INSERT INTO `papers` (`id`, `ano`, `journal`, `titulo`, `autores`, `afiliacao`, `pais`, `citacoes`, `palavra_chave`, `categorias`, `doi`, `pubmed`, `abstract`) VALUES
(88565, 2017, 'plos', 'Spatial dynamics and control of a crop pathogen with mixed-mode transmission', 'McQuaid, Christopher Finn|van den Bosch, Frank|Szyniszewska, Anna|Alicai, Titus|Pariyo, Anthony|Chikoti, Patrick Chiza|Gilligan, Christopher Aidan', 'Computational and Systems Biology, Rothamsted Research, West Common, Harpenden, United Kingdom.|Computational and Systems Biology, Rothamsted Research, West Common, Harpenden, United Kingdom.|Computational and Systems Biology, Rothamsted Research, West Common, Harpenden, United Kingdom.|Root Crops Research Programme, National Crops Resources Research Institute, Namulonge, Kampala, Uganda.|Root Crops Research Programme, National Crops Resources Research Institute, Namulonge, Kampala, Uganda.|Zambia Agriculture Research Institute, Plant Protection and Quarantine Division, Mt. Makulu Research Station, Chilanga, Zambia.|Department of Plant Sciences, University of Cambridge, Cambridge, United Kingdom.', 'United Kingdom|United Kingdom|United Kingdom|Uganda|Uganda|Zambia|United Kingdom', 9, 'Computational Biology|Crops, Agricultural|Farms|Host-Pathogen Interactions|Plant Diseases|Seeds', 'Journal Article', '10.1371/journal.pcbi.1005654', '28746374', 'Trade or sharing that moves infectious planting material between farms can, for vertically-transmitted plant diseases, act as a significant force for dispersal of pathogens, particularly where the extent of material movement may be greater than that of infected vectors or inoculum. The network over which trade occurs will then effect dispersal, and is important to consider when attempting to control the disease. We consider the difference that planting material exchange can make to successful control of cassava brown streak disease, an important viral disease affecting one of Africas staple crops. We use a mathematical model of smallholders fields to determine the effect of informal trade on both the spread of the pathogen and its control using clean-seed systems, determining aspects that could limit the damage caused by the disease. In particular, we identify the potentially detrimental effects of markets, and the benefits of a community-based approach to disease control.'),
(88566, 2017, 'plos', 'Growth of bacteria in 3-d colonies', 'Shao, Xinxian|Mugler, Andrew|Kim, Justin|Jeong, Ha Jun|Levin, Bruce R|Nemenman, Ilya', 'Department of Physics, Emory University, Atlanta, GA 30322, USA.|Department of Physics, Emory University, Atlanta, GA 30322, USA.|Department of Biology, Emory University, Atlanta, GA 30322, USA.|Department of Biology, Emory University, Atlanta, GA 30322, USA.|Department of Biology, Emory University, Atlanta, GA 30322, USA.|Department of Physics, Emory University, Atlanta, GA 30322, USA.', 'United States|United States|United States|United States|United States|United States', 9, 'Cell Culture Techniques|Computational Biology|Computer Simulation|Escherichia coli|Models, Biological', 'Journal Article', '10.1371/journal.pcbi.1005679', '28749935', 'The dynamics of growth of bacterial populations has been extensively studied for planktonic cells in well-agitated liquid culture, in which all cells have equal access to nutrients. In the real world, bacteria are more likely to live in physically structured habitats as colonies, within which individual cells vary in their access to nutrients. The dynamics of bacterial growth in such conditions is poorly understood, and, unlike that for liquid culture, there is not a standard broadly used mathematical model for bacterial populations growing in colonies in three dimensions (3-d). By extending the classic Monod model of resource-limited population growth to allow for spatial heterogeneity in the bacterial access to nutrients, we develop a 3-d model of colonies, in which bacteria consume diffusing nutrients in their vicinity. By following the changes in density of E. coli in liquid and embedded in glucose-limited soft agar, we evaluate the fit of this model to experimental data. The model accounts for the experimentally observed presence of a sub-exponential, diffusion-limited growth regime in colonies, which is absent in liquid cultures. The model predicts and our experiments confirm that, as a consequence of inter-colony competition for the diffusing nutrients and of cell death, there is a non-monotonic relationship between total number of colonies within the habitat and the total number of individual cells in all of these colonies. This combined theoretical-experimental study reveals that, within 3-d colonies, E. coli cells are loosely packed, and colonies produce about 2.5 times as many cells as the liquid culture from the same amount of nutrients. We verify that this is because cells in liquid culture are larger than in colonies. Our model provides a baseline description of bacterial growth in 3-d, deviations from which can be used to identify phenotypic heterogeneities and inter-cellular interactions that further contribute to the structure of bacterial communities.'),
(88567, 2017, 'plos', 'Recurrently connected and localized neuronal communities initiate coordinated spontaneous activity in neuronal networks', 'Lonardoni, Davide|Amin, Hayder|Di Marco, Stefano|Maccione, Alessandro|Berdondini, Luca|Nieus, Thierry', 'Neuroscience and Brain Technologies Dept., Fondazione Istituto Italiano di Tecnologia, Genoa, Italy.|Neuroscience and Brain Technologies Dept., Fondazione Istituto Italiano di Tecnologia, Genoa, Italy.|Neuroscience and Brain Technologies Dept., Fondazione Istituto Italiano di Tecnologia, Genoa, Italy.|Neuroscience and Brain Technologies Dept., Fondazione Istituto Italiano di Tecnologia, Genoa, Italy.|Neuroscience and Brain Technologies Dept., Fondazione Istituto Italiano di Tecnologia, Genoa, Italy.|Neuroscience and Brain Technologies Dept., Fondazione Istituto Italiano di Tecnologia, Genoa, Italy.', 'Italy|Italy|Italy|Italy|Italy|Italy', 0, 'Action Potentials|Animals|Cells, Cultured|Computational Biology|Hippocampus|Models, Neurological|Nerve Net|Neurons|Rats', 'Journal Article', '10.1371/journal.pcbi.1005672', '28749937', 'Developing neuronal systems intrinsically generate coordinated spontaneous activity that propagates by involving a large number of synchronously firing neurons. In vivo, waves of spikes transiently characterize the activity of developing brain circuits and are fundamental for activity-dependent circuit formation. In vitro, coordinated spontaneous spiking activity, or network bursts (NBs), interleaved within periods of asynchronous spikes emerge during the development of 2D and 3D neuronal cultures. Several studies have investigated this type of activity and its dynamics, but how a neuronal system generates these coordinated events remains unclear. Here, we investigate at a cellular level the generation of network bursts in spontaneously active neuronal cultures by exploiting high-resolution multielectrode array recordings and computational network modelling. Our analysis reveals that NBs are generated in specialized regions of the network (functional neuronal communities) that feature neuronal links with high cross-correlation peak values, sub-millisecond lags and that share very similar structural connectivity motifs providing recurrent interactions. We show that the particular properties of these local structures enable locally amplifying spontaneous asynchronous spikes and that this mechanism can lead to the initiation of NBs. Through the analysis of simulated and experimental data, we also show that AMPA currents drive the coordinated activity, while NMDA and GABA currents are only involved in shaping the dynamics of NBs. Overall, our results suggest that the presence of functional neuronal communities with recurrent local connections allows a neuronal system to generate spontaneous coordinated spiking activity events. As suggested by the rules used for implementing our computational model, such functional communities might naturally emerge during network development by following simple constraints on distance-based connectivity.'),
(88568, 2017, 'plos', 'Upregulation of an inward rectifying K+ channel can rescue slow Ca2+ oscillations in K(ATP) channel deficient pancreatic islets', 'Yildirim, Vehpi|Vadrevu, Suryakiran|Thompson, Benjamin|Satin, Leslie S|Bertram, Richard', 'Department of Mathematics, Florida State University, Tallahassee, FL, United States of America.|Brehm Diabetes Center, University of Michigan Medical School, Ann Arbor, MI, United States of America.|Brehm Diabetes Center, University of Michigan Medical School, Ann Arbor, MI, United States of America.|Brehm Diabetes Center, University of Michigan Medical School, Ann Arbor, MI, United States of America.|Department of Mathematics and Programs in Molecular Biophysics and Neuroscience, Florida State University, Tallahassee, FL, United States of America.', 'United States|United States|United States|United States|United States', 5, 'Animals|Blood Glucose|Calcium|Insulin|Islets of Langerhans|Male|Mice|Mice, Knockout|Potassium Channels, Inwardly Rectifying|Up-Regulation', 'Journal Article', '10.1371/journal.pcbi.1005686', '28749940', 'Plasma insulin oscillations are known to have physiological importance in the regulation of blood glucose. In insulin-secreting xcexb2-cells of pancreatic islets, K(ATP) channels play a key role in regulating glucose-dependent insulin secretion. In addition, they convey oscillations in cellular metabolism to the membrane by sensing adenine nucleotides, and are thus instrumental in mediating pulsatile insulin secretion. Blocking K(ATP) channels pharmacologically depolarizes the xcexb2-cell plasma membrane and terminates islet oscillations. Surprisingly, when K(ATP) channels are genetically knocked out, oscillations in islet activity persist, and relatively normal blood glucose levels are maintained. Compensation must therefore occur to overcome the loss of K(ATP) channels in K(ATP) knockout mice. In a companion study, we demonstrated a substantial increase in Kir2.1 protein occurs in xcexb2-cells lacking K(ATP) because of SUR1 deletion. In this report, we demonstrate that xcexb2-cells of SUR1 null islets have an upregulated inward rectifying K+ current that helps to compensate for the loss of K(ATP) channels. This current is likely due to the increased expression of Kir2.1 channels. We used mathematical modeling to determine whether an ionic current having the biophysical characteristics of Kir2.1 is capable of rescuing oscillations that are similar in period to those of wild-type islets. By experimentally testing a key model prediction we suggest that Kir2.1 current upregulation is a likely mechanism for rescuing the oscillations seen in islets from mice deficient in K(ATP) channels.'),
(88569, 2017, 'plos', 'TopologyNet: Topology based deep convolutional and multi-task neural networks for biomolecular property predictions', 'Cang, Zixuan|Wei, Guo-Wei', 'Department of Mathematics, Michigan State University, East Lansing, MI 48824, USA.|Department of Mathematics, Michigan State University, East Lansing, MI 48824, USA.', 'United States|United States', 0, 'Computational Biology|Image Processing, Computer-Assisted|Machine Learning|Membrane Proteins|Models, Statistical|Molecular Dynamics Simulation|Neural Networks (Computer)|Protein Binding|Protein Folding', 'Journal Article', '10.1371/journal.pcbi.1005690', '28749969', 'Although deep learning approaches have had tremendous success in image, video and audio processing, computer vision, and speech recognition, their applications to three-dimensional (3D) biomolecular structural data sets have been hindered by the geometric and biological complexity. To address this problem we introduce the element-specific persistent homology (ESPH) method. ESPH represents 3D complex geometry by one-dimensional (1D) topological invariants and retains important biological information via a multichannel image-like representation. This representation reveals hidden structure-function relationships in biomolecules. We further integrate ESPH and deep convolutional neural networks to construct a multichannel topological neural network (TopologyNet) for the predictions of protein-ligand binding affinities and protein stability changes upon mutation. To overcome the deep learning limitations from small and noisy training sets, we propose a multi-task multichannel topological convolutional neural network (MM-TCNN). We demonstrate that TopologyNet outperforms the latest methods in the prediction of protein-ligand binding affinities, mutation induced globular protein folding free energy changes, and mutation induced membrane protein folding free energy changes.'),
(88570, 2017, 'plos', 'mRNA/protein sequence complementarity and its determinants: The impact of affinity scales', 'Bartonek, Lukas|Zagrovic, Bojan', 'Department of Structural and Computational Biology, Max F. Perutz Laboratories, University of Vienna, Campus Vienna Biocenter 5, Vienna, Austria.|Department of Structural and Computational Biology, Max F. Perutz Laboratories, University of Vienna, Campus Vienna Biocenter 5, Vienna, Austria.', 'Austria|Austria', 13, 'Amino Acid Sequence|Base Sequence|Computational Biology|Escherichia coli|Methanocaldococcus|Models, Genetic|Monte Carlo Method|Proteins|RNA, Messenger|Saccharomyces cerevisiae|Software', 'Journal Article', '10.1371/journal.pcbi.1005648', '28750009', 'It has recently been demonstrated that the nucleobase-density profiles of mRNA coding sequences are related in a complementary manner to the nucleobase-affinity profiles of their cognate protein sequences. Based on this, it has been proposed that cognate mRNA/protein pairs may bind in a co-aligned manner, especially if unstructured. Here, we study the dependence of mRNA/protein sequence complementarity on the properties of the nucleobase/amino-acid affinity scales used. Specifically, we sample the space of randomly generated scales by employing a Monte Carlo strategy with a fitness function that depends directly on the level of complementarity. For model organisms representing all three domains of life, we show that even short searches reproducibly converge upon highly optimized scales, implying that the topology of the underlying fitness landscape is decidedly funnel-like. Furthermore, the optimized scales, generated without any consideration of the physicochemical attributes of nucleobases or amino acids, resemble closely the nucleobase/amino-acid binding affinity scales obtained from experimental structures of RNA-protein complexes. This provides support for the claim that mRNA/protein sequence complementarity may indeed be related to binding between the two. Finally, we characterize suboptimal scales and show that intermediate-to-high complementarity can be reached by substantially diverse scales, but with select amino acids contributing disproportionally. Our results expose the dependence of cognate mRNA/protein sequence complementarity on the properties of the underlying nucleobase/amino-acid affinity scales and provide quantitative constraints that any physical scales need to satisfy for the complementarity to hold.'),
(88571, 2017, 'plos', 'A hierarchical Bayesian model for understanding the spatiotemporal dynamics of the intestinal epithelium', 'Maclaren, Oliver J|Parker, Aimée|Pin, Carmen|Carding, Simon R|Watson, Alastair J M|Fletcher, Alexander G|Byrne, Helen M|Maini, Philip K', 'Department of Engineering Science, University of Auckland, Auckland, New Zealand.|Gut Health and Food Safety Research Programme, Institute of Food Research, Norwich, United Kingdom.|Gut Health and Food Safety Research Programme, Institute of Food Research, Norwich, United Kingdom.|Gut Health and Food Safety Research Programme, Institute of Food Research, Norwich, United Kingdom.|Gut Health and Food Safety Research Programme, Institute of Food Research, Norwich, United Kingdom.|School of Mathematics and Statistics, University of Sheffield, Sheffield, United Kingdom.|Wolfson Centre for Mathematical Biology, Mathematical Institute, University of Oxford, Oxford, United Kingdom.|Wolfson Centre for Mathematical Biology, Mathematical Institute, University of Oxford, Oxford, United Kingdom.', 'New Zealand|United Kingdom|United Kingdom|United Kingdom|United Kingdom|United Kingdom|United Kingdo', 0, 'Animals|Bayes Theorem|Computational Biology|Intestinal Mucosa|Mice|Models, Biological|Models, Statistical', 'Journal Article', '10.1371/journal.pcbi.1005688', '28753601', 'Our work addresses two key challenges, one biological and one methodological. First, we aim to understand how proliferation and cell migration rates in the intestinal epithelium are related under healthy, damaged (Ara-C treated) and recovering conditions, and how these relations can be used to identify mechanisms of repair and regeneration. We analyse new data, presented in more detail in a companion paper, in which BrdU/IdU cell-labelling experiments were performed under these respective conditions. Second, in considering how to more rigorously process these data and interpret them using mathematical models, we use a probabilistic, hierarchical approach. This provides a best-practice approach for systematically modelling and understanding the uncertainties that can otherwise undermine the generation of reliable conclusions-uncertainties in experimental measurement and treatment, difficult-to-compare mathematical models of underlying mechanisms, and unknown or unobserved parameters. Both spatially discrete and continuous mechanistic models are considered and related via hierarchical conditional probability assumptions. We perform model checks on both in-sample and out-of-sample datasets and use them to show how to test possible model improvements and assess the robustness of our conclusions. We conclude, for the present set of experiments, that a primarily proliferation-driven model suffices to predict labelled cell dynamics over most time-scales.'),
(88572, 2017, 'plos', 'Automated incorporation of pairwise dependency in transcription factor binding site prediction using dinucleotide weight tensors', 'Omidi, Saeed|Zavolan, Mihaela|Pachkov, Mikhail|Breda, Jeremie|Berger, Severin|van Nimwegen, Erik', 'Biozentrum, University of Basel, Basel, Switzerland.|Biozentrum, University of Basel, Basel, Switzerland.|Biozentrum, University of Basel, Basel, Switzerland.|Biozentrum, University of Basel, Basel, Switzerland.|Biozentrum, University of Basel, Basel, Switzerland.|Biozentrum, University of Basel, Basel, Switzerland.', 'Switzerland|Switzerland|Switzerland|Switzerland|Switzerland|Switzerland', 6, 'Binding Sites|Computational Biology|DNA|Models, Statistical|Nucleotide Motifs|RNA|Sequence Analysis, DNA|Transcription Factors', 'Journal Article', '10.1371/journal.pcbi.1005176', '28753602', 'Gene regulatory networks are ultimately encoded by the sequence-specific binding of (TFs) to short DNA segments. Although it is customary to represent the binding specificity of a TF by a position-specific weight matrix (PSWM), which assumes each position within a site contributes independently to the overall binding affinity, evidence has been accumulating that there can be significant dependencies between positions. Unfortunately, methodological challenges have so far hindered the development of a practical and generally-accepted extension of the PSWM model. On the one hand, simple models that only consider dependencies between nearest-neighbor positions are easy to use in practice, but fail to account for the distal dependencies that are observed in the data. On the other hand, models that allow for arbitrary dependencies are prone to overfitting, requiring regularization schemes that are difficult to use in practice for non-experts. Here we present a new regulatory motif model, called dinucleotide weight tensor (DWT), that incorporates arbitrary pairwise dependencies between positions in binding sites, rigorously from first principles, and free from tunable parameters. We demonstrate the power of the method on a large set of ChIP-seq data-sets, showing that DWTs outperform both PSWMs and motif models that only incorporate nearest-neighbor dependencies. We also demonstrate that DWTs outperform two previously proposed methods. Finally, we show that DWTs inferred from ChIP-seq data also outperform PSWMs on HT-SELEX data for the same TF, suggesting that DWTs capture inherent biophysical properties of the interactions between the DNA binding domains of TFs and their binding sites. We make a suite of DWT tools available at dwt.unibas.ch, that allow users to automatically perform motif finding, i.e. the inference of DWT motifs from a set of sequences, binding site prediction with DWTs, and visualization of DWT dilogo motifs.'),
(88573, 2017, 'plos', 'Dissociating error-based and reinforcement-based loss functions during sensorimotor learning', 'Cashaback, Joshua G A|McGregor, Heather R|Mohatarem, Ayman|Gribble, Paul L', 'Brain and Mind Institute, Department of Psychology, Western University, London, ON, Canada.|Brain and Mind Institute, Department of Psychology, Western University, London, ON, Canada.|Department of Biology, Western University, London, ON, Canada.|Brain and Mind Institute, Department of Psychology, Western University, London, ON, Canada.', 'Canada|Canada|Canada|Canada', 16, 'Adolescent|Adult|Computational Biology|Feedback, Sensory|Hand|Humans|Learning|Reinforcement (Psychology)|Task Performance and Analysis|Uncertainty|Young Adult', 'Journal Article', '10.1371/journal.pcbi.1005623', '28753634', 'It has been proposed that the sensorimotor system uses a loss (cost) function to evaluate potential movements in the presence of random noise. Here we test this idea in the context of both error-based and reinforcement-based learning. In a reaching task, we laterally shifted a cursor relative to true hand position using a skewed probability distribution. This skewed probability distribution had its mean and mode separated, allowing us to dissociate the optimal predictions of an error-based loss function (corresponding to the mean of the lateral shifts) and a reinforcement-based loss function (corresponding to the mode). We then examined how the sensorimotor system uses error feedback and reinforcement feedback, in isolation and combination, when deciding where to aim the hand during a reach. We found that participants compensated differently to the same skewed lateral shift distribution depending on the form of feedback they received. When provided with error feedback, participants compensated based on the mean of the skewed noise. When provided with reinforcement feedback, participants compensated based on the mode. Participants receiving both error and reinforcement feedback continued to compensate based on the mean while repeatedly missing the target, despite receiving auditory, visual and monetary reinforcement feedback that rewarded hitting the target. Our work shows that reinforcement-based and error-based learning are separable and can occur independently. Further, when error and reinforcement feedback are in conflict, the sensorimotor system heavily weights error feedback over reinforcement feedback.'),
(88574, 2017, 'plos', 'Self-regulation strategy, feedback timing and hemodynamic properties modulate learning in a simulated fMRI neurofeedback environment', 'Oblak, Ethan F|Lewis-Peacock, Jarrod A|Sulzer, James S', 'Department of Mechanical Engineering, The University of Texas at Austin, Austin, Texas, USA.|Department of Psychology, The University of Texas at Austin, Austin, Texas, USA.|Department of Mechanical Engineering, The University of Texas at Austin, Austin, Texas, USA.', 'United States|United States|United States', 12, 'Adolescent|Adult|Brain|Female|Hemodynamics|Humans|Learning|Magnetic Resonance Imaging|Male|Models, Neurological|Neurofeedback|Neuroimaging|Visual Cortex|Young Adult', 'Journal Article', '10.1371/journal.pcbi.1005681', '28753639', 'Direct manipulation of brain activity can be used to investigate causal brain-behavior relationships. Current noninvasive neural stimulation techniques are too coarse to manipulate behaviors that correlate with fine-grained spatial patterns recorded by fMRI. However, these activity patterns can be manipulated by having people learn to self-regulate their own recorded neural activity. This technique, known as fMRI neurofeedback, faces challenges as many participants are unable to self-regulate. The causes of this non-responder effect are not well understood due to the cost and complexity of such investigation in the MRI scanner. Here, we investigated the temporal dynamics of the hemodynamic response measured by fMRI as a potential cause of the non-responder effect. Learning to self-regulate the hemodynamic response involves a difficult temporal credit-assignment problem because this signal is both delayed and blurred over time. Two factors critical to this problem are the prescribed self-regulation strategy (cognitive or automatic) and feedback timing (continuous or intermittent). Here, we sought to evaluate how these factors interact with the temporal dynamics of fMRI without using the MRI scanner. We first examined the role of cognitive strategies by having participants learn to regulate a simulated neurofeedback signal using a unidimensional strategy: pressing one of two buttons to rotate a visual grating that stimulates a model of visual cortex. Under these conditions, continuous feedback led to faster regulation compared to intermittent feedback. Yet, since many neurofeedback studies prescribe implicit self-regulation strategies, we created a computational model of automatic reward-based learning to examine whether this result held true for automatic processing. When feedback was delayed and blurred based on the hemodynamics of fMRI, this model learned more reliably from intermittent feedback compared to continuous feedback. These results suggest that different self-regulation mechanisms prefer different feedback timings, and that these factors can be effectively explored and optimized via simulation prior to deployment in the MRI scanner.'),
(88575, 2017, 'plos', 'Learning and executing goal-directed choices by internally generated sequences in spiking neural circuits', 'Palmer, John|Keane, Adam|Gong, Pulin', 'School of Physics, University of Sydney, Sydney, NSW, Australia.|School of Physics, University of Sydney, Sydney, NSW, Australia.|School of Physics, University of Sydney, Sydney, NSW, Australia.', 'Australia|Australia|Australia', 0, 'Algorithms|Animals|Choice Behavior|Hippocampus|Models, Neurological|Models, Statistical|Nerve Net|Neuronal Plasticity|Rats', 'Journal Article', '10.1371/journal.pcbi.1005669', '28759562', 'Recent neural ensemble recordings have established a link between goal-directed spatial decision making and internally generated neural sequences in the hippocampus of rats. To elucidate the synaptic mechanisms of these sequences underlying spatial decision making processes, we develop and investigate a spiking neural circuit model endowed with a combination of two synaptic plasticity mechanisms including spike-timing dependent plasticity (STDP) and synaptic scaling. In this model, the interplay of the combined synaptic plasticity mechanisms and network dynamics gives rise to neural sequences which propagate ahead of the animals decision point to reach goal locations. The dynamical properties of these forward-sweeping sequences and the rates of correct binary choices executed by these sequences are quantitatively consistent with experimental observations, this consistency, however, is lost in our model when only one of STDP or synaptic scaling is included. We further demonstrate that such sequence-based decision making in our network model can adaptively respond to time-varying and probabilistic associations of cues and goal locations, and that our model performs as well as an optimal Kalman filter model. Our results thus suggest that the combination of plasticity phenomena on different timescales provides a candidate mechanism for forming internally generated neural sequences and for implementing adaptive spatial decision making.'),
(88576, 2017, 'plos', 'PCSF: An R-package for network-based interpretation of high-throughput data', 'Akhmedov, Murodzhon|Kedaigle, Amanda|Chong, Renan Escalante|Montemanni, Roberto|Bertoni, Francesco|Fraenkel, Ernest|Kwee, Ivo', 'Dalle Molle Institute for Artificial Intelligence Research (USI/SUPSI), Manno, Switzerland.|Department of Biological Engineering, MIT, Cambridge, Massachusetts, United States of America.|Department of Biological Engineering, MIT, Cambridge, Massachusetts, United States of America.|Dalle Molle Institute for Artificial Intelligence Research (USI/SUPSI), Manno, Switzerland.|Institute of Oncology Research (IOR), Bellinzona, Switzerland.|Department of Biological Engineering, MIT, Cambridge, Massachusetts, United States of America.|Dalle Molle Institute for Artificial Intelligence Research (USI/SUPSI), Manno, Switzerland.', 'Switzerland|United States|United States|Switzerland|Switzerland|United States|Switzerland', 10, 'Computational Biology|Databases, Factual|High-Throughput Screening Assays|Software', 'Journal Article', '10.1371/journal.pcbi.1005694', '28759592', 'With the recent technological developments a vast amount of high-throughput data has been profiled to understand the mechanism of complex diseases. The current bioinformatics challenge is to interpret the data and underlying biology, where efficient algorithms for analyzing heterogeneous high-throughput data using biological networks are becoming increasingly valuable. In this paper, we propose a software package based on the Prize-collecting Steiner Forest graph optimization approach. The PCSF package performs fast and user-friendly network analysis of high-throughput data by mapping the data onto a biological networks such as protein-protein interaction, gene-gene interaction or any other correlation or coexpression based networks. Using the interaction networks as a template, it determines high-confidence subnetworks relevant to the data, which potentially leads to predictions of functional units. It also interactively visualizes the resulting subnetwork with functional enrichment analysis.'),
(88577, 2017, 'plos', 'Rearrangement moves on rooted phylogenetic networks', 'Gambette, Philippe|van Iersel, Leo|Jones, Mark|Lafond, Manuel|Pardi, Fabio|Scornavacca, Celine', 'Laboratoire dInformatique Gaspard-Monge (LIGM), Université Paris-Est, CNRS, ENPC, ESIEE Paris, UPEM, F-77454, Marne-la-Vallée, France.|Delft Institute of Applied Mathematics, Delft University of Technology, Postbus 5031, 2628 CD Delft, The Netherlands.|Delft Institute of Applied Mathematics, Delft University of Technology, Postbus 5031, 2628 CD Delft, The Netherlands.|Department of Mathematics and Statistics, University of Ottawa, K1N 6N5 Ottawa, Canada.|Laboratoire dInformatique, de Robotique et de Microélectronique de Montpellier (LIRMM), Université de Montpellier, CNRS, 34095 Montpellier Cedex 5, France.|Institut de Biologie Computationnelle (IBC), 34095 Montpellier, France.', 'France|Netherlands|Netherlands|Canada|France|France', 0, 'Animals|Computational Biology|Gene Rearrangement|Hominidae|Humans|Models, Genetic|Phylogeny', 'Journal Article', '10.1371/journal.pcbi.1005611', '28763439', 'Phylogenetic tree reconstruction is usually done by local search heuristics that explore the space of the possible tree topologies via simple rearrangements of their structure. Tree rearrangement heuristics have been used in combination with practically all optimization criteria in use, from maximum likelihood and parsimony to distance-based principles, and in a Bayesian context. Their basic components are rearrangement moves that specify all possible ways of generating alternative phylogenies from a given one, and whose fundamental property is to be able to transform, by repeated application, any phylogeny into any other phylogeny. Despite their long tradition in tree-based phylogenetics, very little research has gone into studying similar rearrangement operations for phylogenetic network-that is, phylogenies explicitly representing scenarios that include reticulate events such as hybridization, horizontal gene transfer, population admixture, and recombination. To fill this gap, we propose horizontal moves that ensure that every network of a certain complexity can be reached from any other network of the same complexity, and vertical moves that ensure reachability between networks of different complexities. When applied to phylogenetic trees, our horizontal moves-named rNNI and rSPR-reduce to the best-known moves on rooted phylogenetic trees, nearest-neighbor interchange and rooted subtree pruning and regrafting. Besides a number of reachability results-separating the contributions of horizontal and vertical moves-we prove that rNNI moves are local versions of rSPR moves, and provide bounds on the sizes of the rNNI neighborhoods. The paper focuses on the most biologically meaningful versions of phylogenetic networks, where edges are oriented and reticulation events clearly identified. Moreover, our rearrangement moves are robust to the fact that networks with higher complexity usually allow a better fit with the data. Our goal is to provide a solid basis for practical phylogenetic network reconstruction.'),
(88578, 2017, 'plos', 'Bow-tie signaling in c-di-GMP: Machine learning in a simple biochemical network', 'Yan, Jinyuan|Deforet, Maxime|Boyle, Kerry E|Rahman, Rayees|Liang, Raymond|Okegbe, Chinweike|Dietrich, Lars E P|Qiu, Weigang|Xavier, Joao B', 'Program for Computational and Systems Biology, Memorial Sloan-Kettering Cancer Center, New York, NY, United States of America.|Program for Computational and Systems Biology, Memorial Sloan-Kettering Cancer Center, New York, NY, United States of America.|Program for Computational and Systems Biology, Memorial Sloan-Kettering Cancer Center, New York, NY, United States of America.|Department of Biological Sciences, Hunter College & Graduate Center, CUNY, New York, NY, United States of America.|Department of Biological Sciences, Hunter College & Graduate Center, CUNY, New York, NY, United States of America.|Department of Biological Sciences, Columbia University, New York, NY, United States of America.|Department of Biological Sciences, Columbia University, New York, NY, United States of America.|Department of Biological Sciences, Hunter College & Graduate Center, CUNY, New York, NY, United States of America.|Program for Computational and Systems Biology, Memorial Sloan-Kettering Cancer Center, New York, NY, United States of America.', 'United States|United States|United States|United States|United States|United States|United States|Un', 14, 'Biofilms|Cell Movement|Computational Biology|Cyclic GMP|Machine Learning|Models, Biological|Phenotype|Pseudomonas aeruginosa|Signal Transduction', 'Journal Article', '10.1371/journal.pcbi.1005677', '28767643', 'Bacteria of many species rely on a simple molecule, the intracellular secondary messenger c-di-GMP (Bis-(3-5)-cyclic dimeric guanosine monophosphate), to make a vital choice: whether to stay in one place and form a biofilm, or to leave it in search of better conditions. The c-di-GMP network has a bow-tie shaped architecture that integrates many signals from the outside world-the input stimuli-into intracellular c-di-GMP levels that then regulate genes for biofilm formation or for swarming motility-the output phenotypes. How does the uninformed process of evolution produce a network with the right input/output association and enable bacteria to make the right choice? Inspired by new data from 28 clinical isolates of Pseudomonas aeruginosa and strains evolved in laboratory experiments we propose a mathematical model where the c-di-GMP network is analogous to a machine learning classifier. The analogy immediately suggests a mechanism for learning through evolution: adaptation though incremental changes in c-di-GMP network proteins acquires knowledge from past experiences and enables bacteria to use it to direct future behaviors. Our model clarifies the elusive function of the ubiquitous c-di-GMP network, a key regulator of bacterial social traits associated with virulence. More broadly, the link between evolution and machine learning can help explain how natural selection across fluctuating environments produces networks that enable living organisms to make sophisticated decisions.'),
(88579, 2017, 'plos', 'A model of human motor sequence learning explains facilitation and interference effects based on spike-timing dependent plasticity', 'Wang, Quan|Rothkopf, Constantin A|Triesch, Jochen', 'Frankfurt Institute for Advanced Studies, Ruth-Moufang Str. 1, 60438 Frankfurt, Germany.|Frankfurt Institute for Advanced Studies, Ruth-Moufang Str. 1, 60438 Frankfurt, Germany.|Frankfurt Institute for Advanced Studies, Ruth-Moufang Str. 1, 60438 Frankfurt, Germany.', 'Germany|Germany|Germany', 4, 'Action Potentials|Computational Biology|Humans|Learning|Models, Neurological|Neuronal Plasticity', 'Journal Article', '10.1371/journal.pcbi.1005632', '28767646', 'The ability to learn sequential behaviors is a fundamental property of our brains. Yet a long stream of studies including recent experiments investigating motor sequence learning in adult human subjects have produced a number of puzzling and seemingly contradictory results. In particular, when subjects have to learn multiple action sequences, learning is sometimes impaired by proactive and retroactive interference effects. In other situations, however, learning is accelerated as reflected in facilitation and transfer effects. At present it is unclear what the underlying neural mechanism are that give rise to these diverse findings. Here we show that a recently developed recurrent neural network model readily reproduces this diverse set of findings. The self-organizing recurrent neural network (SORN) model is a network of recurrently connected threshold units that combines a simplified form of spike-timing dependent plasticity (STDP) with homeostatic plasticity mechanisms ensuring network stability, namely intrinsic plasticity (IP) and synaptic normalization (SN). When trained on sequence learning tasks modeled after recent experiments we find that it reproduces the full range of interference, facilitation, and transfer effects. We show how these effects are rooted in the networks changing internal representation of the different sequences across learning and how they depend on an interaction of training schedule and task similarity. Furthermore, since learning in the model is based on fundamental neuronal plasticity mechanisms, the model reveals how these plasticity mechanisms are ultimately responsible for the networks sequence learning abilities. In particular, we find that all three plasticity mechanisms are essential for the network to learn effective internal models of the different training sequences. This ability to form effective internal models is also the basis for the observed interference and facilitation effects. This suggests that STDP, IP, and SN may be the driving forces behind our ability to learn complex action sequences.'),
(88580, 2017, 'plos', 'The Stochastic Early Reaction, Inhibition, and late Action (SERIA) model for antisaccades', 'Aponte, Eduardo A|Schöbi, Dario|Stephan, Klaas E|Heinzle, Jakob', 'Translational Neuromodeling Unit, Institute for Biomedical Engineering, University of Zurich & Swiss Institute of Technology Zurich, Zurich, Switzerland.|Translational Neuromodeling Unit, Institute for Biomedical Engineering, University of Zurich & Swiss Institute of Technology Zurich, Zurich, Switzerland.|Translational Neuromodeling Unit, Institute for Biomedical Engineering, University of Zurich & Swiss Institute of Technology Zurich, Zurich, Switzerland.|Translational Neuromodeling Unit, Institute for Biomedical Engineering, University of Zurich & Swiss Institute of Technology Zurich, Zurich, Switzerland.', 'Switzerland|Switzerland|Switzerland|Switzerland', 8, 'Adult|Algorithms|Bayes Theorem|Computational Biology|Humans|Male|Models, Biological|Psychomotor Performance|Reaction Time|Saccades|Stochastic Processes', 'Journal Article', '10.1371/journal.pcbi.1005692', '28767650', 'The antisaccade task is a classic paradigm used to study the voluntary control of eye movements. It requires participants to suppress a reactive eye movement to a visual target and to concurrently initiate a saccade in the opposite direction. Although several models have been proposed to explain error rates and reaction times in this task, no formal model comparison has yet been performed. Here, we describe a Bayesian modeling approach to the antisaccade task that allows us to formally compare different models on the basis of their evidence. First, we provide a formal likelihood function of actions (pro- and antisaccades) and reaction times based on previously published models. Second, we introduce the Stochastic Early Reaction, Inhibition, and late Action model (SERIA), a novel model postulating two different mechanisms that interact in the antisaccade task: an early GO/NO-GO race decision process and a late GO/GO decision process. Third, we apply these models to a data set from an experiment with three mixed blocks of pro- and antisaccade trials. Bayesian model comparison demonstrates that the SERIA model explains the data better than competing models that do not incorporate a late decision process. Moreover, we show that the early decision process postulated by the SERIA model is, to a large extent, insensitive to the cue presented in a single trial. Finally, we use parameter estimates to demonstrate that changes in reaction time and error rate due to the probability of a trial type (pro- or antisaccade) are best explained by faster or slower inhibition and the probability of generating late voluntary prosaccades.'),
(88581, 2017, 'plos', 'Multi-scale approaches for high-speed imaging and analysis of large neural populations', 'Friedrich, Johannes|Yang, Weijian|Soudry, Daniel|Mu, Yu|Ahrens, Misha B|Yuste, Rafael|Peterka, Darcy S|Paninski, Liam', 'Department of Statistics, Grossman Center for the Statistics of Mind, and Center for Theoretical Neuroscience, Columbia University, New York, New York, United States of America.|NeuroTechnology Center, Department of Biological Sciences, Columbia University, New York, New York, United States of America.|Department of Statistics, Grossman Center for the Statistics of Mind, and Center for Theoretical Neuroscience, Columbia University, New York, New York, United States of America.|Janelia Research Campus, Howard Hughes Medical Institute, Ashburn, Virginia, United States of America.|Janelia Research Campus, Howard Hughes Medical Institute, Ashburn, Virginia, United States of America.|NeuroTechnology Center, Department of Biological Sciences, Columbia University, New York, New York, United States of America.|NeuroTechnology Center, Department of Biological Sciences, Columbia University, New York, New York, United States of America.|Department of Statistics, Grossman Center for the Statistics of Mind, and Center for Theoretical Neuroscience, Columbia University, New York, New York, United States of America.', 'United States|United States|United States|United States|United States|United States|United States|Un', 0, 'Algorithms|Animals|Brain|Computational Biology|Image Processing, Computer-Assisted|Mice|Neurons|Neurophysiology|Zebrafish', 'Journal Article', '10.1371/journal.pcbi.1005685', '28771570', 'Progress in modern neuroscience critically depends on our ability to observe the activity of large neuronal populations with cellular spatial and high temporal resolution. However, two bottlenecks constrain efforts towards fast imaging of large populations. First, the resulting large video data is challenging to analyze. Second, there is an explicit tradeoff between imaging speed, signal-to-noise, and field of view: with current recording technology we cannot image very large neuronal populations with simultaneously high spatial and temporal resolution. Here we describe multi-scale approaches for alleviating both of these bottlenecks. First, we show that spatial and temporal decimation techniques based on simple local averaging provide order-of-magnitude speedups in spatiotemporally demixing calcium video data into estimates of single-cell neural activity. Second, once the shapes of individual neurons have been identified at fine scale (e.g., after an initial phase of conventional imaging with standard temporal and spatial resolution), we find that the spatial/temporal resolution tradeoff shifts dramatically: after demixing we can accurately recover denoised fluorescence traces and deconvolved neural activity of each individual neuron from coarse scale data that has been spatially decimated by an order of magnitude. This offers a cheap method for compressing this large video data, and also implies that it is possible to either speed up imaging significantly, or to zoom out by a corresponding factor to image order-of-magnitude larger neuronal populations with minimal loss in accuracy or temporal resolution.'),
(88582, 2017, 'plos', 'Measuring distance through dense weighted networks: The case of hospital-associated pathogens', 'Donker, Tjibbe|Smieszek, Timo|Henderson, Katherine L|Johnson, Alan P|Walker, A Sarah|Robotham, Julie V', 'The National Institute for Health Research (NIHR) Health Protection Research Unit in Healthcare Associated Infections and Antimicrobial Resistance at University of Oxford in partnership with Public Health England, Oxford, United Kingdom.|National Infection Service, Public Health England, Colindale, London, United Kingdom.|National Infection Service, Public Health England, Colindale, London, United Kingdom.|The National Institute for Health Research (NIHR) Health Protection Research Unit in Healthcare Associated Infections and Antimicrobial Resistance at University of Oxford in partnership with Public Health England, Oxford, United Kingdom.|The National Institute for Health Research (NIHR) Health Protection Research Unit in Healthcare Associated Infections and Antimicrobial Resistance at University of Oxford in partnership with Public Health England, Oxford, United Kingdom.|The National Institute for Health Research (NIHR) Health Protection Research Unit in Healthcare Associated Infections and Antimicrobial Resistance at University of Oxford in partnership with Public Health England, Oxford, United Kingdom.', 'United Kingdom|United Kingdom|United Kingdom|United Kingdom|United Kingdom|United Kingdom', 1, 'Computational Biology|Computer Simulation|Contact Tracing|Cross Infection|Disease Outbreaks|England|Hospitals|Humans', 'Journal Article', '10.1371/journal.pcbi.1005622', '28771581', 'Hospital networks, formed by patients visiting multiple hospitals, affect the spread of hospital-associated infections, resulting in differences in risks for hospitals depending on their network position. These networks are increasingly used to inform strategies to prevent and control the spread of hospital-associated pathogens. However, many studies only consider patients that are received directly from the initial hospital, without considering the effect of indirect trajectories through the network. We determine the optimal way to measure the distance between hospitals within the network, by reconstructing the English hospital network based on shared patients in 2014-2015, and simulating the spread of a hospital-associated pathogen between hospitals, taking into consideration that each intermediate hospital conveys a delay in the further spread of the pathogen. While the risk of transferring a hospital-associated pathogen between directly neighbouring hospitals is a direct reflection of the number of shared patients, the distance between two hospitals far-away in the network is determined largely by the number of intermediate hospitals in the network. Because the network is dense, most long distance transmission chains in fact involve only few intermediate steps, spreading along the many weak links. The dense connectivity of hospital networks, together with a strong regional structure, causes hospital-associated pathogens to spread from the initial outbreak in a two-step process: first, the directly surrounding hospitals are affected through the strong connections, second all other hospitals receive introductions through the multitude of weaker links. Although the strong connections matter for local spread, weak links in the network can offer ideal routes for hospital-associated pathogens to travel further faster. This hold important implications for infection prevention and control efforts: if a local outbreak is not controlled in time, colonised patients will appear in other regions, irrespective of the distance to the initial outbreak, making import screening ever more difficult.');
INSERT INTO `papers` (`id`, `ano`, `journal`, `titulo`, `autores`, `afiliacao`, `pais`, `citacoes`, `palavra_chave`, `categorias`, `doi`, `pubmed`, `abstract`) VALUES
(88583, 2017, 'plos', 'Quantification of transplant-derived circulating cell-free DNA in absence of a donor genotype', 'Sharon, Eilon|Shi, Hao|Kharbanda, Sandhya|Koh, Winston|Martin, Lance R|Khush, Kiran K|Valantine, Hannah|Pritchard, Jonathan K|De Vlaminck, Iwijn', 'Department of Genetics, Stanford University, Stanford, California, United States of America.|Meinig School of Biomedical Engineering, Cornell University, Ithaca, New York, United States of America.|Pediatric Stem Cell Transplantation, Lucille Packard Childrens Hospital, Stanford, California, United States of America.|Howard Hughes Medical Institute, Stanford University, Stanford, California, United States of America.|Howard Hughes Medical Institute, Stanford University, Stanford, California, United States of America.|Division of Cardiovascular Medicine, Stanford University School of Medicine, Stanford, California, United States of America.|National Institutes of Health, Bethesda, Maryland, United States of America.|Department of Genetics, Stanford University, Stanford, California, United States of America.|Meinig School of Biomedical Engineering, Cornell University, Ithaca, New York, United States of America.', 'United States|United States|United States|United States|United States|United States|United States|Un', 0, 'Bone Marrow|DNA|Female|Genotype|Genotyping Techniques|Graft Rejection|Humans|Male|Models, Statistical|Sequence Analysis, DNA|Tissue Donors|Transplantation|Transplants', 'Journal Article', '10.1371/journal.pcbi.1005629', '28771616', 'Quantification of cell-free DNA (cfDNA) in circulating blood derived from a transplanted organ is a powerful approach to monitoring post-transplant injury. Genome transplant dynamics (GTD) quantifies donor-derived cfDNA (dd-cfDNA) by taking advantage of single-nucleotide polymorphisms (SNPs) distributed across the genome to discriminate donor and recipient DNA molecules. In its current implementation, GTD requires genotyping of both the transplant recipient and donor. However, in practice, donor genotype information is often unavailable. Here, we address this issue by developing an algorithm that estimates dd-cfDNA levels in the absence of a donor genotype. Our algorithm predicts heart and lung allograft rejection with an accuracy that is similar to conventional GTD. We furthermore refined the algorithm to handle closely related recipients and donors, a scenario that is common in bone marrow and kidney transplantation. We show that it is possible to estimate dd-cfDNA in bone marrow transplant patients that are unrelated or that are siblings of the donors, using a hidden Markov model (HMM) of identity-by-descent (IBD) states along the genome. Last, we demonstrate that comparing dd-cfDNA to the proportion of donor DNA in white blood cells can differentiate between relapse and the onset of graft-versus-host disease (GVHD). These methods alleviate some of the barriers to the implementation of GTD, which will further widen its clinical application.'),
(88584, 2017, 'plos', 'Computational-experimental approach to drug-target interaction mapping: A case study on kinase inhibitors', 'Cichonska, Anna|Ravikumar, Balaguru|Parri, Elina|Timonen, Sanna|Pahikkala, Tapio|Airola, Antti|Wennerberg, Krister|Rousu, Juho|Aittokallio, Tero', 'Helsinki Institute for Information Technology HIIT, Department of Computer Science, Aalto University, Espoo, Finland.|Institute for Molecular Medicine Finland FIMM, University of Helsinki, Helsinki, Finland.|Institute for Molecular Medicine Finland FIMM, University of Helsinki, Helsinki, Finland.|Institute for Molecular Medicine Finland FIMM, University of Helsinki, Helsinki, Finland.|Department of Information Technology, University of Turku, Turku, Finland.|Department of Information Technology, University of Turku, Turku, Finland.|Institute for Molecular Medicine Finland FIMM, University of Helsinki, Helsinki, Finland.|Helsinki Institute for Information Technology HIIT, Department of Computer Science, Aalto University, Espoo, Finland.|Institute for Molecular Medicine Finland FIMM, University of Helsinki, Helsinki, Finland.', 'Finland|Finland|Finland|Finland|Finland|Finland|Finland|Finland|Finland', 27, 'Algorithms|Computational Biology|Databases, Factual|Drug Discovery|Humans|Models, Statistical|Protein Binding|Protein Kinase Inhibitors|Reproducibility of Results', 'Journal Article', '10.1371/journal.pcbi.1005678', '28787438', 'Due to relatively high costs and labor required for experimental profiling of the full target space of chemical compounds, various machine learning models have been proposed as cost-effective means to advance this process in terms of predicting the most potent compound-target interactions for subsequent verification. However, most of the model predictions lack direct experimental validation in the laboratory, making their practical benefits for drug discovery or repurposing applications largely unknown. Here, we therefore introduce and carefully test a systematic computational-experimental framework for the prediction and pre-clinical verification of drug-target interactions using a well-established kernel-based regression algorithm as the prediction model. To evaluate its performance, we first predicted unmeasured binding affinities in a large-scale kinase inhibitor profiling study, and then experimentally tested 100 compound-kinase pairs. The relatively high correlation of 0.77 (p < 0.0001) between the predicted and measured bioactivities supports the potential of the model for filling the experimental gaps in existing compound-target interaction maps. Further, we subjected the model to a more challenging task of predicting target interactions for such a new candidate drug compound that lacks prior binding profile information. As a specific case study, we used tivozanib, an investigational VEGF receptor inhibitor with currently unknown off-target profile. Among 7 kinases with high predicted affinity, we experimentally validated 4 new off-targets of tivozanib, namely the Src-family kinases FRK and FYN A, the non-receptor tyrosine kinase ABL1, and the serine/threonine kinase SLK. Our sub-sequent experimental validation protocol effectively avoids any possible information leakage between the training and validation data, and therefore enables rigorous model validation for practical applications. These results demonstrate that the kernel-based modeling approach offers practical benefits for probing novel insights into the mode of action of investigational compounds, and for the identification of new target selectivities for drug repurposing applications.'),
(88585, 2017, 'plos', 'A stochastic-field description of finite-size spiking neural networks', 'Dumont, Grégory|Payeur, Alexandre|Longtin, André', 'Group for Neural Theory, Ecole Normale Supérieure, 29 rue dUlm, 75005, Paris, France.|Department of Physics, University of Ottawa, 150 Louis-Pasteur, Ottawa, Canada.|Department of Physics, University of Ottawa, 150 Louis-Pasteur, Ottawa, Canada.', 'France|Canada|Canada', 0, 'Action Potentials|Animals|Brain|Computational Biology|Models, Neurological|Nerve Net|Neurons|Stochastic Processes', 'Journal Article', '10.1371/journal.pcbi.1005691', '28787447', 'Neural network dynamics are governed by the interaction of spiking neurons. Stochastic aspects of single-neuron dynamics propagate up to the network level and shape the dynamical and informational properties of the population. Mean-field models of population activity disregard the finite-size stochastic fluctuations of network dynamics and thus offer a deterministic description of the system. Here, we derive a stochastic partial differential equation (SPDE) describing the temporal evolution of the finite-size refractory density, which represents the proportion of neurons in a given refractory state at any given time. The population activity-the density of active neurons per unit time-is easily extracted from this refractory density. The SPDE includes finite-size effects through a two-dimensional Gaussian white noise that acts both in time and along the refractory dimension. For an infinite number of neurons the standard mean-field theory is recovered. A discretization of the SPDE along its characteristic curves allows direct simulations of the activity of large but finite spiking networks, this constitutes the main advantage of our approach. Linearizing the SPDE with respect to the deterministic asynchronous state allows the theoretical investigation of finite-size activity fluctuations. In particular, analytical expressions for the power spectrum and autocorrelation of activity fluctuations are obtained. Moreover, our approach can be adapted to incorporate multiple interacting populations and quasi-renewal single-neuron dynamics.'),
(88586, 2017, 'plos', 'Stabilization of diastolic calcium signal via calcium pump regulation of complex local calcium releases and transient decay in a computational model of cardiac pacemaker cell with individual release channels', 'Maltsev, Alexander V|Maltsev, Victor A|Stern, Michael D', 'Laboratory of Cardiovascular Science, Intramural Research Program, National Institute on Aging, NIH, 251 Bayview Blvd., Baltimore, MD, United States of America.|Laboratory of Cardiovascular Science, Intramural Research Program, National Institute on Aging, NIH, 251 Bayview Blvd., Baltimore, MD, United States of America.|Laboratory of Cardiovascular Science, Intramural Research Program, National Institute on Aging, NIH, 251 Bayview Blvd., Baltimore, MD, United States of America.', 'United States|United States|United States', 2, 'Animals|Calcium|Calcium Channels, L-Type|Calcium Signaling|Computer Simulation|Models, Cardiovascular|Myocytes, Cardiac|Sinoatrial Node', 'Journal Article', '10.1371/journal.pcbi.1005675', '28792496', 'Intracellular Local Ca releases (LCRs) from sarcoplasmic reticulum (SR) regulate cardiac pacemaker cell function by activation of electrogenic Na/Ca exchanger (NCX) during diastole. Prior studies demonstrated the existence of powerful compensatory mechanisms of LCR regulation via a complex local cross-talk of Ca pump, release and NCX. One major obstacle to study these mechanisms is that LCR exhibit complex Ca release propagation patterns (including merges and separations) that have not been characterized. Here we developed new terminology, classification, and computer algorithms for automatic detection of numerically simulated LCRs and examined LCR regulation by SR Ca pumping rate (Pup) that provides a major contribution to fight-or-flight response. In our simulations the faster SR Ca pumping accelerates action potential-induced Ca transient decay and quickly clears Ca under the cell membrane in diastole, preventing premature releases. Then the SR generates an earlier, more synchronized, and stronger diastolic LCR signal activating an earlier and larger inward NCX current. LCRs at higher Pup exhibit larger amplitudes and faster propagation with more collisions to each other. The LCRs overlap with Ca transient decay, causing an elevation of the average diastolic [Ca] nadir to ~200 nM (at Pup = 24 mM/s). Background Ca (in locations lacking LCRs) quickly decays to resting Ca levels (<100 nM) at high Pup, but remained elevated during slower decay at low Pup. Release propagation is facilitated at higher Pup by a larger LCR amplitude, whereas at low Pup by higher background Ca. While at low Pup LCRs show smaller amplitudes, their larger durations and sizes combined with longer transient decay stabilize integrals of diastolic Ca and NCX current signals. Thus, the local interplay of SR Ca pump and release channels regulates LCRs and Ca transient decay to insure fail-safe pacemaker cell operation within a wide range of rates.'),
(88587, 2017, 'plos', 'Revisiting chemoaffinity theory: Chemotactic implementation of topographic axonal projection', 'Naoki, Honda', 'Graduate School of Biostudies, Kyoto University, Sakyo, Kyoto, Japan.', 'Japan', 3, 'Animals|Axons|Chemotaxis|Computational Biology|Ephrins|Models, Biological|Retina|Signal Transduction|Superior Colliculi', 'Journal Article', '10.1371/journal.pcbi.1005702', '28792499', 'Neural circuits are wired by chemotactic migration of growth cones guided by extracellular guidance cue gradients. How growth cone chemotaxis builds the macroscopic structure of the neural circuit is a fundamental question in neuroscience. I addressed this issue in the case of the ordered axonal projections called topographic maps in the retinotectal system. In the retina and tectum, the erythropoietin-producing hepatocellular (Eph) receptors and their ligands, the ephrins, are expressed in gradients. According to Sperrys chemoaffinity theory, gradients in both the source and target areas enable projecting axons to recognize their proper terminals, but how axons chemotactically decode their destinations is largely unknown. To identify the chemotactic mechanism of topographic mapping, I developed a mathematical model of intracellular signaling in the growth cone that focuses on the growth cones unique chemotactic property of being attracted or repelled by the same guidance cues in different biological situations. The model presented mechanism by which the retinal growth cone reaches the correct terminal zone in the tectum through alternating chemotactic response between attraction and repulsion around a preferred concentration. The model also provided a unified understanding of the contrasting relationships between receptor expression levels and preferred ligand concentrations in EphA/ephrinA- and EphB/ephrinB-encoded topographic mappings. Thus, this study redefines the chemoaffinity theory in chemotactic terms.'),
(88588, 2017, 'plos', 'Confirmation bias in human reinforcement learning: Evidence from counterfactual feedback processing', 'Palminteri, Stefano|Lefebvre, Germain|Kilford, Emma J|Blakemore, Sarah-Jayne', 'Institute of Cognitive Neuroscience, University College London, London, United Kingdom.|Laboratoire de Neurosciences Cognitives, Institut National de la Santé et de la Recherche Médicale, Paris, FR.|Institute of Cognitive Neuroscience, University College London, London, United Kingdom.|Institute of Cognitive Neuroscience, University College London, London, United Kingdom.', 'United Kingdom|-|United Kingdom|United Kingdom', 24, 'Adult|Computational Biology|Decision Making|Feedback, Psychological|Female|Humans|Learning|Male|Reinforcement (Psychology)|Task Performance and Analysis|Young Adult', 'Journal Article', '10.1371/journal.pcbi.1005684', '28800597', 'Previous studies suggest that factual learning, that is, learning from obtained outcomes, is biased, such that participants preferentially take into account positive, as compared to negative, prediction errors. However, whether or not the prediction error valence also affects counterfactual learning, that is, learning from forgone outcomes, is unknown. To address this question, we analysed the performance of two groups of participants on reinforcement learning tasks using a computational model that was adapted to test if prediction error valence influences learning. We carried out two experiments: in the factual learning experiment, participants learned from partial feedback (i.e., the outcome of the chosen option only), in the counterfactual learning experiment, participants learned from complete feedback information (i.e., the outcomes of both the chosen and unchosen option were displayed). In the factual learning experiment, we replicated previous findings of a valence-induced bias, whereby participants learned preferentially from positive, relative to negative, prediction errors. In contrast, for counterfactual learning, we found the opposite valence-induced bias: negative prediction errors were preferentially taken into account, relative to positive ones. When considering valence-induced bias in the context of both factual and counterfactual learning, it appears that people tend to preferentially take into account information that confirms their current choice.'),
(88589, 2017, 'plos', 'A systems approach reveals distinct metabolic strategies among the NCI-60 cancer cell lines', 'Aurich, Maike K|Fleming, Ronan M T|Thiele, Ines', 'Luxembourg Center for Systems Biomedicine, University of Luxembourg, Esch-Sur-Alzette, Luxembourg.|Luxembourg Center for Systems Biomedicine, University of Luxembourg, Esch-Sur-Alzette, Luxembourg.|Luxembourg Center for Systems Biomedicine, University of Luxembourg, Esch-Sur-Alzette, Luxembourg.', 'Luxembourg|Luxembourg|Luxembourg', 12, 'Biomarkers, Tumor|Cell Line, Tumor|Databases, Protein|Humans|Isocitrate Dehydrogenase|Melanoma|Metabolome|Metabolomics|Models, Biological|Systems Biology', 'Journal Article', '10.1371/journal.pcbi.1005698', '28806730', 'The metabolic phenotype of cancer cells is reflected by the metabolites they consume and by the byproducts they release. Here, we use quantitative, extracellular metabolomic data of the NCI-60 panel and a novel computational method to generate 120 condition-specific cancer cell line metabolic models. These condition-specific cancer models used distinct metabolic strategies to generate energy and cofactors. The analysis of the models capability to deal with environmental perturbations revealed three oxotypes, differing in the range of allowable oxygen uptake rates. Interestingly, models based on metabolomic profiles of melanoma cells were distinguished from other models through their low oxygen uptake rates, which were associated with a glycolytic phenotype. A subset of the melanoma cell models required reductive carboxylation. The analysis of protein and RNA expression levels from the Human Protein Atlas showed that IDH2, which was an essential gene in the melanoma models, but not IDH1 protein, was detected in normal skin cell types and melanoma. Moreover, the von Hippel-Lindau tumor suppressor (VHL) protein, whose loss is associated with non-hypoxic HIF-stabilization, reductive carboxylation, and promotion of glycolysis, was uniformly absent in melanoma. Thus, the experimental data supported the predicted role of IDH2 and the absence of VHL protein supported the glycolytic and low oxygen phenotype predicted for melanoma. Taken together, our approach of integrating extracellular metabolomic data with metabolic modeling and the combination of different network interrogation methods allowed insights into the metabolism of cells.'),
(88590, 2017, 'plos', 'Comparing efficacies of moxifloxacin, levofloxacin and gatifloxacin in tuberculosis granulomas using a multi-scale systems pharmacology approach', 'Pienaar, Elsje|Sarathy, Jansy|Prideaux, Brendan|Dietzold, Jillian|Dartois, Véronique|Kirschner, Denise E|Linderman, Jennifer J', 'Department of Chemical Engineering, University of Michigan, Ann Arbor, Michigan, United States of America.|Public Health Research Institute and New Jersey Medical School, Rutgers, Newark, New Jersey, United States of America.|Public Health Research Institute and New Jersey Medical School, Rutgers, Newark, New Jersey, United States of America.|Department of Medicine, Division of Infectious Disease, New Jersey Medical School, Rutgers University, Newark, New Jersey, United States of America.|Public Health Research Institute and New Jersey Medical School, Rutgers, Newark, New Jersey, United States of America.|Department of Microbiology and Immunology, University of Michigan Medical School, Ann Arbor, Michigan, United States of America.|Department of Chemical Engineering, University of Michigan, Ann Arbor, Michigan, United States of America.', 'United States|Jersey|Jersey|Jersey|Jersey|United States|United States', 23, 'Animals|Antitubercular Agents|Computational Biology|Computer Simulation|Female|Fluoroquinolones|Granuloma|Humans|Microbial Sensitivity Tests|Mycobacterium tuberculosis|Rabbits|Tuberculosis', 'Journal Article', '10.1371/journal.pcbi.1005650', '28817561', 'Granulomas are complex lung lesions that are the hallmark of tuberculosis (TB). Understanding antibiotic dynamics within lung granulomas will be vital to improving and shortening the long course of TB treatment. Three fluoroquinolones (FQs) are commonly prescribed as part of multi-drug resistant TB therapy: moxifloxacin (MXF), levofloxacin (LVX) or gatifloxacin (GFX). To date, insufficient data are available to support selection of one FQ over another, or to show that these drugs are clinically equivalent. To predict the efficacy of MXF, LVX and GFX at a single granuloma level, we integrate computational modeling with experimental datasets into a single mechanistic framework, GranSim. GranSim is a hybrid agent-based computational model that simulates granuloma formation and function, FQ plasma and tissue pharmacokinetics and pharmacodynamics and is based on extensive in vitro and in vivo data. We treat in silico granulomas with recommended daily doses of each FQ and compare efficacy by multiple metrics: bacterial load, sterilization rates, early bactericidal activity and efficacy under non-compliance and treatment interruption. GranSim reproduces in vivo plasma pharmacokinetics, spatial and temporal tissue pharmacokinetics and in vitro pharmacodynamics of these FQs. We predict that MXF kills intracellular bacteria more quickly than LVX and GFX due in part to a higher cellular accumulation ratio. We also show that all three FQs struggle to sterilize non-replicating bacteria residing in caseum. This is due to modest drug concentrations inside caseum and high inhibitory concentrations for this bacterial subpopulation. MXF and LVX have higher granuloma sterilization rates compared to GFX, and MXF performs better in a simulated non-compliance or treatment interruption scenario. We conclude that MXF has a small but potentially clinically significant advantage over LVX, as well as LVX over GFX. We illustrate how a systems pharmacology approach combining experimental and computational methods can guide antibiotic selection for TB.'),
(88591, 2017, 'plos', 'An optimal strategy for epilepsy surgery: Disruption of the rich-club?', 'Lopes, Marinho A|Richardson, Mark P|Abela, Eugenio|Rummel, Christian|Schindler, Kaspar|Goodfellow, Marc|Terry, John R', 'Living Systems Institute, University of Exeter, Exeter, United Kingdom.|EPSRC Centre for Predictive Modelling in Healthcare, University of Exeter, Exeter, United Kingdom.|Institute of Psychiatry, Psychology and Neuroscience, Kings College London, London, United Kingdom.|Support Center for Advanced Neuroimaging (SCAN), University of Bern, Bern, Switzerland.|Department of Neurology, Inselspital, Bern, Switzerland.|Living Systems Institute, University of Exeter, Exeter, United Kingdom.|Living Systems Institute, University of Exeter, Exeter, United Kingdom.', 'United Kingdom|United Kingdom|United Kingdom|Switzerland|Switzerland|United Kingdom|United Kingdom', 0, 'Adult|Brain|Computational Biology|Electrocorticography|Epilepsy|Female|Humans|Male|Models, Neurological|Neurons|Seizures|Signal Processing, Computer-Assisted', 'Journal Article', '10.1371/journal.pcbi.1005637', '28817568', 'Surgery is a therapeutic option for people with epilepsy whose seizures are not controlled by anti-epilepsy drugs. In pre-surgical planning, an array of data modalities, often including intra-cranial EEG, is used in an attempt to map regions of the brain thought to be crucial for the generation of seizures. These regions are then resected with the hope that the individual is rendered seizure free as a consequence. However, post-operative seizure freedom is currently sub-optimal, suggesting that the pre-surgical assessment may be improved by taking advantage of a mechanistic understanding of seizure generation in large brain networks. Herein we use mathematical models to uncover the relative contribution of regions of the brain to seizure generation and consequently which brain regions should be considered for resection. A critical advantage of this modeling approach is that the effect of different surgical strategies can be predicted and quantitatively compared in advance of surgery. Herein we seek to understand seizure generation in networks with different topologies and study how the removal of different nodes in these networks reduces the occurrence of seizures. Since this a computationally demanding problem, a first step for this aim is to facilitate tractability of this approach for large networks. To do this, we demonstrate that predictions arising from a neural mass model are preserved in a lower dimensional, canonical model that is quicker to simulate. We then use this simpler model to study the emergence of seizures in artificial networks with different topologies, and calculate which nodes should be removed to render the network seizure free. We find that for scale-free and rich-club networks there exist specific nodes that are critical for seizure generation and should therefore be removed, whereas for small-world networks the strategy should instead focus on removing sufficient brain tissue. We demonstrate the validity of our approach by analysing intra-cranial EEG recordings from a database comprising 16 patients who have undergone epilepsy surgery, revealing rich-club structures within the obtained functional networks. We show that the postsurgical outcome for these patients was better when a greater proportion of the rich club was removed, in agreement with our theoretical predictions.'),
(88592, 2017, 'plos', 'The application of project-based learning in bioinformatics training', 'Emery, Laura R|Morgan, Sarah L', 'European Molecular Biology Laboratory, European Bioinformatics Institute, Wellcome Genome Campus, Hinxton, Cambridge, United Kingdom.|European Molecular Biology Laboratory, European Bioinformatics Institute, Wellcome Genome Campus, Hinxton, Cambridge, United Kingdom.', 'United Kingdom|United Kingdom', 8, 'Computational Biology|Curriculum|Models, Educational|Problem-Based Learning|Teaching', 'Journal Article', '10.1371/journal.pcbi.1005620', '28817584', '-'),
(88593, 2017, 'plos', 'Ten simple rules to initiate and run a postdoctoral association', 'Bruckmann, Chiara|Sebestyén, Endre', 'IFOM, the FIRC Institute of Molecular Oncology, Milan, Italy.|IFOM, the FIRC Institute of Molecular Oncology, Milan, Italy.', 'Italy|Italy', 3, 'Algorithms|Education, Graduate|Education, Professional|Leadership|Models, Organizational|Organizational Objectives|Research|Societies', 'Editorial', '10.1371/journal.pcbi.1005664', '28817586', '-'),
(88594, 2017, 'plos', 'Ten simple rules for getting the most out of a summer laboratory internship', 'Aicher, Toby P|Barabási, Dániel L|Harris, Benjamin D|Nadig, Ajay|Williams, Kaitlin L', 'Department of Molecular Biology & Biochemistry, Middlebury College, Middlebury, Vermont, United States of America.|Department of Physics, University of Notre Dame, Notre Dame, Indiana, United States of America.|Department of Biology, Colgate University, Hamilton, New York, United States of America.|Department of Psychology, Northwestern University, Evanston, Illinois, United States of America.|Department of Life Sciences, Carroll University, Waukesha, Wisconsin, United States of America.', 'United States|India|United States|United States|United States', 3, 'Algorithms|Education, Professional|Internship and Residency|Laboratories|Research|Science', 'Editorial', '10.1371/journal.pcbi.1005606', '28817622', '-'),
(88595, 2017, 'plos', 'Multidomain analyses of a longitudinal human microbiome intestinal cleanout perturbation experiment', 'Fukuyama, Julia|Rumker, Laurie|Sankaran, Kris|Jeganathan, Pratheepa|Dethlefsen, Les|Relman, David A|Holmes, Susan P', 'Statistics Department, Stanford University, Stanford, California, USA.|Department of Microbiology & Immunology, Stanford University School of Medicine, Stanford, California, USA.|Statistics Department, Stanford University, Stanford, California, USA.|Statistics Department, Stanford University, Stanford, California, USA.|Department of Microbiology & Immunology, Stanford University School of Medicine, Stanford, California, USA.|Department of Microbiology & Immunology, Stanford University School of Medicine, Stanford, California, USA.|Statistics Department, Stanford University, Stanford, California, USA.', 'United States|United States|United States|United States|United States|United States|United States', 0, 'Adult|DNA, Bacterial|Diarrhea|Female|Gastrointestinal Microbiome|Humans|Longitudinal Studies|Male|Metagenome|Metagenomics|Middle Aged|Models, Biological|Principal Component Analysis|RNA, Ribosomal, 16S|Young Adult', 'Journal Article', '10.1371/journal.pcbi.1005706', '28821012', 'Our work focuses on the stability, resilience, and response to perturbation of the bacterial communities in the human gut. Informative flash flood-like disturbances that eliminate most gastrointestinal biomass can be induced using a clinically-relevant iso-osmotic agent. We designed and executed such a disturbance in human volunteers using a dense longitudinal sampling scheme extending before and after induced diarrhea. This experiment has enabled a careful multidomain analysis of a controlled perturbation of the human gut microbiota with a new level of resolution. These new longitudinal multidomain data were analyzed using recently developed statistical methods that demonstrate improvements over current practices. By imposing sparsity constraints we have enhanced the interpretability of the analyses and by employing a new adaptive generalized principal components analysis, incorporated modulated phylogenetic information and enhanced interpretation through scoring of the portions of the tree most influenced by the perturbation. Our analyses leverage the taxa-sample duality in the data to show how the gut microbiota recovers following this perturbation. Through a holistic approach that integrates phylogenetic, metagenomic and abundance information, we elucidate patterns of taxonomic and functional change that characterize the community recovery process across individuals. We provide complete code and illustrations of new sparse statistical methods for high-dimensional, longitudinal multidomain data that provide greater interpretability than existing methods.'),
(88596, 2017, 'plos', 'Efficient and accurate causal inference with hidden confounders from genome-transcriptome variation data', 'Wang, Lingfei|Michoel, Tom', 'Division of Genetics and Genomics, The Roslin Institute, The University of Edinburgh, Easter Bush, Midlothian, United Kingdom.|Division of Genetics and Genomics, The Roslin Institute, The University of Edinburgh, Easter Bush, Midlothian, United Kingdom.', 'United Kingdom|United Kingdom', 6, 'Algorithms|Chromosome Mapping|Databases, Genetic|Genetic Variation|High-Throughput Nucleotide Sequencing|Models, Statistical|Transcriptome', 'Journal Article', '10.1371/journal.pcbi.1005703', '28821014', 'Mapping gene expression as a quantitative trait using whole genome-sequencing and transcriptome analysis allows to discover the functional consequences of genetic variation. We developed a novel method and ultra-fast software Findr for higly accurate causal inference between gene expression traits using cis-regulatory DNA variations as causal anchors, which improves current methods by taking into consideration hidden confounders and weak regulations. Findr outperformed existing methods on the DREAM5 Systems Genetics challenge and on the prediction of microRNA and transcription factor targets in human lymphoblastoid cells, while being nearly a million times faster. Findr is publicly available at https://github.com/lingfeiwang/findr.'),
(88597, 2017, 'plos', 'Extracting replicable associations across multiple studies: Empirical Bayes algorithms for controlling the false discovery rate', 'Amar, David|Shamir, Ron|Yekutieli, Daniel', 'The Blavatnik School of Computer Science, Tel Aviv University, Tel Aviv, Israel.|The Blavatnik School of Computer Science, Tel Aviv University, Tel Aviv, Israel.|Department of Statistics and OR, Tel Aviv University, Tel Aviv, Israel.', 'Israel|Israel|Israel', 0, 'Algorithms|Bayes Theorem|Cluster Analysis|Databases, Factual|Databases, Genetic|Genome-Wide Association Study|Genomics|High-Throughput Nucleotide Sequencing|Humans|Neoplasms|Reproducibility of Results', 'Journal Article', '10.1371/journal.pcbi.1005700', '28821015', 'In almost every field in genomics, large-scale biomedical datasets are used to report associations. Extracting associations that recur across multiple studies while controlling the false discovery rate is a fundamental challenge. Here, we propose a new method to allow joint analysis of multiple studies. Given a set of p-values obtained from each study, the goal is to identify associations that recur in at least k > 1 studies while controlling the false discovery rate. We propose several new algorithms that differ in how the study dependencies are modeled, and compare them and extant methods under various simulated scenarios. The top algorithm, SCREEN (Scalable Cluster-based REplicability ENhancement), is our new algorithm that works in three stages: (1) clustering an estimated correlation network of the studies, (2) learning replicability (e.g., of genes) within clusters, and (3) merging the results across the clusters. When we applied SCREEN to two real datasets it greatly outperformed the results obtained via standard meta-analysis. First, on a collection of 29 case-control gene expression cancer studies, we detected a large set of consistently up-regulated genes related to proliferation and cell cycle regulation. These genes are both consistently up-regulated across many cancer studies, and are well connected in known gene networks. Second, on a recent pan-cancer study that examined the expression profiles of patients with and without mutations in the HLA complex, we detected a large active module of up-regulated genes that are both related to immune responses and are well connected in known gene networks. This module covers thrice more genes as compared to the original study at a similar false discovery rate, demonstrating the high power of SCREEN. An implementation of SCREEN is available in the supplement.'),
(88598, 2017, 'plos', 'Neurons eye view: Inferring features of complex stimuli from neural responses', 'Chen, Xin|Beck, Jeffrey M|Pearson, John M', 'Duke Institute for Brain Sciences, Duke University, Durham, North Carolina, United States of America.|Center for Cognitive Neuroscience, Duke University, Durham, North Carolina, United States of America.|Duke Institute for Brain Sciences, Duke University, Durham, North Carolina, United States of America.', 'United States|United States|United States', 0, 'Action Potentials|Algorithms|Animals|Bayes Theorem|Cluster Analysis|Computational Biology|Macaca|Models, Neurological|Neurons|Photic Stimulation', 'Journal Article', '10.1371/journal.pcbi.1005645', '28827790', 'Experiments that study neural encoding of stimuli at the level of individual neurons typically choose a small set of features present in the world-contrast and luminance for vision, pitch and intensity for sound-and assemble a stimulus set that systematically varies along these dimensions. Subsequent analysis of neural responses to these stimuli typically focuses on regression models, with experimenter-controlled features as predictors and spike counts or firing rates as responses. Unfortunately, this approach requires knowledge in advance about the relevant features coded by a given population of neurons. For domains as complex as social interaction or natural movement, however, the relevant feature space is poorly understood, and an arbitrary a priori choice of features may give rise to confirmation bias. Here, we present a Bayesian model for exploratory data analysis that is capable of automatically identifying the features present in unstructured stimuli based solely on neuronal responses. Our approach is unique within the class of latent state space models of neural activity in that it assumes that firing rates of neurons are sensitive to multiple discrete time-varying features tied to the stimulus, each of which has Markov (or semi-Markov) dynamics. That is, we are modeling neural activity as driven by multiple simultaneous stimulus features rather than intrinsic neural dynamics. We derive a fast variational Bayesian inference algorithm and show that it correctly recovers hidden features in synthetic data, as well as ground-truth stimulus features in a prototypical neural dataset. To demonstrate the utility of the algorithm, we also apply it to cluster neural responses and demonstrate successful recovery of features corresponding to monkeys and faces in the image set.'),
(88599, 2017, 'plos', 'Polymodal allosteric regulation of Type 1 Serine/Threonine Kinase Receptors via a conserved electrostatic lock', 'Botello-Smith, Wesley M|Alsamarah, Abdelaziz|Chatterjee, Payal|Xie, Chen|Lacroix, Jerome J|Hao, Jijun|Luo, Yun', 'College of pharmacy, Western University of Health Sciences, Pomona, CA, United States of America.|College of pharmacy, Western University of Health Sciences, Pomona, CA, United States of America.|College of pharmacy, Western University of Health Sciences, Pomona, CA, United States of America.|College of Veterinary Sciences, Western University of Health Sciences, Pomona, CA, United States of America.|Graduate College of Biomedical Sciences, Western University of Health Sciences, Pomona, CA, United States of America.|College of Veterinary Sciences, Western University of Health Sciences, Pomona, CA, United States of America.|College of pharmacy, Western University of Health Sciences, Pomona, CA, United States of America.', 'United States|United States|United States|United States|United States|United States|United States', 7, 'Adenosine Triphosphate|Allosteric Regulation|Arginine|Humans|Molecular Dynamics Simulation|Mutation|Phosphorylation|Protein Binding|Protein-Serine-Threonine Kinases|Static Electricity|Thermodynamics', 'Journal Article', '10.1371/journal.pcbi.1005711', '28827795', 'Type 1 Serine/Threonine Kinase Receptors (STKR1) transduce a wide spectrum of biological signals mediated by TGF-xcexb2 superfamily members. The STKR1 activity is tightly controlled by their regulatory glycine-serine rich (GS) domain adjacent to the kinase domain. Despite decades of studies, it remains unknown how physiological or pathological GS domain modifications are coupled to STKR1 kinase activity. Here, by performing molecular dynamics simulations and free energy calculation of Activin-Like Kinase 2 (ALK2), we found that GS domain phosphorylation, FKBP12 dissociation, and disease mutations all destabilize a D354-R375 salt-bridge, which normally acts as an electrostatic lock to prevent coordination of adenosine triphosphate (ATP) to the catalytic site. We developed a WAFEX-guided principal analysis and unraveled how phosphorylation destabilizes this highly conserved salt-bridge in temporal and physical space. Using current-flow betweenness scores, we identified an allosteric network of residue-residue contacts between the GS domain and the catalytic site that controls the formation and disruption of this salt bridge. Importantly, our novel network analysis approach revealed how certain disease-causing mutations bypass FKBP12-mediated kinase inhibition to produce leaky signaling. We further provide experimental evidence that this salt-bridge lock exists in other STKR1s, and acts as a general safety mechanism in STKR1 to prevent pathological leaky signaling. In summary, our study provides a compelling and unifying allosteric activation mechanism in STKR1 kinases that reconciles a large number of experimental studies and sheds light on a novel therapeutic avenue to target disease-related STKR1 mutants.'),
(88600, 2017, 'plos', 'Host population structure impedes reversion to drug sensitivity after discontinuation of treatment', 'Liechti, Jonas I|Leventhal, Gabriel E|Bonhoeffer, Sebastian', 'Institute for Integrative Biology, ETH Zürich, Zürich, Switzerland.|Institute for Integrative Biology, ETH Zürich, Zürich, Switzerland.|Institute for Integrative Biology, ETH Zürich, Zürich, Switzerland.', 'Switzerland|Switzerland|Switzerland', 0, 'Computational Biology|Computer Simulation|Disease Transmission, Infectious|Drug Resistance|Host-Pathogen Interactions|Humans|Models, Biological', 'Journal Article', '10.1371/journal.pcbi.1005704', '28827796', 'Intense use of antibiotics for the treatment of diseases such as tuberculosis, malaria, Staphylococcus aureus or gonorrhea has led to rapidly increasing population levels of drug resistance. This has generally necessitated a switch to new drugs and the discontinuation of older ones, after which resistance often only declines slowly or even persists indefinitely. These long-term effects are usually ascribed to low fitness costs of resistance in absence of the drug. Here we show that structure in the host population, in particular heterogeneity in number of contacts, also plays an important role in the reversion dynamics. Host contact structure acts both during the phase of intense treatment, leading to non-random distributions of the resistant strain among the infected population, and after the discontinuation of the drug, by affecting the competition dynamics resulting in a mitigation of fitness advantages. As a consequence, we observe both a lower rate of reversion and a lower probability that reversion to sensitivity on the population level occurs after treatment is stopped. Our simulations show that the impact of heterogeneity in the host structure is maximal in the biologically most plausible parameter range, namely when fitness costs of resistance are small.'),
(88601, 2017, 'plos', 'Spatial dynamics of synthetic microbial mutualists and their parasites', 'Amor, Daniel R|Montañez, Raúl|Duran-Nebreda, Salva|Solé, Ricard', 'Physics of Living Systems, Department of Physics, Massachusetts Institute of Technology, Cambridge, Massachusetts, United States of America.|ICREA-Complex Systems Lab, Department of Experimental and Health Sciences, Universitat Pompeu Fabra, Barcelona, Spain.|ICREA-Complex Systems Lab, Department of Experimental and Health Sciences, Universitat Pompeu Fabra, Barcelona, Spain.|ICREA-Complex Systems Lab, Department of Experimental and Health Sciences, Universitat Pompeu Fabra, Barcelona, Spain.', 'United States|Spain|Spain|Spain', 13, 'Bacterial Physiological Phenomena|Biological Evolution|Cell Culture Techniques|Microbial Consortia|Models, Biological|Symbiosis|Synthetic Biology', 'Journal Article', '10.1371/journal.pcbi.1005689', '28827802', 'A major force contributing to the emergence of novelty in nature is the presence of cooperative interactions, where two or more components of a system act in synergy, sometimes leading to higher-order, emergent phenomena. Within molecular evolution, the so called hypercycle defines the simplest model of an autocatalytic cycle, providing major theoretical insights on the evolution of cooperation in the early biosphere. These closed cooperative loops have also inspired our understanding of how catalytic loops appear in ecological systems. In both cases, hypercycle and ecological cooperative loops, the role played by space seems to be crucial for their stability and resilience against parasites. However, it is difficult to test these ideas in natural ecosystems, where time and spatial scales introduce considerable limitations. Here, we use engineered bacteria as a model system to a variety of environmental scenarios identifying trends that transcend the specific model system, such an enhanced genetic diversity in environments requiring mutualistic interactions. Interestingly, we show that improved environments can slow down mutualistic range expansions as a result of genetic drift effects preceding local resource depletion. Moreover, we show that a parasitic strain is excluded from the population during range expansions (which acknowledges a classical prediction). Nevertheless, environmental deterioration can reshape population interactions, this same strain becoming part of a three-species mutualistic web in scenarios in which the two-strain mutualism becomes non functional. The evolutionary and ecological implications for the design of synthetic ecosystems are outlined.'),
(88602, 2017, 'plos', 'Limb-Enhancer Genie: An accessible resource of accurate enhancer predictions in the developing limb', 'Monti, Remo|Barozzi, Iros|Osterwalder, Marco|Lee, Elizabeth|Kato, Momoe|Garvin, Tyler H|Plajzer-Frick, Ingrid|Pickle, Catherine S|Akiyama, Jennifer A|Afzal, Veena|Beerenwinkel, Niko|Dickel, Diane E|Visel, Axel|Pennacchio, Len A', 'Lawrence Berkeley National Laboratory, Berkeley, California, United States of America.|Lawrence Berkeley National Laboratory, Berkeley, California, United States of America.|Lawrence Berkeley National Laboratory, Berkeley, California, United States of America.|Lawrence Berkeley National Laboratory, Berkeley, California, United States of America.|Lawrence Berkeley National Laboratory, Berkeley, California, United States of America.|Lawrence Berkeley National Laboratory, Berkeley, California, United States of America.|Lawrence Berkeley National Laboratory, Berkeley, California, United States of America.|Lawrence Berkeley National Laboratory, Berkeley, California, United States of America.|Lawrence Berkeley National Laboratory, Berkeley, California, United States of America.|Lawrence Berkeley National Laboratory, Berkeley, California, United States of America.|Department of Biosystems Science and Engineering, ETH Zurich, Basel, Switzerland.|Lawrence Berkeley National Laboratory, Berkeley, California, United States of America.|Lawrence Berkeley National Laboratory, Berkeley, California, United States of America.|Lawrence Berkeley National Laboratory, Berkeley, California, United States of America.', 'United States|United States|United States|United States|United States|United States|United States|Un', 5, 'Animals|Enhancer Elements, Genetic|Extremities|Genome|Genomics|Growth and Development|Machine Learning|Mice|Software', 'Journal Article', '10.1371/journal.pcbi.1005720', '28827824', 'Epigenomic mapping of enhancer-associated chromatin modifications facilitates the genome-wide discovery of tissue-specific enhancers in vivo. However, reliance on single chromatin marks leads to high rates of false-positive predictions. More sophisticated, integrative methods have been described, but commonly suffer from limited accessibility to the resulting predictions and reduced biological interpretability. Here we present the Limb-Enhancer Genie (LEG), a collection of highly accurate, genome-wide predictions of enhancers in the developing limb, available through a user-friendly online interface. We predict limb enhancers using a combination of >50 published limb-specific datasets and clusters of evolutionarily conserved transcription factor binding sites, taking advantage of the patterns observed at previously in vivo validated elements. By combining different statistical models, our approach outperforms current state-of-the-art methods and provides interpretable measures of feature importance. Our results indicate that including a previously unappreciated score that quantifies tissue-specific nuclease accessibility significantly improves prediction performance. We demonstrate the utility of our approach through in vivo validation of newly predicted elements. Moreover, we describe general features that can guide the type of datasets to include when predicting tissue-specific enhancers genome-wide, while providing an accessible resource to the general biological community and facilitating the functional interpretation of genetic studies of limb malformations.');
INSERT INTO `papers` (`id`, `ano`, `journal`, `titulo`, `autores`, `afiliacao`, `pais`, `citacoes`, `palavra_chave`, `categorias`, `doi`, `pubmed`, `abstract`) VALUES
(88603, 2017, 'plos', 'Temperature manipulation of neuronal dynamics in a forebrain motor control nucleus', 'Goldin, Matías A|Mindlin, Gabriel B', 'Dynamical Systems Laboratory, Physics Department and IFIBA Conicet, University of Buenos Aires, Pabellón 1, Ciudad Universitaria, Buenos Aires, Argentina.|Dynamical Systems Laboratory, Physics Department and IFIBA Conicet, University of Buenos Aires, Pabellón 1, Ciudad Universitaria, Buenos Aires, Argentina.', 'Argentina|Argentina', 3, 'Action Potentials|Animals|Canaries|Computational Biology|Computer Simulation|Male|Models, Neurological|Neurons|Prosencephalon|Temperature|Vocalization, Animal', 'Journal Article', '10.1371/journal.pcbi.1005699', '28829769', 'Different neuronal types within brain motor areas contribute to the generation of complex motor behaviors. A widely studied songbird forebrain nucleus (HVC) has been recognized as fundamental in shaping the precise timing characteristics of birdsong. This is based, among other evidence, on the stretching and the breaking of song structure when HVC is cooled. However, little is known about the temperature effects that take place in its neurons. To address this, we investigated the dynamics of HVC both experimentally and computationally. We developed a technique where simultaneous electrophysiological recordings were performed during temperature manipulation of HVC. We recorded spontaneous activity and found three effects: widening of the spike shape, decrease of the firing rate and change in the interspike interval distribution. All these effects could be explained with a detailed conductance based model of all the neurons present in HVC. Temperature dependence of the ionic channel time constants explained the first effect, while the second was based in the changes of the maximal conductance using single synaptic excitatory inputs. The last phenomenon, only emerged after introducing a more realistic synaptic input to the inhibitory interneurons. Two timescales were present in the interspike distributions. The behavior of one timescale was reproduced with different input balances received form the excitatory neurons, whereas the other, which disappears with cooling, could not be found assuming poissonian synaptic inputs. Furthermore, the computational model shows that the bursting of the excitatory neurons arises naturally at normal brain temperature and that they have an intrinsic delay at low temperatures. The same effect occurs at single synapses, which may explain song stretching. These findings shed light on the temperature dependence of neuronal dynamics and present a comprehensive framework to study neuronal connectivity. This study, which is based on intrinsic neuronal characteristics, may help to understand emergent behavioral changes.'),
(88604, 2017, 'plos', 'Deciphering HLA-I motifs across HLA peptidomes improves neo-antigen predictions and identifies allostery regulating HLA specificity', 'Bassani-Sternberg, Michal|Chong, Chloé|Guillaume, Philippe|Solleder, Marthe|Pak, HuiSong|Gannon, Philippe O|Kandalaft, Lana E|Coukos, George|Gfeller, David', 'Ludwig Centre for Cancer Research, University of Lausanne, Epalinges, Switzerland.|Ludwig Centre for Cancer Research, University of Lausanne, Epalinges, Switzerland.|Ludwig Centre for Cancer Research, University of Lausanne, Epalinges, Switzerland.|Ludwig Centre for Cancer Research, University of Lausanne, Epalinges, Switzerland.|Ludwig Centre for Cancer Research, University of Lausanne, Epalinges, Switzerland.|Department of Fundamental Oncology, University Hospital of Lausanne, Lausanne, Switzerland.|Ludwig Centre for Cancer Research, University of Lausanne, Epalinges, Switzerland.|Ludwig Centre for Cancer Research, University of Lausanne, Epalinges, Switzerland.|Ludwig Centre for Cancer Research, University of Lausanne, Epalinges, Switzerland.', 'Switzerland|Switzerland|Switzerland|Switzerland|Switzerland|Switzerland|Switzerland|Switzerland|Swit', 53, 'Amino Acid Motifs|Binding Sites|Histocompatibility Antigens Class I|Humans|Peptides|Protein Binding|Proteome|Proteomics', 'Journal Article', '10.1371/journal.pcbi.1005725', '28832583', 'The precise identification of Human Leukocyte Antigen class I (HLA-I) binding motifs plays a central role in our ability to understand and predict (neo-)antigen presentation in infectious diseases and cancer. Here, by exploiting co-occurrence of HLA-I alleles across ten newly generated as well as forty public HLA peptidomics datasets comprising more than 115,000 unique peptides, we show that we can rapidly and accurately identify many HLA-I binding motifs and map them to their corresponding alleles without any a priori knowledge of HLA-I binding specificity. Our approach recapitulates and refines known motifs for 43 of the most frequent alleles, uncovers new motifs for 9 alleles that up to now had less than five known ligands and provides a scalable framework to incorporate additional HLA peptidomics studies in the future. The refined motifs improve neo-antigen and cancer testis antigen predictions, indicating that unbiased HLA peptidomics data are ideal for in silico predictions of neo-antigens from tumor exome sequencing data. The new motifs further reveal distant modulation of the binding specificity at P2 for some HLA-I alleles by residues in the HLA-I binding site but outside of the B-pocket and we unravel the underlying mechanisms by protein structure analysis, mutagenesis and in vitro binding assays.'),
(88605, 2017, 'plos', 'Data driven flexible backbone protein design', 'Sun, Mark G F|Kim, Philip M', 'Department of Computer Science, University of Toronto, Toronto, Canada.|Department of Computer Science, University of Toronto, Toronto, Canada.', 'Canada|Canada', 6, 'Computational Biology|Databases, Protein|Humans|Models, Molecular|Protein Binding|Protein Engineering|Proteins|Ubiquitin', 'Journal Article', '10.1371/journal.pcbi.1005722', '28837553', 'Protein design remains an important problem in computational structural biology. Current computational protein design methods largely use physics-based methods, which make use of information from a single protein structure. This is despite the fact that multiple structures of many protein folds are now readily available in the PDB. While ensemble protein design methods can use multiple protein structures, they treat each structure independently. Here, we introduce a flexible backbone strategy, FlexiBaL-GP, which learns global protein backbone movements directly from multiple protein structures. FlexiBaL-GP uses the machine learning method of Gaussian Process Latent Variable Models to learn a lower dimensional representation of the protein coordinates that best represent backbone movements. These learned backbone movements are used to explore alternative protein backbones, while engineering a protein within a parallel tempered MCMC framework. Using the human ubiquitin-USP21 complex as a model we demonstrate that our design strategy outperforms current strategies for the interface design task of identifying tight binding ubiquitin variants for USP21.'),
(88606, 2017, 'plos', 'Spread of hospital-acquired infections: A comparison of healthcare networks', 'Nekkab, Narimane|Astagneau, Pascal|Temime, Laura|Crépey, Pascal', 'Laboratoire MESuRS, Conservatoire National des Arts et Métiers, 292 Rue Saint-Martin, Paris, France.|Ecole des Hautes Etudes en Santé Publique, Département dEpidémiologie et de Biostatistiques, 15 Avenue du Professeur-Léon-Bernard, Rennes, France.|Laboratoire MESuRS, Conservatoire National des Arts et Métiers, 292 Rue Saint-Martin, Paris, France.|Ecole des Hautes Etudes en Santé Publique, Département dEpidémiologie et de Biostatistiques, 15 Avenue du Professeur-Léon-Bernard, Rennes, France.', 'France|France|France|France', 13, 'Algorithms|Cluster Analysis|Computational Biology|Cross Infection|France|Hospitals|Humans|Infection Control|Patient Transfer', 'Journal Article', '10.1371/journal.pcbi.1005666', '28837555', 'Hospital-acquired infections (HAIs), including emerging multi-drug resistant organisms, threaten healthcare systems worldwide. Efficient containment measures of HAIs must mobilize the entire healthcare network. Thus, to best understand how to reduce the potential scale of HAI epidemic spread, we explore patient transfer patterns in the French healthcare system. Using an exhaustive database of all hospital discharge summaries in France in 2014, we construct and analyze three patient networks based on the following: transfers of patients with HAI (HAI-specific network), patients with suspected HAI (suspected-HAI network), and all patients (general network). All three networks have heterogeneous patient flow and demonstrate small-world and scale-free characteristics. Patient populations that comprise these networks are also heterogeneous in their movement patterns. Ranking of hospitals by centrality measures and comparing community clustering using community detection algorithms shows that despite the differences in patient population, the HAI-specific and suspected-HAI networks rely on the same underlying structure as that of the general network. As a result, the general network may be more reliable in studying potential spread of HAIs. Finally, we identify transfer patterns at both the French regional and departmental (county) levels that are important in the identification of key hospital centers, patient flow trajectories, and regional clusters that may serve as a basis for novel wide-scale infection control strategies.'),
(88607, 2017, 'plos', 'From homeostasis to behavior: Balanced activity in an exploration of embodied dynamic environmental-neural interaction', 'Hellyer, Peter John|Clopath, Claudia|Kehagia, Angie A|Turkheimer, Federico E|Leech, Robert', 'Department of Bioengineering, Imperial College London, London, United Kingdom.|Department of Bioengineering, Imperial College London, London, United Kingdom.|Centre for Neuroimaging Sciences, Institute of Psychiatry, Psychology and Neuroscience, Kings College London, London, United Kingdom.|Centre for Neuroimaging Sciences, Institute of Psychiatry, Psychology and Neuroscience, Kings College London, London, United Kingdom.|Computational, Cognitive and Clinical Neuroimaging Laboratory (C3NL), Imperial College London, Hammersmith Hospital, London, United Kingdom.', 'United Kingdom|United Kingdom|United Kingdom|United Kingdom|United Kingdom', 9, 'Behavior|Brain|Computational Biology|Computer Simulation|Connectome|Environment|Humans|Models, Neurological|Neuroimaging', 'Journal Article', '10.1371/journal.pcbi.1005721', '28837556', 'In recent years, there have been many computational simulations of spontaneous neural dynamics. Here, we describe a simple model of spontaneous neural dynamics that controls an agent moving in a simple virtual environment. These dynamics generate interesting brain-environment feedback interactions that rapidly destabilize neural and behavioral dynamics demonstrating the need for homeostatic mechanisms. We investigate roles for homeostatic plasticity both locally (local inhibition adjusting to balance excitatory input) as well as more globally (regional task negative activity that compensates for task positive, sensory input in another region) balancing neural activity and leading to more stable behavior (trajectories through the environment). Our results suggest complementary functional roles for both local and macroscale mechanisms in maintaining neural and behavioral dynamics and a novel functional role for macroscopic task-negative patterns of activity (e.g., the default mode network).'),
(88608, 2017, 'plos', 'Histologic and biochemical alterations predict pulmonary mechanical dysfunction in aging mice with chronic lung inflammation', 'Massa, Christopher B|Groves, Angela M|Jaggernauth, Smita U|Laskin, Debra L|Gow, Andrew J', 'Department of Pharmacology and Toxicology, The Ernest Mario School of Pharmacy, Rutgers University, Piscataway, New Jersey, United States of America.|Department of Pharmacology and Toxicology, The Ernest Mario School of Pharmacy, Rutgers University, Piscataway, New Jersey, United States of America.|Department of Pharmacology and Toxicology, The Ernest Mario School of Pharmacy, Rutgers University, Piscataway, New Jersey, United States of America.|Department of Pharmacology and Toxicology, The Ernest Mario School of Pharmacy, Rutgers University, Piscataway, New Jersey, United States of America.|Department of Pharmacology and Toxicology, The Ernest Mario School of Pharmacy, Rutgers University, Piscataway, New Jersey, United States of America.', 'Jersey|Jersey|Jersey|Jersey|Jersey', 5, 'Aging|Animals|Chronic Disease|Computational Biology|Inflammation|Lung|Lung Diseases|Male|Mice|Mice, Inbred C57BL|Models, Biological', 'Journal Article', '10.1371/journal.pcbi.1005570', '28837561', 'Both aging and chronic inflammation produce complex structural and biochemical alterations to the lung known to impact work of breathing. Mice deficient in surfactant protein D (Sftpd) develop progressive age-related lung pathology characterized by tissue destruction/remodeling, accumulation of foamy macrophages and alteration in surfactant composition. This study proposes to relate changes in tissue structure seen in normal aging and in chronic inflammation to altered lung mechanics using a computational model. Alterations in lung function in aging and Sftpd -/- mice have been inferred from fitting simple mechanical models to respiratory impedance data (Zrs), however interpretation has been confounded by the simultaneous presence of multiple coexisting pathophysiologic processes. In contrast to the inverse modeling approach, this study uses simulation from experimental measurements to recapitulate how aging and inflammation alter Zrs. Histologic and mechanical measurements were made in C57BL6/J mice and congenic Sftpd-/- mice at 8, 27 and 80 weeks of age (n = 8/group). An anatomic computational model based on published airway morphometry was developed and Zrs was simulated between 0.5 and 20 Hz. End expiratory pressure dependent changes in airway caliber and recruitment were estimated from mechanical measurements. Tissue elements were simulated using the constant phase model of viscoelasticity. Baseline elastance distribution was estimated in 8-week-old wild type mice, and stochastically varied for each condition based on experimentally measured alteration in elastic fiber composition, alveolar geometry and surfactant composition. Weighing reduction in model error against increasing model complexity allowed for identification of essential features underlying mechanical pathology and their contribution to Zrs. Using a maximum likelihood approach, alteration in lung recruitment and diminished elastic fiber density were shown predictive of mechanical alteration at airway opening, to a greater extent than overt acinar wall destruction. Model-predicted deficits in PEEP-dependent lung recruitment correlate with altered lung lining fluid composition independent of age or genotype.'),
(88609, 2017, 'plos', 'Noise correlations in the human brain and their impact on pattern classification', 'Bejjanki, Vikranth R|da Silveira, Rava Azeredo|Cohen, Jonathan D|Turk-Browne, Nicholas B', 'Department of Psychology, Princeton University, Princeton, NJ, United States of America.|Princeton Neuroscience Institute, Princeton University, Princeton, NJ, United States of America.|Department of Psychology, Princeton University, Princeton, NJ, United States of America.|Department of Psychology, Princeton University, Princeton, NJ, United States of America.', 'United States|United States|United States|United States', 3, 'Adult|Algorithms|Attention|Brain|Humans|Magnetic Resonance Imaging|Models, Neurological|Neurons|Pattern Recognition, Physiological', 'Journal Article', '10.1371/journal.pcbi.1005674', '28841641', 'Multivariate decoding methods, such as multivoxel pattern analysis (MVPA), are highly effective at extracting information from brain imaging data. Yet, the precise nature of the information that MVPA draws upon remains controversial. Most current theories emphasize the enhanced sensitivity imparted by aggregating across voxels that have mixed and weak selectivity. However, beyond the selectivity of individual voxels, neural variability is correlated across voxels, and such noise correlations may contribute importantly to accurate decoding. Indeed, a recent computational theory proposed that noise correlations enhance multivariate decoding from heterogeneous neural populations. Here we extend this theory from the scale of neurons to functional magnetic resonance imaging (fMRI) and show that noise correlations between heterogeneous populations of voxels (i.e., voxels selective for different stimulus variables) contribute to the success of MVPA. Specifically, decoding performance is enhanced when voxels with high vs. low noise correlations (measured during rest or in the background of the task) are selected during classifier training. Conversely, voxels that are strongly selective for one class in a GLM or that receive high classification weights in MVPA tend to exhibit high noise correlations with voxels selective for the other class being discriminated against. Furthermore, we use simulations to show that this is a general property of fMRI data and that selectivity and noise correlations can have distinguishable influences on decoding. Taken together, our findings demonstrate that if there is signal in the data, the resulting above-chance classification accuracy is modulated by the magnitude of noise correlations.'),
(88610, 2017, 'plos', 'Towards a category theory approach to analogy: Analyzing re-representation and acquisition of numerical knowledge', 'Navarrete, Jairo A|Dartnell, Pablo', 'Departamento de Ciencias Básicas, Universidad del Bío-Bío, Av. Andrés Bello 702, Chillán, Chile.|Centro de Modelamiento Matemático (CMM), Centro de Investigación Avanzada en Educación (CIAE) de la Universidad de Chile, Periodista José Carrasco Tapia Nº 75, Santiago, Chile.', 'Chile|Chile', 3, 'Algorithms|Cognition|Computational Biology|Computer Simulation|Game Theory|Humans|Learning|Models, Theoretical', 'Journal Article', '10.1371/journal.pcbi.1005683', '28841643', 'Category Theory, a branch of mathematics, has shown promise as a modeling framework for higher-level cognition. We introduce an algebraic model for analogy that uses the language of category theory to explore analogy-related cognitive phenomena. To illustrate the potential of this approach, we use this model to explore three objects of study in cognitive literature. First, (a) we use commutative diagrams to analyze an effect of playing particular educational board games on the learning of numbers. Second, (b) we employ a notion called coequalizer as a formal model of re-representation that explains a property of computational models of analogy called flexibility whereby non-similar representational elements are considered matches and placed in structural correspondence. Finally, (c) we build a formal learning model which shows that re-representation, language processing and analogy making can explain the acquisition of knowledge of rational numbers. These objects of study provide a picture of acquisition of numerical knowledge that is compatible with empirical evidence and offers insights on possible connections between notions such as relational knowledge, analogy, learning, conceptual knowledge, re-representation and procedural knowledge. This suggests that the approach presented here facilitates mathematical modeling of cognition and provides novel ways to think about analogy-related cognitive phenomena.'),
(88611, 2017, 'plos', 'Robust averaging protects decisions from noise in neural computations', 'Li, Vickie|Herce Castañón, Santiago|Solomon, Joshua A|Vandormael, Hildward|Summerfield, Christopher', 'Department of Experimental Psychology, University of Oxford, Oxford, United Kingdom.|Department of Experimental Psychology, University of Oxford, Oxford, United Kingdom.|Centre for Applied Vision Research, City, University of London, London, United Kingdom.|Department of Experimental Psychology, University of Oxford, Oxford, United Kingdom.|Department of Experimental Psychology, University of Oxford, Oxford, United Kingdom.', 'United Kingdom|United Kingdom|United Kingdom|United Kingdom|United Kingdom', 11, 'Adult|Brain|Computational Biology|Computer Simulation|Decision Making|Female|Humans|Male|Models, Neurological|Photic Stimulation|Task Performance and Analysis|Young Adult', 'Journal Article', '10.1371/journal.pcbi.1005723', '28841644', 'An ideal observer will give equivalent weight to sources of information that are equally reliable. However, when averaging visual information, human observers tend to downweight or discount features that are relatively outlying or deviant (robust averaging). Why humans adopt an integration policy that discards important decision information remains unknown. Here, observers were asked to judge the average tilt in a circular array of high-contrast gratings, relative to an orientation boundary defined by a central reference grating. Observers showed robust averaging of orientation, but the extent to which they did so was a positive predictor of their overall performance. Using computational simulations, we show that although robust averaging is suboptimal for a perfect integrator, it paradoxically enhances performance in the presence of late noise, i.e. which corrupts decisions during integration. In other words, robust decision strategies increase the brains resilience to noise arising in neural computations during decision-making.'),
(88612, 2017, 'plos', 'HLA class I haplotype diversity is consistent with selection for frequent existing haplotypes', 'Alter, Idan|Gragert, Loren|Fingerson, Stephanie|Maiers, Martin|Louzoun, Yoram', 'Department of Mathematics, Bar-Ilan University, Ramat Gan, Israel.|National Marrow Donor Program, Minneapolis, Minnesota, United States of America.|National Marrow Donor Program, Minneapolis, Minnesota, United States of America.|National Marrow Donor Program, Minneapolis, Minnesota, United States of America.|Department of Mathematics, Bar-Ilan University, Ramat Gan, Israel.', 'Israel|United States|United States|United States|Israel', 12, 'Alleles|Computational Biology|Genetic Variation|Haplotypes|Histocompatibility Antigens Class I|Humans|Linkage Disequilibrium|Models, Genetic|Selection, Genetic', 'Journal Article', '10.1371/journal.pcbi.1005693', '28846675', 'The major histocompatibility complex (MHC) contains the most polymorphic genetic system in humans, the human leukocyte antigen (HLA) genes of the adaptive immune system. High allelic diversity in HLA is argued to be maintained by balancing selection, such as negative frequency-dependent selection or heterozygote advantage. Selective pressure against immune escape by pathogens can maintain appreciable frequencies of many different HLA alleles. The selection pressures operating on combinations of HLA alleles across loci, or haplotypes, have not been extensively evaluated since the high HLA polymorphism necessitates very large sample sizes, which have not been available until recently. We aimed to evaluate the effect of selection operating at the HLA haplotype level by analyzing HLA A~C~B~DRB1~DQB1 haplotype frequencies derived from over six million individuals genotyped by the National Marrow Donor Program registry. In contrast with alleles, HLA haplotype diversity patterns suggest purifying selection, as certain HLA allele combinations co-occur in high linkage disequilibrium. Linkage disequilibrium is positive (Dij>0) among frequent haplotypes and negative (Dij<0) among rare haplotypes. Fitting the haplotype frequency distribution to several population dynamics models, we found that the best fit was obtained when significant positive frequency-dependent selection (FDS) was incorporated. Finally, the Ewens-Watterson test of homozygosity showed excess homozygosity for 5-locus haplotypes within 23 US populations studied, with an average Fnd of 28.43. Haplotype diversity is most consistent with purifying selection for HLA Class I haplotypes (HLA-A, -B, -C), and was not inferred for HLA Class II haplotypes (-DRB1 and-DQB1). We discuss our empirical results in the context of evolutionary theory, exploring potential mechanisms of selection that maintain high linkage disequilibrium in MHC haplotype blocks.'),
(88613, 2017, 'plos', 'A method of determining where to target surveillance efforts in heterogeneous epidemiological systems', 'Mastin, Alexander J|van den Bosch, Frank|Gottwald, Timothy R|Alonso Chavez, Vasthi|Parnell, Stephen R', 'Ecosystems and Environment Research Centre, School of Environment and Life Sciences, University of Salford, Greater Manchester, United Kingdom.|Computational and Systems Biology, Rothamsted Research, Harpenden, Hertfordshire, United Kingdom.|USDA Agricultural Research Service, Fort Pierce, Florida, United States of America.|Computational and Systems Biology, Rothamsted Research, Harpenden, Hertfordshire, United Kingdom.|Ecosystems and Environment Research Centre, School of Environment and Life Sciences, University of Salford, Greater Manchester, United Kingdom.', 'United Kingdom|United Kingdom|United States|United Kingdom|United Kingdom', 3, 'Animals|Computational Biology|Disease Transmission, Infectious|Disease Vectors|Epidemiological Monitoring|Models, Biological|Models, Statistical|Plant Diseases', 'Journal Article', '10.1371/journal.pcbi.1005712', '28846676', 'The spread of pathogens into new environments poses a considerable threat to human, animal, and plant health, and by extension, human and animal wellbeing, ecosystem function, and agricultural productivity, worldwide. Early detection through effective surveillance is a key strategy to reduce the risk of their establishment. Whilst it is well established that statistical and economic considerations are of vital importance when planning surveillance efforts, it is also important to consider epidemiological characteristics of the pathogen in question-including heterogeneities within the epidemiological system itself. One of the most pronounced realisations of this heterogeneity is seen in the case of vector-borne pathogens, which spread between hosts and vectors-with each group possessing distinct epidemiological characteristics. As a result, an important question when planning surveillance for emerging vector-borne pathogens is where to place sampling resources in order to detect the pathogen as early as possible. We answer this question by developing a statistical function which describes the probability distributions of the prevalences of infection at first detection in both hosts and vectors. We also show how this method can be adapted in order to maximise the probability of early detection of an emerging pathogen within imposed sample size and/or cost constraints, and demonstrate its application using two simple models of vector-borne citrus pathogens. Under the assumption of a linear cost function, we find that sampling costs are generally minimised when either hosts or vectors, but not both, are sampled.'),
(88614, 2017, 'plos', 'Domain-based prediction of the human isoform interactome provides insights into the functional impact of alternative splicing', 'Ghadie, Mohamed Ali|Lambourne, Luke|Vidal, Marc|Xia, Yu', 'Department of Bioengineering, McGill University, Montreal, Québec, Canada.|Department of Bioengineering, McGill University, Montreal, Québec, Canada.|Center for Cancer Systems Biology (CCSB), Dana-Farber Cancer Institute, Boston, Massachusetts, United States of America.|Department of Bioengineering, McGill University, Montreal, Québec, Canada.', 'Canada|Canada|United States|Canada', 9, 'Alternative Splicing|Computational Biology|Humans|Models, Statistical|Neoplasms|Protein Interaction Mapping|Protein Interaction Maps|Protein Isoforms', 'Journal Article', '10.1371/journal.pcbi.1005717', '28846689', 'Alternative splicing is known to remodel protein-protein interaction networks (interactomes), yet large-scale determination of isoform-specific interactions remains challenging. We present a domain-based method to predict the isoform interactome from the reference interactome. First, we construct the domain-resolved reference interactome by mapping known domain-domain interactions onto experimentally-determined interactions between reference proteins. Then, we construct the isoform interactome by predicting that an isoform loses an interaction if it loses the domain mediating the interaction. Our prediction framework is of high-quality when assessed by experimental data. The predicted human isoform interactome reveals extensive network remodeling by alternative splicing. Protein pairs interacting with different isoforms of the same gene tend to be more divergent in biological function, tissue expression, and disease phenotype than protein pairs interacting with the same isoforms. Our prediction method complements experimental efforts, and demonstrates that integrating structural domain information with interactomes provides insights into the functional impact of alternative splicing.'),
(88615, 2017, 'plos', 'A computational model of spatio-temporal cardiac intracellular calcium handling with realistic structure and spatial flux distribution from sarcoplasmic reticulum and t-tubule reconstructions', 'Colman, Michael A|Pinali, Christian|Trafford, Andrew W|Zhang, Henggui|Kitmitto, Ashraf', 'School of Biomedical Sciences, Faculty of Biological Sciences, University of Leeds, Leeds, United Kingdom.|Division of Cardiovascular Sciences, Faculty of Biology, Medicine and Health Sciences, University of Manchester, Manchester, United Kingdom.|Division of Cardiovascular Sciences, Faculty of Biology, Medicine and Health Sciences, University of Manchester, Manchester, United Kingdom.|School of Physics and Astronomy, Faculty of Engineering and Physical Sciences, University of Manchester, Manchester, United Kingdom.|Division of Cardiovascular Sciences, Faculty of Biology, Medicine and Health Sciences, University of Manchester, Manchester, United Kingdom.', 'United Kingdom|United Kingdom|United Kingdom|United Kingdom|United Kingdom', 18, 'Animals|Calcium|Calcium Signaling|Computer Simulation|Heart Ventricles|Humans|Models, Cardiovascular|Sarcoplasmic Reticulum|Sheep|Spatio-Temporal Analysis|Ventricular Function', 'Journal Article', '10.1371/journal.pcbi.1005714', '28859079', 'Intracellular calcium cycling is a vital component of cardiac excitation-contraction coupling. The key structures responsible for controlling calcium dynamics are the cell membrane (comprising the surface sarcolemma and transverse-tubules), the intracellular calcium store (the sarcoplasmic reticulum), and the co-localisation of these two structures to form dyads within which calcium-induced-calcium-release occurs. The organisation of these structures tightly controls intracellular calcium dynamics. In this study, we present a computational model of intracellular calcium cycling in three-dimensions (3-D), which incorporates high resolution reconstructions of these key regulatory structures, attained through imaging of tissue taken from the sheep left ventricle using serial block face scanning electron microscopy. An approach was developed to model the sarcoplasmic reticulum structure at the whole-cell scale, by reducing its full 3-D structure to a 3-D network of one-dimensional strands. The model reproduces intracellular calcium dynamics during control pacing and reveals the high-resolution 3-D spatial structure of calcium gradients and intracellular fluxes in both the cytoplasm and sarcoplasmic reticulum. We also demonstrated the capability of the model to reproduce potentially pro-arrhythmic dynamics under perturbed conditions, pertaining to calcium-transient alternans and spontaneous release events. Comparison with idealised cell models emphasised the importance of structure in determining calcium gradients and controlling the spatial dynamics associated with calcium-transient alternans, wherein the probabilistic nature of dyad activation and recruitment was constrained. The model was further used to highlight the criticality in calcium spark propagation in relation to inter-dyad distances. The model presented provides a powerful tool for future investigation of structure-function relationships underlying physiological and pathophysiological intracellular calcium handling phenomena at the whole-cell. The approach allows for the first time direct integration of high-resolution images of 3-D intracellular structures with models of calcium cycling, presenting the possibility to directly assess the functional impact of structural remodelling at the cellular scale.'),
(88616, 2017, 'plos', 'Mouth-clicks used by blind expert human echolocators - signal description and model based signal synthesis', 'Thaler, Lore|Reich, Galen M|Zhang, Xinyu|Wang, Dinghe|Smith, Graeme E|Tao, Zeng|Abdullah, Raja Syamsul Azmir Bin Raja|Cherniakov, Mikhail|Baker, Christopher J|Kish, Daniel|Antoniou, Michail', 'Department of Psychology, Durham University, Science Site, Durham, United Kingdom.|Department of Electronic Electrical and Systems Engineering, School of Engineering, University of Birmingham, Edgbaston, Birmingham, United Kingdom.|School of Information and Electronics, Beijing Institute of Technology, Beijing, China.|College of Electronic Science and Engineering, National University of Defense Technology, Changsha, China.|Department of Electrical & Computer Engineering, The Ohio State University, Columbus, Ohio, United States of America.|School of Information and Electronics, Beijing Institute of Technology, Beijing, China.|Department of Computer and Communication Systems Engineering, Universiti Putra Malaysia (UPM), Serdang, Selangor, Malaysia.|Department of Electronic Electrical and Systems Engineering, School of Engineering, University of Birmingham, Edgbaston, Birmingham, United Kingdom.|Department of Electronic Electrical and Systems Engineering, School of Engineering, University of Birmingham, Edgbaston, Birmingham, United Kingdom.|World Access for the Blind, Placentia, California, United States.|Department of Electronic Electrical and Systems Engineering, School of Engineering, University of Birmingham, Edgbaston, Birmingham, United Kingdom.', 'United Kingdom|United Kingdom|China|China|United States|China|Malaysia|United Kingdom|United Kingdom', 29, 'Adult|Animals|Blindness|Databases, Factual|Echolocation|Humans|Male|Middle Aged|Models, Biological|Mouth|Signal Processing, Computer-Assisted|Sound Localization|Sound Spectrography', 'Journal Article', '10.1371/journal.pcbi.1005670', '28859082', 'Echolocation is the ability to use sound-echoes to infer spatial information about the environment. Some blind people have developed extraordinary proficiency in echolocation using mouth-clicks. The first step of human biosonar is the transmission (mouth click) and subsequent reception of the resultant sound through the ear. Existing head-related transfer function (HRTF) data bases provide descriptions of reception of the resultant sound. For the current report, we collected a large database of click emissions with three blind people expertly trained in echolocation, which allowed us to perform unprecedented analyses. Specifically, the current report provides the first ever description of the spatial distribution (i.e. beam pattern) of human expert echolocation transmissions, as well as spectro-temporal descriptions at a level of detail not available before. Our data show that transmission levels are fairly constant within a 60° cone emanating from the mouth, but levels drop gradually at further angles, more than for speech. In terms of spectro-temporal features, our data show that emissions are consistently very brief (~3ms duration) with peak frequencies 2-4kHz, but with energy also at 10kHz. This differs from previous reports of durations 3-15ms and peak frequencies 2-8kHz, which were based on less detailed measurements. Based on our measurements we propose to model transmissions as sum of monotones modulated by a decaying exponential, with angular attenuation by a modified cardioid. We provide model parameters for each echolocator. These results are a step towards developing computational models of human biosonar. For example, in bats, spatial and spectro-temporal features of emissions have been used to derive and test model based hypotheses about behaviour. The data we present here suggest similar research opportunities within the context of human echolocation. Relatedly, the data are a basis to develop synthetic models of human echolocation that could be virtual (i.e. simulated) or real (i.e. loudspeaker, microphones), and which will help understanding the link between physical principles and human behaviour.'),
(88617, 2017, 'plos', 'Differential receptive field organizations give rise to nearly identical neural correlations across three parallel sensory maps in weakly electric fish', 'Hofmann, Volker|Chacron, Maurice J', 'Department of Physiology, McGill University, McIntyre Medical Building, Montreal, Québec, Canada.|Department of Physiology, McGill University, McIntyre Medical Building, Montreal, Québec, Canada.', 'Canada|Canada', 11, 'Animals|Computational Biology|Electric Fish|Electrophysiological Phenomena|Models, Neurological|Pyramidal Cells', 'Journal Article', '10.1371/journal.pcbi.1005716', '28863136', 'Understanding how neural populations encode sensory information thereby leading to perception and behavior (i.e., the neural code) remains an important problem in neuroscience. When investigating the neural code, one must take into account the fact that neural activities are not independent but are actually correlated with one another. Such correlations are seen ubiquitously and have a strong impact on neural coding. Here we investigated how differences in the antagonistic center-surround receptive field (RF) organization across three parallel sensory maps influence correlations between the activities of electrosensory pyramidal neurons. Using a model based on known anatomical differences in receptive field center size and overlap, we initially predicted large differences in correlated activity across the maps. However, in vivo electrophysiological recordings showed that, contrary to modeling predictions, electrosensory pyramidal neurons across all three segments displayed nearly identical correlations. To explain this surprising result, we incorporated the effects of RF surround in our model. By systematically varying both the RF surround gain and size relative to that of the RF center, we found that multiple RF structures gave rise to similar levels of correlation. In particular, incorporating known physiological differences in RF structure between the three maps in our model gave rise to similar levels of correlation. Our results show that RF center overlap alone does not determine correlations which has important implications for understanding how RF structure influences correlated neural activity.'),
(88618, 2017, 'plos', 'A conceptual and computational framework for modelling and understanding the non-equilibrium gene regulatory networks of mouse embryonic stem cells', 'Greaves, Richard B|Dietmann, Sabine|Smith, Austin|Stepney, Susan|Halley, Julianne D', 'York Centre for Complex Systems Analysis, University of York, York, United Kingdom.|Wellcome Trust-Medical Research Council Cambridge Stem Cell Institute, University of Cambridge, Cambridge, United Kingdom.|Wellcome Trust-Medical Research Council Cambridge Stem Cell Institute, University of Cambridge, Cambridge, United Kingdom.|York Centre for Complex Systems Analysis, University of York, York, United Kingdom.|York Centre for Complex Systems Analysis, University of York, York, United Kingdom.', 'United Kingdom|United Kingdom|United Kingdom|United Kingdom|United Kingdom', 2, 'Animals|Computational Biology|Computer Simulation|Gene Regulatory Networks|Mice|Models, Genetic|Mouse Embryonic Stem Cells', 'Journal Article', '10.1371/journal.pcbi.1005713', '28863148', 'The capacity of pluripotent embryonic stem cells to differentiate into any cell type in the body makes them invaluable in the field of regenerative medicine. However, because of the complexity of both the core pluripotency network and the process of cell fate computation it is not yet possible to control the fate of stem cells. We present a theoretical model of stem cell fate computation that is based on Halley and Winklers Branching Process Theory (BPT) and on Greaves et al.s agent-based computer simulation derived from that theoretical model. BPT abstracts the complex production and action of a Transcription Factor (TF) into a single critical branching process that may dissipate, maintain, or become supercritical. Here we take the single TF model and extend it to multiple interacting TFs, and build an agent-based simulation of multiple TFs to investigate the dynamics of such coupled systems. We have developed the simulation and the theoretical model together, in an iterative manner, with the aim of obtaining a deeper understanding of stem cell fate computation, in order to influence experimental efforts, which may in turn influence the outcome of cellular differentiation. The model used is an example of self-organization and could be more widely applicable to the modelling of other complex systems. The simulation based on this model, though currently limited in scope in terms of the biology it represents, supports the utility of the Halley and Winkler branching process model in describing the behaviour of stem cell gene regulatory networks. Our simulation demonstrates three key features: (i) the existence of a critical value of the branching process parameter, dependent on the details of the cistrome in question, (ii) the ability of an active cistrome to ignite an otherwise fully dissipated cistrome, and drive it to criticality, (iii) how coupling cistromes together can reduce their critical branching parameter values needed to drive them to criticality.'),
(88619, 2017, 'plos', 'A single Markov-type kinetic model accounting for the macroscopic currents of all human voltage-gated sodium channel isoforms', 'Balbi, Pietro|Massobrio, Paolo|Hellgren Kotaleski, Jeanette', 'Department of Neurorehabilitation, Scientific Institute of Pavia via Boezio IRCCS, Istituti Clinici Scientifici Maugeri SpA, Pavia, Italy.|Department of Informatics, Bioengineering, Robotics and System Engineering (DIBRIS), University of Genova, Genova, Italy.|Department of Neuroscience, Karolinska Institute, Stockholm, Sweden.', 'Italy|Italy|Sweden', 8, 'Cell Line|Computational Biology|Computer Simulation|Humans|Kinetics|Markov Chains|Models, Neurological|Protein Isoforms|Voltage-Gated Sodium Channels', 'Journal Article', '10.1371/journal.pcbi.1005737', '28863150', 'Modelling ionic channels represents a fundamental step towards developing biologically detailed neuron models. Until recently, the voltage-gated ion channels have been mainly modelled according to the formalism introduced by the seminal works of Hodgkin and Huxley (HH). However, following the continuing achievements in the biophysical and molecular comprehension of these pore-forming transmembrane proteins, the HH formalism turned out to carry limitations and inconsistencies in reproducing the ion-channels electrophysiological behaviour. At the same time, Markov-type kinetic models have been increasingly proven to successfully replicate both the electrophysiological and biophysical features of different ion channels. However, in order to model even the finest non-conducting molecular conformational change, they are often equipped with a considerable number of states and related transitions, which make them computationally heavy and less suitable for implementation in conductance-based neurons and large networks of those. In this purely modelling study we develop a Markov-type kinetic model for all human voltage-gated sodium channels (VGSCs). The model framework is detailed, unifying (i.e., it accounts for all ion-channel isoforms) and computationally efficient (i.e. with a minimal set of states and transitions). The electrophysiological data to be modelled are gathered from previously published studies on whole-cell patch-clamp experiments in mammalian cell lines heterologously expressing the human VGSC subtypes (from NaV1.1 to NaV1.9). By adopting a minimum sequence of states, and using the same state diagram for all the distinct isoforms, the model ensures the lightest computational load when used in neuron models and neural networks of increasing complexity. The transitions between the states are described by original ordinary differential equations, which represent the rate of the state transitions as a function of voltage (i.e., membrane potential). The kinetic model, developed in the NEURON simulation environment, appears to be the simplest and most parsimonious way for a detailed phenomenological description of the human VGSCs electrophysiological behaviour.'),
(88620, 2017, 'plos', 'DeepPep: Deep proteome inference from peptide profiles', 'Kim, Minseung|Eetemadi, Ameen|Tagkopoulos, Ilias', 'Department of Computer Science, University of California, Davis, Davis, California, United States of America.|Department of Computer Science, University of California, Davis, Davis, California, United States of America.|Department of Computer Science, University of California, Davis, Davis, California, United States of America.', 'United States|United States|United States', 0, 'Algorithms|Animals|Area Under Curve|Databases, Protein|Drosophila melanogaster|Humans|Neural Networks (Computer)|Peptides|Proteome|Proteomics', 'Journal Article', '10.1371/journal.pcbi.1005661', '28873403', 'Protein inference, the identification of the protein set that is the origin of a given peptide profile, is a fundamental challenge in proteomics. We present DeepPep, a deep-convolutional neural network framework that predicts the protein set from a proteomics mixture, given the sequence universe of possible proteins and a target peptide profile. In its core, DeepPep quantifies the change in probabilistic score of peptide-spectrum matches in the presence or absence of a specific protein, hence selecting as candidate proteins with the largest impact to the peptide profile. Application of the method across datasets argues for its competitive predictive ability (AUC of 0.80±0.18, AUPR of 0.84±0.28) in inferring proteins without need of peptide detectability on which the most competitive methods rely. We find that the convolutional neural network architecture outperforms the traditional artificial neural network architectures without convolution layers in protein inference. We expect that similar deep learning architectures that allow learning nonlinear patterns can be further extended to problems in metagenome profiling and cell type inference. The source code of DeepPep and the benchmark datasets used in this study are available at https://deeppep.github.io/DeepPep/.'),
(88621, 2017, 'plos', 'kWIP: The k-mer weighted inner product, a de novo estimator of genetic similarity', 'Murray, Kevin D|Webers, Christfried|Ong, Cheng Soon|Borevitz, Justin|Warthmann, Norman', 'Research School of Biology, The Australian National University, Canberra, Australia.|Data61, CSIRO, Canberra, Australia.|Data61, CSIRO, Canberra, Australia.|Research School of Biology, The Australian National University, Canberra, Australia.|Research School of Biology, The Australian National University, Canberra, Australia.', 'Australia|Australia|Australia|Australia|Australia', 0, 'Algorithms|Chlamydomonas|Genetic Variation|Genetics, Population|Genomics|Models, Genetic|Models, Statistical|Sequence Analysis, DNA|Software', 'Journal Article', '10.1371/journal.pcbi.1005727', '28873405', 'Modern genomics techniques generate overwhelming quantities of data. Extracting population genetic variation demands computationally efficient methods to determine genetic relatedness between individuals (or samples) in an unbiased manner, preferably de novo. Rapid estimation of genetic relatedness directly from sequencing data has the potential to overcome reference genome bias, and to verify that individuals belong to the correct genetic lineage before conclusions are drawn using mislabelled, or misidentified samples. We present the k-mer Weighted Inner Product (kWIP), an assembly-, and alignment-free estimator of genetic similarity. kWIP combines a probabilistic data structure with a novel metric, the weighted inner product (WIP), to efficiently calculate pairwise similarity between sequencing runs from their k-mer counts. It produces a distance matrix, which can then be further analysed and visualised. Our method does not require prior knowledge of the underlying genomes and applications include establishing sample identity and detecting mix-up, non-obvious genomic variation, and population structure. We show that kWIP can reconstruct the true relatedness between samples from simulated populations. By re-analysing several published datasets we show that our results are consistent with marker-based analyses. kWIP is written in C++, licensed under the GNU GPL, and is available from https://github.com/kdmurray91/kwip.');
INSERT INTO `papers` (`id`, `ano`, `journal`, `titulo`, `autores`, `afiliacao`, `pais`, `citacoes`, `palavra_chave`, `categorias`, `doi`, `pubmed`, `abstract`) VALUES
(88622, 2017, 'plos', 'Estimating short-term synaptic plasticity from pre- and postsynaptic spiking', 'Ghanbari, Abed|Malyshev, Aleksey|Volgushev, Maxim|Stevenson, Ian H', 'Department of Biomedical Engineering, University of Connecticut, Storrs, Connecticut, United States of America.|Institute of Higher Nervous Activity and Neurophysiology, Russian Academy of Science, Moscow, Russia.|Department of Psychological Sciences, University of Connecticut, Storrs, Connecticut, United States of America.|Department of Biomedical Engineering, University of Connecticut, Storrs, Connecticut, United States of America.', 'United States|-|United States|United States', 5, 'Action Potentials|Animals|Computational Biology|Male|Models, Neurological|Models, Statistical|Neuronal Plasticity|Rats|Rats, Wistar|Visual Cortex', 'Journal Article', '10.1371/journal.pcbi.1005738', '28873406', 'Short-term synaptic plasticity (STP) critically affects the processing of information in neuronal circuits by reversibly changing the effective strength of connections between neurons on time scales from milliseconds to a few seconds. STP is traditionally studied using intracellular recordings of postsynaptic potentials or currents evoked by presynaptic spikes. However, STP also affects the statistics of postsynaptic spikes. Here we present two model-based approaches for estimating synaptic weights and short-term plasticity from pre- and postsynaptic spike observations alone. We extend a generalized linear model (GLM) that predicts postsynaptic spiking as a function of the observed pre- and postsynaptic spikes and allow the connection strength (coupling term in the GLM) to vary as a function of time based on the history of presynaptic spikes. Our first model assumes that STP follows a Tsodyks-Markram description of vesicle depletion and recovery. In a second model, we introduce a functional description of STP where we estimate the coupling term as a biophysically unrestrained function of the presynaptic inter-spike intervals. To validate the models, we test the accuracy of STP estimation using the spiking of pre- and postsynaptic neurons with known synaptic dynamics. We first test our models using the responses of layer 2/3 pyramidal neurons to simulated presynaptic input with different types of STP, and then use simulated spike trains to examine the effects of spike-frequency adaptation, stochastic vesicle release, spike sorting errors, and common input. We find that, using only spike observations, both model-based methods can accurately reconstruct the time-varying synaptic weights of presynaptic inputs for different types of STP. Our models also capture the differences in postsynaptic spike responses to presynaptic spikes following short vs long inter-spike intervals, similar to results reported for thalamocortical connections. These models may thus be useful tools for characterizing short-term plasticity from multi-electrode spike recordings in vivo.'),
(88623, 2017, 'plos', 'Two passive mechanical conditions modulate power generation by the outer hair cells', 'Liu, Yanju|Gracewski, Sheryl M|Nam, Jong-Hoon', 'Department of Mechanical Engineering, University of Rochester, Rochester, New York, United States of America.|Department of Mechanical Engineering, University of Rochester, Rochester, New York, United States of America.|Department of Mechanical Engineering, University of Rochester, Rochester, New York, United States of America.', 'United States|United States|United States', 3, 'Animals|Biomechanical Phenomena|Computational Biology|Feedback, Physiological|Hair Cells, Auditory, Outer|Models, Neurological|Organ of Corti', 'Journal Article', '10.1371/journal.pcbi.1005701', '28880884', 'In the mammalian cochlea, small vibrations of the sensory epithelium are amplified due to active electro-mechanical feedback of the outer hair cells. The level of amplification is greater in the base than in the apex of the cochlea. Theoretical studies have used longitudinally varying active feedback properties to reproduce the location-dependent amplification. The active feedback force has been considered to be proportional to the basilar membrane displacement or velocity. An underlying assumption was that organ of Corti mechanics are governed by rigid body kinematics. However, recent progress in vibration measurement techniques reveals that organ of Corti mechanics are too complicated to be fully represented with rigid body kinematics. In this study, two components of the active feedback are considered explicitly-organ of Corti mechanics, and outer hair cell electro-mechanics. Physiological properties for the outer hair cells were incorporated, such as the active force gain, mechano-transduction properties, and membrane RC time constant. Instead of a kinematical model, a fully deformable 3D finite element model was used. We show that the organ of Corti mechanics dictate the longitudinal trend of cochlear amplification. Specifically, our results suggest that two mechanical conditions are responsible for location-dependent cochlear amplification. First, the phase of the outer hair cells somatic force with respect to its elongation rate varies along the cochlear length. Second, the local stiffness of the organ of Corti complex felt by individual outer hair cells varies along the cochlear length. We describe how these two mechanical conditions result in greater amplification toward the base of the cochlea.'),
(88624, 2017, 'plos', 'Mobility can promote the evolution of cooperation via emergent self-assortment dynamics', 'Joshi, Jaideep|Couzin, Iain D|Levin, Simon A|Guttal, Vishwesha', 'Centre for Ecological Sciences, Indian Institute of Science, Bengaluru, India.|Department of Collective Behaviour, Max Planck Institute for Ornithology, Konstanz, Germany.|Department of Ecology and Evolutionary Biology, Princeton University, Princeton, New Jersey, United States of America.|Centre for Ecological Sciences, Indian Institute of Science, Bengaluru, India.', 'India|Germany|Jersey|India', 0, 'Animals|Biological Evolution|Cell Movement|Computational Biology|Cooperative Behavior|Locomotion|Models, Biological|Selection, Genetic', 'Journal Article', '10.1371/journal.pcbi.1005732', '28886010', 'The evolution of costly cooperation, where cooperators pay a personal cost to benefit others, requires that cooperators interact more frequently with other cooperators. This condition, called positive assortment, is known to occur in spatially-structured viscous populations, where individuals typically have low mobility and limited dispersal. However many social organisms across taxa, from cells and bacteria, to birds, fish and ungulates, are mobile, and live in populations with considerable inter-group mixing. In the absence of information regarding others traits or conditional strategies, such mixing may inhibit assortment and limit the potential for cooperation to evolve. Here we employ spatially-explicit individual-based evolutionary simulations to incorporate costs and benefits of two coevolving costly traits: cooperative and local cohesive tendencies. We demonstrate that, despite possessing no information about others traits or payoffs, mobility (via self-propulsion or environmental forcing) facilitates assortment of cooperators via a dynamically evolving difference in the cohesive tendencies of cooperators and defectors. We show analytically that this assortment can also be viewed in a multilevel selection framework, where selection for cooperation among emergent groups can overcome selection against cooperators within the groups. As a result of these dynamics, we find an oscillatory pattern of cooperation and defection that maintains cooperation even in the absence of well known mechanisms such as kin interactions, reciprocity, local dispersal or conditional strategies that require information on others strategies or payoffs. Our results offer insights into differential adhesion based mechanisms for positive assortment and reveal the possibility of cooperative aggregations in dynamic fission-fusion populations.'),
(88625, 2017, 'plos', 'Population FBA predicts metabolic phenotypes in yeast', 'Labhsetwar, Piyush|Melo, Marcelo C R|Cole, John A|Luthey-Schulten, Zaida', 'Center for Biophysics and Quantitative Biology, University of Illinois at Urbana-Champaign, Urbana, Illinois, United States of America.|Center for Biophysics and Quantitative Biology, University of Illinois at Urbana-Champaign, Urbana, Illinois, United States of America.|Department of Physics, University of Illinois at Urbana-Champaign, Urbana, Illinois, United States of America.|Center for Biophysics and Quantitative Biology, University of Illinois at Urbana-Champaign, Urbana, Illinois, United States of America.', 'United States|United States|United States|United States', 5, 'Cell Proliferation|Computer Simulation|Culture Media|Ethanol|Metabolic Flux Analysis|Metabolic Networks and Pathways|Models, Biological|Proteome|Proteomics|Saccharomyces cerevisiae|Saccharomyces cerevisiae Proteins', 'Journal Article', '10.1371/journal.pcbi.1005728', '28886026', 'Using protein counts sampled from single cell proteomics distributions to constrain fluxes through a genome-scale model of metabolism, Population flux balance analysis (Population FBA) successfully described metabolic heterogeneity in a population of independent Escherichia coli cells growing in a defined medium. We extend the methodology to account for correlations in protein expression arising from the co-regulation of genes and apply it to study the growth of independent Saccharomyces cerevisiae cells in two different growth media. We find the partitioning of flux between fermentation and respiration predicted by our model agrees with recent 13C fluxomics experiments, and that our model largely recovers the Crabtree effect (the experimentally known bias among certain yeast species toward fermentation with the production of ethanol even in the presence of oxygen), while FBA without proteomics constraints predicts respirative metabolism almost exclusively. The comparisons to the 13C study showed improvement upon inclusion of the correlations and motivated a technique to systematically identify inconsistent kinetic parameters in the literature. The minor secretion fluxes for glycerol and acetate are underestimated by our method, which indicate a need for further refinements to the metabolic model. For yeast cells grown in synthetic defined (SD) medium, the calculated broad distribution of growth rates matches experimental observations from single cell studies, and we characterize several metabolic phenotypes within our modeled populations that make use of diverse pathways. Fast growing yeast cells are predicted to perform significant amount of respiration, use serine-glycine cycle and produce ethanol in mitochondria as opposed to slow growing cells. We use a genetic algorithm to determine the proteomics constraints necessary to reproduce the growth rate distributions seen experimentally. We find that a core set of 51 constraints are essential but that additional constraints are still necessary to recover the observed growth rate distribution in SD medium.'),
(88626, 2017, 'plos', 'Allosteric conformational change cascade in cytoplasmic dynein revealed by structure-based molecular simulations', 'Kubo, Shintaroh|Li, Wenfei|Takada, Shoji', 'Department of Biophysics, Graduate School of Science, Kyoto University, Kyoto, Japan.|National Laboratory of Solid State Microstructure and Department of Physics, Nanjing University, Nanjing, China.|Department of Biophysics, Graduate School of Science, Kyoto University, Kyoto, Japan.', 'Japan|China|Japan', 0, 'Allosteric Regulation|Cytoplasmic Dyneins|Humans|Molecular Dynamics Simulation|Protein Conformation|Protein Domains', 'Journal Article', '10.1371/journal.pcbi.1005748', '28892477', 'Cytoplasmic dynein is a giant ATP-driven molecular motor that proceeds to the minus end of the microtubule (MT). Dynein hydrolyzes ATP in a ring-like structure, containing 6 AAA+ (ATPases associated with diverse cellular activities) modules, which is ~15 nm away from the MT binding domain (MTBD). This architecture implies that long-distance allosteric couplings exist between the AAA+ ring and the MTBD in order for dynein to move on the MT, although little is known about the mechanisms involved. Here, we have performed comprehensive molecular simulations of the dynein motor domain based on pre- and post- power-stroke structural information and in doing so we address the allosteric conformational changes that occur during the power-stroke and recovery-stroke processes. In the power-stroke process, the N-terminal linker movement was the prerequisite to the nucleotide-dependent AAA1 transition, from which a transition cascade propagated, on average, in a circular manner on the AAA+ ring until it reached the AAA6/C-terminal module. The recovery-stroke process was initiated by the transition of the AAA6/C-terminal, from which the transition cascade split into the two directions of the AAA+ ring, occurring both clockwise and anti-clockwise. In both processes, the MTBD conformational change was regulated by the AAA4 module and the AAA5/Strut module.'),
(88627, 2017, 'plos', 'Cost-efficient vaccination protocols for network epidemiology', 'Holme, Petter|Litvak, Nelly', 'Institute of Innovative Research, Tokyo Institute of Technology, Tokyo, Japan.|Department of Applied Mathematics, University of Twente, Enschede, Netherlands.', 'Japan|Netherlands', 0, 'Communicable Disease Control|Communicable Diseases|Computational Biology|Computer Simulation|Costs and Cost Analysis|Humans|Vaccination', 'Journal Article', '10.1371/journal.pcbi.1005696', '28892481', 'We investigate methods to vaccinate contact networks-i.e. removing nodes in such a way that disease spreading is hindered as much as possible-with respect to their cost-efficiency. Any real implementation of such protocols would come with costs related both to the vaccination itself, and gathering of information about the network. Disregarding this, we argue, would lead to erroneous evaluation of vaccination protocols. We use the susceptible-infected-recovered model-the generic model for diseases making patients immune upon recovery-as our disease-spreading scenario, and analyze outbreaks on both empirical and model networks. For different relative costs, different protocols dominate. For high vaccination costs and low costs of gathering information, the so-called acquaintance vaccination is the most cost efficient. For other parameter values, protocols designed for query-efficient identification of the networks largest degrees are most efficient.'),
(88628, 2017, 'plos', 'Exploring the inhibition mechanism of adenylyl cyclase type 5 by n-terminal myristoylated Gxcexb1i1', 'van Keulen, Siri Camee|Rothlisberger, Ursula', 'Institut des Sciences et Ingxc3xa9nierie Chimiques, xc3x89cole Polytechnicque Fxc3xa9dxc3xa9rale de Lausanne (EPFL), CH-1015 Lausanne, Switzerland.|Institut des Sciences et Ingxc3xa9nierie Chimiques, xc3x89cole Polytechnicque Fxc3xa9dxc3xa9rale de Lausanne (EPFL), CH-1015 Lausanne, Switzerland.', 'Switzerland|Switzerland', 0, 'Adenylyl Cyclases|Binding Sites|Enzyme Inhibitors|GTP-Binding Protein alpha Subunits, Gi-Go|Humans|Molecular Dynamics Simulation|Myristic Acids|Protein Binding|Protein Conformation', 'Journal Article', '10.1371/journal.pcbi.1005673', '28892485', 'Adenylyl cyclase (AC) is an important messenger involved in G-protein-coupled-receptor signal transduction pathways, which is a well-known target for drug development. AC is regulated by activated stimulatory (Gxcexb1s) and inhibitory (Gxcexb1i) G proteins in the cytosol. Although experimental studies have shown that these Gxcexb1 subunits can stimulate or inhibit ACs function in a non-competitive way, it is not well understood what the difference is in their mode of action as both Gxcexb1 subunits appear structurally very similar in a non-lipidated state. However, a significant difference between Gxcexb1s and Gxcexb1i is that while Gxcexb1s does not require any lipidation in order to stimulate AC, N-terminal myristoylation is crucial for Gxcexb1is inhibitory function as AC is not inhibited by non-myristoylated Gxcexb1i. At present, only the conformation of the complex including Gxcexb1s and AC has been resolved via X-ray crystallography. Therefore, understanding the interaction between Gxcexb1i and AC is important as it will provide more insight into the unknown mechanism of AC regulation. This study demonstrates via classical molecular dynamics simulations that the myristoylated Gxcexb1i1 structure is able to interact with apo adenylyl cyclase type 5 in a way that causes inhibition of the catalytic function of the enzyme, suggesting that Gxcexb1 lipidation could play a crucial role in AC regulation and in regulating G protein function by affecting Gxcexb1is active conformation.'),
(88629, 2017, 'plos', 'Funneled potential and flux landscapes dictate the stabilities of both the states and the flow: Fission yeast cell cycle', 'Luo, Xiaosheng|Xu, Liufang|Han, Bo|Wang, Jin', 'Applied Science Department at Little Rock, University of Arkansas, Little Rock, Arkansas, United States of America.|Biophysics & Complex System Center and Theoretical Physics Center, Department of Physics, Jilin University, Changchun, Jilin, China.|Department of Chemistry and Department of Physics and Department of Applied Mathematics, State University of New York at Stony Brook, Stony Brook, New York, United States of America.|Biophysics & Complex System Center and Theoretical Physics Center, Department of Physics, Jilin University, Changchun, Jilin, China.', 'United States|China|United States|China', 0, 'Cell Cycle|Entropy|Gene Regulatory Networks|Genes, Fungal|Models, Statistical|Schizosaccharomyces|Stochastic Processes', 'Journal Article', '10.1371/journal.pcbi.1005710', '28892489', 'Using fission yeast cell cycle as an example, we uncovered that the non-equilibrium network dynamics and global properties are determined by two essential features: the potential landscape and the flux landscape. These two landscapes can be quantified through the decomposition of the dynamics into the detailed balance preserving part and detailed balance breaking non-equilibrium part. While the funneled potential landscape is often crucial for the stability of the single attractor networks, we have uncovered that the funneled flux landscape is crucial for the emergence and maintenance of the stable limit cycle oscillation flow. This provides a new interpretation of the origin for the limit cycle oscillations: There are many cycles and loops existed flowing through the state space and forming the flux landscapes, each cycle with a probability flux going through the loop. The limit cycle emerges when a loop stands out and carries significantly more probability flux than other loops. We explore how robustness ratio (RR) as the gap or steepness versus averaged variations or roughness of the landscape, quantifying the degrees of the funneling of the underlying potential and flux landscapes. We state that these two landscapes complement each other with one crucial for stabilities of states on the cycle and the other crucial for the stability of the flow along the cycle. The flux is directly related to the speed of the cell cycle. This allows us to identify the key factors and structure elements of the networks in determining the stability, speed and robustness of the fission yeast cell cycle oscillations. We see that the non-equilibriumness characterized by the degree of detailed balance breaking from the energy pump quantified by the flux is the cause of the energy dissipation for initiating and sustaining the replications essential for the origin and evolution of life. Regulating the cell cycle speed is crucial for designing the prevention and curing strategy of cancer.'),
(88630, 2017, 'plos', 'Projecting social contact matrices in 152 countries using contact surveys and demographic data', 'Prem, Kiesha|Cook, Alex R|Jit, Mark', 'Saw Swee Hock School of Public Health, National University of Singapore and National University Health System, Singapore, Singapore.|Saw Swee Hock School of Public Health, National University of Singapore and National University Health System, Singapore, Singapore.|Department of Infectious Disease Epidemiology, London School of Hygiene & Tropical Medicine, London, United Kingdom.', 'Singapore|Singapore|United Kingdom', 68, 'Adolescent|Adult|Aged|Aged, 80 and over|Child|Child, Preschool|Communicable Diseases|Computational Biology|Demography|Europe|Family Characteristics|Global Health|Humans|Infant|Infant, Newborn|Middle Aged|Models, Statistical|Social Behavior|Surveys and Questionnaires|Young Adult', 'Journal Article', '10.1371/journal.pcbi.1005697', '28898249', 'Heterogeneities in contact networks have a major effect in determining whether a pathogen can become epidemic or persist at endemic levels. Epidemic models that determine which interventions can successfully prevent an outbreak need to account for social structure and mixing patterns. Contact patterns vary across age and locations (e.g. home, work, and school), and including them as predictors in transmission dynamic models of pathogens that spread socially will improve the models realism. Data from population-based contact diaries in eight European countries from the POLYMOD study were projected to 144 other countries using a Bayesian hierarchical model that estimated the proclivity of age-and-location-specific contact patterns for the countries, using Markov chain Monte Carlo simulation. Household level data from the Demographic and Health Surveys for nine lower-income countries and socio-demographic factors from several on-line databases for 152 countries were used to quantify similarity of countries to estimate contact patterns in the home, work, school and other locations for countries for which no contact data are available, accounting for demographic structure, household structure where known, and a variety of metrics including workforce participation and school enrolment. Contacts are highly assortative with age across all countries considered, but pronounced regional differences in the age-specific contacts at home were noticeable, with more inter-generational contacts in Asian countries than in other settings. Moreover, there were variations in contact patterns by location, with work-place contacts being least assortative. These variations led to differences in the effect of social distancing measures in an age structured epidemic model. Contacts have an important role in transmission dynamic models that use contact rates to characterize the spread of contact-transmissible diseases. This study provides estimates of mixing patterns for societies for which contact data such as POLYMOD are not yet available.'),
(88631, 2017, 'plos', 'Analysis of the relationship between coexpression domains and chromatin 3D organization', 'Soler-Oliva, María E|Guerrero-Martínez, José A|Bachetti, Valentina|Reyes, José C', 'Centro Andaluz de Biología Molecular y Medicina Regenerativa-CABIMER, Consejo Superior de Investigaciones Científicas-Universidad de Sevilla-Universidad Pablo de Olavide (CSIC-USE-UPO), Sevilla, Spain.|Centro Andaluz de Biología Molecular y Medicina Regenerativa-CABIMER, Consejo Superior de Investigaciones Científicas-Universidad de Sevilla-Universidad Pablo de Olavide (CSIC-USE-UPO), Sevilla, Spain.|Centro Andaluz de Biología Molecular y Medicina Regenerativa-CABIMER, Consejo Superior de Investigaciones Científicas-Universidad de Sevilla-Universidad Pablo de Olavide (CSIC-USE-UPO), Sevilla, Spain.|Centro Andaluz de Biología Molecular y Medicina Regenerativa-CABIMER, Consejo Superior de Investigaciones Científicas-Universidad de Sevilla-Universidad Pablo de Olavide (CSIC-USE-UPO), Sevilla, Spain.', 'Spain|Spain|Spain|Spain', 6, 'Breast|Breast Neoplasms|Chromatin|Chromatin Assembly and Disassembly|Cluster Analysis|Computational Biology|Female|Gene Expression Profiling|Gene Expression Regulation|Gene Regulatory Networks|Genome|Humans', 'Journal Article', '10.1371/journal.pcbi.1005708', '28902867', 'Gene order is not random in eukaryotic chromosomes, and co-regulated genes tend to be clustered. The mechanisms that determine co-regulation of large regions of the genome and its connection with chromatin three-dimensional (3D) organization are still unclear however. Here we have adapted a recently described method for identifying chromatin topologically associating domains (TADs) to identify coexpression domains (which we term CODs). Using human normal breast and breast cancer RNA-seq data, we have identified approximately 500 CODs. CODs in the normal and breast cancer genomes share similar characteristics but differ in their gene composition. COD genes have a greater tendency to be coexpressed with genes that reside in other CODs than with non-COD genes. Such inter-COD coexpression is maintained over large chromosomal distances in the normal genome but is partially lost in the cancer genome. Analyzing the relationship between CODs and chromatin 3D organization using Hi-C contact data, we find that CODs do not correspond to TADs. In fact, intra-TAD gene coexpression is the same as random for most chromosomes. However, the contact profile is similar between gene pairs that reside either in the same COD or in coexpressed CODs. These data indicate that co-regulated genes in the genome present similar patterns of contacts irrespective of the frequency of physical chromatin contacts between them.'),
(88632, 2017, 'plos', 'The eBioKit, a stand-alone educational platform for bioinformatics', 'Hernández-de-Diego, Rafael|de Villiers, Etienne P|Klingström, Tomas|Gourlé, Hadrien|Conesa, Ana|Bongcam-Rudloff, Erik', 'SLU-Global Bioinformatics Centre, Department of Animal Breeding and Genetics, Swedish University of Agricultural Sciences, Uppsala, Sweden.|International Livestock Research Institute (ILRI), Nairobi, Kenya.|SLU-Global Bioinformatics Centre, Department of Animal Breeding and Genetics, Swedish University of Agricultural Sciences, Uppsala, Sweden.|SLU-Global Bioinformatics Centre, Department of Animal Breeding and Genetics, Swedish University of Agricultural Sciences, Uppsala, Sweden.|Genomics of Gene Expression Lab, Centro de Investigación Príncipe Felipe, Valencia, Spain.|SLU-Global Bioinformatics Centre, Department of Animal Breeding and Genetics, Swedish University of Agricultural Sciences, Uppsala, Sweden.', 'Sweden|Kenya|Sweden|Sweden|Spain|Sweden', 0, 'Africa|Biomedical Research|Computational Biology|Computers|Developing Countries|Humans|Software|User-Computer Interface', 'Journal Article', '10.1371/journal.pcbi.1005616', '28910280', 'Bioinformatics skills have become essential for many research areas, however, the availability of qualified researchers is usually lower than the demand and training to increase the number of able bioinformaticians is an important task for the bioinformatics community. When conducting training or hands-on tutorials, the lack of control over the analysis tools and repositories often results in undesirable situations during training, as unavailable online tools or version conflicts may delay, complicate, or even prevent the successful completion of a training event. The eBioKit is a stand-alone educational platform that hosts numerous tools and databases for bioinformatics research and allows training to take place in a controlled environment. A key advantage of the eBioKit over other existing teaching solutions is that all the required software and databases are locally installed on the system, significantly reducing the dependence on the internet. Furthermore, the architecture of the eBioKit has demonstrated itself to be an excellent balance between portability and performance, not only making the eBioKit an exceptional educational tool but also providing small research groups with a platform to incorporate bioinformatics analysis in their research. As a result, the eBioKit has formed an integral part of training and research performed by a wide variety of universities and organizations such as the Pan African Bioinformatics Network (H3ABioNet) as part of the initiative Human Heredity and Health in Africa (H3Africa), the Southern Africa Network for Biosciences (SAnBio) initiative, the Biosciences eastern and central Africa (BecA) hub, and the International Glossina Genome Initiative.'),
(88633, 2017, 'plos', 'Stochastic principles governing alternative splicing of RNA', 'Hu, Jianfei|Boritz, Eli|Wylie, William|Douek, Daniel C', 'Genome Analysis Core, Vaccine Research Center, National Institute of Allergy and Infectious Diseases, National Institutes of Health, Bethesda, Maryland, United States of America.|Human Immunology Section, Vaccine Research Center, National Institute of Allergy and Infectious Diseases, National Institutes of Health, Bethesda, Maryland, United States of America.|Human Immunology Section, Vaccine Research Center, National Institute of Allergy and Infectious Diseases, National Institutes of Health, Bethesda, Maryland, United States of America.|Genome Analysis Core, Vaccine Research Center, National Institute of Allergy and Infectious Diseases, National Institutes of Health, Bethesda, Maryland, United States of America.', 'United States|United States|United States|United States', 8, 'Alternative Splicing|Cells, Cultured|Computer Simulation|Gene Expression Regulation|Humans|Models, Genetic|Models, Statistical|RNA|RNA Splice Sites|Stochastic Processes|T-Lymphocytes|Transcription Factors', 'Journal Article', '10.1371/journal.pcbi.1005761', '28910283', 'The dominance of the major transcript isoform relative to other isoforms from the same gene generated by alternative splicing (AS) is essential to the maintenance of normal cellular physiology. However, the underlying principles that determine such dominance remain unknown. Here, we analyzed the physical AS process and found that it can be modeled by a stochastic minimization process, which causes the scaled expression levels of all transcript isoforms to follow the same Weibull extreme value distribution. Surprisingly, we also found a simple equation to describe the median frequency of transcript isoforms of different dominance. This two-parameter Weibull model provides the statistical distribution of all isoforms of all transcribed genes, and reveals that previously unexplained observations concerning relative isoform expression derive from these principles.'),
(88634, 2017, 'plos', 'Modeling antibiotic treatment in hospitals: A systematic approach shows benefits of combination therapy over cycling, mixing, and mono-drug therapies', 'Tepekule, Burcu|Uecker, Hildegard|Derungs, Isabel|Frenoy, Antoine|Bonhoeffer, Sebastian', 'Institute of Integrative Biology, ETH Zurich, Zurich, Switzerland.|Institute of Integrative Biology, ETH Zurich, Zurich, Switzerland.|Institute of Integrative Biology, ETH Zurich, Zurich, Switzerland.|Institute of Integrative Biology, ETH Zurich, Zurich, Switzerland.|Institute of Integrative Biology, ETH Zurich, Zurich, Switzerland.', 'Switzerland|Switzerland|Switzerland|Switzerland|Switzerland', 10, 'Anti-Bacterial Agents|Bacteria|Bacterial Infections|Computational Biology|Discriminant Analysis|Drug Resistance, Bacterial|Drug Therapy, Combination|Hospitals|Humans|Models, Biological', 'Journal Article', '10.1371/journal.pcbi.1005745', '28915236', 'Multiple treatment strategies are available for empiric antibiotic therapy in hospitals, but neither clinical studies nor theoretical investigations have yielded a clear picture when which strategy is optimal and why. Extending earlier work of others and us, we present a mathematical model capturing treatment strategies using two drugs, i.e the multi-drug therapies referred to as cycling, mixing, and combination therapy, as well as monotherapy with either drug. We randomly sample a large parameter space to determine the conditions determining success or failure of these strategies. We find that combination therapy tends to outperform the other treatment strategies. By using linear discriminant analysis and particle swarm optimization, we find that the most important parameters determining success or failure of combination therapy relative to the other treatment strategies are the de novo rate of emergence of double resistance in patients infected with sensitive bacteria and the fitness costs associated with double resistance. The rate at which double resistance is imported into the hospital via patients admitted from the outside community has little influence, as all treatment strategies are affected equally. The parameter sets for which combination therapy fails tend to fall into areas with low biological plausibility as they are characterised by very high rates of de novo emergence of resistance to both drugs compared to a single drug, and the cost of double resistance is considerably smaller than the sum of the costs of single resistance.'),
(88635, 2017, 'plos', 'Synthesizing developmental trajectories', 'Villoutreix, Paul|Andén, Joakim|Lim, Bomyi|Lu, Hang|Kevrekidis, Ioannis G|Singer, Amit|Shvartsman, Stanislav Y', 'Lewis-Sigler Institute for Integrative Genomics, Princeton University, Princeton, New Jersey, United States of America.|Program in Applied and Computational Mathematics, Princeton University, Princeton, New Jersey, United States of America.|Lewis-Sigler Institute for Integrative Genomics, Princeton University, Princeton, New Jersey, United States of America.|School of Chemical and Biomolecular Engineering, Georgia Institute of Technology, Atlanta, Georgia, United States of America.|Program in Applied and Computational Mathematics, Princeton University, Princeton, New Jersey, United States of America.|Program in Applied and Computational Mathematics, Princeton University, Princeton, New Jersey, United States of America.|Lewis-Sigler Institute for Integrative Genomics, Princeton University, Princeton, New Jersey, United States of America.', 'Jersey|Jersey|Jersey|Georgia|Jersey|Jersey|Jersey', 0, 'Animals|Body Patterning|Computational Biology|Drosophila|Image Processing, Computer-Assisted|Microscopy, Confocal|Models, Biological|Supervised Machine Learning', 'Journal Article', '10.1371/journal.pcbi.1005742', '28922353', 'Dynamical processes in biology are studied using an ever-increasing number of techniques, each of which brings out unique features of the system. One of the current challenges is to develop systematic approaches for fusing heterogeneous datasets into an integrated view of multivariable dynamics. We demonstrate that heterogeneous data fusion can be successfully implemented within a semi-supervised learning framework that exploits the intrinsic geometry of high-dimensional datasets. We illustrate our approach using a dataset from studies of pattern formation in Drosophila. The result is a continuous trajectory that reveals the joint dynamics of gene expression, subcellular protein localization, protein phosphorylation, and tissue morphogenesis. Our approach can be readily adapted to other imaging modalities and forms a starting point for further steps of data analytics and modeling of biological dynamics.'),
(88636, 2017, 'plos', 'Reconstructing promoter activity from Lux bioluminescent reporters', 'Iqbal, Mudassar|Doherty, Neil|Page, Anna M L|Qazi, Saara N A|Ajmera, Ishan|Lund, Peter A|Kypraios, Theodore|Scott, David J|Hill, Philip J|Stekel, Dov J', 'Agricultural and Environmental Sciences, School of Biosciences, University of Nottingham, Sutton Bonington Campus, Loughborough, United Kingdom.|Food Sciences, School of Biosciences, University of Nottingham, Sutton Bonington Campus, Loughborough, United Kingdom.|Food Sciences, School of Biosciences, University of Nottingham, Sutton Bonington Campus, Loughborough, United Kingdom.|Food Sciences, School of Biosciences, University of Nottingham, Sutton Bonington Campus, Loughborough, United Kingdom.|Plant and Crop Sciences, School of Biosciences, University of Nottingham, Sutton Bonington Campus, Loughborough, United Kingdom.|School of Biosciences, University of Birmingham, Birmingham, United Kingdom.|School of Mathematical Sciences, University of Nottingham, Nottingham, United Kingdom.|Food Sciences, School of Biosciences, University of Nottingham, Sutton Bonington Campus, Loughborough, United Kingdom.|Food Sciences, School of Biosciences, University of Nottingham, Sutton Bonington Campus, Loughborough, United Kingdom.|Agricultural and Environmental Sciences, School of Biosciences, University of Nottingham, Sutton Bonington Campus, Loughborough, United Kingdom.', 'United Kingdom|United Kingdom|United Kingdom|United Kingdom|United Kingdom|United Kingdom|United Kin', 4, 'Bacterial Proteins|Computational Biology|Escherichia coli|Gene Expression|Genes, Reporter|Luciferases|Luminescent Agents|Nonlinear Dynamics|Promoter Regions, Genetic|Spectrometry, Fluorescence', 'Journal Article', '10.1371/journal.pcbi.1005731', '28922354', 'The bacterial Lux system is used as a gene expression reporter. It is fast, sensitive and non-destructive, enabling high frequency measurements. Originally developed for bacterial cells, it has also been adapted for eukaryotic cells, and can be used for whole cell biosensors, or in real time with live animals without the need for euthanasia. However, correct interpretation of bioluminescent data is limited: the bioluminescence is different from gene expression because of nonlinear molecular and enzyme dynamics of the Lux system. We have developed a computational approach that, for the first time, allows users of Lux assays to infer gene transcription levels from the light output. This approach is based upon a new mathematical model for Lux activity, that includes the actions of LuxAB, LuxEC and Fre, with improved mechanisms for all reactions, as well as synthesis and turn-over of Lux proteins. The model is calibrated with new experimental data for the LuxAB and Fre reactions from Photorhabdus luminescens-the source of modern Lux reporters-while literature data has been used for LuxEC. Importantly, the data show clear evidence for previously unreported product inhibition for the LuxAB reaction. Model simulations show that predicted bioluminescent profiles can be very different from changes in gene expression, with transient peaks of light output, very similar to light output seen in some experimental data sets. By incorporating the calibrated model into a Bayesian inference scheme, we can reverse engineer promoter activity from the bioluminescence. We show examples where a decrease in bioluminescence would be better interpreted as a switching off of the promoter, or where an increase in bioluminescence would be better interpreted as a longer period of gene expression. This approach could benefit all users of Lux technology.'),
(88637, 2017, 'plos', 'Mathematical modeling and quantitative analysis of HIV-1 Gag trafficking and polymerization', 'Liu, Yuewu|Zou, Xiufen', 'School of Mathematics and Statistics, Wuhan University, Computational Science Hubei Key Laboratory, Wuhan University, Wuhan, China.|School of Mathematics and Statistics, Wuhan University, Computational Science Hubei Key Laboratory, Wuhan University, Wuhan, China.', 'China|China', 3, 'Computational Biology|HIV Infections|HIV-1|Host-Pathogen Interactions|Humans|Models, Biological|Polymerization|Protein Transport|Virus Assembly|gag Gene Products, Human Immunodeficiency Virus', 'Journal Article', '10.1371/journal.pcbi.1005733', '28922356', 'Gag, as the major structural protein of HIV-1, is necessary for the assembly of the HIV-1 sphere shell. An in-depth understanding of its trafficking and polymerization is important for gaining further insights into the mechanisms of HIV-1 replication and the design of antiviral drugs. We developed a mathematical model to simulate two biophysical processes, specifically Gag monomer and dimer transport in the cytoplasm and the polymerization of monomers to form a hexamer underneath the plasma membrane. Using experimental data, an optimization approach was utilized to identify the model parameters, and the identifiability and sensitivity of these parameters were then analyzed. Using our model, we analyzed the weight of the pathways involved in the polymerization reactions and concluded that the predominant pathways for the formation of a hexamer might be the polymerization of two monomers to form a dimer, the polymerization of a dimer and a monomer to form a trimer, and the polymerization of two trimers to form a hexamer. We then deduced that the dimer and trimer intermediates might be crucial in hexamer formation. We also explored four theoretical combined methods for Gag suppression, and hypothesized that the N-terminal glycine residue of the MA domain of Gag might be a promising drug target. This work serves as a guide for future theoretical and experimental efforts aiming to understand HIV-1 Gag trafficking and polymerization, and might help accelerate the efficiency of anti-AIDS drug design.'),
(88638, 2017, 'plos', 'Quantifying the effects of antiangiogenic and chemotherapy drug combinations on drug delivery and treatment efficacy', 'Yonucu, Sirin|Yxcexb9lmaz, Defne|Phipps, Colin|Unlu, Mehmet Burcin|Kohandel, Mohammad', 'Department of Physics, Bogazici University, Bebek, Istanbul, Turkey.|Department of Physics, Bogazici University, Bebek, Istanbul, Turkey.|School of Pharmacy, University of Waterloo, Waterloo, Ontario, Canada.|Department of Physics, Bogazici University, Bebek, Istanbul, Turkey.|Department of Applied Mathematics, University of Waterloo, Waterloo, Ontario, Canada.', 'Turkey|Turkey|Canada|Turkey|Canada', 4, 'Antineoplastic Combined Chemotherapy Protocols|Computer Simulation|Dose-Response Relationship, Drug|Drug Therapy, Computer-Assisted|Humans|Models, Biological|Neoplasms|Neovascularization, Pathologic|Treatment Outcome|Tumor Burden', 'Journal Article', '10.1371/journal.pcbi.1005724', '28922358', 'Tumor-induced angiogenesis leads to the development of leaky tumor vessels devoid of structural and morphological integrity. Due to angiogenesis, elevated interstitial fluid pressure (IFP) and low blood perfusion emerge as common properties of the tumor microenvironment that act as barriers for drug delivery. In order to overcome these barriers, normalization of vasculature is considered to be a viable option. However, insight is needed into the phenomenon of normalization and in which conditions it can realize its promise. In order to explore the effect of microenvironmental conditions and drug scheduling on normalization benefit, we build a mathematical model that incorporates tumor growth, angiogenesis and IFP. We administer various theoretical combinations of antiangiogenic agents and cytotoxic nanoparticles through heterogeneous vasculature that displays a similar morphology to tumor vasculature. We observe differences in drug extravasation that depend on the scheduling of combined therapy, for concurrent therapy, total drug extravasation is increased but in adjuvant therapy, drugs can penetrate into deeper regions of tumor.'),
(88639, 2017, 'plos', 'C-reactive protein upregulates the whole blood expression of CD59 - an integrative analysis', 'Lepik, Kaido|Annilo, Tarmo|Kukuškina, Viktorija|eQTLGen Consortium|Kisand, Kai|Kutalik, Zoltán|Peterson, Pärt|Peterson, Hedi', 'Institute of Computer Science, University of Tartu, Tartu, Estonia.|Estonian Genome Center, University of Tartu, Tartu, Estonia.|Estonian Genome Center, University of Tartu, Tartu, Estonia.|Estonian Genome Center, University of Tartu, Tartu, Estonia.|Molecular Pathology, Institute of Biomedical and Translational Medicine, University of Tartu, Tartu, Estonia.|Institute of Social and Preventive Medicine, Lausanne University Hospital, Lausanne, Switzerland.|Molecular Pathology, Institute of Biomedical and Translational Medicine, University of Tartu, Tartu, Estonia.|Institute of Computer Science, University of Tartu, Tartu, Estonia.', 'Estonia|Estonia|Estonia|Estonia|Estonia|Switzerland|Estonia|Estonia', 0, 'Adult|C-Reactive Protein|CD59 Antigens|Cohort Studies|Estonia|Humans|Inflammation|Up-Regulation', 'Journal Article', '10.1371/journal.pcbi.1005766', '28922377', 'Elevated C-reactive protein (CRP) concentrations in the blood are associated with acute and chronic infections and inflammation. Nevertheless, the functional role of increased CRP in multiple bacterial and viral infections as well as in chronic inflammatory diseases remains unclear. Here, we studied the relationship between CRP and gene expression levels in the blood in 491 individuals from the Estonian Biobank cohort, to elucidate the role of CRP in these inflammatory mechanisms. As a result, we identified a set of 1,614 genes associated with changes in CRP levels with a high proportion of interferon-stimulated genes. Further, we performed likelihood-based causality model selection and Mendelian randomization analysis to discover causal links between CRP and the expression of CRP-associated genes. Strikingly, our computational analysis and cell culture stimulation assays revealed increased CRP levels to drive the expression of complement regulatory protein CD59, suggesting CRP to have a critical role in protecting blood cells from the adverse effects of the immune defence system. Our results show the benefit of integrative analysis approaches in hypothesis-free uncovering of causal relationships between traits.'),
(88640, 2017, 'plos', 'Sequence features of viral and human Internal Ribosome Entry Sites predictive of their activity', 'Gritsenko, Alexey A|Weingarten-Gabbay, Shira|Elias-Kirma, Shani|Nir, Ronit|de Ridder, Dick|Segal, Eran', 'The Delft Bioinformatics Laboratory, Department of Intelligent Systems, Delft University of Technology, Delft, The Netherlands.|Department of Computer Science and Applied Mathematics, Weizmann Institute of Science, Rehovot, Israel.|Department of Computer Science and Applied Mathematics, Weizmann Institute of Science, Rehovot, Israel.|Department of Computer Science and Applied Mathematics, Weizmann Institute of Science, Rehovot, Israel.|The Delft Bioinformatics Laboratory, Department of Intelligent Systems, Delft University of Technology, Delft, The Netherlands.|Department of Computer Science and Applied Mathematics, Weizmann Institute of Science, Rehovot, Israel.', 'Netherlands|Israel|Israel|Israel|Netherlands|Israel', 11, 'Databases, Genetic|Decision Trees|Genome, Human|Genome, Viral|Genomics|High-Throughput Nucleotide Sequencing|Humans|Internal Ribosome Entry Sites|Machine Learning|RNA, Messenger|RNA, Viral', 'Journal Article', '10.1371/journal.pcbi.1005734', '28922394', 'Translation of mRNAs through Internal Ribosome Entry Sites (IRESs) has emerged as a prominent mechanism of cellular and viral initiation. It supports cap-independent translation of select cellular genes under normal conditions, and in conditions when cap-dependent translation is inhibited. IRES structure and sequence are believed to be involved in this process. However due to the small number of IRESs known, there have been no systematic investigations of the determinants of IRES activity. With the recent discovery of thousands of novel IRESs in human and viruses, the next challenge is to decipher the sequence determinants of IRES activity. We present the first in-depth computational analysis of a large body of IRESs, exploring RNA sequence features predictive of IRES activity. We identified predictive k-mer features resembling IRES trans-acting factor (ITAF) binding motifs across human and viral IRESs, and found that their effect on expression depends on their sequence, number and position. Our results also suggest that the architecture of retroviral IRESs differs from that of other viruses, presumably due to their exposure to the nuclear environment. Finally, we measured IRES activity of synthetically designed sequences to confirm our prediction of increasing activity as a function of the number of short IRES elements.');
INSERT INTO `papers` (`id`, `ano`, `journal`, `titulo`, `autores`, `afiliacao`, `pais`, `citacoes`, `palavra_chave`, `categorias`, `doi`, `pubmed`, `abstract`) VALUES
(88641, 2017, 'plos', 'Probing eukaryotic cell mechanics via mesoscopic simulations', 'Lykov, Kirill|Nematbakhsh, Yasaman|Shang, Menglin|Lim, Chwee Teck|Pivkin, Igor V', 'Institute of Computational Science, Faculty of Informatics, USI Lugano, Lugano, Switzerland.|NUS Graduate School for Integrative Sciences and Engineering, National University of Singapore, Singapore, Singapore.|BioSystems and Micromechanics (BioSyM) IRG, Singapore-MIT Alliance for Research and Technology (SMART) Centre, Singapore, Singapore.|NUS Graduate School for Integrative Sciences and Engineering, National University of Singapore, Singapore, Singapore.|Institute of Computational Science, Faculty of Informatics, USI Lugano, Lugano, Switzerland.', 'Switzerland|Singapore|Singapore|Singapore|Switzerland', 0, 'Biomechanical Phenomena|Cell Line|Cell Membrane|Cell Nucleus|Computational Biology|Cytoskeleton|Elasticity|Epithelial Cells|Humans|Microfluidics|Micromanipulation|Models, Biological|Viscosity', 'Journal Article', '10.1371/journal.pcbi.1005726', '28922399', 'Cell mechanics has proven to be important in many biological processes. Although there is a number of experimental techniques which allow us to study mechanical properties of cell, there is still a lack of understanding of the role each sub-cellular component plays during cell deformations. We present a new mesoscopic particle-based eukaryotic cell model which explicitly describes cell membrane, nucleus and cytoskeleton. We employ Dissipative Particle Dynamics (DPD) method that provides us with the unified framework for modeling of a cell and its interactions in the flow. Data from micropipette aspiration experiments were used to define model parameters. The model was validated using data from microfluidic experiments. The validated model was then applied to study the impact of the sub-cellular components on the cell viscoelastic response in micropipette aspiration and microfluidic experiments.'),
(88642, 2017, 'plos', 'Probabilistic models for neural populations that naturally capture global coupling and criticality', 'Humplik, Jan|Tkaxc4x8dik, Gaxc5xa1per', 'Institute of Science and Technology Austria, Klosterneuburg, Austria.|Institute of Science and Technology Austria, Klosterneuburg, Austria.', 'Austria|Austria', 12, 'Animals|Computational Biology|Models, Neurological|Models, Statistical|Neurons|Retinal Neurons|Thermodynamics|Urodela', 'Journal Article', '10.1371/journal.pcbi.1005763', '28926564', 'Advances in multi-unit recordings pave the way for statistical modeling of activity patterns in large neural populations. Recent studies have shown that the summed activity of all neurons strongly shapes the population response. A separate recent finding has been that neural populations also exhibit criticality, an anomalously large dynamic range for the probabilities of different population activity patterns. Motivated by these two observations, we introduce a class of probabilistic models which takes into account the prior knowledge that the neural population could be globally coupled and close to critical. These models consist of an energy function which parametrizes interactions between small groups of neurons, and an arbitrary positive, strictly increasing, and twice differentiable function which maps the energy of a population pattern to its probability. We show that: 1) augmenting a pairwise Ising model with a nonlinearity yields an accurate description of the activity of retinal ganglion cells which outperforms previous models based on the summed activity of neurons, 2) prior knowledge that the population is critical translates to prior expectations about the shape of the nonlinearity, 3) the nonlinearity admits an interpretation in terms of a continuous latent variable globally coupling the system whose distribution we can infer from data. Our method is independent of the underlying systems state space, hence, it can be applied to other systems such as natural scenes or amino acid sequences of proteins which are also known to exhibit criticality.'),
(88643, 2017, 'plos', 'Correction: lumpGEM: Systematic generation of subnetworks and elementally balanced lumped reactions for the biosynthesis of target metabolites', 'PLOS Computational Biology Staff', 'Institute of Science and Technology Austria, Klosterneuburg, Austria.', 'Austria', 0, '-', 'Published Erratum', '10.1371/journal.pcbi.1005764', '28926574', '[This corrects the article DOI: 10.1371/journal.pcbi.1005513.].'),
(88644, 2017, 'plos', 'The logic of the floral transition: Reverse-engineering the switch controlling the identity of lateral organs', 'Dinh, Jean-Louis|Farcot, Etienne|Hodgman, Charlie', 'Centre for Plant Integrative Biology, School of Biosciences, University of Nottingham, Sutton Bonington, United Kingdom.|Centre for Plant Integrative Biology, School of Biosciences, University of Nottingham, Sutton Bonington, United Kingdom.|Centre for Plant Integrative Biology, School of Biosciences, University of Nottingham, Sutton Bonington, United Kingdom.', 'United Kingdom|United Kingdom|United Kingdom', 4, 'Algorithms|Computational Biology|Flowers|Gene Expression Profiling|Gene Expression Regulation, Plant|Gene Regulatory Networks|Genetic Engineering|Models, Biological|Plant Development|Plant Leaves', 'Journal Article', '10.1371/journal.pcbi.1005744', '28931004', 'Much laboratory work has been carried out to determine the gene regulatory network (GRN) that results in plant cells becoming flowers instead of leaves. However, this also involves the spatial distribution of different cell types, and poses the question of whether alternative networks could produce the same set of observed results. This issue has been addressed here through a survey of the published intercellular distribution of expressed regulatory genes and techniques both developed and applied to Boolean network models. This has uncovered a large number of models which are compatible with the currently available data. An exhaustive exploration had some success but proved to be unfeasible due to the massive number of alternative models, so genetic programming algorithms have also been employed. This approach allows exploration on the basis of both data-fitting criteria and parsimony of the regulatory processes, ruling out biologically unrealistic mechanisms. One of the conclusions is that, despite the multiplicity of acceptable models, an overall structure dominates, with differences mostly in alternative fine-grained regulatory interactions. The overall structure confirms the known interactions, including some that were not present in the training set, showing that current data are sufficient to determine the overall structure of the GRN. The model stresses the importance of relative spatial location, through explicit references to this aspect. This approach also provides a quantitative indication of how likely some regulatory interactions might be, and can be applied to the study of other developmental transitions.'),
(88645, 2017, 'plos', 'Correction: Dose-response relationships for environmentally mediated infectious disease transmission models', 'PLOS Computational Biology Staff', 'Centre for Plant Integrative Biology, School of Biosciences, University of Nottingham, Sutton Bonington, United Kingdom.', 'United Kingdom', 0, '-', 'Published Erratum', '10.1371/journal.pcbi.1005765', '28931005', '[This corrects the article DOI: 10.1371/journal.pcbi.1005481.].'),
(88646, 2017, 'plos', 'Spatiotemporal network coding of physiological mossy fiber inputs by the cerebellar granular layer', 'Sudhakar, Shyam Kumar|Hong, Sungho|Raikov, Ivan|Publio, Rodrigo|Lang, Claus|Close, Thomas|Guo, Daqing|Negrello, Mario|De Schutter, Erik', 'Computational Neuroscience Unit, Okinawa Institute of Science and Technology, Onna-son, Okinawa, Japan.|Computational Neuroscience Unit, Okinawa Institute of Science and Technology, Onna-son, Okinawa, Japan.|Computational Neuroscience Unit, Okinawa Institute of Science and Technology, Onna-son, Okinawa, Japan.|Computational Neuroscience Unit, Okinawa Institute of Science and Technology, Onna-son, Okinawa, Japan.|Computational Neuroscience Unit, Okinawa Institute of Science and Technology, Onna-son, Okinawa, Japan.|Computational Neuroscience Unit, Okinawa Institute of Science and Technology, Onna-son, Okinawa, Japan.|Computational Neuroscience Unit, Okinawa Institute of Science and Technology, Onna-son, Okinawa, Japan.|Computational Neuroscience Unit, Okinawa Institute of Science and Technology, Onna-son, Okinawa, Japan.|Computational Neuroscience Unit, Okinawa Institute of Science and Technology, Onna-son, Okinawa, Japan.', 'Japan|Japan|Japan|Japan|Japan|Japan|Japan|Japan|Japan', 0, 'Action Potentials|Biological Clocks|Cerebellar Cortex|Computer Simulation|Humans|Models, Neurological|Nerve Fibers|Nerve Net|Spatio-Temporal Analysis|Synaptic Transmission', 'Journal Article', '10.1371/journal.pcbi.1005754', '28934196', 'The granular layer, which mainly consists of granule and Golgi cells, is the first stage of the cerebellar cortex and processes spatiotemporal information transmitted by mossy fiber inputs with a wide variety of firing patterns. To study its dynamics at multiple time scales in response to inputs approximating real spatiotemporal patterns, we constructed a large-scale 3D network model of the granular layer. Patterned mossy fiber activity induces rhythmic Golgi cell activity that is synchronized by shared parallel fiber input and by gap junctions. This leads to long distance synchrony of Golgi cells along the transverse axis, powerfully regulating granule cell firing by imposing inhibition during a specific time window. The essential network mechanisms, including tunable Golgi cell oscillations, on-beam inhibition and NMDA receptors causing first winner keeps winning of granule cells, illustrate how fundamental properties of the granule layer operate in tandem to produce (1) well timed and spatially bound output, (2) a wide dynamic range of granule cell firing and (3) transient and coherent gating oscillations. These results substantially enrich our understanding of granule cell layer processing, which seems to promote spatial group selection of granule cell activity as a function of timing of mossy fiber input.'),
(88647, 2017, 'plos', 'Ten simple rules for successfully completing a graduate degree in Latin America', 'Ruelas Inzunza, Ernesto|Salazar-Rivera, Gabriela I|Láinez, Magdiel|Ruiz-Gómez, María Guadalupe|Domínguez-Eusebio, Carlo A|Cristóbal-Sánchez, Griselda|Teodosio Faustino, Issaac A|Pérez-López, Edel|Campbell, Meagan L|Merfa, Marcus Vinicius|Latorre Beltrán, Ivonne Tatiana|Armas, Fernanda|Mota-Vargas, Claudio', 'Instituto de Biotecnología y Ecología Aplicada, Universidad Veracruzana, Xalapa, Veracruz, Mexico.|Instituto de Biotecnología y Ecología Aplicada, Universidad Veracruzana, Xalapa, Veracruz, Mexico.|Instituto de Biotecnología y Ecología Aplicada, Universidad Veracruzana, Xalapa, Veracruz, Mexico.|Instituto de Biotecnología y Ecología Aplicada, Universidad Veracruzana, Xalapa, Veracruz, Mexico.|Instituto de Biotecnología y Ecología Aplicada, Universidad Veracruzana, Xalapa, Veracruz, Mexico.|Universidad Veracruzana, Centro de Investigaciones Tropicales, Xalapa, Veracruz, Mexico.|Facultad de Biología, Universidad Veracruzana, Xalapa, Veracruz, Mexico.|Department of Entomology and Plant Pathology, Auburn University, Auburn, Alabama, United States.|Instituto de Biotecnología y Ecología Aplicada, Universidad Veracruzana, Xalapa, Veracruz, Mexico.|Department of Entomology and Plant Pathology, Auburn University, Auburn, Alabama, United States.|Independent researcher, Bogotá, Colombia.|Instituto de Ecología A.C., Xalapa, Veracruz, Mexico.|Instituto de Ecología A.C., Xalapa, Veracruz, Mexico.', 'Mexico|Mexico|Mexico|Mexico|Mexico|Mexico|Mexico|United States|Mexico|United States|Colombia|Mexico|', 0, 'Algorithms|Computational Biology|Education, Graduate|Education, Professional|Educational Status|Latin America', 'Editorial', '10.1371/journal.pcbi.1005682', '28934200', '-'),
(88648, 2017, 'plos', 'How can computation advance microbiome research?', 'Nussinov, Ruth|Papin, Jason A', 'National Cancer Institute, Frederick, Maryland, United States of America.|University of Virginia, Charlottesville, Virginia, United States of America.', 'United States|United States', 2, 'Biological Science Disciplines|Computational Biology|Microbiology|Microbiota', 'Editorial', '10.1371/journal.pcbi.1005547', '28934204', '-'),
(88649, 2017, 'plos', 'Ten simple rules for developing a mentor-mentee expectations document', 'Masters, Kristyn S|Kreeger, Pamela K', 'Department of Biomedical Engineering, University of Wisconsin-Madison, Madison, WI, United States of America.|Department of Biomedical Engineering, University of Wisconsin-Madison, Madison, WI, United States of America.', 'United States|United States', 7, 'Algorithms|Communication|Contracts|Documentation|Interprofessional Relations|Mentors|Science', 'Editorial', '10.1371/journal.pcbi.1005709', '28934208', '-'),
(88650, 2017, 'plos', 'Phase changes in neuronal postsynaptic spiking due to short term plasticity', 'McDonnell, Mark D|Graham, Bruce P', 'Computational Learning Systems Laboratory, School of Information Technology and Mathematical Sciences, University of South Australia, Mawson Lakes, Australia.|Computing Science & Mathematics, Faculty of Natural Sciences, University of Stirling, Stirling, United Kingdom.', 'Australia|United Kingdom', 0, 'Action Potentials|Animals|Computational Biology|Models, Neurological|Neuronal Plasticity', 'Journal Article', '10.1371/journal.pcbi.1005634', '28937977', 'In the brain, the postsynaptic response of a neuron to time-varying inputs is determined by the interaction of presynaptic spike times with the short-term dynamics of each synapse. For a neuron driven by stochastic synapses, synaptic depression results in a quite different postsynaptic response to a large population input depending on how correlated in time the spikes across individual synapses are. Here we show using both simulations and mathematical analysis that not only the rate but the phase of the postsynaptic response to a rhythmic population input varies as a function of synaptic dynamics and synaptic configuration. Resultant phase leads may compensate for transmission delays and be predictive of rhythmic changes. This could be particularly important for sensory processing and motor rhythm generation in the nervous system.'),
(88651, 2017, 'plos', 'Limited synapse overproduction can speed development but sometimes with long-term energy and discrimination penalties', 'Ju, Harang|Colbert, Costa M|Levy, William B', 'Informed Simplifications LLC., Earlysville, Virginia, United States of America.|Mad Street Den Inc., Fremont, California, United States of America.|Department of Neurosurgery, University of Virginia, Charlottesville, Virginia, United States of America.', 'United States|United States|United States', 3, 'Computational Biology|Computer Simulation|Models, Neurological|Nerve Net|Neurons|Synapses', 'Journal Article', '10.1371/journal.pcbi.1005750', '28937989', 'Neural circuit development requires that synapses be formed between appropriate neurons. In addition, for a hierarchical network, successful development involves a sequencing of developmental events. It has been suggested that one mechanism that helps speed up development of proper connections is an early overproduction of synapses. Using a computational model of synapse development, such as adaptive synaptogenesis, it is possible to study such overproduction and its role in speeding up development, it is also possible to study other outcomes of synapse overproduction that are seemingly new to the literature. With a fixed number of neurons, adaptive synaptogenesis can control the speed of synaptic development in two ways: by altering the rate constants of the adaptive processes or by altering the initial number of rapidly but non-selectively accrued synapses. Using either mechanism, the simulations reveal that synapse overproduction appears as an unavoidable concomitant of rapid adaptive synaptogenesis. However, the shortest development times, which always produces the greatest amount of synapse overproduction, reduce adult performance by three measures: energy use, discrimination error rates, and proportional neuron allocation. Thus, the results here lead to the hypothesis that the observed speed of neural network development represents a particular inter-generational compromise: quick development benefits parental fecundity while slow development benefits offspring fecundity.'),
(88652, 2017, 'plos', 'Altering neuronal excitability to preserve network connectivity in a computational model of Alzheimers disease', 'de Haan, Willem|van Straaten, Elisabeth C W|Gouw, Alida A|Stam, Cornelis J', 'Department of Clinical Neurophysiology and MEG, VUmc, Amsterdam, The Netherlands.|Department of Clinical Neurophysiology and MEG, VUmc, Amsterdam, The Netherlands.|Department of Clinical Neurophysiology and MEG, VUmc, Amsterdam, The Netherlands.|Department of Clinical Neurophysiology and MEG, VUmc, Amsterdam, The Netherlands.', 'Netherlands|Netherlands|Netherlands|Netherlands', 0, 'Alzheimer Disease|Brain|Computational Biology|Connectome|Humans|Models, Neurological|Nerve Net|Neurons', 'Journal Article', '10.1371/journal.pcbi.1005707', '28938009', 'Neuronal hyperactivity and hyperexcitability of the cerebral cortex and hippocampal region is an increasingly observed phenomenon in preclinical Alzheimers disease (AD). In later stages, oscillatory slowing and loss of functional connectivity are ubiquitous. Recent evidence suggests that neuronal dynamics have a prominent role in AD pathophysiology, making it a potentially interesting therapeutic target. However, although neuronal activity can be manipulated by various (non-)pharmacological means, intervening in a highly integrated system that depends on complex dynamics can produce counterintuitive and adverse effects. Computational dynamic network modeling may serve as a virtual test ground for developing effective interventions. To explore this approach, a previously introduced large-scale neural mass network with human brain topology was used to simulate the temporal evolution of AD-like, activity-dependent network degeneration. In addition, six defense strategies that either enhanced or diminished neuronal excitability were tested against the degeneration process, targeting excitatory and inhibitory neurons combined or separately. Outcome measures described oscillatory, connectivity and topological features of the damaged networks. Over time, the various interventions produced diverse large-scale network effects. Contrary to our hypothesis, the most successful strategy was a selective stimulation of all excitatory neurons in the network, it substantially prolonged the preservation of network integrity. The results of this study imply that functional network damage due to pathological neuronal activity can be opposed by targeted adjustment of neuronal excitability levels. The present approach may help to explore therapeutic effects aimed at preserving or restoring neuronal network integrity and contribute to better-informed intervention choices in future clinical trials in AD.'),
(88653, 2017, 'plos', 'Force encoding in muscle spindles during stretch of passive muscle', 'Blum, Kyle P|Lamotte DIncamps, Boris|Zytnicki, Daniel|Ting, Lena H', 'Wallace H. Coulter Department of Biomedical Engineering, Emory University and Georgia Institute of Technology, Atlanta, Georgia, United States of America.|Center for Neurophysics, Physiology and Pathophysiology, Université Paris Descartes, Paris, France.|Center for Neurophysics, Physiology and Pathophysiology, Université Paris Descartes, Paris, France.|Wallace H. Coulter Department of Biomedical Engineering, Emory University and Georgia Institute of Technology, Atlanta, Georgia, United States of America.', 'Georgia|France|France|Georgia', 0, 'Action Potentials|Computer Simulation|Elastic Modulus|Humans|Mechanotransduction, Cellular|Models, Biological|Muscle Spindles|Muscle, Skeletal|Physical Stimulation|Reflex, Stretch|Stress, Mechanical', 'Journal Article', '10.1371/journal.pcbi.1005767', '28945740', 'Muscle spindle proprioceptive receptors play a primary role in encoding the effects of external mechanical perturbations to the body. During externally-imposed stretches of passive, i.e. electrically-quiescent, muscles, the instantaneous firing rates (IFRs) of muscle spindles are associated with characteristics of stretch such as length and velocity. However, even in passive muscle, there are history-dependent transients of muscle spindle firing that are not uniquely related to muscle length and velocity, nor reproduced by current muscle spindle models. These include acceleration-dependent initial bursts, increased dynamic response to stretch velocity if a muscle has been isometric, and rate relaxation, i.e., a decrease in tonic IFR when a muscle is held at a constant length after being stretched. We collected muscle spindle spike trains across a variety of muscle stretch kinematic conditions, including systematic changes in peak length, velocity, and acceleration. We demonstrate that muscle spindle primary afferents in passive muscle fire in direct relationship to muscle force-related variables, rather than length-related variables. Linear combinations of whole muscle-tendon force and the first time derivative of force (dF/dt) predict the entire time course of transient IFRs in muscle spindle Ia afferents during stretch (i.e., lengthening) of passive muscle, including the initial burst, the dynamic response to lengthening, and rate relaxation following lengthening. Similar to acceleration scaling found previously in postural responses to perturbations, initial burst amplitude scaled equally well to initial stretch acceleration or dF/dt, though later transients were only described by dF/dt. The transient increase in dF/dt at the onset of lengthening reflects muscle short-range stiffness due to cross-bridge dynamics. Our work demonstrates a critical role of muscle cross-bridge dynamics in history-dependent muscle spindle IFRs in passive muscle lengthening conditions relevant to the detection and sensorimotor response to mechanical perturbations to the body, and to previously-described history-dependence in perception of limb position.'),
(88654, 2017, 'plos', 'Predictive representations can link model-based reinforcement learning to model-free mechanisms', 'Russek, Evan M|Momennejad, Ida|Botvinick, Matthew M|Gershman, Samuel J|Daw, Nathaniel D', 'Center for Neural Science, New York University, New York, NY, United States of America.|Princeton Neuroscience Institute and Department of Psychology, Princeton University, Princeton, NJ, United States of America.|DeepMind, London, United Kingdom and Gatsby Computational Neuroscience Unit, University College London, United Kingdom.|Department of Psychology and Center for Brain Science, Harvard University, Cambridge, MA, United States of America.|Princeton Neuroscience Institute and Department of Psychology, Princeton University, Princeton, NJ, United States of America.', 'United States|United States|United Kingdom|United States|United States', 49, 'Algorithms|Animals|Computational Biology|Computer Simulation|Decision Making|Humans|Models, Neurological|Reinforcement (Psychology)|Time Factors', 'Journal Article', '10.1371/journal.pcbi.1005768', '28945743', 'Humans and animals are capable of evaluating actions by considering their long-run future rewards through a process described using model-based reinforcement learning (RL) algorithms. The mechanisms by which neural circuits perform the computations prescribed by model-based RL remain largely unknown, however, multiple lines of evidence suggest that neural circuits supporting model-based behavior are structurally homologous to and overlapping with those thought to carry out model-free temporal difference (TD) learning. Here, we lay out a family of approaches by which model-based computation may be built upon a core of TD learning. The foundation of this framework is the successor representation, a predictive state representation that, when combined with TD learning of value predictions, can produce a subset of the behaviors associated with model-based learning, while requiring less decision-time computation than dynamic programming. Using simulations, we delineate the precise behavioral capabilities enabled by evaluating actions using this approach, and compare them to those demonstrated by biological organisms. We then introduce two new algorithms that build upon the successor representation while progressively mitigating its limitations. Because this framework can account for the full range of observed putatively model-based behaviors while still utilizing a core TD framework, we suggest that it represents a neurally plausible family of mechanisms for model-based evaluation.'),
(88655, 2017, 'plos', 'Relating dynamic brain states to dynamic machine states: Human and machine solutions to the speech recognition problem', 'Wingfield, Cai|Su, Li|Liu, Xunying|Zhang, Chao|Woodland, Phil|Thwaites, Andrew|Fonteneau, Elisabeth|Marslen-Wilson, William D', 'Department of Psychology, University of Cambridge, Cambridge, United Kingdom.|China-UK Centre for Cognition and Ageing Research, Faculty of Psychology, Southwest University, Chongqing, China.|Department of Systems Engineering and Engineering Management, The Chinese University of Hong Kong, Hong Kong, China.|Department of Engineering, University of Cambridge, Cambridge, United Kingdom.|Department of Engineering, University of Cambridge, Cambridge, United Kingdom.|Department of Psychology, University of Cambridge, Cambridge, United Kingdom.|Department of Psychology, University of Cambridge, Cambridge, United Kingdom.|Department of Psychology, University of Cambridge, Cambridge, United Kingdom.', 'United Kingdom|China|China|United Kingdom|United Kingdom|United Kingdom|United Kingdom|United Kingdo', 0, 'Adult|Brain|Electroencephalography|Female|Humans|Magnetoencephalography|Male|Models, Neurological|Neural Networks (Computer)|Speech Perception|Speech Recognition Software|Young Adult', 'Journal Article', '10.1371/journal.pcbi.1005617', '28945744', 'There is widespread interest in the relationship between the neurobiological systems supporting human cognition and emerging computational systems capable of emulating these capacities. Human speech comprehension, poorly understood as a neurobiological process, is an important case in point. Automatic Speech Recognition (ASR) systems with near-human levels of performance are now available, which provide a computationally explicit solution for the recognition of words in continuous speech. This research aims to bridge the gap between speech recognition processes in humans and machines, using novel multivariate techniques to compare incremental machine states, generated as the ASR analysis progresses over time, to the incremental brain states, measured using combined electro- and magneto-encephalography (EMEG), generated as the same inputs are heard by human listeners. This direct comparison of dynamic human and machine internal states, as they respond to the same incrementally delivered sensory input, revealed a significant correspondence between neural response patterns in human superior temporal cortex and the structural properties of ASR-derived phonetic models. Spatially coherent patches in human temporal cortex responded selectively to individual phonetic features defined on the basis of machine-extracted regularities in the speech to lexicon mapping process. These results demonstrate the feasibility of relating human and ASR solutions to the problem of speech recognition, and suggest the potential for further studies relating complex neural computations in human speech comprehension to the rapidly evolving ASR systems that address the same problem domain.'),
(88656, 2017, 'plos', 'Correction: Multiscale Approach to the Determination of the Photoactive Yellow Protein Signaling State Ensemble', 'PLOS Computational Biology Staff', 'Department of Psychology, University of Cambridge, Cambridge, United Kingdom.', 'United Kingdom', 0, '-', 'Published Erratum', '10.1371/journal.pcbi.1005770', '28945749', '[This corrects the article DOI: 10.1371/journal.pcbi.1003797.].'),
(88657, 2017, 'plos', 'Correlated receptor transport processes buffer single-cell heterogeneity', 'Kallenberger, Stefan M|Unger, Anne L|Legewie, Stefan|Lymperopoulos, Konstantinos|Klingmüller, Ursula|Eils, Roland|Herten, Dirk-Peter', 'Department for Bioinformatics and Functional Genomics, Division of Theoretical Bioinformatics, German Cancer Research Center (DKFZ), Institute for Pharmacy and Molecular Biotechnology (IPMB) and BioQuant, Heidelberg University, Heidelberg, Germany.|Cellnetworks Cluster and Institute of Physical Chemistry, BioQuant, Heidelberg University, Heidelberg, Germany.|Institute of Molecular Biology, Mainz, Germany.|Cellnetworks Cluster and Institute of Physical Chemistry, BioQuant, Heidelberg University, Heidelberg, Germany.|Division Systems Biology of Signal Transduction, DKFZ-ZMBH Alliance, German Cancer Research Center (DKFZ), Heidelberg, Germany.|Department for Bioinformatics and Functional Genomics, Division of Theoretical Bioinformatics, German Cancer Research Center (DKFZ), Institute for Pharmacy and Molecular Biotechnology (IPMB) and BioQuant, Heidelberg University, Heidelberg, Germany.|Cellnetworks Cluster and Institute of Physical Chemistry, BioQuant, Heidelberg University, Heidelberg, Germany.', 'Germany|Germany|Germany|Germany|Germany|Germany|Germany', 0, 'Biological Transport|Cell Line, Tumor|Computational Biology|Fluorescent Dyes|Humans|Image Processing, Computer-Assisted|Kinetics|Microscopy, Confocal|Models, Biological|Receptors, Cell Surface|Receptors, Erythropoietin|Single-Cell Analysis', 'Journal Article', '10.1371/journal.pcbi.1005779', '28945754', 'Cells typically vary in their response to extracellular ligands. Receptor transport processes modulate ligand-receptor induced signal transduction and impact the variability in cellular responses. Here, we quantitatively characterized cellular variability in erythropoietin receptor (EpoR) trafficking at the single-cell level based on live-cell imaging and mathematical modeling. Using ensembles of single-cell mathematical models reduced parameter uncertainties and showed that rapid EpoR turnover, transport of internalized EpoR back to the plasma membrane, and degradation of Epo-EpoR complexes were essential for receptor trafficking. EpoR trafficking dynamics in adherent H838 lung cancer cells closely resembled the dynamics previously characterized by mathematical modeling in suspension cells, indicating that dynamic properties of the EpoR system are widely conserved. Receptor transport processes differed by one order of magnitude between individual cells. However, the concentration of activated Epo-EpoR complexes was less variable due to the correlated kinetics of opposing transport processes acting as a buffering system.'),
(88658, 2017, 'plos', 'Infectious reactivation of cytomegalovirus explaining age- and sex-specific patterns of seroprevalence', 'van Boven, Michiel|van de Kassteele, Jan|Korndewal, Marjolein J|van Dorp, Christiaan H|Kretzschmar, Mirjam|van der Klis, Fiona|de Melker, Hester E|Vossen, Ann C|van Baarle, Debbie', 'Centre for Infectious Disease Control, National Institute for Public Health and the Environment, Bilthoven, the Netherlands.|Centre for Infectious Disease Control, National Institute for Public Health and the Environment, Bilthoven, the Netherlands.|Centre for Infectious Disease Control, National Institute for Public Health and the Environment, Bilthoven, the Netherlands.|Centre for Infectious Disease Control, National Institute for Public Health and the Environment, Bilthoven, the Netherlands.|Centre for Infectious Disease Control, National Institute for Public Health and the Environment, Bilthoven, the Netherlands.|Centre for Infectious Disease Control, National Institute for Public Health and the Environment, Bilthoven, the Netherlands.|Centre for Infectious Disease Control, National Institute for Public Health and the Environment, Bilthoven, the Netherlands.|Leiden University Medical Center, Department of Medical Microbiology, Leiden, the Netherlands.|Centre for Infectious Disease Control, National Institute for Public Health and the Environment, Bilthoven, the Netherlands.', 'Netherlands|Netherlands|Netherlands|Netherlands|Netherlands|Netherlands|Netherlands|Netherlands|Neth', 0, 'Adolescent|Adult|Aged|Aged, 80 and over|Child|Child, Preschool|Cross-Sectional Studies|Cytomegalovirus|Cytomegalovirus Infections|Female|Humans|Infant|Infant, Newborn|Male|Middle Aged|Prevalence|Seroepidemiologic Studies|Virus Activation|Young Adult', 'Journal Article', '10.1371/journal.pcbi.1005719', '28949962', 'Human cytomegalovirus (CMV) is a herpes virus with poorly understood transmission dynamics. Person-to-person transmission is thought to occur primarily through transfer of saliva or urine, but no quantitative estimates are available for the contribution of different infection routes. Using data from a large population-based serological study (n = 5,179), we provide quantitative estimates of key epidemiological parameters, including the transmissibility of primary infection, reactivation, and re-infection. Mixture models are fitted to age- and sex-specific antibody response data from the Netherlands, showing that the data can be described by a model with three distributions of antibody measurements, i.e. uninfected, infected, and infected with increased antibody concentration. Estimates of seroprevalence increase gradually with age, such that at 80 years 73% (95%CrI: 64%-78%) of females and 62% (95%CrI: 55%-68%) of males are infected, while 57% (95%CrI: 47%-67%) of females and 37% (95%CrI: 28%-46%) of males have increased antibody concentration. Merging the statistical analyses with transmission models, we find that models with infectious reactivation (i.e. reactivation that can lead to the virus being transmitted to a novel host) fit the data significantly better than models without infectious reactivation. Estimated reactivation rates increase from low values in children to 2%-4% per year in women older than 50 years. The results advance a hypothesis in which transmission from adults after infectious reactivation is a key driver of transmission. We discuss the implications for control strategies aimed at reducing CMV infection in vulnerable groups.'),
(88659, 2017, 'plos', 'Ten simple rules for structuring papers', 'Mensh, Brett|Kording, Konrad', 'Optimize Science, Mill Valley, California, United States of America.|University of Pennsylvania, Philadelphia, Pennsylvania, United States of America.', 'United States|United States', 14, 'Algorithms|Documentation|Periodicals as Topic|Research|Science|Writing', 'Editorial', '10.1371/journal.pcbi.1005619', '28957311', '-'),
(88660, 2017, 'plos', 'A composite network of conserved and tissue specific gene interactions reveals possible genetic interactions in glioma', 'Voigt, André|Nowick, Katja|Almaas, Eivind', 'Network Systems Biology Group, Department of Biotechnology, NTNU - Norwegian University of Science and Technology, Trondheim, Norway.|Bioinformatics Group, Department of Computer Science, and Interdisciplinary Center for Bioinformatics, University of Leipzig, Leipzig, Germany.|Network Systems Biology Group, Department of Biotechnology, NTNU - Norwegian University of Science and Technology, Trondheim, Norway.', 'Norway|Germany|Norway', 0, 'Animals|Brain Neoplasms|Computer Simulation|Gene Expression Profiling|Gene Expression Regulation, Neoplastic|Genes, Neoplasm|Genetic Predisposition to Disease|Glioma|Humans|Models, Genetic|Neoplasm Proteins', 'Journal Article', '10.1371/journal.pcbi.1005739', '28957313', 'Differential co-expression network analyses have recently become an important step in the investigation of cellular differentiation and dysfunctional gene-regulation in cell and tissue disease-states. The resulting networks have been analyzed to identify and understand pathways associated with disorders, or to infer molecular interactions. However, existing methods for differential co-expression network analysis are unable to distinguish between various forms of differential co-expression. To close this gap, here we define the three different kinds (conserved, specific, and differentiated) of differential co-expression and present a systematic framework, CSD, for differential co-expression network analysis that incorporates these interactions on an equal footing. In addition, our method includes a subsampling strategy to estimate the variance of co-expressions. Our framework is applicable to a wide variety of cases, such as the study of differential co-expression networks between healthy and disease states, before and after treatments, or between species. Applying the CSD approach to a published gene-expression data set of cerebral cortex and basal ganglia samples from healthy individuals, we find that the resulting CSD network is enriched in genes associated with cognitive function, signaling pathways involving compounds with well-known roles in the central nervous system, as well as certain neurological diseases. From the CSD analysis, we identify a set of prominent hubs of differential co-expression, whose neighborhood contains a substantial number of genes associated with glioblastoma. The resulting gene-sets identified by our CSD analysis also contain many genes that so far have not been recognized as having a role in glioblastoma, but are good candidates for further studies. CSD may thus aid in hypothesis-generation for functional disease-associations.'),
(88661, 2017, 'plos', 'Flexibility to contingency changes distinguishes habitual and goal-directed strategies in humans', 'Lee, Julie J|Keramati, Mehdi', 'Gatsby Computational Neuroscience Unit, University College London, London, United Kingdom.|Gatsby Computational Neuroscience Unit, University College London, London, United Kingdom.', 'United Kingdom|United Kingdom', 2, 'Adult|Decision Making|Extinction, Psychological|Female|Habits|Habituation, Psychophysiologic|Humans|Male|Models, Psychological|Reinforcement (Psychology)|Task Performance and Analysis', 'Journal Article', '10.1371/journal.pcbi.1005753', '28957319', 'Decision-making in the real world presents the challenge of requiring flexible yet prompt behavior, a balance that has been characterized in terms of a trade-off between a slower, prospective goal-directed model-based (MB) strategy and a fast, retrospective habitual model-free (MF) strategy. Theory predicts that flexibility to changes in both reward values and transition contingencies can determine the relative influence of the two systems in reinforcement learning, but few studies have manipulated the latter. Therefore, we developed a novel two-level contingency change task in which transition contingencies between states change every few trials, MB and MF control predict different responses following these contingency changes, allowing their relative influence to be inferred. Additionally, we manipulated the rate of contingency changes in order to determine whether contingency change volatility would play a role in shifting subjects between a MB and MF strategy. We found that human subjects employed a hybrid MB/MF strategy on the task, corroborating the parallel contribution of MB and MF systems in reinforcement learning. Further, subjects did not remain at one level of MB/MF behaviour but rather displayed a shift towards more MB behavior over the first two blocks that was not attributable to the rate of contingency changes but rather to the extent of training. We demonstrate that flexibility to contingency changes can distinguish MB and MF strategies, with human subjects utilizing a hybrid strategy that shifts towards more MB behavior over blocks, consequently corresponding to a higher payoff.'),
(88662, 2017, 'plos', 'A metabolic core model elucidates how enhanced utilization of glucose and glutamine, with enhanced glutamine-dependent lactate production, promotes cancer cell growth: The WarburQ effect', 'Damiani, Chiara|Colombo, Riccardo|Gaglio, Daniela|Mastroianni, Fabrizia|Pescini, Dario|Westerhoff, Hans Victor|Mauri, Giancarlo|Vanoni, Marco|Alberghina, Lilia', 'SYSBIO Centre of Systems Biology, Milano, Italy.|SYSBIO Centre of Systems Biology, Milano, Italy.|SYSBIO Centre of Systems Biology, Milano, Italy.|SYSBIO Centre of Systems Biology, Milano, Italy.|SYSBIO Centre of Systems Biology, Milano, Italy.|Dept of Molecular Cell Physiology, Faculty of Earth and Life Sciences, VU University, Amsterdam, The Netherlands.|SYSBIO Centre of Systems Biology, Milano, Italy.|SYSBIO Centre of Systems Biology, Milano, Italy.|SYSBIO Centre of Systems Biology, Milano, Italy.', 'Italy|Italy|Italy|Italy|Italy|Netherlands|Italy|Italy|Italy', 17, 'Animals|Cell Proliferation|Computer Simulation|Glucose|Glutamine|Humans|Lactic Acid|Metabolic Flux Analysis|Metabolic Networks and Pathways|Models, Biological|Neoplasms', 'Journal Article', '10.1371/journal.pcbi.1005758', '28957320', 'Cancer cells share several metabolic traits, including aerobic production of lactate from glucose (Warburg effect), extensive glutamine utilization and impaired mitochondrial electron flow. It is still unclear how these metabolic rearrangements, which may involve different molecular events in different cells, contribute to a selective advantage for cancer cell proliferation. To ascertain which metabolic pathways are used to convert glucose and glutamine to balanced energy and biomass production, we performed systematic constraint-based simulations of a model of human central metabolism. Sampling of the feasible flux space allowed us to obtain a large number of randomly mutated cells simulated at different glutamine and glucose uptake rates. We observed that, in the limited subset of proliferating cells, most displayed fermentation of glucose to lactate in the presence of oxygen. At high utilization rates of glutamine, oxidative utilization of glucose was decreased, while the production of lactate from glutamine was enhanced. This emergent phenotype was observed only when the available carbon exceeded the amount that could be fully oxidized by the available oxygen. Under the latter conditions, standard Flux Balance Analysis indicated that: this metabolic pattern is optimal to maximize biomass and ATP production, it requires the activity of a branched TCA cycle, in which glutamine-dependent reductive carboxylation cooperates to the production of lipids and proteins, it is sustained by a variety of redox-controlled metabolic reactions. In a K-ras transformed cell line we experimentally assessed glutamine-induced metabolic changes. We validated computational results through an extension of Flux Balance Analysis that allows prediction of metabolite variations. Taken together these findings offer new understanding of the logic of the metabolic reprogramming that underlies cancer cell growth.'),
(88663, 2017, 'plos', 'Interactions between the tumor and the blood systemic response of breast cancer patients', 'Dumeaux, Vanessa|Fjukstad, Bjørn|Fjosne, Hans E|Frantzen, Jan-Ole|Holmen, Marit Muri|Rodegerdts, Enno|Schlichting, Ellen|Børresen-Dale, Anne-Lise|Bongo, Lars Ailo|Lund, Eiliv|Hallett, Michael', 'Department of Biology, Concordia University, Montreal, QC, Canada.|Department of Computer Science, UiT the Arctic University of Norway, Tromsø, Norway.|Department of Surgery, St. Olavs University Hospital, Trondheim, Norway.|University Hospital of North-Norway, Narvik, Norway.|Department of Radiology and Nuclear Medicine, Oslo University Hospital, Oslo, Norway.|Nordland Central Hospital, Bodø, Norway.|Department of Cancer, Oslo University Hospital, Oslo, Norway.|Department of Cancer Genetics, Oslo University Hospital, Oslo, Norway.|Department of Computer Science, UiT the Arctic University of Norway, Tromsø, Norway.|Institute of Community Medicine, UiT the Arctic University of Norway, Tromsø, Norway.|Department of Biology, Concordia University, Montreal, QC, Canada.', 'Canada|Norway|Norway|Norway|Norway|Norway|Norway|Norway|Norway|Norway|Canada', 0, 'Biomarkers, Tumor|Blood Cells|Breast Neoplasms|Case-Control Studies|Cellular Microenvironment|Female|Gene Expression Profiling|Genomics|Humans|Middle Aged|Signal Transduction|Systems Biology|Tumor Microenvironment', 'Journal Article', '10.1371/journal.pcbi.1005680', '28957325', 'Although systemic immunity is critical to the process of tumor rejection, cancer research has largely focused on immune cells in the tumor microenvironment. To understand molecular changes in the patient systemic response (SR) to the presence of BC, we profiled RNA in blood and matched tumor from 173 patients. We designed a system (MIxT, Matched Interactions Across Tissues) to systematically explore and link molecular processes expressed in each tissue. MIxT confirmed that processes active in the patient SR are especially relevant to BC immunogenicity. The nature of interactions across tissues (i.e. which biological processes are associated and their patterns of expression) varies highly with tumor subtype. For example, aspects of the immune SR are underexpressed proportionally to the level of expression of defined molecular processes specific to basal tumors. The catalog of subtype-specific interactions across tissues from BC patients provides promising new ways to tackle or monitor the disease by exploiting the patient SR.'),
(88664, 2017, 'plos', 'Exploiting ecology in drug pulse sequences in favour of population reduction', 'Bauer, Marianne|Graf, Isabella R|Ngampruetikorn, Vudtiwat|Stephens, Greg J|Frey, Erwin', 'Arnold-Sommerfeld-Center for Theoretical Physics and Center for NanoScience, Department of Physics, Ludwig-Maximilians-Universität München, Munich, Germany.|Arnold-Sommerfeld-Center for Theoretical Physics and Center for NanoScience, Department of Physics, Ludwig-Maximilians-Universität München, Munich, Germany.|Biological Physics Theory Unit, Okinawa Institute of Science and Technology Graduate University, Onna, Okinawa, Japan.|Biological Physics Theory Unit, Okinawa Institute of Science and Technology Graduate University, Onna, Okinawa, Japan.|Arnold-Sommerfeld-Center for Theoretical Physics and Center for NanoScience, Department of Physics, Ludwig-Maximilians-Universität München, Munich, Germany.', 'Germany|Germany|Japan|Japan|Germany', 3, 'Animals|Anti-Bacterial Agents|Bacteria|Bacterial Infections|Caenorhabditis elegans|Computational Biology|Ecology|Models, Biological|Population Dynamics', 'Journal Article', '10.1371/journal.pcbi.1005747', '28957328', 'A deterministic population dynamics model involving birth and death for a two-species system, comprising a wild-type and more resistant species competing via logistic growth, is subjected to two distinct stress environments designed to mimic those that would typically be induced by temporal variation in the concentration of a drug (antibiotic or chemotherapeutic) as it permeates through the population and is progressively degraded. Different treatment regimes, involving single or periodical doses, are evaluated in terms of the minimal population size (a measure of the extinction probability), and the population composition (a measure of the selection pressure for resistance or tolerance during the treatment). We show that there exist timescales over which the low-stress regime is as effective as the high-stress regime, due to the competition between the two species. For multiple periodic treatments, competition can ensure that the minimal population size is attained during the first pulse when the high-stress regime is short, which implies that a single short pulse can be more effective than a more protracted regime. Our results suggest that when the duration of the high-stress environment is restricted, a treatment with one or multiple shorter pulses can produce better outcomes than a single long treatment. If ecological competition is to be exploited for treatments, it is crucial to determine these timescales, and estimate for the minimal population threshold that suffices for extinction. These parameters can be quantified by experiment.');
INSERT INTO `papers` (`id`, `ano`, `journal`, `titulo`, `autores`, `afiliacao`, `pais`, `citacoes`, `palavra_chave`, `categorias`, `doi`, `pubmed`, `abstract`) VALUES
(88665, 2017, 'plos', 'Features of spatial and functional segregation and integration of the primate connectome revealed by trade-off between wiring cost and efficiency', 'Chen, Yuhan|Wang, Shengjun|Hilgetag, Claus C|Zhou, Changsong', 'National Key Laboratory of Cognitive Neuroscience and Learning, Beijing Normal University, Beijing, China.|Department of Physics, Shaanxi Normal University, XiAn, Shaanxi Province, China.|Institute of Computational Neuroscience, University Medical Center Eppendorf, Hamburg, Germany.|Department of Physics, Hong Kong Baptist University, Kowloon Tong, Hong Kong.', 'China|China|Germany|Hong Kong', 9, 'Algorithms|Animals|Brain|Brain Mapping|Computational Biology|Connectome|Databases, Factual|Humans|Macaca|Models, Neurological|Models, Statistical|Nerve Net|Neural Pathways|Primates|Software', 'Journal Article', '10.1371/journal.pcbi.1005776', '28961235', 'The primate connectome, possessing a characteristic global topology and specific regional connectivity profiles, is well organized to support both segregated and integrated brain function. However, the organization mechanisms shaping the characteristic connectivity and its relationship to functional requirements remain unclear. The primate brain connectome is shaped by metabolic economy as well as functional values. Here, we explored the influence of two competing factors and additional advanced functional requirements on the primate connectome employing an optimal trade-off model between neural wiring cost and the representative functional requirement of processing efficiency. Moreover, we compared this model with a generative model combining spatial distance and topological similarity, with the objective of statistically reproducing multiple topological features of the network. The primate connectome indeed displays a cost-efficiency trade-off and that up to 67% of the connections were recovered by optimal combination of the two basic factors of wiring economy and processing efficiency, clearly higher than the proportion of connections (56%) explained by the generative model. While not explicitly aimed for, the trade-off model captured several key topological features of the real connectome as the generative model, yet better explained the connectivity of most regions. The majority of the remaining 33% of connections unexplained by the best trade-off model were long-distance links, which are concentrated on few cortical areas, termed long-distance connectors (LDCs). The LDCs are mainly non-hubs, but form a densely connected group overlapping on spatially segregated functional modalities. LDCs are crucial for both functional segregation and integration across different scales. These organization features revealed by the optimization analysis provide evidence that the demands of advanced functional segregation and integration among spatially distributed regions may play a significant role in shaping the cortical connectome, in addition to the basic cost-efficiency trade-off. These findings also shed light on inherent vulnerabilities of brain networks in diseases.'),
(88666, 2017, 'plos', 'Multi-layer network utilizing rewarded spike time dependent plasticity to learn a foraging task', 'Sanda, Pavel|Skorheim, Steven|Bazhenov, Maxim', 'Department of Medicine, University of California, San Diego, La Jolla, California, United States of America.|Information and Systems Sciences Lab, HRL Laboratories, LLC, Malibu, California, United States of America.|Department of Medicine, University of California, San Diego, La Jolla, California, United States of America.', 'United States|Mali|United States', 0, 'Action Potentials|Algorithms|Animals|Appetitive Behavior|Computational Biology|Feedback|Humans|Machine Learning|Models, Neurological|Neural Networks (Computer)|Neuronal Plasticity', 'Journal Article', '10.1371/journal.pcbi.1005705', '28961245', 'Neural networks with a single plastic layer employing reward modulated spike time dependent plasticity (STDP) are capable of learning simple foraging tasks. Here we demonstrate advanced pattern discrimination and continuous learning in a network of spiking neurons with multiple plastic layers. The network utilized both reward modulated and non-reward modulated STDP and implemented multiple mechanisms for homeostatic regulation of synaptic efficacy, including heterosynaptic plasticity, gain control, output balancing, activity normalization of rewarded STDP and hard limits on synaptic strength. We found that addition of a hidden layer of neurons employing non-rewarded STDP created neurons that responded to the specific combinations of inputs and thus performed basic classification of the input patterns. When combined with a following layer of neurons implementing rewarded STDP, the network was able to learn, despite the absence of labeled training data, discrimination between rewarding patterns and the patterns designated as punishing. Synaptic noise allowed for trial-and-error learning that helped to identify the goal-oriented strategies which were effective in task solving. The study predicts a critical set of properties of the spiking neuronal network with STDP that was sufficient to solve a complex foraging task involving pattern classification and decision making.'),
(88667, 2017, 'plos', 'A theoretical framework for analyzing coupled neuronal networks: Application to the olfactory system', 'Barreiro, Andrea K|Gautam, Shree Hari|Shew, Woodrow L|Ly, Cheng', 'Department of Mathematics, Southern Methodist University, Dallas, Texas, United States of America.|Department of Physics, University of Arkansas, Fayetteville, Arkansas, United States of America.|Department of Physics, University of Arkansas, Fayetteville, Arkansas, United States of America.|Department of Statistical Sciences and Operations Research, Virginia Commonwealth University, Richmond, Virginia, United States of America.', 'United States|United States|United States|United States', 0, 'Animals|Cerebral Cortex|Computational Biology|Male|Models, Neurological|Nerve Net|Odorants|Olfactory Bulb|Olfactory Pathways|Rats|Smell', 'Journal Article', '10.1371/journal.pcbi.1005780', '28968384', 'Determining how synaptic coupling within and between regions is modulated during sensory processing is an important topic in neuroscience. Electrophysiological recordings provide detailed information about neural spiking but have traditionally been confined to a particular region or layer of cortex. Here we develop new theoretical methods to study interactions between and within two brain regions, based on experimental measurements of spiking activity simultaneously recorded from the two regions. By systematically comparing experimentally-obtained spiking statistics to (efficiently computed) model spike rate statistics, we identify regions in model parameter space that are consistent with the experimental data. We apply our new technique to dual micro-electrode array in vivo recordings from two distinct regions: olfactory bulb (OB) and anterior piriform cortex (PC). Our analysis predicts that: i) inhibition within the afferent region (OB) has to be weaker than the inhibition within PC, ii) excitation from PC to OB is generally stronger than excitation from OB to PC, iii) excitation from PC to OB and inhibition within PC have to both be relatively strong compared to presynaptic inputs from OB. These predictions are validated in a spiking neural network model of the OB-PC pathway that satisfies the many constraints from our experimental data. We find when the derived relationships are violated, the spiking statistics no longer satisfy the constraints from the data. In principle this modeling framework can be adapted to other systems and be used to investigate relationships between other neural attributes besides network connection strengths. Thus, this work can serve as a guide to further investigations into the relationships of various neural attributes within and across different regions during sensory processing.'),
(88668, 2017, 'plos', 'A continuum-mechanical skeletal muscle model including actin-titin interaction predicts stable contractions on the descending limb of the force-length relation', 'Heidlauf, Thomas|Klotz, Thomas|Rode, Christian|Siebert, Tobias|Röhrle, Oliver', 'Institute of Applied Mechanics (CE), University of Stuttgart, Stuttgart, Germany.|Institute of Applied Mechanics (CE), University of Stuttgart, Stuttgart, Germany.|Institute of Motion Science, Friedrich-Schiller-University, Jena, Germany.|Department of Sport and Motion Science, University of Stuttgart, Stuttgart, Germany.|Institute of Applied Mechanics (CE), University of Stuttgart, Stuttgart, Germany.', 'Germany|Germany|Germany|Germany|Germany', 13, 'Actins|Animals|Biomechanical Phenomena|Computational Biology|Connectin|Humans|Models, Biological|Muscle Contraction|Muscle, Skeletal', 'Journal Article', '10.1371/journal.pcbi.1005773', '28968385', 'Contractions on the descending limb of the total (active + passive) muscle force-length relationship (i. e. when muscle stiffness is negative) are expected to lead to vast half-sarcomere-length inhomogeneities. This is however not observed in experiments-vast half-sarcomere-length inhomogeneities can be absent in myofibrils contracting in this range, and initial inhomogeneities can even decrease. Here we show that the absence of half-sarcomere-length inhomogeneities can be predicted when considering interactions of the semi-active protein titin with the actin filaments. Including a model of actin-titin interactions within a multi-scale continuum-mechanical model, we demonstrate that stability, accurate forces and nearly homogeneous half-sarcomere lengths can be obtained on the descending limb of the static total force-length relation. This could be a key to durable functioning of the muscle because large local stretches, that might harm, for example, the transverse-tubule system, are avoided.'),
(88669, 2017, 'plos', 'A single-cell spiking model for the origin of grid-cell patterns', 'DAlbis, Tiziano|Kempter, Richard', 'Institute for Theoretical Biology, Department of Biology, Humboldt-Universität zu Berlin, Berlin, Germany.|Institute for Theoretical Biology, Department of Biology, Humboldt-Universität zu Berlin, Berlin, Germany.', 'Germany|Germany', 8, 'Action Potentials|Animals|Computational Biology|Entorhinal Cortex|Grid Cells|Models, Neurological|Single-Cell Analysis', 'Journal Article', '10.1371/journal.pcbi.1005782', '28968386', 'Spatial cognition in mammals is thought to rely on the activity of grid cells in the entorhinal cortex, yet the fundamental principles underlying the origin of grid-cell firing are still debated. Grid-like patterns could emerge via Hebbian learning and neuronal adaptation, but current computational models remained too abstract to allow direct confrontation with experimental data. Here, we propose a single-cell spiking model that generates grid firing fields via spike-rate adaptation and spike-timing dependent plasticity. Through rigorous mathematical analysis applicable in the linear limit, we quantitatively predict the requirements for grid-pattern formation, and we establish a direct link to classical pattern-forming systems of the Turing type. Our study lays the groundwork for biophysically-realistic models of grid-cell activity.'),
(88670, 2017, 'plos', 'Estimating time of HIV-1 infection from next-generation sequence diversity', 'Puller, Vadim|Neher, Richard|Albert, Jan', 'Max Planck Institute for Developmental Biology, Tübingen, Germany.|Max Planck Institute for Developmental Biology, Tübingen, Germany.|Department of Microbiology, Tumor and Cell Biology, Karolinska Institute, Stockholm, Sweden.', 'Germany|Germany|Sweden', 0, 'Genome, Viral|Genomics|HIV Infections|HIV-1|High-Throughput Nucleotide Sequencing|Humans|Models, Statistical|Sequence Analysis, DNA', 'Journal Article', '10.1371/journal.pcbi.1005775', '28968389', 'Estimating the time since infection (TI) in newly diagnosed HIV-1 patients is challenging, but important to understand the epidemiology of the infection. Here we explore the utility of virus diversity estimated by next-generation sequencing (NGS) as novel biomarker by using a recent genome-wide longitudinal dataset obtained from 11 untreated HIV-1-infected patients with known dates of infection. The results were validated on a second dataset from 31 patients. Virus diversity increased linearly with time, particularly at 3rd codon positions, with little inter-patient variation. The precision of the TI estimate improved with increasing sequencing depth, showing that diversity in NGS data yields superior estimates to the number of ambiguous sites in Sanger sequences, which is one of the alternative biomarkers. The full advantage of deep NGS was utilized with continuous diversity measures such as average pairwise distance or site entropy, rather than the fraction of polymorphic sites. The precision depended on the genomic region and codon position and was highest when 3rd codon positions in the entire pol gene were used. For these data, TI estimates had a mean absolute error of around 1 year. The error increased only slightly from around 0.6 years at a TI of 6 months to around 1.1 years at 6 years. Our results show that virus diversity determined by NGS can be used to estimate time since HIV-1 infection many years after the infection, in contrast to most alternative biomarkers. We provide the regression coefficients as well as web tool for TI estimation.'),
(88671, 2017, 'plos', 'Learning causal networks with latent variables from multivariate information in genomic data', 'Verny, Louis|Sella, Nadir|Affeldt, Séverine|Singh, Param Priya|Isambert, Hervé', 'Institut Curie, PSL Research University, CNRS, UMR168, Paris, France.|Institut Curie, PSL Research University, CNRS, UMR168, Paris, France.|Institut Curie, PSL Research University, CNRS, UMR168, Paris, France.|Institut Curie, PSL Research University, CNRS, UMR168, Paris, France.|Institut Curie, PSL Research University, CNRS, UMR168, Paris, France.', 'France|France|France|France|France', 9, 'Animals|Biomarkers|Breast Neoplasms|Cells, Cultured|Computational Biology|Embryo, Mammalian|Female|Gene Expression Profiling|Gene Regulatory Networks|Genomics|Hematopoiesis|Humans|Mice|Models, Genetic|Single-Cell Analysis', 'Journal Article', '10.1371/journal.pcbi.1005662', '28968390', 'Learning causal networks from large-scale genomic data remains challenging in absence of time series or controlled perturbation experiments. We report an information- theoretic method which learns a large class of causal or non-causal graphical models from purely observational data, while including the effects of unobserved latent variables, commonly found in many genomic datasets. Starting from a complete graph, the method iteratively removes dispensable edges, by uncovering significant information contributions from indirect paths, and assesses edge-specific confidences from randomization of available data. The remaining edges are then oriented based on the signature of causality in observational data. The approach and associated algorithm, miic, outperform earlier methods on a broad range of benchmark networks. Causal network reconstructions are presented at different biological size and time scales, from gene regulation in single cells to whole genome duplication in tumor development as well as long term evolution of vertebrates. Miic is publicly available at https://github.com/miicTeam/MIIC.'),
(88672, 2017, 'plos', 'Bistability, non-ergodicity, and inhibition in pairwise maximum-entropy models', 'Rostami, Vahid|Porta Mana, PierGianLuca|Grün, Sonja|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.|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|Germany|Germany', 7, 'Animals|Computational Biology|Entropy|Macaca|Models, Neurological|Motor Cortex|Nerve Net|Neurons', 'Journal Article', '10.1371/journal.pcbi.1005762', '28968396', 'Pairwise maximum-entropy models have been used in neuroscience to predict the activity of neuronal populations, given only the time-averaged correlations of the neuron activities. This paper provides evidence that the pairwise model, applied to experimental recordings, would produce a bimodal distribution for the population-averaged activity, and for some population sizes the second mode would peak at high activities, that experimentally would be equivalent to 90% of the neuron population active within time-windows of few milliseconds. Several problems are connected with this bimodality: 1. The presence of the high-activity mode is unrealistic in view of observed neuronal activity and on neurobiological grounds. 2. Boltzmann learning becomes non-ergodic, hence the pairwise maximum-entropy distribution cannot be found: in fact, Boltzmann learning would produce an incorrect distribution, similarly, common variants of mean-field approximations also produce an incorrect distribution. 3. The Glauber dynamics associated with the model is unrealistically bistable and cannot be used to generate realistic surrogate data. This bimodality problem is first demonstrated for an experimental dataset from 159 neurons in the motor cortex of macaque monkey. Evidence is then provided that this problem affects typical neural recordings of population sizes of a couple of hundreds or more neurons. The cause of the bimodality problem is identified as the inability of standard maximum-entropy distributions with a uniform reference measure to model neuronal inhibition. To eliminate this problem a modified maximum-entropy model is presented, which reflects a basic effect of inhibition in the form of a simple but non-uniform reference measure. This model does not lead to unrealistic bimodalities, can be found with Boltzmann learning, and has an associated Glauber dynamics which incorporates a minimal asymmetric inhibition.'),
(88673, 2017, 'plos', 'Correction: Spatial organization of the budding yeast genome in the cell nucleus and identification of specific chromatin interactions from multi-chromosome constrained chromatin model', 'PLOS Computational Biology Staff', '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', 0, '-', 'Published Erratum', '10.1371/journal.pcbi.1005778', '28968401', '[This corrects the article DOI: 10.1371/journal.pcbi.1005658.].'),
(88674, 2017, 'plos', 'Designing small universal k-mer hitting sets for improved analysis of high-throughput sequencing', 'Orenstein, Yaron|Pellow, David|Marçais, Guillaume|Shamir, Ron|Kingsford, Carl', 'Computer Science and Artificial Intelligence Laboratory, MIT, Cambridge, Massasschusetts, United States of America.|Blavatnik School of Computer Science, Tel-Aviv University, Tel-Aviv, Israel.|Computational Biology Department, School of Computer Science, Carnegie Mellon University, Pittsburgh, Pennsylvania, United States of America.|Blavatnik School of Computer Science, Tel-Aviv University, Tel-Aviv, Israel.|Computational Biology Department, School of Computer Science, Carnegie Mellon University, Pittsburgh, Pennsylvania, United States of America.', 'United States|Israel|United States|Israel|United States', 0, 'Algorithms|Animals|Caenorhabditis elegans|Computational Biology|Computer Heuristics|Genome, Bacterial|Genome, Human|High-Throughput Nucleotide Sequencing|Humans|Sequence Analysis, DNA|Software', 'Journal Article', '10.1371/journal.pcbi.1005777', '28968408', 'With the rapidly increasing volume of deep sequencing data, more efficient algorithms and data structures are needed. Minimizers are a central recent paradigm that has improved various sequence analysis tasks, including hashing for faster read overlap detection, sparse suffix arrays for creating smaller indexes, and Bloom filters for speeding up sequence search. Here, we propose an alternative paradigm that can lead to substantial further improvement in these and other tasks. For integers k and L > k, we say that a set of k-mers is a universal hitting set (UHS) if every possible L-long sequence must contain a k-mer from the set. We develop a heuristic called DOCKS to find a compact UHS, which works in two phases: The first phase is solved optimally, and for the second we propose several efficient heuristics, trading set size for speed and memory. The use of heuristics is motivated by showing the NP-hardness of a closely related problem. We show that DOCKS works well in practice and produces UHSs that are very close to a theoretical lower bound. We present results for various values of k and L and by applying them to real genomes show that UHSs indeed improve over minimizers. In particular, DOCKS uses less than 30% of the 10-mers needed to span the human genome compared to minimizers. The software and computed UHSs are freely available at github.com/Shamir-Lab/DOCKS/ and acgt.cs.tau.ac.il/docks/, respectively.'),
(88675, 2017, 'plos', 'Identifying parameter regions for multistationarity', 'Conradi, Carsten|Feliu, Elisenda|Mincheva, Maya|Wiuf, Carsten', 'Life Science Engineering, HTW Berlin, Berlin, Germany.|Department of Mathematical Sciences, University of Copenhagen, Copenhagen, Denmark.|Department of Mathematical Sciences, Northern Illinois University, DeKalb, Illinois, United States of America.|Department of Mathematical Sciences, University of Copenhagen, Copenhagen, Denmark.', 'Germany|Denmark|United States|Denmark', 0, 'Algorithms|Computer Simulation|Data Interpretation, Statistical|Models, Biological|Models, Statistical|Multivariate Analysis', 'Journal Article', '10.1371/journal.pcbi.1005751', '28972969', 'Mathematical modelling has become an established tool for studying the dynamics of biological systems. Current applications range from building models that reproduce quantitative data to identifying systems with predefined qualitative features, such as switching behaviour, bistability or oscillations. Mathematically, the latter question amounts to identifying parameter values associated with a given qualitative feature. We introduce a procedure to partition the parameter space of a parameterized system of ordinary differential equations into regions for which the system has a unique or multiple equilibria. The procedure is based on the computation of the Brouwer degree, and it creates a multivariate polynomial with parameter depending coefficients. The signs of the coefficients determine parameter regions with and without multistationarity. A particular strength of the procedure is the avoidance of numerical analysis and parameter sampling. The procedure consists of a number of steps. Each of these steps might be addressed algorithmically using various computer programs and available software, or manually. We demonstrate our procedure on several models of gene transcription and cell signalling, and show that in many cases we obtain a complete partitioning of the parameter space with respect to multistationarity.'),
(88676, 2017, 'plos', 'Signatures of criticality arise from random subsampling in simple population models', 'Nonnenmacher, Marcel|Behrens, Christian|Berens, Philipp|Bethge, Matthias|Macke, Jakob H', 'Research Center caesar, an associate of the Max Planck Society, Bonn, Germany.|Bernstein Center for Computational Neuroscience, Tübingen, Germany.|Bernstein Center for Computational Neuroscience, Tübingen, Germany.|Max Planck Institute for Biological Cybernetics, Tübingen, Germany.|Research Center caesar, an associate of the Max Planck Society, Bonn, Germany.', 'Germany|Germany|Germany|Germany|Germany', 15, 'Animals|Cats|Computational Biology|Models, Neurological|Neurons|Retinal Ganglion Cells|Thermodynamics', 'Journal Article', '10.1371/journal.pcbi.1005718', '28972970', 'The rise of large-scale recordings of neuronal activity has fueled the hope to gain new insights into the collective activity of neural ensembles. How can one link the statistics of neural population activity to underlying principles and theories? One attempt to interpret such data builds upon analogies to the behaviour of collective systems in statistical physics. Divergence of the specific heat-a measure of population statistics derived from thermodynamics-has been used to suggest that neural populations are optimized to operate at a critical point. However, these findings have been challenged by theoretical studies which have shown that common inputs can lead to diverging specific heat. Here, we connect signatures of criticality, and in particular the divergence of specific heat, back to statistics of neural population activity commonly studied in neural coding: firing rates and pairwise correlations. We show that the specific heat diverges whenever the average correlation strength does not depend on population size. This is necessarily true when data with correlations is randomly subsampled during the analysis process, irrespective of the detailed structure or origin of correlations. We also show how the characteristic shape of specific heat capacity curves depends on firing rates and correlations, using both analytically tractable models and numerical simulations of a canonical feed-forward population model. To analyze these simulations, we develop efficient methods for characterizing large-scale neural population activity with maximum entropy models. We find that, consistent with experimental findings, increases in firing rates and correlation directly lead to more pronounced signatures. Thus, previous reports of thermodynamical criticality in neural populations based on the analysis of specific heat can be explained by average firing rates and correlations, and are not indicative of an optimized coding strategy. We conclude that a reliable interpretation of statistical tests for theories of neural coding is possible only in reference to relevant ground-truth models.'),
(88677, 2017, 'plos', 'The evolutionary origins of Lévy walk foraging', 'Wosniack, Marina E|Santos, Marcos C|Raposo, Ernesto P|Viswanathan, Gandhi M|da Luz, Marcos G E', 'Departamento de Física, Universidade Federal do Paraná, Curitiba-PR, Brazil.|Departamento de Física, Universidade Federal do Paraná, Curitiba-PR, Brazil.|Laboratório de Física Teórica e Computacional, Departamento de Física, Universidade Federal de Pernambuco, Recife-PE, Brazil.|Department of Physics, Universidade Federal do Rio Grande do Norte, Natal-RN, Brazil.|Departamento de Física, Universidade Federal do Paraná, Curitiba-PR, Brazil.', 'Brazil|Brazil|Brazil|Brazil|Brazil', 21, 'Algorithms|Animals|Appetitive Behavior|Biological Evolution|Computational Biology|Models, Biological', 'Journal Article', '10.1371/journal.pcbi.1005774', '28972973', 'We study through a reaction-diffusion algorithm the influence of landscape diversity on the efficiency of search dynamics. Remarkably, the identical optimal search strategy arises in a wide variety of environments, provided the target density is sparse and the searchers information is restricted to its close vicinity. Our results strongly impact the current debate on the emergentist vs. evolutionary origins of animal foraging. The inherent character of the optimal solution (i.e., independent on the landscape for the broad scenarios assumed here) suggests an interpretation favoring the evolutionary view, as originally implied by the Lévy flight foraging hypothesis. The latter states that, under conditions of scarcity of information and sparse resources, some organisms must have evolved to exploit optimal strategies characterized by heavy-tailed truncated power-law distributions of move lengths. These results strongly suggest that Lévy strategies-and hence the selection pressure for the relevant adaptations-are robust with respect to large changes in habitat. In contrast, the usual emergentist explanation seems not able to explain how very similar Lévy walks can emerge from all the distinct non-Lévy foraging strategies that are needed for the observed large variety of specific environments. We also report that deviations from Lévy can take place in plentiful ecosystems, where locomotion truncation is very frequent due to high encounter rates. So, in this case normal diffusion strategies-performing as effectively as the optimal one-can naturally emerge from Lévy. Our results constitute the strongest theoretical evidence to date supporting the evolutionary origins of experimentally observed Lévy walks.'),
(88678, 2017, 'plos', 'Ten simple rules in considering a career in academia versus government', 'Bourne, Philip E', 'Data Science Institute and Department of Biomedical Engineering, University of Virginia, Charlottesville, Virginia, United States of America.', 'United States', 2, 'Career Choice|Government|Guidelines as Topic|Humans|Universities', 'Editorial', '10.1371/journal.pcbi.1005729', '28981499', '-'),
(88679, 2017, 'plos', 'Differential temperature sensitivity of synaptic and firing processes in a neural mass model of epileptic discharges explains heterogeneous response of experimental epilepsy to focal brain cooling', 'Soriano, Jaymar|Kubo, Takatomi|Inoue, Takao|Kida, Hiroyuki|Yamakawa, Toshitaka|Suzuki, Michiyasu|Ikeda, Kazushi', 'Mathematical Informatics Laboratory, Graduate School of Information Science, Nara Institute of Science and Technology, Ikoma, Japan.|Mathematical Informatics Laboratory, Graduate School of Information Science, Nara Institute of Science and Technology, Ikoma, Japan.|Department of Neurosurgery, Yamaguchi University Graduate School of Medicine, Ube, Japan.|Department of Physiology, Yamaguchi University Graduate School of Medicine, Ube, Japan.|Organization for Innovation and Excellence, Kumamoto University, Kumamoto, Japan.|Department of Neurosurgery, Yamaguchi University Graduate School of Medicine, Ube, Japan.|Mathematical Informatics Laboratory, Graduate School of Information Science, Nara Institute of Science and Technology, Ikoma, Japan.', 'Japan|Japan|Japan|Japan|Japan|Japan|Japan', 0, 'Animals|Body Temperature|Brain|Cold Temperature|Computational Biology|Disease Models, Animal|Epilepsy|Hypothermia, Induced|Male|Models, Neurological|Rats|Rats, Sprague-Dawley|Synaptic Potentials|Synaptic Transmission', 'Journal Article', '10.1371/journal.pcbi.1005736', '28981509', 'Experiments with drug-induced epilepsy in rat brains and epileptic human brain region reveal that focal cooling can suppress epileptic discharges without affecting the brains normal neurological function. Findings suggest a viable treatment for intractable epilepsy cases via an implantable cooling device. However, precise mechanisms by which cooling suppresses epileptic discharges are still not clearly understood. Cooling experiments in vitro presented evidence of reduction in neurotransmitter release from presynaptic terminals and loss of dendritic spines at post-synaptic terminals offering a possible synaptic mechanism. We show that termination of epileptic discharges is possible by introducing a homogeneous temperature factor in a neural mass model which attenuates the post-synaptic impulse responses of the neuronal populations. This result however may be expected since such attenuation leads to reduced post-synaptic potential and when the effect on inhibitory interneurons is less than on excitatory interneurons, frequency of firing of pyramidal cells is consequently reduced. While this is observed in cooling experiments in vitro, experiments in vivo exhibit persistent discharges during cooling but suppressed in magnitude. This leads us to conjecture that reduction in the frequency of discharges may be compensated through intrinsic excitability mechanisms. Such compensatory mechanism is modelled using a reciprocal temperature factor in the firing response function in the neural mass model. We demonstrate that the complete model can reproduce attenuation of both magnitude and frequency of epileptic discharges during cooling. The compensatory mechanism suggests that cooling lowers the average and the variance of the distribution of threshold potential of firing across the population. Bifurcation study with respect to the temperature parameters of the model reveals how heterogeneous response of epileptic discharges to cooling (termination or suppression only) is exhibited. Possibility of differential temperature effects on post-synaptic potential generation of different populations is also explored.'),
(88680, 2017, 'plos', 'A unifying Bayesian account of contextual effects in value-based choice', 'Rigoli, Francesco|Mathys, Christoph|Friston, Karl J|Dolan, Raymond J', 'The Wellcome Trust Centre for Neuroimaging, UCL, 12 Queen Square, London, United Kingdom.|Scuola Internazionale Superiore di Studi Avanzati (SISSA), Trieste, Italy.|The Wellcome Trust Centre for Neuroimaging, UCL, 12 Queen Square, London, United Kingdom.|The Wellcome Trust Centre for Neuroimaging, UCL, 12 Queen Square, London, United Kingdom.', 'United Kingdom|Italy|United Kingdom|United Kingdom', 0, 'Bayes Theorem|Brain|Choice Behavior|Decision Making|Forecasting|Humans|Motivation|Reward', 'Journal Article', '10.1371/journal.pcbi.1005769', '28981514', 'Empirical evidence suggests the incentive value of an option is affected by other options available during choice and by options presented in the past. These contextual effects are hard to reconcile with classical theories and have inspired accounts where contextual influences play a crucial role. However, each account only addresses one or the other of the empirical findings and a unifying perspective has been elusive. Here, we offer a unifying theory of context effects on incentive value attribution and choice based on normative Bayesian principles. This formulation assumes that incentive value corresponds to a precision-weighted prediction error, where predictions are based upon expectations about reward. We show that this scheme explains a wide range of contextual effects, such as those elicited by other options available during choice (or within-choice context effects). These include both conditions in which choice requires an integration of multiple attributes and conditions where a multi-attribute integration is not necessary. Moreover, the same scheme explains context effects elicited by options presented in the past or between-choice context effects. Our formulation encompasses a wide range of contextual influences (comprising both within- and between-choice effects) by calling on Bayesian principles, without invoking ad-hoc assumptions. This helps clarify the contextual nature of incentive value and choice behaviour and may offer insights into psychopathologies characterized by dysfunctional decision-making, such as addiction and pathological gambling.'),
(88681, 2017, 'plos', 'Designing a course model for distance-based online bioinformatics training in Africa: The H3ABioNet experience', 'Gurwitz, Kim T|Aron, Shaun|Panji, Sumir|Maslamoney, Suresh|Fernandes, Pedro L|Judge, David P|Ghouila, Amel|Domelevo Entfellner, Jean-Baka|Guerfali, Fatma Z|Saunders, Colleen|Mansour Alzohairy, Ahmed|Salifu, Samson P|Ahmed, Rehab|Cloete, Ruben|Kayondo, Jonathan|Ssemwanga, Deogratius|Mulder, Nicola|H3ABioNet Consortiums Education Training and Working Group as members of the H3Africa Consortium', 'Computational Biology Division, Department of Integrative Biomedical Sciences, Institute of Infectious Disease and Molecular Medicine, University of Cape Town, Cape Town, 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, Cape Town, South Africa.|Computational Biology Division, Department of Integrative Biomedical Sciences, Institute of Infectious Disease and Molecular Medicine, University of Cape Town, Cape Town, South Africa.|Instituto Gulbenkian de Ciência, Oeiras, Portugal.|Independent bioinformatics training specialist, Cambridge, United Kingdom.|Institut Pasteur de Tunis, LR11IPT02, Laboratory Transmission, Control and Immunobiology of Infections (LTCII), Tunis-Belvédère, Tunisia.|South African National Bioinformatics Institute, Medical Research Council Unit for Bioinformatics Capacity Development, University of the Western Cape, Bellville, South Africa.|Institut Pasteur de Tunis, LR11IPT02, Laboratory Transmission, Control and Immunobiology of Infections (LTCII), Tunis-Belvédère, Tunisia.|South African National Bioinformatics Institute, Medical Research Council Unit for Bioinformatics Capacity Development, University of the Western Cape, Bellville, South Africa.|Genetics Department, Faculty of Agriculture, Zagazig University, Zagazig, Egypt.|Department of Biochemistry and Biotechnology, Kumasi Centre for Collaborative Research, Kwame Nkrumah University of Science and Technology, Kumasi, Ghana.|Centre for Bioinformatics and Systems Biology, Faculty of Science, University of Khartoum, Khartoum, Sudan.|South African National Bioinformatics Institute, Medical Research Council Unit for Bioinformatics Capacity Development, University of the Western Cape, Bellville, South Africa.|Uganda Virus Research Institute, Entebbe, Uganda.|Uganda Virus Research Institute, Entebbe, Uganda.|Computational Biology Division, Department of Integrative Biomedical Sciences, Institute of Infectious Disease and Molecular Medicine, University of Cape Town, Cape Town, South Africa.|Computational Biology Division, Department of Integrative Biomedical Sciences, Institute of Infectious Disease and Molecular Medicine, University of Cape Town, Cape Town, South Africa.', 'South Africa|South Africa|South Africa|South Africa|Portugal|United Kingdom|Tunisia|South Africa|Tun', 7, 'Africa|Computational Biology|Computer-Assisted Instruction|Databases, Factual|Humans|Internet|User-Computer Interface', 'Journal Article', '10.1371/journal.pcbi.1005715', '28981516', 'Africa is not unique in its need for basic bioinformatics training for individuals from a diverse range of academic backgrounds. However, particular logistical challenges in Africa, most notably access to bioinformatics expertise and internet stability, must be addressed in order to meet this need on the continent. H3ABioNet (www.h3abionet.org), the Pan African Bioinformatics Network for H3Africa, has therefore developed an innovative, free-of-charge Introduction to Bioinformatics course, taking these challenges into account as part of its educational efforts to provide on-site training and develop local expertise inside its network. A multiple-delivery-mode learning model was selected for this 3-month course in order to increase access to (mostly) African, expert bioinformatics trainers. The content of the course was developed to include a range of fundamental bioinformatics topics at the introductory level. For the first iteration of the course (2016), classrooms with a total of 364 enrolled participants were hosted at 20 institutions across 10 African countries. To ensure that classroom success did not depend on stable internet, trainers pre-recorded their lectures, and classrooms downloaded and watched these locally during biweekly contact sessions. The trainers were available via video conferencing to take questions during contact sessions, as well as via online question and discussion forums outside of contact session time. This learning model, developed for a resource-limited setting, could easily be adapted to other settings.'),
(88682, 2017, 'plos', 'The ins and outs of vanillyl alcohol oxidase: Identification of ligand migration paths', 'Gygli, Gudrun|Lucas, Maria Fátima|Guallar, Victor|van Berkel, Willem J H', 'Laboratory of Biochemistry, Wageningen University & Research, Stippeneng 4, WE Wageningen, The Netherlands.|Joint BSC-IRB Research Program in Computational Biology, Barcelona Supercomputing Center, Jordi Girona 29, Barcelona, Spain.|Joint BSC-IRB Research Program in Computational Biology, Barcelona Supercomputing Center, Jordi Girona 29, Barcelona, Spain.|Laboratory of Biochemistry, Wageningen University & Research, Stippeneng 4, WE Wageningen, The Netherlands.', 'Netherlands|Spain|Spain|Netherlands', 0, 'Alcohol Oxidoreductases|Amino Acid Sequence|Bacterial Proteins|Binding Sites|Crystallography, X-Ray|Flavin-Adenine Dinucleotide|Hydrogen Peroxide|Kinetics|Ligands|Mixed Function Oxygenases|Models, Molecular|Molecular Docking Simulation|Monte Carlo Method|Oxygen|Phenols|Protein Conformation|Protein Subunits|Sequence Alignment', 'Comparative Study', '10.1371/journal.pcbi.1005787', '28985219', 'Vanillyl alcohol oxidase (VAO) is a homo-octameric flavoenzyme belonging to the VAO/PCMH family. Each VAO subunit consists of two domains, the FAD-binding and the cap domain. VAO catalyses, among other reactions, the two-step conversion of p-creosol (2-methoxy-4-methylphenol) to vanillin (4-hydroxy-3-methoxybenzaldehyde). To elucidate how different ligands enter and exit the secluded active site, Monte Carlo based simulations have been performed. One entry/exit path via the subunit interface and two additional exit paths have been identified for phenolic ligands, all leading to the si side of FAD. We argue that the entry/exit path is the most probable route for these ligands. A fourth path leading to the re side of FAD has been found for the co-ligands dioxygen and hydrogen peroxide. Based on binding energies and on the behaviour of ligands in these four paths, we propose a sequence of events for ligand and co-ligand migration during catalysis. We have also identified two residues, His466 and Tyr503, which could act as concierges of the active site for phenolic ligands, as well as two other residues, Tyr51 and Tyr408, which could act as a gateway to the re side of FAD for dioxygen. Most of the residues in the four paths are also present in VAOs closest relatives, eugenol oxidase and p-cresol methylhydroxylase. Key path residues show movements in our simulations that correspond well to conformations observed in crystal structures of these enzymes. Preservation of other path residues can be linked to the electron acceptor specificity and oligomerisation state of the three enzymes. This study is the first comprehensive overview of ligand and co-ligand migration in a member of the VAO/PCMH family, and provides a proof of concept for the use of an unbiased method to sample this process.'),
(88683, 2017, 'plos', 'Inferring oscillatory modulation in neural spike trains', 'Arai, Kensuke|Kass, Robert E', 'Department of Statistics, Carnegie Mellon University, Pittsburgh, Pennsylvania, United States of America.|Department of Statistics, Carnegie Mellon University, Pittsburgh, Pennsylvania, United States of America.', 'United States|United States', 2, 'Action Potentials|Animals|Computational Biology|Electroencephalography|Models, Neurological|Models, Theoretical|Motor Cortex|Motor Neurons|Rats|Theta Rhythm', 'Journal Article', '10.1371/journal.pcbi.1005596', '28985231', 'Oscillations are observed at various frequency bands in continuous-valued neural recordings like the electroencephalogram (EEG) and local field potential (LFP) in bulk brain matter, and analysis of spike-field coherence reveals that spiking of single neurons often occurs at certain phases of the global oscillation. Oscillatory modulation has been examined in relation to continuous-valued oscillatory signals, and independently from the spike train alone, but behavior or stimulus triggered firing-rate modulation, spiking sparseness, presence of slow modulation not locked to stimuli and irregular oscillations with large variability in oscillatory periods, present challenges to searching for temporal structures present in the spike train. In order to study oscillatory modulation in real data collected under a variety of experimental conditions, we describe a flexible point-process framework we call the Latent Oscillatory Spike Train (LOST) model to decompose the instantaneous firing rate in biologically and behaviorally relevant factors: spiking refractoriness, event-locked firing rate non-stationarity, and trial-to-trial variability accounted for by baseline offset and a stochastic oscillatory modulation. We also extend the LOST model to accommodate changes in the modulatory structure over the duration of the experiment, and thereby discover trial-to-trial variability in the spike-field coherence of a rat primary motor cortical neuron to the LFP theta rhythm. Because LOST incorporates a latent stochastic auto-regressive term, LOST is able to detect oscillations when the firing rate is low, the modulation is weak, and when the modulating oscillation has a broad spectral peak.'),
(88684, 2017, 'plos', 'A Bayesian approach to modelling heterogeneous calcium responses in cell populations', 'Tilxc5xabnaitxc4x97, Agne|Croft, Wayne|Russell, Noah|Bellamy, Tomas C|Thul, Rxc3xbcdiger', 'School of Mathematical Sciences, University of Nottingham, Nottingham, England, United Kingdom.|School of Life Sciences, University of Nottingham, Nottingham, England, United Kingdom.|Department of Electrical and Electronic Engineering, University of Nottingham, Nottingham, England, United Kingdom.|School of Life Sciences, University of Nottingham, Nottingham, England, United Kingdom.|School of Mathematical Sciences, University of Nottingham, Nottingham, England, United Kingdom.', 'United Kingdom|United Kingdom|United Kingdom|United Kingdom|United Kingdom', 0, 'Action Potentials|Bayes Theorem|Calcium|Calcium Signaling|Carbachol|Cholinergic Agonists|HEK293 Cells|Humans|Models, Biological|Single-Cell Analysis|Time Factors', 'Journal Article', '10.1371/journal.pcbi.1005794', '28985235', 'Calcium responses have been observed as spikes of the whole-cell calcium concentration in numerous cell types and are essential for translating extracellular stimuli into cellular responses. While there are several suggestions for how this encoding is achieved, we still lack a comprehensive theory. To achieve this goal it is necessary to reliably predict the temporal evolution of calcium spike sequences for a given stimulus. Here, we propose a modelling framework that allows us to quantitatively describe the timing of calcium spikes. Using a Bayesian approach, we show that Gaussian processes model calcium spike rates with high fidelity and perform better than standard tools such as peri-stimulus time histograms and kernel smoothing. We employ our modelling concept to analyse calcium spike sequences from dynamically-stimulated HEK293T cells. Under these conditions, different cells often experience diverse stimulus time courses, which is a situation likely to occur in vivo. This single cell variability and the concomitant small number of calcium spikes per cell pose a significant modelling challenge, but we demonstrate that Gaussian processes can successfully describe calcium spike rates in these circumstances. Our results therefore pave the way towards a statistical description of heterogeneous calcium oscillations in a dynamic environment.');
INSERT INTO `papers` (`id`, `ano`, `journal`, `titulo`, `autores`, `afiliacao`, `pais`, `citacoes`, `palavra_chave`, `categorias`, `doi`, `pubmed`, `abstract`) VALUES
(88685, 2017, 'plos', 'Object detection through search with a foveated visual system', 'Akbas, Emre|Eckstein, Miguel P', 'Department of Psychological and Brain Sciences, University of California, Santa Barbara, Santa Barbara, California, United States of America.|Department of Psychological and Brain Sciences, University of California, Santa Barbara, Santa Barbara, California, United States of America.', 'United States|United States', 12, 'Animals|Attention|Biomimetics|Computer Simulation|Eye Movements|Fixation, Ocular|Fovea Centralis|Humans|Models, Neurological|Pattern Recognition, Automated|Pattern Recognition, Visual|Space Perception|Visual Cortex|Visual Fields', 'Journal Article', '10.1371/journal.pcbi.1005743', '28991906', 'Humans and many other species sense visual information with varying spatial resolution across the visual field (foveated vision) and deploy eye movements to actively sample regions of interests in scenes. The advantage of such varying resolution architecture is a reduced computational, hence metabolic cost. But what are the performance costs of such processing strategy relative to a scheme that processes the visual field at high spatial resolution? Here we first focus on visual search and combine object detectors from computer vision with a recent model of peripheral pooling regions found at the V1 layer of the human visual system. We develop a foveated object detector that processes the entire scene with varying resolution, uses retino-specific object detection classifiers to guide eye movements, aligns its fovea with regions of interest in the input image and integrates observations across multiple fixations. We compared the foveated object detector against a non-foveated version of the same object detector which processes the entire image at homogeneous high spatial resolution. We evaluated the accuracy of the foveated and non-foveated object detectors identifying 20 different objects classes in scenes from a standard computer vision data set (the PASCAL VOC 2007 dataset). We show that the foveated object detector can approximate the performance of the object detector with homogeneous high spatial resolution processing while bringing significant computational cost savings. Additionally, we assessed the impact of foveation on the computation of bottom-up saliency. An implementation of a simple foveated bottom-up saliency model with eye movements showed agreement in the selection of top salient regions of scenes with those selected by a non-foveated high resolution saliency model. Together, our results might help explain the evolution of foveated visual systems with eye movements as a solution that preserves perceptual performance in visual search while resulting in computational and metabolic savings to the brain.'),
(88686, 2017, 'plos', 'Clonal dominance and transplantation dynamics in hematopoietic stem cell compartments', 'Ashcroft, Peter|Manz, Markus G|Bonhoeffer, Sebastian', 'Institut für Integrative Biologie, ETH Zürich, Zürich, Switzerland.|Division of Hematology, University Hospital Zürich and University of Zürich, Zürich, Switzerland.|Institut für Integrative Biologie, ETH Zürich, Zürich, Switzerland.', 'Switzerland|Switzerland|Switzerland', 8, 'Animals|Computational Biology|Hematopoiesis|Hematopoietic Stem Cell Transplantation|Hematopoietic Stem Cells|Mice|Models, Biological|Stem Cell Niche', 'Journal Article', '10.1371/journal.pcbi.1005803', '28991922', 'Hematopoietic stem cells in mammals are known to reside mostly in the bone marrow, but also transitively passage in small numbers in the blood. Experimental findings have suggested that they exist in a dynamic equilibrium, continuously migrating between these two compartments. Here we construct an individual-based mathematical model of this process, which is parametrised using existing empirical findings from mice. This approach allows us to quantify the amount of migration between the bone marrow niches and the peripheral blood. We use this model to investigate clonal hematopoiesis, which is a significant risk factor for hematologic cancers. We also analyse the engraftment of donor stem cells into non-conditioned and conditioned hosts, quantifying the impact of different treatment scenarios. The simplicity of the model permits a thorough mathematical analysis, providing deeper insights into the dynamics of both the model and of the real-world system. We predict the time taken for mutant clones to expand within a host, as well as chimerism levels that can be expected following transplantation therapy, and the probability that a preconditioned host is reconstituted by donor cells.'),
(88687, 2017, 'plos', 'Image-based model of the spectrin cytoskeleton for red blood cell simulation', 'Fai, Thomas G|Leo-Macias, Alejandra|Stokes, David L|Peskin, Charles S', 'John A. Paulson School of Engineering and Applied Sciences, Harvard University, Cambridge, Massachusetts, United States of America.|Leon H. Charney Division of Cardiology, New York University School of Medicine, New York, New York, United States of America.|Skirball Institute of Biomolecular Medicine, Department of Cell Biology, New York University School of Medicine, New York, New York, United States of America.|Courant Institute of Mathematical Sciences, New York University, New York, New York, United States of America.', 'United States|United States|United States|United States', 0, 'Algorithms|Cytoskeleton|Elasticity|Erythrocyte Deformability|Erythrocytes|Humans|Image Processing, Computer-Assisted|Models, Biological|Spectrin', 'Journal Article', '10.1371/journal.pcbi.1005790', '28991926', 'We simulate deformable red blood cells in the microcirculation using the immersed boundary method with a cytoskeletal model that incorporates structural details revealed by tomographic images. The elasticity of red blood cells is known to be supplied by both their lipid bilayer membranes, which resist bending and local changes in area, and their cytoskeletons, which resist in-plane shear. The cytoskeleton consists of spectrin tetramers that are tethered to the lipid bilayer by ankyrin and by actin-based junctional complexes. We model the cytoskeleton as a random geometric graph, with nodes corresponding to junctional complexes and with edges corresponding to spectrin tetramers such that the edge lengths are given by the end-to-end distances between nodes. The statistical properties of this graph are based on distributions gathered from three-dimensional tomographic images of the cytoskeleton by a segmentation algorithm. We show that the elastic response of our model cytoskeleton, in which the spectrin polymers are treated as entropic springs, is in good agreement with the experimentally measured shear modulus. By simulating red blood cells in flow with the immersed boundary method, we compare this discrete cytoskeletal model to an existing continuum model and predict the extent to which dynamic spectrin network connectivity can protect against failure in the case of a red cell subjected to an applied strain. The methods presented here could form the basis of disease- and patient-specific computational studies of hereditary diseases affecting the red cell cytoskeleton.'),
(88688, 2017, 'plos', 'General principles of binding between cell surface receptors and multi-specific ligands: A computational study', 'Chen, Jiawen|Almo, Steven C|Wu, Yinghao', 'Department of Systems and Computational Biology, Albert Einstein College of Medicine, Bronx, New York, United States of America.|Department of Biochemistry, Albert Einstein College of Medicine, Bronx, New York, United States of America.|Department of Systems and Computational Biology, Albert Einstein College of Medicine, Bronx, New York, United States of America.', 'United States|United States|United States', 0, 'Algorithms|Binding Sites|Computational Biology|Ligands|Molecular Dynamics Simulation|Monte Carlo Method|Protein Binding|Receptors, Cell Surface', 'Journal Article', '10.1371/journal.pcbi.1005805', '29016600', 'The interactions between membrane receptors and extracellular ligands control cell-cell and cell-substrate adhesion, and environmental responsiveness by representing the initial steps of cell signaling pathways. These interactions can be spatial-temporally regulated when different extracellular ligands are tethered. The detailed mechanisms of this spatial-temporal regulation, including the competition between distinct ligands with overlapping binding sites and the conformational flexibility in multi-specific ligand assemblies have not been quantitatively evaluated. We present a new coarse-grained model to realistically simulate the binding process between multi-specific ligands and membrane receptors on cell surfaces. The model simplifies each receptor and each binding site in a multi-specific ligand as a rigid body. Different numbers or types of ligands are spatially organized together in the simulation. These designs were used to test the relation between the overall binding of a multi-specific ligand and the affinity of its cognate binding site. When a variety of ligands are exposed to cells expressing different densities of surface receptors, we demonstrated that ligands with reduced affinities have higher specificity to distinguish cells based on the relative concentrations of their receptors. Finally, modification of intramolecular flexibility was shown to play a role in optimizing the binding between receptors and ligands. In summary, our studies bring new insights to the general principles of ligand-receptor interactions. Future applications of our method will pave the way for new strategies to generate next-generation biologics.'),
(88689, 2017, 'plos', 'Neural coding in the visual system of Drosophila melanogaster: How do small neural populations support visually guided behaviours?', 'Dewar, Alex D M|Wystrach, Antoine|Philippides, Andrew|Graham, Paul', 'Department of Informatics, University of Sussex, Falmer, Brighton, United Kingdom.|Centre de Recherches sur la Cognition Animale, Centre National de la Recherche Scientifique, Université Paul Sabatier, Toulouse, France.|Department of Informatics, University of Sussex, Falmer, Brighton, United Kingdom.|School of Life Sciences, University of Sussex, Falmer, Brighton, United Kingdom.', 'United Kingdom|France|United Kingdom|United Kingdom', 0, 'Animals|Behavior, Animal|Drosophila melanogaster|Models, Neurological|Neural Networks (Computer)|Neurons|Pattern Recognition, Visual|Visual Cortex', 'Journal Article', '10.1371/journal.pcbi.1005735', '29016606', 'All organisms wishing to survive and reproduce must be able to respond adaptively to a complex, changing world. Yet the computational power available is constrained by biology and evolution, favouring mechanisms that are parsimonious yet robust. Here we investigate the information carried in small populations of visually responsive neurons in Drosophila melanogaster. These so-called ring neurons, projecting to the ellipsoid body of the central complex, are reported to be necessary for complex visual tasks such as pattern recognition and visual navigation. Recently the receptive fields of these neurons have been mapped, allowing us to investigate how well they can support such behaviours. For instance, in a simulation of classic pattern discrimination experiments, we show that the pattern of output from the ring neurons matches observed fly behaviour. However, performance of the neurons (as with flies) is not perfect and can be easily improved with the addition of extra neurons, suggesting the neurons receptive fields are not optimised for recognising abstract shapes, a conclusion which casts doubt on cognitive explanations of fly behaviour in pattern recognition assays. Using artificial neural networks, we then assess how easy it is to decode more general information about stimulus shape from the ring neuron population codes. We show that these neurons are well suited for encoding information about size, position and orientation, which are more relevant behavioural parameters for a fly than abstract pattern properties. This leads us to suggest that in order to understand the properties of neural systems, one must consider how perceptual circuits put information at the service of behaviour.'),
(88690, 2017, 'plos', 'The structured low temperature phase of the retinal population code', 'Ioffe, Mark L|Berry, Michael J', 'Department of Physics, Princeton University, Princeton, New Jersey, United States of America.|Princeton Neuroscience Institute, Princeton University, Princeton, New Jersey, United States of America.', 'Jersey|Jersey', 4, 'Action Potentials|Ambystoma|Animals|Cold Temperature|Computational Biology|Entropy|Models, Neurological|Photic Stimulation|Retina|Retinal Ganglion Cells', 'Journal Article', '10.1371/journal.pcbi.1005792', '29020014', 'Recent advances in experimental techniques have allowed the simultaneous recordings of populations of hundreds of neurons, fostering a debate about the nature of the collective structure of population neural activity. Much of this debate has focused on the empirical findings of a phase transition in the parameter space of maximum entropy models describing the measured neural probability distributions, interpreting this phase transition to indicate a critical tuning of the neural code. Here, we instead focus on the possibility that this is a first-order phase transition which provides evidence that the real neural population is in a structured, collective state. We show that this collective state is robust to changes in stimulus ensemble and adaptive state. We find that the pattern of pairwise correlations between neurons has a strength that is well within the strongly correlated regime and does not require fine tuning, suggesting that this state is generic for populations of 100+ neurons. We find a clear correspondence between the emergence of a phase transition, and the emergence of attractor-like structure in the inferred energy landscape. A collective state in the neural population, in which neural activity patterns naturally form clusters, provides a consistent interpretation for our results.'),
(88691, 2017, 'plos', 'Women are underrepresented in computational biology: An analysis of the scholarly literature in biology, computer science and computational biology', 'Bonham, Kevin S|Stefan, Melanie I', 'Microbiology and Immunobiology, Harvard Medical School, Boston, Massachusetts, United States of America.|Centre for Integrative Physiology, Edinburgh Medical School, Biomedical Sciences, University of Edinburgh, Edinburgh, United Kingdom.', 'United States|United Kingdom', 19, 'Authorship|Biology|Career Choice|Computational Biology|Female|Humans|Information Science|Publications|Sex Distribution|Women', 'Journal Article', '10.1371/journal.pcbi.1005134', '29023441', 'While women are generally underrepresented in STEM fields, there are noticeable differences between fields. For instance, the gender ratio in biology is more balanced than in computer science. We were interested in how this difference is reflected in the interdisciplinary field of computational/quantitative biology. To this end, we examined the proportion of female authors in publications from the PubMed and arXiv databases. There are fewer female authors on research papers in computational biology, as compared to biology in general. This is true across authorship position, year, and journal impact factor. A comparison with arXiv shows that quantitative biology papers have a higher ratio of female authors than computer science papers, placing computational biology in between its two parent fields in terms of gender representation. Both in biology and in computational biology, a female last author increases the probability of other authors on the paper being female, pointing to a potential role of female PIs in influencing the gender balance.'),
(88692, 2017, 'plos', 'Systematic, network-based characterization of therapeutic target inhibitors', 'Shen, Yao|Alvarez, Mariano J|Bisikirska, Brygida|Lachmann, Alexander|Realubit, Ronald|Pampou, Sergey|Coku, Jorida|Karan, Charles|Califano, Andrea', 'Department of Systems Biology, Columbia University, New York, New York, United States of America.|Department of Systems Biology, Columbia University, New York, New York, United States of America.|Department of Systems Biology, Columbia University, New York, New York, United States of America.|Department of Systems Biology, Columbia University, New York, New York, United States of America.|JP Sulzberger Columbia Genome Center, Columbia University, New York, New York, United States of America.|JP Sulzberger Columbia Genome Center, Columbia University, New York, New York, United States of America.|Department of Systems Biology, Columbia University, New York, New York, United States of America.|JP Sulzberger Columbia Genome Center, Columbia University, New York, New York, United States of America.|Department of Systems Biology, Columbia University, New York, New York, United States of America.', 'United States|United States|United States|United States|United States|United States|United States|Un', 0, 'Antineoplastic Agents|Cell Line, Tumor|Computational Biology|Drug Discovery|Humans|Neoplasm Proteins|Neoplasms|Protein Interaction Mapping|Proto-Oncogene Proteins c-myc|STAT3 Transcription Factor', 'Journal Article', '10.1371/journal.pcbi.1005599', '29023443', 'A large fraction of the proteins that are being identified as key tumor dependencies represent poor pharmacological targets or lack clinically-relevant small-molecule inhibitors. Availability of fully generalizable approaches for the systematic and efficient prioritization of tumor-context specific protein activity inhibitors would thus have significant translational value. Unfortunately, inhibitor effects on protein activity cannot be directly measured in systematic and proteome-wide fashion by conventional biochemical assays. We introduce OncoLead, a novel network based approach for the systematic prioritization of candidate inhibitors for arbitrary targets of therapeutic interest. In vitro and in vivo validation confirmed that OncoLead analysis can recapitulate known inhibitors as well as prioritize novel, context-specific inhibitors of difficult targets, such as MYC and STAT3. We used OncoLead to generate the first unbiased drug/regulator interaction map, representing compounds modulating the activity of cancer-relevant transcription factors, with potential in precision medicine.'),
(88693, 2017, 'plos', 'Ten simple rules for writing a response to reviewers', 'Noble, William Stafford', 'Departments of Genome Sciences and Computer Science and Engineering, University of Washington, Seattle, Washington, United States of America.', 'United States', 8, 'Guidelines as Topic|Peer Review, Research|Writing', 'Editorial', '10.1371/journal.pcbi.1005730', '29023444', '-'),
(88694, 2017, 'plos', 'Identifying direct contacts between protein complex subunits from their conditional dependence in proteomics datasets', 'Drew, Kevin|Müller, Christian L|Bonneau, Richard|Marcotte, Edward M', 'Center for Systems and Synthetic Biology, Department of Molecular Biosciences, University of Texas at Austin, Austin, TX, United States of America.|Flatiron Institute, Center for Computational Biology, Simons Foundation, New York, NY, United States of America.|Flatiron Institute, Center for Computational Biology, Simons Foundation, New York, NY, United States of America.|Center for Systems and Synthetic Biology, Department of Molecular Biosciences, University of Texas at Austin, Austin, TX, United States of America.', 'United States|United States|United States|United States', 10, 'Bacterial Proteins|Cell Line|Databases, Protein|Humans|Mass Spectrometry|Models, Molecular|Multiprotein Complexes|Protein Conformation|Protein Subunits|Proteomics', 'Journal Article', '10.1371/journal.pcbi.1005625', '29023445', 'Determining the three dimensional arrangement of proteins in a complex is highly beneficial for uncovering mechanistic function and interpreting genetic variation in coding genes comprising protein complexes. There are several methods for determining co-complex interactions between proteins, among them co-fractionation / mass spectrometry (CF-MS), but it remains difficult to identify directly contacting subunits within a multi-protein complex. Correlation analysis of CF-MS profiles shows promise in detecting protein complexes as a whole but is limited in its ability to infer direct physical contacts among proteins in sub-complexes. To identify direct protein-protein contacts within human protein complexes we learn a sparse conditional dependency graph from approximately 3,000 CF-MS experiments on human cell lines. We show substantial performance gains in estimating direct interactions compared to correlation analysis on a benchmark of large protein complexes with solved three-dimensional structures. We demonstrate the methods value in determining the three dimensional arrangement of proteins by making predictions for complexes without known structure (the exocyst and tRNA multi-synthetase complex) and by establishing evidence for the structural position of a recently discovered component of the core human EKC/KEOPS complex, GON7/C14ORF142, providing a more complete 3D model of the complex. Direct contact prediction provides easily calculable additional structural information for large-scale protein complex mapping studies and should be broadly applicable across organisms as more CF-MS datasets become available.'),
(88695, 2017, 'plos', 'Network approaches and applications in biology', 'Ideker, Trey|Nussinov, Ruth', 'Department of Medicine, University of California San Diego, La Jolla, California, United States of America.|Cancer and Inflammation Program, Leidos Biomedical Research, Inc., Frederick National Laboratory for Cancer Research, National Cancer Institute at Frederick, Frederick, Maryland, United States of America.', 'United States|United States', 17, 'Computational Biology', 'Editorial', '10.1371/journal.pcbi.1005771', '29023447', '-'),
(88696, 2017, 'plos', 'Structural host-microbiota interaction networks', 'Guven-Maiorov, Emine|Tsai, Chung-Jung|Nussinov, Ruth', 'Cancer and Inflammation Program, Leidos Biomedical Research, Inc. Frederick National Laboratory for Cancer Research, National Cancer Institute, Frederick, MD, United States of America.|Cancer and Inflammation Program, Leidos Biomedical Research, Inc. Frederick National Laboratory for Cancer Research, National Cancer Institute, Frederick, MD, United States of America.|Cancer and Inflammation Program, Leidos Biomedical Research, Inc. Frederick National Laboratory for Cancer Research, National Cancer Institute, Frederick, MD, United States of America.', 'United States|United States|United States', 19, 'Animals|Computational Biology|Humans|Mice|Microbiota|Models, Molecular|Molecular Mimicry|Protein Interaction Maps|Symbiosis|Toll-Like Receptors', 'Journal Article', '10.1371/journal.pcbi.1005579', '29023448', 'Hundreds of different species colonize multicellular organisms making them metaorganisms. A growing body of data supports the role of microbiota in health and in disease. Grasping the principles of host-microbiota interactions (HMIs) at the molecular level is important since it may provide insights into the mechanisms of infections. The crosstalk between the host and the microbiota may help resolve puzzling questions such as how a microorganism can contribute to both health and disease. Integrated superorganism networks that consider host and microbiota as a whole-may uncover their code, clarifying perhaps the most fundamental question: how they modulate immune surveillance. Within this framework, structural HMI networks can uniquely identify potential microbial effectors that target distinct host nodes or interfere with endogenous host interactions, as well as how mutations on either host or microbial proteins affect the interaction. Furthermore, structural HMIs can help identify master host cell regulator nodes and modules whose tweaking by the microbes promote aberrant activity. Collectively, these data can delineate pathogenic mechanisms and thereby help maximize beneficial therapeutics. To date, challenges in experimental techniques limit large-scale characterization of HMIs. Here we highlight an area in its infancy which we believe will increasingly engage the computational community: predicting interactions across kingdoms, and mapping these on the host cellular networks to figure out how commensal and pathogenic microbiota modulate the host signaling and broadly cross-species consequences.'),
(88697, 2017, 'plos', 'Network propagation in the cytoscape cyberinfrastructure', 'Carlin, Daniel E|Demchak, Barry|Pratt, Dexter|Sage, Eric|Ideker, Trey', 'Department of Medicine, University of California-San Diego, San Diego, California, United States of America.|Department of Medicine, University of California-San Diego, San Diego, California, United States of America.|Department of Medicine, University of California-San Diego, San Diego, California, United States of America.|Department of Medicine, University of California-San Diego, San Diego, California, United States of America.|Department of Medicine, University of California-San Diego, San Diego, California, United States of America.', 'United States|United States|United States|United States|United States', 23, 'Algorithms|Animals|Drug Resistance, Neoplasm|Indoles|Models, Biological|Mutation|Protein Interaction Mapping|Software|Sulfonamides|Systems Biology|Vemurafenib', 'Journal Article', '10.1371/journal.pcbi.1005598', '29023449', 'Network propagation is an important and widely used algorithm in systems biology, with applications in protein function prediction, disease gene prioritization, and patient stratification. However, up to this point it has required significant expertise to run. Here we extend the popular network analysis program Cytoscape to perform network propagation as an integrated function. Such integration greatly increases the access to network propagation by putting it in the hands of biologists and linking it to the many other types of network analysis and visualization available through Cytoscape. We demonstrate the power and utility of the algorithm by identifying mutations conferring resistance to Vemurafenib.'),
(88698, 2017, 'plos', 'Incorporating networks in a probabilistic graphical model to find drivers for complex human diseases', 'Mezlini, Aziz M|Goldenberg, Anna', 'Department of Computer Science, University of Toronto, Toronto, Ontario, Canada.|Department of Computer Science, University of Toronto, Toronto, Ontario, Canada.', 'Canada|Canada', 8, 'Algorithms|Autistic Disorder|Bayes Theorem|Computational Biology|Disease|Epilepsy|Gene Expression Profiling|Humans|Models, Statistical|Neoplasms|Protein Interaction Mapping|Schizophrenia', 'Journal Article', '10.1371/journal.pcbi.1005580', '29023450', 'Discovering genetic mechanisms driving complex diseases is a hard problem. Existing methods often lack power to identify the set of responsible genes. Protein-protein interaction networks have been shown to boost power when detecting gene-disease associations. We introduce a Bayesian framework, Conflux, to find disease associated genes from exome sequencing data using networks as a prior. There are two main advantages to using networks within a probabilistic graphical model. First, networks are noisy and incomplete, a substantial impediment to gene discovery. Incorporating networks into the structure of a probabilistic models for gene inference has less impact on the solution than relying on the noisy network structure directly. Second, using a Bayesian framework we can keep track of the uncertainty of each gene being associated with the phenotype rather than returning a fixed list of genes. We first show that using networks clearly improves gene detection compared to individual gene testing. We then show consistently improved performance of Conflux compared to the state-of-the-art diffusion network-based method Hotnet2 and a variety of other network and variant aggregation methods, using randomly generated and literature-reported gene sets. We test Hotnet2 and Conflux on several network configurations to reveal biases and patterns of false positives and false negatives in each case. Our experiments show that our novel Bayesian framework Conflux incorporates many of the advantages of the current state-of-the-art methods, while offering more flexibility and improved power in many gene-disease association scenarios.'),
(88699, 2017, 'plos', 'Vicus: Exploiting local structures to improve network-based analysis of biological data', 'Wang, Bo|Huang, Lin|Zhu, Yuke|Kundaje, Anshul|Batzoglou, Serafim|Goldenberg, Anna', 'Department of Computer Science, Stanford University, Stanford, California, United States of America.|Department of Computer Science, Stanford University, Stanford, California, United States of America.|Department of Computer Science, Stanford University, Stanford, California, United States of America.|Department of Computer Science, Stanford University, Stanford, California, United States of America.|Department of Computer Science, Stanford University, Stanford, California, United States of America.|SickKids Research Institute, Toronto, Ontario, Canada.', 'United States|United States|United States|United States|United States|Canada', 6, 'Algorithms|Animals|Cluster Analysis|Computational Biology|Escherichia coli|Gene Expression Profiling|Humans|Leukocytes|Mice|Models, Biological|Neoplasms|Protein Interaction Mapping', 'Journal Article', '10.1371/journal.pcbi.1005621', '29023470', 'Biological networks entail important topological features and patterns critical to understanding interactions within complicated biological systems. Despite a great progress in understanding their structure, much more can be done to improve our inference and network analysis. Spectral methods play a key role in many network-based applications. Fundamental to spectral methods is the Laplacian, a matrix that captures the global structure of the network. Unfortunately, the Laplacian does not take into account intricacies of the networks local structure and is sensitive to noise in the network. These two properties are fundamental to biological networks and cannot be ignored. We propose an alternative matrix Vicus. The Vicus matrix captures the local neighborhood structure of the network and thus is more effective at modeling biological interactions. We demonstrate the advantages of Vicus in the context of spectral methods by extensive empirical benchmarking on tasks such as single cell dimensionality reduction, protein module discovery and ranking genes for cancer subtyping. Our experiments show that using Vicus, spectral methods result in more accurate and robust performance in all of these tasks.'),
(88700, 2017, 'plos', 'The role of glutamate in neuronal ion homeostasis: A case study of spreading depolarization', 'Hxc3xbcbel, Niklas|Hosseini-Zare, Mahshid S|xc5xbdiburkus, Jokxc5xabbas|Ullah, Ghanim', 'Department of Physics, University of South Florida, Tampa, Florida, United States of America.|Department of Biology and Biochemistry, University of Houston, Houston, Texas, United States of America.|Department of Biology and Biochemistry, University of Houston, Houston, Texas, United States of America.|Department of Physics, University of South Florida, Tampa, Florida, United States of America.', 'United States|United States|United States|United States', 6, 'Animals|Aspartic Acid|Astrocytes|Brain Diseases|Cell Size|Computational Biology|Electrophysiological Phenomena|Glutamic Acid|Homeostasis|In Vitro Techniques|Ion Channels|Male|Membrane Potentials|Models, Neurological|N-Methylaspartate|Neurons|Rats|Rats, Sprague-Dawley|Receptors, AMPA|Visual Cortex', 'Journal Article', '10.1371/journal.pcbi.1005804', '29023523', 'Simultaneous changes in ion concentrations, glutamate, and cell volume together with exchange of matter between cell network and vasculature are ubiquitous in numerous brain pathologies. A complete understanding of pathological conditions as well as normal brain function, therefore, hinges on elucidating the molecular and cellular pathways involved in these mostly interdependent variations. In this paper, we develop the first computational framework that combines the Hodgkin-Huxley type spiking dynamics, dynamic ion concentrations and glutamate homeostasis, neuronal and astroglial volume changes, and ion exchange with vasculature into a comprehensive model to elucidate the role of glutamate uptake in the dynamics of spreading depolarization (SD)-the electrophysiological event underlying numerous pathologies including migraine, ischemic stroke, aneurysmal subarachnoid hemorrhage, intracerebral hematoma, and trauma. We are particularly interested in investigating the role of glutamate in the duration and termination of SD caused by K+ perfusion and oxygen-glucose deprivation. Our results demonstrate that glutamate signaling plays a key role in the dynamics of SD, and that impaired glutamate uptake leads to recovery failure of neurons from SD. We confirm predictions from our model experimentally by showing that inhibiting astrocytic glutamate uptake using TFB-TBOA nearly quadruples the duration of SD in layers 2-3 of visual cortical slices from juvenile rats. The model equations are either derived purely from first physical principles of electroneutrality, osmosis, and conservation of particles or a combination of these principles and known physiological facts. Accordingly, we claim that our approach can be used as a future guide to investigate the role of glutamate, ion concentrations, and dynamics cell volume in other brain pathologies and normal brain function.'),
(88701, 2017, 'plos', 'BeWith: A Between-Within method to discover relationships between cancer modules via integrated analysis of mutual exclusivity, co-occurrence and functional interactions', 'Dao, Phuong|Kim, Yoo-Ah|Wojtowicz, Damian|Madan, Sanna|Sharan, Roded|Przytycka, Teresa M', 'National Center of Biotechnology Information, National Library of Medicine, NIH, Bethesda, MD, United States of America.|National Center of Biotechnology Information, National Library of Medicine, NIH, Bethesda, MD, United States of America.|National Center of Biotechnology Information, National Library of Medicine, NIH, Bethesda, MD, United States of America.|Department of Computer Science, University of Maryland, College Park, MD, United States of America.|Blavatnik School of Computer Science, Tel Aviv University, Tel Aviv, Israel.|National Center of Biotechnology Information, National Library of Medicine, NIH, Bethesda, MD, United States of America.', 'United States|United States|United States|United States|Israel|United States', 13, 'Algorithms|Computational Biology|Gene Regulatory Networks|Humans|Intracellular Signaling Peptides and Proteins|Mutation|Neoplasms', 'Journal Article', '10.1371/journal.pcbi.1005695', '29023534', 'The analysis of the mutational landscape of cancer, including mutual exclusivity and co-occurrence of mutations, has been instrumental in studying the disease. We hypothesized that exploring the interplay between co-occurrence, mutual exclusivity, and functional interactions between genes will further improve our understanding of the disease and help to uncover new relations between cancer driving genes and pathways. To this end, we designed a general framework, BeWith, for identifying modules with different combinations of mutation and interaction patterns. We focused on three different settings of the BeWith schema: (i) BeME-WithFun, in which the relations between modules are enriched with mutual exclusivity, while genes within each module are functionally related, (ii) BeME-WithCo, which combines mutual exclusivity between modules with co-occurrence within modules, and (iii) BeCo-WithMEFun, which ensures co-occurrence between modules, while the within module relations combine mutual exclusivity and functional interactions. We formulated the BeWith framework using Integer Linear Programming (ILP), enabling us to find optimally scoring sets of modules. Our results demonstrate the utility of BeWith in providing novel information about mutational patterns, driver genes, and pathways. In particular, BeME-WithFun helped identify functionally coherent modules that might be relevant for cancer progression. In addition to finding previously well-known drivers, the identified modules pointed to other novel findings such as the interaction between NCOR2 and NCOA3 in breast cancer. Additionally, an application of the BeME-WithCo setting revealed that gene groups differ with respect to their vulnerability to different mutagenic processes, and helped us to uncover pairs of genes with potentially synergistic effects, including a potential synergy between mutations in TP53 and the metastasis related DCC gene. Overall, BeWith not only helped us uncover relations between potential driver genes and pathways, but also provided additional insights on patterns of the mutational landscape, going beyond cancer driving mutations. Implementation is available at https://www.ncbi.nlm.nih.gov/CBBresearch/Przytycka/software/bewith.html.'),
(88702, 2017, 'plos', 'A machine learning approach for predicting CRISPR-Cas9 cleavage efficiencies and patterns underlying its mechanism of action', 'Abadi, Shiran|Yan, Winston X|Amar, David|Mayrose, Itay', 'Department of Molecular Biology and Ecology of Plants, Tel Aviv University, Tel Aviv, Israel.|Broad Institute of MIT and Harvard, Cambridge, Massachusetts, United States of America.|Blavatnik School of Computer Science, Tel-Aviv University, Tel Aviv, Israel.|Department of Molecular Biology and Ecology of Plants, Tel Aviv University, Tel Aviv, Israel.', 'Israel|United States|Israel|Israel', 28, 'Algorithms|CRISPR-Cas Systems|Computational Biology|Gene Editing|Humans|Machine Learning|RNA, Guide|ROC Curve', 'Journal Article', '10.1371/journal.pcbi.1005807', '29036168', 'The adaptation of the CRISPR-Cas9 system as a genome editing technique has generated much excitement in recent years owing to its ability to manipulate targeted genes and genomic regions that are complementary to a programmed single guide RNA (sgRNA). However, the efficacy of a specific sgRNA is not uniquely defined by exact sequence homology to the target site, thus unintended off-targets might additionally be cleaved. Current methods for sgRNA design are mainly concerned with predicting off-targets for a given sgRNA using basic sequence features and employ elementary rules for ranking possible sgRNAs. Here, we introduce CRISTA (CRISPR Target Assessment), a novel algorithm within the machine learning framework that determines the propensity of a genomic site to be cleaved by a given sgRNA. We show that the predictions made with CRISTA are more accurate than other available methodologies. We further demonstrate that the occurrence of bulges is not a rare phenomenon and should be accounted for in the prediction process. Beyond predicting cleavage efficiencies, the learning process provides inferences regarding patterns that underlie the mechanism of action of the CRISPR-Cas9 system. We discover that attributes that describe the spatial structure and rigidity of the entire genomic site as well as those surrounding the PAM region are a major component of the prediction capabilities.'),
(88703, 2017, 'plos', 'Clusternomics: Integrative context-dependent clustering for heterogeneous datasets', 'Gabasova, Evelina|Reid, John|Wernisch, Lorenz', 'MRC Biostatistics Unit, University of Cambridge, Cambridge, United Kingdom.|MRC Biostatistics Unit, University of Cambridge, Cambridge, United Kingdom.|MRC Biostatistics Unit, University of Cambridge, Cambridge, United Kingdom.', 'United Kingdom|United Kingdom|United Kingdom', 11, 'Algorithms|Breast Neoplasms|Cluster Analysis|Computational Biology|Gene Expression Profiling|Humans|Survival Analysis', 'Journal Article', '10.1371/journal.pcbi.1005781', '29036190', 'Integrative clustering is used to identify groups of samples by jointly analysing multiple datasets describing the same set of biological samples, such as gene expression, copy number, methylation etc. Most existing algorithms for integrative clustering assume that there is a shared consistent set of clusters across all datasets, and most of the data samples follow this structure. However in practice, the structure across heterogeneous datasets can be more varied, with clusters being joined in some datasets and separated in others. In this paper, we present a probabilistic clustering method to identify groups across datasets that do not share the same cluster structure. The proposed algorithm, Clusternomics, identifies groups of samples that share their global behaviour across heterogeneous datasets. The algorithm models clusters on the level of individual datasets, while also extracting global structure that arises from the local cluster assignments. Clusters on both the local and the global level are modelled using a hierarchical Dirichlet mixture model to identify structure on both levels. We evaluated the model both on simulated and on real-world datasets. The simulated data exemplifies datasets with varying degrees of common structure. In such a setting Clusternomics outperforms existing algorithms for integrative and consensus clustering. In a real-world application, we used the algorithm for cancer subtyping, identifying subtypes of cancer from heterogeneous datasets. We applied the algorithm to TCGA breast cancer dataset, integrating gene expression, miRNA expression, DNA methylation and proteomics. The algorithm extracted clinically meaningful clusters with significantly different survival probabilities. We also evaluated the algorithm on lung and kidney cancer TCGA datasets with high dimensionality, again showing clinically significant results and scalability of the algorithm.'),
(88704, 2017, 'plos', 'A quadratically regularized functional canonical correlation analysis for identifying the global structure of pleiotropy with NGS data', 'Lin, Nan|Zhu, Yun|Fan, Ruzong|Xiong, Momiao', 'Department of Biostatistics and Data Science, School of Public Health, The University of Texas Health Science Center at Houston, Houston, TX, United States of America.|Department of Epidemiology, Tulane University School of Public Health and Tropical Medicine, New Orleans, LA, United States of America.|Biostatistics and Bioinformatics Branch (BBB), Division of Intramural Population Health Research (DIPHR), Eunice Kennedy Shriver National Institute of Child Health and Human Development, National Institutes of Health (NIH), Bethesda, MD, United States of America.|Department of Biostatistics and Data Science, School of Public Health, The University of Texas Health Science Center at Houston, Houston, TX, United States of America.', 'United States|United States|United States|United States', 1, 'Algorithms|Computational Biology|Computer Simulation|Databases, Genetic|Genetic Pleiotropy|Genome-Wide Association Study|High-Throughput Nucleotide Sequencing|Humans|Models, Statistical|Phenotype|Polymorphism, Single Nucleotide|Principal Component Analysis|Sequence Analysis, DNA', 'Journal Article', '10.1371/journal.pcbi.1005788', '29040274', 'Investigating the pleiotropic effects of genetic variants can increase statistical power, provide important information to achieve deep understanding of the complex genetic structures of disease, and offer powerful tools for designing effective treatments with fewer side effects. However, the current multiple phenotype association analysis paradigm lacks breadth (number of phenotypes and genetic variants jointly analyzed at the same time) and depth (hierarchical structure of phenotype and genotypes). A key issue for high dimensional pleiotropic analysis is to effectively extract informative internal representation and features from high dimensional genotype and phenotype data. To explore correlation information of genetic variants, effectively reduce data dimensions, and overcome critical barriers in advancing the development of novel statistical methods and computational algorithms for genetic pleiotropic analysis, we proposed a new statistic method referred to as a quadratically regularized functional CCA (QRFCCA) for association analysis which combines three approaches: (1) quadratically regularized matrix factorization, (2) functional data analysis and (3) canonical correlation analysis (CCA). Large-scale simulations show that the QRFCCA has a much higher power than that of the ten competing statistics while retaining the appropriate type 1 errors. To further evaluate performance, the QRFCCA and ten other statistics are applied to the whole genome sequencing dataset from the TwinsUK study. We identify a total of 79 genes with rare variants and 67 genes with common variants significantly associated with the 46 traits using QRFCCA. The results show that the QRFCCA substantially outperforms the ten other statistics.'),
(88705, 2017, 'plos', 'Analysis of temporal transcription expression profiles reveal links between protein function and developmental stages of Drosophila melanogaster', 'Wan, Cen|Lees, Jonathan G|Minneci, Federico|Orengo, Christine A|Jones, David T', 'Department of Computer Science, University College London, London, United Kingdom.|Institute of Structural and Molecular Biology, University College London, London, United Kingdom.|Department of Computer Science, University College London, London, United Kingdom.|Institute of Structural and Molecular Biology, University College London, London, United Kingdom.|Department of Computer Science, University College London, London, United Kingdom.', 'United Kingdom|United Kingdom|United Kingdom|United Kingdom|United Kingdom', 4, 'Animals|Cluster Analysis|Computational Biology|Computer Simulation|Drosophila Proteins|Drosophila melanogaster|Gene Expression Profiling|Models, Statistical|Phenotype|Transcriptome', 'Journal Article', '10.1371/journal.pcbi.1005791', '29045400', 'Accurate gene or protein function prediction is a key challenge in the post-genome era. Most current methods perform well on molecular function prediction, but struggle to provide useful annotations relating to biological process functions due to the limited power of sequence-based features in that functional domain. In this work, we systematically evaluate the predictive power of temporal transcription expression profiles for protein function prediction in Drosophila melanogaster. Our results show significantly better performance on predicting protein function when transcription expression profile-based features are integrated with sequence-derived features, compared with the sequence-derived features alone. We also observe that the combination of expression-based and sequence-based features leads to further improvement of accuracy on predicting all three domains of gene function. Based on the optimal feature combinations, we then propose a novel multi-classifier-based function prediction method for Drosophila melanogaster proteins, FFPred-fly+. Interpreting our machine learning models also allows us to identify some of the underlying links between biological processes and developmental stages of Drosophila melanogaster.'),
(88706, 2017, 'plos', 'Bayesian refinement of protein structures and ensembles against SAXS data using molecular dynamics', 'Shevchuk, Roman|Hub, Jochen S', 'Institute for Microbiology and Genetics, University of Göttingen, Göttingen, Germany.|Institute for Microbiology and Genetics, University of Göttingen, Göttingen, Germany.', 'Germany|Germany', 21, 'Bayes Theorem|Computational Biology|Molecular Dynamics Simulation|Protein Conformation|Proteins|Scattering, Small Angle|X-Ray Diffraction', 'Journal Article', '10.1371/journal.pcbi.1005800', '29045407', 'Small-angle X-ray scattering is an increasingly popular technique used to detect protein structures and ensembles in solution. However, the refinement of structures and ensembles against SAXS data is often ambiguous due to the low information content of SAXS data, unknown systematic errors, and unknown scattering contributions from the solvent. We offer a solution to such problems by combining Bayesian inference with all-atom molecular dynamics simulations and explicit-solvent SAXS calculations. The Bayesian formulation correctly weights the SAXS data versus prior physical knowledge, it quantifies the precision or ambiguity of fitted structures and ensembles, and it accounts for unknown systematic errors due to poor buffer matching. The method further provides a probabilistic criterion for identifying the number of states required to explain the SAXS data. The method is validated by refining ensembles of a periplasmic binding protein against calculated SAXS curves. Subsequently, we derive the solution ensembles of the eukaryotic chaperone heat shock protein 90 (Hsp90) against experimental SAXS data. We find that the SAXS data of the apo state of Hsp90 is compatible with a single wide-open conformation, whereas the SAXS data of Hsp90 bound to ATP or to an ATP-analogue strongly suggest heterogenous ensembles of a closed and a wide-open state.');
INSERT INTO `papers` (`id`, `ano`, `journal`, `titulo`, `autores`, `afiliacao`, `pais`, `citacoes`, `palavra_chave`, `categorias`, `doi`, `pubmed`, `abstract`) VALUES
(88707, 2017, 'plos', 'Unmet needs for analyzing biological big data: A survey of 704 NSF principal investigators', 'Barone, Lindsay|Williams, Jason|Micklos, David', 'DNA Learning Center, Cold Spring Harbor Laboratory, Cold Spring Harbor, New York, United States of America.|DNA Learning Center, Cold Spring Harbor Laboratory, Cold Spring Harbor, New York, United States of America.|DNA Learning Center, Cold Spring Harbor Laboratory, Cold Spring Harbor, New York, United States of America.', 'United States|United States|United States', 0, 'Computational Biology|Databases, Genetic|Humans|Research Personnel|United States', 'Journal Article', '10.1371/journal.pcbi.1005755', '29049281', 'In a 2016 survey of 704 National Science Foundation (NSF) Biological Sciences Directorate principal investigators (BIO PIs), nearly 90% indicated they are currently or will soon be analyzing large data sets. BIO PIs considered a range of computational needs important to their work, including high performance computing (HPC), bioinformatics support, multistep workflows, updated analysis software, and the ability to store, share, and publish data. Previous studies in the United States and Canada emphasized infrastructure needs. However, BIO PIs said the most pressing unmet needs are training in data integration, data management, and scaling analyses for HPC-acknowledging that data science skills will be required to build a deeper understanding of life. This portends a growing data knowledge gap in biology and challenges institutions and funding agencies to redouble their support for computational training in biology.'),
(88708, 2017, 'plos', 'Learning infectious disease epidemiology in a modern framework', 'Handel, Andreas', 'Department of Epidemiology and Biostatistics and Health Informatics Institute and Center for the Ecology of Infectious Diseases, The University of Georgia, Athens, Georgia, United States of America.', 'Georgia', 0, 'Communicable Diseases|Computational Biology|Computer Graphics|Humans|Models, Theoretical|Software|User-Computer Interface', 'Journal Article', '10.1371/journal.pcbi.1005642', '29049284', '-'),
(88709, 2017, 'plos', 'Seasonality in risk of pandemic influenza emergence', 'Fox, Spencer J|Miller, Joel C|Meyers, Lauren Ancel', 'Integrative Biology, The University of Texas at Austin, Austin, Texas, United States of America.|Mathematical Sciences, Monash University, Frankston, Victoria, Australia.|Integrative Biology, The University of Texas at Austin, Austin, Texas, United States of America.', 'United States|Australia|United States', 12, 'Computational Biology|Humans|Influenza, Human|Models, Biological|Pandemics|Risk|Seasons', 'Journal Article', '10.1371/journal.pcbi.1005749', '29049288', 'Influenza pandemics can emerge unexpectedly and wreak global devastation. However, each of the six pandemics since 1889 emerged in the Northern Hemisphere just after the flu season, suggesting that pandemic timing may be predictable. Using a stochastic model fit to seasonal flu surveillance data from the United States, we find that seasonal flu leaves a transient wake of heterosubtypic immunity that impedes the emergence of novel flu viruses. This refractory period provides a simple explanation for not only the spring-summer timing of historical pandemics, but also early increases in pandemic severity and multiple waves of transmission. Thus, pandemic risk may be seasonal and predictable, with the accuracy of pre-pandemic and real-time risk assessments hinging on reliable seasonal influenza surveillance and precise estimates of the breadth and duration of heterosubtypic immunity.'),
(88710, 2017, 'plos', 'A deep convolutional neural network for classification of red blood cells in sickle cell anemia', 'Xu, Mengjia|Papageorgiou, Dimitrios P|Abidi, Sabia Z|Dao, Ming|Zhao, Hong|Karniadakis, George Em', 'Key Laboratory of Medical Image Computing of Ministry of Education, Northeastern University, Shenyang, China.|Department of Materials Science and Engineering, Massachusetts Institute of Technology, Cambridge, Massachusetts, United States of America.|Department of Materials Science and Engineering, Massachusetts Institute of Technology, Cambridge, Massachusetts, United States of America.|Department of Materials Science and Engineering, Massachusetts Institute of Technology, Cambridge, Massachusetts, United States of America.|Key Laboratory of Medical Image Computing of Ministry of Education, Northeastern University, Shenyang, China.|Division of Applied Mathematics, Brown University, Providence, Rhode Island, United States of America.', 'China|United States|United States|United States|China|United States', 0, 'Anemia, Sickle Cell|Computational Biology|Erythrocytes|Humans|Image Interpretation, Computer-Assisted|Microscopy|Neural Networks (Computer)|Pattern Recognition, Automated', 'Journal Article', '10.1371/journal.pcbi.1005746', '29049291', 'Sickle cell disease (SCD) is a hematological disorder leading to blood vessel occlusion accompanied by painful episodes and even death. Red blood cells (RBCs) of SCD patients have diverse shapes that reveal important biomechanical and bio-rheological characteristics, e.g. their density, fragility, adhesive properties, etc. Hence, having an objective and effective way of RBC shape quantification and classification will lead to better insights and eventual better prognosis of the disease. To this end, we have developed an automated, high-throughput, ex-vivo RBC shape classification framework that consists of three stages. First, we present an automatic hierarchical RBC extraction method to detect the RBC region (ROI) from the background, and then separate touching RBCs in the ROI images by applying an improved random walk method based on automatic seed generation. Second, we apply a mask-based RBC patch-size normalization method to normalize the variant size of segmented single RBC patches into uniform size. Third, we employ deep convolutional neural networks (CNNs) to realize RBC classification, the alternating convolution and pooling operations can deal with non-linear and complex patterns. Furthermore, we investigate the specific shape factor quantification for the classified RBC image data in order to develop a general multiscale shape analysis. We perform several experiments on raw microscopy image datasets from 8 SCD patients (over 7,000 single RBC images) through a 5-fold cross validation method both for oxygenated and deoxygenated RBCs. We demonstrate that the proposed framework can successfully classify sickle shape RBCs in an automated manner with high accuracy, and we also provide the corresponding shape factor analysis, which can be used synergistically with the CNN analysis for more robust predictions. Moreover, the trained deep CNN exhibits good performance even for a deoxygenated dataset and distinguishes the subtle differences in texture alteration inside the oxygenated and deoxygenated RBCs.'),
(88711, 2017, 'plos', 'Deconvolving sequence features that discriminate between overlapping regulatory annotations', 'Kakumanu, Akshay|Velasco, Silvia|Mazzoni, Esteban|Mahony, Shaun', 'Center for Eukaryotic Gene Regulation, Department of Biochemistry & Molecular Biology, The Pennsylvania State University, University Park, PA, United States of America.|Department of Biology, New York University, 100 Washington Square East, New York, NY, United States of America.|Department of Biology, New York University, 100 Washington Square East, New York, NY, United States of America.|Center for Eukaryotic Gene Regulation, Department of Biochemistry & Molecular Biology, The Pennsylvania State University, University Park, PA, United States of America.', 'United States|United States|United States|United States', 5, 'Binding Sites|Cell Line|Cell Lineage|Chromatin|Computational Biology|Deoxyribonuclease I|Embryonic Stem Cells|Gene Expression Regulation|Genetic Loci|High-Throughput Nucleotide Sequencing|Humans|Molecular Sequence Annotation|Promoter Regions, Genetic|Regulatory Sequences, Nucleic Acid|Software|Transcription Factors', 'Journal Article', '10.1371/journal.pcbi.1005795', '29049320', 'Genomic loci with regulatory potential can be annotated with various properties. For example, genomic sites bound by a given transcription factor (TF) can be divided according to whether they are proximal or distal to known promoters. Sites can be further labeled according to the cell types and conditions in which they are active. Given such a collection of labeled sites, it is natural to ask what sequence features are associated with each annotation label. However, discovering such label-specific sequence features is often confounded by overlaps between the labels, e.g. if regulatory sites specific to a given cell type are also more likely to be promoter-proximal, it is difficult to assess whether motifs identified in that set of sites are associated with the cell type or associated with promoters. In order to meet this challenge, we developed SeqUnwinder, a principled approach to deconvolving interpretable discriminative sequence features associated with overlapping annotation labels. We demonstrate the novel analysis abilities of SeqUnwinder using three examples. Firstly, SeqUnwinder is able to unravel sequence features associated with the dynamic binding behavior of TFs during motor neuron programming from features associated with chromatin state in the initial embryonic stem cells. Secondly, we characterize distinct sequence properties of multi-condition and cell-specific TF binding sites after controlling for uneven associations with promoter proximity. Finally, we demonstrate the scalability of SeqUnwinder to discover cell-specific sequence features from over one hundred thousand genomic loci that display DNase I hypersensitivity in one or more ENCODE cell lines.'),
(88712, 2017, 'plos', 'Quantifying the strength of quorum sensing crosstalk within microbial communities', 'Silva, Kalinga Pavan T|Chellamuthu, Prithiviraj|Boedicker, James Q', 'Department of Physics and Astronomy, University of Southern California, Los Angeles, CA, United States of America.|Department of Physics and Astronomy, University of Southern California, Los Angeles, CA, United States of America.|Department of Physics and Astronomy, University of Southern California, Los Angeles, CA, United States of America.', 'United States|United States|United States', 0, 'Acyl-Butyrolactones|Bacterial Physiological Phenomena|Bacterial Proteins|Gram-Negative Bacteria|Models, Biological|Quorum Sensing|Signal Transduction', 'Journal Article', '10.1371/journal.pcbi.1005809', '29049387', 'In multispecies microbial communities, the exchange of signals such as acyl-homoserine lactones (AHL) enables communication within and between species of Gram-negative bacteria. This process, commonly known as quorum sensing, aids in the regulation of genes crucial for the survival of species within heterogeneous populations of microbes. Although signal exchange was studied extensively in well-mixed environments, less is known about the consequences of crosstalk in spatially distributed mixtures of species. Here, signaling dynamics were measured in a spatially distributed system containing multiple strains utilizing homologous signaling systems. Crosstalk between strains containing the lux, las and rhl AHL-receptor circuits was quantified. In a distributed population of microbes, the impact of community composition on spatio-temporal dynamics was characterized and compared to simulation results using a modified reaction-diffusion model. After introducing a single term to account for crosstalk between each pair of signals, the model was able to reproduce the activation patterns observed in experiments. We quantified the robustness of signal propagation in the presence of interacting signals, finding that signaling dynamics are largely robust to interference. The ability of several wild isolates to participate in AHL-mediated signaling was investigated, revealing distinct signatures of crosstalk for each species. Our results present a route to characterize crosstalk between species and predict systems-level signaling dynamics in multispecies communities.'),
(88713, 2017, 'plos', 'Distinct prediction errors in mesostriatal circuits of the human brain mediate learning about the values of both states and actions: evidence from high-resolution fMRI', 'Colas, Jaron T|Pauli, Wolfgang M|Larsen, Tobias|Tyszka, J Michael|ODoherty, John P', 'Computation and Neural Systems Program, California Institute of Technology, Pasadena, CA, United States of America.|Computation and Neural Systems Program, California Institute of Technology, Pasadena, CA, United States of America.|Division of the Humanities and Social Sciences, California Institute of Technology, Pasadena, CA, United States of America.|Division of the Humanities and Social Sciences, California Institute of Technology, Pasadena, CA, United States of America.|Computation and Neural Systems Program, California Institute of Technology, Pasadena, CA, United States of America.', 'United States|United States|United States|United States|United States', 5, 'Adaptation, Physiological|Brain Mapping|Computer Simulation|Corpus Striatum|Humans|Image Enhancement|Magnetic Resonance Imaging|Mental Recall|Mesencephalon|Models, Neurological|Nerve Net|Neuronal Plasticity|Reinforcement (Psychology)', 'Journal Article', '10.1371/journal.pcbi.1005810', '29049406', 'Prediction-error signals consistent with formal models of reinforcement learning (RL) have repeatedly been found within dopaminergic nuclei of the midbrain and dopaminoceptive areas of the striatum. However, the precise form of the RL algorithms implemented in the human brain is not yet well determined. Here, we created a novel paradigm optimized to dissociate the subtypes of reward-prediction errors that function as the key computational signatures of two distinct classes of RL models-namely, actor/critic models and action-value-learning models (e.g., the Q-learning model). The state-value-prediction error (SVPE), which is independent of actions, is a hallmark of the actor/critic architecture, whereas the action-value-prediction error (AVPE) is the distinguishing feature of action-value-learning algorithms. To test for the presence of these prediction-error signals in the brain, we scanned human participants with a high-resolution functional magnetic-resonance imaging (fMRI) protocol optimized to enable measurement of neural activity in the dopaminergic midbrain as well as the striatal areas to which it projects. In keeping with the actor/critic model, the SVPE signal was detected in the substantia nigra. The SVPE was also clearly present in both the ventral striatum and the dorsal striatum. However, alongside these purely state-value-based computations we also found evidence for AVPE signals throughout the striatum. These high-resolution fMRI findings suggest that model-free aspects of reward learning in humans can be explained algorithmically with RL in terms of an actor/critic mechanism operating in parallel with a system for more direct action-value learning.'),
(88714, 2017, 'plos', 'Automated deconvolution of structured mixtures from heterogeneous tumor genomic data', 'Roman, Theodore|Xie, Lu|Schwartz, Russell', 'Computational Biology Department, School of Computer Science, Carnegie Mellon University, Pittsburgh, Pennsylvania, United States of America.|Computational Biology Department, School of Computer Science, Carnegie Mellon University, Pittsburgh, Pennsylvania, United States of America.|Computational Biology Department, School of Computer Science, Carnegie Mellon University, Pittsburgh, Pennsylvania, United States of America.', 'United States|United States|United States', 3, 'Breast Neoplasms|Chromosome Mapping|Data Interpretation, Statistical|Female|Gene Dosage|Gene Expression Profiling|Genes, Neoplasm|High-Throughput Nucleotide Sequencing|Humans|Reproducibility of Results|Sensitivity and Specificity|Sequence Analysis, DNA', 'Comparative Study', '10.1371/journal.pcbi.1005815', '29059177', 'With increasing appreciation for the extent and importance of intratumor heterogeneity, much attention in cancer research has focused on profiling heterogeneity on a single patient level. Although true single-cell genomic technologies are rapidly improving, they remain too noisy and costly at present for population-level studies. Bulk sequencing remains the standard for population-scale tumor genomics, creating a need for computational tools to separate contributions of multiple tumor clones and assorted stromal and infiltrating cell populations to pooled genomic data. All such methods are limited to coarse approximations of only a few cell subpopulations, however. In prior work, we demonstrated the feasibility of improving cell type deconvolution by taking advantage of substructure in genomic mixtures via a strategy called simplicial complex unmixing. We improve on past work by introducing enhancements to automate learning of substructured genomic mixtures, with specific emphasis on genome-wide copy number variation (CNV) data, as well as the ability to process quantitative RNA expression data, and heterogeneous combinations of RNA and CNV data. We introduce methods for dimensionality estimation to better decompose mixture model substructure, fuzzy clustering to better identify substructure in sparse, noisy data, and automated model inference methods for other key model parameters. We further demonstrate their effectiveness in identifying mixture substructure in true breast cancer CNV data from the Cancer Genome Atlas (TCGA). Source code is available at https://github.com/tedroman/WSCUnmix.'),
(88715, 2017, 'plos', 'Diverse type 2 diabetes genetic risk factors functionally converge in a phenotype-focused gene network', 'Sandor, Cynthia|Beer, Nicola L|Webber, Caleb', 'Department of Physiology, Anatomy and Genetics, University of Oxford, Oxford, United Kingdom.|Oxford Centre for Diabetes, Endocrinology and Metabolism, Radcliffe Department of Medicine, University of Oxford, Oxford, United Kingdom.|Department of Physiology, Anatomy and Genetics, University of Oxford, Oxford, United Kingdom.', 'United Kingdom|United Kingdom|United Kingdom', 7, 'Diabetes Mellitus, Type 2|Gene Regulatory Networks|Genetic Markers|Genetic Predisposition to Disease|Genetic Variation|Genome-Wide Association Study|Humans|Polymorphism, Single Nucleotide|Prevalence|Proteome|Reproducibility of Results|Risk Factors|Sensitivity and Specificity', 'Journal Article', '10.1371/journal.pcbi.1005816', '29059180', 'Type 2 Diabetes (T2D) constitutes a global health burden. Efforts to uncover predisposing genetic variation have been considerable, yet detailed knowledge of the underlying pathogenesis remains poor. Here, we constructed a T2D phenotypic-linkage network (T2D-PLN), by integrating diverse gene functional information that highlight genes, which when disrupted in mice, elicit similar T2D-relevant phenotypes. Sensitising the network to T2D-relevant phenotypes enabled significant functional convergence to be detected between genes implicated in monogenic or syndromic diabetes and genes lying within genomic regions associated with T2D common risk. We extended these analyses to a recent multiethnic T2D case-control exome of 12,940 individuals that found no evidence of T2D risk association for rare frequency variants outside of previously known T2D risk loci. Examining associations involving protein-truncating variants (PTV), most at low population frequencies, the T2D-PLN was able to identify a convergent set of biological pathways that were perturbed within four of five independent T2D case/control ethnic sets of 2000 to 5000 exomes each. These same pathways were found to be over-represented among both known monogenic or syndromic diabetes genes and genes within T2D-associated common risk loci. Our study demonstrates convergent biology amongst variants representing different classes of T2D genetic risk. Although convergence was observed at the pathway level, few of the contributing genes were found in common between different cohorts or variant classes, most notably between the exome variant sets which suggests that future rare variant studies may be better focusing their power onto a single population of recent common ancestry.'),
(88716, 2017, 'plos', 'Machine learning to design integral membrane channelrhodopsins for efficient eukaryotic expression and plasma membrane localization', 'Bedbrook, Claire N|Yang, Kevin K|Rice, Austin J|Gradinaru, Viviana|Arnold, Frances H', 'Division of Biology and Biological Engineering, California Institute of Technology, Pasadena, California, United States of America.|Division of Chemistry and Chemical Engineering, California Institute of Technology, Pasadena, California, United States of America.|Division of Chemistry and Chemical Engineering, California Institute of Technology, Pasadena, California, United States of America.|Division of Biology and Biological Engineering, California Institute of Technology, Pasadena, California, United States of America.|Division of Biology and Biological Engineering, California Institute of Technology, Pasadena, California, United States of America.', 'United States|United States|United States|United States|United States', 24, 'Cell Membrane|Drug Design|HEK293 Cells|Humans|Ion Channels|Lipid Bilayers|Machine Learning|Rhodopsin|Sequence Analysis, Protein|Structure-Activity Relationship|Subcellular Fractions', 'Journal Article', '10.1371/journal.pcbi.1005786', '29059183', 'There is growing interest in studying and engineering integral membrane proteins (MPs) that play key roles in sensing and regulating cellular response to diverse external signals. A MP must be expressed, correctly inserted and folded in a lipid bilayer, and trafficked to the proper cellular location in order to function. The sequence and structural determinants of these processes are complex and highly constrained. Here we describe a predictive, machine-learning approach that captures this complexity to facilitate successful MP engineering and design. Machine learning on carefully-chosen training sequences made by structure-guided SCHEMA recombination has enabled us to accurately predict the rare sequences in a diverse library of channelrhodopsins (ChRs) that express and localize to the plasma membrane of mammalian cells. These light-gated channel proteins of microbial origin are of interest for neuroscience applications, where expression and localization to the plasma membrane is a prerequisite for function. We trained Gaussian process (GP) classification and regression models with expression and localization data from 218 ChR chimeras chosen from a 118,098-variant library designed by SCHEMA recombination of three parent ChRs. We use these GP models to identify ChRs that express and localize well and show that our models can elucidate sequence and structure elements important for these processes. We also used the predictive models to convert a naturally occurring ChR incapable of mammalian localization into one that localizes well.'),
(88717, 2017, 'plos', 'Decoding brain activity using a large-scale probabilistic functional-anatomical atlas of human cognition', 'Rubin, Timothy N|Koyejo, Oluwasanmi|Gorgolewski, Krzysztof J|Jones, Michael N|Poldrack, Russell A|Yarkoni, Tal', 'Department of Psychological and Brain Sciences, Indiana University Bloomington, Bloomington, IN, United States of America.|Department of Computer Science, University of Illinois at Urbana-Champaign, Urbana, IL, United States of America.|Department of Psychology, Stanford University, Stanford, CA, United States of America.|Department of Psychological and Brain Sciences, Indiana University Bloomington, Bloomington, IN, United States of America.|Department of Psychology, Stanford University, Stanford, CA, United States of America.|Department of Psychology, University of Texas at Austin, Austin, TX, United States of America.', 'India|United States|United States|India|United States|United States', 18, 'Brain|Brain Mapping|Cognition|Humans|Image Processing, Computer-Assisted|Magnetic Resonance Imaging|Models, Neurological', 'Journal Article', '10.1371/journal.pcbi.1005649', '29059185', 'A central goal of cognitive neuroscience is to decode human brain activity-that is, to infer mental processes from observed patterns of whole-brain activation. Previous decoding efforts have focused on classifying brain activity into a small set of discrete cognitive states. To attain maximal utility, a decoding framework must be open-ended, systematic, and context-sensitive-that is, capable of interpreting numerous brain states, presented in arbitrary combinations, in light of prior information. Here we take steps towards this objective by introducing a probabilistic decoding framework based on a novel topic model-Generalized Correspondence Latent Dirichlet Allocation-that learns latent topics from a database of over 11,000 published fMRI studies. The model produces highly interpretable, spatially-circumscribed topics that enable flexible decoding of whole-brain images. Importantly, the Bayesian nature of the model allows one to seed decoder priors with arbitrary images and text-enabling researchers, for the first time, to generate quantitative, context-sensitive interpretations of whole-brain patterns of brain activity.'),
(88718, 2017, 'plos', 'Identification of immune signatures predictive of clinical protection from malaria', 'Valletta, John Joseph|Recker, Mario', 'Centre for Mathematics and the Environment, University of Exeter, Penryn Campus, Penryn, United Kingdom.|Centre for Mathematics and the Environment, University of Exeter, Penryn Campus, Penryn, United Kingdom.', 'United Kingdom|United Kingdom', 11, 'Adolescent|Adult|Aging|Antigens, Protozoan|Autoantibodies|Biomarkers|Child|Child, Preschool|Disease Susceptibility|Humans|Immunity, Innate|Infant|Machine Learning|Malaria|Plasmodium falciparum|Young Adult', 'Journal Article', '10.1371/journal.pcbi.1005812', '29065113', 'Antibodies are thought to play an essential role in naturally acquired immunity to malaria. Prospective cohort studies have frequently shown how continuous exposure to the malaria parasite Plasmodium falciparum cause an accumulation of specific responses against various antigens that correlate with a decreased risk of clinical malaria episodes. However, small effect sizes and the often polymorphic nature of immunogenic parasite proteins make the robust identification of the true targets of protective immunity ambiguous. Furthermore, the degree of individual-level protection conferred by elevated responses to these antigens has not yet been explored. Here we applied a machine learning approach to identify immune signatures predictive of individual-level protection against clinical disease. We find that commonly assumed immune correlates are poor predictors of clinical protection in children. On the other hand, antibody profiles predictive of an individuals malaria protective status can be found in data comprising responses to a large set of diverse parasite proteins. We show that this pattern emerges only after years of continuous exposure to the malaria parasite, whereas susceptibility to clinical episodes in young hosts (< 10 years) cannot be ascertained by measured antibody responses alone.'),
(88719, 2017, 'plos', 'Neural field model to reconcile structure with function in primary visual cortex', 'Rankin, James|Chavane, Frédéric', 'Department of Mathematics, University of Exeter, Exeter, United Kingdom.|Institut de Neurosciences de la Timone, CNRS & Aix-Marseille Université, Faculté de Médecine, Marseille, France.', 'United Kingdom|France', 3, 'Animals|Computer Simulation|Humans|Models, Neurological|Nerve Net|Visual Cortex|Visual Fields|Visual Pathways|Visual Perception', 'Journal Article', '10.1371/journal.pcbi.1005821', '29065120', 'Voltage-sensitive dye imaging experiments in primary visual cortex (V1) have shown that local, oriented visual stimuli elicit stable orientation-selective activation within the stimulus retinotopic footprint. The cortical activation dynamically extends far beyond the retinotopic footprint, but the peripheral spread stays non-selective-a surprising finding given a number of anatomo-functional studies showing the orientation specificity of long-range connections. Here we use a computational model to investigate this apparent discrepancy by studying the expected population response using known published anatomical constraints. The dynamics of input-driven localized states were simulated in a planar neural field model with multiple sub-populations encoding orientation. The realistic connectivity profile has parameters controlling the clustering of long-range connections and their orientation bias. We found substantial overlap between the anatomically relevant parameter range and a steep decay in orientation selective activation that is consistent with the imaging experiments. In this way our study reconciles the reported orientation bias of long-range connections with the functional expression of orientation selective neural activity. Our results demonstrate this sharp decay is contingent on three factors, that long-range connections are sufficiently diffuse, that the orientation bias of these connections is in an intermediate range (consistent with anatomy) and that excitation is sufficiently balanced by inhibition. Conversely, our modelling results predict that, for reduced inhibition strength, spurious orientation selective activation could be generated through long-range lateral connections. Furthermore, if the orientation bias of lateral connections is very strong, or if inhibition is particularly weak, the network operates close to an instability leading to unbounded cortical activation.'),
(88720, 2017, 'plos', 'Prediction of HIV-1 sensitivity to broadly neutralizing antibodies shows a trend towards resistance over time', 'Hake, Anna|Pfeifer, Nico', 'Department Computational Biology and Applied Algorithmics, Max Planck Institute for Informatics, Saarland Informatics Campus, Saarbrücken, Germany.|Department Computational Biology and Applied Algorithmics, Max Planck Institute for Informatics, Saarland Informatics Campus, Saarbrücken, Germany.', 'Germany|Germany', 8, 'Antibodies, Neutralizing|Binding Sites|CD4 Antigens|Drug Resistance, Viral|Epitope Mapping|HIV Antibodies|HIV-1|Humans|Protein Binding|Protein Interaction Mapping|Sequence Analysis, Protein|Time Factors', 'Journal Article', '10.1371/journal.pcbi.1005789', '29065122', 'Treatment with broadly neutralizing antibodies (bNAbs) has proven effective against HIV-1 infections in humanized mice, non-human primates, and humans. Due to the high mutation rate of HIV-1, resistance testing of the patients viral strains to the bNAbs is still inevitable. So far, bNAb resistance can only be tested in expensive and time-consuming neutralization experiments. Here, we introduce well-performing computational models that predict the neutralization response of HIV-1 to bNAbs given only the envelope sequence of the virus. Using non-linear support vector machines based on a string kernel, the models learnt even the important binding sites of bNAbs with more complex epitopes, i.e., the CD4 binding site targeting bNAbs, proving thereby the biological relevance of the models. To increase the interpretability of the models, we additionally provide a new kind of motif logo for each query sequence, visualizing those residues of the test sequence that influenced the prediction outcome the most. Moreover, we predicted the neutralization sensitivity of around 34,000 HIV-1 samples from different time points to a broad range of bNAbs, enabling the first analysis of HIV resistance to bNAbs on a global scale. The analysis showed for many of the bNAbs a trend towards antibody resistance over time, which had previously only been discovered for a small non-representative subset of the global HIV-1 population.'),
(88721, 2017, 'plos', 'Scaffolding the cup-shaped double membrane in autophagy', 'Bahrami, Amir Houshang|Lin, Mary G|Ren, Xuefeng|Hurley, James H|Hummer, Gerhard', 'Department of Theoretical Biophysics, Max Planck Institute of Biophysics, Frankfurt am Main, Germany.|Department of Molecular and Cell Biology and California Institute for Quantitative Biosciences, University of California, Berkeley, California, United States of America.|Department of Molecular and Cell Biology and California Institute for Quantitative Biosciences, University of California, Berkeley, California, United States of America.|Department of Molecular and Cell Biology and California Institute for Quantitative Biosciences, University of California, Berkeley, California, United States of America.|Department of Theoretical Biophysics, Max Planck Institute of Biophysics, Frankfurt am Main, Germany.', 'Germany|United States|United States|United States|Germany', 12, 'Autophagosomes|Autophagy|Autophagy-Related Proteins|Binding Sites|Cell Membrane|Computer Simulation|Membrane Fluidity|Membrane Fusion|Models, Chemical|Models, Molecular|Protein Binding|Protein Conformation|Saccharomyces cerevisiae Proteins', 'Journal Article', '10.1371/journal.pcbi.1005817', '29065154', 'Autophagy is a physiological process for the recycling and degradation of cellular materials. Forming the autophagosome from the phagophore, a cup-shaped double-membrane vesicle, is a critical step in autophagy. The origin of the cup shape of the phagophore is poorly understood. In yeast, fusion of a small number of Atg9-containing vesicles is considered a key step in autophagosome biogenesis, aided by Atg1 complexes (ULK1 in mammals) localized at the preautophagosomal structure (PAS). In particular, the S-shaped Atg17-Atg31-Atg29 subcomplex of Atg1 is critical for phagophore nucleation at the PAS. To study this process, we simulated membrane remodeling processes in the presence and absence of membrane associated Atg17. We show that at least three vesicles need to fuse to induce the phagophore shape, consistent with experimental observations. However, fusion alone is not sufficient. Interactions with 34-nm long, S-shaped Atg17 complexes are required to overcome a substantial kinetic barrier in the transition to the cup-shaped phagophore. Our finding rationalizes the recruitment of Atg17 complexes to the yeast PAS, and their unusual shape. In control simulations without Atg17, with weakly binding Atg17, or with straight instead of S-shaped Atg17, the membrane shape transition did not occur. We confirm the critical role of Atg17-membrane interactions experimentally by showing that mutations of putative membrane interaction sites result in reduction or loss of autophagic activity in yeast. Fusion of a small number of vesicles followed by Atg17-guided membrane shape-remodeling thus emerges as a viable route to phagophore formation.'),
(88722, 2017, 'plos', 'Transcriptomic correlates of neuron electrophysiological diversity', 'Tripathy, Shreejoy J|Toker, Lilah|Li, Brenna|Crichlow, Cindy-Lee|Tebaykin, Dmitry|Mancarci, B Ogan|Pavlidis, Paul', 'Michael Smith Laboratories and Department of Psychiatry, University of British Columbia, Vancouver, BC, Canada.|Michael Smith Laboratories and Department of Psychiatry, University of British Columbia, Vancouver, BC, Canada.|Michael Smith Laboratories and Department of Psychiatry, University of British Columbia, Vancouver, BC, Canada.|Michael Smith Laboratories and Department of Psychiatry, University of British Columbia, Vancouver, BC, Canada.|Michael Smith Laboratories and Department of Psychiatry, University of British Columbia, Vancouver, BC, Canada.|Michael Smith Laboratories and Department of Psychiatry, University of British Columbia, Vancouver, BC, Canada.|Michael Smith Laboratories and Department of Psychiatry, University of British Columbia, Vancouver, BC, Canada.', 'Canada|Canada|Canada|Canada|Canada|Canada|Canada', 13, 'Action Potentials|Animals|Brain|Gene Expression Profiling|Humans|Ion Channels|Membrane Potentials|Mice|Neurons|Synaptic Transmission|Transcriptome', 'Journal Article', '10.1371/journal.pcbi.1005814', '29069078', 'How neuronal diversity emerges from complex patterns of gene expression remains poorly understood. Here we present an approach to understand electrophysiological diversity through gene expression by integrating pooled- and single-cell transcriptomics with intracellular electrophysiology. Using neuroinformatics methods, we compiled a brain-wide dataset of 34 neuron types with paired gene expression and intrinsic electrophysiological features from publically accessible sources, the largest such collection to date. We identified 420 genes whose expression levels significantly correlated with variability in one or more of 11 physiological parameters. We next trained statistical models to infer cellular features from multivariate gene expression patterns. Such models were predictive of gene-electrophysiological relationships in an independent collection of 12 visual cortex cell types from the Allen Institute, suggesting that these correlations might reflect general principles relating expression patterns to phenotypic diversity across very different cell types. Many associations reported here have the potential to provide new insights into how neurons generate functional diversity, and correlations of ion channel genes like Gabrd and Scn1a (Nav1.1) with resting potential and spiking frequency are consistent with known causal mechanisms. Our work highlights the promise and inherent challenges in using cell type-specific transcriptomics to understand the mechanistic origins of neuronal diversity.'),
(88723, 2017, 'plos', 'Un-gating and allosteric modulation of a pentameric ligand-gated ion channel captured by molecular dynamics', 'Martin, Nicolas E|Malik, Siddharth|Calimet, Nicolas|Changeux, Jean-Pierre|Cecchini, Marco', 'Laboratoire dIngxc3xa9nierie des Fonctions Molxc3xa9culaire, ISIS, UMR 7006 CNRS, Universitxc3xa9 de Strasbourg, Strasbourg, France.|Laboratoire dIngxc3xa9nierie des Fonctions Molxc3xa9culaire, ISIS, UMR 7006 CNRS, Universitxc3xa9 de Strasbourg, Strasbourg, France.|Laboratoire dIngxc3xa9nierie des Fonctions Molxc3xa9culaire, ISIS, UMR 7006 CNRS, Universitxc3xa9 de Strasbourg, Strasbourg, France.|CNRS, URA 2182, F-75015 & Collxc3xa8ge de France, Paris, France.|Laboratoire dIngxc3xa9nierie des Fonctions Molxc3xa9culaire, ISIS, UMR 7006 CNRS, Universitxc3xa9 de Strasbourg, Strasbourg, France.', 'France|France|France|France|France', 15, 'Allosteric Regulation|Allosteric Site|Binding Sites|Chloride Channels|Glutamic Acid|Ion Channel Gating|Ivermectin|Ligand-Gated Ion Channels|Ligands|Models, Chemical|Molecular Dynamics Simulation|Neurotransmitter Agents|Protein Binding|Protein Conformation', 'Journal Article', '10.1371/journal.pcbi.1005784', '29069080', 'Pentameric ligand-gated ion channels (pLGICs) mediate intercellular communication at synapses through the opening of an ion pore in response to the binding of a neurotransmitter. Despite the increasing availability of high-resolution structures of pLGICs, a detailed understanding of the functional isomerization from closed to open (gating) and back is currently missing. Here, we provide the first atomistic description of the transition from open to closed (un-gating) in the glutamate-gated chloride channel (GluCl) from Caenorhabditis Elegans. Starting with the active-state structure solved in complex with the neurotransmitter L-glutamate and the positive allosteric modulator (PAM) ivermectin, we analyze the spontaneous relaxation of the channel upon removal of ivermectin by explicit solvent/membrane Molecular Dynamics (MD) simulations. The xcexbcs-long trajectories support the conclusion that ion-channel deactivation is mediated by two distinct quaternary transitions, i.e. a global receptor twisting followed by the radial expansion (or blooming) of the extracellular domain. At variance with previous models, we show that pore closing is exclusively regulated by the global twisting, which controls the position of the xcexb21-xcexb22 loop relative to the M2-M3 loop at the EC/TM domain interface. Additional simulations with L-glutamate restrained to the crystallographic binding mode and ivermectin removed indicate that the same twisting isomerization is regulated by agonist binding at the orthosteric site. These results provide a structural model for gating in pLGICs and suggest a plausible mechanism for the pharmacological action of PAMs in this neurotransmitter receptor family. The simulated un-gating converges to the X-ray structure of GluCl resting state both globally and locally, demonstrating the predictive character of state-of-art MD simulations.'),
(88724, 2017, 'plos', 'Unified thalamic model generates multiple distinct oscillations with state-dependent entrainment by stimulation', 'Li, Guoshi|Henriquez, Craig S|Fröhlich, Flavio', 'Department of Psychiatry, University of North Carolina at Chapel Hill, Chapel Hill, NC, United States of America.|Department of Biomedical Engineering, Duke University, Durham, NC, United States of America.|Department of Psychiatry, University of North Carolina at Chapel Hill, Chapel Hill, NC, United States of America.', 'United States|United States|United States', 12, 'Acetylcholine|Biological Clocks|Computer Simulation|Deep Brain Stimulation|Feedback, Physiological|Humans|Models, Neurological|Nerve Net|Neurotransmitter Agents|Norepinephrine|Oscillometry|Synaptic Transmission|Thalamus', 'Journal Article', '10.1371/journal.pcbi.1005797', '29073146', 'The thalamus plays a critical role in the genesis of thalamocortical oscillations, yet the underlying mechanisms remain elusive. To understand whether the isolated thalamus can generate multiple distinct oscillations, we developed a biophysical thalamic model to test the hypothesis that generation of and transition between distinct thalamic oscillations can be explained as a function of neuromodulation by acetylcholine (ACh) and norepinephrine (NE) and afferent synaptic excitation. Indeed, the model exhibited four distinct thalamic rhythms (delta, sleep spindle, alpha and gamma oscillations) that span the physiological states corresponding to different arousal levels from deep sleep to focused attention. Our simulation results indicate that generation of these distinct thalamic oscillations is a result of both intrinsic oscillatory cellular properties and specific network connectivity patterns. We then systematically varied the ACh/NE and input levels to generate a complete map of the different oscillatory states and their transitions. Lastly, we applied periodic stimulation to the thalamic network and found that entrainment of thalamic oscillations is highly state-dependent. Our results support the hypothesis that ACh/NE modulation and afferent excitation define thalamic oscillatory states and their response to brain stimulation. Our model proposes a broader and more central role of the thalamus in the genesis of multiple distinct thalamo-cortical rhythms than previously assumed.'),
(88725, 2017, 'plos', 'Dynamics and heterogeneity of brain damage in multiple sclerosis', 'Kotelnikova, Ekaterina|Kiani, Narsis A|Abad, Elena|Martinez-Lapiscina, Elena H|Andorra, Magi|Zubizarreta, Irati|Pulido-Valdeolivas, Irene|Pertsovskaya, Inna|Alexopoulos, Leonidas G|Olsson, Tomas|Martin, Roland|Paul, Friedemann|Tegnér, Jesper|Garcia-Ojalvo, Jordi|Villoslada, Pablo', 'Center for Neuroimmunology, Institut dInvestigacions Biomèdiques August Pi Sunyer (IDIBAPS), University of Barcelona, Barcelona, Spain.|Unit of Computational Medicine, Department of Medicine & Science for Life Laboratory, Karolinska Institute, Stockholm, Sweden.|Center for Neuroimmunology, Institut dInvestigacions Biomèdiques August Pi Sunyer (IDIBAPS), University of Barcelona, Barcelona, Spain.|Center for Neuroimmunology, Institut dInvestigacions Biomèdiques August Pi Sunyer (IDIBAPS), University of Barcelona, Barcelona, Spain.|Center for Neuroimmunology, Institut dInvestigacions Biomèdiques August Pi Sunyer (IDIBAPS), University of Barcelona, Barcelona, Spain.|Center for Neuroimmunology, Institut dInvestigacions Biomèdiques August Pi Sunyer (IDIBAPS), University of Barcelona, Barcelona, Spain.|Center for Neuroimmunology, Institut dInvestigacions Biomèdiques August Pi Sunyer (IDIBAPS), University of Barcelona, Barcelona, Spain.|Center for Neuroimmunology, Institut dInvestigacions Biomèdiques August Pi Sunyer (IDIBAPS), University of Barcelona, Barcelona, Spain.|National Technical University of Athens, Athens, Greece.|Unit of Neuroimmunology, Karolinska Institute, Stockholm, Sweden.|Neuroimmunology and MS Research, Neurology Clinic, University Hospital, University Zurich, Zurich, Switzerland.|NeuroCure Clinical Research Center, and the Experimental and Clinical Research Center, Charité Universitätsmedizin Berlin and Max Delbrueck Center for Molecular Medicine Berlin, Berlin, Germany.|Unit of Computational Medicine, Department of Medicine & Science for Life Laboratory, Karolinska Institute, Stockholm, Sweden.|Universitat Pompeu Fabra, Barcelona, Spain.|Center for Neuroimmunology, Institut dInvestigacions Biomèdiques August Pi Sunyer (IDIBAPS), University of Barcelona, Barcelona, Spain.', 'Spain|Sweden|Spain|Spain|Spain|Spain|Spain|Spain|Greece|Sweden|Switzerland|Germany|Sweden|Spain|Spai', 9, 'Brain|Computational Biology|Databases, Factual|Humans|Image Processing, Computer-Assisted|Inflammation|Magnetic Resonance Imaging|Multiple Sclerosis|Prospective Studies', 'Journal Article', '10.1371/journal.pcbi.1005757', '29073203', 'Multiple Sclerosis (MS) is an autoimmune disease driving inflammatory and degenerative processes that damage the central nervous system (CNS). However, it is not well understood how these events interact and evolve to evoke such a highly dynamic and heterogeneous disease. We established a hypothesis whereby the variability in the course of MS is driven by the very same pathogenic mechanisms responsible for the disease, the autoimmune attack on the CNS that leads to chronic inflammation, neuroaxonal degeneration and remyelination. We propose that each of these processes acts more or less severely and at different times in each of the clinical subgroups. To test this hypothesis, we developed a mathematical model that was constrained by experimental data (the expanded disability status scale [EDSS] time series) obtained from a retrospective longitudinal cohort of 66 MS patients with a long-term follow-up (up to 20 years). Moreover, we validated this model in a second prospective cohort of 120 MS patients with a three-year follow-up, for which EDSS data and brain volume time series were available. The clinical heterogeneity in the datasets was reduced by grouping the EDSS time series using an unsupervised clustering analysis. We found that by adjusting certain parameters, albeit within their biological range, the mathematical model reproduced the different disease courses, supporting the dynamic CNS damage hypothesis to explain MS heterogeneity. Our analysis suggests that the irreversible axon degeneration produced in the early stages of progressive MS is mainly due to the higher rate of myelinated axon degeneration, coupled to the lower capacity for remyelination. However, and in agreement with recent pathological studies, degeneration of chronically demyelinated axons is not a key feature that distinguishes this phenotype. Moreover, the model reveals that lower rates of axon degeneration and more rapid remyelination make relapsing MS more resilient than the progressive subtype. Therefore, our results support the hypothesis of a common pathogenesis for the different MS subtypes, even in the presence of genetic and environmental heterogeneity. Hence, MS can be considered as a single disease in which specific dynamics can provoke a variety of clinical outcomes in different patient groups. These results have important implications for the design of therapeutic interventions for MS at different stages of the disease.');
INSERT INTO `papers` (`id`, `ano`, `journal`, `titulo`, `autores`, `afiliacao`, `pais`, `citacoes`, `palavra_chave`, `categorias`, `doi`, `pubmed`, `abstract`) VALUES
(88726, 2017, 'plos', 'Modeling the adenosine system as a modulator of cognitive performance and sleep patterns during sleep restriction and recovery', 'Phillips, Andrew J K|Klerman, Elizabeth B|Butler, James P', 'Division of Sleep Medicine, Departments of Medicine and Neurology, Harvard Medical School, and Division of Sleep and Circadian Disorders, Brigham and Womens Hospital, Boston, MA, United States of America.|Division of Sleep Medicine, Departments of Medicine and Neurology, Harvard Medical School, and Division of Sleep and Circadian Disorders, Brigham and Womens Hospital, Boston, MA, United States of America.|Division of Pulmonary and Critical Care Medicine, Brigham and Womens Hospital, and Department of Medicine, Harvard Medical School, Boston, MA, United States of America.', 'United States|United States|United States', 6, 'Adenosine|Attention|Brain|Cognition|Cognition Disorders|Computer Simulation|Humans|Models, Neurological|Psychomotor Performance|Reaction Time|Recovery of Function|Sleep|Sleep Deprivation', 'Journal Article', '10.1371/journal.pcbi.1005759', '29073206', 'Sleep loss causes profound cognitive impairments and increases the concentrations of adenosine and adenosine A1 receptors in specific regions of the brain. Time courses for performance impairment and recovery differ between acute and chronic sleep loss, but the physiological basis for these time courses is unknown. Adenosine has been implicated in pathways that generate sleepiness and cognitive impairments, but existing mathematical models of sleep and cognitive performance do not explicitly include adenosine. Here, we developed a novel receptor-ligand model of the adenosine system to test the hypothesis that changes in both adenosine and A1 receptor concentrations can capture changes in cognitive performance during acute sleep deprivation (one prolonged wake episode), chronic sleep restriction (multiple nights with insufficient sleep), and subsequent recovery. Parameter values were estimated using biochemical data and reaction time performance on the psychomotor vigilance test (PVT). The model closely fit group-average PVT data during acute sleep deprivation, chronic sleep restriction, and recovery. We tested the models ability to reproduce timing and duration of sleep in a separate experiment where individuals were permitted to sleep for up to 14 hours per day for 28 days. The model accurately reproduced these data, and also correctly predicted the possible emergence of a split sleep pattern (two distinct sleep episodes) under these experimental conditions. Our findings provide a physiologically plausible explanation for observed changes in cognitive performance and sleep during sleep loss and recovery, as well as a new approach for predicting sleep and cognitive performance under planned schedules.'),
(88727, 2017, 'plos', 'Point process analysis of noise in early invertebrate vision', 'Parag, Kris V|Vinnicombe, Glenn', 'Control Group, Department of Engineering, University of Cambridge, United Kingdom.|Control Group, Department of Engineering, University of Cambridge, United Kingdom.', 'United Kingdom|United Kingdom', 4, 'Animals|Bayes Theorem|Computer Simulation|Dose-Response Relationship, Radiation|Drosophila|Markov Chains|Models, Neurological|Models, Statistical|Photic Stimulation|Photoreceptor Cells, Invertebrate|Radiation Dosage|Reproducibility of Results|Sensitivity and Specificity|Signal-To-Noise Ratio|Vision, Ocular', 'Journal Article', '10.1371/journal.pcbi.1005687', '29077703', 'Noise is a prevalent and sometimes even dominant aspect of many biological processes. While many natural systems have adapted to attenuate or even usefully integrate noise, the variability it introduces often still delimits the achievable precision across biological functions. This is particularly so for visual phototransduction, the process responsible for converting photons of light into usable electrical signals (quantum bumps). Here, randomness of both the photon inputs (regarded as extrinsic noise) and the conversion process (intrinsic noise) are seen as two distinct, independent and significant limitations on visual reliability. Past research has attempted to quantify the relative effects of these noise sources by using approximate methods that do not fully account for the discrete, point process and time ordered nature of the problem. As a result the conclusions drawn from these different approaches have led to inconsistent expositions of phototransduction noise performance. This paper provides a fresh and complete analysis of the relative impact of intrinsic and extrinsic noise in invertebrate phototransduction using minimum mean squared error reconstruction techniques based on Bayesian point process (Snyder) filters. An integrate-fire based algorithm is developed to reliably estimate photon times from quantum bumps and Snyder filters are then used to causally estimate random light intensities both at the front and back end of the phototransduction cascade. Comparison of these estimates reveals that the dominant noise source transitions from extrinsic to intrinsic as light intensity increases. By extending the filtering techniques to account for delays, it is further found that among the intrinsic noise components, which include bump latency (mean delay and jitter) and shape (amplitude and width) variance, it is the mean delay that is critical to noise performance. As the timeliness of visual information is important for real-time action, this delay could potentially limit the speed at which invertebrates can respond to stimuli. Consequently, if one wants to increase visual fidelity, reducing the photoconversion lag is much more important than improving the regularity of the electrical signal.'),
(88728, 2017, 'plos', 'The influence of astrocytes on the width of orientation hypercolumns in visual cortex: A computational perspective', 'Philips, Ryan T|Sur, Mriganka|Chakravarthy, V Srinivasa', 'Computational Neuroscience Laboratory, Department of Biotechnology, Bhupat and Jyoti Mehta School of Biosciences, Indian Institute of Technology Madras, Chennai, Tamil Nadu, India.|Picower Institute for Learning and Memory, Department of Brain and Cognitive Sciences, Massachusetts Institute of Technology, Cambridge, Massachusetts, United States of America.|Computational Neuroscience Laboratory, Department of Biotechnology, Bhupat and Jyoti Mehta School of Biosciences, Indian Institute of Technology Madras, Chennai, Tamil Nadu, India.', 'India|United States|India', 1, 'Animals|Astrocytes|Computer Simulation|Humans|Models, Neurological|Nerve Net|Orientation, Spatial|Visual Cortex|Visual Fields|Visual Perception', 'Journal Article', '10.1371/journal.pcbi.1005785', '29077710', 'Orientation preference maps (OPMs) are present in carnivores (such as cats and ferrets) and primates but are absent in rodents. In this study we investigate the possible link between astrocyte arbors and presence of OPMs. We simulate the development of orientation maps with varying hypercolumn widths using a variant of the Laterally Interconnected Synergetically Self-Organizing Map (LISSOM) model, the Gain Control Adaptive Laterally connected (GCAL) model, with an additional layer simulating astrocytic activation. The synaptic activity of V1 neurons is given as input to the astrocyte layer. The activity of this astrocyte layer is now used to modulate bidirectional plasticity of lateral excitatory connections in the V1 layer. By simply varying the radius of the astrocytes, the extent of lateral excitatory neuronal connections can be manipulated. An increase in the radius of lateral excitatory connections subsequently increases the size of a single hypercolumn in the OPM. When these lateral excitatory connections become small enough the OPM disappears and a salt-and-pepper organization emerges.'),
(88729, 2017, 'plos', 'A method to quantify mechanobiologic forces during zebrafish cardiac development using 4-D light sheet imaging and computational modeling', 'Vedula, Vijay|Lee, Juhyun|Xu, Hao|Kuo, C-C Jay|Hsiai, Tzung K|Marsden, Alison L', 'Department of Pediatrics (Cardiology), Stanford University, Stanford, California, United States of America.|Department of Bioengineering, University of California, Los Angeles, Los Angeles, California, United States of America.|Department of Electrical Engineering, University of Southern California, Los Angeles, California, United States of America.|Department of Electrical Engineering, University of Southern California, Los Angeles, California, United States of America.|Department of Bioengineering, University of California, Los Angeles, Los Angeles, California, United States of America.|Department of Pediatrics (Cardiology), Stanford University, Stanford, California, United States of America.', 'United States|United States|United States|United States|United States|United States', 19, 'Animals|Blood Flow Velocity|Cardiac Imaging Techniques|Computer Simulation|Heart Ventricles|Image Interpretation, Computer-Assisted|Imaging, Three-Dimensional|Mechanotransduction, Cellular|Models, Cardiovascular|Morphogenesis|Stress, Mechanical|Ventricular Function|Zebrafish', 'Journal Article', '10.1371/journal.pcbi.1005828', '29084212', 'Blood flow and mechanical forces in the ventricle are implicated in cardiac development and trabeculation. However, the mechanisms of mechanotransduction remain elusive. This is due in part to the challenges associated with accurately quantifying mechanical forces in the developing heart. We present a novel computational framework to simulate cardiac hemodynamics in developing zebrafish embryos by coupling 4-D light sheet imaging with a stabilized finite element flow solver, and extract time-dependent mechanical stimuli data. We employ deformable image registration methods to segment the motion of the ventricle from high resolution 4-D light sheet image data. This results in a robust and efficient workflow, as segmentation need only be performed at one cardiac phase, while wall position in the other cardiac phases is found by image registration. Ventricular hemodynamics are then quantified by numerically solving the Navier-Stokes equations in the moving wall domain with our validated flow solver. We demonstrate the applicability of the workflow in wild type zebrafish and three treated fish types that disrupt trabeculation: (a) chemical treatment using AG1478, an ErbB2 signaling inhibitor that inhibits proliferation and differentiation of cardiac trabeculation, (b) injection of gata1a morpholino oligomer (gata1aMO) suppressing hematopoiesis and resulting in attenuated trabeculation, (c) weak-atriumm58 mutant (wea) with inhibited atrial contraction leading to a highly undeveloped ventricle and poor cardiac function. Our simulations reveal elevated wall shear stress (WSS) in wild type and AG1478 compared to gata1aMO and wea. High oscillatory shear index (OSI) in the grooves between trabeculae, compared to lower values on the ridges, in the wild type suggest oscillatory forces as a possible regulatory mechanism of cardiac trabeculation development. The framework has broad applicability for future cardiac developmental studies focused on quantitatively investigating the role of hemodynamic forces and mechanotransduction during morphogenesis.'),
(88730, 2017, 'plos', 'A mechanistic spatio-temporal framework for modelling individual-to-individual transmission-With an application to the 2014-2015 West Africa Ebola outbreak', 'Lau, Max S Y|Gibson, Gavin J|Adrakey, Hola|McClelland, Amanda|Riley, Steven|Zelner, Jon|Streftaris, George|Funk, Sebastian|Metcalf, Jessica|Dalziel, Benjamin D|Grenfell, Bryan T', 'Department of Ecology and Evolutionary Biology, Princeton University, Princeton, New Jersey, United States of America.|Maxwell Institute for Mathematical Sciences, Department of Actuarial Mathematics and Statistics, Heriot-Watt University, Edinburgh, United Kingdom.|Department of Plant Sciences, University of Cambridge, Cambridge, United Kingdom.|International Federation of Red Cross and Red Crescent Societies, Geneva, Switzerland.|MRC Centre for Outbreak Analysis and Modelling, Department Infectious Disease Epidemiology, Imperial College, London, United Kingdom.|School of Public Health, University of Michigan, Ann Arbor, Michigan, United States of America.|Maxwell Institute for Mathematical Sciences, Department of Actuarial Mathematics and Statistics, Heriot-Watt University, Edinburgh, United Kingdom.|Centre for the Mathematical Modelling of Infectious Diseases, London School of Hygiene & Tropical Medicine, London, United Kingdom.|Department of Ecology and Evolutionary Biology, Princeton University, Princeton, New Jersey, United States of America.|Department of Integrative Biology, Oregon State University, Corvallis, Oregon, United States of America.|Department of Ecology and Evolutionary Biology, Princeton University, Princeton, New Jersey, United States of America.', 'Jersey|United Kingdom|United Kingdom|Switzerland|United Kingdom|United States|United Kingdom|United ', 5, 'Africa, Western|Computer Simulation|Disease Outbreaks|Disease Transmission, Infectious|Geographic Information Systems|Hemorrhagic Fever, Ebola|Humans|Models, Statistical|Prevalence|Proportional Hazards Models|Risk Assessment|Spatio-Temporal Analysis', 'Journal Article', '10.1371/journal.pcbi.1005798', '29084216', 'In recent years there has been growing availability of individual-level spatio-temporal disease data, particularly due to the use of modern communicating devices with GPS tracking functionality. These detailed data have been proven useful for inferring disease transmission to a more refined level than previously. However, there remains a lack of statistically sound frameworks to model the underlying transmission dynamic in a mechanistic manner. Such a development is particularly crucial for enabling a general epidemic predictive framework at the individual level. In this paper we propose a new statistical framework for mechanistically modelling individual-to-individual disease transmission in a landscape with heterogeneous population density. Our methodology is first tested using simulated datasets, validating our inferential machinery. The methodology is subsequently applied to data that describes a regional Ebola outbreak in Western Africa (2014-2015). Our results show that the methods are able to obtain estimates of key epidemiological parameters that are broadly consistent with the literature, while revealing a significantly shorter distance of transmission. More importantly, in contrast to existing approaches, we are able to perform a more general model prediction that takes into account the susceptible population. Finally, our results show that, given reasonable scenarios, the framework can be an effective surrogate for susceptible-explicit individual models which are often computationally challenging.'),
(88731, 2017, 'plos', 'Concerted regulation of npc2 binding to endosomal/lysosomal membranes by bis(monoacylglycero)phosphate and sphingomyelin', 'Enkavi, Giray|Mikkolainen, Heikki|Güngör, Burçin|Ikonen, Elina|Vattulainen, Ilpo', 'Laboratory of Physics, Tampere University of Technology, Tampere, Finland.|Laboratory of Physics, Tampere University of Technology, Tampere, Finland.|Department of Anatomy, Faculty of Medicine, University of Helsinki, Helsinki, Finland.|Department of Anatomy, Faculty of Medicine, University of Helsinki, Helsinki, Finland.|Laboratory of Physics, Tampere University of Technology, Tampere, Finland.', 'Finland|Finland|Finland|Finland|Finland', 0, 'Binding Sites|Carrier Proteins|Endosomes|Glycoproteins|Lipid Bilayers|Lysophospholipids|Lysosomes|Membrane Fluidity|Models, Chemical|Molecular Dynamics Simulation|Monoglycerides|Protein Binding|Protein Conformation|Sphingomyelins|Structure-Activity Relationship', 'Journal Article', '10.1371/journal.pcbi.1005831', '29084218', 'Niemann-Pick Protein C2 (npc2) is a small soluble protein critical for cholesterol transport within and from the lysosome and the late endosome. Intriguingly, npc2-mediated cholesterol transport has been shown to be modulated by lipids, yet the molecular mechanism of npc2-membrane interactions has remained elusive. Here, based on an extensive set of atomistic simulations and free energy calculations, we clarify the mechanism and energetics of npc2-membrane binding and characterize the roles of physiologically relevant key lipids associated with the binding process. Our results capture in atomistic detail two competitively favorable membrane binding orientations of npc2 with a low interconversion barrier. The first binding mode (Prone) places the cholesterol binding pocket in direct contact with the membrane and is characterized by membrane insertion of a loop (V59-M60-G61-I62-P63-V64-P65). This mode is associated with cholesterol uptake and release. On the other hand, the second mode (Supine) places the cholesterol binding pocket away from the membrane surface, but has overall higher membrane binding affinity. We determined that bis(monoacylglycero)phosphate (bmp) is specifically required for strong membrane binding in Prone mode, and that it cannot be substituted by other anionic lipids. Meanwhile, sphingomyelin counteracts bmp by hindering Prone mode without affecting Supine mode. Our results provide concrete evidence that lipids modulate npc2-mediated cholesterol transport either by favoring or disfavoring Prone mode and that they impose this by modulating the accessibility of bmp for interacting with npc2. Overall, we provide a mechanism by which npc2-mediated cholesterol transport is controlled by the membrane composition and how npc2-lipid interactions can regulate the transport rate.'),
(88732, 2017, 'plos', 'Maximum entropy methods for extracting the learned features of deep neural networks', 'Finnegan, Alex|Song, Jun S', 'Department of Physics, University of Illinois, Urbana-Champaign, Urbana, Illinois, United States of America.|Department of Physics, University of Illinois, Urbana-Champaign, Urbana, Illinois, United States of America.', 'United States|United States', 0, 'Algorithms|Computer Simulation|Entropy|Machine Learning|Models, Statistical|Neural Networks (Computer)|Pattern Recognition, Automated|Sequence Analysis, DNA', 'Journal Article', '10.1371/journal.pcbi.1005836', '29084280', 'New architectures of multilayer artificial neural networks and new methods for training them are rapidly revolutionizing the application of machine learning in diverse fields, including business, social science, physical sciences, and biology. Interpreting deep neural networks, however, currently remains elusive, and a critical challenge lies in understanding which meaningful features a network is actually learning. We present a general method for interpreting deep neural networks and extracting network-learned features from input data. We describe our algorithm in the context of biological sequence analysis. Our approach, based on ideas from statistical physics, samples from the maximum entropy distribution over possible sequences, anchored at an input sequence and subject to constraints implied by the empirical function learned by a network. Using our framework, we demonstrate that local transcription factor binding motifs can be identified from a network trained on ChIP-seq data and that nucleosome positioning signals are indeed learned by a network trained on chemical cleavage nucleosome maps. Imposing a further constraint on the maximum entropy distribution also allows us to probe whether a network is learning global sequence features, such as the high GC content in nucleosome-rich regions. This work thus provides valuable mathematical tools for interpreting and extracting learned features from feed-forward neural networks.'),
(88733, 2017, 'plos', 'A Rescorla-Wagner drift-diffusion model of conditioning and timing', 'Luzardo, André|Alonso, Eduardo|Mondragón, Esther', 'Department of Computer Science, City University of London, London, United Kingdom.|Department of Computer Science, City University of London, London, United Kingdom.|Department of Computer Science, City University of London, London, United Kingdom.', 'United Kingdom|United Kingdom|United Kingdom', 9, 'Association Learning|Computational Biology|Computer Simulation|Conditioning, Classical|Humans|Models, Theoretical', 'Journal Article', '10.1371/journal.pcbi.1005796', '29095819', 'Computational models of classical conditioning have made significant contributions to the theoretic understanding of associative learning, yet they still struggle when the temporal aspects of conditioning are taken into account. Interval timing models have contributed a rich variety of time representations and provided accurate predictions for the timing of responses, but they usually have little to say about associative learning. In this article we present a unified model of conditioning and timing that is based on the influential Rescorla-Wagner conditioning model and the more recently developed Timing Drift-Diffusion model. We test the model by simulating 10 experimental phenomena and show that it can provide an adequate account for 8, and a partial account for the other 2. We argue that the model can account for more phenomena in the chosen set than these other similar in scope models: CSC-TD, MS-TD, Learning to Time and Modular Theory. A comparison and analysis of the mechanisms in these models is provided, with a focus on the types of time representation and associative learning rule used.'),
(88734, 2017, 'plos', 'mixOmics: An R package for omics feature selection and multiple data integration', 'Rohart, Florian|Gautier, Benoît|Singh, Amrit|Lê Cao, Kim-Anh', 'The University of Queensland Diamantina Institute, Translational Research Institute, Brisbane, Queensland, Australia.|The University of Queensland Diamantina Institute, Translational Research Institute, Brisbane, Queensland, Australia.|Prevention of Organ Failure (PROOF) Centre of Excellence, Vancouver, British Columbia, Canada.|The University of Queensland Diamantina Institute, Translational Research Institute, Brisbane, Queensland, Australia.', 'Australia|Australia|Canada|Australia', 0, 'Computational Biology|Data Interpretation, Statistical|Genomics|Humans|Metabolomics|Neoplasms|Software|Systems Biology', 'Journal Article', '10.1371/journal.pcbi.1005752', '29099853', 'The advent of high throughput technologies has led to a wealth of publicly available omics data coming from different sources, such as transcriptomics, proteomics, metabolomics. Combining such large-scale biological data sets can lead to the discovery of important biological insights, provided that relevant information can be extracted in a holistic manner. Current statistical approaches have been focusing on identifying small subsets of molecules (a molecular signature) to explain or predict biological conditions, but mainly for a single type of omics. In addition, commonly used methods are univariate and consider each biological feature independently. We introduce mixOmics, an R package dedicated to the multivariate analysis of biological data sets with a specific focus on data exploration, dimension reduction and visualisation. By adopting a systems biology approach, the toolkit provides a wide range of methods that statistically integrate several data sets at once to probe relationships between heterogeneous omics data sets. Our recent methods extend Projection to Latent Structure (PLS) models for discriminant analysis, for data integration across multiple omics data or across independent studies, and for the identification of molecular signatures. We illustrate our latest mixOmics integrative frameworks for the multivariate analyses of omics data available from the package.'),
(88735, 2017, 'plos', 'Base pair probability estimates improve the prediction accuracy of RNA non-canonical base pairs', 'Sloma, Michael F|Mathews, David H', 'Department of Biochemistry & Biophysics and Center for RNA Biology, University of Rochester Medical Center, Rochester, NY, United States of America.|Department of Biochemistry & Biophysics and Center for RNA Biology, University of Rochester Medical Center, Rochester, NY, United States of America.', 'United States|United States', 7, 'Algorithms|Animals|Base Pairing|Base Sequence|Humans|Nucleic Acid Conformation|Nucleotide Motifs|RNA|Software', 'Journal Article', '10.1371/journal.pcbi.1005827', '29107980', 'Prediction of RNA tertiary structure from sequence is an important problem, but generating accurate structure models for even short sequences remains difficult. Predictions of RNA tertiary structure tend to be least accurate in loop regions, where non-canonical pairs are important for determining the details of structure. Non-canonical pairs can be predicted using a knowledge-based model of structure that scores nucleotide cyclic motifs, or NCMs. In this work, a partition function algorithm is introduced that allows the estimation of base pairing probabilities for both canonical and non-canonical interactions. Pairs that are predicted to be probable are more likely to be found in the true structure than pairs of lower probability. Pair probability estimates can be further improved by predicting the structure conserved across multiple homologous sequences using the TurboFold algorithm. These pairing probabilities, used in concert with prior knowledge of the canonical secondary structure, allow accurate inference of non-canonical pairs, an important step towards accurate prediction of the full tertiary structure. Software to predict non-canonical base pairs and pairing probabilities is now provided as part of the RNAstructure software package.'),
(88736, 2017, 'plos', 'Competitive tuning: Competitions role in setting the frequency-dependence of Ca2+-dependent proteins', 'Romano, Daniel R|Pharris, Matthew C|Patel, Neal M|Kinzer-Ursem, Tamara L', 'Weldon School of Biomedical Engineering, Purdue University, West Lafayette, IN, United States of America.|Weldon School of Biomedical Engineering, Purdue University, West Lafayette, IN, United States of America.|Weldon School of Biomedical Engineering, Purdue University, West Lafayette, IN, United States of America.|Weldon School of Biomedical Engineering, Purdue University, West Lafayette, IN, United States of America.', 'United States|United States|United States|United States', 10, 'Animals|Binding, Competitive|Calcium|Computer Simulation|Hippocampus|Intracellular Calcium-Sensing Proteins|Long-Term Potentiation|Mice|Mice, Knockout|Neuronal Plasticity|Phosphorylation|Protein Binding|Signal Transduction', 'Journal Article', '10.1371/journal.pcbi.1005820', '29107982', 'A number of neurological disorders arise from perturbations in biochemical signaling and protein complex formation within neurons. Normally, proteins form networks that when activated produce persistent changes in a synapses molecular composition. In hippocampal neurons, calcium ion (Ca2+) flux through N-methyl-D-aspartate (NMDA) receptors activates Ca2+/calmodulin signal transduction networks that either increase or decrease the strength of the neuronal synapse, phenomena known as long-term potentiation (LTP) or long-term depression (LTD), respectively. The calcium-sensor calmodulin (CaM) acts as a common activator of the networks responsible for both LTP and LTD. This is possible, in part, because CaM binding proteins are tuned to different Ca2+ flux signals by their unique binding and activation dynamics. Computational modeling is used to describe the binding and activation dynamics of Ca2+/CaM signal transduction and can be used to guide focused experimental studies. Although CaM binds over 100 proteins, practical limitations cause many models to include only one or two CaM-activated proteins. In this work, we view Ca2+/CaM as a limiting resource in the signal transduction pathway owing to its low abundance relative to its binding partners. With this view, we investigate the effect of competitive binding on the dynamics of CaM binding partner activation. Using an explicit model of Ca2+, CaM, and seven highly-expressed hippocampal CaM binding proteins, we find that competition for CaM binding serves as a tuning mechanism: the presence of competitors shifts and sharpens the Ca2+ frequency-dependence of CaM binding proteins. Notably, we find that simulated competition may be sufficient to recreate the in vivo frequency dependence of the CaM-dependent phosphatase calcineurin. Additionally, competition alone (without feedback mechanisms or spatial parameters) could replicate counter-intuitive experimental observations of decreased activation of Ca2+/CaM-dependent protein kinase II in knockout models of neurogranin. We conclude that competitive tuning could be an important dynamic process underlying synaptic plasticity.'),
(88737, 2017, 'plos', 'Individual versus superensemble forecasts of seasonal influenza outbreaks in the United States', 'Yamana, Teresa K|Kandula, Sasikiran|Shaman, Jeffrey', 'Department of Environmental Health Sciences, Mailman School of Public Health, Columbia University, New York, New York, United States of America.|Department of Environmental Health Sciences, Mailman School of Public Health, Columbia University, New York, New York, United States of America.|Department of Environmental Health Sciences, Mailman School of Public Health, Columbia University, New York, New York, United States of America.', 'United States|United States|United States', 12, 'Bayes Theorem|Computer Simulation|Disease Outbreaks|Forecasting|Humans|Incidence|Influenza A virus|Influenza, Human|Models, Statistical|Retrospective Studies|Seasons|United States', 'Comparative Study', '10.1371/journal.pcbi.1005801', '29107987', 'Recent research has produced a number of methods for forecasting seasonal influenza outbreaks. However, differences among the predicted outcomes of competing forecast methods can limit their use in decision-making. Here, we present a method for reconciling these differences using Bayesian model averaging. We generated retrospective forecasts of peak timing, peak incidence, and total incidence for seasonal influenza outbreaks in 48 states and 95 cities using 21 distinct forecast methods, and combined these individual forecasts to create weighted-average superensemble forecasts. We compared the relative performance of these individual and superensemble forecast methods by geographic location, timing of forecast, and influenza season. We find that, overall, the superensemble forecasts are more accurate than any individual forecast method and less prone to producing a poor forecast. Furthermore, we find that these advantages increase when the superensemble weights are stratified according to the characteristics of the forecast or geographic location. These findings indicate that different competing influenza prediction systems can be combined into a single more accurate forecast product for operational delivery in real time.'),
(88738, 2017, 'plos', 'Insight into glucocorticoid receptor signalling through interactome model analysis', 'Bakker, Emyr|Tian, Kun|Mutti, Luciano|Demonacos, Constantinos|Schwartz, Jean-Marc|Krstic-Demonacos, Marija', 'Biomedical Research Centre, School of Environment and Life Sciences, University of Salford, Salford, United Kingdom.|Biomedical Research Centre, School of Environment and Life Sciences, University of Salford, Salford, United Kingdom.|Biomedical Research Centre, School of Environment and Life Sciences, University of Salford, Salford, 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.|Biomedical Research Centre, School of Environment and Life Sciences, University of Salford, Salford, United Kingdom.', 'United Kingdom|United Kingdom|United Kingdom|United Kingdom|United Kingdom|United Kingdom', 3, 'Adolescent|Apoptosis|Child|Child, Preschool|Computer Simulation|Female|Gene Expression Regulation|Gene Regulatory Networks|Glucocorticoids|Humans|Male|Models, Biological|Neoplasms|Protein Interaction Maps|Receptors, Glucocorticoid|Signal Transduction|Systems Biology', 'Journal Article', '10.1371/journal.pcbi.1005825', '29107989', 'Glucocorticoid hormones (GCs) are used to treat a variety of diseases because of their potent anti-inflammatory effect and their ability to induce apoptosis in lymphoid malignancies through the glucocorticoid receptor (GR). Despite ongoing research, high glucocorticoid efficacy and widespread usage in medicine, resistance, disease relapse and toxicity remain factors that need addressing. Understanding the mechanisms of glucocorticoid signalling and how resistance may arise is highly important towards improving therapy. To gain insight into this we undertook a systems biology approach, aiming to generate a Boolean model of the glucocorticoid receptor protein interaction network that encapsulates functional relationships between the GR, its target genes or genes that target GR, and the interactions between the genes that interact with the GR. This model named GEB052 consists of 52 nodes representing genes or proteins, the model input (GC) and model outputs (cell death and inflammation), connected by 241 logical interactions of activation or inhibition. 323 changes in the relationships between model constituents following in silico knockouts were uncovered, and steady-state analysis followed by cell-based microarray genome-wide model validation led to an average of 57% correct predictions, which was taken further by assessment of model predictions against patient microarray data. Lastly, semi-quantitative model analysis via microarray data superimposed onto the model with a score flow algorithm has also been performed, which demonstrated significantly higher correct prediction ratios (average of 80%), and the model has been assessed as a predictive clinical tool using published patient microarray data. In summary we present an in silico simulation of the glucocorticoid receptor interaction network, linked to downstream biological processes that can be analysed to uncover relationships between GR and its interactants. Ultimately the model provides a platform for future development both by directing laboratory research and allowing for incorporation of further components, encapsulating more interactions/genes involved in glucocorticoid receptor signalling.'),
(88739, 2017, 'plos', 'Allosteric modulation of cardiac myosin dynamics by omecamtiv mecarbil', 'Hashem, Shaima|Tiberti, Matteo|Fornili, Arianna', 'School of Biological and Chemical Sciences, Queen Mary University of London, London, United Kingdom.|School of Biological and Chemical Sciences, Queen Mary University of London, London, United Kingdom.|School of Biological and Chemical Sciences, Queen Mary University of London, London, United Kingdom.', 'United Kingdom|United Kingdom|United Kingdom', 6, 'Allosteric Regulation|Allosteric Site|Cardiac Myosins|Crystallography, X-Ray|Humans|Molecular Dynamics Simulation|Protein Conformation|Urea', 'Journal Article', '10.1371/journal.pcbi.1005826', '29108014', 'New promising avenues for the pharmacological treatment of skeletal and heart muscle diseases rely on direct sarcomeric modulators, which are molecules that can directly bind to sarcomeric proteins and either inhibit or enhance their activity. A recent breakthrough has been the discovery of the myosin activator omecamtiv mecarbil (OM), which has been shown to increase the power output of the cardiac muscle and is currently in clinical trials for the treatment of heart failure. While the overall effect of OM on the mechano-chemical cycle of myosin is to increase the fraction of myosin molecules in the sarcomere that are strongly bound to actin, the molecular basis of its action is still not completely clear. We present here a Molecular Dynamics study of the motor domain of human cardiac myosin bound to OM, where the effects of the drug on the dynamical properties of the protein are investigated for the first time with atomistic resolution. We found that OM has a double effect on myosin dynamics, inducing a) an increased coupling of the motions of the converter and lever arm subdomains to the rest of the protein and b) a rewiring of the network of dynamic correlations, which produces preferential communication pathways between the OM binding site and distant functional regions. The location of the residues responsible for these effects suggests possible strategies for the future development of improved drugs and the targeting of specific cardiomyopathy-related mutations.'),
(88740, 2017, 'plos', 'Metabolic dynamics restricted by conserved carriers: Jamming and feedback', 'Hatakeyama, Tetsuhiro S|Furusawa, Chikara', 'Department of Basic Science, Graduate School of Arts and Sciences, The University of Tokyo, Meguro-ku, Tokyo, Japan.|Quantitative Biology Center (QBiC), RIKEN, Suita, Osaka, Japan.', 'Japan|Japan', 1, 'Algorithms|Computer Simulation|Escherichia coli|Feedback, Physiological|Glycolysis|Kinetics|Metabolic Networks and Pathways|Models, Biological', 'Journal Article', '10.1371/journal.pcbi.1005847', '29112954', 'To uncover the processes and mechanisms of cellular physiology, it first necessary to gain an understanding of the underlying metabolic dynamics. Recent studies using a constraint-based approach succeeded in predicting the steady states of cellular metabolic systems by utilizing conserved quantities in the metabolic networks such as carriers such as ATP/ADP as an energy carrier or NADH/NAD+ as a hydrogen carrier. Although such conservation quantities restrict not only the steady state but also the dynamics themselves, the latter aspect has not yet been completely understood. Here, to study the dynamics of metabolic systems, we propose adopting a carrier cycling cascade (CCC), which includes the dynamics of both substrates and carriers, a commonly observed motif in metabolic systems such as the glycolytic and fermentation pathways. We demonstrate that the conservation laws lead to the jamming of the flux and feedback. The CCC can show slow relaxation, with a longer timescale than that of elementary reactions, and is accompanied by both robustness against small environmental fluctuations and responsiveness against large environmental changes. Moreover, the CCC demonstrates robustness against internal fluctuations due to the feedback based on the moiety conservation. We identified the key parameters underlying the robustness of this model against external and internal fluctuations and estimated it in several metabolic systems.'),
(88741, 2017, 'plos', 'Reading wild minds: A computational assay of Theory of Mind sophistication across seven primate species', 'Devaine, Marie|San-Galli, Aurore|Trapanese, Cinzia|Bardino, Giulia|Hano, Christelle|Saint Jalme, Michel|Bouret, Sebastien|Masi, Shelly|Daunizeau, Jean', 'Université Pierre et Marie Curie, Paris, France.|Université Pierre et Marie Curie, Paris, France.|Museum National dHistoire Naturelle, UMR 7206, Paris, France.|Institut du Cerveau et de la Moelle épinière, Paris, France.|INSERM UMR S975, Paris, France.|Museum National dHistoire Naturelle, UMR 7206, Paris, France.|Université Pierre et Marie Curie, Paris, France.|Museum National dHistoire Naturelle, UMR 7206, Paris, France.|Université Pierre et Marie Curie, Paris, France.', 'France|France|France|France|France|France|France|France|France', 13, 'Animals|Behavior, Animal|Computational Biology|Computer Simulation|Game Theory|Primates|Reading|Social Behavior|Social Perception|Social Skills|Theory of Mind', 'Journal Article', '10.1371/journal.pcbi.1005833', '29112973', 'Theory of Mind (ToM), i.e. the ability to understand others mental states, endows humans with highly adaptive social skills such as teaching or deceiving. Candidate evolutionary explanations have been proposed for the unique sophistication of human ToM among primates. For example, the Machiavellian intelligence hypothesis states that the increasing complexity of social networks may have induced a demand for sophisticated ToM. This type of scenario ignores neurocognitive constraints that may eventually be crucial limiting factors for ToM evolution. In contradistinction, the cognitive scaffolding hypothesis asserts that a species opportunity to develop sophisticated ToM is mostly determined by its general cognitive capacity (on which ToM is scaffolded). However, the actual relationships between ToM sophistication and either brain volume (a proxy for general cognitive capacity) or social group size (a proxy for social network complexity) are unclear. Here, we let 39 individuals sampled from seven non-human primate species (lemurs, macaques, mangabeys, orangutans, gorillas and chimpanzees) engage in simple dyadic games against artificial ToM players (via a familiar human caregiver). Using computational analyses of primates choice sequences, we found that the probability of exhibiting a ToM-compatible learning style is mainly driven by species brain volume (rather than by social group size). Moreover, primates social cognitive sophistication culminates in a precursor form of ToM, which still falls short of human fully-developed ToM abilities.'),
(88742, 2017, 'plos', 'Correction: Ten simple rules for structuring papers', 'PLOS Computational Biology Staff', 'Université Pierre et Marie Curie, Paris, France.', 'France', 0, '-', 'Published Erratum', '10.1371/journal.pcbi.1005830', '29121064', '[This corrects the article DOI: 10.1371/journal.pcbi.1005619.].'),
(88743, 2017, 'plos', 'A modeling study of budding yeast colony formation and its relationship to budding pattern and aging', 'Wang, Yanli|Lo, Wing-Cheong|Chou, Ching-Shan', 'Department of Mathematics, The Ohio State University, Columbus, Ohio, United States of America.|Department of Mathematics, City University of Hong Kong, Hong Kong, China.|Department of Mathematics, The Ohio State University, Columbus, Ohio, United States of America.', 'United States|China|United States', 3, 'Cell Death|Cell Division|Cell Lineage|Cell Size|Computer Simulation|Haploidy|Models, Biological|Models, Statistical|Saccharomycetales|Software|Time Factors', 'Journal Article', '10.1371/journal.pcbi.1005843', '29121651', 'Budding yeast, which undergoes polarized growth during budding and mating, has been a useful model system to study cell polarization. Bud sites are selected differently in haploid and diploid yeast cells: haploid cells bud in an axial manner, while diploid cells bud in a bipolar manner. While previous studies have been focused on the molecular details of the bud site selection and polarity establishment, not much is known about how different budding patterns give rise to different functions at the population level. In this paper, we develop a two-dimensional agent-based model to study budding yeast colonies with cell-type specific biological processes, such as budding, mating, mating type switch, consumption of nutrients, and cell death. The model demonstrates that the axial budding pattern enhances mating probability at an early stage and the bipolar budding pattern improves colony development under nutrient limitation. Our results suggest that the frequency of mating type switch might control the trade-off between diploidization and inbreeding. The effect of cellular aging is also studied through our model. Based on the simulations, colonies initiated by an aged haploid cell show declined mating probability at an early stage and recover as the rejuvenated offsprings become the majority. Colonies initiated with aged diploid cells do not show disadvantage in colony expansion possibly due to the fact that young cells contribute the most to colony expansion.'),
(88744, 2017, 'plos', 'Are there physicochemical differences between allosteric and competitive ligands?', 'Smith, Richard D|Lu, Jing|Carlson, Heather A', 'Department of Medicinal Chemistry, University of Michigan, Ann Arbor, MI, United States of America.|Department of Computational Medicine and Bioinformatics, University of Michigan, Ann Arbor, MI, United States of America.|Department of Medicinal Chemistry, University of Michigan, Ann Arbor, MI, United States of America.', 'United States|United States|United States', 9, 'Algorithms|Allosteric Regulation|Allosteric Site|Catalytic Domain|Chemistry, Physical|Computational Biology|Databases, Factual|Hydrophobic and Hydrophilic Interactions|Ligands|Proteins', 'Comparative Study', '10.1371/journal.pcbi.1005813', '29125840', 'Previous studies have compared the physicochemical properties of allosteric compounds to non-allosteric compounds. Those studies have found that allosteric compounds tend to be smaller, more rigid, more hydrophobic, and more drug-like than non-allosteric compounds. However, previous studies have not properly corrected for the fact that some protein targets have much more data than other systems. This generates concern regarding the possible skew that can be introduced by the inherent bias in the available data. Hence, this study aims to determine how robust the previous findings are to the addition of newer data. This study utilizes the Allosteric Database (ASD v3.0) and ChEMBL v20 to systematically obtain large datasets of both allosteric and competitive ligands. This dataset contains 70,219 and 9,511 unique ligands for the allosteric and competitive sets, respectively. Physically relevant compound descriptors were computed to examine the differences in their chemical properties. Particular attention was given to removing redundancy in the data and normalizing across ligand diversity and varied protein targets. The resulting distributions only show that allosteric ligands tend to be more aromatic and rigid and do not confirm the increase in hydrophobicity or difference in drug-likeness. These results are robust across different normalization schemes.'),
(88745, 2017, 'plos', 'Correction: Error-Robust Modes of the Retinal Population Code', 'PLOS Computational Biology Staff', 'Department of Medicinal Chemistry, University of Michigan, Ann Arbor, MI, United States of America.', 'United States', 0, '-', 'Published Erratum', '10.1371/journal.pcbi.1005855', '29125841', '[This corrects the article DOI: 10.1371/journal.pcbi.1005148.].'),
(88746, 2017, 'plos', 'Significant associations between driver gene mutations and DNA methylation alterations across many cancer types', 'Chen, Yun-Ching|Gotea, Valer|Margolin, Gennady|Elnitski, Laura', 'Genomic Functional Analysis Section, National Human Genome Research Institute, National Institutes of Health, Bethesda, Maryland, United States.|Genomic Functional Analysis Section, National Human Genome Research Institute, National Institutes of Health, Bethesda, Maryland, United States.|Genomic Functional Analysis Section, National Human Genome Research Institute, National Institutes of Health, Bethesda, Maryland, United States.|Genomic Functional Analysis Section, National Human Genome Research Institute, National Institutes of Health, Bethesda, Maryland, United States.', 'United States|United States|United States|United States', 11, 'Computational Biology|CpG Islands|DNA Methylation|Genetic Association Studies|Genome|Humans|Mutation|Neoplasms|Principal Component Analysis|Signal Transduction', 'Journal Article', '10.1371/journal.pcbi.1005840', '29125844', 'Recent evidence shows that mutations in several driver genes can cause aberrant methylation patterns, a hallmark of cancer. In light of these findings, we hypothesized that the landscapes of tumor genomes and epigenomes are tightly interconnected. We measured this relationship using principal component analyses and methylation-mutation associations applied at the nucleotide level and with respect to genome-wide trends. We found that a few mutated driver genes were associated with genome-wide patterns of aberrant hypomethylation or CpG island hypermethylation in specific cancer types. In addition, we identified associations between 737 mutated driver genes and site-specific methylation changes. Moreover, using these mutation-methylation associations, we were able to distinguish between two uterine and two thyroid cancer subtypes. The driver gene mutation-associated methylation differences between the thyroid cancer subtypes were linked to differential gene expression in JAK-STAT signaling, NADPH oxidation, and other cancer-related pathways. These results establish that driver gene mutations are associated with methylation alterations capable of shaping regulatory network functions. In addition, the methodology presented here can be used to subdivide tumors into more homogeneous subsets corresponding to underlying molecular characteristics, which could improve treatment efficacy.');
