INSERT INTO `papers` (`id`, `ano`, `journal`, `titulo`, `autores`, `afiliacao`, `pais`, `citacoes`, `palavra_chave`, `categorias`, `doi`, `pubmed`, `abstract`) VALUES
(88747, 2017, 'plos', 'Automated visualization of rule-based models', 'Sekar, John Arul Prakash|Tapia, Jose-Juan|Faeder, James R', 'Department of Computational & Systems Biology, University of Pittsburgh, Pittsburgh, PA, United States of America.|Department of Computational & Systems Biology, University of Pittsburgh, Pittsburgh, PA, United States of America.|Department of Computational & Systems Biology, University of Pittsburgh, Pittsburgh, PA, United States of America.', 'United States|United States|United States', 7, 'Algorithms|Computational Biology|Data Compression|Humans|Image Processing, Computer-Assisted|Models, Biological|Signal Transduction', 'Journal Article', '10.1371/journal.pcbi.1005857', '29131816', 'Frameworks such as BioNetGen, Kappa and Simmune use reaction rules to specify biochemical interactions compactly, where each rule specifies a mechanism such as binding or phosphorylation and its structural requirements. Current rule-based models of signaling pathways have tens to hundreds of rules, and these numbers are expected to increase as more molecule types and pathways are added. Visual representations are critical for conveying rule-based models, but current approaches to show rules and interactions between rules scale poorly with model size. Also, inferring design motifs that emerge from biochemical interactions is an open problem, so current approaches to visualize model architecture rely on manual interpretation of the model. Here, we present three new visualization tools that constitute an automated visualization framework for rule-based models: (i) a compact rule visualization that efficiently displays each rule, (ii) the atom-rule graph that conveys regulatory interactions in the model as a bipartite network, and (iii) a tunable compression pipeline that incorporates expert knowledge and produces compact diagrams of model architecture when applied to the atom-rule graph. The compressed graphs convey network motifs and architectural features useful for understanding both small and large rule-based models, as we show by application to specific examples. Our tools also produce more readable diagrams than current approaches, as we show by comparing visualizations of 27 published models using standard graph metrics. We provide an implementation in the open source and freely available BioNetGen framework, but the underlying methods are general and can be applied to rule-based models from the Kappa and Simmune frameworks also. We expect that these tools will promote communication and analysis of rule-based models and their eventual integration into comprehensive whole-cell models.'),
(88748, 2017, 'plos', 'Characterizing steady states of genome-scale metabolic networks in continuous cell cultures', 'Fernandez-de-Cossio-Diaz, Jorge|Leon, Kalet|Mulet, Roberto', 'Systems Biology Department, Center of Molecular Immunlogy, Havana, Cuba.|Systems Biology Department, Center of Molecular Immunlogy, Havana, Cuba.|Group of Complex Systems and Statistical Physics. Department of Theoretical Physics, Physics Faculty, University of Havana, Cuba.', 'Cuba|Cuba|Cuba', 7, 'Animals|Biotechnology|CHO Cells|Cell Culture Techniques|Cricetinae|Cricetulus|Genome|Genomics|Metabolic Networks and Pathways', 'Journal Article', '10.1371/journal.pcbi.1005835', '29131817', 'In the continuous mode of cell culture, a constant flow carrying fresh media replaces culture fluid, cells, nutrients and secreted metabolites. Here we present a model for continuous cell culture coupling intra-cellular metabolism to extracellular variables describing the state of the bioreactor, taking into account the growth capacity of the cell and the impact of toxic byproduct accumulation. We provide a method to determine the steady states of this system that is tractable for metabolic networks of arbitrary complexity. We demonstrate our approach in a toy model first, and then in a genome-scale metabolic network of the Chinese hamster ovary cell line, obtaining results that are in qualitative agreement with experimental observations. We derive a number of consequences from the model that are independent of parameter values. The ratio between cell density and dilution rate is an ideal control parameter to fix a steady state with desired metabolic properties. This conclusion is robust even in the presence of multi-stability, which is explained in our model by a negative feedback loop due to toxic byproduct accumulation. A complex landscape of steady states emerges from our simulations, including multiple metabolic switches, which also explain why cell-line and media benchmarks carried out in batch culture cannot be extrapolated to perfusion. On the other hand, we predict invariance laws between continuous cell cultures with different parameters. A practical consequence is that the chemostat is an ideal experimental model for large-scale high-density perfusion cultures, where the complex landscape of metabolic transitions is faithfully reproduced.'),
(88749, 2017, 'plos', 'Electrical stimulus artifact cancellation and neural spike detection on large multi-electrode arrays', 'Mena, Gonzalo E|Grosberg, Lauren E|Madugula, Sasidhar|Hottowy, Pawexc5x82|Litke, Alan|Cunningham, John|Chichilnisky, E J|Paninski, Liam', 'Statistics Department, Columbia University, New York, New York, United States of America.|Department of Neurosurgery and Hansen Experimental Physics Laboratory, Stanford University, Stanford, California, United States of America.|Department of Neurosurgery and Hansen Experimental Physics Laboratory, Stanford University, Stanford, California, United States of America.|Physics and Applied Computer Science, AGH University of Science and Technology, Krakow, Poland.|Santa Cruz Institute for Particle Physics, University of California, Santa Cruz, Santa Cruz, California, United States of America.|Statistics Department, Columbia University, New York, New York, United States of America.|Department of Neurosurgery and Hansen Experimental Physics Laboratory, Stanford University, Stanford, California, United States of America.|Statistics Department, Columbia University, New York, New York, United States of America.', 'United States|United States|United States|Poland|United States|United States|United States|United St', 0, 'Action Potentials|Algorithms|Animals|Artifacts|Electric Stimulation|Electrodes|Humans|Models, Statistical|Primates|Retinal Neurons|Signal-To-Noise Ratio', 'Journal Article', '10.1371/journal.pcbi.1005842', '29131818', 'Simultaneous electrical stimulation and recording using multi-electrode arrays can provide a valuable technique for studying circuit connectivity and engineering neural interfaces. However, interpreting these measurements is challenging because the spike sorting process (identifying and segregating action potentials arising from different neurons) is greatly complicated by electrical stimulation artifacts across the array, which can exhibit complex and nonlinear waveforms, and overlap temporarily with evoked spikes. Here we develop a scalable algorithm based on a structured Gaussian Process model to estimate the artifact and identify evoked spikes. The effectiveness of our methods is demonstrated in both real and simulated 512-electrode recordings in the peripheral primate retina with single-electrode and several types of multi-electrode stimulation. We establish small error rates in the identification of evoked spikes, with a computational complexity that is compatible with real-time data analysis. This technology may be helpful in the design of future high-resolution sensory prostheses based on tailored stimulation (e.g., retinal prostheses), and for closed-loop neural stimulation at a much larger scale than currently possible.'),
(88750, 2017, 'plos', 'Correction: Unmet needs for analyzing biological big data: A survey of 704 NSF principal investigators', 'PLOS Computational Biology Staff', 'Statistics Department, Columbia University, New York, New York, United States of America.', 'United States', 0, '-', 'Published Erratum', '10.1371/journal.pcbi.1005858', '29131819', '[This corrects the article DOI: 10.1371/journal.pcbi.1005755.].'),
(88751, 2017, 'plos', 'Improving virtual screening of G protein-coupled receptors via ligand-directed modeling', 'Coudrat, Thomas|Simms, John|Christopoulos, Arthur|Wootten, Denise|Sexton, Patrick M', 'Drug Discovery Biology and Department of Pharmacology, Monash Institute of Pharmaceutical Sciences, Monash University, Parkville, Victoria, Australia.|School of Life and Health Sciences, Aston University, Birmingham, United Kingdom.|Drug Discovery Biology and Department of Pharmacology, Monash Institute of Pharmaceutical Sciences, Monash University, Parkville, Victoria, Australia.|Drug Discovery Biology and Department of Pharmacology, Monash Institute of Pharmaceutical Sciences, Monash University, Parkville, Victoria, Australia.|Drug Discovery Biology and Department of Pharmacology, Monash Institute of Pharmaceutical Sciences, Monash University, Parkville, Victoria, Australia.', 'Australia|United Kingdom|Australia|Australia|Australia', 0, 'Binding Sites|Computational Biology|Crystallography, X-Ray|Drug Design|Humans|Ligands|Molecular Docking Simulation|Protein Binding|Protein Conformation|Receptors, G-Protein-Coupled', 'Journal Article', '10.1371/journal.pcbi.1005819', '29131821', 'G protein-coupled receptors (GPCRs) play crucial roles in cell physiology and pathophysiology. There is increasing interest in using structural information for virtual screening (VS) of libraries and for structure-based drug design to identify novel agonist or antagonist leads. However, the sparse availability of experimentally determined GPCR/ligand complex structures with diverse ligands impedes the application of structure-based drug design (SBDD) programs directed to identifying new molecules with a select pharmacology. In this study, we apply ligand-directed modeling (LDM) to available GPCR X-ray structures to improve VS performance and selectivity towards molecules of specific pharmacological profile. The described method refines a GPCR binding pocket conformation using a single known ligand for that GPCR. The LDM method is a computationally efficient, iterative workflow consisting of protein sampling and ligand docking. We developed an extensive benchmark comparing LDM-refined binding pockets to GPCR X-ray crystal structures across seven different GPCRs bound to a range of ligands of different chemotypes and pharmacological profiles. LDM-refined models showed improvement in VS performance over origin X-ray crystal structures in 21 out of 24 cases. In all cases, the LDM-refined models had superior performance in enriching for the chemotype of the refinement ligand. This likely contributes to the LDM success in all cases of inhibitor-bound to agonist-bound binding pocket refinement, a key task for GPCR SBDD programs. Indeed, agonist ligands are required for a plethora of GPCRs for therapeutic intervention, however GPCR X-ray structures are mostly restricted to their inactive inhibitor-bound state.'),
(88752, 2017, 'plos', 'Predictive model identifies key network regulators of cardiomyocyte mechano-signaling', 'Tan, Philip M|Buchholz, Kyle S|Omens, Jeffrey H|McCulloch, Andrew D|Saucerman, Jeffrey J', 'Department of Biomedical Engineering, University of Virginia, Charlottesville, Virginia, United States of America.|Departments of Bioengineering and Medicine, University of California San Diego, La Jolla, California, United States of America.|Departments of Bioengineering and Medicine, University of California San Diego, La Jolla, California, United States of America.|Departments of Bioengineering and Medicine, University of California San Diego, La Jolla, California, United States of America.|Department of Biomedical Engineering, University of Virginia, Charlottesville, Virginia, United States of America.', 'United States|United States|United States|United States|United States', 0, 'Animals|Computational Biology|Mechanotransduction, Cellular|Models, Cardiovascular|Myocytes, Cardiac|Protein Interaction Maps|Proteins|Reproducibility of Results', 'Journal Article', '10.1371/journal.pcbi.1005854', '29131824', 'Mechanical strain is a potent stimulus for growth and remodeling in cells. Although many pathways have been implicated in stretch-induced remodeling, the control structures by which signals from distinct mechano-sensors are integrated to modulate hypertrophy and gene expression in cardiomyocytes remain unclear. Here, we constructed and validated a predictive computational model of the cardiac mechano-signaling network in order to elucidate the mechanisms underlying signal integration. The model identifies calcium, actin, Ras, Raf1, PI3K, and JAK as key regulators of cardiac mechano-signaling and characterizes crosstalk logic imparting differential control of transcription by AT1R, integrins, and calcium channels. We find that while these regulators maintain mostly independent control over distinct groups of transcription factors, synergy between multiple pathways is necessary to activate all the transcription factors necessary for gene transcription and hypertrophy. We also identify a PKG-dependent mechanism by which valsartan/sacubitril, a combination drug recently approved for treating heart failure, inhibits stretch-induced hypertrophy, and predict further efficacious pairs of drug targets in the network through a network-wide combinatorial search.'),
(88753, 2017, 'plos', 'A model-based clustering method to detect infectious disease transmission outbreaks from sequence variation', 'McCloskey, Rosemary M|Poon, Art F Y', 'BC Centre for Excellence in HIV/AIDS, Vancouver, British Columbia, Canada.|Department of Pathology and Laboratory Medicine, Western University, London, Ontario, Canada.', 'Canada|Canada', 0, 'Cluster Analysis|Communicable Diseases|Computational Biology|Computer Simulation|Disease Outbreaks|Humans|Markov Chains|Models, Biological', 'Journal Article', '10.1371/journal.pcbi.1005868', '29131825', 'Clustering infections by genetic similarity is a popular technique for identifying potential outbreaks of infectious disease, in part because sequences are now routinely collected for clinical management of many infections. A diverse number of nonparametric clustering methods have been developed for this purpose. These methods are generally intuitive, rapid to compute, and readily scale with large data sets. However, we have found that nonparametric clustering methods can be biased towards identifying clusters of diagnosis-where individuals are sampled sooner post-infection-rather than the clusters of rapid transmission that are meant to be potential foci for public health efforts. We develop a fundamentally new approach to genetic clustering based on fitting a Markov-modulated Poisson process (MMPP), which represents the evolution of transmission rates along the tree relating different infections. We evaluated this model-based method alongside five nonparametric clustering methods using both simulated and actual HIV sequence data sets. For simulated clusters of rapid transmission, the MMPP clustering method obtained higher mean sensitivity (85%) and specificity (91%) than the nonparametric methods. When we applied these clustering methods to published sequences from a study of HIV-1 genetic clusters in Seattle, USA, we found that the MMPP method categorized about half (46%) as many individuals to clusters compared to the other methods. Furthermore, the mean internal branch lengths that approximate transmission rates were significantly shorter in clusters extracted using MMPP, but not by other methods. We determined that the computing time for the MMPP method scaled linearly with the size of trees, requiring about 30 seconds for a tree of 1,000 tips and about 20 minutes for 50,000 tips on a single computer. This new approach to genetic clustering has significant implications for the application of pathogen sequence analysis to public health, where it is critical to robustly and accurately identify clusters for the most cost-effective deployment of outbreak management and prevention resources.'),
(88754, 2017, 'plos', 'A free-boundary model of a motile cell explains turning behavior', 'Nickaeen, Masoud|Novak, Igor L|Pulford, Stephanie|Rumack, Aaron|Brandon, Jamie|Slepchenko, Boris M|Mogilner, Alex', 'Richard D. Berlin Center for Cell Analysis and Modeling, Department of Cell Biology, University of Connecticut Health Center, Farmington, CT, United States of America.|Richard D. Berlin Center for Cell Analysis and Modeling, Department of Cell Biology, University of Connecticut Health Center, Farmington, CT, United States of America.|Center for Engineering Learning & Teaching, University of Washington, Seattle, WA, United States of America.|Department of Computer Science, Cornell University, Ithaca, NY, United States of America.|Department of Mathematics, Adrian College, Adrian, MI, United States of America.|Richard D. Berlin Center for Cell Analysis and Modeling, Department of Cell Biology, University of Connecticut Health Center, Farmington, CT, United States of America.|Courant Institute and Department of Biology, New York University, New York, NY, United States of America.', 'United States|United States|United States|United States|United States|United States|United States', 0, 'Actins|Biomechanical Phenomena|Cell Movement|Cell Shape|Models, Theoretical|Myosins|Pseudopodia', 'Journal Article', '10.1371/journal.pcbi.1005862', '29136638', 'To understand shapes and movements of cells undergoing lamellipodial motility, we systematically explore minimal free-boundary models of actin-myosin contractility consisting of the force-balance and myosin transport equations. The models account for isotropic contraction proportional to myosin density, viscous stresses in the actin network, and constant-strength viscous-like adhesion. The contraction generates a spatially graded centripetal actin flow, which in turn reinforces the contraction via myosin redistribution and causes retraction of the lamellipodial boundary. Actin protrusion at the boundary counters the retraction, and the balance of the protrusion and retraction shapes the lamellipodium. The model analysis shows that initiation of motility critically depends on three dimensionless parameter combinations, which represent myosin-dependent contractility, a characteristic viscosity-adhesion length, and a rate of actin protrusion. When the contractility is sufficiently strong, cells break symmetry and move steadily along either straight or circular trajectories, and the motile behavior is sensitive to conditions at the cell boundary. Scanning of a model parameter space shows that the contractile mechanism of motility supports robust cell turning in conditions where short viscosity-adhesion lengths and fast protrusion cause an accumulation of myosin in a small region at the cell rear, destabilizing the axial symmetry of a moving cell.'),
(88755, 2017, 'plos', 'A coupled-oscillator model of olfactory bulb gamma oscillations', 'Li, Guoshi|Cleland, Thomas A', 'Dept. Psychology, Cornell University, Ithaca, NY United States of America.|Dept. Psychology, Cornell University, Ithaca, NY United States of America.', 'United States|United States', 9, 'Action Potentials|Animals|Computational Biology|Gamma Rhythm|Models, Neurological|Olfactory Bulb|Rats', 'Journal Article', '10.1371/journal.pcbi.1005760', '29140973', 'The olfactory bulb transforms not only the information content of the primary sensory representation, but also its underlying coding metric. High-variance, slow-timescale primary odor representations are transformed by bulbar circuitry into secondary representations based on principal neuron spike patterns that are tightly regulated in time. This emergent fast timescale for signaling is reflected in gamma-band local field potentials, presumably serving to efficiently integrate olfactory sensory information into the temporally regulated information networks of the central nervous system. To understand this transformation and its integration with interareal coordination mechanisms requires that we understand its fundamental dynamical principles. Using a biophysically explicit, multiscale model of olfactory bulb circuitry, we here demonstrate that an inhibition-coupled intrinsic oscillator framework, pyramidal resonance interneuron network gamma (PRING), best captures the diversity of physiological properties exhibited by the olfactory bulb. Most importantly, these properties include global zero-phase synchronization in the gamma band, the phase-restriction of informative spikes in principal neurons with respect to this common clock, and the robustness of this synchronous oscillatory regime to multiple challenging conditions observed in the biological system. These conditions include substantial heterogeneities in afferent activation levels and excitatory synaptic weights, high levels of uncorrelated background activity among principal neurons, and spike frequencies in both principal neurons and interneurons that are irregular in time and much lower than the gamma frequency. This coupled cellular oscillator architecture permits stable and replicable ensemble responses to diverse sensory stimuli under various external conditions as well as to changes in network parameters arising from learning-dependent synaptic plasticity.'),
(88756, 2017, 'plos', 'A Bayesian method for detecting pairwise associations in compositional data', 'Schwager, Emma|Mallick, Himel|Ventz, Steffen|Huttenhower, Curtis', 'Department of Biostatistics, Harvard T.H. Chan School of Public Health, Boston, Massachusetts, United States of America.|Department of Biostatistics, Harvard T.H. Chan School of Public Health, Boston, Massachusetts, United States of America.|Department of Computer Science and Statistics, University of Rhode Island, Kingstown, Rhode Island, United States of America.|Department of Biostatistics, Harvard T.H. Chan School of Public Health, Boston, Massachusetts, United States of America.', 'United States|United States|United States|United States', 0, 'Algorithms|Bayes Theorem|Computational Biology|Computer Simulation|Ecology|Humans|Markov Chains|Microbiota|Models, Biological|Proteobacteria', 'Journal Article', '10.1371/journal.pcbi.1005852', '29140991', 'Compositional data consist of vectors of proportions normalized to a constant sum from a basis of unobserved counts. The sum constraint makes inference on correlations between unconstrained features challenging due to the information loss from normalization. However, such correlations are of long-standing interest in fields including ecology. We propose a novel Bayesian framework (BAnOCC: Bayesian Analysis of Compositional Covariance) to estimate a sparse precision matrix through a LASSO prior. The resulting posterior, generated by MCMC sampling, allows uncertainty quantification of any function of the precision matrix, including the correlation matrix. We also use a first-order Taylor expansion to approximate the transformation from the unobserved counts to the composition in order to investigate what characteristics of the unobserved counts can make the correlations more or less difficult to infer. On simulated datasets, we show that BAnOCC infers the true network as well as previous methods while offering the advantage of posterior inference. Larger and more realistic simulated datasets further showed that BAnOCC performs well as measured by type I and type II error rates. Finally, we apply BAnOCC to a microbial ecology dataset from the Human Microbiome Project, which in addition to reproducing established ecological results revealed unique, competition-based roles for Proteobacteria in multiple distinct habitats.'),
(88757, 2017, 'plos', 'Correction: A Unifying Probabilistic View of Associative Learning', 'PLOS Computational Biology Staff', 'Department of Biostatistics, Harvard T.H. Chan School of Public Health, Boston, Massachusetts, United States of America.', 'United States', 0, '-', 'Published Erratum', '10.1371/journal.pcbi.1005829', '29145388', '[This corrects the article DOI: 10.1371/journal.pcbi.1004567.].'),
(88758, 2017, 'plos', 'The use of ambient humidity conditions to improve influenza forecast', 'Shaman, Jeffrey|Kandula, Sasikiran|Yang, Wan|Karspeck, Alicia', 'Department of Environmental Health Sciences, Mailman School of Public Health, Columbia University, New York, NY, United States of America.|Department of Environmental Health Sciences, Mailman School of Public Health, Columbia University, New York, NY, United States of America.|Department of Environmental Health Sciences, Mailman School of Public Health, Columbia University, New York, NY, United States of America.|National Center for Atmospheric Research, Boulder, CO, United States of America.', 'United States|United States|United States|United States', 8, 'Algorithms|Computational Biology|Computer Simulation|Disease Outbreaks|Forecasting|Humans|Humidity|Influenza, Human|Retrospective Studies|United States', 'Journal Article', '10.1371/journal.pcbi.1005844', '29145389', 'Laboratory and epidemiological evidence indicate that ambient humidity modulates the survival and transmission of influenza. Here we explore whether the inclusion of humidity forcing in mathematical models describing influenza transmission improves the accuracy of forecasts generated with those models. We generate retrospective forecasts for 95 cities over 10 seasons in the United States and assess both forecast accuracy and error. Overall, we find that humidity forcing improves forecast performance (at 1-4 lead weeks, 3.8% more peak week and 4.4% more peak intensity forecasts are accurate than with no forcing) and that forecasts generated using daily climatological humidity forcing generally outperform forecasts that utilize daily observed humidity forcing (4.4% and 2.6% respectively). These findings hold for predictions of outbreak peak intensity, peak timing, and incidence over 2- and 4-week horizons. The results indicate that use of climatological humidity forcing is warranted for current operational influenza forecast.'),
(88759, 2017, 'plos', 'Estimating the probabilities of rare arrhythmic events in multiscale computational models of cardiac cells and tissue', 'Walker, Mark A|Gurev, Viatcheslav|Rice, John J|Greenstein, Joseph L|Winslow, Raimond L', 'Department of Biomedical Engineering and Institute for Computational Medicine, Johns Hopkins University, Baltimore, MD, United States of America.|TJ Watson Research Center, IBM, Yorktown Heights, NY, United States of America.|TJ Watson Research Center, IBM, Yorktown Heights, NY, United States of America.|Department of Biomedical Engineering and Institute for Computational Medicine, Johns Hopkins University, Baltimore, MD, United States of America.|Department of Biomedical Engineering and Institute for Computational Medicine, Johns Hopkins University, Baltimore, MD, United States of America.', 'United States|United States|United States|United States|United States', 0, 'Animals|Arrhythmias, Cardiac|Calcium|Calcium Signaling|Cells, Cultured|Computer Simulation|Dogs|Heart Ventricles|Membrane Potentials|Models, Cardiovascular|Myocytes, Cardiac|Probability|Ryanodine Receptor Calcium Release Channel|Sarcoplasmic Reticulum', 'Journal Article', '10.1371/journal.pcbi.1005783', '29145393', 'Ectopic heartbeats can trigger reentrant arrhythmias, leading to ventricular fibrillation and sudden cardiac death. Such events have been attributed to perturbed Ca2+ handling in cardiac myocytes leading to spontaneous Ca2+ release and delayed afterdepolarizations (DADs). However, the ways in which perturbation of specific molecular mechanisms alters the probability of ectopic beats is not understood. We present a multiscale model of cardiac tissue incorporating a biophysically detailed three-dimensional model of the ventricular myocyte. This model reproduces realistic Ca2+ waves and DADs driven by stochastic Ca2+ release channel (RyR) gating and is used to study mechanisms of DAD variability. In agreement with previous experimental and modeling studies, key factors influencing the distribution of DAD amplitude and timing include cytosolic and sarcoplasmic reticulum Ca2+ concentrations, inwardly rectifying potassium current (IK1) density, and gap junction conductance. The cardiac tissue model is used to investigate how random RyR gating gives rise to probabilistic triggered activity in a one-dimensional myocyte tissue model. A novel spatial-average filtering method for estimating the probability of extreme (i.e. rare, high-amplitude) stochastic events from a limited set of spontaneous Ca2+ release profiles is presented. These events occur when randomly organized clusters of cells exhibit synchronized, high amplitude Ca2+ release flux. It is shown how reduced IK1 density and gap junction coupling, as observed in heart failure, increase the probability of extreme DADs by multiple orders of magnitude. This method enables prediction of arrhythmia likelihood and its modulation by alterations of other cellular mechanisms.'),
(88760, 2017, 'plos', 'The role of Allee effect in modelling post resection recurrence of glioblastoma', 'Neufeld, Zoltan|von Witt, William|Lakatos, Dora|Wang, Jiaming|Hegedus, Balazs|Czirok, Andras', 'School of Mathematics and Physics, The University of Queensland, St. Lucia, Brisbane, Queensland, Australia.|School of Mathematics and Physics, The University of Queensland, St. Lucia, Brisbane, Queensland, Australia.|Department of Biological Physics, Eotvos University, Budapest, Hungary.|School of Gifted Young, University of Science and Technology of China, Hefei, China.|Department of Thoracic Surgery, Ruhrlandklinik, University Duisburg-Essen, Essen, Germany.|Department of Biological Physics, Eotvos University, Budapest, Hungary.', 'Australia|Australia|Hungary|China|Germany|Hungary', 0, 'Algorithms|Brain Neoplasms|Cell Proliferation|Computational Biology|Diffusion|Glioblastoma|Humans|Models, Biological|Neoplasm Recurrence, Local', 'Journal Article', '10.1371/journal.pcbi.1005818', '29149169', 'Resection of the bulk of a tumour often cannot eliminate all cancer cells, due to their infiltration into the surrounding healthy tissue. This may lead to recurrence of the tumour at a later time. We use a reaction-diffusion equation based model of tumour growth to investigate how the invasion front is delayed by resection, and how this depends on the density and behaviour of the remaining cancer cells. We show that the delay time is highly sensitive to qualitative details of the proliferation dynamics of the cancer cell population. The typically assumed logistic type proliferation leads to unrealistic results, predicting immediate recurrence. We find that in glioblastoma cell cultures the cell proliferation rate is an increasing function of the density at small cell densities. Our analysis suggests that cooperative behaviour of cancer cells, analogous to the Allee effect in ecology, can play a critical role in determining the time until tumour recurrence.'),
(88761, 2017, 'plos', 'Trade-off and flexibility in the dynamic regulation of the cullin-RING ubiquitin ligase repertoire', 'Straube, Ronny|Shah, Meera|Flockerzi, Dietrich|Wolf, Dieter A', 'Max Planck Institute for Dynamics of Complex Technical Systems Magdeburg, Magdeburg, Germany.|Sanford Burnham Prebys Medical Discovery Institute, La Jolla, California, United States of America.|Max Planck Institute for Dynamics of Complex Technical Systems Magdeburg, Magdeburg, Germany.|Sanford Burnham Prebys Medical Discovery Institute, La Jolla, California, United States of America.', 'Germany|United States|Germany|United States', 0, 'Computational Biology|Computer Simulation|Pliability|Protein Binding|Schizosaccharomyces pombe Proteins|Transcription Factors|Ubiquitin-Protein Ligases', 'Journal Article', '10.1371/journal.pcbi.1005869', '29149173', 'Cullin-RING ubiquitin ligases (CRLs) catalyze the ubiquitylation of substrates many of which are degraded by the 26S proteasome. Their modular architecture enables recognition of numerous substrates via exchangeable substrate receptors that competitively bind to a cullin scaffold with high affinity. Due to the plasticity of these interactions there is ongoing uncertainty how cells maintain a flexible CRL repertoire in view of changing substrate loads. Based on a series of in vivo and in vitro studies, different groups proposed that the exchange of substrate receptors is mediated by a protein exchange factor named Cand1. Here, we have performed mathematical modeling to provide a quantitative underpinning of this hypothesis. First we show that the exchange activity of Cand1 necessarily leads to a trade-off between high ligase activity and fast receptor exchange. Supported by measurements we argue that this trade-off yields an optimal Cand1 concentration in cells where the time scale for substrate degradation becomes minimal. In a second step we show through simulations that (i) substrates bias the CRL repertoire leading to preferential assembly of ligases for which substrates are available and (ii) differences in binding affinities or substrate receptor abundances create a temporal hierarchy for the degradation of substrates. Finally, we compare the Cand1-mediated exchange cycle with an alternative architecture lacking Cand1 which indicates superiority of a system with exchange factor if substrate receptors bind substrates and the cullin scaffold in a random order. Together, our results provide general constraints for the operating regimes of molecular exchange systems and suggest that Cand1 endows the CRL network with the properties of an on demand system allowing cells to dynamically adjust their CRL repertoire to fluctuating substrate abundances.'),
(88762, 2017, 'plos', 'Cell cycle time series gene expression data encoded as cyclic attractors in Hopfield systems', 'Szedlak, Anthony|Sims, Spencer|Smith, Nicholas|Paternostro, Giovanni|Piermarocchi, Carlo', 'Department of Physics and Astronomy, Michigan State University, East Lansing, Michigan, United States of America.|Department of Physics and Astronomy, Michigan State University, East Lansing, Michigan, United States of America.|Salgomed Inc., Del Mar, California, United States of America.|Sanford Burnham Prebys Medical Discovery Institute, La Jolla, California, United States of America.|Department of Physics and Astronomy, Michigan State University, East Lansing, Michigan, United States of America.', 'United States|United States|United States|United States|United States', 4, 'Algorithms|Cell Cycle|Computational Biology|Gene Expression Profiling|Gene Silencing|HeLa Cells|Humans|Models, Genetic|Neural Networks (Computer)|Saccharomyces cerevisiae|Transcriptome', 'Journal Article', '10.1371/journal.pcbi.1005849', '29149186', 'Modern time series gene expression and other omics data sets have enabled unprecedented resolution of the dynamics of cellular processes such as cell cycle and response to pharmaceutical compounds. In anticipation of the proliferation of time series data sets in the near future, we use the Hopfield model, a recurrent neural network based on spin glasses, to model the dynamics of cell cycle in HeLa (human cervical cancer) and S. cerevisiae cells. We study some of the rich dynamical properties of these cyclic Hopfield systems, including the ability of populations of simulated cells to recreate experimental expression data and the effects of noise on the dynamics. Next, we use a genetic algorithm to identify sets of genes which, when selectively inhibited by local external fields representing gene silencing compounds such as kinase inhibitors, disrupt the encoded cell cycle. We find, for example, that inhibiting the set of four kinases AURKB, NEK1, TTK, and WEE1 causes simulated HeLa cells to accumulate in the M phase. Finally, we suggest possible improvements and extensions to our model.'),
(88763, 2017, 'plos', 'A hierarchical stochastic model for bistable perception', 'Albert, Stefan|Schmack, Katharina|Sterzer, Philipp|Schneider, Gaby', 'Institute of Mathematics, Goethe University, Frankfurt (Main), Germany.|Department of Psychiatry and Psychotherapy, Charité Universitätsmedizin Berlin, Germany.|Department of Psychiatry and Psychotherapy, Charité Universitätsmedizin Berlin, Germany.|Institute of Mathematics, Goethe University, Frankfurt (Main), Germany.', 'Germany|Germany|Germany|Germany', 0, 'Case-Control Studies|Cognition Disorders|Humans|Markov Chains|Models, Theoretical|Schizophrenia|Stochastic Processes', 'Journal Article', '10.1371/journal.pcbi.1005856', '29155808', 'Viewing of ambiguous stimuli can lead to bistable perception alternating between the possible percepts. During continuous presentation of ambiguous stimuli, percept changes occur as single events, whereas during intermittent presentation of ambiguous stimuli, percept changes occur at more or less regular intervals either as single events or bursts. Response patterns can be highly variable and have been reported to show systematic differences between patients with schizophrenia and healthy controls. Existing models of bistable perception often use detailed assumptions and large parameter sets which make parameter estimation challenging. Here we propose a parsimonious stochastic model that provides a link between empirical data analysis of the observed response patterns and detailed models of underlying neuronal processes. Firstly, we use a Hidden Markov Model (HMM) for the times between percept changes, which assumes one single state in continuous presentation and a stable and an unstable state in intermittent presentation. The HMM captures the observed differences between patients with schizophrenia and healthy controls, but remains descriptive. Therefore, we secondly propose a hierarchical Brownian model (HBM), which produces similar response patterns but also provides a relation to potential underlying mechanisms. The main idea is that neuronal activity is described as an activity difference between two competing neuronal populations reflected in Brownian motions with drift. This differential activity generates switching between the two conflicting percepts and between stable and unstable states with similar mechanisms on different neuronal levels. With only a small number of parameters, the HBM can be fitted closely to a high variety of response patterns and captures group differences between healthy controls and patients with schizophrenia. At the same time, it provides a link to mechanistic models of bistable perception, linking the group differences to potential underlying mechanisms.'),
(88764, 2017, 'plos', 'Multivariate pattern dependence', 'Anzellotti, Stefano|Caramazza, Alfonso|Saxe, Rebecca', 'Brain and Cognitive Sciences Department, MIT, Cambridge, Massachusetts, United States of America.|Department of Psychology, Harvard University, Cambridge, Massachusetts, United States of America.|Brain and Cognitive Sciences Department, MIT, Cambridge, Massachusetts, United States of America.', 'United States|United States|United States', 7, 'Adolescent|Adult|Brain|Female|Humans|Male|Multivariate Analysis|Pattern Recognition, Physiological|Pattern Recognition, Visual|Young Adult', 'Journal Article', '10.1371/journal.pcbi.1005799', '29155809', 'When we perform a cognitive task, multiple brain regions are engaged. Understanding how these regions interact is a fundamental step to uncover the neural bases of behavior. Most research on the interactions between brain regions has focused on the univariate responses in the regions. However, fine grained patterns of response encode important information, as shown by multivariate pattern analysis. In the present article, we introduce and apply multivariate pattern dependence (MVPD): a technique to study the statistical dependence between brain regions in humans in terms of the multivariate relations between their patterns of responses. MVPD characterizes the responses in each brain region as trajectories in region-specific multidimensional spaces, and models the multivariate relationship between these trajectories. We applied MVPD to the posterior superior temporal sulcus (pSTS) and to the fusiform face area (FFA), using a searchlight approach to reveal interactions between these seed regions and the rest of the brain. Across two different experiments, MVPD identified significant statistical dependence not detected by standard functional connectivity. Additionally, MVPD outperformed univariate connectivity in its ability to explain independent variance in the responses of individual voxels. In the end, MVPD uncovered different connectivity profiles associated with different representational subspaces of FFA: the first principal component of FFA shows differential connectivity with occipital and parietal regions implicated in the processing of low-level properties of faces, while the second and third components show differential connectivity with anterior temporal regions implicated in the processing of invariant representations of face identity.'),
(88765, 2017, 'plos', 'An efficient moments-based inference method for within-host bacterial infection dynamics', 'Price, David J|Breuzé, Alexandre|Dybowski, Richard|Mastroeni, Piero|Restif, Olivier', 'Department of Veterinary Medicine, University of Cambridge, Cambridge, United Kingdom.|Department of Veterinary Medicine, University of Cambridge, Cambridge, United Kingdom.|Department of Veterinary Medicine, University of Cambridge, Cambridge, United Kingdom.|Department of Veterinary Medicine, University of Cambridge, Cambridge, United Kingdom.|Department of Veterinary Medicine, University of Cambridge, Cambridge, United Kingdom.', 'United Kingdom|United Kingdom|United Kingdom|United Kingdom|United Kingdom', 2, 'Animals|Bacterial Infections|Computational Biology|Host-Pathogen Interactions|Models, Biological|Stochastic Processes', 'Journal Article', '10.1371/journal.pcbi.1005841', '29155811', 'Over the last ten years, isogenic tagging (IT) has revolutionised the study of bacterial infection dynamics in laboratory animal models. However, quantitative analysis of IT data has been hindered by the piecemeal development of relevant statistical models. The most promising approach relies on stochastic Markovian models of bacterial population dynamics within and among organs. Here we present an efficient numerical method to fit such stochastic dynamic models to in vivo experimental IT data. A common approach to statistical inference with stochastic dynamic models relies on producing large numbers of simulations, but this remains a slow and inefficient method for all but simple problems, especially when tracking bacteria in multiple locations simultaneously. Instead, we derive and solve the systems of ordinary differential equations for the two lower-order moments of the stochastic variables (mean, variance and covariance). For any given model structure, and assuming linear dynamic rates, we demonstrate how the model parameters can be efficiently and accurately estimated by divergence minimisation. We then apply our method to an experimental dataset and compare the estimates and goodness-of-fit to those obtained by maximum likelihood estimation. While both sets of parameter estimates had overlapping confidence regions, the new method produced lower values for the division and death rates of bacteria: these improved the goodness-of-fit at the second time point at the expense of that of the first time point. This flexible framework can easily be applied to a range of experimental systems. Its computational efficiency paves the way for model comparison and optimal experimental design.'),
(88766, 2017, 'plos', 'fluEvidenceSynthesis: An R package for evidence synthesis based analysis of epidemiological outbreaks', 'van Leeuwen, Edwin|Klepac, Petra|Thorrington, Dominic|Pebody, Richard|Baguelin, Marc', 'Respiratory Diseases Department, Public Health England, London, United Kingdom.|Respiratory Diseases Department, Public Health England, London, United Kingdom.|Respiratory Diseases Department, Public Health England, London, United Kingdom.|Respiratory Diseases Department, Public Health England, London, United Kingdom.|Respiratory Diseases Department, Public Health England, London, United Kingdom.', 'United Kingdom|United Kingdom|United Kingdom|United Kingdom|United Kingdom', 1, 'Bayes Theorem|Computational Biology|Disease Outbreaks|Humans|Influenza Vaccines|Influenza, Human|Models, Theoretical|United Kingdom', 'Journal Article', '10.1371/journal.pcbi.1005838', '29155812', 'Public health related decisions often have to balance the cost of intervention strategies with the benefit of the reduction in disease burden. While the cost can often be inferred, forward modelling of the effect of different intervention options is complicated and disease specific. Here we introduce a package that is aimed to simplify this process. The package allows one to infer parameters using a Bayesian approach, perform forward modelling of the likely results of the proposed intervention and finally perform cost effectiveness analysis of the results. The package is based on a method previously used in the United Kingdom to inform vaccination strategies for influenza, with extensions to make it easily adaptable to other diseases and data sources.'),
(88767, 2017, 'plos', 'Optimal synaptic signaling connectome for locomotory behavior in Caenorhabditis elegans: Design minimizing energy cost', 'Rakowski, Franciszek|Karbowski, Jan', 'Interdisciplinary Centre for Mathematical and Computational Modeling, University of Warsaw, Warsaw, Poland.|Nalecz Institute of Biocybernetics and Biomedical Engineering, Polish Academy of Sciences, Warsaw, Poland.', 'Poland|Poland', 0, 'Animals|Caenorhabditis elegans|Computational Biology|Connectome|Energy Metabolism|Interneurons|Locomotion|Models, Biological|Signal Transduction|Synapses', 'Journal Article', '10.1371/journal.pcbi.1005834', '29155814', 'The detailed knowledge of C. elegans connectome for 3 decades has not contributed dramatically to our understanding of worms behavior. One of main reasons for this situation has been the lack of data on the type of synaptic signaling between particular neurons in the worms connectome. The aim of this study was to determine synaptic polarities for each connection in a small pre-motor circuit controlling locomotion. Even in this compact network of just 7 neurons the space of all possible patterns of connection types (excitation vs. inhibition) is huge. To deal effectively with this combinatorial problem we devised a novel and relatively fast technique based on genetic algorithms and large-scale parallel computations, which we combined with detailed neurophysiological modeling of interneuron dynamics and compared the theory to the available behavioral data. As a result of these massive computations, we found that the optimal connectivity pattern that matches the best locomotory data is the one in which all interneuron connections are inhibitory, even those terminating on motor neurons. This finding is consistent with recent experimental data on cholinergic signaling in C. elegans, and it suggests that the system controlling locomotion is designed to save metabolic energy. Moreover, this result provides a solid basis for a more realistic modeling of neural control in these worms, and our novel powerful computational technique can in principle be applied (possibly with some modifications) to other small-scale functional circuits in C. elegans.');
INSERT INTO `papers` (`id`, `ano`, `journal`, `titulo`, `autores`, `afiliacao`, `pais`, `citacoes`, `palavra_chave`, `categorias`, `doi`, `pubmed`, `abstract`) VALUES
(88768, 2017, 'plos', 'Choose, rate or squeeze: Comparison of economic value functions elicited by different behavioral tasks', 'Lopez-Persem, Alizée|Rigoux, Lionel|Bourgeois-Gironde, Sacha|Daunizeau, Jean|Pessiglione, Mathias', 'Motivation, Brain and Behavior (MBB) team, Institut du Cerveau et de la Moelle épinière (ICM), Hôpital de la Pitié-Salpêtrière, Paris, France.|Max Planck Institute for Metabolism Research Cologne, Cologne, Germany.|Laboratoire dÉconomie Mathématique et de Microéconomie Appliquée (LEMMA), Université Panthéon-Assas, Paris, France.|Motivation, Brain and Behavior (MBB) team, Institut du Cerveau et de la Moelle épinière (ICM), Hôpital de la Pitié-Salpêtrière, Paris, France.|Motivation, Brain and Behavior (MBB) team, Institut du Cerveau et de la Moelle épinière (ICM), Hôpital de la Pitié-Salpêtrière, Paris, France.', 'France|Germany|France|France|France', 6, 'Adult|Bayes Theorem|Choice Behavior|Economics|Female|Humans|Magnetic Resonance Imaging|Male|Models, Theoretical|Task Performance and Analysis|Young Adult', 'Comparative Study', '10.1371/journal.pcbi.1005848', '29161252', 'A standard view in neuroeconomics is that to make a choice, an agent first assigns subjective values to available options, and then compares them to select the best. In choice tasks, these cardinal values are typically inferred from the preference expressed by subjects between options presented in pairs. Alternatively, cardinal values can be directly elicited by asking subjects to place a cursor on an analog scale (rating task) or to exert a force on a power grip (effort task). These tasks can vary in many respects: they can notably be more or less costly and consequential. Here, we compared the value functions elicited by choice, rating and effort tasks on options composed of two monetary amounts: one for the subject (gain) and one for a charity (donation). Bayesian model selection showed that despite important differences between the three tasks, they all elicited a same value function, with similar weighting of gain and donation, but variable concavity. Moreover, value functions elicited by the different tasks could predict choices with equivalent accuracy. Our finding therefore suggests that comparable value functions can account for various motivated behaviors, beyond economic choice. Nevertheless, we report slight differences in the computational efficiency of parameter estimation that may guide the design of future studies.'),
(88769, 2017, 'plos', 'Identifying influential neighbors in animal flocking', 'Jiang, Li|Giuggioli, Luca|Perna, Andrea|Escobedo, Ramón|Lecheval, Valentin|Sire, Clément|Han, Zhangang|Theraulaz, Guy', 'School of Systems Science, Beijing Normal University, Beijing, China.|Bristol Centre for Complexity Sciences, Department of Engineering Mathematics and School of Biological Sciences, University of Bristol, Bristol, United Kingdom.|Life Sciences, Roehampton University, London, United Kingdom.|Centre de Recherches sur la Cognition Animale, Centre de Biologie Intégrative (CBI), Centre National de la Recherche Scientifique (CNRS), Université Paul Sabatier (UPS), Toulouse, France.|Centre de Recherches sur la Cognition Animale, Centre de Biologie Intégrative (CBI), Centre National de la Recherche Scientifique (CNRS), Université Paul Sabatier (UPS), Toulouse, France.|Laboratoire de Physique Théorique, CNRS & Université de Toulouse (UPS), Toulouse, France.|School of Systems Science, Beijing Normal University, Beijing, China.|Centre de Recherches sur la Cognition Animale, Centre de Biologie Intégrative (CBI), Centre National de la Recherche Scientifique (CNRS), Université Paul Sabatier (UPS), Toulouse, France.', 'China|United Kingdom|United Kingdom|France|France|France|China|France', 0, 'Algorithms|Animals|Behavior, Animal|Birds|Computational Biology|Computer Simulation|Fishes|Models, Biological|Movement|Software|Swimming|Temperature', 'Journal Article', '10.1371/journal.pcbi.1005822', '29161269', 'Schools of fish and flocks of birds can move together in synchrony and decide on new directions of movement in a seamless way. This is possible because group members constantly share directional information with their neighbors. Although detecting the directionality of other group members is known to be important to maintain cohesion, it is not clear how many neighbors each individual can simultaneously track and pay attention to, and what the spatial distribution of these influential neighbors is. Here, we address these questions on shoals of Hemigrammus rhodostomus, a species of fish exhibiting strong schooling behavior. We adopt a data-driven analysis technique based on the study of short-term directional correlations to identify which neighbors have the strongest influence over the participation of an individual in a collective U-turn event. We find that fish mainly react to one or two neighbors at a time. Moreover, we find no correlation between the distance rank of a neighbor and its likelihood to be influential. We interpret our results in terms of fish allocating sequential and selective attention to their neighbors.'),
(88770, 2017, 'plos', 'Tracking urban human activity from mobile phone calling patterns', 'Monsivais, Daniel|Ghosh, Asim|Bhattacharya, Kunal|Dunbar, Robin I M|Kaski, Kimmo', 'Department of Computer Science, Aalto University School of Science, Espoo, Finland.|Department of Computer Science, Aalto University School of Science, Espoo, Finland.|Department of Computer Science, Aalto University School of Science, Espoo, Finland.|Department of Computer Science, Aalto University School of Science, Espoo, Finland.|Department of Computer Science, Aalto University School of Science, Espoo, Finland.', 'Finland|Finland|Finland|Finland|Finland', 8, 'Adult|Aged|Aged, 80 and over|Algorithms|Cell Phone|Circadian Clocks|Circadian Rhythm|Cities|Data Collection|Environment|Female|Human Activities|Humans|Light|Lighting|Male|Middle Aged|Movement|Probability|Seasons|Sleep|Temperature|Time Factors|Urban Population|Young Adult', 'Journal Article', '10.1371/journal.pcbi.1005824', '29161270', 'Timings of human activities are marked by circadian clocks which in turn are entrained to different environmental signals. In an urban environment the presence of artificial lighting and various social cues tend to disrupt the natural entrainment with the sunlight. However, it is not completely understood to what extent this is the case. Here we exploit the large-scale data analysis techniques to study the mobile phone calling activity of people in large cities to infer the dynamics of urban daily rhythms. From the calling patterns of about 1,000,000 users spread over different cities but lying inside the same time-zone, we show that the onset and termination of the calling activity synchronizes with the east-west progression of the sun. We also find that the onset and termination of the calling activity of users follows a yearly dynamics, varying across seasons, and that its timings are entrained to solar midnight. Furthermore, we show that the average mid-sleep time of people living in urban areas depends on the age and gender of each cohort as a result of biological and social factors.'),
(88771, 2017, 'plos', 'Fragmentation modes and the evolution of life cycles', 'Pichugin, Yuriy|Peña, Jorge|Rainey, Paul B|Traulsen, Arne', 'Max Planck Institute for Evolutionary Biology, Plön, Germany.|Max Planck Institute for Evolutionary Biology, Plön, Germany.|Max Planck Institute for Evolutionary Biology, Plön, Germany.|Max Planck Institute for Evolutionary Biology, Plön, Germany.', 'Germany|Germany|Germany|Germany', 7, 'Animals|Bacteria|Biological Evolution|Cell Physiological Phenomena|Computational Biology|Life Cycle Stages|Models, Biological|Reproduction', 'Journal Article', '10.1371/journal.pcbi.1005860', '29166656', 'Reproduction is a defining feature of living systems. To reproduce, aggregates of biological units (e.g., multicellular organisms or colonial bacteria) must fragment into smaller parts. Fragmentation modes in nature range from binary fission in bacteria to collective-level fragmentation and the production of unicellular propagules in multicellular organisms. Despite this apparent ubiquity, the adaptive significance of fragmentation modes has received little attention. Here, we develop a model in which groups arise from the division of single cells that do not separate but stay together until the moment of group fragmentation. We allow for all possible fragmentation patterns and calculate the population growth rate of each associated life cycle. Fragmentation modes that maximise growth rate comprise a restrictive set of patterns that include production of unicellular propagules and division into two similar size groups. Life cycles marked by single-cell bottlenecks maximise population growth rate under a wide range of conditions. This surprising result offers a new evolutionary explanation for the widespread occurrence of this mode of reproduction. All in all, our model provides a framework for exploring the adaptive significance of fragmentation modes and their associated life cycles.'),
(88772, 2017, 'plos', 'Initial-state-dependent, robust, transient neural dynamics encode conscious visual perception', 'Baria, Alexis T|Maniscalco, Brian|He, Biyu J', 'National Institute of Neurological Disorders and Stroke, National Institutes of Health, Bethesda, Maryland, United States of America.|National Institute of Neurological Disorders and Stroke, National Institutes of Health, Bethesda, Maryland, United States of America.|National Institute of Neurological Disorders and Stroke, National Institutes of Health, Bethesda, Maryland, United States of America.', 'United States|United States|United States', 0, 'Adult|Brain|Computational Biology|Female|Humans|Magnetoencephalography|Male|Models, Neurological|Signal Processing, Computer-Assisted|Task Performance and Analysis|Visual Perception|Young Adult', 'Journal Article', '10.1371/journal.pcbi.1005806', '29176808', 'Recent research has identified late-latency, long-lasting neural activity as a robust correlate of conscious perception. Yet, the dynamical nature of this activity is poorly understood, and the mechanisms governing its presence or absence and the associated conscious perception remain elusive. We applied dynamic-pattern analysis to whole-brain slow (< 5 Hz) cortical dynamics recorded by magnetoencephalography (MEG) in human subjects performing a threshold-level visual perception task. Up to 1 second before stimulus onset, brain activity pattern across widespread cortices significantly predicted whether a threshold-level visual stimulus was later consciously perceived. This initial state of brain activity interacts nonlinearly with stimulus input to shape the evolving cortical activity trajectory, with seen and unseen trials following well separated trajectories. We observed that cortical activity trajectories during conscious perception are fast evolving and robust to small variations in the initial state. In addition, spontaneous brain activity pattern prior to stimulus onset also influences unconscious perceptual making in unseen trials. Together, these results suggest that brain dynamics underlying conscious visual perception belongs to the class of initial-state-dependent, robust, transient neural dynamics.'),
(88773, 2017, 'plos', 'The effect of spatial randomness on the average fixation time of mutants', 'Farhang-Sardroodi, Suzan|Darooneh, Amir H|Nikbakht, Moladad|Komarova, Natalia L|Kohandel, Mohammad', 'Department of Physics, University of Zanjan, Zanjan, Iran.|Department of Physics, University of Zanjan, Zanjan, Iran.|Department of Physics, University of Zanjan, Zanjan, Iran.|Department of Mathematics, University of California Irvine, Irvine, California, United States of America.|Department of Applied Mathematics, University of Waterloo, Waterloo, Ontario, Canada.', '-|-|-|United States|Canada', 0, 'Computational Biology|Evolution, Molecular|Genetic Fitness|Models, Biological|Models, Statistical|Mutation|Population Dynamics', 'Journal Article', '10.1371/journal.pcbi.1005864', '29176825', 'The mean conditional fixation time of a mutant is an important measure of stochastic population dynamics, widely studied in ecology and evolution. Here, we investigate the effect of spatial randomness on the mean conditional fixation time of mutants in a constant population of cells, N. Specifically, we assume that fitness values of wild type cells and mutants at different locations come from given probability distributions and do not change in time. We study spatial arrangements of cells on regular graphs with different degrees, from the circle to the complete graph, and vary assumptions on the fitness probability distributions. Some examples include: identical probability distributions for wild types and mutants, cases when only one of the cell types has random fitness values while the other has deterministic fitness, and cases where the mutants are advantaged or disadvantaged. Using analytical calculations and stochastic numerical simulations, we find that randomness has a strong impact on fixation time. In the case of complete graphs, randomness accelerates mutant fixation for all population sizes, and in the case of circular graphs, randomness delays mutant fixation for N larger than a threshold value (for small values of N, different behaviors are observed depending on the fitness distribution functions). These results emphasize fundamental differences in population dynamics under different assumptions on cell connectedness. They are explained by the existence of randomly occurring dead zones that can significantly delay fixation on networks with low connectivity, and by the existence of randomly occurring lucky zones that can facilitate fixation on networks of high connectivity. Results for death-birth and birth-death formulations of the Moran process, as well as for the (haploid) Wright Fisher model are presented.'),
(88774, 2017, 'plos', 'Strawberry: Fast and accurate genome-guided transcript reconstruction and quantification from RNA-Seq', 'Liu, Ruolin|Dickerson, Julie', 'Department of Electrical and Computational Engineering, Iowa State University, Ames, Iowa, United States of America.|Department of Electrical and Computational Engineering, Iowa State University, Ames, Iowa, United States of America.', 'United States|United States', 7, 'Algorithms|Genomics|RNA|Sequence Alignment|Sequence Analysis, RNA|Software', 'Journal Article', '10.1371/journal.pcbi.1005851', '29176847', 'We propose a novel method and software tool, Strawberry, for transcript reconstruction and quantification from RNA-Seq data under the guidance of genome alignment and independent of gene annotation. Strawberry consists of two modules: assembly and quantification. The novelty of Strawberry is that the two modules use different optimization frameworks but utilize the same data graph structure, which allows a highly efficient, expandable and accurate algorithm for dealing large data. The assembly module parses aligned reads into splicing graphs, and uses network flow algorithms to select the most likely transcripts. The quantification module uses a latent class model to assign read counts from the nodes of splicing graphs to transcripts. Strawberry simultaneously estimates the transcript abundances and corrects for sequencing bias through an EM algorithm. Based on simulations, Strawberry outperforms Cufflinks and StringTie in terms of both assembly and quantification accuracies. Under the evaluation of a real data set, the estimated transcript expression by Strawberry has the highest correlation with Nanostring probe counts, an independent experiment measure for transcript expression.'),
(88775, 2017, 'plos', 'Dynamical compensation and structural identifiability of biological models: Analysis, implications, and reconciliation', 'Villaverde, Alejandro F|Banga, Julio R', 'Bioprocess Engineering Group, IIM-CSIC, Vigo, Spain.|Bioprocess Engineering Group, IIM-CSIC, Vigo, Spain.', 'Spain|Spain', 0, 'Feedback, Physiological|Humans|Models, Biological|Systems Biology', 'Journal Article', '10.1371/journal.pcbi.1005878', '29186132', 'The concept of dynamical compensation has been recently introduced to describe the ability of a biological system to keep its output dynamics unchanged in the face of varying parameters. However, the original definition of dynamical compensation amounts to lack of structural identifiability. This is relevant if model parameters need to be estimated, as is often the case in biological modelling. Care should we taken when using an unidentifiable model to extract biological insight: the estimated values of structurally unidentifiable parameters are meaningless, and model predictions about unmeasured state variables can be wrong. Taking this into account, we explore alternative definitions of dynamical compensation that do not necessarily imply structural unidentifiability. Accordingly, we show different ways in which a model can be made identifiable while exhibiting dynamical compensation. Our analyses enable the use of the new concept of dynamical compensation in the context of parameter identification, and reconcile it with the desirable property of structural identifiability.'),
(88776, 2017, 'plos', 'A network diffusion approach to inferring sample-specific function reveals functional changes associated with breast cancer', 'Patkar, Sushant|Magen, Assaf|Sharan, Roded|Hannenhalli, Sridhar', 'Center for Bioinformatics and Computational Biology, University of Maryland, College Park, Maryland, United States of America.|Center for Bioinformatics and Computational Biology, University of Maryland, College Park, Maryland, United States of America.|Blavatnik School of Computer Science, Tel Aviv University, Tel Aviv, Israel.|Center for Bioinformatics and Computational Biology, University of Maryland, College Park, Maryland, United States of America.', 'United States|United States|Israel|United States', 7, 'Algorithms|Breast|Breast Neoplasms|Cluster Analysis|Computational Biology|Diffusion|Female|Gene Expression Profiling|Humans|Mutation|Protein Interaction Maps|Transcriptome', 'Journal Article', '10.1371/journal.pcbi.1005793', '29190299', 'Guilt-by-association codifies the empirical observation that a genes function is informed by its neighborhood in a biological network. This would imply that when a genes network context is altered, for instance in disease condition, so could be the genes function. Although context-specific changes in biological networks have been explored, the potential changes they may induce on the functional roles of genes are yet to be characterized. Here we analyze, for the first time, the network-induced potential functional changes in breast cancer. Using transcriptomic samples for 1047 breast tumors and 110 healthy breast tissues from TCGA, we derive sample-specific protein interaction networks and assign sample-specific functions to genes via a diffusion strategy. Testing for significant changes in the inferred functions between normal and cancer samples, we find several functions to have significantly gained or lost genes in cancer, not due to differential expression of genes known to perform the function, but rather due to changes in the network topology. Our predicted functional changes are supported by mutational and copy number profiles in breast cancers. Our diffusion-based functional assignment provides a novel characterization of a tumor that is complementary to the standard approach based on functional annotation alone. Importantly, this characterization is effective in predicting patient survival, as well as in predicting several known histopathological subtypes of breast cancer.'),
(88777, 2017, 'plos', 'Metabomatching: Using genetic association to identify metabolites in proton NMR spectroscopy', 'Rueedi, Rico|Mallol, Roger|Raffler, Johannes|Lamparter, David|Friedrich, Nele|Vollenweider, Peter|Waeber, Gérard|Kastenmüller, Gabi|Kutalik, Zoltán|Bergmann, Sven', 'Department of Computational Biology, University of Lausanne, Lausanne, Switzerland.|Department of Computational Biology, University of Lausanne, Lausanne, Switzerland.|Institute of Bioinformatics and Systems Biology, Helmholtz Zentrum München, German Research Center for Environmental Health, Neuherberg, Germany.|Department of Computational Biology, University of Lausanne, Lausanne, Switzerland.|Institute of Clinical Chemistry and Laboratory Medicine, University Medicine Greifswald, Greifswald, Germany.|Department of Medicine, Internal Medicine, Lausanne University Hospital (CHUV), Lausanne, Switzerland.|Department of Medicine, Internal Medicine, Lausanne University Hospital (CHUV), Lausanne, Switzerland.|Institute of Bioinformatics and Systems Biology, Helmholtz Zentrum München, German Research Center for Environmental Health, Neuherberg, Germany.|Swiss Institute of Bioinformatics, Lausanne, Switzerland.|Department of Computational Biology, University of Lausanne, Lausanne, Switzerland.', 'Switzerland|Switzerland|Germany|Switzerland|Germany|Switzerland|Switzerland|Germany|Switzerland|Swit', 4, 'Databases, Genetic|Genome-Wide Association Study|Humans|Magnetic Resonance Spectroscopy|Metabolomics', 'Journal Article', '10.1371/journal.pcbi.1005839', '29194434', 'A metabolome-wide genome-wide association study (mGWAS) aims to discover the effects of genetic variants on metabolome phenotypes. Most mGWASes use as phenotypes concentrations of limited sets of metabolites that can be identified and quantified from spectral information. In contrast, in an untargeted mGWAS both identification and quantification are forgone and, instead, all measured metabolome features are tested for association with genetic variants. While the untargeted approach does not discard data that may have eluded identification, the interpretation of associated features remains a challenge. To address this issue, we developed metabomatching to identify the metabolites underlying significant associations observed in untargeted mGWASes on proton NMR metabolome data. Metabomatching capitalizes on genetic spiking, the concept that because metabolome features associated with a genetic variant tend to correspond to the peaks of the NMR spectrum of the underlying metabolite, genetic association can allow for identification. Applied to the untargeted mGWASes in the SHIP and CoLaus cohorts and using 180 reference NMR spectra of the urine metabolome database, metabomatching successfully identified the underlying metabolite in 14 of 19, and 8 of 9 associations, respectively. The accuracy and efficiency of our method make it a strong contender for facilitating or complementing metabolomics analyses in large cohorts, where the availability of genetic, or other data, enables our approach, but targeted quantification is limited.'),
(88778, 2017, 'plos', 'Genetic drift and selection in many-allele range expansions', 'Weinstein, Bryan T|Lavrentovich, Maxim O|Möbius, Wolfram|Murray, Andrew W|Nelson, David R', 'School of Engineering and Applied Sciences, Harvard University, Cambridge, Massachusetts, United States of America.|Department of Physics and Astronomy, University of Pennsylvania, Philadelphia, Pennsylvania, United States of America.|Living Systems Institute, University of Exeter, Exeter, United Kingdom.|FAS Center for Systems Biology, Harvard University, Cambridge, Massachusetts, United States of America.|School of Engineering and Applied Sciences, Harvard University, Cambridge, Massachusetts, United States of America.', 'United States|United States|United Kingdom|United States|United States', 0, 'Algorithms|Alleles|Computational Biology|Computer Simulation|Escherichia coli|Evolution, Molecular|Genetic Drift|Models, Genetic|Selection, Genetic', 'Journal Article', '10.1371/journal.pcbi.1005866', '29194439', 'We experimentally and numerically investigate the evolutionary dynamics of four competing strains of E. coli with differing expansion velocities in radially expanding colonies. We compare experimental measurements of the average fraction, correlation functions between strains, and the relative rates of genetic domain wall annihilations and coalescences to simulations modeling the population as a one-dimensional ring of annihilating and coalescing random walkers with deterministic biases due to selection. The simulations reveal that the evolutionary dynamics can be collapsed onto master curves governed by three essential parameters: (1) an expansion length beyond which selection dominates over genetic drift, (2) a characteristic angular correlation describing the size of genetic domains, and (3) a dimensionless constant quantifying the interplay between a colonys curvature at the frontier and its selection length scale. We measure these parameters with a new technique that precisely measures small selective differences between spatially competing strains and show that our simulations accurately predict the dynamics without additional fitting. Our results suggest that the random walk model can act as a useful predictive tool for describing the evolutionary dynamics of range expansions composed of an arbitrary number of genotypes with different fitnesses.'),
(88779, 2017, 'plos', 'Sequence-dependent nucleosome sliding in rotation-coupled and uncoupled modes revealed by molecular simulations', 'Niina, Toru|Brandani, Giovanni B|Tan, Cheng|Takada, Shoji', 'Department of Biophysics, Graduate School of Science, Kyoto University, Kyoto, Japan.|Department of Biophysics, Graduate School of Science, Kyoto University, Kyoto, Japan.|Department of Biophysics, Graduate School of Science, Kyoto University, Kyoto, Japan.|Department of Biophysics, Graduate School of Science, Kyoto University, Kyoto, Japan.', 'Japan|Japan|Japan|Japan', 15, 'Base Sequence|Chromatin Assembly and Disassembly|Computational Biology|Histones|Hydrogen Bonding|Models, Genetic|Molecular Dynamics Simulation|Nucleosomes|Sequence Analysis, DNA', 'Journal Article', '10.1371/journal.pcbi.1005880', '29194442', 'While nucleosome positioning on eukaryotic genome play important roles for genetic regulation, molecular mechanisms of nucleosome positioning and sliding along DNA are not well understood. Here we investigated thermally-activated spontaneous nucleosome sliding mechanisms developing and applying a coarse-grained molecular simulation method that incorporates both long-range electrostatic and short-range hydrogen-bond interactions between histone octamer and DNA. The simulations revealed two distinct sliding modes depending on the nucleosomal DNA sequence. A uniform DNA sequence showed frequent sliding with one base pair step in a rotation-coupled manner, akin to screw-like motions. On the contrary, a strong positioning sequence, the so-called 601 sequence, exhibits rare, abrupt transitions of five and ten base pair steps without rotation. Moreover, we evaluated the importance of hydrogen bond interactions on the sliding mode, finding that strong and weak bonds favor respectively the rotation-coupled and -uncoupled sliding movements.'),
(88780, 2017, 'plos', 'Olfactory coding in the turbulent realm', 'Jacob, Vincent|Monsempès, Christelle|Rospars, Jean-Pierre|Masson, Jean-Baptiste|Lucas, Philippe', 'Institute of Ecology and Environmental Sciences, INRA, route de St Cyr, Versailles, France.|Institute of Ecology and Environmental Sciences, INRA, route de St Cyr, Versailles, France.|Institute of Ecology and Environmental Sciences, INRA, route de St Cyr, Versailles, France.|Decision and Bayesian Computation, Pasteur Institute, CNRS UMR 3571, 25-28 rue du Dr Roux, 75015 Paris, France.|Institute of Ecology and Environmental Sciences, INRA, route de St Cyr, Versailles, France.', 'France|France|France|France|France', 8, 'Animals|Appetitive Behavior|Arthropod Antennae|Computational Biology|Male|Moths|Olfactory Pathways|Olfactory Receptor Neurons|Pheromones', 'Journal Article', '10.1371/journal.pcbi.1005870', '29194457', 'Long-distance olfactory search behaviors depend on odor detection dynamics. Due to turbulence, olfactory signals travel as bursts of variable concentration and spacing and are characterized by long-tail distributions of odor/no-odor events, challenging the computing capacities of olfactory systems. How animals encode complex olfactory scenes to track the plume far from the source remains unclear. Here we focus on the coding of the plume temporal dynamics in moths. We compare responses of olfactory receptor neurons (ORNs) and antennal lobe projection neurons (PNs) to sequences of pheromone stimuli either with white-noise patterns or with realistic turbulent temporal structures simulating a large range of distances (8 to 64 m) from the odor source. For the first time, we analyze what information is extracted by the olfactory system at large distances from the source. Neuronal responses are analyzed using linear-nonlinear models fitted with white-noise stimuli and used for predicting responses to turbulent stimuli. We found that neuronal firing rate is less correlated with the dynamic odor time course when distance to the source increases because of improper coding during long odor and no-odor events that characterize large distances. Rapid adaptation during long puffs does not preclude however the detection of puff transitions in PNs. Individual PNs but not individual ORNs encode the onset and offset of odor puffs for any temporal structure of stimuli. A higher spontaneous firing rate coupled to an inhibition phase at the end of PN responses contributes to this coding property. This allows PNs to decode the temporal structure of the odor plume at any distance to the source, an essential piece of information moths can use in their tracking behavior.'),
(88781, 2017, 'plos', 'A model of the onset of the senescence associated secretory phenotype after DNA damage induced senescence', 'Meyer, Patrick|Maity, Pallab|Burkovski, Andre|Schwab, Julian|Mxc3xbcssel, Christoph|Singh, Karmveer|Ferreira, Filipa F|Krug, Linda|Maier, Harald J|Wlaschek, Meinhard|Wirth, Thomas|Kestler, Hans A|Scharffetter-Kochanek, Karin', 'Department of Dermatology and Allergic Diseases, University of Ulm, Germany.|Department of Dermatology and Allergic Diseases, University of Ulm, Germany.|Institute of Medical Systems Biology, University of Ulm, Germany.|Institute of Medical Systems Biology, University of Ulm, Germany.|Institute of Medical Systems Biology, University of Ulm, Germany.|Department of Dermatology and Allergic Diseases, University of Ulm, Germany.|Department of Dermatology and Allergic Diseases, University of Ulm, Germany.|Department of Dermatology and Allergic Diseases, University of Ulm, Germany.|Aging Research Center (ARC), University of Ulm, Germany.|Department of Dermatology and Allergic Diseases, University of Ulm, Germany.|Institute of Physiological Chemistry, University of Ulm, Germany.|Aging Research Center (ARC), University of Ulm, Germany.|Department of Dermatology and Allergic Diseases, University of Ulm, Germany.', 'Germany|Germany|Germany|Germany|Germany|Germany|Germany|Germany|Germany|Germany|Germany|Germany|Germ', 16, 'Animals|Cells, Cultured|Cellular Senescence|Computational Biology|Computer Simulation|DNA Damage|Fibroblasts|Interleukin-6|Interleukin-8|Mice|Models, Biological|Signal Transduction', 'Journal Article', '10.1371/journal.pcbi.1005741', '29206223', 'Cells and tissues are exposed to stress from numerous sources. Senescence is a protective mechanism that prevents malignant tissue changes and constitutes a fundamental mechanism of aging. It can be accompanied by a senescence associated secretory phenotype (SASP) that causes chronic inflammation. We present a Boolean network model-based gene regulatory network of the SASP, incorporating published gene interaction data. The simulation results describe current biological knowledge. The model predicts different in-silico knockouts that prevent key SASP-mediators, IL-6 and IL-8, from getting activated upon DNA damage. The NF-xcexbaB Essential Modulator (NEMO) was the most promising in-silico knockout candidate and we were able to show its importance in the inhibition of IL-6 and IL-8 following DNA-damage in murine dermal fibroblasts in-vitro. We strengthen the speculated regulator function of the NF-xcexbaB signaling pathway in the onset and maintenance of the SASP using in-silico and in-vitro approaches. We were able to mechanistically show, that DNA damage mediated SASP triggering of IL-6 and IL-8 is mainly relayed through NF-xcexbaB, giving access to possible therapy targets for SASP-accompanied diseases.'),
(88782, 2017, 'plos', 'Efficient encoding of motion is mediated by gap junctions in the fly visual system', 'Wang, Siwei|Borst, Alexander|Zaslavsky, Noga|Tishby, Naftali|Segev, Idan', 'Department of Neurobiology, Hebrew University Jerusalem, Jerusalem, Israel.|Max Planck Institute of Neurobiology, Martinstried, Munich, Germany.|The Edmond and Lily Safra Center for Brain Sciences, Hebrew University Jerusalem, Jerusalem, Israel.|The Edmond and Lily Safra Center for Brain Sciences, Hebrew University Jerusalem, Jerusalem, Israel.|Department of Neurobiology, Hebrew University Jerusalem, Jerusalem, Israel.', 'Israel|Germany|Israel|Israel|Israel', 3, 'Animals|Computational Biology|Diptera|Gap Junctions|Motion Perception|Photoreceptor Cells|Visual Pathways', 'Journal Article', '10.1371/journal.pcbi.1005846', '29206224', 'Understanding the computational implications of specific synaptic connectivity patterns is a fundamental goal in neuroscience. In particular, the computational role of ubiquitous electrical synapses operating via gap junctions remains elusive. In the fly visual system, the cells in the vertical-system network, which play a key role in visual processing, primarily connect to each other via axonal gap junctions. This network therefore provides a unique opportunity to explore the functional role of gap junctions in sensory information processing. Our information theoretical analysis of a realistic VS network model shows that within 10 ms following the onset of the visual input, the presence of axonal gap junctions enables the VS system to efficiently encode the axis of rotation, xcexb8, of the flys ego motion. This encoding efficiency, measured in bits, is near-optimal with respect to the physical limits of performance determined by the statistical structure of the visual input itself. The VS network is known to be connected to downstream pathways via a subset of triplets of the vertical system cells, we found that because of the axonal gap junctions, the efficiency of this subpopulation in encoding xcexb8 is superior to that of the whole vertical system network and is robust to a wide range of signal to noise ratios. We further demonstrate that this efficient encoding of motion by this subpopulation is necessary for the flys visually guided behavior, such as banked turns in evasive maneuvers. Because gap junctions are formed among the axons of the vertical system cells, they only impact the systems readout, while maintaining the dendritic input intact, suggesting that the computational principles implemented by neural circuitries may be much richer than previously appreciated based on point neuron models. Our study provides new insights as to how specific network connectivity leads to efficient encoding of sensory stimuli.'),
(88783, 2017, 'plos', 'pSSAlib: The partial-propensity stochastic chemical network simulator', 'Ostrenko, Oleksandr|Incardona, Pietro|Ramaswamy, Rajesh|Brusch, Lutz|Sbalzarini, Ivo F', 'Center for Information Services and High Performance Computing, TU Dresden, Dresden, Germany.|Chair of Scientific Computing for Systems Biology, Faculty of Computer Science, TU Dresden, Dresden, Germany.|Max Planck Institute for the Physics of Complex Systems, Dresden, Germany.|Center for Information Services and High Performance Computing, TU Dresden, Dresden, Germany.|Center for Advancing Electronics Dresden, TU Dresden, Dresden, Germany.', 'Germany|Germany|Germany|Germany|Germany', 3, 'Algorithms|Biochemical Phenomena|Computational Biology|Computer Simulation|Kinetics|Models, Biological|Reproducibility of Results|Software|Stochastic Processes', 'Journal Article', '10.1371/journal.pcbi.1005865', '29206229', 'Chemical reaction networks are ubiquitous in biology, and their dynamics is fundamentally stochastic. Here, we present the software library pSSAlib, which provides a complete and concise implementation of the most efficient partial-propensity methods for simulating exact stochastic chemical kinetics. pSSAlib can import models encoded in Systems Biology Markup Language, supports time delays in chemical reactions, and stochastic spatiotemporal reaction-diffusion systems. It also provides tools for statistical analysis of simulation results and supports multiple output formats. It has previously been used for studies of biochemical reaction pathways and to benchmark other stochastic simulation methods. Here, we describe pSSAlib in detail and apply it to a new model of the endocytic pathway in eukaryotic cells, leading to the discovery of a stochastic counterpart of the cut-out switch motif underlying early-to-late endosome conversion. pSSAlib is provided as a stand-alone command-line tool and as a developer API. We also provide a plug-in for the SBMLToolbox. The open-source code and pre-packaged installers are freely available from http://mosaic.mpi-cbg.de.'),
(88784, 2017, 'plos', 'Correction: Signatures of criticality arise from random subsampling in simple population models', 'PLOS Computational Biology Staff', 'Center for Advancing Electronics Dresden, TU Dresden, Dresden, Germany.', 'Germany', 0, '-', 'Journal Article', '10.1371/journal.pcbi.1005886', '29211725', '[This corrects the article DOI: 10.1371/journal.pcbi.1005718.].'),
(88785, 2017, 'plos', 'Automated classification of dolphin echolocation click types from the Gulf of Mexico', 'Frasier, Kaitlin E|Roch, Marie A|Soldevilla, Melissa S|Wiggins, Sean M|Garrison, Lance P|Hildebrand, John A', 'Scripps Institution of Oceanography, La Jolla, California, United States of America.|San Diego State University, San Diego, California, United States of America.|NOAA NMFS Southeast Fisheries Science Center, Protected Resources and Biodiversity Division, Miami, Florida, United States of America.|Scripps Institution of Oceanography, La Jolla, California, United States of America.|NOAA NMFS Southeast Fisheries Science Center, Protected Resources and Biodiversity Division, Miami, Florida, United States of America.|Scripps Institution of Oceanography, La Jolla, California, United States of America.', 'United States|United States|United States|United States|United States|United States', 12, 'Algorithms|Animals|Computational Biology|Dolphins|Echolocation|Gulf of Mexico|Pattern Recognition, Automated|Signal Processing, Computer-Assisted|Sound Spectrography|Vocalization, Animal', 'Journal Article', '10.1371/journal.pcbi.1005823', '29216184', 'Delphinids produce large numbers of short duration, broadband echolocation clicks which may be useful for species classification in passive acoustic monitoring efforts. A challenge in echolocation click classification is to overcome the many sources of variability to recognize underlying patterns across many detections. An automated unsupervised network-based classification method was developed to simulate the approach a human analyst uses when categorizing click types: Clusters of similar clicks were identified by incorporating multiple click characteristics (spectral shape and inter-click interval distributions) to distinguish within-type from between-type variation, and identify distinct, persistent click types. Once click types were established, an algorithm for classifying novel detections using existing clusters was tested. The automated classification method was applied to a dataset of 52 million clicks detected across five monitoring sites over two years in the Gulf of Mexico (GOM). Seven distinct click types were identified, one of which is known to be associated with an acoustically identifiable delphinid (Rissos dolphin) and six of which are not yet identified. All types occurred at multiple monitoring locations, but the relative occurrence of types varied, particularly between continental shelf and slope locations. Automatically-identified click types from autonomous seafloor recorders without verifiable species identification were compared with clicks detected on sea-surface towed hydrophone arrays in the presence of visually identified delphinid species. These comparisons suggest potential species identities for the animals producing some echolocation click types. The network-based classification method presented here is effective for rapid, unsupervised delphinid click classification across large datasets in which the click types may not be known a priori.'),
(88786, 2017, 'plos', 'A cyber-linked undergraduate research experience in computational biomolecular structure prediction and design', 'Alford, Rebecca F|Leaver-Fay, Andrew|Gonzales, Lynda|Dolan, Erin L|Gray, Jeffrey J', 'Department of Chemical and Biomolecular Engineering, Johns Hopkins University, Baltimore, Maryland, United States of America.|Department of Biochemistry and Biophysics, University of North Carolina at Chapel Hill, Chapel Hill, North Carolina, United States of America.|Texas Institute for Discovery Education in Science, University of Texas, Austin, Texas, United States of America.|Texas Institute for Discovery Education in Science, University of Texas, Austin, Texas, United States of America.|Department of Chemical and Biomolecular Engineering, Johns Hopkins University, Baltimore, Maryland, United States of America.', 'United States|United States|United States|United States|United States', 2, 'Adult|Computational Biology|Female|Humans|Internet|Male|Molecular Conformation|Research|Self Efficacy|Students|United States|Universities|Workforce', 'Journal Article', '10.1371/journal.pcbi.1005837', '29216185', 'Computational biology is an interdisciplinary field, and many computational biology research projects involve distributed teams of scientists. To accomplish their work, these teams must overcome both disciplinary and geographic barriers. Introducing new training paradigms is one way to facilitate research progress in computational biology. Here, we describe a new undergraduate program in biomolecular structure prediction and design in which students conduct research at labs located at geographically-distributed institutions while remaining connected through an online community. This 10-week summer program begins with one week of training on computational biology methods development, transitions to eight weeks of research, and culminates in one week at the Rosetta annual conference. To date, two cohorts of students have participated, tackling research topics including vaccine design, enzyme design, protein-based materials, glycoprotein modeling, crowd-sourced science, RNA processing, hydrogen bond networks, and amyloid formation. Students in the program report outcomes comparable to students who participate in similar in-person programs. These outcomes include the development of a sense of community and increases in their scientific self-efficacy, scientific identity, and science values, all predictors of continuing in a science research career. Furthermore, the program attracted students from diverse backgrounds, which demonstrates the potential of this approach to broaden the participation of young scientists from backgrounds traditionally underrepresented in computational biology.'),
(88787, 2017, 'plos', 'Ten simple rules for international short-term research stays', 'Forero, Diego A|Lopez-Leon, Sandra|Patrinos, George P', 'Laboratory of NeuroPsychiatric Genetics, Biomedical Sciences Research Group, School of Medicine, Universidad Antonio Nariño, Bogotá, Colombia.|Global Drug Development, Novartis Pharmaceuticals Corporation, East Hanover, New Jersey, United States of America.|Department of Pharmacy, University of Patras School of Health Sciences, Patras, Greece.', 'Colombia|Jersey|Greece', 2, 'Cooperative Behavior|Humans|Internationality|Research', 'Editorial', '10.1371/journal.pcbi.1005832', '29216186', '-'),
(88788, 2017, 'plos', 'Non-linear auto-regressive models for cross-frequency coupling in neural time series', 'Dupré la Tour, Tom|Tallot, Lucille|Grabot, Laetitia|Doyère, Valérie|van Wassenhove, Virginie|Grenier, Yves|Gramfort, Alexandre', 'LTCI, Télécom ParisTech, Université Paris-Saclay, Paris, France.|Neuroscience Paris Seine, CNRS, INSERM, Sorbonne Universités, Université Pierre et Marie Curie, Paris, France.|Cognitive Neuroimaging Unit, CEA/DRF/Joliot, INSERM, Université Paris-Sud, Université Paris-Saclay, NeuroSpin center, Gif-sur-Yvette, France.|Neuro-PSI, Université Paris-Sud, Université Paris Saclay, CNRS, Orsay, France.|Cognitive Neuroimaging Unit, CEA/DRF/Joliot, INSERM, Université Paris-Sud, Université Paris-Saclay, NeuroSpin center, Gif-sur-Yvette, France.|LTCI, Télécom ParisTech, Université Paris-Saclay, Paris, France.|LTCI, Télécom ParisTech, Université Paris-Saclay, Paris, France.', 'France|France|France|France|France|France|France', 10, 'Action Potentials|Brain|Models, Neurological|Neurons', 'Journal Article', '10.1371/journal.pcbi.1005893', '29227989', 'We address the issue of reliably detecting and quantifying cross-frequency coupling (CFC) in neural time series. Based on non-linear auto-regressive models, the proposed method provides a generative and parametric model of the time-varying spectral content of the signals. As this method models the entire spectrum simultaneously, it avoids the pitfalls related to incorrect filtering or the use of the Hilbert transform on wide-band signals. As the model is probabilistic, it also provides a score of the model goodness of fit via the likelihood, enabling easy and legitimate model selection and parameter comparison, this data-driven feature is unique to our model-based approach. Using three datasets obtained with invasive neurophysiological recordings in humans and rodents, we demonstrate that these models are able to replicate previous results obtained with other metrics, but also reveal new insights such as the influence of the amplitude of the slow oscillation. Using simulations, we demonstrate that our parametric method can reveal neural couplings with shorter signals than non-parametric methods. We also show how the likelihood can be used to find optimal filtering parameters, suggesting new properties on the spectrum of the driving signal, but also to estimate the optimal delay between the coupled signals, enabling a directionality estimation in the coupling.'),
(88789, 2017, 'plos', 'Predicting the pathogenicity of novel variants in mitochondrial tRNA with MitoTIP', 'Sonney, Sanjay|Leipzig, Jeremy|Lott, Marie T|Zhang, Shiping|Procaccio, Vincent|Wallace, Douglas C|Sondheimer, Neal', 'Division of Clinical and Metabolic Genetics, The Hospital for Sick Children, Toronto, Ontario, Canada.|Department of Biomedical and Health Informatics, The Childrens Hospital of Philadelphia, Philadelphia, Pennsylvania, United States of America.|The Center for Mitochondrial and Epigenomic Medicine, The Childrens Hospital of Philadelphia, Philadelphia, Pennsylvania, United States of America.|The Center for Mitochondrial and Epigenomic Medicine, The Childrens Hospital of Philadelphia, Philadelphia, Pennsylvania, United States of America.|UMR CNRS 6015-INSERM U1083, MitoVasc Institute, Angers University Hospital, Angers, France.|The Center for Mitochondrial and Epigenomic Medicine, The Childrens Hospital of Philadelphia, Philadelphia, Pennsylvania, United States of America.|Division of Clinical and Metabolic Genetics, The Hospital for Sick Children, Toronto, Ontario, Canada.', 'Canada|United States|United States|United States|France|United States|Canada', 25, 'Mitochondria|Nucleic Acid Conformation|RNA, Transfer|Virulence', 'Journal Article', '10.1371/journal.pcbi.1005867', '29227991', 'Novel or rare variants in mitochondrial tRNA sequences may be observed after mitochondrial DNA analysis. Determining whether these variants are pathogenic is critical, but confirmation of the effect of a variant on mitochondrial function can be challenging. We have used available databases of benign and pathogenic variants, alignment between diverse tRNAs, structural information and comparative genomics to predict the impact of all possible single-base variants and deletions. The Mitochondrial tRNA Informatics Predictor (MitoTIP) is available through MITOMAP at www.mitomap.org. The source code for MitoTIP is available at www.github.com/sonneysa/MitoTIP.');
INSERT INTO `papers` (`id`, `ano`, `journal`, `titulo`, `autores`, `afiliacao`, `pais`, `citacoes`, `palavra_chave`, `categorias`, `doi`, `pubmed`, `abstract`) VALUES
(88790, 2017, 'plos', 'Thalamocortical control of propofol phase-amplitude coupling', 'Soplata, Austin E|McCarthy, Michelle M|Sherfey, Jason|Lee, Shane|Purdon, Patrick L|Brown, Emery N|Kopell, Nancy', 'Graduate Program for Neuroscience, Boston University, Boston, Massachusetts, United States of America.|Department of Mathematics & Statistics, Boston University, Boston, Massachusetts, United States of America.|Department of Psychological and Brain Sciences, Boston University, Boston, Massachusetts, United States of America.|Department of Neuroscience, Brown University, Providence, Rhode Island, United States of America.|Department of Anesthesia, Critical Care and Pain Medicine, Massachusetts General Hospital, Harvard Medical School, Boston, Massachusetts, United States of America.|Department of Anesthesia, Critical Care and Pain Medicine, Massachusetts General Hospital, Harvard Medical School, Boston, Massachusetts, United States of America.|Department of Mathematics & Statistics, Boston University, Boston, Massachusetts, United States of America.', 'United States|United States|United States|United States|United States|United States|United States', 8, 'Aged|Alpha Rhythm|Computer Simulation|Electroencephalography|Humans|Propofol|Thalamus|Unconsciousness', 'Journal Article', '10.1371/journal.pcbi.1005879', '29227992', 'The anesthetic propofol elicits many different spectral properties on the EEG, including alpha oscillations (8-12 Hz), Slow Wave Oscillations (SWO, 0.1-1.5 Hz), and dose-dependent phase-amplitude coupling (PAC) between alpha and SWO. Propofol is known to increase GABAA inhibition and decrease H-current strength, but how it generates these rhythms and their interactions is still unknown. To investigate both generation of the alpha rhythm and its PAC to SWO, we simulate a Hodgkin-Huxley network model of a hyperpolarized thalamus and corticothalamic inputs. We find, for the first time, that the model thalamic network is capable of independently generating the sustained alpha seen in propofol, which may then be relayed to cortex and expressed on the EEG. This dose-dependent sustained alpha critically relies on propofol GABAA potentiation to alter the intrinsic spindling mechanisms of the thalamus. Furthermore, the H-current conductance and background excitation of these thalamic cells must be within specific ranges to exhibit any intrinsic oscillations, including sustained alpha. We also find that, under corticothalamic SWO UP and DOWN states, thalamocortical output can exhibit maximum alpha power at either the peak or trough of this SWO, this implies the thalamus may be the source of propofol-induced PAC. Hyperpolarization level is the main determinant of whether the thalamus exhibits trough-max PAC, which is associated with lower propofol dose, or peak-max PAC, associated with higher dose. These findings suggest: the thalamus generates a novel rhythm under GABAA potentiation such as under propofol, its hyperpolarization may determine whether a patient experiences trough-max or peak-max PAC, and the thalamus is a critical component of propofol-induced cortical spectral phenomena. Changes to the thalamus may be a critical part of how propofol accomplishes its effects, including unconsciousness.'),
(88791, 2017, 'plos', 'Correction: Identifying influential neighbors in animal flocking', 'PLOS Computational Biology Staff', 'Department of Mathematics & Statistics, Boston University, Boston, Massachusetts, United States of America.', 'United States', 1, '-', 'Journal Article', '10.1371/journal.pcbi.1005902', '29232367', '[This corrects the article DOI: 10.1371/journal.pcbi.1005822.].'),
(88792, 2017, 'plos', 'Stabilizing patterns in time: Neural network approach', 'Ben-Shushan, Nadav|Tsodyks, Misha', 'Department of Physics, The Weizmann Institute of science, Rehovot, Israel.|Department of Neurobiology, The Weizmann Institute of science, Rehovot, Israel.', 'Israel|Israel', 1, 'Algorithms|Artificial Intelligence|Computer Simulation|Machine Learning|Neural Networks (Computer)', 'Journal Article', '10.1371/journal.pcbi.1005861', '29232710', 'Recurrent and feedback networks are capable of holding dynamic memories. Nonetheless, training a network for that task is challenging. In order to do so, one should face non-linear propagation of errors in the system. Small deviations from the desired dynamics due to error or inherent noise might have a dramatic effect in the future. A method to cope with these difficulties is thus needed. In this work we focus on recurrent networks with linear activation functions and binary output unit. We characterize its ability to reproduce a temporal sequence of actions over its output unit. We suggest casting the temporal learning problem to a perceptron problem. In the discrete case a finite margin appears, providing the network, to some extent, robustness to noise, for which it performs perfectly (i.e. producing a desired sequence for an arbitrary number of cycles flawlessly). In the continuous case the margin approaches zero when the output unit changes its state, hence the network is only able to reproduce the sequence with slight jitters. Numerical simulation suggest that in the discrete time case, the longest sequence that can be learned scales, at best, as square root of the network size. A dramatic effect occurs when learning several short sequences in parallel, that is, their total length substantially exceeds the length of the longest single sequence the network can learn. This model easily generalizes to an arbitrary number of output units, which boost its performance. This effect is demonstrated by considering two practical examples for sequence learning. This work suggests a way to overcome stability problems for training recurrent networks and further quantifies the performance of a network under the specific learning scheme.'),
(88793, 2017, 'plos', 'Correction: Sequential inference as a mode of cognition and its correlates in fronto-parietal and hippocampal brain regions', 'PLOS Computational Biology Staff', 'Department of Neurobiology, The Weizmann Institute of science, Rehovot, Israel.', 'Israel', 0, '-', 'Journal Article', '10.1371/journal.pcbi.1005908', '29236695', '[This corrects the article DOI: 10.1371/journal.pcbi.1005418.].'),
(88794, 2017, 'plos', 'Novel linear motif filtering protocol reveals the role of the LC8 dynein light chain in the Hippo pathway', 'Erdxc5x91s, Gxc3xa1bor|Szaniszlxc3xb3, Tamxc3xa1s|Pajkos, Mxc3xa1tyxc3xa1s|Hajdu-Soltxc3xa9sz, Borbxc3xa1la|Kiss, Bence|Pxc3xa1l, Gxc3xa1bor|Nyitray, Lxc3xa1szlxc3xb3|Dosztxc3xa1nyi, Zsuzsanna', 'MTA-ELTE Lendxc3xbclet Bioinformatics Research Group, Department of Biochemistry, Exc3xb6tvxc3xb6s Lorxc3xa1nd University, Budapest, Hungary.|MTA-ELTE Lendxc3xbclet Bioinformatics Research Group, Department of Biochemistry, Exc3xb6tvxc3xb6s Lorxc3xa1nd University, Budapest, Hungary.|MTA-ELTE Lendxc3xbclet Bioinformatics Research Group, Department of Biochemistry, Exc3xb6tvxc3xb6s Lorxc3xa1nd University, Budapest, Hungary.|MTA-ELTE Lendxc3xbclet Bioinformatics Research Group, Department of Biochemistry, Exc3xb6tvxc3xb6s Lorxc3xa1nd University, Budapest, Hungary.|Department of Biochemistry, Exc3xb6tvxc3xb6s Lorxc3xa1nd University, Budapest, Hungary.|Department of Biochemistry, Exc3xb6tvxc3xb6s Lorxc3xa1nd University, Budapest, Hungary.|Department of Biochemistry, Exc3xb6tvxc3xb6s Lorxc3xa1nd University, Budapest, Hungary.|MTA-ELTE Lendxc3xbclet Bioinformatics Research Group, Department of Biochemistry, Exc3xb6tvxc3xb6s Lorxc3xa1nd University, Budapest, Hungary.', 'Hungary|Hungary|Hungary|Hungary|Hungary|Hungary|Hungary|Hungary', 11, 'Computational Biology|Conserved Sequence|Cytoplasmic Dyneins|Databases, Protein|Evolution, Molecular|Humans|Phylogeny|Protein Binding|Protein Interaction Domains and Motifs|Protein Interaction Maps|Protein-Serine-Threonine Kinases|Signal Transduction', 'Journal Article', '10.1371/journal.pcbi.1005885', '29240760', 'Protein-protein interactions (PPIs) formed between short linear motifs and globular domains play important roles in many regulatory and signaling processes but are highly underrepresented in current protein-protein interaction databases. These types of interactions are usually characterized by a specific binding motif that captures the key amino acids shared among the interaction partners. However, the computational proteome-level identification of interaction partners based on the known motif is hindered by the huge number of randomly occurring matches from which biologically relevant motif hits need to be extracted. In this work, we established a novel bioinformatic filtering protocol to efficiently explore interaction network of a hub protein. We introduced a novel measure that enabled the optimization of the elements and parameter settings of the pipeline which was built from multiple sequence-based prediction methods. In addition, data collected from PPI databases and evolutionary analyses were also incorporated to further increase the biological relevance of the identified motif hits. The approach was applied to the dynein light chain LC8, a ubiquitous eukaryotic hub protein that has been suggested to be involved in motor-related functions as well as promoting the dimerization of various proteins by recognizing linear motifs in its partners. From the list of putative binding motifs collected by our protocol, several novel peptides were experimentally verified to bind LC8. Altogether 71 potential new motif instances were identified. The expanded list of LC8 binding partners revealed the evolutionary plasticity of binding partners despite the highly conserved binding interface. In addition, it also highlighted a novel, conserved function of LC8 in the upstream regulation of the Hippo signaling pathway. Beyond the LC8 system, our work also provides general guidelines that can be applied to explore the interaction network of other linear motif binding proteins or protein domains.'),
(88795, 2017, 'plos', 'Costs of task allocation with local feedback: Effects of colony size and extra workers in social insects and other multi-agent systems', 'Radeva, Tsvetomira|Dornhaus, Anna|Lynch, Nancy|Nagpal, Radhika|Su, Hsin-Hao', 'Electrical Engineering and Computer Science Department, Massachusetts Institute of Technology, Cambridge, MA, USA.|Department of Ecology and Evolutionary Biology, The University of Arizona, Tucson, AZ, USA.|Electrical Engineering and Computer Science Department, Massachusetts Institute of Technology, Cambridge, MA, USA.|School of Engineering and Applied Sciences, Harvard University, Cambridge, MA, USA.|Electrical Engineering and Computer Science Department, Massachusetts Institute of Technology, Cambridge, MA, USA.', 'United States|United States|United States|United States|United States', 2, 'Algorithms|Animals|Behavior, Animal|Body Temperature Regulation|Computational Biology|Computer Simulation|Feedback, Physiological|Insecta|Models, Biological|Social Behavior|Systems Biology|Task Performance and Analysis', 'Journal Article', '10.1371/journal.pcbi.1005904', '29240763', 'Adaptive collective systems are common in biology and beyond. Typically, such systems require a task allocation algorithm: a mechanism or rule-set by which individuals select particular roles. Here we study the performance of such task allocation mechanisms measured in terms of the time for individuals to allocate to tasks. We ask: (1) Is task allocation fundamentally difficult, and thus costly? (2) Does the performance of task allocation mechanisms depend on the number of individuals? And (3) what other parameters may affect their efficiency? We use techniques from distributed computing theory to develop a model of a social insect colony, where workers have to be allocated to a set of tasks, however, our model is generalizable to other systems. We show, first, that the ability of workers to quickly assess demand for work in tasks they are not currently engaged in crucially affects whether task allocation is quickly achieved or not. This indicates that in social insect tasks such as thermoregulation, where temperature may provide a global and near instantaneous stimulus to measure the need for cooling, for example, it should be easy to match the number of workers to the need for work. In other tasks, such as nest repair, it may be impossible for workers not directly at the work site to know that this task needs more workers. We argue that this affects whether task allocation mechanisms are under strong selection. Second, we show that colony size does not affect task allocation performance under our assumptions. This implies that when effects of colony size are found, they are not inherent in the process of task allocation itself, but due to processes not modeled here, such as higher variation in task demand for smaller colonies, benefits of specialized workers, or constant overhead costs. Third, we show that the ratio of the number of available workers to the workload crucially affects performance. Thus, workers in excess of those needed to complete all tasks improve task allocation performance. This provides a potential explanation for the phenomenon that social insect colonies commonly contain inactive workers: these may be a surplus set of workers that improves colony function by speeding up optimal allocation of workers to tasks. Overall our study shows how limitations at the individual level can affect group level outcomes, and suggests new hypotheses that can be explored empirically.'),
(88796, 2017, 'plos', 'Specific excitatory connectivity for feature integration in mouse primary visual cortex', 'Muir, Dylan R|Molina-Luna, Patricia|Roth, Morgane M|Helmchen, Fritjof|Kampa, Björn M', 'Biozentrum, University of Basel, Basel, Switzerland.|Laboratory of Neural Circuit Dynamics, Brain Research Institute, University of Zurich, Zurich, Switzerland.|Biozentrum, University of Basel, Basel, Switzerland.|Laboratory of Neural Circuit Dynamics, Brain Research Institute, University of Zurich, Zurich, Switzerland.|Laboratory of Neural Circuit Dynamics, Brain Research Institute, University of Zurich, Zurich, Switzerland.', 'Switzerland|Switzerland|Switzerland|Switzerland|Switzerland', 2, 'Animals|Calcium Signaling|Computational Biology|Female|Male|Mice|Mice, Inbred C57BL|Models, Neurological|Nerve Net|Neurons|Orientation|Photic Stimulation|Synapses|Visual Cortex|Visual Pathways|Visual Perception', 'Journal Article', '10.1371/journal.pcbi.1005888', '29240769', 'Local excitatory connections in mouse primary visual cortex (V1) are stronger and more prevalent between neurons that share similar functional response features. However, the details of how functional rules for local connectivity shape neuronal responses in V1 remain unknown. We hypothesised that complex responses to visual stimuli may arise as a consequence of rules for selective excitatory connectivity within the local network in the superficial layers of mouse V1. In mouse V1 many neurons respond to overlapping grating stimuli (plaid stimuli) with highly selective and facilitatory responses, which are not simply predicted by responses to single gratings presented alone. This complexity is surprising, since excitatory neurons in V1 are considered to be mainly tuned to single preferred orientations. Here we examined the consequences for visual processing of two alternative connectivity schemes: in the first case, local connections are aligned with visual properties inherited from feedforward input (a like-to-like scheme specifically connecting neurons that share similar preferred orientations), in the second case, local connections group neurons into excitatory subnetworks that combine and amplify multiple feedforward visual properties (a feature binding scheme). By comparing predictions from large scale computational models with in vivo recordings of visual representations in mouse V1, we found that responses to plaid stimuli were best explained by assuming feature binding connectivity. Unlike under the like-to-like scheme, selective amplification within feature-binding excitatory subnetworks replicated experimentally observed facilitatory responses to plaid stimuli, explained selective plaid responses not predicted by grating selectivity, and was consistent with broad anatomical selectivity observed in mouse V1. Our results show that visual feature binding can occur through local recurrent mechanisms without requiring feedforward convergence, and that such a mechanism is consistent with visual responses and cortical anatomy in mouse V1.'),
(88797, 2017, 'plos', 'A master equation approach to actin polymerization applied to endocytosis in yeast', 'Wang, Xinxin|Carlsson, Anders E', 'Department of Bioinformatics, UT Southwestern Medical Center, Dallas, Texas, United States of America.|Department of Physics and NSF Center for Engineering MechanoBiology, Washington University, St. Louis, Missouri, United States of America.', 'United States|United States', 0, 'Actins|Biomechanical Phenomena|Cell Membrane|Computational Biology|Computer Simulation|Endocytosis|Models, Biological|Molecular Motor Proteins|Mutation|Polymerization|Saccharomyces cerevisiae|Saccharomyces cerevisiae Proteins', 'Journal Article', '10.1371/journal.pcbi.1005901', '29240771', 'We present a Master Equation approach to calculating polymerization dynamics and force generation by branched actin networks at membranes. The method treats the time evolution of the F-actin distribution in three dimensions, with branching included as a directional spreading term. It is validated by comparison with stochastic simulations of force generation by actin polymerization at obstacles coated with actin nucleation promoting factors (NPFs). The method is then used to treat the dynamics of actin polymerization and force generation during endocytosis in yeast, using a model in which NPFs form a ring around the endocytic site, centered by a spot of molecules attaching the actin network strongly to the membrane. We find that a spontaneous actin filament nucleation mechanism is required for adequate forces to drive the process, that partial inhibition of branching and polymerization lead to different characteristic responses, and that a limited range of polymerization-rate values provide effective invagination and obtain correct predictions for the effects of mutations in the active regions of the NPFs.'),
(88798, 2017, 'plos', 'Feature reliability determines specificity and transfer of perceptual learning in orientation search', 'Yashar, Amit|Denison, Rachel N', 'Department of Psychology and Center for Neural Science, New York University, New York, New York, United States of America.|Department of Psychology and Center for Neural Science, New York University, New York, New York, United States of America.', 'United States|United States', 0, 'Adult|Brain|Computational Biology|Female|Humans|Learning|Male|Models, Neurological|Models, Psychological|Neuronal Plasticity|Orientation|Photic Stimulation|Reproducibility of Results|Spatial Learning|Task Performance and Analysis|Transfer (Psychology)|Visual Perception|Young Adult', 'Journal Article', '10.1371/journal.pcbi.1005882', '29240813', 'Training can modify the visual system to produce a substantial improvement on perceptual tasks and therefore has applications for treating visual deficits. Visual perceptual learning (VPL) is often specific to the trained feature, which gives insight into processes underlying brain plasticity, but limits VPLs effectiveness in rehabilitation. Under what circumstances VPL transfers to untrained stimuli is poorly understood. Here we report a qualitatively new phenomenon: intrinsic variation in the representation of features determines the transfer of VPL. Orientations around cardinal are represented more reliably than orientations around oblique in V1, which has been linked to behavioral consequences such as visual search asymmetries. We studied VPL for visual search of near-cardinal or oblique targets among distractors of the other orientation while controlling for other display and task attributes, including task precision, task difficulty, and stimulus exposure. Learning was the same in all training conditions, however, transfer depended on the orientation of the target, with full transfer of learning from near-cardinal to oblique targets but not the reverse. To evaluate the idea that representational reliability was the key difference between the orientations in determining VPL transfer, we created a model that combined orientation-dependent reliability, improvement of reliability with learning, and an optimal search strategy. Modeling suggested that not only search asymmetries but also the asymmetric transfer of VPL depended on preexisting differences between the reliability of near-cardinal and oblique representations. Transfer asymmetries in model behavior also depended on having different learning rates for targets and distractors, such that greater learning for low-reliability distractors facilitated transfer. These findings suggest that training on sensory features with intrinsically low reliability may maximize the generalizability of learning in complex visual environments.'),
(88799, 2017, 'plos', 'Ten simple rules for writing a career development award proposal', 'Botham, Crystal M|Arribere, Joshua A|Brubaker, Sky W|Beier, Kevin T', 'Stanford Biosciences Grant Writing Academy, Stanford University, Stanford, California, United States of America.|Department of Molecular, Cell, and Developmental Biology, University of California, Santa Cruz, Santa Cruz, California, United States of America.|Department of Microbiology and Immunology, Stanford University, Stanford, California, United States of America.|Department of Biology, Stanford University, Stanford, California, United States of America.', 'United States|United States|United States|United States', 0, 'Competitive Bidding|Humans|Research Design|Time Factors|Writing', 'Editorial', '10.1371/journal.pcbi.1005863', '29240828', '-'),
(88800, 2017, 'plos', 'Optimal occlusion uniformly partitions red blood cells fluxes within a microvascular network', 'Chang, Shyr-Shea|Tu, Shenyinying|Baek, Kyung In|Pietersen, Andrew|Liu, Yu-Hsiu|Savage, Van M|Hwang, Sheng-Ping L|Hsiai, Tzung K|Roper, Marcus', 'Department of Mathematics, University of California Los Angeles, Los Angeles, California, United States of America.|Department of Mathematics, University of California Los Angeles, Los Angeles, California, United States of America.|Department of Bioengineering, School of Engineering & Applied Science, University of California Los Angeles, Los Angeles, California, United States of America.|Department of Bioengineering, School of Engineering & Applied Science, University of California Los Angeles, Los Angeles, California, United States of America.|Department of Life Science, National Taiwan University, Taipei, Taiwan, Republic of China.|Department of Biomathematics, University of California Los Angeles, Los Angeles, California, United States of America.|Institute of Cellular and Organismic Biology, Academia Sinica, Nankang, Taipei, Taiwan, Republic of China.|Department of Bioengineering, School of Engineering & Applied Science, University of California Los Angeles, Los Angeles, California, United States of America.|Department of Mathematics, University of California Los Angeles, Los Angeles, California, United States of America.', 'United States|United States|United States|United States|China|United States|China|United States|Unit', 6, 'Animals|Animals, Genetically Modified|Blood Flow Velocity|Computational Biology|Erythrocytes|Feedback, Physiological|Hemorheology|Microcirculation|Microvessels|Models, Cardiovascular|Zebrafish', 'Journal Article', '10.1371/journal.pcbi.1005892', '29244812', 'In animals, gas exchange between blood and tissues occurs in narrow vessels, whose diameter is comparable to that of a red blood cell. Red blood cells must deform to squeeze through these narrow vessels, transiently blocking or occluding the vessels they pass through. Although the dynamics of vessel occlusion have been studied extensively, it remains an open question why microvessels need to be so narrow. We study occlusive dynamics within a model microvascular network: the embryonic zebrafish trunk. We show that pressure feedbacks created when red blood cells enter the finest vessels of the trunk act together to uniformly partition red blood cells through the microvasculature. Using mathematical models as well as direct observation, we show that these occlusive feedbacks are tuned throughout the trunk network to prevent the vessels closest to the heart from short-circuiting the network. Thus occlusion is linked with another open question of microvascular function: how are red blood cells delivered at the same rate to each micro-vessel? Our analysis shows that tuning of occlusive feedbacks increase the total dissipation within the network by a factor of 11, showing that uniformity of flows rather than minimization of transport costs may be prioritized by the microvascular network.'),
(88801, 2017, 'plos', 'MAGPIE: Simplifying access and execution of computational models in the life sciences', 'Baldow, Christoph|Salentin, Sebastian|Schroeder, Michael|Roeder, Ingo|Glauche, Ingmar', 'Institute for Medical Informatics and Biometry, Medizinische Fakultät Carl Gustav Carus, Technische Universität Dresden, Dresden, Germany.|Biotechnology Center (BIOTEC), Technische Universität Dresden, Dresden, Germany.|Biotechnology Center (BIOTEC), Technische Universität Dresden, Dresden, Germany.|Institute for Medical Informatics and Biometry, Medizinische Fakultät Carl Gustav Carus, Technische Universität Dresden, Dresden, Germany.|Institute for Medical Informatics and Biometry, Medizinische Fakultät Carl Gustav Carus, Technische Universität Dresden, Dresden, Germany.', 'Germany|Germany|Germany|Germany|Germany', 2, 'Biological Science Disciplines|Computational Biology|Computer Simulation|Humans|Models, Biological|Models, Statistical|Programming Languages|Reproducibility of Results|Software|Systems Biology', 'Journal Article', '10.1371/journal.pcbi.1005898', '29244826', 'Over the past decades, quantitative methods linking theory and observation became increasingly important in many areas of life science. Subsequently, a large number of mathematical and computational models has been developed. The BioModels database alone lists more than 140,000 Systems Biology Markup Language (SBML) models. However, while the exchange within specific model classes has been supported by standardisation and database efforts, the generic application and especially the re-use of models is still limited by practical issues such as easy and straight forward model execution. MAGPIE, a Modeling and Analysis Generic Platform with Integrated Evaluation, closes this gap by providing a software platform for both, publishing and executing computational models without restrictions on the programming language, thereby combining a maximum on flexibility for programmers with easy handling for non-technical users. MAGPIE goes beyond classical SBML platforms by including all models, independent of the underlying programming language, ranging from simple script models to complex data integration and computations. We demonstrate the versatility of MAGPIE using four prototypic example cases. We also outline the potential of MAGPIE to improve transparency and reproducibility of computational models in life sciences. A demo server is available at magpie.imb.medizin.tu-dresden.de.'),
(88802, 2017, 'plos', 'Filament turnover tunes both force generation and dissipation to control long-range flows in a model actomyosin cortex', 'McFadden, William M|McCall, Patrick M|Gardel, Margaret L|Munro, Edwin M', 'Biophysical Sciences Program, University of Chicago, Chicago, Illinois, United States of America.|Department of Physics, University of Chicago, Chicago, Illinois, United States of America.|Department of Physics, University of Chicago, Chicago, Illinois, United States of America.|Institute for Biophysical Dynamics, University of Chicago, Chicago, Illinois, United States of America.', 'United States|United States|United States|United States', 7, 'Actin Cytoskeleton|Actomyosin|Animals|Biomechanical Phenomena|Computational Biology|Computer Simulation|Cytoskeleton|Models, Biological|Molecular Motor Proteins|Morphogenesis|Rheology|Stress, Physiological|Viscosity', 'Journal Article', '10.1371/journal.pcbi.1005811', '29253848', 'Actomyosin-based cortical flow is a fundamental engine for cellular morphogenesis. Cortical flows are generated by cross-linked networks of actin filaments and myosin motors, in which active stress produced by motor activity is opposed by passive resistance to network deformation. Continuous flow requires local remodeling through crosslink unbinding and and/or filament disassembly. But how local remodeling tunes stress production and dissipation, and how this in turn shapes long range flow, remains poorly understood. Here, we study a computational model for a cross-linked network with active motors based on minimal requirements for production and dissipation of contractile stress: Asymmetric filament compliance, spatial heterogeneity of motor activity, reversible cross-links and filament turnover. We characterize how the production and dissipation of network stress depend, individually, on cross-link dynamics and filament turnover, and how these dependencies combine to determine overall rates of cortical flow. Our analysis predicts that filament turnover is required to maintain active stress against external resistance and steady state flow in response to external stress. Steady state stress increases with filament lifetime up to a characteristic time xcfx84m, then decreases with lifetime above xcfx84m. Effective viscosity increases with filament lifetime up to a characteristic time xcfx84c, and then becomes independent of filament lifetime and sharply dependent on crosslink dynamics. These individual dependencies of active stress and effective viscosity define multiple regimes of steady state flow. In particular our model predicts that when filament lifetimes are shorter than both xcfx84c and xcfx84m, the dependencies of effective viscosity and steady state stress on filament turnover cancel one another, such that flow speed is insensitive to filament turnover, and shows a simple dependence on motor activity and crosslink dynamics. These results provide a framework for understanding how animal cells tune cortical flow through local control of network remodeling.'),
(88803, 2017, 'plos', 'Invariant recognition drives neural representations of action sequences', 'Tacchetti, Andrea|Isik, Leyla|Poggio, Tomaso', 'Center for Brains Minds and Machines, Massachusetts Institute of Technology, Cambridge, MA, United States.|Center for Brains Minds and Machines, Massachusetts Institute of Technology, Cambridge, MA, United States.|Center for Brains Minds and Machines, Massachusetts Institute of Technology, Cambridge, MA, United States.', 'United States|United States|United States', 5, 'Computational Biology|Cues|Discrimination (Psychology)|Humans|Magnetoencephalography|Models, Neurological|Neural Networks (Computer)|Photic Stimulation|Recognition (Psychology)|Visual Cortex|Visual Perception', 'Journal Article', '10.1371/journal.pcbi.1005859', '29253864', 'Recognizing the actions of others from visual stimuli is a crucial aspect of human perception that allows individuals to respond to social cues. Humans are able to discriminate between similar actions despite transformations, like changes in viewpoint or actor, that substantially alter the visual appearance of a scene. This ability to generalize across complex transformations is a hallmark of human visual intelligence. Advances in understanding action recognition at the neural level have not always translated into precise accounts of the computational principles underlying what representations of action sequences are constructed by human visual cortex. Here we test the hypothesis that invariant action discrimination might fill this gap. Recently, the study of artificial systems for static object perception has produced models, Convolutional Neural Networks (CNNs), that achieve human level performance in complex discriminative tasks. Within this class, architectures that better support invariant object recognition also produce image representations that better match those implied by human and primate neural data. However, whether these models produce representations of action sequences that support recognition across complex transformations and closely follow neural representations of actions remains unknown. Here we show that spatiotemporal CNNs accurately categorize video stimuli into action classes, and that deliberate model modifications that improve performance on an invariant action recognition task lead to data representations that better match human neural recordings. Our results support our hypothesis that performance on invariant discrimination dictates the neural representations of actions computed in the brain. These results broaden the scope of the invariant recognition framework for understanding visual intelligence from perception of inanimate objects and faces in static images to the study of human perception of action sequences.'),
(88804, 2017, 'plos', 'An error-tuned model for sensorimotor learning', 'Ingram, James N|Sadeghi, Mohsen|Flanagan, J Randall|Wolpert, Daniel M', 'Department of Engineering, University of Cambridge, Trumpington Street, Cambridge, United Kingdom.|Department of Engineering, University of Cambridge, Trumpington Street, Cambridge, United Kingdom.|Department of Psychology and Centre for Neuroscience Studies, Queens University, Kingston, ON, Canada.|Department of Engineering, University of Cambridge, Trumpington Street, Cambridge, United Kingdom.', 'United Kingdom|United Kingdom|Canada|United Kingdom', 4, 'Adaptation, Physiological|Biomechanical Phenomena|Computational Biology|Humans|Learning|Memory|Models, Neurological|Models, Psychological|Motor Skills|Psychomotor Performance|Sensorimotor Cortex|Task Performance and Analysis|Visual Perception', 'Journal Article', '10.1371/journal.pcbi.1005883', '29253869', 'Current models of sensorimotor control posit that motor commands are generated by combining multiple modules which may consist of internal models, motor primitives or motor synergies. The mechanisms which select modules based on task requirements and modify their output during learning are therefore critical to our understanding of sensorimotor control. Here we develop a novel modular architecture for multi-dimensional tasks in which a set of fixed primitives are each able to compensate for errors in a single direction in the task space. The contribution of the primitives to the motor output is determined by both top-down contextual information and bottom-up error information. We implement this model for a task in which subjects learn to manipulate a dynamic object whose orientation can vary. In the model, visual information regarding the context (the orientation of the object) allows the appropriate primitives to be engaged. This top-down module selection is implemented by a Gaussian function tuned for the visual orientation of the object. Second, each modules contribution adapts across trials in proportion to its ability to decrease the current kinematic error. Specifically, adaptation is implemented by cosine tuning of primitives to the current direction of the error, which we show to be theoretically optimal for reducing error. This error-tuned model makes two novel predictions. First, interference should occur between alternating dynamics only when the kinematic errors associated with each oppose one another. In contrast, dynamics which lead to orthogonal errors should not interfere. Second, kinematic errors alone should be sufficient to engage the appropriate modules, even in the absence of contextual information normally provided by vision. We confirm both these predictions experimentally and show that the model can also account for data from previous experiments. Our results suggest that two interacting processes account for module selection during sensorimotor control and learning.'),
(88805, 2017, 'plos', 'Optimal number of spacers in CRISPR arrays', 'Martynov, Alexander|Severinov, Konstantin|Ispolatov, Iaroslav', 'Center for Data-Intensive Biomedicine and Biotechnology, Skolkovo Institute of Science and Technology, Moscow, Russia.|Center for Data-Intensive Biomedicine and Biotechnology, Skolkovo Institute of Science and Technology, Moscow, Russia.|Department of Physics, University of Santiago de Chile, Santiago, Chile.', '-|-|Chile', 8, 'Adaptive Immunity|Archaea|Bacteria|CRISPR-Cas Systems|Clustered Regularly Interspaced Short Palindromic Repeats|Computational Biology|Computer Simulation|DNA, Intergenic|DNA, Viral|Models, Genetic|Models, Immunological|Mutation|Prokaryotic Cells', 'Journal Article', '10.1371/journal.pcbi.1005891', '29253874', 'Prokaryotic organisms survive under constant pressure of viruses. CRISPR-Cas system provides its prokaryotic host with an adaptive immune defense against viruses that have been previously encountered. It consists of two components: Cas-proteins that cleave the foreign DNA and CRISPR array that suits as a virus recognition key. CRISPR array consists of a series of spacers, short pieces of DNA that originate from and match the corresponding parts of viral DNA called protospacers. Here we estimate the number of spacers in a CRISPR array of a prokaryotic cell which maximizes its protection against a viral attack. The optimality follows from a competition between two trends: too few distinct spacers make host vulnerable to an attack by a virus with mutated corresponding protospacers, while an excessive variety of spacers dilutes the number of the CRISPR complexes armed with the most recent and thus most useful spacers. We first evaluate the optimal number of spacers in a simple scenario of an infection by a single viral species and later consider a more general case of multiple viral species. We find that depending on such parameters as the concentration of CRISPR-Cas interference complexes and its preference to arm with more recently acquired spacers, the rate of viral mutation, and the number of viral species, the predicted optimal number of spacers lies within a range that agrees with experimentally-observed values.'),
(88806, 2017, 'plos', 'Complete hazard ranking to analyze right-censored data: An ALS survival study', 'Huang, Zhengnan|Zhang, Hongjiu|Boss, Jonathan|Goutman, Stephen A|Mukherjee, Bhramar|Dinov, Ivo D|Guan, Yuanfang|Pooled Resource Open-Access ALS Clinical Trials Consortium', 'Department of Computational Medicine and Bioinformatics, 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 Biostatistics, University of Michigan, Ann Arbor, MI, United States of America.|Department of Neurology, University of Michigan, Ann Arbor, MI, United States of America.|Department of Biostatistics, University of Michigan, Ann Arbor, MI, United States of America.|Department of Health Behavior and Biological Sciences, 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 Computational Medicine and Bioinformatics, University of Michigan, Ann Arbor, MI, United States of America.', 'United States|United States|United States|United States|United States|United States|United States|Un', 9, 'Algorithms|Amyotrophic Lateral Sclerosis|Computational Biology|Databases, Factual|Female|Humans|Kaplan-Meier Estimate|Machine Learning|Male|Normal Distribution|Proportional Hazards Models|Regression Analysis|Statistics, Nonparametric|Survival Analysis', 'Journal Article', '10.1371/journal.pcbi.1005887', '29253881', 'Survival analysis represents an important outcome measure in clinical research and clinical trials, further, survival ranking may offer additional advantages in clinical trials. In this study, we developed GuanRank, a non-parametric ranking-based technique to transform patients survival data into a linear space of hazard ranks. The transformation enables the utilization of machine learning base-learners including Gaussian process regression, Lasso, and random forest on survival data. The method was submitted to the DREAM Amyotrophic Lateral Sclerosis (ALS) Stratification Challenge. Ranked first place, the model gave more accurate ranking predictions on the PRO-ACT ALS dataset in comparison to Cox proportional hazard model. By utilizing right-censored data in its training process, the method demonstrated its state-of-the-art predictive power in ALS survival ranking. Its feature selection identified multiple important factors, some of which conflicts with previous studies.'),
(88807, 2017, 'plos', 'LRSSLMDA: Laplacian Regularized Sparse Subspace Learning for MiRNA-Disease Association prediction', 'Chen, Xing|Huang, Li', 'School of Information and Control Engineering, China University of Mining and Technology, Xuzhou, China.|Business Analytics Centre, National University of Singapore, Singapore.', 'China|Singapore', 133, 'Biomarkers, Tumor|Computational Biology|Computer Simulation|Databases, Nucleic Acid|Female|Genetic Association Studies|Genetic Markers|Genetic Predisposition to Disease|Humans|Machine Learning|Male|MicroRNAs|Models, Genetic|Models, Statistical|Neoplasms', 'Evaluation Studies', '10.1371/journal.pcbi.1005912', '29253885', 'Predicting novel microRNA (miRNA)-disease associations is clinically significant due to miRNAs potential roles of diagnostic biomarkers and therapeutic targets for various human diseases. Previous studies have demonstrated the viability of utilizing different types of biological data to computationally infer new disease-related miRNAs. Yet researchers face the challenge of how to effectively integrate diverse datasets and make reliable predictions. In this study, we presented a computational model named Laplacian Regularized Sparse Subspace Learning for MiRNA-Disease Association prediction (LRSSLMDA), which projected miRNAs/diseases statistical feature profile and graph theoretical feature profile to a common subspace. It used Laplacian regularization to preserve the local structures of the training data and a L1-norm constraint to select important miRNA/disease features for prediction. The strength of dimensionality reduction enabled the model to be easily extended to much higher dimensional datasets than those exploited in this study. Experimental results showed that LRSSLMDA outperformed ten previous models: the AUC of 0.9178 in global leave-one-out cross validation (LOOCV) and the AUC of 0.8418 in local LOOCV indicated the models superior prediction accuracy, and the average AUC of 0.9181+/-0.0004 in 5-fold cross validation justified its accuracy and stability. In addition, three types of case studies further demonstrated its predictive power. Potential miRNAs related to Colon Neoplasms, Lymphoma, Kidney Neoplasms, Esophageal Neoplasms and Breast Neoplasms were predicted by LRSSLMDA. Respectively, 98%, 88%, 96%, 98% and 98% out of the top 50 predictions were validated by experimental evidences. Therefore, we conclude that LRSSLMDA would be a valuable computational tool for miRNA-disease association prediction.'),
(88808, 2017, 'plos', 'Correction: Reading wild minds: A computational assay of Theory of Mind sophistication across seven primate species', 'PLOS Computational Biology Staff', 'Business Analytics Centre, National University of Singapore, Singapore.', 'Singapore', 0, '-', 'Journal Article', '10.1371/journal.pcbi.1005917', '29261654', '[This corrects the article DOI: 10.1371/journal.pcbi.1005833.].'),
(88809, 2017, 'plos', 'Molecular recognition and packing frustration in a helical protein', 'Huynh, Loan|Neale, Chris|Pomxc3xa8s, Rxc3xa9gis|Chan, Hue Sun', 'Department of Biochemistry, University of Toronto, Toronto, Ontario, Canada.|Department of Physics, Applied Physics, and Astronomy, Rensselaer Polytechnic Institute, Troy, New York, United States of America.|Department of Biochemistry, University of Toronto, Toronto, Ontario, Canada.|Department of Biochemistry, University of Toronto, Toronto, Ontario, Canada.', 'Canada|United States|Canada|Canada', 4, 'Colicins|Computational Biology|Computer Simulation|Models, Molecular|Molecular Dynamics Simulation|Protein Conformation, alpha-Helical|Protein Folding|Thermodynamics', 'Journal Article', '10.1371/journal.pcbi.1005909', '29261665', 'Biomolecular recognition entails attractive forces for the functional native states and discrimination against potential nonnative interactions that favor alternate stable configurations. The challenge posed by the competition of nonnative stabilization against native-centric forces is conceptualized as frustration. Experiment indicates that frustration is often minimal in evolved biological systems although nonnative possibilities are intuitively abundant. Much of the physical basis of minimal frustration in protein folding thus remains to be elucidated. Here we make progress by studying the colicin immunity protein Im9. To assess the energetic favorability of nonnative versus native interactions, we compute free energies of association of various combinations of the four helices in Im9 (referred to as H1, H2, H3, and H4) by extensive explicit-water molecular dynamics simulations (total simulated time > 300 xcexbcs), focusing primarily on the pairs with the largest native contact surfaces, H1-H2 and H1-H4. Frustration is detected in H1-H2 packing in that a nonnative packing orientation is significantly stabilized relative to native, whereas such a prominent nonnative effect is not observed for H1-H4 packing. However, in contrast to the favored nonnative H1-H2 packing in isolation, the native H1-H2 packing orientation is stabilized by H3 and loop residues surrounding H4. Taken together, these results showcase the contextual nature of molecular recognition, and suggest further that nonnative effects in H1-H2 packing may be largely avoided by the experimentally inferred Im9 folding transition state with native packing most developed at the H1-H4 rather than the H1-H2 interface.'),
(88810, 2017, 'plos', 'Mechanistic modeling quantifies the influence of tumor growth kinetics on the response to anti-angiogenic treatment', 'Gaddy, Thomas D|Wu, Qianhui|Arnheim, Alyssa D|Finley, Stacey D', 'Department of Chemical Engineering and Materials Science, University of Southern California, Los Angeles, California, United States of America.|Department of Biomedical Engineering, University of Southern California, Los Angeles, California, United States of America.|Department of Biomedical Engineering, Boston University, Boston, Massachusetts, United States of America.|Department of Chemical Engineering and Materials Science, University of Southern California, Los Angeles, California, United States of America.', 'United States|United States|United States|United States', 7, 'Angiogenesis Inhibitors|Humans|Models, Theoretical|Neoplasms|Receptors, Vascular Endothelial Growth Factor|Systems Biology|Vascular Endothelial Growth Factor A', 'Journal Article', '10.1371/journal.pcbi.1005874', '29267273', 'Tumors exploit angiogenesis, the formation of new blood vessels from pre-existing vasculature, in order to obtain nutrients required for continued growth and proliferation. Targeting factors that regulate angiogenesis, including the potent promoter vascular endothelial growth factor (VEGF), is therefore an attractive strategy for inhibiting tumor growth. Computational modeling can be used to identify tumor-specific properties that influence the response to anti-angiogenic strategies. Here, we build on our previous systems biology model of VEGF transport and kinetics in tumor-bearing mice to include a tumor compartment whose volume depends on the angiogenic signal produced when VEGF binds to its receptors on tumor endothelial cells. We trained and validated the model using published in vivo measurements of xenograft tumor volume, producing a model that accurately predicts the tumors response to anti-angiogenic treatment. We applied the model to investigate how tumor growth kinetics influence the response to anti-angiogenic treatment targeting VEGF. Based on multivariate regression analysis, we found that certain intrinsic kinetic parameters that characterize the growth of tumors could successfully predict response to anti-VEGF treatment, the reduction in tumor volume. Lastly, we use the trained model to predict the response to anti-VEGF therapy for tumors expressing different levels of VEGF receptors. The model predicts that certain tumors are more sensitive to treatment than others, and the response to treatment shows a nonlinear dependence on the VEGF receptor expression. Overall, this model is a useful tool for predicting how tumors will respond to anti-VEGF treatment, and it complements pre-clinical in vivo mouse studies.');
INSERT INTO `papers` (`id`, `ano`, `journal`, `titulo`, `autores`, `afiliacao`, `pais`, `citacoes`, `palavra_chave`, `categorias`, `doi`, `pubmed`, `abstract`) VALUES
(88811, 2017, 'plos', 'Theoretical perspectives on central chemosensitivity: CO2/H+-sensitive neurons in the locus coeruleus', 'Quintero, Maria C|Putnam, Robert W|Cordovez, Juan M', 'Biomedical Engineering Department, Universidad de Los Andes, Bogotá, Colombia.|Department of Neuroscience, Cell Biology, and Physiology, Boonshoft School of Medicine, Wright State University, Dayton, Ohio, United States of America.|Biomedical Engineering Department, Universidad de Los Andes, Bogotá, Colombia.', 'Colombia|United States|Colombia', 0, 'Action Potentials|Animals|Carbon Dioxide|Chemoreceptor Cells|Computational Biology|Electric Stimulation|Electrophysiological Phenomena|Humans|Hydrogen-Ion Concentration|Hypercapnia|Hypocapnia|Locus Coeruleus|Models, Neurological|Synaptic Transmission', 'Journal Article', '10.1371/journal.pcbi.1005853', '29267284', 'Central chemoreceptors are highly sensitive neurons that respond to changes in pH and CO2 levels. An increase in CO2/H+ typically reflects a rise in the firing rate of these neurons, which stimulates an increase in ventilation. Here, we present an ionic current model that reproduces the basic electrophysiological activity of individual CO2/H+-sensitive neurons from the locus coeruleus (LC). We used this model to explore chemoreceptor discharge patterns in response to electrical and chemical stimuli. The modeled neurons showed both stimulus-evoked activity and spontaneous activity under physiological parameters. Neuronal responses to electrical and chemical stimulation showed specific firing patterns of spike frequency adaptation, postinhibitory rebound, and post-stimulation recovery. Conversely, the response to chemical stimulation alone (based on physiological CO2/H+ changes), in the absence of external depolarizing stimulation, showed no signs of postinhibitory rebound or post-stimulation recovery, and no depolarizing sag. A sensitivity analysis for the firing-rate response to the different stimuli revealed that the contribution of an applied stimulus current exceeded that of the chemical signals. The firing-rate response increased indefinitely with injected depolarizing current, but reached saturation with chemical stimuli. Our computational model reproduced the regular pacemaker-like spiking pattern, action potential shape, and most of the membrane properties that characterize CO2/H+-sensitive neurons from the locus coeruleus. This validates the model and highlights its potential as a tool for studying the cellular mechanisms underlying the altered central chemosensitivity present in a variety of disorders such as sudden infant death syndrome, depression, and anxiety. In addition, the model results suggest that small external electrical signals play a greater role in determining the chemosensitive response to changes in CO2/H+ than previously thought. This highlights the importance of considering electrical synaptic transmission in studies of intrinsic chemosensitivity.'),
(88812, 2017, 'plos', 'Correction: Dynamic Maternal Gradients Control Timing and Shift-Rates for Drosophila Gap Gene Expression', 'PLOS Computational Biology Staff', 'Biomedical Engineering Department, Universidad de Los Andes, Bogotá, Colombia.', 'Colombia', 0, '-', 'Journal Article', '10.1371/journal.pcbi.1005918', '29272271', '[This corrects the article DOI: 10.1371/journal.pcbi.1005285.].'),
(88813, 2017, 'plos', 'Physiological models of the lateral superior olive', 'Ashida, Go|Tollin, Daniel J|Kretzberg, Jutta', 'Cluster of Excellence Hearing4all, Department of Neuroscience, University of Oldenburg, Oldenburg, Germany.|Department of Physiology and Biophysics, University of Colorado School of Medicine, Aurora, Colorado, United States of America.|Cluster of Excellence Hearing4all, Department of Neuroscience, University of Oldenburg, Oldenburg, Germany.', 'Germany|United States|Germany', 11, 'Acoustic Stimulation|Animals|Cats|Computational Biology|Computer Simulation|Electrophysiological Phenomena|Models, Neurological|Neurons|Rodentia|Sound Localization|Superior Olivary Complex', 'Comparative Study', '10.1371/journal.pcbi.1005903', '29281618', 'In computational biology, modeling is a fundamental tool for formulating, analyzing and predicting complex phenomena. Most neuron models, however, are designed to reproduce certain small sets of empirical data. Hence their outcome is usually not compatible or comparable with other models or datasets, making it unclear how widely applicable such models are. In this study, we investigate these aspects of modeling, namely credibility and generalizability, with a specific focus on auditory neurons involved in the localization of sound sources. The primary cues for binaural sound localization are comprised of interaural time and level differences (ITD/ILD), which are the timing and intensity differences of the sound waves arriving at the two ears. The lateral superior olive (LSO) in the auditory brainstem is one of the locations where such acoustic information is first computed. An LSO neuron receives temporally structured excitatory and inhibitory synaptic inputs that are driven by ipsi- and contralateral sound stimuli, respectively, and changes its spike rate according to binaural acoustic differences. Here we examine seven contemporary models of LSO neurons with different levels of biophysical complexity, from predominantly functional ones (shot-noise models) to those with more detailed physiological components (variations of integrate-and-fire and Hodgkin-Huxley-type). These models, calibrated to reproduce known monaural and binaural characteristics of LSO, generate largely similar results to each other in simulating ITD and ILD coding. Our comparisons of physiological detail, computational efficiency, predictive performances, and further expandability of the models demonstrate (1) that the simplistic, functional LSO models are suitable for applications where low computational costs and mathematical transparency are needed, (2) that more complex models with detailed membrane potential dynamics are necessary for simulation studies where sub-neuronal nonlinear processes play important roles, and (3) that, for general purposes, intermediate models might be a reasonable compromise between simplicity and biological plausibility.'),
(88814, 2017, 'plos', 'High-resolution global peptide-protein docking using fragments-based PIPER-FlexPepDock', 'Alam, Nawsad|Goldstein, Oriel|Xia, Bing|Porter, Kathryn A|Kozakov, Dima|Schueler-Furman, Ora', 'Department of Microbiology and Molecular Genetics, Institute for Medical Research Israel-Canada, Faculty of Medicine, The Hebrew University, Jerusalem, Israel.|School of Computer Sciences and Engineering, The Hebrew University, Jerusalem, Israel.|Department of Biomedical Engineering, Boston University, Boston, Massachusetts, United States of America.|Department of Biomedical Engineering, Boston University, Boston, Massachusetts, United States of America.|Department of Applied Mathematics and Statistics, Stony Brook University, Stony Brook, New York, United States of America.|Department of Microbiology and Molecular Genetics, Institute for Medical Research Israel-Canada, Faculty of Medicine, The Hebrew University, Jerusalem, Israel.', 'Canada|Israel|United States|United States|United States|Canada', 30, 'Algorithms|Computational Biology|Computer Simulation|Crystallography, X-Ray|Models, Molecular|Molecular Docking Simulation|Molecular Dynamics Simulation|Peptide Fragments|Protein Conformation|Protein Interaction Mapping|Software', 'Journal Article', '10.1371/journal.pcbi.1005905', '29281622', 'Peptide-protein interactions contribute a significant fraction of the protein-protein interactome. Accurate modeling of these interactions is challenging due to the vast conformational space associated with interactions of highly flexible peptides with large receptor surfaces. To address this challenge we developed a fragment based high-resolution peptide-protein docking protocol. By streamlining the Rosetta fragment picker for accurate peptide fragment ensemble generation, the PIPER docking algorithm for exhaustive fragment-receptor rigid-body docking and Rosetta FlexPepDock for flexible full-atom refinement of PIPER docked models, we successfully addressed the challenge of accurate and efficient global peptide-protein docking at high-resolution with remarkable accuracy, as validated on a small but representative set of peptide-protein complex structures well resolved by X-ray crystallography. Our approach opens up the way to high-resolution modeling of many more peptide-protein interactions and to the detailed study of peptide-protein association in general. PIPER-FlexPepDock is freely available to the academic community as a server at http://piperfpd.furmanlab.cs.huji.ac.il.'),
(88815, 2017, 'plos', 'System identification of signaling dependent gene expression with different time-scale data', 'Tsuchiya, Takaho|Fujii, Masashi|Matsuda, Naoki|Kunida, Katsuyuki|Uda, Shinsuke|Kubota, Hiroyuki|Konishi, Katsumi|Kuroda, Shinya', 'Department of Biological Sciences, Graduate School of Science, University of Tokyo, Tokyo, Japan.|Department of Biological Sciences, Graduate School of Science, University of Tokyo, Tokyo, Japan.|Department of Biological Sciences, Graduate School of Science, University of Tokyo, Tokyo, Japan.|Department of Biological Sciences, Graduate School of Science, University of Tokyo, Tokyo, Japan.|Division of Integrated Omics, Research Center for Transomics Medicine, Medical Institute of Bioregulation, Kyushu University, Fukuoka, Japan.|Division of Integrated Omics, Research Center for Transomics Medicine, Medical Institute of Bioregulation, Kyushu University, Fukuoka, Japan.|Department of Computer Science, Faculty of Informatics, Kogakuin University, Tokyo, Japan.|Department of Biological Sciences, Graduate School of Science, University of Tokyo, Tokyo, Japan.', 'Japan|Japan|Japan|Japan|Japan|Japan|Japan|Japan', 4, 'Animals|Cell Differentiation|Computational Biology|Cyclic AMP Response Element-Binding Protein|Gene Expression|Kinetics|MAP Kinase Signaling System|Models, Biological|Neurites|PC12 Cells|Rats|Signal Transduction|Systems Biology', 'Journal Article', '10.1371/journal.pcbi.1005913', '29281625', 'Cells decode information of signaling activation at a scale of tens of minutes by downstream gene expression with a scale of hours to days, leading to cell fate decisions such as cell differentiation. However, no system identification method with such different time scales exists. Here we used compressed sensing technology and developed a system identification method using data of different time scales by recovering signals of missing time points. We measured phosphorylation of ERK and CREB, immediate early gene expression products, and mRNAs of decoder genes for neurite elongation in PC12 cell differentiation and performed system identification, revealing the input-output relationships between signaling and gene expression with sensitivity such as graded or switch-like response and with time delay and gain, representing signal transfer efficiency. We predicted and validated the identified system using pharmacological perturbation. Thus, we provide a versatile method for system identification using data with different time scales.'),
(88816, 2017, 'plos', 'Local motion adaptation enhances the representation of spatial structure at EMD arrays', 'Li, Jinglin|Lindemann, Jens P|Egelhaaf, Martin', 'Department of Neurobiology and Cluster of Excellence Cognitive Interaction Technology (CITEC), Bielefeld University, Bielefeld, Germany.|Department of Neurobiology and Cluster of Excellence Cognitive Interaction Technology (CITEC), Bielefeld University, Bielefeld, Germany.|Department of Neurobiology and Cluster of Excellence Cognitive Interaction Technology (CITEC), Bielefeld University, Bielefeld, Germany.', 'Germany|Germany|Germany', 3, 'Adaptation, Physiological|Animals|Computational Biology|Flight, Animal|Insecta|Models, Biological|Models, Neurological|Motion|Motion Perception|Optic Flow|Photic Stimulation|Saccades|Spatial Processing|Visual Pathways', 'Journal Article', '10.1371/journal.pcbi.1005919', '29281631', 'Neuronal representation and extraction of spatial information are essential for behavioral control. For flying insects, a plausible way to gain spatial information is to exploit distance-dependent optic flow that is generated during translational self-motion. Optic flow is computed by arrays of local motion detectors retinotopically arranged in the second neuropile layer of the insect visual system. These motion detectors have adaptive response characteristics, i.e. their responses to motion with a constant or only slowly changing velocity decrease, while their sensitivity to rapid velocity changes is maintained or even increases. We analyzed by a modeling approach how motion adaptation affects signal representation at the output of arrays of motion detectors during simulated flight in artificial and natural 3D environments. We focused on translational flight, because spatial information is only contained in the optic flow induced by translational locomotion. Indeed, flies, bees and other insects segregate their flight into relatively long intersaccadic translational flight sections interspersed with brief and rapid saccadic turns, presumably to maximize periods of translation (80% of the flight). With a novel adaptive model of the insect visual motion pathway we could show that the motion detector responses to background structures of cluttered environments are largely attenuated as a consequence of motion adaptation, while responses to foreground objects stay constant or even increase. This conclusion even holds under the dynamic flight conditions of insects.'),
(88817, 2017, 'plos', 'Scalable multi-sample single-cell data analysis by Partition-Assisted Clustering and Multiple Alignments of Networks', 'Li, Ye Henry|Li, Dangna|Samusik, Nikolay|Wang, Xiaowei|Guan, Leying|Nolan, Garry P|Wong, Wing Hung', 'Structural Biology Department and Public Policy Program, Stanford University, Stanford, United States of America.|Institute for Computational and Mathematical Engineering, Stanford University, Stanford, United States of America.|Department of Microbiology and Immunology, Baxter Laboratory, Stanford University, Stanford, United States of America.|Statistics Department, Stanford University, Stanford, United States of America.|Statistics Department, Stanford University, Stanford, United States of America.|Department of Microbiology and Immunology, Baxter Laboratory, Stanford University, Stanford, United States of America.|Statistics Department, Stanford University, Stanford, United States of America.', 'United States|United States|United States|United States|United States|United States|United States', 5, 'Animals|Biomarkers|Cluster Analysis|Computational Biology|Computer Simulation|Data Interpretation, Statistical|Databases, Factual|Flow Cytometry|Gene Expression|Humans|Mice|Single-Cell Analysis', 'Journal Article', '10.1371/journal.pcbi.1005875', '29281633', 'Mass cytometry (CyTOF) has greatly expanded the capability of cytometry. It is now easy to generate multiple CyTOF samples in a single study, with each sample containing single-cell measurement on 50 markers for more than hundreds of thousands of cells. Current methods do not adequately address the issues concerning combining multiple samples for subpopulation discovery, and these issues can be quickly and dramatically amplified with increasing number of samples. To overcome this limitation, we developed Partition-Assisted Clustering and Multiple Alignments of Networks (PAC-MAN) for the fast automatic identification of cell populations in CyTOF data closely matching that of expert manual-discovery, and for alignments between subpopulations across samples to define dataset-level cellular states. PAC-MAN is computationally efficient, allowing the management of very large CyTOF datasets, which are increasingly common in clinical studies and cancer studies that monitor various tissue samples for each subject.'),
(88818, 2017, 'plos', 'MPLasso: Inferring microbial association networks using prior microbial knowledge', 'Lo, Chieh|Marculescu, Radu', 'Department of Electrical and Computer Engineering, Carnegie Mellon University, Pittsburgh, Pennsylvania, United States of America.|Department of Electrical and Computer Engineering, Carnegie Mellon University, Pittsburgh, Pennsylvania, United States of America.', 'United States|United States', 10, 'Algorithms|Computational Biology|Data Mining|Databases, Genetic|Humans|Machine Learning|Microbial Consortia|Microbial Interactions|Microbiota|Models, Biological', 'Journal Article', '10.1371/journal.pcbi.1005915', '29281638', 'Due to the recent advances in high-throughput sequencing technologies, it becomes possible to directly analyze microbial communities in human body and environment. To understand how microbial communities adapt, develop, and interact with the human body and the surrounding environment, one of the fundamental challenges is to infer the interactions among different microbes. However, due to the compositional and high-dimensional nature of microbial data, statistical inference cannot offer reliable results. Consequently, new approaches that can accurately and robustly estimate the associations (putative interactions) among microbes are needed to analyze such compositional and high-dimensional data. We propose a novel framework called Microbial Prior Lasso (MPLasso) which integrates graph learning algorithm with microbial co-occurrences and associations obtained from scientific literature by using automated text mining. We show that MPLasso outperforms existing models in terms of accuracy, microbial network recovery rate, and reproducibility. Furthermore, the association networks we obtain from the Human Microbiome Project datasets show credible results when compared against laboratory data.'),
(88819, 2017, 'plos', 'Firing rate equations require a spike synchrony mechanism to correctly describe fast oscillations in inhibitory networks', 'Devalle, Federico|Roxin, Alex|Montbrió, Ernest', 'Center for Brain and Cognition, Department of Information and Communication Technologies, Universitat Pompeu Fabra, Barcelona, Spain.|Centre de Recerca Matemàtica, Campus de Bellaterra, Edifici C, Bellaterra, Barcelona, Spain.|Center for Brain and Cognition, Department of Information and Communication Technologies, Universitat Pompeu Fabra, Barcelona, Spain.', 'Spain|Spain|Spain', 18, 'Action Potentials|Animals|Computational Biology|Computer Simulation|Humans|Interneurons|Models, Neurological|Nerve Net|Neural Networks (Computer)|Synapses|Synaptic Transmission', 'Journal Article', '10.1371/journal.pcbi.1005881', '29287081', 'Recurrently coupled networks of inhibitory neurons robustly generate oscillations in the gamma band. Nonetheless, the corresponding Wilson-Cowan type firing rate equation for such an inhibitory population does not generate such oscillations without an explicit time delay. We show that this discrepancy is due to a voltage-dependent spike-synchronization mechanism inherent in networks of spiking neurons which is not captured by standard firing rate equations. Here we investigate an exact low-dimensional description for a network of heterogeneous canonical Class 1 inhibitory neurons which includes the sub-threshold dynamics crucial for generating synchronous states. In the limit of slow synaptic kinetics the spike-synchrony mechanism is suppressed and the standard Wilson-Cowan equations are formally recovered as long as external inputs are also slow. However, even in this limit synchronous spiking can be elicited by inputs which fluctuate on a time-scale of the membrane time-constant of the neurons. Our meanfield equations therefore represent an extension of the standard Wilson-Cowan equations in which spike synchrony is also correctly described.'),
(88820, 2018, 'plos', 'Mathematical modeling identifies optimum lapatinib dosing schedules for the treatment of glioblastoma patients', 'Stein, Shayna|Zhao, Rui|Haeno, Hiroshi|Vivanco, Igor|Michor, Franziska', 'Department of Biostatistics, Harvard T. H. Chan School of Public Health, Boston, Massasschusetts, United States of America.|Department of Biostatistics, Harvard T. H. Chan School of Public Health, Boston, Massasschusetts, United States of America.|Department of Biology, Kyushu University, Fukuoka, Japan.|Division of Cancer Therapeutics, The Institute of Cancer Research, London, United Kingdom.|Department of Biostatistics, Harvard T. H. Chan School of Public Health, Boston, Massasschusetts, United States of America.', 'United States|United States|Japan|United Kingdom|United States', 14, 'Antineoplastic Agents|Blood-Brain Barrier|Brain Neoplasms|Cell Line, Tumor|Computational Biology|Drug Administration Schedule|ErbB Receptors|Glioblastoma|Humans|Lapatinib|Logistic Models|Maximum Tolerated Dose|Models, Biological|Mutation|Protein Kinase Inhibitors|Quinazolines', 'Journal Article', '10.1371/journal.pcbi.1005924', '29293494', 'Human primary glioblastomas (GBM) often harbor mutations within the epidermal growth factor receptor (EGFR). Treatment of EGFR-mutant GBM cell lines with the EGFR/HER2 tyrosine kinase inhibitor lapatinib can effectively induce cell death in these models. However, EGFR inhibitors have shown little efficacy in the clinic, partly because of inappropriate dosing. Here, we developed a computational approach to model the in vitro cellular dynamics of the EGFR-mutant cell line SF268 in response to different lapatinib concentrations and dosing schedules. We then used this approach to identify an effective treatment strategy within the clinical toxicity limits of lapatinib, and developed a partial differential equation modeling approach to study the in vivo GBM treatment response by taking into account the heterogeneous and diffusive nature of the disease. Despite the inability of lapatinib to induce tumor regressions with a continuous daily schedule, our modeling approach consistently predicts that continuous dosing remains the best clinically feasible strategy for slowing down tumor growth and lowering overall tumor burden, compared to pulsatile schedules currently known to be tolerated, even when considering drug resistance, reduced lapatinib tumor concentrations due to the blood brain barrier, and the phenotypic switch from proliferative to migratory cell phenotypes that occurs in hypoxic microenvironments. Our mathematical modeling and statistical analysis platform provides a rational method for comparing treatment schedules in search for optimal dosing strategies for glioblastoma and other cancer types.'),
(88821, 2018, 'plos', 'Probing instructions for expression regulation in gene nucleotide compositions', 'Bessière, Chloé|Taha, May|Petitprez, Florent|Vandel, Jimmy|Marin, Jean-Michel|Bréhélin, Laurent|Lèbre, Sophie|Lecellier, Charles-Henri', 'IBC, Univ. Montpellier, CNRS, Montpellier, France.|IBC, Univ. Montpellier, CNRS, Montpellier, France.|IBC, Univ. Montpellier, CNRS, Montpellier, France.|IBC, Univ. Montpellier, CNRS, Montpellier, France.|IBC, Univ. Montpellier, CNRS, Montpellier, France.|IBC, Univ. Montpellier, CNRS, Montpellier, France.|IBC, Univ. Montpellier, CNRS, Montpellier, France.|IBC, Univ. Montpellier, CNRS, Montpellier, France.', 'France|France|France|France|France|France|France|France', 4, 'Base Composition|Computational Biology|DNA Copy Number Variations|Enhancer Elements, Genetic|Gene Expression Regulation|Genome, Human|Humans|Models, Genetic|Neoplasms|Polymorphism, Single Nucleotide|Promoter Regions, Genetic|Quantitative Trait Loci|RNA, Messenger|Regulatory Sequences, Nucleic Acid|Transcription Factors', 'Journal Article', '10.1371/journal.pcbi.1005921', '29293496', 'Gene expression is orchestrated by distinct regulatory regions to ensure a wide variety of cell types and functions. A challenge is to identify which regulatory regions are active, what are their associated features and how they work together in each cell type. Several approaches have tackled this problem by modeling gene expression based on epigenetic marks, with the ultimate goal of identifying driving regions and associated genomic variations that are clinically relevant in particular in precision medicine. However, these models rely on experimental data, which are limited to specific samples (even often to cell lines) and cannot be generated for all regulators and all patients. In addition, we show here that, although these approaches are accurate in predicting gene expression, inference of TF combinations from this type of models is not straightforward. Furthermore these methods are not designed to capture regulation instructions present at the sequence level, before the binding of regulators or the opening of the chromatin. Here, we probe sequence-level instructions for gene expression and develop a method to explain mRNA levels based solely on nucleotide features. Our method positions nucleotide composition as a critical component of gene expression. Moreover, our approach, able to rank regulatory regions according to their contribution, unveils a strong influence of the gene body sequence, in particular introns. We further provide evidence that the contribution of nucleotide content can be linked to co-regulations associated with genome 3D architecture and to associations of genes within topologically associated domains.'),
(88822, 2018, 'plos', 'Model-driven discovery of long-chain fatty acid metabolic reprogramming in heterogeneous prostate cancer cells', 'Marín de Mas, Igor|Aguilar, Esther|Zodda, Erika|Balcells, Cristina|Marin, Silvia|Dallmann, Guido|Thomson, Timothy M|Papp, Balázs|Cascante, Marta', 'Department of Biochemistry and Molecular Biomedicine, Faculty of Biology, Universitat de Barcelona, Barcelona, Spain.|Department of Biochemistry and Molecular Biomedicine, Faculty of Biology, Universitat de Barcelona, Barcelona, Spain.|Department of Biochemistry and Molecular Biomedicine, Faculty of Biology, Universitat de Barcelona, Barcelona, Spain.|Department of Biochemistry and Molecular Biomedicine, Faculty of Biology, Universitat de Barcelona, Barcelona, Spain.|Department of Biochemistry and Molecular Biomedicine, Faculty of Biology, Universitat de Barcelona, Barcelona, Spain.|Biocrates Life Sciences AG, Innsbruck, Austria.|Department of Cell Biology, Barcelona Institute for Molecular Biology (IBMB), National Research Council (CSIC), Barcelona, Spain.|Synthetic and Systems Biology Unit, Institute of Biochemistry, Biological Research Center of the Hungarian Academy of Sciences, Szeged, Hungary.|Department of Biochemistry and Molecular Biomedicine, Faculty of Biology, Universitat de Barcelona, Barcelona, Spain.', 'Spain|Spain|Spain|Spain|Spain|Austria|Spain|Hungary|Spain', 10, 'Arachidonic Acid|Biological Transport, Active|Cell Line, Tumor|Cell Proliferation|Computational Biology|Docosahexaenoic Acids|Eicosanoids|Epithelial-Mesenchymal Transition|Epoxy Compounds|Fatty Acids|Humans|Male|Metabolic Networks and Pathways|Mitochondria|Models, Biological|Neoplasm Invasiveness|Prostatic Neoplasms|Transcriptome', 'Journal Article', '10.1371/journal.pcbi.1005914', '29293497', 'Epithelial-mesenchymal-transition promotes intra-tumoral heterogeneity, by enhancing tumor cell invasiveness and promoting drug resistance. We integrated transcriptomic data for two clonal subpopulations from a prostate cancer cell line (PC-3) into a genome-scale metabolic network model to explore their metabolic differences and potential vulnerabilities. In this dual cell model, PC-3/S cells express Epithelial-mesenchymal-transition markers and display high invasiveness and low metastatic potential, while PC-3/M cells present the opposite phenotype and higher proliferative rate. Model-driven analysis and experimental validations unveiled a marked metabolic reprogramming in long-chain fatty acids metabolism. While PC-3/M cells showed an enhanced entry of long-chain fatty acids into the mitochondria, PC-3/S cells used long-chain fatty acids as precursors of eicosanoid metabolism. We suggest that this metabolic reprogramming endows PC-3/M cells with augmented energy metabolism for fast proliferation and PC-3/S cells with increased eicosanoid production impacting angiogenesis, cell adhesion and invasion. PC-3/S metabolism also promotes the accumulation of docosahexaenoic acid, a long-chain fatty acid with antiproliferative effects. The potential therapeutic significance of our model was supported by a differential sensitivity of PC-3/M cells to etomoxir, an inhibitor of long-chain fatty acid transport to the mitochondria.'),
(88823, 2018, 'plos', 'Improving pairwise comparison of protein sequences with domain co-occurrence', 'Menichelli, Christophe|Gascuel, Olivier|Bréhélin, Laurent', 'IBC, LIRMM, Univ. Montpellier, CNRS, Montpellier, France.|IBC, LIRMM, Univ. Montpellier, CNRS, Montpellier, France.|IBC, LIRMM, Univ. Montpellier, CNRS, Montpellier, France.', 'France|France|France', 1, 'Algorithms|Amino Acid Sequence|Computational Biology|Databases, Protein|Plasmodium falciparum|Protein Domains|Proteins|Protozoan Proteins|Sequence Alignment|Sequence Analysis, Protein', 'Journal Article', '10.1371/journal.pcbi.1005889', '29293498', 'Comparing and aligning protein sequences is an essential task in bioinformatics. More specifically, local alignment tools like BLAST are widely used for identifying conserved protein sub-sequences, which likely correspond to protein domains or functional motifs. However, to limit the number of false positives, these tools are used with stringent sequence-similarity thresholds and hence can miss several hits, especially for species that are phylogenetically distant from reference organisms. A solution to this problem is then to integrate additional contextual information to the procedure. Here, we propose to use domain co-occurrence to increase the sensitivity of pairwise sequence comparisons. Domain co-occurrence is a strong feature of proteins, since most protein domains tend to appear with a limited number of other domains on the same protein. We propose a method to take this information into account in a typical BLAST analysis and to construct new domain families on the basis of these results. We used Plasmodium falciparum as a case study to evaluate our method. The experimental findings showed an increase of 14% of the number of significant BLAST hits and an increase of 25% of the proteome area that can be covered with a domain. Our method identified 2240 new domains for which, in most cases, no model of the Pfam database could be linked. Moreover, our study of the quality of the new domains in terms of alignment and physicochemical properties show that they are close to that of standard Pfam domains. Source code of the proposed approach and supplementary data are available at: https://gite.lirmm.fr/menichelli/pairwise-comparison-with-cooccurrence.'),
(88824, 2018, 'plos', 'Integration of pan-cancer transcriptomics with RPPA proteomics reveals mechanisms of epithelial-mesenchymal transition', 'Koplev, Simon|Lin, Katie|Dohlman, Anders B|Maayan, Avi', 'Department of Pharmacological Sciences, Mount Sinai Center for Bioinformatics, Icahn School of Medicine at Mount Sinai, One Gustave L. Levy Place, New York, NY, United States of America.|Department of Pharmacological Sciences, Mount Sinai Center for Bioinformatics, Icahn School of Medicine at Mount Sinai, One Gustave L. Levy Place, New York, NY, United States of America.|Department of Pharmacological Sciences, Mount Sinai Center for Bioinformatics, Icahn School of Medicine at Mount Sinai, One Gustave L. Levy Place, New York, NY, United States of America.|Department of Pharmacological Sciences, Mount Sinai Center for Bioinformatics, Icahn School of Medicine at Mount Sinai, One Gustave L. Levy Place, New York, NY, United States of America.', 'United States|United States|United States|United States', 15, 'Antigens, CD|Cadherins|Carcinogenesis|Cell Line, Tumor|Computational Biology|Epithelial-Mesenchymal Transition|Histone Deacetylase Inhibitors|Humans|Models, Genetic|Models, Statistical|Neoplasms|Phosphorylation|Protein Array Analysis|Protein Kinase Inhibitors|Proteomics|RNA, Messenger|RNA, Neoplasm|Transcriptome', 'Journal Article', '10.1371/journal.pcbi.1005911', '29293502', 'Integrating data from multiple regulatory layers across cancer types could elucidate additional mechanisms of oncogenesis. Using antibody-based protein profiling of 736 cancer cell lines, along with matching transcriptomic data, we show that pan-cancer bimodality in the amounts of mRNA, protein, and protein phosphorylation reveals mechanisms related to the epithelial-mesenchymal transition (EMT). Based on the bimodal expression of E-cadherin, we define an EMT signature consisting of 239 genes, many of which were not previously associated with EMT. By querying gene expression signatures collected from cancer cell lines after small-molecule perturbations, we identify enrichment for histone deacetylase (HDAC) inhibitors as inducers of EMT, and kinase inhibitors as mesenchymal-to-epithelial transition (MET) promoters. Causal modeling of protein-based signaling identifies putative drivers of EMT. In conclusion, integrative analysis of pan-cancer proteomic and transcriptomic data reveals key regulatory mechanisms of oncogenic transformation.'),
(88825, 2018, 'plos', 'A systematic atlas of chaperome deregulation topologies across the human cancer landscape', 'Hadizadeh Esfahani, Ali|Sverchkova, Angelina|Saez-Rodriguez, Julio|Schuppert, Andreas A|Brehme, Marc', 'Joint Research Center for Computational Biomedicine (JRC-COMBINE), RWTH Aachen University, Aachen, Germany.|Joint Research Center for Computational Biomedicine (JRC-COMBINE), RWTH Aachen University, Faculty of Medicine, Aachen, Germany.|Joint Research Center for Computational Biomedicine (JRC-COMBINE), RWTH Aachen University, Faculty of Medicine, Aachen, Germany.|Joint Research Center for Computational Biomedicine (JRC-COMBINE), RWTH Aachen University, Aachen, Germany.|Joint Research Center for Computational Biomedicine (JRC-COMBINE), RWTH Aachen University, Aachen, Germany.', 'Germany|Germany|Germany|Germany|Germany', 19, 'Adenosine Triphosphate|Computational Biology|Gene Expression Profiling|Humans|Metabolic Networks and Pathways|Models, Biological|Molecular Chaperones|Neoplasms|Neurodegenerative Diseases|Protein Interaction Maps|Proteome|Proteostasis|Proteostasis Deficiencies|Software', 'Journal Article', '10.1371/journal.pcbi.1005890', '29293508', 'Proteome balance is safeguarded by the proteostasis network (PN), an intricately regulated network of conserved processes that evolved to maintain native function of the diverse ensemble of protein species, ensuring cellular and organismal health. Proteostasis imbalances and collapse are implicated in a spectrum of human diseases, from neurodegeneration to cancer. The characteristics of PN disease alterations however have not been assessed in a systematic way. Since the chaperome is among the central components of the PN, we focused on the chaperome in our study by utilizing a curated functional ontology of the human chaperome that we connect in a high-confidence physical protein-protein interaction network. Challenged by the lack of a systems-level understanding of proteostasis alterations in the heterogeneous spectrum of human cancers, we assessed gene expression across more than 10,000 patient biopsies covering 22 solid cancers. We derived a novel customized Meta-PCA dimension reduction approach yielding M-scores as quantitative indicators of disease expression changes to condense the complexity of cancer transcriptomics datasets into quantitative functional network topographies. We confirm upregulation of the HSP90 family and also highlight HSP60s, Prefoldins, HSP100s, ER- and mitochondria-specific chaperones as pan-cancer enriched. Our analysis also reveals a surprisingly consistent strong downregulation of small heat shock proteins (sHSPs) and we stratify two cancer groups based on the preferential upregulation of ATP-dependent chaperones. Strikingly, our analyses highlight similarities between stem cell and cancer proteostasis, and diametrically opposed chaperome deregulation between cancers and neurodegenerative diseases. We developed a web-based Proteostasis Profiler tool (Pro2) enabling intuitive analysis and visual exploration of proteostasis disease alterations using gene expression data. Our study showcases a comprehensive profiling of chaperome shifts in human cancers and sets the stage for a systematic global analysis of PN alterations across the human diseasome towards novel hypotheses for therapeutic network re-adjustment in proteostasis disorders.'),
(88826, 2018, 'plos', 'Ten simple rules for drawing scientific comics', 'McDermott, Jason E|Partridge, Matthew|Bromberg, Yana', 'Computational Biology and Bioinformatics, Pacific Northwest National Laboratory, Richland, Washington, United States of America.|Engineering Photonics, Cranfield University, Cranfield, Bedfordshire, United Kingdom.|Department of Biochemistry and Microbiology, Rutgers University, New Brunswick, New Jersey, United States of America.', 'United States|United Kingdom|Jersey', 5, 'Communication|Computational Biology|Humans|Science in the Arts|Wit and Humor as Topic', 'Editorial', '10.1371/journal.pcbi.1005845', '29300733', '-'),
(88827, 2018, 'plos', 'Ten simple rules for biologists learning to program', 'Carey, Maureen A|Papin, Jason A', 'Department of Microbiology, Immunology, and Cancer Biology, University of Virginia School of Medicine, Charlottesville, Virginia, United States of America.|Department of Biomedical Engineering, University of Virginia, Charlottesville, Virginia, United States of America.', 'United States|United States', 16, 'Computational Biology|Computer Literacy|Humans|Learning|Programming Languages|Software', 'Editorial', '10.1371/journal.pcbi.1005871', '29300745', '-'),
(88828, 2018, 'plos', 'A neural network model for the orbitofrontal cortex and task space acquisition during reinforcement learning', 'Zhang, Zhewei|Cheng, Zhenbo|Lin, Zhongqiao|Nie, Chechang|Yang, Tianming', 'Institute of Neuroscience, Key Laboratory of Primate Neurobiology, CAS Center for Excellence in Brain Science and Intelligence Technology, Shanghai Institutes for Biological Sciences, Chinese Academy of Sciences.|Department of Computer Science and Technology, Zhejiang University of Technology, Hangzhou, China.|Institute of Neuroscience, Key Laboratory of Primate Neurobiology, CAS Center for Excellence in Brain Science and Intelligence Technology, Shanghai Institutes for Biological Sciences, Chinese Academy of Sciences.|Institute of Neuroscience, Key Laboratory of Primate Neurobiology, CAS Center for Excellence in Brain Science and Intelligence Technology, Shanghai Institutes for Biological Sciences, Chinese Academy of Sciences.|Institute of Neuroscience, Key Laboratory of Primate Neurobiology, CAS Center for Excellence in Brain Science and Intelligence Technology, Shanghai Institutes for Biological Sciences, Chinese Academy of Sciences.', '-|China|-|-|-', 6, 'Animals|Cognition|Decision Making|Electrophysiology|Frontal Lobe|Humans|Learning|Magnetic Resonance Imaging|Markov Chains|Models, Neurological|Nerve Net|Neural Networks (Computer)|Neurons|Prefrontal Cortex|Probability|Reinforcement (Psychology)|Spatial Learning', 'Journal Article', '10.1371/journal.pcbi.1005925', '29300746', 'Reinforcement learning has been widely used in explaining animal behavior. In reinforcement learning, the agent learns the value of the states in the task, collectively constituting the task state space, and uses the knowledge to choose actions and acquire desired outcomes. It has been proposed that the orbitofrontal cortex (OFC) encodes the task state space during reinforcement learning. However, it is not well understood how the OFC acquires and stores task state information. Here, we propose a neural network model based on reservoir computing. Reservoir networks exhibit heterogeneous and dynamic activity patterns that are suitable to encode task states. The information can be extracted by a linear readout trained with reinforcement learning. We demonstrate how the network acquires and stores task structures. The network exhibits reinforcement learning behavior and its aspects resemble experimental findings of the OFC. Our study provides a theoretical explanation of how the OFC may contribute to reinforcement learning and a new approach to understanding the neural mechanism underlying reinforcement learning.'),
(88829, 2018, 'plos', 'Functional interrogation of Plasmodium genus metabolism identifies species- and stage-specific differences in nutrient essentiality and drug targeting', 'Abdel-Haleem, Alyaa M|Hefzi, Hooman|Mineta, Katsuhiko|Gao, Xin|Gojobori, Takashi|Palsson, Bernhard O|Lewis, Nathan E|Jamshidi, Neema', 'King Abdullah University of Science and Technology (KAUST), Computational Bioscience Research Centre (CBRC), Thuwal, Saudi Arabia.|Department of Bioengineering, University of California, San Diego, La Jolla, CA, United States of America.|King Abdullah University of Science and Technology (KAUST), Computational Bioscience Research Centre (CBRC), Thuwal, Saudi Arabia.|King Abdullah University of Science and Technology (KAUST), Computational Bioscience Research Centre (CBRC), Thuwal, Saudi Arabia.|King Abdullah University of Science and Technology (KAUST), Computational Bioscience Research Centre (CBRC), Thuwal, Saudi Arabia.|Department of Bioengineering, University of California, San Diego, La Jolla, CA, United States of America.|Novo Nordisk Foundation Center for Biosustainability at the University of California, San Diego School of Medicine, La Jolla, CA, United States of America.|Institute of Engineering in Medicine, University of California, San Diego, La Jolla, CA, United States of America.', 'Saudi Arabia|United States|Saudi Arabia|Saudi Arabia|Saudi Arabia|United States|United States|United', 5, 'Animals|Choline|Culicidae|Disease Models, Animal|Food|Gene Deletion|Gene Expression Regulation|Genome|Glycolysis|Humans|Life Cycle Stages|Malaria|Models, Biological|Pantothenic Acid|Plasmodium falciparum|Species Specificity|Systems Biology|Thiamine', 'Journal Article', '10.1371/journal.pcbi.1005895', '29300748', 'Several antimalarial drugs exist, but differences between life cycle stages among malaria species pose challenges for developing more effective therapies. To understand the diversity among stages and species, we reconstructed genome-scale metabolic models (GeMMs) of metabolism for five life cycle stages and five species of Plasmodium spanning the blood, transmission, and mosquito stages. The stage-specific models of Plasmodium falciparum uncovered stage-dependent changes in central carbon metabolism and predicted potential targets that could affect several life cycle stages. The species-specific models further highlight differences between experimental animal models and the human-infecting species. Comparisons between human- and rodent-infecting species revealed differences in thiamine (vitamin B1), choline, and pantothenate (vitamin B5) metabolism. Thus, we show that genome-scale analysis of multiple stages and species of Plasmodium can prioritize potential drug targets that could be both anti-malarials and transmission blocking agents, in addition to guiding translation from non-human experimental disease models.'),
(88830, 2018, 'plos', 'Representability of algebraic topology for biomolecules in machine learning based scoring and virtual screening', 'Cang, Zixuan|Mu, Lin|Wei, Guo-Wei', 'Department of Mathematics, Michigan State University, East Lansing, Michigan, United States of America.|Computer Science and Mathematics Division, Oak Ridge National Laboratory, Oak Ridge, Tennessee, United States of America.|Department of Mathematics, Michigan State University, East Lansing, Michigan, United States of America.', 'United States|United States|United States', 38, 'Algorithms|Area Under Curve|Computational Biology|Databases, Protein|Humans|Ligands|Machine Learning|Models, Neurological|Molecular Dynamics Simulation|Neural Networks (Computer)|Nucleic Acids|Protein Binding|Protein Interaction Mapping|Proteins|Static Electricity', 'Journal Article', '10.1371/journal.pcbi.1005929', '29309403', 'This work introduces a number of algebraic topology approaches, including multi-component persistent homology, multi-level persistent homology, and electrostatic persistence for the representation, characterization, and description of small molecules and biomolecular complexes. In contrast to the conventional persistent homology, multi-component persistent homology retains critical chemical and biological information during the topological simplification of biomolecular geometric complexity. Multi-level persistent homology enables a tailored topological description of inter- and/or intra-molecular interactions of interest. Electrostatic persistence incorporates partial charge information into topological invariants. These topological methods are paired with Wasserstein distance to characterize similarities between molecules and are further integrated with a variety of machine learning algorithms, including k-nearest neighbors, ensemble of trees, and deep convolutional neural networks, to manifest their descriptive and predictive powers for protein-ligand binding analysis and virtual screening of small molecules. Extensive numerical experiments involving 4,414 protein-ligand complexes from the PDBBind database and 128,374 ligand-target and decoy-target pairs in the DUD database are performed to test respectively the scoring power and the discriminatory power of the proposed topological learning strategies. It is demonstrated that the present topological learning outperforms other existing methods in protein-ligand binding affinity prediction and ligand-decoy discrimination.'),
(88831, 2018, 'plos', 'Cardinal features of involuntary force variability can arise from the closed-loop control of viscoelastic afferented muscles', 'Nagamori, Akira|Laine, Christopher M|Valero-Cuevas, Francisco J', 'Division of Biokinesiology and Physical Therapy, University of Southern California, Los Angeles, California, United States of America.|Division of Biokinesiology and Physical Therapy, University of Southern California, Los Angeles, California, United States of America.|Division of Biokinesiology and Physical Therapy, University of Southern California, Los Angeles, California, United States of America.', 'United States|United States|United States', 8, 'Computer Simulation|Elasticity|Humans|Isometric Contraction|Mechanoreceptors|Models, Biological|Models, Neurological|Motor Neurons|Muscle Spindles|Muscle, Skeletal|Sensory Receptor Cells|Tendons|Viscosity', 'Journal Article', '10.1371/journal.pcbi.1005884', '29309405', 'Involuntary force variability below 15 Hz arises from, and is influenced by, many factors including descending neural drive, proprioceptive feedback, and mechanical properties of muscles and tendons. However, their potential interactions that give rise to the well-structured spectrum of involuntary force variability are not well understood due to a lack of experimental techniques. Here, we investigated the generation, modulation, and interactions among different sources of force variability using a physiologically-grounded closed-loop simulation of an afferented muscle model. The closed-loop simulation included a musculotendon model, muscle spindle, Golgi tendon organ (GTO), and a tracking controller which enabled target-guided force tracking. We demonstrate that closed-loop control of an afferented musculotendon suffices to replicate and explain surprisingly many cardinal features of involuntary force variability. Specifically, we present 1) a potential origin of low-frequency force variability associated with co-modulation of motor unit firing rates (i.e.,common drive), 2) an in-depth characterization of how proprioceptive feedback pathways suffice to generate 5-12 Hz physiological tremor, and 3) evidence that modulation of those feedback pathways (i.e., presynaptic inhibition of Ia and Ib afferents, and spindle sensitivity via fusimotor drive) influence the full spectrum of force variability. These results highlight the previously underestimated importance of closed-loop neuromechanical interactions in explaining involuntary force variability during voluntary isometric force control. Furthermore, these results provide the basis for a unifying theory that relates spinal circuitry to various manifestations of altered involuntary force variability in fatigue, aging and neurological disease.');
INSERT INTO `papers` (`id`, `ano`, `journal`, `titulo`, `autores`, `afiliacao`, `pais`, `citacoes`, `palavra_chave`, `categorias`, `doi`, `pubmed`, `abstract`) VALUES
(88832, 2018, 'plos', 'Robust and efficient coding with grid cells', 'Vágó, Lajos|Ujfalussy, Balázs B', 'NAP-B PATTERN Group, MTA Wigner Research Center for Physics, Budapest, Hungary.|NAP-B PATTERN Group, MTA Wigner Research Center for Physics, Budapest, Hungary.', 'Hungary|Hungary', 2, 'Algorithms|Animals|Behavior, Animal|Computational Biology|Computer Graphics|Computer Simulation|Entorhinal Cortex|Grid Cells|Models, Neurological|Neurons|Probability|Programming Languages|Rodentia|Space Perception|Systems Biology', 'Journal Article', '10.1371/journal.pcbi.1005922', '29309406', 'The neuronal code arising from the coordinated activity of grid cells in the rodent entorhinal cortex can uniquely represent space across a large range of distances, but the precise conditions for optimal coding capacity are known only for environments with finite size. Here we consider a coding scheme that is suitable for unbounded environments, and present a novel, number theoretic approach to derive the grid parameters that maximise the coding range in the presence of noise. We derive an analytic upper bound on the coding range and provide examples for grid scales that achieve this bound and hence are optimal for encoding in unbounded environments. We show that in the absence of neuronal noise, the capacity of the system is extremely sensitive to the choice of the grid periods. However, when the accuracy of the representation is limited by neuronal noise, the capacity quickly becomes more robust against the choice of grid scales as the number of modules increases. Importantly, we found that the capacity of the system is near optimal even for random scale choices already for a realistic number of grid modules. Our study demonstrates that robust and efficient coding can be achieved without parameter tuning in the case of grid cell representation and provides a solid theoretical explanation for the large diversity of the grid scales observed in experimental studies. Moreover, we suggest that having multiple grid modules in the entorhinal cortex is not only required for the exponentially large coding capacity, but is also a prerequisite for the robustness of the system.'),
(88833, 2018, 'plos', 'Bowhead: Bayesian modelling of cell velocity during concerted cell migration', 'Engel, Mathias|Longden, James|Ferkinghoff-Borg, Jesper|Robin, Xavier|Saginc, Gaye|Linding, Rune', 'Biotech Research and Innovation Centre, University of Copenhagen, Copenhagen, Denmark.|Biotech Research and Innovation Centre, University of Copenhagen, Copenhagen, Denmark.|Biotech Research and Innovation Centre, University of Copenhagen, Copenhagen, Denmark.|Biotech Research and Innovation Centre, University of Copenhagen, Copenhagen, Denmark.|Biotech Research and Innovation Centre, University of Copenhagen, Copenhagen, Denmark.|Biotech Research and Innovation Centre, University of Copenhagen, Copenhagen, Denmark.', 'Denmark|Denmark|Denmark|Denmark|Denmark|Denmark', 0, 'Algorithms|Bayes Theorem|Breast Neoplasms|Cell Cycle Proteins|Cell Line, Tumor|Cell Movement|Computational Biology|Female|Gene Expression Regulation, Neoplastic|Humans|Molecular Motor Proteins|Myosin Heavy Chains|Normal Distribution|Octamer Transcription Factor-3|Phenotype|Protein-Serine-Threonine Kinases|Proto-Oncogene Proteins|RNA, Small Interfering|Signal-To-Noise Ratio|Time Factors|Wound Healing', 'Journal Article', '10.1371/journal.pcbi.1005900', '29309407', 'Cell migration is a central biological process that requires fine coordination of molecular events in time and space. A deregulation of the migratory phenotype is also associated with pathological conditions including cancer where cell motility has a causal role in tumor spreading and metastasis formation. Thus cell migration is of critical and strategic importance across the complex disease spectrum as well as for the basic understanding of cell phenotype. Experimental studies of the migration of cells in monolayers are often conducted with wound healing assays. Analysis of these assays has traditionally relied on how the wound area changes over time. However this method does not take into account the shape of the wound. Given the many options for creating a wound healing assay and the fact that wound shape invariably changes as cells migrate this is a significant flaw. Here we present a novel software package for analyzing concerted cell velocity in wound healing assays. Our method encompasses a wound detection algorithm based on cell confluency thresholding and employs a Bayesian approach in order to estimate concerted cell velocity with an associated likelihood. We have applied this method to study the effect of siRNA knockdown on the migration of a breast cancer cell line and demonstrate that cell velocity can track wound healing independently of wound shape and provides a more robust quantification with significantly higher signal to noise ratios than conventional analyses of wound area. The software presented here will enable other researchers in any field of cell biology to quantitatively analyze and track live cell migratory processes and is therefore expected to have a significant impact on the study of cell migration, including cancer relevant processes. Installation instructions, documentation and source code can be found at http://bowhead.lindinglab.science licensed under GPLv3.'),
(88834, 2018, 'plos', 'Modeling the genetic relatedness of Plasmodium falciparum parasites following meiotic recombination and cotransmission', 'Wong, Wesley|Wenger, Edward A|Hartl, Daniel L|Wirth, Dyann F', 'Department of Immunology and Infectious Diseases, Harvard T. H. Chan School of Public Health, Boston, Massachusetts, United States of America.|Institute for Disease Modeling, Bellevue, Washington, United States of America.|Department of Immunology and Infectious Diseases, Harvard T. H. Chan School of Public Health, Boston, Massachusetts, United States of America.|Department of Immunology and Infectious Diseases, Harvard T. H. Chan School of Public Health, Boston, Massachusetts, United States of America.', 'United States|United States|United States|United States', 7, 'Alleles|Animals|Anopheles|Computer Simulation|Female|Hepatocytes|Humans|Malaria, Falciparum|Male|Meiosis|Models, Genetic|Mosquito Vectors|Oocysts|Pedigree|Plasmodium falciparum|Polymorphism, Single Nucleotide|Probability|Recombination, Genetic', 'Journal Article', '10.1371/journal.pcbi.1005923', '29315306', 'Unlike in most pathogens, multiple-strain (polygenomic) infections of P. falciparum are frequently composed of genetic siblings. These genetic siblings are the result of sexual reproduction and can coinfect the same host when cotransmitted by the same mosquito. The degree with which coinfecting strains are related varies among infections and populations. Because sexual recombination occurs within the mosquito, the relatedness of cotransmitted strains could depend on transmission dynamics, but little is actually known of the factors that influence the relatedness of cotransmitted strains. Part of the uncertainty stems from an incomplete understanding of how within-host and within-vector dynamics affect cotransmission. Cotransmission is difficult to examine experimentally but can be explored using a computational model. We developed a malaria transmission model that simulates sexual reproduction in order to understand what determines the relatedness of cotransmitted strains. This study highlights how the relatedness of cotransmitted strains depends on both within-host and within-vector dynamics including the complexity of infection. We also used our transmission model to analyze the genetic relatedness of polygenomic infections following a series of multiple transmission events and examined the effects of superinfection. Understanding the factors that influence the relatedness of cotransmitted strains could lead to a better understanding of the population-genetic correlates of transmission and therefore be important for public health.'),
(88835, 2018, 'plos', 'Bayesian inference of phylogenetic networks from bi-allelic genetic markers', 'Zhu, Jiafan|Wen, Dingqiao|Yu, Yun|Meudt, Heidi M|Nakhleh, Luay', 'Computer Science, Rice University, Houston, Texas, United States of America.|Computer Science, Rice University, Houston, Texas, United States of America.|Computer Science, Rice University, Houston, Texas, United States of America.|Museum of New Zealand Te Papa Tongarewa, Wellington, New Zealand.|Computer Science, Rice University, Houston, Texas, United States of America.', 'United States|United States|United States|New Zealand|United States', 12, 'Algorithms|Alleles|Bayes Theorem|Computational Biology|Computer Simulation|Genes, Plant|Genetic Markers|Likelihood Functions|Models, Genetic|New Zealand|Nucleic Acid Hybridization|Phylogeny|Plantaginaceae|Polymorphism, Single Nucleotide|Probability|Recombination, Genetic|Software', 'Journal Article', '10.1371/journal.pcbi.1005932', '29320496', 'Phylogenetic networks are rooted, directed, acyclic graphs that model reticulate evolutionary histories. Recently, statistical methods were devised for inferring such networks from either gene tree estimates or the sequence alignments of multiple unlinked loci. Bi-allelic markers, most notably single nucleotide polymorphisms (SNPs) and amplified fragment length polymorphisms (AFLPs), provide a powerful source of genome-wide data. In a recent paper, a method called SNAPP was introduced for statistical inference of species trees from unlinked bi-allelic markers. The generative process assumed by the method combined both a model of evolution for the bi-allelic markers, as well as the multispecies coalescent. A novel component of the method was a polynomial-time algorithm for exact computation of the likelihood of a fixed species tree via integration over all possible gene trees for a given marker. Here we report on a method for Bayesian inference of phylogenetic networks from bi-allelic markers. Our method significantly extends the algorithm for exact computation of phylogenetic network likelihood via integration over all possible gene trees. Unlike the case of species trees, the algorithm is no longer polynomial-time on all instances of phylogenetic networks. Furthermore, the method utilizes a reversible-jump MCMC technique to sample the posterior of phylogenetic networks given bi-allelic marker data. Our method has a very good performance in terms of accuracy and robustness as we demonstrate on simulated data, as well as a data set of multiple New Zealand species of the plant genus Ourisia (Plantaginaceae). We implemented the method in the publicly available, open-source PhyloNet software package.'),
(88836, 2018, 'plos', 'Identifying human diamine sensors for death related putrescine and cadaverine molecules', 'Izquierdo, Cristina|Gómez-Tamayo, José C|Nebel, Jean-Christophe|Pardo, Leonardo|Gonzalez, Angel', 'Laboratori de Medicina Computacional, Unitat de Bioestadística, Facultat de Medicina, Universitat Autònoma de Barcelona, E-08193 Bellaterra, Spain.|Laboratori de Medicina Computacional, Unitat de Bioestadística, Facultat de Medicina, Universitat Autònoma de Barcelona, E-08193 Bellaterra, Spain.|Faculty of Science, Engineering and Computing, Kingston University, London, United Kingdom.|Laboratori de Medicina Computacional, Unitat de Bioestadística, Facultat de Medicina, Universitat Autònoma de Barcelona, E-08193 Bellaterra, Spain.|Laboratori de Medicina Computacional, Unitat de Bioestadística, Facultat de Medicina, Universitat Autònoma de Barcelona, E-08193 Bellaterra, Spain.', 'Spain|Spain|United Kingdom|Spain|Spain', 8, 'Animals|Aspartic Acid|Behavior, Animal|Cadaverine|Cell Cycle Proteins|Computational Biology|Computer Simulation|Diamines|Humans|Ligands|Molecular Docking Simulation|Nuclear Proteins|Olfactory Mucosa|Phylogeny|Polyamines|Protein Binding|Putrescine|Receptors, G-Protein-Coupled|Smell|Zebrafish', 'Journal Article', '10.1371/journal.pcbi.1005945', '29324768', 'Pungent chemical compounds originating from decaying tissue are strong drivers of animal behavior. Two of the best-characterized death smell components are putrescine (PUT) and cadaverine (CAD), foul-smelling molecules produced by decarboxylation of amino acids during decomposition. These volatile polyamines act as necromones, triggering avoidance or attractive responses, which are fundamental for the survival of a wide range of species. The few studies that have attempted to identify the cognate receptors for these molecules have suggested the involvement of the seven-helix trace amine-associated receptors (TAARs), localized in the olfactory epithelium. However, very little is known about the precise chemosensory receptors that sense these compounds in the majority of organisms and the molecular basis of their interactions. In this work, we have used computational strategies to characterize the binding between PUT and CAD with the TAAR6 and TAAR8 human receptors. Sequence analysis, homology modeling, docking and molecular dynamics studies suggest a tandem of negatively charged aspartates in the binding pocket of these receptors which are likely to be involved in the recognition of these small biogenic diamines.'),
(88837, 2018, 'plos', 'Assessing an effective undergraduate module teaching applied bioinformatics to biology students', 'Madlung, Andreas', 'University of Puget Sound, Department of Biology, Tacoma, Washington.', '-', 0, 'Computational Biology|Curriculum|Educational Measurement|High-Throughput Nucleotide Sequencing|Humans|Sequence Analysis, RNA|Students|Surveys and Questionnaires|Teaching', 'Journal Article', '10.1371/journal.pcbi.1005872', '29324777', 'Applied bioinformatics skills are becoming ever more indispensable for biologists, yet incorporation of these skills into the undergraduate biology curriculum is lagging behind, in part due to a lack of instructors willing and able to teach basic bioinformatics in classes that dont specifically focus on quantitative skill development, such as statistics or computer sciences. To help undergraduate course instructors who themselves did not learn bioinformatics as part of their own education and are hesitant to plunge into teaching big data analysis, a module was developed that is written in plain-enough language, using publicly available computing tools and data, to allow novice instructors to teach next-generation sequence analysis to upper-level undergraduate students. To determine if the module allowed students to develop a better understanding of and appreciation for applied bioinformatics, various tools were developed and employed to assess the impact of the module. This article describes both the module and its assessment. Students found the activity valuable for their education and, in focus group discussions, emphasized that they saw a need for more and earlier instruction of big data analysis as part of the undergraduate biology curriculum.'),
(88838, 2018, 'plos', 'Disentangling and modeling interactions in fish with burst-and-coast swimming reveal distinct alignment and attraction behaviors', 'Calovi, Daniel S|Litchinko, Alexandra|Lecheval, Valentin|Lopez, Ugo|Pérez Escudero, Alfonso|Chaté, Hugues|Sire, Clément|Theraulaz, Guy', 'Centre de Recherches sur la Cognition Animale, Centre de Biologie Intégrative (CBI), Centre National de la Recherche Scientifique (CNRS) & Université de Toulouse - Paul Sabatier, 31062 Toulouse, France.|Centre de Recherches sur la Cognition Animale, Centre de Biologie Intégrative (CBI), Centre National de la Recherche Scientifique (CNRS) & Université de Toulouse - Paul Sabatier, 31062 Toulouse, France.|Centre de Recherches sur la Cognition Animale, Centre de Biologie Intégrative (CBI), Centre National de la Recherche Scientifique (CNRS) & Université de Toulouse - Paul Sabatier, 31062 Toulouse, France.|Centre de Recherches sur la Cognition Animale, Centre de Biologie Intégrative (CBI), Centre National de la Recherche Scientifique (CNRS) & Université de Toulouse - Paul Sabatier, 31062 Toulouse, France.|Centre de Recherches sur la Cognition Animale, Centre de Biologie Intégrative (CBI), Centre National de la Recherche Scientifique (CNRS) & Université de Toulouse - Paul Sabatier, 31062 Toulouse, France.|Service de Physique de lÉtat Condensé, CEA - Saclay, 91191 Gif-sur-Yvette, France.|Laboratoire de Physique Théorique, CNRS & Université de Toulouse - Paul Sabatier, 31062 Toulouse, France.|Centre de Recherches sur la Cognition Animale, Centre de Biologie Intégrative (CBI), Centre National de la Recherche Scientifique (CNRS) & Université de Toulouse - Paul Sabatier, 31062 Toulouse, France.', 'France|France|France|France|France|France|France|France', 17, 'Animals|Anisotropy|Behavior, Animal|Body Size|Computational Biology|Fishes|Interpersonal Relations|Models, Biological|Probability|Signal Processing, Computer-Assisted|Social Behavior|Software|Stochastic Processes|Swimming|Temperature', 'Journal Article', '10.1371/journal.pcbi.1005933', '29324853', 'The development of tracking methods for automatically quantifying individual behavior and social interactions in animal groups has open up new perspectives for building quantitative and predictive models of collective behavior. In this work, we combine extensive data analyses with a modeling approach to measure, disentangle, and reconstruct the actual functional form of interactions involved in the coordination of swimming in Rummy-nose tetra (Hemigrammus rhodostomus). This species of fish performs burst-and-coast swimming behavior that consists of sudden heading changes combined with brief accelerations followed by quasi-passive, straight decelerations. We quantify the spontaneous stochastic behavior of a fish and the interactions that govern wall avoidance and the reaction to a neighboring fish, the latter by exploiting general symmetry constraints for the interactions. In contrast with previous experimental works, we find that both attraction and alignment behaviors control the reaction of fish to a neighbor. We then exploit these results to build a model of spontaneous burst-and-coast swimming and interactions of fish, with all parameters being estimated or directly measured from experiments. This model quantitatively reproduces the key features of the motion and spatial distributions observed in experiments with a single fish and with two fish. This demonstrates the power of our method that exploits large amounts of data for disentangling and fully characterizing the interactions that govern collective behaviors in animals groups.'),
(88839, 2018, 'plos', 'Modeling the assembly order of multimeric heteroprotein complexes', 'Peterson, Lenna X|Togawa, Yoichiro|Esquivel-Rodriguez, Juan|Terashi, Genki|Christoffer, Charles|Roy, Amitava|Shin, Woong-Hee|Kihara, Daisuke', 'Department of Biological Sciences, Purdue University, West Lafayette, Indiana, United States of America.|Department of Biological Sciences, Purdue University, West Lafayette, Indiana, United States of America.|Department of Computer Science, Purdue University, West Lafayette, Indiana, United States of America.|Department of Biological Sciences, Purdue University, West Lafayette, Indiana, United States of America.|Department of Computer Science, Purdue University, West Lafayette, Indiana, United States of America.|Department of Biological Sciences, Purdue University, West Lafayette, Indiana, United States of America.|Department of Biological Sciences, Purdue University, West Lafayette, Indiana, United States of America.|Department of Biological Sciences, Purdue University, West Lafayette, Indiana, United States of America.', 'India|India|India|India|India|India|India|India', 6, 'Algorithms|Cholera Toxin|Computational Biology|Databases, Protein|Helicobacter pylori|Humans|Models, Statistical|Molecular Docking Simulation|Protein Binding|Protein Domains|Protein Interaction Mapping|Proteins|Software|Thermodynamics', 'Journal Article', '10.1371/journal.pcbi.1005937', '29329283', 'Protein-protein interactions are the cornerstone of numerous biological processes. Although an increasing number of protein complex structures have been determined using experimental methods, relatively fewer studies have been performed to determine the assembly order of complexes. In addition to the insights into the molecular mechanisms of biological function provided by the structure of a complex, knowing the assembly order is important for understanding the process of complex formation. Assembly order is also practically useful for constructing subcomplexes as a step toward solving the entire complex experimentally, designing artificial protein complexes, and developing drugs that interrupt a critical step in the complex assembly. There are several experimental methods for determining the assembly order of complexes, however, these techniques are resource-intensive. Here, we present a computational method that predicts the assembly order of protein complexes by building the complex structure. The method, named Path-LzerD, uses a multimeric protein docking algorithm that assembles a protein complex structure from individual subunit structures and predicts assembly order by observing the simulated assembly process of the complex. Benchmarked on a dataset of complexes with experimental evidence of assembly order, Path-LZerD was successful in predicting the assembly pathway for the majority of the cases. Moreover, when compared with a simple approach that infers the assembly path from the buried surface area of subunits in the native complex, Path-LZerD has the strong advantage that it can be used for cases where the complex structure is not known. The path prediction accuracy decreased when starting from unbound monomers, particularly for larger complexes of five or more subunits, for which only a part of the assembly path was correctly identified. As the first method of its kind, Path-LZerD opens a new area of computational protein structure modeling and will be an indispensable approach for studying protein complexes.'),
(88840, 2018, 'plos', 'A direct interaction of cholesterol with the dopamine transporter prevents its out-to-inward transition', 'Zeppelin, Talia|Ladefoged, Lucy Kate|Sinning, Steffen|Periole, Xavier|Schiøtt, Birgit', 'Department of Chemistry, Aarhus University, Aarhus C, Denmark.|Department of Chemistry, Aarhus University, Aarhus C, Denmark.|Department of Chemistry, Aarhus University, Aarhus C, Denmark.|Department of Chemistry, Aarhus University, Aarhus C, Denmark.|Department of Chemistry, Aarhus University, Aarhus C, Denmark.', 'Denmark|Denmark|Denmark|Denmark|Denmark', 0, 'Amino Acid Motifs|Animals|Binding Sites|Cholesterol|Computer Simulation|Crystallography, X-Ray|Dopamine|Dopamine Plasma Membrane Transport Proteins|Drosophila melanogaster|Humans|Lipid Bilayers|Molecular Dynamics Simulation|Neurotransmitter Agents|Protein Conformation|Signal Transduction|Software|Synaptic Transmission|Vesicular Monoamine Transport Proteins', 'Journal Article', '10.1371/journal.pcbi.1005907', '29329285', 'Monoamine transporters (MATs) carry out neurotransmitter reuptake from the synaptic cleft, a key step in neurotransmission, which is targeted in the treatment of neurological disorders. Cholesterol (CHOL), a major component of the synaptic plasma membrane, has been shown to exhibit a modulatory effect on MATs. Recent crystal structures of the dopamine transporter (DAT) revealed the presence of two conserved CHOL-like molecules, suggesting a functional protein-CHOL direct interaction. Here, we present extensive atomistic molecular dynamics (MD) simulations of DAT in an outward-facing conformation. In the absence of bound CHOL, DAT undergoes structural changes reflecting early events of dopamine transport: transition to an inward-facing conformation. In contrast, in the presence of bound CHOL, these conformational changes are inhibited, seemingly by an immobilization of the intracellular interface of transmembrane helix 1a and 5 by CHOL. We also provide evidence, from coarse grain MD simulations that the CHOL sites observed in the DAT crystal structures are preserved in all human monoamine transporters (dopamine, serotonin and norepinephrine), suggesting that our findings might extend to the entire family.'),
(88841, 2018, 'plos', 'The E265A mutation disrupts dynamic binding poses of SB269652 at the dopamine D2 and D3 receptors', 'Verma, Ravi Kumar|Abramyan, Ara M|Michino, Mayako|Free, R Benjamin|Sibley, David R|Javitch, Jonathan A|Lane, J Robert|Shi, Lei', 'Computational Chemistry and Molecular Biophysics Unit, Molecular Targets and Medications Discovery Branch, National Institute on Drug Abuse-Intramural Research Program, National Institutes of Health, Baltimore, Maryland, United States.|Computational Chemistry and Molecular Biophysics Unit, Molecular Targets and Medications Discovery Branch, National Institute on Drug Abuse-Intramural Research Program, National Institutes of Health, Baltimore, Maryland, United States.|Computational Chemistry and Molecular Biophysics Unit, Molecular Targets and Medications Discovery Branch, National Institute on Drug Abuse-Intramural Research Program, National Institutes of Health, Baltimore, Maryland, United States.|Molecular Neuropharmacology Section, National Institute of Neurologic Disorders and Stroke, National Institutes of Health, Bethesda, Maryland, United States.|Molecular Neuropharmacology Section, National Institute of Neurologic Disorders and Stroke, National Institutes of Health, Bethesda, Maryland, United States.|Departments of Psychiatry and Pharmacology, College of Physicians and Surgeons, Columbia University, New York, New York, United States.|Drug Discovery Biology, Department of Pharmacology and Medicinal Chemistry, Monash Institute of Pharmaceutical Sciences, Monash University (Parkville campus), Parkville, Victoria, Australia.|Computational Chemistry and Molecular Biophysics Unit, Molecular Targets and Medications Discovery Branch, National Institute on Drug Abuse-Intramural Research Program, National Institutes of Health, Baltimore, Maryland, United States.', 'United States|United States|United States|United States|United States|United States|Australia|United', 5, 'Allosteric Regulation|Allosteric Site|Bayes Theorem|Cluster Analysis|Computer Simulation|Humans|Hydrogen Bonding|Indoles|Isoquinolines|Ligands|Markov Chains|Molecular Dynamics Simulation|Mutation|Phenotype|Protein Binding|Protein Domains|Protein Structure, Secondary|Receptors, Dopamine D2|Receptors, Dopamine D3|Structure-Activity Relationship', 'Journal Article', '10.1371/journal.pcbi.1005948', '29337986', 'The dopamine D2 and D3 receptors (D2R and D3R) are important targets for antipsychotics and for the treatment of drug abuse. SB269652, a bitopic ligand that simultaneously binds both the orthosteric binding site (OBS) and a secondary binding pocket (SBP) in both D2R and D3R, was found to be a negative allosteric modulator. Previous studies identified Glu2.65 in the SBP to be a key determinant of both the affinity of SB269652 and the magnitude of its cooperativity with orthosteric ligands, as the E2.65A mutation decreased both of these parameters. However, the proposed hydrogen bond (H-bond) between Glu2.65 and the indole moiety of SB269652 is not a strong interaction, and a structure activity relationship study of SB269652 indicates that this H-bond may not be the only element that determines its allosteric properties. To understand the structural basis of the observed phenotype of E2.65A, we carried out molecular dynamics simulations with a cumulative length of ~77 xcexbcs of D2R and D3R wild-type and their E2.65A mutants bound to SB269652. In combination with Markov state model analysis and by characterizing the equilibria of ligand binding modes in different conditions, we found that in both D2R and D3R, whereas the tetrahydroisoquinoline moiety of SB269652 is stably bound in the OBS, the indole-2-carboxamide moiety is dynamic and only intermittently forms H-bonds with Glu2.65. Our results also indicate that the E2.65A mutation significantly affects the overall shape and size of the SBP, as well as the conformation of the N terminus. Thus, our findings suggest that the key role of Glu2.65 in mediating the allosteric properties of SB269652 extends beyond a direct interaction with SB269652, and provide structural insights for rational design of SB269652 derivatives that may retain its allosteric properties.'),
(88842, 2018, 'plos', 'Clustering gene expression time series data using an infinite Gaussian process mixture model', 'McDowell, Ian C|Manandhar, Dinesh|Vockley, Christopher M|Schmid, Amy K|Reddy, Timothy E|Engelhardt, Barbara E', 'Computational Biology & Bioinformatics Graduate Program, Duke University, Durham, North Carolina, United States of America.|Computational Biology & Bioinformatics Graduate Program, Duke University, Durham, North Carolina, United States of America.|Center for Genomic & Computational Biology, Duke University, Durham, North Carolina, United States of America.|Center for Genomic & Computational Biology, Duke University, Durham, North Carolina, United States of America.|Computational Biology & Bioinformatics Graduate Program, Duke University, Durham, North Carolina, United States of America.|Department of Computer Science, Princeton University, Princeton, New Jersey, United States of America.', 'United States|United States|United States|United States|United States|Jersey', 15, 'A549 Cells|Algorithms|Cell Line, Tumor|Cluster Analysis|Computational Biology|Computer Simulation|Dexamethasone|Gene Expression Profiling|Gene Expression Regulation, Neoplastic|Glucocorticoids|Histones|Humans|Hydrogen Bonding|Hydrogen Peroxide|Lung Neoplasms|Models, Biological|Normal Distribution|Oligonucleotide Array Sequence Analysis|Sequence Analysis, RNA|Time Factors|Transcription Factors', 'Journal Article', '10.1371/journal.pcbi.1005896', '29337990', 'Transcriptome-wide time series expression profiling is used to characterize the cellular response to environmental perturbations. The first step to analyzing transcriptional response data is often to cluster genes with similar responses. Here, we present a nonparametric model-based method, Dirichlet process Gaussian process mixture model (DPGP), which jointly models data clusters with a Dirichlet process and temporal dependencies with Gaussian processes. We demonstrate the accuracy of DPGP in comparison to state-of-the-art approaches using hundreds of simulated data sets. To further test our method, we apply DPGP to published microarray data from a microbial model organism exposed to stress and to novel RNA-seq data from a human cell line exposed to the glucocorticoid dexamethasone. We validate our clusters by examining local transcription factor binding and histone modifications. Our results demonstrate that jointly modeling cluster number and temporal dependencies can reveal shared regulatory mechanisms. DPGP software is freely available online at https://github.com/PrincetonUniversity/DP_GP_cluster.'),
(88843, 2018, 'plos', 'HaSAPPy: A tool for candidate identification in pooled forward genetic screens of haploid mammalian cells', 'Di Minin, Giulio|Postlmayr, Andreas|Wutz, Anton', 'Institute of Molecular Health Sciences, Department of Biology, Swiss Federal Institute of Technology ETH Hönggerberg, Zurich, Switzerland.|Institute of Molecular Health Sciences, Department of Biology, Swiss Federal Institute of Technology ETH Hönggerberg, Zurich, Switzerland.|Institute of Molecular Health Sciences, Department of Biology, Swiss Federal Institute of Technology ETH Hönggerberg, Zurich, Switzerland.', 'Switzerland|Switzerland|Switzerland', 1, 'Algorithms|Alleles|Animals|Computational Biology|Computer Graphics|Gene Library|Genome, Human|Haploidy|Humans|Mice|Mouse Embryonic Stem Cells|Mutagenesis, Insertional|Mutation|Phenotype|Picornaviridae|Programming Languages|Sequence Analysis, DNA|Software', 'Journal Article', '10.1371/journal.pcbi.1005950', '29337991', 'Haploid cells are increasingly used for screening of complex pathways in animal genomes. Hemizygous mutations introduced through viral insertional mutagenesis can be directly selected for phenotypic changes. Here we present HaSAPPy a tool for analysing sequencing datasets of screens using insertional mutations in large pools of haploid cells. Candidate gene prediction is implemented through identification of enrichment of insertional mutations after selection by simultaneously evaluating several parameters. We have developed HaSAPPy for analysis of genetic screens for silencing factors of X chromosome inactivation in haploid mouse embryonic stem cells. To benchmark the performance, we further analyse several datasets of genetic screens in human haploid cells for which candidates have been validated. Our results support the effective candidate prediction strategy of HaSAPPy. HaSAPPy is implemented in Python, licensed under the MIT license, and is available from https://github.com/gdiminin/HaSAPPy.'),
(88844, 2018, 'plos', 'A dynamical systems approach for estimating phase interactions between rhythms of different frequencies from experimental data', 'Onojima, Takayuki|Goto, Takahiro|Mizuhara, Hiroaki|Aoyagi, Toshio', 'Graduate School of Informatics, Kyoto University, Kyoto, Japan.|Graduate School of Informatics, Kyoto University, Kyoto, Japan.|Graduate School of Informatics, Kyoto University, Kyoto, Japan.|Graduate School of Informatics, Kyoto University, Kyoto, Japan.', 'Japan|Japan|Japan|Japan', 4, 'Adult|Bayes Theorem|Brain|Electroencephalography|Female|Healthy Volunteers|Humans|Male|Models, Neurological|Normal Distribution|Oscillometry|Periodicity|Reproducibility of Results|Signal Processing, Computer-Assisted|Systems Analysis|Young Adult', 'Journal Article', '10.1371/journal.pcbi.1005928', '29337999', 'Synchronization of neural oscillations as a mechanism of brain function is attracting increasing attention. Neural oscillation is a rhythmic neural activity that can be easily observed by noninvasive electroencephalography (EEG). Neural oscillations show the same frequency and cross-frequency synchronization for various cognitive and perceptual functions. However, it is unclear how this neural synchronization is achieved by a dynamical system. If neural oscillations are weakly coupled oscillators, the dynamics of neural synchronization can be described theoretically using a phase oscillator model. We propose an estimation method to identify the phase oscillator model from real data of cross-frequency synchronized activities. The proposed method can estimate the coupling function governing the properties of synchronization. Furthermore, we examine the reliability of the proposed method using time-series data obtained from numerical simulation and an electronic circuit experiment, and show that our method can estimate the coupling function correctly. Finally, we estimate the coupling function between EEG oscillation and the speech sound envelope, and discuss the validity of these results.'),
(88845, 2018, 'plos', 'Interrupting behaviour: Minimizing decision costs via temporal commitment and low-level interrupts', 'Lloyd, Kevin|Dayan, Peter', 'Gatsby Computational Neuroscience Unit, London, United Kingdom.|Gatsby Computational Neuroscience Unit, London, United Kingdom.', 'United Kingdom|United Kingdom', 4, 'Adrenergic Neurons|Algorithms|Animals|Choice Behavior|Computational Biology|Decision Making|Ecosystem|Feeding Behavior|Hawks|Learning|Predatory Behavior|Probability|Rats|Software|Time Factors', 'Journal Article', '10.1371/journal.pcbi.1005916', '29338004', 'Ideal decision-makers should constantly assess all sources of information about opportunities and threats, and be able to redetermine their choices promptly in the face of change. However, perpetual monitoring and reassessment impose inordinate sensing and computational costs, making them impractical for animals and machines alike. The obvious alternative of committing for extended periods of time to limited sensory strategies associated with particular courses of action can be dangerous and wasteful. Here, we explore the intermediate possibility of making provisional temporal commitments whilst admitting interruption based on limited broader observation. We simulate foraging under threat of predation to elucidate the benefits of such a scheme. We relate our results to diseases of distractibility and roving attention, and consider mechanistic substrates such as noradrenergic neuromodulation.'),
(88846, 2018, 'plos', 'Inferring cell state by quantitative motility analysis reveals a dynamic state system and broken detailed balance', 'Kimmel, Jacob C|Chang, Amy Y|Brack, Andrew S|Marshall, Wallace F', 'Dept. of Biochemistry and Biophysics, Center for Cellular Construction, University of California San Francisco, San Francisco, CA, United States of America.|Dept. of Biochemistry and Biophysics, Center for Cellular Construction, University of California San Francisco, San Francisco, CA, United States of America.|Eli and Edythe Broad Center for Regenerative Medicine and Stem Cell Research, University of California San Francisco, San Francisco, CA, United States of America.|Dept. of Biochemistry and Biophysics, Center for Cellular Construction, University of California San Francisco, San Francisco, CA, United States of America.', 'United States|United States|United States|United States', 11, 'Algorithms|Animals|Cell Movement|Cluster Analysis|Computational Biology|Female|Fibroblasts|Kinetics|Leukocytes, Mononuclear|Male|Mice|Mice, Inbred C57BL|Muscles|Nonlinear Dynamics|Phenotype|Probability|Signal Transduction|Stem Cells', 'Journal Article', '10.1371/journal.pcbi.1005927', '29338005', 'Cell populations display heterogeneous and dynamic phenotypic states at multiple scales. Similar to molecular features commonly used to explore cell heterogeneity, cell behavior is a rich phenotypic space that may allow for identification of relevant cell states. Inference of cell state from cell behavior across a time course may enable the investigation of dynamics of transitions between heterogeneous cell states, a task difficult to perform with destructive molecular observations. Cell motility is one such easily observed cell behavior with known biomedical relevance. To investigate heterogenous cell states and their dynamics through the lens of cell behavior, we developed Heteromotility, a software tool to extract quantitative motility features from timelapse cell images. In mouse embryonic fibroblasts (MEFs), myoblasts, and muscle stem cells (MuSCs), Heteromotility analysis identifies multiple motility phenotypes within the population. In all three systems, the motility state identity of individual cells is dynamic. Quantification of state transitions reveals that MuSCs undergoing activation transition through progressive motility states toward the myoblast phenotype. Transition rates during MuSC activation suggest non-linear kinetics. By probability flux analysis, we find that this MuSC motility state system breaks detailed balance, while the MEF and myoblast systems do not. Balanced behavior state transitions can be captured by equilibrium formalisms, while unbalanced switching between states violates equilibrium conditions and would require an external driving force. Our data indicate that the system regulating cell behavior can be decomposed into a set of attractor states which depend on the identity of the cell, together with a set of transitions between states. These results support a conceptual view of cell populations as dynamical systems, responding to inputs from signaling pathways and generating outputs in the form of state transitions and observable motile behaviors.'),
(88847, 2018, 'plos', 'A model for cooperative gating of L-type Ca2+ channels and its effects on cardiac alternans dynamics', 'Sato, Daisuke|Dixon, Rose E|Santana, Luis F|Navedo, Manuel F', 'Department of Pharmacology, University of California, Davis, Davis, CA, USA.|Department of Physiology & Membrane Biology, University of California, Davis, Davis, CA, USA.|Department of Physiology & Membrane Biology, University of California, Davis, Davis, CA, USA.|Department of Pharmacology, University of California, Davis, Davis, CA, USA.', 'United States|United States|United States|United States', 7, 'Action Potentials|Animals|Arrhythmias, Cardiac|Calcium|Calcium Channels, L-Type|Calcium Signaling|Computational Biology|Computer Simulation|Excitation Contraction Coupling|Heart Rate|Markov Chains|Models, Biological|Myocardial Contraction|Myocardium|Myocytes, Cardiac|Normal Distribution|Programming Languages|Rabbits|Sarcoplasmic Reticulum|Stochastic Processes', 'Journal Article', '10.1371/journal.pcbi.1005906', '29338006', 'In ventricular myocytes, membrane depolarization during the action potential (AP) causes synchronous activation of multiple L-type CaV1.2 channels (LTCCs), which trigger the release of calcium (Ca2+) from the sarcoplasmic reticulum (SR). This results in an increase in intracellular Ca2+ (Cai) that initiates contraction. During pulsus alternans, cardiac contraction is unstable, going from weak to strong in successive beats despite a constant heart rate. These cardiac alternans can be caused by the instability of membrane potential (Vm) due to steep AP duration (APD) restitution (Vm-driven alternans), instability of Cai cycling (Ca2+-driven alternans), or both, and may be modulated by functional coupling between clustered CaV1.2 (e.g. cooperative gating). Here, mathematical analysis and computational models were used to determine how changes in the strength of cooperative gating between LTCCs may impact membrane voltage and intracellular Ca2+ dynamics in the heart. We found that increasing the degree of coupling between LTCCs increases the amplitude of Ca2+ currents (ICaL) and prolongs AP duration (APD). Increased AP duration is known to promote cardiac alternans, a potentially arrhythmogenic substrate. In addition, our analysis shows that increasing the strength of cooperative activation of LTCCs makes the coupling of Ca2+ on the membrane voltage (Caixe2x86x92Vm coupling) more positive and destabilizes the Vm-Cai dynamics for Vm-driven alternans and Cai-driven alternans, but not for quasiperiodic oscillation. These results suggest that cooperative gating of LTCCs may have a major impact on cardiac excitation-contraction coupling, not only by prolonging APD, but also by altering Caixe2x86x92Vm coupling and potentially promoting cardiac arrhythmias.'),
(88848, 2018, 'plos', 'Interactions between species introduce spurious associations in microbiome studies', 'Menon, Rajita|Ramanan, Vivek|Korolev, Kirill S', 'Department of Physics, Boston University, Boston, Massachusetts, United States of America.|BRITE Bioinformatics REU Program, Boston University, Boston, Massachusetts, United States of America.|Department of Physics, Boston University, Boston, Massachusetts, United States of America.', 'United States|United States|United States', 11, 'Algorithms|Child|Computational Biology|Crohn Disease|Gastrointestinal Microbiome|Genome-Wide Association Study|Humans|Inflammatory Bowel Diseases|Microbial Interactions|Models, Statistical|Phenotype|Regression Analysis|Reproducibility of Results|Software', 'Journal Article', '10.1371/journal.pcbi.1005939', '29338008', 'Microbiota contribute to many dimensions of host phenotype, including disease. To link specific microbes to specific phenotypes, microbiome-wide association studies compare microbial abundances between two groups of samples. Abundance differences, however, reflect not only direct associations with the phenotype, but also indirect effects due to microbial interactions. We found that microbial interactions could easily generate a large number of spurious associations that provide no mechanistic insight. Using techniques from statistical physics, we developed a method to remove indirect associations and applied it to the largest dataset on pediatric inflammatory bowel disease. Our method corrected the inflation of p-values in standard association tests and showed that only a small subset of associations is directly linked to the disease. Direct associations had a much higher accuracy in separating cases from controls and pointed to immunomodulation, butyrate production, and the brain-gut axis as important factors in the inflammatory bowel disease.'),
(88849, 2018, 'plos', 'A theory of how active behavior stabilises neural activity: Neural gain modulation by closed-loop environmental feedback', 'Buckley, Christopher L|Toyoizumi, Taro', 'Laboratory for Neural Computation and Adaptation, RIKEN Brain Science Institute, Saitama, Japan.|Laboratory for Neural Computation and Adaptation, RIKEN Brain Science Institute, Saitama, Japan.', 'Japan|Japan', 6, 'Animals|Animals, Genetically Modified|Computer Simulation|Feedback|Membrane Potentials|Models, Neurological|Motor Skills|Musculoskeletal Physiological Phenomena|Nervous System Physiological Phenomena|Neurons|Normal Distribution|Reproducibility of Results|Rodentia|Signal Transduction|Signal-To-Noise Ratio|Touch|Vibrissae|Virtual Reality|Zebrafish', 'Journal Article', '10.1371/journal.pcbi.1005926', '29342146', 'During active behaviours like running, swimming, whisking or sniffing, motor actions shape sensory input and sensory percepts guide future motor commands. Ongoing cycles of sensory and motor processing constitute a closed-loop feedback system which is central to motor control and, it has been argued, for perceptual processes. This closed-loop feedback is mediated by brainwide neural circuits but how the presence of feedback signals impacts on the dynamics and function of neurons is not well understood. Here we present a simple theory suggesting that closed-loop feedback between the brain/body/environment can modulate neural gain and, consequently, change endogenous neural fluctuations and responses to sensory input. We support this theory with modeling and data analysis in two vertebrate systems. First, in a model of rodent whisking we show that negative feedback mediated by whisking vibrissa can suppress coherent neural fluctuations and neural responses to sensory input in the barrel cortex. We argue this suppression provides an appealing account of a brain state transition (a marked change in global brain activity) coincident with the onset of whisking in rodents. Moreover, this mechanism suggests a novel signal detection mechanism that selectively accentuates active, rather than passive, whisker touch signals. This mechanism is consistent with a predictive coding strategy that is sensitive to the consequences of motor actions rather than the difference between the predicted and actual sensory input. We further support the theory by re-analysing previously published two-photon data recorded in zebrafish larvae performing closed-loop optomotor behaviour in a virtual swim simulator. We show, as predicted by this theory, that the degree to which each cell contributes in linking sensory and motor signals well explains how much its neural fluctuations are suppressed by closed-loop optomotor behaviour. More generally we argue that our results demonstrate the dependence of neural fluctuations, across the brain, on closed-loop brain/body/environment interactions strongly supporting the idea that brain function cannot be fully understood through open-loop approaches alone.');
INSERT INTO `papers` (`id`, `ano`, `journal`, `titulo`, `autores`, `afiliacao`, `pais`, `citacoes`, `palavra_chave`, `categorias`, `doi`, `pubmed`, `abstract`) VALUES
(88850, 2018, 'plos', 'The ISCB Student Council Internship Program: Expanding computational biology capacity worldwide', 'Anupama, Jigisha|Francescatto, Margherita|Rahman, Farzana|Fatima, Nazeefa|DeBlasio, Dan|Shanmugam, Avinash Kumar|Satagopam, Venkata|Santos, Alberto|Kolekar, Pandurang|Michaut, Magali|Guney, Emre', 'University College Dublin, Dublin, Ireland.|Fondazione Bruno Kessler, Trento, Italy.|Genomics and Computational Biology Group, School of Computing and Mathematics, University of South Wales, Treforest, Wales, United Kingdom.|Department of Biology, Faculty of Science, Lund University, Lund, Sweden.|Computational Biology Department, Carnegie Mellon University, Pittsburgh, Pennsylvania, United States of America.|University of Michigan, Ann Arbor, Michigan, United States of America.|Luxembourg Centre for Systems Biomedicine, Université du Luxembourg, Luxembourg City, Luxembourg.|Novo Nordisk Foundation Center for Protein Research, Copenhagen, Denmark.|Strand Life Sciences Pvt Ltd, Bengaluru, India.|The Netherlands Cancer Institute, Amsterdam, Netherlands.|Joint IRB-BSC-CRG Program in Computational Biology, Institute for Research in Biomedicine, Barcelona, Catalonia, Spain.', 'Ireland|Italy|United Kingdom|Sweden|United States|United States|Luxembourg|Denmark|India|Netherlands', 0, 'Algorithms|Australia|Computational Biology|Curriculum|Developing Countries|Europe|Geography|Humans|Internship and Residency|Program Development|Students|Universities', 'Journal Article', '10.1371/journal.pcbi.1005802', '29346365', 'Education and training are two essential ingredients for a successful career. On one hand, universities provide students a curriculum for specializing in ones field of study, and on the other, internships complement coursework and provide invaluable training experience for a fruitful career. Consequently, undergraduates and graduates are encouraged to undertake an internship during the course of their degree. The opportunity to explore ones research interests in the early stages of their education is important for students because it improves their skill set and gives their career a boost. In the long term, this helps to close the gap between skills and employability among students across the globe and balance the research capacity in the field of computational biology. However, training opportunities are often scarce for computational biology students, particularly for those who reside in less-privileged regions. Aimed at helping students develop research and academic skills in computational biology and alleviating the divide across countries, the Student Council of the International Society for Computational Biology introduced its Internship Program in 2009. The Internship Program is committed to providing access to computational biology training, especially for students from developing regions, and improving competencies in the field. Here, we present how the Internship Program works and the impact of the internship opportunities so far, along with the challenges associated with this program.'),
(88851, 2018, 'plos', 'Mechanical feedback coordinates cell wall expansion and assembly in yeast mating morphogenesis', 'Banavar, Samhita P|Gomez, Carlos|Trogdon, Michael|Petzold, Linda R|Yi, Tau-Mu|Campàs, Otger', 'Department of Physics, University of California, Santa Barbara, Santa Barbara, California, United States of America.|California NanoSystems Institute, University of California, Santa Barbara, Santa Barbara, California, United States of America.|Department of Mechanical Engineering, University of California, Santa Barbara, Santa Barbara, California, United States of America.|Department of Mechanical Engineering, University of California, Santa Barbara, Santa Barbara, California, United States of America.|Department of Molecular, Cell and Developmental Biology, University of California, Santa Barbara, Santa Barbara, California, United States of America.|California NanoSystems Institute, University of California, Santa Barbara, Santa Barbara, California, United States of America.', 'United States|United States|United States|United States|United States|United States', 5, 'Cell Cycle|Cell Membrane|Cell Proliferation|Cell Shape|Cell Wall|Exocytosis|Genes, Mating Type, Fungal|Green Fluorescent Proteins|Intracellular Signaling Peptides and Proteins|Membrane Glycoproteins|Membrane Proteins|Models, Theoretical|Morphogenesis|Phenotype|Saccharomyces cerevisiae|Saccharomyces cerevisiae Proteins|Stress, Mechanical', 'Journal Article', '10.1371/journal.pcbi.1005940', '29346368', 'The shaping of individual cells requires a tight coordination of cell mechanics and growth. However, it is unclear how information about the mechanical state of the wall is relayed to the molecular processes building it, thereby enabling the coordination of cell wall expansion and assembly during morphogenesis. Combining theoretical and experimental approaches, we show that a mechanical feedback coordinating cell wall assembly and expansion is essential to sustain mating projection growth in budding yeast (Saccharomyces cerevisiae). Our theoretical results indicate that the mechanical feedback provided by the Cell Wall Integrity pathway, with cell wall stress sensors Wsc1 and Mid2 increasingly activating membrane-localized cell wall synthases Fks1/2 upon faster cell wall expansion, stabilizes mating projection growth without affecting cell shape. Experimental perturbation of the osmotic pressure and cell wall mechanics, as well as compromising the mechanical feedback through genetic deletion of the stress sensors, leads to cellular phenotypes that support the theoretical predictions. Our results indicate that while the existence of mechanical feedback is essential to stabilize mating projection growth, the shape and size of the cell are insensitive to the feedback.'),
(88852, 2018, 'plos', 'A mathematical model for IL-6-mediated, stem cell driven tumor growth and targeted treatment', 'Nazari, Fereshteh|Pearson, Alexander T|Nör, Jacques Eduardo|Jackson, Trachette L', 'Simon A. Levin Mathematical, Computational, and Modeling Sciences Center, School of Human Evolution and Social Change, Arizona State University, Tempe, Arizona, United States of America.|Division of Hematology/Oncology, Department of Internal Medicine, University of Michigan Cancer Center, Ann Arbor, Michigan, United States of America.|Departments of Cardiology, Restorative Sciences, and Endontics, University of Michigan, Ann Arbor, Michigan, United States of America.|Department of Mathematics, University of Michigan, Ann Arbor, Michigan, United States of America.', 'United States|United States|United States|United States', 10, 'Algorithms|Animals|Antibodies, Monoclonal|Antibodies, Monoclonal, Humanized|Binding Sites|Cisplatin|Computer Simulation|Endothelial Cells|Humans|Interleukin-6|Mice|Mice, SCID|Models, Theoretical|Neoplasm Transplantation|Neoplasms|Neoplastic Stem Cells|Phenotype|Receptors, Interleukin-6|Signal Transduction|Time Factors', 'Journal Article', '10.1371/journal.pcbi.1005920', '29351275', 'Targeting key regulators of the cancer stem cell phenotype to overcome their critical influence on tumor growth is a promising new strategy for cancer treatment. Here we present a modeling framework that operates at both the cellular and molecular levels, for investigating IL-6 mediated, cancer stem cell driven tumor growth and targeted treatment with anti-IL6 antibodies. Our immediate goal is to quantify the influence of IL-6 on cancer stem cell self-renewal and survival, and to characterize the subsequent impact on tumor growth dynamics. By including the molecular details of IL-6 binding, we are able to quantify the temporal changes in fractional occupancies of bound receptors and their influence on tumor volume. There is a strong correlation between the model output and experimental data for primary tumor xenografts. We also used the model to predict tumor response to administration of the humanized IL-6R monoclonal antibody, tocilizumab (TCZ), and we found that as little as 1mg/kg of TCZ administered weekly for 7 weeks is sufficient to result in tumor reduction and a sustained deceleration of tumor growth.'),
(88853, 2018, 'plos', 'Static length changes of cochlear outer hair cells can tune low-frequency hearing', 'Ciganovixc4x87, Nikola|Warren, Rebecca L|Kexc3xa7eli, Batu|Jacob, Stefan|Fridberger, Anders|Reichenbach, Tobias', 'Department of Bioengineering, Imperial College London, South Kensington Campus, London SW7 2AZ, United Kingdom.|Department of Clinical and Experimental Medicine, Linkxc3xb6ping University, SE-581 85 Linkxc3xb6ping, Sweden.|Department of Clinical and Experimental Medicine, Linkxc3xb6ping University, SE-581 85 Linkxc3xb6ping, Sweden.|The Rolf Luft Research Center for Diabetes and Endocrinology, Karolinska Institutet, SE-171 77 Stockholm, Sweden.|Department of Clinical and Experimental Medicine, Linkxc3xb6ping University, SE-581 85 Linkxc3xb6ping, Sweden.|Department of Bioengineering, Imperial College London, South Kensington Campus, London SW7 2AZ, United Kingdom.', 'United Kingdom|Sweden|Sweden|Sweden|Sweden|United Kingdom', 1, 'Animals|Biomechanical Phenomena|Cochlea|Computational Biology|Elasticity|Female|Guinea Pigs|Hair Cells, Auditory, Inner|Hair Cells, Auditory, Outer|Hearing|Interferometry|Male|Microscopy, Confocal|Models, Biological|Motion|Music|Neurons|Organ of Corti|Signal Processing, Computer-Assisted', 'Journal Article', '10.1371/journal.pcbi.1005936', '29351276', 'The cochlea not only transduces sound-induced vibration into neural spikes, it also amplifies weak sound to boost its detection. Actuators of this active process are sensory outer hair cells in the organ of Corti, whereas the inner hair cells transduce the resulting motion into electric signals that propagate via the auditory nerve to the brain. However, how the outer hair cells modulate the stimulus to the inner hair cells remains unclear. Here, we combine theoretical modeling and experimental measurements near the cochlear apex to study the way in which length changes of the outer hair cells deform the organ of Corti. We develop a geometry-based kinematic model of the apical organ of Corti that reproduces salient, yet counter-intuitive features of the organs motion. Our analysis further uncovers a mechanism by which a static length change of the outer hair cells can sensitively tune the signal transmitted to the sensory inner hair cells. When the outer hair cells are in an elongated state, stimulation of inner hair cells is largely inhibited, whereas outer hair cell contraction leads to a substantial enhancement of sound-evoked motion near the hair bundles. This novel mechanism for regulating the sensitivity of the hearing organ applies to the low frequencies that are most important for the perception of speech and music. We suggest that the proposed mechanism might underlie frequency discrimination at low auditory frequencies, as well as our ability to selectively attend auditory signals in noisy surroundings.'),
(88854, 2018, 'plos', 'What drives the perceptual change resulting from speech motor adaptation? Evaluation of hypotheses in a Bayesian modeling framework', 'Patri, Jean-François|Perrier, Pascal|Schwartz, Jean-Luc|Diard, Julien', 'Univ. Grenoble Alpes, CNRS, GIPSA-Lab UMR 5216, F-38000 Grenoble, France.|Univ. Grenoble Alpes, CNRS, GIPSA-Lab UMR 5216, F-38000 Grenoble, France.|Univ. Grenoble Alpes, CNRS, GIPSA-Lab UMR 5216, F-38000 Grenoble, France.|Univ. Grenoble Alpes, CNRS, LPNC UMR 5105, F-38000 Grenoble, France.', 'France|France|France|France', 8, 'Acoustic Stimulation|Auditory Perception|Bayes Theorem|Computational Biology|Computer Simulation|Feedback, Sensory|Hearing|Humans|Models, Biological|Models, Statistical|Motor Skills|Normal Distribution|Speech|Speech Acoustics|Speech Perception', 'Journal Article', '10.1371/journal.pcbi.1005942', '29357357', 'Shifts in perceptual boundaries resulting from speech motor learning induced by perturbations of the auditory feedback were taken as evidence for the involvement of motor functions in auditory speech perception. Beyond this general statement, the precise mechanisms underlying this involvement are not yet fully understood. In this paper we propose a quantitative evaluation of some hypotheses concerning the motor and auditory updates that could result from motor learning, in the context of various assumptions about the roles of the auditory and somatosensory pathways in speech perception. This analysis was made possible thanks to the use of a Bayesian model that implements these hypotheses by expressing the relationships between speech production and speech perception in a joint probability distribution. The evaluation focuses on how the hypotheses can (1) predict the location of perceptual boundary shifts once the perturbation has been removed, (2) account for the magnitude of the compensation in presence of the perturbation, and (3) describe the correlation between these two behavioral characteristics. Experimental findings about changes in speech perception following adaptation to auditory feedback perturbations serve as reference. Simulations suggest that they are compatible with a framework in which motor adaptation updates both the auditory-motor internal model and the auditory characterization of the perturbed phoneme, and where perception involves both auditory and somatosensory pathways.'),
(88855, 2018, 'plos', 'Correction: Lack of Ecological and Life History Context Can Create the Illusion of Social Interactions in Dictyostelium discoideum', 'PLOS Computational Biology Staff', 'Univ. Grenoble Alpes, CNRS, LPNC UMR 5105, F-38000 Grenoble, France.', 'France', 0, '-', 'Journal Article', '10.1371/journal.pcbi.1005850', '29360835', '[This corrects the article DOI: 10.1371/journal.pcbi.1005246.].'),
(88856, 2018, 'plos', 'Modeling visual-based pitch, lift and speed control strategies in hoverflies', 'Goulard, Roman|Vercher, Jean-Louis|Viollet, Stéphane', 'Aix Marseille Univ, CNRS, ISM, Marseille, France.|Aix Marseille Univ, CNRS, ISM, Marseille, France.|Aix Marseille Univ, CNRS, ISM, Marseille, France.', 'France|France|France', 2, 'Algorithms|Animals|Behavior, Animal|Computational Biology|Computer Simulation|Diptera|Female|Flight, Animal|Gravitation|Image Processing, Computer-Assisted|Male|Models, Biological|Optic Flow|Orientation|Vision, Ocular', 'Journal Article', '10.1371/journal.pcbi.1005894', '29361632', 'To avoid crashing onto the floor, a free falling fly needs to trigger its wingbeats quickly and control the orientation of its thrust accurately and swiftly to stabilize its pitch and hence its speed. Behavioural data have suggested that the vertical optic flow produced by the fall and crossing the visual field plays a key role in this anti-crash response. Free fall behavior analyses have also suggested that flying insect may not rely on graviception to stabilize their flight. Based on these two assumptions, we have developed a model which accounts for hoverflies´ position and pitch orientation recorded in 3D with a fast stereo camera during experimental free falls. Our dynamic model shows that optic flow-based control combined with closed-loop control of the pitch suffice to stabilize the flight properly. In addition, our model sheds a new light on the visual-based feedback control of fly´s pitch, lift and thrust. Since graviceptive cues are possibly not used by flying insects, the use of a vertical reference to control the pitch is discussed, based on the results obtained on a complete dynamic model of a virtual fly falling in a textured corridor. This model would provide a useful tool for understanding more clearly how insects may or not estimate their absolute attitude.'),
(88857, 2018, 'plos', 'Predicting peak spectral sensitivities of vertebrate cone visual pigments using atomistic molecular simulations', 'Patel, Jagdish Suresh|Brown, Celeste J|Ytreberg, F Marty|Stenkamp, Deborah L', 'Center for Modeling Complex Interactions, University of Idaho, Moscow, ID, United States of America.|Center for Modeling Complex Interactions, University of Idaho, Moscow, ID, United States of America.|Center for Modeling Complex Interactions, University of Idaho, Moscow, ID, United States of America.|Department of Biological Sciences, University of Idaho, Moscow, ID, United States of America.', 'United States|United States|United States|United States', 0, 'Amino Acid Sequence|Animals|Cichlids|Computer Simulation|Cone Opsins|Humans|Lipid Bilayers|Models, Molecular|Molecular Dynamics Simulation|Opsins|Oryzias|Phylogeny|Pigmentation|Poecilia|Retinal Cone Photoreceptor Cells|Retinal Pigments|Rod Opsins|Species Specificity|Vertebrates|Water|Zebrafish', 'Journal Article', '10.1371/journal.pcbi.1005974', '29364888', 'Vision is the dominant sensory modality in many organisms for foraging, predator avoidance, and social behaviors including mate selection. Vertebrate visual perception is initiated when light strikes rod and cone photoreceptors within the neural retina of the eye. Sensitivity to individual colors, i.e., peak spectral sensitivities (xcexbbmax) of visual pigments, are a function of the type of chromophore and the amino acid sequence of the associated opsin protein in the photoreceptors. Large differences in peak spectral sensitivities can result from minor differences in amino acid sequence of cone opsins. To determine how minor sequence differences could result in large spectral shifts we selected a spectrally-diverse group of 14 teleost Rh2 cone opsins for which sequences and xcexbbmax are experimentally known. Classical molecular dynamics simulations were carried out after embedding chromophore-associated homology structures within explicit bilayers and water. These simulations revealed structural features of visual pigments, particularly within the chromophore, that contributed to diverged spectral sensitivities. Statistical tests performed on all the observed structural parameters associated with the chromophore revealed that a two-term, first-order regression model was sufficient to accurately predict xcexbbmax over a range of 452-528 nm. The approach was accurate, efficient and simple in that site-by-site molecular modifications or complex quantum mechanics models were not required to predict xcexbbmax. These studies identify structural features associated with the chromophore that may explain diverged spectral sensitivities, and provide a platform for future, functionally predictive opsin modeling.'),
(88858, 2018, 'plos', 'Sequence determinants of protein phase behavior from a coarse-grained model', 'Dignon, Gregory L|Zheng, Wenwei|Kim, Young C|Best, Robert B|Mittal, Jeetain', 'Department of Chemical and Biomolecular Engineering, Lehigh University, Bethlehem, Pennsylvania, United States of America.|Laboratory of Chemical Physics, National Institute of Diabetes and Digestive and Kidney Diseases, National Institutes of Health, Bethesda, Maryland, United States of America.|Center for Materials Physics and Technology, Naval Research Laboratory, Washington, DC, United States of America.|Laboratory of Chemical Physics, National Institute of Diabetes and Digestive and Kidney Diseases, National Institutes of Health, Bethesda, Maryland, United States of America.|Department of Chemical and Biomolecular Engineering, Lehigh University, Bethlehem, Pennsylvania, United States of America.', 'United States|United States|United States|United States|United States', 14, 'Computational Biology|Computer Simulation|Hydrophobic and Hydrophilic Interactions|Mutation|Nuclear Proteins|Organelles|Polymers|Protein Folding|RNA-Binding Protein FUS|RNA-Binding Proteins|Sequence Analysis|Static Electricity|Temperature', 'Journal Article', '10.1371/journal.pcbi.1005941', '29364893', 'Membraneless organelles important to intracellular compartmentalization have recently been shown to comprise assemblies of proteins which undergo liquid-liquid phase separation (LLPS). However, many proteins involved in this phase separation are at least partially disordered. The molecular mechanism and the sequence determinants of this process are challenging to determine experimentally owing to the disordered nature of the assemblies, motivating the use of theoretical and simulation methods. This work advances a computational framework for conducting simulations of LLPS with residue-level detail, and allows for the determination of phase diagrams and coexistence densities of proteins in the two phases. The model includes a short-range contact potential as well as a simplified treatment of electrostatic energy. Interaction parameters are optimized against experimentally determined radius of gyration data for multiple unfolded or intrinsically disordered proteins (IDPs). These models are applied to two systems which undergo LLPS: the low complexity domain of the RNA-binding protein FUS and the DEAD-box helicase protein LAF-1. We develop a novel simulation method to determine thermodynamic phase diagrams as a function of the total protein concentration and temperature. We show that the model is capable of capturing qualitative changes in the phase diagram due to phosphomimetic mutations of FUS and to the presence or absence of the large folded domain in LAF-1. We also explore the effects of chain-length, or multivalency, on the phase diagram, and obtain results consistent with Flory-Huggins theory for polymers. Most importantly, the methodology presented here is flexible so that it can be easily extended to other pair potentials, be used with other enhanced sampling methods, and may incorporate additional features for biological systems of interest.'),
(88859, 2018, 'plos', 'The role of spatial heterogeneity in the evolution of local and global infections of viruses', 'Saeki, Koich|Sasaki, Akira', 'Department of Evolutionary Studies of Biosystems, SOKENDAI (The Graduate University for Advanced Studies), Hayama, Kanagawa, Japan.|Department of Evolutionary Studies of Biosystems, SOKENDAI (The Graduate University for Advanced Studies), Hayama, Kanagawa, Japan.', 'Japan|Japan', 3, 'Algorithms|Animals|Cell-Free System|Computer Simulation|Epidemics|Evolution, Molecular|Global Health|HIV Infections|Host-Parasite Interactions|Humans|Models, Biological|Models, Statistical|Monte Carlo Method|Probability|Time Factors|Virulence|Virus Diseases|Viruses', 'Journal Article', '10.1371/journal.pcbi.1005952', '29370194', 'Viruses have two modes spread in a host body, one is to release infectious particles from infected cells (global infection) and the other is to infect directly from an infected cell to an adjacent cell (local infection). Since the mode of spread affects the evolution of life history traits, such as virulence, it is important to reveal what level of global and local infection is selected. Previous studies of the evolution of global and local infection have paid little attention to its dependency on the measures of spatial configuration. Here we show the evolutionarily stable proportion of global and local infection, and how it depends on the distribution of target cells. Using an epidemic model on a regular lattice, we consider the infection dynamics by pair approximation and check the evolutionarily stable strategy. We also conduct the Monte-Carlo simulation to observe evolutionary dynamics. We show that a higher local infection is selected as target cells become clustered. Surprisingly, the selected strategy depends not only on the degree of clustering but also the abundance of target cells per se.'),
(88860, 2018, 'plos', 'MUMmer4: A fast and versatile genome alignment system', 'Marçais, Guillaume|Delcher, Arthur L|Phillippy, Adam M|Coston, Rachel|Salzberg, Steven L|Zimin, Aleksey', 'Institute for Physical Science and Technology, University of Maryland, College Park, Maryland, United States of America.|Center for Computational Biology, Johns Hopkins School of Medicine, Baltimore, Maryland, United States of America.|National Human Genome Research Institute, Bethesda, Maryland, United States of America.|Center for Computational Biology, Johns Hopkins School of Medicine, Baltimore, Maryland, United States of America.|Center for Computational Biology, Johns Hopkins School of Medicine, Baltimore, Maryland, United States of America.|Institute for Physical Science and Technology, University of Maryland, College Park, Maryland, United States of America.', 'United States|United States|United States|United States|United States|United States', 151, 'Algorithms|Animals|Arabidopsis|Computational Biology|Genome, Human|Genome, Plant|Genomics|Humans|Models, Theoretical|Pan troglodytes|Polymorphism, Single Nucleotide|Programming Languages|Sequence Alignment|Sequence Analysis, DNA|Sequence Analysis, Protein|Software', 'Journal Article', '10.1371/journal.pcbi.1005944', '29373581', 'The MUMmer system and the genome sequence aligner nucmer included within it are among the most widely used alignment packages in genomics. Since the last major release of MUMmer version 3 in 2004, it has been applied to many types of problems including aligning whole genome sequences, aligning reads to a reference genome, and comparing different assemblies of the same genome. Despite its broad utility, MUMmer3 has limitations that can make it difficult to use for large genomes and for the very large sequence data sets that are common today. In this paper we describe MUMmer4, a substantially improved version of MUMmer that addresses genome size constraints by changing the 32-bit suffix tree data structure at the core of MUMmer to a 48-bit suffix array, and that offers improved speed through parallel processing of input query sequences. With a theoretical limit on the input size of 141Tbp, MUMmer4 can now work with input sequences of any biologically realistic length. We show that as a result of these enhancements, the nucmer program in MUMmer4 is easily able to handle alignments of large genomes, we illustrate this with an alignment of the human and chimpanzee genomes, which allows us to compute that the two species are 98% identical across 96% of their length. With the enhancements described here, MUMmer4 can also be used to efficiently align reads to reference genomes, although it is less sensitive and accurate than the dedicated read aligners. The nucmer aligner in MUMmer4 can now be called from scripting languages such as Perl, Python and Ruby. These improvements make MUMer4 one the most versatile genome alignment packages available.'),
(88861, 2018, 'plos', 'Identification of allosteric inhibitors of the ecto-5-nucleotidase (CD73) targeting the dimer interface', 'Rahimova, Rahila|Fontanel, Simon|Lionne, Corinne|Jordheim, Lars Peter|Peyrottes, Suzanne|Chaloin, Laurent', 'Institut de Recherche en Infectiologie de Montpellier (IRIM), Univ. Montpellier, CNRS, Montpellier, France, Institut de Biologie Computationnelle (IBC), Montpellier, France.|Institut de Génomique Fonctionnelle (IGF), Univ. Montpellier, CNRS, Montpellier, France.|Centre de Biologie Structurale (CBS), Univ. Montpellier, CNRS, INSERM, Montpellier, France.|Centre Léon Bérard (CLB), Centre de Recherche en Cancérologie de Lyon (CRCL), Univ. de Lyon, INSERM, CNRS, Lyon, France.|Institut des Biomolécules Max-Mousseron (IBMM), CNRS, Univ. Montpellier, ENSCM, Montpellier, France.|Institut de Recherche en Infectiologie de Montpellier (IRIM), Univ. Montpellier, CNRS, Montpellier, France, Institut de Biologie Computationnelle (IBC), Montpellier, France.', 'France|France|France|France|France|France', 0, '5-Nucleotidase|Adenosine|Allosteric Site|Antibodies, Monoclonal|Antineoplastic Agents|Cell Proliferation|Computational Biology|Crystallography, X-Ray|GPI-Linked Proteins|Humans|Immune System|Inflammation|Kinetics|Magnetic Resonance Spectroscopy|Models, Statistical|Molecular Dynamics Simulation|Phenotype|Protein Binding|Protein Conformation|Protein Multimerization|Recombinant Proteins|Software', 'Journal Article', '10.1371/journal.pcbi.1005943', '29377887', 'The ecto-5-nucleotidase CD73 plays an important role in the production of immune-suppressive adenosine in tumor micro-environment, and has become a validated drug target in oncology. Indeed, the anticancer immune response involves extracellular ATP to block cell proliferation through T-cell activation. However, in the tumor micro-environment, two extracellular membrane-bound enzymes (CD39 and CD73) are overexpressed and hydrolyze efficiently ATP into AMP then further into immune-suppressive adenosine. To circumvent the impact of CD73-generated adenosine, we applied an original bioinformatics approach to identify new allosteric inhibitors targeting the dimerization interface of CD73, which should impair the large dynamic motions required for its enzymatic function. Several hit compounds issued from virtual screening campaigns showed a potent inhibition of recombinant CD73 with inhibition constants in the low micromolar range and exhibited a non-competitive inhibition mode. The structure-activity relationships studies indicated that several amino acid residues (D366, H456, K471, Y484 and E543 for polar interactions and G453-454, I455, H456, L475, V542 and G544 for hydrophobic contacts) located at the dimerization interface are involved in the tight binding of hit compounds and likely contributed for their inhibitory activity. Overall, the gathered information will guide the upcoming lead optimization phase that may lead to potent and selective CD73 inhibitors, able to restore the anticancer immune response.'),
(88862, 2018, 'plos', 'Biophysical network modeling of the dLGN circuit: Effects of cortical feedback on spatial response properties of relay cells', 'Martínez-Cañada, Pablo|Mobarhan, Milad Hobbi|Halnes, Geir|Fyhn, Marianne|Morillas, Christian|Pelayo, Francisco|Einevoll, Gaute T', 'Department of Computer Architecture and Technology, University of Granada, Granada, Spain.|Center for Integrative Neuroplasticity (CINPLA), University of Oslo, Oslo, Norway.|Center for Integrative Neuroplasticity (CINPLA), University of Oslo, Oslo, Norway.|Center for Integrative Neuroplasticity (CINPLA), University of Oslo, Oslo, Norway.|Department of Computer Architecture and Technology, University of Granada, Granada, Spain.|Department of Computer Architecture and Technology, University of Granada, Granada, Spain.|Center for Integrative Neuroplasticity (CINPLA), University of Oslo, Oslo, Norway.', 'Spain|Norway|Norway|Norway|Spain|Spain|Norway', 2, 'Animals|Computer Simulation|Feedback|Geniculate Bodies|Humans|Interneurons|Membrane Potentials|Models, Neurological|Neurons|Normal Distribution|Orientation|Retina|Retinal Ganglion Cells|Synapses|Synaptic Transmission|Thalamic Nuclei|Visual Cortex|Visual Pathways', 'Journal Article', '10.1371/journal.pcbi.1005930', '29377888', 'Despite half-a-century of research since the seminal work of Hubel and Wiesel, the role of the dorsal lateral geniculate nucleus (dLGN) in shaping the visual signals is not properly understood. Placed on route from retina to primary visual cortex in the early visual pathway, a striking feature of the dLGN circuit is that both the relay cells (RCs) and interneurons (INs) not only receive feedforward input from retinal ganglion cells, but also a prominent feedback from cells in layer 6 of visual cortex. This feedback has been proposed to affect synchronicity and other temporal properties of the RC firing. It has also been seen to affect spatial properties such as the center-surround antagonism of thalamic receptive fields, i.e., the suppression of the response to very large stimuli compared to smaller, more optimal stimuli. Here we explore the spatial effects of cortical feedback on the RC response by means of a a comprehensive network model with biophysically detailed, single-compartment and multicompartment neuron models of RCs, INs and a population of orientation-selective layer 6 simple cells, consisting of pyramidal cells (PY). We have considered two different arrangements of synaptic feedback from the ON and OFF zones in the visual cortex to the dLGN: phase-reversed (push-pull) and phase-matched (push-push), as well as different spatial extents of the corticothalamic projection pattern. Our simulation results support that a phase-reversed arrangement provides a more effective way for cortical feedback to provide the increased center-surround antagonism seen in experiments both for flashing spots and, even more prominently, for patch gratings. This implies that ON-center RCs receive direct excitation from OFF-dominated cortical cells and indirect inhibitory feedback from ON-dominated cortical cells. The increased center-surround antagonism in the model is accompanied by spatial focusing, i.e., the maximum RC response occurs for smaller stimuli when feedback is present.'),
(88863, 2018, 'plos', 'The extent of ribosome queuing in budding yeast', 'Diament, Alon|Feldman, Anna|Schochet, Elisheva|Kupiec, Martin|Arava, Yoav|Tuller, Tamir', 'Biomedical Engineering Dept., Tel Aviv University, Tel Aviv, Israel.|Biomedical Engineering Dept., Tel Aviv University, Tel Aviv, Israel.|The Blavatnik School of Computer Science, Tel Aviv University, Tel Aviv, Israel.|Dept. of Molecular Microbiology and Biotechnology, Tel Aviv University, Tel Aviv, Israel.|Biology Dept., Technion-Israel Institute of Technology, Haifa, Israel.|Biomedical Engineering Dept., Tel Aviv University, Tel Aviv, Israel.', 'Israel|Israel|Israel|Israel|Israel|Israel', 0, 'Calibration|Codon|Computational Biology|Computer Simulation|Gene Expression Regulation|High-Throughput Nucleotide Sequencing|Models, Theoretical|Normal Distribution|Open Reading Frames|Probability|Protein Biosynthesis|RNA, Messenger|RNA, Transfer|Ribosomes|Saccharomyces cerevisiae|Sequence Analysis, RNA|Software|Transcriptome', 'Journal Article', '10.1371/journal.pcbi.1005951', '29377894', 'Ribosome queuing is a fundamental phenomenon suggested to be related to topics such as genome evolution, synthetic biology, gene expression regulation, intracellular biophysics, and more. However, this phenomenon hasnt been quantified yet at a genomic level. Nevertheless, methodologies for studying translation (e.g. ribosome footprints) are usually calibrated to capture only single ribosome protected footprints (mRPFs) and thus limited in their ability to detect ribosome queuing. On the other hand, most of the models in the field assume and analyze a certain level of queuing. Here we present an experimental-computational approach for studying ribosome queuing based on sequencing of RNA footprints extracted from pairs of ribosomes (dRPFs) using a modified ribosome profiling protocol. We combine our approach with traditional ribosome profiling to generate a detailed profile of ribosome traffic. The data are analyzed using computational models of translation dynamics. The approach was implemented on the Saccharomyces cerevisiae transcriptome. Our data shows that ribosome queuing is more frequent than previously thought: the measured ratio of ribosomes within dRPFs to mRPFs is 0.2-0.35, suggesting that at least one to five translating ribosomes is in a traffic jam, these queued ribosomes cannot be captured by traditional methods. We found that specific regions are enriched with queued ribosomes, such as the 5-end of ORFs, and regions upstream to mRPF peaks, among others. While queuing is related to higher density of ribosomes on the transcript (characteristic of highly translated genes), we report cases where traffic jams are relatively more severe in lowly expressed genes and possibly even selected for. In addition, our analysis demonstrates that higher adaptation of the coding region to the intracellular tRNA levels is associated with lower queuing levels. Our analysis also suggests that the Saccharomyces cerevisiae transcriptome undergoes selection for eliminating traffic jams. Thus, our proposed approach is an essential tool for high resolution analysis of ribosome traffic during mRNA translation and understanding its evolution.'),
(88864, 2018, 'plos', 'Reactome graph database: Efficient access to complex pathway data', 'Fabregat, Antonio|Korninger, Florian|Viteri, Guilherme|Sidiropoulos, Konstantinos|Marin-Garcia, Pablo|Ping, Peipei|Wu, Guanming|Stein, Lincoln|DEustachio, Peter|Hermjakob, Henning', 'European Molecular Biology Laboratory, European Bioinformatics Institute (EMBL-EBI), Wellcome Genome Campus, Hinxton, United Kingdom.|European Molecular Biology Laboratory, European Bioinformatics Institute (EMBL-EBI), Wellcome Genome Campus, Hinxton, United Kingdom.|European Molecular Biology Laboratory, European Bioinformatics Institute (EMBL-EBI), Wellcome Genome Campus, Hinxton, United Kingdom.|European Molecular Biology Laboratory, European Bioinformatics Institute (EMBL-EBI), Wellcome Genome Campus, Hinxton, United Kingdom.|Fundación Investigación INCLIVA, Universitat de València, Valencia, Spain.|NIH BD2K Center of Excellence and Department of Physiology, Medicine and Bioinformatics, University of California, Los Angeles, California, United States of America.|Oregon Health and Science University, Portland, Oregon, United States of America.|Ontario Institute for Cancer Research, Toronto, Canada.|NYU Langone Medical Center, New York, New York, United States of America.|European Molecular Biology Laboratory, European Bioinformatics Institute (EMBL-EBI), Wellcome Genome Campus, Hinxton, United Kingdom.', 'United Kingdom|United Kingdom|United Kingdom|United Kingdom|Spain|United States|United States|Canada', 40, 'Computational Biology|Computer Graphics|Databases, Factual|Humans|Information Storage and Retrieval|Internet|Knowledge Bases|Software|Systems Biology|User-Computer Interface', 'Journal Article', '10.1371/journal.pcbi.1005968', '29377902', 'Reactome is a free, open-source, open-data, curated and peer-reviewed knowledgebase of biomolecular pathways. One of its main priorities is to provide easy and efficient access to its high quality curated data. At present, biological pathway databases typically store their contents in relational databases. This limits access efficiency because there are performance issues associated with queries traversing highly interconnected data. The same data in a graph database can be queried more efficiently. Here we present the rationale behind the adoption of a graph database (Neo4j) as well as the new ContentService (REST API) that provides access to these data. The Neo4j graph database and its query language, Cypher, provide efficient access to the complex Reactome data model, facilitating easy traversal and knowledge discovery. The adoption of this technology greatly improved query efficiency, reducing the average query time by 93%. The web service built on top of the graph database provides programmatic access to Reactome data by object oriented queries, but also supports more complex queries that take advantage of the new underlying graph-based data storage. By adopting graph database technology we are providing a high performance pathway data resource to the community. The Reactome graph database use case shows the power of NoSQL database engines for complex biological data types.'),
(88865, 2018, 'plos', 'Metabolic plasticity in synthetic lethal mutants: Viability at higher cost', 'Massucci, Francesco Alessandro|Sagués, Francesc|Serrano, M Ángeles', 'Departament de Física de la Matèria Condensada, Universitat de Barcelona, Martí i Franquès 1, Barcelona, Spain.|Departament de Química Física, Universitat de Barcelona, Martí i Franquès 1, Barcelona, Spain.|Departament de Física de la Matèria Condensada, Universitat de Barcelona, Martí i Franquès 1, Barcelona, Spain.', 'Spain|Spain|Spain', 1, 'Cell Membrane|Cluster Analysis|Computational Biology|Culture Media|Escherichia coli|Genome|Genome, Bacterial|Glucose|Metabolic Networks and Pathways|Models, Theoretical|Oxygen Consumption|Salmonella enterica|Shigella sonnei|Synthetic Lethal Mutations', 'Journal Article', '10.1371/journal.pcbi.1005949', '29381693', 'The most frequent form of pairwise synthetic lethality (SL) in metabolic networks is known as plasticity synthetic lethality. It occurs when the simultaneous inhibition of paired functional and silent metabolic reactions or genes is lethal, while the default of the functional partner is backed up by the activation of the silent one. Using computational techniques on bacterial genome-scale metabolic reconstructions, we found that the failure of the functional partner triggers a critical reorganization of fluxes to ensure viability in the mutant which not only affects the SL pair but a significant fraction of other interconnected reactions, forming what we call a SL cluster. Interestingly, SL clusters show a strong entanglement both in terms of reactions and genes. This strong overlap mitigates the acquired vulnerabilities and increased structural and functional costs that pay for the robustness provided by essential plasticity. Finally, the participation of coessential reactions and genes in different SL clusters is very heterogeneous and those at the intersection of many SL clusters could serve as supertargets for more efficient drug action in the treatment of complex diseases and to elucidate improved strategies directed to reduce undesired resistance to chemicals in pathogens.'),
(88866, 2018, 'plos', 'SozRank: A new approach for localizing the epileptic seizure onset zone', 'Murin, Yonathan|Kim, Jeremy|Parvizi, Josef|Goldsmith, Andrea', 'Department of Electrical Engineering, Stanford University, Stanford, CA, United States of America.|Department of Electrical Engineering, Stanford University, Stanford, CA, United States of America.|Department of Neurology & Neurological Sciences, Stanford University, Stanford, CA, United States of America.|Department of Electrical Engineering, Stanford University, Stanford, CA, United States of America.', 'United States|United States|United States|United States', 0, 'Algorithms|Anticonvulsants|Brain|Computational Biology|Computer Simulation|Electrocorticography|Electroencephalography|Epilepsy|False Positive Reactions|Humans|Models, Neurological|Models, Statistical|Oscillometry|Probability|Seizures|Signal Processing, Computer-Assisted|Software', 'Journal Article', '10.1371/journal.pcbi.1005953', '29381703', 'Epilepsy is one of the most common neurological disorders affecting about 1% of the world population. For patients with focal seizures that cannot be treated with antiepileptic drugs, the common treatment is a surgical procedure for removal of the seizure onset zone (SOZ). In this work we introduce an algorithm for automatic localization of the seizure onset zone (SOZ) in epileptic patients based on electrocorticography (ECoG) recordings. The proposed algorithm builds upon the hypothesis that the abnormal excessive (or synchronous) neuronal activity in the brain leading to seizures starts in the SOZ and then spreads to other areas in the brain. Thus, when this abnormal activity starts, signals recorded at electrodes close to the SOZ should have a relatively large causal influence on the rest of the recorded signals. The SOZ localization is executed in two steps. First, the algorithm represents the set of electrodes using a directed graph in which nodes correspond to recording electrodes and the edges weights quantify the pair-wise causal influence between the recorded signals. Then, the algorithm infers the SOZ from the estimated graph using a variant of the PageRank algorithm followed by a novel post-processing phase. Inference results for 19 patients show a close match between the SOZ inferred by the proposed approach and the SOZ estimated by expert neurologists (success rate of 17 out of 19).'),
(88867, 2018, 'plos', 'Predicting pathogenicity behavior in Escherichia coli population through a state dependent model and TRS profiling', 'Bartoszek, Krzysztof|Majchrzak, Marta|Sakowski, Sebastian|Kubiak-Szeligowska, Anna B|Kaj, Ingemar|Parniewski, Pawel', 'Department of Mathematics, Uppsala University, Uppsala, Sweden.|Institute of Medical Biology, Polish Academy of Sciences, Lodz, Poland.|Faculty of Mathematics and Computer Science, University of Lodz, Lodz, Poland.|Institute of Medical Biology, Polish Academy of Sciences, Lodz, Poland.|Department of Mathematics, Uppsala University, Uppsala, Sweden.|Institute of Medical Biology, Polish Academy of Sciences, Lodz, Poland.', 'Sweden|Poland|Poland|Poland|Sweden|Poland', 0, 'Computational Biology|Computer Simulation|Diarrhea|Escherichia coli|Escherichia coli Infections|Extinction, Biological|Gene Expression Regulation, Bacterial|Genetic Speciation|Humans|Microsatellite Repeats|Models, Biological|Models, Genetic|Phenotype|Phylogeny|Polymerase Chain Reaction|Probability|Software|Trinucleotide Repeats|Urinary Tract Infections|Virulence|Virulence Factors', 'Journal Article', '10.1371/journal.pcbi.1005931', '29385125', 'The Binary State Speciation and Extinction (BiSSE) model is a branching process based model that allows the diversification rates to be controlled by a binary trait. We develop a general approach, based on the BiSSE model, for predicting pathogenicity in bacterial populations from microsatellites profiling data. A comprehensive approach for predicting pathogenicity in E. coli populations is proposed using the state-dependent branching process model combined with microsatellites TRS-PCR profiling. Additionally, we have evaluated the possibility of using the BiSSE model for estimating parameters from genetic data. We analyzed a real dataset (from 251 E. coli strains) and confirmed previous biological observations demonstrating a prevalence of some virulence traits in specific bacterial sub-groups. The method may be used to predict pathogenicity of other bacterial taxa.'),
(88868, 2018, 'plos', 'GSimp: A Gibbs sampler based left-censored missing value imputation approach for metabolomics studies', 'Wei, Runmin|Wang, Jingye|Jia, Erik|Chen, Tianlu|Ni, Yan|Jia, Wei', 'Metabolomics Shared Resource, University of Hawaii Cancer Center, Honolulu, Hawaii, United States of America.|Metabolomics Shared Resource, University of Hawaii Cancer Center, Honolulu, Hawaii, United States of America.|High School, Punahou School, Honolulu, Hawaii, United States of America.|Shanghai Key Laboratory of Diabetes Mellitus and Center for Translational Medicine, Shanghai Jiao Tong University Affiliated Sixth Peoples Hospital, Shanghai, China.|Metabolomics Shared Resource, University of Hawaii Cancer Center, Honolulu, Hawaii, United States of America.|Metabolomics Shared Resource, University of Hawaii Cancer Center, Honolulu, Hawaii, United States of America.', 'United States|United States|United States|China|United States|United States', 0, 'Algorithms|Bile Acids and Salts|Computational Biology|Computer Simulation|Data Interpretation, Statistical|Databases, Factual|Fatty Acids, Nonesterified|Humans|Limit of Detection|Mass Spectrometry|Metabolomics|Models, Statistical|Multivariate Analysis|Principal Component Analysis|Probability|Programming Languages|Software|Stochastic Processes', 'Journal Article', '10.1371/journal.pcbi.1005973', '29385130', 'Left-censored missing values commonly exist in targeted metabolomics datasets and can be considered as missing not at random (MNAR). Improper data processing procedures for missing values will cause adverse impacts on subsequent statistical analyses. However, few imputation methods have been developed and applied to the situation of MNAR in the field of metabolomics. Thus, a practical left-censored missing value imputation method is urgently needed. We developed an iterative Gibbs sampler based left-censored missing value imputation approach (GSimp). We compared GSimp with other three imputation methods on two real-world targeted metabolomics datasets and one simulation dataset using our imputation evaluation pipeline. The results show that GSimp outperforms other imputation methods in terms of imputation accuracy, observation distribution, univariate and multivariate analyses, and statistical sensitivity. Additionally, a parallel version of GSimp was developed for dealing with large scale metabolomics datasets. The R code for GSimp, evaluation pipeline, tutorial, real-world and simulated targeted metabolomics datasets are available at: https://github.com/WandeRum/GSimp.');
INSERT INTO `papers` (`id`, `ano`, `journal`, `titulo`, `autores`, `afiliacao`, `pais`, `citacoes`, `palavra_chave`, `categorias`, `doi`, `pubmed`, `abstract`) VALUES
(88869, 2018, 'plos', 'Evolutionary analysis of polyproline motifs in Escherichia coli reveals their regulatory role in translation', 'Qi, Fei|Motz, Magdalena|Jung, Kirsten|Lassak, Jürgen|Frishman, Dmitrij', 'Department of Bioinformatics, Wissenschaftzentrum Weihenstephan, Technische Universität München, Freising, Germany.|Center for Integrated Protein Science Munich, Ludwig-Maximilians-Universität München, Munich, Germany.|Center for Integrated Protein Science Munich, Ludwig-Maximilians-Universität München, Munich, Germany.|Center for Integrated Protein Science Munich, Ludwig-Maximilians-Universität München, Munich, Germany.|Department of Bioinformatics, Wissenschaftzentrum Weihenstephan, Technische Universität München, Freising, Germany.', 'Germany|Germany|Germany|Germany|Germany', 11, 'Amino Acid Motifs|Escherichia coli|Escherichia coli Proteins|Evolution, Molecular|Peptide Chain Elongation, Translational|Peptide Elongation Factors|Peptides|Phylogeny|Protein Biosynthesis|Protein Folding|Proteome|Proteomics|Ribosomes', 'Journal Article', '10.1371/journal.pcbi.1005987', '29389943', 'Translation of consecutive prolines causes ribosome stalling, which is alleviated but cannot be fully compensated by the elongation factor P. However, the presence of polyproline motifs in about one third of the E. coli proteins underlines their potential functional importance, which remains largely unexplored. We conducted an evolutionary analysis of polyproline motifs in the proteomes of 43 E. coli strains and found evidence of evolutionary selection against translational stalling, which is especially pronounced in proteins with high translational efficiency. Against the overall trend of polyproline motif loss in evolution, we observed their enrichment in the vicinity of translational start sites, in the inter-domain regions of multi-domain proteins, and downstream of transmembrane helices. Our analysis demonstrates that the time gain caused by ribosome pausing at polyproline motifs might be advantageous in protein regions bracketing domains and transmembrane helices. Polyproline motifs might therefore be crucial for co-translational folding and membrane insertion.'),
(88870, 2018, 'plos', 'Ten simple rules for writing a popular science book', 'Kucharski, Adam J', 'Centre for the Mathematical Modelling of Infectious Disease, London School of Hygiene and Tropical Medicine, London, United Kingdom.', 'United Kingdom', 0, 'Books|Communication|Science|Writing', 'Editorial', '10.1371/journal.pcbi.1005808', '29389987', '-'),
(88871, 2018, 'plos', 'The development and application of bioinformatics core competencies to improve bioinformatics training and education', 'Mulder, Nicola|Schwartz, Russell|Brazas, Michelle D|Brooksbank, Cath|Gaeta, Bruno|Morgan, Sarah L|Pauley, Mark A|Rosenwald, Anne|Rustici, Gabriella|Sierk, Michael|Warnow, Tandy|Welch, Lonnie', 'Computational Biology Division, Department of Integrative Biomedical Sciences, Institute of Infectious Disease and Molecular Medicine, University of Cape Town, Cape Town, South Africa.|Department of Biological Sciences and Computational Biology Department, Carnegie Mellon University, Pittsburgh, Pennsylvania, United States of America.|Ontario Institute for Cancer Research, Toronto, Canada.|EMBL-EBI, Wellcome Genome Campus, Hinxton, Cambridge, United Kingdom.|School of Computer Science and Engineering, University of New South Wales, Sydney, Australia.|EMBL-EBI, Wellcome Genome Campus, Hinxton, Cambridge, United Kingdom.|School of Interdisciplinary Informatics, University of Nebraska at Omaha, Omaha, Nebraska, United States of America.|Department of Biology, Georgetown University, Washington, DC, United States of America.|Department of Genetics, University of Cambridge, Cambridge, United Kingdom.|Saint Vincent College, Latrobe, Pennsylvania, United States of America.|Department of Computer Science and Department of Bioengineering, University of Illinois, Urbana-Champaign, Champaign, United States of America.|School of Electrical Engineering and Computer Science, Ohio University, Athens, Ohio, United States of America.', 'South Africa|United States|Canada|United Kingdom|Australia|United Kingdom|United States|United State', 16, 'Advisory Committees|Africa|Algorithms|Computational Biology|Curriculum|Education, Graduate|Genetic Predisposition to Disease|Illinois|New South Wales|Ohio|Pennsylvania|Software|Surveys and Questionnaires|Systems Biology|United Kingdom|Universities', 'Journal Article', '10.1371/journal.pcbi.1005772', '29390004', 'Bioinformatics is recognized as part of the essential knowledge base of numerous career paths in biomedical research and healthcare. However, there is little agreement in the field over what that knowledge entails or how best to provide it. These disagreements are compounded by the wide range of populations in need of bioinformatics training, with divergent prior backgrounds and intended application areas. The Curriculum Task Force of the International Society of Computational Biology (ISCB) Education Committee has sought to provide a framework for training needs and curricula in terms of a set of bioinformatics core competencies that cut across many user personas and training programs. The initial competencies developed based on surveys of employers and training programs have since been refined through a multiyear process of community engagement. This report describes the current status of the competencies and presents a series of use cases illustrating how they are being applied in diverse training contexts. These use cases are intended to demonstrate how others can make use of the competencies and engage in the process of their continuing refinement and application. The report concludes with a consideration of remaining challenges and future plans.'),
(88872, 2018, 'plos', 'Simulation enabled search for explanatory mechanisms of the fracture healing process', 'Kennedy, Ryan C|Marmor, Meir|Marcucio, Ralph|Hunt, C Anthony', 'Department of Bioengineering and Therapeutic Sciences, University of California, San Francisco, California, United States of America.|Department of Orthopaedic Surgery, San Francisco General Hospital Orthopaedic Trauma Institute, University of California, San Francisco, California, United States of America.|Department of Orthopaedic Surgery, San Francisco General Hospital Orthopaedic Trauma Institute, University of California, San Francisco, California, United States of America.|Department of Bioengineering and Therapeutic Sciences, University of California, San Francisco, California, United States of America.', 'United States|United States|United States|United States', 1, 'Animals|Biomechanical Phenomena|Biomimetics|Bony Callus|Computer Simulation|Fracture Healing|Fractures, Bone|Humans|Mice|Models, Biological|Monte Carlo Method|Software|Tibia', 'Journal Article', '10.1371/journal.pcbi.1005980', '29394245', 'A significant portion of bone fractures fail to heal properly, increasing healthcare costs. Advances in fracture management have slowed because translation barriers have limited generation of mechanism-based explanations for the healing process. When uncertainties are numerous, analogical modeling can be an effective strategy for developing plausible explanations of complex phenomena. We demonstrate the feasibility of engineering analogical models in software to facilitate discovery of biomimetic explanations for how fracture healing may progress. Concrete analogical models-Callus Analogs-were created using the MASON simulation toolkit. We designated a Target Region initial state within a characteristic tissue section of mouse tibia fracture at day-7 and posited a corresponding day-10 Target Region final state. The goal was to discover a coarse-grain analog mechanism that would enable the discretized initial state to transform itself into the corresponding Target Region final state, thereby providing an alternative way to study the healing process. One of nine quasi-autonomous Tissue Unit types is assigned to each grid space, which maps to an 80xc3x9780 xcexbcm region of the tissue section. All Tissue Units have an opportunity each time step to act based on individualized logic, probabilities, and information about adjacent neighbors. Action causes transition from one Tissue Unit type to another, and simulation through several thousand time steps generates a coarse-grain analog-a theory-of the healing process. We prespecified a minimum measure of success: simulated and actual Target Region states achieve xe2x89xa5 70% Similarity. We used an iterative refinement protocol to explore many combinations of Tissue Unit logic and action constraints. Workflows progressed through four stages of analog mechanisms. Similarities of 73-90% were achieved for Mechanisms 2-4. The range of Upper-Level similarities increased to 83-94% when we allowed for uncertainty about two Tissue Unit designations. We have demonstrated how Callus Analog experiments provide domain experts with a fresh medium and tools for thinking about and understanding the fracture healing process.'),
(88873, 2018, 'plos', 'A computational framework for cortical microtubule dynamics in realistically shaped plant cells', 'Chakrabortty, Bandan|Blilou, Ikram|Scheres, Ben|Mulder, Bela M', 'Plant Developmental Biology, Wageningen University, Wageningen, The Netherlands.|Laboratory of plant cell and developmental biology, King Abdullah University of Science and Technology, Thuwal, Kingdom of Saudi Arabia.|Plant Developmental Biology, Wageningen University, Wageningen, The Netherlands.|Department of Living Matter, Institute AMOLF, Amsterdam, The Netherlands.', 'Netherlands|Saudi Arabia|Netherlands|Netherlands', 17, 'Algorithms|Anisotropy|Arabidopsis|Arabidopsis Proteins|Cell Membrane|Computational Biology|Computer Simulation|Hedera|Microscopy, Confocal|Microtubules|Models, Biological|Normal Distribution|Plant Cells|Plant Leaves|Probability|Software|Stochastic Processes|Tobacco|Tubulin', 'Journal Article', '10.1371/journal.pcbi.1005959', '29394250', 'Plant morphogenesis is strongly dependent on the directional growth and the subsequent oriented division of individual cells. It has been shown that the plant cortical microtubule array plays a key role in controlling both these processes. This ordered structure emerges as the collective result of stochastic interactions between large numbers of dynamic microtubules. To elucidate this complex self-organization process a number of analytical and computational approaches to study the dynamics of cortical microtubules have been proposed. To date, however, these models have been restricted to two dimensional planes or geometrically simple surfaces in three dimensions, which strongly limits their applicability as plant cells display a wide variety of shapes. This limitation is even more acute, as both local as well as global geometrical features of cells are expected to influence the overall organization of the array. Here we describe a framework for efficiently simulating microtubule dynamics on triangulated approximations of arbitrary three dimensional surfaces. This allows the study of microtubule array organization on realistic cell surfaces obtained by segmentation of microscopic images. We validate the framework against expected or known results for the spherical and cubical geometry. We then use it to systematically study the individual contributions of global geometry, cell-edge induced catastrophes and cell-face induced stability to array organization in a cuboidal geometry. Finally, we apply our framework to analyze the highly non-trivial geometry of leaf pavement cells of Arabidopsis thaliana, Nicotiana benthamiana and Hedera helix. We show that our simulations can predict multiple features of the microtubule array structure in these cells, revealing, among others, strong constraints on the orientation of division planes.'),
(88874, 2018, 'plos', 'A maximum-entropy model for predicting chromatin contacts', 'Farré, Pau|Emberly, Eldon', 'Department of Physics, Simon Fraser University, Burnaby, BC V5A1S6, Canada.|Department of Physics, Simon Fraser University, Burnaby, BC V5A1S6, Canada.', 'Canada|Canada', 2, 'Algorithms|Animals|Bayes Theorem|Chromatin|Cluster Analysis|DNA|Drosophila melanogaster|Gene Expression Profiling|Genome|Models, Statistical|Mutation|Nucleic Acid Conformation|Polymers|Probability|Protein Binding|Protein Folding|Proteins', 'Journal Article', '10.1371/journal.pcbi.1005956', '29401453', 'The packaging of DNA inside a nucleus shows complex structure stabilized by a host of DNA-bound factors. Both the distribution of these factors and the contacts between different genomic locations of the DNA can now be measured on a genome-wide scale. This has advanced the development of models aimed at predicting the conformation of DNA given only the locations of bound factors-the chromatin folding problem. Here we present a maximum-entropy model that is able to predict a contact map representation of structure given a sequence of bound factors. Non-local effects due to the sequence neighborhood around contacting sites are found to be important for making accurate predictions. Lastly, we show that the model can be used to infer a sequence of bound factors given only a measurement of structure. This opens up the possibility for efficiently predicting sequence regions that may play a role in generating cell-type specific structural differences.'),
(88875, 2018, 'plos', 'Biophysical attributes that affect CaMKII activation deduced with a novel spatial stochastic simulation approach', 'Li, Ximing|Holmes, William R', 'Department of Biological Sciences, Neuroscience Program, Ohio University, Athens, Ohio, United States of America.|Department of Biological Sciences, Neuroscience Program, Ohio University, Athens, Ohio, United States of America.', 'United States|United States', 5, 'Algorithms|Animals|Binding Sites|Biophysics|Calcium|Calcium-Calmodulin-Dependent Protein Kinase Type 2|Calmodulin|Computer Simulation|Cytoplasm|Dendritic Spines|Enzyme Activation|Humans|Models, Neurological|Neurons|Phosphorylation|Probability|Protein Binding|Signal Transduction|Stochastic Processes|Synapses', 'Journal Article', '10.1371/journal.pcbi.1005946', '29401454', 'Calcium/calmodulin-dependent protein kinase II (CaMKII) holoenzymes play a critical role in decoding Ca2+ signals in neurons. Understanding how this occurs has been the focus of numerous studies including many that use models. However, CaMKII is notoriously difficult to simulate in detail because of its multi-subunit nature, which causes a combinatorial explosion in the number of species that must be modeled. To study the Ca2+-calmodulin-CaMKII reaction network with detailed kinetics while including the effect of diffusion, we have customized an existing stochastic particle-based simulator, Smoldyn, to manage the problem of combinatorial explosion. With this new method, spatial and temporal aspects of the signaling network can be studied without compromising biochemical details. We used this new method to examine how calmodulin molecules, both partially loaded and fully loaded with Ca2+, choose pathways to interact with and activate CaMKII under various Ca2+ input conditions. We found that the dependence of CaMKII phosphorylation on Ca2+ signal frequency is intrinsic to the network kinetics and the activation pattern can be modulated by the relative amount of Ca2+ to calmodulin and by the rate of Ca2+ diffusion. Depending on whether Ca2+ influx is saturating or not, calmodulin molecules could choose different routes within the network to activate CaMKII subunits, resulting in different frequency dependence patterns. In addition, the size of the holoenzyme produces a subtle effect on CaMKII activation. The more extended the subunits are organized, the easier for calmodulin molecules to access and activate the subunits. The findings suggest that particular intracellular environmental factors such as crowding and calmodulin availability can play an important role in decoding Ca2+ signals and can give rise to distinct CaMKII activation patterns in dendritic spines, Ca2+ channel nanodomains and cytoplasm.'),
(88876, 2018, 'plos', 'Membrane perturbing properties of toxin mycolactone from Mycobacterium ulcerans', 'López, Cesar A|Unkefer, Clifford J|Swanson, Basil I|Swanson, Jessica M J|Gnanakaran, S', 'Theoretical Biology and Biophysics Group, Los Alamos National Laboratory, New Mexico, United States of America.|BioSciences Division, Los Alamos National Laboratory, New Mexico, United States of America.|BioSciences Division, Los Alamos National Laboratory, New Mexico, United States of America.|Department of Chemistry, University of Chicago, Illinois, United States of America.|Theoretical Biology and Biophysics Group, Los Alamos National Laboratory, New Mexico, United States of America.', 'Mexico|Mexico|Mexico|United States|Mexico', 10, 'Animals|Bacterial Toxins|Biological Transport|Buruli Ulcer|Cell Membrane|Endoplasmic Reticulum|Exotoxins|Glycerol|Humans|Lipid Bilayers|Lipids|Macrolides|Magnetic Resonance Spectroscopy|Molecular Dynamics Simulation|Mycobacterium ulcerans|Octanols|Protein Transport|Software|Stress, Mechanical|Temperature|Virulence|Virulence Factors|Water', 'Journal Article', '10.1371/journal.pcbi.1005972', '29401455', 'Mycolactone is the exotoxin produced by Mycobacterium ulcerans and is the virulence factor behind the neglected tropical disease Buruli ulcer. The toxin has a broad spectrum of biological effects within the host organism, stemming from its interaction with at least two molecular targets and the inhibition of protein uptake into the endoplasmic reticulum. Although it has been shown that the toxin can passively permeate into host cells, it is clearly lipophilic. Association with lipid carriers would have substantial implications for the toxins distribution within a host organism, delivery to cellular targets, diagnostic susceptibility, and mechanisms of pathogenicity. Yet the toxins interactions with, and distribution in, lipids are unknown. Herein we have used coarse-grained molecular dynamics simulations, guided by all-atom simulations, to study the interaction of mycolactone with pure and mixed lipid membranes. Using established techniques, we calculated the toxins preferential localization, membrane translocation, and impact on membrane physical and dynamical properties. The computed water-octanol partition coefficient indicates that mycolactone prefers to be in an organic phase rather than in an aqueous environment. Our results show that in a solvated membrane environment the exotoxin mainly localizes in the water-membrane interface, with a preference for the glycerol moiety of lipids, consistent with the reported studies that found it in lipid extracts of the cell. The calculated association constant to the model membrane is similar to the reported association constant for Wiskott-Aldrich syndrome protein. Mycolactone is shown to modify the physical properties of membranes, lowering the transition temperature, compressibility modulus, and critical line tension at which pores can be stabilized. It also shows a tendency to behave as a linactant, a molecule that localizes at the boundary between different fluid lipid domains in membranes and promotes inter-mixing of domains. This property has implications for the toxins cellular access, T-cell immunosuppression, and therapeutic potential.'),
(88877, 2018, 'plos', 'A phylogenetic method to perform genome-wide association studies in microbes that accounts for population structure and recombination', 'Collins, Caitlin|Didelot, Xavier', 'Department of Infectious Disease Epidemiology, Imperial College London, London, United Kingdom.|Department of Infectious Disease Epidemiology, Imperial College London, London, United Kingdom.', 'United Kingdom|United Kingdom', 34, 'Algorithms|Cluster Analysis|Computational Biology|Computer Simulation|Drug Resistance, Bacterial|Gene Expression Regulation, Bacterial|Genetic Association Studies|Genome, Bacterial|Genomics|Humans|Models, Statistical|Neisseria meningitidis|Penicillins|Phenotype|Phylogeny|Polymorphism, Single Nucleotide|Programming Languages|Recombination, Genetic|Software', 'Journal Article', '10.1371/journal.pcbi.1005958', '29401456', 'Genome-Wide Association Studies (GWAS) in microbial organisms have the potential to vastly improve the way we understand, manage, and treat infectious diseases. Yet, microbial GWAS methods established thus far remain insufficiently able to capitalise on the growing wealth of bacterial and viral genetic sequence data. Facing clonal population structure and homologous recombination, existing GWAS methods struggle to achieve both the precision necessary to reject spurious findings and the power required to detect associations in microbes. In this paper, we introduce a novel phylogenetic approach that has been tailor-made for microbial GWAS, which is applicable to organisms ranging from purely clonal to frequently recombining, and to both binary and continuous phenotypes. Our approach is robust to the confounding effects of both population structure and recombination, while maintaining high statistical power to detect associations. Thorough testing via application to simulated data provides strong support for the power and specificity of our approach and demonstrates the advantages offered over alternative cluster-based and dimension-reduction methods. Two applications to Neisseria meningitidis illustrate the versatility and potential of our method, confirming previously-identified penicillin resistance loci and resulting in the identification of both well-characterised and novel drivers of invasive disease. Our method is implemented as an open-source R package called treeWAS which is freely available at https://github.com/caitiecollins/treeWAS.'),
(88878, 2018, 'plos', 'Imaging of neural oscillations with embedded inferential and group prevalence statistics', 'Donhauser, Peter W|Florin, Esther|Baillet, Sylvain', 'McConnell Brain Imaging Centre, Montreal Neurological Institute, McGill University, Montréal, Québec, Canada.|Institute of Clinical Neuroscience and Medical Psychology, Medical Faculty, Heinrich Heine Universität, Düsseldorf, Germany.|McConnell Brain Imaging Centre, Montreal Neurological Institute, McGill University, Montréal, Québec, Canada.', 'Canada|Germany|Canada', 1, 'Adult|Algorithms|Brain|Brain Mapping|Electroencephalography|Electrophysiological Phenomena|Female|Healthy Volunteers|Humans|Image Processing, Computer-Assisted|Magnetoencephalography|Male|Middle Aged|Models, Neurological|Models, Statistical|Neurons|Oscillometry|Prevalence|Signal Processing, Computer-Assisted|Signal-To-Noise Ratio|Vision, Ocular|Young Adult', 'Journal Article', '10.1371/journal.pcbi.1005990', '29408902', 'Magnetoencephalography and electroencephalography (MEG, EEG) are essential techniques for studying distributed signal dynamics in the human brain. In particular, the functional role of neural oscillations remains to be clarified. For that reason, imaging methods need to identify distinct brain regions that concurrently generate oscillatory activity, with adequate separation in space and time. Yet, spatial smearing and inhomogeneous signal-to-noise are challenging factors to source reconstruction from external sensor data. The detection of weak sources in the presence of stronger regional activity nearby is a typical complication of MEG/EEG source imaging. We propose a novel, hypothesis-driven source reconstruction approach to address these methodological challenges. The imaging with embedded statistics (iES) method is a subspace scanning technique that constrains the mapping problem to the actual experimental design. A major benefit is that, regardless of signal strength, the contributions from all oscillatory sources, which activity is consistent with the tested hypothesis, are equalized in the statistical maps produced. We present extensive evaluations of iES on group MEG data, for mapping 1) induced oscillations using experimental contrasts, 2) ongoing narrow-band oscillations in the resting-state, 3) co-modulation of brain-wide oscillatory power with a seed region, and 4) co-modulation of oscillatory power with peripheral signals (pupil dilation). Along the way, we demonstrate several advantages of iES over standard source imaging approaches. These include the detection of oscillatory coupling without rejection of zero-phase coupling, and detection of ongoing oscillations in deeper brain regions, where signal-to-noise conditions are unfavorable. We also show that iES provides a separate evaluation of oscillatory synchronization and desynchronization in experimental contrasts, which has important statistical advantages. The flexibility of iES allows it to be adjusted to many experimental questions in systems neuroscience.'),
(88879, 2018, 'plos', 'Interpretation of correlated neural variability from models of feed-forward and recurrent circuits', 'Pernice, Volker|da Silveira, Rava Azeredo', 'Department of Physics, Ecole Normale Supérieure, Paris, France.|Department of Physics, Ecole Normale Supérieure, Paris, France.', 'France|France', 1, 'Action Potentials|Algorithms|Animals|Auditory Cortex|Computer Simulation|Mice|Models, Neurological|Models, Statistical|Nerve Net|Neurons|Poisson Distribution|Signal Processing, Computer-Assisted|Stochastic Processes', 'Journal Article', '10.1371/journal.pcbi.1005979', '29408930', 'Neural populations respond to the repeated presentations of a sensory stimulus with correlated variability. These correlations have been studied in detail, with respect to their mechanistic origin, as well as their influence on stimulus discrimination and on the performance of population codes. A number of theoretical studies have endeavored to link network architecture to the nature of the correlations in neural activity. Here, we contribute to this effort: in models of circuits of stochastic neurons, we elucidate the implications of various network architectures-recurrent connections, shared feed-forward projections, and shared gain fluctuations-on the stimulus dependence in correlations. Specifically, we derive mathematical relations that specify the dependence of population-averaged covariances on firing rates, for different network architectures. In turn, these relations can be used to analyze data on population activity. We examine recordings from neural populations in mouse auditory cortex. We find that a recurrent network model with random effective connections captures the observed statistics. Furthermore, using our circuit model, we investigate the relation between network parameters, correlations, and how well different stimuli can be discriminated from one another based on the population activity. As such, our approach allows us to relate properties of the neural circuit to information processing.'),
(88880, 2018, 'plos', 'A computational approach to distinguish somatic vs germline origin of genomic alterations from deep sequencing of cancer specimens without a matched normal', 'Sun, James X|He, Yuting|Sanford, Eric|Montesion, Meagan|Frampton, Garrett M|Vignot, Stéphane|Soria, Jean-Charles|Ross, Jeffrey S|Miller, Vincent A|Stephens, Phil J|Lipson, Doron|Yelensky, Roman', 'Foundation Medicine, Inc., Cambridge, MA, United States of America.|Foundation Medicine, Inc., Cambridge, MA, United States of America.|Foundation Medicine, Inc., Cambridge, MA, United States of America.|Foundation Medicine, Inc., Cambridge, MA, United States of America.|Foundation Medicine, Inc., Cambridge, MA, United States of America.|Institut National de la Santé et de la Recherche Médicale (INSERM) U981, Gustave Roussy, Villejuif Grand, Paris, France.|Institut National de la Santé et de la Recherche Médicale (INSERM) U981, Gustave Roussy, Villejuif Grand, Paris, France.|Foundation Medicine, Inc., Cambridge, MA, United States of America.|Foundation Medicine, Inc., Cambridge, MA, United States of America.|Foundation Medicine, Inc., Cambridge, MA, United States of America.|Foundation Medicine, Inc., Cambridge, MA, United States of America.|Foundation Medicine, Inc., Cambridge, MA, United States of America.', 'United States|United States|United States|United States|United States|France|France|United States|Un', 58, 'Algorithms|Alleles|Breast Neoplasms|Carcinoma, Non-Small-Cell Lung|Colonic Neoplasms|Computational Biology|Computer Simulation|DNA Copy Number Variations|Databases, Genetic|Exome|Exons|Female|Gene Frequency|Genome, Human|Genomics|Germ-Line Mutation|Heterozygote|High-Throughput Nucleotide Sequencing|Homozygote|Humans|Lung Neoplasms|Mutation|Neoplasms|Ploidies|Polymorphism, Single Nucleotide|Probability|Reproducibility of Results|Sequence Analysis, DNA', 'Journal Article', '10.1371/journal.pcbi.1005965', '29415044', 'A key constraint in genomic testing in oncology is that matched normal specimens are not commonly obtained in clinical practice. Thus, while well-characterized genomic alterations do not require normal tissue for interpretation, a significant number of alterations will be unknown in whether they are germline or somatic, in the absence of a matched normal control. We introduce SGZ (somatic-germline-zygosity), a computational method for predicting somatic vs. germline origin and homozygous vs. heterozygous or sub-clonal state of variants identified from deep massively parallel sequencing (MPS) of cancer specimens. The method does not require a patient matched normal control, enabling broad application in clinical research. SGZ predicts the somatic vs. germline status of each alteration identified by modeling the alterations allele frequency (AF), taking into account the tumor content, tumor ploidy, and the local copy number. Accuracy of the prediction depends on the depth of sequencing and copy number model fit, which are achieved in our clinical assay by sequencing to high depth (>500x) using MPS, covering 394 cancer-related genes and over 3,500 genome-wide single nucleotide polymorphisms (SNPs). Calls are made using a statistic based on read depth and local variability of SNP AF. To validate the method, we first evaluated performance on samples from 30 lung and colon cancer patients, where we sequenced tumors and matched normal tissue. We examined predictions for 17 somatic hotspot mutations and 20 common germline SNPs in 20,182 clinical cancer specimens. To assess the impact of stromal admixture, we examined three cell lines, which were titrated with their matched normal to six levels (10-75%). Overall, predictions were made in 85% of cases, with 95-99% of variants predicted correctly, a significantly superior performance compared to a basic approach based on AF alone. We then applied the SGZ method to the COSMIC database of known somatic variants in cancer and found >50 that are in fact more likely to be germline.'),
(88881, 2018, 'plos', 'The feasibility of equilibria in large ecosystems: A primary but neglected concept in the complexity-stability debate', 'Dougoud, Michaël|Vinckenbosch, Laura|Rohr, Rudolf P|Bersier, Louis-Félix|Mazza, Christian', 'Department of Mathematics, University of Fribourg, Fribourg, Switzerland.|Department of Mathematics, University of Fribourg, Fribourg, Switzerland.|Department of Biology, Unit of Ecology and Evolution, University of Fribourg, Fribourg, Switzerland.|Department of Biology, Unit of Ecology and Evolution, University of Fribourg, Fribourg, Switzerland.|Department of Mathematics, University of Fribourg, Fribourg, Switzerland.', 'Switzerland|Switzerland|Switzerland|Switzerland|Switzerland', 8, 'Animals|Computer Simulation|Ecology|Ecosystem|Food Chain|Models, Biological|Models, Statistical|Normal Distribution|Predatory Behavior|Probability', 'Journal Article', '10.1371/journal.pcbi.1005988', '29420532', 'The consensus that complexity begets stability in ecosystems was challenged in the seventies, a result recently extended to ecologically-inspired networks. The approaches assume the existence of a feasible equilibrium, i.e. with positive abundances. However, this key assumption has not been tested. We provide analytical results complemented by simulations which show that equilibrium feasibility vanishes in species rich systems. This result leaves us in the uncomfortable situation in which the existence of a feasible equilibrium assumed in local stability criteria is far from granted. We extend our analyses by changing interaction structure and intensity, and find that feasibility and stability is warranted irrespective of species richness with weak interactions. Interestingly, we find that the dynamical behaviour of ecologically inspired architectures is very different and richer than that of unstructured systems. Our results suggest that a general understanding of ecosystem dynamics requires focusing on the interplay between interaction strength and network architecture.'),
(88882, 2018, 'plos', 'Electrical receptive fields of retinal ganglion cells: Influence of presynaptic neurons', 'Maturana, Matias I|Apollo, Nicholas V|Garrett, David J|Kameneva, Tatiana|Cloherty, Shaun L|Grayden, David B|Burkitt, Anthony N|Ibbotson, Michael R|Meffin, Hamish', 'National Vision Research Institute, Australian College of Optometry, Carlton, Victoria, Australia.|School of Physics, The University of Melbourne, Parkville, VIC, Australia.|School of Physics, The University of Melbourne, Parkville, VIC, Australia.|NeuroEngineering Laboratory, Department of Biomedical Engineering, The University of Melbourne, Australia.|National Vision Research Institute, Australian College of Optometry, Carlton, Victoria, Australia.|Department of Medicine, St Vincents Hospital Melbourne, The University of Melbourne, VIC, Australia.|NeuroEngineering Laboratory, Department of Biomedical Engineering, The University of Melbourne, Australia.|National Vision Research Institute, Australian College of Optometry, Carlton, Victoria, Australia.|National Vision Research Institute, Australian College of Optometry, Carlton, Victoria, Australia.', 'Australia|Australia|Australia|Australia|Australia|Australia|Australia|Australia|Australia', 7, 'Action Potentials|Algorithms|Animals|Computer Simulation|Electric Stimulation|Electrodes|Light|Models, Neurological|Neurons|Presynaptic Terminals|Rats|Reproducibility of Results|Retina|Retinal Ganglion Cells|Signal-To-Noise Ratio|Software|Synapses|Vision, Ocular|Visual Cortex', 'Journal Article', '10.1371/journal.pcbi.1005997', '29432411', 'Implantable retinal stimulators activate surviving neurons to restore a sense of vision in people who have lost their photoreceptors through degenerative diseases. Complex spatial and temporal interactions occur in the retina during multi-electrode stimulation. Due to these complexities, most existing implants activate only a few electrodes at a time, limiting the repertoire of available stimulation patterns. Measuring the spatiotemporal interactions between electrodes and retinal cells, and incorporating them into a model may lead to improved stimulation algorithms that exploit the interactions. Here, we present a computational model that accurately predicts both the spatial and temporal nonlinear interactions of multi-electrode stimulation of rat retinal ganglion cells (RGCs). The model was verified using in vitro recordings of ON, OFF, and ON-OFF RGCs in response to subretinal multi-electrode stimulation with biphasic pulses at three stimulation frequencies (10, 20, 30 Hz). The model gives an estimate of each cells spatiotemporal electrical receptive fields (ERFs), i.e., the pattern of stimulation leading to excitation or suppression in the neuron. All cells had excitatory ERFs and many also had suppressive sub-regions of their ERFs. We show that the nonlinearities in observed responses arise largely from activation of presynaptic interneurons. When synaptic transmission was blocked, the number of sub-regions of the ERF was reduced, usually to a single excitatory ERF. This suggests that direct cell activation can be modeled accurately by a one-dimensional model with linear interactions between electrodes, whereas indirect stimulation due to summated presynaptic responses is nonlinear.'),
(88883, 2018, 'plos', 'Hub connectivity, neuronal diversity, and gene expression in the Caenorhabditis elegans connectome', 'Arnatkevicxccx86ixc5xabtxc4x97, Aurina|Fulcher, Ben D|Pocock, Roger|Fornito, Alex', 'Brain and Mental Health Laboratory, Monash Institute of Cognitive and Clinical Neurosciences, School of Psychological Sciences, Monash University, Clayton, VIC, Australia.|Brain and Mental Health Laboratory, Monash Institute of Cognitive and Clinical Neurosciences, School of Psychological Sciences, Monash University, Clayton, VIC, Australia.|Development and Stem Cells Program, Monash Biomedicine Discovery Institute and Department of Anatomy and Developmental Biology, Monash University, Clayton, VIC, Australia.|Brain and Mental Health Laboratory, Monash Institute of Cognitive and Clinical Neurosciences, School of Psychological Sciences, Monash University, Clayton, VIC, Australia.', 'Australia|Australia|Australia|Australia', 15, 'Animals|Brain|Caenorhabditis elegans|Caenorhabditis elegans Proteins|Cerebral Cortex|Computer Simulation|Connectome|Gap Junctions|Gene Expression|Gene Expression Profiling|Gene Expression Regulation|Humans|Interneurons|Mice|Models, Neurological|Neural Pathways|Neurons|Oxygen', 'Journal Article', '10.1371/journal.pcbi.1005989', '29432412', 'Studies of nervous system connectivity, in a wide variety of species and at different scales of resolution, have identified several highly conserved motifs of network organization. One such motif is a heterogeneous distribution of connectivity across neural elements, such that some elements act as highly connected and functionally important network hubs. These brain network hubs are also densely interconnected, forming a so-called rich club. Recent work in mouse has identified a distinctive transcriptional signature of neural hubs, characterized by tightly coupled expression of oxidative metabolism genes, with similar genes characterizing macroscale inter-modular hub regions of the human cortex. Here, we sought to determine whether hubs of the neuronal C. elegans connectome also show tightly coupled gene expression. Using open data on the chemical and electrical connectivity of 279 C. elegans neurons, and binary gene expression data for each neuron across 948 genes, we computed a correlated gene expression score for each pair of neurons, providing a measure of their gene expression similarity. We demonstrate that connections between hub neurons are the most similar in their gene expression while connections between nonhubs are the least similar. Genes with the greatest contribution to this effect are involved in glutamatergic and cholinergic signaling, and other communication processes. We further show that coupled expression between hub neurons cannot be explained by their neuronal subtype (i.e., sensory, motor, or interneuron), separation distance, chemically secreted neurotransmitter, birth time, pairwise lineage distance, or their topological module affiliation. Instead, this coupling is intrinsically linked to the identity of most hubs as command interneurons, a specific class of interneurons that regulates locomotion. Our results suggest that neural hubs may possess a distinctive transcriptional signature, preserved across scales and species, that is related to the involvement of hubs in regulating the higher-order behaviors of a given organism.'),
(88884, 2018, 'plos', 'Same but not alike: Structure, flexibility and energetics of domains in multi-domain proteins are influenced by the presence of other domains', 'Vishwanath, Sneha|de Brevern, Alexandre G|Srinivasan, Narayanaswamy', 'Molecular Biophysics Unit, Indian Institute of Science, Bangalore, India.|INSERM, U 1134, DSIMB, Paris, France.|Molecular Biophysics Unit, Indian Institute of Science, Bangalore, India.', 'India|France|India', 7, 'Animals|Computer Simulation|Cyclophilins|DNA Polymerase beta|Fibronectins|Hexokinase|Humans|Models, Molecular|Molecular Dynamics Simulation|Neuraminidase|Protein Binding|Protein Domains|Protein Folding|Protein Interaction Mapping|Protein Structure, Tertiary|Proteins|Proteome|Rats', 'Journal Article', '10.1371/journal.pcbi.1006008', '29432415', 'The majority of the proteins encoded in the genomes of eukaryotes contain more than one domain. Reasons for high prevalence of multi-domain proteins in various organisms have been attributed to higher stability and functional and folding advantages over single-domain proteins. Despite these advantages, many proteins are composed of only one domain while their homologous domains are part of multi-domain proteins. In the study presented here, differences in the properties of protein domains in single-domain and multi-domain systems and their influence on functions are discussed. We studied 20 pairs of identical protein domains, which were crystallized in two forms (a) tethered to other proteins domains and (b) tethered to fewer protein domains than (a) or not tethered to any protein domain. Results suggest that tethering of domains in multi-domain proteins influences the structural, dynamic and energetic properties of the constituent protein domains. 50% of the protein domain pairs show significant structural deviations while 90% of the protein domain pairs show differences in dynamics and 12% of the residues show differences in the energetics. To gain further insights on the influence of tethering on the function of the domains, 4 pairs of homologous protein domains, where one of them is a full-length single-domain protein and the other protein domain is a part of a multi-domain protein, were studied. Analyses showed that identical and structurally equivalent functional residues show differential dynamics in homologous protein domains, though comparable dynamics between in-silico generated chimera protein and multi-domain proteins were observed. From these observations, the differences observed in the functions of homologous proteins could be attributed to the presence of tethered domain. Overall, we conclude that tethered domains in multi-domain proteins not only provide stability or folding advantages but also influence pathways resulting in differences in function or regulatory properties.'),
(88885, 2018, 'plos', 'Heritable tumor cell division rate heterogeneity induces clonal dominance', 'Palm, Margriet M|Elemans, Marjet|Beltman, Joost B', 'Division of Drug Discovery and Safety, Leiden Academic Center for Drug Research, Leiden University, Leiden, The Netherlands.|Division of Drug Discovery and Safety, Leiden Academic Center for Drug Research, Leiden University, Leiden, The Netherlands.|Division of Drug Discovery and Safety, Leiden Academic Center for Drug Research, Leiden University, Leiden, The Netherlands.', 'Netherlands|Netherlands|Netherlands', 3, 'Animals|Cell Differentiation|Cell Division|Clone Cells|Computer Simulation|Genotype|HeLa Cells|Humans|K562 Cells|Likelihood Functions|Models, Biological|Mutation|Neoplasms|Neoplastic Stem Cells|Phenotype|Poisson Distribution|Sequence Analysis, DNA|Stochastic Processes', 'Journal Article', '10.1371/journal.pcbi.1005954', '29432417', 'Tumors consist of a hierarchical population of cells that differ in their phenotype and genotype. This hierarchical organization of cells means that a few clones (i.e., cells and several generations of offspring) are abundant while most are rare, which is called clonal dominance. Such dominance also occurred in published in vitro iterated growth and passage experiments with tumor cells in which genetic barcodes were used for lineage tracing. A potential source for such heterogeneity is that dominant clones derive from cancer stem cells with an unlimited self-renewal capacity. Furthermore, ongoing evolution and selection within the growing population may also induce clonal dominance. To understand how clonal dominance developed in the iterated growth and passage experiments, we built a computational model that accurately simulates these experiments. The model simulations reproduced the clonal dominance that developed in in vitro iterated growth and passage experiments when the division rates vary between cells, due to a combination of initial variation and of ongoing mutational processes. In contrast, the experimental results can neither be reproduced with a model that considers random growth and passage, nor with a model based on cancer stem cells. Altogether, our model suggests that in vitro clonal dominance develops due to selection of fast-dividing clones.'),
(88886, 2018, 'plos', 'Spike and burst coding in thalamocortical relay cells', 'Zeldenrust, Fleur|Chameau, Pascal|Wadman, Wytse J', 'Department of Neurophysiology, Donders Institute for Brain, Cognition and Behaviour, Radboud University, Nijmegen, the Netherlands.|Cellular and Systems Neurobiology, Swammerdam Institute for Life Sciences, University of Amsterdam, Amsterdam, the Netherlands.|Cellular and Systems Neurobiology, Swammerdam Institute for Life Sciences, University of Amsterdam, Amsterdam, the Netherlands.', 'Netherlands|Netherlands|Netherlands', 0, 'Action Potentials|Animals|Brain|Calcium|Calcium Channels|Cell Count|Electrophysiology|Fourier Analysis|Geniculate Bodies|Membrane Potentials|Models, Neurological|Neurons|Normal Distribution|Patch-Clamp Techniques|Poisson Distribution|Probability|Rats|Rats, Wistar|Signal Processing, Computer-Assisted|Thalamus', 'Journal Article', '10.1371/journal.pcbi.1005960', '29432418', 'Mammalian thalamocortical relay (TCR) neurons switch their firing activity between a tonic spiking and a bursting regime. In a combined experimental and computational study, we investigated the features in the input signal that single spikes and bursts in the output spike train represent and how this code is influenced by the membrane voltage state of the neuron. Identical frozen Gaussian noise current traces were injected into TCR neurons in rat brain slices as well as in a validated three-compartment TCR model cell. The resulting membrane voltage traces and spike trains were analyzed by calculating the coherence and impedance. Reverse correlation techniques gave the Event-Triggered Average (ETA) and the Event-Triggered Covariance (ETC). This demonstrated that the feature selectivity started relatively long before the events (up to 300 ms) and showed a clear distinction between spikes (selective for fluctuations) and bursts (selective for integration). The model cell was fine-tuned to mimic the frozen noise initiated spike and burst responses to within experimental accuracy, especially for the mixed mode regimes. The information content carried by the various types of events in the signal as well as by the whole signal was calculated. Bursts phase-lock to and transfer information at lower frequencies than single spikes. On depolarization the neuron transits smoothly from the predominantly bursting regime to a spiking regime, in which it is more sensitive to high-frequency fluctuations. The model was then used to elucidate properties that could not be assessed experimentally, in particular the role of two important subthreshold voltage-dependent currents: the low threshold activated calcium current (IT) and the cyclic nucleotide modulated h current (Ih). The ETAs of those currents and their underlying activation/inactivation states not only explained the state dependence of the firing regime but also the long-lasting concerted dynamic action of the two currents. Finally, the model was used to investigate the more realistic high-conductance state, where fluctuations are caused by (synaptic) conductance changes instead of current injection. Under standard conditions bursts are difficult to initiate, given the high degree of inactivation of the T-type calcium current. Strong and/or precisely timed inhibitory currents were able to remove this inactivation.');
INSERT INTO `papers` (`id`, `ano`, `journal`, `titulo`, `autores`, `afiliacao`, `pais`, `citacoes`, `palavra_chave`, `categorias`, `doi`, `pubmed`, `abstract`) VALUES
(88887, 2018, 'plos', 'History dependence in insect flight decisions during odor tracking', 'Pang, Rich|van Breugel, Floris|Dickinson, Michael|Riffell, Jeffrey A|Fairhall, Adrienne', 'Neuroscience Graduate Program, University of Washington, Seattle, Washington, United States of America.|Division of Biology and Bioengineering, California Institute of Technology, Pasadena, California, United States of America.|Division of Biology and Bioengineering, California Institute of Technology, Pasadena, California, United States of America.|Department of Biology, University of Washington, Seattle, Washington, United States of America.|Department of Physiology and Biophysics, University of Washington, Seattle, Washington, United States of America.', 'United States|United States|United States|United States|United States', 8, 'Aedes|Algorithms|Animals|Behavior, Animal|Computer Simulation|Decision Making|Drosophila melanogaster|Flight, Animal|Learning|Linear Models|Memory, Short-Term|Models, Biological|Odorants|Probability|Sexual Behavior, Animal|Smell', 'Journal Article', '10.1371/journal.pcbi.1005969', '29432454', 'Natural decision-making often involves extended decision sequences in response to variable stimuli with complex structure. As an example, many animals follow odor plumes to locate food sources or mates, but turbulence breaks up the advected odor signal into intermittent filaments and puffs. This scenario provides an opportunity to ask how animals use sparse, instantaneous, and stochastic signal encounters to generate goal-oriented behavioral sequences. Here we examined the trajectories of flying fruit flies (Drosophila melanogaster) and mosquitoes (Aedes aegypti) navigating in controlled plumes of attractive odorants. While it is known that mean odor-triggered flight responses are dominated by upwind turns, individual responses are highly variable. We asked whether deviations from mean responses depended on specific features of odor encounters, and found that odor-triggered turns were slightly but significantly modulated by two features of odor encounters. First, encounters with higher concentrations triggered stronger upwind turns. Second, encounters occurring later in a sequence triggered weaker upwind turns. To contextualize the latter history dependence theoretically, we examined trajectories simulated from three normative tracking strategies. We found that neither a purely reactive strategy nor a strategy in which the tracker learned the plume centerline over time captured the observed history dependence. In contrast, infotaxis, in which flight decisions maximized expected information gain about source location, exhibited a history dependence aligned in sign with the data, though much larger in magnitude. These findings suggest that while true plume tracking is dominated by a reactive odor response it might also involve a history-dependent modulation of responses consistent with the accumulation of information about a source over multi-encounter timescales. This suggests that short-term memory processes modulating decision sequences may play a role in natural plume tracking.'),
(88888, 2018, 'plos', 'Recognition of sites of functional specialisation in all known eukaryotic protein kinase families', 'Kalaivani, Raju|Reema, Raju|Srinivasan, Narayanaswamy', 'Molecular Biophysics Unit, Indian Institute of Science, Bangalore, Karnataka, India.|Molecular Biophysics Unit, Indian Institute of Science, Bangalore, Karnataka, India.|Molecular Biophysics Unit, Indian Institute of Science, Bangalore, Karnataka, India.', 'India|India|India', 0, 'Adenosine Triphosphate|Animals|Binding Sites|Catalytic Domain|Cluster Analysis|Computational Biology|Cyclin-Dependent Kinases|Entropy|Humans|MAP Kinase Signaling System|Models, Statistical|Mutation|Phosphorylation|Phylogeny|Probability|Protein Binding|Protein Domains|Protein Kinases|Protein-Serine-Threonine Kinases|ROC Curve|Substrate Specificity', 'Journal Article', '10.1371/journal.pcbi.1005975', '29438395', 'The conserved function of protein phosphorylation, catalysed by members of protein kinase superfamily, is regulated in different ways in different kinase families. Further, differences in activating triggers, cellular localisation, domain architecture and substrate specificity between kinase families are also well known. While the transfer of xcexb3-phosphate from ATP to the hydroxyl group of Ser/Thr/Tyr is mediated by a conserved Asp, the characteristic functional and regulatory sites are specialized at the level of families or sub-families. Such family-specific sites of functional specialization are unknown for most families of kinases. In this work, we systematically identify the family-specific residue features by comparing the extent of conservation of physicochemical properties, Shannon entropy and statistical probability of residue distributions between families of kinases. An integrated discriminatory score, which combines these three features, is developed to demarcate the functionally specialized sites in a kinase family from other sites. We achieved an area under ROC curve of 0.992 for the discrimination of kinase families. Our approach was extensively tested on well-studied families CDK and MAPK, wherein specific protein interaction sites and substrate recognition sites were successfully detected (p-value < 0.05). We also find that the known family-specific oncogenic driver mutation sites were scored high by our method. The method was applied to all known kinases encompassing 107 families from diverse eukaryotic organisms leading to a comprehensive list of family-specific functional sites. Apart from other uses, our method facilitates identification of specific protein interaction sites and drug target sites in a kinase family.'),
(88889, 2018, 'plos', 'Self-crowding of AMPA receptors in the excitatory postsynaptic density can effectuate anomalous receptor sub-diffusion', 'Gupta, Rahul', 'School of Computational and Integrative Sciences, Jawaharlal Nehru University, New Delhi, India.', 'India', 4, 'Algorithms|Animals|Computer Simulation|Diffusion|Excitatory Postsynaptic Potentials|Hippocampus|Humans|Membrane Proteins|Neurons|Post-Synaptic Density|Protein Binding|Protein Domains|Protein Transport|Receptors, AMPA|Synapses|Synaptic Transmission', 'Journal Article', '10.1371/journal.pcbi.1005984', '29444074', 'AMPA receptors (AMPARs) and their associations with auxiliary transmembrane proteins are bulky structures with large steric-exclusion volumes. Hence, self-crowding of AMPARs, depending on the local density, may affect their lateral diffusion in the postsynaptic membrane as well as in the highly crowded postsynaptic density (PSD) at excitatory synapses. Earlier theoretical studies considered only the roles of transmembrane obstacles and the AMPAR-binding submembranous scaffold proteins in shaping receptor diffusion within PSD. Using lattice model of diffusion, the present study investigates the additional impacts of self-crowding on the anomalousity and effective diffusion coefficient (Deff) of AMPAR diffusion. A recursive algorithm for avoiding false self-blocking during diffusion simulation is also proposed. The findings suggest that high density of AMPARs in the obstacle-free membrane itself engenders strongly anomalous diffusion and severe decline in Deff. Adding transmembrane obstacles to the membrane accentuates the anomalousity arising from self-crowding due to the reduced free diffusion space. Contrarily, enhanced AMPAR-scaffold binding, either through increase in binding strength or scaffold density or both, ameliorates the anomalousity resulting from self-crowding. However, binding has differential impacts on Deff depending on the receptor density. Increase in binding causes consistent decrease in Deff for low and moderate receptor density. For high density, binding increases Deff as long as it reduces anomalousity associated with intense self-crowding. Given a sufficiently strong binding condition when diffusion acquires normal behavior, further increase in binding causes decrease in Deff. Supporting earlier experimental observations are mentioned and implications of present findings to the experimental observations on AMPAR diffusion are also drawn.'),
(88890, 2018, 'plos', 'Optimizing homeostatic cell renewal in hierarchical tissues', 'Alvarado, Cesar|Fider, Nicole A|Wearing, Helen J|Komarova, Natalia L', 'Department of Mathematics and Statistics, University of New Mexico, Albuquerque, New Mexico, United States of America.|Department of Mathematics, University of California Irvine, Irvine, California, United States of America.|Department of Mathematics and Statistics, University of New Mexico, Albuquerque, New Mexico, United States of America.|Department of Mathematics, University of California Irvine, Irvine, California, United States of America.', 'Mexico|United States|Mexico|United States', 0, 'Animals|Cell Differentiation|Cell Division|Cell Proliferation|Computational Biology|Computer Simulation|Genes, Tumor Suppressor|Hematopoiesis|Homeostasis|Humans|Models, Biological|Mutation|Neoplasms|Probability|Risk|Stem Cells|Stochastic Processes', 'Journal Article', '10.1371/journal.pcbi.1005967', '29447149', 'In order to maintain homeostasis, mature cells removed from the top compartment of hierarchical tissues have to be replenished by means of differentiation and self-renewal events happening in the more primitive compartments. As each cell division is associated with a risk of mutation, cell division patterns have to be optimized, in order to minimize or delay the risk of malignancy generation. Here we study this optimization problem, focusing on the role of division tree length, that is, the number of layers of cells activated in response to the loss of terminally differentiated cells, which is related to the balance between differentiation and self-renewal events in the compartments. Using both analytical methods and stochastic simulations in a metapopulation-style model, we find that shorter division trees are advantageous if the objective is to minimize the total number of one-hit mutants in the cell population. Longer division trees on the other hand minimize the accumulation of two-hit mutants, which is a more likely evolutionary goal given the key role played by tumor suppressor genes in cancer initiation. While division tree length is the most important property determining mutant accumulation, we also find that increasing the size of primitive compartments helps to delay two-hit mutant generation.'),
(88891, 2018, 'plos', 'Life cycle synchronization is a viral drug resistance mechanism', 'Neagu, Iulia A|Olejarz, Jason|Freeman, Mark|Rosenbloom, Daniel I S|Nowak, Martin A|Hill, Alison L', 'Program for Evolutionary Dynamics, Department of Mathematics and Department of Organismic & Evolutionary Biology, Harvard University, Cambridge, Massachusetts, United States of America.|Program for Evolutionary Dynamics, Department of Mathematics and Department of Organismic & Evolutionary Biology, Harvard University, Cambridge, Massachusetts, United States of America.|Program for Evolutionary Dynamics, Department of Mathematics and Department of Organismic & Evolutionary Biology, Harvard University, Cambridge, Massachusetts, United States of America.|Department of Biomedical Informatics, Columbia University Medical Center, New York, New York, United States of America.|Program for Evolutionary Dynamics, Department of Mathematics and Department of Organismic & Evolutionary Biology, Harvard University, Cambridge, Massachusetts, United States of America.|Program for Evolutionary Dynamics, Department of Mathematics and Department of Organismic & Evolutionary Biology, Harvard University, Cambridge, Massachusetts, United States of America.', 'United States|United States|United States|United States|United States|United States', 9, 'Anti-HIV Agents|Antiviral Agents|Basic Reproduction Number|Computational Biology|Computer Simulation|Drug Resistance, Viral|Drug Tolerance|Genotype|HIV Infections|HIV-1|Humans|Models, Theoretical|Phenotype|Stochastic Processes|Virus Diseases|Virus Replication', 'Journal Article', '10.1371/journal.pcbi.1005947', '29447150', 'Viral infections are one of the major causes of death worldwide, with HIV infection alone resulting in over 1.2 million casualties per year. Antiviral drugs are now being administered for a variety of viral infections, including HIV, hepatitis B and C, and influenza. These therapies target a specific phase of the viruss life cycle, yet their ultimate success depends on a variety of factors, such as adherence to a prescribed regimen and the emergence of viral drug resistance. The epidemiology and evolution of drug resistance have been extensively characterized, and it is generally assumed that drug resistance arises from mutations that alter the viruss susceptibility to the direct action of the drug. In this paper, we consider the possibility that a virus population can evolve towards synchronizing its life cycle with the pattern of drug therapy. The periodicity of the drug treatment could then allow for a virus strain whose life cycle length is a multiple of the dosing interval to replicate only when the concentration of the drug is lowest. This process, referred to as drug tolerance by synchronization, could allow the virus population to maximize its overall fitness without having to alter drug binding or complete its life cycle in the drugs presence. We use mathematical models and stochastic simulations to show that life cycle synchronization can indeed be a mechanism of viral drug tolerance. We show that this effect is more likely to occur when the variability in both viral life cycle and drug dose timing are low. More generally, we find that in the presence of periodic drug levels, time-averaged calculations of viral fitness do not accurately predict drug levels needed to eradicate infection, even if there is no synchronization. We derive an analytical expression for viral fitness that is sufficient to explain the drug-pattern-dependent survival of strains with any life cycle length. We discuss the implications of these findings for clinically relevant antiviral strategies.'),
(88892, 2018, 'plos', 'Quick tips for creating effective and impactful biological pathways using the Systems Biology Graphical Notation', 'Touré, Vasundra|Le Novère, Nicolas|Waltemath, Dagmar|Wolkenhauer, Olaf', 'Department of Systems Biology and Bioinformatics, University of Rostock, Rostock, Germany.|Babraham Institute, Babraham Research Campus, Cambridge, United Kingdom.|Department of Systems Biology and Bioinformatics, University of Rostock, Rostock, Germany.|Department of Systems Biology and Bioinformatics, University of Rostock, Rostock, Germany.', 'Germany|United Kingdom|Germany|Germany', 1, 'Animals|Cell Cycle|Computational Biology|Computer Graphics|Drosophila|Humans|Interdisciplinary Communication|Internet|Models, Biological|Programming Languages|Software|Systems Biology', 'Journal Article', '10.1371/journal.pcbi.1005740', '29447151', '-'),
(88893, 2018, 'plos', 'A multiscale modelling approach to assess the impact of metabolic zonation and microperfusion on the hepatic carbohydrate metabolism', 'Berndt, Nikolaus|Horger, Marius Stefan|Bulik, Sascha|Holzhütter, Hermann-Georg', 'Computational Biochemistry Group, Institute of Biochemistry, Charite-University Medicine Berlin, Charitéplatz 1, Berlin.|Department of Diagnostic and Interventional Radiology, Eberhard-Karls-University Tubingen, Tuebingen, Germany.|Computational Biochemistry Group, Institute of Biochemistry, Charite-University Medicine Berlin, Charitéplatz 1, Berlin.|Computational Biochemistry Group, Institute of Biochemistry, Charite-University Medicine Berlin, Charitéplatz 1, Berlin.', '-|Germany|-|-', 0, 'Animals|Biochemical Phenomena|Blood Flow Velocity|Blood Glucose|Blood Pressure|Carbohydrate Metabolism|Dogs|Fibrosis|Glucose|Glycogen|Hepatocytes|Humans|Kinetics|Liver|Liver Cirrhosis|Mice|Microcirculation|Models, Theoretical|Perfusion|Rats|Tomography, X-Ray Computed', 'Journal Article', '10.1371/journal.pcbi.1006005', '29447152', 'The capacity of the liver to convert the metabolic input received from the incoming portal and arterial blood into the metabolic output of the outgoing venous blood has three major determinants: The intra-hepatic blood flow, the transport of metabolites between blood vessels (sinusoids) and hepatocytes and the metabolic capacity of hepatocytes. These determinants are not constant across the organ: Even in the normal organ, but much more pronounced in the fibrotic and cirrhotic liver, regional variability of the capillary blood pressure, tissue architecture and the expression level of metabolic enzymes (zonation) have been reported. Understanding how this variability may affect the regional metabolic capacity of the liver is important for the interpretation of functional liver tests and planning of pharmacological and surgical interventions. Here we present a mathematical model of the sinusoidal tissue unit (STU) that is composed of a single sinusoid surrounded by the space of Disse and a monolayer of hepatocytes. The total metabolic output of the liver (arterio-venous glucose difference) is obtained by integration across the metabolic output of a representative number of STUs. Application of the model to the hepatic glucose metabolism provided the following insights: (i) At portal glucose concentrations between 6-8 mM, an intra-sinusoidal glucose cycle may occur which is constituted by glucose producing periportal hepatocytes and glucose consuming pericentral hepatocytes, (ii) Regional variability of hepatic blood flow is higher than the corresponding regional variability of the metabolic output, (iii) a spatially resolved metabolic functiogram of the liver is constructed. Variations of tissue parameters are equally important as variations of enzyme activities for the control of the arterio-venous glucose difference.'),
(88894, 2018, 'plos', 'A model of risk and mental state shifts during social interaction', 'Hula, Andreas|Vilares, Iris|Lohrenz, Terry|Dayan, Peter|Montague, P Read', 'Austrian Institute of Technology, Vienna, Austria.|Wellcome Trust Centre for Neuroimaging, University College London, London, United Kingdom.|Human Neuroimaging Laboratory, Virginia Tech Carilion Research Institute, Roanoke, Virginia, United States of America.|Wellcome Trust Centre for Neuroimaging, University College London, London, United Kingdom.|Wellcome Trust Centre for Neuroimaging, University College London, London, United Kingdom.', 'Austria|United Kingdom|United States|United Kingdom|United Kingdom', 13, 'Algorithms|Bayes Theorem|Borderline Personality Disorder|Competitive Behavior|Computer Simulation|Cooperative Behavior|Game Theory|Games, Experimental|Guilt|Healthy Volunteers|Humans|Interpersonal Relations|Learning|Markov Chains|Models, Economic|Models, Statistical|Risk|Social Behavior|Temperature|Trust', 'Journal Article', '10.1371/journal.pcbi.1005935', '29447153', 'Cooperation and competition between human players in repeated microeconomic games offer a window onto social phenomena such as the establishment, breakdown and repair of trust. However, although a suitable starting point for the quantitative analysis of such games exists, namely the Interactive Partially Observable Markov Decision Process (I-POMDP), computational considerations and structural limitations have limited its application, and left unmodelled critical features of behavior in a canonical trust task. Here, we provide the first analysis of two central phenomena: a form of social risk-aversion exhibited by the player who is in control of the interaction in the game, and irritation or anger, potentially exhibited by both players. Irritation arises when partners apparently defect, and it potentially causes a precipitate breakdown in cooperation. Failing to model ones partners propensity for it leads to substantial economic inefficiency. We illustrate these behaviours using evidence drawn from the play of large cohorts of healthy volunteers and patients. We show that for both cohorts, a particular subtype of player is largely responsible for the breakdown of trust, a finding which sheds new light on borderline personality disorder.'),
(88895, 2018, 'plos', 'Examining the controllability of sepsis using genetic algorithms on an agent-based model of systemic inflammation', 'Cockrell, Robert Chase|An, Gary', 'Department of Surgery, University of Chicago, Chicago, Illinois, United States of America.|Department of Surgery, University of Chicago, Chicago, Illinois, United States of America.', 'United States|United States', 0, 'Algorithms|Blood|Clinical Trials as Topic|Computational Biology|Computer Simulation|Cytokines|Endothelium, Vascular|Humans|Immunity, Innate|Inflammation|Models, Biological|Models, Statistical|Mortality|Oxygen|Probability|Programming Languages|Sepsis|Stochastic Processes|Systemic Inflammatory Response Syndrome|United States|Vascular System Injuries', 'Journal Article', '10.1371/journal.pcbi.1005876', '29447154', 'Sepsis, a manifestation of the bodys inflammatory response to injury and infection, has a mortality rate of between 28%-50% and affects approximately 1 million patients annually in the United States. Currently, there are no therapies targeting the cellular/molecular processes driving sepsis that have demonstrated the ability to control this disease process in the clinical setting. We propose that this is in great part due to the considerable heterogeneity of the clinical trajectories that constitute clinical sepsis, and that determining how this system can be controlled back into a state of health requires the application of concepts drawn from the field of dynamical systems. In this work, we consider the human immune system to be a random dynamical system, and investigate its potential controllability using an agent-based model of the innate immune response (the Innate Immune Response ABM or IIRABM) as a surrogate, proxy system. Simulation experiments with the IIRABM provide an explanation as to why single/limited cytokine perturbations at a single, or small number of, time points is unlikely to significantly improve the mortality rate of sepsis. We then use genetic algorithms (GA) to explore and characterize multi-targeted control strategies for the random dynamical immune system that guide it from a persistent, non-recovering inflammatory state (functionally equivalent to the clinical states of systemic inflammatory response syndrome (SIRS) or sepsis) to a state of health. We train the GA on a single parameter set with multiple stochastic replicates, and show that while the calculated results show good generalizability, more advanced strategies are needed to achieve the goal of adaptive personalized medicine. This work evaluating the extent of interventions needed to control a simplified surrogate model of sepsis provides insight into the scope of the clinical challenge, and can serve as a guide on the path towards true precision control of sepsis.'),
(88896, 2018, 'plos', 'A comprehensive and quantitative comparison of text-mining in 15 million full-text articles versus their corresponding abstracts', 'Westergaard, David|Stærfeldt, Hans-Henrik|Tønsberg, Christian|Jensen, Lars Juhl|Brunak, Søren', 'Center for Biological Sequence Analysis, Department of Bio and Health Informatics, Technical University of Denmark, Lyngby, Denmark.|Center for Biological Sequence Analysis, Department of Bio and Health Informatics, Technical University of Denmark, Lyngby, Denmark.|Office for Innovation and Sector Services, Technical Information Center of Denmark, Technical University of Denmark, Lyngby, Denmark.|Novo Nordisk Foundation Center for Protein Research, Faculty of Health and Medical Sciences, University of Copenhagen, Copenhagen, Denmark.|Center for Biological Sequence Analysis, Department of Bio and Health Informatics, Technical University of Denmark, Lyngby, Denmark.', 'Denmark|Denmark|Denmark|Denmark|Denmark', 40, 'Abstracting and Indexing as Topic|Area Under Curve|Computational Biology|Data Mining|False Positive Reactions|Genes|Information Storage and Retrieval|MEDLINE|Periodicals as Topic|Proteins|ROC Curve|Software|Terminology as Topic', 'Journal Article', '10.1371/journal.pcbi.1005962', '29447159', 'Across academia and industry, text mining has become a popular strategy for keeping up with the rapid growth of the scientific literature. Text mining of the scientific literature has mostly been carried out on collections of abstracts, due to their availability. Here we present an analysis of 15 million English scientific full-text articles published during the period 1823-2016. We describe the development in article length and publication sub-topics during these nearly 250 years. We showcase the potential of text mining by extracting published protein-protein, disease-gene, and protein subcellular associations using a named entity recognition system, and quantitatively report on their accuracy using gold standard benchmark data sets. We subsequently compare the findings to corresponding results obtained on 16.5 million abstracts included in MEDLINE and show that text mining of full-text articles consistently outperforms using abstracts only.'),
(88897, 2018, 'plos', 'Modeling the interactions of sense and antisense Period transcripts in the mammalian circadian clock network', 'Battogtokh, Dorjsuren|Kojima, Shihoko|Tyson, John J', 'Department of Biological Sciences, Virginia Polytechnic Institute and State University, Blacksburg, Virginia, United States of America.|Department of Biological Sciences, Virginia Polytechnic Institute and State University, Blacksburg, Virginia, United States of America.|Department of Biological Sciences, Virginia Polytechnic Institute and State University, Blacksburg, Virginia, United States of America.', 'United States|United States|United States', 2, 'Animals|Cell Cycle|Circadian Clocks|Circadian Rhythm|Cytoplasm|Gene Expression|Gene Expression Regulation|Liver|Mice|Models, Theoretical|Oligonucleotides, Antisense|Oscillometry|Period Circadian Proteins|Phosphorylation|RNA, Messenger|Transcription Factors', 'Journal Article', '10.1371/journal.pcbi.1005957', '29447160', 'In recent years, it has become increasingly apparent that antisense transcription plays an important role in the regulation of gene expression. The circadian clock is no exception: an antisense transcript of the mammalian core-clock gene PERIOD2 (PER2), which we shall refer to as Per2AS RNA, oscillates with a circadian period and a nearly 12 h phase shift from the peak expression of Per2 mRNA. In this paper, we ask whether Per2AS plays a regulatory role in the mammalian circadian clock by studying in silico the potential effects of interactions between Per2 and Per2AS RNAs on circadian rhythms. Based on the antiphasic expression pattern, we consider two hypotheses about how Per2 and Per2AS mutually interfere with each others expression. In our pre-transcriptional model, the transcription of Per2AS RNA from the non-coding strand represses the transcription of Per2 mRNA from the coding strand and vice versa. In our post-transcriptional model, Per2 and Per2AS transcripts form a double-stranded RNA duplex, which is rapidly degraded. To study these two possible mechanisms, we have added terms describing our alternative hypotheses to a published mathematical model of the molecular regulatory network of the mammalian circadian clock. Our pre-transcriptional model predicts that transcriptional interference between Per2 and Per2AS can generate alternative modes of circadian oscillations, which we characterize in terms of the amplitude and phase of oscillation of core clock genes. In our post-transcriptional model, Per2/Per2AS duplex formation dampens the circadian rhythm. In a model that combines pre- and post-transcriptional controls, the period, amplitude and phase of circadian proteins exhibit non-monotonic dependencies on the rate of expression of Per2AS. All three models provide potential explanations of the observed antiphasic, circadian oscillations of Per2 and Per2AS RNAs. They make discordant predictions that can be tested experimentally in order to distinguish among these alternative hypotheses.'),
(88898, 2018, 'plos', 'In silico analysis of antibiotic-induced Clostridium difficile infection: Remediation techniques and biological adaptations', 'Jones, Eric W|Carlson, Jean M', 'Department of Physics, University of California at Santa Barbara, Santa Barbara, California, United States of America.|Department of Physics, University of California at Santa Barbara, Santa Barbara, California, United States of America.', 'United States|United States', 0, 'Adaptation, Biological|Animals|Anti-Bacterial Agents|Clostridium Infections|Clostridium difficile|Computer Simulation|Disease Models, Animal|Fecal Microbiota Transplantation|Feces|Gastrointestinal Microbiome|Humans|Mice|Models, Theoretical|Mutation|Spores, Bacterial', 'Journal Article', '10.1371/journal.pcbi.1006001', '29451873', 'In this paper we study antibiotic-induced C. difficile infection (CDI), caused by the toxin-producing C. difficile (CD), and implement clinically-inspired simulated treatments in a computational framework that synthesizes a generalized Lotka-Volterra (gLV) model with SIR modeling techniques. The gLV model uses parameters derived from an experimental mouse model, in which the mice are administered antibiotics and subsequently dosed with CD. We numerically identify which of the experimentally measured initial conditions are vulnerable to CD colonization, then formalize the notion of CD susceptibility analytically. We simulate fecal transplantation, a clinically successful treatment for CDI, and discover that both the transplant timing and transplant donor are relevant to the the efficacy of the treatment, a result which has clinical implications. We incorporate two nongeneric yet dangerous attributes of CD into the gLV model, sporulation and antibiotic-resistant mutation, and for each identify relevant SIR techniques that describe the desired attribute. Finally, we rely on the results of our framework to analyze an experimental study of fecal transplants in mice, and are able to explain observed experimental results, validate our simulated results, and suggest model-motivated experiments.'),
(88899, 2018, 'plos', 'A stochastic and dynamical view of pluripotency in mouse embryonic stem cells', 'Lin, Yen Ting|Hufton, Peter G|Lee, Esther J|Potoyan, Davit A', 'Theoretical Division and Center for Nonlinear Studies, Los Alamos National Laboratory, Los Alamos, New Mexico, United States of America.|School of Physics and Astronomy, The University of Manchester, Manchester, United Kingdom.|Department of Bioengineering, Rice University, Houston, Texas, United States of America.|Department of Chemistry, Iowa State University, Ames, Iowa, United States of America.', 'Mexico|United Kingdom|United States|United States', 13, 'Algorithms|Animals|Cell Differentiation|Cell Lineage|Computational Biology|Epigenesis, Genetic|Gene Expression Regulation|Gene Regulatory Networks|Machine Learning|Mice|Models, Theoretical|Mouse Embryonic Stem Cells|Pluripotent Stem Cells|Principal Component Analysis|Promoter Regions, Genetic|Protein Binding|Signal Transduction|Stochastic Processes|Transcription Factors', 'Journal Article', '10.1371/journal.pcbi.1006000', '29451874', 'Pluripotent embryonic stem cells are of paramount importance for biomedical sciences because of their innate ability for self-renewal and differentiation into all major cell lines. The fateful decision to exit or remain in the pluripotent state is regulated by complex genetic regulatory networks. The rapid growth of single-cell sequencing data has greatly stimulated applications of statistical and machine learning methods for inferring topologies of pluripotency regulating genetic networks. The inferred network topologies, however, often only encode Boolean information while remaining silent about the roles of dynamics and molecular stochasticity inherent in gene expression. Herein we develop a framework for systematically extending Boolean-level network topologies into higher resolution models of networks which explicitly account for the promoter architectures and gene state switching dynamics. We show the framework to be useful for disentangling the various contributions that gene switching, external signaling, and network topology make to the global heterogeneity and dynamics of transcription factor populations. We find the pluripotent state of the network to be a steady state which is robust to global variations of gene switching rates which we argue are a good proxy for epigenetic states of individual promoters. The temporal dynamics of exiting the pluripotent state, on the other hand, is significantly influenced by the rates of genetic switching which makes cells more responsive to changes in extracellular signals.'),
(88900, 2018, 'plos', 'Control fast or control smart: When should invading pathogens be controlled?', 'Thompson, Robin N|Gilligan, Christopher A|Cunniffe, Nik J', 'Department of Plant Sciences, University of Cambridge, Cambridge CB2 3EA, United Kingdom.|Department of Plant Sciences, University of Cambridge, Cambridge CB2 3EA, United Kingdom.|Department of Plant Sciences, University of Cambridge, Cambridge CB2 3EA, United Kingdom.', 'United Kingdom|United Kingdom|United Kingdom', 0, 'Algorithms|Animals|Computer Simulation|Decision Making|Disease Outbreaks|Epidemics|Foot-and-Mouth Disease|Health Policy|Humans|Infectious Disease Medicine|Influenza, Human|Models, Biological|Probability|Vaccination', 'Journal Article', '10.1371/journal.pcbi.1006014', '29451878', 'The intuitive response to an invading pathogen is to start disease management as rapidly as possible, since this would be expected to minimise the future impacts of disease. However, since more spread data become available as an outbreak unfolds, processes underpinning pathogen transmission can almost always be characterised more precisely later in epidemics. This allows the future progression of any outbreak to be forecast more accurately, and so enables control interventions to be targeted more precisely. There is also the chance that the outbreak might die out without any intervention whatsoever, making prophylactic control unnecessary. Optimal decision-making involves continuously balancing these potential benefits of waiting against the possible costs of further spread. We introduce a generic, extensible data-driven algorithm based on parameter estimation and outbreak simulation for making decisions in real-time concerning when and how to control an invading pathogen. The Control Smart Algorithm (CSA) resolves the trade-off between the competing advantages of controlling as soon as possible and controlling later when more information has become available. We show-using a generic mathematical model representing the transmission of a pathogen of agricultural animals or plants through a population of farms or fields-how the CSA allows the timing and level of deployment of vaccination or chemical control to be optimised. In particular, the algorithm outperforms simpler strategies such as intervening when the outbreak size reaches a pre-specified threshold, or controlling when the outbreak has persisted for a threshold length of time. This remains the case even if the simpler methods are fully optimised in advance. Our work highlights the potential benefits of giving careful consideration to the question of when to start disease management during emerging outbreaks, and provides a concrete framework to allow policy-makers to make this decision.'),
(88901, 2018, 'plos', 'Trade-off between synergy and efficacy in combinations of HIV-1 latency-reversing agents', 'Gupta, Vipul|Dixit, Narendra M', 'Department of Chemical Engineering, Indian Institute of Science, Bangalore, India.|Department of Chemical Engineering, Indian Institute of Science, Bangalore, India.', 'India|India', 5, 'Anti-HIV Agents|CD4-Positive T-Lymphocytes|Computer Simulation|HIV Infections|HIV-1|Histone Deacetylase Inhibitors|Humans|Immune System|Models, Biological|Protein Kinase C|Stochastic Processes|Virus Activation|Virus Latency', 'Journal Article', '10.1371/journal.pcbi.1006004', '29451894', 'Eradicating HIV-1 infection is difficult because of the reservoir of latently infected cells that gets established soon after infection, remains hidden from antiretroviral drugs and host immune responses, and retains the capacity to reignite infection following the cessation of treatment. Drugs called latency-reversing agents (LRAs) are being developed to reactivate latently infected cells and render them susceptible to viral cytopathicity or immune killing. Whereas individual LRAs have failed to induce adequate reactivation, pairs of LRAs have been identified recently that act synergistically and hugely increase reactivation levels compared to individual LRAs. The maximum synergy achievable with LRA pairs is of clinical importance, as it would allow latency-reversal with minimal drug exposure. Here, we employed stochastic simulations of HIV-1 transcription and translation in latently infected cells to estimate this maximum synergy. We incorporated the predominant mechanisms of action of the two most promising classes of LRAs, namely, protein kinase C agonists and histone deacetylase inhibitors, and quantified the activity of individual LRAs in the two classes by mapping our simulations to corresponding in vitro experiments. Without any adjustable parameters, our simulations then quantitatively captured experimental observations of latency-reversal when the LRAs were used in pairs. Performing simulations representing a wide range of drug concentrations, we estimated the maximum synergy achievable with these LRA pairs. Importantly, we found with all the LRA pairs we considered that concentrations yielding the maximum synergy did not yield the maximum latency-reversal. Increasing concentrations to increase latency-reversal compromised synergy, unravelling a trade-off between synergy and efficacy in LRA combinations. The maximum synergy realizable with LRA pairs would thus be restricted by the desired level of latency-reversal, a constrained optimum we elucidated with our simulations. We expect this trade-off to be important in defining optimal LRA combinations that would maximize synergy while ensuring adequate latency-reversal.'),
(88902, 2018, 'plos', 'Metabolic enzyme cost explains variable trade-offs between microbial growth rate and yield', 'Wortel, Meike T|Noor, Elad|Ferris, Michael|Bruggeman, Frank J|Liebermeister, Wolfram', 'Centre for Ecological and Evolutionary Synthesis (CEES), Department of Biosciences, University of Oslo, Oslo, Norway.|Institute of Molecular Systems Biology, Eidgenössische Technische Hochschule, Zürich, Switzerland.|Computer Sciences Department and Wisconsin Institute for Discovery, University of Wisconsin, Madison, Wisconsin, United States of America.|Systems Bioinformatics Section, Amsterdam Institute for Molecules, Medicines and Systems (AIMMS), Vrije Universiteit, Amsterdam, The Netherlands.|INRA, UR1404, MaIAGE, Université Paris-Saclay, Jouy-en-Josas, France.', 'Norway|Switzerland|United States|Netherlands|France', 17, 'Biochemical Phenomena|Biomass|Enzymes|Escherichia coli|Glucose|Kinetics|Metabolic Networks and Pathways|Models, Biological|Models, Statistical|Oxygen|Systems Biology|Thermodynamics', 'Journal Article', '10.1371/journal.pcbi.1006010', '29451895', 'Microbes may maximize the number of daughter cells per time or per amount of nutrients consumed. These two strategies correspond, respectively, to the use of enzyme-efficient or substrate-efficient metabolic pathways. In reality, fast growth is often associated with wasteful, yield-inefficient metabolism, and a general thermodynamic trade-off between growth rate and biomass yield has been proposed to explain this. We studied growth rate/yield trade-offs by using a novel modeling framework, Enzyme-Flux Cost Minimization (EFCM) and by assuming that the growth rate depends directly on the enzyme investment per rate of biomass production. In a comprehensive mathematical model of core metabolism in E. coli, we screened all elementary flux modes leading to cell synthesis, characterized them by the growth rates and yields they provide, and studied the shape of the resulting rate/yield Pareto front. By varying the model parameters, we found that the rate/yield trade-off is not universal, but depends on metabolic kinetics and environmental conditions. A prominent trade-off emerges under oxygen-limited growth, where yield-inefficient pathways support a 2-to-3 times higher growth rate than yield-efficient pathways. EFCM can be widely used to predict optimal metabolic states and growth rates under varying nutrient levels, perturbations of enzyme parameters, and single or multiple gene knockouts.'),
(88903, 2018, 'plos', 'Integrating linear optimization with structural modeling to increase HIV neutralization breadth', 'Sevy, Alexander M|Panda, Swetasudha|Crowe, James E|Meiler, Jens|Vorobeychik, Yevgeniy', 'Center for Structural Biology, Vanderbilt University, Nashville, TN, United States of America.|Electrical Engineering and Computer Science, Vanderbilt University, Nashville, TN, United States of America.|Vanderbilt Vaccine Center, Vanderbilt University Medical Center, Nashville, TN, United States of America.|Center for Structural Biology, Vanderbilt University, Nashville, TN, United States of America.|Electrical Engineering and Computer Science, Vanderbilt University, Nashville, TN, United States of America.', 'United States|United States|United States|United States|United States', 3, 'Algorithms|Amino Acid Motifs|Antibodies, Neutralizing|Computational Biology|Epitopes|HIV Antibodies|HIV Infections|HIV-1|Humans|Linear Models|Machine Learning|Regression Analysis|Software|Support Vector Machine', 'Journal Article', '10.1371/journal.pcbi.1005999', '29451898', 'Computational protein design has been successful in modeling fixed backbone proteins in a single conformation. However, when modeling large ensembles of flexible proteins, current methods in protein design have been insufficient. Large barriers in the energy landscape are difficult to traverse while redesigning a protein sequence, and as a result current design methods only sample a fraction of available sequence space. We propose a new computational approach that combines traditional structure-based modeling using the Rosetta software suite with machine learning and integer linear programming to overcome limitations in the Rosetta sampling methods. We demonstrate the effectiveness of this method, which we call BROAD, by benchmarking the performance on increasing predicted breadth of anti-HIV antibodies. We use this novel method to increase predicted breadth of naturally-occurring antibody VRC23 against a panel of 180 divergent HIV viral strains and achieve 100% predicted binding against the panel. In addition, we compare the performance of this method to state-of-the-art multistate design in Rosetta and show that we can outperform the existing method significantly. We further demonstrate that sequences recovered by this method recover known binding motifs of broadly neutralizing anti-HIV antibodies. Finally, our approach is general and can be extended easily to other protein systems. Although our modeled antibodies were not tested in vitro, we predict that these variants would have greatly increased breadth compared to the wild-type antibody.'),
(88904, 2018, 'plos', 'Exploiting the geometry of the solution space to reduce sensitivity to neuromotor noise', 'Zhang, Zhaoran|Guo, Dena|Huber, Meghan E|Park, Se-Woong|Sternad, Dagmar', 'Department of Bioengineering, Northeastern University, Boston, Massachusetts, United States of America.|Department of Physics, Northeastern University, Boston, Massachusetts, United States of America.|Department of Mechanical Engineering, Massachusetts Institute of Technology, Cambridge, Massachusetts, United States of America.|Department of Biology, Northeastern University, Boston, Massachusetts, United States of America.|Department of Physics, Northeastern University, Boston, Massachusetts, United States of America.', 'United States|United States|United States|United States|United States', 5, 'Adult|Arm|Biomechanical Phenomena|Female|Hand|Humans|Male|Models, Neurological|Movement|Muscle, Skeletal|Psychomotor Performance|Regression Analysis|Reproducibility of Results|Young Adult', 'Journal Article', '10.1371/journal.pcbi.1006013', '29462147', 'Throwing is a uniquely human skill that requires a high degree of coordination to successfully hit a target. Timing of ball release appears crucial as previous studies report required timing accuracies as short as 1-2ms, which however appear physiologically challenging. This study mathematically and experimentally demonstrates that humans can overcome these seemingly stringent timing requirements by shaping their hand trajectories to create extended timing windows, where ball releases achieve target hits despite temporal imprecision. Subjects practiced four task variations in a virtual environment, each with a distinct geometry of the solution space and different demands for timing. Model-based analyses of arm trajectories revealed that subjects first decreased timing error, followed by lengthening timing windows in their hand trajectories. This pattern was invariant across solution spaces, except for a control case. Hence, the exquisite skill that humans evolved for throwing is achieved by developing strategies that are less sensitive to temporal variability arising from neuromotor noise. This analysis also provides an explanation why coaches emphasize the follow-through in many ball sports.'),
(88905, 2018, 'plos', 'The self-organization of plant microtubules inside the cell volume yields their cortical localization, stable alignment, and sensitivity to external cues', 'Mirabet, Vincent|Krupinski, Pawel|Hamant, Olivier|Meyerowitz, Elliot M|Jönsson, Henrik|Boudaoud, Arezki', 'Reproduction et Développement des Plantes, Univ. Lyon, ENS de Lyon, UCB Lyon 1, CNRS, INRA, F-69364 Lyon, France.|Computational Biology and Biological Physics Group, Department of Theoretical Physics, Lund University, Lund, Sweden.|Reproduction et Développement des Plantes, Univ. Lyon, ENS de Lyon, UCB Lyon 1, CNRS, INRA, F-69364 Lyon, France.|Sainsbury Laboratory, University of Cambridge, Cambridge, United Kingdom.|Sainsbury Laboratory, University of Cambridge, Cambridge, United Kingdom.|Reproduction et Développement des Plantes, Univ. Lyon, ENS de Lyon, UCB Lyon 1, CNRS, INRA, F-69364 Lyon, France.', 'France|Sweden|France|United Kingdom|United Kingdom|France', 0, 'Anisotropy|Cell Membrane|Cell Shape|Cell Size|Cell Wall|Cellulose|Computer Simulation|Cytoplasm|Microtubules|Plant Cells', 'Journal Article', '10.1371/journal.pcbi.1006011', '29462151', 'Many cell functions rely on the ability of microtubules to self-organize as complex networks. In plants, cortical microtubules are essential to determine cell shape as they guide the deposition of cellulose microfibrils, and thus control mechanical anisotropy of the cell wall. Here we analyze how, in turn, cell shape may influence microtubule behavior. Building upon previous models that confined microtubules to the cell surface, we introduce an agent model of microtubules enclosed in a three-dimensional volume. We show that the microtubule network has spontaneous aligned configurations that could explain many experimental observations without resorting to specific regulation. In particular, we find that the preferred cortical localization of microtubules emerges from directional persistence of the microtubules, and their interactions with each other and with the stiff wall. We also identify microtubule parameters that seem relatively insensitive to cell shape, such as length or number. In contrast, microtubule array anisotropy depends on local curvature of the cell surface and global orientation follows robustly the longest axis of the cell. Lastly, we find that geometric cues may be overcome, as the network is capable of reorienting toward weak external directional cues. Altogether our simulations show that the microtubule network is a good transducer of weak external polarity, while at the same time, easily reaching stable global configurations.');
INSERT INTO `papers` (`id`, `ano`, `journal`, `titulo`, `autores`, `afiliacao`, `pais`, `citacoes`, `palavra_chave`, `categorias`, `doi`, `pubmed`, `abstract`) VALUES
(88906, 2018, 'plos', 'Prediction of infectious disease epidemics via weighted density ensembles', 'Ray, Evan L|Reich, Nicholas G', 'Department of Mathematics and Statistics, Mount Holyoke College, South Hadley, Massachusetts, United States of America.|Department of Biostatistics and Epidemiology, University of Massachusetts, Amherst, Massachusetts, United States of America.', 'United States|United States', 24, 'Algorithms|Centers for Disease Control and Prevention (U.S.)|Communicable Diseases|Computational Biology|Epidemics|Humans|Incidence|Infectious Disease Medicine|Influenza, Human|Models, Biological|Models, Statistical|Predictive Value of Tests|Prospective Studies|Public Health|Reproducibility of Results|Retrospective Studies|Seasons|Uncertainty|United States', 'Journal Article', '10.1371/journal.pcbi.1005910', '29462167', 'Accurate and reliable predictions of infectious disease dynamics can be valuable to public health organizations that plan interventions to decrease or prevent disease transmission. A great variety of models have been developed for this task, using different model structures, covariates, and targets for prediction. Experience has shown that the performance of these models varies, some tend to do better or worse in different seasons or at different points within a season. Ensemble methods combine multiple models to obtain a single prediction that leverages the strengths of each model. We considered a range of ensemble methods that each form a predictive density for a target of interest as a weighted sum of the predictive densities from component models. In the simplest case, equal weight is assigned to each component model, in the most complex case, the weights vary with the region, prediction target, week of the season when the predictions are made, a measure of component model uncertainty, and recent observations of disease incidence. We applied these methods to predict measures of influenza season timing and severity in the United States, both at the national and regional levels, using three component models. We trained the models on retrospective predictions from 14 seasons (1997/1998-2010/2011) and evaluated each models prospective, out-of-sample performance in the five subsequent influenza seasons. In this test phase, the ensemble methods showed average performance that was similar to the best of the component models, but offered more consistent performance across seasons than the component models. Ensemble methods offer the potential to deliver more reliable predictions to public health decision makers.'),
(88907, 2018, 'plos', 'Memory functions reveal structural properties of gene regulatory networks', 'Herrera-Delgado, Edgar|Perez-Carrasco, Ruben|Briscoe, James|Sollich, Peter', 'The Francis Crick Institute, London, United Kingdom.|The Francis Crick Institute, London, United Kingdom.|The Francis Crick Institute, London, United Kingdom.|Department of Mathematics, Kings College London, Strand, London, United Kingdom.', 'United Kingdom|United Kingdom|United Kingdom|United Kingdom', 6, 'Algorithms|Amino Acid Motifs|Animals|DNA|Gene Expression Regulation|Gene Regulatory Networks|Memory|Mice|Models, Genetic|Models, Statistical|Neural Networks (Computer)|Neural Tube|Neurons|Nonlinear Dynamics|Oligodendrocyte Transcription Factor 2|PAX6 Transcription Factor|Stochastic Processes|Systems Biology|Thermodynamics', 'Journal Article', '10.1371/journal.pcbi.1006003', '29470492', 'Gene regulatory networks (GRNs) control cellular function and decision making during tissue development and homeostasis. Mathematical tools based on dynamical systems theory are often used to model these networks, but the size and complexity of these models mean that their behaviour is not always intuitive and the underlying mechanisms can be difficult to decipher. For this reason, methods that simplify and aid exploration of complex networks are necessary. To this end we develop a broadly applicable form of the Zwanzig-Mori projection. By first converting a thermodynamic state ensemble model of gene regulation into mass action reactions we derive a general method that produces a set of time evolution equations for a subset of components of a network. The influence of the rest of the network, the bulk, is captured by memory functions that describe how the subnetwork reacts to its own past state via components in the bulk. These memory functions provide probes of near-steady state dynamics, revealing information not easily accessible otherwise. We illustrate the method on a simple cross-repressive transcriptional motif to show that memory functions not only simplify the analysis of the subnetwork but also have a natural interpretation. We then apply the approach to a GRN from the vertebrate neural tube, a well characterised developmental transcriptional network composed of four interacting transcription factors. The memory functions reveal the function of specific links within the neural tube network and identify features of the regulatory structure that specifically increase the robustness of the network to initial conditions. Taken together, the study provides evidence that Zwanzig-Mori projections offer powerful and effective tools for simplifying and exploring the behaviour of GRNs.'),
(88908, 2018, 'plos', 'Association between expression of random gene sets and survival is evident in multiple cancer types and may be explained by sub-classification', 'Shimoni, Yishai', 'IBM Research-Haifa, Haifa, Israel.', 'Israel', 0, 'Adenocarcinoma|Algorithms|Brain Neoplasms|Breast Neoplasms|Cell Proliferation|Cluster Analysis|Cohort Studies|Colonic Neoplasms|Databases, Genetic|Disease Progression|Gene Expression Profiling|Gene Expression Regulation, Neoplastic|Genome, Human|Glioblastoma|Humans|Oligonucleotide Array Sequence Analysis|Probability|Prognosis|Sequence Analysis, RNA', 'Journal Article', '10.1371/journal.pcbi.1006026', '29470520', 'One of the goals of cancer research is to identify a set of genes that cause or control disease progression. However, although multiple such gene sets were published, these are usually in very poor agreement with each other, and very few of the genes proved to be functional therapeutic targets. Furthermore, recent findings from a breast cancer gene-expression cohort showed that sets of genes selected randomly can be used to predict survival with a much higher probability than expected. These results imply that many of the genes identified in breast cancer gene expression analysis may not be causal of cancer progression, even though they can still be highly predictive of prognosis. We performed a similar analysis on all the cancer types available in the cancer genome atlas (TCGA), namely, estimating the predictive power of random gene sets for survival. Our work shows that most cancer types exhibit the property that random selections of genes are more predictive of survival than expected. In contrast to previous work, this property is not removed by using a proliferation signature, which implies that proliferation may not always be the confounder that drives this property. We suggest one possible solution in the form of data-driven sub-classification to reduce this property significantly. Our results suggest that the predictive power of random gene sets may be used to identify the existence of sub-classes in the data, and thus may allow better understanding of patient stratification. Furthermore, by reducing the observed bias this may allow more direct identification of biologically relevant, and potentially causal, genes.'),
(88909, 2018, 'plos', 'A biophysical model of dynamic balancing of excitation and inhibition in fast oscillatory large-scale networks', 'Abeysuriya, Romesh G|Hadida, Jonathan|Sotiropoulos, Stamatios N|Jbabdi, Saad|Becker, Robert|Hunt, Benjamin A E|Brookes, Matthew J|Woolrich, Mark W', 'Oxford Centre for Human Brain Activity, Wellcome Centre for Integrative Neuroimaging, Department of Psychiatry, University of Oxford, United Kingdom.|Oxford Centre for Human Brain Activity, Wellcome Centre for Integrative Neuroimaging, Department of Psychiatry, University of Oxford, United Kingdom.|Oxford Centre for Functional Magnetic Resonance Imaging of the Brain, Wellcome Centre for Integrative Neuroimaging, University of Oxford, United Kingdom.|Oxford Centre for Functional Magnetic Resonance Imaging of the Brain, Wellcome Centre for Integrative Neuroimaging, University of Oxford, United Kingdom.|Oxford Centre for Human Brain Activity, Wellcome Centre for Integrative Neuroimaging, Department of Psychiatry, University of Oxford, United Kingdom.|Sir Peter Mansfield Imaging Centre, School of Physics and Astronomy, University of Nottingham, United Kingdom.|Sir Peter Mansfield Imaging Centre, School of Physics and Astronomy, University of Nottingham, United Kingdom.|Oxford Centre for Human Brain Activity, Wellcome Centre for Integrative Neuroimaging, Department of Psychiatry, University of Oxford, United Kingdom.', 'United Kingdom|United Kingdom|United Kingdom|United Kingdom|United Kingdom|United Kingdom|United Kin', 0, 'Brain|Brain Mapping|Connectome|Electrophysiology|Humans|Magnetoencephalography|Models, Neurological|Nerve Net|Neural Inhibition|Neural Pathways|Neuronal Plasticity|Neurons|Oscillometry|Population Dynamics|Rest', 'Journal Article', '10.1371/journal.pcbi.1006007', '29474352', 'Over long timescales, neuronal dynamics can be robust to quite large perturbations, such as changes in white matter connectivity and grey matter structure through processes including learning, aging, development and certain disease processes. One possible explanation is that robust dynamics are facilitated by homeostatic mechanisms that can dynamically rebalance brain networks. In this study, we simulate a cortical brain network using the Wilson-Cowan neural mass model with conduction delays and noise, and use inhibitory synaptic plasticity (ISP) to dynamically achieve a spatially local balance between excitation and inhibition. Using MEG data from 55 subjects we find that ISP enables us to simultaneously achieve high correlation with multiple measures of functional connectivity, including amplitude envelope correlation and phase locking. Further, we find that ISP successfully achieves local E/I balance, and can consistently predict the functional connectivity computed from real MEG data, for a much wider range of model parameters than is possible with a model without ISP.'),
(88910, 2018, 'plos', 'PhysiCell: An open source physics-based cell simulator for 3-D multicellular systems', 'Ghaffarizadeh, Ahmadreza|Heiland, Randy|Friedman, Samuel H|Mumenthaler, Shannon M|Macklin, Paul', 'Lawrence J. Ellison Institute for Transformative Medicine, University of Southern California, Los Angeles, California, United States of America.|Intelligent Systems Engineering, Indiana University, Bloomington, Indiana, United States of America.|Lawrence J. Ellison Institute for Transformative Medicine, University of Southern California, Los Angeles, California, United States of America.|Lawrence J. Ellison Institute for Transformative Medicine, University of Southern California, Los Angeles, California, United States of America.|Lawrence J. Ellison Institute for Transformative Medicine, University of Southern California, Los Angeles, California, United States of America.', 'United States|India|United States|United States|United States', 0, 'Apoptosis|Biological Transport|Biomechanical Phenomena|Breast Neoplasms|Carcinoma, Intraductal, Noninfiltrating|Cell Communication|Cell Cycle|Computational Biology|Computer Simulation|Female|Humans|Immune System|Models, Biological|Necrosis|Phenotype|Reproducibility of Results|Signal Transduction|Software|Spheroids, Cellular|Stochastic Processes|Systems Biology', 'Journal Article', '10.1371/journal.pcbi.1005991', '29474446', 'Many multicellular systems problems can only be understood by studying how cells move, grow, divide, interact, and die. Tissue-scale dynamics emerge from systems of many interacting cells as they respond to and influence their microenvironment. The ideal virtual laboratory for such multicellular systems simulates both the biochemical microenvironment (the stage) and many mechanically and biochemically interacting cells (the players upon the stage). PhysiCell-physics-based multicellular simulator-is an open source agent-based simulator that provides both the stage and the players for studying many interacting cells in dynamic tissue microenvironments. It builds upon a multi-substrate biotransport solver to link cell phenotype to multiple diffusing substrates and signaling factors. It includes biologically-driven sub-models for cell cycling, apoptosis, necrosis, solid and fluid volume changes, mechanics, and motility out of the box. The C++ code has minimal dependencies, making it simple to maintain and deploy across platforms. PhysiCell has been parallelized with OpenMP, and its performance scales linearly with the number of cells. Simulations up to 105-106 cells are feasible on quad-core desktop workstations, larger simulations are attainable on single HPC compute nodes. We demonstrate PhysiCell by simulating the impact of necrotic core biomechanics, 3-D geometry, and stochasticity on the dynamics of hanging drop tumor spheroids and ductal carcinoma in situ (DCIS) of the breast. We demonstrate stochastic motility, chemical and contact-based interaction of multiple cell types, and the extensibility of PhysiCell with examples in synthetic multicellular systems (a cellular cargo delivery system, with application to anti-cancer treatments), cancer heterogeneity, and cancer immunology. PhysiCell is a powerful multicellular systems simulator that will be continually improved with new capabilities and performance improvements. It also represents a significant independent code base for replicating results from other simulation platforms. The PhysiCell source code, examples, documentation, and support are available under the BSD license at http://PhysiCell.MathCancer.org and http://PhysiCell.sf.net.'),
(88911, 2018, 'plos', 'Systems-level computational modeling demonstrates fuel selection switching in high capacity running and low capacity running rats', 'Moxley, Michael A|Vinnakota, Kalyan C|Bazil, Jason N|Qi, Nathan R|Beard, Daniel A', 'Department of Molecular and Integrative Physiology, University of Michigan, Ann Arbor, Michigan, United States of America.|Department of Molecular and Integrative Physiology, University of Michigan, Ann Arbor, Michigan, United States of America.|Department of Physiology, Michigan State University, East Lansing, MI, United States of America.|Department of Internal Medicine, University of Michigan, Ann Arbor, MI, United States of America.|Department of Molecular and Integrative Physiology, University of Michigan, Ann Arbor, Michigan, United States of America.', 'United States|United States|United States|United States|United States', 0, 'Adenosine Triphosphatases|Adenosine Triphosphate|Algorithms|Animals|Carbon Dioxide|Computer Simulation|Fatty Acids|Glucose|Mitochondria|Models, Statistical|Muscle, Skeletal|Oxidation-Reduction|Oxygen|Physical Conditioning, Animal|Proteomics|Rats|Running|Thermodynamics', 'Journal Article', '10.1371/journal.pcbi.1005982', '29474500', 'High capacity and low capacity running rats, HCR and LCR respectively, have been bred to represent two extremes of running endurance and have recently demonstrated disparities in fuel usage during transient aerobic exercise. HCR rats can maintain fatty acid (FA) utilization throughout the course of transient aerobic exercise whereas LCR rats rely predominantly on glucose utilization. We hypothesized that the difference between HCR and LCR fuel utilization could be explained by a difference in mitochondrial density. To test this hypothesis and to investigate mechanisms of fuel selection, we used a constraint-based kinetic analysis of whole-body metabolism to analyze transient exercise data from these rats. Our model analysis used a thermodynamically constrained kinetic framework that accounts for glycolysis, the TCA cycle, and mitochondrial FA transport and oxidation. The model can effectively match the observed relative rates of oxidation of glucose versus FA, as a function of ATP demand. In searching for the minimal differences required to explain metabolic function in HCR versus LCR rats, it was determined that the whole-body metabolic phenotype of LCR, compared to the HCR, could be explained by a ~50% reduction in total mitochondrial activity with an additional 5-fold reduction in mitochondrial FA transport activity. Finally, we postulate that over sustained periods of exercise that LCR can partly overcome the initial deficit in FA catabolic activity by upregulating FA transport and/or oxidation processes.'),
(88912, 2018, 'plos', 'Differential tissue growth and cell adhesion alone drive early tooth morphogenesis: An ex vivo and in silico study', 'Marin-Riera, Miquel|Moustakas-Verho, Jacqueline|Savriama, Yoland|Jernvall, Jukka|Salazar-Ciudad, Isaac', 'Department of Genetics and Microbiology, Universitat Autònoma de Barcelona, Barcelona, Spain.|Centre of Excellence in Experimental and Computational Developmental Biology, Institute of Biotechnology, University of Helsinki, Helsinki, Finland.|Centre of Excellence in Experimental and Computational Developmental Biology, Institute of Biotechnology, University of Helsinki, Helsinki, Finland.|Centre of Excellence in Experimental and Computational Developmental Biology, Institute of Biotechnology, University of Helsinki, Helsinki, Finland.|Department of Genetics and Microbiology, Universitat Autònoma de Barcelona, Barcelona, Spain.', 'Spain|Finland|Finland|Finland|Spain', 0, 'Animals|Cell Adhesion|Cell Movement|Cell Proliferation|Computer Simulation|Dentin|Ectoderm|Epithelial Cells|Gastrulation|Gene Expression Regulation, Developmental|In Vitro Techniques|Mesoderm|Mice|Models, Biological|Odontogenesis|Signal Transduction|Stress, Mechanical|Tooth', 'Journal Article', '10.1371/journal.pcbi.1005981', '29481561', 'From gastrulation to late organogenesis animal development involves many genetic and bio-mechanical interactions between epithelial and mesenchymal tissues. Ectodermal organs, such as hairs, feathers and teeth are well studied examples of organs whose development is based on epithelial-mesenchymal interactions. These develop from a similar primordium through an epithelial folding and its interaction with the mesenchyme. Despite extensive knowledge on the molecular pathways involved, little is known about the role of bio-mechanical processes in the morphogenesis of these organs. We propose a simple computational model for the biomechanics of one such organ, the tooth, and contrast its predictions against cell-tracking experiments, mechanical relaxation experiments and the observed tooth shape changes over developmental time. We found that two biomechanical processes, differential tissue growth and differential cell adhesion, were enough, in the model, for the development of the 3D morphology of the early tooth germ. This was largely determined by the length and direction of growth of the cervical loops, lateral folds of the enamel epithelium. The formation of these cervical loops was found to require accelerated epithelial growth relative to other tissues and their direction of growth depended on specific differential adhesion between the three tooth tissues. These two processes and geometrical constraints in early tooth bud also explained the shape asymmetry between the lateral cervical loops and those forming in the anterior and posterior of the tooth. By performing mechanical perturbations ex vivo and in silico we inferred the distribution and direction of tensile stresses in the mesenchyme that restricted cervical loop lateral growth and forced them to grow downwards. Overall our study suggests detailed quantitative explanations for how bio-mechanical processes lead to specific morphological 3D changes over developmental time.'),
(88913, 2018, 'plos', 'Mathematical modelling of the antibiotic-induced morphological transition of Pseudomonas aeruginosa', 'Spalding, Chloe|Keen, Emma|Smith, David J|Krachler, Anne-Marie|Jabbari, Sara', 'School of Mathematics, University of Birmingham, Edgbaston Campus, Birmingham, United Kingdom.|Institute of Microbiology and Infection, School of Biosciences, University of Birmingham, Edgbaston Campus, Birmingham, United Kingdom.|School of Mathematics, University of Birmingham, Edgbaston Campus, Birmingham, United Kingdom.|Department of Microbiology and Molecular Genetics, University of Texas McGovern Medical School at Houston, Houston, Texas, United States of America.|School of Mathematics, University of Birmingham, Edgbaston Campus, Birmingham, United Kingdom.', 'United Kingdom|United Kingdom|United Kingdom|United States|United Kingdom', 0, 'Anti-Bacterial Agents|Antimicrobial Cationic Peptides|Cytoplasm|Humans|Meropenem|Microbial Sensitivity Tests|Microscopy, Fluorescence|Models, Theoretical|Phenotype|Pseudomonas Infections|Pseudomonas aeruginosa|Thienamycins|beta-Lactamases', 'Journal Article', '10.1371/journal.pcbi.1006012', '29481562', 'Here we formulate a mechanistic mathematical model to describe the growth dynamics of P. aeruginosa in the presence of the xcexb2-lactam antibiotic meropenem. The model is mechanistic in the sense that carrying capacity is taken into account through the dynamics of nutrient availability rather than via logistic growth. In accordance with our experimental results we incorporate a sub-population of cells, differing in morphology from the normal bacillary shape of P. aeruginosa bacteria, which we assume have immunity from direct antibiotic action. By fitting this model to experimental data we obtain parameter values that give insight into the growth of a bacterial population that includes different cell morphologies. The analysis of two parameters sets, that produce different long term behaviour, allows us to manipulate the system theoretically in order to explore the advantages of a shape transition that may potentially be a mechanism that allows P. aeruginosa to withstand antibiotic effects. Our results suggest that inhibition of this shape transition may be detrimental to bacterial growth and thus suggest that the transition may be a defensive mechanism implemented by bacterial machinery. In addition to this we provide strong theoretical evidence for the potential therapeutic strategy of using antimicrobial peptides (AMPs) in combination with meropenem. This proposed combination therapy exploits the shape transition as AMPs induce cell lysis by forming pores in the cytoplasmic membrane, which becomes exposed in the spherical cells.'),
(88914, 2018, 'plos', 'Multiscale modeling of layer formation in epidermis', 'Du, Huijing|Wang, Yangyang|Haensel, Daniel|Lee, Briana|Dai, Xing|Nie, Qing', 'Department of Mathematics, University of Nebraska-Lincoln, Lincoln, NE, United States of America.|Department of Mathematics, University of California Irvine, Irvine, CA, United States of America.|Center for Complex Biological Systems, University of California Irvine, Irvine, CA, United States of America.|Center for Complex Biological Systems, University of California Irvine, Irvine, CA, United States of America.|Center for Complex Biological Systems, University of California Irvine, Irvine, CA, United States of America.|Department of Mathematics, University of California Irvine, Irvine, CA, United States of America.', 'United States|United States|United States|United States|United States|United States', 9, 'Algorithms|Animals|Biomechanical Phenomena|Cell Adhesion|Cell Differentiation|Cell Division|Cell Lineage|Cell Proliferation|Computer Graphics|Computer Simulation|Epidermal Cells|Epidermis|Gene Expression Regulation|Gene Expression Regulation, Developmental|Homeostasis|Humans|Imaging, Three-Dimensional|Mice|Mice, Transgenic|Models, Biological|Models, Statistical|Signal Transduction|Stem Cells|Stochastic Processes|Transcription Factors|Wound Healing', 'Journal Article', '10.1371/journal.pcbi.1006006', '29481568', 'The mammalian skin epidermis is a stratified epithelium composed of multiple layers of epithelial cells that exist in appropriate sizes and proportions, and with distinct boundaries separating each other. How the epidermis develops from a single layer of committed precursor cells to form a complex multilayered structure of multiple cell types remains elusive. Here, we construct stochastic, three-dimensional, and multiscale models consisting of a lineage of multiple cell types to study the control of epidermal development. Symmetric and asymmetric cell divisions, stochastic cell fate transitions within the lineage, extracellular morphogens, cell-to-cell adhesion forces, and cell signaling are included in model. A GPU algorithm was developed and implemented to accelerate the simulations. These simulations show that a balance between cell proliferation and differentiation during lineage progression is crucial for the development and maintenance of the epidermal tissue. We also find that selective intercellular adhesion is critical to sharpening the boundary between layers and to the formation of a highly ordered structure. The long-range action of a morphogen provides additional feedback regulations, enhancing the robustness of overall layer formation. Our model is built upon previous experimental findings revealing the role of Ovol transcription factors in regulating epidermal development. Direct comparisons of experimental and simulation perturbations show remarkable consistency. Taken together, our results highlight the major determinants of a well-stratified epidermis: balanced proliferation and differentiation, and a combination of both short- (symmetric/asymmetric division and selective cell adhesion) and long-range (morphogen) regulations. These underlying principles have broad implications for other developmental or regenerative processes leading to the formation of multilayered tissue structures, as well as for pathological processes such as epidermal wound healing.'),
(88915, 2018, 'plos', 'Genetic programming based models in plant tissue culture: An addendum to traditional statistical approach', 'Mridula, Meenu R|Nair, Ashalatha S|Kumar, K Satheesh', 'Department of Botany, University of Kerala, Kariavattom, Thiruvananthapuram, Kerala, India.|Department of Botany, University of Kerala, Kariavattom, Thiruvananthapuram, Kerala, India.|Department of Future Studies, University of Kerala, Kariavattom, Thiruvananthapuram, Kerala, India.', 'India|India|India', 0, 'Acetic Acid|Algorithms|Charcoal|Culture Media|Genes, Plant|Magnoliopsida|Models, Genetic|Models, Statistical|Naphthalenes|Plant Growth Regulators|Plant Roots|Plant Shoots|Regeneration|Regression Analysis|Tissue Culture Techniques', 'Journal Article', '10.1371/journal.pcbi.1005976', '29485995', 'In this paper, we compared the efficacy of observation based modeling approach using a genetic algorithm with the regular statistical analysis as an alternative methodology in plant research. Preliminary experimental data on in vitro rooting was taken for this study with an aim to understand the effect of charcoal and naphthalene acetic acid (NAA) on successful rooting and also to optimize the two variables for maximum result. Observation-based modelling, as well as traditional approach, could identify NAA as a critical factor in rooting of the plantlets under the experimental conditions employed. Symbolic regression analysis using the software deployed here optimised the treatments studied and was successful in identifying the complex non-linear interaction among the variables, with minimalistic preliminary data. The presence of charcoal in the culture medium has a significant impact on root generation by reducing basal callus mass formation. Such an approach is advantageous for establishing in vitro culture protocols as these models will have significant potential for saving time and expenditure in plant tissue culture laboratories, and it further reduces the need for specialised background.'),
(88916, 2018, 'plos', 'Ligand-induced perturbation of the HIF-2xcexb1:ARNT dimer dynamics', 'Motta, Stefano|Minici, Claudia|Corrada, Dario|Bonati, Laura|Pandini, Alessandro', 'Department of Earth and Environmental Sciences, University of Milano-Bicocca, Milan, Italy.|Department of Immunology, Transplantation, and Infectious Diseases, DIBIT Fondazione San Raffaele, Milan, Italy.|Department of Earth and Environmental Sciences, University of Milano-Bicocca, Milan, Italy.|Department of Earth and Environmental Sciences, University of Milano-Bicocca, Milan, Italy.|Department of Computer Science-Synthetic Biology Theme, Brunel University London, Uxbridge, United Kingdom.', 'Italy|Italy|Italy|Italy|United Kingdom', 7, 'Animals|Aryl Hydrocarbon Receptor Nuclear Translocator|Basic Helix-Loop-Helix Transcription Factors|Crystallography, X-Ray|Ligands|Mice|Molecular Dynamics Simulation|Mutation|Oscillometry|Oxygen|Protein Binding|Protein Domains|Protein Multimerization|Thermodynamics|Transcription, Genetic|Water', 'Journal Article', '10.1371/journal.pcbi.1006021', '29489822', 'Hypoxia inducible factors (HIFs) are transcription factors belonging to the basic helix-loop-helix PER-ARNT-SIM (bHLH-PAS) protein family with a role in sensing oxygen levels in the cell. Under hypoxia, the HIF-xcexb1 degradation pathway is blocked and dimerization with the aryl hydrocarbon receptor nuclear translocator (ARNT) makes HIF-xcexb1 transcriptionally active. Due to the common hypoxic environment of tumors, inhibition of this mechanism by destabilization of HIF-xcexb1:ARNT dimerization has been proposed as a promising therapeutic strategy. Following the discovery of a druggable cavity within the PAS-B domain of HIF-2xcexb1, research efforts have been directed to identify artificial ligands that can impair heterodimerization. Although the crystallographic structures of the HIF-2xcexb1:ARNT complex have elucidated the dimer architecture and the 0X3-inhibitor placement within the HIF-2xcexb1 PAS-B, unveiling the inhibition mechanism requires investigation of how ligand-induced perturbations could dynamically propagate through the structure and affect dimerization. To this end, we compared evolutionary features, intrinsic dynamics and energetic properties of the dimerization interfaces of HIF-2xcexb1:ARNT in both the apo and holo forms. Residue conservation analysis highlighted inter-domain connecting elements that have a role in dimerization. Analysis of domain contributions to the dimerization energy demonstrated the importance of bHLH and PAS-A of both partners and of HIF-2xcexb1 PAS-B domain in dimer stabilization. Among quaternary structure oscillations revealed by Molecular Dynamics simulations, the hinge-bending motion of the ARNT PAS-B domain around the flexible PAS-A/PAS-B linker supports a general model for ARNT dimerization in different heterodimers. Comparison of the HIF-2xcexb1:ARNT dynamics in the apo and 0X3-bound forms indicated a model of inhibition where the HIF-2xcexb1-PAS-B interfaces are destabilised as a result of water-bridged ligand-protein interactions and these local effects allosterically propagate to perturb the correlated motions of the domains and inter-domain communication. These findings will guide the design of improved inhibitors to contrast cell survival in tumor masses.'),
(88917, 2018, 'plos', 'Inverse tissue mechanics of cell monolayer expansion', 'Kondo, Yohei|Aoki, Kazuhiro|Ishii, Shin', 'Graduate School of Informatics, Kyoto University, Kyoto, Japan.|Division of Quantitative Biology, National Institute for Basic Biology, Aichi, Japan.|Graduate School of Informatics, Kyoto University, Kyoto, Japan.', 'Japan|Japan|Japan', 0, 'Animals|Biomechanical Phenomena|Cell Culture Techniques|Cell Cycle|Cell Movement|Cell Proliferation|Dogs|Elastic Modulus|Elasticity|Machine Learning|Madin Darby Canine Kidney Cells|Mechanotransduction, Cellular|Microscopy, Atomic Force|Models, Biological|Morphogenesis|Stress, Mechanical', 'Journal Article', '10.1371/journal.pcbi.1006029', '29494578', 'Living tissues undergo deformation during morphogenesis. In this process, cells generate mechanical forces that drive the coordinated cell motion and shape changes. Recent advances in experimental and theoretical techniques have enabled in situ measurement of the mechanical forces, but the characterization of mechanical properties that determine how these forces quantitatively affect tissue deformation remains challenging, and this represents a major obstacle for the complete understanding of morphogenesis. Here, we proposed a non-invasive reverse-engineering approach for the estimation of the mechanical properties, by combining tissue mechanics modeling and statistical machine learning. Our strategy is to model the tissue as a continuum mechanical system and to use passive observations of spontaneous tissue deformation and force fields to statistically estimate the model parameters. This method was applied to the analysis of the collective migration of Madin-Darby canine kidney cells, and the tissue flow and force were simultaneously observed by the phase contrast imaging and traction force microscopy. We found that our monolayer elastic model, whose elastic moduli were reverse-engineered, enabled a long-term forecast of the traction force fields when given the tissue flow fields, indicating that the elasticity contributes to the evolution of the tissue stress. Furthermore, we investigated the tissues in which myosin was inhibited by blebbistatin treatment, and observed a several-fold reduction in the elastic moduli. The obtained results validate our framework, which paves the way to the estimation of mechanical properties of living tissues during morphogenesis.'),
(88918, 2018, 'plos', 'Ten simple rules for collaborative lesson development', 'Devenyi, Gabriel A|Emonet, Rémi|Harris, Rayna M|Hertweck, Kate L|Irving, Damien|Milligan, Ian|Wilson, Greg', 'Douglas Mental Health University Institute, McGill University, Montreal, Quebec, Canada.|Univ Lyon, UJM-Saint-Etienne, Saint-Étienne, France.|The University of Texas at Austin, Austin, Texas, United States of America.|The University of Texas at Tyler, Tyler, Texas, United States of America.|CSIRO Oceans and Atmosphere, Hobart, Tasmania, Australia.|University of Waterloo, Waterloo, Ontario, Canada.|DataCamp, Toronto, Ontario, Canada.', 'Canada|France|United States|United States|Australia|Canada|Canada', 6, 'Cooperative Behavior|Databases, Factual|Humans|Informatics|Software', 'Editorial', '10.1371/journal.pcbi.1005963', '29494585', '-'),
(88919, 2018, 'plos', 'An evolutionary learning and network approach to identifying key metabolites for osteoarthritis', 'Hu, Ting|Oksanen, Karoliina|Zhang, Weidong|Randell, Ed|Furey, Andrew|Sun, Guang|Zhai, Guangju', 'Department of Computer Science, Memorial University, St. Johns, Newfoundland and Labrador, Canada.|Department of Computer Science, Memorial University, St. Johns, Newfoundland and Labrador, Canada.|Faculty of Medicine, Memorial University, St. Johns, Newfoundland and Labrador, Canada.|Faculty of Medicine, Memorial University, St. Johns, Newfoundland and Labrador, Canada.|Faculty of Medicine, Memorial University, St. Johns, Newfoundland and Labrador, Canada.|Faculty of Medicine, Memorial University, St. Johns, Newfoundland and Labrador, Canada.|Faculty of Medicine, Memorial University, St. Johns, Newfoundland and Labrador, Canada.', 'Canada|Canada|Canada|Canada|Canada|Canada|Canada', 0, 'Algorithms|Databases, Factual|Humans|Machine Learning|Metabolome|Metabolomics|Osteoarthritis|ROC Curve|Systems Biology', 'Journal Article', '10.1371/journal.pcbi.1005986', '29494586', 'Metabolomics studies use quantitative analyses of metabolites from body fluids or tissues in order to investigate a sequence of cellular processes and biological systems in response to genetic and environmental influences. This promises an immense potential for a better understanding of the pathogenesis of complex diseases. Most conventional metabolomics analysis methods exam one metabolite at a time and may overlook the synergistic effect of combining multiple metabolites. In this article, we proposed a new bioinformatics framework that infers the non-linear synergy among multiple metabolites using a symbolic model and subsequently, identify key metabolites using network analysis. Such a symbolic model is able to represent a complex non-linear relationship among a set of metabolites associated with osteoarthritis (OA) and is automatically learned using an evolutionary algorithm. Applied to the Newfoundland Osteoarthritis Study (NFOAS) dataset, our methodology was able to identify nine key metabolites including some known osteoarthritis-associated metabolites and some novel metabolic markers that have never been reported before. The results demonstrate the effectiveness of our methodology and more importantly, with further investigations, propose new hypotheses that can help better understand the OA disease.'),
(88920, 2018, 'plos', 'speaq 20: A complete workflow for high-throughput 1D NMR spectra processing and quantification', 'Beirnaert, Charlie|Meysman, Pieter|Vu, Trung Nghia|Hermans, Nina|Apers, Sandra|Pieters, Luc|Covaci, Adrian|Laukens, Kris', 'Adrem Data Lab, Department of Mathematics and Computer Science, University of Antwerp, Antwerp, Belgium.|Adrem Data Lab, Department of Mathematics and Computer Science, University of Antwerp, Antwerp, Belgium.|Department of Medical Epidemiology and Biostatistics, Karolinska Institutet, Stockholm, Sweden.|Natural Products & Food Research and Analysis (NatuRA), Department of Pharmaceutical Sciences, University of Antwerp, Wilrijk, Belgium.|Natural Products & Food Research and Analysis (NatuRA), Department of Pharmaceutical Sciences, University of Antwerp, Wilrijk, Belgium.|Natural Products & Food Research and Analysis (NatuRA), Department of Pharmaceutical Sciences, University of Antwerp, Wilrijk, Belgium.|Toxicological Center, Department of Pharmaceutical Sciences, University of Antwerp, Wilrijk, Belgium.|Adrem Data Lab, Department of Mathematics and Computer Science, University of Antwerp, Antwerp, Belgium.', 'Belgium|Belgium|Sweden|Belgium|Belgium|Belgium|Belgium|Belgium', 0, 'Algorithms|Chromatography, Liquid|Magnetic Resonance Imaging|Magnetic Resonance Spectroscopy|Metabolomics|Software|Workflow', 'Journal Article', '10.1371/journal.pcbi.1006018', '29494588', 'Nuclear Magnetic Resonance (NMR) spectroscopy is, together with liquid chromatography-mass spectrometry (LC-MS), the most established platform to perform metabolomics. In contrast to LC-MS however, NMR data is predominantly being processed with commercial software. Meanwhile its data processing remains tedious and dependent on user interventions. As a follow-up to speaq, a previously released workflow for NMR spectral alignment and quantitation, we present speaq 2.0. This completely revised framework to automatically analyze 1D NMR spectra uses wavelets to efficiently summarize the raw spectra with minimal information loss or user interaction. The tool offers a fast and easy workflow that starts with the common approach of peak-picking, followed by grouping, thus avoiding the binning step. This yields a matrix consisting of features, samples and peak values that can be conveniently processed either by using included multivariate statistical functions or by using many other recently developed methods for NMR data analysis. speaq 2.0 facilitates robust and high-throughput metabolomics based on 1D NMR but is also compatible with other NMR frameworks or complementary LC-MS workflows. The methods are benchmarked using a simulated dataset and two publicly available datasets. speaq 2.0 is distributed through the existing speaq R package to provide a complete solution for NMR data processing. The package and the code for the presented case studies are freely available on CRAN (https://cran.r-project.org/package=speaq) and GitHub (https://github.com/beirnaert/speaq).'),
(88921, 2018, 'plos', 'Receptor recharge time drastically reduces the number of captured particles', 'Handy, Gregory|Lawley, Sean D|Borisyuk, Alla', 'Department of Mathematics, University of Utah, Salt Lake City, Utah, United States of America.|Department of Mathematics, University of Utah, Salt Lake City, Utah, United States of America.|Department of Mathematics, University of Utah, Salt Lake City, Utah, United States of America.', 'United States|United States|United States', 4, 'Computational Biology|Diffusion|Kinetics|Models, Biological|Models, Theoretical|Monte Carlo Method|Probability|Receptors, Cell Surface', 'Journal Article', '10.1371/journal.pcbi.1006015', '29494590', 'Many diverse biological systems are described by randomly moving particles that can be captured by traps in their environment. Examples include neurotransmitters diffusing in the synaptic cleft before binding to receptors and prey roaming an environment before capture by predators. In most cases, the traps cannot capture particles continuously. Rather, each trap must wait a transitory recharge time after capturing a particle before additional captures. This recharge time is often overlooked. In the case of instant recharge, the average number of particles captured before they escape grows linearly in the total number of particles. In stark contrast, we prove that for any nonzero recharge time, the average number of captured particles grows at most logarithmically in the total particle number. This is a fundamental effect of recharge, as it holds under very general assumptions on particle motion and spatial domain. Furthermore, we characterize the parameter regime in which a given recharge time will dramatically affect a system, allowing researchers to easily verify if they need to account for recharge in their specific system. Finally, we consider a few examples, including a neural system in which recharge reduces neurotransmitter bindings by several orders of magnitude.'),
(88922, 2018, 'plos', 'Correction: Correlated receptor transport processes buffer single-cell heterogeneity', 'PLOS Computational Biology Staff', 'Department of Mathematics, University of Utah, Salt Lake City, Utah, United States of America.', 'United States', 0, '-', 'Journal Article', '10.1371/journal.pcbi.1006037', '29494615', '[This corrects the article DOI: 10.1371/journal.pcbi.1005779.].'),
(88923, 2018, 'plos', 'Shared activity patterns arising at genetic susceptibility loci reveal underlying genomic and cellular architecture of human disease', 'Baillie, J Kenneth|Bretherick, Andrew|Haley, Christopher S|Clohisey, Sara|Gray, Alan|Neyton, Lucile P A|Barrett, Jeffrey|Stahl, Eli A|Tenesa, Albert|Andersson, Robin|Brown, J Ben|Faulkner, Geoffrey J|Lizio, Marina|Schaefer, Ulf|Daub, Carsten|Itoh, Masayoshi|Kondo, Naoto|Lassmann, Timo|Kawai, Jun|IIBDGC Consortium|Mole, Damian|Bajic, Vladimir B|Heutink, Peter|Rehli, Michael|Kawaji, Hideya|Sandelin, Albin|Suzuki, Harukazu|Satsangi, Jack|Wells, Christine A|Hacohen, Nir|Freeman, Thomas C|Hayashizaki, Yoshihide|Carninci, Piero|Forrest, Alistair R R|Hume, David A', 'Division of Genetics and Genomics, The Roslin Institute, University of Edinburgh, Edinburgh, United Kingdom.|Division of Genetics and Genomics, The Roslin Institute, University of Edinburgh, Edinburgh, United Kingdom.|Division of Genetics and Genomics, The Roslin Institute, University of Edinburgh, Edinburgh, United Kingdom.|Division of Genetics and Genomics, The Roslin Institute, University of Edinburgh, Edinburgh, United Kingdom.|Edinburgh Parallel Computing Centre, The University of Edinburgh, Edinburgh, United Kingdom.|Division of Genetics and Genomics, The Roslin Institute, University of Edinburgh, Edinburgh, United Kingdom.|Statistical Genetics, Wellcome Trust Sanger Institute, Wellcome Trust Genome Campus, Hinxton, Cambridge, United Kingdom.|Center for Statistical Genetics, Icahn School of Medicine at Mount Sinai, New York, United States of America.|Division of Genetics and Genomics, The Roslin Institute, University of Edinburgh, Edinburgh, United Kingdom.|The Bioinformatics Centre, Department of Biology & Biotech Research and Innovation Centre, University of Copenhagen, Copenhagen, Denmark.|Department of Statistics, University of California, Berkeley, United States of America.|Mater Research Institute, University of Queensland, University of Queensland, Brisbane, Australia.|RIKEN Omics Science Center, Yokohama, Japan, Division of Genomic Technologies, RIKEN Center for Life Science Technologies, Yokohama, Japan.|Department for Infectious Disease Informatics, Public Health England, Colindale, United Kingdom.|RIKEN Omics Science Center, Yokohama, Japan, Division of Genomic Technologies, RIKEN Center for Life Science Technologies, Yokohama, Japan.|RIKEN Omics Science Center, Yokohama, Japan, Division of Genomic Technologies, RIKEN Center for Life Science Technologies, Yokohama, Japan.|RIKEN Omics Science Center, Yokohama, Japan, Division of Genomic Technologies, RIKEN Center for Life Science Technologies, Yokohama, Japan.|RIKEN Omics Science Center, Yokohama, Japan, Division of Genomic Technologies, RIKEN Center for Life Science Technologies, Yokohama, Japan.|RIKEN Omics Science Center, Yokohama, Japan, Division of Genomic Technologies, RIKEN Center for Life Science Technologies, Yokohama, Japan.|RIKEN Omics Science Center, Yokohama, Japan, Division of Genomic Technologies, RIKEN Center for Life Science Technologies, Yokohama, Japan.|Centre for Inflammation Research, University of Edinburgh, Edinburgh, United Kingdom.|King Abdullah University of Science and Technology (KAUST), Computational Bioscience Research Center, Thuwal, Kingdom of Saudi Arabia.|German Center for Neurodegenerative Diseases, Tübingen, Germany.|Dept. Hematology, University Hospital Regensburg, Regensburg, Germany.|RIKEN Omics Science Center, Yokohama, Japan, Division of Genomic Technologies, RIKEN Center for Life Science Technologies, Yokohama, Japan.|The Bioinformatics Centre, Department of Biology & Biotech Research and Innovation Centre, University of Copenhagen, Copenhagen, Denmark.|RIKEN Omics Science Center, Yokohama, Japan, Division of Genomic Technologies, RIKEN Center for Life Science Technologies, Yokohama, Japan.|Institute for Genetics and Molecular Medicine, University of Edinburgh, Edinburgh, United Kingdom.|Australian Institute for Bioengineering and Nanotechnology, University of Queensland, St Lucia, Brisbane Australia.|Broad Institute of Harvard and MIT, Cambridge, United States of America.|Division of Genetics and Genomics, The Roslin Institute, University of Edinburgh, Edinburgh, United Kingdom.|RIKEN Omics Science Center, Yokohama, Japan, Division of Genomic Technologies, RIKEN Center for Life Science Technologies, Yokohama, Japan.|RIKEN Omics Science Center, Yokohama, Japan, Division of Genomic Technologies, RIKEN Center for Life Science Technologies, Yokohama, Japan.|Harry Perkins Institute of Medical Research, and the Centre for Medical Research, University of Western Australia, QEII Medical Centre, Nedlands, Perth, Western Australia, Australia.|Division of Genetics and Genomics, The Roslin Institute, University of Edinburgh, Edinburgh, United Kingdom.', 'United Kingdom|United Kingdom|United Kingdom|United Kingdom|United Kingdom|United Kingdom|United Kin', 0, 'Crohn Disease|Databases, Genetic|Gene Expression Profiling|Genetic Predisposition to Disease|Genomics|Humans|Promoter Regions, Genetic|Transcriptome', 'Journal Article', '10.1371/journal.pcbi.1005934', '29494619', 'Genetic variants underlying complex traits, including disease susceptibility, are enriched within the transcriptional regulatory elements, promoters and enhancers. There is emerging evidence that regulatory elements associated with particular traits or diseases share similar patterns of transcriptional activity. Accordingly, shared transcriptional activity (coexpression) may help prioritise loci associated with a given trait, and help to identify underlying biological processes. Using cap analysis of gene expression (CAGE) profiles of promoter- and enhancer-derived RNAs across 1824 human samples, we have analysed coexpression of RNAs originating from trait-associated regulatory regions using a novel quantitative method (network density analysis, NDA). For most traits studied, phenotype-associated variants in regulatory regions were linked to tightly-coexpressed networks that are likely to share important functional characteristics. Coexpression provides a new signal, independent of phenotype association, to enable fine mapping of causative variants. The NDA coexpression approach identifies new genetic variants associated with specific traits, including an association between the regulation of the OCT1 cation transporter and genetic variants underlying circulating cholesterol levels. NDA strongly implicates particular cell types and tissues in disease pathogenesis. For example, distinct groupings of disease-associated regulatory regions implicate two distinct biological processes in the pathogenesis of ulcerative colitis, a further two separate processes are implicated in Crohns disease. Thus, our functional analysis of genetic predisposition to disease defines new distinct disease endotypes. We predict that patients with a preponderance of susceptibility variants in each group are likely to respond differently to pharmacological therapy. Together, these findings enable a deeper biological understanding of the causal basis of complex traits.');
