Animals|Behavior, Animal|Computational Biology|Isopoda|Models, Biological|Social Behavior', 'Journal Article', '10.1371/journal.pcbi.1004290', '26067565', 'In gregarious species, social interactions maintain group cohesion and the associated adaptive values of group living. The understanding of mechanisms leading to group cohesion is essential for understanding the collective dynamics of groups and the spatio-temporal distribution of organisms in environment. In this view, social aggregation in terrestrial isopods represents an interesting model due to its recurrence both in the field and in the laboratory. In this study, and under a perturbation context, we experimentally tested the stability of groups of woodlice according to group size and time spent in group. Our results indicate that the response to the disturbance of groups decreases with increases in these two variables. Models neglecting social effects cannot reproduce experimental data, attesting that cohesion of aggregation in terrestrial isopods is partly governed by a social effect. In particular, models involving calmed and excited individuals and a social transition between these two behavioural states more accurately reproduced our experimental data. Therefore, we concluded that group cohesion (and collective response to stimulus) in terrestrial isopods is governed by a transitory resting state under the influence of density of conspecifics and time spent in group. Lastly, we discuss the nature of direct or indirect interactions possibly implicated. '),
(87209, 2015, 'plos', 'The Physiological Molecular Shape of Spectrin: A Compact Supercoil Resembling a Chinese Finger Trap', 'Brown, Jeffrey W|Bullitt, Esther|Sriswasdi, Sira|Harper, Sandra|Speicher, David W|McKnight, C James', 'Department of Physiology and Biophysics, Boston University School of Medicine, Boston, Massachusetts, United States of America, Internal Medicine Residency Program, University of Pittsburgh Medical Center, UPMC Montefiore Hospital, Pittsburgh, Pennsylvania, United States of America.|Department of Physiology and Biophysics, Boston University School of Medicine, Boston, Massachusetts, United States of America.|Center for Systems and Computational Biology, and Molecular and Cellular Oncogenesis Program, the Wistar Institute, Philadelphia, Pennsylvania, United States of America, Genomics and Computational Biology Graduate Group, University of Pennsylvania, Philadelphia, Pennsylvania, United States of America.|Center for Systems and Computational Biology, and Molecular and Cellular Oncogenesis Program, the Wistar Institute, Philadelphia, Pennsylvania, United States of America.|Center for Systems and Computational Biology, and Molecular and Cellular Oncogenesis Program, the Wistar Institute, Philadelphia, Pennsylvania, United States of America, Genomics and Computational Biology Graduate Group, University of Pennsylvania, Philadelphia, Pennsylvania, United States of America.|Department of Physiology and Biophysics, Boston University School of Medicine, Boston, Massachusetts, United States of America.', 'United States|United States|United States|United States|United States|United States', 15, 'Crystallography, X-Ray|Humans|Models, Molecular|Protein Conformation|Spectrin', 'Journal Article', '10.1371/journal.pcbi.1004302', '26067675', 'The primary, secondary, and tertiary structures of spectrin are reasonably well defined, but the structural basis for the known dramatic molecular shape change, whereby the molecular length can increase three-fold, is not understood. In this study, we combine previously reported biochemical and high-resolution crystallographic data with structural mass spectroscopy and electron microscopic data to derive a detailed, experimentally-supported quaternary structure of the spectrin heterotetramer. In addition to explaining spectrins physiological resting length of ~55-65 nm, our model provides a mechanism by which spectrin is able to undergo a seamless three-fold extension while remaining a linear filament, an experimentally observed property. According to the proposed model, spectrins quaternary structure and mechanism of extension is similar to a Chinese Finger Trap: at shorter molecular lengths spectrin is a hollow cylinder that extends by increasing the pitch of each spectrin repeat, which decreases the internal diameter. We validated our model with electron microscopy, which demonstrated that, as predicted, spectrin is hollow at its biological resting length of ~55-65 nm. The model is further supported by zero-length chemical crosslink data indicative of an approximately 90 degree bend between adjacent spectrin repeats. The domain-domain interactions in our model are entirely consistent with those present in the prototypical linear antiparallel heterotetramer as well as recently reported inter-strand chemical crosslinks. The model is consistent with all known physical properties of spectrin, and upon full extension our Chinese Finger Trap Model reduces to the ~180-200 nm molecular model currently in common use. '),
(87210, 2015, 'plos', '2015 ISCB Overton Prize Awarded to Curtis Huttenhower', 'Fogg, Christiana N|Kovats, Diane E', 'Freelance Science Writer, Kensington, Maryland, United States of America.|International Society for Computational Biology, La Jolla, California, United States of America.', 'United States|United States', 0, 'Awards and Prizes|Computational Biology|Humans|United States', 'Journal Article', '10.1371/journal.pcbi.1004319', '26067840', '-'),
(87211, 2015, 'plos', 'Stochastic Dynamics Underlying Cognitive Stability and Flexibility', 'Ueltzhöffer, Kai|Armbruster-Genç, Diana J N|Fiebach, Christian J', 'Department of Psychology, Goethe University Frankfurt, Frankfurt am Main, Germany, Bernstein Center for Computational Neuroscience, Heidelberg University, Mannheim, Germany.|Department of Psychology, Goethe University Frankfurt, Frankfurt am Main, Germany, Bernstein Center for Computational Neuroscience, Heidelberg University, Mannheim, Germany.|Department of Psychology, Goethe University Frankfurt, Frankfurt am Main, Germany, Bernstein Center for Computational Neuroscience, Heidelberg University, Mannheim, Germany, Department of Neuroradiology, Heidelberg University, Im Neuenheimer Feld, Heidelberg, Germany, Donders Institute for Brain, Cognition and Behaviour, Radboud University, Nijmegen, The Netherlands, IDeA Center for Individual Development and Adaptive Education, Frankfurt am Main, Germany.', 'Germany|Germany|Germany', 13, 'Adult|Brain|Brain Mapping|Cognition|Computational Biology|Female|Humans|Magnetic Resonance Imaging|Male|Memory, Short-Term|Models, Neurological|Reaction Time|Task Performance and Analysis|Young Adult', 'Journal Article', '10.1371/journal.pcbi.1004331', '26068119', 'Cognitive stability and flexibility are core functions in the successful pursuit of behavioral goals. While there is evidence for a common frontoparietal network underlying both functions and for a key role of dopamine in the modulation of flexible versus stable behavior, the exact neurocomputational mechanisms underlying those executive functions and their adaptation to environmental demands are still unclear. In this work we study the neurocomputational mechanisms underlying cue based task switching (flexibility) and distractor inhibition (stability) in a paradigm specifically designed to probe both functions. We develop a physiologically plausible, explicit model of neural networks that maintain the currently active task rule in working memory and implement the decision process. We simplify the four-choice decision network to a nonlinear drift-diffusion process that we canonically derive from a generic winner-take-all network model. By fitting our model to the behavioral data of individual subjects, we can reproduce their full behavior in terms of decisions and reaction time distributions in baseline as well as distractor inhibition and switch conditions. Furthermore, we predict the individual hemodynamic response timecourse of the rule-representing network and localize it to a frontoparietal network including the inferior frontal junction area and the intraparietal sulcus, using functional magnetic resonance imaging. This refines the understanding of task-switch-related frontoparietal brain activity as reflecting attractor-like working memory representations of task rules. Finally, we estimate the subject-specific stability of the rule-representing attractor states in terms of the minimal action associated with a transition between different rule states in the phase-space of the fitted models. This stability measure correlates with switching-specific thalamocorticostriatal activation, i.e., with a system associated with flexible working memory updating and dopaminergic modulation of cognitive flexibility. These results show that stochastic dynamical systems can implement the basic computations underlying cognitive stability and flexibility and explain neurobiological bases of individual differences. '),
(87212, 2015, 'plos', 'The Sense of Confidence during Probabilistic Learning: A Normative Account', 'Meyniel, Florent|Schlunegger, Daniel|Dehaene, Stanislas', 'Cognitive Neuroimaging Unit, U992, INSERM, Gif/Yvette, France, NeuroSpin Center, DSV/I2BM, CEA, Gif/Yvette, France.|Cognitive Neuroimaging Unit, U992, INSERM, Gif/Yvette, France, NeuroSpin Center, DSV/I2BM, CEA, Gif/Yvette, France.|Cognitive Neuroimaging Unit, U992, INSERM, Gif/Yvette, France, NeuroSpin Center, DSV/I2BM, CEA, Gif/Yvette, France, Collège de France, Paris, France.', 'France|France|France', 51, 'Adult|Algorithms|Computational Biology|Female|Humans|Learning|Male|Models, Neurological|Models, Statistical|Task Performance and Analysis|Uncertainty|Young Adult', 'Journal Article', '10.1371/journal.pcbi.1004305', '26076466', 'Learning in a stochastic environment consists of estimating a model from a limited amount of noisy data, and is therefore inherently uncertain. However, many classical models reduce the learning process to the updating of parameter estimates and neglect the fact that learning is also frequently accompanied by a variable feeling of knowing or confidence. The characteristics and the origin of these subjective confidence estimates thus remain largely unknown. Here we investigate whether, during learning, humans not only infer a model of their environment, but also derive an accurate sense of confidence from their inferences. In our experiment, humans estimated the transition probabilities between two visual or auditory stimuli in a changing environment, and reported their mean estimate and their confidence in this report. To formalize the link between both kinds of estimate and assess their accuracy in comparison to a normative reference, we derive the optimal inference strategy for our task. Our results indicate that subjects accurately track the likelihood that their inferences are correct. Learning and estimating confidence in what has been learned appear to be two intimately related abilities, suggesting that they arise from a single inference process. We show that human performance matches several properties of the optimal probabilistic inference. In particular, subjective confidence is impacted by environmental uncertainty, both at the first level (uncertainty in stimulus occurrence given the inferred stochastic characteristics) and at the second level (uncertainty due to unexpected changes in these stochastic characteristics). Confidence also increases appropriately with the number of observations within stable periods. Our results support the idea that humans possess a quantitative sense of confidence in their inferences about abstract non-sensory parameters of the environment. This ability cannot be reduced to simple heuristics, it seems instead a core property of the learning process. '),
(87213, 2015, 'plos', 'Posterior Probability Matching and Human Perceptual Decision Making', 'Murray, Richard F|Patel, Khushbu|Yee, Alan', 'Department of Psychology and Centre for Vision Research, York University, Toronto, Ontario, Canada.|Department of Psychology and Centre for Vision Research, York University, Toronto, Ontario, Canada.|Department of Psychology and Centre for Vision Research, York University, Toronto, Ontario, Canada.', 'Canada|Canada|Canada', 9, 'Computational Biology|Decision Making|Humans|Models, Neurological|Perception', 'Journal Article', '10.1371/journal.pcbi.1004342', '26079134', 'Probability matching is a classic theory of decision making that was first developed in models of cognition. Posterior probability matching, a variant in which observers match their response probabilities to the posterior probability of each response being correct, is being used increasingly often in models of perception. However, little is known about whether posterior probability matching is consistent with the vast literature on vision and hearing that has developed within signal detection theory. Here we test posterior probability matching models using two tools from detection theory. First, we examine the models performance in a two-pass experiment, where each block of trials is presented twice, and we measure the proportion of times that the model gives the same response twice to repeated stimuli. We show that at low performance levels, posterior probability matching models give highly inconsistent responses across repeated presentations of identical trials. We find that practised human observers are more consistent across repeated trials than these models predict, and we find some evidence that less practised observers more consistent as well. Second, we compare the performance of posterior probability matching models on a discrimination task to the performance of a theoretical ideal observer that achieves the best possible performance. We find that posterior probability matching is very inefficient at low-to-moderate performance levels, and that human observers can be more efficient than is ever possible according to posterior probability matching models. These findings support classic signal detection models, and rule out a broad class of posterior probability matching models for expert performance on perceptual tasks that range in complexity from contrast discrimination to symmetry detection. However, our findings leave open the possibility that inexperienced observers may show posterior probability matching behaviour, and our methods provide new tools for testing for such a strategy. '),
(87214, 2015, 'plos', 'Deciphering Signaling Pathway Networks to Understand the Molecular Mechanisms of Metformin Action', 'Sun, Jingchun|Zhao, Min|Jia, Peilin|Wang, Lily|Wu, Yonghui|Iverson, Carissa|Zhou, Yubo|Bowton, Erica|Roden, Dan M|Denny, Joshua C|Aldrich, Melinda C|Xu, Hua|Zhao, Zhongming', 'School of Biomedical Informatics, The University of Texas Health Science Center at Houston, Houston, Texas, United States of America, Department of Biomedical Informatics, Vanderbilt University School of Medicine, Nashville, Tennessee, United States of America.|Department of Biomedical Informatics, Vanderbilt University School of Medicine, Nashville, Tennessee, United States of America.|Department of Biomedical Informatics, Vanderbilt University School of Medicine, Nashville, Tennessee, United States of America.|Department of Biostatistics, Vanderbilt University School of Medicine, Nashville, Tennessee, United States of America.|School of Biomedical Informatics, The University of Texas Health Science Center at Houston, Houston, Texas, United States of America.|Department of Thoracic Surgery, Vanderbilt University School of Medicine, Nashville, Tennessee, United States of America, Center for Human Genetics Research, Vanderbilt University, Nashville, Tennessee, United States of America.|National Center for Drug Screening, Shanghai Institute of Materia Medica, Chinese Academy of Sciences, Shanghai, Peoples Republic of China.|Institute for Clinical and Translational Research, School of Medicine, Vanderbilt University, Nashville, Tennessee, United States of America.|Department of Medicine, Vanderbilt University School of Medicine, Nashville, Tennessee, United States of America, Department of Pharmacology, Vanderbilt University School of Medicine, Nashville, Tennessee, United States of America.|Department of Biomedical Informatics, Vanderbilt University School of Medicine, Nashville, Tennessee, United States of America.|Department of Thoracic Surgery, Vanderbilt University School of Medicine, Nashville, Tennessee, United States of America, Center for Human Genetics Research, Vanderbilt University, Nashville, Tennessee, United States of America, Division of Epidemiology, Vanderbilt University School of Medicine, Nashville, Tennessee, United States of America.|School of Biomedical Informatics, The University of Texas Health Science Center at Houston, Houston, Texas, United States of America.|Department of Biomedical Informatics, Vanderbilt University School of Medicine, Nashville, Tennessee, United States of America, Center for Quantitative Sciences, Vanderbilt University School of Medicine, Nashville, Tennessee, United States of America, Department of Cancer Biology, Vanderbilt University School of Medicine, Nashville, Tennessee, United States of America.', 'United States|United States|United States|United States|United States|United States|China|United Sta', 16, 'Animals|Antineoplastic Agents|Computational Biology|Diabetes Mellitus, Type 2|Gene Expression Profiling|Genome-Wide Association Study|Humans|Hypoglycemic Agents|Metformin|Mice|Neoplasms|Rats|Signal Transduction', 'Journal Article', '10.1371/journal.pcbi.1004202', '26083494', 'A drug exerts its effects typically through a signal transduction cascade, which is non-linear and involves intertwined networks of multiple signaling pathways. Construction of such a signaling pathway network (SPNetwork) can enable identification of novel drug targets and deep understanding of drug action. However, it is challenging to synopsize critical components of these interwoven pathways into one network. To tackle this issue, we developed a novel computational framework, the Drug-specific Signaling Pathway Network (DSPathNet). The DSPathNet amalgamates the prior drug knowledge and drug-induced gene expression via random walk algorithms. Using the drug metformin, we illustrated this framework and obtained one metformin-specific SPNetwork containing 477 nodes and 1,366 edges. To evaluate this network, we performed the gene set enrichment analysis using the disease genes of type 2 diabetes (T2D) and cancer, one T2D genome-wide association study (GWAS) dataset, three cancer GWAS datasets, and one GWAS dataset of cancer patients with T2D on metformin. The results showed that the metformin network was significantly enriched with disease genes for both T2D and cancer, and that the network also included genes that may be associated with metformin-associated cancer survival. Furthermore, from the metformin SPNetwork and common genes to T2D and cancer, we generated a subnetwork to highlight the molecule crosstalk between T2D and cancer. The follow-up network analyses and literature mining revealed that seven genes (CDKN1A, ESR1, MAX, MYC, PPARGC1A, SP1, and STK11) and one novel MYC-centered pathway with CDKN1A, SP1, and STK11 might play important roles in metformins antidiabetic and anticancer effects. Some results are supported by previous studies. In summary, our study 1) develops a novel framework to construct drug-specific signal transduction networks, 2) provides insights into the molecular mode of metformin, 3) serves a model for exploring signaling pathways to facilitate understanding of drug action, disease pathogenesis, and identification of drug targets. '),
(87215, 2015, 'plos', 'Automated High-Throughput Characterization of Single Neurons by Means of Simplified Spiking Models', 'Pozzorini, Christian|Mensi, Skander|Hagens, Olivier|Naud, Richard|Koch, Christof|Gerstner, Wulfram', '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.|Laboratory of Neural Microcircuitry (LNMC), Brain Mind Institute, School of Life Sciences, École Polytechnique Fédérale de Lausanne, Lausanne, Switzerland.|Department of Physics, University of Ottawa, Ottawa, Canada.|Allen Institute for Brain Science, Seattle, Washington, USA.|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|Canada|United States|Switzerland', 25, 'Action Potentials|Animals|Brain|Computational Biology|Computer Simulation|Electrophysiology|High-Throughput Screening Assays|Male|Mice|Mice, Inbred C57BL|Models, Neurological|Neurons', 'Journal Article', '10.1371/journal.pcbi.1004275', '26083597', 'Single-neuron models are useful not only for studying the emergent properties of neural circuits in large-scale simulations, but also for extracting and summarizing in a principled way the information contained in electrophysiological recordings. Here we demonstrate that, using a convex optimization procedure we previously introduced, a Generalized Integrate-and-Fire model can be accurately fitted with a limited amount of data. The model is capable of predicting both the spiking activity and the subthreshold dynamics of different cell types, and can be used for online characterization of neuronal properties. A protocol is proposed that, combined with emergent technologies for automatic patch-clamp recordings, permits automated, in vitro high-throughput characterization of single neurons. '),
(87216, 2015, 'plos', 'Revealing Pathway Dynamics in Heart Diseases by Analyzing Multiple Differential Networks', 'Ma, Xiaoke|Gao, Long|Karamanlidis, Georgios|Gao, Peng|Lee, Chi Fung|Garcia-Menendez, Lorena|Tian, Rong|Tan, Kai', 'Department of Internal Medicine, University of Iowa, Iowa City, Iowa, United States of America.|Department of Biomedical Engineering, University of Iowa, Iowa City, Iowa, United States of America.|Department of Anesthesiology and Pain Medicine, Mitochondria and Metabolism Center, University of Washington School of Medicine, Seattle, Washington, United States of America.|Department of Internal Medicine, University of Iowa, Iowa City, Iowa, United States of America.|Department of Anesthesiology and Pain Medicine, Mitochondria and Metabolism Center, University of Washington School of Medicine, Seattle, Washington, United States of America.|Department of Anesthesiology and Pain Medicine, Mitochondria and Metabolism Center, University of Washington School of Medicine, Seattle, Washington, United States of America.|Department of Anesthesiology and Pain Medicine, Mitochondria and Metabolism Center, University of Washington School of Medicine, Seattle, Washington, United States of America.|Department of Internal Medicine, University of Iowa, Iowa City, Iowa, United States of America.', 'United States|United States|United States|United States|United States|United States|United States|Un', 37, 'Algorithms|Animals|Computational Biology|Gene Expression Profiling|Gene Regulatory Networks|Heart Failure|Mice|Mice, Transgenic|Systems Biology|Transcriptome', 'Journal Article', '10.1371/journal.pcbi.1004332', '26083688', 'Development of heart diseases is driven by dynamic changes in both the activity and connectivity of gene pathways. Understanding these dynamic events is critical for understanding pathogenic mechanisms and development of effective treatment. Currently, there is a lack of computational methods that enable analysis of multiple gene networks, each of which exhibits differential activity compared to the network of the baseline/healthy condition. We describe the iMDM algorithm to identify both unique and shared gene modules across multiple differential co-expression networks, termed M-DMs (multiple differential modules). We applied iMDM to a time-course RNA-Seq dataset generated using a murine heart failure model generated on two genotypes. We showed that iMDM achieves higher accuracy in inferring gene modules compared to using single or multiple co-expression networks. We found that condition-specific M-DMs exhibit differential activities, mediate different biological processes, and are enriched for genes with known cardiovascular phenotypes. By analyzing M-DMs that are present in multiple conditions, we revealed dynamic changes in pathway activity and connectivity across heart failure conditions. We further showed that module dynamics were correlated with the dynamics of disease phenotypes during the development of heart failure. Thus, pathway dynamics is a powerful measure for understanding pathogenesis. iMDM provides a principled way to dissect the dynamics of gene pathways and its relationship to the dynamics of disease phenotype. With the exponential growth of omics data, our method can aid in generating systems-level insights into disease progression. '),
(87217, 2015, 'plos', 'Modeling the Impact of White-Plague Coral Disease in Climate Change Scenarios', 'Zvuloni, Assaf|Artzy-Randrup, Yael|Katriel, Guy|Loya, Yossi|Stone, Lewi', 'Israel Nature and Parks Authority, Eilat, Israel, Department of Zoology, Tel Aviv University, Ramat Aviv, Tel Aviv, Israel, The H. Steinitz Marine Biology Laboratory, Eilat, Israel.|Institute for Biodiversity and Ecosystem Dynamics, University of Amsterdam, Amsterdam, The Netherlands.|Department of Mathematics, ORT Braude College, Karmiel, Israel.|Department of Zoology, Tel Aviv University, Ramat Aviv, Tel Aviv, Israel.|Department of Zoology, Tel Aviv University, Ramat Aviv, Tel Aviv, Israel, School of Mathematical and Geospatial Sciences, RMIT University, Melbourne, Australia.', 'Israel|Netherlands|Israel|Israel|Australia', 6, 'Animals|Anthozoa|Climate Change|Communicable Diseases|Computational Biology|Coral Reefs|Environmental Monitoring|Models, Biological|Temperature', 'Journal Article', '10.1371/journal.pcbi.1004151', '26086846', 'Coral reefs are in global decline, with coral diseases increasing both in prevalence and in space, a situation that is expected only to worsen as future thermal stressors increase. Through intense surveillance, we have collected a unique and highly resolved dataset from the coral reef of Eilat (Israel, Red Sea), that documents the spatiotemporal dynamics of a White Plague Disease (WPD) outbreak over the course of a full season. Based on modern statistical methodologies, we develop a novel spatial epidemiological model that uses a maximum-likelihood procedure to fit the data and assess the transmission pattern of WPD. We link the model to sea surface temperature (SST) and test the possible effect of increasing temperatures on disease dynamics. Our results reveal that the likelihood of a susceptible coral to become infected is governed both by SST and by its spatial location relative to nearby infected corals. The model shows that the magnitude of WPD epidemics strongly depends on demographic circumstances, under one extreme, when recruitment is free-space regulated and coral density remains relatively constant, even an increase of only 0.5°C in SST can cause epidemics to double in magnitude. In reality, however, the spatial nature of transmission can effectively protect the community, restricting the magnitude of annual epidemics. This is because the probability of susceptible corals to become infected is negatively associated with coral density. Based on our findings, we expect that infectious diseases having a significant spatial component, such as Red-Sea WPD, will never lead to a complete destruction of the coral community under increased thermal stress. However, this also implies that signs of recovery of local coral communities may be misleading, indicative more of spatial dynamics than true rehabilitation of these communities. In contrast to earlier generic models, our approach captures dynamics of WPD both in space and time, accounting for the highly seasonal nature of annual WPD outbreaks. '),
(87218, 2015, 'plos', 'Is Model Fitting Necessary for Model-Based fMRI?', 'Wilson, Robert C|Niv, Yael', 'Department of Psychology and Cognitive Science Program, University of Arizona, Tucson Arizona, United States of America.|Princeton Neuroscience Institute, Princeton University, Princeton, New Jersey, United States of America.', 'United States|Jersey', 33, 'Brain|Choice Behavior|Computational Biology|Humans|Magnetic Resonance Imaging|Models, Neurological|Reinforcement (Psychology)', 'Journal Article', '10.1371/journal.pcbi.1004237', '26086934', 'Model-based analysis of fMRI data is an important tool for investigating the computational role of different brain regions. With this method, theoretical models of behavior can be leveraged to find the brain structures underlying variables from specific algorithms, such as prediction errors in reinforcement learning. One potential weakness with this approach is that models often have free parameters and thus the results of the analysis may depend on how these free parameters are set. In this work we asked whether this hypothetical weakness is a problem in practice. We first developed general closed-form expressions for the relationship between results of fMRI analyses using different regressors, e.g., one corresponding to the true process underlying the measured data and one a model-derived approximation of the true generative regressor. Then, as a specific test case, we examined the sensitivity of model-based fMRI to the learning rate parameter in reinforcement learning, both in theory and in two previously-published datasets. We found that even gross errors in the learning rate lead to only minute changes in the neural results. Our findings thus suggest that precise model fitting is not always necessary for model-based fMRI. They also highlight the difficulty in using fMRI data for arbitrating between different models or model parameters. While these specific results pertain only to the effect of learning rate in simple reinforcement learning models, we provide a template for testing for effects of different parameters in other models. '),
(87219, 2015, 'plos', 'Emergence of Functional Specificity in Balanced Networks with Synaptic Plasticity', 'Sadeh, Sadra|Clopath, Claudia|Rotter, Stefan', 'Bernstein Center Freiburg & Faculty of Biology, University of Freiburg, Freiburg im Breisgau, Germany, Bioengineering Department, Imperial College London, London, United Kingdom.|Bioengineering Department, Imperial College London, London, United Kingdom.|Bernstein Center Freiburg & Faculty of Biology, University of Freiburg, Freiburg im Breisgau, Germany.', 'Germany|United Kingdom|Germany', 12, 'Animals|Computational Biology|Mice|Models, Neurological|Nerve Net|Neuronal Plasticity|Neurons|Visual Cortex', 'Journal Article', '10.1371/journal.pcbi.1004307', '26090844', 'In rodent visual cortex, synaptic connections between orientation-selective neurons are unspecific at the time of eye opening, and become to some degree functionally specific only later during development. An explanation for this two-stage process was proposed in terms of Hebbian plasticity based on visual experience that would eventually enhance connections between neurons with similar response features. For this to work, however, two conditions must be satisfied: First, orientation selective neuronal responses must exist before specific recurrent synaptic connections can be established. Second, Hebbian learning must be compatible with the recurrent network dynamics contributing to orientation selectivity, and the resulting specific connectivity must remain stable for unspecific background activity. Previous studies have mainly focused on very simple models, where the receptive fields of neurons were essentially determined by feedforward mechanisms, and where the recurrent network was small, lacking the complex recurrent dynamics of large-scale networks of excitatory and inhibitory neurons. Here we studied the emergence of functionally specific connectivity in large-scale recurrent networks with synaptic plasticity. Our results show that balanced random networks, which already exhibit highly selective responses at eye opening, can develop feature-specific connectivity if appropriate rules of synaptic plasticity are invoked within and between excitatory and inhibitory populations. If these conditions are met, the initial orientation selectivity guides the process of Hebbian learning and, as a result, functionally specific and a surplus of bidirectional connections emerge. Our results thus demonstrate the cooperation of synaptic plasticity and recurrent dynamics in large-scale functional networks with realistic receptive fields, highlight the role of inhibition as a critical element in this process, and paves the road for further computational studies of sensory processing in neocortical network models equipped with synaptic plasticity. '),
(87220, 2015, 'plos', 'A Minimal Regulatory Network of Extrinsic and Intrinsic Factors Recovers Observed Patterns of CD4+ T Cell Differentiation and Plasticity', 'Martinez-Sanchez, Mariana Esther|Mendoza, Luis|Villarreal, Carlos|Alvarez-Buylla, Elena R', 'Departamento de Ecologxc3xada Funcional, Instituto de Ecologxc3xada, Universidad Nacional Autxc3xb3noma de Mxc3xa9xico, Coyoacxc3xa1n, Mxc3xa9xico Distrito Federal, Mxc3xa9xico, Centro de Ciencias de la Complejidad, Universidad Nacional Autxc3xb3noma de Mxc3xa9xico, Coyoacxc3xa1n, Mxc3xa9xico Distrito Federal, Mxc3xa9xico.|Departamento de Biologxc3xada Molecular y Biotecnologxc3xada, Instituto de Investigaciones Biomxc3xa9dicas, Universidad Nacional Autxc3xb3noma de Mxc3xa9xico, Mxc3xa9xico Distrito Federal, Mxc3xa9xico.|Centro de Ciencias de la Complejidad, Universidad Nacional Autxc3xb3noma de Mxc3xa9xico, Coyoacxc3xa1n, Mxc3xa9xico Distrito Federal, Mxc3xa9xico, Departamento de Fxc3xadsica Texc3xb3rica, Instituto de Fxc3xadsica, Universidad Nacional Autxc3xb3noma de Mxc3xa9xico, Mxc3xa9xico Distrito Federal, Mxc3xa9xico.|Departamento de Ecologxc3xada Funcional, Instituto de Ecologxc3xada, Universidad Nacional Autxc3xb3noma de Mxc3xa9xico, Coyoacxc3xa1n, Mxc3xa9xico Distrito Federal, Mxc3xa9xico, Centro de Ciencias de la Complejidad, Universidad Nacional Autxc3xb3noma de Mxc3xa9xico, Coyoacxc3xa1n, Mxc3xa9xico Distrito Federal, Mxc3xa9xico.', '-|-|-|-', 29, 'CD4-Positive T-Lymphocytes|Cell Differentiation|Cell Plasticity|Cellular Microenvironment|Computational Biology|Cytokines|Models, Immunological|Signal Transduction', 'Journal Article', '10.1371/journal.pcbi.1004324', '26090929', 'CD4+ T cells orchestrate the adaptive immune response in vertebrates. While both experimental and modeling work has been conducted to understand the molecular genetic mechanisms involved in CD4+ T cell responses and fate attainment, the dynamic role of intrinsic (produced by CD4+ T lymphocytes) versus extrinsic (produced by other cells) components remains unclear, and the mechanistic and dynamic understanding of the plastic responses of these cells remains incomplete. In this work, we studied a regulatory network for the core transcription factors involved in CD4+ T cell-fate attainment. We first show that this core is not sufficient to recover common CD4+ T phenotypes. We thus postulate a minimal Boolean regulatory network model derived from a larger and more comprehensive network that is based on experimental data. The minimal network integrates transcriptional regulation, signaling pathways and the micro-environment. This network model recovers reported configurations of most of the characterized cell types (Th0, Th1, Th2, Th17, Tfh, Th9, iTreg, and Foxp3-independent T regulatory cells). This transcriptional-signaling regulatory network is robust and recovers mutant configurations that have been reported experimentally. Additionally, this model recovers many of the plasticity patterns documented for different T CD4+ cell types, as summarized in a cell-fate map. We tested the effects of various micro-environments and transient perturbations on such transitions among CD4+ T cell types. Interestingly, most cell-fate transitions were induced by transient activations, with the opposite behavior associated with transient inhibitions. Finally, we used a novel methodology was used to establish that T-bet, TGF-xcexb2 and suppressors of cytokine signaling proteins are keys to recovering observed CD4+ T cell plastic responses. In conclusion, the observed CD4+ T cell-types and transition patterns emerge from the feedback between the intrinsic or intracellular regulatory core and the micro-environment. We discuss the broader use of this approach for other plastic systems and possible therapeutic interventions. '),
(87221, 2015, 'plos', 'High Stimulus-Related Information in Barrel Cortex Inhibitory Interneurons', 'Reyes-Puerta, Vicente|Kim, Suam|Sun, Jyh-Jang|Imbrosci, Barbara|Kilb, Werner|Luhmann, Heiko J', 'Institute of Physiology, University Medical Center of the Johannes Gutenberg University, Mainz, Germany.|Institute of Physiology, University Medical Center of the Johannes Gutenberg University, Mainz, Germany.|Institute of Physiology, University Medical Center of the Johannes Gutenberg University, Mainz, Germany.|Institute of Physiology, University Medical Center of the Johannes Gutenberg University, Mainz, Germany.|Institute of Physiology, University Medical Center of the Johannes Gutenberg University, Mainz, Germany.|Institute of Physiology, University Medical Center of the Johannes Gutenberg University, Mainz, Germany.', 'Germany|Germany|Germany|Germany|Germany|Germany', 11, 'Action Potentials|Animals|Computational Biology|Interneurons|Male|Models, Neurological|Nerve Net|Rats|Rats, Wistar|Somatosensory Cortex', 'Journal Article', '10.1371/journal.pcbi.1004121', '26098109', 'The manner in which populations of inhibitory (INH) and excitatory (EXC) neocortical neurons collectively encode stimulus-related information is a fundamental, yet still unresolved question. Here we address this question by simultaneously recording with large-scale multi-electrode arrays (of up to 128 channels) the activity of cell ensembles (of up to 74 neurons) distributed along all layers of 3-4 neighboring cortical columns in the anesthetized adult rat somatosensory barrel cortex in vivo. Using two different whisker stimulus modalities (location and frequency) we show that individual INH neurons--classified as such according to their distinct extracellular spike waveforms--discriminate better between restricted sets of stimuli (xe2x89xa46 stimulus classes) than EXC neurons in granular and infra-granular layers. We also demonstrate that ensembles of INH cells jointly provide as much information about such stimuli as comparable ensembles containing the ~20% most informative EXC neurons, however presenting less information redundancy - a result which was consistent when applying both theoretical information measurements and linear discriminant analysis classifiers. These results suggest that a consortium of INH neurons dominates the information conveyed to the neocortical network, thereby efficiently processing incoming sensory activity. This conclusion extends our view on the role of the inhibitory system to orchestrate cortical activity.'),
(87222, 2015, 'plos', 'Integration of Metabolic and Quorum Sensing Signals Governing the Decision to Cooperate in a Bacterial Social Trait', 'Boyle, Kerry E|Monaco, Hilary|van Ditmarsch, Dave|Deforet, Maxime|Xavier, Joao B', 'Program in Immunology and Microbial Pathogenesis, Weill Cornell Graduate School of Medical Sciences, New York, New York, United States of America, Program in Computational Biology, Memorial Sloan Kettering Cancer Center, New York, New York, United States of America.|Program in Computational Biology, Memorial Sloan Kettering Cancer Center, New York, New York, United States of America, Tri-Institutional Training Program in Computational Biology and Medicine, New York, New York, United States of America.|Program in Computational Biology, Memorial Sloan Kettering Cancer Center, New York, New York, United States of America.|Program in Computational Biology, Memorial Sloan Kettering Cancer Center, New York, New York, United States of America.|Program in Immunology and Microbial Pathogenesis, Weill Cornell Graduate School of Medical Sciences, New York, New York, United States of America, Program in Computational Biology, Memorial Sloan Kettering Cancer Center, New York, New York, United States of America, Tri-Institutional Training Program in Computational Biology and Medicine, New York, New York, United States of America.', 'United States|United States|United States|United States|United States', 26, 'Algorithms|Bacterial Proteins|Biomass|Food|Gene Expression Regulation, Bacterial|Genes, Bacterial|Green Fluorescent Proteins|Iron|Kinetics|Lipids|Metabolic Networks and Pathways|Microscopy, Fluorescence|Models, Theoretical|Nitrogen|Operon|Promoter Regions, Genetic|Pseudomonas aeruginosa|Quorum Sensing|Software', 'Journal Article', '10.1371/journal.pcbi.1004279', '26102206', 'Many unicellular organisms live in multicellular communities that rely on cooperation between cells. However, cooperative traits are vulnerable to exploitation by non-cooperators (cheaters). We expand our understanding of the molecular mechanisms that allow multicellular systems to remain robust in the face of cheating by dissecting the dynamic regulation of cooperative rhamnolipids required for swarming in Pseudomonas aeruginosa. We combine mathematical modeling and experiments to quantitatively characterize the integration of metabolic and population density signals (quorum sensing) governing expression of the rhamnolipid synthesis operon rhlAB. The combined computational/experimental analysis reveals that when nutrients are abundant, rhlAB promoter activity increases gradually in a density dependent way. When growth slows down due to nutrient limitation, rhlAB promoter activity can stop abruptly, decrease gradually or even increase depending on whether the growth-limiting nutrient is the carbon source, nitrogen source or iron. Starvation by specific nutrients drives growth on intracellular nutrient pools as well as the qualitative rhlAB promoter response, which itself is modulated by quorum sensing. Our quantitative analysis suggests a supply-driven activation that integrates metabolic prudence with quorum sensing in a non-digital manner and allows P. aeruginosa cells to invest in cooperation only when the population size is large enough (quorum sensing) and individual cells have enough metabolic resources to do so (metabolic prudence). Thus, the quantitative description of rhlAB regulatory dynamics brings a greater understating to the regulation required to make swarming cooperation stable. '),
(87223, 2015, 'plos', 'Inference of Network Dynamics and Metabolic Interactions in the Gut Microbiome', 'Steinway, Steven N|Biggs, Matthew B|Loughran, Thomas P|Papin, Jason A|Albert, Reka', 'College of Medicine, Pennsylvania State University, Hershey, Pennsylvania, United States of America, University of Virginia Cancer Center, University of Virginia, Charlottesville, Virginia, United States of America.|Department of Biomedical Engineering, University of Virginia, Charlottesville, Virginia, United States of America.|University of Virginia Cancer Center, University of Virginia, Charlottesville, Virginia, United States of America.|Department of Biomedical Engineering, University of Virginia, Charlottesville, Virginia, United States of America.|Department of Physics, Pennsylvania State University, University Park, Pennsylvania, United States of America.', 'United States|United States|United States|United States|United States', 63, 'Algorithms|Animals|Anti-Bacterial Agents|Clindamycin|Clostridium Infections|Clostridium difficile|Coculture Techniques|Computer Simulation|Gastrointestinal Microbiome|Gastrointestinal Tract|Metabolic Networks and Pathways|Mice|Microbiota', 'Journal Article', '10.1371/journal.pcbi.1004338', '26102287', 'We present a novel methodology to construct a Boolean dynamic model from time series metagenomic information and integrate this modeling with genome-scale metabolic network reconstructions to identify metabolic underpinnings for microbial interactions. We apply this in the context of a critical health issue: clindamycin antibiotic treatment and opportunistic Clostridium difficile infection. Our model recapitulates known dynamics of clindamycin antibiotic treatment and C. difficile infection and predicts therapeutic probiotic interventions to suppress C. difficile infection. Genome-scale metabolic network reconstructions reveal metabolic differences between community members and are used to explore the role of metabolism in the observed microbial interactions. In vitro experimental data validate a key result of our computational model, that B. intestinihominis can in fact slow C. difficile growth. '),
(87224, 2015, 'plos', 'Antenna Mechanism of Length Control of Actin Cables', 'Mohapatra, Lishibanya|Goode, Bruce L|Kondev, Jane', 'Department of Physics, Brandeis University, Waltham, Massachusetts, United States of America.|Department of Biology and Rosenstiel Basic Medical Sciences Research Center, Brandeis University, Waltham, Massachusetts, United States of America.|Department of Physics, Brandeis University, Waltham, Massachusetts, United States of America.', 'United States|United States|United States', 10, 'Actins|Computational Biology|Microtubule-Associated Proteins|Models, Molecular|Myosins|Polymerization|Saccharomyces cerevisiae|Saccharomyces cerevisiae Proteins', 'Journal Article', '10.1371/journal.pcbi.1004160', '26107518', 'Actin cables are linear cytoskeletal structures that serve as tracks for myosin-based intracellular transport of vesicles and organelles in both yeast and mammalian cells. In a yeast cell undergoing budding, cables are in constant dynamic turnover yet some cables grow from the bud neck toward the back of the mother cell until their length roughly equals the diameter of the mother cell. This raises the question: how is the length of these cables controlled? Here we describe a novel molecular mechanism for cable length control inspired by recent experimental observations in cells. This antenna mechanism involves three key proteins: formins, which polymerize actin, Smy1 proteins, which bind formins and inhibit actin polymerization, and myosin motors, which deliver Smy1 to formins, leading to a length-dependent actin polymerization rate. We compute the probability distribution of cable lengths as a function of several experimentally tuneable parameters such as the formin-binding affinity of Smy1 and the concentration of myosin motors delivering Smy1. These results provide testable predictions of the antenna mechanism of actin-cable length control. ');
INSERT INTO `papers` (`id`, `ano`, `journal`, `titulo`, `autores`, `afiliacao`, `pais`, `citacoes`, `palavra_chave`, `categorias`, `doi`, `pubmed`, `abstract`) VALUES
(87225, 2015, 'plos', 'Emerging Object Representations in the Visual System Predict Reaction Times for Categorization', 'Ritchie, J Brendan|Tovar, David A|Carlson, Thomas A', 'Department of Philosophy, University of Maryland, College Park, Maryland, United States of America, Perception in Action Research Centre, Department of Cognitive Science, Macquarie University, Sydney, New South Wales, Australia, ARC Centre of Excellence in Cognition and its Disorders, Macquarie University, Sydney, New South Wales, Australia.|School of Medicine, Vanderbilt University, Nashville, Tennessee, United States of America.|Perception in Action Research Centre, Department of Cognitive Science, Macquarie University, Sydney, New South Wales, Australia, ARC Centre of Excellence in Cognition and its Disorders, Macquarie University, Sydney, New South Wales, Australia.', 'Australia|United States|Australia', 28, 'Adult|Attention|Computational Biology|Decision Making|Humans|Magnetoencephalography|Male|Reaction Time|Visual Cortex|Young Adult', 'Journal Article', '10.1371/journal.pcbi.1004316', '26107634', 'Recognizing an object takes just a fraction of a second, less than the blink of an eye. Applying multivariate pattern analysis, or brain decoding, methods to magnetoencephalography (MEG) data has allowed researchers to characterize, in high temporal resolution, the emerging representation of object categories that underlie our capacity for rapid recognition. Shortly after stimulus onset, object exemplars cluster by category in a high-dimensional activation space in the brain. In this emerging activation space, the decodability of exemplar category varies over time, reflecting the brains transformation of visual inputs into coherent category representations. How do these emerging representations relate to categorization behavior? Recently it has been proposed that the distance of an exemplar representation from a categorical boundary in an activation space is critical for perceptual decision-making, and that reaction times should therefore correlate with distance from the boundary. The predictions of this distance hypothesis have been born out in human inferior temporal cortex (IT), an area of the brain crucial for the representation of object categories. When viewed in the context of a time varying neural signal, the optimal time to read out category information is when category representations in the brain are most decodable. Here, we show that the distance from a decision boundary through activation space, as measured using MEG decoding methods, correlates with reaction times for visual categorization during the period of peak decodability. Our results suggest that the brain begins to read out information about exemplar category at the optimal time for use in choice behaviour, and support the hypothesis that the structure of the representation for objects in the visual system is partially constitutive of the decision process in recognition. '),
(87226, 2015, 'plos', 'Ten Years of PLoS Computational Biology: A Decade of Appreciation and Innovation', 'Bourne, Philip E|Brenner, Steven E|Eisen, Michael B', 'Office of the Director, National Institutes of Health, Bethesda, Maryland, United States of America.|Department of Plant and Microbial Biology, University of California, Berkeley, Berkeley, California, United States of America, Department of Molecular and Cell Biology, University of California, Berkeley, Berkeley, California, United States of America.|Department of Molecular and Cell Biology, University of California, Berkeley, Berkeley, California, United States of America.', 'United States|United States|United States', 0, 'Computational Biology|Humans|Periodicals as Topic', 'Editorial', '10.1371/journal.pcbi.1004317', '26107720', '-'),
(87227, 2015, 'plos', 'Computational Biology: Moving into the Future One Click at a Time', 'Fogg, Christiana N|Kovats, Diane E', 'Freelance Science Writer, Kensington, Maryland, United States of America.|Executive Director, International Society for Computational Biology, La Jolla, California, United States of America.', 'United States|United States', 0, 'Computational Biology|History, 20th Century|History, 21st Century|Humans|Periodicals as Topic', 'Historical Article', '10.1371/journal.pcbi.1004323', '26107876', '-'),
(87228, 2015, 'plos', 'BASiCS: Bayesian Analysis of Single-Cell Sequencing Data', 'Vallejos, Catalina A|Marioni, John C|Richardson, Sylvia', 'MRC Biostatistics Unit, Cambridge Institute of Public Health, Cambridge, United Kingdom, EMBL European Bioinformatics Institute, Cambridge, United Kingdom.|EMBL European Bioinformatics Institute, Cambridge, United Kingdom.|MRC Biostatistics Unit, Cambridge Institute of Public Health, Cambridge, United Kingdom.', 'United Kingdom|United Kingdom|United Kingdom', 103, 'Animals|Bayes Theorem|Computational Biology|Embryonic Stem Cells|Gene Expression Profiling|Mice|Oligonucleotide Array Sequence Analysis|RNA, Messenger|Reproducibility of Results|Single-Cell Analysis', 'Journal Article', '10.1371/journal.pcbi.1004333', '26107944', 'Single-cell mRNA sequencing can uncover novel cell-to-cell heterogeneity in gene expression levels in seemingly homogeneous populations of cells. However, these experiments are prone to high levels of unexplained technical noise, creating new challenges for identifying genes that show genuine heterogeneous expression within the population of cells under study. BASiCS (Bayesian Analysis of Single-Cell Sequencing data) is an integrated Bayesian hierarchical model where: (i) cell-specific normalisation constants are estimated as part of the model parameters, (ii) technical variability is quantified based on spike-in genes that are artificially introduced to each analysed cells lysate and (iii) the total variability of the expression counts is decomposed into technical and biological components. BASiCS also provides an intuitive detection criterion for highly (or lowly) variable genes within the population of cells under study. This is formalised by means of tail posterior probabilities associated to high (or low) biological cell-to-cell variance contributions, quantities that can be easily interpreted by users. We demonstrate our method using gene expression measurements from mouse Embryonic Stem Cells. Cross-validation and meaningful enrichment of gene ontology categories within genes classified as highly (or lowly) variable supports the efficacy of our approach. '),
(87229, 2015, 'plos', 'Antibiotic Restriction Might Facilitate the Emergence of Multi-drug Resistance', 'Obolski, Uri|Stein, Gideon Y|Hadany, Lilach', 'Department of Molecular Biology and Ecology of Plants, Tel-Aviv University, Tel Aviv, Israel.|Internal Medicine B, Beilinson Hospital, Rabin Medical Center, Petah Tikva and Sackler Faculty of Medicine, Tel Aviv, Israel.|Department of Molecular Biology and Ecology of Plants, Tel-Aviv University, Tel Aviv, Israel.', 'Israel|Israel|Israel', 19, 'Anti-Bacterial Agents|Bacterial Infections|Computational Biology|Drug Resistance, Multiple, Bacterial|Humans|Models, Biological', 'Journal Article', '10.1371/journal.pcbi.1004340', '26110266', 'High antibiotic resistance frequencies have become a major public health issue. The decrease in new antibiotics production, combined with increasing frequencies of multi-drug resistant (MDR) bacteria, cause substantial limitations in treatment options for some bacterial infections. To diminish overall resistance, and especially the occurrence of bacteria that are resistant to all antibiotics, certain drugs are deliberately scarcely used--mainly when other options are exhausted. We use a mathematical model to explore the efficiency of such antibiotic restrictions. We assume two commonly used drugs and one restricted drug. The model is examined for the mixing strategy of antibiotic prescription, in which one of the drugs is randomly assigned to each incoming patient. Data obtained from Rabin medical center, Israel, is used to estimate realistic single and double antibiotic resistance frequencies in incoming patients. We find that broad usage of the hitherto restricted drug can reduce the number of incorrectly treated patients, and reduce the spread of bacteria resistant to both common antibiotics. Such double resistant infections are often eventually treated with the restricted drug, and therefore are prone to become resistant to all three antibiotics. Thus, counterintuitively, a broader usage of a formerly restricted drug can sometimes lead to a decrease in the emergence of bacteria resistant to all drugs. We recommend re-examining restriction of specific drugs, when multiple resistance to the relevant alternative drugs already exists.'),
(87230, 2015, 'plos', 'Keys to Lipid Selection in Fatty Acid Amide Hydrolase Catalysis: Structural Flexibility, Gating Residues and Multiple Binding Pockets', 'Palermo, Giulia|Bauer, Inga|Campomanes, Pablo|Cavalli, Andrea|Armirotti, Andrea|Girotto, Stefania|Rothlisberger, Ursula|De Vivo, Marco', 'Laboratory of Molecular Modeling and Drug Discovery, Istituto Italiano di Tecnologia, Genova, Italy.|CompuNet, Istituto Italiano di Tecnologia, Genova, Italy.|Laboratory of Computational Chemistry and Biochemistry, Institute of Chemical Sciences and Engineering, École Polytechnique Fédérale de Lausanne, Lausanne, Switzerland.|CompuNet, Istituto Italiano di Tecnologia, Genova, Italy, Department of Pharmacy and Biotechnology, University of Bologna, Bologna, Italy.|D3-PharmaChemistry, Istituto Italiano di Tecnologia, Genova, Italy.|CompuNet, Istituto Italiano di Tecnologia, Genova, Italy.|Laboratory of Computational Chemistry and Biochemistry, Institute of Chemical Sciences and Engineering, École Polytechnique Fédérale de Lausanne, Lausanne, Switzerland.|Laboratory of Molecular Modeling and Drug Discovery, Istituto Italiano di Tecnologia, Genova, Italy.', 'Italy|Italy|Switzerland|Italy|Italy|Italy|Switzerland|Italy', 25, 'Amidohydrolases|Arachidonic Acids|Binding Sites|Catalysis|Computational Biology|Endocannabinoids|Humans|Molecular Dynamics Simulation|Mutation|Polyunsaturated Alkamides|Protein Conformation', 'Journal Article', '10.1371/journal.pcbi.1004231', '26111155', 'The fatty acid amide hydrolase (FAAH) regulates the endocannabinoid system cleaving primarily the lipid messenger anandamide. FAAH has been well characterized over the years and, importantly, it represents a promising drug target to treat several diseases, including inflammatory-related diseases and cancer. But its enzymatic mechanism for lipid selection to specifically hydrolyze anandamide, rather than similar bioactive lipids, remains elusive. Here, we clarify this mechanism in FAAH, examining the role of the dynamic paddle, which is formed by the gating residues Phe432 and Trp531 at the boundary between two cavities that form the FAAH catalytic site (the membrane-access and the acyl chain-binding pockets). We integrate microsecond-long MD simulations of wild type and double mutant model systems (Phe432Ala and Trp531Ala) of FAAH, embedded in a realistic membrane/water environment, with mutagenesis and kinetic experiments. We comparatively analyze three fatty acid substrates with different hydrolysis rates (anandamide > oleamide > palmitoylethanolamide). Our findings identify FAAHs mechanism to selectively accommodate anandamide into a multi-pocket binding site, and to properly orient the substrate in pre-reactive conformations for efficient hydrolysis that is interceded by the dynamic paddle. Our findings therefore endorse a structural framework for a lipid selection mechanism mediated by structural flexibility and gating residues between multiple binding cavities, as found in FAAH. Based on the available structural data, this exquisite catalytic strategy for substrate specificity seems to be shared by other lipid-degrading enzymes with similar enzymatic architecture. The mechanistic insights for lipid selection might assist de-novo enzyme design or drug discovery efforts. '),
(87231, 2015, 'plos', 'The Decay of Motor Memories Is Independent of Context Change Detection', 'Brennan, Andrew E|Smith, Maurice A', 'School of Engineering and Applied Sciences, Harvard University, Cambridge, Massachusetts, United States of America.|School of Engineering and Applied Sciences, Harvard University, Cambridge, Massachusetts, United States of America, Center for Brain Science, Harvard University, Cambridge, Massachusetts, United States of America.', 'United States|United States', 17, 'Adolescent|Adult|Algorithms|Computational Biology|Female|Humans|Learning|Male|Memory|Models, Neurological|Young Adult', 'Journal Article', '10.1371/journal.pcbi.1004278', '26111244', 'When the error signals that guide human motor learning are withheld following training, recently-learned motor memories systematically regress toward untrained performance. It has previously been hypothesized that this regression results from an intrinsic volatility in these memories, resulting in an inevitable decay in the absence of ongoing error signals. However, a recently-proposed alternative posits that even recently-acquired motor memories are intrinsically stable, decaying only if a change in context is detected. This new theory, the context-dependent decay hypothesis, makes two key predictions: (1) after error signals are withheld, decay onset should be systematically delayed until the context change is detected, and (2) manipulations that impair detection by masking context changes should result in prolonged delays in decay onset and reduced decay amplitude at any given time. Here we examine the decay of motor adaptation following the learning of novel environmental dynamics in order to carefully evaluate this hypothesis. To account for potential issues in previous work that supported the context-dependent decay hypothesis, we measured decay using a balanced and baseline-referenced experimental design that allowed for direct comparisons between analogous masked and unmasked context changes. Using both an unbiased variant of the previous decay onset analysis and a novel highly-powered group-level version of this analysis, we found no evidence for systematically delayed decay onset nor for the masked context change affecting decay amplitude or its onset time. We further show how previous estimates of decay onset latency can be substantially biased in the presence of noise, and even more so with correlated noise, explaining the discrepancy between the previous results and our findings. Our results suggest that the decay of motor memories is an intrinsic feature of error-based learning that does not depend on context change detection. '),
(87232, 2015, 'plos', 'A Computational, Tissue-Realistic Model of Pressure Ulcer Formation in Individuals with Spinal Cord Injury', 'Ziraldo, Cordelia|Solovyev, Alexey|Allegretti, Ana|Krishnan, Shilpa|Henzel, M Kristi|Sowa, Gwendolyn A|Brienza, David|An, Gary|Mi, Qi|Vodovotz, Yoram', 'Department of Computational and Systems Biology, University of Pittsburgh, Pittsburgh, Pennsylvania, United States of America, Joint PhD Program in Computational Biology, University of Pittsburgh and Carnegie Mellon University, Pittsburgh, Pennsylvania, United States of America, Center for Inflammation and Regenerative Modeling, McGowan Institute for Regenerative Medicine, University of Pittsburgh, Pittsburgh, Pennsylvania, United States of America.|Center for Inflammation and Regenerative Modeling, McGowan Institute for Regenerative Medicine, University of Pittsburgh, Pittsburgh, Pennsylvania, United States of America, Department of Mathematics, University of Pittsburgh, Pittsburgh, Pennsylvania, United States of America.|Department of Rehabilitation Science and Technology, School of Health and Rehabilitation Science, University of Pittsburgh, Pittsburgh, Pennsylvania, United States of America.|Department of Rehabilitation Science and Technology, School of Health and Rehabilitation Science, University of Pittsburgh, Pittsburgh, Pennsylvania, United States of America.|Spinal Cord Injury/Disorders Center, Louis Stokes Cleveland Veterans Affairs Medical Center, Cleveland, Ohio, United States of America.|Department of Physical Medicine and Rehabilitation, University of Pittsburgh School of Medicine, Pittsburgh, Pennsylvania, United States of America.|Department of Rehabilitation Science and Technology, School of Health and Rehabilitation Science, University of Pittsburgh, Pittsburgh, Pennsylvania, United States of America, McGowan Institute for Regenerative Medicine, University of Pittsburgh, Pittsburgh, Pennsylvania, United States of America, Department of Bioengineering, University of Pittsburgh, Pittsburgh, Pennsylvania, United States of America.|Center for Inflammation and Regenerative Modeling, McGowan Institute for Regenerative Medicine, University of Pittsburgh, Pittsburgh, Pennsylvania, United States of America, McGowan Institute for Regenerative Medicine, University of Pittsburgh, Pittsburgh, Pennsylvania, United States of America, Department of Surgery, University of Chicago, Chicago, Illinois, United States of America.|Center for Inflammation and Regenerative Modeling, McGowan Institute for Regenerative Medicine, University of Pittsburgh, Pittsburgh, Pennsylvania, United States of America, McGowan Institute for Regenerative Medicine, University of Pittsburgh, Pittsburgh, Pennsylvania, United States of America, Department of Sports Medicine and Nutrition, University of Pittsburgh, Pittsburgh, Pennsylvania, United States of America.|Center for Inflammation and Regenerative Modeling, McGowan Institute for Regenerative Medicine, University of Pittsburgh, Pittsburgh, Pennsylvania, United States of America, McGowan Institute for Regenerative Medicine, University of Pittsburgh, Pittsburgh, Pennsylvania, United States of America, Department of Surgery, University of Pittsburgh, Pittsburgh, Pennsylvania, United States of America.', 'United States|United States|United States|United States|United States|United States|United States|Un', 16, 'Algorithms|Chemotactic Factors|Computer Simulation|Humans|Models, Biological|Pressure|Pressure Ulcer|Spinal Cord Injuries', 'Journal Article', '10.1371/journal.pcbi.1004309', '26111346', 'People with spinal cord injury (SCI) are predisposed to pressure ulcers (PU). PU remain a significant burden in cost of care and quality of life despite improved mechanistic understanding and advanced interventions. An agent-based model (ABM) of ischemia/reperfusion-induced inflammation and PU (the PUABM) was created, calibrated to serial images of post-SCI PU, and used to investigate potential treatments in silico. Tissue-level features of the PUABM recapitulated visual patterns of ulcer formation in individuals with SCI. These morphological features, along with simulated cell counts and mediator concentrations, suggested that the influence of inflammatory dynamics caused simulations to be committed to better vs. worse outcomes by 4 days of simulated time and prior to ulcer formation. Sensitivity analysis of model parameters suggested that increasing oxygen availability would reduce PU incidence. Using the PUABM, in silico trials of anti-inflammatory treatments such as corticosteroids and a neutralizing antibody targeted at Damage-Associated Molecular Pattern molecules (DAMPs) suggested that, at best, early application at a sufficiently high dose could attenuate local inflammation and reduce pressure-associated tissue damage, but could not reduce PU incidence. The PUABM thus shows promise as an adjunct for mechanistic understanding, diagnosis, and design of therapies in the setting of PU. '),
(87233, 2015, 'plos', 'Time-Course Gene Set Analysis for Longitudinal Gene Expression Data', 'Hejblum, Boris P|Skinner, Jason|Thiébaut, Rodolphe', 'Univ. Bordeaux, ISPED, Centre INSERM U897-Epidemiologie-Biostatistique, F-33000 Bordeaux, France, INSERM, ISPED, Centre INSERM U897-Epidemiologie-Biostatistique, F-33000 Bordeaux, France, INRIA, Team SISTM, F-33000 Bordeaux, France, Vaccine Research Institute-VRI, Hôpital Henri Mondor, Créteil, France.|Vaccine Research Institute-VRI, Hôpital Henri Mondor, Créteil, France, Baylor Institute for Immunology Research, Dallas, Texas, United States of America.|Univ. Bordeaux, ISPED, Centre INSERM U897-Epidemiologie-Biostatistique, F-33000 Bordeaux, France, INSERM, ISPED, Centre INSERM U897-Epidemiologie-Biostatistique, F-33000 Bordeaux, France, INRIA, Team SISTM, F-33000 Bordeaux, France, Vaccine Research Institute-VRI, Hôpital Henri Mondor, Créteil, France, Baylor Institute for Immunology Research, Dallas, Texas, United States of America.', 'France|France|France', 27, 'AIDS Vaccines|Antiretroviral Therapy, Highly Active|Cluster Analysis|Computational Biology|Databases, Factual|Gene Expression Profiling|HIV Infections|Humans|Influenza Vaccines|Influenza, Human|Models, Biological|Models, Statistical', 'Journal Article', '10.1371/journal.pcbi.1004310', '26111374', 'Gene set analysis methods, which consider predefined groups of genes in the analysis of genomic data, have been successfully applied for analyzing gene expression data in cross-sectional studies. The time-course gene set analysis (TcGSA) introduced here is an extension of gene set analysis to longitudinal data. The proposed method relies on random effects modeling with maximum likelihood estimates. It allows to use all available repeated measurements while dealing with unbalanced data due to missing at random (MAR) measurements. TcGSA is a hypothesis driven method that identifies a priori defined gene sets with significant expression variations over time, taking into account the potential heterogeneity of expression within gene sets. When biological conditions are compared, the method indicates if the time patterns of gene sets significantly differ according to these conditions. The interest of the method is illustrated by its application to two real life datasets: an HIV therapeutic vaccine trial (DALIA-1 trial), and data from a recent study on influenza and pneumococcal vaccines. In the DALIA-1 trial TcGSA revealed a significant change in gene expression over time within 69 gene sets during vaccination, while a standard univariate individual gene analysis corrected for multiple testing as well as a standard a Gene Set Enrichment Analysis (GSEA) for time series both failed to detect any significant pattern change over time. When applied to the second illustrative data set, TcGSA allowed the identification of 4 gene sets finally found to be linked with the influenza vaccine too although they were found to be associated to the pneumococcal vaccine only in previous analyses. In our simulation study TcGSA exhibits good statistical properties, and an increased power compared to other approaches for analyzing time-course expression patterns of gene sets. The method is made available for the community through an R package. '),
(87234, 2015, 'plos', 'Spatio-temporal Dynamics and Mechanisms of Stress Granule Assembly', 'Ohshima, Daisuke|Arimoto-Matsuzaki, Kyoko|Tomida, Taichiro|Takekawa, Mutsuhiro|Ichikawa, Kazuhisa', 'Division of Mathematical Oncology, The Institute of Medical Science, The University of Tokyo, Tokyo, Japan.|Division of Molecular Cell Signaling, The Institute of Medical Science, The University of Tokyo, Tokyo, Japan.|Division of Molecular Cell Signaling, The Institute of Medical Science, The University of Tokyo, Tokyo, Japan.|Division of Cell Signaling and Molecular Medicine, The Institute of Medical Science, The University of Tokyo, Tokyo, Japan.|Division of Mathematical Oncology, The Institute of Medical Science, The University of Tokyo, Tokyo, Japan.', 'Japan|Japan|Japan|Japan|Japan', 11, 'Animals|Arsenites|COS Cells|Cercopithecus aethiops|Computational Biology|Computer Simulation|Cytoplasmic Granules|HeLa Cells|Humans|Models, Biological|Spatio-Temporal Analysis|Stress, Physiological', 'Journal Article', '10.1371/journal.pcbi.1004326', '26115353', 'Stress granules (SGs) are non-membranous cytoplasmic aggregates of mRNAs and related proteins, assembled in response to environmental stresses such as heat shock, hypoxia, endoplasmic reticulum (ER) stress, chemicals (e.g. arsenite), and viral infections. SGs are hypothesized as a loci of mRNA triage and/or maintenance of proper translation capacity ratio to the pool of mRNAs. In brain ischemia, hippocampal CA3 neurons, which are resilient to ischemia, assemble SGs. In contrast, CA1 neurons, which are vulnerable to ischemia, do not assemble SGs. These results suggest a critical role SG plays in regards to cell fate decisions. Thus SG assembly along with its dynamics should determine the cell fate. However, the process that exactly determines the SG assembly dynamics is largely unknown. In this paper, analyses of experimental data and computer simulations were used to approach this problem. SGs were assembled as a result of applying arsenite to HeLa cells. The number of SGs increased after a short latent period, reached a maximum, then decreased during the application of arsenite. At the same time, the size of SGs grew larger and became localized at the perinuclear region. A minimal mathematical model was constructed, and stochastic simulations were run to test the modeling. Since SGs are discrete entities as there are only several tens of them in a cell, commonly used deterministic simulations could not be employed. The stochastic simulations replicated observed dynamics of SG assembly. In addition, these stochastic simulations predicted a gamma distribution relative to the size of SGs. This same distribution was also found in our experimental data suggesting the existence of multiple fusion steps in the SG assembly. Furthermore, we found that the initial steps in the SG assembly process and microtubules were critical to the dynamics. Thus our experiments and stochastic simulations presented a possible mechanism regulating SG assembly. '),
(87235, 2015, 'plos', 'Rational Design and Adaptive Management of Combination Therapies for Hepatitis C Virus Infection', 'Ke, Ruian|Loverdo, Claude|Qi, Hangfei|Sun, Ren|Lloyd-Smith, James O', 'Department of Ecology and Evolutionary Biology, University of California, Los Angeles, Los Angeles, California, United States of America.|Department of Ecology and Evolutionary Biology, University of California, Los Angeles, Los Angeles, California, United States of America, CNRS/UPMC Univ Paris 06, UMR 8237, Laboratoire Jean Perrin LJP, Paris, France.|Department of Molecular and Medical Pharmacology, University of California, Los Angeles, Los Angeles, California, United States of America.|Department of Molecular and Medical Pharmacology, University of California, Los Angeles, Los Angeles, California, United States of America, The Molecular Biology Institute, University of California, Los Angeles, Los Angeles, California, United States of America, Department of Infectious Diseases, Novartis Institutes for BioMedical Research, Emeryville, California, United States of America, Zhejiang University, Hangzhou, China.|Department of Ecology and Evolutionary Biology, University of California, Los Angeles, Los Angeles, California, United States of America, Fogarty International Center, National Institutes of Health, Bethesda, Maryland, United States of America.', 'United States|France|United States|China|United States', 14, 'Antiviral Agents|Computational Biology|Drug Resistance, Viral|Genetic Fitness|Hepacivirus|Hepatitis C|Humans|Medication Adherence|Models, Biological', 'Journal Article', '10.1371/journal.pcbi.1004040', '26125950', 'Recent discoveries of direct acting antivirals against Hepatitis C virus (HCV) have raised hopes of effective treatment via combination therapies. Yet rapid evolution and high diversity of HCV populations, combined with the reality of suboptimal treatment adherence, make drug resistance a clinical and public health concern. We develop a general model incorporating viral dynamics and pharmacokinetics/ pharmacodynamics to assess how suboptimal adherence affects resistance development and clinical outcomes. We derive design principles and adaptive treatment strategies, identifying a high-risk period when missing doses is particularly risky for de novo resistance, and quantifying the number of additional doses needed to compensate when doses are missed. Using data from large-scale resistance assays, we demonstrate that the risk of resistance can be reduced substantially by applying these principles to a combination therapy of daclatasvir and asunaprevir. By providing a mechanistic framework to link patient characteristics to the risk of resistance, these findings show the potential of rational treatment design. '),
(87236, 2015, 'plos', 'High Accuracy Decoding of Dynamical Motion from a Large Retinal Population', 'Marre, Olivier|Botella-Soler, Vicente|Simmons, Kristina D|Mora, Thierry|Tkaxc4x8dik, Gaxc5xa1per|Berry, Michael J', 'Department of Molecular Biology and Neuroscience Institute, Princeton University, Princeton, United States of America, Institut de la Vision, INSERM UMRS 968, UPMC UM 80, CNRS UMR 7210, Paris, France.|Institute of Science and Technology Austria, Klosterneuburg, Austria.|Department of Psychology, University of Pennsylvania, Philadelphia, United States of America.|Laboratoire de Physique Statistique, xc3x89cole Normale Supxc3xa9rieure, CNRS and UPMC, Paris, France.|Institute of Science and Technology Austria, Klosterneuburg, Austria.|Department of Molecular Biology and Neuroscience Institute, Princeton University, Princeton, United States of America.', 'France|Austria|United States|France|Austria|United States', 0, 'Action Potentials|Animals|Computer Simulation|Guinea Pigs|Light|Models, Neurological|Motion Perception|Nerve Net|Photic Stimulation|Retinal Ganglion Cells|Synaptic Transmission|Urodela|Vision, Ocular', 'Journal Article', '10.1371/journal.pcbi.1004304', '26132103', 'Motion tracking is a challenge the visual system has to solve by reading out the retinal population. It is still unclear how the information from different neurons can be combined together to estimate the position of an object. Here we recorded a large population of ganglion cells in a dense patch of salamander and guinea pig retinas while displaying a bar moving diffusively. We show that the bars position can be reconstructed from retinal activity with a precision in the hyperacuity regime using a linear decoder acting on 100+ cells. We then took advantage of this unprecedented precision to explore the spatial structure of the retinas population code. The classical view would have suggested that the firing rates of the cells form a moving hill of activity tracking the bars position. Instead, we found that most ganglion cells in the salamander fired sparsely and idiosyncratically, so that their neural image did not track the bar. Furthermore, ganglion cell activity spanned an area much larger than predicted by their receptive fields, with cells coding for motion far in their surround. As a result, population redundancy was high, and we could find multiple, disjoint subsets of neurons that encoded the trajectory with high precision. This organization allows for diverse collections of ganglion cells to represent high-accuracy motion information in a form easily read out by downstream neural circuits. '),
(87237, 2015, 'plos', 'Rigidity Emerges during Antibody Evolution in Three Distinct Antibody Systems: Evidence from QSFR Analysis of Fab Fragments', 'Li, Tong|Tracka, Malgorzata B|Uddin, Shahid|Casas-Finet, Jose|Jacobs, Donald J|Livesay, Dennis R', 'Department of Bioinformatics and Genomics, University of North Carolina at Charlotte, Charlotte, North Carolina, United States of America.|Department of Formulation Sciences, MedImmune Ltd., Cambridge, United Kingdom.|Department of Formulation Sciences, MedImmune Ltd., Cambridge, United Kingdom.|Analytical Biochemistry Department, MedImmune LLC, Gaithersburg, Maryland, United States of America.|Department of Physics and Optical Science, University of North Carolina at Charlotte, Charlotte, North Carolina, United States of America.|Department of Bioinformatics and Genomics, University of North Carolina at Charlotte, Charlotte, North Carolina, United States of America.', 'United States|United Kingdom|United Kingdom|United States|United States|United States', 0, 'Antibodies|Computer Simulation|Evolution, Molecular|Immunoglobulin Fab Fragments|Models, Chemical|Models, Genetic|Mutation|Protein Conformation|Quantitative Structure-Activity Relationship', 'Journal Article', '10.1371/journal.pcbi.1004327', '26132144', 'The effects of somatic mutations that transform polyspecific germline (GL) antibodies to affinity mature (AM) antibodies with monospecificity are compared among three GL-AM Fab pairs. In particular, changes in conformational flexibility are assessed using a Distance Constraint Model (DCM). We have previously established that the DCM can be robustly applied across a series of antibody fragments (VL to Fab), and subsequently, the DCM was combined with molecular dynamics (MD) simulations to similarly characterize five thermostabilizing scFv mutants. The DCM is an ensemble based statistical mechanical approach that accounts for enthalpy/entropy compensation due to network rigidity, which has been quite successful in elucidating conformational flexibility and Quantitative Stability/Flexibility Relationships (QSFR) in proteins. Applied to three disparate antibody systems changes in QSFR quantities indicate that the VH domain is typically rigidified, whereas the VL domain and CDR L2 loop become more flexible during affinity maturation. The increase in CDR H3 loop rigidity is consistent with other studies in the literature. The redistribution of conformational flexibility is largely controlled by nonspecific changes in the H-bond network, although certain Arg to Asp salt bridges create highly localized rigidity increases. Taken together, these results reveal an intricate flexibility/rigidity response that accompanies affinity maturation. '),
(87238, 2015, 'plos', 'From What Is? to What Isnt? Computational Biology', 'Nussinov, Ruth|Bonhoeffer, Sebastian|Papin, Jason A|Sporns, Olaf', 'Cancer and Inflammation Program, Leidos Biomedical Research, Inc., Frederick National Laboratory for Cancer Research, National Cancer Institute, Frederick, Maryland, United States of America, Sackler Institute of Molecular Medicine, Department of Human Genetics and Molecular Medicine, Sackler School of Medicine, Tel Aviv University, Tel Aviv, Israel.|Theoretical Biology Group, Institute of Integrative Biology, ETH Zurich, Zurich, Switzerland.|Department of Biomedical Engineering, University of Virginia, Charlottesville, Virginia, United States of America.|Department of Psychological and Brain Sciences, Indiana University, Bloomington, Indiana, United States of America.', 'Israel|Switzerland|United States|India', 0, 'Computational Biology|Genomics|Models, Biological|Periodicals as Topic|Research Design|Terminology as Topic', 'Editorial', '10.1371/journal.pcbi.1004318', '26134043', '-'),
(87239, 2015, 'plos', 'Structural Model of RNA Polymerase II Elongation Complex with Complete Transcription Bubble Reveals NTP Entry Routes', 'Zhang, Lu|Silva, Daniel-Adriano|Pardo-Avila, Fátima|Wang, Dong|Huang, Xuhui', 'Department of Chemistry and State Key Laboratory of Molecular Neuroscience, Center for System Biology and Human Health, School of Science and IAS, The Hong Kong University of Science and Technology, Kowloon, Hong Kong.|Department of Chemistry and State Key Laboratory of Molecular Neuroscience, Center for System Biology and Human Health, School of Science and IAS, The Hong Kong University of Science and Technology, Kowloon, Hong Kong.|Department of Chemistry and State Key Laboratory of Molecular Neuroscience, Center for System Biology and Human Health, School of Science and IAS, The Hong Kong University of Science and Technology, Kowloon, Hong Kong.|Skaggs School of Pharmacy and Pharmaceutical Sciences, University of California, San Diego, La Jolla, California, United States of America.|Department of Chemistry and State Key Laboratory of Molecular Neuroscience, Center for System Biology and Human Health, School of Science and IAS, The Hong Kong University of Science and Technology, Kowloon, Hong Kong.', 'Hong Kong|Hong Kong|Hong Kong|United States|Hong Kong', 8, 'Binding Sites|DNA|Diffusion|Molecular Dynamics Simulation|Nucleic Acid Conformation|Nucleotides|Protein Binding|Protein Conformation|RNA|RNA Polymerase II|Transcription, Genetic', 'Journal Article', '10.1371/journal.pcbi.1004354', '26134169', 'The RNA polymerase II (Pol II) is a eukaryotic enzyme that catalyzes the synthesis of the messenger RNA using a DNA template. Despite numerous biochemical and biophysical studies, it remains elusive whether the secondary channel is the only route for NTP to reach the active site of the enzyme or if the main channel could be an alternative. On this regard, crystallographic structures of Pol II have been extremely useful to understand the structural basis of transcription, however, the conformation of the unpaired non-template DNA part of the full transcription bubble (TB) is still unknown. Since diffusion routes of the nucleoside triphosphate (NTP) substrate through the main channel might overlap with the TB region, gaining structural information of the full TB is critical for a complete understanding of Pol II transcription process. In this study, we have built a structural model of Pol II with a complete transcription bubble based on multiple sources of existing structural data and used Molecular Dynamics (MD) simulations together with structural analysis to shed light on NTP entry pathways. Interestingly, we found that although both channels have enough space to allow NTP loading, the percentage of MD conformations containing enough space for NTP loading through the secondary channel is twice higher than that of the main channel. Further energetic study based on MD simulations with NTP loaded in the channels has revealed that the diffusion of the NTP through the main channel is greatly disfavored by electrostatic repulsion between the NTP and the highly negatively charged backbones of nucleotides in the non-template DNA strand. Taken together, our results suggest that the secondary channel is the major route for NTP entry during Pol II transcription. '),
(87240, 2015, 'plos', 'Predicting Binding Free Energy Change Caused by Point Mutations with Knowledge-Modified MM/PBSA Method', 'Petukh, Marharyta|Li, Minghui|Alexov, Emil', 'Computational Biophysics and Bioinformatics, Department of Physics, Clemson University, Clemson, South Carolina, United States of America.|National Center for Biotechnology Information, National Library of Medicine, National Institutes of Health, Bethesda, Maryland, United States of America.|Computational Biophysics and Bioinformatics, Department of Physics, Clemson University, Clemson, South Carolina, United States of America.', 'United States|United States|United States', 0, 'Amino Acid Sequence|Amino Acid Substitution|Binding Sites|Computer Simulation|Energy Transfer|Models, Chemical|Models, Statistical|Molecular Sequence Data|Point Mutation|Protein Binding|Protein Interaction Mapping|Proteins|Sequence Analysis, Protein', 'Evaluation Studies', '10.1371/journal.pcbi.1004276', '26146996', 'A new methodology termed Single Amino Acid Mutation based change in Binding free Energy (SAAMBE) was developed to predict the changes of the binding free energy caused by mutations. The method utilizes 3D structures of the corresponding protein-protein complexes and takes advantage of both approaches: sequence- and structure-based methods. The method has two components: a MM/PBSA-based component, and an additional set of statistical terms delivered from statistical investigation of physico-chemical properties of protein complexes. While the approach is rigid body approach and does not explicitly consider plausible conformational changes caused by the binding, the effect of conformational changes, including changes away from binding interface, on electrostatics are mimicked with amino acid specific dielectric constants. This provides significant improvement of SAAMBE predictions as indicated by better match against experimentally determined binding free energy changes over 1300 mutations in 43 proteins. The final benchmarking resulted in a very good agreement with experimental data (correlation coefficient 0.624) while the algorithm being fast enough to allow for large-scale calculations (the average time is less than a minute per mutation). '),
(87241, 2015, 'plos', 'Design of Protein Multi-specificity Using an Independent Sequence Search Reduces the Barrier to Low Energy Sequences', 'Sevy, Alexander M|Jacobs, Tim M|Crowe, James E|Meiler, Jens', 'Center for Structural Biology, Vanderbilt University, Nashville, Tennessee, United States of America.|Department of Biochemistry, University of North Carolina at Chapel Hill, Chapel Hill, North Carolina, United States of America.|Vanderbilt Vaccine Center, Vanderbilt University Medical Center, Nashville, Tennessee, United States of America.|Center for Structural Biology, Vanderbilt University, Nashville, Tennessee, United States of America, Department of Chemistry, Vanderbilt University, Nashville, Tennessee, United States of America.', 'United States|United States|United States|United States', 0, 'Algorithms|Amino Acid Sequence|Binding Sites|Computer Simulation|Directed Molecular Evolution|Drug Design|Energy Transfer|Models, Chemical|Models, Molecular|Molecular Sequence Data|Protein Binding|Protein Engineering|Proteins|Sequence Analysis, Protein|Structure-Activity Relationship|Thermodynamics', 'Journal Article', '10.1371/journal.pcbi.1004300', '26147100', 'Computational protein design has found great success in engineering proteins for thermodynamic stability, binding specificity, or enzymatic activity in a single state design (SSD) paradigm. Multi-specificity design (MSD), on the other hand, involves considering the stability of multiple protein states simultaneously. We have developed a novel MSD algorithm, which we refer to as REstrained CONvergence in multi-specificity design (RECON). The algorithm allows each state to adopt its own sequence throughout the design process rather than enforcing a single sequence on all states. Convergence to a single sequence is encouraged through an incrementally increasing convergence restraint for corresponding positions. Compared to MSD algorithms that enforce (constrain) an identical sequence on all states the energy landscape is simplified, which accelerates the search drastically. As a result, RECON can readily be used in simulations with a flexible protein backbone. We have benchmarked RECON on two design tasks. First, we designed antibodies derived from a common germline gene against their diverse targets to assess recovery of the germline, polyspecific sequence. Second, we design promiscuous, polyspecific proteins against all binding partners and measure recovery of the native sequence. We show that RECON is able to efficiently recover native-like, biologically relevant sequences in this diverse set of protein complexes. '),
(87242, 2015, 'plos', 'Measuring Asymmetry in Time-Stamped Phylogenies', 'Dearlove, Bethany L|Frost, Simon D W', 'Department of Veterinary Medicine, University of Cambridge, Cambridge, United Kingdom.|Department of Veterinary Medicine, University of Cambridge, Cambridge, United Kingdom.', 'United Kingdom|United Kingdom', 9, 'Biological Evolution|Computer Simulation|Genetic Speciation|Genetic Variation|Genetics, Population|Models, Genetic|Models, Statistical|Mutation|Pedigree|Phylogeny|Viruses', 'Journal Article', '10.1371/journal.pcbi.1004312', '26147205', 'Previous work has shown that asymmetry in viral phylogenies may be indicative of heterogeneity in transmission, for example due to acute HIV infection or the presence of core groups with higher contact rates. Hence, evidence of asymmetry may provide clues to underlying population structure, even when direct information on, for example, stage of infection or contact rates, are missing. However, current tests of phylogenetic asymmetry (a) suffer from false positives when the tips of the phylogeny are sampled at different times and (b) only test for global asymmetry, and hence suffer from false negatives when asymmetry is localised to part of a phylogeny. We present a simple permutation-based approach for testing for asymmetry in a phylogeny, where we compare the observed phylogeny with random phylogenies with the same sampling and coalescence times, to reduce the false positive rate. We also demonstrate how profiles of measures of asymmetry calculated over a range of evolutionary times in the phylogeny can be used to identify local asymmetry. In combination with different metrics of asymmetry, this combined approach offers detailed insights of how phylogenies reconstructed from real viral datasets may deviate from the simplistic assumptions of commonly used coalescent and birth-death process models. '),
(87243, 2015, 'plos', 'Thermodynamics and H2 Transfer in a Methanogenic, Syntrophic Community', 'Hamilton, Joshua J|Calixto Contreras, Montserrat|Reed, Jennifer L', 'Department of Chemical and Biological Engineering, University of Wisconsin-Madison, Madison, Wisconsin, United States of America.|Department of Chemical and Biological Engineering, University of Wisconsin-Madison, Madison, Wisconsin, United States of America.|Department of Chemical and Biological Engineering, University of Wisconsin-Madison, Madison, Wisconsin, United States of America.', 'United States|United States|United States', 0, 'Computer Simulation|Deltaproteobacteria|Energy Transfer|Hydrogen|Methane|Methanospirillum|Microbial Consortia|Models, Biological|Symbiosis|Thermodynamics', 'Journal Article', '10.1371/journal.pcbi.1004364', '26147299', 'Microorganisms in nature do not exist in isolation but rather interact with other species in their environment. Some microbes interact via syntrophic associations, in which the metabolic by-products of one species serve as nutrients for another. These associations sustain a variety of natural communities, including those involved in methanogenesis. In anaerobic syntrophic communities, energy is transferred from one species to another, either through direct contact and exchange of electrons, or through small molecule diffusion. Thermodynamics plays an important role in governing these interactions, as the oxidation reactions carried out by the first community member are only possible because degradation products are consumed by the second community member. This work presents the development and analysis of genome-scale network reconstructions of the bacterium Syntrophobacter fumaroxidans and the methanogenic archaeon Methanospirillum hungatei. The models were used to verify proposed mechanisms of ATP production within each species. We then identified additional constraints and the cellular objective function required to match experimental observations. The thermodynamic S. fumaroxidans model could not explain why S. fumaroxidans does not produce H2 in monoculture, indicating that current methods might not adequately estimate the thermodynamics, or that other cellular processes (e.g., regulation) play a role. We also developed a thermodynamic coculture model of the association between the organisms. The coculture model correctly predicted the exchange of both H2 and formate between the two species and suggested conditions under which H2 and formate produced by S. fumaroxidans would be fully consumed by M. hungatei. ');
INSERT INTO `papers` (`id`, `ano`, `journal`, `titulo`, `autores`, `afiliacao`, `pais`, `citacoes`, `palavra_chave`, `categorias`, `doi`, `pubmed`, `abstract`) VALUES
(87244, 2015, 'plos', 'Stability of Neuronal Networks with Homeostatic Regulation', 'Harnack, Daniel|Pelko, Miha|Chaillet, Antoine|Chitour, Yacine|van Rossum, Mark C W', 'School of Informatics, University of Edinburgh, Edinburgh, United Kingdom.|School of Informatics, University of Edinburgh, Edinburgh, United Kingdom.|L2S-Univ. Paris Sud-CentraleSupélec, Gif sur Yvette, France.|L2S-Univ. Paris Sud-CentraleSupélec, Gif sur Yvette, France.|School of Informatics, University of Edinburgh, Edinburgh, United Kingdom.', 'United Kingdom|United Kingdom|France|France|United Kingdom', 0, 'Action Potentials|Animals|Biological Clocks|Computer Simulation|Feedback, Physiological|Homeostasis|Humans|Models, Neurological|Nerve Net', 'Journal Article', '10.1371/journal.pcbi.1004357', '26154297', 'Neurons are equipped with homeostatic mechanisms that counteract long-term perturbations of their average activity and thereby keep neurons in a healthy and information-rich operating regime. While homeostasis is believed to be crucial for neural function, a systematic analysis of homeostatic control has largely been lacking. The analysis presented here analyses the necessary conditions for stable homeostatic control. We consider networks of neurons with homeostasis and show that homeostatic control that is stable for single neurons, can destabilize activity in otherwise stable recurrent networks leading to strong non-abating oscillations in the activity. This instability can be prevented by slowing down the homeostatic control. The stronger the network recurrence, the slower the homeostasis has to be. Next, we consider how non-linearities in the neural activation function affect these constraints. Finally, we consider the case that homeostatic feedback is mediated via a cascade of multiple intermediate stages. Counter-intuitively, the addition of extra stages in the homeostatic control loop further destabilizes activity in single neurons and networks. Our theoretical framework for homeostasis thus reveals previously unconsidered constraints on homeostasis in biological networks, and identifies conditions that require the slow time-constants of homeostatic regulation observed experimentally. '),
(87245, 2015, 'plos', 'Correction: An Integrative Approach for Modeling and Simulation of Heterocyst Pattern Formation in Cyanobacteria Filaments', 'PLOS Computational Biology Staff', 'School of Informatics, University of Edinburgh, Edinburgh, United Kingdom.', 'United Kingdom', 0, '-', 'Published Erratum', '10.1371/journal.pcbi.1004378', '26154339', '-'),
(87246, 2015, 'plos', 'Evaluating Spatial Interaction Models for Regional Mobility in Sub-Saharan Africa', 'Wesolowski, Amy|OMeara, Wendy Prudhomme|Eagle, Nathan|Tatem, Andrew J|Buckee, Caroline O', 'Department of Epidemiology, Harvard School of Public Health, Boston, Massachusetts, United States of America, Center for Communicable Disease Dynamics, Harvard School of Public Health, Boston, Massachusetts, United States of America.|Department of Medicine, Duke University and Duke Global Health Institute, Durham, North Carolina, United States of America.|Department of Epidemiology, Harvard School of Public Health, Boston, Massachusetts, United States of America, College of Computer and Information Science, Northeastern University, Boston, Massachusetts, United States of America.|Department of Geography and Environment, University of Southampton, Southampton, United Kingdom, Fogarty International Center, National Institutes of Health, Bethesda, Maryland, United States of America.|Department of Epidemiology, Harvard School of Public Health, Boston, Massachusetts, United States of America, Center for Communicable Disease Dynamics, Harvard School of Public Health, Boston, Massachusetts, United States of America.', 'United States|United States|United States|United Kingdom|United States', 0, 'Africa South of the Sahara|Cell Phone|Computer Simulation|Employment|Humans|Models, Statistical|Population Dynamics|Spatio-Temporal Analysis|Travel', 'Journal Article', '10.1371/journal.pcbi.1004267', '26158274', 'Simple spatial interaction models of human mobility based on physical laws have been used extensively in the social, biological, and physical sciences, and in the study of the human dynamics underlying the spread of disease. Recent analyses of commuting patterns and travel behavior in high-income countries have led to the suggestion that these models are highly generalizable, and as a result, gravity and radiation models have become standard tools for describing population mobility dynamics for infectious disease epidemiology. Communities in Sub-Saharan Africa may not conform to these models, however, physical accessibility, availability of transport, and cost of travel between locations may be variable and severely constrained compared to high-income settings, informal labor movements rather than regular commuting patterns are often the norm, and the rise of mega-cities across the continent has important implications for travel between rural and urban areas. Here, we first review how infectious disease frameworks incorporate human mobility on different spatial scales and use anonymous mobile phone data from nearly 15 million individuals to analyze the spatiotemporal dynamics of the Kenyan population. We find that gravity and radiation models fail in systematic ways to capture human mobility measured by mobile phones, both severely overestimate the spatial spread of travel and perform poorly in rural areas, but each exhibits different characteristic patterns of failure with respect to routes and volumes of travel. Thus, infectious disease frameworks that rely on spatial interaction models are likely to misrepresent population dynamics important for the spread of disease in many African populations. '),
(87247, 2015, 'plos', 'Genome Modeling System: A Knowledge Management Platform for Genomics', 'Griffith, Malachi|Griffith, Obi L|Smith, Scott M|Ramu, Avinash|Callaway, Matthew B|Brummett, Anthony M|Kiwala, Michael J|Coffman, Adam C|Regier, Allison A|Oberkfell, Ben J|Sanderson, Gabriel E|Mooney, Thomas P|Nutter, Nathaniel G|Belter, Edward A|Du, Feiyu|Long, Robert L|Abbott, Travis E|Ferguson, Ian T|Morton, David L|Burnett, Mark M|Weible, James V|Peck, Joshua B|Dukes, Adam|McMichael, Joshua F|Lolofie, Justin T|Derickson, Brian R|Hundal, Jasreet|Skidmore, Zachary L|Ainscough, Benjamin J|Dees, Nathan D|Schierding, William S|Kandoth, Cyriac|Kim, Kyung H|Lu, Charles|Harris, Christopher C|Maher, Nicole|Maher, Christopher A|Magrini, Vincent J|Abbott, Benjamin S|Chen, Ken|Clark, Eric|Das, Indraniel|Fan, Xian|Hawkins, Amy E|Hepler, Todd G|Wylie, Todd N|Leonard, Shawn M|Schroeder, William E|Shi, Xiaoqi|Carmichael, Lynn K|Weil, Matthew R|Wohlstadter, Richard W|Stiehr, Gary|McLellan, Michael D|Pohl, Craig S|Miller, Christopher A|Koboldt, Daniel C|Walker, Jason R|Eldred, James M|Larson, David E|Dooling, David J|Ding, Li|Mardis, Elaine R|Wilson, Richard K', 'The Genome Institute, Washington University in St. Louis, St. Louis, Missouri, United States of America, Department of Genetics, Washington University School of Medicine, St. Louis, Missouri, United States of America.|The Genome Institute, Washington University in St. Louis, St. Louis, Missouri, United States of America, Department of Medicine, Washington University School of Medicine, St. Louis, Missouri, United States of America.|The Genome Institute, Washington University in St. Louis, St. Louis, Missouri, United States of America.|The Genome Institute, Washington University in St. Louis, St. Louis, Missouri, United States of America.|The Genome Institute, Washington University in St. Louis, St. Louis, Missouri, United States of America.|The Genome Institute, Washington University in St. Louis, St. Louis, Missouri, United States of America.|The Genome Institute, Washington University in St. Louis, St. Louis, Missouri, United States of America.|The Genome Institute, Washington University in St. Louis, St. Louis, Missouri, United States of America.|The Genome Institute, Washington University in St. Louis, St. Louis, Missouri, United States of America.|The Genome Institute, Washington University in St. Louis, St. Louis, Missouri, United States of America.|The Genome Institute, Washington University in St. Louis, St. Louis, Missouri, United States of America.|The Genome Institute, Washington University in St. Louis, St. Louis, Missouri, United States of America.|The Genome Institute, Washington University in St. Louis, St. Louis, Missouri, United States of America.|The Genome Institute, Washington University in St. Louis, St. Louis, Missouri, United States of America.|The Genome Institute, Washington University in St. Louis, St. Louis, Missouri, United States of America.|The Genome Institute, Washington University in St. Louis, St. Louis, Missouri, United States of America.|The Genome Institute, Washington University in St. Louis, St. Louis, Missouri, United States of America.|The Genome Institute, Washington University in St. Louis, St. Louis, Missouri, United States of America.|The Genome Institute, Washington University in St. Louis, St. Louis, Missouri, United States of America.|The Genome Institute, Washington University in St. Louis, St. Louis, Missouri, United States of America.|The Genome Institute, Washington University in St. Louis, St. Louis, Missouri, United States of America.|The Genome Institute, Washington University in St. Louis, St. Louis, Missouri, United States of America.|The Genome Institute, Washington University in St. Louis, St. Louis, Missouri, United States of America.|The Genome Institute, Washington University in St. Louis, St. Louis, Missouri, United States of America.|The Genome Institute, Washington University in St. Louis, St. Louis, Missouri, United States of America.|The Genome Institute, Washington University in St. Louis, St. Louis, Missouri, United States of America.|The Genome Institute, Washington University in St. Louis, St. Louis, Missouri, United States of America.|The Genome Institute, Washington University in St. Louis, St. Louis, Missouri, United States of America.|The Genome Institute, Washington University in St. Louis, St. Louis, Missouri, United States of America.|The Genome Institute, Washington University in St. Louis, St. Louis, Missouri, United States of America.|The Genome Institute, Washington University in St. Louis, St. Louis, Missouri, United States of America.|The Genome Institute, Washington University in St. Louis, St. Louis, Missouri, United States of America.|The Genome Institute, Washington University in St. Louis, St. Louis, Missouri, United States of America.|The Genome Institute, Washington University in St. Louis, St. Louis, Missouri, United States of America.|The Genome Institute, Washington University in St. Louis, St. Louis, Missouri, United States of America.|Department of Medicine, Washington University School of Medicine, St. Louis, Missouri, United States of America.|The Genome Institute, Washington University in St. Louis, St. Louis, Missouri, United States of America, Department of Medicine, Washington University School of Medicine, St. Louis, Missouri, United States of America, Siteman Cancer Center, Washington University School of Medicine, St. Louis, Missouri, United States of America.|The Genome Institute, Washington University in St. Louis, St. Louis, Missouri, United States of America, Department of Genetics, Washington University School of Medicine, St. Louis, Missouri, United States of America.|The Genome Institute, Washington University in St. Louis, St. Louis, Missouri, United States of America.|The Genome Institute, Washington University in St. Louis, St. Louis, Missouri, United States of America.|The Genome Institute, Washington University in St. Louis, St. Louis, Missouri, United States of America.|The Genome Institute, Washington University in St. Louis, St. Louis, Missouri, United States of America.|The Genome Institute, Washington University in St. Louis, St. Louis, Missouri, United States of America.|The Genome Institute, Washington University in St. Louis, St. Louis, Missouri, United States of America.|The Genome Institute, Washington University in St. Louis, St. Louis, Missouri, United States of America.|The Genome Institute, Washington University in St. Louis, St. Louis, Missouri, United States of America.|The Genome Institute, Washington University in St. Louis, St. Louis, Missouri, United States of America.|The Genome Institute, Washington University in St. Louis, St. Louis, Missouri, United States of America.|The Genome Institute, Washington University in St. Louis, St. Louis, Missouri, United States of America.|The Genome Institute, Washington University in St. Louis, St. Louis, Missouri, United States of America.|The Genome Institute, Washington University in St. Louis, St. Louis, Missouri, United States of America.|The Genome Institute, Washington University in St. Louis, St. Louis, Missouri, United States of America.|The Genome Institute, Washington University in St. Louis, St. Louis, Missouri, United States of America.|The Genome Institute, Washington University in St. Louis, St. Louis, Missouri, United States of America.|The Genome Institute, Washington University in St. Louis, St. Louis, Missouri, United States of America.|The Genome Institute, Washington University in St. Louis, St. Louis, Missouri, United States of America.|The Genome Institute, Washington University in St. Louis, St. Louis, Missouri, United States of America.|The Genome Institute, Washington University in St. Louis, St. Louis, Missouri, United States of America.|The Genome Institute, Washington University in St. Louis, St. Louis, Missouri, United States of America.|The Genome Institute, Washington University in St. Louis, St. Louis, Missouri, United States of America, Department of Genetics, Washington University School of Medicine, St. Louis, Missouri, United States of America.|The Genome Institute, Washington University in St. Louis, St. Louis, Missouri, United States of America.|The Genome Institute, Washington University in St. Louis, St. Louis, Missouri, United States of America, Department of Genetics, Washington University School of Medicine, St. Louis, Missouri, United States of America, Siteman Cancer Center, Washington University School of Medicine, St. Louis, Missouri, United States of America.|The Genome Institute, Washington University in St. Louis, St. Louis, Missouri, United States of America, Department of Genetics, Washington University School of Medicine, St. Louis, Missouri, United States of America, Department of Medicine, Washington University School of Medicine, St. Louis, Missouri, United States of America, Siteman Cancer Center, Washington University School of Medicine, St. Louis, Missouri, United States of America, Department of Molecular Microbiology, Washington University School of Medicine, St. Louis, Missouri, United States of America.|The Genome Institute, Washington University in St. Louis, St. Louis, Missouri, United States of America, Department of Genetics, Washington University School of Medicine, St. Louis, Missouri, United States of America, Department of Medicine, Washington University School of Medicine, St. Louis, Missouri, United States of America, Siteman Cancer Center, Washington University School of Medicine, St. Louis, Missouri, United States of America, Department of Molecular Microbiology, Washington University School of Medicine, St. Louis, Missouri, United States of America.', 'United States|United States|United States|United States|United States|United States|United States|Un', 40, 'Algorithms|Chromosome Mapping|Computer Simulation|Database Management Systems|Databases, Genetic|Genome, Human|Humans|Knowledge Bases|Models, Genetic|Sequence Alignment|Sequence Analysis, DNA|User-Computer Interface', 'Journal Article', '10.1371/journal.pcbi.1004274', '26158448', 'In this work, we present the Genome Modeling System (GMS), an analysis information management system capable of executing automated genome analysis pipelines at a massive scale. The GMS framework provides detailed tracking of samples and data coupled with reliable and repeatable analysis pipelines. The GMS also serves as a platform for bioinformatics development, allowing a large team to collaborate on data analysis, or an individual researcher to leverage the work of others effectively within its data management system. Rather than separating ad-hoc analysis from rigorous, reproducible pipelines, the GMS promotes systematic integration between the two. As a demonstration of the GMS, we performed an integrated analysis of whole genome, exome and transcriptome sequencing data from a breast cancer cell line (HCC1395) and matched lymphoblastoid line (HCC1395BL). These data are available for users to test the software, complete tutorials and develop novel GMS pipeline configurations. The GMS is available at https://github.com/genome/gms. '),
(87248, 2015, 'plos', 'How Co-translational Folding of Multi-domain Protein Is Affected by Elongation Schedule: Molecular Simulations', 'Tanaka, Tomohiro|Hori, Naoto|Takada, Shoji', 'Department of Biophysics, Graduate School of Science, Kyoto University, Kyoto, Japan.|Department of Biophysics, Graduate School of Science, Kyoto University, Kyoto, Japan.|Department of Biophysics, Graduate School of Science, Kyoto University, Kyoto, Japan.', 'Japan|Japan|Japan', 0, 'Elastic Modulus|Escherichia coli Proteins|Models, Chemical|Molecular Dynamics Simulation|Peptide Chain Elongation, Translational|Protein Conformation|Protein Folding|Protein Structure, Tertiary', 'Journal Article', '10.1371/journal.pcbi.1004356', '26158498', 'Co-translational folding (CTF) facilitates correct folding in vivo, but its precise mechanism remains elusive. For the CTF of a three-domain protein SufI, it was reported that the translational attenuation is obligatory to acquire the functional state. Here, to gain structural insights on the underlying mechanisms, we performed comparative molecular simulations of SufI that mimic CTF as well as refolding schemes. A CTF scheme that relied on a codon-based prediction of translational rates exhibited folding probability markedly higher than that by the refolding scheme. When the CTF schedule is speeded up, the success rate dropped. These agree with experiments. Structural investigation clarified that misfolding of the middle domain was much more frequent in the refolding scheme than that in the codon-based CTF scheme. The middle domain is less stable and can fold via interactions with the folded N-terminal domain. Folding pathway networks showed the codon-based CTF gives narrower pathways to the native state than the refolding scheme. '),
(87249, 2015, 'plos', 'A Diffusive Homeostatic Signal Maintains Neural Heterogeneity and Responsiveness in Cortical Networks', 'Sweeney, Yann|Hellgren Kotaleski, Jeanette|Hennig, Matthias H', 'Institute for Adaptive and Neural Computation, School of Informatics, University of Edinburgh, Edinburgh, United Kingdom, Department of Computational Biology, School of Computer Science and Communication, Royal Institute of Technology, Stockholm, Sweden.|Department of Computational Biology, School of Computer Science and Communication, Royal Institute of Technology, Stockholm, Sweden.|Institute for Adaptive and Neural Computation, School of Informatics, University of Edinburgh, Edinburgh, United Kingdom.', 'United Kingdom|Sweden|United Kingdom', 11, 'Action Potentials|Animals|Computer Simulation|Homeostasis|Humans|Models, Neurological|Nerve Net|Neuronal Plasticity|Neurotransmitter Agents|Nitric Oxide', 'Journal Article', '10.1371/journal.pcbi.1004389', '26158556', 'Gaseous neurotransmitters such as nitric oxide (NO) provide a unique and often overlooked mechanism for neurons to communicate through diffusion within a network, independent of synaptic connectivity. NO provides homeostatic control of intrinsic excitability. Here we conduct a theoretical investigation of the distinguishing roles of NO-mediated diffusive homeostasis in comparison with canonical non-diffusive homeostasis in cortical networks. We find that both forms of homeostasis provide a robust mechanism for maintaining stable activity following perturbations. However, the resulting networks differ, with diffusive homeostasis maintaining substantial heterogeneity in activity levels of individual neurons, a feature disrupted in networks with non-diffusive homeostasis. This results in networks capable of representing input heterogeneity, and linearly responding over a broader range of inputs than those undergoing non-diffusive homeostasis. We further show that these properties are preserved when homeostatic and Hebbian plasticity are combined. These results suggest a mechanism for dynamically maintaining neural heterogeneity, and expose computational advantages of non-local homeostatic processes. '),
(87250, 2015, 'plos', 'Heterogeneous Network Edge Prediction: A Data Integration Approach to Prioritize Disease-Associated Genes', 'Himmelstein, Daniel S|Baranzini, Sergio E', 'Biological & Medical Informatics, University of California, San Francisco, San Francisco, California, United States of America.|Biological & Medical Informatics, University of California, San Francisco, San Francisco, California, United States of America, Department of Neurology, University of California, San Francisco, San Francisco, California, United States of America, Institute for Human Genetics, University of California, San Francisco, San Francisco, California, United States of America.', 'United States|United States', 35, 'Algorithms|Animals|Chromosome Mapping|Data Mining|Databases, Genetic|Genetic Predisposition to Disease|Genome-Wide Association Study|Humans|Protein Interaction Mapping|Proteome|Signal Transduction|Systems Integration', 'Journal Article', '10.1371/journal.pcbi.1004259', '26158728', 'The first decade of Genome Wide Association Studies (GWAS) has uncovered a wealth of disease-associated variants. Two important derivations will be the translation of this information into a multiscale understanding of pathogenic variants and leveraging existing data to increase the power of existing and future studies through prioritization. We explore edge prediction on heterogeneous networks--graphs with multiple node and edge types--for accomplishing both tasks. First we constructed a network with 18 node types--genes, diseases, tissues, pathophysiologies, and 14 MSigDB (molecular signatures database) collections--and 19 edge types from high-throughput publicly-available resources. From this network composed of 40,343 nodes and 1,608,168 edges, we extracted features that describe the topology between specific genes and diseases. Next, we trained a model from GWAS associations and predicted the probability of association between each protein-coding gene and each of 29 well-studied complex diseases. The model, which achieved 132-fold enrichment in precision at 10% recall, outperformed any individual domain, highlighting the benefit of integrative approaches. We identified pleiotropy, transcriptional signatures of perturbations, pathways, and protein interactions as influential mechanisms explaining pathogenesis. Our method successfully predicted the results (with AUROC = 0.79) from a withheld multiple sclerosis (MS) GWAS despite starting with only 13 previously associated genes. Finally, we combined our network predictions with statistical evidence of association to propose four novel MS genes, three of which (JAK2, REL, RUNX3) validated on the masked GWAS. Furthermore, our predictions provide biological support highlighting REL as the causal gene within its gene-rich locus. Users can browse all predictions online (http://het.io). Heterogeneous network edge prediction effectively prioritized genetic associations and provides a powerful new approach for data integration across multiple domains.'),
(87251, 2015, 'plos', 'A Computational Model of a Descending Mechanosensory Pathway Involved in Active Tactile Sensing', 'Ache, Jan M|Dürr, Volker', 'Department of Biological Cybernetics, Faculty of Biology, Bielefeld University, Bielefeld, Germany, Cognitive Interaction Technology-Center of Excellence, Bielefeld University, Bielefeld, Germany.|Department of Biological Cybernetics, Faculty of Biology, Bielefeld University, Bielefeld, Germany, Cognitive Interaction Technology-Center of Excellence, Bielefeld University, Bielefeld, Germany.', 'Germany|Germany', 0, 'Animals|Computer Simulation|Insecta|Mechanoreceptors|Mechanotransduction, Cellular|Models, Neurological|Neural Pathways|Sense Organs|Touch', 'Journal Article', '10.1371/journal.pcbi.1004263', '26158851', 'Many animals, including humans, rely on active tactile sensing to explore the environment and negotiate obstacles, especially in the dark. Here, we model a descending neural pathway that mediates short-latency proprioceptive information from a tactile sensor on the head to thoracic neural networks. We studied the nocturnal stick insect Carausius morosus, a model organism for the study of adaptive locomotion, including tactually mediated reaching movements. Like mammals, insects need to move their tactile sensors for probing the environment. Cues about sensor position and motion are therefore crucial for the spatial localization of tactile contacts and the coordination of fast, adaptive motor responses. Our model explains how proprioceptive information about motion and position of the antennae, the main tactile sensors in insects, can be encoded by a single type of mechanosensory afferents. Moreover, it explains how this information is integrated and mediated to thoracic neural networks by a diverse population of descending interneurons (DINs). First, we quantified responses of a DIN population to changes in antennal position, motion and direction of movement. Using principal component (PC) analysis, we find that only two PCs account for a large fraction of the variance in the DIN response properties. We call the two-dimensional space spanned by these PCs coding-space because it captures essential features of the entire DIN population. Second, we model the mechanoreceptive input elements of this descending pathway, a population of proprioceptive mechanosensory hairs monitoring deflection of the antennal joints. Finally, we propose a computational framework that can model the response properties of all important DIN types, using the hair field model as its only input. This DIN model is validated by comparison of tuning characteristics, and by mapping the modelled neurons into the two-dimensional coding-space of the real DIN population. This reveals the versatility of the framework for modelling a complete descending neural pathway. '),
(87252, 2015, 'plos', 'Geometry of the Gene Expression Space of Individual Cells', 'Korem, Yael|Szekely, Pablo|Hart, Yuval|Sheftel, Hila|Hausser, Jean|Mayo, Avi|Rothenberg, Michael E|Kalisky, Tomer|Alon, Uri', 'Department of Molecular Cell Biology, Weizmann Institute of Science, Rehovot, Israel.|Department of Molecular Cell Biology, Weizmann Institute of Science, Rehovot, Israel.|Department of Molecular Cell Biology, Weizmann Institute of Science, Rehovot, Israel.|Department of Molecular Cell Biology, Weizmann Institute of Science, Rehovot, Israel.|Department of Molecular Cell Biology, Weizmann Institute of Science, Rehovot, Israel.|Department of Molecular Cell Biology, Weizmann Institute of Science, Rehovot, Israel.|Department of Medicine, Division of Gastroenterology and Hepatology, and Institute for Stem Cell Biology and Regenerative Medicine, Stanford University, Stanford, California, United States of America.|Faculty of Engineering, Bar Ilan University, Ramat Gan, Israel.|Department of Molecular Cell Biology, Weizmann Institute of Science, Rehovot, Israel.', 'Israel|Israel|Israel|Israel|Israel|Israel|United States|Israel|Israel', 29, 'Animals|Cell Differentiation|Cells, Cultured|Computer Simulation|Gene Expression Regulation|Humans|Mice|Models, Biological|Models, Statistical|Proteins|Spatio-Temporal Analysis', 'Journal Article', '10.1371/journal.pcbi.1004224', '26161936', 'There is a revolution in the ability to analyze gene expression of single cells in a tissue. To understand this data we must comprehend how cells are distributed in a high-dimensional gene expression space. One open question is whether cell types form discrete clusters or whether gene expression forms a continuum of states. If such a continuum exists, what is its geometry? Recent theory on evolutionary trade-offs suggests that cells that need to perform multiple tasks are arranged in a polygon or polyhedron (line, triangle, tetrahedron and so on, generally called polytopes) in gene expression space, whose vertices are the expression profiles optimal for each task. Here, we analyze single-cell data from human and mouse tissues profiled using a variety of single-cell technologies. We fit the data to shapes with different numbers of vertices, compute their statistical significance, and infer their tasks. We find cases in which single cells fill out a continuum of expression states within a polyhedron. This occurs in intestinal progenitor cells, which fill out a tetrahedron in gene expression space. The four vertices of this tetrahedron are each enriched with genes for a specific task related to stemness and early differentiation. A polyhedral continuum of states is also found in spleen dendritic cells, known to perform multiple immune tasks: cells fill out a tetrahedron whose vertices correspond to key tasks related to maturation, pathogen sensing and communication with lymphocytes. A mixture of continuum-like distributions and discrete clusters is found in other cell types, including bone marrow and differentiated intestinal crypt cells. This approach can be used to understand the geometry and biological tasks of a wide range of single-cell datasets. The present results suggest that the concept of cell type may be expanded. In addition to discreet clusters in gene-expression space, we suggest a new possibility: a continuum of states within a polyhedron, in which the vertices represent specialists at key tasks. '),
(87253, 2015, 'plos', 'Modeling Inhibitory Interneurons in Efficient Sensory Coding Models', 'Zhu, Mengchen|Rozell, Christopher J', 'Wallace H. Coulter Department of Biomedical Engineering, Georgia Institute of Technology, Atlanta, Georgia, United States of America.|School of Electrical and Computer Engineering, Georgia Institute of Technology, Atlanta, Georgia, United States of America.', 'Georgia|Georgia', 11, 'Action Potentials|Animals|Computer Simulation|Humans|Interneurons|Models, Neurological|Nerve Net|Neural Inhibition|Visual Cortex|Visual Perception', 'Journal Article', '10.1371/journal.pcbi.1004353', '26172289', 'There is still much unknown regarding the computational role of inhibitory cells in the sensory cortex. While modeling studies could potentially shed light on the critical role played by inhibition in cortical computation, there is a gap between the simplicity of many models of sensory coding and the biological complexity of the inhibitory subpopulation. In particular, many models do not respect that inhibition must be implemented in a separate subpopulation, with those inhibitory interneurons having a diversity of tuning properties and characteristic E/I cell ratios. In this study we demonstrate a computational framework for implementing inhibition in dynamical systems models that better respects these biophysical observations about inhibitory interneurons. The main approach leverages recent work related to decomposing matrices into low-rank and sparse components via convex optimization, and explicitly exploits the fact that models and input statistics often have low-dimensional structure that can be exploited for efficient implementations. While this approach is applicable to a wide range of sensory coding models (including a family of models based on Bayesian inference in a linear generative model), for concreteness we demonstrate the approach on a network implementing sparse coding. We show that the resulting implementation stays faithful to the original coding goals while using inhibitory interneurons that are much more biophysically plausible. '),
(87254, 2015, 'plos', 'A Developmental Switch for Hebbian Plasticity', 'Martens, Marijn B|Celikel, Tansu|Tiesinga, Paul H E', 'Donders Institute for Brain, Cognition and Behaviour, Centre for Neuroscience, Department of Neuroinformatics, Radboud University Nijmegen, Nijmegen, The Netherlands.|Donders Institute for Brain, Cognition and Behaviour, Centre for Neuroscience, Department of Neurophysiology, Radboud University Nijmegen, Nijmegen, The Netherlands.|Donders Institute for Brain, Cognition and Behaviour, Centre for Neuroscience, Department of Neuroinformatics, Radboud University Nijmegen, Nijmegen, The Netherlands.', 'Netherlands|Netherlands|Netherlands', 4, 'Aging|Animals|Humans|Learning|Models, Neurological|Nerve Net|Neuronal Plasticity|Neurotransmitter Agents|Synapses|Synaptic Transmission', 'Journal Article', '10.1371/journal.pcbi.1004386', '26172394', 'Hebbian forms of synaptic plasticity are required for the orderly development of sensory circuits in the brain and are powerful modulators of learning and memory in adulthood. During development, emergence of Hebbian plasticity leads to formation of functional circuits. By modeling the dynamics of neurotransmitter release during early postnatal cortical development we show that a developmentally regulated switch in vesicle exocytosis mode triggers associative (i.e. Hebbian) plasticity. Early in development spontaneous vesicle exocytosis (SVE), often considered as synaptic noise, is important for homogenization of synaptic weights and maintenance of synaptic weights in the appropriate dynamic range. Our results demonstrate that SVE has a permissive, whereas subsequent evoked vesicle exocytosis (EVE) has an instructive role in the expression of Hebbian plasticity. A timed onset for Hebbian plasticity can be achieved by switching from SVE to EVE and the balance between SVE and EVE can control the effective rate of Hebbian plasticity. We further show that this developmental switch in neurotransmitter release mode enables maturation of spike-timing dependent plasticity. A mis-timed or inadequate SVE to EVE switch may lead to malformation of brain networks thereby contributing to the etiology of neurodevelopmental disorders. '),
(87255, 2015, 'plos', 'Emergence of Slow-Switching Assemblies in Structured Neuronal Networks', 'Schaub, Michael T|Billeh, Yazan N|Anastassiou, Costas A|Koch, Christof|Barahona, Mauricio', 'Department of Mathematics, Imperial College London, London, United Kingdom.|Computation and Neural Systems Program, California Institute of Technology, Pasadena, California, United States of America.|Allen Institute for Brain Science, Seattle, Washington, United States of America.|Allen Institute for Brain Science, Seattle, Washington, United States of America.|Department of Mathematics, Imperial College London, London, United Kingdom.', 'United Kingdom|United States|United States|United States|United Kingdom', 17, 'Action Potentials|Animals|Computer Simulation|Connectome|Humans|Long-Term Potentiation|Models, Anatomic|Models, Neurological|Nerve Net|Neuronal Plasticity|Spatio-Temporal Analysis|Synaptic Transmission', 'Journal Article', '10.1371/journal.pcbi.1004196', '26176664', 'Unraveling the interplay between connectivity and spatio-temporal dynamics in neuronal networks is a key step to advance our understanding of neuronal information processing. Here we investigate how particular features of network connectivity underpin the propensity of neural networks to generate slow-switching assembly (SSA) dynamics, i.e., sustained epochs of increased firing within assemblies of neurons which transition slowly between different assemblies throughout the network. We show that the emergence of SSA activity is linked to spectral properties of the asymmetric synaptic weight matrix. In particular, the leading eigenvalues that dictate the slow dynamics exhibit a gap with respect to the bulk of the spectrum, and the associated Schur vectors exhibit a measure of block-localization on groups of neurons, thus resulting in coherent dynamical activity on those groups. Through simple rate models, we gain analytical understanding of the origin and importance of the spectral gap, and use these insights to develop new network topologies with alternative connectivity paradigms which also display SSA activity. Specifically, SSA dynamics involving excitatory and inhibitory neurons can be achieved by modifying the connectivity patterns between both types of neurons. We also show that SSA activity can occur at multiple timescales reflecting a hierarchy in the connectivity, and demonstrate the emergence of SSA in small-world like networks. Our work provides a step towards understanding how network structure (uncovered through advancements in neuroanatomy and connectomics) can impact on spatio-temporal neural activity and constrain the resulting dynamics. '),
(87256, 2015, 'plos', 'Adaptive Synaptogenesis Constructs Neural Codes That Benefit Discrimination', 'Thomas, Blake T|Blalock, Davis W|Levy, William B', 'Informed Simplifications, LLC., Earlysville, Virginia, United States of America.|Department of Computer Science, Massachusetts Institute of Technology, Cambridge, Massachusetts, United States of America.|Department of Neurosurgery, School of Medicine, University of Virginia, Charlottesville, Virginia, United States of America.', 'United States|United States|United States', 5, 'Adaptation, Physiological|Animals|Computer Simulation|Discrimination Learning|Humans|Models, Neurological|Nerve Net|Neurogenesis|Neuronal Plasticity|Synapses|Synaptic Transmission', 'Journal Article', '10.1371/journal.pcbi.1004299', '26176744', 'Intelligent organisms face a variety of tasks requiring the acquisition of expertise within a specific domain, including the ability to discriminate between a large number of similar patterns. From an energy-efficiency perspective, effective discrimination requires a prudent allocation of neural resources with more frequent patterns and their variants being represented with greater precision. In this work, we demonstrate a biologically plausible means of constructing a single-layer neural network that adaptively (i.e., without supervision) meets this criterion. Specifically, the adaptive algorithm includes synaptogenesis, synaptic shedding, and bi-directional synaptic weight modification to produce a network with outputs (i.e. neural codes) that represent input patterns proportional to the frequency of related patterns. In addition to pattern frequency, the correlational structure of the input environment also affects allocation of neural resources. The combined synaptic modification mechanisms provide an explanation of neuron allocation in the case of self-taught experts. '),
(87257, 2015, 'plos', 'Hydrophobic Gating of Ion Permeation in Magnesium Channel CorA', 'Neale, Chris|Chakrabarti, Nilmadhab|Pomorski, Pawel|Pai, Emil F|Pomès, Régis', 'Molecular Structure and Function, The Hospital for Sick Children, Toronto, Ontario, Canada, Department of Biochemistry, University of Toronto, Toronto, Ontario, Canada.|Molecular Structure and Function, The Hospital for Sick Children, Toronto, Ontario, Canada.|Shared Hierarchical Academic Research Computing Network, Department of Physics and Astronomy, University of Waterloo, Waterloo, Ontario, Canada.|Department of Biochemistry, University of Toronto, Toronto, Ontario, Canada, Department of Medical Biophysics, University of Toronto, Toronto, Ontario, Canada, Department of Molecular Genetics, University of Toronto, Toronto, Ontario, Canada, Ontario Cancer Institute/Princess Margaret Cancer Centre, Campbell Family Institute for Cancer Research, Toronto, Ontario, Canada.|Molecular Structure and Function, The Hospital for Sick Children, Toronto, Ontario, Canada, Department of Biochemistry, University of Toronto, Toronto, Ontario, Canada.', 'Canada|Canada|Canada|Canada|Canada', 21, 'Cation Transport Proteins|Escherichia coli Proteins|Hydrophobic and Hydrophilic Interactions|Ion Channel Gating|Ions|Magnesium|Models, Chemical|Molecular Dynamics Simulation|Permeability|Water|Wettability', 'Journal Article', '10.1371/journal.pcbi.1004303', '26181442', 'Ion channels catalyze ionic permeation across membranes via water-filled pores. To understand how changes in intracellular magnesium concentration regulate the influx of Mg2+ into cells, we examine early events in the relaxation of Mg2+ channel CorA toward its open state using massively-repeated molecular dynamics simulations conducted either with or without regulatory ions. The pore of CorA contains a 2-nm-long hydrophobic bottleneck which remained dehydrated in most simulations. However, rapid hydration or wetting events concurrent with small-amplitude fluctuations in pore diameter occurred spontaneously and reversibly. In the absence of regulatory ions, wetting transitions are more likely and include a wet state that is significantly more stable and more hydrated. The free energy profile for Mg2+ permeation presents a barrier whose magnitude is anticorrelated to pore diameter and the extent of hydrophobic hydration. These findings support an allosteric mechanism whereby wetting of a hydrophobic gate couples changes in intracellular magnesium concentration to the onset of ionic conduction. '),
(87258, 2015, 'plos', 'Identification of Ohnolog Genes Originating from Whole Genome Duplication in Early Vertebrates, Based on Synteny Comparison across Multiple Genomes', 'Singh, Param Priya|Arora, Jatin|Isambert, Hervé', 'CNRS UMR168, UPMC, Institut Curie, Research Center, Paris, France.|CNRS UMR168, UPMC, Institut Curie, Research Center, Paris, France.|CNRS UMR168, UPMC, Institut Curie, Research Center, Paris, France.', 'France|France|France', 46, 'Animals|Chromosome Mapping|Gene Dosage|Gene Duplication|Genetic Linkage|Genome|Humans|Sequence Homology, Amino Acid|Species Specificity|Synteny|Vertebrates', 'Journal Article', '10.1371/journal.pcbi.1004394', '26181593', 'Whole genome duplications (WGD) have now been firmly established in all major eukaryotic kingdoms. In particular, all vertebrates descend from two rounds of WGDs, that occurred in their jawless ancestor some 500 MY ago. Paralogs retained from WGD, also coined ohnologs after Susumu Ohno, have been shown to be typically associated with development, signaling and gene regulation. Ohnologs, which amount to about 20 to 35% of genes in the human genome, have also been shown to be prone to dominant deleterious mutations and frequently implicated in cancer and genetic diseases. Hence, identifying ohnologs is central to better understand the evolution of vertebrates and their susceptibility to genetic diseases. Early computational analyses to identify vertebrate ohnologs relied on content-based synteny comparisons between the human genome and a single invertebrate outgroup genome or within the human genome itself. These approaches are thus limited by lineage specific rearrangements in individual genomes. We report, in this study, the identification of vertebrate ohnologs based on the quantitative assessment and integration of synteny conservation between six amniote vertebrates and six invertebrate outgroups. Such a synteny comparison across multiple genomes is shown to enhance the statistical power of ohnolog identification in vertebrates compared to earlier approaches, by overcoming lineage specific genome rearrangements. Ohnolog gene families can be browsed and downloaded for three statistical confidence levels or recompiled for specific, user-defined, significance criteria at http://ohnologs.curie.fr/. In the light of the importance of WGD on the genetic makeup of vertebrates, our analysis provides a useful resource for researchers interested in gaining further insights on vertebrate evolution and genetic diseases. '),
(87259, 2015, 'plos', 'Markov State Models Reveal a Two-Step Mechanism of miRNA Loading into the Human Argonaute Protein: Selective Binding followed by Structural Re-arrangement', 'Jiang, Hanlun|Sheong, Fu Kit|Zhu, Lizhe|Gao, Xin|Bernauer, Julie|Huang, Xuhui', 'Bioengineering Graduate Program, Division of Biomedical Engineering, The Hong Kong University of Science and Technology, Clear Water Bay, Kowloon, Hong Kong, The HKUST Shenzhen Research Institute, Shenzhen, China.|Department of Chemistry, The Hong Kong University of Science and Technology, Clear Water Bay, Kowloon, Hong Kong.|The HKUST Shenzhen Research Institute, Shenzhen, China, Department of Chemistry, The Hong Kong University of Science and Technology, Clear Water Bay, Kowloon, Hong Kong, Center of Systems Biology and Human Health, School of Science and Institute for Advance Study, The Hong Kong University of Science and Technology, Clear Water Bay, Kowloon, Hong Kong.|Computer, Electrical and Mathematical Sciences and Engineering Division, King Abdullah University of Science and Technology, Thuwal, Saudi Arabia.|Inria Saclay-Île de France, Bâtiment Alan Turing, Campus de lÉcole Polytechnique, Palaiseau, France, Laboratoire dInformatique de lÉcole Polytechnique (LIX), CNRS UMR 7161, École Polytechnique, Palaiseau, France.|Bioengineering Graduate Program, Division of Biomedical Engineering, The Hong Kong University of Science and Technology, Clear Water Bay, Kowloon, Hong Kong, The HKUST Shenzhen Research Institute, Shenzhen, China, Department of Chemistry, The Hong Kong University of Science and Technology, Clear Water Bay, Kowloon, Hong Kong, Center of Systems Biology and Human Health, School of Science and Institute for Advance Study, The Hong Kong University of Science and Technology, Clear Water Bay, Kowloon, Hong Kong.', 'China|Hong Kong|China|Saudi Arabia|France|China', 28, 'Argonaute Proteins|Binding Sites|Humans|Markov Chains|MicroRNAs|Models, Chemical|Models, Statistical|Molecular Docking Simulation|Protein Binding|Protein Conformation', 'Journal Article', '10.1371/journal.pcbi.1004404', '26181723', 'Argonaute (Ago) proteins and microRNAs (miRNAs) are central components in RNA interference, which is a key cellular mechanism for sequence-specific gene silencing. Despite intensive studies, molecular mechanisms of how Ago recognizes miRNA remain largely elusive. In this study, we propose a two-step mechanism for this molecular recognition: selective binding followed by structural re-arrangement. Our model is based on the results of a combination of Markov State Models (MSMs), large-scale protein-RNA docking, and molecular dynamics (MD) simulations. Using MSMs, we identify an open state of apo human Ago-2 in fast equilibrium with partially open and closed states. Conformations in this open state are distinguished by their largely exposed binding grooves that can geometrically accommodate miRNA as indicated in our protein-RNA docking studies. miRNA may then selectively bind to these open conformations. Upon the initial binding, the complex may perform further structural re-arrangement as shown in our MD simulations and eventually reach the stable binary complex structure. Our results provide novel insights in Ago-miRNA recognition mechanisms and our methodology holds great potential to be widely applied in the studies of other important molecular recognition systems. ');
INSERT INTO `papers` (`id`, `ano`, `journal`, `titulo`, `autores`, `afiliacao`, `pais`, `citacoes`, `palavra_chave`, `categorias`, `doi`, `pubmed`, `abstract`) VALUES
(87260, 2015, 'plos', 'Quantitative Analysis of the Association Angle between T-cell Receptor Vxcexb1/Vxcexb2 Domains Reveals Important Features for Epitope Recognition', 'Hoffmann, Thomas|Krackhardt, Angela M|Antes, Iris', 'Department of Biosciences and Center for Integrated Protein Science Munich,Technische Universitxc3xa4t Mxc3xbcnchen, Freising-Weihenstephan, Germany.|Medizinische Klinik III, Innere Medizin mit Schwerpunkt Hxc3xa4matologie und Onkologie, Technische Universitxc3xa4t Mxc3xbcnchen, Munich, Germany, Clinical Cooperation Group, Antigen specific T cell therapy, Helmholtz Zentrum Mxc3xbcnchen (GmbH), German Center for Environmental Health, Munich, Germany, German Cancer Consortium (DKTK), Munich, Germany.|Department of Biosciences and Center for Integrated Protein Science Munich,Technische Universitxc3xa4t Mxc3xbcnchen, Freising-Weihenstephan, Germany.', 'Germany|Germany|Germany', 5, 'Binding Sites|Computer Simulation|Epitope Mapping|Epitopes, T-Lymphocyte|Models, Chemical|Models, Immunological|Models, Molecular|Protein Binding|Protein Conformation|Protein Structure, Tertiary|Receptors, Antigen, T-Cell, alpha-beta', 'Journal Article', '10.1371/journal.pcbi.1004244', '26185983', 'T-cell receptors (TCR) play an important role in the adaptive immune system as they recognize pathogen- or cancer-based epitopes and thus initiate the cell-mediated immune response. Therefore there exists a growing interest in the optimization of TCRs for medical purposes like adoptive T-cell therapy. However, the molecular mechanisms behind T-cell signaling are still predominantly unknown. For small sets of TCRs it was observed that the angle between their Vxcexb1- and Vxcexb2-domains, which bind the epitope, can vary and might be important for epitope recognition. Here we present a comprehensive, quantitative study of the variation in the Vxcexb1/Vxcexb2 interdomain-angle and its influence on epitope recognition, performing a systematic bioinformatics analysis based on a representative set of experimental TCR structures. For this purpose we developed a new, cuboid-based superpositioning method, which allows a unique, quantitative analysis of the Vxcexb1/Vxcexb2-angles. Angle-based clustering led to six significantly different clusters. Analysis of these clusters revealed the unexpected result that the angle is predominantly influenced by the TCR-clonotype, whereas the bound epitope has only a minor influence. Furthermore we could identify a previously unknown center of rotation (CoR), which is shared by all TCRs. All TCR geometries can be obtained by rotation around this center, rendering it a new, common TCR feature with the potential of improving the accuracy of TCR structure prediction considerably. The importance of Vxcexb1/Vxcexb2 rotation for signaling was confirmed as we observed larger variances in the Vxcexb1/Vxcexb2-angles in unbound TCRs compared to epitope-bound TCRs. Our results strongly support a two-step mechanism for TCR-epitope: First, preformation of a flexible TCR geometry in the unbound state and second, locking of the Vxcexb1/Vxcexb2-angle in a TCR-type specific geometry upon epitope-MHC association, the latter being driven by rotation around the unique center of rotation. '),
(87261, 2015, 'plos', 'Dynamical Localization of DivL and PleC in the Asymmetric Division Cycle of Caulobacter crescentus: A Theoretical Investigation of Alternative Models', 'Subramanian, Kartik|Paul, Mark R|Tyson, John J', 'Graduate Program in Genetics, Bioinformatics and Computational Biology, Virginia Polytechnic Institute and State University, Blacksburg, Virginia, United States of America.|Department of Mechanical Engineering, Virginia Polytechnic Institute and State University, Blacksburg, Virginia, United States of America.|Department of Biological Sciences, Virginia Polytechnic Institute and State University, Blacksburg, Virginia, United States of America, Virginia Bioinformatics Institute, Virginia Polytechnic Institute and State University, Blacksburg, Virginia, United States of America.', 'United States|United States|United States', 7, 'Caulobacter crescentus|Cell Cycle|Cell Cycle Proteins|Computer Simulation|Models, Biological|Spatio-Temporal Analysis|Subcellular Fractions|Tissue Distribution', 'Comparative Study', '10.1371/journal.pcbi.1004348', '26186202', 'Cell-fate asymmetry in the predivisional cell of Caulobacter crescentus requires that the regulatory protein DivL localizes to the new pole of the cell where it up-regulates CckA kinase, resulting in a gradient of CtrA~P across the cell. In the preceding stage of the cell cycle (the stalked cell), DivL is localized uniformly along the cell membrane and maintained in an inactive form by DivK~P. It is unclear how DivL overcomes inhibition by DivK~P in the predivisional cell simply by changing its location to the new pole. It has been suggested that co-localization of DivL with PleC phosphatase at the new pole is essential to DivLs activity there. However, there are contrasting views on whether the bifunctional enzyme, PleC, acts as a kinase or phosphatase at the new pole. To explore these ambiguities, we formulated a mathematical model of the spatiotemporal distributions of DivL, PleC and associated proteins (DivJ, DivK, CckA, and CtrA) during the asymmetric division cycle of a Caulobacter cell. By varying localization profiles of DivL and PleC in our model, we show how the physiologically observed spatial distributions of these proteins are essential for the transition from a stalked cell to a predivisional cell. Our simulations suggest that PleC is a kinase in predivisional cells, and that, by sequestering DivK~P, the kinase form of PleC enables DivL to be reactivated at the new pole. Hence, co-localization of PleC kinase and DivL is essential to establishing cellular asymmetry. Our simulations reproduce the experimentally observed spatial distribution and phosphorylation status of CtrA in wild-type and mutant cells. Based on the model, we explore novel combinations of mutant alleles, making predictions that can be tested experimentally. '),
(87262, 2015, 'plos', 'What Can Interaction Webs Tell Us About Species Roles?', 'Sander, Elizabeth L|Wootton, J Timothy|Allesina, Stefano', 'Department of Ecology & Evolution, University of Chicago, Chicago, Illinois, United States of America.|Department of Ecology & Evolution, University of Chicago, Chicago, Illinois, United States of America.|Department of Ecology & Evolution, University of Chicago, Chicago, Illinois, United States of America, Computation Institute, University of Chicago, Chicago, Illinois, United States of America.', 'United States|United States|United States', 22, 'Animals|Computer Simulation|Ecosystem|Food Chain|Humans|Models, Statistical|Population Dynamics|Predatory Behavior|Species Specificity', 'Journal Article', '10.1371/journal.pcbi.1004330', '26197151', 'The group model is a useful tool to understand broad-scale patterns of interaction in a network, but it has previously been limited in use to food webs, which contain only predator-prey interactions. Natural populations interact with each other in a variety of ways and, although most published ecological networks only include information about a single interaction type (e.g., feeding, pollination), ecologists are beginning to consider networks which combine multiple interaction types. Here we extend the group model to signed directed networks such as ecological interaction webs. As a specific application of this method, we examine the effects of including or excluding specific interaction types on our understanding of species roles in ecological networks. We consider all three currently available interaction webs, two of which are extended plant-mutualist networks with herbivores and parasitoids added, and one of which is an extended intertidal food web with interactions of all possible sign structures (+/+, -/0, etc.). Species in the extended food web grouped similarly with all interactions, only trophic links, and only nontrophic links. However, removing mutualism or herbivory had a much larger effect in the extended plant-pollinator webs. Species removal even affected groups that were not directly connected to those that were removed, as we found by excluding a small number of parasitoids. These results suggest that including additional species in the network provides far more information than additional interactions for this aspect of network structure. Our methods provide a useful framework for simplifying networks to their essential structure, allowing us to identify generalities in network structure and better understand the roles species play in their communities. '),
(87263, 2015, 'plos', 'Neutral Models of Microbiome Evolution', 'Zeng, Qinglong|Sukumaran, Jeet|Wu, Steven|Rodrigo, Allen', 'Biology Department, Duke University, Durham, North Carolina, United States of America.|Biology Department, Duke University, Durham, North Carolina, United States of America.|Biology Department, Duke University, Durham, North Carolina, United States of America.|Biology Department, Duke University, Durham, North Carolina, United States of America.', 'United States|United States|United States|United States', 0, 'Biological Evolution|Computer Simulation|Ecosystem|Genetic Variation|Host Specificity|Microbiota|Models, Genetic', 'Journal Article', '10.1371/journal.pcbi.1004365', '26200800', 'There has been an explosion of research on host-associated microbial communities (i.e.,microbiomes). Much of this research has focused on surveys of microbial diversities across a variety of host species, including humans, with a view to understanding how these microbiomes are distributed across space and time, and how they correlate with host health, disease, phenotype, physiology and ecology. Fewer studies have focused on how these microbiomes may have evolved. In this paper, we develop an agent-based framework to study the dynamics of microbiome evolution. Our framework incorporates neutral models of how hosts acquire their microbiomes, and how the environmental microbial community that is available to the hosts is assembled. Most importantly, our framework also incorporates a Wright-Fisher genealogical model of hosts, so that the dynamics of microbiome evolution is studied on an evolutionary timescale. Our results indicate that the extent of parental contribution to microbial availability from one generation to the next significantly impacts the diversity of microbiomes: the greater the parental contribution, the less diverse the microbiomes. In contrast, even when there is only a very small contribution from a constant environmental pool, microbial communities can remain highly diverse. Finally, we show that our models may be used to construct hypotheses about the types of processes that operate to assemble microbiomes over evolutionary time. '),
(87264, 2015, 'plos', 'Timing and Variability of Galactose Metabolic Gene Activation Depend on the Rate of Environmental Change', 'Nguyen-Huu, Truong D|Gupta, Chinmaya|Ma, Bo|Ott, William|Josixc4x87, Krexc5xa1imir|Bennett, Matthew R', 'Department of Biosciences, Rice University, Houston, Texas, United States of America.|Department of Mathematics, University of Houston, Houston, Texas, United States of America.|Department of Biosciences, Rice University, Houston, Texas, United States of America.|Department of Mathematics, University of Houston, Houston, Texas, United States of America.|Department of Mathematics, University of Houston, Houston, Texas, United States of America, Department of Biology and Biochemistry, University of Houston, Houston, Texas, United States of America.|Department of Biosciences, Rice University, Houston, Texas, United States of America, Institute of Biosciences and Bioengineering, Rice University, Houston, Texas, United States of America.', 'United States|United States|United States|United States|United States|United States', 4, 'Adaptation, Physiological|Bioreactors|Ecosystem|Galactose|Glucose|Saccharomyces cerevisiae|Saccharomyces cerevisiae Proteins|Signal Transduction', 'Journal Article', '10.1371/journal.pcbi.1004399', '26200924', 'Modulation of gene network activity allows cells to respond to changes in environmental conditions. For example, the galactose utilization network in Saccharomyces cerevisiae is activated by the presence of galactose but repressed by glucose. If both sugars are present, the yeast will first metabolize glucose, depleting it from the extracellular environment. Upon depletion of glucose, the genes encoding galactose metabolic proteins will activate. Here, we show that the rate at which glucose levels are depleted determines the timing and variability of galactose gene activation. Paradoxically, we find that Gal1p, an enzyme needed for galactose metabolism, accumulates more quickly if glucose is depleted slowly rather than taken away quickly. Furthermore, the variability of induction times in individual cells depends non-monotonically on the rate of glucose depletion and exhibits a minimum at intermediate depletion rates. Our mathematical modeling suggests that the dynamics of the metabolic transition from glucose to galactose are responsible for the variability in galactose gene activation. These findings demonstrate that environmental dynamics can determine the phenotypic outcome at both the single-cell and population levels. '),
(87265, 2015, 'plos', 'Fast Simulation of Mechanical Heterogeneity in the Electrically Asynchronous Heart Using the MultiPatch Module', 'Walmsley, John|Arts, Theo|Derval, Nicolas|Bordachar, Pierre|Cochet, Hubert|Ploux, Sylvain|Prinzen, Frits W|Delhaas, Tammo|Lumens, Joost', 'Department of Biomedical Engineering, Cardiovascular Research Institute Maastricht (CARIM), Maastricht University, Maastricht, The Netherlands.|Department of Biomedical Engineering, Cardiovascular Research Institute Maastricht (CARIM), Maastricht University, Maastricht, The Netherlands.|Hôpital Cardiologique du Haut-Lévêque, IHU-LIRYC, CHU de Bordeaux, Bordeaux, France.|Hôpital Cardiologique du Haut-Lévêque, IHU-LIRYC, CHU de Bordeaux, Bordeaux, France.|Hôpital Cardiologique du Haut-Lévêque, IHU-LIRYC, CHU de Bordeaux, Bordeaux, France.|Hôpital Cardiologique du Haut-Lévêque, IHU-LIRYC, CHU de Bordeaux, Bordeaux, France.|Department of Physiology, Cardiovascular Research Institute Maastricht (CARIM), Maastricht University, Maastricht, The Netherlands.|Department of Biomedical Engineering, Cardiovascular Research Institute Maastricht (CARIM), Maastricht University, Maastricht, The Netherlands.|Department of Biomedical Engineering, Cardiovascular Research Institute Maastricht (CARIM), Maastricht University, Maastricht, The Netherlands, Hôpital Cardiologique du Haut-Lévêque, IHU-LIRYC, CHU de Bordeaux, Bordeaux, France.', 'Netherlands|Netherlands|France|France|France|France|Netherlands|Netherlands|France', 0, 'Algorithms|Animals|Bundle-Branch Block|Computer Simulation|Excitation Contraction Coupling|Heart Conduction System|Humans|Models, Cardiovascular|Myocardial Contraction|Software|Ventricular Dysfunction, Left', 'Journal Article', '10.1371/journal.pcbi.1004284', '26204520', 'Cardiac electrical asynchrony occurs as a result of cardiac pacing or conduction disorders such as left bundle-branch block (LBBB). Electrically asynchronous activation causes myocardial contraction heterogeneity that can be detrimental for cardiac function. Computational models provide a tool for understanding pathological consequences of dyssynchronous contraction. Simulations of mechanical dyssynchrony within the heart are typically performed using the finite element method, whose computational intensity may present an obstacle to clinical deployment of patient-specific models. We present an alternative based on the CircAdapt lumped-parameter model of the heart and circulatory system, called the MultiPatch module. Cardiac walls are subdivided into an arbitrary number of patches of homogeneous tissue. Tissue properties and activation time can differ between patches. All patches within a wall share a common wall tension and curvature. Consequently, spatial location within the wall is not required to calculate deformation in a patch. We test the hypothesis that activation time is more important than tissue location for determining mechanical deformation in asynchronous hearts. We perform simulations representing an experimental study of myocardial deformation induced by ventricular pacing, and a patient with LBBB and heart failure using endocardial recordings of electrical activation, wall volumes, and end-diastolic volumes. Direct comparison between simulated and experimental strain patterns shows both qualitative and quantitative agreement between model fibre strain and experimental circumferential strain in terms of shortening and rebound stretch during ejection. Local myofibre strain in the patient simulation shows qualitative agreement with circumferential strain patterns observed in the patient using tagged MRI. We conclude that the MultiPatch module produces realistic regional deformation patterns in the asynchronous heart and that activation time is more important than tissue location within a wall for determining myocardial deformation. The CircAdapt model is therefore capable of fast and realistic simulations of dyssynchronous myocardial deformation embedded within the closed-loop cardiovascular system. '),
(87266, 2015, 'plos', 'Decreasing-Rate Pruning Optimizes the Construction of Efficient and Robust Distributed Networks', 'Navlakha, Saket|Barth, Alison L|Bar-Joseph, Ziv', 'Center for Integrative Biology, The Salk Institute for Biological Studies, La Jolla, California, United States of America.|Department of Biological Sciences, Center for the Neural Basis of Cognition, Carnegie Mellon University, Pittsburgh, Pennsylvania, United States of America.|Lane Center for Computational Biology, Machine Learning Department, Carnegie Mellon University, Pittsburgh, Pennsylvania, United States of America.', 'United States|United States|United States', 19, 'Aging|Animals|Brain|Computer Simulation|Connectome|Mice|Models, Anatomic|Models, Neurological|Nerve Net|Neuronal Plasticity|Synapses', 'Journal Article', '10.1371/journal.pcbi.1004347', '26217933', 'Robust, efficient, and low-cost networks are advantageous in both biological and engineered systems. During neural network development in the brain, synapses are massively over-produced and then pruned-back over time. This strategy is not commonly used when designing engineered networks, since adding connections that will soon be removed is considered wasteful. Here, we show that for large distributed routing networks, network function is markedly enhanced by hyper-connectivity followed by aggressive pruning and that the global rate of pruning, a developmental parameter not previously studied by experimentalists, plays a critical role in optimizing network structure. We first used high-throughput image analysis techniques to quantify the rate of pruning in the mammalian neocortex across a broad developmental time window and found that the rate is decreasing over time. Based on these results, we analyzed a model of computational routing networks and show using both theoretical analysis and simulations that decreasing rates lead to more robust and efficient networks compared to other rates. We also present an application of this strategy to improve the distributed design of airline networks. Thus, inspiration from neural network formation suggests effective ways to design distributed networks across several domains. '),
(87267, 2015, 'plos', 'Nullspace Sampling with Holonomic Constraints Reveals Molecular Mechanisms of Protein Gxcexb1s', 'Pachov, Dimitar V|van den Bedem, Henry', 'Department of Chemistry, Stanford University, Stanford, California, United States of America.|Joint Center for Structural Genomics, Stanford Synchrotron Radiation Lightsource, Stanford University, Stanford, California, United States of America.', 'United States|United States', 0, 'Binding Sites|Chromogranins|Diffusion|GTP-Binding Protein alpha Subunits, Gs|Guanosine Diphosphate|Models, Chemical|Molecular Dynamics Simulation|Protein Binding|Protein Conformation|Protein Subunits|Receptors, G-Protein-Coupled', 'Journal Article', '10.1371/journal.pcbi.1004361', '26218073', 'Proteins perform their function or interact with partners by exchanging between conformational substates on a wide range of spatiotemporal scales. Structurally characterizing these exchanges is challenging, both experimentally and computationally. Large, diffusional motions are often on timescales that are difficult to access with molecular dynamics simulations, especially for large proteins and their complexes. The low frequency modes of normal mode analysis (NMA) report on molecular fluctuations associated with biological activity. However, NMA is limited to a second order expansion about a minimum of the potential energy function, which limits opportunities to observe diffusional motions. By contrast, kino-geometric conformational sampling (KGS) permits large perturbations while maintaining the exact geometry of explicit conformational constraints, such as hydrogen bonds. Here, we extend KGS and show that a conformational ensemble of the xcexb1 subunit Gxcexb1s of heterotrimeric stimulatory protein Gs exhibits structural features implicated in its activation pathway. Activation of protein Gs by G protein-coupled receptors (GPCRs) is associated with GDP release and large conformational changes of its xcexb1-helical domain. Our method reveals a coupled xcexb1-helical domain opening motion while, simultaneously, Gxcexb1s helix xcexb15 samples an activated conformation. These motions are moderated in the activated state. The motion centers on a dynamic hub near the nucleotide-binding site of Gxcexb1s, and radiates to helix xcexb14. We find that comparative NMA-based ensembles underestimate the amplitudes of the motion. Additionally, the ensembles fall short in predicting the accepted direction of the full activation pathway. Taken together, our findings suggest that nullspace sampling with explicit, holonomic constraints yields ensembles that illuminate molecular mechanisms involved in GDP release and protein Gs activation, and further establish conformational coupling between key structural elements of Gxcexb1s. '),
(87268, 2015, 'plos', 'Learning the Structure of Biomedical Relationships from Unstructured Text', 'Percha, Bethany|Altman, Russ B', 'Biomedical Informatics Training Program, Stanford University, Stanford, California, United States of America.|Departments of Medicine, Genetics and Bioengineering, Stanford University, Stanford, California, United States of America.', 'United States|United States', 0, 'Algorithms|Data Mining|Drug Interactions|MEDLINE|Machine Learning|Natural Language Processing|Pattern Recognition, Automated|Pharmacogenetics|Vocabulary, Controlled', 'Journal Article', '10.1371/journal.pcbi.1004216', '26219079', 'The published biomedical research literature encompasses most of our understanding of how drugs interact with gene products to produce physiological responses (phenotypes). Unfortunately, this information is distributed throughout the unstructured text of over 23 million articles. The creation of structured resources that catalog the relationships between drugs and genes would accelerate the translation of basic molecular knowledge into discoveries of genomic biomarkers for drug response and prediction of unexpected drug-drug interactions. Extracting these relationships from natural language sentences on such a large scale, however, requires text mining algorithms that can recognize when different-looking statements are expressing similar ideas. Here we describe a novel algorithm, Ensemble Biclustering for Classification (EBC), that learns the structure of biomedical relationships automatically from text, overcoming differences in word choice and sentence structure. We validate EBCs performance against manually-curated sets of (1) pharmacogenomic relationships from PharmGKB and (2) drug-target relationships from DrugBank, and use it to discover new drug-gene relationships for both knowledge bases. We then apply EBC to map the complete universe of drug-gene relationships based on their descriptions in Medline, revealing unexpected structure that challenges current notions about how these relationships are expressed in text. For instance, we learn that newer experimental findings are described in consistently different ways than established knowledge, and that seemingly pure classes of relationships can exhibit interesting chimeric structure. The EBC algorithm is flexible and adaptable to a wide range of problems in biomedical text mining. '),
(87269, 2015, 'plos', 'Inferring Pairwise Interactions from Biological Data Using Maximum-Entropy Probability Models', 'Stein, Richard R|Marks, Debora S|Sander, Chris', '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.|Computational Biology Program, Sloan Kettering Institute, Memorial Sloan Kettering Cancer Center, New York, New York, United States of America.', 'United States|United States|United States', 39, 'Algorithms|Amino Acid Sequence|Binding Sites|Computer Simulation|Entropy|Models, Chemical|Models, Statistical|Molecular Sequence Data|Protein Binding|Protein Interaction Mapping|Proteins|Sequence Analysis, Protein', 'Journal Article', '10.1371/journal.pcbi.1004182', '26225866', 'Maximum entropy-based inference methods have been successfully used to infer direct interactions from biological datasets such as gene expression data or sequence ensembles. Here, we review undirected pairwise maximum-entropy probability models in two categories of data types, those with continuous and categorical random variables. As a concrete example, we present recently developed inference methods from the field of protein contact prediction and show that a basic set of assumptions leads to similar solution strategies for inferring the model parameters in both variable types. These parameters reflect interactive couplings between observables, which can be used to predict global properties of the biological system. Such methods are applicable to the important problems of protein 3-D structure prediction and association of gene-gene networks, and they enable potential applications to the analysis of gene alteration patterns and to protein design. '),
(87270, 2015, 'plos', 'Optimal Prediction of Moving Sound Source Direction in the Owl', 'Cox, Weston|Fischer, Brian J', 'Department of Electrical and Computer Engineering, Seattle University, Seattle, Washington, United States of America.|Department of Mathematics, Seattle University, Seattle, Washington, United States of America.', 'United States|United States', 0, 'Animals|Computer Simulation|Mesencephalon|Models, Neurological|Motion Perception|Nerve Net|Pattern Recognition, Physiological|Predatory Behavior|Sound Localization|Strigiformes', 'Journal Article', '10.1371/journal.pcbi.1004360', '26226048', 'Capturing natures statistical structure in behavioral responses is at the core of the ability to function adaptively in the environment. Bayesian statistical inference describes how sensory and prior information can be combined optimally to guide behavior. An outstanding open question of how neural coding supports Bayesian inference includes how sensory cues are optimally integrated over time. Here we address what neural response properties allow a neural system to perform Bayesian prediction, i.e., predicting where a source will be in the near future given sensory information and prior assumptions. The work here shows that the population vector decoder will perform Bayesian prediction when the receptive fields of the neurons encode the target dynamics with shifting receptive fields. We test the model using the system that underlies sound localization in barn owls. Neurons in the owls midbrain show shifting receptive fields for moving sources that are consistent with the predictions of the model. We predict that neural populations can be specialized to represent the statistics of dynamic stimuli to allow for a vector read-out of Bayes-optimal predictions. '),
(87271, 2015, 'plos', 'Forecasting Influenza Epidemics in Hong Kong', 'Yang, Wan|Cowling, Benjamin J|Lau, Eric H Y|Shaman, Jeffrey', 'Department of Environmental Health Sciences, Mailman School of Public Health, Columbia University, New York, New York, United States of America.|WHO Collaborating Centre for Epidemiology and Biostatistics, School of Public Health, Li Ka Shing Faculty of Medicine, The University of Hong Kong, Hong Kong Special Administrative Region, China.|WHO Collaborating Centre for Epidemiology and Biostatistics, School of Public Health, Li Ka Shing Faculty of Medicine, The University of Hong Kong, Hong Kong Special Administrative Region, China.|Department of Environmental Health Sciences, Mailman School of Public Health, Columbia University, New York, New York, United States of America.', 'United States|China|China|United States', 0, 'Computer Simulation|Forecasting|Hong Kong|Humans|Incidence|Influenza, Human|Models, Statistical|Pandemics|Population Surveillance|Reproducibility of Results|Risk Assessment|Sensitivity and Specificity', 'Journal Article', '10.1371/journal.pcbi.1004383', '26226185', 'Recent advances in mathematical modeling and inference methodologies have enabled development of systems capable of forecasting seasonal influenza epidemics in temperate regions in real-time. However, in subtropical and tropical regions, influenza epidemics can occur throughout the year, making routine forecast of influenza more challenging. Here we develop and report forecast systems that are able to predict irregular non-seasonal influenza epidemics, using either the ensemble adjustment Kalman filter or a modified particle filter in conjunction with a susceptible-infected-recovered (SIR) model. We applied these model-filter systems to retrospectively forecast influenza epidemics in Hong Kong from January 1998 to December 2013, including the 2009 pandemic. The forecast systems were able to forecast both the peak timing and peak magnitude for 44 epidemics in 16 years caused by individual influenza strains (i.e., seasonal influenza A(H1N1), pandemic A(H1N1), A(H3N2), and B), as well as 19 aggregate epidemics caused by one or more of these influenza strains. Average forecast accuracies were 37% (for both peak timing and magnitude) at 1-3 week leads, and 51% (peak timing) and 50% (peak magnitude) at 0 lead. Forecast accuracy increased as the spread of a given forecast ensemble decreased, the forecast accuracy for peak timing (peak magnitude) increased up to 43% (45%) for H1N1, 93% (89%) for H3N2, and 53% (68%) for influenza B at 1-3 week leads. These findings suggest that accurate forecasts can be made at least 3 weeks in advance for subtropical and tropical regions. '),
(87272, 2015, 'plos', 'Asynchronous Rate Chaos in Spiking Neuronal Circuits', 'Harish, Omri|Hansel, David', 'Center for Neurophysics, Physiology and Pathologies, CNRS UMR8119 and Institute of Neuroscience and Cognition, Université Paris Descartes, Paris, France.|Center for Neurophysics, Physiology and Pathologies, CNRS UMR8119 and Institute of Neuroscience and Cognition, Université Paris Descartes, Paris, France, The Alexander Silberman Institute of Life Sciences, The Hebrew University of Jerusalem, Jerusalem, Israel.', 'France|France', 0, 'Action Potentials|Animals|Biological Clocks|Computer Simulation|Feedback, Physiological|Humans|Models, Neurological|Models, Statistical|Nerve Net|Neural Inhibition|Neuronal Plasticity|Nonlinear Dynamics', 'Journal Article', '10.1371/journal.pcbi.1004266', '26230679', 'The brain exhibits temporally complex patterns of activity with features similar to those of chaotic systems. Theoretical studies over the last twenty years have described various computational advantages for such regimes in neuronal systems. Nevertheless, it still remains unclear whether chaos requires specific cellular properties or network architectures, or whether it is a generic property of neuronal circuits. We investigate the dynamics of networks of excitatory-inhibitory (EI) spiking neurons with random sparse connectivity operating in the regime of balance of excitation and inhibition. Combining Dynamical Mean-Field Theory with numerical simulations, we show that chaotic, asynchronous firing rate fluctuations emerge generically for sufficiently strong synapses. Two different mechanisms can lead to these chaotic fluctuations. One mechanism relies on slow I-I inhibition which gives rise to slow subthreshold voltage and rate fluctuations. The decorrelation time of these fluctuations is proportional to the time constant of the inhibition. The second mechanism relies on the recurrent E-I-E feedback loop. It requires slow excitation but the inhibition can be fast. In the corresponding dynamical regime all neurons exhibit rate fluctuations on the time scale of the excitation. Another feature of this regime is that the population-averaged firing rate is substantially smaller in the excitatory population than in the inhibitory population. This is not necessarily the case in the I-I mechanism. Finally, we discuss the neurophysiological and computational significance of our results. '),
(87273, 2015, 'plos', 'Interdomain Contacts Control Native State Switching of RfaH on a Dual-Funneled Landscape', 'Ramxc3xadrez-Sarmiento, Cxc3xa9sar A|Noel, Jeffrey K|Valenzuela, Sandro L|Artsimovitch, Irina', 'Departamento de Biologxc3xada, Facultad de Ciencias, Universidad de Chile, xc3x91uxc3xb1oa, Santiago, Chile.|Center for Theoretical Biological Physics, Rice University, Houston, Texas, United States of America.|Departamento de Biologxc3xada, Facultad de Ciencias, Universidad de Chile, xc3x91uxc3xb1oa, Santiago, Chile.|Department of Microbiology and The Center for RNA Biology, The Ohio State University, Columbus, Ohio, United States of America.', 'Chile|United States|Chile|United States', 17, 'Binding Sites|Computer Simulation|DNA-Directed RNA Polymerases|Escherichia coli Proteins|Models, Chemical|Molecular Dynamics Simulation|Peptide Elongation Factors|Protein Binding|Protein Conformation|Protein Folding|Protein Structure, Tertiary|Trans-Activators', 'Journal Article', '10.1371/journal.pcbi.1004379', '26230837', 'RfaH is a virulence factor from Escherichia coli whose C-terminal domain (CTD) undergoes a dramatic xcexb1-to-xcexb2 conformational transformation. The CTD in its xcexb1-helical fold is stabilized by interactions with the N-terminal domain (NTD), masking an RNA polymerase binding site until a specific recruitment site is encountered. Domain dissociation is triggered upon binding to DNA, allowing the NTD to interact with RNA polymerase to facilitate transcription while the CTD refolds into the xcexb2-barrel conformation that interacts with the ribosome to activate translation. However, structural details of this transformation process in the context of the full protein remain to be elucidated. Here, we explore the mechanism of the xcexb1-to-xcexb2 conformational transition of RfaH in the full-length protein using a dual-basin structure-based model. Our simulations capture several features described experimentally, such as the requirement of disruption of interdomain contacts to trigger the xcexb1-to-xcexb2 transformation, confirms the roles of previously indicated residues E48 and R138, and suggests a new important role for F130, in the stability of the interdomain interaction. These native basins are connected through an intermediate state that builds up upon binding to the NTD and shares features from both folds, in agreement with previous in silico studies of the isolated CTD. We also examine the effect of RNA polymerase binding on the stabilization of the xcexb2 fold. Our study shows that native-biased models are appropriate for interrogating the detailed mechanisms of structural rearrangements during the dramatic transformation process of RfaH. '),
(87274, 2015, 'plos', 'Spike-Triggered Covariance Analysis Reveals Phenomenological Diversity of Contrast Adaptation in the Retina', 'Liu, Jian K|Gollisch, Tim', 'Department of Ophthalmology, University Medical Center Göttingen, Göttingen, Germany, Bernstein Center for Computational Neuroscience Göttingen, Göttingen, Germany.|Department of Ophthalmology, University Medical Center Göttingen, Göttingen, Germany, Bernstein Center for Computational Neuroscience Göttingen, Göttingen, Germany.', 'Germany|Germany', 0, 'Action Potentials|Adaptation, Ocular|Animals|Computer Simulation|Contrast Sensitivity|Models, Neurological|Nerve Net|Neural Inhibition|Retinal Ganglion Cells|Urodela', 'Journal Article', '10.1371/journal.pcbi.1004425', '26230927', 'When visual contrast changes, retinal ganglion cells adapt by adjusting their sensitivity as well as their temporal filtering characteristics. The latter has classically been described by contrast-induced gain changes that depend on temporal frequency. Here, we explored a new perspective on contrast-induced changes in temporal filtering by using spike-triggered covariance analysis to extract multiple parallel temporal filters for individual ganglion cells. Based on multielectrode-array recordings from ganglion cells in the isolated salamander retina, we found that contrast adaptation of temporal filtering can largely be captured by contrast-invariant sets of filters with contrast-dependent weights. Moreover, differences among the ganglion cells in the filter sets and their contrast-dependent contributions allowed us to phenomenologically distinguish three types of filter changes. The first type is characterized by newly emerging features at higher contrast, which can be reproduced by computational models that contain response-triggered gain-control mechanisms. The second type follows from stronger adaptation in the Off pathway as compared to the On pathway in On-Off-type ganglion cells. Finally, we found that, in a subset of neurons, contrast-induced filter changes are governed by particularly strong spike-timing dynamics, in particular by pronounced stimulus-dependent latency shifts that can be observed in these cells. Together, our results show that the contrast dependence of temporal filtering in retinal ganglion cells has a multifaceted phenomenology and that a multi-filter analysis can provide a useful basis for capturing the underlying signal-processing dynamics. '),
(87275, 2015, 'plos', 'Dynamics of the Heat Stress Response of Ceramides with Different Fatty-Acyl Chain Lengths in Bakers Yeast', 'Chen, Po-Wei|Fonseca, Luis L|Hannun, Yusuf A|Voit, Eberhard O', 'Wallace H. Coulter Department of Biomedical Engineering, Georgia Institute of Technology, Atlanta, Georgia, United States of America, The George W. Woodruff School of Mechanical Engineering, Georgia Institute of Technology, Atlanta, Georgia, United States of America.|Wallace H. Coulter Department of Biomedical Engineering, Georgia Institute of Technology, Atlanta, Georgia, United States of America.|The Cancer Center at Stony Brook Medicine, Stony Brook University, Health Science Center, Stony Brook, New York, United States of America.|Wallace H. Coulter Department of Biomedical Engineering, Georgia Institute of Technology, Atlanta, Georgia, United States of America.', 'Georgia|Georgia|United States|Georgia', 6, 'Ceramides|Computational Biology|Heat-Shock Response|Saccharomyces cerevisiae|Sphingolipids', 'Journal Article', '10.1371/journal.pcbi.1004373', '26241868', 'The article demonstrates that computational modeling has the capacity to convert metabolic snapshots, taken sequentially over time, into a description of cellular, dynamic strategies. The specific application is a detailed analysis of a set of actions with which Saccharomyces cerevisiae responds to heat stress. Using time dependent metabolic concentration data, we use a combination of mathematical modeling, reverse engineering, and optimization to infer dynamic changes in enzyme activities within the sphingolipid pathway. The details of the sphingolipid responses to heat stress are important, because they guide some of the longer-term alterations in gene expression, with which the cells adapt to the increased temperature. The analysis indicates that all enzyme activities in the system are affected and that the shapes of the time trends in activities depend on the fatty-acyl CoA chain lengths of the different ceramide species in the system. '),
(87276, 2015, 'plos', 'Dynamic Allostery of the Catabolite Activator Protein Revealed by Interatomic Forces', 'Louet, Maxime|Seifert, Christian|Hensen, Ulf|Gräter, Frauke', 'Heidelberg Institutes for Theoretical Studies gGmbH, Heidelberg, Germany.|Heidelberg Institutes for Theoretical Studies gGmbH, Heidelberg, Germany.|Eidgenössische Technische Hochschule Zürich, Department of Biosystem Science and Engineering, Basel, Switzerland.|Heidelberg Institutes for Theoretical Studies gGmbH, Heidelberg, Germany, CAS-MPG Partner Institute and Key Laboratory for Computational Biology, Shanghai, China.', 'Germany|Germany|Switzerland|China', 0, 'Allosteric Site|Cyclic AMP Receptor Protein|Entropy|Escherichia coli Proteins|Molecular Dynamics Simulation|Nuclear Magnetic Resonance, Biomolecular|Principal Component Analysis|Protein Binding', 'Journal Article', '10.1371/journal.pcbi.1004358', '26244893', 'The Catabolite Activator Protein (CAP) is a showcase example for entropic allostery. For full activation and DNA binding, the homodimeric protein requires the binding of two cyclic AMP (cAMP) molecules in an anti-cooperative manner, the source of which appears to be largely of entropic nature according to previous experimental studies. We here study at atomic detail the allosteric regulation of CAP with Molecular dynamics (MD) simulations. We recover the experimentally observed entropic penalty for the second cAMP binding event with our recently developed force covariance entropy estimator and reveal allosteric communication pathways with Force Distribution Analyses (FDA). Our observations show that CAP binding results in characteristic changes in the interaction pathways connecting the two cAMP allosteric binding sites with each other, as well as with the DNA binding domains. We identified crucial relays in the mostly symmetric allosteric activation network, and suggest point mutants to test this mechanism. Our study suggests inter-residue forces, as opposed to coordinates, as a highly sensitive measure for structural adaptations that, even though minute, can very effectively propagate allosteric signals. '),
(87277, 2015, 'plos', 'Evolution of Self-Organized Task Specialization in Robot Swarms', 'Ferrante, Eliseo|Turgut, Ali Emre|Duéñez-Guzmán, Edgar|Dorigo, Marco|Wenseleers, Tom', 'Laboratory of Socio-Ecology and Social Evolution, Zoological Institute, KU Leuven, Leuven, Belgium.|Mechanical Engineering Department, Middle East Technical University, Ankara, Turkey.|Laboratory of Socio-Ecology and Social Evolution, Zoological Institute, KU Leuven, Leuven, Belgium.|IRIDIA-CoDE, Université Libre de Bruxelles, Brussels, Belgium.|Laboratory of Socio-Ecology and Social Evolution, Zoological Institute, KU Leuven, Leuven, Belgium.', 'Belgium|Turkey|Belgium|Belgium|Belgium', 53, 'Animals|Ants|Artificial Intelligence|Biological Evolution|Computational Biology|Models, Biological|Robotics|Social Behavior|Task Performance and Analysis|Work', 'Journal Article', '10.1371/journal.pcbi.1004273', '26247819', 'Division of labor is ubiquitous in biological systems, as evidenced by various forms of complex task specialization observed in both animal societies and multicellular organisms. Although clearly adaptive, the way in which division of labor first evolved remains enigmatic, as it requires the simultaneous co-occurrence of several complex traits to achieve the required degree of coordination. Recently, evolutionary swarm robotics has emerged as an excellent test bed to study the evolution of coordinated group-level behavior. Here we use this framework for the first time to study the evolutionary origin of behavioral task specialization among groups of identical robots. The scenario we study involves an advanced form of division of labor, common in insect societies and known as task partitioning, whereby two sets of tasks have to be carried out in sequence by different individuals. Our results show that task partitioning is favored whenever the environment has features that, when exploited, reduce switching costs and increase the net efficiency of the group, and that an optimal mix of task specialists is achieved most readily when the behavioral repertoires aimed at carrying out the different subtasks are available as pre-adapted building blocks. Nevertheless, we also show for the first time that self-organized task specialization could be evolved entirely from scratch, starting only from basic, low-level behavioral primitives, using a nature-inspired evolutionary method known as Grammatical Evolution. Remarkably, division of labor was achieved merely by selecting on overall group performance, and without providing any prior information on how the global object retrieval task was best divided into smaller subtasks. We discuss the potential of our method for engineering adaptively behaving robot swarms and interpret our results in relation to the likely path that nature took to evolve complex sociality and task specialization.'),
(87278, 2015, 'plos', 'Automatic Adaptation to Fast Input Changes in a Time-Invariant Neural Circuit', 'Bharioke, Arjun|Chklovskii, Dmitri B', 'Janelia Research Campus, Howard Hughes Medical Institute, Ashburn, Virginia, United States of America.|Janelia Research Campus, Howard Hughes Medical Institute, Ashburn, Virginia, United States of America.', 'United States|United States', 0, 'Algorithms|Animals|Computational Biology|Feedback, Physiological|Finches|Models, Neurological|Neurons|Signal Transduction', 'Journal Article', '10.1371/journal.pcbi.1004315', '26247884', 'Neurons must faithfully encode signals that can vary over many orders of magnitude despite having only limited dynamic ranges. For a correlated signal, this dynamic range constraint can be relieved by subtracting away components of the signal that can be predicted from the past, a strategy known as predictive coding, that relies on learning the input statistics. However, the statistics of input natural signals can also vary over very short time scales e.g., following saccades across a visual scene. To maintain a reduced transmission cost to signals with rapidly varying statistics, neuronal circuits implementing predictive coding must also rapidly adapt their properties. Experimentally, in different sensory modalities, sensory neurons have shown such adaptations within 100 ms of an input change. Here, we show first that linear neurons connected in a feedback inhibitory circuit can implement predictive coding. We then show that adding a rectification nonlinearity to such a feedback inhibitory circuit allows it to automatically adapt and approximate the performance of an optimal linear predictive coding network, over a wide range of inputs, while keeping its underlying temporal and synaptic properties unchanged. We demonstrate that the resulting changes to the linearized temporal filters of this nonlinear network match the fast adaptations observed experimentally in different sensory modalities, in different vertebrate species. Therefore, the nonlinear feedback inhibitory network can provide automatic adaptation to fast varying signals, maintaining the dynamic range necessary for accurate neuronal transmission of natural inputs. ');
INSERT INTO `papers` (`id`, `ano`, `journal`, `titulo`, `autores`, `afiliacao`, `pais`, `citacoes`, `palavra_chave`, `categorias`, `doi`, `pubmed`, `abstract`) VALUES
(87279, 2015, 'plos', 'Informatics for RNA Sequencing: A Web Resource for Analysis on the Cloud', 'Griffith, Malachi|Walker, Jason R|Spies, Nicholas C|Ainscough, Benjamin J|Griffith, Obi L', 'McDonnell Genome Institute, Washington University School of Medicine, St. Louis, Missouri, United States of America, Siteman Cancer Center, Washington University School of Medicine, St. Louis, Missouri, United States of America, Department of Genetics, Washington University School of Medicine, St. Louis, Missouri, United States of America.|McDonnell Genome Institute, Washington University School of Medicine, St. Louis, Missouri, United States of America.|McDonnell Genome Institute, Washington University School of Medicine, St. Louis, Missouri, United States of America.|McDonnell Genome Institute, Washington University School of Medicine, St. Louis, Missouri, United States of America, Siteman Cancer Center, Washington University School of Medicine, St. Louis, Missouri, United States of America.|McDonnell Genome Institute, Washington University School of Medicine, St. Louis, Missouri, United States of America, Siteman Cancer Center, Washington University School of Medicine, St. Louis, Missouri, United States of America, Department of Genetics, Washington University School of Medicine, St. Louis, Missouri, United States of America, Department of Medicine, Washington University School of Medicine, St. Louis, Missouri, United States of America.', 'United States|United States|United States|United States|United States', 31, 'Computational Biology|Gene Expression Profiling|Humans|Internet|RNA|Sequence Analysis, RNA|Software', 'Journal Article', '10.1371/journal.pcbi.1004393', '26248053', 'Massively parallel RNA sequencing (RNA-seq) has rapidly become the assay of choice for interrogating RNA transcript abundance and diversity. This article provides a detailed introduction to fundamental RNA-seq molecular biology and informatics concepts. We make available open-access RNA-seq tutorials that cover cloud computing, tool installation, relevant file formats, reference genomes, transcriptome annotations, quality-control strategies, expression, differential expression, and alternative splicing analysis methods. These tutorials and additional training resources are accompanied by complete analysis pipelines and test datasets made available without encumbrance at www.rnaseq.wiki. '),
(87280, 2015, 'plos', 'The Force at the Tip--Modelling Tension and Proliferation in Sprouting Angiogenesis', 'Santos-Oliveira, Patrícia|Correia, António|Rodrigues, Tiago|Ribeiro-Rodrigues, Teresa M|Matafome, Paulo|Rodríguez-Manzaneque, Juan Carlos|Seiça, Raquel|Girão, Henrique|Travasso, Rui D M', 'CFisUC, Department of Physics, University of Coimbra, Coimbra, Portugal.|Institute for Biomedical Imaging and Life Sciences (IBILI), Faculty of Medicine, University of Coimbra, Coimbra, Portugal.|Institute for Biomedical Imaging and Life Sciences (IBILI), Faculty of Medicine, University of Coimbra, Coimbra, Portugal.|Institute for Biomedical Imaging and Life Sciences (IBILI), Faculty of Medicine, University of Coimbra, Coimbra, Portugal.|Institute for Biomedical Imaging and Life Sciences (IBILI), Faculty of Medicine, University of Coimbra, Coimbra, Portugal, Department of Complementary Sciences, Coimbra Health School (ESTeSC), Instituto Politécnico de Coimbra, Coimbra, Portugal.|Centre for Genomics and Oncological Research: Pfizer/Universidad de Granada/Junta de Andalucía (GENYO), Granada, Spain.|Institute for Biomedical Imaging and Life Sciences (IBILI), Faculty of Medicine, University of Coimbra, Coimbra, Portugal.|Institute for Biomedical Imaging and Life Sciences (IBILI), Faculty of Medicine, University of Coimbra, Coimbra, Portugal.|CFisUC, Department of Physics, University of Coimbra, Coimbra, Portugal.', 'Portugal|Portugal|Portugal|Portugal|Portugal|Spain|Portugal|Portugal|Portugal', 23, 'Animals|Blood Vessels|Cell Proliferation|Computational Biology|Humans|Mice|Models, Cardiovascular|Neovascularization, Pathologic|Neovascularization, Physiologic|Vascular Endothelial Growth Factor A', 'Journal Article', '10.1371/journal.pcbi.1004436', '26248210', 'Sprouting angiogenesis, where new blood vessels grow from pre-existing ones, is a complex process where biochemical and mechanical signals regulate endothelial cell proliferation and movement. Therefore, a mathematical description of sprouting angiogenesis has to take into consideration biological signals as well as relevant physical processes, in particular the mechanical interplay between adjacent endothelial cells and the extracellular microenvironment. In this work, we introduce the first phase-field continuous model of sprouting angiogenesis capable of predicting sprout morphology as a function of the elastic properties of the tissues and the traction forces exerted by the cells. The model is very compact, only consisting of three coupled partial differential equations, and has the clear advantage of a reduced number of parameters. This model allows us to describe sprout growth as a function of the cell-cell adhesion forces and the traction force exerted by the sprout tip cell. In the absence of proliferation, we observe that the sprout either achieves a maximum length or, when the traction and adhesion are very large, it breaks. Endothelial cell proliferation alters significantly sprout morphology, and we explore how different types of endothelial cell proliferation regulation are able to determine the shape of the growing sprout. The largest region in parameter space with well formed long and straight sprouts is obtained always when the proliferation is triggered by endothelial cell strain and its rate grows with angiogenic factor concentration. We conclude that in this scenario the tip cell has the role of creating a tension in the cells that follow its lead. On those first stalk cells, this tension produces strain and/or empty spaces, inevitably triggering cell proliferation. The new cells occupy the space behind the tip, the tension decreases, and the process restarts. Our results highlight the ability of mathematical models to suggest relevant hypotheses with respect to the role of forces in sprouting, hence underlining the necessary collaboration between modelling and molecular biology techniques to improve the current state-of-the-art. '),
(87281, 2015, 'plos', 'Knowledge-Based Analysis for Detecting Key Signaling Events from Time-Series Phosphoproteomics Data', 'Yang, Pengyi|Zheng, Xiaofeng|Jayaswal, Vivek|Hu, Guang|Yang, Jean Yee Hwa|Jothi, Raja', 'Epigenetics & Stem Cell Biology Laboratory, National Institute of Environmental Health Sciences, National Institutes of Health, Research Triangle Park, Durham, North Carolina, United States of America, Biostatistics Branch, National Institute of Environmental Health Sciences, National Institutes of Health, Research Triangle Park, Durham, North Carolina, United States of America.|Epigenetics & Stem Cell Biology Laboratory, National Institute of Environmental Health Sciences, National Institutes of Health, Research Triangle Park, Durham, North Carolina, United States of America.|Centre for Mathematical Biology, School of Mathematics and Statistics, University of Sydney, Sydney, Australia.|Epigenetics & Stem Cell Biology Laboratory, National Institute of Environmental Health Sciences, National Institutes of Health, Research Triangle Park, Durham, North Carolina, United States of America.|Centre for Mathematical Biology, School of Mathematics and Statistics, University of Sydney, Sydney, Australia.|Epigenetics & Stem Cell Biology Laboratory, National Institute of Environmental Health Sciences, National Institutes of Health, Research Triangle Park, Durham, North Carolina, United States of America, Biostatistics Branch, National Institute of Environmental Health Sciences, National Institutes of Health, Research Triangle Park, Durham, North Carolina, United States of America.', 'United States|United States|Australia|United States|Australia|United States', 0, 'Cell Communication|Cell Differentiation|Cell Line|Databases, Protein|Embryonic Stem Cells|Humans|Knowledge Bases|Phosphoproteins|Proteome|Proteomics|Signal Transduction', 'Journal Article', '10.1371/journal.pcbi.1004403', '26252020', 'Cell signaling underlies transcription/epigenetic control of a vast majority of cell-fate decisions. A key goal in cell signaling studies is to identify the set of kinases that underlie key signaling events. In a typical phosphoproteomics study, phosphorylation sites (substrates) of active kinases are quantified proteome-wide. By analyzing the activities of phosphorylation sites over a time-course, the temporal dynamics of signaling cascades can be elucidated. Since many substrates of a given kinase have similar temporal kinetics, clustering phosphorylation sites into distinctive clusters can facilitate identification of their respective kinases. Here we present a knowledge-based CLUster Evaluation (CLUE) approach for identifying the most informative partitioning of a given temporal phosphoproteomics data. Our approach utilizes prior knowledge, annotated kinase-substrate relationships mined from literature and curated databases, to first generate biologically meaningful partitioning of the phosphorylation sites and then determine key kinases associated with each cluster. We demonstrate the utility of the proposed approach on two time-series phosphoproteomics datasets and identify key kinases associated with human embryonic stem cell differentiation and insulin signaling pathway. The proposed approach will be a valuable resource in the identification and characterizing of signaling networks from phosphoproteomics data. '),
(87282, 2015, 'plos', 'Modularity of Protein Folds as a Tool for Template-Free Modeling of Structures', 'Vallat, Brinda|Madrid-Aliste, Carlos|Fiser, Andras', 'Department of Systems and Computational Biology, Albert Einstein College of Medicine, Bronx, New York, New York, United States of America.|Department of Systems and Computational Biology, Albert Einstein College of Medicine, Bronx, New York, New York, United States of America.|Department of Systems and Computational Biology, Albert Einstein College of Medicine, Bronx, New York, New York, United States of America.', 'United States|United States|United States', 0, 'Algorithms|Amino Acid Motifs|Computational Biology|Models, Molecular|Protein Conformation|Protein Folding|Proteins|Sequence Analysis, Protein|Software', 'Journal Article', '10.1371/journal.pcbi.1004419', '26252221', 'Predicting the three-dimensional structure of proteins from their amino acid sequences remains a challenging problem in molecular biology. While the current structural coverage of proteins is almost exclusively provided by template-based techniques, the modeling of the rest of the protein sequences increasingly require template-free methods. However, template-free modeling methods are much less reliable and are usually applicable for smaller proteins, leaving much space for improvement. We present here a novel computational method that uses a library of supersecondary structure fragments, known as Smotifs, to model protein structures. The library of Smotifs has saturated over time, providing a theoretical foundation for efficient modeling. The method relies on weak sequence signals from remotely related protein structures to create a library of Smotif fragments specific to the target protein sequence. This Smotif library is exploited in a fragment assembly protocol to sample decoys, which are assessed by a composite scoring function. Since the Smotif fragments are larger in size compared to the ones used in other fragment-based methods, the proposed modeling algorithm, SmotifTF, can employ an exhaustive sampling during decoy assembly. SmotifTF successfully predicts the overall fold of the target proteins in about 50% of the test cases and performs competitively when compared to other state of the art prediction methods, especially when sequence signal to remote homologs is diminishing. Smotif-based modeling is complementary to current prediction methods and provides a promising direction in addressing the structure prediction problem, especially when targeting larger proteins for modeling. '),
(87283, 2015, 'plos', 'Irradiation of Neurons with High-Energy Charged Particles: An In Silico Modeling Approach', 'Alp, Murat|Parihar, Vipan K|Limoli, Charles L|Cucinotta, Francis A', 'Department of Health Physics and Diagnostic Sciences, University of Nevada, Las Vegas, Las Vegas, Nevada, United States of America.|Department of Radiation Oncology, University of California, Irvine, Irvine, California, United States of America.|Department of Radiation Oncology, University of California, Irvine, Irvine, California, United States of America.|Department of Health Physics and Diagnostic Sciences, University of Nevada, Las Vegas, Las Vegas, Nevada, United States of America.', 'United States|United States|United States|United States', 0, 'Animals|Computational Biology|Computer Simulation|Dendrites|Dentate Gyrus|Mice|Models, Neurological|Monte Carlo Method|Neurons|Pseudopodia|Radiochemistry|Radiometry', 'Journal Article', '10.1371/journal.pcbi.1004428', '26252394', 'In this work, a stochastic computational model of microscopic energy deposition events is used to study for the first time damage to irradiated neuronal cells of the mouse hippocampus. An extensive library of radiation tracks for different particle types is created to score energy deposition in small voxels and volume segments describing a neurons morphology that later are sampled for given particle fluence or dose. Methods included the construction of in silico mouse hippocampal granule cells from neuromorpho.org with spine and filopodia segments stochastically distributed along the dendritic branches. The model is tested with high-energy (56)Fe, (12)C, and (1)H particles and electrons. Results indicate that the tree-like structure of the neuronal morphology and the microscopic dose deposition of distinct particles may lead to different outcomes when cellular injury is assessed, leading to differences in structural damage for the same absorbed dose. The significance of the microscopic dose in neuron components is to introduce specific local and global modes of cellular injury that likely contribute to spine, filopodia, and dendrite pruning, impacting cognition and possibly the collapse of the neuron. Results show that the heterogeneity of heavy particle tracks at low doses, compared to the more uniform dose distribution of electrons, juxtaposed with neuron morphology make it necessary to model the spatial dose painting for specific neuronal components. Going forward, this work can directly support the development of biophysical models of the modifications of spine and dendritic morphology observed after low dose charged particle irradiation by providing accurate descriptions of the underlying physical insults to complex neuron structures at the nano-meter scale.'),
(87284, 2015, 'plos', 'Exhaustive Analysis of a Genotype Space Comprising 10(15 )Central Carbon Metabolisms Reveals an Organization Conducive to Metabolic Innovation', 'Hosseini, Sayed-Rzgar|Barve, Aditya|Wagner, Andreas', 'Institute of Evolutionary Biology and Environmental Sciences, University of Zürich, Zürich, Switzerland, Swiss Institute of Bioinformatics, Quartier Sorge, Batiment Genopode, Lausanne, Switzerland.|Institute of Evolutionary Biology and Environmental Sciences, University of Zürich, Zürich, Switzerland, Swiss Institute of Bioinformatics, Quartier Sorge, Batiment Genopode, Lausanne, Switzerland.|Institute of Evolutionary Biology and Environmental Sciences, University of Zürich, Zürich, Switzerland, Swiss Institute of Bioinformatics, Quartier Sorge, Batiment Genopode, Lausanne, Switzerland, Santa Fe Institute, Santa Fe, New Mexico, United States of America.', 'Switzerland|Switzerland|Switzerland', 8, 'Biological Evolution|Carbon|Computational Biology|Genotype|Metabolism|Models, Genetic|Phenotype', 'Journal Article', '10.1371/journal.pcbi.1004329', '26252881', 'All biological evolution takes place in a space of possible genotypes and their phenotypes. The structure of this space defines the evolutionary potential and limitations of an evolving system. Metabolism is one of the most ancient and fundamental evolving systems, sustaining life by extracting energy from extracellular nutrients. Here we study metabolisms potential for innovation by analyzing an exhaustive genotype-phenotype map for a space of 10(15) metabolisms that encodes all possible subsets of 51 reactions in central carbon metabolism. Using flux balance analysis, we predict the viability of these metabolisms on 10 different carbon sources which give rise to 1024 potential metabolic phenotypes. Although viable metabolisms with any one phenotype comprise a tiny fraction of genotype space, their absolute numbers exceed 10(9) for some phenotypes. Metabolisms with any one phenotype typically form a single network of genotypes that extends far or all the way through metabolic genotype space, where any two genotypes can be reached from each other through a series of single reaction changes. The minimal distance of genotype networks associated with different phenotypes is small, such that one can reach metabolisms with novel phenotypes--viable on new carbon sources--through one or few genotypic changes. Exceptions to these principles exist for those metabolisms whose complexity (number of reactions) is close to the minimum needed for viability. Increasing metabolic complexity enhances the potential for both evolutionary conservation and evolutionary innovation.'),
(87285, 2015, 'plos', 'A Spatially Detailed Model of Isometric Contraction Based on Competitive Binding of Troponin I Explains Cooperative Interactions between Tropomyosin and Crossbridges', 'Land, Sander|Niederer, Steven A', 'Department of Biomedical Engineering, Kings College London, United Kingdom.|Department of Biomedical Engineering, Kings College London, United Kingdom.', 'United Kingdom|United Kingdom', 0, 'Animals|Binding, Competitive|Humans|Isometric Contraction|Mice|Models, Biological|Rats|Tropomyosin|Troponin I', 'Journal Article', '10.1371/journal.pcbi.1004376', '26262582', 'Biophysical models of cardiac tension development provide a succinct representation of our understanding of force generation in the heart. The link between protein kinetics and interactions that gives rise to high cooperativity is not yet fully explained from experiments or previous biophysical models. We propose a biophysical ODE-based representation of cross-bridge (XB), tropomyosin and troponin within a contractile regulatory unit (RU) to investigate the mechanisms behind cooperative activation, as well as the role of cooperativity in dynamic tension generation across different species. The model includes cooperative interactions between regulatory units (RU-RU), between crossbridges (XB-XB), as well more complex interactions between crossbridges and regulatory units (XB-RU interactions). For the steady-state force-calcium relationship, our framework predicts that: (1) XB-RU effects are key in shifting the half-activation value of the force-calcium relationship towards lower [Ca(2+)], but have only small effects on cooperativity. (2) XB-XB effects approximately double the duty ratio of myosin, but do not significantly affect cooperativity. (3) RU-RU effects derived from the long-range action of tropomyosin are a major factor in cooperative activation, with each additional unblocked RU increasing the rate of additional RUs unblocking. (4) Myosin affinity for short (1-4 RU) unblocked stretches of actin of is very low, and the resulting suppression of force at low [Ca(2+)] is a major contributor in the biphasic force-calcium relationship. We also reproduce isometric tension development across mouse, rat and human at physiological temperature and pacing rate, and conclude that species differences require only changes in myosin affinity and troponin I/troponin C affinity. Furthermore, we show that the calcium dependence of the rate of tension redevelopment k(tr) is explained by transient blocking of RUs by a temporary decrease in XB-RU effects.'),
(87286, 2015, 'plos', 'Manifold Based Optimization for Single-Cell 3D Genome Reconstruction', 'Paulsen, Jonas|Gramstad, Odin|Collas, Philippe', 'Department of Molecular Medicine, Institute of Basic Medical Sciences, Faculty of Medicine, and Norwegian Center for Stem Cell Research, University of Oslo, 0317 Oslo, Norway.|Department of Molecular Medicine, Institute of Basic Medical Sciences, Faculty of Medicine, and Norwegian Center for Stem Cell Research, University of Oslo, 0317 Oslo, Norway.|Department of Molecular Medicine, Institute of Basic Medical Sciences, Faculty of Medicine, and Norwegian Center for Stem Cell Research, University of Oslo, 0317 Oslo, Norway.', 'Norway|Norway|Norway', 16, 'Algorithms|Animals|Chromosome Mapping|Chromosomes|Computational Biology|Genome|Imaging, Three-Dimensional|Mice', 'Journal Article', '10.1371/journal.pcbi.1004396', '26262780', 'The three-dimensional (3D) structure of the genome is important for orchestration of gene expression and cell differentiation. While mapping genomes in 3D has for a long time been elusive, recent adaptations of high-throughput sequencing to chromosome conformation capture (3C) techniques, allows for genome-wide structural characterization for the first time. However, reconstruction of consensus 3D genomes from 3C-based data is a challenging problem, since the data are aggregated over millions of cells. Recent single-cell adaptations to the 3C-technique, however, allow for non-aggregated structural assessment of genome structure, but data suffer from sparse and noisy interaction sampling. We present a manifold based optimization (MBO) approach for the reconstruction of 3D genome structure from chromosomal contact data. We show that MBO is able to reconstruct 3D structures based on the chromosomal contacts, imposing fewer structural violations than comparable methods. Additionally, MBO is suitable for efficient high-throughput reconstruction of large systems, such as entire genomes, allowing for comparative studies of genomic structure across cell-lines and different species. '),
(87287, 2015, 'plos', 'Partial Unwrapping and Histone Tail Dynamics in Nucleosome Revealed by Coarse-Grained Molecular Simulations', 'Kenzaki, Hiroo|Takada, Shoji', 'Advanced Center for Computing and Communication, RIKEN, Hirosawa, Wako, Saitama, Japan, Department of Biophysics, Graduate School of Science, Kyoto University, Kyoto, Kitashirakawa Sakyo, Kyoto, Japan.|Advanced Center for Computing and Communication, RIKEN, Hirosawa, Wako, Saitama, Japan, Department of Biophysics, Graduate School of Science, Kyoto University, Kyoto, Kitashirakawa Sakyo, Kyoto, Japan.', 'Japan|Japan', 0, 'Computational Biology|DNA|Histones|Models, Genetic|Molecular Dynamics Simulation|Nucleosomes', 'Journal Article', '10.1371/journal.pcbi.1004443', '26262925', 'Nucleosomes, basic units of chromatin, are known to show spontaneous DNA unwrapping dynamics that are crucial for transcriptional activation, but its structural details are yet to be elucidated. Here, employing a coarse-grained molecular model that captures residue-level structural details up to histone tails, we simulated equilibrium fluctuations and forced unwrapping of single nucleosomes at various conditions. The equilibrium simulations showed spontaneous unwrapping from outer DNA and subsequent rewrapping dynamics, which are in good agreement with experiments. We found several distinct partially unwrapped states of nucleosomes, as well as reversible transitions among these states. At a low salt concentration, histone tails tend to sit in the concave cleft between the histone octamer and DNA, tightening the nucleosome. At a higher salt concentration, the tails tend to bound to the outer side of DNA or be expanded outwards, which led to higher degree of unwrapping. Of the four types of histone tails, H3 and H2B tail dynamics are markedly correlated with partial unwrapping of DNA, and, moreover, their contributions were distinct. Acetylation in histone tails was simply mimicked by changing their charges, which enhanced the unwrapping, especially markedly for H3 and H2B tails. '),
(87288, 2015, 'plos', 'The Beta Cell in Its Cluster: Stochastic Graphs of Beta Cell Connectivity in the Islets of Langerhans', 'Striegel, Deborah A|Hara, Manami|Periwal, Vipul', 'Laboratory of Biological Modeling, National Institute of Diabetes and Digestive and Kidney Diseases, National Institutes of Health, Bethesda, Maryland, United States of America.|Department of Medicine, University of Chicago, Chicago, Illinois, United States of America.|Laboratory of Biological Modeling, National Institute of Diabetes and Digestive and Kidney Diseases, National Institutes of Health, Bethesda, Maryland, United States of America.', 'United States|United States|United States', 0, 'Adult|Aged|Aged, 80 and over|Algorithms|Computational Biology|Diabetes Mellitus, Type 2|Female|Humans|Insulin-Secreting Cells|Islets of Langerhans|Male|Middle Aged|Stochastic Processes', 'Journal Article', '10.1371/journal.pcbi.1004423', '26266953', 'Pancreatic islets of Langerhans consist of endocrine cells, primarily xcexb1, xcexb2 and xcexb4 cells, which secrete glucagon, insulin, and somatostatin, respectively, to regulate plasma glucose. xcexb2 cells form irregular locally connected clusters within islets that act in concert to secrete insulin upon glucose stimulation. Due to the central functional significance of this local connectivity in the placement of xcexb2 cells in an islet, it is important to characterize it quantitatively. However, quantification of the seemingly stochastic cytoarchitecture of xcexb2 cells in an islet requires mathematical methods that can capture topological connectivity in the entire xcexb2-cell population in an islet. Graph theory provides such a framework. Using large-scale imaging data for thousands of islets containing hundreds of thousands of cells in human organ donor pancreata, we show that quantitative graph characteristics differ between control and type 2 diabetic islets. Further insight into the processes that shape and maintain this architecture is obtained by formulating a stochastic theory of xcexb2-cell rearrangement in whole islets, just as the normal equilibrium distribution of the Ornstein-Uhlenbeck process can be viewed as the result of the interplay between a random walk and a linear restoring force. Requiring that rearrangements maintain the observed quantitative topological graph characteristics strongly constrained possible processes. Our results suggest that xcexb2-cell rearrangement is dependent on its connectivity in order to maintain an optimal cluster size in both normal and T2D islets. '),
(87289, 2015, 'plos', 'A Bayesian Attractor Model for Perceptual Decision Making', 'Bitzer, Sebastian|Bruineberg, Jelle|Kiebel, Stefan J', 'Max Planck Institute for Human Cognitive and Brain Sciences, Department of Neurology, 04103 Leipzig, Germany, Department of Psychology, Technische Universität Dresden, 01062 Dresden, Germany.|Max Planck Institute for Human Cognitive and Brain Sciences, Department of Neurology, 04103 Leipzig, Germany, Department of Philosophy, Institute for Logic, Language and Computation, University of Amsterdam, 1012 GC, Amsterdam, the Netherlands.|Max Planck Institute for Human Cognitive and Brain Sciences, Department of Neurology, 04103 Leipzig, Germany, Department of Psychology, Technische Universität Dresden, 01062 Dresden, Germany, Biomagnetic Centre, Hans Berger Clinic for Neurology, University Hospital Jena, 07747 Jena, Germany.', 'Germany|Germany|Germany', 14, 'Animals|Bayes Theorem|Behavior, Animal|Computational Biology|Decision Making|Haplorhini|Models, Neurological|Reaction Time', 'Journal Article', '10.1371/journal.pcbi.1004442', '26267143', 'Even for simple perceptual decisions, the mechanisms that the brain employs are still under debate. Although current consensus states that the brain accumulates evidence extracted from noisy sensory information, open questions remain about how this simple model relates to other perceptual phenomena such as flexibility in decisions, decision-dependent modulation of sensory gain, or confidence about a decision. We propose a novel approach of how perceptual decisions are made by combining two influential formalisms into a new model. Specifically, we embed an attractor model of decision making into a probabilistic framework that models decision making as Bayesian inference. We show that the new model can explain decision making behaviour by fitting it to experimental data. In addition, the new model combines for the first time three important features: First, the model can update decisions in response to switches in the underlying stimulus. Second, the probabilistic formulation accounts for top-down effects that may explain recent experimental findings of decision-related gain modulation of sensory neurons. Finally, the model computes an explicit measure of confidence which we relate to recent experimental evidence for confidence computations in perceptual decision tasks. '),
(87290, 2015, 'plos', 'One Size Doesnt Fit All - RefEditor: Building Personalized Diploid Reference Genome to Improve Read Mapping and Genotype Calling in Next Generation Sequencing Studies', 'Yuan, Shuai|Johnston, H Richard|Zhang, Guosheng|Li, Yun|Hu, Yi-Juan|Qin, Zhaohui S', 'Mathematics & Computer Science Department, Emory University, Atlanta, Georgia, United States of America.|Department of Biostatistics and Bioinformatics, Rollins School of Public Health, Emory University, Atlanta, Georgia, United States of America.|Department of Genetics, Department of Biostatistics, Department of Computer Science, University of North Carolina, Chapel Hill, Chapel Hill, North Carolina, United States of America.|Department of Genetics, Department of Biostatistics, Department of Computer Science, University of North Carolina, Chapel Hill, Chapel Hill, North Carolina, United States of America.|Department of Biostatistics and Bioinformatics, Rollins School of Public Health, Emory University, Atlanta, Georgia, United States of America.|Department of Biostatistics and Bioinformatics, Rollins School of Public Health, Emory University, Atlanta, Georgia, United States of America.', 'Georgia|Georgia|United States|United States|Georgia|Georgia', 0, 'Chromosome Mapping|Databases, Genetic|Diploidy|Genome|Genomics|Genotyping Techniques|High-Throughput Nucleotide Sequencing|Humans|Sequence Analysis, DNA|Software', 'Journal Article', '10.1371/journal.pcbi.1004448', '26267278', 'With rapid decline of the sequencing cost, researchers today rush to embrace whole genome sequencing (WGS), or whole exome sequencing (WES) approach as the next powerful tool for relating genetic variants to human diseases and phenotypes. A fundamental step in analyzing WGS and WES data is mapping short sequencing reads back to the reference genome. This is an important issue because incorrectly mapped reads affect the downstream variant discovery, genotype calling and association analysis. Although many read mapping algorithms have been developed, the majority of them uses the universal reference genome and do not take sequence variants into consideration. Given that genetic variants are ubiquitous, it is highly desirable if they can be factored into the read mapping procedure. In this work, we developed a novel strategy that utilizes genotypes obtained a priori to customize the universal haploid reference genome into a personalized diploid reference genome. The new strategy is implemented in a program named RefEditor. When applying RefEditor to real data, we achieved encouraging improvements in read mapping, variant discovery and genotype calling. Compared to standard approaches, RefEditor can significantly increase genotype calling consistency (from 43% to 61% at 4X coverage, from 82% to 92% at 20X coverage) and reduce Mendelian inconsistency across various sequencing depths. Because many WGS and WES studies are conducted on cohorts that have been genotyped using array-based genotyping platforms previously or concurrently, we believe the proposed strategy will be of high value in practice, which can also be applied to the scenario where multiple NGS experiments are conducted on the same cohort. The RefEditor sources are available at https://github.com/superyuan/refeditor. '),
(87291, 2015, 'plos', 'The Role of Cell Volume in the Dynamics of Seizure, Spreading Depression, and Anoxic Depolarization', 'Ullah, Ghanim|Wei, Yina|Dahlem, Markus A|Wechselberger, Martin|Schiff, Steven J', 'Department of Physics, University of South Florida, Tampa, Florida 33620, United States of America.|Department of Cell Biology and Neuroscience, University of California, Riverside, California 92501 United States of America.|Humboldt-Universität zu Berlin, 10115 Berlin, Germany.|School of Mathematics and Statistics, University of Sydney, New South Wales, 2006, Australia.|Center for Neural Engineering, Departments of Engineering Science and Mechanics, Neurosurgery, and Physics, The Pennsylvania State University, University Park, Pennsylvania 16802, United States of America.', 'United States|United States|Germany|Australia|United States', 32, 'Brain|Cell Size|Cellular Microenvironment|Computational Biology|Depression|Humans|Hypoxia|Models, Neurological|Neurons|Seizures', 'Journal Article', '10.1371/journal.pcbi.1004414', '26273829', 'Cell volume changes are ubiquitous in normal and pathological activity of the brain. Nevertheless, we know little of how cell volume affects neuronal dynamics. We here performed the first detailed study of the effects of cell volume on neuronal dynamics. By incorporating cell swelling together with dynamic ion concentrations and oxygen supply into Hodgkin-Huxley type spiking dynamics, we demonstrate the spontaneous transition between epileptic seizure and spreading depression states as the cell swells and contracts in response to changes in osmotic pressure. Our use of volume as an order parameter further revealed a dynamical definition for the experimentally described physiological ceiling that separates seizure from spreading depression, as well as predicted a second ceiling that demarcates spreading depression from anoxic depolarization. Our model highlights the neuroprotective role of glial K buffering against seizures and spreading depression, and provides novel insights into anoxic depolarization and the relevant cell swelling during ischemia. We argue that the dynamics of seizures, spreading depression, and anoxic depolarization lie along a continuum of the repertoire of the neuron membrane that can be understood only when the dynamic ion concentrations, oxygen homeostasis,and cell swelling in response to osmotic pressure are taken into consideration. Our results demonstrate the feasibility of a unified framework for a wide range of neuronal behaviors that may be of substantial importance in the understanding of and potentially developing universal intervention strategies for these pathological states. '),
(87292, 2015, 'plos', 'Systematic Mapping of Protein Mutational Space by Prolonged Drift Reveals the Deleterious Effects of Seemingly Neutral Mutations', 'Rockah-Shmuel, Liat|Tóth-Petróczy, Ágnes|Tawfik, Dan S', 'Department of Biological Chemistry, Weizmann Institute of Science, Rehovot, Israel.|Department of Biological Chemistry, Weizmann Institute of Science, Rehovot, Israel.|Department of Biological Chemistry, Weizmann Institute of Science, Rehovot, Israel.', 'Israel|Israel|Israel', 0, 'Bacterial Proteins|Computational Biology|DNA Modification Methylases|Evolution, Molecular|Genetic Drift|Haemophilus|Models, Genetic|Mutation|Proteins', 'Journal Article', '10.1371/journal.pcbi.1004421', '26274323', 'Systematic mappings of the effects of protein mutations are becoming increasingly popular. Unexpectedly, these experiments often find that proteins are tolerant to most amino acid substitutions, including substitutions in positions that are highly conserved in nature. To obtain a more realistic distribution of the effects of protein mutations, we applied a laboratory drift comprising 17 rounds of random mutagenesis and selection of M.HaeIII, a DNA methyltransferase. During this drift, multiple mutations gradually accumulated. Deep sequencing of the drifted gene ensembles allowed determination of the relative effects of all possible single nucleotide mutations. Despite being averaged across many different genetic backgrounds, about 67% of all nonsynonymous, missense mutations were evidently deleterious, and an additional 16% were likely to be deleterious. In the early generations, the frequency of most deleterious mutations remained high. However, by the 17th generation, their frequency was consistently reduced, and those remaining were accepted alongside compensatory mutations. The tolerance to mutations measured in this laboratory drift correlated with sequence exchanges seen in M.HaeIIIs natural orthologs. The biophysical constraints dictating purging in nature and in this laboratory drift also seemed to overlap. Our experiment therefore provides an improved method for measuring the effects of protein mutations that more closely replicates the natural evolutionary forces, and thereby a more realistic view of the mutational space of proteins. '),
(87293, 2015, 'plos', 'Unbiased Quantitative Models of Protein Translation Derived from Ribosome Profiling Data', 'Gritsenko, Alexey A|Hulsman, Marc|Reinders, Marcel J T|de Ridder, Dick', 'The Delft Bioinformatics Lab, Department of Intelligent Systems, Delft University of Technology, Delft, The Netherlands, Platform Green Synthetic Biology, Delft, The Netherlands, Kluyver Centre for Genomics of Industrial Fermentation, Delft, The Netherlands.|The Delft Bioinformatics Lab, Department of Intelligent Systems, Delft University of Technology, Delft, The Netherlands.|The Delft Bioinformatics Lab, Department of Intelligent Systems, Delft University of Technology, Delft, The Netherlands, Kluyver Centre for Genomics of Industrial Fermentation, Delft, The Netherlands.|The Delft Bioinformatics Lab, Department of Intelligent Systems, Delft University of Technology, Delft, The Netherlands, Platform Green Synthetic Biology, Delft, The Netherlands, Kluyver Centre for Genomics of Industrial Fermentation, Delft, The Netherlands, Bioinformatics Group, Wageningen University, Wageningen, The Netherlands.', 'Netherlands|Netherlands|Netherlands|Netherlands', 13, 'Computational Biology|Models, Genetic|Protein Biosynthesis|RNA, Fungal|RNA, Messenger|Ribosomes|Saccharomyces cerevisiae', 'Journal Article', '10.1371/journal.pcbi.1004336', '26275099', 'Translation of RNA to protein is a core process for any living organism. While for some steps of this process the effect on protein production is understood, a holistic understanding of translation still remains elusive. In silico modelling is a promising approach for elucidating the process of protein synthesis. Although a number of computational models of the process have been proposed, their application is limited by the assumptions they make. Ribosome profiling (RP), a relatively new sequencing-based technique capable of recording snapshots of the locations of actively translating ribosomes, is a promising source of information for deriving unbiased data-driven translation models. However, quantitative analysis of RP data is challenging due to high measurement variance and the inability to discriminate between the number of ribosomes measured on a gene and their speed of translation. We propose a solution in the form of a novel multi-scale interpretation of RP data that allows for deriving models with translation dynamics extracted from the snapshots. We demonstrate the usefulness of this approach by simultaneously determining for the first time per-codon translation elongation and per-gene translation initiation rates of Saccharomyces cerevisiae from RP data for two versions of the Totally Asymmetric Exclusion Process (TASEP) model of translation. We do this in an unbiased fashion, by fitting the models using only RP data with a novel optimization scheme based on Monte Carlo simulation to keep the problem tractable. The fitted models match the data significantly better than existing models and their predictions show better agreement with several independent protein abundance datasets than existing models. Results additionally indicate that the tRNA pool adaptation hypothesis is incomplete, with evidence suggesting that tRNA post-transcriptional modifications and codon context may play a role in determining codon elongation rates. '),
(87294, 2015, 'plos', 'Controlled Measurement and Comparative Analysis of Cellular Components in E coli Reveals Broad Regulatory Changes in Response to Glucose Starvation', 'Houser, John R|Barnhart, Craig|Boutz, Daniel R|Carroll, Sean M|Dasgupta, Aurko|Michener, Joshua K|Needham, Brittany D|Papoulas, Ophelia|Sridhara, Viswanadham|Sydykova, Dariya K|Marx, Christopher J|Trent, M Stephen|Barrick, Jeffrey E|Marcotte, Edward M|Wilke, Claus O', 'Institute for Cellular and Molecular Biology, The University of Texas at Austin, Austin, Texas, United States of America, Center for Systems and Synthetic Biology, The University of Texas at Austin, Austin, Texas, United States of America.|Institute for Cellular and Molecular Biology, The University of Texas at Austin, Austin, Texas, United States of America, Center for Systems and Synthetic Biology, The University of Texas at Austin, Austin, Texas, United States of America.|Institute for Cellular and Molecular Biology, The University of Texas at Austin, Austin, Texas, United States of America, Center for Systems and Synthetic Biology, The University of Texas at Austin, Austin, Texas, United States of America.|Department of Organismic and Evolutionary Biology, Harvard University, Boston, Massachusetts, United States of America.|Institute for Cellular and Molecular Biology, The University of Texas at Austin, Austin, Texas, United States of America, Center for Systems and Synthetic Biology, The University of Texas at Austin, Austin, Texas, United States of America.|Department of Organismic and Evolutionary Biology, Harvard University, Boston, Massachusetts, United States of America.|Institute for Cellular and Molecular Biology, The University of Texas at Austin, Austin, Texas, United States of America, Center for Systems and Synthetic Biology, The University of Texas at Austin, Austin, Texas, United States of America.|Institute for Cellular and Molecular Biology, The University of Texas at Austin, Austin, Texas, United States of America, Center for Systems and Synthetic Biology, The University of Texas at Austin, Austin, Texas, United States of America.|Center for Computational Biology and Bioinformatics, The University of Texas at Austin, Austin, Texas, United States of America.|Institute for Cellular and Molecular Biology, The University of Texas at Austin, Austin, Texas, United States of America.|Department of Organismic and Evolutionary Biology, Harvard University, Boston, Massachusetts, United States of America, Faculty of Arts and Sciences Center for Systems Biology, Harvard University, Boston, Massachusetts, United States of America, Department of Biological Sciences, University of Idaho, Moscow, Idaho, United States of America, Institute for Bioinformatics and Evolutionary Studies, University of Idaho, Moscow, Idaho, United States of America.|Institute for Cellular and Molecular Biology, The University of Texas at Austin, Austin, Texas, United States of America, Center for Systems and Synthetic Biology, The University of Texas at Austin, Austin, Texas, United States of America, Department of Infectious Diseases, College of Veterinary Medicine, University of Georgia, Athens, Georgia, United States of America.|Institute for Cellular and Molecular Biology, The University of Texas at Austin, Austin, Texas, United States of America, Center for Systems and Synthetic Biology, The University of Texas at Austin, Austin, Texas, United States of America, Center for Computational Biology and Bioinformatics, The University of Texas at Austin, Austin, Texas, United States of America, Department of Molecular Biosciences, The University of Texas at Austin, Austin, Texas, United States of America.|Institute for Cellular and Molecular Biology, The University of Texas at Austin, Austin, Texas, United States of America, Center for Systems and Synthetic Biology, The University of Texas at Austin, Austin, Texas, United States of America, Center for Computational Biology and Bioinformatics, The University of Texas at Austin, Austin, Texas, United States of America, Department of Molecular Biosciences, The University of Texas at Austin, Austin, Texas, United States of America.|Institute for Cellular and Molecular Biology, The University of Texas at Austin, Austin, Texas, United States of America, Center for Systems and Synthetic Biology, The University of Texas at Austin, Austin, Texas, United States of America, Center for Computational Biology and Bioinformatics, The University of Texas at Austin, Austin, Texas, United States of America, Department of Integrative Biology, The University of Texas at Austin, Austin, Texas, United States of America.', 'United States|United States|United States|United States|United States|United States|United States|Un', 11, 'Algorithms|Escherichia coli|Gene Expression Profiling|Gene Expression Regulation, Bacterial|Glucose|Systems Biology', 'Journal Article', '10.1371/journal.pcbi.1004400', '26275208', 'How do bacteria regulate their cellular physiology in response to starvation? Here, we present a detailed characterization of Escherichia coli growth and starvation over a time-course lasting two weeks. We have measured multiple cellular components, including RNA and proteins at deep genomic coverage, as well as lipid modifications and flux through central metabolism. Our study focuses on the physiological response of E. coli in stationary phase as a result of being starved for glucose, not on the genetic adaptation of E. coli to utilize alternative nutrients. In our analysis, we have taken advantage of the temporal correlations within and among RNA and protein abundances to identify systematic trends in gene regulation. Specifically, we have developed a general computational strategy for classifying expression-profile time courses into distinct categories in an unbiased manner. We have also developed, from dynamic models of gene expression, a framework to characterize protein degradation patterns based on the observed temporal relationships between mRNA and protein abundances. By comparing and contrasting our transcriptomic and proteomic data, we have identified several broad physiological trends in the E. coli starvation response. Strikingly, mRNAs are widely down-regulated in response to glucose starvation, presumably as a strategy for reducing new protein synthesis. By contrast, protein abundances display more varied responses. The abundances of many proteins involved in energy-intensive processes mirror the corresponding mRNA profiles while proteins involved in nutrient metabolism remain abundant even though their corresponding mRNAs are down-regulated.');
INSERT INTO `papers` (`id`, `ano`, `journal`, `titulo`, `autores`, `afiliacao`, `pais`, `citacoes`, `palavra_chave`, `categorias`, `doi`, `pubmed`, `abstract`) VALUES
(87295, 2015, 'plos', 'Curation of the Mammalian Palmitoylome Indicates a Pivotal Role for Palmitoylation in Diseases and Disorders of the Nervous System and Cancers', 'Sanders, Shaun S|Martin, Dale D O|Butland, Stefanie L|Lavallée-Adam, Mathieu|Calzolari, Diego|Kay, Chris|Yates, John R|Hayden, Michael R', 'Centre for Molecular Medicine and Therapeutics, Department of Medical Genetics, Child & Family Research Institute, University of British Columbia, Vancouver, British Columbia, Canada.|Centre for Molecular Medicine and Therapeutics, Department of Medical Genetics, Child & Family Research Institute, University of British Columbia, Vancouver, British Columbia, Canada.|Centre for Molecular Medicine and Therapeutics, Department of Medical Genetics, Child & Family Research Institute, University of British Columbia, Vancouver, British Columbia, Canada.|Department of Chemical Physiology, The Scripps Research Institute, La Jolla, California, United States of America.|Department of Chemical Physiology, The Scripps Research Institute, La Jolla, California, United States of America.|Centre for Molecular Medicine and Therapeutics, Department of Medical Genetics, Child & Family Research Institute, University of British Columbia, Vancouver, British Columbia, Canada.|Department of Chemical Physiology, The Scripps Research Institute, La Jolla, California, United States of America.|Centre for Molecular Medicine and Therapeutics, Department of Medical Genetics, Child & Family Research Institute, University of British Columbia, Vancouver, British Columbia, Canada.', 'Canada|Canada|Canada|United States|United States|Canada|United States|Canada', 0, 'Cysteine|Databases, Protein|Humans|Lipoylation|Neoplasms|Nervous System Diseases|Palmitates|Proteome|Proteomics', 'Journal Article', '10.1371/journal.pcbi.1004405', '26275289', 'Palmitoylation involves the reversible posttranslational addition of palmitate to cysteines and promotes membrane binding and subcellular localization. Recent advancements in the detection and identification of palmitoylated proteins have led to multiple palmitoylation proteomics studies but these datasets are contained within large supplemental tables, making downstream analysis and data mining time-consuming and difficult. Consequently, we curated the data from 15 palmitoylation proteomics studies into one compendium containing 1,838 genes encoding palmitoylated proteins, representing approximately 10% of the genome. Enrichment analysis revealed highly significant enrichments for Gene Ontology biological processes, pathway maps, and process networks related to the nervous system. Strikingly, 41% of synaptic genes encode a palmitoylated protein in the compendium. The top disease associations included cancers and diseases and disorders of the nervous system, with Schizophrenia, HD, and pancreatic ductal carcinoma among the top five, suggesting that aberrant palmitoylation may play a pivotal role in the balance of cell death and survival. This compendium provides a much-needed resource for cell biologists and the palmitoylation field, providing new perspectives for cancer and neurodegeneration. '),
(87296, 2015, 'plos', 'Innate Immunity and the Inter-exposure Interval Determine the Dynamics of Secondary Influenza Virus Infection and Explain Observed Viral Hierarchies', 'Cao, Pengxing|Yan, Ada W C|Heffernan, Jane M|Petrie, Stephen|Moss, Robert G|Carolan, Louise A|Guarnaccia, Teagan A|Kelso, Anne|Barr, Ian G|McVernon, Jodie|Laurie, Karen L|McCaw, James M', 'Centre for Epidemiology and Biostatistics, Melbourne School of Population and Global Health, The University of Melbourne, Melbourne, Australia.|Centre for Epidemiology and Biostatistics, Melbourne School of Population and Global Health, The University of Melbourne, Melbourne, Australia.|Centre for Epidemiology and Biostatistics, Melbourne School of Population and Global Health, The University of Melbourne, Melbourne, Australia, Modelling Infection and Immunity Lab, Centre for Disease Modelling, York Institute for Health Research, York University, Toronto, Ontario, Canada, Mathematics and Statistics, York University, Toronto, Ontario, Canada.|Centre for Epidemiology and Biostatistics, Melbourne School of Population and Global Health, The University of Melbourne, Melbourne, Australia.|Centre for Epidemiology and Biostatistics, Melbourne School of Population and Global Health, The University of Melbourne, Melbourne, Australia.|WHO Collaborating Centre for Reference and Research on Influenza at the Peter Doherty Institute for Infection and Immunity, Parkville, Victoria, Australia.|WHO Collaborating Centre for Reference and Research on Influenza at the Peter Doherty Institute for Infection and Immunity, Parkville, Victoria, Australia.|WHO Collaborating Centre for Reference and Research on Influenza at the Peter Doherty Institute for Infection and Immunity, Parkville, Victoria, Australia.|WHO Collaborating Centre for Reference and Research on Influenza at the Peter Doherty Institute for Infection and Immunity, Parkville, Victoria, Australia.|Centre for Epidemiology and Biostatistics, Melbourne School of Population and Global Health, The University of Melbourne, Melbourne, Australia, Modelling and Simulation, Infection and Immunity Theme, Murdoch Childrens Research Institute, The Royal Childrens Hospital, Parkville, Victoria, Australia.|WHO Collaborating Centre for Reference and Research on Influenza at the Peter Doherty Institute for Infection and Immunity, Parkville, Victoria, Australia.|Centre for Epidemiology and Biostatistics, Melbourne School of Population and Global Health, The University of Melbourne, Melbourne, Australia, Modelling and Simulation, Infection and Immunity Theme, Murdoch Childrens Research Institute, The Royal Childrens Hospital, Parkville, Victoria, Australia, School of Mathematics and Statistics, The University of Melbourne, Melbourne, Australia.', 'Australia|Australia|Australia|Australia|Australia|Australia|Australia|Australia|Australia|Australia|', 32, 'Animals|Computational Biology|Disease Models, Animal|Ferrets|Host-Pathogen Interactions|Humans|Immunity, Innate|Influenza, Human|Models, Immunological|Orthomyxoviridae|Orthomyxoviridae Infections|Viral Load', 'Journal Article', '10.1371/journal.pcbi.1004334', '26284917', 'Influenza is an infectious disease that primarily attacks the respiratory system. Innate immunity provides both a very early defense to influenza virus invasion and an effective control of viral growth. Previous modelling studies of virus-innate immune response interactions have focused on infection with a single virus and, while improving our understanding of viral and immune dynamics, have been unable to effectively evaluate the relative feasibility of different hypothesised mechanisms of antiviral immunity. In recent experiments, we have applied consecutive exposures to different virus strains in a ferret model, and demonstrated that viruses differed in their ability to induce a state of temporary immunity or viral interference capable of modifying the infection kinetics of the subsequent exposure. These results imply that virus-induced early immune responses may be responsible for the observed viral hierarchy. Here we introduce and analyse a family of within-host models of re-infection viral kinetics which allow for different viruses to stimulate the innate immune response to different degrees. The proposed models differ in their hypothesised mechanisms of action of the non-specific innate immune response. We compare these alternative models in terms of their abilities to reproduce the re-exposure data. Our results show that 1) a model with viral control mediated solely by a virus-resistant state, as commonly considered in the literature, is not able to reproduce the observed viral hierarchy, 2) the synchronised and desynchronised behaviour of consecutive virus infections is highly dependent upon the interval between primary virus and challenge virus exposures and is consistent with virus-dependent stimulation of the innate immune response. Our study provides the first mechanistic explanation for the recently observed influenza viral hierarchies and demonstrates the importance of understanding the host response to multi-strain viral infections. Re-exposure experiments provide a new paradigm in which to study the immune response to influenza and its role in viral control. '),
(87297, 2015, 'plos', 'A Stochastic Multiscale Model That Explains the Segregation of Axonal Microtubules and Neurofilaments in Neurological Diseases', 'Xue, Chuan|Shtylla, Blerta|Brown, Anthony', 'Department of Mathematics, Ohio State University, Columbus, Ohio, United States of America.|Department of Mathematics, Pomona College, Claremont, California, United States of America.|Department of Neuroscience, Ohio State University, Columbus, Ohio, United States of America.', 'United States|United States|United States', 0, 'Algorithms|Animals|Axons|Computational Biology|Humans|Intermediate Filaments|Mice|Microtubules|Models, Neurological|Nervous System Diseases', 'Journal Article', '10.1371/journal.pcbi.1004406', '26285012', 'The organization of the axonal cytoskeleton is a key determinant of the normal function of an axon, which is a long thin projection of a neuron. Under normal conditions two axonal cytoskeletal polymers, microtubules and neurofilaments, align longitudinally in axons and are interspersed in axonal cross-sections. However, in many neurotoxic and neurodegenerative disorders, microtubules and neurofilaments segregate apart from each other, with microtubules and membranous organelles clustered centrally and neurofilaments displaced to the periphery. This striking segregation precedes the abnormal and excessive neurofilament accumulation in these diseases, which in turn leads to focal axonal swellings. While neurofilament accumulation suggests an impairment of neurofilament transport along axons, the underlying mechanism of their segregation from microtubules remains poorly understood for over 30 years. To address this question, we developed a stochastic multiscale model for the cross-sectional distribution of microtubules and neurofilaments in axons. The model describes microtubules, neurofilaments and organelles as interacting particles in a 2D cross-section, and is built upon molecular processes that occur on a time scale of seconds or shorter. It incorporates the longitudinal transport of neurofilaments and organelles through this domain by allowing stochastic arrival and departure of these cargoes, and integrates the dynamic interactions of these cargoes with microtubules mediated by molecular motors. Simulations of the model demonstrate that organelles can pull nearby microtubules together, and in the absence of neurofilament transport, this mechanism gradually segregates microtubules from neurofilaments on a time scale of hours, similar to that observed in toxic neuropathies. This suggests that the microtubule-neurofilament segregation can be a consequence of the selective impairment of neurofilament transport. The model generates the experimentally testable prediction that the rate and extent of segregation will be dependent on the sizes of the moving organelles as well as the density of their traffic. '),
(87298, 2015, 'plos', 'Nonconsensus Protein Binding to Repetitive DNA Sequence Elements Significantly Affects Eukaryotic Genomes', 'Afek, Ariel|Cohen, Hila|Barber-Zucker, Shiran|Gordân, Raluca|Lukatsky, David B', 'Department of Chemistry, Ben-Gurion University of the Negev, Beer-Sheva, Israel.|Department of Chemistry, Ben-Gurion University of the Negev, Beer-Sheva, Israel.|Department of Chemistry, Ben-Gurion University of the Negev, Beer-Sheva, Israel.|Center for Genomic and Computational Biology, Department of Biostatistics and Bioinformatics, Duke University, Durham, North Carolina, United States of America.|Department of Chemistry, Ben-Gurion University of the Negev, Beer-Sheva, Israel.', 'Israel|Israel|Israel|United States|Israel', 0, 'Animals|Base Sequence|Binding Sites|Caenorhabditis elegans|Computational Biology|DNA|DNA-Binding Proteins|Drosophila melanogaster|Genome|Models, Genetic|Molecular Sequence Data|Protein Binding|Repetitive Sequences, Nucleic Acid|Thermodynamics|Transcription Factors', 'Journal Article', '10.1371/journal.pcbi.1004429', '26285121', 'Recent genome-wide experiments in different eukaryotic genomes provide an unprecedented view of transcription factor (TF) binding locations and of nucleosome occupancy. These experiments revealed that a large fraction of TF binding events occur in regions where only a small number of specific TF binding sites (TFBSs) have been detected. Furthermore, in vitro protein-DNA binding measurements performed for hundreds of TFs indicate that TFs are bound with wide range of affinities to different DNA sequences that lack known consensus motifs. These observations have thus challenged the classical picture of specific protein-DNA binding and strongly suggest the existence of additional recognition mechanisms that affect protein-DNA binding preferences. We have previously demonstrated that repetitive DNA sequence elements characterized by certain symmetries statistically affect protein-DNA binding preferences. We call this binding mechanism nonconsensus protein-DNA binding in order to emphasize the point that specific consensus TFBSs do not contribute to this effect. In this paper, using the simple statistical mechanics model developed previously, we calculate the nonconsensus protein-DNA binding free energy for the entire C. elegans and D. melanogaster genomes. Using the available chromatin immunoprecipitation followed by sequencing (ChIP-seq) results on TF-DNA binding preferences for ~100 TFs, we show that DNA sequences characterized by low predicted free energy of nonconsensus binding have statistically higher experimental TF occupancy and lower nucleosome occupancy than sequences characterized by high free energy of nonconsensus binding. This is in agreement with our previous analysis performed for the yeast genome. We suggest therefore that nonconsensus protein-DNA binding assists the formation of nucleosome-free regions, as TFs outcompete nucleosomes at genomic locations with enhanced nonconsensus binding. In addition, here we perform a new, large-scale analysis using in vitro TF-DNA preferences obtained from the universal protein binding microarrays (PBM) for ~90 eukaryotic TFs belonging to 22 different DNA-binding domain types. As a result of this new analysis, we conclude that nonconsensus protein-DNA binding is a widespread phenomenon that significantly affects protein-DNA binding preferences and need not require the presence of consensus (specific) TFBSs in order to achieve genome-wide TF-DNA binding specificity. '),
(87299, 2015, 'plos', 'The Interplay between Wnt Mediated Expansion and Negative Regulation of Growth Promotes Robust Intestinal Crypt Structure and Homeostasis', 'Du, Huijing|Nie, Qing|Holmes, William R', 'Center for Complex Biological Systems and Department of Mathematics, University of California Irvine, Irvine, California, United States of America.|Center for Complex Biological Systems and Department of Mathematics, University of California Irvine, Irvine, California, United States of America.|Center for Complex Biological Systems and Department of Mathematics, University of California Irvine, Irvine, California, United States of America, Department of Physics and Astronomy, Vanderbilt University, Nashville, Tennessee, United States of America.', 'United States|United States|United States', 15, 'Animals|Cell Movement|Computational Biology|Homeostasis|Intestinal Mucosa|Mice|Models, Biological|Stem Cells|Wnt Proteins|Wnt Signaling Pathway', 'Journal Article', '10.1371/journal.pcbi.1004285', '26288152', 'The epithelium of the small intestinal crypt, which has a vital role in protecting the underlying tissue from the harsh intestinal environment, is completely renewed every 4-5 days by a small pool of stem cells at the base of each crypt. How is this renewal controlled and homeostasis maintained, particularly given the rapid nature of this process? Here, based on the recent observations from in vitro mini gut studies, we use a hybrid stochastic model of the crypt to investigate how exogenous niche signaling (from Wnt and BMP) combines with auto-regulation to promote homeostasis. This model builds on the sub-cellular element method to account for the three-dimensional structure of the crypt, external regulation by Wnt and BMP, internal regulation by Notch signaling, as well as regulation by internally generated diffusible signals. Results show that Paneth cell derived Wnt signals, which have been observed experimentally to sustain crypts in cultured organs, have a dramatically different influence on niche dynamics than does mesenchyme derived Wnt. While this signaling can indeed act as a redundant backup to the exogenous gradient, it introduces a positive feedback that destabilizes the niche and causes its uncontrolled expansion. We find that in this setting, BMP has a critical role in constraining this expansion, consistent with observations that its removal leads to crypt fission. Further results also point to a new hypothesis for the role of Ephrin mediated motility of Paneth cells, specifically that it is required to constrain niche expansion and maintain the crypts spatial structure. Combined, these provide an alternative view of crypt homeostasis where the niche is in a constant state of expansion and the spatial structure of the crypt arises as a balance between this expansion and the action of various sources of negative regulation that hold it in check. '),
(87300, 2015, 'plos', 'Correction: The Opponent Channel Population Code of Sound Location Is an Efficient Representation of Natural Binaural Sounds', 'PLOS Computational Biology Staff', 'Center for Complex Biological Systems and Department of Mathematics, University of California Irvine, Irvine, California, United States of America, Department of Physics and Astronomy, Vanderbilt University, Nashville, Tennessee, United States of America.', 'United States', 0, '-', 'Published Erratum', '10.1371/journal.pcbi.1004377', '26288200', '-'),
(87301, 2015, 'plos', 'Experimentally Verified Parameter Sets for Modelling Heterogeneous Neocortical Pyramidal-Cell Populations', 'Harrison, Paul M|Badel, Laurent|Wall, Mark J|Richardson, Magnus J E', 'MOAC Doctoral Training Centre, University of Warwick, Coventry, United Kingdom, School of Life Sciences, University of Warwick, Coventry, United Kingdom, Warwick Systems Biology Centre, University of Warwick, Coventry, United Kingdom.|Laboratory for Circuit Mechanisms of Sensory Perception, RIKEN Brain Science Institute, Wako, Saitama, Japan.|School of Life Sciences, University of Warwick, Coventry, United Kingdom.|Warwick Systems Biology Centre, University of Warwick, Coventry, United Kingdom.', 'United Kingdom|Japan|United Kingdom|United Kingdom', 0, 'Algorithms|Animals|Computational Biology|Male|Models, Neurological|Neocortex|Pyramidal Cells|Rats|Rats, Wistar', 'Journal Article', '10.1371/journal.pcbi.1004165', '26291316', 'Models of neocortical networks are increasingly including the diversity of excitatory and inhibitory neuronal classes. Significant variability in cellular properties are also seen within a nominal neuronal class and this heterogeneity can be expected to influence the population response and information processing in networks. Recent studies have examined the population and network effects of variability in a particular neuronal parameter with some plausibly chosen distribution. However, the empirical variability and covariance seen across multiple parameters are rarely included, partly due to the lack of data on parameter correlations in forms convenient for model construction. To addess this we quantify the heterogeneity within and between the neocortical pyramidal-cell classes in layers 2/3, 4, and the slender-tufted and thick-tufted pyramidal cells of layer 5 using a combination of intracellular recordings, single-neuron modelling and statistical analyses. From the response to both square-pulse and naturalistic fluctuating stimuli, we examined the class-dependent variance and covariance of electrophysiological parameters and identify the role of the h current in generating parameter correlations. A byproduct of the dynamic I-V method we employed is the straightforward extraction of reduced neuron models from experiment. Empirically these models took the refractory exponential integrate-and-fire form and provide an accurate fit to the perisomatic voltage responses of the diverse pyramidal-cell populations when the class-dependent statistics of the model parameters were respected. By quantifying the parameter statistics we obtained an algorithm which generates populations of model neurons, for each of the four pyramidal-cell classes, that adhere to experimentally observed marginal distributions and parameter correlations. As well as providing this tool, which we hope will be of use for exploring the effects of heterogeneity in neocortical networks, we also provide the code for the dynamic I-V method and make the full electrophysiological data set available.'),
(87302, 2015, 'plos', 'Impact of School Cycles and Environmental Forcing on the Timing of Pandemic Influenza Activity in Mexican States, May-December 2009', 'Tamerius, James|Viboud, Cécile|Shaman, Jeffrey|Chowell, Gerardo', 'Department of Geographical and Sustainability Sciences, University of Iowa, Iowa City, Iowa, United States of America.|Fogarty International Center, National Institutes of Health, Bethesda, Maryland, United States of America.|Environmental Health Sciences, Columbia University, New York, New York, United States of America.|School of Public Health, Georgia State University, Atlanta, Georgia, United States of America.', 'United States|United States|United States|Georgia', 14, 'Humans|Influenza, Human|Mexico|Pandemics|Schools|Seasons', 'Journal Article', '10.1371/journal.pcbi.1004337', '26291446', 'While a relationship between environmental forcing and influenza transmission has been established in inter-pandemic seasons, the drivers of pandemic influenza remain debated. In particular, school effects may predominate in pandemic seasons marked by an atypical concentration of cases among children. For the 2009 A/H1N1 pandemic, Mexico is a particularly interesting case study due to its broad geographic extent encompassing temperate and tropical regions, well-documented regional variation in the occurrence of pandemic outbreaks, and coincidence of several school breaks during the pandemic period. Here we fit a series of transmission models to daily laboratory-confirmed influenza data in 32 Mexican states using MCMC approaches, considering a meta-population framework or the absence of spatial coupling between states. We use these models to explore the effect of environmental, school-related and travel factors on the generation of spatially-heterogeneous pandemic waves. We find that the spatial structure of the pandemic is best understood by the interplay between regional differences in specific humidity (explaining the occurrence of pandemic activity towards the end of the school term in late May-June 2009 in more humid southeastern states), school vacations (preventing influenza transmission during July-August in all states), and regional differences in residual susceptibility (resulting in large outbreaks in early fall 2009 in central and northern Mexico that had yet to experience fully-developed outbreaks). Our results are in line with the concept that very high levels of specific humidity, as present during summer in southeastern Mexico, favor influenza transmission, and that school cycles are a strong determinant of pandemic wave timing. '),
(87303, 2015, 'plos', 'Contribution of Sequence Motif, Chromatin State, and DNA Structure Features to Predictive Models of Transcription Factor Binding in Yeast', 'Tsai, Zing Tsung-Yeh|Shiu, Shin-Han|Tsai, Huai-Kuang', 'Institute of Information Science, Academia Sinica, Taipei, Taiwan, Department of Plant Biology, Michigan State University, East Lansing, Michigan, United States of America.|Department of Plant Biology, Michigan State University, East Lansing, Michigan, United States of America.|Institute of Information Science, Academia Sinica, Taipei, Taiwan.', 'United States|United States|-', 15, 'Chromatin|Computational Biology|DNA, Fungal|Fungal Proteins|Nucleotide Motifs|Protein Binding|Saccharomyces cerevisiae|Transcription Factors', 'Journal Article', '10.1371/journal.pcbi.1004418', '26291518', 'Transcription factor (TF) binding is determined by the presence of specific sequence motifs (SM) and chromatin accessibility, where the latter is influenced by both chromatin state (CS) and DNA structure (DS) properties. Although SM, CS, and DS have been used to predict TF binding sites, a predictive model that jointly considers CS and DS has not been developed to predict either TF-specific binding or general binding properties of TFs. Using budding yeast as model, we found that machine learning classifiers trained with either CS or DS features alone perform better in predicting TF-specific binding compared to SM-based classifiers. In addition, simultaneously considering CS and DS further improves the accuracy of the TF binding predictions, indicating the highly complementary nature of these two properties. The contributions of SM, CS, and DS features to binding site predictions differ greatly between TFs, allowing TF-specific predictions and potentially reflecting different TF binding mechanisms. In addition, a TF-agnostic predictive model based on three DNA intrinsic properties (in silico predicted nucleosome occupancy, major groove geometry, and dinucleotide free energy) that can be calculated from genomic sequences alone has performance that rivals the model incorporating experiment-derived data. This intrinsic property model allows prediction of binding regions not only across TFs, but also across DNA-binding domain families with distinct structural folds. Furthermore, these predicted binding regions can help identify TF binding sites that have a significant impact on target gene expression. Because the intrinsic property model allows prediction of binding regions across DNA-binding domain families, it is TF agnostic and likely describes general binding potential of TFs. Thus, our findings suggest that it is feasible to establish a TF agnostic model for identifying functional regulatory regions in potentially any sequenced genome. '),
(87304, 2015, 'plos', 'A Three-Threshold Learning Rule Approaches the Maximal Capacity of Recurrent Neural Networks', 'Alemi, Alireza|Baldassi, Carlo|Brunel, Nicolas|Zecchina, Riccardo', 'Human Genetics Foundation (HuGeF), Turin, Italy, DISAT, Politecnico di Torino, Turin, Italy.|Human Genetics Foundation (HuGeF), Turin, Italy, DISAT, Politecnico di Torino, Turin, Italy.|Departments of Statistics and Neurobiology, University of Chicago, Chicago, Illinois, United States of America.|Human Genetics Foundation (HuGeF), Turin, Italy, DISAT, Politecnico di Torino, Turin, Italy.', 'Italy|Italy|United States|Italy', 11, 'Algorithms|Computational Biology|Computer Simulation|Memory|Models, Neurological|Nerve Net|Neural Networks (Computer)|Neurons', 'Journal Article', '10.1371/journal.pcbi.1004439', '26291608', 'Understanding the theoretical foundations of how memories are encoded and retrieved in neural populations is a central challenge in neuroscience. A popular theoretical scenario for modeling memory function is the attractor neural network scenario, whose prototype is the Hopfield model. The model simplicity and the locality of the synaptic update rules come at the cost of a poor storage capacity, compared with the capacity achieved with perceptron learning algorithms. Here, by transforming the perceptron learning rule, we present an online learning rule for a recurrent neural network that achieves near-maximal storage capacity without an explicit supervisory error signal, relying only upon locally accessible information. The fully-connected network consists of excitatory binary neurons with plastic recurrent connections and non-plastic inhibitory feedback stabilizing the network dynamics, the memory patterns to be memorized are presented online as strong afferent currents, producing a bimodal distribution for the neuron synaptic inputs. Synapses corresponding to active inputs are modified as a function of the value of the local fields with respect to three thresholds. Above the highest threshold, and below the lowest threshold, no plasticity occurs. In between these two thresholds, potentiation/depression occurs when the local field is above/below an intermediate threshold. We simulated and analyzed a network of binary neurons implementing this rule and measured its storage capacity for different sizes of the basins of attraction. The storage capacity obtained through numerical simulations is shown to be close to the value predicted by analytical calculations. We also measured the dependence of capacity on the strength of external inputs. Finally, we quantified the statistics of the resulting synaptic connectivity matrix, and found that both the fraction of zero weight synapses and the degree of symmetry of the weight matrix increase with the number of stored patterns. '),
(87305, 2015, 'plos', 'Self-Organization of Microcircuits in Networks of Spiking Neurons with Plastic Synapses', 'Ocker, Gabriel Koch|Litwin-Kumar, Ashok|Doiron, Brent', 'Department of Neuroscience, University of Pittsburgh, Pittsburgh, Pennsylvania, United States of America, Center for the Neural Basis of Cognition, University of Pittsburgh and Carnegie Melon University, Pittsburgh, Pennsylvania, United States of America.|Center for the Neural Basis of Cognition, University of Pittsburgh and Carnegie Melon University, Pittsburgh, Pennsylvania, United States of America, Department of Mathematics, University of Pittsburgh, Pittsburgh, Pennsylvania, United States of America, Center for Theoretical Neuroscience, Columbia University, New York, New York, United States of America.|Center for the Neural Basis of Cognition, University of Pittsburgh and Carnegie Melon University, Pittsburgh, Pennsylvania, United States of America, Department of Mathematics, University of Pittsburgh, Pittsburgh, Pennsylvania, United States of America.', 'United States|United States|United States', 0, 'Action Potentials|Computational Biology|Models, Neurological|Nerve Net|Neuronal Plasticity|Neurons|Synapses', 'Journal Article', '10.1371/journal.pcbi.1004458', '26291697', 'The synaptic connectivity of cortical networks features an overrepresentation of certain wiring motifs compared to simple random-network models. This structure is shaped, in part, by synaptic plasticity that promotes or suppresses connections between neurons depending on their joint spiking activity. Frequently, theoretical studies focus on how feedforward inputs drive plasticity to create this network structure. We study the complementary scenario of self-organized structure in a recurrent network, with spike timing-dependent plasticity driven by spontaneous dynamics. We develop a self-consistent theory for the evolution of network structure by combining fast spiking covariance with a slow evolution of synaptic weights. Through a finite-size expansion of network dynamics we obtain a low-dimensional set of nonlinear differential equations for the evolution of two-synapse connectivity motifs. With this theory in hand, we explore how the form of the plasticity rule drives the evolution of microcircuits in cortical networks. When potentiation and depression are in approximate balance, synaptic dynamics depend on weighted divergent, convergent, and chain motifs. For additive, Hebbian STDP these motif interactions create instabilities in synaptic dynamics that either promote or suppress the initial network structure. Our work provides a consistent theoretical framework for studying how spiking activity in recurrent networks interacts with synaptic plasticity to determine network structure. '),
(87306, 2015, 'plos', 'Changes in Postural Syntax Characterize Sensory Modulation and Natural Variation of C elegans Locomotion', 'Schwarz, Roland F|Branicky, Robyn|Grundy, Laura J|Schafer, William R|Brown, André E X', 'European Bioinformatics Institute, Hinxton, United Kingdom.|MRC Laboratory of Molecular Biology, Cambridge, United Kingdom.|MRC Laboratory of Molecular Biology, Cambridge, United Kingdom.|MRC Laboratory of Molecular Biology, Cambridge, United Kingdom.|MRC Clinical Sciences Centre, Imperial College London, London, United Kingdom.', 'United Kingdom|United Kingdom|United Kingdom|United Kingdom|United Kingdom', 0, 'Animals|Behavior, Animal|Caenorhabditis elegans|Cluster Analysis|Computational Biology|Locomotion|Optogenetics', 'Journal Article', '10.1371/journal.pcbi.1004322', '26295152', 'Locomotion is driven by shape changes coordinated by the nervous system through time, thus, enumerating an animals complete repertoire of shape transitions would provide a basis for a comprehensive understanding of locomotor behaviour. Here we introduce a discrete representation of behaviour in the nematode C. elegans. At each point in time, the worms posture is approximated by its closest matching template from a set of 90 postures and locomotion is represented as sequences of postures. The frequency distribution of postural sequences is heavy-tailed with a core of frequent behaviours and a much larger set of rarely used behaviours. Responses to optogenetic and environmental stimuli can be quantified as changes in postural syntax: worms show different preferences for different sequences of postures drawn from the same set of templates. A discrete representation of behaviour will enable the use of methods developed for other kinds of discrete data in bioinformatics and language processing to be harnessed for the study of behaviour. '),
(87307, 2015, 'plos', 'Tipping the Scale from Disorder to Alpha-helix: Folding of Amphiphilic Peptides in the Presence of Macroscopic and Molecular Interfaces', 'Dalgicdir, Cahit|Globisch, Christoph|Peter, Christine|Sayar, Mehmet', 'College of Engineering, Koç University, Istanbul, Turkey.|Theoretical Chemistry, University of Konstanz, Konstanz, Germany.|Theoretical Chemistry, University of Konstanz, Konstanz, Germany.|College of Engineering, Koç University, Istanbul, Turkey.', 'Turkey|Germany|Germany|Turkey', 21, 'Algorithms|Computational Biology|Computer Simulation|Hydrophobic and Hydrophilic Interactions|Peptides|Protein Folding|Protein Structure, Secondary', 'Journal Article', '10.1371/journal.pcbi.1004328', '26295346', 'Secondary amphiphilicity is inherent to the secondary structural elements of proteins. By forming energetically favorable contacts with each other these amphiphilic building blocks give rise to the formation of a tertiary structure. Small proteins and peptides, on the other hand, are usually too short to form multiple structural elements and cannot stabilize them internally. Therefore, these molecules are often found to be structurally ambiguous up to the point of a large degree of intrinsic disorder in solution. Consequently, their conformational preference is particularly susceptible to environmental conditions such as pH, salts, or presence of interfaces. In this study we use molecular dynamics simulations to analyze the conformational behavior of two synthetic peptides, LKKLLKLLKKLLKL (LK) and EAALAEALAEALAE (EALA), with built-in secondary amphiphilicity upon forming an alpha-helix. We use these model peptides to systematically study their aggregation and the influence of macroscopic and molecular interfaces on their conformational preferences. We show that the peptides are neither random coils in bulk water nor fully formed alpha helices, but adopt multiple conformations and secondary structure elements with short lifetimes. These provide a basis for conformation-selection and population-shift upon environmental changes. Differences in these peptides response to macroscopic and molecular interfaces (presented by an aggregation partner) can be linked to their inherent alpha-helical tendencies in bulk water. We find that the peptides aggregation behavior is also strongly affected by presence or absence of an interface, and rather subtly depends on their surface charge and hydrophobicity. '),
(87308, 2015, 'plos', 'Correction: Time-Course Gene Set Analysis for Longitudinal Gene Expression Data', 'PLOS Computational Biology Staff', 'College of Engineering, Koç University, Istanbul, Turkey.', 'Turkey', 0, '-', 'Published Erratum', '10.1371/journal.pcbi.1004446', '26295484', '-'),
(87309, 2015, 'plos', 'Formation and Dynamics of Waves in a Cortical Model of Cholinergic Modulation', 'Roach, James P|Ben-Jacob, Eshel|Sander, Leonard M|Zochowski, Michal R', 'Neuroscience Graduate Program, University of Michigan, Ann Arbor, Michigan, United States of America.|School of Physics and Astronomy, Tel-Aviv University, Tel Aviv, Israel, Center for Theoretical Biological Physics, and Department of Biochemistry and Cell Biology, Rice University, Houston, Texas, United States of America.|Department of Physics & Center for Studies of Complex Systems, University of Michigan, Ann Arbor, Michigan, United States of America.|Neuroscience Graduate Program, University of Michigan, Ann Arbor, Michigan, United States of America, Department of Physics & Center for Studies of Complex Systems, University of Michigan, Ann Arbor, Michigan, United States of America, Biophysics Program, University of Michigan, Ann Arbor, Michigan, United States of America.', 'United States|Israel|United States|United States', 5, 'Acetylcholine|Action Potentials|Cerebral Cortex|Cholinergic Agents|Computational Biology|Computer Simulation|Humans|Models, Neurological|Neurons|Potassium|Sleep', 'Journal Article', '10.1371/journal.pcbi.1004449', '26295587', 'Acetylcholine (ACh) is a regulator of neural excitability and one of the neurochemical substrates of sleep. Amongst the cellular effects induced by cholinergic modulation are a reduction in spike-frequency adaptation (SFA) and a shift in the phase response curve (PRC). We demonstrate in a biophysical model how changes in neural excitability and network structure interact to create three distinct functional regimes: localized asynchronous, traveling asynchronous, and traveling synchronous. Our results qualitatively match those observed experimentally. Cortical activity during slow wave sleep (SWS) differs from that during REM sleep or waking states. During SWS there are traveling patterns of activity in the cortex, in other states stationary patterns occur. Our model is a network composed of Hodgkin-Huxley type neurons with a M-current regulated by ACh. Regulation of ACh level can account for dynamical changes between functional regimes. Reduction of the magnitude of this current recreates the reduction in SFA the shift from a type 2 to a type 1 PRC observed in the presence of ACh. When SFA is minimal (in waking or REM sleep state, high ACh) patterns of activity are localized and easily pinned by network inhomogeneities. When SFA is present (decreasing ACh), traveling waves of activity naturally arise. A further decrease in ACh leads to a high degree of synchrony within traveling waves. We also show that the level of ACh determines how sensitive network activity is to synaptic heterogeneity. These regimes may have a profound functional significance as stationary patterns may play a role in the proper encoding of external input as memory and traveling waves could lead to synaptic regularization, giving unique insights into the role and significance of ACh in determining patterns of cortical activity and functional differences arising from the patterns. '),
(87310, 2015, 'plos', 'Structure Learning in Bayesian Sensorimotor Integration', 'Genewein, Tim|Hez, Eduard|Razzaghpanah, Zeynab|Braun, Daniel A', 'Max Planck Institute for Biological Cybernetics, Tübingen, Germany, Max Planck Institute for Intelligent Systems, Tübingen, Germany, Graduate Training Centre of Neuroscience, Tübingen, Germany.|Max Planck Institute for Biological Cybernetics, Tübingen, Germany, Max Planck Institute for Intelligent Systems, Tübingen, Germany, University of Tübingen, Tübingen, Germany.|Max Planck Institute for Biological Cybernetics, Tübingen, Germany, Max Planck Institute for Intelligent Systems, Tübingen, Germany, University of Tübingen, Tübingen, Germany.|Max Planck Institute for Biological Cybernetics, Tübingen, Germany, Max Planck Institute for Intelligent Systems, Tübingen, Germany.', 'Germany|Germany|Germany|Germany', 0, 'Bayes Theorem|Computational Biology|Feedback, Sensory|Female|Hand|Humans|Learning|Male|Psychomotor Performance', 'Journal Article', '10.1371/journal.pcbi.1004369', '26305797', 'Previous studies have shown that sensorimotor processing can often be described by Bayesian learning, in particular the integration of prior and feedback information depending on its degree of reliability. Here we test the hypothesis that the integration process itself can be tuned to the statistical structure of the environment. We exposed human participants to a reaching task in a three-dimensional virtual reality environment where we could displace the visual feedback of their hand position in a two dimensional plane. When introducing statistical structure between the two dimensions of the displacement, we found that over the course of several days participants adapted their feedback integration process in order to exploit this structure for performance improvement. In control experiments we found that this adaptation process critically depended on performance feedback and could not be induced by verbal instructions. Our results suggest that structural learning is an important meta-learning component of Bayesian sensorimotor integration. '),
(87311, 2015, 'plos', 'Asymmetric Evolutionary Games', 'McAvoy, Alex|Hauert, Christoph', 'Department of Mathematics, University of British Columbia, Vancouver, British Columbia, Canada.|Department of Mathematics, University of British Columbia, Vancouver, British Columbia, Canada.', 'Canada|Canada', 20, 'Animals|Biological Evolution|Computational Biology|Cultural Evolution|Ecology|Game Theory|Genotype|Humans|Models, Theoretical', 'Journal Article', '10.1371/journal.pcbi.1004349', '26308326', 'Evolutionary game theory is a powerful framework for studying evolution in populations of interacting individuals. A common assumption in evolutionary game theory is that interactions are symmetric, which means that the players are distinguished by only their strategies. In nature, however, the microscopic interactions between players are nearly always asymmetric due to environmental effects, differing baseline characteristics, and other possible sources of heterogeneity. To model these phenomena, we introduce into evolutionary game theory two broad classes of asymmetric interactions: ecological and genotypic. Ecological asymmetry results from variation in the environments of the players, while genotypic asymmetry is a consequence of the players having differing baseline genotypes. We develop a theory of these forms of asymmetry for games in structured populations and use the classical social dilemmas, the Prisoners Dilemma and the Snowdrift Game, for illustrations. Interestingly, asymmetric games reveal essential differences between models of genetic evolution based on reproduction and models of cultural evolution based on imitation that are not apparent in symmetric games. '),
(87312, 2015, 'plos', 'Refinement and Pattern Formation in Neural Circuits by the Interaction of Traveling Waves with Spike-Timing Dependent Plasticity', 'Bennett, James E M|Bair, Wyeth', 'Dept. Physiology, Anatomy and Genetics, University of Oxford, Oxford, United Kingdom.|Dept. Biological Structure, University of Washington, Seattle, Washington, United States of America.', 'United Kingdom|United States', 0, 'Action Potentials|Algorithms|Animals|Brain|Cats|Computational Biology|Computer Simulation|Ferrets|Mice|Models, Neurological|Neuronal Plasticity|Neurons|Retina', 'Journal Article', '10.1371/journal.pcbi.1004422', '26308406', 'Traveling waves in the developing brain are a prominent source of highly correlated spiking activity that may instruct the refinement of neural circuits. A candidate mechanism for mediating such refinement is spike-timing dependent plasticity (STDP), which translates correlated activity patterns into changes in synaptic strength. To assess the potential of these phenomena to build useful structure in developing neural circuits, we examined the interaction of wave activity with STDP rules in simple, biologically plausible models of spiking neurons. We derive an expression for the synaptic strength dynamics showing that, by mapping the time dependence of STDP into spatial interactions, traveling waves can build periodic synaptic connectivity patterns into feedforward circuits with a broad class of experimentally observed STDP rules. The spatial scale of the connectivity patterns increases with wave speed and STDP time constants. We verify these results with simulations and demonstrate their robustness to likely sources of noise. We show how this pattern formation ability, which is analogous to solutions of reaction-diffusion systems that have been widely applied to biological pattern formation, can be harnessed to instruct the refinement of postsynaptic receptive fields. Our results hold for rich, complex wave patterns in two dimensions and over several orders of magnitude in wave speeds and STDP time constants, and they provide predictions that can be tested under existing experimental paradigms. Our model generalizes across brain areas and STDP rules, allowing broad application to the ubiquitous occurrence of traveling waves and to wave-like activity patterns induced by moving stimuli. '),
(87313, 2015, 'plos', 'Mechanism for Collective Cell Alignment in Myxococcus xanthus Bacteria', 'Balagam, Rajesh|Igoshin, Oleg A', 'Department of Bioengineering and Center for Theoretical Biological Physics, Rice University, Houston, Texas, United States of America.|Department of Bioengineering and Center for Theoretical Biological Physics, Rice University, Houston, Texas, United States of America.', 'United States|United States', 0, 'Bacterial Adhesion|Cell Movement|Computational Biology|Models, Biological|Myxococcus xanthus', 'Journal Article', '10.1371/journal.pcbi.1004474', '26308508', 'Myxococcus xanthus cells self-organize into aligned groups, clusters, at various stages of their lifecycle. Formation of these clusters is crucial for the complex dynamic multi-cellular behavior of these bacteria. However, the mechanism underlying the cell alignment and clustering is not fully understood. Motivated by studies of clustering in self-propelled rods, we hypothesized that M. xanthus cells can align and form clusters through pure mechanical interactions among cells and between cells and substrate. We test this hypothesis using an agent-based simulation framework in which each agent is based on the biophysical model of an individual M. xanthus cell. We show that model agents, under realistic cell flexibility values, can align and form cell clusters but only when periodic reversals of cell directions are suppressed. However, by extending our model to introduce the observed ability of cells to deposit and follow slime trails, we show that effective trail-following leads to clusters in reversing cells. Furthermore, we conclude that mechanical cell alignment combined with slime-trail-following is sufficient to explain the distinct clustering behaviors observed for wild-type and non-reversing M. xanthus mutants in recent experiments. Our results are robust to variation in model parameters, match the experimentally observed trends and can be applied to understand surface motility patterns of other bacterial species. ');
