INSERT INTO `papers` (`id`, `ano`, `journal`, `titulo`, `autores`, `afiliacao`, `pais`, `citacoes`, `palavra_chave`, `categorias`, `doi`, `pubmed`, `abstract`) VALUES
(88388, 2017, 'plos', 'Highly accessible AU-rich regions in 3 untranslated regions are hotspots for binding of regulatory factors', 'Plass, Mireya|Rasmussen, Simon H|Krogh, Anders', 'Section for Computational and RNA Biology, Department of Biology, University of Copenhagen, Ole Maaløes Vej 5, Copenhagen, Denmark.|Section for Computational and RNA Biology, Department of Biology, University of Copenhagen, Ole Maaløes Vej 5, Copenhagen, Denmark.|Section for Computational and RNA Biology, Department of Biology, University of Copenhagen, Ole Maaløes Vej 5, Copenhagen, Denmark.', 'Denmark|Denmark|Denmark', 17, '3 Untranslated Regions|Binding Sites|Computational Biology|HEK293 Cells|Humans|Immunoprecipitation|MicroRNAs|Polyadenylation|RNA-Binding Proteins', 'Journal Article', '10.1371/journal.pcbi.1005460', '28410363', 'Post-transcriptional regulation is regarded as one of the major processes involved in the regulation of gene expression. It is mainly performed by RNA binding proteins and microRNAs, which target RNAs and typically affect their stability. Recent efforts from the scientific community have aimed at understanding post-transcriptional regulation at a global scale by using high-throughput sequencing techniques such as cross-linking and immunoprecipitation (CLIP), which facilitates identification of binding sites of these regulatory factors. However, the diversity in the experimental procedures and bioinformatics analyses has hindered the integration of multiple datasets and thus limited the development of an integrated view of post-transcriptional regulation. In this work, we have performed a comprehensive analysis of 107 CLIP datasets from 49 different RBPs in HEK293 cells to shed light on the complex interactions that govern post-transcriptional regulation. By developing a more stringent CLIP analysis pipeline we have discovered the existence of conserved regulatory AU-rich regions in the 3UTRs where miRNAs and RBPs that regulate several processes such as polyadenylation or mRNA stability bind. Analogous to promoters, many factors have binding sites overlapping or in close proximity in these hotspots and hence the regulation of the mRNA may depend on their relative concentrations. This hypothesis is supported by RBP knockdown experiments that alter the relative concentration of RBPs in the cell. Upon AGO2 knockdown (KD), transcripts containing free target sites show increased expression levels compared to those containing target sites in hotspots, which suggests that target sites within hotspots are less available for miRNAs to bind. Interestingly, these hotspots appear enriched in genes with regulatory functions such as DNA binding and RNA binding. Taken together, our results suggest that hotspots are functional regulatory elements that define an extra layer of regulation of post-transcriptional regulatory networks.'),
(88389, 2017, 'plos', 'Heterogeneous firing responses predict diverse couplings to presynaptic activity in mice layer V pyramidal neurons', 'Zerlaut, Yann|Destexhe, Alain', 'Unité de Neurosciences, Information et Complexité. Centre National de la Recherche Scientifique. 1 avenue de la terrasse, Gif sur Yvette, France.|Unité de Neurosciences, Information et Complexité. Centre National de la Recherche Scientifique. 1 avenue de la terrasse, Gif sur Yvette, France.', 'France|France', 2, 'Action Potentials|Animals|Humans|Mice|Models, Neurological|Neocortex|Pyramidal Cells|Synapses', 'Journal Article', '10.1371/journal.pcbi.1005452', '28410418', 'In this study, we present a theoretical framework combining experimental characterizations and analytical calculus to capture the firing rate input-output properties of single neurons in the fluctuation-driven regime. Our framework consists of a two-step procedure to treat independently how the dendritic input translates into somatic fluctuation variables, and how the latter determine action potential firing. We use this framework to investigate the functional impact of the heterogeneity in firing responses found experimentally in young mice layer V pyramidal cells. We first design and calibrate in vitro a simplified morphological model of layer V pyramidal neurons with a dendritic tree following Ralls branching rule. Then, we propose an analytical derivation for the membrane potential fluctuations at the soma as a function of the properties of the synaptic input in dendrites. This mathematical description allows us to easily emulate various forms of synaptic input: either balanced, unbalanced, synchronized, purely proximal or purely distal synaptic activity. We find that those different forms of dendritic input activity lead to various impact on the somatic membrane potential fluctuations properties, thus raising the possibility that individual neurons will differentially couple to specific forms of activity as a result of their different firing response. We indeed found such a heterogeneous coupling between synaptic input and firing response for all types of presynaptic activity. This heterogeneity can be explained by different levels of cellular excitability in the case of the balanced, unbalanced, synchronized and purely distal activity. A notable exception appears for proximal dendritic inputs: increasing the input level can either promote firing response in some cells, or suppress it in some other cells whatever their individual excitability. This behavior can be explained by different sensitivities to the speed of the fluctuations, which was previously associated to different levels of sodium channel inactivation and density. Because local network connectivity rather targets proximal dendrites, our results suggest that this aspect of biophysical heterogeneity might be relevant to neocortical processing by controlling how individual neurons couple to local network activity.'),
(88390, 2017, 'plos', 'Simple biochemical networks allow accurate sensing of multiple ligands with a single receptor', 'Singh, Vijay|Nemenman, Ilya', 'Department of Physics, Emory University, Atlanta, Georgia, United States of America.|Department of Physics, Emory University, Atlanta, Georgia, United States of America.', 'Georgia|Georgia', 7, 'Computational Biology|Computer Simulation|Kinetics|Ligands|Models, Biological|Protein Binding|Receptors, Cell Surface|Signal Transduction', 'Journal Article', '10.1371/journal.pcbi.1005490', '28410433', 'Cells use surface receptors to estimate concentrations of external ligands. Limits on the accuracy of such estimations have been well studied for pairs of ligand and receptor species. However, the environment typically contains many ligands, which can bind to the same receptors with different affinities, resulting in cross-talk. In traditional rate models, such cross-talk prevents accurate inference of concentrations of individual ligands. In contrast, here we show that knowing the precise timing sequence of stochastic binding and unbinding events allows one receptor to provide information about multiple ligands simultaneously and with a high accuracy. We show that such high-accuracy estimation of multiple concentrations can be realized with simple structural modifications of the familiar kinetic proofreading biochemical network diagram. We give two specific examples of such modifications. We argue that structural and functional features of real cellular biochemical sensory networks in immune cells, such as feedforward and feedback loops or ligand antagonism, sometimes can be understood as solutions to the accurate multi-ligand estimation problem.'),
(88391, 2017, 'plos', 'Dynamics of adaptive immunity against phage in bacterial populations', 'Bradde, Serena|Vucelja, Marija|Texc5x9fileanu, Tiberiu|Balasubramanian, Vijay', 'Initiative for the Theoretical Sciences, The Graduate Center, CUNY, New York, New York, United States of America.|Center for Studies in Physics and Biology, The Rockefeller University, New York, New York, United States of America.|Initiative for the Theoretical Sciences, The Graduate Center, CUNY, New York, New York, United States of America.|Initiative for the Theoretical Sciences, The Graduate Center, CUNY, New York, New York, United States of America.', 'United States|United States|United States|United States', 8, 'Bacteria|Bacteriophages|CRISPR-Cas Systems|Computational Biology|Genome, Bacterial|Host-Pathogen Interactions|Models, Biological', 'Journal Article', '10.1371/journal.pcbi.1005486', '28414716', 'The CRISPR (clustered regularly interspaced short palindromic repeats) mechanism allows bacteria to adaptively defend against phages by acquiring short genomic sequences (spacers) that target specific sequences in the viral genome. We propose a population dynamical model where immunity can be both acquired and lost. The model predicts regimes where bacterial and phage populations can co-exist, others where the populations exhibit damped oscillations, and still others where one population is driven to extinction. Our model considers two key parameters: (1) ease of acquisition and (2) spacer effectiveness in conferring immunity. Analytical calculations and numerical simulations show that if spacers differ mainly in ease of acquisition, or if the probability of acquiring them is sufficiently high, bacteria develop a diverse population of spacers. On the other hand, if spacers differ mainly in their effectiveness, their final distribution will be highly peaked, akin to a winner-take-all scenario, leading to a specialized spacer distribution. Bacteria can interpolate between these limiting behaviors by actively tuning their overall acquisition probability.'),
(88392, 2017, 'plos', 'Achieving global perfect homeostasis through transporter regulation', 'Savir, Yonatan|Martynov, Alexander|Springer, Michael', 'Department of Physiology, Biophysics and Systems Biology, Faculty of Medicine, Technion, Haifa, Israel.|Center for Data-Intensive Biomedicine and Biotechnology, Skolkovo Institute of Science and Technology, Moscow, Russia.|Department of Systems Biology, Harvard Medical School, Boston, Massachusetts, United States of America.', 'Israel|-|United States', 7, 'Biological Transport|Gene Expression Regulation|Homeostasis|Membrane Transport Proteins|Models, Biological|Systems Biology|Yeasts', 'Journal Article', '10.1371/journal.pcbi.1005458', '28414718', 'Nutrient homeostasis-the maintenance of relatively constant internal nutrient concentrations in fluctuating external environments-is essential to the survival of most organisms. Transcriptional regulation of plasma membrane transporters by internal nutrient concentrations is typically assumed to be the main mechanism by which homeostasis is achieved. While this mechanism is homeostatic we show that it does not achieve global perfect homeostasis-a condition where internal nutrient concentrations are completely independent of external nutrient concentrations for all external nutrient concentrations. We show that the criterion for global perfect homeostasis is that transporter levels must be inversely proportional to net nutrient flux into the cell and that downregulation of active transporters (activity-dependent regulation) is a simple and biologically plausible mechanism that meets this criterion. Activity-dependent transporter regulation creates a trade-off between robustness and efficiency, i.e., the systems ability to withstand perturbation in external nutrients and the transporter production rate needed to maintain homeostasis. Additionally, we show that a system that utilizes both activity-dependent transporter downregulation and regulation of transporter synthesis by internal nutrient levels can create a system that mitigates the shortcomings of each of the individual mechanisms. This analysis highlights the utility of activity-dependent regulation in achieving homeostasis and calls for a re-examination of the mechanisms of regulation of other homeostatic systems.'),
(88393, 2017, 'plos', 'Effect of transcription factor resource sharing on gene expression noise', 'Das, Dipjyoti|Dey, Supravat|Brewster, Robert C|Choubey, Sandeep', 'Department of Molecular, Cellular and Developmental Biology, Yale University, New Haven, Connecticut, United States of America.|Laboratoire Charles Coulomb, Université de Montpellier and CNRS, Montpellier, France.|Program in Systems Biology, University of Massachusetts Medical School, Worcester, Massachusetts, United States of America.|FAS Center for Systems Biology, Harvard University, Cambridge, Massachusetts, United States of America.', 'United States|France|United States|United States', 11, 'Binding Sites|Computational Biology|Gene Dosage|Gene Expression Regulation|Kinetics|Promoter Regions, Genetic|RNA, Messenger|Transcription Factors', 'Journal Article', '10.1371/journal.pcbi.1005491', '28414750', 'Gene expression is intrinsically a stochastic (noisy) process with important implications for cellular functions. Deciphering the underlying mechanisms of gene expression noise remains one of the key challenges of regulatory biology. Theoretical models of transcription often incorporate the kinetics of how transcription factors (TFs) interact with a single promoter to impact gene expression noise. However, inside single cells multiple identical gene copies as well as additional binding sites can compete for a limiting pool of TFs. Here we develop a simple kinetic model of transcription, which explicitly incorporates this interplay between TF copy number and its binding sites. We show that TF sharing enhances noise in mRNA distribution across an isogenic population of cells. Moreover, when a single gene copy shares its TFs with multiple competitor sites, the mRNA variance as a function of the mean remains unaltered by their presence. Hence, all the data for variance as a function of mean expression collapse onto a single master curve independent of the strength and number of competitor sites. However, this result does not hold true when the competition stems from multiple copies of the same gene. Therefore, although previous studies showed that the mean expression follows a universal master curve, our findings suggest that different scenarios of competition bear distinct signatures at the level of variance. Intriguingly, the introduction of competitor sites can transform a unimodal mRNA distribution into a multimodal distribution. These results demonstrate the impact of limited availability of TF resource on the regulation of noise in gene expression.'),
(88394, 2017, 'plos', 'Semantic prioritization of novel causative genomic variants', 'Boudellioua, Imane|Mahamad Razali, Rozaimi B|Kulmanov, Maxat|Hashish, Yasmeen|Bajic, Vladimir B|Goncalves-Serra, Eva|Schoenmakers, Nadia|Gkoutos, Georgios V|Schofield, Paul N|Hoehndorf, Robert', 'King Abdullah University of Science and Technology, Computer, Electrical & Mathematical Sciences and Engineering Division, Computational Bioscience Research Center, Thuwal, Saudi Arabia.|King Abdullah University of Science and Technology, Computer, Electrical & Mathematical Sciences and Engineering Division, Computational Bioscience Research Center, Thuwal, Saudi Arabia.|King Abdullah University of Science and Technology, Computer, Electrical & Mathematical Sciences and Engineering Division, Computational Bioscience Research Center, Thuwal, Saudi Arabia.|King Abdullah University of Science and Technology, Computer, Electrical & Mathematical Sciences and Engineering Division, Computational Bioscience Research Center, Thuwal, Saudi Arabia.|King Abdullah University of Science and Technology, Computer, Electrical & Mathematical Sciences and Engineering Division, Computational Bioscience Research Center, Thuwal, Saudi Arabia.|Wellcome Trust Sanger Institute, Wellcome Trust Genome Campus, Hinxton, United Kingdom.|University of Cambridge Metabolic Research Laboratories, Wellcome Trust-Medical Research Council, Institute of Metabolic Science, Addenbrookes Hospital, Cambridge, United Kingdom.|College of Medical and Dental Sciences, Institute of Cancer and Genomic Sciences, Centre for Computational Biology, University of Birmingham, Birmingham, United Kingdom.|Department of Physiology, Development & Neuroscience, University of Cambridge, Cambridge, United Kingdom.|King Abdullah University of Science and Technology, Computer, Electrical & Mathematical Sciences and Engineering Division, Computational Bioscience Research Center, Thuwal, Saudi Arabia.', 'Saudi Arabia|Saudi Arabia|Saudi Arabia|Saudi Arabia|Saudi Arabia|United Kingdom|United Kingdom|Unite', 15, 'Algorithms|Computational Biology|Exome|Genetic Variation|Genome|Humans|Molecular Sequence Annotation|Phenotype|Retrospective Studies|Semantics', 'Journal Article', '10.1371/journal.pcbi.1005500', '28414800', 'Discriminating the causative disease variant(s) for individuals with inherited or de novo mutations presents one of the main challenges faced by the clinical genetics community today. Computational approaches for variant prioritization include machine learning methods utilizing a large number of features, including molecular information, interaction networks, or phenotypes. Here, we demonstrate the PhenomeNET Variant Predictor (PVP) system that exploits semantic technologies and automated reasoning over genotype-phenotype relations to filter and prioritize variants in whole exome and whole genome sequencing datasets. We demonstrate the performance of PVP in identifying causative variants on a large number of synthetic whole exome and whole genome sequences, covering a wide range of diseases and syndromes. In a retrospective study, we further illustrate the application of PVP for the interpretation of whole exome sequencing data in patients suffering from congenital hypothyroidism. We find that PVP accurately identifies causative variants in whole exome and whole genome sequencing datasets and provides a powerful resource for the discovery of causal variants.'),
(88395, 2017, 'plos', 'Probabilistic fluorescence-based synapse detection', 'Simhal, Anish K|Aguerrebere, Cecilia|Collman, Forrest|Vogelstein, Joshua T|Micheva, Kristina D|Weinberg, Richard J|Smith, Stephen J|Sapiro, Guillermo', 'Electrical and Computer Engineering, Duke University, Durham, North Carolina, United States of America.|Electrical and Computer Engineering, Duke University, Durham, North Carolina, United States of America.|Synapse Biology, Allen Institute for Brain Sciences, Seattle, Washington, United States of America.|Department of Biomedical Engineering, Johns Hopkins University, Baltimore, Maryland, United States of America.|Molecular and Cellular Physiology, Stanford University School of Medicine, Stanford, California, United States of America.|Department of Cell Biology and Physiology, University of North Carolina, Chapel Hill, Chapel Hill, North Carolina, United States of America.|Synapse Biology, Allen Institute for Brain Sciences, Seattle, Washington, United States of America.|Electrical and Computer Engineering, Duke University, Durham, North Carolina, United States of America.', 'United States|United States|United States|United States|United States|United States|United States|Un', 8, 'Algorithms|Animals|Cerebral Cortex|Computational Biology|Humans|Image Processing, Computer-Assisted|Microscopy, Electron|Models, Statistical|Optical Imaging|Synapses|Tomography', 'Journal Article', '10.1371/journal.pcbi.1005493', '28414801', 'Deeper exploration of the brains vast synaptic networks will require new tools for high-throughput structural and molecular profiling of the diverse populations of synapses that compose those networks. Fluorescence microscopy (FM) and electron microscopy (EM) offer complementary advantages and disadvantages for single-synapse analysis. FM combines exquisite molecular discrimination capacities with high speed and low cost, but rigorous discrimination between synaptic and non-synaptic fluorescence signals is challenging. In contrast, EM remains the gold standard for reliable identification of a synapse, but offers only limited molecular discrimination and is slow and costly. To develop and test single-synapse image analysis methods, we have used datasets from conjugate array tomography (cAT), which provides voxel-conjugate FM and EM (annotated) images of the same individual synapses. We report a novel unsupervised probabilistic method for detection of synapses from multiplex FM (muxFM) image data, and evaluate this method both by comparison to EM gold standard annotated data and by examining its capacity to reproduce known important features of cortical synapse distributions. The proposed probabilistic model-based synapse detector accepts molecular-morphological synapse models as user queries, and delivers a volumetric map of the probability that each voxel represents part of a synapse. Taking human annotation of cAT EM data as ground truth, we show that our algorithm detects synapses from muxFM data alone as successfully as human annotators seeing only the muxFM data, and accurately reproduces known architectural features of cortical synapse distributions. This approach opens the door to data-driven discovery of new synapse types and their density. We suggest that our probabilistic synapse detector will also be useful for analysis of standard confocal and super-resolution FM images, where EM cross-validation is not practical.'),
(88396, 2017, 'plos', 'Erroneous energy-generating cycles in published genome scale metabolic networks: Identification and removal', 'Fritzemeier, Claus Jonathan|Hartleb, Daniel|Szappanos, Balxc3xa1zs|Papp, Balxc3xa1zs|Lercher, Martin J', 'Institute for Computer Science and Cluster of Excellence on Plant Sciences, Heinrich Heine University, Dxc3xbcsseldorf, Germany.|Institute for Computer Science and Cluster of Excellence on Plant Sciences, Heinrich Heine University, Dxc3xbcsseldorf, Germany.|Synthetic and Systems Biology Unit, Institute of Biochemistry, Biological Research Centre of the Hungarian Academy of Sciences, Szeged, Hungary.|Synthetic and Systems Biology Unit, Institute of Biochemistry, Biological Research Centre of the Hungarian Academy of Sciences, Szeged, Hungary.|Institute for Computer Science and Cluster of Excellence on Plant Sciences, Heinrich Heine University, Dxc3xbcsseldorf, Germany.', 'Germany|Germany|Hungary|Hungary|Germany', 7, 'Computational Biology|Energy Metabolism|Genome|Metabolic Flux Analysis|Metabolic Networks and Pathways|Models, Biological|Research Design', 'Journal Article', '10.1371/journal.pcbi.1005494', '28419089', 'Energy metabolism is central to cellular biology. Thus, genome-scale models of heterotrophic unicellular species must account appropriately for the utilization of external nutrients to synthesize energy metabolites such as ATP. However, metabolic models designed for flux-balance analysis (FBA) may contain thermodynamically impossible energy-generating cycles: without nutrient consumption, these models are still capable of charging energy metabolites (such as ADPxe2x86x92ATP or NADP+xe2x86x92NADPH). Here, we show that energy-generating cycles occur in over 85% of metabolic models without extensive manual curation, such as those contained in the ModelSEED and MetaNetX databases, in contrast, such cycles are rare in the manually curated models of the BiGG database. Energy generating cycles may represent model errors, e.g., erroneous assumptions on reaction reversibilities. Alternatively, part of the cycle may be thermodynamically feasible in one environment, while the remainder is thermodynamically feasible in another environment, as standard FBA does not account for thermodynamics, combining these into an FBA model allows erroneous energy generation. The presence of energy-generating cycles typically inflates maximal biomass production rates by 25%, and may lead to biases in evolutionary simulations. We present efficient computational methods (i) to identify energy generating cycles, using FBA, and (ii) to identify minimal sets of model changes that eliminate them, using a variant of the GlobalFit algorithm.'),
(88397, 2017, 'plos', 'Robust information propagation through noisy neural circuits', 'Zylberberg, Joel|Pouget, Alexandre|Latham, Peter E|Shea-Brown, Eric', 'Department of Physiology and Biophysics, Center for Neuroscience, and Computational Bioscience Program, University of Colorado School of Medicine, Aurora, Colorado, United States of America.|Department of Basic Neuroscience, University of Geneva, Geneva, Switzerland.|Gatsby Computational Neuroscience Unit, University College London, London, United Kingdom.|Department of Applied Mathematics, University of Washington, Seattle, Washington, United States of America.', 'United States|Switzerland|United Kingdom|United States', 7, 'Computational Biology|Computer Simulation|Models, Neurological|Nerve Net|Sensory Receptor Cells', 'Journal Article', '10.1371/journal.pcbi.1005497', '28419098', 'Sensory neurons give highly variable responses to stimulation, which can limit the amount of stimulus information available to downstream circuits. Much work has investigated the factors that affect the amount of information encoded in these population responses, leading to insights about the role of covariability among neurons, tuning curve shape, etc. However, the informativeness of neural responses is not the only relevant feature of population codes, of potentially equal importance is how robustly that information propagates to downstream structures. For instance, to quantify the retinas performance, one must consider not only the informativeness of the optic nerve responses, but also the amount of information that survives the spike-generating nonlinearity and noise corruption in the next stage of processing, the lateral geniculate nucleus. Our study identifies the set of covariance structures for the upstream cells that optimize the ability of information to propagate through noisy, nonlinear circuits. Within this optimal family are covariances with differential correlations, which are known to reduce the information encoded in neural population activities. Thus, covariance structures that maximize information in neural population codes, and those that maximize the ability of this information to propagate, can be very different. Moreover, redundancy is neither necessary nor sufficient to make population codes robust against corruption by noise: redundant codes can be very fragile, and synergistic codes can-in some cases-optimize robustness against noise.'),
(88398, 2017, 'plos', 'Towards a theory of cortical columns: From spiking neurons to interacting neural populations of finite size', 'Schwalger, Tilo|Deger, Moritz|Gerstner, Wulfram', 'Brain Mind Institute, School of Computer and Communication Sciences and School of Life Sciences, École Polytechnique Fédérale de Lausanne (EPFL), Lausanne, Switzerland.|Brain Mind Institute, School of Computer and Communication Sciences and School of Life Sciences, École Polytechnique Fédérale de Lausanne (EPFL), Lausanne, Switzerland.|Brain Mind Institute, School of Computer and Communication Sciences and School of Life Sciences, École Polytechnique Fédérale de Lausanne (EPFL), Lausanne, Switzerland.', 'Switzerland|Switzerland|Switzerland', 0, 'Action Potentials|Algorithms|Computational Biology|Models, Neurological|Neural Networks (Computer)|Neurons|Visual Cortex', 'Journal Article', '10.1371/journal.pcbi.1005507', '28422957', 'Neural population equations such as neural mass or field models are widely used to study brain activity on a large scale. However, the relation of these models to the properties of single neurons is unclear. Here we derive an equation for several interacting populations at the mesoscopic scale starting from a microscopic model of randomly connected generalized integrate-and-fire neuron models. Each population consists of 50-2000 neurons of the same type but different populations account for different neuron types. The stochastic population equations that we find reveal how spike-history effects in single-neuron dynamics such as refractoriness and adaptation interact with finite-size fluctuations on the population level. Efficient integration of the stochastic mesoscopic equations reproduces the statistical behavior of the population activities obtained from microscopic simulations of a full spiking neural network model. The theory describes nonlinear emergent dynamics such as finite-size-induced stochastic transitions in multistable networks and synchronization in balanced networks of excitatory and inhibitory neurons. The mesoscopic equations are employed to rapidly integrate a model of a cortical microcircuit consisting of eight neuron types, which allows us to predict spontaneous population activities as well as evoked responses to thalamic input. Our theory establishes a general framework for modeling finite-size neural population dynamics based on single cell and synapse parameters and offers an efficient approach to analyzing cortical circuits and computations.'),
(88399, 2017, 'plos', 'Cheminformatics-aided discovery of small-molecule Protein-Protein Interaction (PPI) dual inhibitors of Tumor Necrosis Factor (TNF) and Receptor Activator of NF-xcexbaB Ligand (RANKL)', 'Melagraki, Georgia|Ntougkos, Evangelos|Rinotas, Vagelis|Papaneophytou, Christos|Leonis, Georgios|Mavromoustakos, Thomas|Kontopidis, George|Douni, Eleni|Afantitis, Antreas|Kollias, George', 'Division of Immunology, Biomedical Sciences Research Center Alexander Fleming, Vari, Greece.|Division of Immunology, Biomedical Sciences Research Center Alexander Fleming, Vari, Greece.|Division of Immunology, Biomedical Sciences Research Center Alexander Fleming, Vari, Greece.|Veterinary School, University of Thessaly, Karditsa, Greece.|NovaMechanics Ltd, Nicosia, Cyprus.|Laboratory of Organic Chemistry, Department of Chemistry, National and Kapodistrian University of Athens, Athens, Greece.|Veterinary School, University of Thessaly, Karditsa, Greece.|Division of Immunology, Biomedical Sciences Research Center Alexander Fleming, Vari, Greece.|Division of Immunology, Biomedical Sciences Research Center Alexander Fleming, Vari, Greece.|Division of Immunology, Biomedical Sciences Research Center Alexander Fleming, Vari, Greece.', 'Greece|Greece|Greece|Greece|Cyprus|Greece|Greece|Greece|Greece|Greece', 0, 'Animals|Anti-Inflammatory Agents|Bone Marrow Cells|Cell Line|Cell Survival|Cells, Cultured|Computer Simulation|Drug Discovery|Humans|Ligands|Mice|Protein Interaction Domains and Motifs|RANK Ligand|Tumor Necrosis Factor-alpha', 'Journal Article', '10.1371/journal.pcbi.1005372', '28426652', 'We present an in silico drug discovery pipeline developed and applied for the identification and virtual screening of small-molecule Protein-Protein Interaction (PPI) compounds that act as dual inhibitors of TNF and RANKL through the trimerization interface. The cheminformatics part of the pipeline was developed by combining structure-based with ligand-based modeling using the largest available set of known TNF inhibitors in the literature (2481 small molecules). To facilitate virtual screening, the consensus predictive model was made freely available at: http://enalos.insilicotox.com/TNFPubChem/. We thus generated a priority list of nine small molecules as candidates for direct TNF function inhibition. In vitro evaluation of these compounds led to the selection of two small molecules that act as potent direct inhibitors of TNF function, with IC50 values comparable to those of a previously-described direct inhibitor (SPD304), but with significantly reduced toxicity. These molecules were also identified as RANKL inhibitors and validated in vitro with respect to this second functionality. Direct binding of the two compounds was confirmed both for TNF and RANKL, as well as their ability to inhibit the biologically-active trimer forms. Molecular dynamics calculations were also carried out for the two small molecules in each protein to offer additional insight into the interactions that govern TNF and RANKL complex formation. To our knowledge, these compounds, namely T8 and T23, constitute the second and third published examples of dual small-molecule direct function inhibitors of TNF and RANKL, and could serve as lead compounds for the development of novel treatments for inflammatory and autoimmune diseases.'),
(88400, 2017, 'plos', 'Exhaustive search of linear information encoding protein-peptide recognition', 'Kelil, Abdellali|Dubreuil, Benjamin|Levy, Emmanuel D|Michnick, Stephen W', 'Donnelly Centre for Cellular and Biomolecular Research, University of Toronto, Toronto, Ontario, Canada.|Department of Structural Biology, Weizmann Institute of Science, Rehovot, Israel.|Department of Biochemistry and Molecular Medicine, University of Montreal, Montreal, Quebec, Canada.|Department of Biochemistry and Molecular Medicine, University of Montreal, Montreal, Quebec, Canada.', 'Canada|Israel|Canada|Canada', 1, 'Algorithms|Binding Sites|Computational Biology|GRB2 Adaptor Protein|Humans|Peptides|Protein Binding|Protein Interaction Domains and Motifs|Saccharomyces cerevisiae Proteins|Sequence Analysis, Protein|src Homology Domains', 'Journal Article', '10.1371/journal.pcbi.1005499', '28426660', 'High-throughput in vitro methods have been extensively applied to identify linear information that encodes peptide recognition. However, these methods are limited in number of peptides, sequence variation, and length of peptides that can be explored, and often produce solutions that are not found in the cell. Despite the large number of methods developed to attempt addressing these issues, the exhaustive search of linear information encoding protein-peptide recognition has been so far physically unfeasible. Here, we describe a strategy, called DALEL, for the exhaustive search of linear sequence information encoded in proteins that bind to a common partner. We applied DALEL to explore binding specificity of SH3 domains in the budding yeast Saccharomyces cerevisiae. Using only the polypeptide sequences of SH3 domain binding proteins, we succeeded in identifying the majority of known SH3 binding sites previously discovered either in vitro or in vivo. Moreover, we discovered a number of sites with both non-canonical sequences and distinct properties that may serve ancillary roles in peptide recognition. We compared DALEL to a variety of state-of-the-art algorithms in the blind identification of known binding sites of the human Grb2 SH3 domain. We also benchmarked DALEL on curated biological motifs derived from the ELM database to evaluate the effect of increasing/decreasing the enrichment of the motifs. Our strategy can be applied in conjunction with experimental data of proteins interacting with a common partner to identify binding sites among them. Yet, our strategy can also be applied to any group of proteins of interest to identify enriched linear motifs or to exhaustively explore the space of linear information encoded in a polypeptide sequence. Finally, we have developed a webserver located at http://michnick.bcm.umontreal.ca/dalel, offering user-friendly interface and providing different scenarios utilizing DALEL.'),
(88401, 2017, 'plos', 'Oncodomains: A protein domain-centric framework for analyzing rare variants in tumor samples', 'Peterson, Thomas A|Gauran, Iris Ivy M|Park, Junyong|Park, DoHwan|Kann, Maricel G', 'Department of Biological Sciences, University of Maryland, Baltimore County, Baltimore, Maryland, United States of America.|Department of Mathematics and Statistics, University of Maryland, Baltimore County, Baltimore, Maryland, United States of America.|Department of Mathematics and Statistics, University of Maryland, Baltimore County, Baltimore, Maryland, United States of America.|Department of Mathematics and Statistics, University of Maryland, Baltimore County, Baltimore, Maryland, United States of America.|Department of Biological Sciences, University of Maryland, Baltimore County, Baltimore, Maryland, United States of America.', 'United States|United States|United States|United States|United States', 0, 'Computational Biology|Databases, Protein|Epidermal Growth Factor|Humans|Mitochondrial Proteins|Models, Molecular|Mutation|Neoplasms|Oncogene Proteins|Protein Binding|Protein Domains|ras Proteins', 'Journal Article', '10.1371/journal.pcbi.1005428', '28426665', 'The fight against cancer is hindered by its highly heterogeneous nature. Genome-wide sequencing studies have shown that individual malignancies contain many mutations that range from those commonly found in tumor genomes to rare somatic variants present only in a small fraction of lesions. Such rare somatic variants dominate the landscape of genomic mutations in cancer, yet efforts to correlate somatic mutations found in one or few individuals with functional roles have been largely unsuccessful. Traditional methods for identifying somatic variants that drive cancer are gene-centric in that they consider only somatic variants within a particular gene and make no comparison to other similar genes in the same family that may play a similar role in cancer. In this work, we present oncodomain hotspots, a new domain-centric method for identifying clusters of somatic mutations across entire gene families using protein domain models. Our analysis confirms that our approach creates a framework for leveraging structural and functional information encapsulated by protein domains into the analysis of somatic variants in cancer, enabling the assessment of even rare somatic variants by comparison to similar genes. Our results reveal a vast landscape of somatic variants that act at the level of domain families altering pathways known to be involved with cancer such as protein phosphorylation, signaling, gene regulation, and cell metabolism. Due to oncodomain hotspots unique ability to assess rare variants, we expect our method to become an important tool for the analysis of sequenced tumor genomes, complementing existing methods.'),
(88402, 2017, 'plos', 'A dynamic genetic-hormonal regulatory network model explains multiple cellular behaviors of the root apical meristem of Arabidopsis thaliana', 'García-Gómez, Mónica L|Azpeitia, Eugenio|Álvarez-Buylla, Elena R', 'Departamento de Ecología Funcional, Instituto de Ecología, Universidad Nacional Autónoma de México, Coyoacán, Ciudad de México, México.|INRIA project-team Virtual Plants, joint with CIRAD and INRA, Montpellier, France.|Departamento de Ecología Funcional, Instituto de Ecología, Universidad Nacional Autónoma de México, Coyoacán, Ciudad de México, México.', '-|France|-', 10, 'Arabidopsis|Arabidopsis Proteins|Cell Differentiation|Computational Biology|Cytokinins|Gene Expression Regulation, Plant|Gene Regulatory Networks|Indoleacetic Acids|Meristem|Models, Biological|Signal Transduction', 'Journal Article', '10.1371/journal.pcbi.1005488', '28426669', 'The study of the concerted action of hormones and transcription factors is fundamental to understand cell differentiation and pattern formation during organ development. The root apical meristem of Arabidopsis thaliana is a useful model to address this. It has a stem cell niche near its tip conformed of a quiescent organizer and stem or initial cells around it, then a proliferation domain followed by a transition domain, where cells diminish division rate before transiting to the elongation zone, here, cells grow anisotropically prior to their final differentiation towards the plant base. A minimal model of the gene regulatory network that underlies cell-fate specification and patterning at the root stem cell niche was proposed before. In this study, we update and couple such network with both the auxin and cytokinin hormone signaling pathways to address how they collectively give rise to attractors that correspond to the genetic and hormonal activity profiles that are characteristic of different cell types along A. thaliana root apical meristem. We used a Boolean model of the genetic-hormonal regulatory network to integrate known and predicted regulatory interactions into alternative models. Our analyses show that, after adding some putative missing interactions, the model includes the necessary and sufficient components and regulatory interactions to recover attractors characteristic of the root cell types, including the auxin and cytokinin activity profiles that correlate with different cellular behaviors along the root apical meristem. Furthermore, the model predicts the existence of activity configurations that could correspond to the transition domain. The model also provides a possible explanation for apparently paradoxical cellular behaviors in the root meristem. For example, how auxin may induce and at the same time inhibit WOX5 expression. According to the model proposed here the hormonal regulation of WOX5 might depend on the cell type. Our results illustrate how non-linear multi-stable qualitative network models can aid at understanding how transcriptional regulators and hormonal signaling pathways are dynamically coupled and may underlie both the acquisition of cell fate and the emergence of hormonal activity profiles that arise during complex organ development.'),
(88403, 2017, 'plos', 'Representational models: A common framework for understanding encoding, pattern-component, and representational-similarity analysis', 'Diedrichsen, Jörn|Kriegeskorte, Nikolaus', 'Brain and Mind Institute, Department for Computer Science, Department for Statistical and Actuarial Science, Western University, London, Canada.|Cognitive and Brain Sciences Unit, Cambridge University, Cambridge, United Kingdom.', 'Canada|United Kingdom', 0, 'Algorithms|Brain|Computational Biology|Linear Models|Magnetic Resonance Imaging|Models, Neurological|Neurons', 'Journal Article', '10.1371/journal.pcbi.1005508', '28437426', 'Representational models specify how activity patterns in populations of neurons (or, more generally, in multivariate brain-activity measurements) relate to sensory stimuli, motor responses, or cognitive processes. In an experimental context, representational models can be defined as hypotheses about the distribution of activity profiles across experimental conditions. Currently, three different methods are being used to test such hypotheses: encoding analysis, pattern component modeling (PCM), and representational similarity analysis (RSA). Here we develop a common mathematical framework for understanding the relationship of these three methods, which share one core commonality: all three evaluate the second moment of the distribution of activity profiles, which determines the representational geometry, and thus how well any feature can be decoded from population activity. Using simulated data for three different experimental designs, we compare the power of the methods to adjudicate between competing representational models. PCM implements a likelihood-ratio test and therefore provides the most powerful test if its assumptions hold. However, the other two approaches-when conducted appropriately-can perform similarly. In encoding analysis, the linear model needs to be appropriately regularized, which effectively imposes a prior on the activity profiles. With such a prior, an encoding model specifies a well-defined distribution of activity profiles. In RSA, the unequal variances and statistical dependencies of the dissimilarity estimates need to be taken into account to reach near-optimal power in inference. The three methods render different aspects of the information explicit (e.g. single-response tuning in encoding analysis and population-response representational dissimilarity in RSA) and have specific advantages in terms of computational demands, ease of use, and extensibility. The three methods are properly construed as complementary components of a single data-analytical toolkit for understanding neural representations on the basis of multivariate brain-activity data.'),
(88404, 2017, 'plos', 'Intrinsically-generated fluctuating activity in excitatory-inhibitory networks', 'Mastrogiuseppe, Francesca|Ostojic, Srdjan', 'Laboratoire de Neurosciences Cognitives, INSERM U960, École Normale Supérieure - PSL Research University, Paris, France.|Laboratoire de Neurosciences Cognitives, INSERM U960, École Normale Supérieure - PSL Research University, Paris, France.', 'France|France', 22, 'Action Potentials|Computational Biology|Models, Neurological|Nerve Net|Neurons', 'Journal Article', '10.1371/journal.pcbi.1005498', '28437436', 'Recurrent networks of non-linear units display a variety of dynamical regimes depending on the structure of their synaptic connectivity. A particularly remarkable phenomenon is the appearance of strongly fluctuating, chaotic activity in networks of deterministic, but randomly connected rate units. How this type of intrinsically generated fluctuations appears in more realistic networks of spiking neurons has been a long standing question. To ease the comparison between rate and spiking networks, recent works investigated the dynamical regimes of randomly-connected rate networks with segregated excitatory and inhibitory populations, and firing rates constrained to be positive. These works derived general dynamical mean field (DMF) equations describing the fluctuating dynamics, but solved these equations only in the case of purely inhibitory networks. Using a simplified excitatory-inhibitory architecture in which DMF equations are more easily tractable, here we show that the presence of excitation qualitatively modifies the fluctuating activity compared to purely inhibitory networks. In presence of excitation, intrinsically generated fluctuations induce a strong increase in mean firing rates, a phenomenon that is much weaker in purely inhibitory networks. Excitation moreover induces two different fluctuating regimes: for moderate overall coupling, recurrent inhibition is sufficient to stabilize fluctuations, for strong coupling, firing rates are stabilized solely by the upper bound imposed on activity, even if inhibition is stronger than excitation. These results extend to more general network architectures, and to rate networks receiving noisy inputs mimicking spiking activity. Finally, we show that signatures of the second dynamical regime appear in networks of integrate-and-fire neurons.'),
(88405, 2017, 'plos', 'ESPRIT-Forest: Parallel clustering of massive amplicon sequence data in subquadratic time', 'Cai, Yunpeng|Zheng, Wei|Yao, Jin|Yang, Yujie|Mai, Volker|Mao, Qi|Sun, Yijun', 'Shenzhen Institutes of Advanced Technology, Chinese Academy of Sciences, Shenzhen, China.|Department of Computer Science and Engineering, The State University of New York at Buffalo, Buffalo, New York, United States of America.|Department of Microbiology and Immunology, The State University of New York at Buffalo, Buffalo, New York, United States of America.|Shenzhen Institutes of Advanced Technology, Chinese Academy of Sciences, Shenzhen, China.|Department of Epidemiology, University of Florida, Gainesville, Florida, United States of America.|Department of Microbiology and Immunology, The State University of New York at Buffalo, Buffalo, New York, United States of America.|Department of Computer Science and Engineering, The State University of New York at Buffalo, Buffalo, New York, United States of America.', 'China|United States|United States|China|United States|United States|United States', 8, 'Algorithms|Cluster Analysis|Computational Biology|Databases, Genetic|Humans|Microbiota|RNA, Ribosomal, 16S|Sequence Alignment|Sequence Analysis, RNA', 'Journal Article', '10.1371/journal.pcbi.1005518', '28437450', 'The rapid development of sequencing technology has led to an explosive accumulation of genomic sequence data. Clustering is often the first step to perform in sequence analysis, and hierarchical clustering is one of the most commonly used approaches for this purpose. However, it is currently computationally expensive to perform hierarchical clustering of extremely large sequence datasets due to its quadratic time and space complexities. In this paper we developed a new algorithm called ESPRIT-Forest for parallel hierarchical clustering of sequences. The algorithm achieves subquadratic time and space complexity and maintains a high clustering accuracy comparable to the standard method. The basic idea is to organize sequences into a pseudo-metric based partitioning tree for sub-linear time searching of nearest neighbors, and then use a new multiple-pair merging criterion to construct clusters in parallel using multiple threads. The new algorithm was tested on the human microbiome project (HMP) dataset, currently one of the largest published microbial 16S rRNA sequence dataset. Our experiment demonstrated that with the power of parallel computing it is now compu- tationally feasible to perform hierarchical clustering analysis of tens of millions of sequences. The software is available at http://www.acsu.buffalo.edu/xe2x88xbcyijunsun/lab/ESPRIT-Forest.html.');
INSERT INTO `papers` (`id`, `ano`, `journal`, `titulo`, `autores`, `afiliacao`, `pais`, `citacoes`, `palavra_chave`, `categorias`, `doi`, `pubmed`, `abstract`) VALUES
(88406, 2017, 'plos', 'Predicting explorative motor learning using decision-making and motor noise', 'Chen, Xiuli|Mohr, Kieran|Galea, Joseph M', 'School of Psychology, University of Birmingham, Birmingham, United Kingdom.|School of Psychology, University of Birmingham, Birmingham, United Kingdom.|School of Psychology, University of Birmingham, Birmingham, United Kingdom.', 'United Kingdom|United Kingdom|United Kingdom', 7, 'Adult|Algorithms|Computational Biology|Decision Making|Female|Humans|Learning|Male|Models, Neurological|Motor Activity|Psychomotor Performance|Young Adult', 'Journal Article', '10.1371/journal.pcbi.1005503', '28437451', 'A fundamental problem faced by humans is learning to select motor actions based on noisy sensory information and incomplete knowledge of the world. Recently, a number of authors have asked whether this type of motor learning problem might be very similar to a range of higher-level decision-making problems. If so, participant behaviour on a high-level decision-making task could be predictive of their performance during a motor learning task. To investigate this question, we studied performance during an explorative motor learning task and a decision-making task which had a similar underlying structure with the exception that it was not subject to motor (execution) noise. We also collected an independent measurement of each participants level of motor noise. Our analysis showed that explorative motor learning and decision-making could be modelled as the (approximately) optimal solution to a Partially Observable Markov Decision Process bounded by noisy neural information processing. The model was able to predict participant performance in motor learning by using parameters estimated from the decision-making task and the separate motor noise measurement. This suggests that explorative motor learning can be formalised as a sequential decision-making process that is adjusted for motor noise, and raises interesting questions regarding the neural origin of explorative motor learning.'),
(88407, 2017, 'plos', 'An aggregation-removal model for the formation and size determination of post-synaptic scaffold domains', 'Ranft, Jonas|Almeida, Leandro G|Rodriguez, Pamela C|Triller, Antoine|Hakim, Vincent', 'Laboratoire Physique Statistique, CNRS, Ecole Normale Supérieure, PSL Research University, Université Pierre et Marie Curie, Paris, France.|IBENS, Ecole Normale Supérieure, PSL Research University, CNRS, INSERM, Paris, France.|IBENS, Ecole Normale Supérieure, PSL Research University, CNRS, INSERM, Paris, France.|IBENS, Ecole Normale Supérieure, PSL Research University, CNRS, INSERM, Paris, France.|Laboratoire Physique Statistique, CNRS, Ecole Normale Supérieure, PSL Research University, Université Pierre et Marie Curie, Paris, France.', 'France|France|France|France|France', 10, 'Animals|Carrier Proteins|Cells, Cultured|Computer Simulation|Membrane Proteins|Models, Neurological|Neurons|Particle Size|Rats, Sprague-Dawley|Receptors, Glycine|Spinal Cord|Synapses', 'Journal Article', '10.1371/journal.pcbi.1005516', '28437460', 'The formation and stability of synapses are key questions in neuroscience. Post-synaptic domains have been classically conceived as resulting from local insertion and turnover of proteins at the synapse. However, insertion is likely to occur outside the post-synaptic domains and advances in single-molecule imaging have shown that proteins diffuse in the plane of the membrane prior to their accumulation at synapses. We quantitatively investigated this scenario using computer simulations and mathematical analysis, taking for definiteness the specific case of inhibitory synapse components, i.e., the glycine receptor (GlyR) and the associated gephyrin scaffolding protein. The observed domain sizes of scaffold clusters can be explained by a dynamic balance between the aggregation of gephyrin proteins diffusing while bound to GlyR and their turnover at the neuron membrane. We also predict the existence of extrasynaptic clusters with a characteristic size distribution that significantly contribute to the size fluctuations of synaptic domains. New super-resolution data for gephyrin proteins established the existence of extrasynaptic clusters the sizes of which are consistent with the model predictions in a range of model parameters. At a general level, our results highlight aggregation with removal as a non-equilibrium phase separation which produces structures of tunable size.'),
(88408, 2017, 'plos', 'Variable habitat conditions drive species covariation in the human microbiota', 'Fisher, Charles K|Mora, Thierry|Walczak, Aleksandra M', 'Laboratoire de physique théorique, CNRS, UPMC and École normale supérieure, Paris, France.|Laboratoire de physique statistique, CNRS, UPMC and École normale supérieure, Paris, France.|Laboratoire de physique théorique, CNRS, UPMC and École normale supérieure, Paris, France.', 'France|France|France', 6, 'Computational Biology|Ecosystem|Humans|Microbiota|Models, Biological|Species Specificity', 'Journal Article', '10.1371/journal.pcbi.1005435', '28448493', 'Two species with similar resource requirements respond in a characteristic way to variations in their habitat-their abundances rise and fall in concert. We use this idea to learn how bacterial populations in the microbiota respond to habitat conditions that vary from person-to-person across the human population. Our mathematical framework shows that habitat fluctuations are sufficient for explaining intra-bodysite correlations in relative species abundances from the Human Microbiome Project. We explicitly show that the relative abundances of closely related species are positively correlated and can be predicted from taxonomic relationships. We identify a small set of functional pathways related to metabolism and maintenance of the cell wall that form the basis of a common resource sharing niche space of the human microbiota.'),
(88409, 2017, 'plos', 'Correction: Spatial separation of two different pathways accounting for the generation of calcium signals in astrocytes', 'PLOS Computational Biology Staff', 'Laboratoire de physique théorique, CNRS, UPMC and École normale supérieure, Paris, France.', 'France', 0, '-', 'Published Erratum', '10.1371/journal.pcbi.1005514', '28448496', '[This corrects the article DOI: 10.1371/journal.pcbi.1005377.].'),
(88410, 2017, 'plos', 'Personalized glucose forecasting for type 2 diabetes using data assimilation', 'Albers, David J|Levine, Matthew|Gluckman, Bruce|Ginsberg, Henry|Hripcsak, George|Mamykina, Lena', 'Department of Biomedical Informatics, Columbia University, New York, New York, United States of America.|Department of Biomedical Informatics, Columbia University, New York, New York, United States of America.|Departments of Engineering Sciences and Mechanics, Neurosurgery, and Biomedical Engineering, Pennsylvania State University, University Park, Pennsylvania, United States of America.|Department of Medicine, Columbia University, New York, New York, United States of America.|Department of Biomedical Informatics, Columbia University, New York, New York, United States of America.|Department of Biomedical Informatics, Columbia University, New York, New York, United States of America.', 'United States|United States|United States|United States|United States|United States', 23, 'Adult|Algorithms|Blood Glucose|Computational Biology|Diabetes Mellitus, Type 2|Female|Humans|Insulin|Male|Patient-Specific Modeling', 'Journal Article', '10.1371/journal.pcbi.1005232', '28448498', 'Type 2 diabetes leads to premature death and reduced quality of life for 8% of Americans. Nutrition management is critical to maintaining glycemic control, yet it is difficult to achieve due to the high individual differences in glycemic response to nutrition. Anticipating glycemic impact of different meals can be challenging not only for individuals with diabetes, but also for expert diabetes educators. Personalized computational models that can accurately forecast an impact of a given meal on an individuals blood glucose levels can serve as the engine for a new generation of decision support tools for individuals with diabetes. However, to be useful in practice, these computational engines need to generate accurate forecasts based on limited datasets consistent with typical self-monitoring practices of individuals with type 2 diabetes. This paper uses three forecasting machines: (i) data assimilation, a technique borrowed from atmospheric physics and engineering that uses Bayesian modeling to infuse data with human knowledge represented in a mechanistic model, to generate real-time, personalized, adaptable glucose forecasts, (ii) model averaging of data assimilation output, and (iii) dynamical Gaussian process model regression. The proposed data assimilation machine, the primary focus of the paper, uses a modified dual unscented Kalman filter to estimate states and parameters, personalizing the mechanistic models. Model selection is used to make a personalized model selection for the individual and their measurement characteristics. The data assimilation forecasts are empirically evaluated against actual postprandial glucose measurements captured by individuals with type 2 diabetes, and against predictions generated by experienced diabetes educators after reviewing a set of historical nutritional records and glucose measurements for the same individual. The evaluation suggests that the data assimilation forecasts compare well with specific glucose measurements and match or exceed in accuracy expert forecasts. We conclude by examining ways to present predictions as forecast-derived range quantities and evaluate the comparative advantages of these ranges.'),
(88411, 2017, 'plos', 'When do correlations increase with firing rates in recurrent networks?', 'Barreiro, Andrea K|Ly, Cheng', 'Department of Mathematics, Southern Methodist University, Dallas, Texas, United States of America.|Department of Statistical Sciences and Operations Research, Virginia Commonwealth University, Richmond, Virginia, United States of America.', 'United States|United States', 6, 'Action Potentials|Animals|Cerebral Cortex|Computational Biology|Computer Simulation|Mice|Models, Neurological|Nerve Net', 'Journal Article', '10.1371/journal.pcbi.1005506', '28448499', 'A central question in neuroscience is to understand how noisy firing patterns are used to transmit information. Because neural spiking is noisy, spiking patterns are often quantified via pairwise correlations, or the probability that two cells will spike coincidentally, above and beyond their baseline firing rate. One observation frequently made in experiments, is that correlations can increase systematically with firing rate. Theoretical studies have determined that stimulus-dependent correlations that increase with firing rate can have beneficial effects on information coding, however, we still have an incomplete understanding of what circuit mechanisms do, or do not, produce this correlation-firing rate relationship. Here, we studied the relationship between pairwise correlations and firing rates in recurrently coupled excitatory-inhibitory spiking networks with conductance-based synapses. We found that with stronger excitatory coupling, a positive relationship emerged between pairwise correlations and firing rates. To explain these findings, we used linear response theory to predict the full correlation matrix and to decompose correlations in terms of graph motifs. We then used this decomposition to explain why covariation of correlations with firing rate-a relationship previously explained in feedforward networks driven by correlated input-emerges in some recurrent networks but not in others. Furthermore, when correlations covary with firing rate, this relationship is reflected in low-rank structure in the correlation matrix.'),
(88412, 2017, 'plos', 'Slow diffusive dynamics in a chaotic balanced neural network', 'Shaham, Nimrod|Burak, Yoram', 'Racah Institute of Physics, The Hebrew University of Jerusalem, Jerusalem, Israel.|Racah Institute of Physics, The Hebrew University of Jerusalem, Jerusalem, Israel.', 'Israel|Israel', 3, 'Animals|Computational Biology|Computer Simulation|Diffusion|Memory|Models, Neurological|Nerve Net|Neurons', 'Journal Article', '10.1371/journal.pcbi.1005505', '28459813', 'It has been proposed that neural noise in the cortex arises from chaotic dynamics in the balanced state: in this model of cortical dynamics, the excitatory and inhibitory inputs to each neuron approximately cancel, and activity is driven by fluctuations of the synaptic inputs around their mean. It remains unclear whether neural networks in the balanced state can perform tasks that are highly sensitive to noise, such as storage of continuous parameters in working memory, while also accounting for the irregular behavior of single neurons. Here we show that continuous parameter working memory can be maintained in the balanced state, in a neural circuit with a simple network architecture. We show analytically that in the limit of an infinite network, the dynamics generated by this architecture are characterized by a continuous set of steady balanced states, allowing for the indefinite storage of a continuous parameter. In finite networks, we show that the chaotic noise drives diffusive motion along the approximate attractor, which gradually degrades the stored memory. We analyze the dynamics and show that the slow diffusive motion induces slowly decaying temporal cross correlations in the activity, which differ substantially from those previously described in the balanced state. We calculate the diffusivity, and show that it is inversely proportional to the system size. For large enough (but realistic) neural population sizes, and with suitable tuning of the network connections, the proposed balanced network can sustain continuous parameter values in memory over time scales larger by several orders of magnitude than the single neuron time scale.'),
(88413, 2017, 'plos', 'Co-occurring protein phosphorylation are functionally associated', 'Li, Ying|Zhou, Xueya|Zhai, Zichao|Li, Tingting', 'Department of Biomedical Informatics, School of Basic Medical Sciences, Peking University Health Science Center, Beijing, China.|Department of Psychiatry and Centre for Genomic Sciences, Li Ka Shing Faculty of Medicine, The University of Hong Kong, Hong Kong SAR, China.|Department of Biomedical Informatics, School of Basic Medical Sciences, Peking University Health Science Center, Beijing, China.|Department of Biomedical Informatics, School of Basic Medical Sciences, Peking University Health Science Center, Beijing, China.', 'China|China|China|China', 0, 'Animals|Cell Line, Tumor|Databases, Protein|Humans|Mice|Phosphorylation|Protein Processing, Post-Translational|Proteins|Proteome|Proteomics', 'Journal Article', '10.1371/journal.pcbi.1005502', '28459814', 'Post-translational modifications (PTMs) add a further layer of complexity to the proteome and regulate a wide range of cellular protein functions. With the increasing number of known PTM sites, it becomes imperative to understand their functional interplays. In this study, we proposed a novel analytical strategy to explore functional relationships between PTM sites by testing their tendency to be modified together (co-occurrence) under the same condition, and applied it to proteome-wide human phosphorylation data collected under 88 different laboratory or physiological conditions. Co-occurring phosphorylation occurs significantly more frequently than randomly expected and include many known examples of cross-talk or functional connections. Such pairs, either within the same phosphoprotein or between interacting partners, are more likely to be in sequence or structural proximity, be phosphorylated by the same kinases, participate in similar biological processes, and show residue co-evolution across vertebrates. In addition, we also found that their co-occurrence states tend to be conserved in orthologous phosphosites in the mouse proteome. Together, our results support that the co-occurring phosphorylation are functionally associated. Comparison with existing methods further suggests that co-occurrence analysis can be a useful complement to uncover novel functional associations between PTM sites.'),
(88414, 2017, 'plos', 'phyC: Clustering cancer evolutionary trees', 'Matsui, Yusuke|Niida, Atsushi|Uchi, Ryutaro|Mimori, Koshi|Miyano, Satoru|Shimamura, Teppei', 'Division of Systems Biology, Nagoya University Graduate School of Medicine, Nagoya, Japan.|Division of Health Medical Computational Science, Health Intelligence Center, The Institute of Medical Science, The University of Tokyo, Tokyo, Japan.|Department of Otorhinolaryngology, Graduate School of Medical Sciences, Kyushu University, Fukuoka, Japan.|Department of Surgery, Kyushu University Beppu Hospital, Beppu, Japan.|Laboratory of DNA Information Analysis, Human Genome Center, Institute of Medical Science, The University of Tokyo, Tokyo, Japan.|Division of Systems Biology, Nagoya University Graduate School of Medicine, Nagoya, Japan.', 'Japan|Japan|Japan|Japan|Japan|Japan', 5, 'Carcinoma, Non-Small-Cell Lung|Carcinoma, Renal Cell|Cluster Analysis|Computational Biology|Evolution, Molecular|Humans|Lung Neoplasms|Neoplasms|Software', 'Journal Article', '10.1371/journal.pcbi.1005509', '28459850', 'Multi-regional sequencing provides new opportunities to investigate genetic heterogeneity within or between common tumors from an evolutionary perspective. Several state-of-the-art methods have been proposed for reconstructing cancer evolutionary trees based on multi-regional sequencing data to develop models of cancer evolution. However, there have been few studies on comparisons of a set of cancer evolutionary trees. We propose a clustering method (phyC) for cancer evolutionary trees, in which sub-groups of the trees are identified based on topology and edge length attributes. For interpretation, we also propose a method for evaluating the sub-clonal diversity of trees in the clusters, which provides insight into the acceleration of sub-clonal expansion. Simulation showed that the proposed method can detect true clusters with sufficient accuracy. Application of the method to actual multi-regional sequencing data of clear cell renal carcinoma and non-small cell lung cancer allowed for the detection of clusters related to cancer type or phenotype. phyC is implemented with R(xe2x89xa53.2.2) and is available from https://github.com/ymatts/phyC.'),
(88415, 2017, 'plos', 'Nucleotide-time alignment for molecular recorders', 'Cybulski, Thaddeus R|Boyden, Edward S|Church, George M|Tyo, Keith E J|Kording, Konrad P', 'Department of Physical Medicine and Rehabilitation, Rehabilitation Institute of Chicago, Northwestern University, Chicago, Illinois, United States of America.|Media Lab, Massachusetts Institute of Technology, Cambridge, Massachusetts, United States of America.|Biophysics Program, Harvard University, Boston, Massachusetts, United States of America.|Department of Chemical and Biological Engineering, Northwestern University, Evanston, Illinois, United States of America.|Department of Physical Medicine and Rehabilitation, Rehabilitation Institute of Chicago, Northwestern University, Chicago, Illinois, United States of America.', 'United States|United States|United States|United States|United States', 0, 'Algorithms|Calcium|Computational Biology|Computer Simulation|DNA|DNA-Directed DNA Polymerase|Models, Biological|Neurons|Neurosciences|Nucleotides|Single-Cell Analysis|Time Factors', 'Journal Article', '10.1371/journal.pcbi.1005483', '28459860', 'Using a DNA polymerase to record intracellular calcium levels has been proposed as a novel neural recording technique, promising massive-scale, single-cell resolution monitoring of large portions of the brain. This technique relies on local storage of neural activity in strands of DNA, followed by offline analysis of that DNA. In simple implementations of this scheme, the time when each nucleotide was written cannot be determined directly by post-hoc DNA sequencing, the timing data must be estimated instead. Here, we use a Dynamic Time Warping-based algorithm to perform this estimation, exploiting correlations between neural activity and observed experimental variables to translate DNA-based signals to an estimate of neural activity over time. This algorithm improves the parallelizability of traditional Dynamic Time Warping, allowing several-fold increases in computation speed. The algorithm also provides a solution to several critical problems with the molecular recording paradigm: determining recording start times and coping with DNA polymerase pausing. The algorithm can generally locate DNA-based records to within <10% of a recording window, allowing for the estimation of unobserved incorporation times and latent neural tunings. We apply our technique to an in silico motor control neuroscience experiment, using the algorithm to estimate both timings of DNA-based data and the directional tuning of motor cortical cells during a center-out reaching task. We also use this algorithm to explore the impact of polymerase characteristics on system performance, determining the precision of a molecular recorder as a function of its kinetic and error-generating properties. We find useful ranges of properties for DNA polymerase-based recorders, providing guidance for future protein engineering attempts. This work demonstrates a useful general extension to dynamic alignment algorithms, as well as direct applications of that extension toward the development of molecular recorders, providing a necessary stepping stone for future biological work.'),
(88416, 2017, 'plos', 'Modelling of the cancer cell cycle as a tool for rational drug development: A systems pharmacology approach to cyclotherapy', 'Jackson, Robert C|Di Veroli, Giovanni Y|Koh, Siang-Boon|Goldlust, Ian|Richards, Frances M|Jodrell, Duncan I', 'Pharmacometrics Ltd, Cambridge, United Kingdom.|Cancer Research UK Cambridge Institute, University of Cambridge, Cambridge, United Kingdom.|Cancer Research UK Cambridge Institute, University of Cambridge, Cambridge, United Kingdom.|Cancer Research UK Cambridge Institute, University of Cambridge, Cambridge, United Kingdom.|Cancer Research UK Cambridge Institute, University of Cambridge, Cambridge, United Kingdom.|Cancer Research UK Cambridge Institute, University of Cambridge, Cambridge, United Kingdom.', 'United Kingdom|United Kingdom|United Kingdom|United Kingdom|United Kingdom|United Kingdom', 3, 'Antineoplastic Agents|Cell Cycle Checkpoints|Cell Line, Tumor|Computational Biology|Drug Discovery|Humans|Models, Biological|Neoplasms|Pharmacology', 'Journal Article', '10.1371/journal.pcbi.1005529', '28467408', 'The dynamic of cancer is intimately linked to a dysregulation of the cell cycle and signalling pathways. It has been argued that selectivity of treatments could exploit loss of checkpoint function in cancer cells, a concept termed cyclotherapy. Quantitative approaches that describe these dysregulations can provide guidance in the design of novel or existing cancer therapies. We describe and illustrate this strategy via a mathematical model of the cell cycle that includes descriptions of the G1-S checkpoint and the spindle assembly checkpoint (SAC), the EGF signalling pathway and apoptosis. We incorporated sites of action of four drugs (palbociclib, gemcitabine, paclitaxel and actinomycin D) to illustrate potential applications of this approach. We show how drug effects on multiple cell populations can be simulated, facilitating simultaneous prediction of effects on normal and transformed cells. The consequences of aberrant signalling pathways or of altered expression of pro- or anti-apoptotic proteins can thus be compared. We suggest that this approach, particularly if used in conjunction with pharmacokinetic modelling, could be used to predict effects of specific oncogene expression patterns on drug response. The strategy could be used to search for synthetic lethality and optimise combination protocol designs.'),
(88417, 2017, 'plos', 'Mechanisms underlying different onset patterns of focal seizures', 'Wang, Yujiang|Trevelyan, Andrew J|Valentin, Antonio|Alarcon, Gonzalo|Taylor, Peter N|Kaiser, Marcus', 'Interdisciplinary Computing and Complex BioSystems (ICOS) research group, School of Computing Science, Newcastle University, Newcastle upon Tyne, United Kingdom.|Institute of Neuroscience, Newcastle University, Newcastle upon Tyne, United Kingdom.|Department of Basic and Clinical Neuroscience, Institute of Psychiatry, Psychology and Neuroscience, Kings College London, London, United Kingdom.|Department of Basic and Clinical Neuroscience, Institute of Psychiatry, Psychology and Neuroscience, Kings College London, London, United Kingdom.|Interdisciplinary Computing and Complex BioSystems (ICOS) research group, School of Computing Science, Newcastle University, Newcastle upon Tyne, United Kingdom.|Interdisciplinary Computing and Complex BioSystems (ICOS) research group, School of Computing Science, Newcastle University, Newcastle upon Tyne, United Kingdom.', 'United Kingdom|United Kingdom|United Kingdom|United Kingdom|United Kingdom|United Kingdom', 20, 'Brain|Computational Biology|Computer Simulation|Humans|Models, Neurological|Seizures', 'Journal Article', '10.1371/journal.pcbi.1005475', '28472032', 'Focal seizures are episodes of pathological brain activity that appear to arise from a localised area of the brain. The onset patterns of focal seizure activity have been studied intensively, and they have largely been distinguished into two types-low amplitude fast oscillations (LAF), or high amplitude spikes (HAS). Here we explore whether these two patterns arise from fundamentally different mechanisms. Here, we use a previously established computational model of neocortical tissue, and validate it as an adequate model using clinical recordings of focal seizures. We then reproduce the two onset patterns in their most defining properties and investigate the possible mechanisms underlying the different focal seizure onset patterns in the model. We show that the two patterns are associated with different mechanisms at the spatial scale of a single ECoG electrode. The LAF onset is initiated by independent patches of localised activity, which slowly invade the surrounding tissue and coalesce over time. In contrast, the HAS onset is a global, systemic transition to a coexisting seizure state triggered by a local event. We find that such a global transition is enabled by an increase in the excitability of the healthy surrounding tissue, which by itself does not generate seizures, but can support seizure activity when incited. In our simulations, the difference in surrounding tissue excitability also offers a simple explanation of the clinically reported difference in surgical outcomes. Finally, we demonstrate in the model how changes in tissue excitability could be elucidated, in principle, using active stimulation. Taken together, our modelling results suggest that the excitability of the tissue surrounding the seizure core may play a determining role in the seizure onset pattern, as well as in the surgical outcome.'),
(88418, 2017, 'plos', 'Ten simple rules to make the most out of your undergraduate research career', 'Yu, Megan|Kuo, Yu-Min', 'University of Virginia, Charlottesville, Virginia, United States of America.|Department of Cell Biology and Anatomy, College of Medicine, National Cheng Kung University, Tainan, Taiwan.', 'United States|-', 4, 'Algorithms|Career Choice|Curriculum|Education, Professional|Research', 'Editorial', '10.1371/journal.pcbi.1005484', '28472033', '-'),
(88419, 2017, 'plos', 'Ten simple rules to consider regarding preprint submission', 'Bourne, Philip E|Polka, Jessica K|Vale, Ronald D|Kiley, Robert', 'Office of the Director, The National Institutes of Health, Bethesda, Maryland, United States of America.|Whitehead Institute, Cambridge, Massachusetts, United States of America.|Department of Cellular and Molecular Pharmacology and the Howard Hughes Medical Institute, University of California San Francisco, San Francisco, California, United States of America.|Wellcome Library, The Wellcome Trust, London, United Kingdom.', 'United States|United States|United States|United Kingdom', 30, 'Algorithms|Checklist|Documentation|Information Dissemination|Peer Review, Research|Periodicals as Topic|Writing', 'Editorial', '10.1371/journal.pcbi.1005473', '28472041', '-'),
(88420, 2017, 'plos', 'A mathematical model coupling polarity signaling to cell adhesion explains diverse cell migration patterns', 'Holmes, William R|Park, JinSeok|Levchenko, Andre|Edelstein-Keshet, Leah', 'Department of Physics and Astronomy, Vanderbilt University, Nashville, Tennessee, United States of America.|Department of Biomedical Engineering, Yale University, New Haven, Connecticut, United States of America.|Department of Biomedical Engineering, Yale University, New Haven, Connecticut, United States of America.|Department of Mathematics, University of British Columbia, Vancouver BC, Canada.', 'United States|United States|United States|Canada', 19, 'Cell Physiological Phenomena|Computational Biology|Extracellular Matrix|Models, Biological|rho GTP-Binding Proteins', 'Journal Article', '10.1371/journal.pcbi.1005524', '28472054', 'Protrusion and retraction of lamellipodia are common features of eukaryotic cell motility. As a cell migrates through its extracellular matrix (ECM), lamellipod growth increases cell-ECM contact area and enhances engagement of integrin receptors, locally amplifying ECM input to internal signaling cascades. In contrast, contraction of lamellipodia results in reduced integrin engagement that dampens the level of ECM-induced signaling. These changes in cell shape are both influenced by, and feed back onto ECM signaling. Motivated by experimental observations on melanoma cells lines (1205Lu and SBcl2) migrating on fibronectin (FN) coated topographic substrates (anisotropic post-density arrays), we probe this interplay between intracellular and ECM signaling. Experimentally, cells exhibited one of three lamellipodial dynamics: persistently polarized, random, or oscillatory, with competing lamellipodia oscillating out of phase (Park et al., 2017). Pharmacological treatments, changes in FN density, and substrate topography all affected the fraction of cells exhibiting these behaviours. We use these observations as constraints to test a sequence of hypotheses for how intracellular (GTPase) and ECM signaling jointly regulate lamellipodial dynamics. The models encoding these hypotheses are predicated on mutually antagonistic Rac-Rho signaling, Rac-mediated protrusion (via activation of Arp2/3 actin nucleation) and Rho-mediated contraction (via ROCK phosphorylation of myosin light chain), which are coupled to ECM signaling that is modulated by protrusion/contraction. By testing each model against experimental observations, we identify how the signaling layers interact to generate the diverse range of cell behaviors, and how various molecular perturbations and changes in ECM signaling modulate the fraction of cells exhibiting each. We identify several factors that play distinct but critical roles in generating the observed dynamic: (1) competition between lamellipodia for shared pools of Rac and Rho, (2) activation of RhoA by ECM signaling, and (3) feedback from lamellipodial growth or contraction to cell-ECM contact area and therefore to the ECM signaling level.'),
(88421, 2017, 'plos', 'Top-down control of cortical gamma-band communication via pulvinar induced phase shifts in the alpha rhythm', 'Quax, Silvan|Jensen, Ole|Tiesinga, Paul', 'Department of Neuroinformatics, Donders Institute, Radboud University, Nijmegen, The Netherlands.|School of Psychology, Centre for Human Brain Health, University of Birmingham, Birmingham, United Kingdom.|Department of Neuroinformatics, Donders Institute, Radboud University, Nijmegen, The Netherlands.', 'Netherlands|United Kingdom|Netherlands', 15, 'Action Potentials|Alpha Rhythm|Animals|Computational Biology|Computer Simulation|Gamma Rhythm|Humans|Models, Neurological|Neural Pathways|Pulvinar', 'Journal Article', '10.1371/journal.pcbi.1005519', '28472057', 'Selective routing of information between cortical areas is required in order to combine different sources of information according to cognitive demand. Recent experiments have suggested that alpha band activity originating from the pulvinar coordinates this inter-areal cortical communication. Using a computer model we investigated whether top-down induced shifts in the relative alpha phase between two cortical areas could modulate cortical communication, quantified in terms of changes in gamma band coherence between them. The network model was comprised of two uni-directionally connected neuronal populations of spiking neurons, each representing a cortical area. We find that the phase difference of the alpha oscillations modulating the two neuronal populations strongly affected the interregional gamma-band neuronal coherence. We confirmed that a higher gamma band coherence also resulted in more efficient transmission of spiking information between cortical areas, thereby confirming the value of gamma coherence as a proxy for cortical information transmission. In a model where both neuronal populations were connected bi-directionally, the relative alpha phase determined the directionality of communication between the populations. Our results show the feasibility of a physiological realistic mechanism for routing information in the brain based on coupled oscillations. Our model results in a set of testable predictions regarding phase shifts in alpha oscillations under different task demands requiring experimental quantification of neuronal oscillations in different regions in e.g. attention paradigms.'),
(88422, 2017, 'plos', 'Widespread position-specific conservation of synonymous rare codons within coding sequences', 'Chaney, Julie L|Steele, Aaron|Carmichael, Rory|Rodriguez, Anabel|Specht, Alicia T|Ngo, Kim|Li, Jun|Emrich, Scott|Clark, Patricia L', 'Department of Chemistry & Biochemistry, University of Notre Dame, Notre Dame, Indiana, United States of America.|Department of Computer Science & Engineering, University of Notre Dame, Notre Dame, Indiana, United States of America.|Department of Computer Science & Engineering, University of Notre Dame, Notre Dame, Indiana, United States of America.|Department of Chemistry & Biochemistry, University of Notre Dame, Notre Dame, Indiana, United States of America.|Department of Applied and Computational Mathematics & Statistics, University of Notre Dame, Notre Dame, Indiana, United States of America.|Department of Chemistry & Biochemistry, University of Notre Dame, Notre Dame, Indiana, United States of America.|Department of Applied and Computational Mathematics & Statistics, University of Notre Dame, Notre Dame, Indiana, United States of America.|Department of Computer Science & Engineering, University of Notre Dame, Notre Dame, Indiana, United States of America.|Department of Chemistry & Biochemistry, University of Notre Dame, Notre Dame, Indiana, United States of America.', 'India|India|India|India|India|India|India|India|India', 36, 'Amino Acid Sequence|Codon|Computational Biology|Conserved Sequence|Models, Molecular|Open Reading Frames|RNA, Messenger', 'Journal Article', '10.1371/journal.pcbi.1005531', '28475588', 'Synonymous rare codons are considered to be sub-optimal for gene expression because they are translated more slowly than common codons. Yet surprisingly, many protein coding sequences include large clusters of synonymous rare codons. Rare codons at the 5 terminus of coding sequences have been shown to increase translational efficiency. Although a general functional role for synonymous rare codons farther within coding sequences has not yet been established, several recent reports have identified rare-to-common synonymous codon substitutions that impair folding of the encoded protein. Here we test the hypothesis that although the usage frequencies of synonymous codons change from organism to organism, codon rarity will be conserved at specific positions in a set of homologous coding sequences, for example to tune translation rate without altering a protein sequence. Such conservation of rarity-rather than specific codon identity-could coordinate co-translational folding of the encoded protein. We demonstrate that many rare codon cluster positions are indeed conserved within homologous coding sequences across diverse eukaryotic, bacterial, and archaeal species, suggesting they result from positive selection and have a functional role. Most conserved rare codon clusters occur within rather than between conserved protein domains, challenging the view that their primary function is to facilitate co-translational folding after synthesis of an autonomous structural unit. Instead, many conserved rare codon clusters separate smaller protein structural motifs within structural domains. These smaller motifs typically fold faster than an entire domain, on a time scale more consistent with translation rate modulation by synonymous codon usage. While proteins with conserved rare codon clusters are structurally and functionally diverse, they are enriched in functions associated with organism growth and development, suggesting an important role for synonymous codon usage in organism physiology. The identification of conserved rare codon clusters advances our understanding of distinct, functional roles for otherwise synonymous codons and enables experimental testing of the impact of synonymous codon usage on the production of functional proteins.'),
(88423, 2017, 'plos', 'MAGERI: Computational pipeline for molecular-barcoded targeted resequencing', 'Shugay, Mikhail|Zaretsky, Andrew R|Shagin, Dmitriy A|Shagina, Irina A|Volchenkov, Ivan A|Shelenkov, Andrew A|Lebedin, Mikhail Y|Bagaev, Dmitriy V|Lukyanov, Sergey|Chudakov, Dmitriy M', 'Shemyakin-Ovchinnikov Institute of bioorganic chemistry RAS, Miklukho-Maklaya 16/10, Moscow, Russia.|Shemyakin-Ovchinnikov Institute of bioorganic chemistry RAS, Miklukho-Maklaya 16/10, Moscow, Russia.|Shemyakin-Ovchinnikov Institute of bioorganic chemistry RAS, Miklukho-Maklaya 16/10, Moscow, Russia.|Shemyakin-Ovchinnikov Institute of bioorganic chemistry RAS, Miklukho-Maklaya 16/10, Moscow, Russia.|Pirogov Russian National Research Medical University, Ostrovityanova 1, Moscow, Russia.|Pirogov Russian National Research Medical University, Ostrovityanova 1, Moscow, Russia.|Shemyakin-Ovchinnikov Institute of bioorganic chemistry RAS, Miklukho-Maklaya 16/10, Moscow, Russia.|Shemyakin-Ovchinnikov Institute of bioorganic chemistry RAS, Miklukho-Maklaya 16/10, Moscow, Russia.|Shemyakin-Ovchinnikov Institute of bioorganic chemistry RAS, Miklukho-Maklaya 16/10, Moscow, Russia.|Shemyakin-Ovchinnikov Institute of bioorganic chemistry RAS, Miklukho-Maklaya 16/10, Moscow, Russia.', '-|-|-|-|-|-|-|-|-|-', 16, 'Biomarkers, Tumor|Computational Biology|Databases, Genetic|High-Throughput Nucleotide Sequencing|Humans|Neoplasms|RNA, Viral|Sequence Analysis, DNA|Sequence Analysis, RNA|Software', 'Journal Article', '10.1371/journal.pcbi.1005480', '28475621', 'Unique molecular identifiers (UMIs) show outstanding performance in targeted high-throughput resequencing, being the most promising approach for the accurate identification of rare variants in complex DNA samples. This approach has application in multiple areas, including cancer diagnostics, thus demanding dedicated software and algorithms. Here we introduce MAGERI, a computational pipeline that efficiently handles all caveats of UMI-based analysis to obtain high-fidelity mutation profiles and call ultra-rare variants. Using an extensive set of benchmark datasets including gold-standard biological samples with known variant frequencies, cell-free DNA from tumor patient blood samples and publicly available UMI-encoded datasets we demonstrate that our method is both robust and efficient in calling rare variants. The versatility of our software is supported by accurate results obtained for both tumor DNA and viral RNA samples in datasets prepared using three different UMI-based protocols.'),
(88424, 2017, 'plos', 'A systems-level model reveals that 1,2-Propanediol utilization microcompartments enhance pathway flux through intermediate sequestration', 'Jakobson, Christopher M|Tullman-Ercek, Danielle|Slininger, Marilyn F|Mangan, Niall M', 'Department of Chemical and Biological Engineering, Northwestern University, Evanston, IL, USA.|Department of Chemical and Biological Engineering, Northwestern University, Evanston, IL, USA.|Department of Chemical and Biomolecular Engineering, University of California, Berkeley, Berkeley, CA, USA.|Department of Applied Mathematics, University of Washington, Seattle, WA, USA.', 'United States|United States|United States|United States', 22, 'Cellular Microenvironment|Intracellular Space|Metabolic Networks and Pathways|Models, Biological|Propylene Glycol|Salmonella enterica|Systems Biology', 'Journal Article', '10.1371/journal.pcbi.1005525', '28475631', 'The spatial organization of metabolism is common to all domains of life. Enteric and other bacteria use subcellular organelles known as bacterial microcompartments to spatially organize the metabolism of pathogenicity-relevant carbon sources, such as 1,2-propanediol. The organelles are thought to sequester a private cofactor pool, minimize the effects of toxic intermediates, and enhance flux through the encapsulated metabolic pathways. We develop a mathematical model of the function of the 1,2-propanediol utilization microcompartment of Salmonella enterica and use it to analyze the function of the microcompartment organelles in detail. Our model makes accurate estimates of doubling times based on an optimized compartment shell permeability determined by maximizing metabolic flux in the model. The compartments function primarily to decouple cytosolic intermediate concentrations from the concentrations in the microcompartment, allowing significant enhancement in pathway flux by the generation of large concentration gradients across the microcompartment shell. We find that selective permeability of the microcompartment shell is not absolutely necessary, but is often beneficial in establishing this intermediate-trapping function. Our findings also implicate active transport of the 1,2-propanediol substrate under conditions of low external substrate concentration, and we present a mathematical bound, in terms of external 1,2-propanediol substrate concentration and diffusive rates, on when active transport of the substrate is advantageous. By allowing us to predict experimentally inaccessible aspects of microcompartment function, such as intra-microcompartment metabolite concentrations, our model presents avenues for future research and underscores the importance of carefully considering changes in external metabolite concentrations and other conditions during batch cultures. Our results also suggest that the encapsulation of heterologous pathways in bacterial microcompartments might yield significant benefits for pathway flux, as well as for toxicity mitigation.'),
(88425, 2017, 'plos', 'Post-transcriptional regulation across human tissues', 'Franks, Alexander|Airoldi, Edoardo|Slavov, Nikolai', 'Department of Statistics, University of Washington, Seattle, WA 98195, USA.|Department of Statistics, Harvard University, Cambridge, MA 02138, USA.|Department of Bioengineering, Northeastern University, Boston, MA 02115, USA.', 'United States|United States|United States', 48, 'Databases, Protein|Gene Expression Regulation|Humans|Organ Specificity|Proteome|RNA, Messenger|Transcription, Genetic', 'Journal Article', '10.1371/journal.pcbi.1005535', '28481885', 'Transcriptional and post-transcriptional regulation shape tissue-type-specific proteomes, but their relative contributions remain contested. Estimates of the factors determining protein levels in human tissues do not distinguish between (i) the factors determining the variability between the abundances of different proteins, i.e., mean-level-variability and, (ii) the factors determining the physiological variability of the same protein across different tissue types, i.e., across-tissues variability. We sought to estimate the contribution of transcript levels to these two orthogonal sources of variability, and found that scaled mRNA levels can account for most of the mean-level-variability but not necessarily for across-tissues variability. The reliable quantification of the latter estimate is limited by substantial measurement noise. However, protein-to-mRNA ratios exhibit substantial across-tissues variability that is functionally concerted and reproducible across different datasets, suggesting extensive post-transcriptional regulation. These results caution against estimating protein fold-changes from mRNA fold-changes between different cell-types, and highlight the contribution of post-transcriptional regulation to shaping tissue-type-specific proteomes.'),
(88426, 2017, 'plos', 'Epidemiological modeling of Trypanosoma cruzi: Low stercorarian transmission and failure of host adaptive immunity explain the frequency of mixed infections in humans', 'Tomasini, Nicolás|Ragone, Paula Gabriela|Gourbière, Sébastien|Aparicio, Juan Pablo|Diosque, Patricio', 'Instituto de Patología Experimental, Facultad de Ciencias de la Salud, CONICET, Universidad Nacional de Salta, Salta, Argentina.|Instituto de Patología Experimental, Facultad de Ciencias de la Salud, CONICET, Universidad Nacional de Salta, Salta, Argentina.|UMR 228 ESPACE-DEV-IMAGES, Institut de Modélisation et dAnalyses en Géo-Environnement et Santé, Université de Perpignan Via Domitia, Perpignan, France.|Instituto de Investigaciones en Energía no Convencional, CONICET, Universidad Nacional de Salta, Salta, Argentina.|Instituto de Patología Experimental, Facultad de Ciencias de la Salud, CONICET, Universidad Nacional de Salta, Salta, Argentina.', 'Argentina|Argentina|France|Argentina|Argentina', 5, 'Adaptive Immunity|Algorithms|Animals|Chagas Disease|Coinfection|Computational Biology|Dogs|Host-Pathogen Interactions|Humans|Insect Vectors|Models, Biological|Trypanosoma cruzi', 'Journal Article', '10.1371/journal.pcbi.1005532', '28481887', 'People living in areas with active vector-borne transmission of Chagas disease have multiple contacts with its causative agent, Trypanosoma cruzi. Reinfections by T. cruzi are possible at least in animal models leading to lower or even hardly detectable parasitaemia. In humans, although reinfections are thought to have major public health implications by increasing the risk of chronic manifestations of the disease, there is little quantitative knowledge about their frequency and the timing of parasite re-inoculation in the course of the disease. Here, we implemented stochastic agent-based models i) to estimate the rate of re-inoculation in humans and ii) to assess how frequent are reinfections during the acute and chronic stages of the disease according to alternative hypotheses on the adaptive immune response following a primary infection. By using a hybrid genetic algorithm, the models were fitted to epidemiological data of Argentinean rural villages where mixed infections by different genotypes of T. cruzi reach 56% in humans. To explain this percentage, the best model predicted 0.032 (0.008-0.042) annual reinfections per individual with 98.4% of them occurring in the chronic phase. In addition, the parasite escapes to the adaptive immune response mounted after the primary infection in at least 20% of the events of re-inoculation. With these low annual rates, the risks of reinfection during the typically long chronic stage of the disease stand around 14% (4%-18%) and 60% (21%-70%) after 5 and 30 years, with most individuals being re-infected 1-3 times overall. These low rates are better explained by the weak efficiency of the stercorarian mode of transmission than a highly efficient adaptive immune response. Those estimates are of particular interest for vaccine development and for our understanding of the higher risk of chronic disease manifestations suffered by infected people living in endemic areas.');
INSERT INTO `papers` (`id`, `ano`, `journal`, `titulo`, `autores`, `afiliacao`, `pais`, `citacoes`, `palavra_chave`, `categorias`, `doi`, `pubmed`, `abstract`) VALUES
(88427, 2017, 'plos', 'The decay of motor adaptation to novel movement dynamics reveals an asymmetry in the stability of motion state-dependent learning', 'Hosseini, Eghbal A|Nguyen, Katrina P|Joiner, Wilsaan M', 'Department of Bioengineering, Sensorimotor Integration Laboratory, George Mason University, Fairfax, VA United States.|Department of Bioengineering, Sensorimotor Integration Laboratory, George Mason University, Fairfax, VA United States.|Department of Bioengineering, Sensorimotor Integration Laboratory, George Mason University, Fairfax, VA United States.', 'United States|United States|United States', 4, 'Adaptation, Physiological|Computational Biology|Female|Humans|Learning|Male|Movement|Psychomotor Performance|Task Performance and Analysis', 'Journal Article', '10.1371/journal.pcbi.1005492', '28481891', 'Motor adaptation paradigms provide a quantitative method to study short-term modification of motor commands. Despite the growing understanding of the role motion states (e.g., velocity) play in this form of motor learning, there is little information on the relative stability of memories based on these movement characteristics, especially in comparison to the initial adaptation. Here, we trained subjects to make reaching movements perturbed by force patterns dependent upon either limb position or velocity. Following training, subjects were exposed to a series of error-clamp trials to measure the temporal characteristics of the feedforward motor output during the decay of learning. The compensatory force patterns were largely based on the perturbation kinematic (e.g., velocity), but also showed a small contribution from the other motion kinematic (e.g., position). However, the velocity contribution in response to the position-based perturbation decayed at a slower rate than the position contribution to velocity-based training, suggesting a difference in stability. Next, we modified a previous model of motor adaptation to reflect this difference and simulated the behavior for different learning goals. We were interested in the stability of learning when the perturbations were based on different combinations of limb position or velocity that subsequently resulted in biased amounts of motion-based learning. We trained additional subjects on these combined motion-state perturbations and confirmed the predictions of the model. Specifically, we show that (1) there is a significant separation between the observed gain-space trajectories for the learning and decay of adaptation and (2) for combined motion-state perturbations, the gain associated to changes in limb position decayed at a faster rate than the velocity-dependent gain, even when the position-dependent gain at the end of training was significantly greater. Collectively, these results suggest that the state-dependent adaptation associated with movement velocity is relatively more stable than that based on position.'),
(88428, 2017, 'plos', 'Single-molecule protein identification by sub-nanopore sensors', 'Kolmogorov, Mikhail|Kennedy, Eamonn|Dong, Zhuxin|Timp, Gregory|Pevzner, Pavel A', 'Department of Computer Science and Engineering, University of California San Diego, La Jolla, California, United States of America.|Electrical Engineering and Biological Science, University of Notre Dame, Notre Dame, Indiana, United States of America.|Electrical Engineering and Biological Science, University of Notre Dame, Notre Dame, Indiana, United States of America.|Electrical Engineering and Biological Science, University of Notre Dame, Notre Dame, Indiana, United States of America.|Department of Computer Science and Engineering, University of California San Diego, La Jolla, California, United States of America.', 'United States|India|India|India|United States', 23, 'Algorithms|Databases, Protein|Nanopores|Nanotechnology|Proteins', 'Journal Article', '10.1371/journal.pcbi.1005356', '28486472', 'Recent advances in top-down mass spectrometry enabled identification of intact proteins, but this technology still faces challenges. For example, top-down mass spectrometry suffers from a lack of sensitivity since the ion counts for a single fragmentation event are often low. In contrast, nanopore technology is exquisitely sensitive to single intact molecules, but it has only been successfully applied to DNA sequencing, so far. Here, we explore the potential of sub-nanopores for single-molecule protein identification (SMPI) and describe an algorithm for identification of the electrical current blockade signal (nanospectrum) resulting from the translocation of a denaturated, linearly charged protein through a sub-nanopore. The analysis of identification p-values suggests that the current technology is already sufficient for matching nanospectra against small protein databases, e.g., protein identification in bacterial proteomes.'),
(88429, 2017, 'plos', 'Sequential inference as a mode of cognition and its correlates in fronto-parietal and hippocampal brain regions', 'FitzGerald, Thomas H B|Hämmerer, Dorothea|Friston, Karl J|Li, Shu-Chen|Dolan, Raymond J', 'The Wellcome Trust Centre for Neuroimaging, University College London, London, United Kingdom.|The Wellcome Trust Centre for Neuroimaging, University College London, London, United Kingdom.|The Wellcome Trust Centre for Neuroimaging, University College London, London, United Kingdom.|Chair of Lifespan Developmental Neuroscience, Department of Psychology, TU Dresden, Dresden, Germany.|The Wellcome Trust Centre for Neuroimaging, University College London, London, United Kingdom.', 'United Kingdom|United Kingdom|United Kingdom|Germany|United Kingdom', 8, 'Adult|Aged|Bayes Theorem|Cognition|Computational Biology|Female|Frontal Lobe|Hippocampus|Humans|Male|Middle Aged|Models, Neurological|Parietal Lobe|Task Performance and Analysis|Young Adult', 'Journal Article', '10.1371/journal.pcbi.1005418', '28486504', 'Normative models of human cognition often appeal to Bayesian filtering, which provides optimal online estimates of unknown or hidden states of the world, based on previous observations. However, in many cases it is necessary to optimise beliefs about sequences of states rather than just the current state. Importantly, Bayesian filtering and sequential inference strategies make different predictions about beliefs and subsequent choices, rendering them behaviourally dissociable. Taking data from a probabilistic reversal task we show that subjects choices provide strong evidence that they are representing short sequences of states. Between-subject measures of this implicit sequential inference strategy had a neurobiological underpinning and correlated with grey matter density in prefrontal and parietal cortex, as well as the hippocampus. Our findings provide, to our knowledge, the first evidence for sequential inference in human cognition, and by exploiting between-subject variation in this measure we provide pointers to its neuronal substrates.'),
(88430, 2017, 'plos', 'Short-term activity cycles impede information transmission in ant colonies', 'Richardson, Thomas O|Liechti, Jonas I|Stroeymeyt, Nathalie|Bonhoeffer, Sebastian|Keller, Laurent', 'Department of Ecology and Evolution, University of Lausanne, Switzerland.|Department of Environmental Systems Science, ETH Zürich, Switzerland.|Department of Ecology and Evolution, University of Lausanne, Switzerland.|Department of Environmental Systems Science, ETH Zürich, Switzerland.|Department of Ecology and Evolution, University of Lausanne, Switzerland.', 'Switzerland|Switzerland|Switzerland|Switzerland|Switzerland', 6, 'Activity Cycles|Animal Communication|Animals|Ants|Computational Biology|Models, Biological|Periodicity', 'Journal Article', '10.1371/journal.pcbi.1005527', '28489896', 'Rhythmical activity patterns are ubiquitous in nature. We study an oscillatory biological system: collective activity cycles in ant colonies. Ant colonies have become model systems for research on biological networks because the interactions between the component parts are visible to the naked eye, and because the time-ordered contact network formed by these interactions serves as the substrate for the distribution of information and other resources throughout the colony. To understand how the collective activity cycles influence the contact network transport properties, we used an automated tracking system to record the movement of all the individuals within nine different ant colonies. From these trajectories we extracted over two million ant-to-ant interactions. Time-series analysis of the temporal fluctuations of the overall colony interaction and movement rates revealed that both the period and amplitude of the activity cycles exhibit a diurnal cycle, in which daytime cycles are faster and of greater amplitude than night cycles. Using epidemiology-derived models of transmission over networks, we compared the transmission properties of the observed periodic contact networks with those of synthetic aperiodic networks. These simulations revealed that contrary to some predictions, regularly-oscillating contact networks should impede information transmission. Further, we provide a mechanistic explanation for this effect, and present evidence in support of it.'),
(88431, 2017, 'plos', 'FIMTrack: An open source tracking and locomotion analysis software for small animals', 'Risse, Benjamin|Berh, Dimitri|Otto, Nils|Klämbt, Christian|Jiang, Xiaoyi', 'School of Informatics, University of Edinburgh, Edinburgh, Scotland, United Kingdom.|Faculty of Mathematics and Computer Science, University of Münster, Münster, Germany.|Department of Behaviour and Neuronal Biology, University of Münster, Münster, Germany.|Department of Behaviour and Neuronal Biology, University of Münster, Münster, Germany.|Faculty of Mathematics and Computer Science, University of Münster, Münster, Germany.', 'United Kingdom|Germany|Germany|Germany|Germany', 0, 'Algorithms|Animals|Caenorhabditis elegans|Computational Biology|Image Processing, Computer-Assisted|Locomotion|Software', 'Journal Article', '10.1371/journal.pcbi.1005530', '28493862', 'Imaging and analyzing the locomotion behavior of small animals such as Drosophila larvae or C. elegans worms has become an integral subject of biological research. In the past we have introduced FIM, a novel imaging system feasible to extract high contrast images. This system in combination with the associated tracking software FIMTrack is already used by many groups all over the world. However, so far there has not been an in-depth discussion of the technical aspects. Here we elaborate on the implementation details of FIMTrack and give an in-depth explanation of the used algorithms. Among others, the software offers several tracking strategies to cover a wide range of different model organisms, locomotion types, and camera properties. Furthermore, the software facilitates stimuli-based analysis in combination with built-in manual tracking and correction functionalities. All features are integrated in an easy-to-use graphical user interface. To demonstrate the potential of FIMTrack we provide an evaluation of its accuracy using manually labeled data. The source code is available under the GNU GPLv3 at https://github.com/i-git/FIMTrack and pre-compiled binaries for Windows and Mac are available at http://fim.uni-muenster.de.'),
(88432, 2017, 'plos', 'Identifying stochastic oscillations in single-cell live imaging time series using Gaussian processes', 'Phillips, Nick E|Manning, Cerys|Papalopulu, Nancy|Rattray, Magnus', 'Faculty of Biology, Medicine and Health, University of Manchester, Manchester, United Kingdom.|Faculty of Biology, Medicine and Health, University of Manchester, Manchester, United Kingdom.|Faculty of Biology, Medicine and Health, University of Manchester, Manchester, United Kingdom.|Faculty of Biology, Medicine and Health, University of Manchester, Manchester, United Kingdom.', 'United Kingdom|United Kingdom|United Kingdom|United Kingdom', 7, 'Animals|Biological Clocks|Cell Line|Image Processing, Computer-Assisted|Luminescent Measurements|Mice|Normal Distribution|Single-Cell Analysis|Stochastic Processes', 'Journal Article', '10.1371/journal.pcbi.1005479', '28493880', 'Multiple biological processes are driven by oscillatory gene expression at different time scales. Pulsatile dynamics are thought to be widespread, and single-cell live imaging of gene expression has lead to a surge of dynamic, possibly oscillatory, data for different gene networks. However, the regulation of gene expression at the level of an individual cell involves reactions between finite numbers of molecules, and this can result in inherent randomness in expression dynamics, which blurs the boundaries between aperiodic fluctuations and noisy oscillators. This underlies a new challenge to the experimentalist because neither intuition nor pre-existing methods work well for identifying oscillatory activity in noisy biological time series. Thus, there is an acute need for an objective statistical method for classifying whether an experimentally derived noisy time series is periodic. Here, we present a new data analysis method that combines mechanistic stochastic modelling with the powerful methods of non-parametric regression with Gaussian processes. Our method can distinguish oscillatory gene expression from random fluctuations of non-oscillatory expression in single-cell time series, despite peak-to-peak variability in period and amplitude of single-cell oscillations. We show that our method outperforms the Lomb-Scargle periodogram in successfully classifying cells as oscillatory or non-oscillatory in data simulated from a simple genetic oscillator model and in experimental data. Analysis of bioluminescent live-cell imaging shows a significantly greater number of oscillatory cells when luciferase is driven by a Hes1 promoter (10/19), which has previously been reported to oscillate, than the constitutive MoMuLV 5 LTR (MMLV) promoter (0/25). The method can be applied to data from any gene network to both quantify the proportion of oscillating cells within a population and to measure the period and quality of oscillations. It is publicly available as a MATLAB package.'),
(88433, 2017, 'plos', 'Mixture models reveal multiple positional bias types in RNA-Seq data and lead to accurate transcript concentration estimates', 'Tuerk, Andreas|Wiktorin, Gregor|Güler, Serhat', 'Lexogen GmbH, Vienna, Austria.|Lexogen GmbH, Vienna, Austria.|Lexogen GmbH, Vienna, Austria.', 'Austria|Austria|Austria', 0, 'Algorithms|Computational Biology|Gene Expression Profiling|Humans|Models, Genetic|Models, Statistical|RNA|Sequence Analysis, RNA', 'Journal Article', '10.1371/journal.pcbi.1005515', '28505151', 'Accuracy of transcript quantification with RNA-Seq is negatively affected by positional fragment bias. This article introduces Mix2 (rd. mixquare), a transcript quantification method which uses a mixture of probability distributions to model and thereby neutralize the effects of positional fragment bias. The parameters of Mix2 are trained by Expectation Maximization resulting in simultaneous transcript abundance and bias estimates. We compare Mix2 to Cufflinks, RSEM, eXpress and PennSeq, state-of-the-art quantification methods implementing some form of bias correction. On four synthetic biases we show that the accuracy of Mix2 overall exceeds the accuracy of the other methods and that its bias estimates converge to the correct solution. We further evaluate Mix2 on real RNA-Seq data from the Microarray and Sequencing Quality Control (MAQC, SEQC) Consortia. On MAQC data, Mix2 achieves improved correlation to qPCR measurements with a relative increase in R2 between 4% and 50%. Mix2 also yields repeatable concentration estimates across technical replicates with a relative increase in R2 between 8% and 47% and reduced standard deviation across the full concentration range. We further observe more accurate detection of differential expression with a relative increase in true positives between 74% and 378% for 5% false positives. In addition, Mix2 reveals 5 dominant biases in MAQC data deviating from the common assumption of a uniform fragment distribution. On SEQC data, Mix2 yields higher consistency between measured and predicted concentration ratios. A relative error of 20% or less is obtained for 51% of transcripts by Mix2, 40% of transcripts by Cufflinks and RSEM and 30% by eXpress. Titration order consistency is correct for 47% of transcripts for Mix2, 41% for Cufflinks and RSEM and 34% for eXpress. We, further, observe improved repeatability across laboratory sites with a relative increase in R2 between 8% and 44% and reduced standard deviation.'),
(88434, 2017, 'plos', 'A predictive coding account of bistable perception - a model-based fMRI study', 'Weilnhammer, Veith|Stuke, Heiner|Hesselmann, Guido|Sterzer, Philipp|Schmack, Katharina', 'Department of Psychiatry, Charité Universitätsmedizin Berlin, 10117 Berlin, Germany.|Department of Psychiatry, Charité Universitätsmedizin Berlin, 10117 Berlin, Germany.|Department of Psychiatry, Charité Universitätsmedizin Berlin, 10117 Berlin, Germany.|Department of Psychiatry, Charité Universitätsmedizin Berlin, 10117 Berlin, Germany.|Department of Psychiatry, Charité Universitätsmedizin Berlin, 10117 Berlin, Germany.', 'Germany|Germany|Germany|Germany|Germany', 26, 'Adult|Bayes Theorem|Computational Biology|Computer Simulation|Female|Frontal Lobe|Humans|Magnetic Resonance Imaging|Male|Models, Neurological|Task Performance and Analysis|Visual Perception|Young Adult', 'Journal Article', '10.1371/journal.pcbi.1005536', '28505152', 'In bistable vision, subjective perception wavers between two interpretations of a constant ambiguous stimulus. This dissociation between conscious perception and sensory stimulation has motivated various empirical studies on the neural correlates of bistable perception, but the neurocomputational mechanism behind endogenous perceptual transitions has remained elusive. Here, we recurred to a generic Bayesian framework of predictive coding and devised a model that casts endogenous perceptual transitions as a consequence of prediction errors emerging from residual evidence for the suppressed percept. Data simulations revealed close similarities between the models predictions and key temporal characteristics of perceptual bistability, indicating that the model was able to reproduce bistable perception. Fitting the predictive coding model to behavioural data from an fMRI-experiment on bistable perception, we found a correlation across participants between the model parameter encoding perceptual stabilization and the behaviourally measured frequency of perceptual transitions, corroborating that the model successfully accounted for participants perception. Formal model comparison with established models of bistable perception based on mutual inhibition and adaptation, noise or a combination of adaptation and noise was used for the validation of the predictive coding model against the established models. Most importantly, model-based analyses of the fMRI data revealed that prediction error time-courses derived from the predictive coding model correlated with neural signal time-courses in bilateral inferior frontal gyri and anterior insulae. Voxel-wise model selection indicated a superiority of the predictive coding model over conventional analysis approaches in explaining neural activity in these frontal areas, suggesting that frontal cortex encodes prediction errors that mediate endogenous perceptual transitions in bistable perception. Taken together, our current work provides a theoretical framework that allows for the analysis of behavioural and neural data using a predictive coding perspective on bistable perception. In this, our approach posits a crucial role of prediction error signalling for the resolution of perceptual ambiguities.'),
(88435, 2017, 'plos', 'An independent component analysis confounding factor correction framework for identifying broad impact expression quantitative trait loci', 'Ju, Jin Hyun|Shenoy, Sushila A|Crystal, Ronald G|Mezey, Jason G', 'Department of Genetic Medicine, Weill Cornell Medical College, New York, NY, United States of America.|Department of Genetic Medicine, Weill Cornell Medical College, New York, NY, United States of America.|Department of Genetic Medicine, Weill Cornell Medical College, New York, NY, United States of America.|Department of Genetic Medicine, Weill Cornell Medical College, New York, NY, United States of America.', 'United States|United States|United States|United States', 0, 'Algorithms|Anxiety|Computational Biology|Databases, Genetic|Depression|Gene Regulatory Networks|Genome-Wide Association Study|Humans|Models, Genetic|Models, Statistical|Netherlands|Quantitative Trait Loci', 'Journal Article', '10.1371/journal.pcbi.1005537', '28505156', 'Genome-wide expression Quantitative Trait Loci (eQTL) studies in humans have provided numerous insights into the genetics of both gene expression and complex diseases. While the majority of eQTL identified in genome-wide analyses impact a single gene, eQTL that impact many genes are particularly valuable for network modeling and disease analysis. To enable the identification of such broad impact eQTL, we introduce CONFETI: Confounding Factor Estimation Through Independent component analysis. CONFETI is designed to address two conflicting issues when searching for broad impact eQTL: the need to account for non-genetic confounding factors that can lower the power of the analysis or produce broad impact eQTL false positives, and the tendency of methods that account for confounding factors to model broad impact eQTL as non-genetic variation. The key advance of the CONFETI framework is the use of Independent Component Analysis (ICA) to identify variation likely caused by broad impact eQTL when constructing the sample covariance matrix used for the random effect in a mixed model. We show that CONFETI has better performance than other mixed model confounding factor methods when considering broad impact eQTL recovery from synthetic data. We also used the CONFETI framework and these same confounding factor methods to identify eQTL that replicate between matched twin pair datasets in the Multiple Tissue Human Expression Resource (MuTHER), the Depression Genes Networks study (DGN), the Netherlands Study of Depression and Anxiety (NESDA), and multiple tissue types in the Genotype-Tissue Expression (GTEx) consortium. These analyses identified both cis-eQTL and trans-eQTL impacting individual genes, and CONFETI had better or comparable performance to other mixed model confounding factor analysis methods when identifying such eQTL. In these analyses, we were able to identify and replicate a few broad impact eQTL although the overall number was small even when applying CONFETI. In light of these results, we discuss the broad impact eQTL that have been previously reported from the analysis of human data and suggest that considerable caution should be exercised when making biological inferences based on these reported eQTL.'),
(88436, 2017, 'plos', 'High-order epistasis shapes evolutionary trajectories', 'Sailer, Zachary R|Harms, Michael J', 'Institute of Molecular Biology, University of Oregon, Eugene, OR, USA.|Institute of Molecular Biology, University of Oregon, Eugene, OR, USA.', 'United States|United States', 0, 'Computational Biology|Epistasis, Genetic|Evolution, Molecular|Genotype|Mutation', 'Journal Article', '10.1371/journal.pcbi.1005541', '28505183', 'High-order epistasis-where the effect of a mutation is determined by interactions with two or more other mutations-makes small, but detectable, contributions to genotype-fitness maps. While epistasis between pairs of mutations is known to be an important determinant of evolutionary trajectories, the evolutionary consequences of high-order epistasis remain poorly understood. To determine the effect of high-order epistasis on evolutionary trajectories, we computationally removed high-order epistasis from experimental genotype-fitness maps containing all binary combinations of five mutations. We then compared trajectories through maps both with and without high-order epistasis. We found that high-order epistasis strongly shapes the accessibility and probability of evolutionary trajectories. A closer analysis revealed that the magnitude of epistasis, not its order, predicts is effects on evolutionary trajectories. We further find that high-order epistasis makes it impossible to predict evolutionary trajectories from the individual and paired effects of mutations. We therefore conclude that high-order epistasis profoundly shapes evolutionary trajectories through genotype-fitness maps.'),
(88437, 2017, 'plos', 'SteadyCom: Predicting microbial abundances while ensuring community stability', 'Chan, Siu Hung Joshua|Simons, Margaret N|Maranas, Costas D', 'Department of Chemical Engineering, The Pennsylvania State University, University Park, Pennsylvania, United States of America.|Department of Chemical Engineering, The Pennsylvania State University, University Park, Pennsylvania, United States of America.|Department of Chemical Engineering, The Pennsylvania State University, University Park, Pennsylvania, United States of America.', 'United States|United States|United States', 45, 'Algorithms|Bacteria|Genomics|Metabolic Flux Analysis|Metabolic Networks and Pathways|Microbial Consortia', 'Journal Article', '10.1371/journal.pcbi.1005539', '28505184', 'Genome-scale metabolic modeling has become widespread for analyzing microbial metabolism. Extending this established paradigm to more complex microbial communities is emerging as a promising way to unravel the interactions and biochemical repertoire of these omnipresent systems. While several modeling techniques have been developed for microbial communities, little emphasis has been placed on the need to impose a time-averaged constant growth rate across all members for a community to ensure co-existence and stability. In the absence of this constraint, the faster growing organism will ultimately displace all other microbes in the community. This is particularly important for predicting steady-state microbiota composition as it imposes significant restrictions on the allowable community membership, composition and phenotypes. In this study, we introduce the SteadyCom optimization framework for predicting metabolic flux distributions consistent with the steady-state requirement. SteadyCom can be rapidly converged by iteratively solving linear programming (LP) problem and the number of iterations is independent of the number of organisms. A significant advantage of SteadyCom is compatibility with flux variability analysis. SteadyCom is first demonstrated for a community of four E. coli double auxotrophic mutants and is then applied to a gut microbiota model consisting of nine species, with representatives from the phyla Bacteroidetes, Firmicutes, Actinobacteria and Proteobacteria. In contrast to the direct use of FBA, SteadyCom is able to predict the change in species abundance in response to changes in diets with minimal additional imposed constraints on the model. By randomizing the uptake rates of microbes, an abundance profile with a good agreement to experimental gut microbiota is inferred. SteadyCom provides an important step towards the cross-cutting task of predicting the composition of a microbial community in a given environment.'),
(88438, 2017, 'plos', 'Combining inferred regulatory and reconstructed metabolic networks enhances phenotype prediction in yeast', 'Wang, Zhuo|Danziger, Samuel A|Heavner, Benjamin D|Ma, Shuyi|Smith, Jennifer J|Li, Song|Herricks, Thurston|Simeonidis, Evangelos|Baliga, Nitin S|Aitchison, John D|Price, Nathan D', 'Key laboratory for the Genetics of Developmental and Neuropsychiatric Disorders (Ministry of Education), Bio-X Institutes, Shanghai Jiao Tong University, Shanghai, China.|Institute for Systems Biology, Seattle, Washington, United States of America.|Institute for Systems Biology, Seattle, Washington, United States of America.|Institute for Systems Biology, Seattle, Washington, United States of America.|Institute for Systems Biology, Seattle, Washington, United States of America.|Institute for Systems Biology, Seattle, Washington, United States of America.|Institute for Systems Biology, Seattle, Washington, United States of America.|Institute for Systems Biology, Seattle, Washington, United States of America.|Institute for Systems Biology, Seattle, Washington, United States of America.|Institute for Systems Biology, Seattle, Washington, United States of America.|Institute for Systems Biology, Seattle, Washington, United States of America.', 'China|United States|United States|United States|United States|United States|United States|United Sta', 0, 'Gene Regulatory Networks|Metabolic Networks and Pathways|Models, Biological|Phenotype|Saccharomyces cerevisiae|Systems Biology', 'Journal Article', '10.1371/journal.pcbi.1005489', '28520713', 'Gene regulatory and metabolic network models have been used successfully in many organisms, but inherent differences between them make networks difficult to integrate. Probabilistic Regulation Of Metabolism (PROM) provides a partial solution, but it does not incorporate network inference and underperforms in eukaryotes. We present an Integrated Deduced And Metabolism (IDREAM) method that combines statistically inferred Environment and Gene Regulatory Influence Network (EGRIN) models with the PROM framework to create enhanced metabolic-regulatory network models. We used IDREAM to predict phenotypes and genetic interactions between transcription factors and genes encoding metabolic activities in the eukaryote, Saccharomyces cerevisiae. IDREAM models contain many fewer interactions than PROM and yet produce significantly more accurate growth predictions. IDREAM consistently outperformed PROM using any of three popular yeast metabolic models and across three experimental growth conditions. Importantly, IDREAMs enhanced accuracy makes it possible to identify subtle synthetic growth defects. With experimental validation, these novel genetic interactions involving the pyruvate dehydrogenase complex suggested a new role for fatty acid-responsive factor Oaf1 in regulating acetyl-CoA production in glucose grown cells.'),
(88439, 2017, 'plos', 'BacArena: Individual-based metabolic modeling of heterogeneous microbes in complex communities', 'Bauer, Eugen|Zimmermann, Johannes|Baldini, Federico|Thiele, Ines|Kaleta, Christoph', 'Luxembourg Centre for Systems Biomedicine, Université du Luxembourg, Esch-sur-Alzette, Luxembourg.|Research Group Medical Systems Biology, Institute for Experimental Medicine, Christian-Albrechts-University Kiel, Kiel, Germany.|Luxembourg Centre for Systems Biomedicine, Université du Luxembourg, Esch-sur-Alzette, Luxembourg.|Luxembourg Centre for Systems Biomedicine, Université du Luxembourg, Esch-sur-Alzette, Luxembourg.|Research Group Medical Systems Biology, Institute for Experimental Medicine, Christian-Albrechts-University Kiel, Kiel, Germany.', 'Luxembourg|Germany|Luxembourg|Luxembourg|Germany', 0, 'Biofilms|Gastrointestinal Microbiome|Humans|Metabolic Flux Analysis|Microbial Consortia|Microbial Interactions|Models, Biological|Pseudomonas aeruginosa', 'Journal Article', '10.1371/journal.pcbi.1005544', '28531184', 'Recent advances focusing on the metabolic interactions within and between cellular populations have emphasized the importance of microbial communities for human health. Constraint-based modeling, with flux balance analysis in particular, has been established as a key approach for studying microbial metabolism, whereas individual-based modeling has been commonly used to study complex dynamics between interacting organisms. In this study, we combine both techniques into the R package BacArena (https://cran.r-project.org/package=BacArena) to generate novel biological insights into Pseudomonas aeruginosa biofilm formation as well as a seven species model community of the human gut. For our P. aeruginosa model, we found that cross-feeding of fermentation products cause a spatial differentiation of emerging metabolic phenotypes in the biofilm over time. In the human gut model community, we found that spatial gradients of mucus glycans are important for niche formations which shape the overall community structure. Additionally, we could provide novel hypothesis concerning the metabolic interactions between the microbes. These results demonstrate the importance of spatial and temporal multi-scale modeling approaches such as BacArena.'),
(88440, 2017, 'plos', 'Multi-scale computational study of the mechanical regulation of cell mitotic rounding in epithelia', 'Nematbakhsh, Ali|Sun, Wenzhao|Brodskiy, Pavel A|Amiri, Aboutaleb|Narciso, Cody|Xu, Zhiliang|Zartman, Jeremiah J|Alber, Mark', 'Department of Applied and Computational Mathematics and Statistics, University of Notre Dame, Notre Dame, Indiana, United States of America.|Department of Applied and Computational Mathematics and Statistics, University of Notre Dame, Notre Dame, Indiana, United States of America.|Department of Chemical and Biomolecular Engineering, University of Notre Dame, Notre Dame, Indiana, United States of America.|Department of Physics, University of Notre Dame, Notre Dame, Indiana, United States of America.|Department of Chemical and Biomolecular Engineering, University of Notre Dame, Notre Dame, Indiana, United States of America.|Department of Applied and Computational Mathematics and Statistics, University of Notre Dame, Notre Dame, Indiana, United States of America.|Department of Chemical and Biomolecular Engineering, University of Notre Dame, Notre Dame, Indiana, United States of America.|Department of Applied and Computational Mathematics and Statistics, University of Notre Dame, Notre Dame, Indiana, United States of America.', 'India|India|India|India|India|India|India|India', 2, 'Animals|Cell Line|Cell Shape|Computational Biology|Drosophila|Epithelial Cells|Humans|Mitosis|Models, Biological', 'Journal Article', '10.1371/journal.pcbi.1005533', '28531187', 'Mitotic rounding during cell division is critical for preventing daughter cells from inheriting an abnormal number of chromosomes, a condition that occurs frequently in cancer cells. Cells must significantly expand their apical area and transition from a polygonal to circular apical shape to achieve robust mitotic rounding in epithelial tissues, which is where most cancers initiate. However, how cells mechanically regulate robust mitotic rounding within packed tissues is unknown. Here, we analyze mitotic rounding using a newly developed multi-scale subcellular element computational model that is calibrated using experimental data. Novel biologically relevant features of the model include separate representations of the sub-cellular components including the apical membrane and cytoplasm of the cell at the tissue scale level as well as detailed description of cell properties during mitotic rounding. Regression analysis of predictive model simulation results reveals the relative contributions of osmotic pressure, cell-cell adhesion and cortical stiffness to mitotic rounding. Mitotic area expansion is largely driven by regulation of cytoplasmic pressure. Surprisingly, mitotic shape roundness within physiological ranges is most sensitive to variation in cell-cell adhesivity and stiffness. An understanding of how perturbed mechanical properties impact mitotic rounding has important potential implications on, amongst others, how tumors progressively become more genetically unstable due to increased chromosomal aneuploidy and more aggressive.'),
(88441, 2017, 'plos', 'PyLDM - An open source package for lifetime density analysis of time-resolved spectroscopic data', 'Dorlhiac, Gabriel F|Fare, Clyde|van Thor, Jasper J', 'Department of Life Sciences, Faculty of Natural Science, South Kensington Campus, Imperial College London, London, United Kingdom.|Department of Life Sciences, Faculty of Natural Science, South Kensington Campus, Imperial College London, London, United Kingdom.|Department of Life Sciences, Faculty of Natural Science, South Kensington Campus, Imperial College London, London, United Kingdom.', 'United Kingdom|United Kingdom|United Kingdom', 0, 'Algorithms|Computational Biology|Software|Spectrum Analysis|Time Factors', 'Journal Article', '10.1371/journal.pcbi.1005528', '28531219', 'Ultrafast spectroscopy offers temporal resolution for probing processes in the femto- and picosecond regimes. This has allowed for investigation of energy and charge transfer in numerous photoactive compounds and complexes. However, analysis of the resultant data can be complicated, particularly in more complex biological systems, such as photosystems. Historically, the dual approach of global analysis and target modelling has been used to elucidate kinetic descriptions of the system, and the identity of transient species respectively. With regards to the former, the technique of lifetime density analysis (LDA) offers an appealing alternative. While global analysis approximates the data to the sum of a small number of exponential decays, typically on the order of 2-4, LDA uses a semi-continuous distribution of 100 lifetimes. This allows for the elucidation of lifetime distributions, which may be expected from investigation of complex systems with many chromophores, as opposed to averages. Furthermore, the inherent assumption of linear combinations of decays in global analysis means the technique is unable to describe dynamic motion, a process which is resolvable with LDA. The technique was introduced to the field of photosynthesis over a decade ago by the Holzwarth group. The analysis has been demonstrated to be an important tool to evaluate complex dynamics such as photosynthetic energy transfer, and complements traditional global and target analysis techniques. Although theory has been well described, no open source code has so far been available to perform lifetime density analysis. Therefore, we introduce a python (2.7) based package, PyLDM, to address this need. We furthermore provide a direct comparison of the capabilities of LDA with those of the more familiar global analysis, as well as providing a number of statistical techniques for dealing with the regularization of noisy data.'),
(88442, 2017, 'plos', 'Protein charge distribution in proteomes and its impact on translation', 'Requixc3xa3o, Rodrigo D|Fernandes, Luiza|de Souza, Henrique Josxc3xa9 Araujo|Rossetto, Silvana|Domitrovic, Tatiana|Palhano, Fernando L', 'Programa de Biologia Estrutural, Instituto de Bioquxc3xadmica Mxc3xa9dica Leopoldo de Meis, Universidade Federal do Rio de Janeiro, Rio de Janeiro, Rio de Janeiro, Brazil.|Programa de Biologia Estrutural, Instituto de Bioquxc3xadmica Mxc3xa9dica Leopoldo de Meis, Universidade Federal do Rio de Janeiro, Rio de Janeiro, Rio de Janeiro, Brazil.|Programa de Pxc3xb3s-Graduaxc3xa7xc3xa3o em Informxc3xa1tica, Universidade Federal do Rio de Janeiro, Rio de Janeiro, Rio de Janeiro, Brazil.|Programa de Pxc3xb3s-Graduaxc3xa7xc3xa3o em Informxc3xa1tica, Universidade Federal do Rio de Janeiro, Rio de Janeiro, Rio de Janeiro, Brazil.|Departamento de Virologia, Instituto de Microbiologia Paulo de Gxc3xb3es, Universidade Federal do Rio de Janeiro, Rio de Janeiro, Brazil.|Programa de Biologia Estrutural, Instituto de Bioquxc3xadmica Mxc3xa9dica Leopoldo de Meis, Universidade Federal do Rio de Janeiro, Rio de Janeiro, Rio de Janeiro, Brazil.', 'Brazil|Brazil|Brazil|Brazil|Brazil|Brazil', 15, 'Amino Acids|Arabidopsis|Protein Biosynthesis|Proteins|Proteome|Ribosomes|Saccharomyces cerevisiae', 'Journal Article', '10.1371/journal.pcbi.1005549', '28531225', 'As proteins are synthesized, the nascent polypeptide must pass through a negatively charged exit tunnel. During this stage, positively charged stretches can interact with the ribosome walls and slow the translation. Therefore, charged polypeptides may be important factors that affect protein expression. To determine the frequency and distribution of positively and negatively charged stretches in different proteomes, the net charge was calculated for every 30 consecutive amino acid residues, which corresponds to the length of the ribosome exit tunnel. The following annotated and reviewed proteins in the UniProt database (Swiss-Prot) were analyzed: 551,705 proteins from different organisms and a total of 180 million protein segments. We observed that there were more negative than positive stretches and that super-charged positive sequences (i.e., net charges xe2x89xa5 14) were underrepresented in the proteomes. Overall, the proteins were more positively charged at their N-termini and C-termini, and this feature was present in most organisms and subcellular localizations. To investigate whether the N-terminal charges affect the elongation rates, previously published ribosomal profiling data obtained from S. cerevisiae, without translation-interfering drugs, were analyzed. We observed a nonlinear effect of the charge on the ribosome occupancy in which values xe2x89xa5 +5 and xe2x89xa4 -6 showed increased and reduced ribosome densities, respectively. These groups also showed different distributions across 80S monosomes and polysomes. Basic polypeptides are more common within short proteins that are translated by monosomes, whereas negative stretches are more abundant in polysome-translated proteins. These findings suggest that the nascent peptide charge impacts translation and can be one of the factors that regulate translation efficiency and protein expression.'),
(88443, 2017, 'plos', 'Correction: Complex Dynamics of Virus Spread from Low Infection Multiplicities: Implications for the Spread of Oncolytic Viruses', 'PLOS Computational Biology Staff', 'Programa de Biologia Estrutural, Instituto de Bioquxc3xadmica Mxc3xa9dica Leopoldo de Meis, Universidade Federal do Rio de Janeiro, Rio de Janeiro, Rio de Janeiro, Brazil.', 'Brazil', 0, '-', 'Published Erratum', '10.1371/journal.pcbi.1005548', '28542168', '[This corrects the article DOI: 10.1371/journal.pcbi.1005241.].'),
(88444, 2017, 'plos', 'Uncovering direct and indirect molecular determinants of chromatin loops using a computational integrative approach', 'Mourad, Raphaël|Li, Lang|Cuvier, Olivier', 'Laboratoire de Biologie Moléculaire Eucaryote (LBME), CNRS, Université Paul Sabatier (UPS), Toulouse, France.|Center for Computational Biology and Bioinformatics (CCBB), Indiana University, Indianapolis, Indiana, United States of America.|Laboratoire de Biologie Moléculaire Eucaryote (LBME), CNRS, Université Paul Sabatier (UPS), Toulouse, France.', 'France|India|France', 4, 'Animals|Binding Sites|Chromatin|Computational Biology|DNA|Drosophila|Humans|Reproducibility of Results', 'Journal Article', '10.1371/journal.pcbi.1005538', '28542178', 'Chromosomal organization in 3D plays a central role in regulating cell-type specific transcriptional and DNA replication timing programs. Yet it remains unclear to what extent the resulting long-range contacts depend on specific molecular drivers. Here we propose a model that comprehensively assesses the influence on contacts of DNA-binding proteins, cis-regulatory elements and DNA consensus motifs. Using real data, we validate a large number of predictions for long-range contacts involving known architectural proteins and DNA motifs. Our model outperforms existing approaches including enrichment test, random forests and correlation, and it uncovers numerous novel long-range contacts in Drosophila and human. The model uncovers the orientation-dependent specificity for long-range contacts between CTCF motifs in Drosophila, highlighting its conserved property in 3D organization of metazoan genomes. Our model further unravels long-range contacts depending on co-factors recruited to DNA indirectly, as illustrated by the influence of cohesin in stabilizing long-range contacts between CTCF sites. It also reveals asymmetric contacts such as enhancer-promoter contacts that highlight opposite influences of the transcription factors EBF1, EGR1 or MEF2C depending on RNA Polymerase II pausing.'),
(88445, 2017, 'plos', 'Jupyter and Galaxy: Easing entry barriers into complex data analyses for biomedical researchers', 'Grüning, Björn A|Rasche, Eric|Rebolledo-Jaramillo, Boris|Eberhard, Carl|Houwaart, Torsten|Chilton, John|Coraor, Nate|Backofen, Rolf|Taylor, James|Nekrutenko, Anton', 'Bioinformatics Group, Department of Computer Science, Albert-Ludwigs-University, Freiburg, Freiburg, Germany.|Department of Biochemistry and Biophysics, Texas A&M University, College Station, Texas, United States of America.|Centro de Genética y Genómica, Universidad del Desarrollo, Santiago, Chile.|Department of Biology, Johns Hopkins University, Baltimore, Maryland, United States of America.|Bioinformatics Group, Department of Computer Science, Albert-Ludwigs-University, Freiburg, Freiburg, Germany.|Department of Biochemistry and Molecular Biology, The Pennsylvania State University, University Park, Pennsylvania, United States of America.|Department of Biochemistry and Molecular Biology, The Pennsylvania State University, University Park, Pennsylvania, United States of America.|Bioinformatics Group, Department of Computer Science, Albert-Ludwigs-University, Freiburg, Freiburg, Germany.|Department of Biology, Johns Hopkins University, Baltimore, Maryland, United States of America.|Department of Biochemistry and Molecular Biology, The Pennsylvania State University, University Park, Pennsylvania, United States of America.', 'Germany|United States|Chile|United States|Germany|United States|United States|Germany|United States|', 0, 'Biomedical Research|Computational Biology|High-Throughput Nucleotide Sequencing|Humans|Research Personnel|Software', 'Journal Article', '10.1371/journal.pcbi.1005425', '28542180', 'What does it take to convert a heap of sequencing data into a publishable result? First, common tools are employed to reduce primary data (sequencing reads) to a form suitable for further analyses (i.e., the list of variable sites). The subsequent exploratory stage is much more ad hoc and requires the development of custom scripts and pipelines, making it problematic for biomedical researchers. Here, we describe a hybrid platform combining common analysis pathways with the ability to explore data interactively. It aims to fully encompass and simplify the raw data-to-publication pathway and make it reproducible.'),
(88446, 2017, 'plos', 'Spontaneous cortical activity is transiently poised close to criticality', 'Hahn, Gerald|Ponce-Alvarez, Adrian|Monier, Cyril|Benvenuti, Giacomo|Kumar, Arvind|Chavane, Frédéric|Deco, Gustavo|Frégnac, Yves', 'Unité de Neuroscience, Information et Complexité (UNIC), CNRS, Gif-sur-Yvette, France.|Center for Brain and Cognition, Computational Neuroscience Group, Department of Information and Communication Technologies, Universitat Pompeu Fabra, Barcelona, Spain.|Unité de Neuroscience, Information et Complexité (UNIC), CNRS, Gif-sur-Yvette, France.|Institut des Neurosciences de la Timone, CNRS, Marseille, France.|Bernstein Center for Computational Neuroscience, Freiburg, Germany.|Institut des Neurosciences de la Timone, CNRS, Marseille, France.|Center for Brain and Cognition, Computational Neuroscience Group, Department of Information and Communication Technologies, Universitat Pompeu Fabra, Barcelona, Spain.|Unité de Neuroscience, Information et Complexité (UNIC), CNRS, Gif-sur-Yvette, France.', 'France|Spain|France|France|Germany|France|Spain|France', 27, 'Action Potentials|Animals|Cats|Cerebral Cortex|Computational Biology|Haplorhini|Models, Neurological|Neurons|Wakefulness', 'Journal Article', '10.1371/journal.pcbi.1005543', '28542191', 'Brain activity displays a large repertoire of dynamics across the sleep-wake cycle and even during anesthesia. It was suggested that criticality could serve as a unifying principle underlying the diversity of dynamics. This view has been supported by the observation of spontaneous bursts of cortical activity with scale-invariant sizes and durations, known as neuronal avalanches, in recordings of mesoscopic cortical signals. However, the existence of neuronal avalanches in spiking activity has been equivocal with studies reporting both its presence and absence. Here, we show that signs of criticality in spiking activity can change between synchronized and desynchronized cortical states. We analyzed the spontaneous activity in the primary visual cortex of the anesthetized cat and the awake monkey, and found that neuronal avalanches and thermodynamic indicators of criticality strongly depend on collective synchrony among neurons, LFP fluctuations, and behavioral state. We found that synchronized states are associated to criticality, large dynamical repertoire and prolonged epochs of eye closure, while desynchronized states are associated to sub-criticality, reduced dynamical repertoire, and eyes open conditions. Our results show that criticality in cortical dynamics is not stationary, but fluctuates during anesthesia and between different vigilance states.');
INSERT INTO `papers` (`id`, `ano`, `journal`, `titulo`, `autores`, `afiliacao`, `pais`, `citacoes`, `palavra_chave`, `categorias`, `doi`, `pubmed`, `abstract`) VALUES
(88447, 2017, 'plos', 'An agent-based model of leukocyte transendothelial migration during atherogenesis', 'Bhui, Rita|Hayenga, Heather N', 'Department of Physics, University of Texas, Dallas, Richardson TX, United States of America.|Department of Bioengineering, University of Texas, Dallas, Richardson TX, United States of America.', 'United States|United States', 0, 'Animals|Atherosclerosis|Computational Biology|Computer Simulation|Cytokines|Hemodynamics|Humans|Leukocytes|Mice|Models, Cardiovascular|Plaque, Atherosclerotic|Transendothelial and Transepithelial Migration', 'Journal Article', '10.1371/journal.pcbi.1005523', '28542193', 'A vast amount of work has been dedicated to the effects of hemodynamics and cytokines on leukocyte adhesion and trans-endothelial migration (TEM) and subsequent accumulation of leukocyte-derived foam cells in the artery wall. However, a comprehensive mechanobiological model to capture these spatiotemporal events and predict the growth and remodeling of an atherosclerotic artery is still lacking. Here, we present a multiscale model of leukocyte TEM and plaque evolution in the left anterior descending (LAD) coronary artery. The approach integrates cellular behaviors via agent-based modeling (ABM) and hemodynamic effects via computational fluid dynamics (CFD). In this computational framework, the ABM implements the diffusion kinetics of key biological proteins, namely Low Density Lipoprotein (LDL), Tissue Necrosis Factor alpha (TNF-xcexb1), Interlukin-10 (IL-10) and Interlukin-1 beta (IL-1xcexb2), to predict chemotactic driven leukocyte migration into and within the artery wall. The ABM also considers wall shear stress (WSS) dependent leukocyte TEM and compensatory arterial remodeling obeying Glagovs phenomenon. Interestingly, using fully developed steady blood flow does not result in a representative number of leukocyte TEM as compared to pulsatile flow, whereas passing WSS at peak systole of the pulsatile flow waveform does. Moreover, using the model, we have found leukocyte TEM increases monotonically with decreases in luminal volume. At critical plaque shapes the WSS changes rapidly resulting in sudden increases in leukocyte TEM suggesting lumen volumes that will give rise to rapid plaque growth rates if left untreated. Overall this multi-scale and multi-physics approach appropriately captures and integrates the spatiotemporal events occurring at the cellular level in order to predict leukocyte transmigration and plaque evolution.'),
(88448, 2017, 'plos', 'Predicting cryptic links in host-parasite networks', 'Dallas, Tad|Park, Andrew W|Drake, John M', 'University of Georgia, Odum School of Ecology, Athens, Georgia, United States of America.|University of Georgia, Odum School of Ecology, Athens, Georgia, United States of America.|University of Georgia, Odum School of Ecology, Athens, Georgia, United States of America.', 'Georgia|Georgia|Georgia', 16, 'Algorithms|Animals|Computational Biology|Computer Simulation|Host-Parasite Interactions|Mammals|Models, Biological|Parasitic Diseases, Animal', 'Journal Article', '10.1371/journal.pcbi.1005557', '28542200', 'Networks are a way to represent interactions among one (e.g., social networks) or more (e.g., plant-pollinator networks) classes of nodes. The ability to predict likely, but unobserved, interactions has generated a great deal of interest, and is sometimes referred to as the link prediction problem. However, most studies of link prediction have focused on social networks, and have assumed a completely censused network. In biological networks, it is unlikely that all interactions are censused, and ignoring incomplete detection of interactions may lead to biased or incorrect conclusions. Previous attempts to predict network interactions have relied on known properties of network structure, making the approach sensitive to observation errors. This is an obvious shortcoming, as networks are dynamic, and sometimes not well sampled, leading to incomplete detection of links. Here, we develop an algorithm to predict missing links based on conditional probability estimation and associated, node-level features. We validate this algorithm on simulated data, and then apply it to a desert small mammal host-parasite network. Our approach achieves high accuracy on simulated and observed data, providing a simple method to accurately predict missing links in networks without relying on prior knowledge about network structure.'),
(88449, 2017, 'plos', 'ROTS: An R package for reproducibility-optimized statistical testing', 'Suomi, Tomi|Seyednasrollah, Fatemeh|Jaakkola, Maria K|Faux, Thomas|Elo, Laura L', 'Turku Centre for Biotechnology, University of Turku and Åbo Akademi University, Turku, Finland.|Turku Centre for Biotechnology, University of Turku and Åbo Akademi University, Turku, Finland.|Turku Centre for Biotechnology, University of Turku and Åbo Akademi University, Turku, Finland.|Turku Centre for Biotechnology, University of Turku and Åbo Akademi University, Turku, Finland.|Turku Centre for Biotechnology, University of Turku and Åbo Akademi University, Turku, Finland.', 'Finland|Finland|Finland|Finland|Finland', 0, 'Cells, Cultured|Computational Biology|Humans|Internet|Mass Spectrometry|Models, Statistical|Proteins|Proteomics|Reproducibility of Results|Sequence Analysis, RNA|Software', 'Journal Article', '10.1371/journal.pcbi.1005562', '28542205', 'Differential expression analysis is one of the most common types of analyses performed on various biological data (e.g. RNA-seq or mass spectrometry proteomics). It is the process that detects features, such as genes or proteins, showing statistically significant differences between the sample groups under comparison. A major challenge in the analysis is the choice of an appropriate test statistic, as different statistics have been shown to perform well in different datasets. To this end, the reproducibility-optimized test statistic (ROTS) adjusts a modified t-statistic according to the inherent properties of the data and provides a ranking of the features based on their statistical evidence for differential expression between two groups. ROTS has already been successfully applied in a range of different studies from transcriptomics to proteomics, showing competitive performance against other state-of-the-art methods. To promote its widespread use, we introduce here a Bioconductor R package for performing ROTS analysis conveniently on different types of omics data. To illustrate the benefits of ROTS in various applications, we present three case studies, involving proteomics and RNA-seq data from public repositories, including both bulk and single cell data. The package is freely available from Bioconductor (https://www.bioconductor.org/packages/ROTS).'),
(88450, 2017, 'plos', 'Ten simple rules for surviving an interdisciplinary PhD', 'Demharter, Samuel|Pearce, Nicholas|Beattie, Kylie|Frost, Isabel|Leem, Jinwoo|Martin, Alistair|Oppenheimer, Robert|Regep, Cristian|Rukat, Tammo|Skates, Alexander|Trendel, Nicola|Gavaghan, David J|Deane, Charlotte M|Knapp, Bernhard', 'Doctoral Training Centre for Systems Biology, University of Oxford, Oxford, United Kingdom.|Doctoral Training Centre for Systems Approaches to Biomedical Science, University of Oxford, Oxford, United Kingdom.|Doctoral Training Centre for Systems Approaches to Biomedical Science, University of Oxford, Oxford, United Kingdom.|Doctoral Training Centre for Systems Biology, University of Oxford, Oxford, United Kingdom.|Doctoral Training Centre for Systems Approaches to Biomedical Science, University of Oxford, Oxford, United Kingdom.|Doctoral Training Centre for Life Sciences Interface, University of Oxford, Oxford, United Kingdom.|Doctoral Training Centre for Synthetic Biology, University of Oxford, Oxford, United Kingdom.|Doctoral Training Centre for Life Sciences Interface, University of Oxford, Oxford, United Kingdom.|Doctoral Training Centre for Systems Approaches to Biomedical Science, University of Oxford, Oxford, United Kingdom.|Doctoral Training Centre for Systems Approaches to Biomedical Science, University of Oxford, Oxford, United Kingdom.|Doctoral Training Centre for Systems Approaches to Biomedical Science, University of Oxford, Oxford, United Kingdom.|Doctoral Training Centre for Life Sciences Interface, University of Oxford, Oxford, United Kingdom.|Doctoral Training Centre for Systems Approaches to Biomedical Science, University of Oxford, Oxford, United Kingdom.|Doctoral Training Centre for Systems Approaches to Biomedical Science, University of Oxford, Oxford, United Kingdom.', 'United Kingdom|United Kingdom|United Kingdom|United Kingdom|United Kingdom|United Kingdom|United Kin', 0, 'Algorithms|Career Choice|Curriculum|Education, Professional|Interdisciplinary Research|Research', 'Editorial', '10.1371/journal.pcbi.1005512', '28542231', '-'),
(88451, 2017, 'plos', 'Automatically tracking neurons in a moving and deforming brain', 'Nguyen, Jeffrey P|Linder, Ashley N|Plummer, George S|Shaevitz, Joshua W|Leifer, Andrew M', 'Department of Physics, Princeton University, Princeton, New Jersey, United States of America.|Princeton Neuroscience Institute, 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 Physics, Princeton University, Princeton, New Jersey, United States of America.|Department of Physics, Princeton University, Princeton, New Jersey, United States of America.', 'Jersey|Jersey|Jersey|Jersey|Jersey', 0, 'Algorithms|Animals|Brain|Caenorhabditis elegans|Cluster Analysis|Imaging, Three-Dimensional|Microscopy, Fluorescence|Neuroimaging|Neurons', 'Journal Article', '10.1371/journal.pcbi.1005517', '28545068', 'Advances in optical neuroimaging techniques now allow neural activity to be recorded with cellular resolution in awake and behaving animals. Brain motion in these recordings pose a unique challenge. The location of individual neurons must be tracked in 3D over time to accurately extract single neuron activity traces. Recordings from small invertebrates like C. elegans are especially challenging because they undergo very large brain motion and deformation during animal movement. Here we present an automated computer vision pipeline to reliably track populations of neurons with single neuron resolution in the brain of a freely moving C. elegans undergoing large motion and deformation. 3D volumetric fluorescent images of the animals brain are straightened, aligned and registered, and the locations of neurons in the images are found via segmentation. Each neuron is then assigned an identity using a new time-independent machine-learning approach we call Neuron Registration Vector Encoding. In this approach, non-rigid point-set registration is used to match each segmented neuron in each volume with a set of reference volumes taken from throughout the recording. The way each neuron matches with the references defines a feature vector which is clustered to assign an identity to each neuron in each volume. Finally, thin-plate spline interpolation is used to correct errors in segmentation and check consistency of assigned identities. The Neuron Registration Vector Encoding approach proposed here is uniquely well suited for tracking neurons in brains undergoing large deformations. When applied to whole-brain calcium imaging recordings in freely moving C. elegans, this analysis pipeline located 156 neurons for the duration of an 8 minute recording and consistently found more neurons more quickly than manual or semi-automated approaches.'),
(88452, 2017, 'plos', 'Simultaneous inference of phylogenetic and transmission trees in infectious disease outbreaks', 'Klinkenberg, Don|Backer, Jantien A|Didelot, Xavier|Colijn, Caroline|Wallinga, Jacco', 'Department of Epidemiology and Surveillance, National Institute for Public Health and the Environment, Bilthoven, The Netherlands.|Department of Epidemiology and Surveillance, National Institute for Public Health and the Environment, Bilthoven, The Netherlands.|Department of Infectious Disease Epidemiology, Imperial College London, London, United Kingdom.|Department of Mathematics, Imperial College London, London, United Kingdom.|Department of Epidemiology and Surveillance, National Institute for Public Health and the Environment, Bilthoven, The Netherlands.', 'Netherlands|Netherlands|United Kingdom|United Kingdom|Netherlands', 34, 'Algorithms|Bacteria|Bacterial Infections|Computational Biology|Disease Transmission, Infectious|Genome, Bacterial|Genome, Viral|Humans|Phylogeny|Polymorphism, Single Nucleotide|Virus Diseases|Viruses', 'Journal Article', '10.1371/journal.pcbi.1005495', '28545083', 'Whole-genome sequencing of pathogens from host samples becomes more and more routine during infectious disease outbreaks. These data provide information on possible transmission events which can be used for further epidemiologic analyses, such as identification of risk factors for infectivity and transmission. However, the relationship between transmission events and sequence data is obscured by uncertainty arising from four largely unobserved processes: transmission, case observation, within-host pathogen dynamics and mutation. To properly resolve transmission events, these processes need to be taken into account. Recent years have seen much progress in theory and method development, but existing applications make simplifying assumptions that often break up the dependency between the four processes, or are tailored to specific datasets with matching model assumptions and code. To obtain a method with wider applicability, we have developed a novel approach to reconstruct transmission trees with sequence data. Our approach combines elementary models for transmission, case observation, within-host pathogen dynamics, and mutation, under the assumption that the outbreak is over and all cases have been observed. We use Bayesian inference with MCMC for which we have designed novel proposal steps to efficiently traverse the posterior distribution, taking account of all unobserved processes at once. This allows for efficient sampling of transmission trees from the posterior distribution, and robust estimation of consensus transmission trees. We implemented the proposed method in a new R package phybreak. The method performs well in tests of both new and published simulated data. We apply the model to five datasets on densely sampled infectious disease outbreaks, covering a wide range of epidemiological settings. Using only sampling times and sequences as data, our analyses confirmed the original results or improved on them: the more realistic infection times place more confidence in the inferred transmission trees.'),
(88453, 2017, 'plos', 'Transcriptomics technologies', 'Lowe, Rohan|Shirley, Neil|Bleackley, Mark|Dolan, Stephen|Shafee, Thomas', 'La Trobe Institute for Molecular Science, La Trobe University, Melbourne, Australia.|ARC Centre of Excellence in Plant Cell Walls, University of Adelaide, Adelaide, Australia.|La Trobe Institute for Molecular Science, La Trobe University, Melbourne, Australia.|Department of Biochemistry, University of Cambridge, Cambridge, United Kingdom.|La Trobe Institute for Molecular Science, La Trobe University, Melbourne, Australia.', 'Australia|Australia|Australia|United Kingdom|Australia', 0, 'Animals|Cluster Analysis|Gene Expression Profiling|High-Throughput Nucleotide Sequencing|Humans|Image Processing, Computer-Assisted|Mice|Oligonucleotide Array Sequence Analysis|Organ Specificity|RNA|Rats|Sequence Analysis, RNA', 'Journal Article', '10.1371/journal.pcbi.1005457', '28545146', 'Transcriptomics technologies are the techniques used to study an organisms transcriptome, the sum of all of its RNA transcripts. The information content of an organism is recorded in the DNA of its genome and expressed through transcription. Here, mRNA serves as a transient intermediary molecule in the information network, whilst noncoding RNAs perform additional diverse functions. A transcriptome captures a snapshot in time of the total transcripts present in a cell. The first attempts to study the whole transcriptome began in the early 1990s, and technological advances since the late 1990s have made transcriptomics a widespread discipline. Transcriptomics has been defined by repeated technological innovations that transform the field. There are two key contemporary techniques in the field: microarrays, which quantify a set of predetermined sequences, and RNA sequencing (RNA-Seq), which uses high-throughput sequencing to capture all sequences. Measuring the expression of an organisms genes in different tissues, conditions, or time points gives information on how genes are regulated and reveals details of an organisms biology. It can also help to infer the functions of previously unannotated genes. Transcriptomic analysis has enabled the study of how gene expression changes in different organisms and has been instrumental in the understanding of human disease. An analysis of gene expression in its entirety allows detection of broad coordinated trends which cannot be discerned by more targeted assays.'),
(88454, 2017, 'plos', 'Chemomechanical regulation of myosin Ic cross-bridges: Deducing the elastic properties of an ensemble from single-molecule mechanisms', 'Berger, Florian|Hudspeth, A J', 'Laboratory of Sensory Neuroscience, The Rockefeller University, New York, NY, USA.|Laboratory of Sensory Neuroscience, The Rockefeller University, New York, NY, USA.', 'United States|United States', 3, 'Biophysical Phenomena|Computational Biology|Elasticity|Humans|Myosins', 'Journal Article', '10.1371/journal.pcbi.1005566', '28549064', 'Myosin Ic is thought to be the principal constituent of the motor that adjusts mechanical responsiveness during adaptation to prolonged stimuli by hair cells, the sensory receptors of the inner ear. In this context myosin molecules operate neither as filaments, as occurs in muscles, nor as single or few molecules, as characterizes intracellular transport. Instead, myosin Ic molecules occur in a complex cluster in which they may exhibit cooperative properties. To better understand the motors remarkable function, we introduce a theoretical description of myosin Ics chemomechanical cycle based on experimental data from recent single-molecule studies. The cycle consists of distinct chemical states that the myosin molecule stochastically occupies. We explicitly calculate the probabilities of the occupancy of these states and show their dependence on the external force, the availability of actin, and the nucleotide concentrations as required by thermodynamic constraints. This analysis highlights that the strong binding of myosin Ic to actin is dominated by the ADP state for small external forces and by the ATP state for large forces. Our approach shows how specific parameter values of the chemomechanical cycle for myosin Ic result in behaviors distinct from those of other members of the myosin family. Integrating this single-molecule cycle into a simplified ensemble description, we predict that the average number of bound myosin heads is regulated by the external force and nucleotide concentrations. The elastic properties of such an ensemble are determined by the average number of myosin cross-bridges. Changing the binding probabilities and myosins stiffness under a constant force results in a mechanical relaxation which is large enough to account for fast adaptation in hair cells.'),
(88455, 2017, 'plos', 'Correction: Intrinsic Noise Profoundly Alters the Dynamics and Steady State of Morphogen-Controlled Bistable Genetic Switches', 'PLOS Computational Biology Staff', 'Laboratory of Sensory Neuroscience, The Rockefeller University, New York, NY, USA.', 'United States', 0, '-', 'Published Erratum', '10.1371/journal.pcbi.1005563', '28549069', '[This corrects the article DOI: 10.1371/journal.pcbi.1005154.].'),
(88456, 2017, 'plos', 'Adaptation towards scale-free dynamics improves cortical stimulus discrimination at the cost of reduced detection', 'Clawson, Wesley P|Wright, Nathaniel C|Wessel, Ralf|Shew, Woodrow L', 'Department of Physics, University of Arkansas, Fayetteville, Arkansas, United States of America.|Department of Physics, Washington University, Saint Louis, Missouri, United States of America.|Department of Physics, Washington University, Saint Louis, Missouri, United States of America.|Department of Physics, University of Arkansas, Fayetteville, Arkansas, United States of America.', 'United States|United States|United States|United States', 0, 'Adaptation, Physiological|Animals|Models, Neurological|Neural Pathways|Neurons|Retina|Turtles|Visual Cortex', 'Journal Article', '10.1371/journal.pcbi.1005574', '28557985', 'Fundamental to the function of nervous systems is the ability to reorganize to cope with changing sensory input. Although well-studied in single neurons, how such adaptive versatility manifests in the collective population dynamics and function of cerebral cortex remains unknown. Here we measured population neural activity with microelectrode arrays in turtle visual cortex while visually stimulating the retina. First, we found that, following the onset of stimulation, adaptation tunes the collective population dynamics towards a special regime with scale-free spatiotemporal activity, after an initial large-scale transient response. Concurrently, we observed an adaptive tradeoff between two important aspects of population coding-sensory detection and discrimination. As adaptation tuned the cortex toward scale-free dynamics, stimulus discrimination was enhanced, while stimulus detection was reduced. Finally, we used a network-level computational model to show that short-term synaptic depression was sufficient to mechanistically explain our experimental results. In the model, scale-free dynamics emerge only when the model operates near a special regime called criticality. Together our model and experimental results suggest unanticipated functional benefits and costs of adaptation near criticality in visual cortex.'),
(88457, 2017, 'plos', 'On the effects of alternative optima in context-specific metabolic model predictions', 'Robaina-Estxc3xa9vez, Semidxc3xa1n|Nikoloski, Zoran', 'Systems Biology and Mathematical Modeling Group, Max Planck Institute of Molecular Plant Physiology, Potsdam-Golm, Germany.|Systems Biology and Mathematical Modeling Group, Max Planck Institute of Molecular Plant Physiology, Potsdam-Golm, Germany.', 'Germany|Germany', 5, 'Arabidopsis|Computational Biology|Humans|Metabolic Networks and Pathways|Models, Biological|Plant Leaves', 'Journal Article', '10.1371/journal.pcbi.1005568', '28557990', 'The integration of experimental data into genome-scale metabolic models can greatly improve flux predictions. This is achieved by restricting predictions to a more realistic context-specific domain, like a particular cell or tissue type. Several computational approaches to integrate data have been proposed-generally obtaining context-specific (sub)models or flux distributions. However, these approaches may lead to a multitude of equally valid but potentially different models or flux distributions, due to possible alternative optima in the underlying optimization problems. Although this issue introduces ambiguity in context-specific predictions, it has not been generally recognized, especially in the case of model reconstructions. In this study, we analyze the impact of alternative optima in four state-of-the-art context-specific data integration approaches, providing both flux distributions and/or metabolic models. To this end, we present three computational methods and apply them to two particular case studies: leaf-specific predictions from the integration of gene expression data in a metabolic model of Arabidopsis thaliana, and liver-specific reconstructions derived from a human model with various experimental data sources. The application of these methods allows us to obtain the following results: (i) we sample the space of alternative flux distributions in the leaf- and the liver-specific case and quantify the ambiguity of the predictions. In addition, we show how the inclusion of xe2x84x931-regularization during data integration reduces the ambiguity in both cases. (ii) We generate sets of alternative leaf- and liver-specific models that are optimal to each one of the evaluated model reconstruction approaches. We demonstrate that alternative models of the same context contain a marked fraction of disparate reactions. Further, we show that a careful balance between model sparsity and metabolic functionality helps in reducing the discrepancies between alternative models. Finally, our findings indicate that alternative optima must be taken into account for rendering the context-specific metabolic model predictions less ambiguous.'),
(88458, 2017, 'plos', 'Hard real-time closed-loop electrophysiology with the Real-Time eXperiment Interface (RTXI)', 'Patel, Yogi A|George, Ansel|Dorval, Alan D|White, John A|Christini, David J|Butera, Robert J', 'Bioengineering Graduate Program, Georgia Institute of Technology, Atlanta, Georgia, United States of America.|Department of Physiology and Biophysics, Weill Cornell Medical College, New York, New York, United States of America.|Department of Bioengineering, University of Utah, Salt Lake City, Utah, United States of America.|Department of Biomedical Engineering, Boston University, Boston, Massachusetts, United States of America.|Department of Physiology and Biophysics, Weill Cornell Medical College, New York, New York, United States of America.|Bioengineering Graduate Program, Georgia Institute of Technology, Atlanta, Georgia, United States of America.', 'Georgia|United States|United States|United States|United States|Georgia', 28, 'Animals|Biomedical Research|Electrophysiological Phenomena|Humans|Software|Systems Biology', 'Journal Article', '10.1371/journal.pcbi.1005430', '28557998', 'The ability to experimentally perturb biological systems has traditionally been limited to static pre-programmed or operator-controlled protocols. In contrast, real-time control allows dynamic probing of biological systems with perturbations that are computed on-the-fly during experimentation. Real-time control applications for biological research are available, however, these systems are costly and often restrict the flexibility and customization of experimental protocols. The Real-Time eXperiment Interface (RTXI) is an open source software platform for achieving hard real-time data acquisition and closed-loop control in biological experiments while retaining the flexibility needed for experimental settings. RTXI has enabled users to implement complex custom closed-loop protocols in single cell, cell network, animal, and human electrophysiology studies. RTXI is also used as a free and open source, customizable electrophysiology platform in open-loop studies requiring online data acquisition, processing, and visualization. RTXI is easy to install, can be used with an extensive range of external experimentation and data acquisition hardware, and includes standard modules for implementing common electrophysiology protocols.'),
(88459, 2017, 'plos', 'sourceR: Classification and source attribution of infectious agents among heterogeneous populations', 'Miller, Poppy|Marshall, Jonathan|French, Nigel|Jewell, Chris', 'CHICAS, Faculty of Health and Medicine, Lancaster University, Lancaster, England, United Kingdom.|Institute of Fundamental Sciences, Massey University, Palmerston North, New Zealand.|mEpiLab, Massey University, Palmerston North, New Zealand.|CHICAS, Faculty of Health and Medicine, Lancaster University, Lancaster, England, United Kingdom.', 'United Kingdom|New Zealand|New Zealand|United Kingdom', 6, 'Animals|Bacteria|Bayes Theorem|Campylobacter Infections|Campylobacter jejuni|Computational Biology|Foodborne Diseases|Humans|Models, Biological|New Zealand|Software|Zoonoses', 'Journal Article', '10.1371/journal.pcbi.1005564', '28558033', 'Zoonotic diseases are a major cause of morbidity, and productivity losses in both human and animal populations. Identifying the source of food-borne zoonoses (e.g. an animal reservoir or food product) is crucial for the identification and prioritisation of food safety interventions. For many zoonotic diseases it is difficult to attribute human cases to sources of infection because there is little epidemiological information on the cases. However, microbial strain typing allows zoonotic pathogens to be categorised, and the relative frequencies of the strain types among the sources and in human cases allows inference on the likely source of each infection. We introduce sourceR, an R package for quantitative source attribution, aimed at food-borne diseases. It implements a Bayesian model using strain-typed surveillance data from both human cases and source samples, capable of identifying important sources of infection. The model measures the force of infection from each source, allowing for varying survivability, pathogenicity and virulence of pathogen strains, and varying abilities of the sources to act as vehicles of infection. A Bayesian non-parametric (Dirichlet process) approach is used to cluster pathogen strain types by epidemiological behaviour, avoiding model overfitting and allowing detection of strain types associated with potentially high virulence. sourceR is demonstrated using Campylobacter jejuni isolate data collected in New Zealand between 2005 and 2008. Chicken from a particular poultry supplier was identified as the major source of campylobacteriosis, which is qualitatively similar to results of previous studies using the same dataset. Additionally, the software identifies a cluster of 9 multilocus sequence types with abnormally high virulence in humans. sourceR enables straightforward attribution of cases of zoonotic infection to putative sources of infection. As sourceR develops, we intend it to become an important and flexible resource for food-borne disease attribution studies.'),
(88460, 2017, 'plos', 'Dynamic decomposition of spatiotemporal neural signals', 'Ambrogioni, Luca|van Gerven, Marcel A J|Maris, Eric', 'Radboud University, Donders Institute for Brain, Cognition and Behaviour, Nijmegen, The Netherlands.|Radboud University, Donders Institute for Brain, Cognition and Behaviour, Nijmegen, The Netherlands.|Radboud University, Donders Institute for Brain, Cognition and Behaviour, Nijmegen, The Netherlands.', 'Netherlands|Netherlands|Netherlands', 2, 'Adult|Female|Humans|Magnetoencephalography|Male|Middle Aged|Models, Neurological|Models, Statistical|Neocortex|Nerve Net|Regression Analysis|Task Performance and Analysis|Young Adult', 'Journal Article', '10.1371/journal.pcbi.1005540', '28558039', 'Neural signals are characterized by rich temporal and spatiotemporal dynamics that reflect the organization of cortical networks. Theoretical research has shown how neural networks can operate at different dynamic ranges that correspond to specific types of information processing. Here we present a data analysis framework that uses a linearized model of these dynamic states in order to decompose the measured neural signal into a series of components that capture both rhythmic and non-rhythmic neural activity. The method is based on stochastic differential equations and Gaussian process regression. Through computer simulations and analysis of magnetoencephalographic data, we demonstrate the efficacy of the method in identifying meaningful modulations of oscillatory signals corrupted by structured temporal and spatiotemporal noise. These results suggest that the method is particularly suitable for the analysis and interpretation of complex temporal and spatiotemporal neural signals.'),
(88461, 2017, 'plos', 'Novel mRNA-specific effects of ribosome drop-off on translation rate and polysome profile', 'Bonnin, Pierre|Kern, Norbert|Young, Neil T|Stansfield, Ian|Romano, M Carmen', 'Institute for Complex Systems and Mathematical Biology, Physics Department, University of Aberdeen, Aberdeen, UK.|Université Montpellier 2, Laboratoire Charles Coulomb UMR 5221, Montpellier, France.|Institute of Medical Sciences, University of Aberdeen, Foresterhill, Aberdeen, UK.|Institute of Medical Sciences, University of Aberdeen, Foresterhill, Aberdeen, UK.|Institute for Complex Systems and Mathematical Biology, Physics Department, University of Aberdeen, Aberdeen, UK.', 'United Kingdom|France|United Kingdom|United Kingdom|United Kingdom', 9, 'Computational Biology|Polyribosomes|Protein Biosynthesis|RNA, Fungal|RNA, Messenger|Ribosomes|Saccharomyces cerevisiae', 'Journal Article', '10.1371/journal.pcbi.1005555', '28558053', 'The well established phenomenon of ribosome drop-off plays crucial roles in translational accuracy and nutrient starvation responses during protein translation. When cells are under stress conditions, such as amino acid starvation or aminoacyl-tRNA depletion due to a high level of recombinant protein expression, ribosome drop-off can substantially affect the efficiency of protein expression. Here we introduce a mathematical model that describes the effects of ribosome drop-off on the ribosome density along the mRNA and on the concomitant protein synthesis rate. Our results show that ribosome premature termination may lead to non-intuitive ribosome density profiles, such as a ribosome density which increases from the 5 to the 3 end. Importantly, the model predicts that the effects of ribosome drop-off on the translation rate are mRNA-specific, and we quantify their resilience to drop-off, showing that the mRNAs which present ribosome queues are much less affected by ribosome drop-off than those which do not. Moreover, among those mRNAs that do not present ribosome queues, resilience to drop-off correlates positively with the elongation rate, so that sequences using fast codons are expected to be less affected by ribosome drop-off. This result is consistent with a genome-wide analysis of S. cerevisiae, which reveals that under favourable growth conditions mRNAs coding for proteins involved in the translation machinery, known to be highly codon biased and using preferentially fast codons, are highly resilient to ribosome drop-off. Moreover, in physiological conditions, the translation rate of mRNAs coding for regulatory, stress-related proteins, is less resilient to ribosome drop-off. This model therefore allows analysis of variations in the translational efficiency of individual mRNAs by accounting for the full range of known ribosome behaviours, as well as explaining mRNA-specific variations in ribosome density emerging from ribosome profiling studies.'),
(88462, 2017, 'plos', 'Assessing computational genomics skills: Our experience in the H3ABioNet African bioinformatics network', 'Jongeneel, C Victor|Achinike-Oduaran, Ovokeraye|Adebiyi, Ezekiel|Adebiyi, Marion|Adeyemi, Seun|Akanle, Bola|Aron, Shaun|Ashano, Efejiro|Bendou, Hocine|Botha, Gerrit|Chimusa, Emile|Choudhury, Ananyo|Donthu, Ravikiran|Drnevich, Jenny|Falola, Oluwadamila|Fields, Christopher J|Hazelhurst, Scott|Hendry, Liesl|Isewon, Itunuoluwa|Khetani, Radhika S|Kumuthini, Judit|Kimuda, Magambo Phillip|Magosi, Lerato|Mainzer, Liudmila Sergeevna|Maslamoney, Suresh|Mbiyavanga, Mamana|Meintjes, Ayton|Mugutso, Danny|Mpangase, Phelelani|Munthali, Richard|Nembaware, Victoria|Ndhlovu, Andrew|Odia, Trust|Okafor, Adaobi|Oladipo, Olaleye|Panji, Sumir|Pillay, Venesa|Rendon, Gloria|Sengupta, Dhriti|Mulder, Nicola', 'High-Performance Biological Computing, Roy J. Carver Biotechnology Center, University of Illinois at Urbana-Champaign, Urbana, Illinois, United States of America.|Sydney Brenner Institute for Molecular Bioscience, University of the Witwatersrand, Johannesburg, South Africa.|Department of Computer and Information Sciences, Covenant University, Ota, Nigeria.|Department of Computer and Information Sciences, Covenant University, Ota, Nigeria.|Covenant University Bioinformatics Research (CUBRe), Covenant University, Ota, Nigeria.|Covenant University Bioinformatics Research (CUBRe), Covenant University, Ota, Nigeria.|Sydney Brenner Institute for Molecular Bioscience, University of the Witwatersrand, Johannesburg, South Africa.|Covenant University Bioinformatics Research (CUBRe), Covenant University, Ota, Nigeria.|Computational Biology Division, Department of Integrative Biomedical Sciences, Institute of Infectious Disease and Molecular Medicine, University of Cape Town, South Africa.|Computational Biology Division, Department of Integrative Biomedical Sciences, Institute of Infectious Disease and Molecular Medicine, University of Cape Town, South Africa.|Computational Biology Division, Department of Integrative Biomedical Sciences, Institute of Infectious Disease and Molecular Medicine, University of Cape Town, South Africa.|Sydney Brenner Institute for Molecular Bioscience, University of the Witwatersrand, Johannesburg, South Africa.|High-Performance Biological Computing, Roy J. Carver Biotechnology Center, University of Illinois at Urbana-Champaign, Urbana, Illinois, United States of America.|High-Performance Biological Computing, Roy J. Carver Biotechnology Center, University of Illinois at Urbana-Champaign, Urbana, Illinois, United States of America.|Covenant University Bioinformatics Research (CUBRe), Covenant University, Ota, Nigeria.|High-Performance Biological Computing, Roy J. Carver Biotechnology Center, University of Illinois at Urbana-Champaign, Urbana, Illinois, United States of America.|Sydney Brenner Institute for Molecular Bioscience, University of the Witwatersrand, Johannesburg, South Africa.|Sydney Brenner Institute for Molecular Bioscience, University of the Witwatersrand, Johannesburg, South Africa.|Department of Computer and Information Sciences, Covenant University, Ota, Nigeria.|High-Performance Biological Computing, Roy J. Carver Biotechnology Center, University of Illinois at Urbana-Champaign, Urbana, Illinois, United States of America.|Centre for Proteomic and Genomic Research, Cape Town, South Africa.|Research Unit in Bioinformatics (RUBi), Department of Biochemistry and Microbiology, Rhodes University, Grahamstown, South Africa.|Botswana Harvard AIDS Institute Partnership, Gaborone, Botswana.|High-Performance Biological Computing, Roy J. Carver Biotechnology Center, University of Illinois at Urbana-Champaign, Urbana, Illinois, United States of America.|Computational Biology Division, Department of Integrative Biomedical Sciences, Institute of Infectious Disease and Molecular Medicine, University of Cape Town, South Africa.|Computational Biology Division, Department of Integrative Biomedical Sciences, Institute of Infectious Disease and Molecular Medicine, University of Cape Town, South Africa.|Computational Biology Division, Department of Integrative Biomedical Sciences, Institute of Infectious Disease and Molecular Medicine, University of Cape Town, South Africa.|Computational Biology Division, Department of Integrative Biomedical Sciences, Institute of Infectious Disease and Molecular Medicine, University of Cape Town, South Africa.|Sydney Brenner Institute for Molecular Bioscience, University of the Witwatersrand, Johannesburg, South Africa.|Sydney Brenner Institute for Molecular Bioscience, University of the Witwatersrand, Johannesburg, South Africa.|Computational Biology Division, Department of Integrative Biomedical Sciences, Institute of Infectious Disease and Molecular Medicine, University of Cape Town, South Africa.|Sydney Brenner Institute for Molecular Bioscience, University of the Witwatersrand, Johannesburg, South Africa.|Covenant University Bioinformatics Research (CUBRe), Covenant University, Ota, Nigeria.|Covenant University Bioinformatics Research (CUBRe), Covenant University, Ota, Nigeria.|Covenant University Bioinformatics Research (CUBRe), Covenant University, Ota, Nigeria.|Computational Biology Division, Department of Integrative Biomedical Sciences, Institute of Infectious Disease and Molecular Medicine, University of Cape Town, South Africa.|Sydney Brenner Institute for Molecular Bioscience, University of the Witwatersrand, Johannesburg, South Africa.|High-Performance Biological Computing, Roy J. Carver Biotechnology Center, University of Illinois at Urbana-Champaign, Urbana, Illinois, United States of America.|Sydney Brenner Institute for Molecular Bioscience, University of the Witwatersrand, Johannesburg, South Africa.|Computational Biology Division, Department of Integrative Biomedical Sciences, Institute of Infectious Disease and Molecular Medicine, University of Cape Town, South Africa.', 'United States|South Africa|Niger|Niger|Niger|Niger|South Africa|Niger|South Africa|South Africa|Sout', 4, 'African Continental Ancestry Group|Database Management Systems|Databases, Genetic|Developing Countries|Genomics|Humans|Nigeria|South Africa', 'Journal Article', '10.1371/journal.pcbi.1005419', '28570565', 'The H3ABioNet pan-African bioinformatics network, which is funded to support the Human Heredity and Health in Africa (H3Africa) program, has developed node-assessment exercises to gauge the ability of its participating research and service groups to analyze typical genome-wide datasets being generated by H3Africa research groups. We describe a framework for the assessment of computational genomics analysis skills, which includes standard operating procedures, training and test datasets, and a process for administering the exercise. We present the experiences of 3 research groups that have taken the exercise and the impact on their ability to manage complex projects. Finally, we discuss the reasons why many H3ABioNet nodes have declined so far to participate and potential strategies to encourage them to do so.'),
(88463, 2017, 'plos', 'A review of active learning approaches to experimental design for uncovering biological networks', 'Sverchkov, Yuriy|Craven, Mark', 'Department of Biostatistics and Medical Informatics, University of Wisconsin-Madison, Madison, Wisconsin, United States of America.|Department of Biostatistics and Medical Informatics, University of Wisconsin-Madison, Madison, Wisconsin, United States of America.', 'United States|United States', 0, 'Algorithms|Computational Biology|Gene Regulatory Networks|Metabolic Networks and Pathways|Research Design|Supervised Machine Learning', 'Journal Article', '10.1371/journal.pcbi.1005466', '28570593', 'Various types of biological knowledge describe networks of interactions among elementary entities. For example, transcriptional regulatory networks consist of interactions among proteins and genes. Current knowledge about the exact structure of such networks is highly incomplete, and laboratory experiments that manipulate the entities involved are conducted to test hypotheses about these networks. In recent years, various automated approaches to experiment selection have been proposed. Many of these approaches can be characterized as active machine learning algorithms. Active learning is an iterative process in which a model is learned from data, hypotheses are generated from the model to propose informative experiments, and the experiments yield new data that is used to update the model. This review describes the various models, experiment selection strategies, validation techniques, and successful applications described in the literature, highlights common themes and notable distinctions among methods, and identifies likely directions of future research and open problems in the area.'),
(88464, 2017, 'plos', 'Epidemiological and economic impact of pandemic influenza in Chicago: Priorities for vaccine interventions', 'Dorratoltaj, Nargesalsadat|Marathe, Achla|Lewis, Bryan L|Swarup, Samarth|Eubank, Stephen G|Abbas, Kaja M', 'Department of Population Health Sciences, Virginia Tech, Blacksburg, VA, United States of America.|Network Dynamics and Simulation Science Lab, Biocomplexity Institute, Virginia Tech, Blacksburg, VA, United States of America.|Network Dynamics and Simulation Science Lab, Biocomplexity Institute, Virginia Tech, Blacksburg, VA, United States of America.|Network Dynamics and Simulation Science Lab, Biocomplexity Institute, Virginia Tech, Blacksburg, VA, United States of America.|Department of Population Health Sciences, Virginia Tech, Blacksburg, VA, United States of America.|Department of Population Health Sciences, Virginia Tech, Blacksburg, VA, United States of America.', 'United States|United States|United States|United States|United States|United States', 0, 'Adolescent|Adult|Aged|Chicago|Child|Child, Preschool|Computational Biology|Humans|Infant|Infant, Newborn|Influenza Vaccines|Influenza, Human|Middle Aged|Models, Statistical|Pandemics|Vaccination|Young Adult', 'Journal Article', '10.1371/journal.pcbi.1005521', '28570660', 'The study objective is to estimate the epidemiological and economic impact of vaccine interventions during influenza pandemics in Chicago, and assist in vaccine intervention priorities. Scenarios of delay in vaccine introduction with limited vaccine efficacy and limited supplies are not unlikely in future influenza pandemics, as in the 2009 H1N1 influenza pandemic. We simulated influenza pandemics in Chicago using agent-based transmission dynamic modeling. Population was distributed among high-risk and non-high risk among 0-19, 20-64 and 65+ years subpopulations. Different attack rate scenarios for catastrophic (30.15%), strong (21.96%), and moderate (11.73%) influenza pandemics were compared against vaccine intervention scenarios, at 40% coverage, 40% efficacy, and unit cost of $28.62. Sensitivity analysis for vaccine compliance, vaccine efficacy and vaccine start date was also conducted. Vaccine prioritization criteria include risk of death, total deaths, net benefits, and return on investment. The risk of death is the highest among the high-risk 65+ years subpopulation in the catastrophic influenza pandemic, and highest among the high-risk 0-19 years subpopulation in the strong and moderate influenza pandemics. The proportion of total deaths and net benefits are the highest among the high-risk 20-64 years subpopulation in the catastrophic, strong and moderate influenza pandemics. The return on investment is the highest in the high-risk 0-19 years subpopulation in the catastrophic, strong and moderate influenza pandemics. Based on risk of death and return on investment, high-risk groups of the three age group subpopulations can be prioritized for vaccination, and the vaccine interventions are cost saving for all age and risk groups. The attack rates among the children are higher than among the adults and seniors in the catastrophic, strong, and moderate influenza pandemic scenarios, due to their larger social contact network and homophilous interactions in school. Based on return on investment and higher attack rates among children, we recommend prioritizing children (0-19 years) and seniors (65+ years) after high-risk groups for influenza vaccination during times of limited vaccine supplies. Based on risk of death, we recommend prioritizing seniors (65+ years) after high-risk groups for influenza vaccination during times of limited vaccine supplies.');
INSERT INTO `papers` (`id`, `ano`, `journal`, `titulo`, `autores`, `afiliacao`, `pais`, `citacoes`, `palavra_chave`, `categorias`, `doi`, `pubmed`, `abstract`) VALUES
(88465, 2017, 'plos', 'Breakdown of local information processing may underlie isoflurane anesthesia effects', 'Wollstadt, Patricia|Sellers, Kristin K|Rudelt, Lucas|Priesemann, Viola|Hutt, Axel|Fröhlich, Flavio|Wibral, Michael', 'MEG Unit, Brain Imaging Center, Goethe University, Frankfurt/Main, Germany.|Department of Psychiatry, University of North Carolina at Chapel Hill, Chapel Hill, NC 27599, USA.|Max Planck Institute for Dynamics and Self-Organization, Göttingen, Germany.|Max Planck Institute for Dynamics and Self-Organization, Göttingen, Germany.|Deutscher Wetterdienst, Section FE 12 - Data Assimilation, Offenbach/Main, Germany.|Department of Psychiatry, University of North Carolina at Chapel Hill, Chapel Hill, NC 27599, USA.|MEG Unit, Brain Imaging Center, Goethe University, Frankfurt/Main, Germany.', 'Germany|United States|Germany|Germany|Germany|United States|Germany', 0, 'Anesthesia|Anesthetics, Inhalation|Animals|Consciousness|Female|Ferrets|Isoflurane|Mental Processes|Prefrontal Cortex|Unconsciousness', 'Journal Article', '10.1371/journal.pcbi.1005511', '28570661', 'The disruption of coupling between brain areas has been suggested as the mechanism underlying loss of consciousness in anesthesia. This hypothesis has been tested previously by measuring the information transfer between brain areas, and by taking reduced information transfer as a proxy for decoupling. Yet, information transfer is a function of the amount of information available in the information source-such that transfer decreases even for unchanged coupling when less source information is available. Therefore, we reconsidered past interpretations of reduced information transfer as a sign of decoupling, and asked whether impaired local information processing leads to a loss of information transfer. An important prediction of this alternative hypothesis is that changes in locally available information (signal entropy) should be at least as pronounced as changes in information transfer. We tested this prediction by recording local field potentials in two ferrets after administration of isoflurane in concentrations of 0.0%, 0.5%, and 1.0%. We found strong decreases in the source entropy under isoflurane in area V1 and the prefrontal cortex (PFC)-as predicted by our alternative hypothesis. The decrease in source entropy was stronger in PFC compared to V1. Information transfer between V1 and PFC was reduced bidirectionally, but with a stronger decrease from PFC to V1. This links the stronger decrease in information transfer to the stronger decrease in source entropy-suggesting reduced source entropy reduces information transfer. This conclusion fits the observation that the synaptic targets of isoflurane are located in local cortical circuits rather than on the synapses formed by interareal axonal projections. Thus, changes in information transfer under isoflurane seem to be a consequence of changes in local processing more than of decoupling between brain areas. We suggest that source entropy changes must be considered whenever interpreting changes in information transfer as decoupling.'),
(88466, 2017, 'plos', 'A motor unit-based model of muscle fatigue', 'Potvin, Jim R|Fuglevand, Andrew J', 'Department of Kinesiology, McMaster University, Hamilton, Ontario, Canada.|Department of Physiology, College of Medicine, University of Arizona, Tucson, Arizona, United States of America.', 'Canada|United States', 27, 'Computational Biology|Humans|Isometric Contraction|Models, Biological|Muscle Fatigue|Muscle Fibers, Skeletal|Muscle, Skeletal', 'Journal Article', '10.1371/journal.pcbi.1005581', '28574981', 'Muscle fatigue is a temporary decline in the force and power capacity of skeletal muscle resulting from muscle activity. Because control of muscle is realized at the level of the motor unit (MU), it seems important to consider the physiological properties of motor units when attempting to understand and predict muscle fatigue. Therefore, we developed a phenomenological model of motor unit fatigue as a tractable means to predict muscle fatigue for a variety of tasks and to illustrate the individual contractile responses of MUs whose collective action determines the trajectory of changes in muscle force capacity during prolonged activity. An existing MU population model was used to simulate MU firing rates and isometric muscle forces and, to that model, we added fatigue-related changes in MU force, contraction time, and firing rate associated with sustained voluntary contractions. The model accurately estimated endurance times for sustained isometric contractions across a wide range of target levels. In addition, simulations were run for situations that have little experimental precedent to demonstrate the potential utility of the model to predict motor unit fatigue for more complicated, real-world applications. Moreover, the model provided insight into the complex orchestration of MU force contributions during fatigue, that would be unattainable with current experimental approaches.'),
(88467, 2017, 'plos', 'MMTF-An efficient file format for the transmission, visualization, and analysis of macromolecular structures', 'Bradley, Anthony R|Rose, Alexander S|Pavelka, Antonxc3xadn|Valasatava, Yana|Duarte, Jose M|Prlixc4x87, Andreas|Rose, Peter W', 'Structural Bioinformatics Laboratory, San Diego Supercomputer Center, University of California, San Diego, La Jolla, CA, United States of America.|Structural Bioinformatics Laboratory, San Diego Supercomputer Center, University of California, San Diego, La Jolla, CA, United States of America.|Structural Bioinformatics Laboratory, San Diego Supercomputer Center, University of California, San Diego, La Jolla, CA, United States of America.|Structural Bioinformatics Laboratory, San Diego Supercomputer Center, University of California, San Diego, La Jolla, CA, United States of America.|Structural Bioinformatics Laboratory, San Diego Supercomputer Center, University of California, San Diego, La Jolla, CA, United States of America.|Structural Bioinformatics Laboratory, San Diego Supercomputer Center, University of California, San Diego, La Jolla, CA, United States of America.|Structural Bioinformatics Laboratory, San Diego Supercomputer Center, University of California, San Diego, La Jolla, CA, United States of America.', 'United States|United States|United States|United States|United States|United States|United States', 16, 'Computational Biology|Databases, Chemical|Internet|Macromolecular Substances|Molecular Structure|Software', 'Journal Article', '10.1371/journal.pcbi.1005575', '28574982', 'Recent advances in experimental techniques have led to a rapid growth in complexity, size, and number of macromolecular structures that are made available through the Protein Data Bank. This creates a challenge for macromolecular visualization and analysis. Macromolecular structure files, such as PDB or PDBx/mmCIF files can be slow to transfer, parse, and hard to incorporate into third-party software tools. Here, we present a new binary and compressed data representation, the MacroMolecular Transmission Format, MMTF, as well as software implementations in several languages that have been developed around it, which address these issues. We describe the new format and its APIs and demonstrate that it is several times faster to parse, and about a quarter of the file size of the current standard format, PDBx/mmCIF. As a consequence of the new data representation, it is now possible to visualize structures with millions of atoms in a web browser, keep the whole PDB archive in memory or parse it within few minutes on average computers, which opens up a new way of thinking how to design and implement efficient algorithms in structural bioinformatics. The PDB archive is available in MMTF file format through web services and data that are updated on a weekly basis.'),
(88468, 2017, 'plos', 'Network-assisted target identification for haploinsufficiency and homozygous profiling screens', 'Wang, Sheng|Peng, Jian', 'Department of Computer Science, University of Illinois at Urbana-Champaign, Urbana, Illinois, United States of America.|Department of Computer Science, University of Illinois at Urbana-Champaign, Urbana, Illinois, United States of America.', 'United States|United States', 7, 'Antifungal Agents|Biological Assay|Drug Discovery|Gene Expression Profiling|Gene Expression Regulation, Fungal|Gene Targeting|Genome, Fungal|Haploinsufficiency|Homozygote|Network Meta-Analysis|Saccharomyces cerevisiae|Signal Transduction', 'Journal Article', '10.1371/journal.pcbi.1005553', '28574983', 'Chemical genomic screens have recently emerged as a systematic approach to drug discovery on a genome-wide scale. Drug target identification and elucidation of the mechanism of action (MoA) of hits from these noisy high-throughput screens remain difficult. Here, we present GIT (Genetic Interaction Network-Assisted Target Identification), a network analysis method for drug target identification in haploinsufficiency profiling (HIP) and homozygous profiling (HOP) screens. With the drug-induced phenotypic fitness defect of the deletion of a gene, GIT also incorporates the fitness defects of the genes neighbors in the genetic interaction network. On three genome-scale yeast chemical genomic screens, GIT substantially outperforms previous scoring methods on target identification on HIP and HOP assays, respectively. Finally, we showed that by combining HIP and HOP assays, GIT further boosts target identification and reveals potential drugs mechanism of action.'),
(88469, 2017, 'plos', 'A state space approach for piecewise-linear recurrent neural networks for identifying computational dynamics from neural measurements', 'Durstewitz, Daniel', 'Dept. of Theoretical Neuroscience, Bernstein Center for Computational Neuroscience Heidelberg-Mannheim, Central Institute of Mental Health, Medical Faculty Mannheim/ Heidelberg University, Mannheim, Germany.', 'Germany', 0, 'Algorithms|Animals|Computational Biology|Humans|Likelihood Functions|Models, Neurological|Nerve Net|Stochastic Processes', 'Journal Article', '10.1371/journal.pcbi.1005542', '28574992', 'The computational and cognitive properties of neural systems are often thought to be implemented in terms of their (stochastic) network dynamics. Hence, recovering the system dynamics from experimentally observed neuronal time series, like multiple single-unit recordings or neuroimaging data, is an important step toward understanding its computations. Ideally, one would not only seek a (lower-dimensional) state space representation of the dynamics, but would wish to have access to its statistical properties and their generative equations for in-depth analysis. Recurrent neural networks (RNNs) are a computationally powerful and dynamically universal formal framework which has been extensively studied from both the computational and the dynamical systems perspective. Here we develop a semi-analytical maximum-likelihood estimation scheme for piecewise-linear RNNs (PLRNNs) within the statistical framework of state space models, which accounts for noise in both the underlying latent dynamics and the observation process. The Expectation-Maximization algorithm is used to infer the latent state distribution, through a global Laplace approximation, and the PLRNN parameters iteratively. After validating the procedure on toy examples, and using inference through particle filters for comparison, the approach is applied to multiple single-unit recordings from the rodent anterior cingulate cortex (ACC) obtained during performance of a classical working memory task, delayed alternation. Models estimated from kernel-smoothed spike time data were able to capture the essential computational dynamics underlying task performance, including stimulus-selective delay activity. The estimated models were rarely multi-stable, however, but rather were tuned to exhibit slow dynamics in the vicinity of a bifurcation point. In summary, the present work advances a semi-analytical (thus reasonably fast) maximum-likelihood estimation framework for PLRNNs that may enable to recover relevant aspects of the nonlinear dynamics underlying observed neuronal time series, and directly link these to computational properties.'),
(88470, 2017, 'plos', 'Mechanisms of generation of membrane potential resonance in a neuron with multiple resonant ionic currents', 'Fox, David M|Tseng, Hua-An|Smolinski, Tomasz G|Rotstein, Horacio G|Nadim, Farzan', 'Federated Department of Biological Sciences, New Jersey Institute of Technology and Rutgers University, Newark, New Jersey, United States of America.|Federated Department of Biological Sciences, New Jersey Institute of Technology and Rutgers University, Newark, New Jersey, United States of America.|Department of Computer and Information Sciences, Delaware State University, Dover, Delaware, United States of America.|Federated Department of Biological Sciences, New Jersey Institute of Technology and Rutgers University, Newark, New Jersey, United States of America.|Federated Department of Biological Sciences, New Jersey Institute of Technology and Rutgers University, Newark, New Jersey, United States of America.', 'Jersey|Jersey|United States|Jersey|Jersey', 11, 'Animals|Brachyura|Computational Biology|Ion Transport|Membrane Potentials|Models, Neurological|Neurons|Patch-Clamp Techniques', 'Journal Article', '10.1371/journal.pcbi.1005565', '28582395', 'Neuronal membrane potential resonance (MPR) is associated with subthreshold and network oscillations. A number of voltage-gated ionic currents can contribute to the generation or amplification of MPR, but how the interaction of these currents with linear currents contributes to MPR is not well understood. We explored this in the pacemaker PD neurons of the crab pyloric network. The PD neuron MPR is sensitive to blockers of H- (IH) and calcium-currents (ICa). We used the impedance profile of the biological PD neuron, measured in voltage clamp, to constrain parameter values of a conductance-based model using a genetic algorithm and obtained many optimal parameter combinations. Unlike most cases of MPR, in these optimal models, the values of resonant- (fres) and phasonant- (fxcfx95 = 0) frequencies were almost identical. Taking advantage of this fact, we linked the peak phase of ionic currents to their amplitude, in order to provide a mechanistic explanation the dependence of MPR on the ICa gating variable time constants. Additionally, we found that distinct pairwise correlations between ICa parameters contributed to the maintenance of fres and resonance power (QZ). Measurements of the PD neuron MPR at more hyperpolarized voltages resulted in a reduction of fres but no change in QZ. Constraining the optimal models using these data unmasked a positive correlation between the maximal conductances of IH and ICa. Thus, although IH is not necessary for MPR in this neuron type, it contributes indirectly by constraining the parameters of ICa.'),
(88471, 2017, 'plos', 'Reduction of multiscale stochastic biochemical reaction networks using exact moment derivation', 'Kim, Jae Kyoung|Sontag, Eduardo D', 'Department of Mathematical Sciences, Korea Advanced Institute of Science and Technology, Daejeon, Korea.|Department of Mathematics and Center for Quantitative Biology, Rutgers University, New Brunswick, New Jersey, United States of America.', '-|Jersey', 8, 'Algorithms|Animals|Computer Simulation|Humans|Models, Biological|Models, Statistical|Proteome|Signal Transduction|Stochastic Processes', 'Journal Article', '10.1371/journal.pcbi.1005571', '28582397', 'Biochemical reaction networks (BRNs) in a cell frequently consist of reactions with disparate timescales. The stochastic simulations of such multiscale BRNs are prohibitively slow due to high computational cost for the simulations of fast reactions. One way to resolve this problem uses the fact that fast species regulated by fast reactions quickly equilibrate to their stationary distribution while slow species are unlikely to be changed. Thus, on a slow timescale, fast species can be replaced by their quasi-steady state (QSS): their stationary conditional expectation values for given slow species. As the QSS are determined solely by the state of slow species, such replacement leads to a reduced model, where fast species are eliminated. However, it is challenging to derive the QSS in the presence of nonlinear reactions. While various approximation schemes for the QSS have been developed, they often lead to considerable errors. Here, we propose two classes of multiscale BRNs which can be reduced by deriving an exact QSS rather than approximations. Specifically, if fast species constitute either a feedforward network or a complex balanced network, the reduced model based on the exact QSS can be derived. Such BRNs are frequently observed in a cell as the feedforward network is one of fundamental motifs of gene or protein regulatory networks. Furthermore, complex balanced networks also include various types of fast reversible bindings such as bindings between transcriptional factors and gene regulatory sites. The reduced models based on exact QSS, which can be calculated by the computational packages provided in this work, accurately approximate the slow scale dynamics of the original full model with much lower computational cost.'),
(88472, 2017, 'plos', 'Dynamic metabolic modeling of heterotrophic and mixotrophic microalgal growth on fermentative wastes', 'Baroukh, Caroline|Turon, Violette|Bernard, Olivier', 'INRA, UR0050 Laboratoire de Biotechnologie de lEnvironnement, Narbonne, France.|INRA, UR0050 Laboratoire de Biotechnologie de lEnvironnement, Narbonne, France.|INRIA, BIOCORE, Sophia-Antipolis, FRANCE.', 'France|France|-', 0, 'Biofuels|Biomass|Carbon Cycle|Chlorella|Computational Biology|Fermentation|Heterotrophic Processes|Microalgae|Models, Biological', 'Journal Article', '10.1371/journal.pcbi.1005590', '28582469', 'Microalgae are promising microorganisms for the production of numerous molecules of interest, such as pigments, proteins or triglycerides that can be turned into biofuels. Heterotrophic or mixotrophic growth on fermentative wastes represents an interesting approach to achieving higher biomass concentrations, while reducing cost and improving the environmental footprint. Fermentative wastes generally consist of a blend of diverse molecules and it is thus crucial to understand microalgal metabolism in such conditions, where switching between substrates might occur. Metabolic modeling has proven to be an efficient tool for understanding metabolism and guiding the optimization of biomass or target molecule production. Here, we focused on the metabolism of Chlorella sorokiniana growing heterotrophically and mixotrophically on acetate and butyrate. The metabolism was represented by 172 metabolic reactions. The DRUM modeling framework with a mildly relaxed quasi-steady-state assumption was used to account for the switching between substrates and the presence of light. Nine experiments were used to calibrate the model and nine experiments for the validation. The model efficiently predicted the experimental data, including the transient behavior during heterotrophic, autotrophic, mixotrophic and diauxic growth. It shows that an accurate model of metabolism can now be constructed, even in dynamic conditions, with the presence of several carbon substrates. It also opens new perspectives for the heterotrophic and mixotrophic use of microalgae, especially for biofuel production from wastes.'),
(88473, 2017, 'plos', 'Fast and general tests of genetic interaction for genome-wide association studies', 'Frxc3xa5nberg, Mattias|Strawbridge, Rona J|Hamsten, Anders|PROCARDIS consortium|de Faire, Ulf|Lagergren, Jens|Sennblad, Bengt', 'Cardiovascular Medicine Unit, Department of Medicine, Solna, Karolinska Institutet, Stockholm, Sweden.|Cardiovascular Medicine Unit, Department of Medicine, Solna, Karolinska Institutet, Stockholm, Sweden.|Cardiovascular Medicine Unit, Department of Medicine, Solna, Karolinska Institutet, Stockholm, Sweden.|Cardiovascular Medicine Unit, Department of Medicine, Solna, Karolinska Institutet, Stockholm, Sweden.|Division of Cardiovascular Epidemiology, Institute of Environmental Medicine, Karolinska Institutet, Stockholm, Sweden.|Science for Life Laboratory, Stockholm, Sweden.|Cardiovascular Medicine Unit, Department of Medicine, Solna, Karolinska Institutet, Stockholm, Sweden.', 'Sweden|Sweden|Sweden|Sweden|Sweden|Sweden|Sweden', 1, 'Algorithms|Animals|Chromosome Mapping|Epistasis, Genetic|Genetic Association Studies|Genome-Wide Association Study|Humans|Linear Models|Models, Genetic|Models, Theoretical', 'Journal Article', '10.1371/journal.pcbi.1005556', '28586362', 'A complex disease has, by definition, multiple genetic causes. In theory, these causes could be identified individually, but their identification will likely benefit from informed use of anticipated interactions between causes. In addition, characterizing and understanding interactions must be considered key to revealing the etiology of any complex disease. Large-scale collaborative efforts are now paving the way for comprehensive studies of interaction. As a consequence, there is a need for methods with a computational efficiency sufficient for modern data sets as well as for improvements of statistical accuracy and power. Another issue is that, currently, the relation between different methods for interaction inference is in many cases not transparent, complicating the comparison and interpretation of results between different interaction studies. In this paper we present computationally efficient tests of interaction for the complete family of generalized linear models (GLMs). The tests can be applied for inference of single or multiple interaction parameters, but we show, by simulation, that jointly testing the full set of interaction parameters yields superior power and control of false positive rate. Based on these tests we also describe how to combine results from multiple independent studies of interaction in a meta-analysis. We investigate the impact of several assumptions commonly made when modeling interactions. We also show that, across the important class of models with a full set of interaction parameters, jointly testing the interaction parameters yields identical results. Further, we apply our method to genetic data for cardiovascular disease. This allowed us to identify a putative interaction involved in Lp(a) plasma levels between two tag variants in the LPA locus (p = 2.42 xe2x8bx85 10-09) as well as replicate the interaction (p = 6.97 xe2x8bx85 10-07). Finally, our meta-analysis method is used in a small (N = 16,181) study of interactions in myocardial infarction.'),
(88474, 2017, 'plos', 'An integrated calcium imaging processing toolbox for the analysis of neuronal population dynamics', 'Romano, Sebastián A|Pérez-Schuster, Verónica|Jouary, Adrien|Boulanger-Weill, Jonathan|Candeo, Alessia|Pietri, Thomas|Sumbre, Germán', 'Ecole Normale Supérieure, PSL Research University, CNRS, Inserm, Institut de Biologie de lENS, IBENS, Paris, France.|Ecole Normale Supérieure, PSL Research University, CNRS, Inserm, Institut de Biologie de lENS, IBENS, Paris, France.|Ecole Normale Supérieure, PSL Research University, CNRS, Inserm, Institut de Biologie de lENS, IBENS, Paris, France.|Ecole Normale Supérieure, PSL Research University, CNRS, Inserm, Institut de Biologie de lENS, IBENS, Paris, France.|Ecole Normale Supérieure, PSL Research University, CNRS, Inserm, Institut de Biologie de lENS, IBENS, Paris, France.|Ecole Normale Supérieure, PSL Research University, CNRS, Inserm, Institut de Biologie de lENS, IBENS, Paris, France.|Ecole Normale Supérieure, PSL Research University, CNRS, Inserm, Institut de Biologie de lENS, IBENS, Paris, France.', 'France|France|France|France|France|France|France', 22, 'Action Potentials|Calcium|Calcium Signaling|Cell Tracking|Connectome|Image Interpretation, Computer-Assisted|Molecular Imaging|Neurons|Programming Languages|Reproducibility of Results|Sensitivity and Specificity|Software|Systems Integration|Voltage-Sensitive Dye Imaging', 'Journal Article', '10.1371/journal.pcbi.1005526', '28591182', 'The development of new imaging and optogenetics techniques to study the dynamics of large neuronal circuits is generating datasets of unprecedented volume and complexity, demanding the development of appropriate analysis tools. We present a comprehensive computational workflow for the analysis of neuronal population calcium dynamics. The toolbox includes newly developed algorithms and interactive tools for image pre-processing and segmentation, estimation of significant single-neuron single-trial signals, mapping event-related neuronal responses, detection of activity-correlated neuronal clusters, exploration of population dynamics, and analysis of clusters features against surrogate control datasets. The modules are integrated in a modular and versatile processing pipeline, adaptable to different needs. The clustering module is capable of detecting flexible, dynamically activated neuronal assemblies, consistent with the distributed population coding of the brain. We demonstrate the suitability of the toolbox for a variety of calcium imaging datasets. The toolbox open-source code, a step-by-step tutorial and a case study dataset are available at https://github.com/zebrain-lab/Toolbox-Romano-et-al.'),
(88475, 2017, 'plos', 'Mechanisms underlying a thalamocortical transformation during active tactile sensation', 'Gutnisky, Diego Adrian|Yu, Jianing|Hires, Samuel Andrew|To, Minh-Son|Bale, Michael Ross|Svoboda, Karel|Golomb, David', 'Janelia Research Campus, HHMI, Ashburn, Virginia, United States of America.|Janelia Research Campus, HHMI, Ashburn, Virginia, United States of America.|Janelia Research Campus, HHMI, Ashburn, Virginia, United States of America.|Dept. of Human Physiology and Centre for Neuroscience, Flinders University, South Australia, Australia.|Faculty of Life Sciences, University of Manchester, United Kingdom.|Janelia Research Campus, HHMI, Ashburn, Virginia, United States of America.|Janelia Research Campus, HHMI, Ashburn, Virginia, United States of America.', 'United States|United States|United States|Australia|United Kingdom|United States|United States', 0, 'Afferent Pathways|Animals|Computer Simulation|Evoked Potentials, Motor|Evoked Potentials, Somatosensory|Mice|Models, Neurological|Movement|Nerve Net|Neuronal Plasticity|Sensorimotor Cortex|Thalamus|Touch|Vibrissae', 'Journal Article', '10.1371/journal.pcbi.1005576', '28591219', 'During active somatosensation, neural signals expected from movement of the sensors are suppressed in the cortex, whereas information related to touch is enhanced. This tactile suppression underlies low-noise encoding of relevant tactile features and the brains ability to make fine tactile discriminations. Layer (L) 4 excitatory neurons in the barrel cortex, the major target of the somatosensory thalamus (VPM), respond to touch, but have low spike rates and low sensitivity to the movement of whiskers. Most neurons in VPM respond to touch and also show an increase in spike rate with whisker movement. Therefore, signals related to self-movement are suppressed in L4. Fast-spiking (FS) interneurons in L4 show similar dynamics to VPM neurons. Stimulation of halorhodopsin in FS interneurons causes a reduction in FS neuron activity and an increase in L4 excitatory neuron activity. This decrease of activity of L4 FS neurons contradicts the paradoxical effect predicted in networks stabilized by inhibition and in strongly-coupled networks. To explain these observations, we constructed a model of the L4 circuit, with connectivity constrained by in vitro measurements. The model explores the various synaptic conductance strengths for which L4 FS neurons actively suppress baseline and movement-related activity in layer 4 excitatory neurons. Feedforward inhibition, in concert with recurrent intracortical circuitry, produces tactile suppression. Synaptic delays in feedforward inhibition allow transmission of temporally brief volleys of activity associated with touch. Our model provides a mechanistic explanation of a behavior-related computation implemented by the thalamocortical circuit.'),
(88476, 2017, 'plos', 'Leveraging functional annotations in genetic risk prediction for human complex diseases', 'Hu, Yiming|Lu, Qiongshi|Powles, Ryan|Yao, Xinwei|Yang, Can|Fang, Fang|Xu, Xinran|Zhao, Hongyu', 'Department of Biostatistics, Yale School of Public Health, New Haven, CT, United States of America.|Department of Biostatistics, Yale School of Public Health, New Haven, CT, United States of America.|Program of Computational Biology and Bioinformatics, Yale University, New Haven, CT, United States of America.|Yale College, New Haven, CT, United States of America.|Department of Mathematics, Hong Kong Baptist University, Kowloon, Hong Kong.|Department of Biostatistics, Yale School of Public Health, New Haven, CT, United States of America.|Department of Biostatistics, Yale School of Public Health, New Haven, CT, United States of America.|Department of Biostatistics, Yale School of Public Health, New Haven, CT, United States of America.', 'United States|United States|United States|United States|Hong Kong|United States|United States|United', 22, 'Chromosome Mapping|Data Interpretation, Statistical|Data Mining|Databases, Genetic|Epigenomics|Genetic Association Studies|Genetic Predisposition to Disease|Genetic Variation|Genome, Human|Humans|Linkage Disequilibrium|Polymorphism, Single Nucleotide|Proportional Hazards Models|Quantitative Trait Loci|Risk Assessment', 'Journal Article', '10.1371/journal.pcbi.1005589', '28594818', 'Genetic risk prediction is an important goal in human genetics research and precision medicine. Accurate prediction models will have great impacts on both disease prevention and early treatment strategies. Despite the identification of thousands of disease-associated genetic variants through genome wide association studies (GWAS), genetic risk prediction accuracy remains moderate for most diseases, which is largely due to the challenges in both identifying all the functionally relevant variants and accurately estimating their effect sizes in the presence of linkage disequilibrium. In this paper, we introduce AnnoPred, a principled framework that leverages diverse types of genomic and epigenomic functional annotations in genetic risk prediction for complex diseases. AnnoPred is trained using GWAS summary statistics in a Bayesian framework in which we explicitly model various functional annotations and allow for linkage disequilibrium estimated from reference genotype data. Compared with state-of-the-art risk prediction methods, AnnoPred achieves consistently improved prediction accuracy in both extensive simulations and real data.'),
(88477, 2017, 'plos', 'Unicycler: Resolving bacterial genome assemblies from short and long sequencing reads', 'Wick, Ryan R|Judd, Louise M|Gorrie, Claire L|Holt, Kathryn E', 'Department of Biochemistry and Molecular Biology, Bio21 Molecular Science and Biotechnology Institute, The University of Melbourne, Victoria, Australia.|Department of Biochemistry and Molecular Biology, Bio21 Molecular Science and Biotechnology Institute, The University of Melbourne, Victoria, Australia.|Department of Biochemistry and Molecular Biology, Bio21 Molecular Science and Biotechnology Institute, The University of Melbourne, Victoria, Australia.|Department of Biochemistry and Molecular Biology, Bio21 Molecular Science and Biotechnology Institute, The University of Melbourne, Victoria, Australia.', 'Australia|Australia|Australia|Australia', 764, 'Algorithms|Chromosome Mapping|Genome, Bacterial|High-Throughput Nucleotide Sequencing|Sequence Alignment|Sequence Analysis, DNA|Software|User-Computer Interface', 'Journal Article', '10.1371/journal.pcbi.1005595', '28594827', 'The Illumina DNA sequencing platform generates accurate but short reads, which can be used to produce accurate but fragmented genome assemblies. Pacific Biosciences and Oxford Nanopore Technologies DNA sequencing platforms generate long reads that can produce complete genome assemblies, but the sequencing is more expensive and error-prone. There is significant interest in combining data from these complementary sequencing technologies to generate more accurate hybrid assemblies. However, few tools exist that truly leverage the benefits of both types of data, namely the accuracy of short reads and the structural resolving power of long reads. Here we present Unicycler, a new tool for assembling bacterial genomes from a combination of short and long reads, which produces assemblies that are accurate, complete and cost-effective. Unicycler builds an initial assembly graph from short reads using the de novo assembler SPAdes and then simplifies the graph using information from short and long reads. Unicycler uses a novel semi-global aligner to align long reads to the assembly graph. Tests on both synthetic and real reads show Unicycler can assemble larger contigs with fewer misassemblies than other hybrid assemblers, even when long-read depth and accuracy are low. Unicycler is open source (GPLv3) and available at github.com/rrwick/Unicycler.'),
(88478, 2017, 'plos', 'Mendel,MD: A user-friendly open-source web tool for analyzing WES and WGS in the diagnosis of patients with Mendelian disorders', 'G C C L Cardenas, Raony|D Linhares, Natália|L Ferreira, Raquel|Pena, Sérgio D J', 'Laboratório de Genômica Clínica, Faculdade de Medicina da UFMG, Universidade Federal de Minas Gerais, Belo Horizonte, Brazil.|Laboratório de Genômica Clínica, Faculdade de Medicina da UFMG, Universidade Federal de Minas Gerais, Belo Horizonte, Brazil.|Laboratório de Genômica Clínica, Faculdade de Medicina da UFMG, Universidade Federal de Minas Gerais, Belo Horizonte, Brazil.|Laboratório de Genômica Clínica, Faculdade de Medicina da UFMG, Universidade Federal de Minas Gerais, Belo Horizonte, Brazil.', 'Brazil|Brazil|Brazil|Brazil', 3, 'Databases, Genetic|Genetic Diseases, Inborn|Genome|Genomics|High-Throughput Nucleotide Sequencing|Humans|Internet|Software', 'Journal Article', '10.1371/journal.pcbi.1005520', '28594829', 'Whole exome and whole genome sequencing have both become widely adopted methods for investigating and diagnosing human Mendelian disorders. As pangenomic agnostic tests, they are capable of more accurate and agile diagnosis compared to traditional sequencing methods. This article describes new software called Mendel,MD, which combines multiple types of filter options and makes use of regularly updated databases to facilitate exome and genome annotation, the filtering process and the selection of candidate genes and variants for experimental validation and possible diagnosis. This tool offers a user-friendly interface, and leads clinicians through simple steps by limiting the number of candidates to achieve a final diagnosis of a medical genetics case. A useful innovation is the 1-click method, which enables listing all the relevant variants in genes present at OMIM for perusal by clinicians. Mendel,MD was experimentally validated using clinical cases from the literature and was tested by students at the Universidade Federal de Minas Gerais, at GENE-Núcleo de Genética Médica in Brazil and at the Childrens University Hospital in Dublin, Ireland. We show in this article how it can simplify and increase the speed of identifying the culprit mutation in each of the clinical cases that were received for further investigation. Mendel,MD proved to be a reliable web-based tool, being open-source and time efficient for identifying the culprit mutation in different clinical cases of patients with Mendelian Disorders. It is also freely accessible for academic users on the following URL: https://mendelmd.org.'),
(88479, 2017, 'plos', 'A comprehensive overview and evaluation of circular RNA detection tools', 'Zeng, Xiangxiang|Lin, Wei|Guo, Maozu|Zou, Quan', 'School of Information Science and Engineering, Xiamen University, Xiamen, China.|School of Information Science and Engineering, Xiamen University, Xiamen, China.|School of Electrical and Information Engineering, Beijing University of Civil Engineering and Architecture, Beijing, China.|School of Computer Science and Technology, Tianjin University, Tianjin, China.', 'China|China|China|China', 0, 'Base Sequence|Database Management Systems|Databases, Nucleic Acid|HeLa Cells|Humans|RNA|Sequence Alignment|Sequence Analysis, RNA', 'Journal Article', '10.1371/journal.pcbi.1005420', '28594838', 'Circular RNA (circRNA) is mainly generated by the splice donor of a downstream exon joining to an upstream splice acceptor, a phenomenon known as backsplicing. It has been reported that circRNA can function as microRNA (miRNA) sponges, transcriptional regulators, or potential biomarkers. The availability of massive non-polyadenylated transcriptomes data has facilitated the genome-wide identification of thousands of circRNAs. Several circRNA detection tools or pipelines have recently been developed, and it is essential to provide useful guidelines on these pipelines for users, including a comprehensive and unbiased comparison. Here, we provide an improved and easy-to-use circRNA read simulator that can produce mimicking backsplicing reads supporting circRNAs deposited in CircBase. Moreover, we compared the performance of 11 circRNA detection tools on both simulated and real datasets. We assessed their performance regarding metrics such as precision, sensitivity, F1 score, and Area under Curve. It is concluded that no single method dominated on all of these metrics. Among all of the state-of-the-art tools, CIRI, CIRCexplorer, and KNIFE, which achieved better balanced performance between their precision and sensitivity, compared favorably to the other methods.'),
(88480, 2017, 'plos', 'Temperature-amplitude coupling for stable biological rhythms at different temperatures', 'Kurosawa, Gen|Fujioka, Atsuko|Koinuma, Satoshi|Mochizuki, Atsushi|Shigeyoshi, Yasufumi', 'Theoretical Biology Laboratory, RIKEN, Wako, Japan.|Department of Anatomy and Neurobiology, Kindai University Faculty of Medicine, Osakasayama City, Osaka, Japan.|Department of Anatomy and Neurobiology, Kindai University Faculty of Medicine, Osakasayama City, Osaka, Japan.|Theoretical Biology Laboratory, RIKEN, Wako, Japan.|Department of Anatomy and Neurobiology, Kindai University Faculty of Medicine, Osakasayama City, Osaka, Japan.', 'Japan|Japan|Japan|Japan|Japan', 0, 'Animals|Cell Line, Tumor|Computational Biology|Models, Biological|Periodicity|Rats|Temperature', 'Journal Article', '10.1371/journal.pcbi.1005501', '28594845', 'Most biological processes accelerate with temperature, for example cell division. In contrast, the circadian rhythm period is robust to temperature fluctuation, termed temperature compensation. Temperature compensation is peculiar because a system-level property (i.e., the circadian period) is stable under varying temperature while individual components of the system (i.e., biochemical reactions) are usually temperature-sensitive. To understand the mechanism for period stability, we measured the time series of circadian clock transcripts in cultured C6 glioma cells. The amplitudes of Cry1 and Dbp circadian expression increased significantly with temperature. In contrast, other clock transcripts demonstrated no significant change in amplitude. To understand these experimental results, we analyzed mathematical models with different network topologies. It was found that the geometric mean amplitude of gene expression must increase to maintain a stable period with increasing temperatures and reaction speeds for all models studied. To investigate the generality of this temperature-amplitude coupling mechanism for period stability, we revisited data on the yeast metabolic cycle (YMC) period, which is also stable under temperature variation. We confirmed that the YMC amplitude increased at higher temperatures, suggesting temperature-amplitude coupling as a common mechanism shared by circadian and 4 h-metabolic rhythms.'),
(88481, 2017, 'plos', 'Metabolic network segmentation: A probabilistic graphical modeling approach to identify the sites and sequential order of metabolic regulation from non-targeted metabolomics data', 'Kuehne, Andreas|Mayr, Urs|Sévin, Daniel C|Claassen, Manfred|Zamboni, Nicola', 'Institute of Molecular Systems Biology, ETH Zurich, Switzerland.|Institute of Molecular Systems Biology, ETH Zurich, Switzerland.|Institute of Molecular Systems Biology, ETH Zurich, Switzerland.|Institute of Molecular Systems Biology, ETH Zurich, Switzerland.|Institute of Molecular Systems Biology, ETH Zurich, Switzerland.', 'Switzerland|Switzerland|Switzerland|Switzerland|Switzerland', 0, 'Computer Graphics|Computer Simulation|Gene Expression Profiling|Gene Expression Regulation|Metabolic Flux Analysis|Metabolic Networks and Pathways|Metabolome|Metabolomics|Models, Biological|Models, Statistical|Proteome', 'Journal Article', '10.1371/journal.pcbi.1005577', '28598965', 'In recent years, the number of large-scale metabolomics studies on various cellular processes in different organisms has increased drastically. However, it remains a major challenge to perform a systematic identification of mechanistic regulatory events that mediate the observed changes in metabolite levels, due to complex interdependencies within metabolic networks. We present the metabolic network segmentation (MNS) algorithm, a probabilistic graphical modeling approach that enables genome-scale, automated prediction of regulated metabolic reactions from differential or serial metabolomics data. The algorithm sections the metabolic network into modules of metabolites with consistent changes. Metabolic reactions that connect different modules are the most likely sites of metabolic regulation. In contrast to most state-of-the-art methods, the MNS algorithm is independent of arbitrary pathway definitions, and its probabilistic nature facilitates assessments of noisy and incomplete measurements. With serial (i.e., time-resolved) data, the MNS algorithm also indicates the sequential order of metabolic regulation. We demonstrated the power and flexibility of the MNS algorithm with three, realistic case studies with bacterial and human cells. Thus, this approach enables the identification of mechanistic regulatory events from large-scale metabolomics data, and contributes to the understanding of metabolic processes and their interplay with cellular signaling and regulation processes.'),
(88482, 2017, 'plos', 'Mitochondrial respiration and ROS emission during xcexb2-oxidation in the heart: An experimental-computational study', 'Cortassa, Sonia|Sollott, Steven J|Aon, Miguel A', 'Laboratory of Cardiovascular Science, National Institute on Aging, National Institutes of Health, Baltimore, MD, United States of America.|Laboratory of Cardiovascular Science, National Institute on Aging, National Institutes of Health, Baltimore, MD, United States of America.|Laboratory of Cardiovascular Science, National Institute on Aging, National Institutes of Health, Baltimore, MD, United States of America.', 'United States|United States|United States', 12, 'Animals|Cell Respiration|Cells, Cultured|Computer Simulation|Diabetes Mellitus|Electron Transport|Guinea Pigs|Hydrogen Peroxide|Lipid Metabolism|Male|Metabolism|Mitochondria, Heart|Models, Cardiovascular|Oxidation-Reduction|Oxygen|Palmitoyl Coenzyme A|Reactive Oxygen Species', 'Journal Article', '10.1371/journal.pcbi.1005588', '28598967', 'Lipids are main fuels for cellular energy and mitochondria their major oxidation site. Yet unknown is to what extent the fuel role of lipids is influenced by their uncoupling effects, and how this affects mitochondrial energetics, redox balance and the emission of reactive oxygen species (ROS). Employing a combined experimental-computational approach, we comparatively analyze xcexb2-oxidation of palmitoyl CoA (PCoA) in isolated heart mitochondria from Sham and streptozotocin (STZ)-induced type 1 diabetic (T1DM) guinea pigs (GPs). Parallel high throughput measurements of the rates of oxygen consumption (VO2) and hydrogen peroxide (H2O2) emission as a function of PCoA concentration, in the presence of L-carnitine and malate, were performed. We found that PCoA concentration < 200 nmol/mg mito protein resulted in low H2O2 emission flux, increasing thereafter in Sham and T1DM GPs under both states 4 and 3 respiration with diabetic mitochondria releasing higher amounts of ROS. Respiratory uncoupling and ROS excess occurred at PCoA > 600 nmol/mg mito prot, in both control and diabetic animals. Also, for the first time, we show that an integrated two compartment mitochondrial model of xcexb2-oxidation of long-chain fatty acids and main energy-redox processes is able to simulate the relationship between VO2 and H2O2 emission as a function of lipid concentration. Model and experimental results indicate that PCoA oxidation and its concentration-dependent uncoupling effect, together with a partial lipid-dependent decrease in the rate of superoxide generation, modulate H2O2 emission as a function of VO2. Results indicate that keeping low levels of intracellular lipid is crucial for mitochondria and cells to maintain ROS within physiological levels compatible with signaling and reliable energy supply.'),
(88483, 2017, 'plos', 'Ribosome reinitiation can explain length-dependent translation of messenger RNA', 'Rogers, David W|Böttcher, Marvin A|Traulsen, Arne|Greig, Duncan', 'Experimental Evolution Research Group, Max Planck Institute for Evolutionary Biology, Plön, Germany.|Department of Evolutionary Theory, Max Planck Institute for Evolutionary Biology, Plön, Germany.|Department of Evolutionary Theory, Max Planck Institute for Evolutionary Biology, Plön, Germany.|Experimental Evolution Research Group, Max Planck Institute for Evolutionary Biology, Plön, Germany.', 'Germany|Germany|Germany|Germany', 8, 'Computer Simulation|Models, Chemical|Models, Genetic|Peptide Chain Elongation, Translational|Peptide Chain Initiation, Translational|Protein Modification, Translational|RNA, Messenger|Ribosomes|Structure-Activity Relationship|Transcription Factors', 'Journal Article', '10.1371/journal.pcbi.1005592', '28598992', 'Models of mRNA translation usually presume that transcripts are linear, upon reaching the end of a transcript each terminating ribosome returns to the cytoplasmic pool before initiating anew on a different transcript. A consequence of linear models is that faster translation of a given mRNA is unlikely to generate more of the encoded protein, particularly at low ribosome availability. Recent evidence indicates that eukaryotic mRNAs are circularized, potentially allowing terminating ribosomes to preferentially reinitiate on the same transcript. Here we model the effect of ribosome reinitiation on translation and show that, at high levels of reinitiation, protein synthesis rates are dominated by the time required to translate a given transcript. Our model provides a simple mechanistic explanation for many previously enigmatic features of eukaryotic translation, including the negative correlation of both ribosome densities and protein abundance on transcript length, the importance of codon usage in determining protein synthesis rates, and the negative correlation between transcript length and both codon adaptation and 5 mRNA folding energies. In contrast to linear models where translation is largely limited by initiation rates, our model reveals that all three stages of translation-initiation, elongation, and termination/reinitiation-determine protein synthesis rates even at low ribosome availability.');
INSERT INTO `papers` (`id`, `ano`, `journal`, `titulo`, `autores`, `afiliacao`, `pais`, `citacoes`, `palavra_chave`, `categorias`, `doi`, `pubmed`, `abstract`) VALUES
(88484, 2017, 'plos', 'Rosetta:MSF: a modular framework for multi-state computational protein design', 'Lxc3xb6ffler, Patrick|Schmitz, Samuel|Hupfeld, Enrico|Sterner, Reinhard|Merkl, Rainer', 'Institute of Biophysics and Physical Biochemistry, University of Regensburg, Regensburg, Germany.|Institute of Biophysics and Physical Biochemistry, University of Regensburg, Regensburg, Germany.|Institute of Biophysics and Physical Biochemistry, University of Regensburg, Regensburg, Germany.|Institute of Biophysics and Physical Biochemistry, University of Regensburg, Regensburg, Germany.|Institute of Biophysics and Physical Biochemistry, University of Regensburg, Regensburg, Germany.', 'Germany|Germany|Germany|Germany|Germany', 0, 'Algorithms|Computer Simulation|Models, Chemical|Models, Molecular|Programming Languages|Protein Conformation|Protein Engineering|Proteins|Sequence Analysis, Protein|Software', 'Journal Article', '10.1371/journal.pcbi.1005600', '28604768', 'Computational protein design (CPD) is a powerful technique to engineer existing proteins or to design novel ones that display desired properties. Rosetta is a software suite including algorithms for computational modeling and analysis of protein structures and offers many elaborate protocols created to solve highly specific tasks of protein engineering. Most of Rosettas protocols optimize sequences based on a single conformation (i. e. design state). However, challenging CPD objectives like multi-specificity design or the concurrent consideration of positive and negative design goals demand the simultaneous assessment of multiple states. This is why we have developed the multi-state framework MSF that facilitates the implementation of Rosettas single-state protocols in a multi-state environment and made available two frequently used protocols. Utilizing MSF, we demonstrated for one of these protocols that multi-state design yields a 15% higher performance than single-state design on a ligand-binding benchmark consisting of structural conformations. With this protocol, we designed de novo nine retro-aldolases on a conformational ensemble deduced from a (xcexb2xcexb1)8-barrel protein. All variants displayed measurable catalytic activity, testifying to a high success rate for this concept of multi-state enzyme design.'),
(88485, 2017, 'plos', 'Locking of correlated neural activity to ongoing oscillations', 'Kühn, Tobias|Helias, Moritz', 'Institute of Neuroscience and Medicine (INM-6) and Institute for Advanced Simulation (IAS-6) and JARA BRAIN Institute I, Jülich Research Centre, Jülich, Germany.|Institute of Neuroscience and Medicine (INM-6) and Institute for Advanced Simulation (IAS-6) and JARA BRAIN Institute I, Jülich Research Centre, Jülich, Germany.', 'Germany|Germany', 1, 'Action Potentials|Animals|Biological Clocks|Brain|Brain Waves|Computer Simulation|Cortical Synchronization|Feedback, Physiological|Humans|Models, Neurological|Nerve Net|Neurons', 'Journal Article', '10.1371/journal.pcbi.1005534', '28604771', 'Population-wide oscillations are ubiquitously observed in mesoscopic signals of cortical activity. In these network states a global oscillatory cycle modulates the propensity of neurons to fire. Synchronous activation of neurons has been hypothesized to be a separate channel of signal processing information in the brain. A salient question is therefore if and how oscillations interact with spike synchrony and in how far these channels can be considered separate. Experiments indeed showed that correlated spiking co-modulates with the static firing rate and is also tightly locked to the phase of beta-oscillations. While the dependence of correlations on the mean rate is well understood in feed-forward networks, it remains unclear why and by which mechanisms correlations tightly lock to an oscillatory cycle. We here demonstrate that such correlated activation of pairs of neurons is qualitatively explained by periodically-driven random networks. We identify the mechanisms by which covariances depend on a driving periodic stimulus. Mean-field theory combined with linear response theory yields closed-form expressions for the cyclostationary mean activities and pairwise zero-time-lag covariances of binary recurrent random networks. Two distinct mechanisms cause time-dependent covariances: the modulation of the susceptibility of single neurons (via the external input and network feedback) and the time-varying variances of single unit activities. For some parameters, the effectively inhibitory recurrent feedback leads to resonant covariances even if mean activities show non-resonant behavior. Our analytical results open the question of time-modulated synchronous activity to a quantitative analysis.'),
(88486, 2017, 'plos', 'Atrial arrhythmogenicity of KCNJ2 mutations in short QT syndrome: Insights from virtual human atria', 'Whittaker, Dominic G|Ni, Haibo|El Harchi, Aziza|Hancox, Jules C|Zhang, Henggui', 'Biological Physics Group, School of Physics & Astronomy, The University of Manchester, Manchester, United Kingdom.|Biological Physics Group, School of Physics & Astronomy, The University of Manchester, Manchester, United Kingdom.|Department of Physiology, Pharmacology and Neuroscience, and Cardiovascular Research Laboratories, School of Medical Sciences, University of Bristol, Bristol, United Kingdom.|Biological Physics Group, School of Physics & Astronomy, The University of Manchester, Manchester, United Kingdom.|Biological Physics Group, School of Physics & Astronomy, The University of Manchester, Manchester, United Kingdom.', 'United Kingdom|United Kingdom|United Kingdom|United Kingdom|United Kingdom', 18, 'Action Potentials|Arrhythmias, Cardiac|Atrial Fibrillation|Computer Simulation|Excitation Contraction Coupling|Genetic Predisposition to Disease|Heart Atria|Heart Conduction System|Humans|Ion Channel Gating|Models, Cardiovascular|Models, Genetic|Mutation|Myocardial Contraction|Potassium|Potassium Channels, Inwardly Rectifying', 'Journal Article', '10.1371/journal.pcbi.1005593', '28609477', 'Gain-of-function mutations in KCNJ2-encoded Kir2.1 channels underlie variant 3 (SQT3) of the short QT syndrome, which is associated with atrial fibrillation (AF). Using biophysically-detailed human atria computer models, this study investigated the mechanistic link between SQT3 mutations and atrial arrhythmogenesis, and potential ion channel targets for treatment of SQT3. A contemporary model of the human atrial action potential (AP) was modified to recapitulate functional changes in IK1 due to heterozygous and homozygous forms of the D172N and E299V Kir2.1 mutations. Wild-type (WT) and mutant formulations were incorporated into multi-scale homogeneous and heterogeneous tissue models. Effects of mutations on AP duration (APD), conduction velocity (CV), effective refractory period (ERP), tissue excitation threshold and their rate-dependence, as well as the wavelength of re-entry (WL) were quantified. The D172N and E299V Kir2.1 mutations produced distinct effects on IK1 and APD shortening. Both mutations decreased WL for re-entry through a reduction in ERP and CV. Stability of re-entrant excitation waves in 2D and 3D tissue models was mediated by changes to tissue excitability and dispersion of APD in mutation conditions. Combined block of IK1 and IKr was effective in terminating re-entry associated with heterozygous D172N conditions, whereas IKr block alone may be a safer alternative for the E299V mutation. Combined inhibition of IKr and IKur produced a synergistic anti-arrhythmic effect in both forms of SQT3. In conclusion, this study provides mechanistic insights into atrial proarrhythmia with SQT3 Kir2.1 mutations and highlights possible pharmacological strategies for management of SQT3-linked AF.'),
(88487, 2017, 'plos', 'Histone posttranslational modifications predict specific alternative exon subtypes in mammalian brain', 'Hu, Qiwen|Kim, Eun Ji|Feng, Jian|Grant, Gregory R|Heller, Elizabeth A', 'Department of Systems Pharmacology and Translational Therapeutics, University of Pennsylvania, Philadelphia, PA, United States of America.|Department of Systems Pharmacology and Translational Therapeutics, University of Pennsylvania, Philadelphia, PA, United States of America.|Department of Biological Science, Florida State University, Tallahassee, FL, United States of America.|Department of Genetics, University of Pennsylvania, Philadelphia, PA, United States of America.|Department of Systems Pharmacology and Translational Therapeutics, University of Pennsylvania, Philadelphia, PA, United States of America.', 'United States|United States|United States|United States|United States', 0, 'Animals|Brain|Cocaine-Related Disorders|Computer Simulation|Exons|Histones|Mice|Models, Genetic|Nerve Tissue Proteins|Protein Processing, Post-Translational|RNA Splice Sites', 'Journal Article', '10.1371/journal.pcbi.1005602', '28609483', 'A compelling body of literature, based on next generation chromatin immunoprecipitation and RNA sequencing of reward brain regions indicates that the regulation of the epigenetic landscape likely underlies chronic drug abuse and addiction. It is now critical to develop highly innovative computational strategies to reveal the relevant regulatory transcriptional mechanisms that may underlie neuropsychiatric disease. We have analyzed chromatin regulation of alternative splicing, which is implicated in cocaine exposure in mice. Recent literature has described chromatin-regulated alternative splicing, suggesting a novel function for drug-induced neuroepigenetic remodeling. However, the extent of the genome-wide association between particular histone modifications and alternative splicing remains unexplored. To address this, we have developed novel computational approaches to model the association between alternative splicing and histone posttranslational modifications in the nucleus accumbens (NAc), a brain reward region. Using classical statistical methods and machine learning to combine ChIP-Seq and RNA-Seq data, we found that specific histone modifications are strongly associated with various aspects of differential splicing. H3K36me3 and H3K4me1 have the strongest association with splicing indicating they play a significant role in alternative splicing in brain reward tissue.'),
(88488, 2017, 'plos', 'GINOM: A statistical framework for assessing interval overlap of multiple genomic features', 'Bryner, Darshan|Criscione, Stephen|Leith, Andrew|Huynh, Quyen|Huffer, Fred|Neretti, Nicola', 'Naval Surface Warfare Center Panama City Division, Panama City, Florida, United States of America.|Department of Molecular Biology, Cell Biology and Biochemistry, Brown University, Providence, Rhode Island, United States of America.|Department of Molecular Biology, Cell Biology and Biochemistry, Brown University, Providence, Rhode Island, United States of America.|Institute for Brain and Neural Systems, Brown University, Providence, Rhode Island, United States of America.|Department of Statistics, Florida State University, Tallahassee, Florida, United States of America.|Department of Molecular Biology, Cell Biology and Biochemistry, Brown University, Providence, Rhode Island, United States of America.', 'Panama|United States|United States|United States|United States|United States', 0, 'Algorithms|Chromosome Mapping|Computer Simulation|Genome|High-Throughput Nucleotide Sequencing|Models, Genetic|Models, Statistical|Sequence Alignment|Sequence Analysis, DNA|Sequence Homology, Nucleic Acid|Software', 'Journal Article', '10.1371/journal.pcbi.1005586', '28617797', 'A common problem in genomics is to test for associations between two or more genomic features, typically represented as intervals interspersed across the genome. Existing methodologies can test for significant pairwise associations between two genomic intervals, however, they cannot test for associations involving multiple sets of intervals. This limits our ability to uncover more complex, yet biologically important associations between multiple sets of genomic features. We introduce GINOM (Genomic INterval Overlap Model), a new method that enables testing of significant associations between multiple genomic features. We demonstrate GINOMs ability to identify higher-order associations with both simulated and real data. In particular, we used GINOM to explore L1 retrotransposable element insertion bias in lung cancer and found a significant pairwise association between L1 insertions and heterochromatic marks. Unlike other methods, GINOM also detected an association between L1 insertions and gene bodies marked by a facultative heterochromatic mark, which could explain the observed bias for L1 insertions towards cancer-associated genes.'),
(88489, 2017, 'plos', 'Robust transmission of rate coding in the inhibitory Purkinje cell to cerebellar nuclei pathway in awake mice', 'Abbasi, Samira|Hudson, Amber E|Maran, Selva K|Cao, Ying|Abbasi, Ataollah|Heck, Detlef H|Jaeger, Dieter', 'Department of Biology, Emory University, Atlanta, GA, United States of America.|Department of Biology, Emory University, Atlanta, GA, United States of America.|Department of Biology, Emory University, Atlanta, GA, United States of America.|Department of Anatomy and Neurobiology, University of Tennessee Health Science Center, Memphis, Tennessee, United States of America.|Computational Neuroscience Laboratory, Department of Biomedical Engineering, Faculty of Electrical Engineering, Sahand University of Technology, Tabriz, Iran.|Department of Anatomy and Neurobiology, University of Tennessee Health Science Center, Memphis, Tennessee, United States of America.|Department of Biology, Emory University, Atlanta, GA, United States of America.', 'United States|United States|United States|United States|-|United States|United States', 3, 'Action Potentials|Animals|Cerebellar Nuclei|Computer Simulation|Female|Male|Mice|Mice, Inbred C57BL|Models, Neurological|Nerve Net|Neural Inhibition|Neural Pathways|Purkinje Cells|Wakefulness', 'Journal Article', '10.1371/journal.pcbi.1005578', '28617798', 'Neural coding through inhibitory projection pathways remains poorly understood. We analyze the transmission properties of the Purkinje cell (PC) to cerebellar nucleus (CN) pathway in a modeling study using a data set recorded in awake mice containing respiratory rate modulation. We find that inhibitory transmission from tonically active PCs can transmit a behavioral rate code with high fidelity. We parameterized the required population code in PC activity and determined that 20% of PC inputs to a full compartmental CN neuron model need to be rate-comodulated for transmission of a rate code. Rate covariance in PC inputs also accounts for the high coefficient of variation in CN spike trains, while the balance between excitation and inhibition determines spike rate and local spike train variability. Overall, our modeling study can fully account for observed spike train properties of cerebellar output in awake mice, and strongly supports rate coding in the cerebellum.'),
(88490, 2017, 'plos', 'Inferring repeat-protein energetics from evolutionary information', 'Espada, Rocío|Parra, R Gonzalo|Mora, Thierry|Walczak, Aleksandra M|Ferreiro, Diego U', 'Protein Physiology Lab, Universidad de Buenos Aires, Facultad de Ciencias Exactas y Naturales, Departamento de Química Biológica. Buenos Aires, Argentina. / CONICET - Universidad de Buenos Aires. Instituto de Química Biológica de la Facultad de Ciencias Exactas y Naturales (IQUIBICEN). Buenos Aires, Argentina.|Quantitative and Computational Biology Group, Max Planck Institute for Biophysical Chemistry, Goettingen, Germany.|Laboratoire de physique statistique, Ecole Normale Supérieure, CNRS and UPMC, 75005 Paris, France.|CNRS and Laboratoire de Physique Théorique, Ecole Normale Supérieure, Paris, France.|Protein Physiology Lab, Universidad de Buenos Aires, Facultad de Ciencias Exactas y Naturales, Departamento de Química Biológica. Buenos Aires, Argentina. / CONICET - Universidad de Buenos Aires. Instituto de Química Biológica de la Facultad de Ciencias Exactas y Naturales (IQUIBICEN). Buenos Aires, Argentina.', 'Argentina|Germany|France|France|Argentina', 0, 'Energy Transfer|Evolution, Chemical|Models, Chemical|Models, Molecular|Point Mutation|Protein Conformation|Protein Folding|Proteins|Repetitive Sequences, Amino Acid|Sequence Analysis, Protein|Structure-Activity Relationship', 'Journal Article', '10.1371/journal.pcbi.1005584', '28617812', 'Natural protein sequences contain a record of their history. A common constraint in a given protein family is the ability to fold to specific structures, and it has been shown possible to infer the main native ensemble by analyzing covariations in extant sequences. Still, many natural proteins that fold into the same structural topology show different stabilization energies, and these are often related to their physiological behavior. We propose a description for the energetic variation given by sequence modifications in repeat proteins, systems for which the overall problem is simplified by their inherent symmetry. We explicitly account for single amino acid and pair-wise interactions and treat higher order correlations with a single term. We show that the resulting evolutionary field can be interpreted with structural detail. We trace the variations in the energetic scores of natural proteins and relate them to their experimental characterization. The resulting energetic evolutionary field allows the prediction of the folding free energy change for several mutants, and can be used to generate synthetic sequences that are statistically indistinguishable from the natural counterparts.'),
(88491, 2017, 'plos', 'Molecular determinants for the thermodynamic and functional divergence of uniporter GLUT1 and proton symporter XylE', 'Ke, Meng|Yuan, Yafei|Jiang, Xin|Yan, Nieng|Gong, Haipeng', 'MOE Key Laboratory of Bioinformatics, Tsinghua University, Beijing, China.|State Key Laboratory of Bio-membrane and Membrane Biotechnology, Tsinghua University, Beijing, China.|State Key Laboratory of Bio-membrane and Membrane Biotechnology, Tsinghua University, Beijing, China.|State Key Laboratory of Bio-membrane and Membrane Biotechnology, Tsinghua University, Beijing, China.|MOE Key Laboratory of Bioinformatics, Tsinghua University, Beijing, China.', 'China|China|China|China|China', 0, 'Energy Transfer|Escherichia coli Proteins|Glucose Transporter Type 1|Humans|Models, Chemical|Molecular Dynamics Simulation|Protein Binding|Protein Conformation|Structure-Activity Relationship|Symporters|Thermodynamics', 'Comparative Study', '10.1371/journal.pcbi.1005603', '28617850', 'GLUT1 facilitates the down-gradient translocation of D-glucose across cell membrane in mammals. XylE, an Escherichia coli homolog of GLUT1, utilizes proton gradient as an energy source to drive uphill D-xylose transport. Previous studies of XylE and GLUT1 suggest that the variation between an acidic residue (Asp27 in XylE) and a neutral one (Asn29 in GLUT1) is a key element for their mechanistic divergence. In this work, we combined computational and biochemical approaches to investigate the mechanism of proton coupling by XylE and the functional divergence between GLUT1 and XylE. Using molecular dynamics simulations, we evaluated the free energy profiles of the transition between inward- and outward-facing conformations for the apo proteins. Our results revealed the correlation between the protonation state and conformational preference in XylE, which is supported by the crystal structures. In addition, our simulations suggested a thermodynamic difference between XylE and GLUT1 that cannot be explained by the single residue variation at the protonation site. To understand the molecular basis, we applied Bayesian network models to analyze the alteration in the architecture of the hydrogen bond networks during conformational transition. The models and subsequent experimental validation suggest that multiple residue substitutions are required to produce the thermodynamic and functional distinction between XylE and GLUT1. Despite the lack of simulation studies with substrates, these computational and biochemical characterizations provide unprecedented insight into the mechanistic difference between proton symporters and uniporters.'),
(88492, 2017, 'plos', 'Sensory noise predicts divisive reshaping of receptive fields', 'Chalk, Matthew|Masset, Paul|Deneve, Sophie|Gutkin, Boris', 'Institute of Science and Technology Austria, Klosterneuburg, Austria.|Department of Neuroscience, Cold Spring Harbor Laboratory, Cold Spring Harbor, New York, United States of America.|National Research University Higher School of Economics, Center for Cognition and Decision Making, Moscow, Russia.|National Research University Higher School of Economics, Center for Cognition and Decision Making, Moscow, Russia.', 'Austria|United States|-|-', 4, 'Animals|Computer Simulation|Cues|Humans|Models, Neurological|Models, Statistical|Nerve Net|Neuronal Plasticity|Retinal Ganglion Cells|Signal-To-Noise Ratio|Visual Fields|Visual Perception', 'Journal Article', '10.1371/journal.pcbi.1005582', '28622330', 'In order to respond reliably to specific features of their environment, sensory neurons need to integrate multiple incoming noisy signals. Crucially, they also need to compete for the interpretation of those signals with other neurons representing similar features. The form that this competition should take depends critically on the noise corrupting these signals. In this study we show that for the type of noise commonly observed in sensory systems, whose variance scales with the mean signal, sensory neurons should selectively divide their input signals by their predictions, suppressing ambiguous cues while amplifying others. Any change in the stimulus context alters which inputs are suppressed, leading to a deep dynamic reshaping of neural receptive fields going far beyond simple surround suppression. Paradoxically, these highly variable receptive fields go alongside and are in fact required for an invariant representation of external sensory features. In addition to offering a normative account of context-dependent changes in sensory responses, perceptual inference in the presence of signal-dependent noise accounts for ubiquitous features of sensory neurons such as divisive normalization, gain control and contrast dependent temporal dynamics.'),
(88493, 2017, 'plos', 'In silico assessment of genetic variation in KCNA5 reveals multiple mechanisms of human atrial arrhythmogenesis', 'Colman, Michael A|Ni, Haibo|Liang, Bo|Schmitt, Nicole|Zhang, Henggui', 'Biological Physics Group, School of Physics and Astronomy, University of Manchester, Manchester, United Kingdom.|Biological Physics Group, School of Physics and Astronomy, University of Manchester, Manchester, United Kingdom.|Department of Biomedical Sciences, Faculty of Health and Medical Sciences, University of Copenhagen, Copenhagen, Denmark.|Department of Biomedical Sciences, Faculty of Health and Medical Sciences, University of Copenhagen, Copenhagen, Denmark.|Biological Physics Group, School of Physics and Astronomy, University of Manchester, Manchester, United Kingdom.', 'United Kingdom|United Kingdom|Denmark|Denmark|United Kingdom', 16, 'Atrial Fibrillation|Computer Simulation|Genetic Variation|Heart Conduction System|Humans|Ion Channel Gating|Kv1.5 Potassium Channel|Models, Cardiovascular|Models, Genetic|Mutation|Polymorphism, Single Nucleotide|Signal Transduction|Structure-Activity Relationship', 'Journal Article', '10.1371/journal.pcbi.1005587', '28622331', 'A recent experimental study investigating patients with lone atrial fibrillation identified six novel mutations in the KCNA5 gene. The mutants exhibited both gain- and loss-of-function of the atrial specific ultra-rapid delayed rectifier K+ current, IKur. The aim of this study is to elucidate and quantify the functional impact of these KCNA5 mutations on atrial electrical activity. A multi-scale model of the human atria was updated to incorporate detailed experimental data on IKur from both wild-type and mutants. The effects of the mutations on human atrial action potential and rate dependence were investigated at the cellular level. In tissue, we assessed the effects of the mutations on the vulnerability to unidirectional conduction patterns and dynamics of re-entrant excitation waves. Gain-of-function mutations shortened the action potential duration in single cells, and stabilised and accelerated re-entrant excitation in tissue. Loss-of-function mutations had heterogeneous effects on action potential duration and promoted early-after-depolarisations following beta-adrenergic stimulation. In the tissue model, loss-of-function mutations facilitated breakdown of excitation waves at more physiological excitation rates than the wild-type, and the generation of early-after-depolarisations promoted unidirectional patterns of excitation. Gain- and loss-of-function IKur mutations produced multiple mechanisms of atrial arrhythmogenesis, with significant differences between the two groups of mutations. This study provides new insights into understanding the mechanisms by which mutant IKur contributes to atrial arrhythmias. In addition, as IKur is an atrial-specific channel and a number of IKur-selective blockers have been developed as anti-AF agents, this study also helps to understand some contradictory results on both pro- and anti-arrhythmic effects of blocking IKur.'),
(88494, 2017, 'plos', 'A knowledge-based T2-statistic to perform pathway analysis for quantitative proteomic data', 'Lai, En-Yu|Chen, Yi-Hau|Wu, Kun-Pin', 'Institute of Biomedical Informatics, National Yang-Ming University, Taipei 11221, Taiwan.|Institute of Statistical Science, Academia Sinica, Taipei 11529, Taiwan.|Institute of Biomedical Informatics, National Yang-Ming University, Taipei 11221, Taiwan.', '-|-|-', 0, 'Algorithms|Computer Simulation|Data Interpretation, Statistical|Knowledge Bases|Models, Biological|Models, Statistical|Proteome|Proteomics|Signal Transduction', 'Journal Article', '10.1371/journal.pcbi.1005601', '28622336', 'Approaches to identify significant pathways from high-throughput quantitative data have been developed in recent years. Still, the analysis of proteomic data stays difficult because of limited sample size. This limitation also leads to the practice of using a competitive null as common approach, which fundamentally implies genes or proteins as independent units. The independent assumption ignores the associations among biomolecules with similar functions or cellular localization, as well as the interactions among them manifested as changes in expression ratios. Consequently, these methods often underestimate the associations among biomolecules and cause false positives in practice. Some studies incorporate the sample covariance matrix into the calculation to address this issue. However, sample covariance may not be a precise estimation if the sample size is very limited, which is usually the case for the data produced by mass spectrometry. In this study, we introduce a multivariate test under a self-contained null to perform pathway analysis for quantitative proteomic data. The covariance matrix used in the test statistic is constructed by the confidence scores retrieved from the STRING database or the HitPredict database. We also design an integrating procedure to retain pathways of sufficient evidence as a pathway group. The performance of the proposed T2-statistic is demonstrated using five published experimental datasets: the T-cell activation, the cAMP/PKA signaling, the myoblast differentiation, and the effect of dasatinib on the BCR-ABL pathway are proteomic datasets produced by mass spectrometry, and the protective effect of myocilin via the MAPK signaling pathway is a gene expression dataset of limited sample size. Compared with other popular statistics, the proposed T2-statistic yields more accurate descriptions in agreement with the discussion of the original publication. We implemented the T2-statistic into an R package T2GA, which is available at https://github.com/roqe/T2GA.'),
(88495, 2017, 'plos', 'Solving the influence maximization problem reveals regulatory organization of the yeast cell cycle', 'Gibbs, David L|Shmulevich, Ilya', 'Institute for Systems Biology, Seattle, Washington, United States of America.|Institute for Systems Biology, Seattle, Washington, United States of America.', 'United States|United States', 2, 'Algorithms|Cell Cycle|Cell Cycle Proteins|Computer Simulation|Gene Expression Regulation, Fungal|Models, Biological|Saccharomyces cerevisiae|Saccharomyces cerevisiae Proteins|Signal Transduction', 'Journal Article', '10.1371/journal.pcbi.1005591', '28628618', 'The Influence Maximization Problem (IMP) aims to discover the set of nodes with the greatest influence on network dynamics. The problem has previously been applied in epidemiology and social network analysis. Here, we demonstrate the application to cell cycle regulatory network analysis for Saccharomyces cerevisiae. Fundamentally, gene regulation is linked to the flow of information. Therefore, our implementation of the IMP was framed as an information theoretic problem using network diffusion. Utilizing more than 26,000 regulatory edges from YeastMine, gene expression dynamics were encoded as edge weights using time lagged transfer entropy, a method for quantifying information transfer between variables. By picking a set of source nodes, a diffusion process covers a portion of the network. The size of the network cover relates to the influence of the source nodes. The set of nodes that maximizes influence is the solution to the IMP. By solving the IMP over different numbers of source nodes, an influence ranking on genes was produced. The influence ranking was compared to other metrics of network centrality. Although the top genes from each centrality ranking contained well-known cell cycle regulators, there was little agreement and no clear winner. However, it was found that influential genes tend to directly regulate or sit upstream of genes ranked by other centrality measures. The influential nodes act as critical sources of information flow, potentially having a large impact on the state of the network. Biological events that affect influential nodes and thereby affect information flow could have a strong effect on network dynamics, potentially leading to disease. Code and data can be found at: https://github.com/gibbsdavidl/miergolf.'),
(88496, 2017, 'plos', 'An efficient coding theory for a dynamic trajectory predicts non-uniform allocation of entorhinal grid cells to modules', 'Mosheiff, Noga|Agmon, Haggai|Moriel, Avraham|Burak, Yoram', 'Racah Institute of Physics, Hebrew University of Jerusalem, Jerusalem, Israel.|Edmond and Lily Safra Center for Brain Sciences, Hebrew University of Jerusalem, Jerusalem, Israel.|Racah Institute of Physics, Hebrew University of Jerusalem, Jerusalem, Israel.|Racah Institute of Physics, Hebrew University of Jerusalem, Jerusalem, Israel.', 'Israel|Israel|Israel|Israel', 4, 'Animals|Computer Simulation|Entorhinal Cortex|Grid Cells|Models, Neurological|Orientation|Rats|Space Perception|Spatial Navigation|Spatio-Temporal Analysis', 'Journal Article', '10.1371/journal.pcbi.1005597', '28628647', 'Grid cells in the entorhinal cortex encode the position of an animal in its environment with spatially periodic tuning curves with different periodicities. Recent experiments established that these cells are functionally organized in discrete modules with uniform grid spacing. Here we develop a theory for efficient coding of position, which takes into account the temporal statistics of the animals motion. The theory predicts a sharp decrease of module population sizes with grid spacing, in agreement with the trend seen in the experimental data. We identify a simple scheme for readout of the grid cell code by neural circuitry, that can match in accuracy the optimal Bayesian decoder. This readout scheme requires persistence over different timescales, depending on the grid cell module. Thus, we propose that the brain may employ an efficient representation of position which takes advantage of the spatiotemporal statistics of the encoded variable, in similarity to the principles that govern early sensory processing.'),
(88497, 2017, 'plos', 'Brain network eigenmodes provide a robust and compact representation of the structural connectome in health and disease', 'Wang, Maxwell B|Owen, Julia P|Mukherjee, Pratik|Raj, Ashish', 'Department of Radiology & Biomedical Imaging, University of California, San Francisco, California, United States of America.|Department of Radiology & Biomedical Imaging, University of California, San Francisco, California, United States of America.|Department of Radiology & Biomedical Imaging, University of California, San Francisco, California, United States of America.|Department of Radiology, Weill Cornell Medical College, New York, New York, United States of America.', 'United States|United States|United States|United States', 15, 'Adult|Agenesis of Corpus Callosum|Brain|Brain Diseases|Connectome|Diffusion Tensor Imaging|Female|Humans|Image Interpretation, Computer-Assisted|Male|Nerve Net|Neural Pathways|Reproducibility of Results|Sensitivity and Specificity|White Matter', 'Journal Article', '10.1371/journal.pcbi.1005550', '28640803', 'Recent research has demonstrated the use of the structural connectome as a powerful tool to characterize the network architecture of the brain and potentially generate biomarkers for neurologic and psychiatric disorders. In particular, the anatomic embedding of the edges of the cerebral graph have been postulated to elucidate the relative importance of white matter tracts to the overall network connectivity, explaining the varying effects of localized white matter pathology on cognition and behavior. Here, we demonstrate the use of a linear diffusion model to quantify the impact of these perturbations on brain connectivity. We show that the eigenmodes governing the dynamics of this model are strongly conserved between healthy subjects regardless of cortical and sub-cortical parcellations, but show significant, interpretable deviations in improperly developed brains. More specifically, we investigated the effect of agenesis of the corpus callosum (AgCC), one of the most common brain malformations to identify differences in the effect of virtual corpus callosotomies and the neurodevelopmental disorder itself. These findings, including the strong correspondence between regions of highest importance from graph eigenmodes of network diffusion and nexus regions of white matter from edge density imaging, show converging evidence toward understanding the relationship between white matter anatomy and the structural connectome.'),
(88498, 2017, 'plos', 'Boolean analysis reveals systematic interactions among low-abundance species in the human gut microbiome', 'Claussen, Jens Christian|Skiecevixc4x8dienxc4x97, Jurgita|Wang, Jun|Rausch, Philipp|Karlsen, Tom H|Lieb, Wolfgang|Baines, John F|Franke, Andre|Hxc3xbctt, Marc-Thorsten', 'Computational Systems Biology, Department of Life Sciences and Chemistry, Jacobs University Bremen, Campus Ring 1, D-28759 Bremen, Germany.|Institute for Digestive Research, Lithuanian University of Health Sciences, Kaunas, Lithuania.|Institute for Experimental Medicine, Christian Albrechts University of Kiel, Kiel, Germany.|Institute for Experimental Medicine, Christian Albrechts University of Kiel, Kiel, Germany.|Institute of Clinical Medicine, Faculty of Medicine, University of Oslo, Postbox 1171 Blindern, 0318 Oslo, Norway.|Institute of Epidemiology and Biobank PopGen, Christian Albrechts University of Kiel, Kiel, Germany.|Institute for Experimental Medicine, Christian Albrechts University of Kiel, Kiel, Germany.|Institute for Digestive Research, Lithuanian University of Health Sciences, Kaunas, Lithuania.|Computational Systems Biology, Department of Life Sciences and Chemistry, Jacobs University Bremen, Campus Ring 1, D-28759 Bremen, Germany.', 'Germany|Lithuania|Germany|Germany|Norway|Germany|Germany|Lithuania|Germany', 0, 'Bacterial Load|Computer Simulation|Data Interpretation, Statistical|Gastrointestinal Microbiome|Gastrointestinal Tract|Humans|Metagenome|Microbial Interactions|Microbiota|Models, Biological|Models, Statistical|Pattern Recognition, Automated', 'Journal Article', '10.1371/journal.pcbi.1005361', '28640804', 'The analysis of microbiome compositions in the human gut has gained increasing interest due to the broader availability of data and functional databases and substantial progress in data analysis methods, but also due to the high relevance of the microbiome in human health and disease. While most analyses infer interactions among highly abundant species, the large number of low-abundance species has received less attention. Here we present a novel analysis method based on Boolean operations applied to microbial co-occurrence patterns. We calibrate our approach with simulated data based on a dynamical Boolean network model from which we interpret the statistics of attractor states as a theoretical proxy for microbiome composition. We show that for given fractions of synergistic and competitive interactions in the model our Boolean abundance analysis can reliably detect these interactions. Analyzing a novel data set of 822 microbiome compositions of the human gut, we find a large number of highly significant synergistic interactions among these low-abundance species, forming a connected network, and a few isolated competitive interactions.'),
(88499, 2017, 'plos', 'High-confidence assessment of functional impact of human mitochondrial non-synonymous genome variations by APOGEE', 'Castellana, Stefano|Fusilli, Caterina|Mazzoccoli, Gianluigi|Biagini, Tommaso|Capocefalo, Daniele|Carella, Massimo|Vescovi, Angelo Luigi|Mazza, Tommaso', 'IRCCS Casa Sollievo della Sofferenza, Bioinformatics unit, San Giovanni Rotondo (FG), Italy.|IRCCS Casa Sollievo della Sofferenza, Bioinformatics unit, San Giovanni Rotondo (FG), Italy.|IRCCS Casa Sollievo della Sofferenza, Department of Medical Sciences, Division of Internal Medicine, San Giovanni Rotondo (FG), Italy.|IRCCS Casa Sollievo della Sofferenza, Bioinformatics unit, San Giovanni Rotondo (FG), Italy.|IRCCS Casa Sollievo della Sofferenza, Bioinformatics unit, San Giovanni Rotondo (FG), Italy.|IRCCS Casa Sollievo della Sofferenza, Medical Genetics unit, San Giovanni Rotondo (FG), Italy.|IRCSS Casa Sollievo della Sofferenza, ISBReMIT- Institute for Stem Cell Biology, Regenerative Medicine and Innovative Therapies, San Giovanni Rotondo (FG), Italy.|IRCCS Casa Sollievo della Sofferenza, Bioinformatics unit, San Giovanni Rotondo (FG), Italy.', 'Italy|Italy|Italy|Italy|Italy|Italy|Italy|Italy', 11, 'Algorithms|Chromosome Mapping|DNA Mutational Analysis|Genetic Variation|Genome, Human|Genome, Mitochondrial|Humans|Machine Learning|Pattern Recognition, Automated|Reproducibility of Results|Sensitivity and Specificity|Software', 'Journal Article', '10.1371/journal.pcbi.1005628', '28640805', '24,189 are all the possible non-synonymous amino acid changes potentially affecting the human mitochondrial DNA. Only a tiny subset was functionally evaluated with certainty so far, while the pathogenicity of the vast majority was only assessed in-silico by software predictors. Since these tools proved to be rather incongruent, we have designed and implemented APOGEE, a machine-learning algorithm that outperforms all existing prediction methods in estimating the harmfulness of mitochondrial non-synonymous genome variations. We provide a detailed description of the underlying algorithm, of the selected and manually curated training and test sets of variants, as well as of its classification ability.'),
(88500, 2017, 'plos', 'Good enough practices in scientific computing', 'Wilson, Greg|Bryan, Jennifer|Cranston, Karen|Kitzes, Justin|Nederbragt, Lex|Teal, Tracy K', 'Software Carpentry Foundation, Austin, Texas, United States of America.|RStudio and Department of Statistics, University of British Columbia, Vancouver, British Columbia, Canada.|Department of Biology, Duke University, Durham, North Carolina, United States of America.|Energy and Resources Group, University of California, Berkeley, Berkeley, California, United States of America.|Centre for Ecological and Evolutionary Synthesis, University of Oslo, Oslo, Norway.|Data Carpentry, Davis, California, United States of America.', 'United States|Canada|United States|United States|Norway|United States', 0, 'Computer Security|Computing Methodologies|Data Accuracy|Documentation|Guidelines as Topic|Research|Science|Software', 'Journal Article', '10.1371/journal.pcbi.1005510', '28640806', 'Computers are now essential in all branches of science, but most researchers are never taught the equivalent of basic lab skills for research computing. As a result, data can get lost, analyses can take much longer than necessary, and researchers are limited in how effectively they can work with software and data. Computing workflows need to follow the same practices as lab projects and notebooks, with organized data, documented steps, and the project structured for reproducibility, but researchers new to computing often dont know where to start. This paper presents a set of good computing practices that every researcher can adopt, regardless of their current level of computational skill. These practices, which encompass data management, programming, collaborating with colleagues, organizing projects, tracking work, and writing manuscripts, are drawn from a wide variety of published sources from our daily lives and from our work with volunteer organizations that have delivered workshops to over 11,000 people since 2010.'),
(88501, 2017, 'plos', 'Transmembrane helical interactions in the CFTR channel pore', 'Das, Jhuma|Aleksandrov, Andrei A|Cui, Liying|He, Lihua|Riordan, John R|Dokholyan, Nikolay V', 'Department of Biochemistry and Biophysics, University of North Carolina at Chapel Hill, Chapel Hill, North Carolina, United States of America.|Department of Biochemistry and Biophysics, University of North Carolina at Chapel Hill, Chapel Hill, North Carolina, United States of America.|Department of Biochemistry and Biophysics, University of North Carolina at Chapel Hill, Chapel Hill, North Carolina, United States of America.|Department of Biochemistry and Biophysics, University of North Carolina at Chapel Hill, Chapel Hill, North Carolina, United States of America.|Department of Biochemistry and Biophysics, University of North Carolina at Chapel Hill, Chapel Hill, North Carolina, United States of America.|Department of Biochemistry and Biophysics, University of North Carolina at Chapel Hill, Chapel Hill, North Carolina, United States of America.', 'United States|United States|United States|United States|United States|United States', 0, 'Amino Acid Motifs|Binding Sites|Cell Membrane|Cell Membrane Permeability|Chlorine|Cystic Fibrosis Transmembrane Conductance Regulator|Diffusion|Models, Chemical|Molecular Dynamics Simulation|Protein Binding', 'Journal Article', '10.1371/journal.pcbi.1005594', '28640808', 'Mutations in the Cystic Fibrosis Transmembrane Conductance Regulator (CFTR) gene affect CFTR protein biogenesis or its function as a chloride channel, resulting in dysregulation of epithelial fluid transport in the lung, pancreas and other organs in cystic fibrosis (CF). Development of pharmaceutical strategies to treat CF requires understanding of the mechanisms underlying channel function. However, incomplete 3D structural information on the unique ABC ion channel, CFTR, hinders elucidation of its functional mechanism and correction of cystic fibrosis causing mutants. Several CFTR homology models have been developed using bacterial ABC transporters as templates but these have low sequence similarity to CFTR and are not ion channels. Here, we refine an earlier model in an outward (OWF) and develop an inward (IWF) facing model employing an integrated experimental-molecular dynamics simulation (200 ns) approach. Our IWF structure agrees well with a recently solved cryo-EM structure of a CFTR IWF state. We utilize cysteine cross-linking to verify positions and orientations of residues within trans-membrane helices (TMHs) of the OWF conformation and to reconstruct a physiologically relevant pore structure. Comparison of pore profiles of the two conformations reveal a radius sufficient to permit passage of hydrated Cl- ions in the OWF but not the IWF model. To identify structural determinants that distinguish the two conformations and possible rearrangements of TMHs within them responsible for channel gating, we perform cross-linking by bifunctional reagents of multiple predicted pairs of cysteines in TMH 6 and 12 and 6 and 9. To determine whether the effects of cross-linking on gating observed are the result of switching of the channel from open to close state, we also treat the same residue pairs with monofunctional reagents in separate experiments. Both types of reagents prevent ion currents indicating that pore blockage is primarily responsible.');
INSERT INTO `papers` (`id`, `ano`, `journal`, `titulo`, `autores`, `afiliacao`, `pais`, `citacoes`, `palavra_chave`, `categorias`, `doi`, `pubmed`, `abstract`) VALUES
(88502, 2017, 'plos', 'LASSIM-A network inference toolbox for genome-wide mechanistic modeling', 'Magnusson, Rasmus|Mariotti, Guido Pio|Köpsén, Mattias|Lövfors, William|Gawel, Danuta R|Jörnsten, Rebecka|Linde, Jörg|Nordling, Torbjörn E M|Nyman, Elin|Schulze, Sylvie|Nestor, Colm E|Zhang, Huan|Cedersund, Gunnar|Benson, Mikael|Tjärnberg, Andreas|Gustafsson, Mika', 'Bioinformatics Unit, Department of Physics, Chemistry and Biology, Linköping University, Linköping, Sweden.|Bioinformatics Unit, Department of Physics, Chemistry and Biology, Linköping University, Linköping, Sweden.|Centre for Personalised Medicine, Department of Clinical and Experimental Medicine, Linköping University, Linköping, Sweden.|Centre for Personalised Medicine, Department of Clinical and Experimental Medicine, Linköping University, Linköping, Sweden.|Centre for Personalised Medicine, Department of Clinical and Experimental Medicine, Linköping University, Linköping, Sweden.|Mathematical Sciences, Chalmers University of Technology, University of Gothenburg, Gothenburg, Sweden.|Leibniz-Institute for Natural Product Research and Infection Biology, Hans-Knoell-Institute, Research Group Systems Biology and Bioinformatics, Jena, Germany.|Department of Mechanical Engineering, National Cheng Kung University, Tainan, Taiwan.|Integrative Systems Biology, Department of Biomedical Engineering, Linköping University, Linköping, Sweden.|Leibniz-Institute for Natural Product Research and Infection Biology, Hans-Knoell-Institute, Research Group Systems Biology and Bioinformatics, Jena, Germany.|Centre for Personalised Medicine, Department of Clinical and Experimental Medicine, Linköping University, Linköping, Sweden.|Centre for Personalised Medicine, Department of Clinical and Experimental Medicine, Linköping University, Linköping, Sweden.|Integrative Systems Biology, Department of Biomedical Engineering, Linköping University, Linköping, Sweden.|Centre for Personalised Medicine, Department of Clinical and Experimental Medicine, Linköping University, Linköping, Sweden.|Bioinformatics Unit, Department of Physics, Chemistry and Biology, Linköping University, Linköping, Sweden.|Bioinformatics Unit, Department of Physics, Chemistry and Biology, Linköping University, Linköping, Sweden.', 'Sweden|Sweden|Sweden|Sweden|Sweden|Sweden|Germany|-|Sweden|Germany|Sweden|Sweden|Sweden|Sweden|Swede', 2, 'Algorithms|Cell Differentiation|Cells, Cultured|Chromosome Mapping|Computer Simulation|Gene Expression Regulation, Developmental|Humans|Models, Genetic|Programming Languages|Proteome|Signal Transduction|Software|Th2 Cells', 'Journal Article', '10.1371/journal.pcbi.1005608', '28640810', 'Recent technological advancements have made time-resolved, quantitative, multi-omics data available for many model systems, which could be integrated for systems pharmacokinetic use. Here, we present large-scale simulation modeling (LASSIM), which is a novel mathematical tool for performing large-scale inference using mechanistically defined ordinary differential equations (ODE) for gene regulatory networks (GRNs). LASSIM integrates structural knowledge about regulatory interactions and non-linear equations with multiple steady state and dynamic response expression datasets. The rationale behind LASSIM is that biological GRNs can be simplified using a limited subset of core genes that are assumed to regulate all other gene transcription events in the network. The LASSIM method is implemented as a general-purpose toolbox using the PyGMO Python package to make the most of multicore computers and high performance clusters, and is available at https://gitlab.com/Gustafsson-lab/lassim. As a method, LASSIM works in two steps, where it first infers a non-linear ODE system of the pre-specified core gene expression. Second, LASSIM in parallel optimizes the parameters that model the regulation of peripheral genes by core system genes. We showed the usefulness of this method by applying LASSIM to infer a large-scale non-linear model of naïve Th2 cell differentiation, made possible by integrating Th2 specific bindings, time-series together with six public and six novel siRNA-mediated knock-down experiments. ChIP-seq showed significant overlap for all tested transcription factors. Next, we performed novel time-series measurements of total T-cells during differentiation towards Th2 and verified that our LASSIM model could monitor those data significantly better than comparable models that used the same Th2 bindings. In summary, the LASSIM toolbox opens the door to a new type of model-based data analysis that combines the strengths of reliable mechanistic models with truly systems-level data. We demonstrate the power of this approach by inferring a mechanistically motivated, genome-wide model of the Th2 transcription regulatory system, which plays an important role in several immune related diseases.'),
(88503, 2017, 'plos', 'A novel algorithm identifies stress-induced alterations in mitochondrial connectivity and inner membrane structure from confocal images', 'Ouellet, Mathieu|Guillebaud, Gérald|Gervais, Valerie|Lupien St-Pierre, David|Germain, Marc', 'Département de Chimie, Biochimie et Physique, Université du Québec à Trois-Rivières, Trois-Rivières, Quebec, Canada.|Groupe de Recherche en Signalisation Cellulaire, Université du Québec à Trois-Rivières, Trois-Rivières, Quebec, Canada.|Département de Biologie Médicale, Université du Québec à Trois-Rivières, Trois-Rivières, Quebec, Canada.|Département de Génie Industriel, Université du Québec à Trois-Rivières, Trois-Rivières, Quebec, Canada.|Groupe de Recherche en Signalisation Cellulaire, Université du Québec à Trois-Rivières, Trois-Rivières, Quebec, Canada.', 'Canada|Canada|Canada|Canada|Canada', 0, 'Algorithms|Image Interpretation, Computer-Assisted|Microscopy, Confocal|Mitochondria|Mitochondrial Membranes|Stress, Physiological', 'Journal Article', '10.1371/journal.pcbi.1005612', '28640814', 'Mitochondria exist as a highly interconnected network that is exquisitely sensitive to variations in nutrient availability, as well as a large array of cellular stresses. Changes in length and connectivity of this network, as well as alterations in the mitochondrial inner membrane (cristae), regulate cell fate by controlling metabolism, proliferation, differentiation, and cell death. Given the key roles of mitochondrial dynamics, the process by which mitochondria constantly fuse and fragment, the measure of mitochondrial length and connectivity provides crucial information on the health and activity of various cell populations. However, despite the importance of accurately measuring mitochondrial networks, the tools required to rapidly and accurately provide this information are lacking. Here, we developed a novel probabilistic approach to automatically measure mitochondrial length distribution and connectivity from confocal images. This method accurately identified mitochondrial changes caused by starvation or the inhibition of mitochondrial function. In addition, we successfully used the algorithm to measure changes in mitochondrial inner membrane/matrix occurring in response to Complex III inhibitors. As cristae rearrangements play a critical role in metabolic regulation and cell survival, this provides a rapid method to screen for proteins or compounds affecting this process. The algorithm will thus provide a robust tool to dissect the molecular mechanisms underlying the key roles of mitochondria in the regulation of cell fate.'),
(88504, 2017, 'plos', 'Olfactory learning without the mushroom bodies: Spiking neural network models of the honeybee lateral antennal lobe tract reveal its capacities in odour memory tasks of varied complexities', 'MaBouDi, HaDi|Shimazaki, Hideaki|Giurfa, Martin|Chittka, Lars', 'School of Biological and Chemical Sciences, Queen Mary University of London, London, United Kingdom.|RIKEN Brain Science Institute, Saitama, Japan.|Research Centre on Animal Cognition, Center for Integrative Biology, CNRS, University of Toulouse, Toulouse, France.|School of Biological and Chemical Sciences, Queen Mary University of London, London, United Kingdom.', 'United Kingdom|Japan|France|United Kingdom', 7, 'Animals|Arthropod Antennae|Bees|Computer Simulation|Health Services Research|Learning|Memory|Mental Recall|Models, Neurological|Nerve Net|Neuronal Plasticity|Odorants|Olfactory Pathways|Olfactory Receptor Neurons|Smell|Task Performance and Analysis', 'Journal Article', '10.1371/journal.pcbi.1005551', '28640825', 'The honeybee olfactory system is a well-established model for understanding functional mechanisms of learning and memory. Olfactory stimuli are first processed in the antennal lobe, and then transferred to the mushroom body and lateral horn through dual pathways termed medial and lateral antennal lobe tracts (m-ALT and l-ALT). Recent studies reported that honeybees can perform elemental learning by associating an odour with a reward signal even after lesions in m-ALT or blocking the mushroom bodies. To test the hypothesis that the lateral pathway (l-ALT) is sufficient for elemental learning, we modelled local computation within glomeruli in antennal lobes with axons of projection neurons connecting to a decision neuron (LHN) in the lateral horn. We show that inhibitory spike-timing dependent plasticity (modelling non-associative plasticity by exposure to different stimuli) in the synapses from local neurons to projection neurons decorrelates the projection neurons outputs. The strength of the decorrelations is regulated by global inhibitory feedback within antennal lobes to the projection neurons. By additionally modelling octopaminergic modification of synaptic plasticity among local neurons in the antennal lobes and projection neurons to LHN connections, the model can discriminate and generalize olfactory stimuli. Although positive patterning can be accounted for by the l-ALT model, negative patterning requires further processing and mushroom body circuits. Thus, our model explains several-but not all-types of associative olfactory learning and generalization by a few neural layers of odour processing in the l-ALT. As an outcome of the combination between non-associative and associative learning, the modelling approach allows us to link changes in structural organization of honeybees antennal lobes with their behavioural performances over the course of their life.'),
(88505, 2017, 'plos', 'Linking structure and activity in nonlinear spiking networks', 'Ocker, Gabriel Koch|Josixc4x87, Krexc5xa1imir|Shea-Brown, Eric|Buice, Michael A', 'Allen Institute for Brain Science, Seattle, Washington, United States of America.|Department of Mathematics and Department of Biology and Biochemistry, University of Houston, Houston, Texas, 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.', 'United States|United States|United States|United States', 15, 'Action Potentials|Animals|Computer Simulation|Connectome|Humans|Models, Anatomic|Models, Neurological|Models, Statistical|Nerve Net|Nonlinear Dynamics|Structure-Activity Relationship', 'Journal Article', '10.1371/journal.pcbi.1005583', '28644840', 'Recent experimental advances are producing an avalanche of data on both neural connectivity and neural activity. To take full advantage of these two emerging datasets we need a framework that links them, revealing how collective neural activity arises from the structure of neural connectivity and intrinsic neural dynamics. This problem of structure-driven activity has drawn major interest in computational neuroscience. Existing methods for relating activity and architecture in spiking networks rely on linearizing activity around a central operating point and thus fail to capture the nonlinear responses of individual neurons that are the hallmark of neural information processing. Here, we overcome this limitation and present a new relationship between connectivity and activity in networks of nonlinear spiking neurons by developing a diagrammatic fluctuation expansion based on statistical field theory. We explicitly show how recurrent network structure produces pairwise and higher-order correlated activity, and how nonlinearities impact the networks spiking activity. Our findings open new avenues to investigating how single-neuron nonlinearities-including those of different cell types-combine with connectivity to shape population activity and function.'),
(88506, 2017, 'plos', 'Low-dimensional spike rate models derived from networks of adaptive integrate-and-fire neurons: Comparison and implementation', 'Augustin, Moritz|Ladenbauer, Josef|Baumann, Fabian|Obermayer, Klaus', 'Department of Software Engineering and Theoretical Computer Science, Technische Universität Berlin, Berlin, Germany.|Department of Software Engineering and Theoretical Computer Science, Technische Universität Berlin, Berlin, Germany.|Department of Software Engineering and Theoretical Computer Science, Technische Universität Berlin, Berlin, Germany.|Department of Software Engineering and Theoretical Computer Science, Technische Universität Berlin, Berlin, Germany.', 'Germany|Germany|Germany|Germany', 16, 'Action Potentials|Adaptation, Physiological|Animals|Computer Simulation|Humans|Models, Neurological|Models, Statistical|Nerve Net|Neuronal Plasticity|Neurons|Nonlinear Dynamics|Synaptic Transmission', 'Comparative Study', '10.1371/journal.pcbi.1005545', '28644841', 'The spiking activity of single neurons can be well described by a nonlinear integrate-and-fire model that includes somatic adaptation. When exposed to fluctuating inputs sparsely coupled populations of these model neurons exhibit stochastic collective dynamics that can be effectively characterized using the Fokker-Planck equation. This approach, however, leads to a model with an infinite-dimensional state space and non-standard boundary conditions. Here we derive from that description four simple models for the spike rate dynamics in terms of low-dimensional ordinary differential equations using two different reduction techniques: one uses the spectral decomposition of the Fokker-Planck operator, the other is based on a cascade of two linear filters and a nonlinearity, which are determined from the Fokker-Planck equation and semi-analytically approximated. We evaluate the reduced models for a wide range of biologically plausible input statistics and find that both approximation approaches lead to spike rate models that accurately reproduce the spiking behavior of the underlying adaptive integrate-and-fire population. Particularly the cascade-based models are overall most accurate and robust, especially in the sensitive region of rapidly changing input. For the mean-driven regime, when input fluctuations are not too strong and fast, however, the best performing model is based on the spectral decomposition. The low-dimensional models also well reproduce stable oscillatory spike rate dynamics that are generated either by recurrent synaptic excitation and neuronal adaptation or through delayed inhibitory synaptic feedback. The computational demands of the reduced models are very low but the implementation complexity differs between the different model variants. Therefore we have made available implementations that allow to numerically integrate the low-dimensional spike rate models as well as the Fokker-Planck partial differential equation in efficient ways for arbitrary model parametrizations as open source software. The derived spike rate descriptions retain a direct link to the properties of single neurons, allow for convenient mathematical analyses of network states, and are well suited for application in neural mass/mean-field based brain network models.'),
(88507, 2017, 'plos', 'Comorbidities in the diseasome are more apparent than real: What Bayesian filtering reveals about the comorbidities of depression', 'Marx, Peter|Antal, Peter|Bolgar, Bence|Bagdy, Gyorgy|Deakin, Bill|Juhasz, Gabriella', 'MTA-SE Neuropsychopharmacology and Neurochemistry Research Group, Hungarian Academy of Sciences, Semmelweis University, Budapest, Hungary.|Department of Measurement and Information Systems, Budapest University of Technology and Economics, Budapest, Hungary.|Department of Measurement and Information Systems, Budapest University of Technology and Economics, Budapest, Hungary.|MTA-SE Neuropsychopharmacology and Neurochemistry Research Group, Hungarian Academy of Sciences, Semmelweis University, Budapest, Hungary.|Neuroscience and Psychiatry Unit, School of Biological Sciences, Faculty of Biology Medicine and Health, The University of Manchester, Manchester, UK and Greater Manchester Mental Health NHS Foundation Trust, Manchester, UK.|MTA-SE Neuropsychopharmacology and Neurochemistry Research Group, Hungarian Academy of Sciences, Semmelweis University, Budapest, Hungary.', 'Hungary|Hungary|Hungary|Hungary|United Kingdom|Hungary', 0, 'Bayes Theorem|Comorbidity|Computer Simulation|Data Interpretation, Statistical|Data Mining|Depression|Humans|Incidence|Irritable Bowel Syndrome|Mental Disorders|Metabolic Diseases|Migraine Disorders|Models, Statistical|Neurodegenerative Diseases|Pattern Recognition, Automated|Proportional Hazards Models|Reproducibility of Results|Risk Assessment|Sensitivity and Specificity', 'Journal Article', '10.1371/journal.pcbi.1005487', '28644851', 'Comorbidity patterns have become a major source of information to explore shared mechanisms of pathogenesis between disorders. In hypothesis-free exploration of comorbid conditions, disease-disease networks are usually identified by pairwise methods. However, interpretation of the results is hindered by several confounders. In particular a very large number of pairwise associations can arise indirectly through other comorbidity associations and they increase exponentially with the increasing breadth of the investigated diseases. To investigate and filter this effect, we computed and compared pairwise approaches with a systems-based method, which constructs a sparse Bayesian direct multimorbidity map (BDMM) by systematically eliminating disease-mediated comorbidity relations. Additionally, focusing on depression-related parts of the BDMM, we evaluated correspondence with results from logistic regression, text-mining and molecular-level measures for comorbidities such as genetic overlap and the interactome-based association score. We used a subset of the UK Biobank Resource, a cross-sectional dataset including 247 diseases and 117,392 participants who filled out a detailed questionnaire about mental health. The sparse comorbidity map confirmed that depressed patients frequently suffer from both psychiatric and somatic comorbid disorders. Notably, anxiety and obesity show strong and direct relationships with depression. The BDMM identified further directly co-morbid somatic disorders, e.g. irritable bowel syndrome, fibromyalgia, or migraine. Using the subnetwork of depression and metabolic disorders for functional analysis, the interactome-based system-level score showed the best agreement with the sparse disease network. This indicates that these epidemiologically strong disease-disease relations have improved correspondence with expected molecular-level mechanisms. The substantially fewer number of comorbidity relations in the BDMM compared to pairwise methods implies that biologically meaningful comorbid relations may be less frequent than earlier pairwise methods suggested. The computed interactive comprehensive multimorbidity views over the diseasome are available on the web at Co=MorNet: bioinformatics.mit.bme.hu/UKBNetworks.'),
(88508, 2017, 'plos', 'NetNorM: Capturing cancer-relevant information in somatic exome mutation data with gene networks for cancer stratification and prognosis', 'Le Morvan, Marine|Zinovyev, Andrei|Vert, Jean-Philippe', 'MINES ParisTech, PSL Research University, CBIO-Centre for Computational Biology, 75006 Paris, France.|MINES ParisTech, PSL Research University, CBIO-Centre for Computational Biology, 75006 Paris, France.|MINES ParisTech, PSL Research University, CBIO-Centre for Computational Biology, 75006 Paris, France.', 'France|France|France', 0, 'Algorithms|Biomarkers, Tumor|Carcinogenesis|Chromosome Mapping|Exome|Gene Regulatory Networks|Genetic Markers|Genetic Predisposition to Disease|Genetic Testing|Genome, Human|Genome-Wide Association Study|Humans|Mutation|Neoplasms|Polymorphism, Single Nucleotide|Prognosis|Risk Assessment|Risk Factors|Software|Survival Analysis', 'Journal Article', '10.1371/journal.pcbi.1005573', '28650955', 'Genome-wide somatic mutation profiles of tumours can now be assessed efficiently and promise to move precision medicine forward. Statistical analysis of mutation profiles is however challenging due to the low frequency of most mutations, the varying mutation rates across tumours, and the presence of a majority of passenger events that hide the contribution of driver events. Here we propose a method, NetNorM, to represent whole-exome somatic mutation data in a form that enhances cancer-relevant information using a gene network as background knowledge. We evaluate its relevance for two tasks: survival prediction and unsupervised patient stratification. Using data from 8 cancer types from The Cancer Genome Atlas (TCGA), we show that it improves over the raw binary mutation data and network diffusion for these two tasks. In doing so, we also provide a thorough assessment of somatic mutations prognostic power which has been overlooked by previous studies because of the sparse and binary nature of mutations.'),
(88509, 2017, 'plos', 'MFPred: Rapid and accurate prediction of protein-peptide recognition multispecificity using self-consistent mean field theory', 'Rubenstein, Aliza B|Pethe, Manasi A|Khare, Sagar D', 'Computational Biology & Molecular Biophysics Program, Rutgers, The State University of New Jersey, Piscataway, NJ.|Department of Chemistry and Chemical Biology, Rutgers, The State University of New Jersey, Piscataway, NJ.|Computational Biology & Molecular Biophysics Program, Rutgers, The State University of New Jersey, Piscataway, NJ.', 'Jersey|Jersey|Jersey', 5, 'Algorithms|Binding Sites|Computer Simulation|Models, Chemical|Models, Molecular|Peptides|Protein Binding|Protein Interaction Mapping|Proteins|Reproducibility of Results|Sensitivity and Specificity|Sequence Analysis, Protein|Software', 'Journal Article', '10.1371/journal.pcbi.1005614', '28650961', 'Multispecificity-the ability of a single receptor protein molecule to interact with multiple substrates-is a hallmark of molecular recognition at protein-protein and protein-peptide interfaces, including enzyme-substrate complexes. The ability to perform structure-based prediction of multispecificity would aid in the identification of novel enzyme substrates, protein interaction partners, and enable design of novel enzymes targeted towards alternative substrates. The relatively slow speed of current biophysical, structure-based methods limits their use for prediction and, especially, design of multispecificity. Here, we develop a rapid, flexible-backbone self-consistent mean field theory-based technique, MFPred, for multispecificity modeling at protein-peptide interfaces. We benchmark our method by predicting experimentally determined peptide specificity profiles for a range of receptors: protease and kinase enzymes, and protein recognition modules including SH2, SH3, MHC Class I and PDZ domains. We observe robust recapitulation of known specificities for all receptor-peptide complexes, and comparison with other methods shows that MFPred results in equivalent or better prediction accuracy with a ~10-1000-fold decrease in computational expense. We find that modeling bound peptide backbone flexibility is key to the observed accuracy of the method. We used MFPred for predicting with high accuracy the impact of receptor-side mutations on experimentally determined multispecificity of a protease enzyme. Our approach should enable the design of a wide range of altered receptor proteins with programmed multispecificities.'),
(88510, 2017, 'plos', 'Optimal structure of metaplasticity for adaptive learning', 'Khorsand, Peyman|Soltani, Alireza', 'Department of Psychological and Brain Sciences, Dartmouth College, New Hampshire, United States of America.|Department of Psychological and Brain Sciences, Dartmouth College, New Hampshire, United States of America.', 'United States|United States', 0, 'Adaptation, Physiological|Brain|Computer Simulation|Humans|Models, Neurological|Models, Statistical|Nerve Net|Neuronal Plasticity|Reward|Synaptic Transmission', 'Journal Article', '10.1371/journal.pcbi.1005630', '28658247', 'Learning from reward feedback in a changing environment requires a high degree of adaptability, yet the precise estimation of reward information demands slow updates. In the framework of estimating reward probability, here we investigated how this tradeoff between adaptability and precision can be mitigated via metaplasticity, i.e. synaptic changes that do not always alter synaptic efficacy. Using the mean-field and Monte Carlo simulations we identified superior metaplastic models that can substantially overcome the adaptability-precision tradeoff. These models can achieve both adaptability and precision by forming two separate sets of meta-states: reservoirs and buffers. Synapses in reservoir meta-states do not change their efficacy upon reward feedback, whereas those in buffer meta-states can change their efficacy. Rapid changes in efficacy are limited to synapses occupying buffers, creating a bottleneck that reduces noise without significantly decreasing adaptability. In contrast, more-populated reservoirs can generate a strong signal without manifesting any observable plasticity. By comparing the behavior of our model and a few competing models during a dynamic probability estimation task, we found that superior metaplastic models perform close to optimally for a wider range of model parameters. Finally, we found that metaplastic models are robust to changes in model parameters and that metaplastic transitions are crucial for adaptive learning since replacing them with graded plastic transitions (transitions that change synaptic efficacy) reduces the ability to overcome the adaptability-precision tradeoff. Overall, our results suggest that ubiquitous unreliability of synaptic changes evinces metaplasticity that can provide a robust mechanism for mitigating the tradeoff between adaptability and precision and thus adaptive learning.'),
(88511, 2017, 'plos', 'Landscape and variation of novel retroduplications in 26 human populations', 'Zhang, Yan|Li, Shantao|Abyzov, Alexej|Gerstein, Mark B', 'Program in Computational Biology and Bioinformatics, Yale University, New Haven, Connecticut, United States of America.|Program in Computational Biology and Bioinformatics, Yale University, New Haven, Connecticut, United States of America.|Department of Health Sciences Research, Center for Individualized Medicine, Mayo Clinic, Rochester, Minnesota, United States of America.|Program in Computational Biology and Bioinformatics, Yale University, New Haven, Connecticut, United States of America.', 'United States|United States|United States|United States', 8, 'DNA Transposable Elements|Exome|Gene Duplication|Genetic Variation|Genome, Human|High-Throughput Nucleotide Sequencing|Humans|Retroelements|Sequence Analysis, DNA|Species Specificity', 'Journal Article', '10.1371/journal.pcbi.1005567', '28662076', 'Retroduplications come from reverse transcription of mRNAs and their insertion back into the genome. Here, we performed comprehensive discovery and analysis of retroduplications in a large cohort of 2,535 individuals from 26 human populations, as part of 1000 Genomes Phase 3. We developed an integrated approach to discover novel retroduplications combining high-coverage exome and low-coverage whole-genome sequencing data, utilizing information from both exon-exon junctions and discordant paired-end reads. We found 503 parent genes having novel retroduplications absent from the reference genome. Based solely on retroduplication variation, we built phylogenetic trees of human populations, these represent superpopulation structure well and indicate that variable retroduplications are effective population markers. We further identified 43 retroduplication parent genes differentiating superpopulations. This group contains several interesting insertion events, including a SLMO2 retroduplication and insertion into CAV3, which has a potential disease association. We also found retroduplications to be associated with a variety of genomic features: (1) Insertion sites were correlated with regular nucleosome positioning. (2) They, predictably, tend to avoid conserved functional regions, such as exons, but, somewhat surprisingly, also avoid introns. (3) Retroduplications tend to be co-inserted with young L1 elements, indicating recent retrotranspositional activity, and (4) they have a weak tendency to originate from highly expressed parent genes. Our investigation provides insight into the functional impact and association with genomic elements of retroduplications. We anticipate our approach and analytical methodology to have application in a more clinical context, where exome sequencing data is abundant and the discovery of retroduplications can potentially improve the accuracy of SNP calling.'),
(88512, 2017, 'plos', 'Detecting similar binding pockets to enable systems polypharmacology', 'Duran-Frigola, Miquel|Siragusa, Lydia|Ruppin, Eytan|Barril, Xavier|Cruciani, Gabriele|Aloy, Patrick', 'Joint IRB-BSC-CRG Program in Computational Biology, Institute for Research in Biomedicine (IRB Barcelona), The Barcelona Institute of Science and Technology, Barcelona, Catalonia, Spain.|Molecular Discovery Limited, London, United Kingdom.|Department of Computer Science & Center for Bioinformatics and Computational Biology, University of Maryland, College Park, Maryland, United States of America.|Departament de Fisicoquímica, Facultat de Farmàcia, Universitat de Barcelona, Barcelona, Catalonia, Spain.|Molecular Discovery Limited, London, United Kingdom.|Joint IRB-BSC-CRG Program in Computational Biology, Institute for Research in Biomedicine (IRB Barcelona), The Barcelona Institute of Science and Technology, Barcelona, Catalonia, Spain.', 'Spain|United Kingdom|United States|Spain|United Kingdom|Spain', 0, 'Antineoplastic Agents|Binding Sites|Drug Discovery|Humans|Molecular Docking Simulation|Neoplasm Proteins|Polypharmacology|Polypharmacy|Protein Binding|Protein Conformation|Protein Interaction Domains and Motifs|Protein Interaction Mapping|Sequence Analysis, Protein|Systems Biology', 'Journal Article', '10.1371/journal.pcbi.1005522', '28662117', 'In the era of systems biology, multi-target pharmacological strategies hold promise for tackling disease-related networks. In this regard, drug promiscuity may be leveraged to interfere with multiple receptors: the so-called polypharmacology of drugs can be anticipated by analyzing the similarity of binding sites across the proteome. Here, we perform a pairwise comparison of 90,000 putative binding pockets detected in 3,700 proteins, and find that 23,000 pairs of proteins have at least one similar cavity that could, in principle, accommodate similar ligands. By inspecting these pairs, we demonstrate how the detection of similar binding sites expands the space of opportunities for the rational design of drug polypharmacology. Finally, we illustrate how to leverage these opportunities in protein-protein interaction networks related to several therapeutic classes and tumor types, and in a genome-scale metabolic model of leukemia.'),
(88513, 2017, 'plos', 'Active Vertex Model for cell-resolution description of epithelial tissue mechanics', 'Barton, Daniel L|Henkes, Silke|Weijer, Cornelis J|Sknepnek, Rastko', 'Division of Physics, School of Science and Engineering, University of Dundee, Dundee, United Kingdom.|Institute of Complex Systems and Mathematical Biology, Department of Physics, University of Aberdeen, Aberdeen, United Kingdom.|Division of Cell and Developmental Biology, School of Life Sciences, University of Dundee, Dundee, United Kingdom.|Division of Physics, School of Science and Engineering, University of Dundee, Dundee, United Kingdom.', 'United Kingdom|United Kingdom|United Kingdom|United Kingdom', 60, 'Animals|Apoptosis|Cell Communication|Cell Movement|Cell Proliferation|Computer Simulation|Elastic Modulus|Epithelial Cells|Epithelium|Humans|Mechanotransduction, Cellular|Mitosis|Models, Biological|Morphogenesis|Organ Size|Stress, Mechanical|Wound Healing', 'Journal Article', '10.1371/journal.pcbi.1005569', '28665934', 'We introduce an Active Vertex Model (AVM) for cell-resolution studies of the mechanics of confluent epithelial tissues consisting of tens of thousands of cells, with a level of detail inaccessible to similar methods. The AVM combines the Vertex Model for confluent epithelial tissues with active matter dynamics. This introduces a natural description of the cell motion and accounts for motion patterns observed on multiple scales. Furthermore, cell contacts are generated dynamically from positions of cell centres. This not only enables efficient numerical implementation, but provides a natural description of the T1 transition events responsible for local tissue rearrangements. The AVM also includes cell alignment, cell-specific mechanical properties, cell growth, division and apoptosis. In addition, the AVM introduces a flexible, dynamically changing boundary of the epithelial sheet allowing for studies of phenomena such as the fingering instability or wound healing. We illustrate these capabilities with a number of case studies.'),
(88514, 2017, 'plos', '2017 Outstanding Contributions to ISCB Award: Fran Lewitter', 'Fogg, Christiana N|Kovats, Diane E|Berger, Bonnie', 'Freelance science writer, Kensington, Maryland, United States of America.|Department of Mathematics, Massachusetts Institute of Technology (MIT), Cambridge, Massachusetts, United States of America.|Department of Mathematics, Massachusetts Institute of Technology (MIT), Cambridge, Massachusetts, United States of America.', 'United States|United States|United States', 0, 'Awards and Prizes|Computational Biology|History, 21st Century|Humans', 'Historical Article', '10.1371/journal.pcbi.1005560', '28665935', '-'),
(88515, 2017, 'plos', '2017 ISCB Innovator Award: Aviv Regev', 'Fogg, Christiana N|Kovats, Diane E|Berger, Bonnie', 'Freelance science writer, Kensington, Maryland, United States of America.|Department of Mathematics, Massachusetts Institute of Technology (MIT), Cambridge, Massachusetts, United States of America.|Department of Mathematics, Massachusetts Institute of Technology (MIT), Cambridge, Massachusetts, United States of America.', 'United States|United States|United States', 0, 'Awards and Prizes|Computational Biology', 'Journal Article', '10.1371/journal.pcbi.1005558', '28665936', '-'),
(88516, 2017, 'plos', '2017 ISCB Overton Prize awarded to Christoph Bock', 'Fogg, Christiana N|Kovats, Diane E|Berger, Bonnie', 'Freelance Science Writer, Kensington, Maryland, United States of America.|Department of Mathematics, MIT, Cambridge, Massachusetts, United States of America.|Department of Mathematics, MIT, Cambridge, Massachusetts, United States of America.', 'United States|United States|United States', 0, 'Awards and Prizes|Computational Biology|Epigenesis, Genetic|History, 21st Century|Humans', 'Historical Article', '10.1371/journal.pcbi.1005559', '28665945', '-'),
(88517, 2017, 'plos', '2017 ISCB Accomplishment by a Senior Scientist Award given to Pavel Pevzner', 'Fogg, Christiana N|Kovats, Diane E|Berger, Bonnie', 'Freelance science writer, Kensington, Maryland, United States of America.|Department of Mathematics, MIT, Cambridge, Massachusetts, United States of America.|Department of Mathematics, MIT, Cambridge, Massachusetts, United States of America.', 'United States|United States|United States', 0, 'Awards and Prizes|Humans|Societies, Scientific', 'Journal Article', '10.1371/journal.pcbi.1005561', '28665953', '-'),
(88518, 2017, 'plos', 'Independent regulation of gene expression level and noise by histone modifications', 'Wu, Shaohuan|Li, Ke|Li, Yingshu|Zhao, Tong|Li, Ting|Yang, Yu-Fei|Qian, Wenfeng', 'State Key Laboratory of Plant Genomics, Institute of Genetics and Developmental Biology, Chinese Academy of Sciences, Beijing, China.|State Key Laboratory of Plant Genomics, Institute of Genetics and Developmental Biology, Chinese Academy of Sciences, Beijing, China.|Key Laboratory of Genetic Network Biology, Institute of Genetics and Developmental Biology, Chinese Academy of Sciences, Beijing, China.|Institute of Microbiology, Chinese Academy of Sciences, Beijing, China.|State Key Laboratory of Molecular Developmental Biology, Institute of Genetics and Developmental Biology, Chinese Academy of Sciences, Beijing, China.|State Key Laboratory of Plant Genomics, Institute of Genetics and Developmental Biology, Chinese Academy of Sciences, Beijing, China.|State Key Laboratory of Plant Genomics, Institute of Genetics and Developmental Biology, Chinese Academy of Sciences, Beijing, China.', 'China|China|China|China|China|China|China', 17, 'Cells, Cultured|Computer Simulation|Gene Expression|Gene Expression Regulation|Histone Code|Histones|Human Embryonic Stem Cells|Humans|Models, Genetic|Models, Statistical|Signal-To-Noise Ratio|Stochastic Processes', 'Journal Article', '10.1371/journal.pcbi.1005585', '28665997', 'The inherent stochasticity generates substantial gene expression variation among isogenic cells under identical conditions, which is frequently referred to as gene expression noise or cell-to-cell expression variability. Similar to (average) expression level, expression noise is also subject to natural selection. Yet it has been observed that noise is negatively correlated with expression level, which manifests as a potential constraint for simultaneous optimization of both. Here, we studied expression noise in human embryonic cells with computational analysis on single-cell RNA-seq data and in yeast with flow cytometry experiments. We showed that this coupling is overcome, to a certain degree, by a histone modification strategy in multiple embryonic developmental stages in human, as well as in yeast. Importantly, this epigenetic strategy could fit into a burst-like gene expression model: promoter-localized histone modifications (such as H3K4 methylation) are associated with both burst size and burst frequency, which together influence expression level, while gene-body-localized ones (such as H3K79 methylation) are more associated with burst frequency, which influences both expression level and noise. We further knocked out the only writer of H3K79 methylation in yeast, and observed that expression noise is indeed increased. Consistently, dosage sensitive genes, such as genes in the Wnt signaling pathway, tend to be marked with gene-body-localized histone modifications, while stress responding genes, such as genes regulating autophagy, tend to be marked with promoter-localized ones. Our findings elucidate that the division of labor among histone modifications facilitates the independent regulation of expression level and noise, extend the histone code hypothesis to include expression noise, and shed light on the optimization of transcriptome in evolution.'),
(88519, 2017, 'plos', 'Expanding signaling-molecule wavefront model of cell polarization in the Drosophila wing primordium', 'Wortman, Juliana C|Nahmad, Marcos|Zhang, Peng Cheng|Lander, Arthur D|Yu, Clare C', 'Department of Physics and Astronomy, University of California, Irvine, Irvine, California, United States of America.|Center for Complex Biological Systems, University of California, Irvine, Irvine, California, United States of America.|Center for Complex Biological Systems, University of California, Irvine, Irvine, California, United States of America.|Center for Complex Biological Systems, University of California, Irvine, Irvine, California, United States of America.|Department of Physics and Astronomy, University of California, Irvine, Irvine, California, United States of America.', 'United States|United States|United States|United States|United States', 4, 'Animals|Cadherins|Cell Adhesion Molecules|Cell Polarity|Computer Simulation|Drosophila|Drosophila Proteins|Gene Expression Regulation, Developmental|Membrane Glycoproteins|Models, Biological|Myosins|Organogenesis|Wings, Animal', 'Journal Article', '10.1371/journal.pcbi.1005610', '28671940', 'In developing tissues, cell polarization and proliferation are regulated by morphogens and signaling pathways. Cells throughout the Drosophila wing primordium typically show subcellular localization of the unconventional myosin Dachs on the distal side of cells (nearest the center of the disc). Dachs localization depends on the spatial distribution of bonds between the protocadherins Fat (Ft) and Dachsous (Ds), which form heterodimers between adjacent cells, and the Golgi kinase Four-jointed (Fj), which affects the binding affinities of Ft and Ds. The Fj concentration forms a linear gradient while the Ds concentration is roughly uniform throughout most of the wing pouch with a steep transition region that propagates from the center to the edge of the pouch during the third larval instar. Although the Fj gradient is an important cue for polarization, it is unclear how the polarization is affected by cell division and the expanding Ds transition region, both of which can alter the distribution of Ft-Ds heterodimers around the cell periphery. We have developed a computational model to address these questions. In our model, the binding affinity of Ft and Ds depends on phosphorylation by Fj. We assume that the asymmetry of the Ft-Ds bond distribution around the cell periphery defines the polarization, with greater asymmetry promoting cell proliferation. Our model predicts that this asymmetry is greatest in the radially-expanding transition region that leaves polarized cells in its wake. These cells naturally retain their bond distribution asymmetry after division by rapidly replenishing Ft-Ds bonds at new cell-cell interfaces. Thus we predict that the distal localization of Dachs in cells throughout the pouch requires the movement of the Ds transition region and the simple presence, rather than any specific spatial pattern, of Fj.'),
(88520, 2017, 'plos', 'Universal features of dendrites through centripetal branch ordering', 'Vormberg, Alexandra|Effenberger, Felix|Muellerleile, Julia|Cuntz, Hermann', 'Ernst Strüngmann Institute (ESI) for Neuroscience in Cooperation with Max Planck Society, Frankfurt/Main, Germany.|Ernst Strüngmann Institute (ESI) for Neuroscience in Cooperation with Max Planck Society, Frankfurt/Main, Germany.|Institute of Clinical Neuroanatomy, Goethe University Frankfurt/Main, Germany.|Ernst Strüngmann Institute (ESI) for Neuroscience in Cooperation with Max Planck Society, Frankfurt/Main, Germany.', 'Germany|Germany|Germany|Germany', 0, 'Animals|Computer Simulation|Dendrites|Humans|Models, Anatomic|Models, Neurological|Models, Statistical|Neuronal Plasticity', 'Journal Article', '10.1371/journal.pcbi.1005615', '28671947', 'Dendrites form predominantly binary trees that are exquisitely embedded in the networks of the brain. While neuronal computation is known to depend on the morphology of dendrites, their underlying topological blueprint remains unknown. Here, we used a centripetal branch ordering scheme originally developed to describe river networks-the Horton-Strahler order (SO)-to examine hierarchical relationships of branching statistics in reconstructed and model dendritic trees. We report on a number of universal topological relationships with SO that are true for all binary trees and distinguish those from SO-sorted metric measures that appear to be cell type-specific. The latter are therefore potential new candidates for categorising dendritic tree structures. Interestingly, we find a faithful correlation of branch diameters with centripetal branch orders, indicating a possible functional importance of SO for dendritic morphology and growth. Also, simulated local voltage responses to synaptic inputs are strongly correlated with SO. In summary, our study identifies important SO-dependent measures in dendritic morphology that are relevant for neural function while at the same time it describes other relationships that are universal for all dendrites.'),
(88521, 2017, 'plos', 'Speciation trajectories in recombining bacterial species', 'Marttinen, Pekka|Hanage, William P', 'Helsinki Institute for Information Technology HIIT, Department of Computer Science, Aalto University, Espoo, Finland.|Center for Communicable Disease Dynamics, Department of Epidemiology, Harvard TH Chan School of Public Health, Boston, MA, USA.', 'Finland|United States', 13, 'Bacteria|Cluster Analysis|Ecosystem|Evolution, Molecular|Genetic Speciation|Genetic Variation|Models, Genetic|Recombination, Genetic', 'Journal Article', '10.1371/journal.pcbi.1005640', '28671999', 'It is generally agreed that bacterial diversity can be classified into genetically and ecologically cohesive units, but what produces such variation is a topic of intensive research. Recombination may maintain coherent species of frequently recombining bacteria, but the emergence of distinct clusters within a recombining species, and the impact of habitat structure in this process are not well described, limiting our understanding of how new species are created. Here we present a model of bacterial evolution in overlapping habitat space. We show that the amount of habitat overlap determines the outcome for a pair of clusters, which may range from fast clonal divergence with little interaction between the clusters to a stationary population structure, where different clusters maintain an equilibrium distance between each other for an indefinite time. We fit our model to two data sets. In Streptococcus pneumoniae, we find a genomically and ecologically distinct subset, held at a relatively constant genetic distance from the majority of the population through frequent recombination with it, while in Campylobacter jejuni, we find a minority population we predict will continue to diverge at a higher rate. This approach may predict and define speciation trajectories in multiple bacterial species.'),
(88522, 2017, 'plos', 'Classification and analysis of a large collection of in vivo bioassay descriptions', 'Zwierzyna, Magdalena|Overington, John P', 'BenevolentAI, London, United Kingdom.|BenevolentAI, London, United Kingdom.', 'United Kingdom|United Kingdom', 0, 'Biological Assay|Data Mining|Databases, Factual|Drug Evaluation, Preclinical|High-Throughput Screening Assays|Machine Learning|Natural Language Processing|Reproducibility of Results|Sensitivity and Specificity', 'Journal Article', '10.1371/journal.pcbi.1005641', '28678787', 'Testing potential drug treatments in animal disease models is a decisive step of all preclinical drug discovery programs. Yet, despite the importance of such experiments for translational medicine, there have been relatively few efforts to comprehensively and consistently analyze the data produced by in vivo bioassays. This is partly due to their complexity and lack of accepted reporting standards-publicly available animal screening data are only accessible in unstructured free-text format, which hinders computational analysis. In this study, we use text mining to extract information from the descriptions of over 100,000 drug screening-related assays in rats and mice. We retrieve our dataset from ChEMBL-an open-source literature-based database focused on preclinical drug discovery. We show that in vivo assay descriptions can be effectively mined for relevant information, including experimental factors that might influence the outcome and reproducibility of animal research: genetic strains, experimental treatments, and phenotypic readouts used in the experiments. We further systematize extracted information using unsupervised language model (Word2Vec), which learns semantic similarities between terms and phrases, allowing identification of related animal models and classification of entire assay descriptions. In addition, we show that random forest models trained on features generated by Word2Vec can predict the class of drugs tested in different in vivo assays with high accuracy. Finally, we combine information mined from text with curated annotations stored in ChEMBL to investigate the patterns of usage of different animal models across a range of experiments, drug classes, and disease areas.');
INSERT INTO `papers` (`id`, `ano`, `journal`, `titulo`, `autores`, `afiliacao`, `pais`, `citacoes`, `palavra_chave`, `categorias`, `doi`, `pubmed`, `abstract`) VALUES
(88523, 2017, 'plos', 'A phase transition induces chaos in a predator-prey ecosystem with a dynamic fitness landscape', 'Gilpin, William|Feldman, Marcus W', 'Department of Applied Physics, Stanford University, Stanford, California, United States of America.|Department of Biology, Stanford University, Stanford, California, United States of America.', 'United States|United States', 4, 'Animals|Computer Simulation|Ecosystem|Evolution, Molecular|Food Chain|Genetic Fitness|Genetics, Population|Models, Genetic|Nonlinear Dynamics|Predatory Behavior|Selection, Genetic', 'Journal Article', '10.1371/journal.pcbi.1005644', '28678792', 'In many ecosystems, natural selection can occur quickly enough to influence the population dynamics and thus future selection. This suggests the importance of extending classical population dynamics models to include such eco-evolutionary processes. Here, we describe a predator-prey model in which the prey population growth depends on a prey density-dependent fitness landscape. We show that this two-species ecosystem is capable of exhibiting chaos even in the absence of external environmental variation or noise, and that the onset of chaotic dynamics is the result of the fitness landscape reversibly alternating between epochs of stabilizing and disruptive selection. We draw an analogy between the fitness function and the free energy in statistical mechanics, allowing us to use the physical theory of first-order phase transitions to understand the onset of rapid cycling in the chaotic predator-prey dynamics. We use quantitative techniques to study the relevance of our model to observational studies of complex ecosystems, finding that the evolution-driven chaotic dynamics confer community stability at the edge of chaos while creating a wide distribution of opportunities for speciation during epochs of disruptive selection-a potential observable signature of chaotic eco-evolutionary dynamics in experimental studies.'),
(88524, 2017, 'plos', 'Quantifying critical states of complex diseases using single-sample dynamic network biomarkers', 'Liu, Xiaoping|Chang, Xiao|Liu, Rui|Yu, Xiangtian|Chen, Luonan|Aihara, Kazuyuki', 'Institute of Industrial Science, the University of Tokyo, Tokyo, Japan.|Institute of Industrial Science, the University of Tokyo, Tokyo, Japan.|School of Mathematics, South China University of Technology, Guangzhou, China.|Key Laboratory of Systems Biology, CAS Center for Excellence in Molecular Cell Science, Innovation Center for Cell Signaling Network, Institute of Biochemistry and Cell Biology, Shanghai Institutes for Biological Sciences, Chinese Academy of Sciences, Shanghai, China.|Institute of Industrial Science, the University of Tokyo, Tokyo, Japan.|Institute of Industrial Science, the University of Tokyo, Tokyo, Japan.', 'Japan|Japan|China|China|Japan|Japan', 11, 'Algorithms|Biomarkers, Tumor|Data Interpretation, Statistical|Diagnosis, Computer-Assisted|Disease Progression|Humans|Neoplasms|Reproducibility of Results|Sensitivity and Specificity|Signal Transduction', 'Journal Article', '10.1371/journal.pcbi.1005633', '28678795', 'Dynamic network biomarkers (DNB) can identify the critical state or tipping point of a disease, thereby predicting rather than diagnosing the disease. However, it is difficult to apply the DNB theory to clinical practice because evaluating DNB at the critical state required the data of multiple samples on each individual, which are generally not available, and thus limit the applicability of DNB. In this study, we developed a novel method, i.e., single-sample DNB (sDNB), to detect early-warning signals or critical states of diseases in individual patients with only a single sample for each patient, thus opening a new way to predict diseases in a personalized way. In contrast to the information of differential expressions used in traditional biomarkers to diagnose disease, sDNB is based on the information of differential associations, thereby having the ability to predict disease or diagnose near-future disease. Applying this method to datasets for influenza virus infection and cancer metastasis led to accurate identification of the critical states or correct prediction of the immediate diseases based on individual samples. We successfully identified the critical states or tipping points just before the appearance of disease symptoms for influenza virus infection and the onset of distant metastasis for individual patients with cancer, thereby demonstrating the effectiveness and efficiency of our method for quantifying critical states at the single-sample level.'),
(88525, 2017, 'plos', 'Epistasis in genomic and survival data of cancer patients', 'Matlak, Dariusz|Szczurek, Ewa', 'Faculty of Mathematics, Informatics and Mechanics, University of Warsaw, Warsaw, Poland.|Faculty of Mathematics, Informatics and Mechanics, University of Warsaw, Warsaw, Poland.', 'Poland|Poland', 1, 'Biomarkers, Tumor|Computer Simulation|Epistasis, Genetic|Genetic Fitness|Genetic Markers|Genetic Predisposition to Disease|Genome, Human|Humans|Likelihood Functions|Models, Statistical|Neoplasm Proteins|Neoplasms|Prevalence|Proportional Hazards Models|Risk Factors|Survival Analysis', 'Journal Article', '10.1371/journal.pcbi.1005626', '28678836', 'Cancer aggressiveness and its effect on patient survival depends on mutations in the tumor genome. Epistatic interactions between the mutated genes may guide the choice of anticancer therapy and set predictive factors of its success. Inhibitors targeting synthetic lethal partners of genes mutated in tumors are already utilized for efficient and specific treatment in the clinic. The space of possible epistatic interactions, however, is overwhelming, and computational methods are needed to limit the experimental effort of validating the interactions for therapy and characterizing their biomarkers. Here, we introduce SurvLRT, a statistical likelihood ratio test for identifying epistatic gene pairs and triplets from cancer patient genomic and survival data. Compared to established approaches, SurvLRT performed favorable in predicting known, experimentally verified synthetic lethal partners of PARP1 from TCGA data. Our approach is the first to test for epistasis between triplets of genes to identify biomarkers of synthetic lethality-based therapy. SurvLRT proved successful in identifying the known gene TP53BP1 as the biomarker of success of the therapy targeting PARP in BRCA1 deficient tumors. Search for other biomarkers for the same interaction revealed a region whose deletion was a more significant biomarker than deletion of TP53BP1. With the ability to detect not only pairwise but twelve different types of triple epistasis, applicability of SurvLRT goes beyond cancer therapy, to the level of characterization of shapes of fitness landscapes.'),
(88526, 2017, 'plos', 'Combination therapeutics of Nilotinib and radiation in acute lymphoblastic leukemia as an effective method against drug-resistance', 'Kaveh, Kamran|Takahashi, Yutaka|Farrar, Michael A|Storme, Guy|Guido, Marcucci|Piepenburg, Jamie|Penning, Jackson|Foo, Jasmine|Leder, Kevin Z|Hui, Susanta K', 'Program for Evolutionary Dynamics, Harvard University, Cambridge, Massachusetts, United States of America.|Department of Radiation Oncology, University of Minnesota, Minneapolis, Minnesota, United States of America.|Department of Laboratory Medicine and Pathology, University of Minnesota, Minneapolis, Minnesota, United States of America.|Department of Radiotherapy, Universitair Ziekenhuis Brussel, Brussels, Belgium.|Department of Hematology and Beckman Research Institute, City of Hope National Medical Center, Duarte, California, United States of America.|Department of Radiation Oncology, University of Minnesota, Minneapolis, Minnesota, United States of America.|Department of Mathematics, University of Minnesota, Minneapolis, Minnesota, United States of America.|Department of Mathematics, University of Minnesota, Minneapolis, Minnesota, United States of America.|Industrial and Systems Engineering, University of Minnesota, Minneapolis, Minnesota, United States of America.|Department of Radiation Oncology, University of Minnesota, Minneapolis, Minnesota, United States of America.', 'United States|United States|United States|Belgium|United States|United States|United States|United S', 0, 'Animals|Apoptosis|Cell Line, Tumor|Chemoradiotherapy|Computer Simulation|Drug Resistance, Neoplasm|Mice|Models, Biological|Precursor Cell Lymphoblastic Leukemia-Lymphoma|Protein-Tyrosine Kinases|Proto-Oncogene Proteins c-akt|Pyrimidines|Treatment Outcome', 'Journal Article', '10.1371/journal.pcbi.1005482', '28683103', 'Philadelphia chromosome-positive (Ph+) acute lymphoblastic leukemia (ALL) is characterized by a very poor prognosis and a high likelihood of acquired chemo-resistance. Although tyrosine kinase inhibitor (TKI) therapy has improved clinical outcome, most ALL patients relapse following treatment with TKI due to the development of resistance. We developed an in vitro model of Nilotinib-resistant Ph+ leukemia cells to investigate whether low dose radiation (LDR) in combination with TKI therapy overcome chemo-resistance. Additionally, we developed a mathematical model, parameterized by cell viability experiments under Nilotinib treatment and LDR, to explain the cellular response to combination therapy. The addition of LDR significantly reduced drug resistance both in vitro and in computational model. Decreased expression level of phosphorylated AKT suggests that the combination treatment plays an important role in overcoming resistance through the AKT pathway. Model-predicted cellular responses to the combined therapy provide good agreement with experimental results. Augmentation of LDR and Nilotinib therapy seems to be beneficial to control Ph+ leukemia resistance and the quantitative model can determine optimal dosing schedule to enhance the effectiveness of the combination therapy.'),
(88527, 2017, 'plos', 'Persisting fetal clonotypes influence the structure and overlap of adult human T cell receptor repertoires', 'Pogorelyy, Mikhail V|Elhanati, Yuval|Marcou, Quentin|Sycheva, Anastasiia L|Komech, Ekaterina A|Nazarov, Vadim I|Britanova, Olga V|Chudakov, Dmitriy M|Mamedov, Ilgar Z|Lebedev, Yury B|Mora, Thierry|Walczak, Aleksandra M', 'Shemyakin-Ovchinnikov Institute of Bioorganic Chemistry, Moscow, Russian Federation.|Laboratoire de physique théorique, CNRS, UPMC and École normale supérieure, Paris, France.|Laboratoire de physique théorique, CNRS, UPMC and École normale supérieure, Paris, France.|Shemyakin-Ovchinnikov Institute of Bioorganic Chemistry, Moscow, Russian Federation.|Shemyakin-Ovchinnikov Institute of Bioorganic Chemistry, Moscow, Russian Federation.|Shemyakin-Ovchinnikov Institute of Bioorganic Chemistry, Moscow, Russian Federation.|Shemyakin-Ovchinnikov Institute of Bioorganic Chemistry, Moscow, Russian Federation.|Shemyakin-Ovchinnikov Institute of Bioorganic Chemistry, Moscow, Russian Federation.|Shemyakin-Ovchinnikov Institute of Bioorganic Chemistry, Moscow, Russian Federation.|Shemyakin-Ovchinnikov Institute of Bioorganic Chemistry, Moscow, Russian Federation.|Laboratoire de physique statistique, CNRS, UPMC and École normale supérieure, Paris, France.|Laboratoire de physique théorique, CNRS, UPMC and École normale supérieure, Paris, France.', 'Russian Federation|France|France|Russian Federation|Russian Federation|Russian Federation|Russian Fe', 15, 'Aging|Base Sequence|Cells, Cultured|Gene Expression Regulation, Developmental|Gene Rearrangement, T-Lymphocyte|Genetic Variation|Humans|Molecular Sequence Data|Receptors, Antigen, T-Cell|Recombination, Genetic|T-Cell Antigen Receptor Specificity|Twins, Monozygotic', 'Journal Article', '10.1371/journal.pcbi.1005572', '28683116', 'The diversity of T-cell receptors recognizing foreign pathogens is generated through a highly stochastic recombination process, making the independent production of the same sequence rare. Yet unrelated individuals do share receptors, which together constitute a public repertoire of abundant clonotypes. The TCR repertoire is initially formed prenatally, when the enzyme inserting random nucleotides is downregulated, producing a limited diversity subset. By statistically analyzing deep sequencing T-cell repertoire data from twins, unrelated individuals of various ages, and cord blood, we show that T-cell clones generated before birth persist and maintain high abundances in adult organisms for decades, slowly decaying with age. Our results suggest that large, low-diversity public clones are created during pre-natal life, and survive over long periods, providing the basis of the public repertoire.'),
(88528, 2017, 'plos', 'Rapid target foraging with reach or gaze: The hand looks further ahead than the eye', 'Diamond, Jonathan S|Wolpert, Daniel M|Flanagan, J Randall', 'Centre for Neuroscience Studies, Queens University, Kingston, Ontario, Canada.|Department of Engineering, University of Cambridge, Cambridge, United Kingdom.|Centre for Neuroscience Studies, Queens University, Kingston, Ontario, Canada.', 'Canada|United Kingdom|Canada', 0, 'Attention|Choice Behavior|Cues|Feedback, Sensory|Feeding Behavior|Female|Fixation, Ocular|Hand|Humans|Male|Movement|Psychomotor Performance|Reward|Visual Perception|Young Adult', 'Journal Article', '10.1371/journal.pcbi.1005504', '28683138', 'Real-world tasks typically consist of a series of target-directed actions and often require choices about which targets to act on and in what order. Such choice behavior can be assessed from an optimal foraging perspective whereby target selection is shaped by a balance between rewards and costs. Here we evaluated such decision-making in a rapid movement foraging task. On a given trial, participants were presented with 15 targets of varying size and value and were instructed to harvest as much reward as possible by either moving a handle to the targets (hand task) or by briefly fixating them (eye task). The short trial duration enabled participants to harvest about half the targets, ensuring that total reward was due to choice behavior. We developed a probabilistic model to predict target-by-target harvesting choices that considered the rewards and movement-related costs (i.e., target distance and size) associated with the current target as well as future targets. In the hand task, in comparison to the eye task, target choice was more strongly influenced by movement-related costs and took into account a greater number of future targets, consistent with the greater costs associated with arm movement. In both tasks, participants exhibited near-optimal behaviour and in a constrained version of the hand task in which choices could only be based on target positions, participants consistently chose among the shortest movement paths. Our results demonstrate that people can rapidly and effectively integrate values and movement-related costs associated with current and future targets when sequentially harvesting targets.'),
(88529, 2017, 'plos', 'Inherent limitations of probabilistic models for protein-DNA binding specificity', 'Ruan, Shuxiang|Stormo, Gary D', 'Department of Genetics and The Edison Center for Genome Sciences and Systems Biology, Washington University School of Medicine, St. Louis, Missouri, United States of America.|Department of Genetics and The Edison Center for Genome Sciences and Systems Biology, Washington University School of Medicine, St. Louis, Missouri, United States of America.', 'United States|United States', 9, 'Computational Biology|Computer Simulation|DNA|Models, Statistical|Software|Transcription Factors', 'Journal Article', '10.1371/journal.pcbi.1005638', '28686588', 'The specificities of transcription factors are most commonly represented with probabilistic models. These models provide a probability for each base occurring at each position within the binding site and the positions are assumed to contribute independently. The model is simple and intuitive and is the basis for many motif discovery algorithms. However, the model also has inherent limitations that prevent it from accurately representing true binding probabilities, especially for the highest affinity sites under conditions of high protein concentration. The limitations are not due to the assumption of independence between positions but rather are caused by the non-linear relationship between binding affinity and binding probability and the fact that independent normalization at each position skews the site probabilities. Generally probabilistic models are reasonably good approximations, but new high-throughput methods allow for biophysical models with increased accuracy that should be used whenever possible.'),
(88530, 2017, 'plos', 'Cannabinoids disrupt memory encoding by functionally isolating hippocampal CA1 from CA3', 'Sandler, Roman A|Fetterhoff, Dustin|Hampson, Robert E|Deadwyler, Sam A|Marmarelis, Vasilis Z', 'Department of Biomedical Engineering, University of Southern California, Los Angeles, California, United States of America.|Department of Physiology & Pharmacology, Wake Forest University, Winston-Salem, North Carolina, United States of America.|Department of Physiology & Pharmacology, Wake Forest University, Winston-Salem, North Carolina, United States of America.|Department of Physiology & Pharmacology, Wake Forest University, Winston-Salem, North Carolina, United States of America.|Department of Biomedical Engineering, University of Southern California, Los Angeles, California, United States of America.', 'United States|United States|United States|United States|United States', 6, 'Animals|Behavior, Animal|CA1 Region, Hippocampal|CA3 Region, Hippocampal|Cannabinoids|Computational Biology|Male|Memory, Short-Term|Models, Neurological|Rats|Rats, Long-Evans|Task Performance and Analysis', 'Journal Article', '10.1371/journal.pcbi.1005624', '28686594', 'Much of the research on cannabinoids (CBs) has focused on their effects at the molecular and synaptic level. However, the effects of CBs on the dynamics of neural circuits remains poorly understood. This study aims to disentangle the effects of CBs on the functional dynamics of the hippocampal Schaffer collateral synapse by using data-driven nonparametric modeling. Multi-unit activity was recorded from rats doing an working memory task in control sessions and under the influence of exogenously administered tetrahydrocannabinol (THC), the primary CB found in marijuana. It was found that THC left firing rate unaltered and only slightly reduced theta oscillations. Multivariate autoregressive models, estimated from spontaneous spiking activity, were then used to describe the dynamical transformation from CA3 to CA1. They revealed that THC served to functionally isolate CA1 from CA3 by reducing feedforward excitation and theta information flow. The functional isolation was compensated by increased feedback excitation within CA1, thus leading to unaltered firing rates. Finally, both of these effects were shown to be correlated with memory impairments in the working memory task. By elucidating the circuit mechanisms of CBs, these results help close the gap in knowledge between the cellular and behavioral effects of CBs.'),
(88531, 2017, 'plos', 'Flux balance analysis predicts Warburg-like effects of mouse hepatocyte deficient in miR-122a', 'Wu, Hua-Qing|Cheng, Mei-Ling|Lai, Jin-Mei|Wu, Hsuan-Hui|Chen, Meng-Chun|Liu, Wen-Huan|Wu, Wu-Hsiung|Chang, Peter Mu-Hsin|Huang, Chi-Ying F|Tsou, Ann-Ping|Shiao, Ming-Shi|Wang, Feng-Sheng', 'Department of Chemical Engineering, National Chung Cheng University, Chiayi, Taiwan.|Department of Biomedical Sciences, Chang Gung University, Tao-Yuan, Taiwan.|Department of Life Science, Fu-Jen Catholic University, New Taipei City, Taiwan.|Institute of Biopharmaceutical Sciences, National Yang-Ming University, Taipei, Taiwan.|Department of Chemical Engineering, National Chung Cheng University, Chiayi, Taiwan.|Department of Chemical Engineering, National Chung Cheng University, Chiayi, Taiwan.|Department of Chemical Engineering, National Chung Cheng University, Chiayi, Taiwan.|Department of Oncology, Taipei Veterans General Hospital, Taipei, Taiwan.|Institute of Biopharmaceutical Sciences, National Yang-Ming University, Taipei, Taiwan.|Department of Biotechnology and Laboratory Science in Medicine, National Yang-Ming University, Taipei, Taiwan.|Department of Biomedical Sciences, Chang Gung University, Tao-Yuan, Taiwan.|Department of Chemical Engineering, National Chung Cheng University, Chiayi, Taiwan.', '-|-|-|-|-|-|-|-|-|-|-|-', 7, 'Animals|Glucose|Hepatocytes|Humans|Liver|Liver Neoplasms|Metabolic Flux Analysis|Metabolomics|Mice|Mice, Knockout|MicroRNAs', 'Journal Article', '10.1371/journal.pcbi.1005618', '28686599', 'The liver is a vital organ involving in various major metabolic functions in human body. MicroRNA-122 (miR-122) plays an important role in the regulation of liver metabolism, but its intrinsic physiological functions require further clarification. This study integrated the genome-scale metabolic model of hepatocytes and mouse experimental data with germline deletion of Mir122a (Mir122a-/-) to infer Warburg-like effects. Elevated expression of MiR-122a target genes in Mir122a-/-mice, especially those encoding for metabolic enzymes, was applied to analyze the flux distributions of the genome-scale metabolic model in normal and deficient states. By definition of the similarity ratio, we compared the flux fold change of the genome-scale metabolic model computational results and metabolomic profiling data measured through a liquid-chromatography with mass spectrometer, respectively, for hepatocytes of 2-month-old mice in normal and deficient states. The Ddc gene demonstrated the highest similarity ratio of 95% to the biological hypothesis of the Warburg effect, and similarity of 75% to the experimental observation. We also used 2, 6, and 11 months of mir-122 knockout mice liver cell to examined the expression pattern of DDC in the knockout mice livers to show upregulated profiles of DDC from the data. Furthermore, through a bioinformatics (LINCS program) prediction, BTK inhibitors and withaferin A could downregulate DDC expression, suggesting that such drugs could potentially alter the early events of metabolomics of liver cancer cells.'),
(88532, 2017, 'plos', 'Hybrid modeling and prediction of dynamical systems', 'Hamilton, Franz|Lloyd, Alun L|Flores, Kevin B', 'Department of Mathematics, North Carolina State University, Raleigh, North Carolina, United States of America.|Department of Mathematics, North Carolina State University, Raleigh, North Carolina, United States of America.|Department of Mathematics, North Carolina State University, Raleigh, North Carolina, United States of America.', 'United States|United States|United States', 0, 'Models, Biological|Models, Statistical|Neurons|Statistics, Nonparametric|Systems Biology', 'Journal Article', '10.1371/journal.pcbi.1005655', '28692642', 'Scientific analysis often relies on the ability to make accurate predictions of a systems dynamics. Mechanistic models, parameterized by a number of unknown parameters, are often used for this purpose. Accurate estimation of the model state and parameters prior to prediction is necessary, but may be complicated by issues such as noisy data and uncertainty in parameters and initial conditions. At the other end of the spectrum exist nonparametric methods, which rely solely on data to build their predictions. While these nonparametric methods do not require a model of the system, their performance is strongly influenced by the amount and noisiness of the data. In this article, we consider a hybrid approach to modeling and prediction which merges recent advancements in nonparametric analysis with standard parametric methods. The general idea is to replace a subset of a mechanistic models equations with their corresponding nonparametric representations, resulting in a hybrid modeling and prediction scheme. Overall, we find that this hybrid approach allows for more robust parameter estimation and improved short-term prediction in situations where there is a large uncertainty in model parameters. We demonstrate these advantages in the classical Lorenz-63 chaotic system and in networks of Hindmarsh-Rose neurons before application to experimentally collected structured population data.'),
(88533, 2017, 'plos', 'Inverse stochastic resonance in networks of spiking neurons', 'Uzuntarla, Muhammet|Barreto, Ernest|Torres, Joaquin J', 'Department of Biomedical Engineering, Bulent Ecevit University, Engineering Faculty, Zonguldak, Turkey.|Department of Physics and Astronomy and The Krasnow Institute for Advanced Study, George Mason University, Fairfax, Virginia, United States of America.|Department of Electromagnetism and Physics of Matter, and Institute Carlos I for Theoretical and Computational Physics, University of Granada, Granada, Spain.', 'Turkey|United States|Spain', 30, 'Action Potentials|Algorithms|Computational Biology|Humans|Models, Neurological|Nerve Net|Neurons|Stochastic Processes', 'Journal Article', '10.1371/journal.pcbi.1005646', '28692643', 'Inverse Stochastic Resonance (ISR) is a phenomenon in which the average spiking rate of a neuron exhibits a minimum with respect to noise. ISR has been studied in individual neurons, but here, we investigate ISR in scale-free networks, where the average spiking rate is calculated over the neuronal population. We use Hodgkin-Huxley model neurons with channel noise (i.e., stochastic gating variable dynamics), and the network connectivity is implemented via electrical or chemical connections (i.e., gap junctions or excitatory/inhibitory synapses). We find that the emergence of ISR depends on the interplay between each neurons intrinsic dynamical structure, channel noise, and network inputs, where the latter in turn depend on network structure parameters. We observe that with weak gap junction or excitatory synaptic coupling, network heterogeneity and sparseness tend to favor the emergence of ISR. With inhibitory coupling, ISR is quite robust. We also identify dynamical mechanisms that underlie various features of this ISR behavior. Our results suggest possible ways of experimentally observing ISR in actual neuronal systems.'),
(88534, 2017, 'plos', 'Correction: Accuracy Maximization Analysis for Sensory-Perceptual Tasks: Computational Improvements, Filter Robustness, and Coding Advantages for Scaled Additive Noise', 'PLOS Computational Biology Staff', 'Department of Electromagnetism and Physics of Matter, and Institute Carlos I for Theoretical and Computational Physics, University of Granada, Granada, Spain.', 'Spain', 0, '-', 'Published Erratum', '10.1371/journal.pcbi.1005636', '28692644', '[This corrects the article DOI: 10.1371/journal.pcbi.1005281.].'),
(88535, 2017, 'plos', 'Temporal specificity of the initial adaptive response in motor adaptation', 'Joiner, Wilsaan M|Sing, Gary C|Smith, Maurice A', 'John A. Paulson School of Engineering and Applied Sciences, Harvard University, Cambridge, Massachusetts, United States of America.|John A. Paulson School of Engineering and Applied Sciences, Harvard University, Cambridge, Massachusetts, United States of America.|John A. Paulson School of Engineering and Applied Sciences, Harvard University, Cambridge, Massachusetts, United States of America.', 'United States|United States|United States', 3, 'Adaptation, Physiological|Computer Simulation|Feedback, Sensory|Female|Humans|Learning|Male|Models, Neurological|Movement|Psychomotor Performance|Stereotyped Behavior|Time Factors|Volition|Young Adult', 'Journal Article', '10.1371/journal.pcbi.1005438', '28692658', 'Repeated exposure to a novel physical environment eventually leads to a mature adaptive response whereby feedforward changes in motor output mirror both the amplitude and temporal structure of the environmental perturbations. However, adaptive responses at the earliest stages of learning have been found to be not only smaller, but systematically less specific in their temporal structure compared to later stages of learning. This observation has spawned a lively debate as to whether the temporal structure of the initial adaptive response is, in fact, stereotyped and non-specific. To settle this debate, we directly measured the adaptive responses to velocity-dependent and position-dependent force-field perturbations (vFFs and pFFs) at the earliest possible stage of motor learning in humans-after just a single-movement exposure. In line with previous work, we found these earliest stage adaptive responses to be more similar than the perturbations that induced them. However, the single-trial adaptive responses for vFF and pFF perturbations were clearly distinct, and the disparity between them reflected the difference between the temporal structure of the perturbations that drove them. Critically, we observed these differences between single-trial adaptive responses when vFF and pFF perturbations were randomly intermingled from one trial to the next within the same block, indicating perturbation response specificity at the single trial level. These findings demonstrate that the initial adaptive responses to physical perturbations are not stereotyped. Instead, the neural plasticity in sensorimotor areas is sensitive to the temporal structure of a movement perturbation even at the earliest stage in learning. This insight has direct implications for the development of computational models of early-stage motor adaptation and the evolution of this adaptive response with continued training.'),
(88536, 2017, 'plos', 'Noise, multisensory integration, and previous response in perceptual disambiguation', 'Parise, Cesare V|Ernst, Marc O', 'Oculus Research, Redmond, Washington, United States of America.|Cognitive Neuroscience Department and Cognitive Interaction Technology-Center of Excellence, Bielefeld University, Bielefeld, Germany.', 'United States|Germany', 5, 'Acoustic Stimulation|Adult|Algorithms|Auditory Perception|Computational Biology|Decision Making|Female|Humans|Male|Models, Psychological|Photic Stimulation|Psychophysics|Visual Perception|Young Adult', 'Journal Article', '10.1371/journal.pcbi.1005546', '28692700', 'Sensory information about the state of the world is generally ambiguous. Understanding how the nervous system resolves such ambiguities to infer the actual state of the world is a central quest for sensory neuroscience. However, the computational principles of perceptual disambiguation are still poorly understood: What drives perceptual decision-making between multiple equally valid solutions? Here we investigate how humans gather and combine sensory information-within and across modalities-to disambiguate motion perception in an ambiguous audiovisual display, where two moving stimuli could appear as either streaming through, or bouncing off each other. By combining psychophysical classification tasks with reverse correlation analyses, we identified the particular spatiotemporal stimulus patterns that elicit a stream or a bounce percept, respectively. From that, we developed and tested a computational model for uni- and multi-sensory perceptual disambiguation that tightly replicates human performance. Specifically, disambiguation relies on knowledge of prototypical bouncing events that contain characteristic patterns of motion energy in the dynamic visual display. Next, the visual information is linearly integrated with auditory cues and prior knowledge about the history of recent perceptual interpretations. What is more, we demonstrate that perceptual decision-making with ambiguous displays is systematically driven by noise, whose random patterns not only promote alternation, but also provide signal-like information that biases perception in highly predictable fashion.'),
(88537, 2017, 'plos', 'Possible roles of mechanical cell elimination intrinsic to growing tissues from the perspective of tissue growth efficiency and homeostasis', 'Lee, Sang-Woo|Morishita, Yoshihiro', 'Laboratory for Developmental Morphogeometry, RIKEN Quantitative Biology Center, Kobe, Japan.|Laboratory for Developmental Morphogeometry, RIKEN Quantitative Biology Center, Kobe, Japan.', 'Japan|Japan', 0, 'Animals|Biological Phenomena|Biomechanical Phenomena|Cell Physiological Phenomena|Computational Biology|Drosophila|Epithelium|Genetic Fitness|Homeostasis|Models, Biological|Plant Development|Xenopus', 'Journal Article', '10.1371/journal.pcbi.1005651', '28704373', 'Cell competition is a phenomenon originally described as the competition between cell populations with different genetic backgrounds, losing cells with lower fitness are eliminated. With the progress in identification of related molecules, some reports described the relevance of cell mechanics during elimination. Furthermore, recent live imaging studies have shown that even in tissues composed of genetically identical cells, a non-negligible number of cells are eliminated during growth. Thus, mechanical cell elimination (MCE) as a consequence of mechanical cellular interactions is an unavoidable event in growing tissues and a commonly observed phenomenon. Here, we studied MCE in a genetically-homogeneous tissue from the perspective of tissue growth efficiency and homeostasis. First, we propose two quantitative measures, cell and tissue fitness, to evaluate cellular competitiveness and tissue growth efficiency, respectively. By mechanical tissue simulation in a pure population where all cells have the same mechanical traits, we clarified the dependence of cell elimination rate or cell fitness on different mechanical/growth parameters. In particular, we found that geometrical (specifically, cell size) and mechanical (stress magnitude) heterogeneities are common determinants of the elimination rate. Based on these results, we propose possible mechanical feedback mechanisms that could improve tissue growth efficiency and density/stress homeostasis. Moreover, when cells with different mechanical traits are mixed (e.g., in the presence of phenotypic variation), we show that MCE could drive a drastic shift in cell trait distribution, thereby improving tissue growth efficiency through the selection of cellular traits, i.e. intra-tissue evolution. Along with the improvement of growth efficiency, cell density, stress state, and phenotype (mechanical traits) were also shown to be homogenized through growth. More theoretically, we propose a mathematical model that approximates cell competition dynamics, by which the time evolution of tissue fitness and cellular trait distribution can be predicted without directly simulating a cell-based mechanical model.'),
(88538, 2017, 'plos', 'Spatial organization of the budding yeast genome in the cell nucleus and identification of specific chromatin interactions from multi-chromosome constrained chromatin model', 'Gürsoy, Gamze|Xu, Yun|Liang, Jie', 'The Richard and Loan Hill Department of Bioengineering, Program in Bioinformatics, University of Illinois at Chicago, Chicago, Illinois, United States of America.|The Richard and Loan Hill Department of Bioengineering, Program in Bioinformatics, University of Illinois at Chicago, Chicago, Illinois, United States of America.|The Richard and Loan Hill Department of Bioengineering, Program in Bioinformatics, University of Illinois at Chicago, Chicago, Illinois, United States of America.', 'United States|United States|United States', 0, 'Cell Nucleus|Chromatin|Chromosomes, Fungal|Genome, Fungal|Genomics|Models, Genetic|Saccharomycetales|Single-Cell Analysis', 'Journal Article', '10.1371/journal.pcbi.1005658', '28704374', 'Nuclear landmarks and biochemical factors play important roles in the organization of the yeast genome. The interaction pattern of budding yeast as measured from genome-wide 3C studies are largely recapitulated by model polymer genomes subject to landmark constraints. However, the origin of inter-chromosomal interactions, specific roles of individual landmarks, and the roles of biochemical factors in yeast genome organization remain unclear. Here we describe a multi-chromosome constrained self-avoiding chromatin model (mC-SAC) to gain understanding of the budding yeast genome organization. With significantly improved sampling of genome structures, both intra- and inter-chromosomal interaction patterns from genome-wide 3C studies are accurately captured in our model at higher resolution than previous studies. We show that nuclear confinement is a key determinant of the intra-chromosomal interactions, and centromere tethering is responsible for the inter-chromosomal interactions. In addition, important genomic elements such as fragile sites and tRNA genes are found to be clustered spatially, largely due to centromere tethering. We uncovered previously unknown interactions that were not captured by genome-wide 3C studies, which are found to be enriched with tRNA genes, RNAPIII and TFIIS binding. Moreover, we identified specific high-frequency genome-wide 3C interactions that are unaccounted for by polymer effects under landmark constraints. These interactions are enriched with important genes and likely play biological roles.'),
(88539, 2017, 'plos', 'Cooperative stochastic binding and unbinding explain synaptic size dynamics and statistics', 'Shomar, Aseel|Geyrhofer, Lukas|Ziv, Noam E|Brenner, Naama', 'Department of Chemical Engineering, Technion, Haifa, Israel.|Department of Chemical Engineering, Technion, Haifa, Israel.|Network Biology Research Laboratories, Lorry Lokey Center for Life Sciences and Engineering, Technion, Haifa, Israel.|Department of Chemical Engineering, Technion, Haifa, Israel.', 'Israel|Israel|Israel|Israel', 0, 'Animals|Cerebral Cortex|Computational Biology|Models, Neurological|Neurons|Particle Size|Protein Binding|Rats|Stochastic Processes|Synapses|Synaptic Transmission', 'Journal Article', '10.1371/journal.pcbi.1005668', '28704399', 'Synapses are dynamic molecular assemblies whose sizes fluctuate significantly over time-scales of hours and days. In the current study, we examined the possibility that the spontaneous microscopic dynamics exhibited by synaptic molecules can explain the macroscopic size fluctuations of individual synapses and the statistical properties of synaptic populations. We present a mesoscopic model, which ties the two levels. Its basic premise is that synaptic size fluctuations reflect cooperative assimilation and removal of molecules at a patch of postsynaptic membrane. The introduction of cooperativity to both assimilation and removal in a stochastic biophysical model of these processes, gives rise to features qualitatively similar to those measured experimentally: nanoclusters of synaptic scaffolds, fluctuations in synaptic sizes, skewed, stable size distributions and their scaling in response to perturbations. Our model thus points to the potentially fundamental role of cooperativity in dictating synaptic remodeling dynamics and offers a conceptual understanding of these dynamics in terms of central microscopic features and processes.'),
(88540, 2017, 'plos', 'Deciphering the regulation of P2X4 receptor channel gating by ivermectin using Markov models', 'Mackay, Laurent|Zemkova, Hana|Stojilkovic, Stanko S|Sherman, Arthur|Khadra, Anmar', 'Department of Physiology, McGill University, Montreal, Québec, Canada.|Department of Cellular and Molecular Neuroendocrinology, Institute of Physiology Academy of Sciences of the Czech Republic, Prague, Czech Republic.|Section on Cellular Signaling, Eunice Kennedy Shiver National Institute of Child Health and Human Development, National Institutes of Health, Bethesda, Maryland, United States of America.|Laboratory of Biological Modeling, National Institute of Diabetes, Digestive and Kidney Diseases, National Institutes of Health, Bethesda, Maryland, United States of America.|Department of Physiology, McGill University, Montreal, Québec, Canada.', 'Canada|-|United States|United States|Canada', 0, 'Adenosine Triphosphate|Algorithms|Binding Sites|HEK293 Cells|Humans|Ion Channel Gating|Ivermectin|Markov Chains|Patch-Clamp Techniques|Receptors, Purinergic P2X4', 'Journal Article', '10.1371/journal.pcbi.1005643', '28708827', 'The P2X4 receptor (P2X4R) is a member of a family of purinergic channels activated by extracellular ATP through three orthosteric binding sites and allosterically regulated by ivermectin (IVM), a broad-spectrum antiparasitic agent. Treatment with IVM increases the efficacy of ATP to activate P2X4R, slows both receptor desensitization during sustained ATP application and receptor deactivation after ATP washout, and makes the receptor pore permeable to NMDG+, a large organic cation. Previously, we developed a Markov model based on the presence of one IVM binding site, which described some effects of IVM on rat P2X4R. Here we present two novel models, both with three IVM binding sites. The simpler one-layer model can reproduce many of the observed time series of evoked currents, but does not capture well the short time scales of activation, desensitization, and deactivation. A more complex two-layer model can reproduce the transient changes in desensitization observed upon IVM application, the significant increase in ATP-induced current amplitudes at low IVM concentrations, and the modest increase in the unitary conductance. In addition, the two-layer model suggests that this receptor can exist in a deeply inactivated state, not responsive to ATP, and that its desensitization rate can be altered by each of the three IVM binding sites. In summary, this study provides a detailed analysis of P2X4R kinetics and elucidates the orthosteric and allosteric mechanisms regulating its channel gating.'),
(88541, 2017, 'plos', 'A new index for characterizing micro-bead motion in a flow induced by ciliary beating: Part II, modeling', 'Bottier, Mathieu|Peña Fernández, Marta|Pelle, Gabriel|Isabey, Daniel|Louis, Bruno|Grotberg, James B|Filoche, Marcel', 'Eq. 13, Institut Mondor de Recherche Biomédicale, Inserm U955, Créteil, France.|Eq. 13, Institut Mondor de Recherche Biomédicale, Inserm U955, Créteil, France.|Eq. 13, Institut Mondor de Recherche Biomédicale, Inserm U955, Créteil, France.|Eq. 13, Institut Mondor de Recherche Biomédicale, Inserm U955, Créteil, France.|Eq. 13, Institut Mondor de Recherche Biomédicale, Inserm U955, Créteil, France.|Department of Biomedical Engineering, University of Michigan, Ann Arbor, MI, USA.|Eq. 13, Institut Mondor de Recherche Biomédicale, Inserm U955, Créteil, France.', 'France|France|France|France|France|United States|France', 7, 'Animals|Biological Clocks|Biological Transport, Active|Cilia|Computer Simulation|Humans|Lung|Microfluidics|Microspheres|Models, Biological|Mucociliary Clearance|Mucus|Respiratory Mucosa', 'Journal Article', '10.1371/journal.pcbi.1005552', '28708866', 'Mucociliary clearance is one of the major lines of defense of the human respiratory system. The mucus layer coating the airways is constantly moved along and out of the lung by the activity of motile cilia, expelling at the same time particles trapped in it. The efficiency of the cilia motion can experimentally be assessed by measuring the velocity of micro-beads traveling through the fluid surrounding the cilia. Here we present a mathematical model of the fluid flow and of the micro-beads motion. The coordinated movement of the ciliated edge is represented as a continuous envelope imposing a periodic moving velocity boundary condition on the surrounding fluid. Vanishing velocity and vanishing shear stress boundary conditions are applied to the fluid at a finite distance above the ciliated edge. The flow field is expanded in powers of the amplitude of the individual cilium movement. It is found that the continuous component of the horizontal velocity at the ciliated edge generates a 2D fluid velocity field with a parabolic profile in the vertical direction, in agreement with the experimental measurements. Conversely, we show than this model can be used to extract microscopic properties of the cilia motion by extrapolating the micro-bead velocity measurement at the ciliated edge. Finally, we derive from these measurements a scalar index providing a direct assessment of the cilia beating efficiency. This index can easily be measured in patients without any modification of the current clinical procedures.'),
(88542, 2017, 'plos', 'A new index for characterizing micro-bead motion in a flow induced by ciliary beating: Part I, experimental analysis', 'Bottier, Mathieu|Blanchon, Sylvain|Pelle, Gabriel|Bequignon, Emilie|Isabey, Daniel|Coste, André|Escudier, Estelle|Grotberg, James B|Papon, Jean-François|Filoche, Marcel|Louis, Bruno', 'Inserm U955, Equipe 13, Créteil, France.|Inserm U955, Equipe 13, Créteil, France.|Inserm U955, Equipe 13, Créteil, France.|Inserm U955, Equipe 13, Créteil, France.|Inserm U955, Equipe 13, Créteil, France.|Inserm U955, Equipe 13, Créteil, France.|Inserm, U933, Paris, France.|Department of Biomedical Engineering, University of Michigan, Ann Arbor, MI, USA.|Inserm U955, Equipe 13, Créteil, France.|Inserm U955, Equipe 13, Créteil, France.|Inserm U955, Equipe 13, Créteil, France.', 'France|France|France|France|France|France|France|United States|France|France|France', 2, 'Biological Clocks|Biological Transport, Active|Cilia|Computer Simulation|Humans|Image Interpretation, Computer-Assisted|Lung|Microfluidics|Microscopy, Video|Microspheres|Models, Biological|Mucociliary Clearance|Mucus|Respiratory Mucosa', 'Journal Article', '10.1371/journal.pcbi.1005605', '28708889', 'Mucociliary clearance is one of the major lines of defense of the respiratory system. The mucus layer coating the pulmonary airways is moved along and out of the lung by the activity of motile cilia, thus expelling the particles trapped in it. Here we compare ex vivo measurements of a Newtonian flow induced by cilia beating (using micro-beads as tracers) and a mathematical model of this fluid flow, presented in greater detail in a second companion article. Samples of nasal epithelial cells placed in water are recorded by high-speed video-microscopy and ciliary beat pattern is inferred. Automatic tracking of micro-beads, used as markers of the flow generated by cilia motion, enables us also to assess the velocity profile as a function of the distance above the cilia. This profile is shown to be essentially parabolic. The obtained experimental data are used to feed a 2D mathematical and numerical model of the coupling between cilia, fluid, and micro-bead motion. From the model and the experimental measurements, the shear stress exerted by the cilia is deduced. Finally, this shear stress, which can easily be measured in the clinical setting, is proposed as a new index for characterizing the efficiency of ciliary beating.'),
(88543, 2017, 'plos', 'A curated genome-scale metabolic model of Bordetella pertussis metabolism', 'Fyson, Nick|King, Jerry|Belcher, Thomas|Preston, Andrew|Colijn, Caroline', 'Department of Mathematics, Imperial College, London, UK.|The Milner Centre for Evolution and Department of Biology and Biochemistry, University of Bath, Bath, UK.|The Milner Centre for Evolution and Department of Biology and Biochemistry, University of Bath, Bath, UK.|The Milner Centre for Evolution and Department of Biology and Biochemistry, University of Bath, Bath, UK.|Department of Mathematics, Imperial College, London, UK.', 'United Kingdom|United Kingdom|United Kingdom|United Kingdom|United Kingdom', 1, 'Bordetella pertussis|Fumarates|Genome, Bacterial|Glutamic Acid|Humans|Metabolic Flux Analysis|Models, Biological|ROC Curve|Whooping Cough', 'Journal Article', '10.1371/journal.pcbi.1005639', '28715411', 'The Gram-negative bacterium Bordetella pertussis is the causative agent of whooping cough, a serious respiratory infection causing hundreds of thousands of deaths annually worldwide. There are effective vaccines, but their production requires growing large quantities of B. pertussis. Unfortunately, B. pertussis has relatively slow growth in culture, with low biomass yields and variable growth characteristics. B. pertussis also requires a relatively expensive growth medium. We present a new, curated flux balance analysis-based model of B. pertussis metabolism. We enhance the model with an experimentally-determined biomass objective function, and we perform extensive manual curation. We test the models predictions with a genome-wide screen for essential genes using a transposon-directed insertional sequencing (TraDIS) approach. We test its predictions of growth for different carbon sources in the medium. The model predicts essentiality with an accuracy of 83% and correctly predicts improvements in growth under increased glutamate:fumarate ratios. We provide the model in SBML format, along with gene essentiality predictions.');
INSERT INTO `papers` (`id`, `ano`, `journal`, `titulo`, `autores`, `afiliacao`, `pais`, `citacoes`, `palavra_chave`, `categorias`, `doi`, `pubmed`, `abstract`) VALUES
(88544, 2017, 'plos', 'Blood vessel tortuosity selects against evolution of aggressive tumor cells in confined tissue environments: A modeling approach', 'Szabó, András|Merks, Roeland M H', 'Centrum Wiskunde & Informatica, Amsterdam, The Netherlands.|Centrum Wiskunde & Informatica, Amsterdam, The Netherlands.', 'Netherlands|Netherlands', 1, 'Animals|Computational Biology|Computer Simulation|Humans|Mice|Models, Biological|Mutation|Neoplasms|Neovascularization, Pathologic|Tumor Microenvironment', 'Journal Article', '10.1371/journal.pcbi.1005635', '28715420', 'Cancer is a disease of cellular regulation, often initiated by genetic mutation within cells, and leading to a heterogeneous cell population within tissues. In the competition for nutrients and growth space within the tumors the phenotype of each cell determines its success. Selection in this process is imposed by both the microenvironment (neighboring cells, extracellular matrix, and diffusing substances), and the whole of the organism through for example the blood supply. In this view, the development of tumor cells is in close interaction with their increasingly changing environment: the more cells can change, the more their environment will change. Furthermore, instabilities are also introduced on the organism level: blood supply can be blocked by increased tissue pressure or the tortuosity of the tumor-neovascular vessels. This coupling between cell, microenvironment, and organism results in behavior that is hard to predict. Here we introduce a cell-based computational model to study the effect of blood flow obstruction on the micro-evolution of cells within a cancerous tissue. We demonstrate that stages of tumor development emerge naturally, without the need for sequential mutation of specific genes. Secondly, we show that instabilities in blood supply can impact the overall development of tumors and lead to the extinction of the dominant aggressive phenotype, showing a clear distinction between the fitness at the cell level and survival of the population. This provides new insights into potential side effects of recent tumor vasculature normalization approaches.'),
(88545, 2017, 'plos', 'Atomistic fingerprint of hyaluronan-CD44 binding', 'Vuorio, Joni|Vattulainen, Ilpo|Martinez-Seara, Hector', 'Department of Physics, Tampere University of Technology, Tampere, Finland.|Department of Physics, Tampere University of Technology, Tampere, Finland.|Department of Physics, Tampere University of Technology, Tampere, Finland.', 'Finland|Finland|Finland', 10, 'Computational Biology|Humans|Hyaluronan Receptors|Hyaluronic Acid|Molecular Dynamics Simulation|Protein Binding|Protein Conformation', 'Journal Article', '10.1371/journal.pcbi.1005663', '28715483', 'Hyaluronan is a polyanionic, megadalton-scale polysaccharide, which initiates cell signaling by interacting with several receptor proteins including CD44 involved in cell-cell interactions and cell adhesion. Previous studies of the CD44 hyaluronan binding domain have identified multiple widespread residues to be responsible for its recognition capacity. In contrast, the X-ray structural characterization of CD44 has revealed a single binding mode associated with interactions that involve just a fraction of these residues. In this study, we show through atomistic molecular dynamics simulations that hyaluronan can bind CD44 with three topographically different binding modes that in unison define an interaction fingerprint, thus providing a plausible explanation for the disagreement between the earlier studies. Our results confirm that the known crystallographic mode is the strongest of the three binding modes. The other two modes represent metastable configurations that are readily available in the initial stages of the binding, and they are also the most frequently observed modes in our unbiased simulations. We further discuss how CD44, fostered by the weaker binding modes, diffuses along HA when attached. This 1D diffusion combined with the constrained relative orientation of the diffusing proteins is likely to influence the aggregation kinetics of CD44. Importantly, CD44 aggregation has been suggested to be a possible mechanism in CD44-mediated signaling.'),
(88546, 2017, 'plos', 'Correction: Parameter estimation for multistage clonal expansion models from cancer incidence data: A practical identifiability analysis', 'Brouwer, Andrew F|Meza, Rafael|Eisenberg, Marisa C', 'Department of Physics, Tampere University of Technology, Tampere, Finland.|Department of Physics, Tampere University of Technology, Tampere, Finland.|Department of Physics, Tampere University of Technology, Tampere, Finland.', 'Finland|Finland|Finland', 0, '-', 'Published Erratum', '10.1371/journal.pcbi.1005660', '28715500', '[This corrects the article DOI: 10.1371/journal.pcbi.1005431.].'),
(88547, 2017, 'plos', 'Diversity and distribution of nuclease bacteriocins in bacterial genomes revealed using Hidden Markov Models', 'Sharp, Connor|Bray, James|Housden, Nicholas G|Maiden, Martin C J|Kleanthous, Colin', 'Department of Biochemistry, University of Oxford, Oxford, United Kingdom.|Department of Zoology, University of Oxford, Oxford, United Kingdom.|Department of Biochemistry, University of Oxford, Oxford, United Kingdom.|Department of Zoology, University of Oxford, Oxford, United Kingdom.|Department of Biochemistry, University of Oxford, Oxford, United Kingdom.', 'United Kingdom|United Kingdom|United Kingdom|United Kingdom|United Kingdom', 17, 'Anti-Infective Agents|Bacterial Proteins|Bacteriocins|Computer Simulation|Deoxyribonucleases|Gammaproteobacteria|Genome, Bacterial|Markov Chains|Pseudomonas aeruginosa', 'Journal Article', '10.1371/journal.pcbi.1005652', '28715501', 'Bacteria exploit an arsenal of antimicrobial peptides and proteins to compete with each other. Three main competition systems have been described: type six secretion systems (T6SS), contact dependent inhibition (CDI), and bacteriocins. Unlike T6SS and CDI systems, bacteriocins do not require contact between bacteria but are diffusible toxins released into the environment. Identified almost a century ago, our understanding of bacteriocin distribution and prevalence in bacterial populations remains poor. In the case of protein bacteriocins, this is because of high levels of sequence diversity and difficulties in distinguishing their killing domains from those of other competition systems. Here, we develop a robust bioinformatics pipeline exploiting Hidden Markov Models for the identification of nuclease bacteriocins (NBs) in bacteria of which, to-date, only a handful are known. NBs are large (>60 kDa) toxins that target nucleic acids (DNA, tRNA or rRNA) in the cytoplasm of susceptible bacteria, usually closely related to the producing organism. We identified >3000 NB genes located on plasmids or on the chromosome from 53 bacterial species distributed across different ecological niches, including human, animals, plants, and the environment. A newly identified NB predicted to be specific for Pseudomonas aeruginosa (pyocin Sn) was produced and shown to kill P. aeruginosa thereby validating our pipeline. Intriguingly, while the genes encoding the machinery needed for NB translocation across the cell envelope are widespread in Gram-negative bacteria, NBs are found exclusively in xcexb3-proteobacteria. Similarity network analysis demonstrated that NBs fall into eight groups each with a distinct arrangement of protein domains involved in import. The only structural feature conserved across all groups was a sequence motif critical for cell-killing that is generally not found in bacteriocins targeting the periplasm, implying a specific role in translocating the nuclease to the cytoplasm. Finally, we demonstrate a significant association between nuclease colicins, NBs specific for Escherichia coli, and virulence factors, suggesting NBs play a role in infection processes, most likely by enabling pathogens to outcompete commensal bacteria.'),
(88548, 2017, 'plos', 'Correction: Hard real-time closed-loop electrophysiology with the Real-Time eXperiment Interface (RTXI)', 'PLOS Computational Biology Staff', 'Department of Biochemistry, University of Oxford, Oxford, United Kingdom.', 'United Kingdom', 0, '-', 'Published Erratum', '10.1371/journal.pcbi.1005656', '28715502', '[This corrects the article DOI: 10.1371/journal.pcbi.1005430.].'),
(88549, 2017, 'plos', 'CLIC, a tool for expanding biological pathways based on co-expression across thousands of datasets', 'Li, Yang|Jourdain, Alexis A|Calvo, Sarah E|Liu, Jun S|Mootha, Vamsi K', 'Howard Hughes Medical Institute and Department of Molecular Biology and the Center for Genomic Medicine, Massachusetts General Hospital, Boston, MA, United States of America and Department of Systems Biology, Harvard Medical School, Boston, MA United States of America.|Howard Hughes Medical Institute and Department of Molecular Biology and the Center for Genomic Medicine, Massachusetts General Hospital, Boston, MA, United States of America and Department of Systems Biology, Harvard Medical School, Boston, MA United States of America.|Howard Hughes Medical Institute and Department of Molecular Biology and the Center for Genomic Medicine, Massachusetts General Hospital, Boston, MA, United States of America and Department of Systems Biology, Harvard Medical School, Boston, MA United States of America.|Department of Statistics, Harvard University, Cambridge, MA, United States of America.|Howard Hughes Medical Institute and Department of Molecular Biology and the Center for Genomic Medicine, Massachusetts General Hospital, Boston, MA, United States of America and Department of Systems Biology, Harvard Medical School, Boston, MA United States of America.', 'United States|United States|United States|United States|United States', 0, 'Algorithms|Cluster Analysis|Databases, Factual|Gene Expression Profiling|Gene Regulatory Networks|Genomics|Humans|Models, Biological|Signal Transduction|Software|Transcriptome', 'Journal Article', '10.1371/journal.pcbi.1005653', '28719601', 'In recent years, there has been a huge rise in the number of publicly available transcriptional profiling datasets. These massive compendia comprise billions of measurements and provide a special opportunity to predict the function of unstudied genes based on co-expression to well-studied pathways. Such analyses can be very challenging, however, since biological pathways are modular and may exhibit co-expression only in specific contexts. To overcome these challenges we introduce CLIC, CLustering by Inferred Co-expression. CLIC accepts as input a pathway consisting of two or more genes. It then uses a Bayesian partition model to simultaneously partition the input gene set into coherent co-expressed modules (CEMs), while assigning the posterior probability for each dataset in support of each CEM. CLIC then expands each CEM by scanning the transcriptome for additional co-expressed genes, quantified by an integrated log-likelihood ratio (LLR) score weighted for each dataset. As a byproduct, CLIC automatically learns the conditions (datasets) within which a CEM is operative. We implemented CLIC using a compendium of 1774 mouse microarray datasets (28628 microarrays) or 1887 human microarray datasets (45158 microarrays). CLIC analysis reveals that of 910 canonical biological pathways, 30% consist of strongly co-expressed gene modules for which new members are predicted. For example, CLIC predicts a functional connection between protein C7orf55 (FMC1) and the mitochondrial ATP synthase complex that we have experimentally validated. CLIC is freely available at www.gene-clic.org. We anticipate that CLIC will be valuable both for revealing new components of biological pathways as well as the conditions in which they are active.'),
(88550, 2017, 'plos', 'Stress-induced mutagenesis: Stress diversity facilitates the persistence of mutator genes', 'Lukaxc4x8dixc5xa1inovxc3xa1, Marta|Novak, Sebastian|Paixxc3xa3o, Tiago', 'Institute of Science and Technology Austria, Klosterneuburg, Austria.|Institute of Science and Technology Austria, Klosterneuburg, Austria.|Institute of Science and Technology Austria, Klosterneuburg, Austria.', 'Austria|Austria|Austria', 0, 'Alleles|Computational Biology|Evolution, Molecular|Models, Genetic|Mutagenesis|Mutation|Stress, Physiological', 'Journal Article', '10.1371/journal.pcbi.1005609', '28719607', 'Mutator strains are expected to evolve when the availability and effect of beneficial mutations are high enough to counteract the disadvantage from deleterious mutations that will inevitably accumulate. As the population becomes more adapted to its environment, both availability and effect of beneficial mutations necessarily decrease and mutation rates are predicted to decrease. It has been shown that certain molecular mechanisms can lead to increased mutation rates when the organism finds itself in a stressful environment. While this may be a correlated response to other functions, it could also be an adaptive mechanism, raising mutation rates only when it is most advantageous. Here, we use a mathematical model to investigate the plausibility of the adaptive hypothesis. We show that such a mechanism can be mantained if the population is subjected to diverse stresses. By simulating various antibiotic treatment schemes, we find that combination treatments can reduce the effectiveness of second-order selection on stress-induced mutagenesis. We discuss the implications of our results to strategies of antibiotic therapy.'),
(88551, 2017, 'plos', 'Automatic analysis and 3D-modelling of Hi-C data using TADbit reveals structural features of the fly chromatin colors', 'Serra, François|Baù, Davide|Goodstadt, Mike|Castillo, David|Filion, Guillaume J|Marti-Renom, Marc A', 'CNAG-CRG, Centre for Genomic Regulation (CRG), Barcelona Institute of Science and Technology (BIST), Barcelona, Spain.|CNAG-CRG, Centre for Genomic Regulation (CRG), Barcelona Institute of Science and Technology (BIST), Barcelona, Spain.|CNAG-CRG, Centre for Genomic Regulation (CRG), Barcelona Institute of Science and Technology (BIST), Barcelona, Spain.|CNAG-CRG, Centre for Genomic Regulation (CRG), Barcelona Institute of Science and Technology (BIST), Barcelona, Spain.|Gene Regulation, Stem Cells and Cancer Program, Centre for Genomic Regulation (CRG), Barcelona, Spain.|CNAG-CRG, Centre for Genomic Regulation (CRG), Barcelona Institute of Science and Technology (BIST), Barcelona, Spain.', 'Spain|Spain|Spain|Spain|Spain|Spain', 0, 'Algorithms|Animals|Chromatin|Computational Biology|Drosophila melanogaster|Genome, Insect|Imaging, Three-Dimensional|Software', 'Journal Article', '10.1371/journal.pcbi.1005665', '28723903', 'The sequence of a genome is insufficient to understand all genomic processes carried out in the cell nucleus. To achieve this, the knowledge of its three-dimensional architecture is necessary. Advances in genomic technologies and the development of new analytical methods, such as Chromosome Conformation Capture (3C) and its derivatives, provide unprecedented insights in the spatial organization of genomes. Here we present TADbit, a computational framework to analyze and model the chromatin fiber in three dimensions. Our package takes as input the sequencing reads of 3C-based experiments and performs the following main tasks: (i) pre-process the reads, (ii) map the reads to a reference genome, (iii) filter and normalize the interaction data, (iv) analyze the resulting interaction matrices, (v) build 3D models of selected genomic domains, and (vi) analyze the resulting models to characterize their structural properties. To illustrate the use of TADbit, we automatically modeled 50 genomic domains from the fly genome revealing differential structural features of the previously defined chromatin colors, establishing a link between the conformation of the genome and the local chromatin composition. TADbit provides three-dimensional models built from 3C-based experiments, which are ready for visualization and for characterizing their relation to gene expression and epigenetic states. TADbit is an open-source Python library available for download from https://github.com/3DGenomes/tadbit.'),
(88552, 2017, 'plos', 'Grandmothering and cognitive resources are required for the emergence of menopause and extensive post-reproductive lifespan', 'Aimé, Carla|André, Jean-Baptiste|Raymond, Michel', 'Institut des sciences de lévolution de Montpellier. CNRS UMR 5554 -IRD-Université de Montpellier, Montpellier, France.|Institut des sciences de lévolution de Montpellier. CNRS UMR 5554 -IRD-Université de Montpellier, Montpellier, France.|Institut des sciences de lévolution de Montpellier. CNRS UMR 5554 -IRD-Université de Montpellier, Montpellier, France.', 'France|France|France', 10, 'Aging|Biological Evolution|Cognition|Ecology|Family|Female|Grandparents|Humans|Menopause|Parenting', 'Journal Article', '10.1371/journal.pcbi.1005631', '28727724', 'Menopause, the permanent cessation of ovulation, occurs in humans well before the end of the expected lifespan, leading to an extensive post-reproductive period which remains a puzzle for evolutionary biologists. All human populations display this particularity, thus, it is difficult to empirically evaluate the conditions for its emergence. In this study, we used artificial neural networks to model the emergence and evolution of allocation decisions related to reproduction in simulated populations. When allocation decisions were allowed to freely evolve, both menopause and extensive post-reproductive life-span emerged under some ecological conditions. This result allowed us to test various hypotheses about the required conditions for the emergence of menopause and extensive post-reproductive life-span. Our findings did not support the Maternal Hypothesis (menopause has evolved to avoid the risk of dying in childbirth, which is higher in older women). In contrast, results supported a shared prediction from the Grandmother Hypothesis and the Embodied Capital Model. Indeed, we found that extensive post-reproductive lifespan allows resource reallocation to increase fertility of the children and survival of the grandchildren. Furthermore, neural capital development and the skill intensiveness of the foraging niche, rather than strength, played a major role in shaping the age profile of somatic and cognitive senescence in our simulated populations. This result supports the Embodied Capital Model rather than the Grand-Mother Hypothesis. Finally, in simulated populations where menopause had already evolved, we found that reduced post-reproductive lifespan lead to reduced childrens fertility and grandchildrens survival. The results are discussed in the context of the evolutionary emergence of menopause and extensive post-reproductive life-span.'),
(88553, 2017, 'plos', 'redGEM: Systematic reduction and analysis of genome-scale metabolic reconstructions for development of consistent core metabolic models', 'Ataman, Meric|Hernandez Gardiol, Daniel F|Fengos, Georgios|Hatzimanikatis, Vassily', 'Laboratory of Computational Systems Biotechnology, École Polytechnique Fédérale de Lausanne (EPFL), CH, Lausanne, Switzerland.|Laboratory of Computational Systems Biotechnology, École Polytechnique Fédérale de Lausanne (EPFL), CH, Lausanne, Switzerland.|Laboratory of Computational Systems Biotechnology, École Polytechnique Fédérale de Lausanne (EPFL), CH, Lausanne, Switzerland.|Laboratory of Computational Systems Biotechnology, École Polytechnique Fédérale de Lausanne (EPFL), CH, Lausanne, Switzerland.', 'Switzerland|Switzerland|Switzerland|Switzerland', 0, 'Algorithms|Escherichia coli|Genome|Metabolic Networks and Pathways|Models, Biological|Software|Systems Biology', 'Journal Article', '10.1371/journal.pcbi.1005444', '28727725', 'Genome-scale metabolic reconstructions have proven to be valuable resources in enhancing our understanding of metabolic networks as they encapsulate all known metabolic capabilities of the organisms from genes to proteins to their functions. However the complexity of these large metabolic networks often hinders their utility in various practical applications. Although reduced models are commonly used for modeling and in integrating experimental data, they are often inconsistent across different studies and laboratories due to different criteria and detail, which can compromise transferability of the findings and also integration of experimental data from different groups. In this study, we have developed a systematic semi-automatic approach to reduce genome-scale models into core models in a consistent and logical manner focusing on the central metabolism or subsystems of interest. The method minimizes the loss of information using an approach that combines graph-based search and optimization methods. The resulting core models are shown to be able to capture key properties of the genome-scale models and preserve consistency in terms of biomass and by-product yields, flux and concentration variability and gene essentiality. The development of these consistently-reduced models will help to clarify and facilitate integration of different experimental data to draw new understanding that can be directly extendable to genome-scale models.'),
(88554, 2017, 'plos', 'Effect of depth information on multiple-object tracking in three dimensions: A probabilistic perspective', 'Cooke, James R H|Ter Horst, Arjan C|van Beers, Robert J|Medendorp, W Pieter', 'Radboud University, Donders Institute for Brain, Cognition and Behaviour, Nijmegen, The Netherlands.|Radboud University, Donders Institute for Brain, Cognition and Behaviour, Nijmegen, The Netherlands.|Radboud University, Donders Institute for Brain, Cognition and Behaviour, Nijmegen, The Netherlands.|Radboud University, Donders Institute for Brain, Cognition and Behaviour, Nijmegen, The Netherlands.', 'Netherlands|Netherlands|Netherlands|Netherlands', 1, 'Adolescent|Adult|Bayes Theorem|Computational Biology|Female|Fixation, Ocular|Humans|Male|Models, Statistical|Photic Stimulation|Psychometrics|Pursuit, Smooth|Young Adult', 'Journal Article', '10.1371/journal.pcbi.1005554', '28727743', 'Many daily situations require us to track multiple objects and people. This ability has traditionally been investigated in observers tracking objects in a plane. This simplification of reality does not address how observers track objects when targets move in three dimensions. Here, we study how observers track multiple objects in 2D and 3D while manipulating the average speed of the objects and the average distance between them. We show that performance declines as speed increases and distance decreases and that overall tracking accuracy is always higher in 3D than in 2D. The effects of distance and dimensionality interact to produce a more than additive improvement in performance during tracking in 3D compared to 2D. We propose an ideal observer model that uses the object dynamics and noisy observations to track the objects. This model provides a good fit to the data and explains the key findings of our experiment as originating from improved inference of object identity by adding the depth dimension.'),
(88555, 2017, 'plos', 'lumpGEM: Systematic generation of subnetworks and elementally balanced lumped reactions for the biosynthesis of target metabolites', 'Ataman, Meric|Hatzimanikatis, Vassily', 'Laboratory of Computational Systems Biotechnology, Ecole Polytechnique Federale de Lausanne (EPFL), Lausanne, Switzerland.|Laboratory of Computational Systems Biotechnology, Ecole Polytechnique Federale de Lausanne (EPFL), Lausanne, Switzerland.', 'Switzerland|Switzerland', 14, 'Escherichia coli|Genomics|Metabolic Networks and Pathways|Models, Biological|Systems Biology', 'Journal Article', '10.1371/journal.pcbi.1005513', '28727789', 'In the post-genomic era, Genome-scale metabolic networks (GEMs) have emerged as invaluable tools to understand metabolic capabilities of organisms. Different parts of these metabolic networks are defined as subsystems/pathways, which are sets of functional roles to implement a specific biological process or structural complex, such as glycolysis and TCA cycle. Subsystem/pathway definition is also employed to delineate the biosynthetic routes that produce biomass building blocks. In databases, such as MetaCyc and SEED, these representations are composed of linear routes from precursors to target biomass building blocks. However, this approach cannot capture the nested, complex nature of GEMs. Here we implemented an algorithm, lumpGEM, which generates biosynthetic subnetworks composed of reactions that can synthesize a target metabolite from a set of defined core precursor metabolites. lumpGEM captures balanced subnetworks, which account for the fate of all metabolites along the synthesis routes, thus encapsulating reactions from various subsystems/pathways to balance these metabolites in the metabolic network. Moreover, lumpGEM collapses these subnetworks into elementally balanced lumped reactions that specify the cost of all precursor metabolites and cofactors. It also generates alternative subnetworks and lumped reactions for the same metabolite, accounting for the flexibility of organisms. lumpGEM is applicable to any GEM and any target metabolite defined in the network. Lumped reactions generated by lumpGEM can be also used to generate properly balanced reduced core metabolic models.'),
(88556, 2017, 'plos', 'Advances in using Internet searches to track dengue', 'Yang, Shihao|Kou, Samuel C|Lu, Fred|Brownstein, John S|Brooke, Nicholas|Santillana, Mauricio', 'Department of Statistics, Harvard University, Cambridge, MA, USA.|Department of Statistics, Harvard University, Cambridge, MA, USA.|Computational Health Informatics Program, Boston Childrens Hospital, Boston, MA, USA.|Computational Health Informatics Program, Boston Childrens Hospital, Boston, MA, USA.|The Synergist, Brussels, Belgium.|Computational Health Informatics Program, Boston Childrens Hospital, Boston, MA, USA.', 'United States|United States|United States|United States|Belgium|United States', 0, 'Asia, Southeastern|Brazil|Computational Biology|Databases, Factual|Dengue|History, 20th Century|History, 21st Century|Humans|Internet|Mexico|Population Surveillance|Search Engine', 'Historical Article', '10.1371/journal.pcbi.1005607', '28727821', 'Dengue is a mosquito-borne disease that threatens over half of the worlds population. Despite being endemic to more than 100 countries, government-led efforts and tools for timely identification and tracking of new infections are still lacking in many affected areas. Multiple methodologies that leverage the use of Internet-based data sources have been proposed as a way to complement dengue surveillance efforts. Among these, dengue-related Google search trends have been shown to correlate with dengue activity. We extend a methodological framework, initially proposed and validated for flu surveillance, to produce near real-time estimates of dengue cases in five countries/states: Mexico, Brazil, Thailand, Singapore and Taiwan. Our result shows that our modeling framework can be used to improve the tracking of dengue activity in multiple locations around the world.'),
(88557, 2017, 'plos', 'A data-driven modeling approach to identify disease-specific multi-organ networks driving physiological dysregulation', 'Anderson, Warren D|DeCicco, Danielle|Schwaber, James S|Vadigepalli, Rajanikanth', 'Daniel Baugh Institute for Functional Genomics and Computational Biology, Department of Pathology, Anatomy, and Cell Biology, Sidney Kimmel Medical College, Thomas Jefferson University, Philadelphia, PA, USA.|Daniel Baugh Institute for Functional Genomics and Computational Biology, Department of Pathology, Anatomy, and Cell Biology, Sidney Kimmel Medical College, Thomas Jefferson University, Philadelphia, PA, USA.|Daniel Baugh Institute for Functional Genomics and Computational Biology, Department of Pathology, Anatomy, and Cell Biology, Sidney Kimmel Medical College, Thomas Jefferson University, Philadelphia, PA, USA.|Daniel Baugh Institute for Functional Genomics and Computational Biology, Department of Pathology, Anatomy, and Cell Biology, Sidney Kimmel Medical College, Thomas Jefferson University, Philadelphia, PA, USA.', 'United States|United States|United States|United States', 0, 'Adrenal Glands|Animals|Autonomic Nervous System Diseases|Brain Stem|Cardiovascular Diseases|Computational Biology|Gene Expression Profiling|Gene Regulatory Networks|Kidney|Male|Models, Biological|Models, Statistical|Rats|Rats, Inbred SHR|Rats, Inbred WKY', 'Journal Article', '10.1371/journal.pcbi.1005627', '28732007', 'Multiple physiological systems interact throughout the development of a complex disease. Knowledge of the dynamics and connectivity of interactions across physiological systems could facilitate the prevention or mitigation of organ damage underlying complex diseases, many of which are currently refractory to available therapeutics (e.g., hypertension). We studied the regulatory interactions operating within and across organs throughout disease development by integrating in vivo analysis of gene expression dynamics with a reverse engineering approach to infer data-driven dynamic network models of multi-organ gene regulatory influences. We obtained experimental data on the expression of 22 genes across five organs, over a time span that encompassed the development of autonomic nervous system dysfunction and hypertension. We pursued a unique approach for identification of continuous-time models that jointly described the dynamics and structure of multi-organ networks by estimating a sparse subset of xe2x88xbc12,000 possible gene regulatory interactions. Our analyses revealed that an autonomic dysfunction-specific multi-organ sequence of gene expression activation patterns was associated with a distinct gene regulatory network. We analyzed the model structures for adaptation motifs, and identified disease-specific network motifs involving genes that exhibited aberrant temporal dynamics. Bioinformatic analyses identified disease-specific single nucleotide variants within or near transcription factor binding sites upstream of key genes implicated in maintaining physiological homeostasis. Our approach illustrates a novel framework for investigating the pathogenesis through model-based analysis of multi-organ system dynamics and network properties. Our results yielded novel candidate molecular targets driving the development of cardiovascular disease, metabolic syndrome, and immune dysfunction.'),
(88558, 2017, 'plos', 'Long-time analytic approximation of large stochastic oscillators: Simulation, analysis and inference', 'Minas, Giorgos|Rand, David A', 'Zeeman Institute for Systems Biology & Infectious Disease Epidemiology Research, University of Warwick, Coventry, United Kingdom.|Zeeman Institute for Systems Biology & Infectious Disease Epidemiology Research, University of Warwick, Coventry, United Kingdom.', 'United Kingdom|United Kingdom', 5, 'Algorithms|Biological Clocks|Circadian Clocks|Computational Biology|Computer Simulation|Models, Biological|NF-kappa B|Signal Transduction|Stochastic Processes', 'Journal Article', '10.1371/journal.pcbi.1005676', '28742083', 'In order to analyse large complex stochastic dynamical models such as those studied in systems biology there is currently a great need for both analytical tools and also algorithms for accurate and fast simulation and estimation. We present a new stochastic approximation of biological oscillators that addresses these needs. Our method, called phase-corrected LNA (pcLNA) overcomes the main limitations of the standard Linear Noise Approximation (LNA) to remain uniformly accurate for long times, still maintaining the speed and analytically tractability of the LNA. As part of this, we develop analytical expressions for key probability distributions and associated quantities, such as the Fisher Information Matrix and Kullback-Leibler divergence and we introduce a new approach to system-global sensitivity analysis. We also present algorithms for statistical inference and for long-term simulation of oscillating systems that are shown to be as accurate but much faster than leaping algorithms and algorithms for integration of diffusion equations. Stochastic versions of published models of the circadian clock and NF-xcexbaB system are used to illustrate our results.'),
(88559, 2017, 'plos', 'MrTADFinder: A network modularity based approach to identify topologically associating domains in multiple resolutions', 'Yan, Koon-Kiu|Lou, Shaoke|Gerstein, Mark', 'Program in Computational Biology and Bioinformatics, Yale University, New Haven, CT, United States of America.|Program in Computational Biology and Bioinformatics, Yale University, New Haven, CT, United States of America.|Program in Computational Biology and Bioinformatics, Yale University, New Haven, CT, United States of America.', 'United States|United States|United States', 16, 'Algorithms|Cell Line|Cell Nucleus|Chromatin|Chromosomes|Computational Biology|Genome|Humans|Models, Genetic|Protein Binding|Transcription Factors', 'Journal Article', '10.1371/journal.pcbi.1005647', '28742097', 'Genome-wide proximity ligation based assays such as Hi-C have revealed that eukaryotic genomes are organized into structural units called topologically associating domains (TADs). From a visual examination of the chromosomal contact map, however, it is clear that the organization of the domains is not simple or obvious. Instead, TADs exhibit various length scales and, in many cases, a nested arrangement. Here, by exploiting the resemblance between TADs in a chromosomal contact map and densely connected modules in a network, we formulate TAD identification as a network optimization problem and propose an algorithm, MrTADFinder, to identify TADs from intra-chromosomal contact maps. MrTADFinder is based on the network-science concept of modularity. A key component of it is deriving an appropriate background model for contacts in a random chain, by numerically solving a set of matrix equations. The background model preserves the observed coverage of each genomic bin as well as the distance dependence of the contact frequency for any pair of bins exhibited by the empirical map. Also, by introducing a tunable resolution parameter, MrTADFinder provides a self-consistent approach for identifying TADs at different length scales, hence the acronym Mr standing for Multiple Resolutions. We then apply MrTADFinder to various Hi-C datasets. The identified domain boundaries are marked by characteristic signatures in chromatin marks and transcription factors (TF) that are consistent with earlier work. Moreover, by calling TADs at different length scales, we observe that boundary signatures change with resolution, with different chromatin features having different characteristic length scales. Furthermore, we report an enrichment of HOT (high-occupancy target) regions near TAD boundaries and investigate the role of different TFs in determining boundaries at various resolutions. To further explore the interplay between TADs and epigenetic marks, as tumor mutational burden is known to be coupled to chromatin structure, we examine how somatic mutations are distributed across boundaries and find a clear stepwise pattern. Overall, MrTADFinder provides a novel computational framework to explore the multi-scale structures in Hi-C contact maps.'),
(88560, 2017, 'plos', 'Reconstructing the regulatory circuit of cell fate determination in yeast mating response', 'Shao, Bin|Yuan, Haiyu|Zhang, Rongfei|Wang, Xuan|Zhang, Shuwen|Ouyang, Qi|Hao, Nan|Luo, Chunxiong', 'Center for Quantitative Biology, Academy for Advanced Interdisciplinary Studies, Peking University, Beijing, China.|The State Key Laboratory for Artificial Microstructures and Mesoscopic Physics, School of Physics, Peking University, Beijing, China.|Center for Quantitative Biology, Academy for Advanced Interdisciplinary Studies, Peking University, Beijing, China.|School of Informatics and Computing, Indiana University, Bloomington, Indiana, United States of America.|Center for Quantitative Biology, Academy for Advanced Interdisciplinary Studies, Peking University, Beijing, China.|Center for Quantitative Biology, Academy for Advanced Interdisciplinary Studies, Peking University, Beijing, China.|Section of Molecular Biology, Division of Biological Sciences, University of California San Diego, La Jolla, California, United States of America.|Center for Quantitative Biology, Academy for Advanced Interdisciplinary Studies, Peking University, Beijing, China.', 'China|China|China|India|China|China|United States|China', 3, 'Gene Regulatory Networks|Models, Biological|Pheromones|Proteomics|Saccharomyces cerevisiae|Saccharomyces cerevisiae Proteins', 'Journal Article', '10.1371/journal.pcbi.1005671', '28742153', 'Massive technological advances enabled high-throughput measurements of proteomic changes in biological processes. However, retrieving biological insights from large-scale protein dynamics data remains a challenging task. Here we used the mating differentiation in yeast Saccharomyces cerevisiae as a model and developed integrated experimental and computational approaches to analyze the proteomic dynamics during the process of cell fate determination. When exposed to a high dose of mating pheromone, the yeast cell undergoes growth arrest and forms a shmoo-like morphology, however, at intermediate doses, chemotropic elongated growth is initialized. To understand the gene regulatory networks that control this differentiation switch, we employed a high-throughput microfluidic imaging system that allows real-time and simultaneous measurements of cell growth and protein expression. Using kinetic modeling of protein dynamics, we classified the stimulus-dependent changes in protein abundance into two sources: global changes due to physiological alterations and gene-specific changes. A quantitative framework was proposed to decouple gene-specific regulatory modes from the growth-dependent global modulation of protein abundance. Based on the temporal patterns of gene-specific regulation, we established the network architectures underlying distinct cell fates using a reverse engineering method and uncovered the dose-dependent rewiring of gene regulatory network during mating differentiation. Furthermore, our results suggested a potential crosstalk between the pheromone response pathway and the target of rapamycin (TOR)-regulated ribosomal biogenesis pathway, which might underlie a cell differentiation switch in yeast mating response. In summary, our modeling approach addresses the distinct impacts of the global and gene-specific regulation on the control of protein dynamics and provides new insights into the mechanisms of cell fate determination. We anticipate that our integrated experimental and modeling strategies could be widely applicable to other biological systems.'),
(88561, 2017, 'plos', 'xcexb2-adrenergic signaling broadly contributes to LTP induction', 'Jxc8xa9drzejewska-Szmek, Joanna|Luczak, Vincent|Abel, Ted|Blackwell, Kim T', 'The Krasnow Institute for Advanced Studies, George Mason University, Fairfax, Virginia, United States of America.|Department of Biology, University of Pennsylvania, Philadelphia, Pennsylvania, United States of America.|Department of Biology, University of Pennsylvania, Philadelphia, Pennsylvania, United States of America.|The Krasnow Institute for Advanced Studies, George Mason University, Fairfax, Virginia, United States of America.', 'United States|United States|United States|United States', 0, 'Animals|CA1 Region, Hippocampal|Calcium|Dendrites|Long-Term Potentiation|Models, Neurological|Receptors, Adrenergic, beta|Signal Transduction', 'Journal Article', '10.1371/journal.pcbi.1005657', '28742159', 'Long-lasting forms of long-term potentiation (LTP) represent one of the major cellular mechanisms underlying learning and memory. One of the fundamental questions in the field of LTP is why different molecules are critical for long-lasting forms of LTP induced by diverse experimental protocols. Further complexity stems from spatial aspects of signaling networks, such that some molecules function in the dendrite and some are critical in the spine. We investigated whether the diverse experimental evidence can be unified by creating a spatial, mechanistic model of multiple signaling pathways in hippocampal CA1 neurons. Our results show that the combination of activity of several key kinases can predict the occurrence of long-lasting forms of LTP for multiple experimental protocols. Specifically Ca2+/calmodulin activated kinase II, protein kinase A and exchange protein activated by cAMP (Epac) together predict the occurrence of LTP in response to strong stimulation (multiple trains of 100 Hz) or weak stimulation augmented by isoproterenol. Furthermore, our analysis suggests that activation of the xcexb2-adrenergic receptor either via canonical (Gs-coupled) or non-canonical (Gi-coupled) pathways underpins most forms of long-lasting LTP. Simulations make the experimentally testable prediction that a complete antagonist of the xcexb2-adrenergic receptor will likely block long-lasting LTP in response to strong stimulation. Collectively these results suggest that converging molecular mechanisms allow CA1 neurons to flexibly utilize signaling mechanisms best tuned to temporal pattern of synaptic input to achieve long-lasting LTP and memory storage.'),
(88562, 2017, 'plos', 'A mixture of sparse coding models explaining properties of face neurons related to holistic and parts-based processing', 'Hosoya, Haruo|Hyvärinen, Aapo', 'Cognitive Mechanisms Laboratories, ATR International, Kyoto, Japan.|Department of Computer Science and HIIT, University of Helsinki, Helsinki, Finland.', 'Japan|Finland', 4, 'Algorithms|Animals|Bayes Theorem|Computational Biology|Face|Learning|Macaca|Models, Neurological|Neurons|Pattern Recognition, Visual', 'Journal Article', '10.1371/journal.pcbi.1005667', '28742816', 'Experimental studies have revealed evidence of both parts-based and holistic representations of objects and faces in the primate visual system. However, it is still a mystery how such seemingly contradictory types of processing can coexist within a single system. Here, we propose a novel theory called mixture of sparse coding models, inspired by the formation of category-specific subregions in the inferotemporal (IT) cortex. We developed a hierarchical network that constructed a mixture of two sparse coding submodels on top of a simple Gabor analysis. The submodels were each trained with face or non-face object images, which resulted in separate representations of facial parts and object parts. Importantly, evoked neural activities were modeled by Bayesian inference, which had a top-down explaining-away effect that enabled recognition of an individual part to depend strongly on the category of the whole input. We show that this explaining-away effect was indeed crucial for the units in the face submodel to exhibit significant selectivity to face images over object images in a similar way to actual face-selective neurons in the macaque IT cortex. Furthermore, the model explained, qualitatively and quantitatively, several tuning properties to facial features found in the middle patch of face processing in IT as documented by Freiwald, Tsao, and Livingstone (2009). These included, in particular, tuning to only a small number of facial features that were often related to geometrically large parts like face outline and hair, preference and anti-preference of extreme facial features (e.g., very large/small inter-eye distance), and reduction of the gain of feature tuning for partial face stimuli compared to whole face stimuli. Thus, we hypothesize that the coding principle of facial features in the middle patch of face processing in the macaque IT cortex may be closely related to mixture of sparse coding models.'),
(88563, 2017, 'plos', 'Adjudicating between face-coding models with individual-face fMRI responses', 'Carlin, Johan D|Kriegeskorte, Nikolaus', 'MRC Cognition and Brain Sciences Unit, University of Cambridge, Cambridge, United Kingdom.|MRC Cognition and Brain Sciences Unit, University of Cambridge, Cambridge, United Kingdom.', 'United Kingdom|United Kingdom', 12, 'Algorithms|Brain|Brain Mapping|Face|Facial Recognition|Humans|Magnetic Resonance Imaging|Models, Neurological|Principal Component Analysis', 'Journal Article', '10.1371/journal.pcbi.1005604', '28746335', 'The perceptual representation of individual faces is often explained with reference to a norm-based face space. In such spaces, individuals are encoded as vectors where identity is primarily conveyed by direction and distinctiveness by eccentricity. Here we measured human fMRI responses and psychophysical similarity judgments of individual face exemplars, which were generated as realistic 3D animations using a computer-graphics model. We developed and evaluated multiple neurobiologically plausible computational models, each of which predicts a representational distance matrix and a regional-mean activation profile for 24 face stimuli. In the fusiform face area, a face-space coding model with sigmoidal ramp tuning provided a better account of the data than one based on exemplar tuning. However, an image-processing model with weighted banks of Gabor filters performed similarly. Accounting for the data required the inclusion of a measurement-level population averaging mechanism that approximates how fMRI voxels locally average distinct neuronal tunings. Our study demonstrates the importance of comparing multiple models and of modeling the measurement process in computational neuroimaging.'),
(88564, 2017, 'plos', 'OpenMM 7: Rapid development of high performance algorithms for molecular dynamics', 'Eastman, Peter|Swails, Jason|Chodera, John D|McGibbon, Robert T|Zhao, Yutong|Beauchamp, Kyle A|Wang, Lee-Ping|Simmonett, Andrew C|Harrigan, Matthew P|Stern, Chaya D|Wiewiora, Rafal P|Brooks, Bernard R|Pande, Vijay S', 'Department of Chemistry, Stanford University, Stanford, California, United States of America.|Department of Chemistry and Chemical Biology and BioMaPS Institute, Rutgers University, Piscataway, New Jersey, United States of America.|Computational and Systems Biology Program, Sloan Kettering Institute, Memorial Sloan Kettering Cancer Center, New York, New York, United States of America.|Department of Chemistry, Stanford University, Stanford, California, United States of America.|Department of Chemistry, Stanford University, Stanford, California, United States of America.|Computational and Systems Biology Program, Sloan Kettering Institute, Memorial Sloan Kettering Cancer Center, New York, New York, United States of America.|Department of Chemistry, University of California, Davis, Davis, California, United States of America.|Laboratory of Computational Biology, National Heart, Lung, and Blood Institute, National Institutes of Health, Bethesda, Maryland, United States of America.|Department of Chemistry, Stanford University, Stanford, California, United States of America.|Computational and Systems Biology Program, Sloan Kettering Institute, Memorial Sloan Kettering Cancer Center, New York, New York, United States of America.|Computational and Systems Biology Program, Sloan Kettering Institute, Memorial Sloan Kettering Cancer Center, New York, New York, United States of America.|Laboratory of Computational Biology, National Heart, Lung, and Blood Institute, National Institutes of Health, Bethesda, Maryland, United States of America.|Department of Chemistry, Stanford University, Stanford, California, United States of America.', 'United States|Jersey|United States|United States|United States|United States|United States|United St', 233, 'Algorithms|Computational Biology|Molecular Dynamics Simulation|Software', 'Journal Article', '10.1371/journal.pcbi.1005659', '28746339', 'OpenMM is a molecular dynamics simulation toolkit with a unique focus on extensibility. It allows users to easily add new features, including forces with novel functional forms, new integration algorithms, and new simulation protocols. Those features automatically work on all supported hardware types (including both CPUs and GPUs) and perform well on all of them. In many cases they require minimal coding, just a mathematical description of the desired function. They also require no modification to OpenMM itself and can be distributed independently of OpenMM. This makes it an ideal tool for researchers developing new simulation methods, and also allows those new methods to be immediately available to the larger community.');
