INSERT INTO `papers` (`id`, `ano`, `journal`, `titulo`, `autores`, `afiliacao`, `pais`, `citacoes`, `palavra_chave`, `categorias`, `doi`, `pubmed`, `abstract`) VALUES
(88206, 2017, 'plos', 'A Topological Criterion for Filtering Information in Complex Brain Networks', 'De Vico Fallani, Fabrizio|Latora, Vito|Chavez, Mario', 'Inria Paris, Aramis project-team, Paris, France.|School of Mathematical Sciences, Queen Mary University of London, London, United Kingdom.|CNRS UMR-7225, Sorbonne Universités, UPMC Univ Paris 06, Inserm, Institut du cerveau et de la moelle (ICM) - Hôpital Pitié-Salpêtrière, Paris, France.', 'France|United Kingdom|France', 31, 'Brain|Brain Mapping|Computational Biology|Computer Simulation|Humans|Models, Statistical|Nerve Net', 'Journal Article', '10.1371/journal.pcbi.1005305', '28076353', 'In many biological systems, the network of interactions between the elements can only be inferred from experimental measurements. In neuroscience, non-invasive imaging tools are extensively used to derive either structural or functional brain networks in-vivo. As a result of the inference process, we obtain a matrix of values corresponding to a fully connected and weighted network. To turn this into a useful sparse network, thresholding is typically adopted to cancel a percentage of the weakest connections. The structural properties of the resulting network depend on how much of the inferred connectivity is eventually retained. However, how to objectively fix this threshold is still an open issue. We introduce a criterion, the efficiency cost optimization (ECO), to select a threshold based on the optimization of the trade-off between the efficiency of a network and its wiring cost. We prove analytically and we confirm through numerical simulations that the connection density maximizing this trade-off emphasizes the intrinsic properties of a given network, while preserving its sparsity. Moreover, this density threshold can be determined a-priori, since the number of connections to filter only depends on the network size according to a power-law. We validate this result on several brain networks, from micro- to macro-scales, obtained with different imaging modalities. Finally, we test the potential of ECO in discriminating brain states with respect to alternative filtering methods. ECO advances our ability to analyze and compare biological networks, inferred from experimental data, in a fast and principled way.'),
(88207, 2017, 'plos', 'Multiple Choice Neurodynamical Model of the Uncertain Option Task', 'Insabato, Andrea|Pannunzi, Mario|Deco, Gustavo', 'Universitat Pompeu Fabra, Center for Brain and Cognition, Barcelona, Spain.|Universitat Pompeu Fabra, Center for Brain and Cognition, Barcelona, Spain.|Universitat Pompeu Fabra, Center for Brain and Cognition, Barcelona, Spain.', 'Spain|Spain|Spain', 3, 'Animals|Cerebral Cortex|Choice Behavior|Computational Biology|Haplorhini|Models, Neurological|Reward|Uncertainty', 'Journal Article', '10.1371/journal.pcbi.1005250', '28076355', 'The uncertain option task has been recently adopted to investigate the neural systems underlying the decision confidence. Latterly single neurons activity has been recorded in lateral intraparietal cortex of monkeys performing an uncertain option task, where the subject is allowed to opt for a small but sure reward instead of making a risky perceptual decision. We propose a multiple choice model implemented in a discrete attractors network. This model is able to reproduce both behavioral and neurophysiological experimental data and therefore provides support to the numerous perspectives that interpret the uncertain option task as a sensory-motor association. The model explains the behavioral and neural data recorded in monkeys as the result of the multistable attractor landscape and produces several testable predictions. One of these predictions may help distinguish our model from a recently proposed continuous attractor model.'),
(88208, 2017, 'plos', 'The Power of Malaria Vaccine Trials Using Controlled Human Malaria Infection', 'Coffeng, Luc E|Hermsen, Cornelus C|Sauerwein, Robert W|de Vlas, Sake J', 'Department of Public Health, Erasmus MC, University Medical Center Rotterdam, Rotterdam, The Netherlands.|Department of Medical Microbiology, Radboud University Medical Center, Nijmegen, The Netherlands.|Department of Medical Microbiology, Radboud University Medical Center, Nijmegen, The Netherlands.|Department of Public Health, Erasmus MC, University Medical Center Rotterdam, Rotterdam, The Netherlands.', 'Netherlands|Netherlands|Netherlands|Netherlands', 14, 'Bayes Theorem|Biomedical Research|Clinical Trials as Topic|Computational Biology|Computer Simulation|Healthy Volunteers|Humans|Malaria Vaccines|Malaria, Falciparum|Models, Statistical|Plasmodium falciparum', 'Journal Article', '10.1371/journal.pcbi.1005255', '28081133', 'Controlled human malaria infection (CHMI) in healthy human volunteers is an important and powerful tool in clinical malaria vaccine development. However, power calculations are essential to obtain meaningful estimates of protective efficacy, while minimizing the risk of adverse events. To optimize power calculations for CHMI-based malaria vaccine trials, we developed a novel non-linear statistical model for parasite kinetics as measured by qPCR, using data from mosquito-based CHMI experiments in 57 individuals. We robustly account for important sources of variation between and within individuals using a Bayesian framework. Study power is most dependent on the number of individuals in each treatment arm, inter-individual variation in vaccine efficacy and the number of blood samples taken per day matter relatively little. Due to high inter-individual variation in the number of first-generation parasites, hepatic vaccine trials required significantly more study subjects than erythrocytic vaccine trials. We provide power calculations for hypothetical malaria vaccine trials of various designs and conclude that so far, power calculations have been overly optimistic. We further illustrate how upcoming techniques like needle-injected CHMI may reduce required sample sizes.'),
(88209, 2017, 'plos', 'Pain: A Statistical Account', 'Tabor, Abby|Thacker, Michael A|Moseley, G Lorimer|Körding, Konrad P', 'Centre for Pain Research, University of Bath, North East Somerset, United Kingdom.|Centre for Human and Aerospace Physiological Sciences/Pain Section, Neuroimaging, Institute of Psychiatry, Kings College London, London, United Kingdom.|Sansom Institute for Health Research, University of South Australia, Adelaide, South Australia, Australia.|Rehabilitation Institute of Chicago, Northwestern University, Chicago, Illinois, United States of America.', 'United Kingdom|United Kingdom|Australia|United States', 26, 'Bayes Theorem|Humans|Models, Neurological|Models, Statistical|Pain|Pain Perception', 'Journal Article', '10.1371/journal.pcbi.1005142', '28081134', 'Perception is seen as a process that utilises partial and noisy information to construct a coherent understanding of the world. Here we argue that the experience of pain is no different, it is based on incomplete, multimodal information, which is used to estimate potential bodily threat. We outline a Bayesian inference model, incorporating the key components of cue combination, causal inference, and temporal integration, which highlights the statistical problems in everyday perception. It is from this platform that we are able to review the pain literature, providing evidence from experimental, acute, and persistent phenomena to demonstrate the advantages of adopting a statistical account in pain. Our probabilistic conceptualisation suggests a principles-based view of pain, explaining a broad range of experimental and clinical findings and making testable predictions.'),
(88210, 2017, 'plos', 'Could a Neuroscientist Understand a Microprocessor?', 'Jonas, Eric|Kording, Konrad Paul', 'Department of Electrical Engineering and Computer Science, University of California, Berkeley, Berkeley, California, United States of America.|Department of Physical Medicine and Rehabilitation, Northwestern University and Rehabilitation Institute of Chicago, Chicago, Illinois, United States of America.', 'United States|United States', 73, 'Algorithms|Computational Biology|Computer Simulation|Connectome|Databases, Factual|Microcomputers|Models, Neurological|Neural Networks (Computer)|Neurosciences|Video Games', 'Journal Article', '10.1371/journal.pcbi.1005268', '28081141', 'There is a popular belief in neuroscience that we are primarily data limited, and that producing large, multimodal, and complex datasets will, with the help of advanced data analysis algorithms, lead to fundamental insights into the way the brain processes information. These datasets do not yet exist, and if they did we would have no way of evaluating whether or not the algorithmically-generated insights were sufficient or even correct. To address this, here we take a classical microprocessor as a model organism, and use our ability to perform arbitrary experiments on it to see if popular data analysis methods from neuroscience can elucidate the way it processes information. Microprocessors are among those artificial information processing systems that are both complex and that we understand at all levels, from the overall logical flow, via logical gates, to the dynamics of transistors. We show that the approaches reveal interesting structure in the data but do not meaningfully describe the hierarchy of information processing in the microprocessor. This suggests current analytic approaches in neuroscience may fall short of producing meaningful understanding of neural systems, regardless of the amount of data. Additionally, we argue for scientists using complex non-linear dynamical systems with known ground truth, such as the microprocessor as a validation platform for time-series and structure discovery methods.'),
(88211, 2017, 'plos', 'Correction: A Stochastic Model of the Yeast Cell Cycle Reveals Roles for Feedback Regulation in Limiting Cellular Variability', 'PLOS Computational Biology Staff', 'Department of Physical Medicine and Rehabilitation, Northwestern University and Rehabilitation Institute of Chicago, Chicago, Illinois, United States of America.', 'United States', 0, '-', 'Published Erratum', '10.1371/journal.pcbi.1005323', '28081212', '[This corrects the article DOI: 10.1371/journal.pcbi.1005230.].'),
(88212, 2017, 'plos', 'Is the Conformational Ensemble of Alzheimers Axcexb210-40 Peptide Force Field Dependent?', 'Siwy, Christopher M|Lockhart, Christopher|Klimov, Dmitri K', 'School of Systems Biology, George Mason University, Manassas, Virginia, United States of America.|School of Systems Biology, George Mason University, Manassas, Virginia, United States of America.|School of Systems Biology, George Mason University, Manassas, Virginia, United States of America.', 'United States|United States|United States', 12, 'Amyloid beta-Peptides|Computational Biology|Molecular Dynamics Simulation|Peptide Fragments|Protein Conformation', 'Journal Article', '10.1371/journal.pcbi.1005314', '28085875', 'By applying REMD simulations we have performed comparative analysis of the conformational ensembles of amino-truncated Axcexb210-40 peptide produced with five force fields, which combine four protein parameterizations (CHARMM36, CHARMM22*, CHARMM22/cmap, and OPLS-AA) and two water models (standard and modified TIP3P). Axcexb210-40 conformations were analyzed by computing secondary structure, backbone fluctuations, tertiary interactions, and radius of gyration. We have also calculated Axcexb210-40 3JHNHxcexb1-coupling and RDC constants and compared them with their experimental counterparts obtained for the full-length Axcexb21-40 peptide. Our study led us to several conclusions. First, all force fields predict that Axcexb2 adopts unfolded structure dominated by turn and random coil conformations. Second, specific TIP3P water model does not dramatically affect secondary or tertiary Axcexb210-40 structure, albeit standard TIP3P model favors slightly more compact states. Third, although the secondary structures observed in CHARMM36 and CHARMM22/cmap simulations are qualitatively similar, their tertiary interactions show little consistency. Fourth, two force fields, OPLS-AA and CHARMM22* have unique features setting them apart from CHARMM36 or CHARMM22/cmap. OPLS-AA reveals moderate xcexb2-structure propensity coupled with extensive, but weak long-range tertiary interactions leading to Axcexb2 collapsed conformations. CHARMM22* exhibits moderate helix propensity and generates multiple exceptionally stable long- and short-range interactions. Our investigation suggests that among all force fields CHARMM22* differs the most from CHARMM36. Fifth, the analysis of 3JHNHxcexb1-coupling and RDC constants based on CHARMM36 force field with standard TIP3P model led us to an unexpected finding that in silico Axcexb210-40 and experimental Axcexb21-40 constants are generally in better agreement than these quantities computed and measured for identical peptides, such as Axcexb21-40 or Axcexb21-42. This observation suggests that the differences in the conformational ensembles of Axcexb210-40 and Axcexb21-40 are small and the former can be used as proxy of the full-length peptide. Based on this argument, we concluded that CHARMM36 force field with standard TIP3P model produces the most accurate representation of Axcexb210-40 conformational ensemble.'),
(88213, 2017, 'plos', 'Inference of Transmission Network Structure from HIV Phylogenetic Trees', 'Giardina, Federica|Romero-Severson, Ethan Obie|Albert, Jan|Britton, Tom|Leitner, Thomas', 'Department of Mathematics, Stockholm University, Stockholm, Sweden.|Theoretical Biology and Biophysics Group, Los Alamos National Laboratory, Los Alamos, New Mexico, United States of America.|Department of Microbiology, Tumor and Cell Biology, Karolinska Institute, Stockholm, Sweden.|Department of Mathematics, Stockholm University, Stockholm, Sweden.|Theoretical Biology and Biophysics Group, Los Alamos National Laboratory, Los Alamos, New Mexico, United States of America.', 'Sweden|Mexico|Sweden|Sweden|Mexico', 10, 'Bayes Theorem|Computational Biology|Computer Simulation|Disease Outbreaks|HIV Infections|HIV-1|Humans|Models, Biological|Phylogeny|Sweden', 'Journal Article', '10.1371/journal.pcbi.1005316', '28085876', 'Phylogenetic inference is an attractive means to reconstruct transmission histories and epidemics. However, there is not a perfect correspondence between transmission history and virus phylogeny. Both node height and topological differences may occur, depending on the interaction between within-host evolutionary dynamics and between-host transmission patterns. To investigate these interactions, we added a within-host evolutionary model in epidemiological simulations and examined if the resulting phylogeny could recover different types of contact networks. To further improve realism, we also introduced patient-specific differences in infectivity across disease stages, and on the epidemic level we considered incomplete sampling and the age of the epidemic. Second, we implemented an inference method based on approximate Bayesian computation (ABC) to discriminate among three well-studied network models and jointly estimate both network parameters and key epidemiological quantities such as the infection rate. Our ABC framework used both topological and distance-based tree statistics for comparison between simulated and observed trees. Overall, our simulations showed that a virus time-scaled phylogeny (genealogy) may be substantially different from the between-host transmission tree. This has important implications for the interpretation of what a phylogeny reveals about the underlying epidemic contact network. In particular, we found that while the within-host evolutionary process obscures the transmission tree, the diversification process and infectivity dynamics also add discriminatory power to differentiate between different types of contact networks. We also found that the possibility to differentiate contact networks depends on how far an epidemic has progressed, where distance-based tree statistics have more power early in an epidemic. Finally, we applied our ABC inference on two different outbreaks from the Swedish HIV-1 epidemic.'),
(88214, 2017, 'plos', 'A Computational Approach for Identifying Synergistic Drug Combinations', 'Gayvert, Kaitlyn M|Aly, Omar|Platt, James|Bosenberg, Marcus W|Stern, David F|Elemento, Olivier', 'Institute for Computational Biomedicine, Department of Physiology and Biophysics, Weill Cornell Medicine, New York, NY, United States of America.|Institute for Computational Biomedicine, Department of Physiology and Biophysics, Weill Cornell Medicine, New York, NY, United States of America.|Department of Pathology, Yale University School of Medicine, New Haven, Connecticut, United States of America.|Department of Pathology, Yale University School of Medicine, New Haven, Connecticut, United States of America.|Department of Pathology, Yale University School of Medicine, New Haven, Connecticut, United States of America.|Institute for Computational Biomedicine, Department of Physiology and Biophysics, Weill Cornell Medicine, New York, NY, United States of America.', 'United States|United States|United States|United States|United States|United States', 21, 'Antineoplastic Agents|Cell Line, Tumor|Computational Biology|Drug Combinations|Drug Discovery|Drug Synergism|Humans|Melanoma|Models, Theoretical|Proto-Oncogene Proteins B-raf', 'Journal Article', '10.1371/journal.pcbi.1005308', '28085880', 'A promising alternative to address the problem of acquired drug resistance is to rely on combination therapies. Identification of the right combinations is often accomplished through trial and error, a labor and resource intensive process whose scale quickly escalates as more drugs can be combined. To address this problem, we present a broad computational approach for predicting synergistic combinations using easily obtainable single drug efficacy, no detailed mechanistic understanding of drug function, and limited drug combination testing. When applied to mutant BRAF melanoma, we found that our approach exhibited significant predictive power. Additionally, we validated previously untested synergy predictions involving anticancer molecules. As additional large combinatorial screens become available, this methodology could prove to be impactful for identification of drug synergy in context of other types of cancers.'),
(88215, 2017, 'plos', 'A Looping-Based Model for Quenching Repression', 'Pollak, Yaroslav|Goldberg, Sarah|Amit, Roee', 'Biotechnology and Food Engineering, Technion - Israel Institute of Technology, Haifa, Israel.|Biotechnology and Food Engineering, Technion - Israel Institute of Technology, Haifa, Israel.|Biotechnology and Food Engineering, Technion - Israel Institute of Technology, Haifa, Israel.', 'Israel|Israel|Israel', 1, 'Animals|Computational Biology|DNA|Drosophila melanogaster|Enhancer Elements, Genetic|Models, Genetic|Monte Carlo Method|Transcription Factors', 'Journal Article', '10.1371/journal.pcbi.1005337', '28085884', 'We model the regulatory role of proteins bound to looped DNA using a simulation in which dsDNA is represented as a self-avoiding chain, and proteins as spherical protrusions. We simulate long self-avoiding chains using a sequential importance sampling Monte-Carlo algorithm, and compute the probabilities for chain looping with and without a protrusion. We find that a protrusion near one of the chains termini reduces the probability of looping, even for chains much longer than the protrusion-chain-terminus distance. This effect increases with protrusion size, and decreases with protrusion-terminus distance. The reduced probability of looping can be explained via an eclipse-like model, which provides a novel inhibitory mechanism. We test the eclipse model on two possible transcription-factor occupancy states of the D. melanogaster eve 3/7 enhancer, and show that it provides a possible explanation for the experimentally-observed eve stripe 3 and 7 expression patterns.'),
(88216, 2017, 'plos', 'Computational Analysis of Residue Interaction Networks and Coevolutionary Relationships in the Hsp70 Chaperones: A Community-Hopping Model of Allosteric Regulation and Communication', 'Stetz, Gabrielle|Verkhivker, Gennady M', 'Graduate Program in Computational and Data Sciences, Schmid College of Science and Technology, Chapman University, Orange, California, United States of America.|Graduate Program in Computational and Data Sciences, Schmid College of Science and Technology, Chapman University, Orange, California, United States of America.', 'United States|United States', 35, 'Allosteric Regulation|Amino Acids|Binding Sites|Computer Simulation|Evolution, Molecular|HSP70 Heat-Shock Proteins|Models, Chemical|Models, Genetic|Models, Molecular|Molecular Chaperones|Molecular Docking Simulation|Protein Binding|Structure-Activity Relationship', 'Journal Article', '10.1371/journal.pcbi.1005299', '28095400', 'Allosteric interactions in the Hsp70 proteins are linked with their regulatory mechanisms and cellular functions. Despite significant progress in structural and functional characterization of the Hsp70 proteins fundamental questions concerning modularity of the allosteric interaction networks and hierarchy of signaling pathways in the Hsp70 chaperones remained largely unexplored and poorly understood. In this work, we proposed an integrated computational strategy that combined atomistic and coarse-grained simulations with coevolutionary analysis and network modeling of the residue interactions. A novel aspect of this work is the incorporation of dynamic residue correlations and coevolutionary residue dependencies in the construction of allosteric interaction networks and signaling pathways. We found that functional sites involved in allosteric regulation of Hsp70 may be characterized by structural stability, proximity to global hinge centers and local structural environment that is enriched by highly coevolving flexible residues. These specific characteristics may be necessary for regulation of allosteric structural transitions and could distinguish regulatory sites from nonfunctional conserved residues. The observed confluence of dynamics correlations and coevolutionary residue couplings with global networking features may determine modular organization of allosteric interactions and dictate localization of key mediating sites. Community analysis of the residue interaction networks revealed that concerted rearrangements of local interacting modules at the inter-domain interface may be responsible for global structural changes and a population shift in the DnaK chaperone. The inter-domain communities in the Hsp70 structures harbor the majority of regulatory residues involved in allosteric signaling, suggesting that these sites could be integral to the network organization and coordination of structural changes. Using a network-based formalism of allostery, we introduced a community-hopping model of allosteric communication. Atomistic reconstruction of signaling pathways in the DnaK structures captured a direction-specific mechanism and molecular details of signal transmission that are fully consistent with the mutagenesis experiments. The results of our study reconciled structural and functional experiments from a network-centric perspective by showing that global properties of the residue interaction networks and coevolutionary signatures may be linked with specificity and diversity of allosteric regulation mechanisms.'),
(88217, 2017, 'plos', 'A General Shear-Dependent Model for Thrombus Formation', 'Yazdani, Alireza|Li, He|Humphrey, Jay D|Karniadakis, George Em', 'Division of Applied Mathematics, Brown University, Providence, Rhode Island, United States of America.|Division of Applied Mathematics, Brown University, Providence, Rhode Island, United States of America.|Department of Biomedical Engineering, Yale University, New Haven, Connecticut, United States of America.|Division of Applied Mathematics, Brown University, Providence, Rhode Island, United States of America.', 'United States|United States|United States|United States', 35, 'Animals|Blood Coagulation|Blood Flow Velocity|Blood Pressure|Computer Simulation|Humans|Models, Cardiovascular|Platelet Adhesiveness|Platelet Aggregation|Thrombosis', 'Journal Article', '10.1371/journal.pcbi.1005291', '28095402', 'Modeling the transport, activation, and adhesion of platelets is crucial in predicting thrombus formation and growth following a thrombotic event in normal or pathological conditions. We propose a shear-dependent platelet adhesive model based on the Morse potential that is calibrated by existing in vivo and in vitro experimental data and can be used over a wide range of flow shear rates ([Formula: see text]). We introduce an Eulerian-Lagrangian model where hemodynamics is solved on a fixed Eulerian grid, while platelets are tracked using a Lagrangian framework. A force coupling method is introduced for bidirectional coupling of platelet motion with blood flow. Further, we couple the calibrated platelet aggregation model with a tissue-factor/contact pathway coagulation cascade, representing the relevant biology of thrombin generation and the subsequent fibrin deposition. The range of shear rates covered by the proposed model encompass venous and arterial thrombosis, ranging from low-shear-rate conditions in abdominal aortic aneurysms and thoracic aortic dissections to thrombosis in stenotic arteries following plaque rupture, where local shear rates are extremely high.'),
(88218, 2017, 'plos', 'A Likelihood Approach for Real-Time Calibration of Stochastic Compartmental Epidemic Models', 'Zimmer, Christoph|Yaesoubi, Reza|Cohen, Ted', 'Epidemiology of Microbial Diseases, Yale School of Public Health, New Haven, Connecticut, United States of America.|Health Policy and Management, Yale School of Public Health, New Haven, Connecticut, United States of America.|Epidemiology of Microbial Diseases, Yale School of Public Health, New Haven, Connecticut, United States of America.', 'United States|United States|United States', 6, 'Animals|Calibration|Communicable Diseases, Emerging|Computer Simulation|Computer Systems|Data Interpretation, Statistical|Epidemics|Epidemiologic Methods|Humans|Likelihood Functions|Models, Statistical|Reproducibility of Results|Sensitivity and Specificity|Stochastic Processes', 'Comparative Study', '10.1371/journal.pcbi.1005257', '28095403', 'Stochastic transmission dynamic models are especially useful for studying the early emergence of novel pathogens given the importance of chance events when the number of infectious individuals is small. However, methods for parameter estimation and prediction for these types of stochastic models remain limited. In this manuscript, we describe a calibration and prediction framework for stochastic compartmental transmission models of epidemics. The proposed method, Multiple Shooting for Stochastic systems (MSS), applies a linear noise approximation to describe the size of the fluctuations, and uses each new surveillance observation to update the belief about the true epidemic state. Using simulated outbreaks of a novel viral pathogen, we evaluate the accuracy of MSS for real-time parameter estimation and prediction during epidemics. We assume that weekly counts for the number of new diagnosed cases are available and serve as an imperfect proxy of incidence. We show that MSS produces accurate estimates of key epidemic parameters (i.e. mean duration of infectiousness, R0, and Reff) and can provide an accurate estimate of the unobserved number of infectious individuals during the course of an epidemic. MSS also allows for accurate prediction of the number and timing of future hospitalizations and the overall attack rate. We compare the performance of MSS to three state-of-the-art benchmark methods: 1) a likelihood approximation with an assumption of independent Poisson observations, 2) a particle filtering method, and 3) an ensemble Kalman filter method. We find that MSS significantly outperforms each of these three benchmark methods in the majority of epidemic scenarios tested. In summary, MSS is a promising method that may improve on current approaches for calibration and prediction using stochastic models of epidemics.'),
(88219, 2017, 'plos', 'Entropy Transfer between Residue Pairs and Allostery in Proteins: Quantifying Allosteric Communication in Ubiquitin', 'Hacisuleyman, Aysima|Erman, Burak', 'Department of Chemical and Biological Engineering, Koç University, Sariyer, Istanbul, Turkey.|Department of Chemical and Biological Engineering, Koç University, Sariyer, Istanbul, Turkey.', 'Turkey|Turkey', 14, 'Allosteric Site|Amino Acids|Binding Sites|Entropy|Models, Chemical|Molecular Dynamics Simulation|Protein Binding|Protein Conformation|Structure-Activity Relationship|Ubiquitin|Ubiquitination', 'Journal Article', '10.1371/journal.pcbi.1005319', '28095404', 'It has recently been proposed by Gunasakaran et al. that allostery may be an intrinsic property of all proteins. Here, we develop a computational method that can determine and quantify allosteric activity in any given protein. Based on Schreibers transfer entropy formulation, our approach leads to an information transfer landscape for the protein that shows the presence of entropy sinks and sources and explains how pairs of residues communicate with each other using entropy transfer. The model can identify the residues that drive the fluctuations of others. We apply the model to Ubiquitin, whose allosteric activity has not been emphasized until recently, and show that there are indeed systematic pathways of entropy and information transfer between residues that correlate well with the activities of the protein. We use 600 nanosecond molecular dynamics trajectories for Ubiquitin and its complex with human polymerase iota and evaluate entropy transfer between all pairs of residues of Ubiquitin and quantify the binding susceptibility changes upon complex formation. We explain the complex formation propensities of Ubiquitin in terms of entropy transfer. Important residues taking part in allosteric communication in Ubiquitin predicted by our approach are in agreement with results of NMR relaxation dispersion experiments. Finally, we show that time delayed correlation of fluctuations of two interacting residues possesses an intrinsic causality that tells which residue controls the interaction and which one is controlled. Our work shows that time delayed correlations, entropy transfer and causality are the required new concepts for explaining allosteric communication in proteins.'),
(88220, 2017, 'plos', 'A Two-Locus Model of the Evolution of Insecticide Resistance to Inform and Optimise Public Health Insecticide Deployment Strategies', 'Levick, Bethany|South, Andy|Hastings, Ian M', 'Department of Parasitology, Liverpool School of Tropical Medicine, Liverpool, United Kingdom.|Independent consultant, Norwich, United Kingdom.|Department of Parasitology, Liverpool School of Tropical Medicine, Liverpool, United Kingdom.', 'United Kingdom|United Kingdom|United Kingdom', 11, 'Animals|Biological Evolution|Computer Simulation|Culex|Health Policy|Humans|Insecticide Resistance|Insecticides|Malaria|Models, Genetic', 'Journal Article', '10.1371/journal.pcbi.1005327', '28095406', 'We develop a flexible, two-locus model for the spread of insecticide resistance applicable to mosquito species that transmit human diseases such as malaria. The model allows differential exposure of males and females, allows them to encounter high or low concentrations of insecticide, and allows selection pressures and dominance values to differ depending on the concentration of insecticide encountered. We demonstrate its application by investigating the relative merits of sequential use of insecticides versus their deployment as a mixture to minimise the spread of resistance. We recover previously published results as subsets of this model and conduct a sensitivity analysis over an extensive parameter space to identify what circumstances favour mixtures over sequences. Both strategies lasted more than 500 mosquito generations (or about 40 years) in 24% of runs, while in those runs where resistance had spread to high levels by 500 generations, 56% favoured sequential use and 44% favoured mixtures. Mixtures are favoured when insecticide effectiveness (their ability to kill homozygous susceptible mosquitoes) is high and exposure (the proportion of mosquitoes that encounter the insecticide) is low. If insecticides do not reliably kill homozygous sensitive genotypes, it is likely that sequential deployment will be a more robust strategy. Resistance to an insecticide always spreads slower if that insecticide is used in a mixture although this may be insufficient to outperform sequential use: for example, a mixture may last 5 years while the two insecticides deployed individually may last 3 and 4 years giving an overall lifespan of 7 years for sequential use. We emphasise that this paper is primarily about designing and implementing a flexible modelling strategy to investigate the spread of insecticide resistance in vector populations and demonstrate how our model can identify vector control strategies most likely to minimise the spread of insecticide resistance.'),
(88221, 2017, 'plos', 'Approximate Inference for Time-Varying Interactions and Macroscopic Dynamics of Neural Populations', 'Donner, Christian|Obermayer, Klaus|Shimazaki, Hideaki', 'Bernstein Center for Computational Neuroscience, Berlin, Germany.|Bernstein Center for Computational Neuroscience, Berlin, Germany.|RIKEN Brain Science Institute, Wako-shi, Saitama, Japan.', 'Germany|Germany|Japan', 7, 'Action Potentials|Animals|Bayes Theorem|Brain|Computer Simulation|Humans|Models, Neurological|Models, Statistical|Nerve Net|Neuronal Plasticity|Nonlinear Dynamics|Synaptic Transmission|Time Factors', 'Journal Article', '10.1371/journal.pcbi.1005309', '28095421', 'The models in statistical physics such as an Ising model offer a convenient way to characterize stationary activity of neural populations. Such stationary activity of neurons may be expected for recordings from in vitro slices or anesthetized animals. However, modeling activity of cortical circuitries of awake animals has been more challenging because both spike-rates and interactions can change according to sensory stimulation, behavior, or an internal state of the brain. Previous approaches modeling the dynamics of neural interactions suffer from computational cost, therefore, its application was limited to only a dozen neurons. Here by introducing multiple analytic approximation methods to a state-space model of neural population activity, we make it possible to estimate dynamic pairwise interactions of up to 60 neurons. More specifically, we applied the pseudolikelihood approximation to the state-space model, and combined it with the Bethe or TAP mean-field approximation to make the sequential Bayesian estimation of the model parameters possible. The large-scale analysis allows us to investigate dynamics of macroscopic properties of neural circuitries underlying stimulus processing and behavior. We show that the model accurately estimates dynamics of network properties such as sparseness, entropy, and heat capacity by simulated data, and demonstrate utilities of these measures by analyzing activity of monkey V4 neurons as well as a simulated balanced network of spiking neurons.'),
(88222, 2017, 'plos', 'A New Approach to Model Pitch Perception Using Sparse Coding', 'Barzelay, Oded|Furst, Miriam|Barak, Omri', 'School of Electrical Engineering, Faculty of Engineering, Tel-Aviv University, Tel Aviv, Israel.|School of Electrical Engineering, Faculty of Engineering, Tel-Aviv University, Tel Aviv, Israel.|Rappaport Faculty of Medicine, Network Biology Research Laboratories, Technion, Haifa, Israel.', 'Israel|Israel|Israel', 3, 'Acoustic Stimulation|Cochlear Nerve|Computational Biology|Humans|Models, Neurological|Music|Nerve Fibers|Pitch Perception', 'Journal Article', '10.1371/journal.pcbi.1005338', '28099436', 'Our acoustical environment abounds with repetitive sounds, some of which are related to pitch perception. It is still unknown how the auditory system, in processing these sounds, relates a physical stimulus and its percept. Since, in mammals, all auditory stimuli are conveyed into the nervous system through the auditory nerve (AN) fibers, a model should explain the perception of pitch as a function of this particular input. However, pitch perception is invariant to certain features of the physical stimulus. For example, a missing fundamental stimulus with resolved or unresolved harmonics, or a low and high-level amplitude stimulus with the same spectral content-these all give rise to the same percept of pitch. In contrast, the AN representations for these different stimuli are not invariant to these effects. In fact, due to saturation and non-linearity of both cochlear and inner hair cells responses, these differences are enhanced by the AN fibers. Thus there is a difficulty in explaining how pitch percept arises from the activity of the AN fibers. We introduce a novel approach for extracting pitch cues from the AN population activity for a given arbitrary stimulus. The method is based on a technique known as sparse coding (SC). It is the representation of pitch cues by a few spatiotemporal atoms (templates) from among a large set of possible ones (a dictionary). The amount of activity of each atom is represented by a non-zero coefficient, analogous to an active neuron. Such a technique has been successfully applied to other modalities, particularly vision. The model is composed of a cochlear model, an SC processing unit, and a harmonic sieve. We show that the model copes with different pitch phenomena: extracting resolved and non-resolved harmonics, missing fundamental pitches, stimuli with both high and low amplitudes, iterated rippled noises, and recorded musical instruments.'),
(88223, 2017, 'plos', 'Ten Simple Rules to Enable Multi-site Collaborations through Data Sharing', 'Boland, Mary Regina|Karczewski, Konrad J|Tatonetti, Nicholas P', 'Department of Biomedical Informatics, Columbia University, New York, New York, United States of America.|Program in Medical and Population Genetics, Broad Institute of MIT and Harvard, Cambridge, Massachusetts, United States of America.|Department of Biomedical Informatics, Columbia University, New York, New York, United States of America.', 'United States|United States|United States', 11, 'Cooperative Behavior|Guidelines as Topic|Humans|Information Dissemination', 'Editorial', '10.1371/journal.pcbi.1005278', '28103227', '-'),
(88224, 2017, 'plos', 'Computing the Dynamic Supramolecular Structural Proteome', 'Nussinov, Ruth|Papin, Jason A|Vakser, Ilya', 'Cancer and Inflammation Program, Leidos Biomedical Research, Inc., Frederick National Laboratory for Cancer Research, National Cancer Institute, Frederick, Maryland, United States of America.|University of Virginia, Charlottesville, Virginia, United States of America.|Center for Computational Biology, The University of Kansas, Lawrence, Kansas, United States of America.', 'United States|United States|United States', 2, 'Computational Biology|Protein Conformation|Proteome', 'Editorial', '10.1371/journal.pcbi.1005290', '28103234', '-'),
(88225, 2017, 'plos', 'Real Time Multiplicative Memory Amplification Mediated by Whole-Cell Scaling of Synaptic Response in Key Neurons', 'Reuveni, Iris|Ghosh, Sourav|Barkai, Edi', 'Sagol Department of Neurobiology, Faculty of Natural Sciences, University of Haifa, Haifa, Israel.|Sagol Department of Neurobiology, Faculty of Natural Sciences, University of Haifa, Haifa, Israel.|Sagol Department of Neurobiology, Faculty of Natural Sciences, University of Haifa, Haifa, Israel.', 'Israel|Israel|Israel', 4, 'Animals|Calcium-Calmodulin-Dependent Protein Kinase Type 2|Computational Biology|Maze Learning|Memory|Models, Neurological|Neurons|Rats|Synapses', 'Journal Article', '10.1371/journal.pcbi.1005306', '28103235', 'Intense spiking response of a memory-pattern is believed to play a crucial role both in normal learning and pathology, where it can create biased behavior. We recently proposed a novel model for memory amplification where the simultaneous two-fold increase of all excitatory (AMPAR-mediated) and inhibitory (GABAAR-mediated) synapses in a sub-group of cells that constitutes a memory-pattern selectively amplifies this memory. Here we confirm the cellular basis of this model by validating its major predictions in four sets of experiments, and demonstrate its induction via a whole-cell transduction mechanism. Subsequently, using theory and simulations, we show that this whole-cell two-fold increase of all inhibitory and excitatory synapses functions as an instantaneous and multiplicative amplifier of the neurons spiking. The amplification mechanism acts through multiplication of the net synaptic current, where it scales both the average and the standard deviation of the current. In the excitation-inhibition balance regime, this scaling creates a linear multiplicative amplifier of the cells spiking response. Moreover, the direct scaling of the synaptic input enables the amplification of the spiking response to be synchronized with rapid changes in synaptic input, and to be independent of previous spiking activity. These traits enable instantaneous real-time amplification during brief elevations of excitatory synaptic input. Furthermore, the multiplicative nature of the amplifier ensures that the net effect of the amplification is large mainly when the synaptic input is mostly excitatory. When induced on all cells that comprise a memory-pattern, these whole-cell modifications enable a substantial instantaneous amplification of the memory-pattern when the memory is activated. The amplification mechanism is induced by CaMKII dependent phosphorylation that doubles the conductance of all GABAA and AMPA receptors in a subset of neurons. This whole-cell transduction mechanism enables both long-term induction of memory amplification when necessary and extinction when not further required.'),
(88226, 2017, 'plos', 'Identifying T Cell Receptors from High-Throughput Sequencing: Dealing with Promiscuity in TCRxcexb1 and TCRxcexb2 Pairing', 'Lee, Edward S|Thomas, Paul G|Mold, Jeff E|Yates, Andrew J', 'Institute of Infection, Immunity & Inflammation, Glasgow Biomedical Research Centre, University of Glasgow, Glasgow, United Kingdom.|St. Jude Childrens Research Hospital, Memphis, Tennessee, United States of America.|Karolinska Institute, CMB, Stockholm, Sweden.|Institute of Infection, Immunity & Inflammation, Glasgow Biomedical Research Centre, University of Glasgow, Glasgow, United Kingdom.', 'United Kingdom|United States|Sweden|United Kingdom', 12, 'Algorithms|Cells, Cultured|Complementarity Determining Regions|Computational Biology|High-Throughput Nucleotide Sequencing|Humans|Receptors, Antigen, T-Cell|T-Lymphocytes', 'Journal Article', '10.1371/journal.pcbi.1005313', '28103239', 'Characterisation of the T cell receptors (TCR) involved in immune responses is important for the design of vaccines and immunotherapies for cancer and autoimmune disease. The specificity of the interaction between the TCR heterodimer and its peptide-MHC ligand derives largely from the juxtaposed hypervariable CDR3 regions on the TCRxcexb1 and TCRxcexb2 chains, and obtaining the paired sequences of these regions is a standard for functionally defining the TCR. A brute force approach to identifying the TCRs in a population of T cells is to use high-throughput single-cell sequencing, but currently this process remains costly and risks missing small clones. Alternatively, CDR3xcexb1 and CDR3xcexb2 sequences can be associated using their frequency of co-occurrence in independent samples, but this approach can be confounded by the sharing of CDR3xcexb1 and CDR3xcexb2 across clones, commonly observed within epitope-specific T cell populations. The accurate, exhaustive, and economical recovery of TCR sequences from such populations therefore remains a challenging problem. Here we describe an algorithm for performing frequency-based pairing (alphabetr) that accommodates CDR3xcexb1- and CDR3xcexb2-sharing, cells expressing two TCRxcexb1 chains, and multiple forms of sequencing error. The algorithm also yields accurate estimates of clonal frequencies.'),
(88227, 2017, 'plos', 'Contextual Refinement of Regulatory Targets Reveals Effects on Breast Cancer Prognosis of the Regulome', 'Andrews, Erik|Wang, Yue|Xia, Tian|Cheng, Wenqing|Cheng, Chao', 'Department of Genetics, Geisel School of Medicine at Dartmouth, Hanover, New Hampshire, United States of America.|Department of Genetics, Geisel School of Medicine at Dartmouth, Hanover, New Hampshire, United States of America.|School of Electronic Information and Communications, Huazhong University of Science and Technology, Wuhan, Hubei, China.|School of Electronic Information and Communications, Huazhong University of Science and Technology, Wuhan, Hubei, China.|Department of Genetics, Geisel School of Medicine at Dartmouth, Hanover, New Hampshire, United States of America.', 'United States|United States|China|China|United States', 4, 'Algorithms|Breast Neoplasms|Data Curation|Female|Gene Expression Regulation, Neoplastic|Gene Regulatory Networks|Humans|Molecular Sequence Annotation|Prognosis', 'Journal Article', '10.1371/journal.pcbi.1005340', '28103241', 'Gene expression regulators, such as transcription factors (TFs) and microRNAs (miRNAs), have varying regulatory targets based on the tissue and physiological state (context) within which they are expressed. While the emergence of regulator-characterizing experiments has inferred the target genes of many regulators across many contexts, methods for transferring regulator target genes across contexts are lacking. Further, regulator target gene lists frequently are not curated or have permissive inclusion criteria, impairing their use. Here, we present a method called iterative Contextual Transcriptional Activity Inference of Regulators (icTAIR) to resolve these issues. icTAIR takes a regulators previously-identified target gene list and combines it with gene expression data from a context, quantifying that regulators activity for that context. It then calculates the correlation between each listed target genes expression and the quantitative score of regulatory activity, removes the uncorrelated genes from the list, and iterates the process until it derives a stable list of refined target genes. To validate and demonstrate icTAIRs power, we use it to refine the MSigDB c3 database of TF, miRNA and unclassified motif target gene lists for breast cancer. We then use its output for survival analysis with clinicopathological multivariable adjustment in 7 independent breast cancer datasets covering 3,430 patients. We uncover many novel prognostic regulators that were obscured prior to refinement, in particular NFY, and offer a detailed look at the composition and relationships among the breast cancer prognostic regulome. We anticipate icTAIR will be of general use in contextually refining regulator target genes for discoveries across many contexts. The icTAIR algorithm can be downloaded from https://github.com/icTAIR.');
INSERT INTO `papers` (`id`, `ano`, `journal`, `titulo`, `autores`, `afiliacao`, `pais`, `citacoes`, `palavra_chave`, `categorias`, `doi`, `pubmed`, `abstract`) VALUES
(88228, 2017, 'plos', 'Effect of the Latent Reservoir on the Evolution of HIV at the Within- and Between-Host Levels', 'Doekes, Hilje M|Fraser, Christophe|Lythgoe, Katrina A', 'Department of Infectious Disease Epidemiology, Imperial College London, London, United Kingdom.|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|United Kingdom', 9, 'Biological Evolution|CD4-Positive T-Lymphocytes|Computational Biology|HIV Infections|HIV-1|Host-Pathogen Interactions|Humans|Models, Biological|Virus Latency', 'Journal Article', '10.1371/journal.pcbi.1005228', '28103248', 'The existence of long-lived reservoirs of latently infected CD4+ T cells is the major barrier to curing HIV, and has been extensively studied in this light. However, the effect of these reservoirs on the evolutionary dynamics of the virus has received little attention. Here, we present a within-host quasispecies model that incorporates a long-lived reservoir, which we then nest into an epidemiological model of HIV dynamics. For biologically plausible parameter values, we find that the presence of a latent reservoir can severely delay evolutionary dynamics within a single host, with longer delays associated with larger relative reservoir sizes and/or homeostatic proliferation of cells within the reservoir. These delays can fundamentally change the dynamics of the virus at the epidemiological scale. In particular, the delay in within-host evolutionary dynamics can be sufficient for the virus to evolve intermediate viral loads consistent with maximising transmission, as is observed, and not the very high viral loads that previous models have predicted, an effect that can be further enhanced if viruses similar to those that initiate infection are preferentially transmitted. These results depend strongly on within-host characteristics such as the relative reservoir size, with the evolution of intermediate viral loads observed only when the within-host dynamics are sufficiently delayed. In conclusion, we argue that the latent reservoir has important, and hitherto under-appreciated, roles in both within- and between-host viral evolution.'),
(88229, 2017, 'plos', 'Complex Dynamics of Virus Spread from Low Infection Multiplicities: Implications for the Spread of Oncolytic Viruses', 'Rodriguez-Brenes, Ignacio A|Hofacre, Andrew|Fan, Hung|Wodarz, Dominik', 'Department of Mathematics, University of California, Irvine, Irvine, California, United States of America.|Department of Molecular Biology and Biochemistry, Cancer Research Institute, University of California, Irvine, Irvine, California, United States of America.|Department of Molecular Biology and Biochemistry, Cancer Research Institute, University of California, Irvine, Irvine, California, United States of America.|Department of Mathematics, University of California, Irvine, Irvine, California, United States of America.', 'United States|United States|United States|United States', 7, 'Computational Biology|HEK293 Cells|Host-Pathogen Interactions|Humans|Models, Biological|Oncolytic Viruses|Virus Replication', 'Journal Article', '10.1371/journal.pcbi.1005241', '28107341', 'While virus growth dynamics have been well-characterized in several infections, data are typically collected once the virus population becomes easily detectable. Earlier dynamics, however, remain less understood. We recently reported unusual early dynamics in an experimental system using adenovirus infection of human embryonic kidney (293) cells. Under identical experimental conditions, inoculation at low infection multiplicities resulted in either robust spread, or in limited spread that eventually stalled, with both outcomes occurring with approximately equal frequencies. The reasons underlying these observations have not been understood. Here, we present further experimental data showing that inhibition of interferon-induced antiviral states in cells results in a significant increase in the percentage of robust infections that are observed, implicating a race between virus replication and the spread of the anti-viral state as a central mechanism. Analysis of a variety of computational models, however, reveals that this alone cannot explain the simultaneous occurrence of both viral growth outcomes under identical conditions, and that additional biological mechanisms have to be invoked to explain the data. One such mechanism is the ability of the virus to overcome the antiviral state through multiple infection of cells. If this is included in the model, two outcomes of viral spread are found to be simultaneously stable, depending on initial conditions. In stochastic versions of such models, the system can go by chance to either state from identical initial conditions, with the relative frequency of the outcomes depending on the strength of the interferon-based anti-viral response, consistent with the experiments. This demonstrates considerable complexity during the early phase of the infection that can influence the ability of a virus to become successfully established. Implications for the initial dynamics of oncolytic virus spread through tumors are discussed.'),
(88230, 2017, 'plos', 'Psychotic Experiences and Overhasty Inferences Are Related to Maladaptive Learning', 'Stuke, Heiner|Stuke, Hannes|Weilnhammer, Veith Andreas|Schmack, Katharina', 'Department of Psychiatry and Psychotherapy, Charité-Universitätsmedizin Berlin Berlin, Germany.|Department of Mathematics, Freie Universität Berlin, Berlin, Germany.|Department of Psychiatry and Psychotherapy, Charité-Universitätsmedizin Berlin Berlin, Germany.|Department of Psychiatry and Psychotherapy, Charité-Universitätsmedizin Berlin Berlin, Germany.', 'Germany|Germany|Germany|Germany', 5, 'Adult|Computational Biology|Female|Hallucinations|Humans|Learning|Male|Models, Psychological|Psychotic Disorders|Young Adult', 'Journal Article', '10.1371/journal.pcbi.1005328', '28107344', 'Theoretical accounts suggest that an alteration in the brains learning mechanisms might lead to overhasty inferences, resulting in psychotic symptoms. Here, we sought to elucidate the suggested link between maladaptive learning and psychosis. Ninety-eight healthy individuals with varying degrees of delusional ideation and hallucinatory experiences performed a probabilistic reasoning task that allowed us to quantify overhasty inferences. Replicating previous results, we found a relationship between psychotic experiences and overhasty inferences during probabilistic reasoning. Computational modelling revealed that the behavioral data was best explained by a novel computational learning model that formalizes the adaptiveness of learning by a non-linear distortion of prediction error processing, where an increased non-linearity implies a growing resilience against learning from surprising and thus unreliable information (large prediction errors). Most importantly, a decreased adaptiveness of learning predicted delusional ideation and hallucinatory experiences. Our current findings provide a formal description of the computational mechanisms underlying overhasty inferences, thereby empirically substantiating theories that link psychosis to maladaptive learning.'),
(88231, 2017, 'plos', 'Modeling an Excitable Biosynthetic Tissue with Inherent Variability for Paired Computational-Experimental Studies', 'Gokhale, Tanmay A|Kim, Jong M|Kirkton, Robert D|Bursac, Nenad|Henriquez, Craig S', 'Department of Biomedical Engineering, Duke University, Durham, North Carolina, United States of America.|Department of Biomedical Engineering, Duke University, Durham, North Carolina, United States of America.|Department of Biomedical Engineering, Duke University, Durham, North Carolina, United States of America.|Department of Biomedical Engineering, Duke University, Durham, North Carolina, United States of America.|Department of Biomedical Engineering, Duke University, Durham, North Carolina, United States of America.', 'United States|United States|United States|United States|United States', 4, 'Cardiac Electrophysiology|Computational Biology|HEK293 Cells|Humans|Models, Cardiovascular|Tissue Culture Techniques|Tissue Engineering', 'Journal Article', '10.1371/journal.pcbi.1005342', '28107358', 'To understand how excitable tissues give rise to arrhythmias, it is crucially necessary to understand the electrical dynamics of cells in the context of their environment. Multicellular monolayer cultures have proven useful for investigating arrhythmias and other conduction anomalies, and because of their relatively simple structure, these constructs lend themselves to paired computational studies that often help elucidate mechanisms of the observed behavior. However, tissue cultures of cardiomyocyte monolayers currently require the use of neonatal cells with ionic properties that change rapidly during development and have thus been poorly characterized and modeled to date. Recently, Kirkton and Bursac demonstrated the ability to create biosynthetic excitable tissues from genetically engineered and immortalized HEK293 cells with well-characterized electrical properties and the ability to propagate action potentials. In this study, we developed and validated a computational model of these excitable HEK293 cells (called Ex293 cells) using existing electrophysiological data and a genetic search algorithm. In order to reproduce not only the mean but also the variability of experimental observations, we examined what sources of variation were required in the computational model. Random cell-to-cell and inter-monolayer variation in both ionic conductances and tissue conductivity was necessary to explain the experimentally observed variability in action potential shape and macroscopic conduction, and the spatial organization of cell-to-cell conductance variation was found to not impact macroscopic behavior, the resulting model accurately reproduces both normal and drug-modified conduction behavior. The development of a computational Ex293 cell and tissue model provides a novel framework to perform paired computational-experimental studies to study normal and abnormal conduction in multidimensional excitable tissue, and the methodology of modeling variation can be applied to models of any excitable cell.'),
(88232, 2017, 'plos', 'Scalable Parameter Estimation for Genome-Scale Biochemical Reaction Networks', 'Fröhlich, Fabian|Kaltenbacher, Barbara|Theis, Fabian J|Hasenauer, Jan', 'Helmholtz Zentrum München - German Research Center for Environmental Health, Institute of Computational Biology, Neuherberg, Germany.|University of Klagenfurt, Institute of Mathematics, Klagenfurt, Austria.|Helmholtz Zentrum München - German Research Center for Environmental Health, Institute of Computational Biology, Neuherberg, Germany.|Helmholtz Zentrum München - German Research Center for Environmental Health, Institute of Computational Biology, Neuherberg, Germany.', 'Germany|Austria|Germany|Germany', 49, 'Computer Simulation|Gene Expression Regulation|Genome|Models, Biological|Models, Statistical|Programming Languages|Proteome|Signal Transduction|Software', 'Journal Article', '10.1371/journal.pcbi.1005331', '28114351', 'Mechanistic mathematical modeling of biochemical reaction networks using ordinary differential equation (ODE) models has improved our understanding of small- and medium-scale biological processes. While the same should in principle hold for large- and genome-scale processes, the computational methods for the analysis of ODE models which describe hundreds or thousands of biochemical species and reactions are missing so far. While individual simulations are feasible, the inference of the model parameters from experimental data is computationally too intensive. In this manuscript, we evaluate adjoint sensitivity analysis for parameter estimation in large scale biochemical reaction networks. We present the approach for time-discrete measurement and compare it to state-of-the-art methods used in systems and computational biology. Our comparison reveals a significantly improved computational efficiency and a superior scalability of adjoint sensitivity analysis. The computational complexity is effectively independent of the number of parameters, enabling the analysis of large- and genome-scale models. Our study of a comprehensive kinetic model of ErbB signaling shows that parameter estimation using adjoint sensitivity analysis requires a fraction of the computation time of established methods. The proposed method will facilitate mechanistic modeling of genome-scale cellular processes, as required in the age of omics.'),
(88233, 2017, 'plos', 'Computational Account of Spontaneous Activity as a Signature of Predictive Coding', 'Koren, Veronika|Denève, Sophie', 'Group for Neural Theory, Département dÉtudes Cognitives, École Normale Supérieure, Paris, France.|Group for Neural Theory, Département dÉtudes Cognitives, École Normale Supérieure, Paris, France.', 'France|France', 13, 'Animals|Biological Clocks|Brain|Brain Waves|Computer Simulation|Feedback, Physiological|Humans|Models, Neurological|Models, Statistical|Nerve Net|Oscillometry', 'Journal Article', '10.1371/journal.pcbi.1005355', '28114353', 'Spontaneous activity is commonly observed in a variety of cortical states. Experimental evidence suggested that neural assemblies undergo slow oscillations with Up ad Down states even when the network is isolated from the rest of the brain. Here we show that these spontaneous events can be generated by the recurrent connections within the network and understood as signatures of neural circuits that are correcting their internal representation. A noiseless spiking neural network can represent its input signals most accurately when excitatory and inhibitory currents are as strong and as tightly balanced as possible. However, in the presence of realistic neural noise and synaptic delays, this may result in prohibitively large spike counts. An optimal working regime can be found by considering terms that control firing rates in the objective function from which the network is derived and then minimizing simultaneously the coding error and the cost of neural activity. In biological terms, this is equivalent to tuning neural thresholds and after-spike hyperpolarization. In suboptimal working regimes, we observe spontaneous activity even in the absence of feed-forward inputs. In an all-to-all randomly connected network, the entire population is involved in Up states. In spatially organized networks with local connectivity, Up states spread through local connections between neurons of similar selectivity and take the form of a traveling wave. Up states are observed for a wide range of parameters and have similar statistical properties in both active and quiescent state. In the optimal working regime, Up states are vanishing, leaving place to asynchronous activity, suggesting that this working regime is a signature of maximally efficient coding. Although they result in a massive increase in the firing activity, the read-out of spontaneous Up states is in fact orthogonal to the stimulus representation, therefore interfering minimally with the network function.'),
(88234, 2017, 'plos', 'High Affinity vs Native Fibronectin in the Modulation of xcexb1vxcexb23 Integrin Conformational Dynamics: Insights from Computational Analyses and Implications for Molecular Design', 'Paladino, Antonella|Civera, Monica|Belvisi, Laura|Colombo, Giorgio', 'Istituto di Chimica del Riconoscimento Molecolare CNR, Milan, Italy.|Dipartimento di Chimica, Universitxc3xa0 degli Studi di Milano, Milan, Italy.|Dipartimento di Chimica, Universitxc3xa0 degli Studi di Milano, Milan, Italy.|Istituto di Chimica del Riconoscimento Molecolare CNR, Milan, Italy.', 'Italy|Italy|Italy|Italy', 8, 'Binding Sites|Drug Discovery|Fibronectins|Integrin alphaVbeta3|Models, Chemical|Molecular Dynamics Simulation|Protein Binding|Protein Conformation|Protein Domains', 'Journal Article', '10.1371/journal.pcbi.1005334', '28114375', 'Understanding how binding events modulate functional motions of multidomain proteins is a major issue in chemical biology. We address several aspects of this problem by analyzing the differential dynamics of xcexb1vxcexb23 integrin bound to wild type (wtFN10, agonist) or high affinity (hFN10, antagonist) mutants of fibronectin. We compare the dynamics of complexes from large-scale domain motions to inter-residue coordinated fluctuations to characterize the distinctive traits of conformational evolution and shed light on the determinants of differential xcexb1vxcexb23 activation induced by different FN sequences. We propose an allosteric model for ligand-based integrin modulation: the conserved integrin binding pocket anchors the ligand, while different residues on the two FN10s act as the drivers that reorganize relevant interaction networks, guiding the shift towards inactive (hFN10-bound) or active states (wtFN10-bound). We discuss the implications of results for the design of integrin inhibitors.'),
(88235, 2017, 'plos', 'Morphological Transformation and Force Generation of Active Cytoskeletal Networks', 'Bidone, Tamara Carla|Jung, Wonyeong|Maruri, Daniel|Borau, Carlos|Kamm, Roger D|Kim, Taeyoon', 'Department of Mechanical and Aerospace Engineering, Polytechnic University of Turin, Turin, Italy.|School of Mechanical Engineering, Purdue University, West Lafayette, Indiana, United States of America.|Weldon School of Biomedical Engineering, Purdue University, West Lafayette, Indiana, United States of America.|Department of Mechanical Engineering, Aragon Institute of Engineering Research (I3A), University of Zaragoza, Zaragoza, Spain.|Departments of Biological Engineering and Mechanical Engineering, Massachusetts Institute of Technology, Cambridge, Massachusetts, United States of America.|Weldon School of Biomedical Engineering, Purdue University, West Lafayette, Indiana, United States of America.', 'Italy|India|India|Spain|United States|India', 18, 'Actin Cytoskeleton|Actomyosin|Animals|Computer Simulation|Cytoskeletal Proteins|Cytoskeleton|Elastic Modulus|Humans|Mechanotransduction, Cellular|Models, Biological|Molecular Motor Proteins|Morphogenesis|Stress, Mechanical', 'Journal Article', '10.1371/journal.pcbi.1005277', '28114384', 'Cells assemble numerous types of actomyosin bundles that generate contractile forces for biological processes, such as cytokinesis and cell migration. One example of contractile bundles is a transverse arc that forms via actomyosin-driven condensation of actin filaments in the lamellipodia of migrating cells and exerts significant forces on the surrounding environments. Structural reorganization of a network into a bundle facilitated by actomyosin contractility is a physiologically relevant and biophysically interesting process. Nevertheless, it remains elusive how actin filaments are reoriented, buckled, and bundled as well as undergo tension buildup during the structural reorganization. In this study, using an agent-based computational model, we demonstrated how the interplay between the density of myosin motors and cross-linking proteins and the rigidity, initial orientation, and turnover of actin filaments regulates the morphological transformation of a cross-linked actomyosin network into a bundle and the buildup of tension occurring during the transformation.'),
(88236, 2017, 'plos', 'Gene Expression Noise Enhances Robust Organization of the Early Mammalian Blastocyst', 'Holmes, William R|Reyes de Mochel, Nabora Soledad|Wang, Qixuan|Du, Huijing|Peng, Tao|Chiang, Michael|Cinquin, Olivier|Cho, Ken|Nie, Qing', 'Department of Physics and Astronomy, Vanderbilt University, Nashville TN, 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.|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.|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.', 'United States|United States|United States|United States|United States|United States|United States|Un', 11, 'Animals|Blastocyst|Cell Differentiation|Cell Plasticity|Cells, Cultured|Computer Simulation|Embryonic Development|Gene Expression Regulation, Developmental|Humans|Mice|Models, Biological|Models, Statistical|Signal-To-Noise Ratio|Stochastic Processes', 'Journal Article', '10.1371/journal.pcbi.1005320', '28114387', 'A critical event in mammalian embryo development is construction of an inner cell mass surrounded by a trophoectoderm (a shell of cells that later form extraembryonic structures). We utilize multi-scale, stochastic modeling to investigate the design principles responsible for robust establishment of these structures. This investigation makes three predictions, each supported by our quantitative imaging. First, stochasticity in the expression of critical genes promotes cell plasticity and has a critical role in accurately organizing the developing mouse blastocyst. Second, asymmetry in the levels of noise variation (expression fluctuation) of Cdx2 and Oct4 provides a means to gain the benefits of noise-mediated plasticity while ameliorating the potentially detrimental effects of stochasticity. Finally, by controlling the timing and pace of cell fate specification, the embryo temporally modulates plasticity and creates a time window during which each cell can continually read its environment and adjusts its fate. These results suggest noise has a crucial role in maintaining cellular plasticity and organizing the blastocyst.'),
(88237, 2017, 'plos', 'Quantitative Comparison of Abundance Structures of Generalized Communities: From B-Cell Receptor Repertoires to Microbiomes', 'Saeedghalati, Mohammadkarim|Farahpour, Farnoush|Budeus, Bettina|Lange, Anja|Westendorf, Astrid M|Seifert, Marc|Küppers, Ralf|Hoffmann, Daniel', 'Bioinformatics and Computational Biophysics, Faculty of Biology, University of Duisburg-Essen, Essen, Germany.|Bioinformatics and Computational Biophysics, Faculty of Biology, University of Duisburg-Essen, Essen, Germany.|Bioinformatics and Computational Biophysics, Faculty of Biology, University of Duisburg-Essen, Essen, Germany.|Bioinformatics and Computational Biophysics, Faculty of Biology, University of Duisburg-Essen, Essen, Germany.|Center for Medical Biotechnology, University of Duisburg-Essen, Essen, Germany.|Institute of Cell Biology (Cancer Research), Medical Faculty, University of Duisburg-Essen, Essen, Germany.|Center for Medical Biotechnology, University of Duisburg-Essen, Essen, Germany.|Bioinformatics and Computational Biophysics, Faculty of Biology, University of Duisburg-Essen, Essen, Germany.', 'Germany|Germany|Germany|Germany|Germany|Germany|Germany|Germany', 5, 'Animals|B-Cell Activation Factor Receptor|Computer Simulation|Genetic Variation|Genetics, Population|Humans|Microbiota|Models, Genetic|Models, Statistical', 'Comparative Study', '10.1371/journal.pcbi.1005362', '28114391', 'The community, the assemblage of organisms co-existing in a given space and time, has the potential to become one of the unifying concepts of biology, especially with the advent of high-throughput sequencing experiments that reveal genetic diversity exhaustively. In this spirit we show that a tool from community ecology, the Rank Abundance Distribution (RAD), can be turned by the new MaxRank normalization method into a generic, expressive descriptor for quantitative comparison of communities in many areas of biology. To illustrate the versatility of the method, we analyze RADs from various generalized communities, i.e. assemblages of genetically diverse cells or organisms, including human B cells, gut microbiomes under antibiotic treatment and of different ages and countries of origin, and other human and environmental microbial communities. We show that normalized RADs enable novel quantitative approaches that help to understand structures and dynamics of complex generalized communities.'),
(88238, 2017, 'plos', 'Inferring the Chemotactic Strategy of P putida and E coli Using Modified Kramers-Moyal Coefficients', 'Pohl, Oliver|Hintsche, Marius|Alirezaeizanjani, Zahra|Seyrich, Maximilian|Beta, Carsten|Stark, Holger', 'Institute of Theoretical Physics, Technical University Berlin, Berlin, Germany.|Institute of Physics and Astronomy, University of Potsdam, Potsdam, Germany.|Institute of Physics and Astronomy, University of Potsdam, Potsdam, Germany.|Institute of Theoretical Physics, Technical University Berlin, Berlin, Germany.|Institute of Physics and Astronomy, University of Potsdam, Potsdam, Germany.|Institute of Theoretical Physics, Technical University Berlin, Berlin, Germany.', 'Germany|Germany|Germany|Germany|Germany|Germany', 13, 'Chemotaxis|Escherichia coli|Image Interpretation, Computer-Assisted|Microscopy, Video|Models, Biological|Models, Statistical|Pattern Recognition, Automated|Pseudomonas putida|Stochastic Processes', 'Journal Article', '10.1371/journal.pcbi.1005329', '28114420', 'Many bacteria perform a run-and-tumble random walk to explore their surrounding and to perform chemotaxis. In this article we present a novel method to infer the relevant parameters of bacterial motion from experimental trajectories including the tumbling events. We introduce a stochastic model for the orientation angle, where a shot-noise process initiates tumbles, and analytically calculate conditional moments, reminiscent of Kramers-Moyal coefficients. Matching them with the moments calculated from experimental trajectories of the bacteria E. coli and Pseudomonas putida, we are able to infer their respective tumble rates, the rotational diffusion constants, and the distributions of tumble angles in good agreement with results from conventional tumble recognizers. We also define a novel tumble recognizer, which explicitly quantifies the error in recognizing tumbles. In the presence of a chemical gradient we condition the moments on the bacterial direction of motion and thereby explore the chemotaxis strategy. For both bacteria we recover and quantify the classical chemotactic strategy, where the tumble rate is smallest along the chemical gradient. In addition, for E. coli we detect some cells, which bias their mean tumble angle towards smaller values. Our findings are supported by a scaling analysis of appropriate ratios of conditional moments, which are directly calculated from experimental data.'),
(88239, 2017, 'plos', 'Optogenetic Stimulation Shifts the Excitability of Cerebral Cortex from Type I to Type II: Oscillation Onset and Wave Propagation', 'Heitmann, Stewart|Rule, Michael|Truccolo, Wilson|Ermentrout, Bard', 'Department of Mathematics, University of Pittsburgh, Pittsburgh, Pennsylvania, USA.|Department of Neuroscience, Brown University, Providence, Rhode Island, USA.|Department of Neuroscience, Brown University, Providence, Rhode Island, USA.|Department of Mathematics, University of Pittsburgh, Pittsburgh, Pennsylvania, USA.', 'United States|United States|United States|United States', 3, 'Animals|Cerebral Cortex|Computational Biology|Gamma Rhythm|Interneurons|Macaca|Models, Neurological|Optogenetics', 'Journal Article', '10.1371/journal.pcbi.1005349', '28118355', 'Constant optogenetic stimulation targeting both pyramidal cells and inhibitory interneurons has recently been shown to elicit propagating waves of gamma-band (40-80 Hz) oscillations in the local field potential of non-human primate motor cortex. The oscillations emerge with non-zero frequency and small amplitude-the hallmark of a type II excitable medium-yet they also propagate far beyond the stimulation site in the manner of a type I excitable medium. How can neural tissue exhibit both type I and type II excitability? We investigated the apparent contradiction by modeling the cortex as a Wilson-Cowan neural field in which optogenetic stimulation was represented by an external current source. In the absence of any external current, the model operated as a type I excitable medium that supported propagating waves of gamma oscillations similar to those observed in vivo. Applying an external current to the population of inhibitory neurons transformed the model into a type II excitable medium. The findings suggest that cortical tissue normally operates as a type I excitable medium but it is locally transformed into a type II medium by optogenetic stimulation which predominantly targets inhibitory neurons. The proposed mechanism accounts for the graded emergence of gamma oscillations at the stimulation site while retaining propagating waves of gamma oscillations in the non-stimulated tissue. It also predicts that gamma waves can be emitted on every second cycle of a 100 Hz oscillation. That prediction was subsequently confirmed by re-analysis of the neurophysiological data. The model thus offers a theoretical account of how optogenetic stimulation alters the excitability of cortical neural fields.'),
(88240, 2017, 'plos', 'Genome-Wide Association between Transcription Factor Expression and Chromatin Accessibility Reveals Regulators of Chromatin Accessibility', 'Lamparter, David|Marbach, Daniel|Rueedi, Rico|Bergmann, Sven|Kutalik, Zoltán', 'Department of Computational Biology, University of Lausanne, Lausanne, Switzerland.|Department of Computational Biology, University of Lausanne, Lausanne, Switzerland.|Department of Computational Biology, University of Lausanne, Lausanne, Switzerland.|Department of Computational Biology, University of Lausanne, Lausanne, Switzerland.|Swiss institute of Bioinformatics, Lausanne, Switzerland.', 'Switzerland|Switzerland|Switzerland|Switzerland|Switzerland', 12, 'Binding Sites|Cell Line|Chromatin|Chromatin Immunoprecipitation|Computational Biology|Genome-Wide Association Study|Humans|Transcription Factors', 'Journal Article', '10.1371/journal.pcbi.1005311', '28118358', 'To better understand genome regulation, it is important to uncover the role of transcription factors in the process of chromatin structure establishment and maintenance. Here we present a data-driven approach to systematically characterise transcription factors that are relevant for this process. Our method uses a linear mixed modelling approach to combine datasets of transcription factor binding motif enrichments in open chromatin and gene expression across the same set of cell lines. Applying this approach to the ENCODE dataset, we confirm already known and imply numerous novel transcription factors that play a role in the establishment or maintenance of open chromatin. In particular, our approach rediscovers many factors that have been annotated as pioneer factors.'),
(88241, 2017, 'plos', 'A Validated Multiscale In-Silico Model for Mechano-sensitive Tumour Angiogenesis and Growth', 'Vavourakis, Vasileios|Wijeratne, Peter A|Shipley, Rebecca|Loizidou, Marilena|Stylianopoulos, Triantafyllos|Hawkes, David J', 'University College London, Centre for Medical Image Computing, Department of Medical Physics & Biomedical Engineering, London, United Kingdom.|University College London, Centre for Medical Image Computing, Department of Medical Physics & Biomedical Engineering, London, United Kingdom.|University College London, Department of Mechanical Engineering, London, United Kingdom.|University College London, Department of Surgery, London, United Kingdom.|University of Cyprus, Department of Mechanical & Manufacturing Engineering, Nicosia, Cyprus.|University College London, Centre for Medical Image Computing, Department of Medical Physics & Biomedical Engineering, London, United Kingdom.', 'United Kingdom|United Kingdom|United Kingdom|United Kingdom|Cyprus|United Kingdom', 0, 'Animals|Blood Flow Velocity|Blood Pressure|Cell Proliferation|Computer Simulation|Humans|Mechanotransduction, Cellular|Models, Biological|Neoplasms|Neovascularization, Pathologic|Shear Strength|Stress, Mechanical|Tumor Microenvironment', 'Evaluation Studies', '10.1371/journal.pcbi.1005259', '28125582', 'Vascularisation is a key feature of cancer growth, invasion and metastasis. To better understand the governing biophysical processes and their relative importance, it is instructive to develop physiologically representative mathematical models with which to compare to experimental data. Previous studies have successfully applied this approach to test the effect of various biochemical factors on tumour growth and angiogenesis. However, these models do not account for the experimentally observed dependency of angiogenic network evolution on growth-induced solid stresses. This work introduces two novel features: the effects of hapto- and mechanotaxis on vessel sprouting, and mechano-sensitive dynamic vascular remodelling. The proposed three-dimensional, multiscale, in-silico model of dynamically coupled angiogenic tumour growth is specified to in-vivo and in-vitro data, chosen, where possible, to provide a physiologically consistent description. The model is then validated against in-vivo data from murine mammary carcinomas, with particular focus placed on identifying the influence of mechanical factors. Crucially, we find that it is necessary to include hapto- and mechanotaxis to recapitulate observed time-varying spatial distributions of angiogenic vasculature.'),
(88242, 2017, 'plos', 'THE REAL McCOIL: A method for the concurrent estimation of the complexity of infection and SNP allele frequency for malaria parasites', 'Chang, Hsiao-Han|Worby, Colin J|Yeka, Adoke|Nankabirwa, Joaniter|Kamya, Moses R|Staedke, Sarah G|Dorsey, Grant|Murphy, Maxwell|Neafsey, Daniel E|Jeffreys, Anna E|Hubbart, Christina|Rockett, Kirk A|Amato, Roberto|Kwiatkowski, Dominic P|Buckee, Caroline O|Greenhouse, Bryan', 'Center for Communicable Disease Dynamics, Department of Epidemiology, Harvard T.H. Chan School of Public Health, Boston, Massachusetts, United States.|Center for Communicable Disease Dynamics, Department of Epidemiology, Harvard T.H. Chan School of Public Health, Boston, Massachusetts, United States.|Makerere University School of Public Health, College of Health Sciences, Kampala, Uganda.|Infectious Disease Research Collaboration, Kampala, Uganda.|Infectious Disease Research Collaboration, Kampala, Uganda.|London School of Hygiene and Tropical Medicine, London, United Kingdom.|Department of Medicine, University of California, San Francisco, San Francisco, California, United States.|Department of Medicine, University of California, San Francisco, San Francisco, California, United States.|Genome Sequencing and Analysis Program, Broad Institute, Cambridge, Massachusetts, United States.|Wellcome Trust Centre for Human Genetics, University of Oxford, Oxford, United Kingdom.|Wellcome Trust Centre for Human Genetics, University of Oxford, Oxford, United Kingdom.|Wellcome Trust Centre for Human Genetics, University of Oxford, Oxford, United Kingdom.|Wellcome Trust Sanger Institute, Cambridge, United Kingdom.|Wellcome Trust Centre for Human Genetics, University of Oxford, Oxford, United Kingdom.|Center for Communicable Disease Dynamics, Department of Epidemiology, Harvard T.H. Chan School of Public Health, Boston, Massachusetts, United States.|Department of Medicine, University of California, San Francisco, San Francisco, California, United States.', 'United States|United States|Uganda|Uganda|Uganda|United Kingdom|United States|United States|United S', 0, 'Gene Frequency|Humans|Malaria, Falciparum|Plasmodium falciparum|Polymorphism, Single Nucleotide|Population Surveillance|Risk Assessment|Risk Factors|Uganda', 'Journal Article', '10.1371/journal.pcbi.1005348', '28125584', 'As many malaria-endemic countries move towards elimination of Plasmodium falciparum, the most virulent human malaria parasite, effective tools for monitoring malaria epidemiology are urgent priorities. P. falciparum population genetic approaches offer promising tools for understanding transmission and spread of the disease, but a high prevalence of multi-clone or polygenomic infections can render estimation of even the most basic parameters, such as allele frequencies, challenging. A previous method, COIL, was developed to estimate complexity of infection (COI) from single nucleotide polymorphism (SNP) data, but relies on monogenomic infections to estimate allele frequencies or requires external allele frequency data which may not available. Estimates limited to monogenomic infections may not be representative, however, and when the average COI is high, they can be difficult or impossible to obtain. Therefore, we developed THE REAL McCOIL, Turning HEterozygous SNP data into Robust Estimates of ALelle frequency, via Markov chain Monte Carlo, and Complexity Of Infection using Likelihood, to incorporate polygenomic samples and simultaneously estimate allele frequency and COI. This approach was tested via simulations then applied to SNP data from cross-sectional surveys performed in three Ugandan sites with varying malaria transmission. We show that THE REAL McCOIL consistently outperforms COIL on simulated data, particularly when most infections are polygenomic. Using field data we show that, unlike with COIL, we can distinguish epidemiologically relevant differences in COI between and within these sites. Surprisingly, for example, we estimated high average COI in a peri-urban subregion with lower transmission intensity, suggesting that many of these cases were imported from surrounding regions with higher transmission intensity. THE REAL McCOIL therefore provides a robust tool for understanding the molecular epidemiology of malaria across transmission settings.'),
(88243, 2017, 'plos', 'The Flash-Lag Effect as a Motion-Based Predictive Shift', 'Khoei, Mina A|Masson, Guillaume S|Perrinet, Laurent U', 'Institut de Neurosciences de la Timone, UMR7289, CNRS / Aix-Marseille Université, Marseille, France.|Institut de Neurosciences de la Timone, UMR7289, CNRS / Aix-Marseille Université, Marseille, France.|Institut de Neurosciences de la Timone, UMR7289, CNRS / Aix-Marseille Université, Marseille, France.', 'France|France|France', 0, 'Animals|Computer Simulation|Humans|Models, Neurological|Models, Statistical|Motion Perception|Nerve Net|Reaction Time|Visual Cortex', 'Journal Article', '10.1371/journal.pcbi.1005068', '28125585', 'Due to its inherent neural delays, the visual system has an outdated access to sensory information about the current position of moving objects. In contrast, living organisms are remarkably able to track and intercept moving objects under a large range of challenging environmental conditions. Physiological, behavioral and psychophysical evidences strongly suggest that position coding is extrapolated using an explicit and reliable representation of objects motion but it is still unclear how these two representations interact. For instance, the so-called flash-lag effect supports the idea of a differential processing of position between moving and static objects. Although elucidating such mechanisms is crucial in our understanding of the dynamics of visual processing, a theory is still missing to explain the different facets of this visual illusion. Here, we reconsider several of the key aspects of the flash-lag effect in order to explore the role of motion upon neural coding of objects position. First, we formalize the problem using a Bayesian modeling framework which includes a graded representation of the degree of belief about visual motion. We introduce a motion-based prediction model as a candidate explanation for the perception of coherent motion. By including the knowledge of a fixed delay, we can model the dynamics of sensory information integration by extrapolating the information acquired at previous instants in time. Next, we simulate the optimal estimation of object position with and without delay compensation and compared it with human perception under a broad range of different psychophysical conditions. Our computational study suggests that the explicit, probabilistic representation of velocity information is crucial in explaining position coding, and therefore the flash-lag effect. We discuss these theoretical results in light of the putative corrective mechanisms that can be used to cancel out the detrimental effects of neural delays and illuminate the more general question of the dynamical representation at the present time of spatial information in the visual pathways.'),
(88244, 2017, 'plos', 'The language of geometry: Fast comprehension of geometrical primitives and rules in human adults and preschoolers', 'Amalric, Marie|Wang, Liping|Pica, Pierre|Figueira, Santiago|Sigman, Mariano|Dehaene, Stanislas', 'Cognitive Neuroimaging Unit, CEA DSV/I2BM, INSERM, Université Paris-Sud, Université Paris-Saclay, NeuroSpin center, Gif/Yvette, France.|Institute of Neuroscience, Key Laboratory of Primate Neurobiology, CAS Center for Excellence in Brain Science and Intelligence Technology, Chinese Academy of Sciences, Shanghai, China.|Instituto do Cérebro, Universidade Federal do Rio Grande do Norte, Natal, Brasil.|Department of Computer Science, FCEN, University of Buenos Aires and ICC-CONICET, Buenos Aires, Argentina.|Neuroscience Laboratory, Universidad Torcuato Di Tella, Buenos Aires, Argentina.|Cognitive Neuroimaging Unit, CEA DSV/I2BM, INSERM, Université Paris-Sud, Université Paris-Saclay, NeuroSpin center, Gif/Yvette, France.', 'France|China|-|Argentina|Argentina|France', 0, 'Adult|Algorithms|Child, Preschool|Comprehension|Concept Formation|Culture|Humans|Indians, South American|Language|Male|Mathematical Concepts|Mathematics|Models, Educational|Terminology as Topic', 'Journal Article', '10.1371/journal.pcbi.1005273', '28125595', 'During language processing, humans form complex embedded representations from sequential inputs. Here, we ask whether a geometrical language with recursive embedding also underlies the human ability to encode sequences of spatial locations. We introduce a novel paradigm in which subjects are exposed to a sequence of spatial locations on an octagon, and are asked to predict future locations. The sequences vary in complexity according to a well-defined language comprising elementary primitives and recursive rules. A detailed analysis of error patterns indicates that primitives of symmetry and rotation are spontaneously detected and used by adults, preschoolers, and adult members of an indigene group in the Amazon, the Munduruku, who have a restricted numerical and geometrical lexicon and limited access to schooling. Furthermore, subjects readily combine these geometrical primitives into hierarchically organized expressions. By evaluating a large set of such combinations, we obtained a first view of the language needed to account for the representation of visuospatial sequences in humans, and conclude that they encode visuospatial sequences by minimizing the complexity of the structured expressions that capture them.'),
(88245, 2017, 'plos', 'The Potential Role of Direct and Indirect Contacts on Infection Spread in Dairy Farm Networks', 'Rossi, Gianluigi|De Leo, Giulio A|Pongolini, Stefano|Natalini, Silvano|Zarenghi, Luca|Ricchi, Matteo|Bolzoni, Luca', 'Dipartimento di Bioscienze, Università degli studi di Parma, Parco Area delle Scienze, Parma, Italy.|Dipartimento di Bioscienze, Università degli studi di Parma, Parco Area delle Scienze, Parma, Italy.|Risk Analysis Unit, Istituto Zooprofilattico Sperimentale della Lombardia e dellEmilia Romagna, Via dei Mercati, Parma, Italy.|Servizio Veterinario e Igiene Alimenti, Assessorato Politiche per la Salute Regione Emilia-Romagna, Viale Aldo Moro, Bologna, Italy.|Servizio Igiene degli Allevamenti e Produzioni Zootecniche, AUSL di Parma, Via Vasari, Parma, Italy.|National Reference Centre for Paratuberculosis, Istituto Zooprofilattico Sperimentale della Lombardia e dellEmilia Romagna, Strada Faggiola 1, loc. Gariga-Podenzano (PC), Italy.|Risk Analysis Unit, Istituto Zooprofilattico Sperimentale della Lombardia e dellEmilia Romagna, Via dei Mercati, Parma, Italy.', 'Italy|Italy|Italy|Italy|Italy|Italy|Italy', 18, 'Agriculture|Animals|Cattle|Cattle Diseases|Communicable Diseases|Computer Simulation|Contact Tracing|Dairying|Disease Outbreaks|Female|Incidence|Italy|Male|Models, Statistical|Risk Factors', 'Journal Article', '10.1371/journal.pcbi.1005301', '28125610', 'Animals exchanges are considered the most effective route of between-farm infectious disease transmission. However, despite being often overlooked, the infection spread due to contaminated equipment, vehicles, or personnel proved to be important for several livestock epidemics. This study investigated the role of indirect contacts in a potential infection spread in the dairy farm network of the Province of Parma (Northern Italy). We built between-farm contact networks using data on cattle exchange (direct contacts), and on-farm visits by veterinarians (indirect contacts). We compared the features of the contact structures by using measures on static and temporal networks. We assessed the disease spreading potential of the direct and indirect network structures in the farm system by using data on the infection state of farms by paratuberculosis. Direct and indirect networks showed non-trivial differences with respect to connectivity, contact distribution, and super-spreaders identification. Furthermore, our analyses on paratuberculosis data suggested that the contributions of direct and indirect contacts on diseases spread are apparent at different spatial scales. Our results highlighted the potential role of indirect contacts in between-farm disease spread and underlined the need for a deeper understanding of these contacts to develop better strategies for prevention of livestock epidemics.');
INSERT INTO `papers` (`id`, `ano`, `journal`, `titulo`, `autores`, `afiliacao`, `pais`, `citacoes`, `palavra_chave`, `categorias`, `doi`, `pubmed`, `abstract`) VALUES
(88246, 2017, 'plos', 'Meneco, a Topology-Based Gap-Filling Tool Applicable to Degraded Genome-Wide Metabolic Networks', 'Prigent, Sylvain|Frioux, Clémence|Dittami, Simon M|Thiele, Sven|Larhlimi, Abdelhalim|Collet, Guillaume|Gutknecht, Fabien|Got, Jeanne|Eveillard, Damien|Bourdon, Jérémie|Plewniak, Frédéric|Tonon, Thierry|Siegel, Anne', 'Institute for Research in IT and Random Systems - IRISA, Université de Rennes 1, Rennes, France.|Institute for Research in IT and Random Systems - IRISA, Université de Rennes 1, Rennes, France.|Sorbonne Universités, UPMC Univ Paris 06, CNRS, UMR 8227, Integrative Biology of Marine Models, Station Biologique de Roscoff, Roscoff, France.|Dyliss, Inria, Rennes, France.|Computer Science Laboratory of Nantes Atlantique - LINA UMR6241, Université de Nantes, Nantes, France.|Institute for Research in IT and Random Systems - IRISA, Université de Rennes 1, Rennes, France.|Molecular Genetics, Genomics and Microbiology - GMGM, Université de Strasbourg, Strasbourg, France.|Institute for Research in IT and Random Systems - IRISA, Université de Rennes 1, Rennes, France.|Computer Science Laboratory of Nantes Atlantique - LINA UMR6241, Université de Nantes, Nantes, France.|Computer Science Laboratory of Nantes Atlantique - LINA UMR6241, Université de Nantes, Nantes, France.|Molecular Genetics, Genomics and Microbiology - GMGM, Université de Strasbourg, Strasbourg, France.|Sorbonne Universités, UPMC Univ Paris 06, CNRS, UMR 8227, Integrative Biology of Marine Models, Station Biologique de Roscoff, Roscoff, France.|Institute for Research in IT and Random Systems - IRISA, Université de Rennes 1, Rennes, France.', 'France|France|France|France|France|France|France|France|France|France|France|France|France', 0, 'Algorithms|Databases, Genetic|Escherichia coli|Genome|Genomics|Metabolic Networks and Pathways|Metabolome|Software|Transcriptome', 'Journal Article', '10.1371/journal.pcbi.1005276', '28129330', 'Increasing amounts of sequence data are becoming available for a wide range of non-model organisms. Investigating and modelling the metabolic behaviour of those organisms is highly relevant to understand their biology and ecology. As sequences are often incomplete and poorly annotated, draft networks of their metabolism largely suffer from incompleteness. Appropriate gap-filling methods to identify and add missing reactions are therefore required to address this issue. However, current tools rely on phenotypic or taxonomic information, or are very sensitive to the stoichiometric balance of metabolic reactions, especially concerning the co-factors. This type of information is often not available or at least prone to errors for newly-explored organisms. Here we introduce Meneco, a tool dedicated to the topological gap-filling of genome-scale draft metabolic networks. Meneco reformulates gap-filling as a qualitative combinatorial optimization problem, omitting constraints raised by the stoichiometry of a metabolic network considered in other methods, and solves this problem using Answer Set Programming. Run on several artificial test sets gathering 10,800 degraded Escherichia coli networks Meneco was able to efficiently identify essential reactions missing in networks at high degradation rates, outperforming the stoichiometry-based tools in scalability. To demonstrate the utility of Meneco we applied it to two case studies. Its application to recent metabolic networks reconstructed for the brown algal model Ectocarpus siliculosus and an associated bacterium Candidatus Phaeomarinobacter ectocarpi revealed several candidate metabolic pathways for algal-bacterial interactions. Then Meneco was used to reconstruct, from transcriptomic and metabolomic data, the first metabolic network for the microalga Euglena mutabilis. These two case studies show that Meneco is a versatile tool to complete draft genome-scale metabolic networks produced from heterogeneous data, and to suggest relevant reactions that explain the metabolic capacity of a biological system.'),
(88247, 2017, 'plos', 'Correction: Suppressed Expression of T-Box Transcription Factors Is Involved in Senescence in Chronic Obstructive Pulmonary Disease', 'PLOS Computational Biology Staff', 'Institute for Research in IT and Random Systems - IRISA, Université de Rennes 1, Rennes, France.', 'France', 0, '-', 'Published Erratum', '10.1371/journal.pcbi.1005263', '28129331', '[This corrects the article DOI: 10.1371/journal.pcbi.1002597.].'),
(88248, 2017, 'plos', 'Identification of Entry Factors Involved in Hepatitis C Virus Infection Based on Host-Mimicking Short Linear Motifs', 'Chiang, Austin W T|Wu, Walt Y L|Wang, Ting|Hwang, Ming-Jing', 'Institute of Biomedical Sciences, Academia Sinica, Taipei, Taiwan.|Institute of Biomedical Sciences, Academia Sinica, Taipei, Taiwan.|Institute of Biomedical Sciences, Academia Sinica, Taipei, Taiwan.|Institute of Biomedical Sciences, Academia Sinica, Taipei, Taiwan.', '-|-|-|-', 4, 'Computational Biology|Hepacivirus|Hepatitis C|Host-Pathogen Interactions|Humans|Molecular Mimicry|Protein Interaction Domains and Motifs|Protein Interaction Maps|Virus Internalization', 'Journal Article', '10.1371/journal.pcbi.1005368', '28129350', 'Host factors that facilitate viral entry into cells can, in principle, be identified from a virus-host protein interaction network, but for most viruses information for such a network is limited. To help fill this void, we developed a bioinformatics approach and applied it to hepatitis C virus (HCV) infection, which is a current concern for global health. Using this approach, we identified short linear sequence motifs, conserved in the envelope proteins of HCV (E1/E2), that potentially can bind human proteins present on the surface of hepatocytes so as to construct an HCV (envelope)-host protein interaction network. Gene Ontology functional and KEGG pathway analyses showed that the identified host proteins are enriched in cell entry and carcinogenesis functionalities. The validity of our results is supported by much published experimental data. Our general approach should be useful when developing antiviral agents, particularly those that target virus-host interactions.'),
(88249, 2017, 'plos', 'Memory replay in balanced recurrent networks', 'Chenkov, Nikolay|Sprekeler, Henning|Kempter, Richard', 'Institute for Theoretical Biology, Humboldt-Universität zu Berlin, Berlin, Germany.|Bernstein Center for Computational Neuroscience Berlin, Berlin, Germany.|Institute for Theoretical Biology, Humboldt-Universität zu Berlin, Berlin, Germany.', 'Germany|Germany|Germany', 0, 'Animals|Brain|Computer Simulation|Feedback, Physiological|Humans|Mental Recall|Models, Neurological|Nerve Net|Neuronal Plasticity|Synapses|Synaptic Transmission', 'Journal Article', '10.1371/journal.pcbi.1005359', '28135266', 'Complex patterns of neural activity appear during up-states in the neocortex and sharp waves in the hippocampus, including sequences that resemble those during prior behavioral experience. The mechanisms underlying this replay are not well understood. How can small synaptic footprints engraved by experience control large-scale network activity during memory retrieval and consolidation? We hypothesize that sparse and weak synaptic connectivity between Hebbian assemblies are boosted by pre-existing recurrent connectivity within them. To investigate this idea, we connect sequences of assemblies in randomly connected spiking neuronal networks with a balance of excitation and inhibition. Simulations and analytical calculations show that recurrent connections within assemblies allow for a fast amplification of signals that indeed reduces the required number of inter-assembly connections. Replay can be evoked by small sensory-like cues or emerge spontaneously by activity fluctuations. Global-potentially neuromodulatory-alterations of neuronal excitability can switch between network states that favor retrieval and consolidation.'),
(88250, 2017, 'plos', 'Effect of mutation mechanisms on variant composition and distribution in Caenorhabditis elegans', 'Hwang, Ho-Yon|Wang, Jiou', 'Department of Biochemistry and Molecular Biology, Bloomberg School of Public Health, Department of Neuroscience, School of Medicine, Johns Hopkins University, Baltimore, MD, United States of America.|Department of Biochemistry and Molecular Biology, Bloomberg School of Public Health, Department of Neuroscience, School of Medicine, Johns Hopkins University, Baltimore, MD, United States of America.', 'United States|United States', 1, 'Animals|Caenorhabditis elegans|Chromosome Mapping|Computer Simulation|Genetics, Population|Genome|Models, Genetic|Models, Statistical|Mutation|Polymorphism, Single Nucleotide|Recombination, Genetic|Selection, Genetic', 'Journal Article', '10.1371/journal.pcbi.1005369', '28135268', 'Genetic diversity is maintained by continuing generation and removal of variants. While examining over 800,000 DNA variants in wild isolates of Caenorhabditis elegans, we made a discovery that the proportions of variant types are not constant across the C. elegans genome. The variant proportion is defined as the fraction of a specific variant type (e.g. single nucleotide polymorphism (SNP) or indel) within a broader set of variants (e.g. all variants or all non-SNPs). The proportions of most variant types show a correlation with the recombination rate. These correlations can be explained as a result of a concerted action of two mutation mechanisms, which we named Morgan and Sanger mechanisms. The two proposed mechanisms act according to the distinct components of the recombination rate, specifically the genetic and physical distance. Regression analysis was used to explore the characteristics and contributions of the two mutation mechanisms. According to our model, ~20-40% of all mutations in C. elegans wild populations are derived from programmed meiotic double strand breaks, which precede chromosomal crossovers and thus may be the point of origin for the Morgan mechanism. A substantial part of the known correlation between the recombination rate and variant distribution appears to be caused by the mutations generated by the Morgan mechanism. Mathematically integrating the mutation model with background selection model gives a more complete depiction of how the variant landscape is shaped in C. elegans. Similar analysis should be possible in other species by examining the correlation between the recombination rate and variant landscape within the context of our mutation model.'),
(88251, 2017, 'plos', 'An Asymmetrically Balanced Organization of Kinases versus Phosphatases across Eukaryotes Determines Their Distinct Impacts', 'Smoly, Ilan|Shemesh, Netta|Ziv-Ukelson, Michal|Ben-Zvi, Anat|Yeger-Lotem, Esti', 'Department of Computer Science, Ben-Gurion University of the Negev, Beer-Sheva, Israel.|National Institute for Biotechnology in the Negev, Ben-Gurion University of the Negev, Beer-Sheva, Israel.|Department of Computer Science, Ben-Gurion University of the Negev, Beer-Sheva, Israel.|National Institute for Biotechnology in the Negev, Ben-Gurion University of the Negev, Beer-Sheva, Israel.|National Institute for Biotechnology in the Negev, Ben-Gurion University of the Negev, Beer-Sheva, Israel.', 'Israel|Israel|Israel|Israel|Israel', 10, 'Animals|Arabidopsis|Drosophila melanogaster|Enzyme Activation|Evolution, Molecular|Gene Expression Regulation, Enzymologic|Genetic Variation|Mice|Phosphoric Monoester Hydrolases|Phosphorylation|Phosphotransferases|Saccharomyces cerevisiae|Species Specificity|Yeasts', 'Journal Article', '10.1371/journal.pcbi.1005221', '28135269', 'Protein phosphorylation underlies cellular response pathways across eukaryotes and is governed by the opposing actions of phosphorylating kinases and de-phosphorylating phosphatases. While kinases and phosphatases have been extensively studied, their organization and the mechanisms by which they balance each other are not well understood. To address these questions we performed quantitative analyses of large-scale omics datasets from yeast, fly, plant, mouse and human. We uncovered an asymmetric balance of a previously-hidden scale: Each organism contained many different kinase genes, and these were balanced by a small set of highly abundant phosphatase proteins. Kinases were much more responsive to perturbations at the gene and protein levels. In addition, kinases had diverse scales of phenotypic impact when manipulated. Phosphatases, in contrast, were stable, highly robust and flatly organized, with rather uniform impact downstream. We validated aspects of this organization experimentally in nematode, and supported additional aspects by theoretic analysis of the dynamics of protein phosphorylation. Our analyses explain the empirical bias in the protein phosphorylation field toward characterization and therapeutic targeting of kinases at the expense of phosphatases. We show quantitatively and broadly that this is not only a historical bias, but stems from wide-ranging differences in their organization and impact. The asymmetric balance between these opposing regulators of protein phosphorylation is also common to opposing regulators of two other post-translational modification systems, suggesting its fundamental value.'),
(88252, 2017, 'plos', 'Optimal Sequential Immunization Can Focus Antibody Responses against Diversity Loss and Distraction', 'Wang, Shenshen', 'Department of Physics and Astronomy, University of California Los Angeles, Los Angeles, California, United States of America.', 'United States', 4, 'AIDS Vaccines|Antibodies, Neutralizing|Antibody Affinity|Antibody Diversity|Antigen-Antibody Reactions|B-Lymphocytes|Biological Evolution|Cell Survival|Cells, Cultured|Computer Simulation|Genetic Variation|Humans|Immunization|Immunization Schedule|Immunogenetic Phenomena|Models, Genetic|Models, Immunological|Models, Statistical|Stochastic Processes', 'Journal Article', '10.1371/journal.pcbi.1005336', '28135270', 'Affinity maturation is a Darwinian process in which B lymphocytes evolve potent antibodies to encountered antigens and generate immune memory. Highly mutable complex pathogens present an immense antigenic diversity that continues to challenge natural immunity and vaccine design. Induction of broadly neutralizing antibodies (bnAbs) against this diversity by vaccination likely requires multiple exposures to distinct but related antigen variants, and yet how affinity maturation advances under such complex stimulation remains poorly understood. To fill the gap, we present an in silico model of affinity maturation to examine two realistic new aspects pertinent to vaccine development: loss in B cell diversity across successive immunization periods against different variants, and the presence of distracting epitopes that entropically disfavor the evolution of bnAbs. We find these new factors, which introduce additional selection pressures and constraints, significantly influence antibody breadth development, in a way that depends crucially on the temporal pattern of immunization (or selection forces). Curiously, a less diverse B cell seed may even favor the expansion and dominance of cross-reactive clones, but only when conflicting selection forces are presented in series rather than in a mixture. Moreover, the level of frustration due to evolutionary conflict dictates the degree of distraction. We further describe how antigenic histories select evolutionary paths of B cell lineages and determine the predominant mode of antibody responses. Sequential immunization with mutationally distant variants is shown to robustly induce bnAbs that focus on conserved elements of the target epitope, by thwarting strain-specific and distracted lineages. An optimal range of antigen dose underlies a fine balance between efficient adaptation and persistent reaction. These findings provide mechanistic guides to aid in design of vaccine strategies against fast mutating pathogens.'),
(88253, 2017, 'plos', 'Binding of DNA-bending non-histone proteins destabilizes regular 30-nm chromatin structure', 'Bajpai, Gaurav|Jain, Ishutesh|Inamdar, Mandar M|Das, Dibyendu|Padinhateeri, Ranjith', 'Department of Biosciences and Bioengineering, Indian Institute of Technology Bombay, Mumbai, India.|Department of Biosciences and Bioengineering, Indian Institute of Technology Bombay, Mumbai, India.|Department of Civil Engineering, Indian Institute of Technology Bombay, Mumbai, India.|Department of Physics, Indian Institute of Technology Bombay, Mumbai, India.|Department of Biosciences and Bioengineering, Indian Institute of Technology Bombay, Mumbai, India.', 'India|India|India|India|India', 9, 'Binding Sites|Chromatin|Chromosomal Proteins, Non-Histone|Computer Simulation|DNA|DNA-Binding Proteins|Elastic Modulus|Models, Chemical|Models, Molecular|Nucleic Acid Conformation|Protein Binding|Protein Conformation', 'Journal Article', '10.1371/journal.pcbi.1005365', '28135276', 'Why most of the in vivo experiments do not find the 30-nm chromatin fiber, well studied in vitro, is a puzzle. Two basic physical inputs that are crucial for understanding the structure of the 30-nm fiber are the stiffness of the linker DNA and the relative orientations of the DNA entering/exiting nucleosomes. Based on these inputs we simulate chromatin structure and show that the presence of non-histone proteins, which bind and locally bend linker DNA, destroys any regular higher order structures (e.g., zig-zag). Accounting for the bending geometry of proteins like nhp6 and HMG-B, our theory predicts phase-diagram for the chromatin structure as a function of DNA-bending non-histone protein density and mean linker DNA length. For a wide range of linker lengths, we show that as we vary one parameter, that is, the fraction of bent linker region due to non-histone proteins, the steady-state structure will show a transition from zig-zag to an irregular structure-a structure that is reminiscent of what is observed in experiments recently. Our theory can explain the recent in vivo observation of irregular chromatin having co-existence of finite fraction of the next-neighbor (i + 2) and neighbor (i + 1) nucleosome interactions.'),
(88254, 2017, 'plos', 'Exploring the inhibitory effect of membrane tension on cell polarization', 'Wang, Weikang|Tao, Kuan|Wang, Jing|Yang, Gen|Ouyang, Qi|Wang, Yugang|Zhang, Lei|Liu, Feng', 'State Key Laboratory of Nuclear Physics and Technology, School of Physics, Peking University, Beijing, Peoples Republic of China.|Center for Quantitative Biology, Peking University, Beijing, Peoples Republic of China.|State Key Laboratory of Nuclear Physics and Technology, School of Physics, Peking University, Beijing, Peoples Republic of China.|State Key Laboratory of Nuclear Physics and Technology, School of Physics, Peking University, Beijing, Peoples Republic of China.|Center for Quantitative Biology, Peking University, Beijing, Peoples Republic of China.|State Key Laboratory of Nuclear Physics and Technology, School of Physics, Peking University, Beijing, Peoples Republic of China.|Center for Quantitative Biology, Peking University, Beijing, Peoples Republic of China.|State Key Laboratory of Nuclear Physics and Technology, School of Physics, Peking University, Beijing, Peoples Republic of China.', 'China|China|China|China|China|China|China|China', 13, 'Actins|Cell Membrane|Cell Polarity|Computer Simulation|Mechanotransduction, Cellular|Membrane Fluidity|Models, Biological|Stress, Mechanical|Tensile Strength|rac GTP-Binding Proteins', 'Journal Article', '10.1371/journal.pcbi.1005354', '28135277', 'Cell polarization toward an attractant is influenced by both physical and chemical factors. Most existing mathematical models are based on reaction-diffusion systems and only focus on the chemical process occurring during cell polarization. However, membrane tension has been shown to act as a long-range inhibitor of cell polarization. Here, we present a cell polarization model incorporating the interplay between Rac GTPase, filamentous actin (F-actin), and cell membrane tension. We further test the predictions of this model by performing single cell measurements of the spontaneous polarization of cancer stem cells (CSCs) and non-stem cancer cells (NSCCs), as the former have lower cell membrane tension. Based on both our model and the experimental results, cell polarization is more sensitive to stimuli under low membrane tension, and high membrane tension improves the robustness and stability of cell polarization such that polarization persists under random perturbations. Furthermore, our simulations are the first to recapitulate the experimental results described by Houk et al., revealing that aspiration (elevation of tension) and release (reduction of tension) result in a decrease in and recovery of the activity of Rac-GTP, respectively, and that the relaxation of tension induces new polarity of the cell body when a cell with the pseudopod-neck-body morphology is severed.'),
(88255, 2017, 'plos', 'Cell Sorting and Noise-Induced Cell Plasticity Coordinate to Sharpen Boundaries between Gene Expression Domains', 'Wang, Qixuan|Holmes, William R|Sosnik, Julian|Schilling, Thomas|Nie, Qing', 'Center for Complex Biological Systems, University of California Irvine, Irvine, CA, United States of America.|Department of Physics and Astronomy, Vanderbilt University, Nashville, TN, 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.', 'United States|United States|United States|United States|United States', 0, 'Animals|Cell Adhesion|Cell Movement|Gene Expression|Gene Expression Regulation|Models, Biological|Models, Statistical|Morphogenesis|Neural Tube|Neuronal Plasticity|Rhombencephalon|Signal-To-Noise Ratio|Stochastic Processes|Zebrafish', 'Journal Article', '10.1371/journal.pcbi.1005307', '28135279', 'A fundamental question in biology is how sharp boundaries of gene expression form precisely in spite of biological variation/noise. Numerous mechanisms position gene expression domains across fields of cells (e.g. morphogens), but how these domains are refined remains unclear. In some cases, domain boundaries sharpen through differential adhesion-mediated cell sorting. However, boundaries can also sharpen through cellular plasticity, with cell fate changes driven by up- or down-regulation of gene expression. In this context, we have argued that noise in gene expression can help cells transition to the correct fate. Here we investigate the efficacy of cell sorting, gene expression plasticity, and their combination in boundary sharpening using multi-scale, stochastic models. We focus on the formation of hindbrain segments (rhombomeres) in the developing zebrafish as an example, but the mechanisms investigated apply broadly to many tissues. Our results indicate that neither sorting nor plasticity is sufficient on its own to sharpen transition regions between different rhombomeres. Rather the two have complementary strengths and weaknesses, which synergize when combined to sharpen gene expression boundaries.'),
(88256, 2017, 'plos', 'Use of chiral cell shape to ensure highly directional swimming in trypanosomes', 'Wheeler, Richard John', 'Sir William Dunn School of Pathology, University of Oxford, Oxford, United Kingdom.', 'United Kingdom', 0, 'Adaptation, Physiological|Cell Movement|Cell Size|Cell Tracking|Computer Simulation|Friction|Hydrodynamics|Microscopy, Video|Models, Biological|Swimming|Trypanosoma|Viscosity', 'Journal Article', '10.1371/journal.pcbi.1005353', '28141804', 'Swimming cells typically move along a helical path or undergo longitudinal rotation as they swim, arising from chiral asymmetry in hydrodynamic drag or propulsion bending the swimming path into a helix. Helical paths are beneficial for some forms of chemotaxis, but why asymmetric shape is so prevalent when a symmetric shape would also allow highly directional swimming is unclear. Here, I analyse the swimming of the insect life cycle stages of two human parasites, Trypanosoma brucei and Leishmania mexicana. This showed quantitatively how chirality in T. brucei cell shape confers highly directional swimming. High speed videomicrographs showed that T. brucei, L. mexicana and a T. brucei RNAi morphology mutant have a range of shape asymmetries, from wild-type T. brucei (highly chiral) to L. mexicana (near-axial symmetry). The chiral cells underwent longitudinal rotation while swimming, with more rapid longitudinal rotation correlating with swimming path directionality. Simulation indicated hydrodynamic drag on the chiral cell shape caused rotation, and the predicted geometry of the resulting swimming path matched the directionality of the observed swimming paths. This simulation of swimming path geometry showed that highly chiral cell shape is a robust mechanism through which microscale swimmers can achieve highly directional swimming at low Reynolds number. It is insensitive to random variation in shape or propulsion (biological noise). Highly symmetric cell shape can give highly directional swimming but is at risk of giving futile circular swimming paths in the presence of biological noise. This suggests the chiral T. brucei cell shape (associated with the lateral attachment of the flagellum) may be an adaptation associated with the bloodstream-inhabiting lifestyle of this parasite for robust highly directional swimming. It also provides a plausible general explanation for why swimming cells tend to have strong asymmetries in cell shape or propulsion.'),
(88257, 2017, 'plos', 'Coevolutionary dynamics of phenotypic diversity and contingent cooperation', 'Wu, Te|Wang, Long|Fu, Feng', 'Center for Complex Systems, Xidian University, Xian, China.|Center for Systems and Control, College of Engineering, Peking University, Beijing, China.|Department of Mathematics, Dartmouth College, Hanover, New Hampshire, United States of America.', 'China|China|United States', 13, 'Animals|Biological Evolution|Computer Simulation|Cooperative Behavior|Genetic Variation|Genetics, Population|Humans|Models, Genetic|Models, Statistical|Mutation|Phenotype', 'Journal Article', '10.1371/journal.pcbi.1005363', '28141806', 'Phenotypic diversity is considered beneficial to the evolution of contingent cooperation, in which cooperators channel their help preferentially towards others of similar phenotypes. However, it remains largely unclear how phenotypic variation arises in the first place and thus leads to the construction of phenotypic complexity. Here we propose a mathematical model to study the coevolutionary dynamics of phenotypic diversity and contingent cooperation. Unlike previous models, our model does not assume any prescribed level of phenotypic diversity, but rather lets it be an evolvable trait. Each individual expresses one phenotype at a time and only the phenotypes expressed are visible to others. Moreover, individuals can differ in their potential of phenotypic variation, which is characterized by the number of distinct phenotypes they can randomly switch to. Each individual incurs a cost proportional to the number of potentially expressible phenotypes so as to retain phenotypic variation and expression. Our results show that phenotypic diversity coevolves with contingent cooperation under a wide range of conditions and that there exists an optimal level of phenotypic diversity best promoting contingent cooperation. It pays for contingent cooperators to elevate their potential of phenotypic variation, thereby increasing their opportunities of establishing cooperation via novel phenotypes, as these new phenotypes serve as secret tags that are difficult for defector to discover and chase after. We also find that evolved high levels of phenotypic diversity can occasionally collapse due to the invasion of defector mutants, suggesting that cooperation and phenotypic diversity can mutually reinforce each other. Thus, our results provide new insights into better understanding the coevolution of cooperation and phenotypic diversity.'),
(88258, 2017, 'plos', 'Self-organised criticality in the evolution of a thermodynamic model of rodent thermoregulatory huddling', 'Wilson, Stuart P', 'Department of Psychology, The University of Sheffield, Sheffield, United Kingdom.', 'United Kingdom', 0, 'Animals|Behavior, Animal|Biological Evolution|Body Temperature Regulation|Competitive Behavior|Computer Simulation|Cooperative Behavior|Energy Transfer|Models, Biological|Models, Statistical|Rats|Thermodynamics', 'Journal Article', '10.1371/journal.pcbi.1005378', '28141809', 'A thermodynamic model of thermoregulatory huddling interactions between endotherms is developed. The model is presented as a Monte Carlo algorithm in which animals are iteratively exchanged between groups, with a probability of exchanging groups defined in terms of the temperature of the environment and the body temperatures of the animals. The temperature-dependent exchange of animals between groups is shown to reproduce a second-order critical phase transition, i.e., a smooth switch to huddling when the environment gets colder, as measured in recent experiments. A peak in the rate at which group sizes change, referred to as pup flow, is predicted at the critical temperature of the phase transition, consistent with a thermodynamic description of huddling, and with a description of the huddle as a self-organising system. The model was subjected to a simple evolutionary procedure, by iteratively substituting the physiologies of individuals that fail to balance the costs of thermoregulation (by huddling in groups) with the costs of thermogenesis (by contributing heat). The resulting tension between cooperative and competitive interactions was found to generate a phenomenon called self-organised criticality, as evidenced by the emergence of avalanches in fitness that propagate across many generations. The emergence of avalanches reveals how huddling can introduce correlations in fitness between individuals and thereby constrain evolutionary dynamics. Finally, a full agent-based model of huddling interactions is also shown to generate criticality when subjected to the same evolutionary pressures. The agent-based model is related to the Monte Carlo model in the way that a Vicsek model is related to an Ising model in statistical physics. Huddling therefore presents an opportunity to use thermodynamic theory to study an emergent adaptive animal behaviour. In more general terms, huddling is proposed as an ideal system for investigating the interaction between self-organisation and natural selection empirically.'),
(88259, 2017, 'plos', 'The missing link: Predicting connectomes from noisy and partially observed tract tracing data', 'Hinne, Max|Meijers, Annet|Bakker, Rembrandt|Tiesinga, Paul H E|Mørup, Morten|van Gerven, Marcel A J', 'Radboud University, Donders Institute for Brain, Cognition and Behaviour, Nijmegen, the Netherlands.|Radboud University, Donders Institute for Brain, Cognition and Behaviour, Nijmegen, the Netherlands.|Institute of Neuroscience and Medicine, Institute for Advanced Simulation and JARA BRAIN Institute I, Jülich Research Centre, Jülich, Germany.|Radboud University, Donders Institute for Brain, Cognition and Behaviour, Nijmegen, the Netherlands.|Technical University of Denmark, DTU Compute, Kgs. Lyngby, Denmark.|Radboud University, Donders Institute for Brain, Cognition and Behaviour, Nijmegen, the Netherlands.', 'Netherlands|Netherlands|Germany|Netherlands|Denmark|Netherlands', 4, 'Animals|Artifacts|Brain|Cerebral Cortex|Computer Simulation|Connectome|Diffusion Tensor Imaging|Macaca|Models, Anatomic|Models, Neurological|Models, Statistical|Sample Size|Signal-To-Noise Ratio|White Matter', 'Journal Article', '10.1371/journal.pcbi.1005374', '28141820', 'Our understanding of the wiring map of the brain, known as the connectome, has increased greatly in the last decade, mostly due to technological advancements in neuroimaging techniques and improvements in computational tools to interpret the vast amount of available data. Despite this, with the exception of the C. elegans roundworm, no definitive connectome has been established for any species. In order to obtain this, tracer studies are particularly appealing, as these have proven highly reliable. The downside of tract tracing is that it is costly to perform, and can only be applied ex vivo. In this paper, we suggest that instead of probing all possible connections, hitherto unknown connections may be predicted from the data that is already available. Our approach uses a latent space model that embeds the connectivity in an abstract physical space. Regions that are close in the latent space have a high chance of being connected, while regions far apart are most likely disconnected in the connectome. After learning the latent embedding from the connections that we did observe, the latent space allows us to predict connections that have not been probed previously. We apply the methodology to two connectivity data sets of the macaque, where we demonstrate that the latent space model is successful in predicting unobserved connectivity, outperforming two baselines and an alternative model in nearly all cases. Furthermore, we show how the latent spatial embedding may be used to integrate multimodal observations (i.e. anterograde and retrograde tracers) for the mouse neocortex. Finally, our probabilistic approach enables us to make explicit which connections are easy to predict and which prove difficult, allowing for informed follow-up studies.'),
(88260, 2017, 'plos', 'Iterative sure independence screening EM-Bayesian LASSO algorithm for multi-locus genome-wide association studies', 'Tamba, Cox Lwaka|Ni, Yuan-Li|Zhang, Yuan-Ming', 'State Key Laboratory of Crop Genetics and Germplasm Enhancement, Nanjing Agricultural University, Nanjing, China.|State Key Laboratory of Crop Genetics and Germplasm Enhancement, Nanjing Agricultural University, Nanjing, China.|State Key Laboratory of Crop Genetics and Germplasm Enhancement, Nanjing Agricultural University, Nanjing, China.', 'China|China|China', 0, 'Algorithms|Bayes Theorem|Chromosome Mapping|Computer Simulation|DNA Mutational Analysis|Data Interpretation, Statistical|Genetic Association Studies|Genetic Markers|Likelihood Functions|Models, Genetic|Models, Statistical|Polymorphism, Single Nucleotide|Quantitative Trait, Heritable', 'Journal Article', '10.1371/journal.pcbi.1005357', '28141824', 'Genome-wide association study (GWAS) entails examining a large number of single nucleotide polymorphisms (SNPs) in a limited sample with hundreds of individuals, implying a variable selection problem in the high dimensional dataset. Although many single-locus GWAS approaches under polygenic background and population structure controls have been widely used, some significant loci fail to be detected. In this study, we used an iterative modified-sure independence screening (ISIS) approach in reducing the number of SNPs to a moderate size. Expectation-Maximization (EM)-Bayesian least absolute shrinkage and selection operator (BLASSO) was used to estimate all the selected SNP effects for true quantitative trait nucleotide (QTN) detection. This method is referred to as ISIS EM-BLASSO algorithm. Monte Carlo simulation studies validated the new method, which has the highest empirical power in QTN detection and the highest accuracy in QTN effect estimation, and it is the fastest, as compared with efficient mixed-model association (EMMA), smoothly clipped absolute deviation (SCAD), fixed and random model circulating probability unification (FarmCPU), and multi-locus random-SNP-effect mixed linear model (mrMLM). To further demonstrate the new method, six flowering time traits in Arabidopsis thaliana were re-analyzed by four methods (New method, EMMA, FarmCPU, and mrMLM). As a result, the new method identified most previously reported genes. Therefore, the new method is a good alternative for multi-locus GWAS.'),
(88261, 2017, 'plos', 'Fundamental Activity Constraints Lead to Specific Interpretations of the Connectome', 'Schuecker, Jannis|Schmidt, Maximilian|van Albada, Sacha J|Diesmann, Markus|Helias, Moritz', 'Institute of Neuroscience and Medicine (INM-6) and Institute for Advanced Simulation (IAS-6) and JARA BRAIN Institute I, Jülich Research Centre, Jülich, Germany.|Institute of Neuroscience and Medicine (INM-6) and Institute for Advanced Simulation (IAS-6) and JARA BRAIN Institute I, Jülich Research Centre, Jülich, Germany.|Institute of Neuroscience and Medicine (INM-6) and Institute for Advanced Simulation (IAS-6) and JARA BRAIN Institute I, Jülich Research Centre, Jülich, Germany.|Institute of Neuroscience and Medicine (INM-6) and Institute for Advanced Simulation (IAS-6) and JARA BRAIN Institute I, Jülich Research Centre, Jülich, Germany.|Institute of Neuroscience and Medicine (INM-6) and Institute for Advanced Simulation (IAS-6) and JARA BRAIN Institute I, Jülich Research Centre, Jülich, Germany.', 'Germany|Germany|Germany|Germany|Germany', 0, 'Animals|Computer Simulation|Connectome|Evoked Potentials, Visual|Humans|Macaca|Models, Anatomic|Models, Neurological|Models, Statistical|Nerve Net|Synaptic Transmission|Visual Cortex|Visual Perception', 'Journal Article', '10.1371/journal.pcbi.1005179', '28146554', 'The continuous integration of experimental data into coherent models of the brain is an increasing challenge of modern neuroscience. Such models provide a bridge between structure and activity, and identify the mechanisms giving rise to experimental observations. Nevertheless, structurally realistic network models of spiking neurons are necessarily underconstrained even if experimental data on brain connectivity are incorporated to the best of our knowledge. Guided by physiological observations, any model must therefore explore the parameter ranges within the uncertainty of the data. Based on simulation results alone, however, the mechanisms underlying stable and physiologically realistic activity often remain obscure. We here employ a mean-field reduction of the dynamics, which allows us to include activity constraints into the process of model construction. We shape the phase space of a multi-scale network model of the vision-related areas of macaque cortex by systematically refining its connectivity. Fundamental constraints on the activity, i.e., prohibiting quiescence and requiring global stability, prove sufficient to obtain realistic layer- and area-specific activity. Only small adaptations of the structure are required, showing that the network operates close to an instability. The procedure identifies components of the network critical to its collective dynamics and creates hypotheses for structural data and future experiments. The method can be applied to networks involving any neuron model with a known gain function.'),
(88262, 2017, 'plos', 'Ten Simple Rules for Developing a Successful Research Proposal in Brazil', 'de Oliveira, Dyoni M|Buckeridge, Marcos S|Dos Santos, Wanderley D', 'Laboratory of Plant Biochemistry, Department of Biochemistry, State University of Maringá, Maringá, Paraná, Brazil.|Department of Botany, Institute of Bioscience, University of São Paulo, São Paulo, São Paulo, Brazil.|Laboratory of Plant Biochemistry, Department of Biochemistry, State University of Maringá, Maringá, Paraná, Brazil.', 'Brazil|Brazil|Brazil', 0, 'Algorithms|Brazil|Computational Biology|Documentation|Research|Research Design|Writing', 'Editorial', '10.1371/journal.pcbi.1005289', '28151931', '-'),
(88263, 2017, 'plos', 'A Comparative Analysis of Drug-Induced Hepatotoxicity in Clinically Relevant Situations', 'Thiel, Christoph|Cordes, Henrik|Fabbri, Lorenzo|Aschmann, Hélène Eloise|Baier, Vanessa|Smit, Ines|Atkinson, Francis|Blank, Lars Mathias|Kuepfer, Lars', 'Institute of Applied Microbiology (iAMB), Aachen Biology and Biotechnology (ABBt), RWTH Aachen University, Worringerweg 1, Aachen, Germany.|Institute of Applied Microbiology (iAMB), Aachen Biology and Biotechnology (ABBt), RWTH Aachen University, Worringerweg 1, Aachen, Germany.|Institute of Applied Microbiology (iAMB), Aachen Biology and Biotechnology (ABBt), RWTH Aachen University, Worringerweg 1, Aachen, Germany.|Institute of Applied Microbiology (iAMB), Aachen Biology and Biotechnology (ABBt), RWTH Aachen University, Worringerweg 1, Aachen, Germany.|Institute of Applied Microbiology (iAMB), Aachen Biology and Biotechnology (ABBt), RWTH Aachen University, Worringerweg 1, Aachen, Germany.|European Molecular Biology Laboratory, European Bioinformatics Institute (EMBL-EBI), Wellcome Genome Campus, Hinxton, Cambridge, United Kingdom.|European Molecular Biology Laboratory, European Bioinformatics Institute (EMBL-EBI), Wellcome Genome Campus, Hinxton, Cambridge, United Kingdom.|Institute of Applied Microbiology (iAMB), Aachen Biology and Biotechnology (ABBt), RWTH Aachen University, Worringerweg 1, Aachen, Germany.|Institute of Applied Microbiology (iAMB), Aachen Biology and Biotechnology (ABBt), RWTH Aachen University, Worringerweg 1, Aachen, Germany.', 'Germany|Germany|Germany|Germany|Germany|United Kingdom|United Kingdom|Germany|Germany', 0, 'Chemical and Drug Induced Liver Injury|Computer Simulation|Hepatocytes|Humans|Liver|Metabolic Clearance Rate|Models, Biological|Pharmacokinetics|Signal Transduction', 'Comparative Study', '10.1371/journal.pcbi.1005280', '28151932', 'Drug-induced toxicity is a significant problem in clinical care. A key problem here is a general understanding of the molecular mechanisms accompanying the transition from desired drug effects to adverse events following administration of either therapeutic or toxic doses, in particular within a patient context. Here, a comparative toxicity analysis was performed for fifteen hepatotoxic drugs by evaluating toxic changes reflecting the transition from therapeutic drug responses to toxic reactions at the cellular level. By use of physiologically-based pharmacokinetic modeling, in vitro toxicity data were first contextualized to quantitatively describe time-resolved drug responses within a patient context. Comparatively studying toxic changes across the considered hepatotoxicants allowed the identification of subsets of drugs sharing similar perturbations on key cellular processes, functional classes of genes, and individual genes. The identified subsets of drugs were next analyzed with regard to drug-related characteristics and their physicochemical properties. Toxic changes were finally evaluated to predict both molecular biomarkers and potential drug-drug interactions. The results may facilitate the early diagnosis of adverse drug events in clinical application.'),
(88264, 2017, 'plos', 'Ten Simple Rules on How to Organize a Scientific Retreat', 'Ponomarenko, Julia|Garrido, Romina|Guigó, Roderic', 'Centre for Genomic Regulation (CRG), Barcelona Institute of Science and Technology, Barcelona, Catalonia, Spain.|Centre for Genomic Regulation (CRG), Barcelona Institute of Science and Technology, Barcelona, Catalonia, Spain.|Centre for Genomic Regulation (CRG), Barcelona Institute of Science and Technology, Barcelona, Catalonia, Spain.', 'Spain|Spain|Spain', 1, 'Algorithms|Group Processes|Leadership|Models, Organizational|Organizational Objectives|Science|Staff Development', 'Editorial', '10.1371/journal.pcbi.1005344', '28151954', '-'),
(88265, 2017, 'plos', 'Correlation-based model of artificially induced plasticity in motor cortex by a bidirectional brain-computer interface', 'Lajoie, Guillaume|Krouchev, Nedialko I|Kalaska, John F|Fairhall, Adrienne L|Fetz, Eberhard E', 'University of Washington Institute for Neuroengineering, University of Washington, Seattle, WA, USA.|Montreal Neurological Institute, McGill University, Montreal, QC, Canada.|Groupe de recherche sur le système nerveux central, Département de neurosciences, Université de Montreal, Montreal, QC, Canada.|University of Washington Institute for Neuroengineering, University of Washington, Seattle, WA, USA.|University of Washington Institute for Neuroengineering, University of Washington, Seattle, WA, USA.', 'United States|Canada|Canada|United States|United States', 0, 'Brain-Computer Interfaces|Computer Simulation|Feedback, Physiological|Humans|Models, Neurological|Models, Statistical|Motor Cortex|Neurofeedback|Neuronal Plasticity|Statistics as Topic', 'Journal Article', '10.1371/journal.pcbi.1005343', '28151957', 'Experiments show that spike-triggered stimulation performed with Bidirectional Brain-Computer-Interfaces (BBCI) can artificially strengthen connections between separate neural sites in motor cortex (MC). When spikes from a neuron recorded at one MC site trigger stimuli at a second target site after a fixed delay, the connections between sites eventually strengthen. It was also found that effective spike-stimulus delays are consistent with experimentally derived spike-timing-dependent plasticity (STDP) rules, suggesting that STDP is key to drive these changes. However, the impact of STDP at the level of circuits, and the mechanisms governing its modification with neural implants remain poorly understood. The present work describes a recurrent neural network model with probabilistic spiking mechanisms and plastic synapses capable of capturing both neural and synaptic activity statistics relevant to BBCI conditioning protocols. Our model successfully reproduces key experimental results, both established and new, and offers mechanistic insights into spike-triggered conditioning. Using analytical calculations and numerical simulations, we derive optimal operational regimes for BBCIs, and formulate predictions concerning the efficacy of spike-triggered conditioning in different regimes of cortical activity.'),
(88266, 2017, 'plos', 'Effects of FGFR2 kinase activation loop dynamics on catalytic activity', 'Karp, Jerome M|Sparks, Samuel|Cowburn, David', 'Department of Biochemistry, Albert Einstein College of Medicine, Bronx, New York, United States of America.|Department of Biochemistry, Albert Einstein College of Medicine, Bronx, New York, United States of America.|Department of Biochemistry, Albert Einstein College of Medicine, Bronx, New York, United States of America.', 'United States|United States|United States', 0, 'Binding Sites|Catalysis|Enzyme Activation|Enzyme Stability|Models, Chemical|Molecular Dynamics Simulation|Protein Binding|Protein Conformation|Protein Domains|Receptor, Fibroblast Growth Factor, Type 2|Structure-Activity Relationship|Tyrosine', 'Journal Article', '10.1371/journal.pcbi.1005360', '28151998', 'The structural mechanisms by which receptor tyrosine kinases (RTKs) regulate catalytic activity are diverse and often based on subtle changes in conformational dynamics. The regulatory mechanism of one such RTK, fibroblast growth factor receptor 2 (FGFR2) kinase, is still unknown, as the numerous crystal structures of the unphosphorylated and phosphorylated forms of the kinase domains show no apparent structural change that could explain how phosphorylation could enable catalytic activity. In this study, we use several enhanced sampling molecular dynamics (MD) methods to elucidate the structural changes to the kinases activation loop that occur upon phosphorylation. We show that phosphorylation favors inward motion of Arg664, while simultaneously favoring outward motion of Leu665 and Pro666. The latter structural change enables the substrate to bind leading to its resultant phosphorylation. Inward motion of Arg664 allows it to interact with the xcexb3-phosphate of ATP as well as the substrate tyrosine. We show that this stabilizes the tyrosine and primes it for the catalytic phosphotransfer, and it may lower the activation barrier of the phosphotransfer reaction. Our work demonstrates the value of including dynamic information gleaned from computer simulation in deciphering RTK regulatory function.');
INSERT INTO `papers` (`id`, `ano`, `journal`, `titulo`, `autores`, `afiliacao`, `pais`, `citacoes`, `palavra_chave`, `categorias`, `doi`, `pubmed`, `abstract`) VALUES
(88267, 2017, 'plos', 'Genome composition and phylogeny of microbes predict their co-occurrence in the environment', 'Kamneva, Olga K', 'Department of Biology, Stanford University, Stanford, California, United States of America.', 'United States', 2, 'Bacteria|Chromosome Mapping|Computer Simulation|Ecosystem|Genome, Bacterial|Microbial Consortia|Microbial Interactions|Models, Genetic|Phylogeny|RNA, Ribosomal, 16S', 'Journal Article', '10.1371/journal.pcbi.1005366', '28152007', 'The genomic information of microbes is a major determinant of their phenotypic properties, yet it is largely unknown to what extent ecological associations between different species can be explained by their genome composition. To bridge this gap, this study introduces two new genome-wide pairwise measures of microbe-microbe interaction. The first (genome content similarity index) quantifies similarity in genome composition between two microbes, while the second (microbe-microbe functional association index) summarizes the topology of a protein functional association network built for a given pair of microbes and quantifies the fraction of network edges crossing organismal boundaries. These new indices are then used to predict co-occurrence between reference genomes from two 16S-based ecological datasets, accounting for phylogenetic relatedness of the taxa. Phylogenetic relatedness was found to be a strong predictor of ecological associations between microbes which explains about 10% of variance in co-occurrence data, but genome composition was found to be a strong predictor as well, it explains up to 4% the variance in co-occurrence when all genomic-based indices are used in combination, even after accounting for evolutionary relationships between the species. On their own, the metrics proposed here explain a larger proportion of variance than previously reported more complex methods that rely on metabolic network comparisons. In summary, results of this study indicate that microbial genomes do indeed contain detectable signal of organismal ecology, and the methods described in the paper can be used to improve mechanistic understanding of microbe-microbe interactions.'),
(88268, 2017, 'plos', 'Dynamic Maternal Gradients Control Timing and Shift-Rates for Drosophila Gap Gene Expression', 'Verd, Berta|Crombach, Anton|Jaeger, Johannes', 'EMBL/CRG Systems Biology Research Unit, Centre for Genomic Regulation (CRG), The Barcelona Institute of Science and Technology, Barcelona, Spain.|EMBL/CRG Systems Biology Research Unit, Centre for Genomic Regulation (CRG), The Barcelona Institute of Science and Technology, Barcelona, Spain.|EMBL/CRG Systems Biology Research Unit, Centre for Genomic Regulation (CRG), The Barcelona Institute of Science and Technology, Barcelona, Spain.', 'Spain|Spain|Spain', 22, 'Animals|Body Patterning|Computer Simulation|Drosophila|Drosophila Proteins|Embryonic Development|Female|Gene Expression Regulation, Developmental|Homeodomain Proteins|Models, Biological|Trans-Activators|Transcription Factors', 'Journal Article', '10.1371/journal.pcbi.1005285', '28158178', 'Pattern formation during development is a highly dynamic process. In spite of this, few experimental and modelling approaches take into account the explicit time-dependence of the rules governing regulatory systems. We address this problem by studying dynamic morphogen interpretation by the gap gene network in Drosophila melanogaster. Gap genes are involved in segment determination during early embryogenesis. They are activated by maternal morphogen gradients encoded by bicoid (bcd) and caudal (cad). These gradients decay at the same time-scale as the establishment of the antero-posterior gap gene pattern. We use a reverse-engineering approach, based on data-driven regulatory models called gene circuits, to isolate and characterise the explicitly time-dependent effects of changing morphogen concentrations on gap gene regulation. To achieve this, we simulate the system in the presence and absence of dynamic gradient decay. Comparison between these simulations reveals that maternal morphogen decay controls the timing and limits the rate of gap gene expression. In the anterior of the embyro, it affects peak expression and leads to the establishment of smooth spatial boundaries between gap domains. In the posterior of the embryo, it causes a progressive slow-down in the rate of gap domain shifts, which is necessary to correctly position domain boundaries and to stabilise the spatial gap gene expression pattern. We use a newly developed method for the analysis of transient dynamics in non-autonomous (time-variable) systems to understand the regulatory causes of these effects. By providing a rigorous mechanistic explanation for the role of maternal gradient decay in gap gene regulation, our study demonstrates that such analyses are feasible and reveal important aspects of dynamic gene regulation which would have been missed by a traditional steady-state approach. More generally, it highlights the importance of transient dynamics for understanding complex regulatory processes in development.'),
(88269, 2017, 'plos', 'Unifying view of mechanical and functional hotspots across class A GPCRs', 'Ponzoni, Luca|Rossetti, Giulia|Maggi, Luca|Giorgetti, Alejandro|Carloni, Paolo|Micheletti, Cristian', 'SISSA, Trieste, Italy.|IAS-5/INM-9: Computational Biomedicine - Institute for Advanced Simulation (IAS) / Institute of Neuroscience and Medicine (INM), Forschungszentrum Jülich, Jülich, Germany.|IAS-5/INM-9: Computational Biomedicine - Institute for Advanced Simulation (IAS) / Institute of Neuroscience and Medicine (INM), Forschungszentrum Jülich, Jülich, Germany.|IAS-5/INM-9: Computational Biomedicine - Institute for Advanced Simulation (IAS) / Institute of Neuroscience and Medicine (INM), Forschungszentrum Jülich, Jülich, Germany.|IAS-5/INM-9: Computational Biomedicine - Institute for Advanced Simulation (IAS) / Institute of Neuroscience and Medicine (INM), Forschungszentrum Jülich, Jülich, Germany.|SISSA, Trieste, Italy.', 'Italy|Germany|Germany|Germany|Germany|Italy', 7, 'Binding Sites|Models, Chemical|Molecular Docking Simulation|Protein Binding|Protein Conformation|Receptors, G-Protein-Coupled|Structure-Activity Relationship', 'Journal Article', '10.1371/journal.pcbi.1005381', '28158180', 'G protein-coupled receptors (GPCRs) are the largest superfamily of signaling proteins. Their activation process is accompanied by conformational changes that have not yet been fully uncovered. Here, we carry out a novel comparative analysis of internal structural fluctuations across a variety of receptors from class A GPCRs, which currently has the richest structural coverage. We infer the local mechanical couplings underpinning the receptors functional dynamics and finally identify those amino acids whose virtual deletion causes a significant softening of the mechanical network. The relevance of these amino acids is demonstrated by their overlap with those known to be crucial for GPCR function, based on static structural criteria. The differences with the latter set allow us to identify those sites whose functional role is more clearly detected by considering dynamical and mechanical properties. Of these sites with a genuine mechanical/dynamical character, the top ranking is amino acid 7x52, a previously unexplored, and experimentally verifiable key site for GPCR conformational response to ligand binding.'),
(88270, 2017, 'plos', 'Correction: When Optimal Feedback Control Is Not Enough: Feedforward Strategies Are Required for Optimal Control with Active Sensing', 'PLOS Computational Biology Staff', 'SISSA, Trieste, Italy.', 'Italy', 0, '-', 'Published Erratum', '10.1371/journal.pcbi.1005370', '28158187', '[This corrects the article DOI: 10.1371/journal.pcbi.1005190.].'),
(88271, 2017, 'plos', 'Insect Bio-inspired Neural Network Provides New Evidence on How Simple Feature Detectors Can Enable Complex Visual Generalization and Stimulus Location Invariance in the Miniature Brain of Honeybees', 'Roper, Mark|Fernando, Chrisantha|Chittka, Lars', 'Biological and Experimental Psychology, School of Biological and Chemical Sciences, Queen Mary University of London, London, United Kingdom.|Google DeepMind, London, United Kingdom.|Biological and Experimental Psychology, School of Biological and Chemical Sciences, Queen Mary University of London, London, United Kingdom.', 'United Kingdom|United Kingdom|United Kingdom', 6, 'Animals|Bees|Biomimetics|Brain|Computer Simulation|Models, Neurological|Nerve Net|Neural Networks (Computer)|Pattern Recognition, Automated|Pattern Recognition, Visual', 'Journal Article', '10.1371/journal.pcbi.1005333', '28158189', 'The ability to generalize over naturally occurring variation in cues indicating food or predation risk is highly useful for efficient decision-making in many animals. Honeybees have remarkable visual cognitive abilities, allowing them to classify visual patterns by common features despite having a relatively miniature brain. Here we ask the question whether generalization requires complex visual recognition or whether it can also be achieved with relatively simple neuronal mechanisms. We produced several simple models inspired by the known anatomical structures and neuronal responses within the bee brain and subsequently compared their ability to generalize achromatic patterns to the observed behavioural performance of honeybees on these cues. Neural networks with just eight large-field orientation-sensitive input neurons from the optic ganglia and a single layer of simple neuronal connectivity within the mushroom bodies (learning centres) show performances remarkably similar to a large proportion of the empirical results without requiring any form of learning, or fine-tuning of neuronal parameters to replicate these results. Indeed, a model simply combining sensory input from both eyes onto single mushroom body neurons returned correct discriminations even with partial occlusion of the patterns and an impressive invariance to the location of the test patterns on the eyes. This model also replicated surprising failures of bees to discriminate certain seemingly highly different patterns, providing novel and useful insights into the inner workings facilitating and limiting the utilisation of visual cues in honeybees. Our results reveal that reliable generalization of visual information can be achieved through simple neuronal circuitry that is biologically plausible and can easily be accommodated in a tiny insect brain.'),
(88272, 2017, 'plos', 'Early and Real-Time Detection of Seasonal Influenza Onset', 'Won, Miguel|Marques-Pita, Manuel|Louro, Carlota|Gonçalves-Sá, Joana', 'Instituto Gulbenkian de Ciência, Oeiras, Portugal.|Instituto Gulbenkian de Ciência, Oeiras, Portugal.|Nova Medical School, Universidade Nova de Lisboa and Saude 24, Lisbon, Portugal.|Instituto Gulbenkian de Ciência, Oeiras, Portugal.', 'Portugal|Portugal|Portugal|Portugal', 7, 'Computer Simulation|Computer Systems|Data Interpretation, Statistical|Disease Outbreaks|Early Diagnosis|Europe|Humans|Influenza, Human|Models, Statistical|Population Surveillance|Prevalence|Proportional Hazards Models|Reproducibility of Results|Risk Assessment|Seasons|Sensitivity and Specificity', 'Evaluation Studies', '10.1371/journal.pcbi.1005330', '28158192', 'Every year, influenza epidemics affect millions of people and place a strong burden on health care services. A timely knowledge of the onset of the epidemic could allow these services to prepare for the peak. We present a method that can reliably identify and signal the influenza outbreak. By combining official Influenza-Like Illness (ILI) incidence rates, searches for ILI-related terms on Google, and an on-call triage phone service, Saúde 24, we were able to identify the beginning of the flu season in 8 European countries, anticipating current official alerts by several weeks. This work shows that it is possible to detect and consistently anticipate the onset of the flu season, in real-time, regardless of the amplitude of the epidemic, with obvious advantages for health care authorities. We also show that the method is not limited to one country, specific region or language, and that it provides a simple and reliable signal that can be used in early detection of other seasonal diseases.'),
(88273, 2017, 'plos', 'ASPASIA: A toolkit for evaluating the effects of biological interventions on SBML model behaviour', 'Evans, Stephanie|Alden, Kieran|Cucurull-Sanchez, Lourdes|Larminie, Christopher|Coles, Mark C|Kullberg, Marika C|Timmis, Jon', 'York Computational Immunology Lab, University of York, York, United Kingdom.|York Computational Immunology Lab, University of York, York, United Kingdom.|GSK Medicines Research Centre, Stevenage, United Kingdom.|GSK Medicines Research Centre, Stevenage, United Kingdom.|York Computational Immunology Lab, University of York, York, United Kingdom.|York Computational Immunology Lab, University of York, York, United Kingdom.|York Computational Immunology Lab, University of York, York, United Kingdom.', 'United Kingdom|United Kingdom|United Kingdom|United Kingdom|United Kingdom|United Kingdom|United Kin', 3, 'Algorithms|Computer Simulation|Models, Biological|Programming Languages|Software|Systems Biology', 'Journal Article', '10.1371/journal.pcbi.1005351', '28158307', 'A calibrated computational model reflects behaviours that are expected or observed in a complex system, providing a baseline upon which sensitivity analysis techniques can be used to analyse pathways that may impact model responses. However, calibration of a model where a behaviour depends on an intervention introduced after a defined time point is difficult, as model responses may be dependent on the conditions at the time the intervention is applied. We present ASPASIA (Automated Simulation Parameter Alteration and SensItivity Analysis), a cross-platform, open-source Java toolkit that addresses a key deficiency in software tools for understanding the impact an intervention has on system behaviour for models specified in Systems Biology Markup Language (SBML). ASPASIA can generate and modify models using SBML solver output as an initial parameter set, allowing interventions to be applied once a steady state has been reached. Additionally, multiple SBML models can be generated where a subset of parameter values are perturbed using local and global sensitivity analysis techniques, revealing the models sensitivity to the intervention. To illustrate the capabilities of ASPASIA, we demonstrate how this tool has generated novel hypotheses regarding the mechanisms by which Th17-cell plasticity may be controlled in vivo. By using ASPASIA in conjunction with an SBML model of Th17-cell polarisation, we predict that promotion of the Th1-associated transcription factor T-bet, rather than inhibition of the Th17-associated transcription factor RORxcexb3t, is sufficient to drive switching of Th17 cells towards an IFN-xcexb3-producing phenotype. Our approach can be applied to all SBML-encoded models to predict the effect that intervention strategies have on system behaviour. ASPASIA, released under the Artistic License (2.0), can be downloaded from http://www.york.ac.uk/ycil/software.'),
(88274, 2017, 'plos', 'Data-driven reverse engineering of signaling pathways using ensembles of dynamic models', 'Henriques, David|Villaverde, Alejandro F|Rocha, Miguel|Saez-Rodriguez, Julio|Banga, Julio R', 'Bioprocess Engineering Group, Spanish National Research Council, IIM-CSIC, Vigo, Spain.|Bioprocess Engineering Group, Spanish National Research Council, IIM-CSIC, Vigo, Spain.|Centre of Biological Engineering, University of Minho, Braga, Portugal.|Joint Research Center for Computational Biomedicine, RWTH-Aachen University, Aachen, Germany.|Bioprocess Engineering Group, Spanish National Research Council, IIM-CSIC, Vigo, Spain.', 'Spain|Spain|Portugal|Germany|Spain', 18, 'Algorithms|Animals|Computer Simulation|Humans|Metabolic Engineering|Metabolic Flux Analysis|Models, Biological|Proteome|Signal Transduction', 'Journal Article', '10.1371/journal.pcbi.1005379', '28166222', 'Despite significant efforts and remarkable progress, the inference of signaling networks from experimental data remains very challenging. The problem is particularly difficult when the objective is to obtain a dynamic model capable of predicting the effect of novel perturbations not considered during model training. The problem is ill-posed due to the nonlinear nature of these systems, the fact that only a fraction of the involved proteins and their post-translational modifications can be measured, and limitations on the technologies used for growing cells in vitro, perturbing them, and measuring their variations. As a consequence, there is a pervasive lack of identifiability. To overcome these issues, we present a methodology called SELDOM (enSEmbLe of Dynamic lOgic-based Models), which builds an ensemble of logic-based dynamic models, trains them to experimental data, and combines their individual simulations into an ensemble prediction. It also includes a model reduction step to prune spurious interactions and mitigate overfitting. SELDOM is a data-driven method, in the sense that it does not require any prior knowledge of the system: the interaction networks that act as scaffolds for the dynamic models are inferred from data using mutual information. We have tested SELDOM on a number of experimental and in silico signal transduction case-studies, including the recent HPN-DREAM breast cancer challenge. We found that its performance is highly competitive compared to state-of-the-art methods for the purpose of recovering network topology. More importantly, the utility of SELDOM goes beyond basic network inference (i.e. uncovering static interaction networks): it builds dynamic (based on ordinary differential equation) models, which can be used for mechanistic interpretations and reliable dynamic predictions in new experimental conditions (i.e. not used in the training). For this task, SELDOMs ensemble prediction is not only consistently better than predictions from individual models, but also often outperforms the state of the art represented by the methods used in the HPN-DREAM challenge.'),
(88275, 2017, 'plos', 'Activated Oncogenic Pathway Modifies Iron Network in Breast Epithelial Cells: A Dynamic Modeling Perspective', 'Chifman, Julia|Arat, Seda|Deng, Zhiyong|Lemler, Erica|Pino, James C|Harris, Leonard A|Kochen, Michael A|Lopez, Carlos F|Akman, Steven A|Torti, Frank M|Torti, Suzy V|Laubenbacher, Reinhard', 'Department of Mathematics and Statistics, American University, Washington, DC, USA.|The Jackson Laboratory, Bar Harbor, ME, USA.|Department of Molecular Biology and Biophysics, University of Connecticut Health Center, Farmington, CT, USA.|Department of Molecular Biology and Biophysics, University of Connecticut Health Center, Farmington, CT, USA.|Chemical and Physical Biology Graduate Program, Vanderbilt University, Nashville, TN, USA.|Department of Cancer Biology, Vanderbilt University, Nashville, TN, USA.|Department of Biomedical Informatics, Vanderbilt University, Nashville, TN, USA.|Department of Cancer Biology, Vanderbilt University, Nashville, TN, USA.|Cancer Program, Roper St Francis HealthCare, Charleston, SC, USA.|Department of Medicine, University of Connecticut Health Center, Farmington, CT, USA.|Department of Molecular Biology and Biophysics, University of Connecticut Health Center, Farmington, CT, USA.|Center for Quantitative Medicine, University of Connecticut Health Center, Farmington, CT, USA.', 'United States|United States|United States|United States|United States|United States|United States|United States|United States|United States|United States|United States', 0, 'Adaptation, Physiological|Animals|Breast|Cell Transformation, Neoplastic|Computer Simulation|Epithelial Cells|Female|Humans|Iron|Iron Regulatory Protein 2|Models, Biological|Signal Transduction|Tumor Cells, Cultured|ras Proteins', 'Evaluation Studies', '10.1371/journal.pcbi.1005352', '28166223', 'Dysregulation of iron metabolism in cancer is well documented and it has been suggested that there is interdependence between excess iron and increased cancer incidence and progression. In an effort to better understand the linkages between iron metabolism and breast cancer, a predictive mathematical model of an expanded iron homeostasis pathway was constructed that includes species involved in iron utilization, oxidative stress response and oncogenic pathways. The model leads to three predictions. The first is that overexpression of iron regulatory protein 2 (IRP2) recapitulates many aspects of the alterations in free iron and iron-related proteins in cancer cells without affecting the oxidative stress response or the oncogenic pathways included in the model. This prediction was validated by experimentation. The second prediction is that iron-related proteins are dramatically affected by mitochondrial ferritin overexpression. This prediction was validated by results in the pertinent literature not used for model construction. The third prediction is that oncogenic Ras pathways contribute to altered iron homeostasis in cancer cells. This prediction was validated by a combination of simulation experiments of Ras overexpression and catalase knockout in conjunction with the literature. The model successfully captures key aspects of iron metabolism in breast cancer cells and provides a framework upon which more detailed models can be built.'),
(88276, 2017, 'plos', 'Multiscale mutation clustering algorithm identifies pan-cancer mutational clusters associated with pathway-level changes in gene expression', 'Poole, William|Leinonen, Kalle|Shmulevich, Ilya|Knijnenburg, Theo A|Bernard, Brady', 'Institute for Systems Biology, Seattle, WA, United States of America.|Institute for Systems Biology, Seattle, WA, United States of America.|Institute for Systems Biology, Seattle, WA, United States of America.|Institute for Systems Biology, Seattle, WA, United States of America.|Institute for Systems Biology, Seattle, WA, United States of America.', 'United States|United States|United States|United States|United States', 10, 'Algorithms|Chromosome Mapping|DNA Mutational Analysis|DNA, Neoplasm|Gene Expression Regulation, Neoplastic|Genes, Neoplasm|High-Throughput Nucleotide Sequencing|Humans|Multigene Family|Mutation|Neoplasms|Signal Transduction', 'Journal Article', '10.1371/journal.pcbi.1005347', '28170390', 'Cancer researchers have long recognized that somatic mutations are not uniformly distributed within genes. However, most approaches for identifying cancer mutations focus on either the entire-gene or single amino-acid level. We have bridged these two methodologies with a multiscale mutation clustering algorithm that identifies variable length mutation clusters in cancer genes. We ran our algorithm on 539 genes using the combined mutation data in 23 cancer types from The Cancer Genome Atlas (TCGA) and identified 1295 mutation clusters. The resulting mutation clusters cover a wide range of scales and often overlap with many kinds of protein features including structured domains, phosphorylation sites, and known single nucleotide variants. We statistically associated these multiscale clusters with gene expression and drug response data to illuminate the functional and clinical consequences of mutations in our clusters. Interestingly, we find multiple clusters within individual genes that have differential functional associations: these include PTEN, FUBP1, and CDH1. This methodology has potential implications in identifying protein regions for drug targets, understanding the biological underpinnings of cancer, and personalizing cancer treatments. Toward this end, we have made the mutation clusters and the clustering algorithm available to the public. Clusters and pathway associations can be interactively browsed at m2c.systemsbiology.net. The multiscale mutation clustering algorithm is available at https://github.com/IlyaLab/M2C.'),
(88277, 2017, 'plos', 'Bayesian phylogeography of influenza A/H3N2 for the 2014-15 season in the United States using three frameworks of ancestral state reconstruction', 'Magee, Daniel|Suchard, Marc A|Scotch, Matthew', 'Department of Biomedical Informatics, Arizona State University, Tempe, Arizona, United States of America.|Departments of Biomathematics and Human Genetics, David Geffen School of Medicine, University of California, Los Angeles, California, United States of America.|Department of Biomedical Informatics, Arizona State University, Tempe, Arizona, United States of America.', 'United States|United States|United States', 0, 'Bayes Theorem|Computer Simulation|Disease Outbreaks|Evolution, Molecular|Genetic Variation|Humans|Incidence|Influenza A Virus, H3N2 Subtype|Influenza, Human|Models, Statistical|Phylogeny|Phylogeography|Population Surveillance|Risk Factors|Seasons|Spatio-Temporal Analysis|Species Specificity|United States|Weather', 'Journal Article', '10.1371/journal.pcbi.1005389', '28170397', 'Ancestral state reconstructions in Bayesian phylogeography of virus pandemics have been improved by utilizing a Bayesian stochastic search variable selection (BSSVS) framework. Recently, this framework has been extended to model the transition rate matrix between discrete states as a generalized linear model (GLM) of genetic, geographic, demographic, and environmental predictors of interest to the virus and incorporating BSSVS to estimate the posterior inclusion probabilities of each predictor. Although the latter appears to enhance the biological validity of ancestral state reconstruction, there has yet to be a comparison of phylogenies created by the two methods. In this paper, we compare these two methods, while also using a primitive method without BSSVS, and highlight the differences in phylogenies created by each. We test six coalescent priors and six random sequence samples of H3N2 influenza during the 2014-15 flu season in the U.S. We show that the GLMs yield significantly greater root state posterior probabilities than the two alternative methods under five of the six priors, and significantly greater Kullback-Leibler divergence values than the two alternative methods under all priors. Furthermore, the GLMs strongly implicate temperature and precipitation as driving forces of this flu season and nearly unanimously identified a single root state, which exhibits the most tropical climate during a typical flu season in the U.S. The GLM, however, appears to be highly susceptible to sampling bias compared with the other methods, which casts doubt on whether its reconstructions should be favored over those created by alternate methods. We report that a BSSVS approach with a Poisson prior demonstrates less bias toward sample size under certain conditions than the GLMs or primitive models, and believe that the connection between reconstruction method and sampling bias warrants further investigation.'),
(88278, 2017, 'plos', 'Computational investigation of sphingosine kinase 1 (SphK1) and calcium dependent ERK1/2 activation downstream of VEGFR2 in endothelial cells', 'Bazzazi, Hojjat|Popel, Aleksander S', 'Department of Biomedical Engineering, School of Medicine, Johns Hopkins University, Baltimore, Maryland, United States of America.|Department of Biomedical Engineering, School of Medicine, Johns Hopkins University, Baltimore, Maryland, United States of America.', 'United States|United States', 0, 'Adaptor Proteins, Signal Transducing|Animals|Calcium|Calcium Signaling|Cells, Cultured|Computer Simulation|Endothelial Cells|Humans|MAP Kinase Signaling System|Models, Cardiovascular|Vascular Endothelial Growth Factor Receptor-2', 'Journal Article', '10.1371/journal.pcbi.1005332', '28178265', 'Vascular endothelial growth factor (VEGF) is a powerful regulator of neovascularization. VEGF binding to its cognate receptor, VEGFR2, activates a number of signaling pathways including ERK1/2. Activation of ERK1/2 is experimentally shown to involve sphingosine kinase 1 (SphK1) activation and its calcium-dependent translocation downstream of ERK1/2. Here we construct a rule-based computational model of signaling downstream of VEGFR2, by including SphK1 and calcium positive feedback mechanisms, and investigate their consequences on ERK1/2 activation. The model predicts the existence of VEGF threshold in ERK1/2 activation that can be continuously tuned by cellular concentrations of SphK1 and sphingosine 1 phosphate (S1P). The computer model also predicts powerful effects of perturbations in plasma and ER calcium pump rates and the current through the CRAC channels on ERK1/2 activation dynamics, highlighting the critical role of intracellular calcium in shaping the pERK1/2 signal. The model is then utilized to simulate anti-angiogenic therapeutic interventions targeting VEGFR2-ERK1/2 axis. Simulations indicate that monotherapies that exclusively target VEGFR2 phosphorylation, VEGF, or VEGFR2 are ineffective in shutting down signaling to ERK1/2. By simulating therapeutic strategies that target multiple nodes of the pathway such as Raf and SphK1, we conclude that combination therapy should be much more effective in blocking VEGF signaling to EKR1/2. The model has important implications for interventions that target signaling pathways in angiogenesis relevant to cancer, vascular diseases, and wound healing.'),
(88279, 2017, 'plos', 'Accuracy Maximization Analysis for Sensory-Perceptual Tasks: Computational Improvements, Filter Robustness, and Coding Advantages for Scaled Additive Noise', 'Burge, Johannes|Jaini, Priyank', 'Department of Psychology, University of Pennsylvania, Philadelphia, PA, United States of America.|Department of Psychology, University of Pennsylvania, Philadelphia, PA, United States of America.', 'United States|United States', 15, 'Computer Simulation|Data Interpretation, Statistical|Humans|Models, Neurological|Models, Statistical|Psychometrics|Reproducibility of Results|Sensitivity and Specificity|Signal-To-Noise Ratio|Task Performance and Analysis|Visual Cortex|Visual Perception', 'Journal Article', '10.1371/journal.pcbi.1005281', '28178266', 'Accuracy Maximization Analysis (AMA) is a recently developed Bayesian ideal observer method for task-specific dimensionality reduction. Given a training set of proximal stimuli (e.g. retinal images), a response noise model, and a cost function, AMA returns the filters (i.e. receptive fields) that extract the most useful stimulus features for estimating a user-specified latent variable from those stimuli. Here, we first contribute two technical advances that significantly reduce AMAs compute time: we derive gradients of cost functions for which two popular estimators are appropriate, and we implement a stochastic gradient descent (AMA-SGD) routine for filter learning. Next, we show how the method can be used to simultaneously probe the impact on neural encoding of natural stimulus variability, the prior over the latent variable, noise power, and the choice of cost function. Then, we examine the geometry of AMAs unique combination of properties that distinguish it from better-known statistical methods. Using binocular disparity estimation as a concrete test case, we develop insights that have general implications for understanding neural encoding and decoding in a broad class of fundamental sensory-perceptual tasks connected to the energy model. Specifically, we find that non-orthogonal (partially redundant) filters with scaled additive noise tend to outperform orthogonal filters with constant additive noise, non-orthogonal filters and scaled additive noise can interact to sculpt noise-induced stimulus encoding uncertainty to match task-irrelevant stimulus variability. Thus, we show that some properties of neural response thought to be biophysical nuisances can confer coding advantages to neural systems. Finally, we speculate that, if repurposed for the problem of neural systems identification, AMA may be able to overcome a fundamental limitation of standard subunit model estimation. As natural stimuli become more widely used in the study of psychophysical and neurophysiological performance, we expect that task-specific methods for feature learning like AMA will become increasingly important.'),
(88280, 2017, 'plos', 'A quantitative model for the rate-limiting process of UGA alternative assignments to stop and selenocysteine codons', 'Chen, Yen-Fu|Lin, Hsiu-Chuan|Chuang, Kai-Neng|Lin, Chih-Hsu|Yen, Hsueh-Chi S|Yeang, Chen-Hsiang', 'Institute of Molecular Biology, Academia Sinica, Taipei, Taiwan.|Institute of Molecular Biology, Academia Sinica, Taipei, Taiwan.|Institute of Molecular Biology, Academia Sinica, Taipei, Taiwan.|Institute of Statistical Science, Academia Sinica, Taipei, Taiwan.|Institute of Molecular Biology, Academia Sinica, Taipei, Taiwan.|Genome and Systems Biology Degree Program, National Taiwan University and Academia Sinica, Taipei, Taiwan.', '-|-|-|-|-|-', 0, 'Codon, Initiator|Codon, Terminator|Computer Simulation|Models, Genetic|Protein Biosynthesis|Proteins|Selenocysteine|Selenoproteins|Sequence Analysis, RNA', 'Journal Article', '10.1371/journal.pcbi.1005367', '28178267', 'Ambiguity in genetic codes exists in cases where certain stop codons are alternatively used to encode non-canonical amino acids. In selenoprotein transcripts, the UGA codon may either represent a translation termination signal or a selenocysteine (Sec) codon. Translating UGA to Sec requires selenium and specialized Sec incorporation machinery such as the interaction between the SECIS element and SBP2 protein, but how these factors quantitatively affect alternative assignments of UGA has not been fully investigated. We developed a model simulating the UGA decoding process. Our model is based on the following assumptions: (1) charged Sec-specific tRNAs (Sec-tRNASec) and release factors compete for a UGA site, (2) Sec-tRNASec abundance is limited by the concentrations of selenium and Sec-specific tRNA (tRNASec) precursors, and (3) all synthesis reactions follow first-order kinetics. We demonstrated that this model captured two prominent characteristics observed from experimental data. First, UGA to Sec decoding increases with elevated selenium availability, but saturates under high selenium supply. Second, the efficiency of Sec incorporation is reduced with increasing selenoprotein synthesis. We measured the expressions of four selenoprotein constructs and estimated their model parameters. Their inferred Sec incorporation efficiencies did not correlate well with their SECIS-SBP2 binding affinities, suggesting the existence of additional factors determining the hierarchy of selenoprotein synthesis under selenium deficiency. This model provides a framework to systematically study the interplay of factors affecting the dual definitions of a genetic codon.'),
(88281, 2017, 'plos', 'Estimating the Respective Contributions of Human and Viral Genetic Variation to HIV Control', 'Bartha, István|McLaren, Paul J|Brumme, Chanson|Harrigan, Richard|Telenti, Amalio|Fellay, Jacques', 'School of Life Sciences, École Polytechnique Fédérale de Lausanne, Lausanne, Switzerland.|National HIV and Retrovirology Laboratory, Public Health Agency of Canada, Winnipeg, Manitoba, Canada.|BC Centre for Excellence in HIV/AIDS, University of British Columbia, Vancouver, British Columbia, Canada.|BC Centre for Excellence in HIV/AIDS, University of British Columbia, Vancouver, British Columbia, Canada.|Genomic Medicine Group, J. Craig Venter Institute, La Jolla, California, United States of America.|School of Life Sciences, École Polytechnique Fédérale de Lausanne, Lausanne, Switzerland.', 'Switzerland|Canada|Canada|Canada|United States|Switzerland', 11, 'AIDS Vaccines|Genetic Association Studies|Genetic Predisposition to Disease|Genetic Variation|Genome, Human|Genome, Viral|HIV|HIV Infections|Host-Pathogen Interactions|Humans|Models, Genetic|Viral Load', 'Journal Article', '10.1371/journal.pcbi.1005339', '28182649', 'We evaluated the fraction of variation in HIV-1 set point viral load attributable to viral or human genetic factors by using joint host/pathogen genetic data from 541 HIV infected individuals. We show that viral genetic diversity explains 29% of the variation in viral load while host factors explain 8.4%. Using a joint model including both host and viral effects, we estimate a total of 30% heritability, indicating that most of the host effects are reflected in viral sequence variation.'),
(88282, 2017, 'plos', 'Representing high throughput expression profiles via perturbation barcodes reveals compound targets', 'Filzen, Tracey M|Kutchukian, Peter S|Hermes, Jeffrey D|Li, Jing|Tudor, Matthew', 'Medical Writing, Merck Research Laboratories, Upper Gwynedd, Pennsylvania, United States of America.|Informatics, Merck Research Laboratories, Boston, Massachusetts, United States of America.|Screening & Protein Sciences, Merck Research Laboratories, North Wales, Pennsylvania, United States of America.|Screening and Compound Profiling, Merck Research Laboratories, Kenilworth, New Jersey, United States of America.|Informatics, Merck Research Laboratories, West Point, Pennsylvania, United States of America.', 'United States|United States|United States|Jersey|United States', 0, 'Animals|Cell Physiological Phenomena|Drug Evaluation, Preclinical|Gene Expression|Gene Expression Profiling|High-Throughput Nucleotide Sequencing|Humans|Molecular Targeted Therapy|Pharmaceutical Preparations', 'Journal Article', '10.1371/journal.pcbi.1005335', '28182661', 'High throughput mRNA expression profiling can be used to characterize the response of cell culture models to perturbations such as pharmacologic modulators and genetic perturbations. As profiling campaigns expand in scope, it is important to homogenize, summarize, and analyze the resulting data in a manner that captures significant biological signals in spite of various noise sources such as batch effects and stochastic variation. We used the L1000 platform for large-scale profiling of 978 representative genes across thousands of compound treatments. Here, a method is described that uses deep learning techniques to convert the expression changes of the landmark genes into a perturbation barcode that reveals important features of the underlying data, performing better than the raw data in revealing important biological insights. The barcode captures compound structure and target information, and predicts a compounds high throughput screening promiscuity, to a higher degree than the original data measurements, indicating that the approach uncovers underlying factors of the expression data that are otherwise entangled or masked by noise. Furthermore, we demonstrate that visualizations derived from the perturbation barcode can be used to more sensitively assign functions to unknown compounds through a guilt-by-association approach, which we use to predict and experimentally validate the activity of compounds on the MAPK pathway. The demonstrated application of deep metric learning to large-scale chemical genetics projects highlights the utility of this and related approaches to the extraction of insights and testable hypotheses from big, sometimes noisy data.'),
(88283, 2017, 'plos', 'Predicting Structure-Function Relations and Survival following Surgical and Bronchoscopic Lung Volume Reduction Treatment of Emphysema', 'Mondoñedo, Jarred R|Suki, Béla', 'Department of Biomedical Engineering, Boston University, Boston, MA, United States of America.|Department of Biomedical Engineering, Boston University, Boston, MA, United States of America.', 'United States|United States', 4, 'Bronchoscopy|Combined Modality Therapy|Computer Simulation|Emphysema|Female|Humans|Lung|Male|Models, Biological|Outcome Assessment (Health Care)|Pneumonectomy|Prevalence|Prognosis|Quality of Life|Reproducibility of Results|Risk Factors|Sensitivity and Specificity|Survival Analysis|Treatment Outcome', 'Journal Article', '10.1371/journal.pcbi.1005282', '28182686', 'Lung volume reduction surgery (LVRS) and bronchoscopic lung volume reduction (bLVR) are palliative treatments aimed at reducing hyperinflation in advanced emphysema. Previous work has evaluated functional improvements and survival advantage for these techniques, although their effects on the micromechanical environment in the lung have yet to be determined. Here, we introduce a computational model to simulate a force-based destruction of elastic networks representing emphysema progression, which we use to track the response to lung volume reduction via LVRS and bLVR. We find that (1) LVRS efficacy can be predicted based on pre-surgical network structure, (2) macroscopic functional improvements following bLVR are related to microscopic changes in mechanical force heterogeneity, and (3) both techniques improve aspects of survival and quality of life influenced by lung compliance, albeit while accelerating disease progression. Our model predictions yield unique insights into the microscopic origins underlying emphysema progression before and after lung volume reduction.'),
(88284, 2017, 'plos', 'Human mobility and the spatial transmission of influenza in the United States', 'Charu, Vivek|Zeger, Scott|Gog, Julia|Bjørnstad, Ottar N|Kissler, Stephen|Simonsen, Lone|Grenfell, Bryan T|Viboud, Cécile', 'Fogarty International Center, National Institutes of Health, Bethesda, MD, United States of America.|Department of Biostatistics, Johns Hopkins Bloomberg School of Public Health, Baltimore, MD, United States of America.|Fogarty International Center, National Institutes of Health, Bethesda, MD, United States of America.|Fogarty International Center, National Institutes of Health, Bethesda, MD, United States of America.|Department of Applied Mathematics and Theoretical Physics, University of Cambridge, Cambridge, United Kingdom.|Fogarty International Center, National Institutes of Health, Bethesda, MD, United States of America.|Fogarty International Center, National Institutes of Health, Bethesda, MD, United States of America.|Fogarty International Center, National Institutes of Health, Bethesda, MD, United States of America.', 'United States|United States|United States|United States|United Kingdom|United States|United States|U', 45, 'Computer Simulation|Disease Outbreaks|Human Migration|Humans|Incidence|Influenza, Human|Models, Statistical|Proportional Hazards Models|Risk Assessment|Risk Factors|Spatio-Temporal Analysis|Transportation|Travel|United States|Urban Population', 'Journal Article', '10.1371/journal.pcbi.1005382', '28187123', 'Seasonal influenza epidemics offer unique opportunities to study the invasion and re-invasion waves of a pathogen in a partially immune population. Detailed patterns of spread remain elusive, however, due to lack of granular disease data. Here we model high-volume city-level medical claims data and human mobility proxies to explore the drivers of influenza spread in the US during 2002-2010. Although the speed and pathways of spread varied across seasons, seven of eight epidemics likely originated in the Southern US. Each epidemic was associated with 1-5 early long-range transmission events, half of which sparked onward transmission. Gravity model estimates indicate a sharp decay in influenza transmission with the distance between infectious and susceptible cities, consistent with spread dominated by work commutes rather than air traffic. Two early-onset seasons associated with antigenic novelty had particularly localized modes of spread, suggesting that novel strains may spread in a more localized fashion than previously anticipated.'),
(88285, 2017, 'plos', 'Correction: Transcriptional Dynamics Reveal Critical Roles for Non-coding RNAs in the Immediate-Early Response', 'PLOS Computational Biology Staff', 'Fogarty International Center, National Institutes of Health, Bethesda, MD, United States of America.', 'United States', 0, '-', 'Published Erratum', '10.1371/journal.pcbi.1005279', '28187127', '[This corrects the article DOI: 10.1371/journal.pcbi.1004217.].'),
(88286, 2017, 'plos', 'An Atlas of Peroxiredoxins Created Using an Active Site Profile-Based Approach to Functionally Relevant Clustering of Proteins', 'Harper, Angela F|Leuthaeuser, Janelle B|Babbitt, Patricia C|Morris, John H|Ferrin, Thomas E|Poole, Leslie B|Fetrow, Jacquelyn S', 'Department of Physics, Wake Forest University, Winston-Salem, North Carolina, United States of America.|Department of Molecular Genetics and Genomics, Wake Forest School of Medicine, Winston-Salem, North Carolina, United States of America.|Department of Bioengineering and Therapeutic Sciences, University of California San Francisco School of Pharmacy, San Francisco, California, United States of America.|Department of Pharmaceutical Chemistry, University of California San Francisco School of Pharmacy, San Francisco, California, United States of America.|Department of Pharmaceutical Chemistry, University of California San Francisco School of Pharmacy, San Francisco, California, United States of America.|Department of Biochemistry, Wake Forest School of Medicine, Winston-Salem, North Carolina, United States of America.|Department of Chemistry, University of Richmond, Richmond, Virginia, United States of America.', 'United States|United States|United States|United States|United States|United States|United States', 7, 'Amino Acid Sequence|Binding Sites|Database Management Systems|Databases, Protein|Enzyme Activation|High-Throughput Screening Assays|Molecular Sequence Data|Multigene Family|Peroxiredoxins|Protein Binding|Protein Interaction Mapping|Sequence Analysis, Protein|Sequence Homology, Amino Acid', 'Journal Article', '10.1371/journal.pcbi.1005284', '28187133', 'Peroxiredoxins (Prxs or Prdxs) are a large protein superfamily of antioxidant enzymes that rapidly detoxify damaging peroxides and/or affect signal transduction and, thus, have roles in proliferation, differentiation, and apoptosis. Prx superfamily members are widespread across phylogeny and multiple methods have been developed to classify them. Here we present an updated atlas of the Prx superfamily identified using a novel method called MISST (Multi-level Iterative Sequence Searching Technique). MISST is an iterative search process developed to be both agglomerative, to add sequences containing similar functional site features, and divisive, to split groups when functional site features suggest distinct functionally-relevant clusters. Superfamily members need not be identified initially-MISST begins with a minimal representative set of known structures and searches GenBank iteratively. Further, the methods novelty lies in the manner in which isofunctional groups are selected, rather than use a single or shifting threshold to identify clusters, the groups are deemed isofunctional when they pass a self-identification criterion, such that the group identifies itself and nothing else in a search of GenBank. The method was preliminarily validated on the Prxs, as the Prxs presented challenges of both agglomeration and division. For example, previous sequence analysis clustered the Prx functional families Prx1 and Prx6 into one group. Subsequent expert analysis clearly identified Prx6 as a distinct functionally relevant group. The MISST process distinguishes these two closely related, though functionally distinct, families. Through MISST search iterations, over 38,000 Prx sequences were identified, which the method divided into six isofunctional clusters, consistent with previous expert analysis. The results represent the most complete computational functional analysis of proteins comprising the Prx superfamily. The feasibility of this novel method is demonstrated by the Prx superfamily results, laying the foundation for potential functionally relevant clustering of the universe of protein sequences.');
INSERT INTO `papers` (`id`, `ano`, `journal`, `titulo`, `autores`, `afiliacao`, `pais`, `citacoes`, `palavra_chave`, `categorias`, `doi`, `pubmed`, `abstract`) VALUES
(88287, 2017, 'plos', 'Metabolic regulation is sufficient for global and robust coordination of glucose uptake, catabolism, energy production and growth in Escherichia coli', 'Millard, Pierre|Smallbone, Kieran|Mendes, Pedro', 'MCISB, Manchester Institute of Biotechnology, University of Manchester, Manchester, United Kingdom.|MCISB, Manchester Institute of Biotechnology, University of Manchester, Manchester, United Kingdom.|MCISB, Manchester Institute of Biotechnology, University of Manchester, Manchester, United Kingdom.', 'United Kingdom|United Kingdom|United Kingdom', 29, 'Cell Proliferation|Computer Simulation|Energy Metabolism|Escherichia coli|Gene Expression Regulation, Bacterial|Gene Expression Regulation, Enzymologic|Glucose|Metabolic Flux Analysis|Metabolic Networks and Pathways|Metabolism|Models, Biological|Signal Transduction', 'Journal Article', '10.1371/journal.pcbi.1005396', '28187134', 'The metabolism of microorganisms is regulated through two main mechanisms: changes of enzyme capacities as a consequence of gene expression modulation (hierarchical control) and changes of enzyme activities through metabolite-enzyme interactions. An increasing body of evidence indicates that hierarchical control is insufficient to explain metabolic behaviors, but the system-wide impact of metabolic regulation remains largely uncharacterized. To clarify its role, we developed and validated a detailed kinetic model of Escherichia coli central metabolism that links growth to environment. Metabolic control analyses confirm that the control is widely distributed across the network and highlight strong interconnections between all the pathways. Exploration of the model solution space reveals that several robust properties emerge from metabolic regulation, from the molecular level (e.g. homeostasis of total metabolite pool) to the overall cellular physiology (e.g. coordination of carbon uptake, catabolism, energy and redox production, and growth), while allowing a large degree of flexibility at most individual metabolic steps. These properties have important physiological implications for E. coli and significantly expand the self-regulating capacities of its metabolism.'),
(88288, 2017, 'plos', 'Correction: Emergence of Slow-Switching Assemblies in Structured Neuronal Networks', 'PLOS Computational Biology Staff', 'MCISB, Manchester Institute of Biotechnology, University of Manchester, Manchester, United Kingdom.', 'United Kingdom', 0, '-', 'Published Erratum', '10.1371/journal.pcbi.1005288', '28187146', '[This corrects the article DOI: 10.1371/journal.pcbi.1004196.].'),
(88289, 2017, 'plos', 'Elucidation of molecular kinetic schemes from macroscopic traces using system identification', 'Fribourg, Miguel|Logothetis, Diomedes E|González-Maeso, Javier|Sealfon, Stuart C|Galocha-Iragüen, Belén|Las-Heras Andrés, Fernando|Brezina, Vladimir', 'Department of Neurology and Center for Translational Systems Biology, Icahn School Of Medicine at Mount Sinai, New York, New York, United States of America.|Department of Pharmaceutical Sciences, Northeastern University, Boston, Massachusetts, United States of America.|Department of Physiology and Biophysics, Virginia Commonwealth University School of Medicine, Richmond, Virginia, United States of America.|Department of Neurology and Center for Translational Systems Biology, Icahn School Of Medicine at Mount Sinai, New York, New York, United States of America.|Department of Signals Systems and Radiocommunications, Universidad Politécnica de Madrid, Madrid, Spain.|Department of Electrical Engineering, Universidad de Oviedo, Gijón, Spain.|Department of Neuroscience, Icahn School of Medicine, New York, New York, United States of America.', 'United States|United States|United States|United States|Spain|Spain|United States', 0, 'Algorithms|Biopolymers|Cell Physiological Phenomena|Computer Simulation|Kinetics|Metabolic Clearance Rate|Models, Biological|Models, Chemical|Signal Transduction', 'Journal Article', '10.1371/journal.pcbi.1005376', '28192423', 'Overall cellular responses to biologically-relevant stimuli are mediated by networks of simpler lower-level processes. Although information about some of these processes can now be obtained by visualizing and recording events at the molecular level, this is still possible only in especially favorable cases. Therefore the development of methods to extract the dynamics and relationships between the different lower-level (microscopic) processes from the overall (macroscopic) response remains a crucial challenge in the understanding of many aspects of physiology. Here we have devised a hybrid computational-analytical method to accomplish this task, the SYStems-based MOLecular kinetic scheme Extractor (SYSMOLE). SYSMOLE utilizes system-identification input-output analysis to obtain a transfer function between the stimulus and the overall cellular response in the Laplace-transformed domain. It then derives a Markov-chain state molecular kinetic scheme uniquely associated with the transfer function by means of a classification procedure and an analytical step that imposes general biological constraints. We first tested SYSMOLE with synthetic data and evaluated its performance in terms of its rate of convergence to the correct molecular kinetic scheme and its robustness to noise. We then examined its performance on real experimental traces by analyzing macroscopic calcium-current traces elicited by membrane depolarization. SYSMOLE derived the correct, previously known molecular kinetic scheme describing the activation and inactivation of the underlying calcium channels and correctly identified the accepted mechanism of action of nifedipine, a calcium-channel blocker clinically used in patients with cardiovascular disease. Finally, we applied SYSMOLE to study the pharmacology of a new class of glutamate antipsychotic drugs and their crosstalk mechanism through a heteromeric complex of G protein-coupled receptors. Our results indicate that our methodology can be successfully applied to accurately derive molecular kinetic schemes from experimental macroscopic traces, and we anticipate that it may be useful in the study of a wide variety of biological systems.'),
(88290, 2017, 'plos', 'Spatial separation of two different pathways accounting for the generation of calcium signals in astrocytes', 'Oschmann, Franziska|Mergenthaler, Konstantin|Jungnickel, Evelyn|Obermayer, Klaus', 'Technische Universität Berlin, Neural Information Processing Group, Berlin, Germany.|Technische Universität Berlin, Neural Information Processing Group, Berlin, Germany.|Technische Universität Berlin, Neural Information Processing Group, Berlin, Germany.|Technische Universität Berlin, Neural Information Processing Group, Berlin, Germany.', 'Germany|Germany|Germany|Germany', 0, 'Animals|Astrocytes|Calcium|Calcium Signaling|Cells, Cultured|Computer Simulation|Glucose Transport Proteins, Facilitative|Humans|Metabolic Flux Analysis|Models, Biological|Receptors, Metabotropic Glutamate|Signal Transduction|Spatio-Temporal Analysis', 'Journal Article', '10.1371/journal.pcbi.1005377', '28192424', 'Astrocytes integrate and process synaptic information and exhibit calcium (Ca2+) signals in response to incoming information from neighboring synapses. The generation of Ca2+ signals is mostly attributed to Ca2+ release from internal Ca2+ stores evoked by an elevated metabotropic glutamate receptor (mGluR) activity. Different experimental results associated the generation of Ca2+ signals to the activity of the glutamate transporter (GluT). The GluT itself does not influence the intracellular Ca2+ concentration, but it indirectly activates Ca2+ entry over the membrane. A closer look into Ca2+ signaling in different astrocytic compartments revealed a spatial separation of those two pathways. Ca2+ signals in the soma are mainly generated by Ca2+ release from internal Ca2+ stores (mGluR-dependent pathway). In astrocytic compartments close to the synapse most Ca2+ signals are evoked by Ca2+ entry over the plasma membrane (GluT-dependent pathway). This assumption is supported by the finding, that the volume ratio between the internal Ca2+ store and the intracellular space decreases from the soma towards the synapse. We extended a model for mGluR-dependent Ca2+ signals in astrocytes with the GluT-dependent pathway. Additionally, we included the volume ratio between the internal Ca2+ store and the intracellular compartment into the model in order to analyze Ca2+ signals either in the soma or close to the synapse. Our model results confirm the spatial separation of the mGluR- and GluT-dependent pathways along the astrocytic process. The model allows to study the binary Ca2+ response during a block of either of both pathways. Moreover, the model contributes to a better understanding of the impact of channel densities on the interaction of both pathways and on the Ca2+ signal.'),
(88291, 2017, 'plos', 'Comparing individual-based approaches to modelling the self-organization of multicellular tissues', 'Osborne, James M|Fletcher, Alexander G|Pitt-Francis, Joe M|Maini, Philip K|Gavaghan, David J', 'School of Mathematics and Statistics, University of Melbourne, Parkville, Victoria, Australia.|School of Mathematics and Statistics, University of Sheffield, Sheffield, United Kingdom.|Department of Computer Science, University of Oxford, Oxford, United Kingdom.|Wolfson Centre for Mathematical Biology, Mathematical Institute, University of Oxford, Oxford, United Kingdom.|Department of Computer Science, University of Oxford, Oxford, United Kingdom.', 'Australia|United Kingdom|United Kingdom|United Kingdom|United Kingdom', 45, 'Algorithms|Animals|Cell Adhesion|Cell Communication|Cell Movement|Cell Proliferation|Computer Simulation|Humans|Models, Biological|Spheroids, Cellular', 'Comparative Study', '10.1371/journal.pcbi.1005387', '28192427', 'The coordinated behaviour of populations of cells plays a central role in tissue growth and renewal. Cells react to their microenvironment by modulating processes such as movement, growth and proliferation, and signalling. Alongside experimental studies, computational models offer a useful means by which to investigate these processes. To this end a variety of cell-based modelling approaches have been developed, ranging from lattice-based cellular automata to lattice-free models that treat cells as point-like particles or extended shapes. However, it remains unclear how these approaches compare when applied to the same biological problem, and what differences in behaviour are due to different model assumptions and abstractions. Here, we exploit the availability of an implementation of five popular cell-based modelling approaches within a consistent computational framework, Chaste (http://www.cs.ox.ac.uk/chaste). This framework allows one to easily change constitutive assumptions within these models. In each case we provide full details of all technical aspects of our model implementations. We compare model implementations using four case studies, chosen to reflect the key cellular processes of proliferation, adhesion, and short- and long-range signalling. These case studies demonstrate the applicability of each model and provide a guide for model usage.'),
(88292, 2017, 'plos', 'Co-emergence of multi-scale cortical activities of irregular firing, oscillations and avalanches achieves cost-efficient information capacity', 'Yang, Dong-Ping|Zhou, Hai-Jun|Zhou, Changsong', 'Department of Physics, Hong Kong Baptist University, Kowloon Tong, Hong Kong.|Institute of Theoretical Physics, Chinese Academy of Sciences, Beijing, China.|Department of Physics, Hong Kong Baptist University, Kowloon Tong, Hong Kong.', 'Hong Kong|China|Hong Kong', 2, 'Action Potentials|Animals|Biological Clocks|Brain|Cognition|Computer Simulation|Energy Metabolism|Humans|Information Storage and Retrieval|Models, Neurological|Models, Statistical|Nerve Net', 'Journal Article', '10.1371/journal.pcbi.1005384', '28192429', 'The brain is highly energy consuming, therefore is under strong selective pressure to achieve cost-efficiency in both cortical connectivities and activities. However, cost-efficiency as a design principle for cortical activities has been rarely studied. Especially it is not clear how cost-efficiency is related to ubiquitously observed multi-scale properties: irregular firing, oscillations and neuronal avalanches. Here we demonstrate that these prominent properties can be simultaneously observed in a generic, biologically plausible neural circuit model that captures excitation-inhibition balance and realistic dynamics of synaptic conductance. Their co-emergence achieves minimal energy cost as well as maximal energy efficiency on information capacity, when neuronal firing are coordinated and shaped by moderate synchrony to reduce otherwise redundant spikes, and the dynamical clusterings are maintained in the form of neuronal avalanches. Such cost-efficient neural dynamics can be employed as a foundation for further efficient information processing under energy constraint.'),
(88293, 2017, 'plos', 'Computational identification of the selenocysteine tRNA (tRNASec) in genomes', 'Santesmasses, Didac|Mariotti, Marco|Guigó, Roderic', 'Centre for Genomic Regulation (CRG), The Barcelona Institute for Science and Technology, Barcelona, Spain.|Centre for Genomic Regulation (CRG), The Barcelona Institute for Science and Technology, Barcelona, Spain.|Centre for Genomic Regulation (CRG), The Barcelona Institute for Science and Technology, Barcelona, Spain.', 'Spain|Spain|Spain', 9, 'Algorithms|Chromosome Mapping|Genetic Markers|Genome|Genome Components|High-Throughput Screening Assays|RNA, Transfer, Amino Acid-Specific|RNA, Transfer, Amino Acyl|Selenocysteine', 'Journal Article', '10.1371/journal.pcbi.1005383', '28192430', 'Selenocysteine (Sec) is known as the 21st amino acid, a cysteine analogue with selenium replacing sulphur. Sec is inserted co-translationally in a small fraction of proteins called selenoproteins. In selenoprotein genes, the Sec specific tRNA (tRNASec) drives the recoding of highly specific UGA codons from stop signals to Sec. Although found in organisms from the three domains of life, Sec is not universal. Many species are completely devoid of selenoprotein genes and lack the ability to synthesize Sec. Since tRNASec is a key component in selenoprotein biosynthesis, its efficient identification in genomes is instrumental to characterize the utilization of Sec across lineages. Available tRNA prediction methods fail to accurately predict tRNASec, due to its unusual structural fold. Here, we present Secmarker, a method based on manually curated covariance models capturing the specific tRNASec structure in archaea, bacteria and eukaryotes. We exploited the non-universality of Sec to build a proper benchmark set for tRNASec predictions, which is not possible for the predictions of other tRNAs. We show that Secmarker greatly improves the accuracy of previously existing methods constituting a valuable tool to identify tRNASec genes, and to efficiently determine whether a genome contains selenoproteins. We used Secmarker to analyze a large set of fully sequenced genomes, and the results revealed new insights in the biology of tRNASec, led to the discovery of a novel bacterial selenoprotein family, and shed additional light on the phylogenetic distribution of selenoprotein containing genomes. Secmarker is freely accessible for download, or online analysis through a web server at http://secmarker.crg.cat.'),
(88294, 2017, 'plos', 'Conformational diversity analysis reveals three functional mechanisms in proteins', 'Monzon, Alexander Miguel|Zea, Diego Javier|Fornasari, María Silvina|Saldaño, Tadeo E|Fernandez-Alberti, Sebastian|Tosatto, Silvio C E|Parisi, Gustavo', 'Departamento de Ciencia y Tecnología, Universidad Nacional de Quilmes (CONICET), Bernal, Buenos Aires, Argentina.|Bioinformatics Unit, Fundación Instituto Leloir (CONICET), Buenos Aires, Argentina.|Departamento de Ciencia y Tecnología, Universidad Nacional de Quilmes (CONICET), Bernal, Buenos Aires, Argentina.|Departamento de Ciencia y Tecnología, Universidad Nacional de Quilmes (CONICET), Bernal, Buenos Aires, Argentina.|Departamento de Ciencia y Tecnología, Universidad Nacional de Quilmes (CONICET), Bernal, Buenos Aires, Argentina.|Department of Biomedical Sciences, University of Padua, Padua, Italy.|Departamento de Ciencia y Tecnología, Universidad Nacional de Quilmes (CONICET), Bernal, Buenos Aires, Argentina.', 'Argentina|Argentina|Argentina|Argentina|Argentina|Italy|Argentina', 8, 'Models, Chemical|Models, Statistical|Molecular Dynamics Simulation|Protein Conformation|Proteins|Structure-Activity Relationship', 'Journal Article', '10.1371/journal.pcbi.1005398', '28192432', 'Protein motions are a key feature to understand biological function. Recently, a large-scale analysis of protein conformational diversity showed a positively skewed distribution with a peak at 0.5 Å C-alpha root-mean-square-deviation (RMSD). To understand this distribution in terms of structure-function relationships, we studied a well curated and large dataset of ~5,000 proteins with experimentally determined conformational diversity. We searched for global behaviour patterns studying how structure-based features change among the available conformer population for each protein. This procedure allowed us to describe the RMSD distribution in terms of three main protein classes sharing given properties. The largest of these protein subsets (~60%), which we call rigid (average RMSD = 0.83 Å), has no disordered regions, shows low conformational diversity, the largest tunnels and smaller and buried cavities. The two additional subsets contain disordered regions, but with differential sequence composition and behaviour. Partially disordered proteins have on average 67% of their conformers with disordered regions, average RMSD = 1.1 Å, the highest number of hinges and the longest disordered regions. In contrast, malleable proteins have on average only 25% of disordered conformers and average RMSD = 1.3 Å, flexible cavities affected in size by the presence of disordered regions and show the highest diversity of cognate ligands. Proteins in each set are mostly non-homologous to each other, share no given fold class, nor functional similarity but do share features derived from their conformer population. These shared features could represent conformational mechanisms related with biological functions.'),
(88295, 2017, 'plos', 'Mathematical models of tissue stem and transit target cell divisions and the risk of radiation- or smoking-associated cancer', 'Little, Mark P|Hendry, Jolyon H', 'Radiation Epidemiology Branch, Division of Cancer Epidemiology and Genetics, National Cancer Institute, NIH, DHHS, Rockville, MD, United States of America.|Christie Medical Physics and Engineering, Christie Hospital and University of Manchester, Wilmslow Road, Manchester M20 4BX, United Kingdom.', 'United States|United Kingdom', 1, 'Animals|Cell Division|Cell Transformation, Neoplastic|Computer Simulation|Epigenesis, Genetic|Humans|Models, Genetic|Mutation|Neoplasms, Radiation-Induced|Neoplastic Stem Cells|Smoke|Smoking|Tobacco', 'Journal Article', '10.1371/journal.pcbi.1005391', '28196079', 'There is compelling biological data to suggest that cancer arises from a series of mutations in single target cells, resulting in defects in cell renewal and differentiation processes which lead to malignancy. Because much mutagenic damage is expressed following cell division, more-rapidly renewing tissues could be at higher risk because of the larger number of cell replications. Cairns suggested that renewing tissues may reduce cancer risk by partitioning the dividing cell populations into lineages comprising infrequently-dividing long-lived stem cells and frequently-dividing short-lived daughter transit cells. We develop generalizations of three recent cancer-induction models that account for the joint maintenance and renewal of stem and transit cells, also competing processes of partially transformed cell proliferation and differentiation/apoptosis. We are particularly interested in using these models to separately assess the probabilities of mutation and development of cancer associated with spontaneous processes and with those linked to a specific environmental mutagen, specifically ionizing radiation or cigarette smoking. All three models demonstrate substantial variation in cancer risks, by at least 20 orders of magnitude, depending on the assumed number of critical mutations required for cancer, and the stem-cell and transition-cell mutation rates. However, in most cases the conditional probabilities of cancer being mutagen-induced range between 7-96%. The relative risks associated with mutagen exposure compared to background rates are also stable, ranging from 1.0-16.0. Very few cancers, generally <0.5%, arise from mutations occurring solely in stem cells rather than in a combination of stem and transit cells. However, for cancers with 2 or 3 critical mutations, a substantial proportion of cancers, in some cases 100%, have at least one mutation derived from a mutated stem cell. Little difference is made to relative risks if competing processes of proliferation and differentiation in the partially transformed stem and transit cell population are allowed for, nor is any difference made if one assumes that transit cells require an extra mutation to confer malignancy from the number required by stem cells. The probability of a cancer being mutagen-induced correlates across cancer sites with the estimated cumulative number of stem cell divisions in the associated tissue (p<0.05), although in some cases there is sensitivity of findings to removal of high-leverage outliers and in some cases only modest variation in probability, but these issues do not affect the validity of the findings. There are no significant correlations (p>0.3) between lifetime cancer-site specific radiation risk and the probability of that cancer being mutagen-induced. These results do not depend on the assumed critical number of mutations leading to cancer, or on the assumed mutagen-associated mutation rate, within the generally-accepted ranges tested. However, there are borderline significant negative correlations (p = 0.08) between the smoking-associated mortality rate difference (current vs former smokers) and the probability of cancer being mutagen-induced. This is only the case where values of the critical number of mutations leading to cancer, k, is 3 or 4 and not for smaller values (1 or 2), but does not strongly depend on the assumed mutagen-associated mutation rate.'),
(88296, 2017, 'plos', 'Depth-dependent flow and pressure characteristics in cortical microvascular networks', 'Schmid, Franca|Tsai, Philbert S|Kleinfeld, David|Jenny, Patrick|Weber, Bruno', 'Institute of Fluid Dynamics, ETH Zurich, Zurich, Switzerland.|Department of Physics, University of California at San Diego, La Jolla, California, United States of America.|Department of Physics, University of California at San Diego, La Jolla, California, United States of America.|Institute of Fluid Dynamics, ETH Zurich, Zurich, Switzerland.|Institute of Pharmacology and Toxicology, University of Zurich, Zurich, Switzerland.', 'Switzerland|United States|United States|Switzerland|Switzerland', 0, 'Animals|Blood Pressure|Cerebral Cortex|Cerebrovascular Circulation|Computer Simulation|Erythrocytes|Mice|Microvessels|Models, Cardiovascular|Vascular Resistance', 'Journal Article', '10.1371/journal.pcbi.1005392', '28196095', 'A better knowledge of the flow and pressure distribution in realistic microvascular networks is needed for improving our understanding of neurovascular coupling mechanisms and the related measurement techniques. Here, numerical simulations with discrete tracking of red blood cells (RBCs) are performed in three realistic microvascular networks from the mouse cerebral cortex. Our analysis is based on trajectories of individual RBCs and focuses on layer-specific flow phenomena until a cortical depth of 1 mm. The individual RBC trajectories reveal that in the capillary bed RBCs preferentially move in plane. Hence, the capillary flow field shows laminar patterns and a layer-specific analysis is valid. We demonstrate that for RBCs entering the capillary bed close to the cortical surface (< 400 xcexbcm) the largest pressure drop takes place in the capillaries (37%), while for deeper regions arterioles are responsible for 61% of the total pressure drop. Further flow characteristics, such as capillary transit time or RBC velocity, also vary significantly over cortical depth. Comparison of purely topological characteristics with flow-based ones shows that a combined interpretation of topology and flow is indispensable. Our results provide evidence that it is crucial to consider layer-specific differences for all investigations related to the flow and pressure distribution in the cortical vasculature. These findings support the hypothesis that for an efficient oxygen up-regulation at least two regulation mechanisms must be playing hand in hand, namely cerebral blood flow increase and microvascular flow homogenization. However, the contribution of both regulation mechanisms to oxygen up-regulation likely varies over depth.'),
(88297, 2017, 'plos', 'A mathematical model of calcium dynamics in HSY cells', 'Han, Jung Min|Tanimura, Akihiko|Kirk, Vivien|Sneyd, James', 'Department of Mathematics, The University of Auckland, Private Bag 92019, Auckland 1142, New Zealand.|Department of Pharmacology, School of Dentistry, Health Sciences University of Hokkaido, Ishikari-Tobetsu, Hokkaido 061-0293, Japan.|Department of Mathematics, The University of Auckland, Private Bag 92019, Auckland 1142, New Zealand.|Department of Mathematics, The University of Auckland, Private Bag 92019, Auckland 1142, New Zealand.', 'New Zealand|Japan|New Zealand|New Zealand', 0, 'Biological Clocks|Calcium|Calcium Signaling|Cell Line|Computer Simulation|Humans|Inositol Phosphates|Models, Biological|Salivary Ducts', 'Journal Article', '10.1371/journal.pcbi.1005275', '28199326', 'Saliva is an essential part of activities such as speaking, masticating and swallowing. Enzymes in salivary fluid protect teeth and gums from infectious diseases, and also initiate the digestion process. Intracellular calcium (Ca2+) plays a critical role in saliva secretion and regulation. Experimental measurements of Ca2+ and inositol trisphosphate (IP3) concentrations in HSY cells, a human salivary duct cell line, show that when the cells are stimulated with adenosine triphosphate (ATP) or carbachol (CCh), they exhibit coupled oscillations with Ca2+ spike peaks preceding IP3 spike peaks. Based on these data, we construct a mathematical model of coupled Ca2+ and IP3 oscillations in HSY cells and perform model simulations of three different experimental settings to forecast Ca2+ responses. The model predicts that when Ca2+ influx from the extracellular space is removed, oscillations gradually slow down until they stop. The model simulation of applying a pulse of IP3 predicts that photolysis of caged IP3 causes a transient increase in the frequency of the Ca2+ oscillations. Lastly, when Ca2+-dependent activation of PLC is inhibited, we see an increase in the oscillation frequency and a decrease in the amplitude. These model predictions are confirmed by experimental data. We conclude that, although concentrations of Ca2+ and IP3 oscillate, Ca2+ oscillations in HSY cells are the result of modulation of the IP3 receptor by intracellular Ca2+, and that the period is modulated by the accompanying IP3 oscillations.'),
(88298, 2017, 'plos', 'A Causal Inference Model Explains Perception of the McGurk Effect and Other Incongruent Audiovisual Speech', 'Magnotti, John F|Beauchamp, Michael S', 'Department of Neurosurgery and Core for Advanced MRI, Baylor College of Medicine, Houston, Texas, United States of America.|Department of Neurosurgery and Core for Advanced MRI, Baylor College of Medicine, Houston, Texas, United States of America.', 'United States|United States', 27, 'Adult|Auditory Perception|Cerebral Cortex|Computer Simulation|Cues|Female|Humans|Illusions|Male|Models, Neurological|Perceptual Masking|Semantics|Set (Psychology)|Speech Perception|Visual Perception', 'Journal Article', '10.1371/journal.pcbi.1005229', '28207734', 'Audiovisual speech integration combines information from auditory speech (talkers voice) and visual speech (talkers mouth movements) to improve perceptual accuracy. However, if the auditory and visual speech emanate from different talkers, integration decreases accuracy. Therefore, a key step in audiovisual speech perception is deciding whether auditory and visual speech have the same source, a process known as causal inference. A well-known illusion, the McGurk Effect, consists of incongruent audiovisual syllables, such as auditory ba + visual ga (AbaVga), that are integrated to produce a fused percept (da). This illusion raises two fundamental questions: first, given the incongruence between the auditory and visual syllables in the McGurk stimulus, why are they integrated, and second, why does the McGurk effect not occur for other, very similar syllables (e.g., AgaVba). We describe a simplified model of causal inference in multisensory speech perception (CIMS) that predicts the perception of arbitrary combinations of auditory and visual speech. We applied this model to behavioral data collected from 60 subjects perceiving both McGurk and non-McGurk incongruent speech stimuli. The CIMS model successfully predicted both the audiovisual integration observed for McGurk stimuli and the lack of integration observed for non-McGurk stimuli. An identical model without causal inference failed to accurately predict perception for either form of incongruent speech. The CIMS model uses causal inference to provide a computational framework for studying how the brain performs one of its most important tasks, integrating auditory and visual speech cues to allow us to communicate with others.'),
(88299, 2017, 'plos', 'Testing the limits of gradient sensing', 'Lakhani, Vinal|Elston, Timothy C', 'Curriculum in Bioinformatics and Computational Biology, University of North Carolina at Chapel Hill, Chapel Hill, North Carolina, United States of America.|Curriculum in Bioinformatics and Computational Biology, University of North Carolina at Chapel Hill, Chapel Hill, North Carolina, United States of America.', 'United States|United States', 2, 'Cell Membrane|Chemotaxis|Computer Simulation|Diffusion|Models, Biological|Models, Chemical|Models, Statistical|Pheromones|Receptors, Pheromone|Saccharomyces cerevisiae', 'Journal Article', '10.1371/journal.pcbi.1005386', '28207738', 'The ability to detect a chemical gradient is fundamental to many cellular processes. In multicellular organisms gradient sensing plays an important role in many physiological processes such as wound healing and development. Unicellular organisms use gradient sensing to move (chemotaxis) or grow (chemotropism) towards a favorable environment. Some cells are capable of detecting extremely shallow gradients, even in the presence of significant molecular-level noise. For example, yeast have been reported to detect pheromone gradients as shallow as 0.1 nM/xcexbcm. Noise reduction mechanisms, such as time-averaging and the internalization of pheromone molecules, have been proposed to explain how yeast cells filter fluctuations and detect shallow gradients. Here, we use a Particle-Based Reaction-Diffusion model of ligand-receptor dynamics to test the effectiveness of these mechanisms and to determine the limits of gradient sensing. In particular, we develop novel simulation methods for establishing chemical gradients that not only allow us to study gradient sensing under steady-state conditions, but also take into account transient effects as the gradient forms. Based on reported measurements of reaction rates, our results indicate neither time-averaging nor receptor endocytosis significantly improves the cells accuracy in detecting gradients over time scales associated with the initiation of polarized growth. Additionally, our results demonstrate the physical barrier of the cell membrane sharpens chemical gradients across the cell. While our studies are motivated by the mating response of yeast, we believe our results and simulation methods will find applications in many different contexts.'),
(88300, 2017, 'plos', 'Quantifying the Value of Perfect Information in Emergency Vaccination Campaigns', 'Bradbury, Naomi V|Probert, William J M|Shea, Katriona|Runge, Michael C|Fonnesbeck, Christopher J|Keeling, Matt J|Ferrari, Matthew J|Tildesley, Michael J', 'School of Veterinary Medicine and Science, University of Nottingham, Leicestershire, United Kingdom.|School of Veterinary Medicine and Science, University of Nottingham, Leicestershire, United Kingdom.|Center for Infectious Disease Dynamics, Department of Biology, Eberly College of Science, The Pennsylvania State University, University Park, Pennsylvania, United States of America.|US Geological Survey, Patuxent Wildlife Research Center, Laurel, Maryland, United States of America.|Department of Biostatistics, Vanderbilt University School of Medicine, Nashville, Tennessee, United States of America.|School of Life Sciences, University of Warwick, Coventry, United Kingdom.|Center for Infectious Disease Dynamics, Department of Biology, Eberly College of Science, The Pennsylvania State University, University Park, Pennsylvania, United States of America.|School of Veterinary Medicine and Science, University of Nottingham, Leicestershire, United Kingdom.', 'United Kingdom|United Kingdom|United States|United States|United States|United Kingdom|United States', 0, 'Animal Culling|Animals|Cost-Benefit Analysis|Emergency Medical Services|Foot-and-Mouth Disease|Health Care Costs|Immunization Programs|Mass Vaccination|Population Surveillance|Prevalence|Risk Assessment|United Kingdom|Viral Vaccines', 'Journal Article', '10.1371/journal.pcbi.1005318', '28207777', 'Foot-and-mouth disease outbreaks in non-endemic countries can lead to large economic costs and livestock losses but the use of vaccination has been contentious, partly due to uncertainty about emergency FMD vaccination. Value of information methods can be applied to disease outbreak problems such as FMD in order to investigate the performance improvement from resolving uncertainties. Here we calculate the expected value of resolving uncertainty about vaccine efficacy, time delay to immunity after vaccination and daily vaccination capacity for a hypothetical FMD outbreak in the UK. If it were possible to resolve all uncertainty prior to the introduction of control, we could expect savings of £55 million in outbreak cost, 221,900 livestock culled and 4.3 days of outbreak duration. All vaccination strategies were found to be preferable to a culling only strategy. However, the optimal vaccination radius was found to be highly dependent upon vaccination capacity for all management objectives. We calculate that by resolving the uncertainty surrounding vaccination capacity we would expect to return over 85% of the above savings, regardless of management objective. It may be possible to resolve uncertainty about daily vaccination capacity before an outbreak, and this would enable decision makers to select the optimal control action via careful contingency planning.'),
(88301, 2017, 'plos', 'Optimality principles reveal a complex interplay of intermediate toxicity and kinetic efficiency in the regulation of prokaryotic metabolism', 'Ewald, Jan|Bartl, Martin|Dandekar, Thomas|Kaleta, Christoph', 'Research Group Theoretical Systems Biology, Department of Bioinformatics, Friedrich-Schiller-Universität Jena, Jena, Germany.|Research Group Theoretical Systems Biology, Department of Bioinformatics, Friedrich-Schiller-Universität Jena, Jena, Germany.|Department of Bioinformatics, Biocenter, Julius-Maximilians-Universität Würzburg, Würzburg, Germany.|Research Group Medical Systems Biology, Christian-Albrechts-Universität zu Kiel, Kiel, Germany.', 'Germany|Germany|Germany|Germany', 6, 'Algorithms|Bacterial Toxins|Cell Proliferation|Cell Survival|Computer Simulation|Escherichia coli|Gene Expression Regulation, Bacterial|Kinetics|Lipopolysaccharides|Metabolic Clearance Rate|Metabolic Flux Analysis|Models, Biological|Signal Transduction', 'Journal Article', '10.1371/journal.pcbi.1005371', '28212377', 'A precise and rapid adjustment of fluxes through metabolic pathways is crucial for organisms to prevail in changing environmental conditions. Based on this reasoning, many guiding principles that govern the evolution of metabolic networks and their regulation have been uncovered. To this end, methods from dynamic optimization are ideally suited since they allow to uncover optimality principles behind the regulation of metabolic networks. We used dynamic optimization to investigate the influence of toxic intermediates in connection with the efficiency of enzymes on the regulation of a linear metabolic pathway. Our results predict that transcriptional regulation favors the control of highly efficient enzymes with less toxic upstream intermediates to reduce accumulation of toxic downstream intermediates. We show that the derived optimality principles hold by the analysis of the interplay between intermediate toxicity and pathway regulation in the metabolic pathways of over 5000 sequenced prokaryotes. Moreover, using the lipopolysaccharide biosynthesis in Escherichia coli as an example, we show how knowledge about the relation of regulation, kinetic efficiency and intermediate toxicity can be used to identify drug targets, which control endogenous toxic metabolites and prevent microbial growth. Beyond prokaryotes, we discuss the potential of our findings for the development of antifungal drugs.'),
(88302, 2017, 'plos', 'Correction: Psychotic Experiences and Overhasty Inferences Are Related to Maladaptive Learning', 'Stuke, Heiner|Stuke, Hannes|Weilnhammer, Veith Andreas|Schmack, Katharina', 'Research Group Medical Systems Biology, Christian-Albrechts-Universität zu Kiel, Kiel, Germany.|Research Group Medical Systems Biology, Christian-Albrechts-Universität zu Kiel, Kiel, Germany.|Research Group Medical Systems Biology, Christian-Albrechts-Universität zu Kiel, Kiel, Germany.|Research Group Medical Systems Biology, Christian-Albrechts-Universität zu Kiel, Kiel, Germany.', 'Germany|Germany|Germany|Germany', 0, '-', 'Published Erratum', '10.1371/journal.pcbi.1005393', '28212380', '[This corrects the article DOI: 10.1371/journal.pcbi.1005328.].'),
(88303, 2017, 'plos', 'graph-GPA: A graphical model for prioritizing GWAS results and investigating pleiotropic architecture', 'Chung, Dongjun|Kim, Hang J|Zhao, Hongyu', 'Department of Public Health Sciences, Medical University of South Carolina, Charleston, South Carolina, United States of America.|Department of Mathematical Sciences, University of Cincinnati, Cincinnati, Ohio, United States of America.|Department of Biostatistics, Yale School of Public Health, New Haven, Connecticut, United States of America.', 'United States|United States|United States', 6, 'Algorithms|Chromosome Mapping|Computer Graphics|Computer Simulation|Genetic Association Studies|Genetic Pleiotropy|Models, Genetic|Models, Statistical|Polymorphism, Single Nucleotide|Programming Languages|User-Computer Interface', 'Journal Article', '10.1371/journal.pcbi.1005388', '28212402', 'Genome-wide association studies (GWAS) have identified tens of thousands of genetic variants associated with hundreds of phenotypes and diseases, which have provided clinical and medical benefits to patients with novel biomarkers and therapeutic targets. However, identification of risk variants associated with complex diseases remains challenging as they are often affected by many genetic variants with small or moderate effects. There has been accumulating evidence suggesting that different complex traits share common risk basis, namely pleiotropy. Recently, several statistical methods have been developed to improve statistical power to identify risk variants for complex traits through a joint analysis of multiple GWAS datasets by leveraging pleiotropy. While these methods were shown to improve statistical power for association mapping compared to separate analyses, they are still limited in the number of phenotypes that can be integrated. In order to address this challenge, in this paper, we propose a novel statistical framework, graph-GPA, to integrate a large number of GWAS datasets for multiple phenotypes using a hidden Markov random field approach. Application of graph-GPA to a joint analysis of GWAS datasets for 12 phenotypes shows that graph-GPA improves statistical power to identify risk variants compared to statistical methods based on smaller number of GWAS datasets. In addition, graph-GPA also promotes better understanding of genetic mechanisms shared among phenotypes, which can potentially be useful for the development of improved diagnosis and therapeutics. The R implementation of graph-GPA is currently available at https://dongjunchung.github.io/GGPA/.'),
(88304, 2017, 'plos', 'Metacoder: An R package for visualization and manipulation of community taxonomic diversity data', 'Foster, Zachary S L|Sharpton, Thomas J|Grünwald, Niklaus J', 'Department of Botany and Plant Pathology, Oregon State University, Corvallis, Oregon, United States of America.|Department of Microbiology, Oregon State University, Corvallis, Oregon, United States of America.|Horticultural Crops Research Laboratory, USDA-ARS, Corvallis, Oregon, United States of America.', 'United States|United States|United States', 83, 'Algorithms|Computer Graphics|DNA|DNA Barcoding, Taxonomic|Genetic Variation|High-Throughput Nucleotide Sequencing|Programming Languages|User-Computer Interface', 'Journal Article', '10.1371/journal.pcbi.1005404', '28222096', 'Community-level data, the type generated by an increasing number of metabarcoding studies, is often graphed as stacked bar charts or pie graphs that use color to represent taxa. These graph types do not convey the hierarchical structure of taxonomic classifications and are limited by the use of color for categories. As an alternative, we developed metacoder, an R package for easily parsing, manipulating, and graphing publication-ready plots of hierarchical data. Metacoder includes a dynamic and flexible function that can parse most text-based formats that contain taxonomic classifications, taxon names, taxon identifiers, or sequence identifiers. Metacoder can then subset, sample, and order this parsed data using a set of intuitive functions that take into account the hierarchical nature of the data. Finally, an extremely flexible plotting function enables quantitative representation of up to 4 arbitrary statistics simultaneously in a tree format by mapping statistics to the color and size of tree nodes and edges. Metacoder also allows exploration of barcode primer bias by integrating functions to run digital PCR. Although it has been designed for data from metabarcoding research, metacoder can easily be applied to any data that has a hierarchical component such as gene ontology or geographic location data. Our package complements currently available tools for community analysis and is provided open source with an extensive online user manual.'),
(88305, 2017, 'plos', 'Two dynamic regimes in the human gut microbiome', 'Gibbons, Sean M|Kearney, Sean M|Smillie, Chris S|Alm, Eric J', 'Department of Biological Engineering, Massachusetts Institute of Technology, Cambridge, MA, United States of America.|Department of Biological Engineering, Massachusetts Institute of Technology, Cambridge, MA, United States of America.|Department of Biological Engineering, Massachusetts Institute of Technology, Cambridge, MA, United States of America.|Department of Biological Engineering, Massachusetts Institute of Technology, Cambridge, MA, United States of America.', 'United States|United States|United States|United States', 0, 'Animals|Bacteria|Computer Simulation|Digestion|Eating|Gastrointestinal Microbiome|Gastrointestinal Tract|Humans|Microbial Interactions|Models, Biological|Models, Statistical|Regression Analysis', 'Journal Article', '10.1371/journal.pcbi.1005364', '28222117', 'The gut microbiome is a dynamic system that changes with host development, health, behavior, diet, and microbe-microbe interactions. Prior work on gut microbial time series has largely focused on autoregressive models (e.g. Lotka-Volterra). However, we show that most of the variance in microbial time series is non-autoregressive. In addition, we show how community state-clustering is flawed when it comes to characterizing within-host dynamics and that more continuous methods are required. Most organisms exhibited stable, mean-reverting behavior suggestive of fixed carrying capacities and abundant taxa were largely shared across individuals. This mean-reverting behavior allowed us to apply sparse vector autoregression (sVAR)-a multivariate method developed for econometrics-to model the autoregressive component of gut community dynamics. We find a strong phylogenetic signal in the non-autoregressive co-variance from our sVAR model residuals, which suggests niche filtering. We show how changes in diet are also non-autoregressive and that Operational Taxonomic Units strongly correlated with dietary variables have much less of an autoregressive component to their variance, which suggests that diet is a major driver of microbial dynamics. Autoregressive variance appears to be driven by multi-day recovery from frequent facultative anaerobe blooms, which may be driven by fluctuations in luminal redox. Overall, we identify two dynamic regimes within the human gut microbiota: one likely driven by external environmental fluctuations, and the other by internal processes.'),
(88306, 2017, 'plos', 'ALKBH7 Variant Related to Prostate Cancer Exhibits Altered Substrate Binding', 'Walker, Alice R|Silvestrov, Pavel|Müller, Tina A|Podolsky, Robert H|Dyson, Gregory|Hausinger, Robert P|Cisneros, Gerardo Andrés', 'Department of Chemistry, Wayne State University, Detroit, MI, United States of America.|Department of Chemistry, Wayne State University, Detroit, MI, United States of America.|Department of Microbiology and Molecular Genetics, Michigan State University, East Lansing, MI, United States of America.|Wayne State University Department of Family Medicine and Public Health Sciences, Wayne State University, Detroit, MI, United States of America.|Karmanos Cancer Institute, Wayne State University, Detroit, MI, United States of America.|Department of Microbiology and Molecular Genetics, Michigan State University, East Lansing, MI, United States of America.|Department of Chemistry, Wayne State University, Detroit, MI, United States of America.', 'United States|United States|United States|United States|United States|United States|United States', 7, 'African Americans|AlkB Enzymes|Binding Sites|Biomarkers, Tumor|Enzyme Activation|Genetic Markers|Genetic Predisposition to Disease|Humans|Ketoglutaric Acids|Male|Mitochondrial Proteins|Molecular Dynamics Simulation|Oxygen|Polymorphism, Single Nucleotide|Prevalence|Prostatic Neoplasms|Protein Binding|Risk Factors|Substrate Specificity|United States', 'Journal Article', '10.1371/journal.pcbi.1005345', '28231280', 'The search for prostate cancer biomarkers has received increased attention and several DNA repair related enzymes have been linked to this dysfunction. Here we report a targeted search for single nucleotide polymorphisms (SNPs) and functional impact characterization of human ALKBH family dioxygenases related to prostate cancer. Our results uncovered a SNP of ALKBH7, rs7540, which is associated with prostate cancer disease in a statistically significantly manner in two separate cohorts, and maintained in African American men. Comparisons of molecular dynamics (MD) simulations on the wild-type and variant protein structures indicate that the resulting alteration in the enzyme induces a significant structural change that reduces ALKBH7s ability to bind its cosubstrate. Experimental spectroscopy studies with purified proteins validate our MD predictions and corroborate the conclusion that this cancer-associated mutation affects productive cosubstrate binding in ALKBH7.');
INSERT INTO `papers` (`id`, `ano`, `journal`, `titulo`, `autores`, `afiliacao`, `pais`, `citacoes`, `palavra_chave`, `categorias`, `doi`, `pubmed`, `abstract`) VALUES
(88307, 2017, 'plos', 'Mindboggling morphometry of human brains', 'Klein, Arno|Ghosh, Satrajit S|Bao, Forrest S|Giard, Joachim|Häme, Yrjö|Stavsky, Eliezer|Lee, Noah|Rossa, Brian|Reuter, Martin|Chaibub Neto, Elias|Keshavan, Anisha', 'Child Mind Institute, New York, New York, United States of America.|McGovern Institute for Brain Research, Massachusetts Institute of Technology, Cambridge, Massachusetts, United States of America.|Department of Electrical and Computer Engineering, University of Akron, Akron, Ohio, United States of America.|University of Louvain, Louvain, Belgium.|Columbia University, New York, New York, United States of America.|Columbia University, New York, New York, United States of America.|Columbia University, New York, New York, United States of America.|TankThink Labs, Boston, Massachusetts, United States of America.|Harvard Medical School, Cambridge, Massachusetts, United States of America.|Sage Bionetworks, Seattle, Washington, United States of America.|University of California San Francisco, San Francisco, California, United States of America.', 'United States|United States|United States|Belgium|United States|United States|United States|United S', 0, 'Algorithms|Anatomic Landmarks|Brain|Brain Diseases|Diffusion Magnetic Resonance Imaging|Female|Humans|Image Interpretation, Computer-Assisted|Imaging, Three-Dimensional|Male|Organ Size|Pattern Recognition, Automated|Reproducibility of Results|Sensitivity and Specificity|Software|Subtraction Technique', 'Journal Article', '10.1371/journal.pcbi.1005350', '28231282', 'Mindboggle (http://mindboggle.info) is an open source brain morphometry platform that takes in preprocessed T1-weighted MRI data and outputs volume, surface, and tabular data containing label, feature, and shape information for further analysis. In this article, we document the software and demonstrate its use in studies of shape variation in healthy and diseased humans. The number of different shape measures and the size of the populations make this the largest and most detailed shape analysis of human brains ever conducted. Brain image morphometry shows great potential for providing much-needed biological markers for diagnosing, tracking, and predicting progression of mental health disorders. Very few software algorithms provide more than measures of volume and cortical thickness, while more subtle shape measures may provide more sensitive and specific biomarkers. Mindboggle computes a variety of (primarily surface-based) shapes: area, volume, thickness, curvature, depth, Laplace-Beltrami spectra, Zernike moments, etc. We evaluate Mindboggles algorithms using the largest set of manually labeled, publicly available brain images in the world and compare them against state-of-the-art algorithms where they exist. All data, code, and results of these evaluations are publicly available.'),
(88308, 2017, 'plos', 'Imputation for transcription factor binding predictions based on deep learning', 'Qin, Qian|Feng, Jianxing', 'Department of Bioinformatics, School of Life Sciences and Technology, Tongji University, Shanghai, China.|Department of Bioinformatics, School of Life Sciences and Technology, Tongji University, Shanghai, China.', 'China|China', 0, 'Binding Sites|Chromatin Immunoprecipitation|Hep G2 Cells|High-Throughput Nucleotide Sequencing|Humans|K562 Cells|Machine Learning|Neural Networks (Computer)|Protein Binding|Protein Interaction Mapping|Reproducibility of Results|Sensitivity and Specificity|Transcription Factors', 'Journal Article', '10.1371/journal.pcbi.1005403', '28234893', 'Understanding the cell-specific binding patterns of transcription factors (TFs) is fundamental to studying gene regulatory networks in biological systems, for which ChIP-seq not only provides valuable data but is also considered as the gold standard. Despite tremendous efforts from the scientific community to conduct TF ChIP-seq experiments, the available data represent only a limited percentage of ChIP-seq experiments, considering all possible combinations of TFs and cell lines. In this study, we demonstrate a method for accurately predicting cell-specific TF binding for TF-cell line combinations based on only a small fraction (4%) of the combinations using available ChIP-seq data. The proposed model, termed TFImpute, is based on a deep neural network with a multi-task learning setting to borrow information across transcription factors and cell lines. Compared with existing methods, TFImpute achieves comparable accuracy on TF-cell line combinations with ChIP-seq data, moreover, TFImpute achieves better accuracy on TF-cell line combinations without ChIP-seq data. This approach can predict cell line specific enhancer activities in K562 and HepG2 cell lines, as measured by massively parallel reporter assays, and predicts the impact of SNPs on TF binding.'),
(88309, 2017, 'plos', 'On the stability and dynamics of stochastic spiking neuron models: Nonlinear Hawkes process and point process GLMs', 'Gerhard, Felipe|Deger, Moritz|Truccolo, Wilson', 'Department of Neuroscience, Brown University, Providence, Rhode Island, United States of America.|School of Computer and Communication Sciences and School of Life Sciences, Brain Mind Institute, École polytechnique fédérale de Lausanne (EPFL), Lausanne, Switzerland.|Department of Neuroscience, Brown University, Providence, Rhode Island, United States of America.', 'United States|Switzerland|United States', 23, 'Action Potentials|Animals|Biological Clocks|Computer Simulation|Humans|Linear Models|Models, Neurological|Multivariate Analysis|Neurons|Nonlinear Dynamics|Signal Processing, Computer-Assisted|Stochastic Processes', 'Journal Article', '10.1371/journal.pcbi.1005390', '28234899', 'Point process generalized linear models (PP-GLMs) provide an important statistical framework for modeling spiking activity in single-neurons and neuronal networks. Stochastic stability is essential when sampling from these models, as done in computational neuroscience to analyze statistical properties of neuronal dynamics and in neuro-engineering to implement closed-loop applications. Here we show, however, that despite passing common goodness-of-fit tests, PP-GLMs estimated from data are often unstable, leading to divergent firing rates. The inclusion of absolute refractory periods is not a satisfactory solution since the activity then typically settles into unphysiological rates. To address these issues, we derive a framework for determining the existence and stability of fixed points of the expected conditional intensity function (CIF) for general PP-GLMs. Specifically, in nonlinear Hawkes PP-GLMs, the CIF is expressed as a function of the previous spike history and exogenous inputs. We use a mean-field quasi-renewal (QR) approximation that decomposes spike history effects into the contribution of the last spike and an average of the CIF over all spike histories prior to the last spike. Fixed points for stationary rates are derived as self-consistent solutions of integral equations. Bifurcation analysis and the number of fixed points predict that the original models can show stable, divergent, and metastable (fragile) dynamics. For fragile models, fluctuations of the single-neuron dynamics predict expected divergence times after which rates approach unphysiologically high values. This metric can be used to estimate the probability of rates to remain physiological for given time periods, e.g., for simulation purposes. We demonstrate the use of the stability framework using simulated single-neuron examples and neurophysiological recordings. Finally, we show how to adapt PP-GLM estimation procedures to guarantee model stability. Overall, our results provide a stability framework for data-driven PP-GLMs and shed new light on the stochastic dynamics of state-of-the-art statistical models of neuronal spiking activity.'),
(88310, 2017, 'plos', 'The genotype-phenotype map of an evolving digital organism', 'Fortuna, Miguel A|Zaman, Luis|Ofria, Charles|Wagner, Andreas', 'Department of Evolutionary Biology and Environmental Studies, University of Zurich, Zurich, Switzerland.|Department of Biology, University of Washington, Seattle, Washington, United States of America.|BEACON Center for the Study of Evolution in Action, Michigan State University, East Lansing, Michigan, Washington, United States of America.|Department of Evolutionary Biology and Environmental Studies, University of Zurich, Zurich, Switzerland.', 'Switzerland|United States|United States|Switzerland', 13, 'Biological Evolution|Computer Simulation|Evolution, Molecular|Genotype|Models, Genetic|Phenotype|Selection, Genetic|Synthetic Biology', 'Journal Article', '10.1371/journal.pcbi.1005414', '28241039', 'To understand how evolving systems bring forth novel and useful phenotypes, it is essential to understand the relationship between genotypic and phenotypic change. Artificial evolving systems can help us understand whether the genotype-phenotype maps of natural evolving systems are highly unusual, and it may help create evolvable artificial systems. Here we characterize the genotype-phenotype map of digital organisms in Avida, a platform for digital evolution. We consider digital organisms from a vast space of 10141 genotypes (instruction sequences), which can form 512 different phenotypes. These phenotypes are distinguished by different Boolean logic functions they can compute, as well as by the complexity of these functions. We observe several properties with parallels in natural systems, such as connected genotype networks and asymmetric phenotypic transitions. The likely common cause is robustness to genotypic change. We describe an intriguing tension between phenotypic complexity and evolvability that may have implications for biological evolution. On the one hand, genotypic change is more likely to yield novel phenotypes in more complex organisms. On the other hand, the total number of novel phenotypes reachable through genotypic change is highest for organisms with simple phenotypes. Artificial evolving systems can help us study aspects of biological evolvability that are not accessible in vastly more complex natural systems. They can also help identify properties, such as robustness, that are required for both human-designed artificial systems and synthetic biological systems to be evolvable.'),
(88311, 2017, 'plos', 'Correction: Behavioral Modeling of Human Choices Reveals Dissociable Effects of Physical Effort and Temporal Delay on Reward Devaluation', 'PLOS Computational Biology Staff', 'Department of Evolutionary Biology and Environmental Studies, University of Zurich, Zurich, Switzerland.', 'Switzerland', 0, '-', 'Published Erratum', '10.1371/journal.pcbi.1005401', '28241040', '[This corrects the article DOI: 10.1371/journal.pcbi.1004116.].'),
(88312, 2017, 'plos', 'Modeling of the axon membrane skeleton structure and implications for its mechanical properties', 'Zhang, Yihao|Abiraman, Krithika|Li, He|Pierce, David M|Tzingounis, Anastasios V|Lykotrafitis, George', 'Department of Mechanical Engineering, University of Connecticut, Storrs, Connecticut, United States of America.|Department of Biomedical Engineering, University of Connecticut, Storrs, Connecticut, United States of America.|Division of Applied Mathematics, Brown University, Providence, Rhode Island, United States of America.|Department of Mechanical Engineering, University of Connecticut, Storrs, Connecticut, United States of America.|Department of Physiology and Neurobiology, University of Connecticut, Storrs, Connecticut, United States of America.|Department of Mechanical Engineering, University of Connecticut, Storrs, Connecticut, United States of America.', 'United States|United States|United States|United States|United States|United States', 28, 'Actins|Animals|Axons|Cell Membrane|Cells, Cultured|Computer Simulation|Elastic Modulus|Finite Element Analysis|Microscopy, Atomic Force|Models, Biological|Models, Chemical|Rats|Spectrin|Stress, Mechanical|Tensile Strength', 'Journal Article', '10.1371/journal.pcbi.1005407', '28241082', 'Super-resolution microscopy recently revealed that, unlike the soma and dendrites, the axon membrane skeleton is structured as a series of actin rings connected by spectrin filaments that are held under tension. Currently, the structure-function relationship of the axonal structure is unclear. Here, we used atomic force microscopy (AFM) to show that the stiffness of the axon plasma membrane is significantly higher than the stiffnesses of dendrites and somata. To examine whether the structure of the axon plasma membrane determines its overall stiffness, we introduced a coarse-grain molecular dynamics model of the axon membrane skeleton that reproduces the structure identified by super-resolution microscopy. Our proposed computational model accurately simulates the median value of the Youngs modulus of the axon plasma membrane determined by atomic force microscopy. It also predicts that because the spectrin filaments are under entropic tension, the thermal random motion of the voltage-gated sodium channels (Nav), which are bound to ankyrin particles, a critical axonal protein, is reduced compared to the thermal motion when spectrin filaments are held at equilibrium. Lastly, our model predicts that because spectrin filaments are under tension, any axonal injuries that lacerate spectrin filaments will likely lead to a permanent disruption of the membrane skeleton due to the inability of spectrin filaments to spontaneously form their initial under-tension configuration.'),
(88313, 2017, 'plos', 'The role of the Hes1 crosstalk hub in Notch-Wnt interactions of the intestinal crypt', 'Kay, Sophie K|Harrington, Heather A|Shepherd, Sarah|Brennan, Keith|Dale, Trevor|Osborne, James M|Gavaghan, David J|Byrne, Helen M', 'Department of Computer Science, University of Oxford, Oxford, U.K.|Mathematical Institute, University of Oxford, Oxford, U.K.|School of Mathematical Sciences, University of Nottingham, Nottingham, U.K.|Wellcome Trust Centre for Cell Matrix Research, University of Manchester, Manchester, U.K.|School of Biosciences, Cardiff University, Cardiff, U.K.|School of Mathematics and Statistics, University of Melbourne, Melbourne, Australia.|Department of Computer Science, University of Oxford, Oxford, U.K.|Department of Computer Science, University of Oxford, Oxford, U.K.', '-|-|-|-|-|Australia|-|-', 4, 'Biological Clocks|Cells, Cultured|Computer Simulation|Humans|Intestinal Mucosa|Models, Biological|Receptor Cross-Talk|Receptors, Notch|Signal Transduction|Transcription Factor HES-1|Wnt Signaling Pathway', 'Journal Article', '10.1371/journal.pcbi.1005400', '28245235', 'The Notch pathway plays a vital role in determining whether cells in the intestinal epithelium adopt a secretory or an absorptive phenotype. Cell fate specification is coordinated via Notchs interaction with the canonical Wnt pathway. Here, we propose a new mathematical model of the Notch and Wnt pathways, in which the Hes1 promoter acts as a hub for pathway crosstalk. Computational simulations of the model can assist in understanding how healthy intestinal tissue is maintained, and predict the likely consequences of biochemical knockouts upon cell fate selection processes. Chemical reaction network theory (CRNT) is a powerful, generalised framework which assesses the capacity of our model for monostability or multistability, by analysing properties of the underlying network structure without recourse to specific parameter values or functional forms for reaction rates. CRNT highlights the role of xcexb2-catenin in stabilising the Notch pathway and damping oscillations, demonstrating that Wnt-mediated actions on the Hes1 promoter can induce dynamic transitions in the Notch system, from multistability to monostability. Time-dependent model simulations of cell pairs reveal the stabilising influence of Wnt upon the Notch pathway, in which xcexb2-catenin- and Dsh-mediated action on the Hes1 promoter are key in shaping the subcellular dynamics. Where Notch-mediated transcription of Hes1 dominates, there is Notch oscillation and maintenance of fate flexibility, Wnt-mediated transcription of Hes1 favours bistability akin to cell fate selection. Cells could therefore regulate the proportion of Wnt- and Notch-mediated control of the Hes1 promoter to coordinate the timing of cell fate selection as they migrate through the intestinal epithelium and are subject to reduced Wnt stimuli. Furthermore, mutant cells characterised by hyperstimulation of the Wnt pathway may, through coupling with Notch, invert cell fate in neighbouring healthy cells, enabling an aberrant cell to maintain its neighbours in mitotically active states.'),
(88314, 2017, 'plos', 'Multiregional integration in the brain during resting-state fMRI activity', 'Hay, Etay|Ritter, Petra|Lobaugh, Nancy J|McIntosh, Anthony R', 'Rotman Research Institute, Baycrest Centre, Toronto, Ontario, Canada.|Department of Neurology, Charité-University Medicine, Berlin, Germany.|MRI Unit, Research Imaging Centre, Centre for Addiction and Mental Health, Toronto, Ontario, Canada.|Rotman Research Institute, Baycrest Centre, Toronto, Ontario, Canada.', 'Canada|Germany|Canada|Canada', 1, 'Brain Mapping|Cerebral Cortex|Comorbidity|Magnetic Resonance Imaging|Models, Neurological|Models, Statistical|Nerve Net|Rest', 'Journal Article', '10.1371/journal.pcbi.1005410', '28248957', 'Data-driven models of functional magnetic resonance imaging (fMRI) activity can elucidate dependencies that involve the combination of multiple brain regions. Activity in some regions during resting-state fMRI can be predicted with high accuracy from the activities of other regions. However, it remains unclear in which regions activity depends on unique integration of multiple predictor regions. To address this question, sparse (parsimonious) models could serve to better determine key interregional dependencies by reducing false positives. We used resting-state fMRI data from 46 subjects, and for each region of interest (ROI) per subject we performed whole-brain recursive feature elimination (RFE) to select the minimal set of ROIs that best predicted activity in the modeled ROI. We quantified the dependence of activity on multiple predictor ROIs, by measuring the gain in prediction accuracy of models that incorporated multiple predictor ROIs compared to models that used a single predictor ROI. We identified regions that showed considerable evidence of multiregional integration and determined the key regions that contributed to their observed activity. Our models reveal fronto-parietal integration networks, little integration in primary sensory regions, as well as redundancy between some regions. Our study demonstrates the utility of whole-brain RFE to generate data-driven models with minimal sets of ROIs that predict activity with high accuracy. By determining the extent to which activity in each ROI depended on integration of signals from multiple ROIs, we find cortical integration networks during resting-state activity.'),
(88315, 2017, 'plos', 'Fidelity of the representation of value in decision-making', 'Bays, Paul M|Dowding, Ben A', 'University of Cambridge, Department of Psychology, Cambridge, United Kingdom.|University of Cambridge, Department of Psychology, Cambridge, United Kingdom.', 'United Kingdom|United Kingdom', 0, 'Adolescent|Adult|Computer Simulation|Decision Making|Decision Support Techniques|Female|Humans|Male|Middle Aged|Models, Neurological|Reinforcement (Psychology)|Reward|Young Adult', 'Journal Article', '10.1371/journal.pcbi.1005405', '28248958', 'The ability to make optimal decisions depends on evaluating the expected rewards associated with different potential actions. This process is critically dependent on the fidelity with which reward value information can be maintained in the nervous system. Here we directly probe the fidelity of value representation following a standard reinforcement learning task. The results demonstrate a previously-unrecognized bias in the representation of value: extreme reward values, both low and high, are stored significantly more accurately and precisely than intermediate rewards. The symmetry between low and high rewards pertained despite substantially higher frequency of exposure to high rewards, resulting from preferential exploitation of more rewarding options. The observed variation in fidelity of value representation retrospectively predicted performance on the reinforcement learning task, demonstrating that the bias in representation has an impact on decision-making. A second experiment in which one or other extreme-valued option was omitted from the learning sequence showed that representational fidelity is primarily determined by the relative position of an encoded value on the scale of rewards experienced during learning. Both variability and guessing decreased with the reduction in the number of options, consistent with allocation of a limited representational resource. These findings have implications for existing models of reward-based learning, which typically assume defectless representation of reward value.'),
(88316, 2017, 'plos', 'A magnesium-induced triplex pre-organizes the SAM-II riboswitch', 'Roy, Susmita|Lammert, Heiko|Hayes, Ryan L|Chen, Bin|LeBlanc, Regan|Dayie, T Kwaku|Onuchic, José N|Sanbonmatsu, Karissa Y', 'Center for Theoretical Biological Physics, Rice University, Houston, Texas, United States of America.|Center for Theoretical Biological Physics, Rice University, Houston, Texas, United States of America.|Center for Theoretical Biological Physics, Rice University, Houston, Texas, United States of America.|Department of Chemistry and Biochemistry, University of Maryland, College Park, Maryland, United States of America.|Department of Chemistry and Biochemistry, University of Maryland, College Park, Maryland, United States of America.|Department of Chemistry and Biochemistry, University of Maryland, College Park, Maryland, United States of America.|Center for Theoretical Biological Physics, Rice University, Houston, Texas, United States of America.|Theoretical Biology and Biophysics Group, Theoretical Division, Los Alamos National Laboratory, Los Alamos, New Mexico, United States of America.', 'United States|United States|United States|United States|United States|United States|United States|Me', 8, 'Binding Sites|Magnesium|Models, Chemical|Molecular Dynamics Simulation|Nucleic Acid Conformation|RNA, Messenger|Riboswitch', 'Journal Article', '10.1371/journal.pcbi.1005406', '28248966', 'Our 13C- and 1H-chemical exchange saturation transfer (CEST) experiments previously revealed a dynamic exchange between partially closed and open conformations of the SAM-II riboswitch in the absence of ligand. Here, all-atom structure-based molecular simulations, with the electrostatic effects of Manning counter-ion condensation and explicit magnesium ions are employed to calculate the folding free energy landscape of the SAM-II riboswitch. We use this analysis to predict that magnesium ions remodel the landscape, shifting the equilibrium away from the extended, partially unfolded state towards a compact, pre-organized conformation that resembles the ligand-bound state. Our CEST and SAXS experiments, at different magnesium ion concentrations, quantitatively confirm our simulation results, demonstrating that magnesium ions induce collapse and pre-organization. Agreement between theory and experiment bolsters microscopic interpretation of our simulations, which shows that triplex formation between helix P2b and loop L1 is highly sensitive to magnesium and plays a key role in pre-organization. Pre-organization of the SAM-II riboswitch allows rapid detection of ligand with high selectivity, which is important for biological function.'),
(88317, 2017, 'plos', 'Novel non-invasive algorithm to identify the origins of re-entry and ectopic foci in the atria from 64-lead ECGs: A computational study', 'Alday, Erick A Perez|Colman, Michael A|Langley, Philip|Zhang, Henggui', 'Biological Physics Group, Department of Physics and Astronomy, University of Manchester, Manchester, United Kingdom.|Theoretical Physics Division, Department of Physics and Astronomy, University of Manchester, Manchester, United Kingdom.|School of Engineering, University of Hull, Hull, United Kingdom.|Biological Physics Group, Department of Physics and Astronomy, University of Manchester, Manchester, United Kingdom.', 'United Kingdom|United Kingdom|United Kingdom|United Kingdom', 5, 'Algorithms|Atrial Premature Complexes|Body Surface Potential Mapping|Computer Simulation|Diagnosis, Computer-Assisted|Electrocardiography|Heart Conduction System|Humans|Models, Cardiovascular|Reproducibility of Results|Sensitivity and Specificity', 'Journal Article', '10.1371/journal.pcbi.1005270', '28253254', 'Atrial tachy-arrhytmias, such as atrial fibrillation (AF), are characterised by irregular electrical activity in the atria, generally associated with erratic excitation underlain by re-entrant scroll waves, fibrillatory conduction of multiple wavelets or rapid focal activity. Epidemiological studies have shown an increase in AF prevalence in the developed world associated with an ageing society, highlighting the need for effective treatment options. Catheter ablation therapy, commonly used in the treatment of AF, requires spatial information on atrial electrical excitation. The standard 12-lead electrocardiogram (ECG) provides a method for non-invasive identification of the presence of arrhythmia, due to irregularity in the ECG signal associated with atrial activation compared to sinus rhythm, but has limitations in providing specific spatial information. There is therefore a pressing need to develop novel methods to identify and locate the origin of arrhythmic excitation. Invasive methods provide direct information on atrial activity, but may induce clinical complications. Non-invasive methods avoid such complications, but their development presents a greater challenge due to the non-direct nature of monitoring. Algorithms based on the ECG signals in multiple leads (e.g. a 64-lead vest) may provide a viable approach. In this study, we used a biophysically detailed model of the human atria and torso to investigate the correlation between the morphology of the ECG signals from a 64-lead vest and the location of the origin of rapid atrial excitation arising from rapid focal activity and/or re-entrant scroll waves. A focus-location algorithm was then constructed from this correlation. The algorithm had success rates of 93% and 76% for correctly identifying the origin of focal and re-entrant excitation with a spatial resolution of 40 mm, respectively. The general approach allows its application to any multi-lead ECG system. This represents a significant extension to our previously developed algorithms to predict the AF origins in association with focal activities.'),
(88318, 2017, 'plos', 'Scalable Design of Paired CRISPR Guide RNAs for Genomic Deletion', 'Pulido-Quetglas, Carlos|Aparicio-Prat, Estel|Arnan, Carme|Polidori, Taisia|Hermoso, Toni|Palumbo, Emilio|Ponomarenko, Julia|Guigo, Roderic|Johnson, Rory', 'Centre for Genomic Regulation (CRG), The Barcelona Institute for Science and Technology, Dr. Aiguader 88, Barcelona, Spain.|Centre for Genomic Regulation (CRG), The Barcelona Institute for Science and Technology, Dr. Aiguader 88, Barcelona, Spain.|Centre for Genomic Regulation (CRG), The Barcelona Institute for Science and Technology, Dr. Aiguader 88, Barcelona, Spain.|Centre for Genomic Regulation (CRG), The Barcelona Institute for Science and Technology, Dr. Aiguader 88, Barcelona, Spain.|Centre for Genomic Regulation (CRG), The Barcelona Institute for Science and Technology, Dr. Aiguader 88, Barcelona, Spain.|Centre for Genomic Regulation (CRG), The Barcelona Institute for Science and Technology, Dr. Aiguader 88, Barcelona, Spain.|Centre for Genomic Regulation (CRG), The Barcelona Institute for Science and Technology, Dr. Aiguader 88, Barcelona, Spain.|Centre for Genomic Regulation (CRG), The Barcelona Institute for Science and Technology, Dr. Aiguader 88, Barcelona, Spain.|Centre for Genomic Regulation (CRG), The Barcelona Institute for Science and Technology, Dr. Aiguader 88, Barcelona, Spain.', 'Spain|Spain|Spain|Spain|Spain|Spain|Spain|Spain|Spain', 0, 'CRISPR-Associated Proteins|Gene Deletion|Gene Editing|Gene Knockdown Techniques|RNA Editing|RNA, Guide', 'Journal Article', '10.1371/journal.pcbi.1005341', '28253259', 'CRISPR-Cas9 technology can be used to engineer precise genomic deletions with pairs of single guide RNAs (sgRNAs). This approach has been widely adopted for diverse applications, from disease modelling of individual loci, to parallelized loss-of-function screens of thousands of regulatory elements. However, no solution has been presented for the unique bioinformatic design requirements of CRISPR deletion. We here present CRISPETa, a pipeline for flexible and scalable paired sgRNA design based on an empirical scoring model. Multiple sgRNA pairs are returned for each target, and any number of targets can be analyzed in parallel, making CRISPETa equally useful for focussed or high-throughput studies. Fast run-times are achieved using a pre-computed off-target database. sgRNA pair designs are output in a convenient format for visualisation and oligonucleotide ordering. We present pre-designed, high-coverage library designs for entire classes of protein-coding and non-coding elements in human, mouse, zebrafish, Drosophila melanogaster and Caenorhabditis elegans. In human cells, we reproducibly observe deletion efficiencies of xe2x89xa550% for CRISPETa designs targeting an enhancer and exonic fragment of the MALAT1 oncogene. In the latter case, deletion results in production of desired, truncated RNA. CRISPETa will be useful for researchers seeking to harness CRISPR for targeted genomic deletion, in a variety of model organisms, from single-target to high-throughput scales.'),
(88319, 2017, 'plos', 'Mechanisms of fast and stringent search in homologous pairing of double-stranded DNA', 'Bitran, Amir|Chiang, Wei-Yin|Levine, Erel|Prentiss, Mara', 'Department of Physics, Harvard University, Cambridge, Massachusetts, United States of America.|Department of Physics, Harvard University, Cambridge, Massachusetts, United States of America.|Department of Physics, Harvard University, Cambridge, Massachusetts, United States of America.|Department of Physics, Harvard University, Cambridge, Massachusetts, United States of America.', 'United States|United States|United States|United States', 2, 'Base Pairing|Binding Sites|Computer Simulation|DNA|Models, Chemical|Models, Molecular|Reproducibility of Results|Sequence Homology, Nucleic Acid', 'Journal Article', '10.1371/journal.pcbi.1005421', '28257444', 'Self-organization in the cell relies on the rapid and specific binding of molecules to their cognate targets. Correct bindings must be stable enough to promote the desired function even in the crowded and fluctuating cellular environment. In systems with many nearly matched targets, rapid and stringent formation of stable products is challenging. Mechanisms that overcome this challenge have been previously proposed, including separating the process into multiple stages, however, how particular in vivo systems overcome the challenge remains unclear. Here we consider a kinetic system, inspired by homology dependent pairing between double stranded DNA in bacteria. By considering a simplified tractable model, we identify different homology testing stages that naturally occur in the system. In particular, we first model dsDNA molecules as short rigid rods containing periodically spaced binding sites. The interaction begins when the centers of two rods collide at a random angle. For most collision angles, the interaction energy is weak because only a few binding sites near the collision point contribute significantly to the binding energy. We show that most incorrect pairings are rapidly rejected at this stage. In rare cases, the two rods enter a second stage by rotating into parallel alignment. While rotation increases the stability of matched and nearly matched pairings, subsequent rotational fluctuations reduce kinetic trapping. Finally, in vivo chromosome are much longer than the persistence length of dsDNA, so we extended the model to include multiple parallel collisions between long dsDNA molecules, and find that those additional interactions can greatly accelerate the searching.'),
(88320, 2017, 'plos', 'Managing uncertainty in metabolic network structure and improving predictions using EnsembleFBA', 'Biggs, Matthew B|Papin, Jason A', 'Department of Biomedical Engineering, University of Virginia, Charlottesville, VA, United States of America.|Department of Biomedical Engineering, University of Virginia, Charlottesville, VA, United States of America.', 'United States|United States', 0, 'Algorithms|Bacteria|Bacterial Proteins|Computer Simulation|Metabolic Flux Analysis|Metabolic Networks and Pathways|Metabolome|Models, Biological|Models, Statistical|Reproducibility of Results|Sensitivity and Specificity|Software', 'Journal Article', '10.1371/journal.pcbi.1005413', '28263984', 'Genome-scale metabolic network reconstructions (GENREs) are repositories of knowledge about the metabolic processes that occur in an organism. GENREs have been used to discover and interpret metabolic functions, and to engineer novel network structures. A major barrier preventing more widespread use of GENREs, particularly to study non-model organisms, is the extensive time required to produce a high-quality GENRE. Many automated approaches have been developed which reduce this time requirement, but automatically-reconstructed draft GENREs still require curation before useful predictions can be made. We present a novel approach to the analysis of GENREs which improves the predictive capabilities of draft GENREs by representing many alternative network structures, all equally consistent with available data, and generating predictions from this ensemble. This ensemble approach is compatible with many reconstruction methods. We refer to this new approach as Ensemble Flux Balance Analysis (EnsembleFBA). We validate EnsembleFBA by predicting growth and gene essentiality in the model organism Pseudomonas aeruginosa UCBPP-PA14. We demonstrate how EnsembleFBA can be included in a systems biology workflow by predicting essential genes in six Streptococcus species and mapping the essential genes to small molecule ligands from DrugBank. We found that some metabolic subsystems contributed disproportionately to the set of predicted essential reactions in a way that was unique to each Streptococcus species, leading to species-specific outcomes from small molecule interactions. Through our analyses of P. aeruginosa and six Streptococci, we show that ensembles increase the quality of predictions without drastically increasing reconstruction time, thus making GENRE approaches more practical for applications which require predictions for many non-model organisms. All of our functions and accompanying example code are available in an open online repository.'),
(88321, 2017, 'plos', 'Inferring epidemiological parameters from phylogenies using regression-ABC: A comparative study', 'Saulnier, Emma|Gascuel, Olivier|Alizon, Samuel', 'Laboratoire Maladies Infectieuses et Vecteurs: Ecologie, Génétique, Evolution et Contrôle - UMR CNRS 5290, IRD 224 et UM, Montpellier, France.|Institut de Biologie Computationnelle (IBC) and Laboratoire dInformatique, de Robotique et de Microélectronique de Montpellier (LIRMM) - UMR 5506, CNRS et UM, Montpellier, France.|Laboratoire Maladies Infectieuses et Vecteurs: Ecologie, Génétique, Evolution et Contrôle - UMR CNRS 5290, IRD 224 et UM, Montpellier, France.', 'France|France|France', 12, 'Algorithms|Bayes Theorem|Computer Simulation|Disease Outbreaks|Ebolavirus|Hemorrhagic Fever, Ebola|Humans|Incidence|Models, Statistical|Phylogeny|Regression Analysis|Risk Factors|Sierra Leone|Virus Latency', 'Journal Article', '10.1371/journal.pcbi.1005416', '28263987', 'Inferring epidemiological parameters such as the R0 from time-scaled phylogenies is a timely challenge. Most current approaches rely on likelihood functions, which raise specific issues that range from computing these functions to finding their maxima numerically. Here, we present a new regression-based Approximate Bayesian Computation (ABC) approach, which we base on a large variety of summary statistics intended to capture the information contained in the phylogeny and its corresponding lineage-through-time plot. The regression step involves the Least Absolute Shrinkage and Selection Operator (LASSO) method, which is a robust machine learning technique. It allows us to readily deal with the large number of summary statistics, while avoiding resorting to Markov Chain Monte Carlo (MCMC) techniques. To compare our approach to existing ones, we simulated target trees under a variety of epidemiological models and settings, and inferred parameters of interest using the same priors. We found that, for large phylogenies, the accuracy of our regression-ABC is comparable to that of likelihood-based approaches involving birth-death processes implemented in BEAST2. Our approach even outperformed these when inferring the host population size with a Susceptible-Infected-Removed epidemiological model. It also clearly outperformed a recent kernel-ABC approach when assuming a Susceptible-Infected epidemiological model with two host types. Lastly, by re-analyzing data from the early stages of the recent Ebola epidemic in Sierra Leone, we showed that regression-ABC provides more realistic estimates for the duration parameters (latency and infectiousness) than the likelihood-based method. Overall, ABC based on a large variety of summary statistics and a regression method able to perform variable selection and avoid overfitting is a promising approach to analyze large phylogenies.'),
(88322, 2017, 'plos', 'Biomarkers are used to predict quantitative metabolite concentration profiles in human red blood cells', 'Yurkovich, James T|Yang, Laurence|Palsson, Bernhard O', 'Department of Bioengineering, University of California, San Diego, La Jolla, California, United States of America.|Department of Bioengineering, University of California, San Diego, La Jolla, California, United States of America.|Department of Bioengineering, University of California, San Diego, La Jolla, California, United States of America.', 'United States|United States|United States', 8, 'Biomarkers|Blood Proteins|Cells, Cultured|Computer Simulation|Erythrocytes|High-Throughput Screening Assays|Humans|Metabolic Flux Analysis|Metabolome|Models, Cardiovascular|Reproducibility of Results|Sensitivity and Specificity', 'Journal Article', '10.1371/journal.pcbi.1005424', '28264007', 'Deep-coverage metabolomic profiling has revealed a well-defined development of metabolic decay in human red blood cells (RBCs) under cold storage conditions. A set of extracellular biomarkers has been recently identified that reliably defines the qualitative state of the metabolic network throughout this metabolic decay process. Here, we extend the utility of these biomarkers by using them to quantitatively predict the concentrations of other metabolites in the red blood cell. We are able to accurately predict the concentration profile of 84 of the 91 (92%) measured metabolites (p < 0.05) in RBC metabolism using only measurements of these five biomarkers. The median of prediction errors (symmetric mean absolute percent error) across all metabolites was 13%. The ability to predict numerous metabolite concentrations from a simple set of biomarkers offers the potential for the development of a powerful workflow that could be used to evaluate the metabolic state of a biological system using a minimal set of measurements.'),
(88323, 2017, 'plos', 'Feedback between motion and sensation provides nonlinear boost in run-and-tumble navigation', 'Long, Junjiajia|Zucker, Steven W|Emonet, Thierry', 'Department of Physics, Yale University, New Haven, Connecticut, United States of America.|Department of Computer Science, Yale University, New Haven, Connecticut, United States of America.|Department of Physics, Yale University, New Haven, Connecticut, United States of America.', 'United States|United States|United States', 0, 'Animals|Computer Simulation|Feedback, Physiological|Gait|Humans|Locomotion|Models, Biological|Motion Perception|Nonlinear Dynamics|Physical Exertion|Rotation|Spatial Navigation', 'Journal Article', '10.1371/journal.pcbi.1005429', '28264023', 'Many organisms navigate gradients by alternating straight motions (runs) with random reorientations (tumbles), transiently suppressing tumbles whenever attractant signal increases. This induces a functional coupling between movement and sensation, since tumbling probability is controlled by the internal state of the organism which, in turn, depends on previous signal levels. Although a negative feedback tends to maintain this internal state close to adapted levels, positive feedback can arise when motion up the gradient reduces tumbling probability, further boosting drift up the gradient. Importantly, such positive feedback can drive large fluctuations in the internal state, complicating analytical approaches. Previous studies focused on what happens when the negative feedback dominates the dynamics. By contrast, we show here that there is a large portion of physiologically-relevant parameter space where the positive feedback can dominate, even when gradients are relatively shallow. We demonstrate how large transients emerge because of non-normal dynamics (non-orthogonal eigenvectors near a stable fixed point) inherent in the positive feedback, and further identify a fundamental nonlinearity that strongly amplifies their effect. Most importantly, this amplification is asymmetric, elongating runs in favorable directions and abbreviating others. The result is a ratchet-like gradient climbing behavior with drift speeds that can approach half the maximum run speed of the organism. Our results thus show that the classical drawback of run-and-tumble navigation-wasteful runs in the wrong direction-can be mitigated by exploiting the non-normal dynamics implicit in the run-and-tumble strategy.'),
(88324, 2017, 'plos', 'Bistable front dynamics in a contractile medium: Travelling wave fronts and cortical advection define stable zones of RhoA signaling at epithelial adherens junctions', 'Priya, Rashmi|Gomez, Guillermo A|Budnar, Srikanth|Acharya, Bipul R|Czirok, Andras|Yap, Alpha S|Neufeld, Zoltan', 'Institute for Molecular Bioscience, Division of Cell Biology and Molecular Medicine, The University of Queensland, St. Lucia, Brisbane, Queensland, Australia.|Institute for Molecular Bioscience, Division of Cell Biology and Molecular Medicine, The University of Queensland, St. Lucia, Brisbane, Queensland, Australia.|Institute for Molecular Bioscience, Division of Cell Biology and Molecular Medicine, The University of Queensland, St. Lucia, Brisbane, Queensland, Australia.|Institute for Molecular Bioscience, Division of Cell Biology and Molecular Medicine, The University of Queensland, St. Lucia, Brisbane, Queensland, Australia.|Department of Anatomy and Cell Biology, University of Kansas Medical Center, Kansas City, Kansas, United States of America.|Institute for Molecular Bioscience, Division of Cell Biology and Molecular Medicine, The University of Queensland, St. Lucia, Brisbane, Queensland, Australia.|School of Mathematics and Physics, The University of Queensland, St. Lucia, Brisbane, Queensland, Australia.', 'Australia|Australia|Australia|Australia|United States|Australia|Australia', 6, 'Actomyosin|Adherens Junctions|Animals|Computer Simulation|Epithelial Cells|Humans|Mechanotransduction, Cellular|Models, Biological|Molecular Motor Proteins|Muscle Contraction|Stress, Mechanical|rhoA GTP-Binding Protein', 'Journal Article', '10.1371/journal.pcbi.1005411', '28273072', 'Mechanical coherence of cell layers is essential for epithelia to function as tissue barriers and to control active tissue dynamics during morphogenesis. RhoA signaling at adherens junctions plays a key role in this process by coupling cadherin-based cell-cell adhesion together with actomyosin contractility. Here we propose and analyze a mathematical model representing core interactions involved in the spatial localization of junctional RhoA signaling. We demonstrate how the interplay between biochemical signaling through positive feedback, combined with diffusion on the cell membrane and mechanical forces generated in the cortex, can determine the spatial distribution of RhoA signaling at cell-cell junctions. This dynamical mechanism relies on the balance between a propagating bistable signal that is opposed by an advective flow generated by an actomyosin stress gradient. Experimental observations on the behavior of the system when contractility is inhibited are in qualitative agreement with the predictions of the model.'),
(88325, 2017, 'plos', 'Correction: Inference of Quantitative Models of Bacterial Promoters from Time-Series Reporter Gene Data', 'PLOS Computational Biology Staff', 'School of Mathematics and Physics, The University of Queensland, St. Lucia, Brisbane, Queensland, Australia.', 'Australia', 0, '-', 'Published Erratum', '10.1371/journal.pcbi.1005402', '28273095', '[This corrects the article DOI: 10.1371/journal.pcbi.1004028.].'),
(88326, 2017, 'plos', 'A model for brain life history evolution', 'González-Forero, Mauricio|Faulwasser, Timm|Lehmann, Laurent', 'Department of Ecology and Evolution, University of Lausanne, Lausanne, Switzerland.|Laboratoire dAutomatique, École Polytechnique Fédérale de Lausanne, Lausanne, Switzerland.|Department of Ecology and Evolution, University of Lausanne, Lausanne, Switzerland.', 'Switzerland|Switzerland|Switzerland', 0, 'Biological Evolution|Brain|Cognition|Energy Metabolism|Life Cycle Stages|Models, Genetic', 'Journal Article', '10.1371/journal.pcbi.1005380', '28278153', 'Complex cognition and relatively large brains are distributed across various taxa, and many primarily verbal hypotheses exist to explain such diversity. Yet, mathematical approaches formalizing verbal hypotheses would help deepen the understanding of brain and cognition evolution. With this aim, we combine elements of life history and metabolic theories to formulate a metabolically explicit mathematical model for brain life history evolution. We assume that some of the brains energetic expense is due to production (learning) and maintenance (memory) of energy-extraction skills (or cognitive abilities, knowledge, information, etc.). We also assume that individuals use such skills to extract energy from the environment, and can allocate this energy to grow and maintain the body, including brain and reproductive tissues. The model can be used to ask what fraction of growth energy should be allocated at each age, given natural selection, to growing brain and other tissues under various biological settings. We apply the model to find uninvadable allocation strategies under a baseline setting (me vs nature), namely when energy-extraction challenges are environmentally determined and are overcome individually but possibly with maternal help, and use modern-human data to estimate models parameter values. The resulting uninvadable strategies yield predictions for brain and body mass throughout ontogeny and for the ages at maturity, adulthood, and brain growth arrest. We find that: (1) a me-vs-nature setting is enough to generate adult brain and body mass of ancient human scale and a sequence of childhood, adolescence, and adulthood stages, (2) large brains are favored by intermediately challenging environments, moderately effective skills, and metabolically expensive memory, and (3) adult skill is proportional to brain mass when metabolic costs of memory saturate the brain metabolic rate allocated to skills.');
INSERT INTO `papers` (`id`, `ano`, `journal`, `titulo`, `autores`, `afiliacao`, `pais`, `citacoes`, `palavra_chave`, `categorias`, `doi`, `pubmed`, `abstract`) VALUES
(88327, 2017, 'plos', 'BIDS apps: Improving ease of use, accessibility, and reproducibility of neuroimaging data analysis methods', 'Gorgolewski, Krzysztof J|Alfaro-Almagro, Fidel|Auer, Tibor|Bellec, Pierre|Capotxc4x83, Mihai|Chakravarty, M Mallar|Churchill, Nathan W|Cohen, Alexander Li|Craddock, R Cameron|Devenyi, Gabriel A|Eklund, Anders|Esteban, Oscar|Flandin, Guillaume|Ghosh, Satrajit S|Guntupalli, J Swaroop|Jenkinson, Mark|Keshavan, Anisha|Kiar, Gregory|Liem, Franziskus|Raamana, Pradeep Reddy|Raffelt, David|Steele, Christopher J|Quirion, Pierre-Olivier|Smith, Robert E|Strother, Stephen C|Varoquaux, Gaxc3xabl|Wang, Yida|Yarkoni, Tal|Poldrack, Russell A', 'Department of Psychology, Stanford University, Stanford, California, United States of America.|Oxford Centre for Functional Magnetic Resonance Imaging of the Brain (FMRIB), Oxford University, Oxford, United Kingdom.|Department of Psychology, Royal Holloway University of London, Egham, United Kingdom.|Centre de Recherche de lInstitut Universitaire Gxc3xa9riatrique de Montrxc3xa9al, Montreal, Canada.|Parallel Computing Lab, Intel Corporation, Santa Clara, CA & Hillsboro, Oregon, United States of America.|Douglas Mental Health University Institute, McGill University, Montreal, Canada.|Keenan Research Centre of the Li Ka Shing Knowledge Institute, St. Michaels Hospital, Ontario, Canada.|Department of Neurology, Boston Childrens Hospital, Boston, Massachusetts, United States of America.|Computational Neuroimaging Lab, Center for Biomedical Imaging and Neuromodulation, Nathan S. Kline Institute for Psychiatric Research, Orangeburg, New York, United States of America.|Douglas Mental Health University Institute, McGill University, Montreal, Canada.|Department of Biomedical Engineering, Linkxc3xb6ping University, Linkxc3xb6ping, Sweden.|Department of Psychology, Stanford University, Stanford, California, United States of America.|Wellcome Trust Centre for Neuroimaging, London, United Kingdom.|McGovern Institute for Brain Research, Massachusetts Institute of Technology, Cambridge, Massachusetts, United States of America.|Department of Psychological and Brain Sciences, Dartmouth College, Hanover, New Hampshire, United States of America.|Oxford Centre for Functional Magnetic Resonance Imaging of the Brain (FMRIB), Oxford University, Oxford, United Kingdom.|UC Berkeley-UCSF Graduate Program in Bioengineering, San Francisco, California, United States of America.|Center for Imaging Science, Johns Hopkins University, Baltimore, Maryland, United States of America.|University Research Priority Program Dynamics of Healthy Aging, University of Zurich, Zurich, Switzerland.|Rotman Research Institute, Baycrest Health Sciences, Toronto, Ontario, Canada.|Florey Institute of Neuroscience and Mental Health, Melbourne, Victoria, Australia.|Douglas Mental Health University Institute, McGill University, Montreal, Canada.|Center for Medical Image Science and Visualization (CMIV), Linkxc3xb6ping University, Linkxc3xb6ping, Sweden.|Florey Institute of Neuroscience and Mental Health, Melbourne, Victoria, Australia.|Rotman Research Institute, Baycrest Health Sciences, Toronto, Ontario, Canada.|Parietal team, INRIA Saclay Ile-de-France, Palaiseau, France.|Parallel Computing Lab, Intel Corporation, Santa Clara, CA & Hillsboro, Oregon, United States of America.|Department of Psychology, University of Texas at Austin, Austin, Texas, United States of America.|Department of Psychology, Stanford University, Stanford, California, United States of America.', 'United States|United Kingdom|United Kingdom|Canada|United States|Canada|Canada|United States|United ', 29, 'Algorithms|Brain|Humans|Image Interpretation, Computer-Assisted|Magnetic Resonance Imaging|Neuroimaging|Radiology Information Systems|Software|User-Computer Interface', 'Journal Article', '10.1371/journal.pcbi.1005209', '28278228', 'The rate of progress in human neurosciences is limited by the inability to easily apply a wide range of analysis methods to the plethora of different datasets acquired in labs around the world. In this work, we introduce a framework for creating, testing, versioning and archiving portable applications for analyzing neuroimaging data organized and described in compliance with the Brain Imaging Data Structure (BIDS). The portability of these applications (BIDS Apps) is achieved by using container technologies that encapsulate all binary and other dependencies in one convenient package. BIDS Apps run on all three major operating systems with no need for complex setup and configuration and thanks to the comprehensiveness of the BIDS standard they require little manual user input. Previous containerized data processing solutions were limited to single user environments and not compatible with most multi-tenant High Performance Computing systems. BIDS Apps overcome this limitation by taking advantage of the Singularity container technology. As a proof of concept, this work is accompanied by 22 ready to use BIDS Apps, packaging a diverse set of commonly used neuroimaging algorithms.'),
(88328, 2017, 'plos', 'A human judgment approach to epidemiological forecasting', 'Farrow, David C|Brooks, Logan C|Hyun, Sangwon|Tibshirani, Ryan J|Burke, Donald S|Rosenfeld, Roni', 'School of Computer Science, Carnegie Mellon University, Pittsburgh, Pennsylvania, United States of America.|School of Computer Science, Carnegie Mellon University, Pittsburgh, Pennsylvania, United States of America.|Department of Statistics, Carnegie Mellon University, Pittsburgh, Pennsylvania, United States of America.|Department of Statistics, Carnegie Mellon University, Pittsburgh, Pennsylvania, United States of America.|Graduate School of Public Health, University of Pittsburgh, Pittsburgh, Pennsylvania, United States of America.|School of Computer Science, Carnegie Mellon University, Pittsburgh, Pennsylvania, United States of America.', 'United States|United States|United States|United States|United States|United States', 0, 'Communicable Diseases|Disease Outbreaks|Epidemiologic Methods|Forecasting|Humans|Models, Statistical|Prevalence|Reproducibility of Results|Risk Assessment|Sensitivity and Specificity|United States', 'Journal Article', '10.1371/journal.pcbi.1005248', '28282375', 'Infectious diseases impose considerable burden on society, despite significant advances in technology and medicine over the past century. Advanced warning can be helpful in mitigating and preparing for an impending or ongoing epidemic. Historically, such a capability has lagged for many reasons, including in particular the uncertainty in the current state of the system and in the understanding of the processes that drive epidemic trajectories. Presently we have access to data, models, and computational resources that enable the development of epidemiological forecasting systems. Indeed, several recent challenges hosted by the U.S. government have fostered an open and collaborative environment for the development of these technologies. The primary focus of these challenges has been to develop statistical and computational methods for epidemiological forecasting, but here we consider a serious alternative based on collective human judgment. We created the web-based Epicast forecasting system which collects and aggregates epidemic predictions made in real-time by human participants, and with these forecasts we ask two questions: how accurate is human judgment, and how do these forecasts compare to their more computational, data-driven alternatives? To address the former, we assess by a variety of metrics how accurately humans are able to predict influenza and chikungunya trajectories. As for the latter, we show that real-time, combined human predictions of the 2014-2015 and 2015-2016 U.S. flu seasons are often more accurate than the same predictions made by several statistical systems, especially for short-term targets. We conclude that there is valuable predictive power in collective human judgment, and we discuss the benefits and drawbacks of this approach.'),
(88329, 2017, 'plos', 'Patient-specific modeling of individual sickle cell behavior under transient hypoxia', 'Li, Xuejin|Du, E|Dao, Ming|Suresh, Subra|Karniadakis, George Em', 'Division of Applied Mathematics, Brown University, Providence, Rhode Island, United States of America.|Department of Materials Science and Engineering, Massachusetts Institute of Technology, Cambridge, Massachusetts, United States of America.|Department of Materials Science and Engineering, Massachusetts Institute of Technology, Cambridge, Massachusetts, United States of America.|Department of Biomedical Engineering, Computational Biology Department, and Department of Materials Science and Engineering, Carnegie Mellon University, Pittsburgh, Pennsylvania, United States of America.|Division of Applied Mathematics, Brown University, Providence, Rhode Island, United States of America.', 'United States|United States|United States|United States|United States', 0, 'Anemia, Sickle Cell|Cell Hypoxia|Cell Movement|Cells, Cultured|Computer Simulation|Erythrocyte Membrane|Erythrocytes, Abnormal|Hemoglobins, Abnormal|Humans|Models, Cardiovascular|Patient-Specific Modeling', 'Journal Article', '10.1371/journal.pcbi.1005426', '28288152', 'Sickle cell disease (SCD) is a highly complex genetic blood disorder in which red blood cells (RBC) exhibit heterogeneous morphology changes and decreased deformability. We employ a kinetic model for cell morphological sickling that invokes parameters derived from patient-specific data. This model is used to investigate the dynamics of individual sickle cells in a capillary-like microenvironment in order to address various mechanisms associated with SCD. We show that all RBCs, both hypoxia-unaffected and hypoxia-affected ones, regularly pass through microgates under oxygenated state. However, the hypoxia-affected cells undergo sickling which significantly alters cell dynamics. In particular, the dense and rigid sickle RBCs are obstructed thereby clogging blood flow while the less dense and deformable ones are capable of circumnavigating dead (trapped) cells ahead of them by choosing a serpentine path. Informed by recent experiments involving microfluidics that provide in vitro quantitative information on cell dynamics under transient hypoxia conditions, we have performed detailed computational simulations of alterations to cell behavior in response to morphological changes and membrane stiffening. Our model reveals that SCD exhibits substantial heterogeneity even within a particular density-fractionated subpopulation. These findings provide unique insights into how individual sickle cells move through capillaries under transient hypoxic conditions, and offer novel possibilities for designing effective therapeutic interventions for SCD.'),
(88330, 2017, 'plos', 'Dynamics robustness of cascading systems', 'Young, Jonathan T|Hatakeyama, Tetsuhiro S|Kaneko, Kunihiko', 'Research Center for Complex Systems Biology, The University of Tokyo, Tokyo, Japan.|Research Center for Complex Systems Biology, The University of Tokyo, Tokyo, Japan.|Research Center for Complex Systems Biology, The University of Tokyo, Tokyo, Japan.', 'Japan|Japan|Japan', 2, 'Animals|Cell Physiological Phenomena|Computer Simulation|Humans|Models, Biological|Multienzyme Complexes|Proteome|Signal Transduction', 'Journal Article', '10.1371/journal.pcbi.1005434', '28288155', 'A most important property of biochemical systems is robustness. Static robustness, e.g., homeostasis, is the insensitivity of a state against perturbations, whereas dynamics robustness, e.g., homeorhesis, is the insensitivity of a dynamic process. In contrast to the extensively studied static robustness, dynamics robustness, i.e., how a system creates an invariant temporal profile against perturbations, is little explored despite transient dynamics being crucial for cellular fates and are reported to be robust experimentally. For example, the duration of a stimulus elicits different phenotypic responses, and signaling networks process and encode temporal information. Hence, robustness in time courses will be necessary for functional biochemical networks. Based on dynamical systems theory, we uncovered a general mechanism to achieve dynamics robustness. Using a three-stage linear signaling cascade as an example, we found that the temporal profiles and response duration post-stimulus is robust to perturbations against certain parameters. Then analyzing the linearized model, we elucidated the criteria of when signaling cascades will display dynamics robustness. We found that changes in the upstream modules are masked in the cascade, and that the response duration is mainly controlled by the rate-limiting module and organization of the cascades kinetics. Specifically, we found two necessary conditions for dynamics robustness in signaling cascades: 1) Constraint on the rate-limiting process: The phosphatase activity in the perturbed module is not the slowest. 2) Constraints on the initial conditions: The kinase activity needs to be fast enough such that each module is saturated even with fast phosphatase activity and upstream changes are attenuated. We discussed the relevance of such robustness to several biological examples and the validity of the above conditions therein. Given the applicability of dynamics robustness to a variety of systems, it will provide a general basis for how biological systems function dynamically.'),
(88331, 2017, 'plos', 'Parameter estimation for multistage clonal expansion models from cancer incidence data: A practical identifiability analysis', 'Brouwer, Andrew F|Meza, Rafael|Eisenberg, Marisa C', 'Department of Epidemiology, University of Michigan, Ann Arbor, Michigan, United States of America.|Department of Epidemiology, University of Michigan, Ann Arbor, Michigan, United States of America.|Department of Epidemiology, University of Michigan, Ann Arbor, Michigan, United States of America.', 'United States|United States|United States', 6, 'Cell Transformation, Neoplastic|Cocarcinogenesis|Computer Simulation|Genetic Predisposition to Disease|Humans|Incidence|Markov Chains|Models, Genetic|Models, Statistical|Pancreatic Neoplasms|Risk Assessment|United States', 'Journal Article', '10.1371/journal.pcbi.1005431', '28288156', 'Many cancers are understood to be the product of multiple somatic mutations or other rate-limiting events. Multistage clonal expansion (MSCE) models are a class of continuous-time Markov chain models that capture the multi-hit initiation-promotion-malignant-conversion hypothesis of carcinogenesis. These models have been used broadly to investigate the epidemiology of many cancers, assess the impact of carcinogen exposures on cancer risk, and evaluate the potential impact of cancer prevention and control strategies on cancer rates. Structural identifiability (the analysis of the maximum parametric information available for a model given perfectly measured data) of certain MSCE models has been previously investigated. However, structural identifiability is a theoretical property and does not address the limitations of real data. In this study, we use pancreatic cancer as a case study to examine the practical identifiability of the two-, three-, and four-stage clonal expansion models given age-specific cancer incidence data using a numerical profile-likelihood approach. We demonstrate that, in the case of the three- and four-stage models, several parameters that are theoretically structurally identifiable, are, in practice, unidentifiable. This result means that key parameters such as the intermediate cell mutation rates are not individually identifiable from the data and that estimation of those parameters, even if structurally identifiable, will not be stable. We also show that products of these practically unidentifiable parameters are practically identifiable, and, based on this, we propose new reparameterizations of the model hazards that resolve the parameter estimation problems. Our results highlight the importance of identifiability to the interpretation of model parameter estimates.'),
(88332, 2017, 'plos', 'Modelling T cell proliferation: Dynamics heterogeneity depending on cell differentiation, age, and genetic background', 'Vibert, Julien|Thomas-Vaslin, Véronique', 'Sorbonne Universités, UPMC Univ Paris 06, INSERM, Immunology-Immunopathology-Immunotherapy (I3) UMRS959, Paris, France.|Sorbonne Universités, UPMC Univ Paris 06, INSERM, Immunology-Immunopathology-Immunotherapy (I3) UMRS959, Paris, France.', 'France|France', 0, 'Animals|Cell Differentiation|Cell Proliferation|Cells, Cultured|Cellular Senescence|Computer Simulation|Genetic Background|Immunogenetic Phenomena|Mice|Models, Genetic|Models, Immunological|T-Lymphocytes', 'Journal Article', '10.1371/journal.pcbi.1005417', '28288157', 'Cell proliferation is the common characteristic of all biological systems. The immune system insures the maintenance of body integrity on the basis of a continuous production of diversified T lymphocytes in the thymus. This involves processes of proliferation, differentiation, selection, death and migration of lymphocytes to peripheral tissues, where proliferation also occurs upon antigen recognition. Quantification of cell proliferation dynamics requires specific experimental methods and mathematical modelling. Here, we assess the impact of genetics and aging on the immune system by investigating the dynamics of proliferation of T lymphocytes across their differentiation through thymus and spleen in mice. Our investigation is based on single-cell multicolour flow cytometry analysis revealing the active incorporation of a thymidine analogue during S phase after pulse-chase-pulse experiments in vivo, versus cell DNA content. A generic mathematical model of state transition simulates through Ordinary Differential Equations (ODEs) the evolution of single cell behaviour during various durations of labelling. It allows us to fit our data, to deduce proliferation rates and estimate cell cycle durations in sub-populations. Our model is simple and flexible and is validated with other durations of pulse/chase experiments. Our results reveal that T cell proliferation is highly heterogeneous but with a specific signature that depends upon genetic origins, is specific to cell differentiation stages in thymus and spleen and is altered with age. In conclusion, our model allows us to infer proliferation rates and cell cycle phase durations from complex experimental 5-ethynyl-2-deoxyuridine (EdU) data, revealing T cell proliferation heterogeneity and specific signatures.'),
(88333, 2017, 'plos', 'Stimulus-specific adaptation in a recurrent network model of primary auditory cortex', 'Yarden, Tohar S|Nelken, Israel', 'Department of Neurobiology, the Alexander Silberman Institute of Life Sciences and the Edmond and Lily Safra Center for Brain Sciences, Hebrew University, Jerusalem, Israel.|Department of Neurobiology, the Alexander Silberman Institute of Life Sciences and the Edmond and Lily Safra Center for Brain Sciences, Hebrew University, Jerusalem, Israel.', 'Israel|Israel', 17, 'Acoustic Stimulation|Adaptation, Physiological|Animals|Auditory Cortex|Computer Simulation|Feedback, Physiological|Humans|Models, Neurological|Nerve Net|Neural Inhibition|Neuronal Plasticity', 'Journal Article', '10.1371/journal.pcbi.1005437', '28288158', 'Stimulus-specific adaptation (SSA) occurs when neurons decrease their responses to frequently-presented (standard) stimuli but not, or not as much, to other, rare (deviant) stimuli. SSA is present in all mammalian species in which it has been tested as well as in birds. SSA confers short-term memory to neuronal responses, and may lie upstream of the generation of mismatch negativity (MMN), an important human event-related potential. Previously published models of SSA mostly rely on synaptic depression of the feedforward, thalamocortical input. Here we study SSA in a recurrent neural network model of primary auditory cortex. When the recurrent, intracortical synapses display synaptic depression, the network generates population spikes (PSs). SSA occurs in this network when deviants elicit a PS but standards do not, and we demarcate the regions in parameter space that allow SSA. While SSA based on PSs does not require feedforward depression, we identify feedforward depression as a mechanism for expanding the range of parameters that support SSA. We provide predictions for experiments that could help differentiate between SSA due to synaptic depression of feedforward connections and SSA due to synaptic depression of recurrent connections. Similar to experimental data, the magnitude of SSA in the model depends on the frequency difference between deviant and standard, probability of the deviant, inter-stimulus interval and input amplitude. In contrast to models based on feedforward depression, our model shows true deviance sensitivity as found in experiments.'),
(88334, 2017, 'plos', 'Fast online deconvolution of calcium imaging data', 'Friedrich, Johannes|Zhou, Pengcheng|Paninski, Liam', 'Department of Statistics, Grossman Center for the Statistics of Mind, and Center for Theoretical Neuroscience, Columbia University, New York, New York, United States of America.|Department of Statistics, Grossman Center for the Statistics of Mind, and Center for Theoretical Neuroscience, Columbia University, New York, New York, United States of America.|Department of Statistics, Grossman Center for the Statistics of Mind, and Center for Theoretical Neuroscience, Columbia University, New York, New York, United States of America.', 'United States|United States|United States', 57, 'Animals|Calcium|Calcium Signaling|Data Interpretation, Statistical|Humans|Image Interpretation, Computer-Assisted|Microscopy, Fluorescence|Molecular Imaging|Neurons|Reproducibility of Results|Sensitivity and Specificity|Voltage-Sensitive Dye Imaging', 'Journal Article', '10.1371/journal.pcbi.1005423', '28291787', 'Fluorescent calcium indicators are a popular means for observing the spiking activity of large neuronal populations, but extracting the activity of each neuron from raw fluorescence calcium imaging data is a nontrivial problem. We present a fast online active set method to solve this sparse non-negative deconvolution problem. Importantly, the algorithm 3progresses through each time series sequentially from beginning to end, thus enabling real-time online estimation of neural activity during the imaging session. Our algorithm is a generalization of the pool adjacent violators algorithm (PAVA) for isotonic regression and inherits its linear-time computational complexity. We gain remarkable increases in processing speed: more than one order of magnitude compared to currently employed state of the art convex solvers relying on interior point methods. Unlike these approaches, our method can exploit warm starts, therefore optimizing model hyperparameters only requires a handful of passes through the data. A minor modification can further improve the quality of activity inference by imposing a constraint on the minimum spike size. The algorithm enables real-time simultaneous deconvolution of O(105) traces of whole-brain larval zebrafish imaging data on a laptop.'),
(88335, 2017, 'plos', 'A thermodynamically consistent model of the post-translational Kai circadian clock', 'Paijmans, Joris|Lubensky, David K|Ten Wolde, Pieter Rein', 'FOM Institute AMOLF, Amsterdam, The Netherlands.|Department of Physics, University of Michigan, Ann Arbor, Michigan, United States of America.|FOM Institute AMOLF, Amsterdam, The Netherlands.', 'Netherlands|United States|Netherlands', 0, 'Bacterial Proteins|Circadian Clocks|Circadian Rhythm Signaling Peptides and Proteins|Computer Simulation|Models, Biological|Models, Chemical|Protein Processing, Post-Translational|Synechococcus|Thermodynamics', 'Journal Article', '10.1371/journal.pcbi.1005415', '28296888', 'The principal pacemaker of the circadian clock of the cyanobacterium S. elongatus is a protein phosphorylation cycle consisting of three proteins, KaiA, KaiB and KaiC. KaiC forms a homohexamer, with each monomer consisting of two domains, CI and CII. Both domains can bind and hydrolyze ATP, but only the CII domain can be phosphorylated, at two residues, in a well-defined sequence. While this system has been studied extensively, how the clock is driven thermodynamically has remained elusive. Inspired by recent experimental observations and building on ideas from previous mathematical models, we present a new, thermodynamically consistent, statistical-mechanical model of the clock. At its heart are two main ideas: i) ATP hydrolysis in the CI domain provides the thermodynamic driving force for the clock, switching KaiC between an active conformational state in which its phosphorylation level tends to rise and an inactive one in which it tends to fall, ii) phosphorylation of the CII domain provides the timer for the hydrolysis in the CI domain. The model also naturally explains how KaiA, by acting as a nucleotide exchange factor, can stimulate phosphorylation of KaiC, and how the differential affinity of KaiA for the different KaiC phosphoforms generates the characteristic temporal order of KaiC phosphorylation. As the phosphorylation level in the CII domain rises, the release of ADP from CI slows down, making the inactive conformational state of KaiC more stable. In the inactive state, KaiC binds KaiB, which not only stabilizes this state further, but also leads to the sequestration of KaiA, and hence to KaiC dephosphorylation. Using a dedicated kinetic Monte Carlo algorithm, which makes it possible to efficiently simulate this system consisting of more than a billion reactions, we show that the model can describe a wealth of experimental data.'),
(88336, 2017, 'plos', 'Classification and adaptive behavior prediction of children with autism spectrum disorder based upon multivariate data analysis of markers of oxidative stress and DNA methylation', 'Howsmon, Daniel P|Kruger, Uwe|Melnyk, Stepan|James, S Jill|Hahn, Juergen', 'Department of Chemical and Biological Engineering, Rensselaer Polytechnic Institute, Troy, New York, United States of America.|Department of Biomedical Engineering, Rensselaer Polytechnic Institute, Troy, New York, United States of America.|Department of Pediatrics, University of Arkansas for Medical Sciences, Little Rock, Arkansas, United States of America.|Department of Pediatrics, University of Arkansas for Medical Sciences, Little Rock, Arkansas, United States of America.|Department of Chemical and Biological Engineering, Rensselaer Polytechnic Institute, Troy, New York, United States of America.', 'United States|United States|United States|United States|United States', 0, 'Autism Spectrum Disorder|Biomarkers|Child|Child, Preschool|DNA Methylation|Data Interpretation, Statistical|Female|Folic Acid|Humans|Male|Multivariate Analysis|Oxidative Stress|Reproducibility of Results|Risk Factors|Sensitivity and Specificity', 'Journal Article', '10.1371/journal.pcbi.1005385', '28301476', 'The number of diagnosed cases of Autism Spectrum Disorders (ASD) has increased dramatically over the last four decades, however, there is still considerable debate regarding the underlying pathophysiology of ASD. This lack of biological knowledge restricts diagnoses to be made based on behavioral observations and psychometric tools. However, physiological measurements should support these behavioral diagnoses in the future in order to enable earlier and more accurate diagnoses. Stepping towards this goal of incorporating biochemical data into ASD diagnosis, this paper analyzes measurements of metabolite concentrations of the folate-dependent one-carbon metabolism and transulfuration pathways taken from blood samples of 83 participants with ASD and 76 age-matched neurotypical peers. Fisher Discriminant Analysis enables multivariate classification of the participants as on the spectrum or neurotypical which results in 96.1% of all neurotypical participants being correctly identified as such while still correctly identifying 97.6% of the ASD cohort. Furthermore, kernel partial least squares is used to predict adaptive behavior, as measured by the Vineland Adaptive Behavior Composite score, where measurement of five metabolites of the pathways was sufficient to predict the Vineland score with an R2 of 0.45 after cross-validation. This level of accuracy for classification as well as severity prediction far exceeds any other approach in this field and is a strong indicator that the metabolites under consideration are strongly correlated with an ASD diagnosis but also that the statistical analysis used here offers tremendous potential for extracting important information from complex biochemical data sets.'),
(88337, 2017, 'plos', 'Fragility of foot process morphology in kidney podocytes arises from chaotic spatial propagation of cytoskeletal instability', 'Falkenberg, Cibele V|Azeloglu, Evren U|Stothers, Mark|Deerinck, Thomas J|Chen, Yibang|He, John C|Ellisman, Mark H|Hone, James C|Iyengar, Ravi|Loew, Leslie M', 'R. D. Berlin Center for Cell Analysis & Modeling, U. Connecticut School of Medicine, Farmington, CT, United States of America.|Department of Pharmacological Sciences, and Division of Nephrology, Icahn School of Medicine at Mount Sinai, New York, NY, United States of America.|Department of Mechanical Engineering, Columbia University, New York, NY, United States of America.|National Center for Microscopy and Imaging Research, UCSD, San Diego, CA, United States of America.|Department of Pharmacological Sciences, and Division of Nephrology, Icahn School of Medicine at Mount Sinai, New York, NY, United States of America.|Department of Pharmacological Sciences, and Division of Nephrology, Icahn School of Medicine at Mount Sinai, New York, NY, United States of America.|National Center for Microscopy and Imaging Research, UCSD, San Diego, CA, United States of America.|Department of Mechanical Engineering, Columbia University, New York, NY, United States of America.|Department of Pharmacological Sciences, and Division of Nephrology, Icahn School of Medicine at Mount Sinai, New York, NY, United States of America.|R. D. Berlin Center for Cell Analysis & Modeling, U. Connecticut School of Medicine, Farmington, CT, United States of America.', 'United States|United States|United States|United States|United States|United States|United States|Un', 8, 'Actin Cytoskeleton|Cell Polarity|Cell Size|Cell Surface Extensions|Cells, Cultured|Computer Simulation|Humans|Models, Biological|Nonlinear Dynamics|Podocytes|Spatio-Temporal Analysis', 'Journal Article', '10.1371/journal.pcbi.1005433', '28301477', 'Kidney podocytes function depends on fingerlike projections (foot processes) that interdigitate with those from neighboring cells to form the glomerular filtration barrier. The integrity of the barrier depends on spatial control of dynamics of actin cytoskeleton in the foot processes. We determined how imbalances in regulation of actin cytoskeletal dynamics could result in pathological morphology. We obtained 3-D electron microscopy images of podocytes and used quantitative features to build dynamical models to investigate how regulation of actin dynamics within foot processes controls local morphology. We find that imbalances in regulation of actin bundling lead to chaotic spatial patterns that could impair the foot process morphology. Simulation results are consistent with experimental observations for cytoskeletal reconfiguration through dysregulated RhoA or Rac1, and they predict compensatory mechanisms for biochemical stability. We conclude that podocyte morphology, optimized for filtration, is intrinsically fragile, whereby local transient biochemical imbalances may lead to permanent morphological changes associated with pathophysiology.'),
(88338, 2017, 'plos', 'Reconstruction and signal propagation analysis of the Syk signaling network in breast cancer cells', 'Naldi, Aurélien|Larive, Romain M|Czerwinska, Urszula|Urbach, Serge|Montcourrier, Philippe|Roy, Christian|Solassol, Jérôme|Freiss, Gilles|Coopman, Peter J|Radulescu, Ovidiu', 'DIMNP, Dynamique des Interactions Membranaires Normales et Pathologiques, CNRS, UMR5235, Montpellier, France.|Université de Montpellier, Montpellier, France.|DIMNP, Dynamique des Interactions Membranaires Normales et Pathologiques, CNRS, UMR5235, Montpellier, France.|Université de Montpellier, Montpellier, France.|Université de Montpellier, Montpellier, France.|DIMNP, Dynamique des Interactions Membranaires Normales et Pathologiques, CNRS, UMR5235, Montpellier, France.|Université de Montpellier, Montpellier, France.|Université de Montpellier, Montpellier, France.|Université de Montpellier, Montpellier, France.|DIMNP, Dynamique des Interactions Membranaires Normales et Pathologiques, CNRS, UMR5235, Montpellier, France.', 'France|France|France|France|France|France|France|France|France|France', 0, 'Breast Neoplasms|Cell Line, Tumor|Computer Simulation|Female|Gene Expression Profiling|Gene Expression Regulation, Neoplastic|Humans|MCF-7 Cells|Models, Biological|Neoplasm Proteins|Signal Transduction|Syk Kinase', 'Journal Article', '10.1371/journal.pcbi.1005432', '28306714', 'The ability to build in-depth cell signaling networks from vast experimental data is a key objective of computational biology. The spleen tyrosine kinase (Syk) protein, a well-characterized key player in immune cell signaling, was surprisingly first shown by our group to exhibit an onco-suppressive function in mammary epithelial cells and corroborated by many other studies, but the molecular mechanisms of this function remain largely unsolved. Based on existing proteomic data, we report here the generation of an interaction-based network of signaling pathways controlled by Syk in breast cancer cells. Pathway enrichment of the Syk targets previously identified by quantitative phospho-proteomics indicated that Syk is engaged in cell adhesion, motility, growth and death. Using the components and interactions of these pathways, we bootstrapped the reconstruction of a comprehensive network covering Syk signaling in breast cancer cells. To generate in silico hypotheses on Syk signaling propagation, we developed a method allowing to rank paths between Syk and its targets. We first annotated the network according to experimental datasets. We then combined shortest path computation with random walk processes to estimate the importance of individual interactions and selected biologically relevant pathways in the network. Molecular and cell biology experiments allowed to distinguish candidate mechanisms that underlie the impact of Syk on the regulation of cortactin and ezrin, both involved in actin-mediated cell adhesion and motility. The Syk network was further completed with the results of our biological validation experiments. The resulting Syk signaling sub-networks can be explored via an online visualization platform.'),
(88339, 2017, 'plos', 'Correction: A Molecular Clock Infers Heterogeneous Tissue Age Among Patients with Barretts Esophagus', 'PLOS Computational Biology Staff', 'DIMNP, Dynamique des Interactions Membranaires Normales et Pathologiques, CNRS, UMR5235, Montpellier, France.', 'France', 0, '-', 'Published Erratum', '10.1371/journal.pcbi.1005439', '28306731', '[This corrects the article DOI: 10.1371/journal.pcbi.1004919.].'),
(88340, 2017, 'plos', 'A general model for metabolic scaling in self-similar asymmetric networks', 'Brummer, Alexander Byers|Savage, Van M|Enquist, Brian J', 'Department of Physics, University of Arizona, Tucson, Arizona, United States of America.|Department of Biomathematics, UCLA David Geffen School of Medicine, Los Angeles, California, United States of America.|Department of Ecology and Evolutionary Biology, University of Arizona, Tucson, Arizona, United States of America.', 'United States|United States|United States', 13, 'Body Size|Computer Simulation|Energy Metabolism|Metabolic Flux Analysis|Metabolic Networks and Pathways|Models, Biological|Signal Transduction', 'Journal Article', '10.1371/journal.pcbi.1005394', '28319153', 'How a particular attribute of an organism changes or scales with its body size is known as an allometry. Biological allometries, such as metabolic scaling, have been hypothesized to result from selection to maximize how vascular networks fill space yet minimize internal transport distances and resistances. The West, Brown, Enquist (WBE) model argues that these two principles (space-filling and energy minimization) are (i) general principles underlying the evolution of the diversity of biological networks across plants and animals and (ii) can be used to predict how the resulting geometry of biological networks then governs their allometric scaling. Perhaps the most central biological allometry is how metabolic rate scales with body size. A core assumption of the WBE model is that networks are symmetric with respect to their geometric properties. That is, any two given branches within the same generation in the network are assumed to have identical lengths and radii. However, biological networks are rarely if ever symmetric. An open question is: Does incorporating asymmetric branching change or influence the predictions of the WBE model? We derive a general network model that relaxes the symmetric assumption and define two classes of asymmetrically bifurcating networks. We show that asymmetric branching can be incorporated into the WBE model. This asymmetric version of the WBE model results in several theoretical predictions for the structure, physiology, and metabolism of organisms, specifically in the case for the cardiovascular system. We show how network asymmetry can now be incorporated in the many allometric scaling relationships via total network volume. Most importantly, we show that the 3/4 metabolic scaling exponent from Kleibers Law can still be attained within many asymmetric networks.'),
(88341, 2017, 'plos', 'A computational analysis of in vivo VEGFR activation by multiple co-expressed ligands', 'Clegg, Lindsay E|Mac Gabhann, Feilim', 'Institute for Computational Medicine, Institute for NanoBioTechnology, and Department of Biomedical Engineering, Johns Hopkins University, Baltimore, Maryland, United States of America.|Institute for Computational Medicine, Institute for NanoBioTechnology, and Department of Biomedical Engineering, Johns Hopkins University, Baltimore, Maryland, United States of America.', 'United States|United States', 0, 'Computer Simulation|Extracellular Matrix Proteins|Humans|Membrane Proteins|Models, Chemical|Protein Binding|Protein Interaction Mapping|Tissue Distribution|Vascular Endothelial Growth Factor A|Vascular Endothelial Growth Factor Receptor-1|Vascular Endothelial Growth Factor Receptor-2', 'Journal Article', '10.1371/journal.pcbi.1005445', '28319199', 'The splice isoforms of vascular endothelial growth A (VEGF) each have different affinities for the extracellular matrix (ECM) and the coreceptor NRP1, which leads to distinct vascular phenotypes in model systems expressing only a single VEGF isoform. ECM-immobilized VEGF can bind to and activate VEGF receptor 2 (VEGFR2) directly, with a different pattern of site-specific phosphorylation than diffusible VEGF. To date, the way in which ECM binding alters the distribution of isoforms of VEGF and of the related placental growth factor (PlGF) in the body and resulting angiogenic signaling is not well-understood. Here, we extend our previous validated cell-level computational model of VEGFR2 ligation, intracellular trafficking, and site-specific phosphorylation, which captured differences in signaling by soluble and immobilized VEGF, to a multi-scale whole-body framework. This computational systems pharmacology model captures the ability of the ECM to regulate isoform-specific growth factor distribution distinctly for VEGF and PlGF, and to buffer free VEGF and PlGF levels in tissue. We show that binding of immobilized growth factor to VEGF receptors, both on endothelial cells and soluble VEGFR1, is likely important to signaling in vivo. Additionally, our model predicts that VEGF isoform-specific properties lead to distinct profiles of VEGFR1 and VEGFR2 binding and VEGFR2 site-specific phosphorylation in vivo, mediated by Neuropilin-1. These predicted signaling changes mirror those observed in murine systems expressing single VEGF isoforms. Simulations predict that, contrary to the ligand-shifting hypothesis, VEGF and PlGF do not compete for receptor binding at physiological concentrations, though PlGF is predicted to slightly increase VEGFR2 phosphorylation when over-expressed by 10-fold. These results are critical to design of appropriate therapeutic strategies to control VEGF availability and signaling in regenerative medicine applications.'),
(88342, 2017, 'plos', 'Structurally detailed coarse-grained model for Sec-facilitated co-translational protein translocation and membrane integration', 'Niesen, Michiel J M|Wang, Connie Y|Van Lehn, Reid C|Miller, Thomas F', 'Division of Chemistry and Chemical Engineering, California Institute of Technology, Pasadena, California, United States of America.|Division of Chemistry and Chemical Engineering, California Institute of Technology, Pasadena, California, United States of America.|Division of Chemistry and Chemical Engineering, California Institute of Technology, Pasadena, California, United States of America.|Division of Chemistry and Chemical Engineering, California Institute of Technology, Pasadena, California, United States of America.', 'United States|United States|United States|United States', 9, 'Binding Sites|Cell Membrane|Lipid Bilayers|Models, Chemical|Molecular Dynamics Simulation|Motion|Protein Binding|Protein Conformation|Protein Folding|Protein Translocation Systems|Protein Transport|Ribosomes|SEC Translocation Channels', 'Journal Article', '10.1371/journal.pcbi.1005427', '28328943', 'We present a coarse-grained simulation model that is capable of simulating the minute-timescale dynamics of protein translocation and membrane integration via the Sec translocon, while retaining sufficient chemical and structural detail to capture many of the sequence-specific interactions that drive these processes. The model includes accurate geometric representations of the ribosome and Sec translocon, obtained directly from experimental structures, and interactions parameterized from nearly 200 xcexbcs of residue-based coarse-grained molecular dynamics simulations. A protocol for mapping amino-acid sequences to coarse-grained beads enables the direct simulation of trajectories for the co-translational insertion of arbitrary polypeptide sequences into the Sec translocon. The model reproduces experimentally observed features of membrane protein integration, including the efficiency with which polypeptide domains integrate into the membrane, the variation in integration efficiency upon single amino-acid mutations, and the orientation of transmembrane domains. The central advantage of the model is that it connects sequence-level protein features to biological observables and timescales, enabling direct simulation for the mechanistic analysis of co-translational integration and for the engineering of membrane proteins with enhanced membrane integration efficiency.'),
(88343, 2017, 'plos', 'Navigating in foldonia: Using accelerated molecular dynamics to explore stability, unfolding and self-healing of the xcexb2-solenoid structure formed by a silk-like polypeptide', 'Zhao, Binwu|Cohen Stuart, Martien A|Hall, Carol K', 'Department of Chemical and Biomolecular Engineering, North Carolina State University, Raleigh, North Carolina, United States.|Laboratory of Physical Chemistry & Colloid Science, Wageningen University, NL, Wageningen, The Netherlands.|Department of Chemical and Biomolecular Engineering, North Carolina State University, Raleigh, North Carolina, United States.', 'United States|Netherlands|United States', 0, 'Models, Chemical|Molecular Dynamics Simulation|Peptides|Protein Conformation|Protein Domains|Protein Folding|Protein Unfolding|Silk', 'Journal Article', '10.1371/journal.pcbi.1005446', '28329017', 'The xcexb2 roll molecules with sequence (GAGAGAGQ)10 stack via hydrogen bonding to form fibrils which have been themselves been used to make viral capsids of DNA strands, supramolecular nanotapes and pH-responsive gels. Accelerated molecular dynamics (aMD) simulations are used to investigate the unfolding of a stack of two xcexb2 roll molecules, (GAGAGAGQ)10, to shed light on the folding mechanism by which silk-inspired polypeptides form fibrils and to identify the dominant forces that keep the silk-inspired polypeptide in a xcexb2 roll configuration. Our study shows that a molecule in a stack of two xcexb2 roll molecules unfolds in a step-wise fashion mainly from the C terminal. The bottom template is found to play an important role in stabilizing the xcexb2 roll structure of the molecule on top by strengthening the hydrogen bonds in the layer that it contacts. Vertical hydrogen bonds within the xcexb2 roll structure are considerably weaker than lateral hydrogen bonds, signifying the importance of lateral hydrogen bonds in stabilizing the xcexb2 roll structure. Finally, an intermediate structure was found containing a xcexb2 hairpin and an anti-parallel xcexb2 sheet consisting of strands from the top and bottom molecules, revealing the self-healing ability of the xcexb2 roll stack.'),
(88344, 2017, 'plos', 'Ten simple rules for forming a scientific professional society', 'Gaëta, Bruno A|De Las Rivas, Javier|Horton, Paul|Meysman, Pieter|Mulder, Nicola|Romano, Paolo|Welch, Lonnie', 'School of Computer Science and Engineering, The University of New South Wales, Sydney, Australia.|Bioinformatics and Functional Genomics Group, Cancer Research Center (CiC-IBMCC, CSIC/USAL/IBSAL), Salamanca, Spain.|Artificial Intelligence Research Center, AIST, Tokyo, Japan.|Biomedical Informatics Research Center Antwerp (biomina), University of Antwerp/Antwerp University Hospital, Antwerp, Belgium.|Computational Biology Division, Department of Integrative Biomedical Sciences, IDM, Faculty of Health Sciences, University of Cape Town, Cape Town, South Africa.|Bioinformatics group, Proteomics laboratory, IRCCS AOU San Martino IST, Genoa, Italy.|School of Electrical Engineering and Computer Science, Ohio University, Athens, Ohio, United States of America.', 'Australia|Spain|Japan|Belgium|South Africa|Italy|United States', 2, 'Computer Security|Datasets as Topic|Ethics, Professional|Guidelines as Topic|Privacy|Societies, Scientific', 'Editorial', '10.1371/journal.pcbi.1005226', '28333920', '-');
INSERT INTO `papers` (`id`, `ano`, `journal`, `titulo`, `autores`, `afiliacao`, `pais`, `citacoes`, `palavra_chave`, `categorias`, `doi`, `pubmed`, `abstract`) VALUES
(88345, 2017, 'plos', 'Bioenergetics-based modeling of Plasmodium falciparum metabolism reveals its essential genes, nutritional requirements, and thermodynamic bottlenecks', 'Chiappino-Pepe, Anush|Tymoshenko, Stepan|Ataman, Meriç|Soldati-Favre, Dominique|Hatzimanikatis, Vassily', 'Laboratory of Computational Systems Biotechnology, École Polytechnique Fédérale de Lausanne, EPFL, Lausanne, Switzerland.|Laboratory of Computational Systems Biotechnology, École Polytechnique Fédérale de Lausanne, EPFL, Lausanne, Switzerland.|Laboratory of Computational Systems Biotechnology, École Polytechnique Fédérale de Lausanne, EPFL, Lausanne, Switzerland.|Department of Microbiology and Molecular Medicine, Faculty of Medicine, University of Geneva, CMU, Geneva, Switzerland.|Laboratory of Computational Systems Biotechnology, École Polytechnique Fédérale de Lausanne, EPFL, Lausanne, Switzerland.', 'Switzerland|Switzerland|Switzerland|Switzerland|Switzerland', 8, 'Computer Simulation|Energy Metabolism|Genes, Essential|Metabolic Flux Analysis|Metabolome|Models, Biological|Nutritional Requirements|Plasmodium falciparum|Protozoan Proteins|Thermodynamics', 'Journal Article', '10.1371/journal.pcbi.1005397', '28333921', 'Novel antimalarial therapies are urgently needed for the fight against drug-resistant parasites. The metabolism of malaria parasites in infected cells is an attractive source of drug targets but is rather complex. Computational methods can handle this complexity and allow integrative analyses of cell metabolism. In this study, we present a genome-scale metabolic model (iPfa) of the deadliest malaria parasite, Plasmodium falciparum, and its thermodynamics-based flux analysis (TFA). Using previous absolute concentration data of the intraerythrocytic parasite, we applied TFA to iPfa and predicted up to 63 essential genes and 26 essential pairs of genes. Of the 63 genes, 35 have been experimentally validated and reported in the literature, and 28 have not been experimentally tested and include previously hypothesized or novel predictions of essential metabolic capabilities. Without metabolomics data, four of the genes would have been incorrectly predicted to be non-essential. TFA also indicated that substrate channeling should exist in two metabolic pathways to ensure the thermodynamic feasibility of the flux. Finally, analysis of the metabolic capabilities of P. falciparum led to the identification of both the minimal nutritional requirements and the genes that can become indispensable upon substrate inaccessibility. This model provides novel insight into the metabolic needs and capabilities of the malaria parasite and highlights metabolites and pathways that should be measured and characterized to identify potential thermodynamic bottlenecks and substrate channeling. The hypotheses presented seek to guide experimental studies to facilitate a better understanding of the parasite metabolism and the identification of targets for more efficient intervention.'),
(88346, 2017, 'plos', 'Network perturbation by recurrent regulatory variants in cancer', 'Jang, Kiwon|Kim, Kwoneel|Cho, Ara|Lee, Insuk|Choi, Jung Kyoon', 'Department of Bio and Brain Engineering, KAIST, Daejeon, Republic of Korea.|Department of Bio and Brain Engineering, KAIST, Daejeon, Republic of Korea.|Department of Biotechnology, College of Life Science and Biotechnology, Yonsei University, Seoul, Republic of Korea.|Department of Biotechnology, College of Life Science and Biotechnology, Yonsei University, Seoul, Republic of Korea.|Department of Bio and Brain Engineering, KAIST, Daejeon, Republic of Korea.', '-|-|-|-|-', 0, 'Animals|Computer Simulation|Gene Expression Regulation, Neoplastic|Genes, Neoplasm|Genetic Variation|Humans|Models, Genetic|Neoplasm Proteins|Neoplasms|Regulatory Elements, Transcriptional|Signal Transduction', 'Journal Article', '10.1371/journal.pcbi.1005449', '28333928', 'Cancer driving genes have been identified as recurrently affected by variants that alter protein-coding sequences. However, a majority of cancer variants arise in noncoding regions, and some of them are thought to play a critical role through transcriptional perturbation. Here we identified putative transcriptional driver genes based on combinatorial variant recurrence in cis-regulatory regions. The identified genes showed high connectivity in the cancer type-specific transcription regulatory network, with high outdegree and many downstream genes, highlighting their causative role during tumorigenesis. In the protein interactome, the identified transcriptional drivers were not as highly connected as coding driver genes but appeared to form a network module centered on the coding drivers. The coding and regulatory variants associated via these interactions between the coding and transcriptional drivers showed exclusive and complementary occurrence patterns across tumor samples. Transcriptional cancer drivers may act through an extensive perturbation of the regulatory network and by altering protein network modules through interactions with coding driver genes.'),
(88347, 2017, 'plos', 'PBMDA: A novel and effective path-based computational model for miRNA-disease association prediction', 'You, Zhu-Hong|Huang, Zhi-An|Zhu, Zexuan|Yan, Gui-Ying|Li, Zheng-Wei|Wen, Zhenkun|Chen, Xing', 'Xinjiang Technical Institute of Physics and Chemistry, Chinese Academy of Science, ürümqi, China.|College of Computer Science and Software Engineering, Shenzhen University, Shenzhen, China.|College of Computer Science and Software Engineering, Shenzhen University, Shenzhen, China.|Academy of Mathematics and Systems Science, Chinese Academy of Sciences, Beijing, China.|School of Computer Science and Technology, China University of Mining and Technology, Xuzhou, China.|College of Computer Science and Software Engineering, Shenzhen University, Shenzhen, China.|School of Information and Control Engineering, China University of Mining and Technology, Xuzhou, China.', 'China|China|China|China|China|China|China', 170, 'Biomarkers, Tumor|Computer Simulation|Genetic Association Studies|Genetic Predisposition to Disease|Humans|MicroRNAs|Models, Genetic|Models, Statistical|Neoplasms|Prevalence|Prognosis|Risk Assessment|Risk Factors|Signal Transduction', 'Journal Article', '10.1371/journal.pcbi.1005455', '28339468', 'In the recent few years, an increasing number of studies have shown that microRNAs (miRNAs) play critical roles in many fundamental and important biological processes. As one of pathogenetic factors, the molecular mechanisms underlying human complex diseases still have not been completely understood from the perspective of miRNA. Predicting potential miRNA-disease associations makes important contributions to understanding the pathogenesis of diseases, developing new drugs, and formulating individualized diagnosis and treatment for diverse human complex diseases. Instead of only depending on expensive and time-consuming biological experiments, computational prediction models are effective by predicting potential miRNA-disease associations, prioritizing candidate miRNAs for the investigated diseases, and selecting those miRNAs with higher association probabilities for further experimental validation. In this study, Path-Based MiRNA-Disease Association (PBMDA) prediction model was proposed by integrating known human miRNA-disease associations, miRNA functional similarity, disease semantic similarity, and Gaussian interaction profile kernel similarity for miRNAs and diseases. This model constructed a heterogeneous graph consisting of three interlinked sub-graphs and further adopted depth-first search algorithm to infer potential miRNA-disease associations. As a result, PBMDA achieved reliable performance in the frameworks of both local and global LOOCV (AUCs of 0.8341 and 0.9169, respectively) and 5-fold cross validation (average AUC of 0.9172). In the cases studies of three important human diseases, 88% (Esophageal Neoplasms), 88% (Kidney Neoplasms) and 90% (Colon Neoplasms) of top-50 predicted miRNAs have been manually confirmed by previous experimental reports from literatures. Through the comparison performance between PBMDA and other previous models in case studies, the reliable performance also demonstrates that PBMDA could serve as a powerful computational tool to accelerate the identification of disease-miRNA associations.'),
(88348, 2017, 'plos', 'Geometry can provide long-range mechanical guidance for embryogenesis', 'Dicko, Mahamar|Saramito, Pierre|Blanchard, Guy B|Lye, Claire M|Sanson, Bénédicte|Étienne, Jocelyn', 'LJK, Univ. Grenoble Alpes, Grenoble, France.|LJK, Univ. Grenoble Alpes, Grenoble, France.|Dept. Physiology, Development and Neuroscience, Univ. Cambridge, Cambridge, United Kingdom.|Dept. Physiology, Development and Neuroscience, Univ. Cambridge, Cambridge, United Kingdom.|Dept. Physiology, Development and Neuroscience, Univ. Cambridge, Cambridge, United Kingdom.|LIPHY, Univ. Grenoble Alpes, Grenoble, France.', 'France|France|United Kingdom|United Kingdom|United Kingdom|France', 0, 'Actomyosin|Animals|Body Patterning|Computer Simulation|Drosophila|Embryo, Nonmammalian|Embryonic Development|Mechanotransduction, Cellular|Models, Biological|Molecular Motor Proteins|Stress, Mechanical', 'Journal Article', '10.1371/journal.pcbi.1005443', '28346461', 'Downstream of gene expression, effectors such as the actomyosin contractile machinery drive embryo morphogenesis. During Drosophila embryonic axis extension, actomyosin has a specific planar-polarised organisation, which is responsible for oriented cell intercalation. In addition to these cell rearrangements, cell shape changes also contribute to tissue deformation. While cell-autonomous dynamics are well described, understanding the tissue-scale behaviour challenges us to solve the corresponding mechanical problem at the scale of the whole embryo, since mechanical resistance of all neighbouring epithelia will feedback on individual cells. Here we propose a novel numerical approach to compute the whole-embryo dynamics of the actomyosin-rich apical epithelial surface. We input in the model specific patterns of actomyosin contractility, such as the planar-polarisation of actomyosin in defined ventro-lateral regions of the embryo. Tissue strain rates and displacements are then predicted over the whole embryo surface according to the global balance of stresses and the material behaviour of the epithelium. Epithelia are modelled using a rheological law that relates the rate of deformation to the local stresses and actomyosin anisotropic contractility. Predicted flow patterns are consistent with the cell flows observed when imaging Drosophila axis extension in toto, using light sheet microscopy. The agreement between model and experimental data indicates that the anisotropic contractility of planar-polarised actomyosin in the ventro-lateral germband tissue can directly cause the tissue-scale deformations of the whole embryo. The three-dimensional mechanical balance is dependent on the geometry of the embryo, whose curved surface is taken into account in the simulations. Importantly, we find that to reproduce experimental flows, the model requires the presence of the cephalic furrow, a fold located anteriorly of the extending tissues. The presence of this geometric feature, through the global mechanical balance, guides the flow and orients extension towards the posterior end.'),
(88349, 2017, 'plos', 'Systematic identification of phosphorylation-mediated protein interaction switches', 'Betts, Matthew J|Wichmann, Oliver|Utz, Mathias|Andre, Timon|Petsalaki, Evangelia|Minguez, Pablo|Parca, Luca|Roth, Frederick P|Gavin, Anne-Claude|Bork, Peer|Russell, Robert B', 'CellNetworks, Bioquant, University of Heidelberg, Im Neuenheimer Feld 267, Heidelberg, Germany.|CellNetworks, Bioquant, University of Heidelberg, Im Neuenheimer Feld 267, Heidelberg, Germany.|CellNetworks, Bioquant, University of Heidelberg, Im Neuenheimer Feld 267, Heidelberg, Germany.|CellNetworks, Bioquant, University of Heidelberg, Im Neuenheimer Feld 267, Heidelberg, Germany.|Lunenfeld-Tanenbaum Research Institute, Mount Sinai Hospital, 600 University Avenue, Toronto, Ontario, Canada.|European Molecular Biology Laboratory, Meyerhofstrasse 1, Heidelberg, Germany.|European Molecular Biology Laboratory, Meyerhofstrasse 1, Heidelberg, Germany.|Lunenfeld-Tanenbaum Research Institute, Mount Sinai Hospital, 600 University Avenue, Toronto, Ontario, Canada.|European Molecular Biology Laboratory, Meyerhofstrasse 1, Heidelberg, Germany.|European Molecular Biology Laboratory, Meyerhofstrasse 1, Heidelberg, Germany.|CellNetworks, Bioquant, University of Heidelberg, Im Neuenheimer Feld 267, Heidelberg, Germany.', 'Germany|Germany|Germany|Germany|Canada|Germany|Germany|Canada|Germany|Germany|Germany', 16, 'Binding Sites|Computer Simulation|Models, Chemical|Models, Molecular|Phosphorylation|Phosphotransferases|Protein Binding|Protein Conformation|Protein Interaction Mapping|Proteome|Sequence Analysis, Protein|Structure-Activity Relationship', 'Journal Article', '10.1371/journal.pcbi.1005462', '28346509', 'Proteomics techniques can identify thousands of phosphorylation sites in a single experiment, the majority of which are new and lack precise information about function or molecular mechanism. Here we present a fast method to predict potential phosphorylation switches by mapping phosphorylation sites to protein-protein interactions of known structure and analysing the properties of the protein interface. We predict 1024 sites that could potentially enable or disable particular interactions. We tested a selection of these switches and showed that phosphomimetic mutations indeed affect interactions. We estimate that there are likely thousands of phosphorylation mediated switches yet to be uncovered, even among existing phosphorylation datasets. The results suggest that phosphorylation sites on globular, as distinct from disordered, parts of the proteome frequently function as switches, which might be one of the ancient roles for kinase phosphorylation.'),
(88350, 2017, 'plos', 'Phylodynamics on local sexual contact networks', 'Rasmussen, David A|Kouyos, Roger|Günthard, Huldrych F|Stadler, Tanja', 'Department of Biosystems Science and Engineering, ETH Zürich, Basel, Switzerland.|Division of Infectious Diseases and Hospital Epidemiology, University Hospital Zürich, University of Zürich, Zürich, Switzerland.|Division of Infectious Diseases and Hospital Epidemiology, University Hospital Zürich, University of Zürich, Zürich, Switzerland.|Department of Biosystems Science and Engineering, ETH Zürich, Basel, Switzerland.', 'Switzerland|Switzerland|Switzerland|Switzerland', 6, 'Biological Evolution|Computer Simulation|Disease Outbreaks|Genetic Variation|HIV Infections|HIV-1|Humans|Models, Statistical|Phylogeny|Prevalence|Sexual Partners|Switzerland', 'Journal Article', '10.1371/journal.pcbi.1005448', '28350852', 'Phylodynamic models are widely used in infectious disease epidemiology to infer the dynamics and structure of pathogen populations. However, these models generally assume that individual hosts contact one another at random, ignoring the fact that many pathogens spread through highly structured contact networks. We present a new framework for phylodynamics on local contact networks based on pairwise epidemiological models that track the status of pairs of nodes in the network rather than just individuals. Shifting our focus from individuals to pairs leads naturally to coalescent models that describe how lineages move through networks and the rate at which lineages coalesce. These pairwise coalescent models not only consider how network structure directly shapes pathogen phylogenies, but also how the relationship between phylogenies and contact networks changes depending on epidemic dynamics and the fraction of infected hosts sampled. By considering pathogen phylogenies in a probabilistic framework, these coalescent models can also be used to estimate the statistical properties of contact networks directly from phylogenies using likelihood-based inference. We use this framework to explore how much information phylogenies retain about the underlying structure of contact networks and to infer the structure of a sexual contact network underlying a large HIV-1 sub-epidemic in Switzerland.'),
(88351, 2017, 'plos', 'High GC content causes orphan proteins to be intrinsically disordered', 'Basile, Walter|Sachenkova, Oxana|Light, Sara|Elofsson, Arne', 'Science for Life Laboratory, Stockholm University, Solna, Sweden.|Science for Life Laboratory, Stockholm University, Solna, Sweden.|Science for Life Laboratory, Stockholm University, Solna, Sweden.|Science for Life Laboratory, Stockholm University, Solna, Sweden.', 'Sweden|Sweden|Sweden|Sweden', 0, 'Animals|Base Composition|Computational Biology|Databases, Protein|Drosophila Proteins|Evolution, Molecular|Gene Ontology|Intrinsically Disordered Proteins|Open Reading Frames|Phylogeny|Saccharomyces cerevisiae Proteins|Selection, Genetic|Structural Homology, Protein', 'Journal Article', '10.1371/journal.pcbi.1005375', '28355220', 'De novo creation of protein coding genes involves the formation of short ORFs from noncoding regions, some of these ORFs might then become fixed in the population. These orphan proteins need to, at the bare minimum, not cause serious harm to the organism, meaning that they should for instance not aggregate. Therefore, although the creation of short ORFs could be truly random, the fixation should be subjected to some selective pressure. The selective forces acting on orphan proteins have been elusive, and contradictory results have been reported. In Drosophila young proteins are more disordered than ancient ones, while the opposite trend is present in yeast. To the best of our knowledge no valid explanation for this difference has been proposed. To solve this riddle we studied structural properties and age of proteins in 187 eukaryotic organisms. We find that, with the exception of length, there are only small differences in the properties between proteins of different ages. However, when we take the GC content into account we noted that it could explain the opposite trends observed for orphans in yeast (low GC) and Drosophila (high GC). GC content is correlated with codons coding for disorder promoting amino acids. This leads us to propose that intrinsic disorder is not a strong determining factor for fixation of orphan proteins. Instead these proteins largely resemble random proteins given a particular GC level. During evolution the properties of a protein change faster than the GC level causing the relationship between disorder and GC to gradually weaken.'),
(88352, 2017, 'plos', 'A critical analysis of computational protein design with sparse residue interaction graphs', 'Jain, Swati|Jou, Jonathan D|Georgiev, Ivelin S|Donald, Bruce R', 'Computational Biology and Bioinformatics Program, Duke University, Durham, North Carolina, United States of America.|Department of Computer Science, Duke University, Durham, North Carolina, United States of America.|Department of Computer Science, Duke University, Durham, North Carolina, United States of America.|Department of Computer Science, Duke University, Durham, North Carolina, United States of America.', 'United States|United States|United States|United States', 0, 'Algorithms|Amino Acid Sequence|Animals|Computational Biology|Computer Graphics|Humans|Models, Molecular|Protein Conformation|Protein Engineering|Proteins|Software|Thermodynamics', 'Journal Article', '10.1371/journal.pcbi.1005346', '28358804', 'Protein design algorithms enumerate a combinatorial number of candidate structures to compute the Global Minimum Energy Conformation (GMEC). To efficiently find the GMEC, protein design algorithms must methodically reduce the conformational search space. By applying distance and energy cutoffs, the protein system to be designed can thus be represented using a sparse residue interaction graph, where the number of interacting residue pairs is less than all pairs of mutable residues, and the corresponding GMEC is called the sparse GMEC. However, ignoring some pairwise residue interactions can lead to a change in the energy, conformation, or sequence of the sparse GMEC vs. the original or the full GMEC. Despite the widespread use of sparse residue interaction graphs in protein design, the above mentioned effects of their use have not been previously analyzed. To analyze the costs and benefits of designing with sparse residue interaction graphs, we computed the GMECs for 136 different protein design problems both with and without distance and energy cutoffs, and compared their energies, conformations, and sequences. Our analysis shows that the differences between the GMECs depend critically on whether or not the design includes core, boundary, or surface residues. Moreover, neglecting long-range interactions can alter local interactions and introduce large sequence differences, both of which can result in significant structural and functional changes. Designs on proteins with experimentally measured thermostability show it is beneficial to compute both the full and the sparse GMEC accurately and efficiently. To this end, we show that a provable, ensemble-based algorithm can efficiently compute both GMECs by enumerating a small number of conformations, usually fewer than 1000. This provides a novel way to combine sparse residue interaction graphs with provable, ensemble-based algorithms to reap the benefits of sparse residue interaction graphs while avoiding their potential inaccuracies.'),
(88353, 2017, 'plos', 'Dysfunctions of the basal ganglia-cerebellar-thalamo-cortical system produce motor tics in Tourette syndrome', 'Caligiore, Daniele|Mannella, Francesco|Arbib, Michael A|Baldassarre, Gianluca', 'Laboratory of Computational Embodied Neuroscience, Institute of Cognitive Sciences and Technologies, National Research Council (CNR-ISTC-LOCEN), Roma, Italy.|Laboratory of Computational Embodied Neuroscience, Institute of Cognitive Sciences and Technologies, National Research Council (CNR-ISTC-LOCEN), Roma, Italy.|Neuroscience Program, USC Brain Project, Computer Science Department, University of Southern California, Los Angeles, California, United States of America.|Laboratory of Computational Embodied Neuroscience, Institute of Cognitive Sciences and Technologies, National Research Council (CNR-ISTC-LOCEN), Roma, Italy.', 'Italy|Italy|United States|Italy', 37, 'Basal Ganglia|Cerebellum|Computer Simulation|Humans|Models, Neurological|Motor Cortex|Nerve Net|Thalamus|Tics|Tourette Syndrome', 'Journal Article', '10.1371/journal.pcbi.1005395', '28358814', 'Motor tics are a cardinal feature of Tourette syndrome and are traditionally associated with an excess of striatal dopamine in the basal ganglia. Recent evidence increasingly supports a more articulated view where cerebellum and cortex, working closely in concert with basal ganglia, are also involved in tic production. Building on such evidence, this article proposes a computational model of the basal ganglia-cerebellar-thalamo-cortical system to study how motor tics are generated in Tourette syndrome. In particular, the model: (i) reproduces the main results of recent experiments about the involvement of the basal ganglia-cerebellar-thalamo-cortical system in tic generation, (ii) suggests an explanation of the system-level mechanisms underlying motor tic production: in this respect, the model predicts that the interplay between dopaminergic signal and cortical activity contributes to triggering the tic event and that the recently discovered basal ganglia-cerebellar anatomical pathway may support the involvement of the cerebellum in tic production, (iii) furnishes predictions on the amount of tics generated when striatal dopamine increases and when the cortex is externally stimulated. These predictions could be important in identifying new brain target areas for future therapies. Finally, the model represents the first computational attempt to study the role of the recently discovered basal ganglia-cerebellar anatomical links. Studying this non-cortex-mediated basal ganglia-cerebellar interaction could radically change our perspective about how these areas interact with each other and with the cortex. Overall, the model also shows the utility of casting Tourette syndrome within a system-level perspective rather than viewing it as related to the dysfunction of a single brain area.'),
(88354, 2017, 'plos', 'Migration of small ligands in globins: Xe diffusion in truncated hemoglobin N', 'Diamantis, Polydefkis|Unke, Oliver T|Meuwly, Markus', 'Department of Chemistry, University of Basel, Basel, Switzerland.|Department of Chemistry, University of Basel, Basel, Switzerland.|Department of Chemistry, University of Basel, Basel, Switzerland.', 'Switzerland|Switzerland|Switzerland', 3, 'Bacterial Proteins|Binding Sites|Computational Biology|Crystallography, X-Ray|Hemoglobins, Abnormal|Ligands|Models, Molecular|Molecular Dynamics Simulation|Mycobacterium tuberculosis|Protein Binding|Protein Conformation|Truncated Hemoglobins|Xenon', 'Journal Article', '10.1371/journal.pcbi.1005450', '28358830', 'In heme proteins, the efficient transport of ligands such as NO or O2 to the binding site is achieved via ligand migration networks. A quantitative assessment of ligand diffusion in these networks is thus essential for a better understanding of the function of these proteins. For this, Xe migration in truncated hemoglobin N (trHbN) of Mycobacterium Tuberculosis was studied using molecular dynamics simulations. Transitions between pockets of the migration network and intra-pocket relaxation occur on similar time scales (10 ps and 20 ps), consistent with low free energy barriers (1-2 kcal/mol). Depending on the pocket from where Xe enters a particular transition, the conformation of the side chains lining the transition region differs which highlights the coupling between ligand and protein degrees of freedom. Furthermore, comparison of transition probabilities shows that Xe migration in trHbN is a non-Markovian process. Memory effects arise due to protein rearrangements and coupled dynamics as Xe moves through it.'),
(88355, 2017, 'plos', 'Ten simple rules for responsible big data research', 'Zook, Matthew|Barocas, Solon|Boyd, Danah|Crawford, Kate|Keller, Emily|Gangadharan, Seeta Peña|Goodman, Alyssa|Hollander, Rachelle|Koenig, Barbara A|Metcalf, Jacob|Narayanan, Arvind|Nelson, Alondra|Pasquale, Frank', 'Department of Geography, University of Kentucky, Lexington, Kentucky, United States of America.|Microsoft Research, New York, New York, United States of America.|Microsoft Research, New York, New York, United States of America.|Microsoft Research, New York, New York, United States of America.|Data & Society, New York, New York, United States of America.|Department of Media and Communications, London School of Economics, London, United Kingdom.|Harvard-Smithsonian Center for Astrophysics, Harvard University, Cambridge, Massachusetts, United States of America.|Center for Engineering Ethics and Society, National Academy of Engineering, Washington, DC, United States of America.|Institute for Health Aging, University of California-San Francisco, San Francisco, California, United States of America.|Ethical Resolve, Santa Cruz, California, United States of America.|Department of Computer Science, Princeton University, Princeton, New Jersey, United States of America.|Department of Sociology, Columbia University, New York, New York, United States of America.|Carey School of Law, University of Maryland, Baltimore, Maryland, United States of America.', 'United States|United States|United States|United States|United States|United Kingdom|United States|U', 0, 'Computational Biology|Financial Management|Guidelines as Topic|Societies, Scientific', 'Editorial', '10.1371/journal.pcbi.1005399', '28358831', '-'),
(88356, 2017, 'plos', 'Ten simple rules for short and swift presentations', 'Lortie, Christopher J', 'Department of Biology, York University, Toronto, Ontario, Canada.', 'Canada', 7, 'Audiovisual Aids|Guidelines as Topic|Humans|Speech', 'Editorial', '10.1371/journal.pcbi.1005373', '28358832', '-'),
(88357, 2017, 'plos', 'Learning about and from others prudence, impatience or laziness: The computational bases of attitude alignment', 'Devaine, Marie|Daunizeau, Jean', 'Brain and Spine Institute (ICM), Paris, France.|Brain and Spine Institute (ICM), Paris, France.', 'France|France', 0, 'Adult|Attitude|Computer Simulation|Concept Formation|Decision Making|Female|Humans|Impulsive Behavior|Intention|Interpersonal Relations|Male|Models, Statistical|Social Behavior|Social Perception|Theory of Mind', 'Journal Article', '10.1371/journal.pcbi.1005422', '28358869', 'Peoples subjective attitude towards costs such as, e.g., risk, delay or effort are key determinants of inter-individual differences in goal-directed behaviour. Thus, the ability to learn about others prudent, impatient or lazy attitudes is likely to be critical for social interactions. Conversely, how adaptive such attitudes are in a given environment is highly uncertain. Thus, the brain may be tuned to garner information about how such costs ought to be arbitrated. In particular, observing others attitude may change ones uncertain belief about how to best behave in related difficult decision contexts. In turn, learning from others attitudes is determined by ones ability to learn about others attitudes. We first derive, from basic optimality principles, the computational properties of such a learning mechanism. In particular, we predict two apparent cognitive biases that would arise when individuals are learning about others attitudes: (i) people should overestimate the degree to which they resemble others (false-consensus bias), and (ii) they should align their own attitudes with others (social influence bias). We show how these two biases non-trivially interact with each other. We then validate these predictions experimentally by profiling peoples attitudes both before and after guessing a series of cost-benefit arbitrages performed by calibrated artificial agents (which are impersonating human individuals).'),
(88358, 2017, 'plos', 'Beware batch culture: Seasonality and niche construction predicted to favor bacterial adaptive diversification', 'Rocabert, Charles|Knibbe, Carole|Consuegra, Jessika|Schneider, Dominique|Beslon, Guillaume', 'Univ. de Lyon, CNRS, INRIA, INSA-Lyon, UCB Lyon 1, LIRIS UMR5205, Lyon, France.|Univ. de Lyon, CNRS, INRIA, INSA-Lyon, UCB Lyon 1, LIRIS UMR5205, Lyon, France.|Univ. Grenoble Alpes, Laboratoire Techniques de lIngénierie Médicale et de la Complexité - Informatique, Mathématiques et Applications, Grenoble (TIMC-IMAG), Grenoble, France.|Univ. Grenoble Alpes, Laboratoire Techniques de lIngénierie Médicale et de la Complexité - Informatique, Mathématiques et Applications, Grenoble (TIMC-IMAG), Grenoble, France.|Univ. de Lyon, CNRS, INRIA, INSA-Lyon, UCB Lyon 1, LIRIS UMR5205, Lyon, France.', 'France|France|France|France|France', 11, 'Adaptation, Physiological|Bacterial Physiological Phenomena|Batch Cell Culture Techniques|Biological Evolution|Computational Biology|Computer Simulation|Ecotype|Escherichia coli|Microbiota|Models, Biological|Seasons|Sympatry', 'Journal Article', '10.1371/journal.pcbi.1005459', '28358919', 'Metabolic cross-feeding interactions between microbial strains are common in nature, and emerge during evolution experiments in the laboratory, even in homogeneous environments providing a single carbon source. In sympatry, when the environment is well-mixed, the reasons why emerging cross-feeding interactions may sometimes become stable and lead to monophyletic genotypic clusters occupying specific niches, named ecotypes, remain unclear. As an alternative to evolution experiments in the laboratory, we developed Evo2Sim, a multi-scale model of in silico experimental evolution, equipped with the whole tool case of experimental setups, competition assays, phylogenetic analysis, and, most importantly, allowing for evolvable ecological interactions. Digital organisms with an evolvable genome structure encoding an evolvable metabolic network evolved for tens of thousands of generations in environments mimicking the dynamics of real controlled environments, including chemostat or batch culture providing a single limiting resource. We show here that the evolution of stable cross-feeding interactions requires seasonal batch conditions. In this case, adaptive diversification events result in two stably co-existing ecotypes, with one feeding on the primary resource and the other on by-products. We show that the regularity of serial transfers is essential for the maintenance of the polymorphism, as it allows for at least two stable seasons and thus two temporal niches. A first season is externally generated by the transfer into fresh medium, while a second one is internally generated by niche construction as the provided nutrient is replaced by secreted by-products derived from bacterial growth. In chemostat conditions, even if cross-feeding interactions emerge, they are not stable on the long-term because fitter mutants eventually invade the whole population. We also show that the long-term evolution of the two stable ecotypes leads to character displacement, at the level of the metabolic network but also of the genome structure. This difference of genome structure between both ecotypes impacts the stability of the cross-feeding interaction, when the population is propagated in chemostat conditions. This study shows the crucial role played by seasonality in temporal niche partitioning and in promoting cross-feeding subgroups into stable ecotypes, a premise to sympatric speciation.'),
(88359, 2017, 'plos', 'Interrogating the topological robustness of gene regulatory circuits by randomization', 'Huang, Bin|Lu, Mingyang|Jia, Dongya|Ben-Jacob, Eshel|Levine, Herbert|Onuchic, Jose N', 'Center for Theoretical Biological Physics, Rice University, Houston, TX, United States of America.|Center for Theoretical Biological Physics, Rice University, Houston, TX, United States of America.|Center for Theoretical Biological Physics, Rice University, Houston, TX, United States of America.|Center for Theoretical Biological Physics, Rice University, Houston, TX, United States of America.|Center for Theoretical Biological Physics, Rice University, Houston, TX, United States of America.|Center for Theoretical Biological Physics, Rice University, Houston, TX, United States of America.', 'United States|United States|United States|United States|United States|United States', 40, 'Computational Biology|Epithelial-Mesenchymal Transition|Gene Expression Regulation|Gene Regulatory Networks|Humans|Kinetics|Models, Genetic|Models, Statistical|Random Allocation', 'Journal Article', '10.1371/journal.pcbi.1005456', '28362798', 'One of the most important roles of cells is performing their cellular tasks properly for survival. Cells usually achieve robust functionality, for example, cell-fate decision-making and signal transduction, through multiple layers of regulation involving many genes. Despite the combinatorial complexity of gene regulation, its quantitative behavior has been typically studied on the basis of experimentally verified core gene regulatory circuitry, composed of a small set of important elements. It is still unclear how such a core circuit operates in the presence of many other regulatory molecules and in a crowded and noisy cellular environment. Here we report a new computational method, named random circuit perturbation (RACIPE), for interrogating the robust dynamical behavior of a gene regulatory circuit even without accurate measurements of circuit kinetic parameters. RACIPE generates an ensemble of random kinetic models corresponding to a fixed circuit topology, and utilizes statistical tools to identify generic properties of the circuit. By applying RACIPE to simple toggle-switch-like motifs, we observed that the stable states of all models converge to experimentally observed gene state clusters even when the parameters are strongly perturbed. RACIPE was further applied to a proposed 22-gene network of the Epithelial-to-Mesenchymal Transition (EMT), from which we identified four experimentally observed gene states, including the states that are associated with two different types of hybrid Epithelial/Mesenchymal phenotypes. Our results suggest that dynamics of a gene circuit is mainly determined by its topology, not by detailed circuit parameters. Our work provides a theoretical foundation for circuit-based systems biology modeling. We anticipate RACIPE to be a powerful tool to predict and decode circuit design principles in an unbiased manner, and to quantitatively evaluate the robustness and heterogeneity of gene expression.'),
(88360, 2017, 'plos', 'Effects of contact structure on the transient evolution of HIV virulence', 'Park, Sang Woo|Bolker, Benjamin M', 'Department of Mathematics & Statistics, McMaster University, Hamilton, Ontario, Canada.|Department of Mathematics & Statistics, McMaster University, Hamilton, Ontario, Canada.', 'Canada|Canada', 2, 'Biological Evolution|Computational Biology|Epidemics|Evolution, Molecular|Female|HIV Infections|HIV-1|Host-Pathogen Interactions|Humans|Male|Models, Biological|Mutation|Sexual Behavior|Time Factors|Viral Load|Virulence', 'Journal Article', '10.1371/journal.pcbi.1005453', '28362805', 'Early in an epidemic, high densities of susceptible hosts select for relatively high parasite virulence, later in the epidemic, lower susceptible densities select for lower virulence. Thus over the course of a typical epidemic the average virulence of parasite strains increases initially, peaks partway through the epidemic, then declines again. However, precise quantitative outcomes, such as the peak virulence reached and its timing, may depend sensitively on epidemiological details. Fraser et al. proposed a model for the eco-evolutionary dynamics of HIV that incorporates the tradeoffs between transmission and virulence (mediated by set-point viral load, SPVL) and their heritability between hosts. Their model used implicit equations to capture the effects of partnership dynamics that are at the core of epidemics of sexually transmitted diseases. Our models combine HIV virulence tradeoffs with a range of contact models, explicitly modeling partnership formation and dissolution and allowing for individuals to transmit disease outside of partnerships. We assess summary statistics such as the peak virulence (corresponding to the maximum value of population mean log10 SPVL achieved throughout the epidemic) across models for a range of parameters applicable to the HIV epidemic in sub-Saharan Africa. Although virulence trajectories are broadly similar across models, the timing and magnitude of the virulence peak vary considerably. Previously developed implicit models predicted lower virulence and slower progression at the peak (a maximum of 3.5 log10 SPVL) compared both to more realistic models and to simple random-mixing models with no partnership structure at all (both with a maximum of xe2x89x88 4.7 log10 SPVL). In this range of models, the simplest random-mixing structure best approximates the most realistic model, this surprising outcome occurs because the dominance of extra-pair contact in the realistic model swamps the effects of partnership structure.'),
(88361, 2017, 'plos', 'The preferred nucleotide contexts of the AID/APOBEC cytidine deaminases have differential effects when mutating retrotransposon and virus sequences compared to host genes', 'Chen, Jeffrey|MacCarthy, Thomas', 'Department of Applied Mathematics and Statistics, Stony Brook University, Stony Book, New York, United States of America.|Department of Applied Mathematics and Statistics, Stony Brook University, Stony Book, New York, United States of America.', 'United States|United States', 0, 'APOBEC Deaminases|Amino Acid Motifs|Animals|Base Composition|Codon|Computational Biology|Genome, Viral|Host-Pathogen Interactions|Humans|Models, Genetic|Mutation|Retroelements|Retroviridae', 'Journal Article', '10.1371/journal.pcbi.1005471', '28362825', 'The AID / APOBEC genes are a family of cytidine deaminases that have evolved in vertebrates, and particularly mammals, to mutate RNA and DNA at distinct preferred nucleotide contexts (or hotspots) on foreign genomes such as viruses and retrotransposons. These enzymes play a pivotal role in intrinsic immunity defense mechanisms, often deleteriously mutating invading retroviruses or retrotransposons and, in the case of AID, changing antibody sequences to drive affinity maturation. We investigate the strength of various hotspots on their known biological targets by evaluating the potential impact of mutations on the DNA coding sequences of these targets, and compare these results to hypothetical hotspots that did not evolve. We find that the existing AID / APOBEC hotspots have a large impact on retrotransposons and non-mammalian viruses while having a much smaller effect on vital mammalian genes, suggesting co-evolution with AID / APOBECs may have had an impact on the genomes of the viruses we analyzed. We determine that GC content appears to be a significant, but not sole, factor in resistance to deaminase activity. We discuss possible mechanisms AID and APOBEC viral targets have adopted to escape the impacts of deamination activity, including changing the GC content of the genome.'),
(88362, 2017, 'plos', 'ARACHNE: A neural-neuroglial network builder with remotely controlled parallel computing', 'Aleksin, Sergey G|Zheng, Kaiyu|Rusakov, Dmitri A|Savtchenko, Leonid P', 'AMC Bridge LLC, Waltham MA, United States of America and Dnipro, Ukraine.|UCL Institute of Neurology, University College London, London WC1N 3BG, United Kingdom.|UCL Institute of Neurology, University College London, London WC1N 3BG, United Kingdom.|UCL Institute of Neurology, University College London, London WC1N 3BG, United Kingdom.', 'Ukraine|United Kingdom|United Kingdom|United Kingdom', 4, 'Cell Communication|Computational Biology|Computer Simulation|Humans|Models, Neurological|Nerve Net|Neural Networks (Computer)|Neuroglia|Neurons|Software|User-Computer Interface', 'Journal Article', '10.1371/journal.pcbi.1005467', '28362877', 'Creating and running realistic models of neural networks has hitherto been a task for computing professionals rather than experimental neuroscientists. This is mainly because such networks usually engage substantial computational resources, the handling of which requires specific programing skills. Here we put forward a newly developed simulation environment ARACHNE: it enables an investigator to build and explore cellular networks of arbitrary biophysical and architectural complexity using the logic of NEURON and a simple interface on a local computer or a mobile device. The interface can control, through the internet, an optimized computational kernel installed on a remote computer cluster. ARACHNE can combine neuronal (wired) and astroglial (extracellular volume-transmission driven) network types and adopt realistic cell models from the NEURON library. The program and documentation (current version) are available at GitHub repository https://github.com/LeonidSavtchenko/Arachne under the MIT License (MIT).'),
(88363, 2017, 'plos', 'Role of non-native electrostatic interactions in the coupled folding and binding of PUMA with Mcl-1', 'Chu, Wen-Ting|Clarke, Jane|Shammas, Sarah L|Wang, Jin', 'State Key Laboratory of Electroanalytical Chemistry, Changchun Institute of Applied Chemistry, Chinese Academy of Sciences, Changchun, Jilin, China.|Department of Chemistry, University of Cambridge, Lensfield Road, Cambridge, United Kingdom.|Department of Chemistry, University of Cambridge, Lensfield Road, Cambridge, United Kingdom.|State Key Laboratory of Electroanalytical Chemistry, Changchun Institute of Applied Chemistry, Chinese Academy of Sciences, Changchun, Jilin, China.', 'China|United Kingdom|United Kingdom|China', 0, 'Apoptosis Regulatory Proteins|Computational Biology|Intrinsically Disordered Proteins|Models, Molecular|Myeloid Cell Leukemia Sequence 1 Protein|Protein Binding|Protein Folding|Static Electricity|Thermodynamics|Tumor Suppressor Proteins', 'Journal Article', '10.1371/journal.pcbi.1005468', '28369057', 'PUMA, which belongs to the BH3-only protein family, is an intrinsically disordered protein (IDP). It binds to its cellular partner Mcl-1 through its BH3 motif, which folds upon binding into an xcexb1 helix. We have applied a structure-based coarse-grained model, with an explicit Debye-Hxc3xbcckel charge model, to probe the importance of electrostatic interactions both in the early and the later stages of this model coupled folding and binding process. This model was carefully calibrated with the experimental data on helical content and affinity, and shown to be consistent with previously published experimental data on binding rate changes with respect to ionic strength. We find that intramolecular electrostatic interactions influence the unbound states of PUMA only marginally. Our results further suggest that intermolecular electrostatic interactions, and in particular non-native electrostatic interactions, are involved in formation of the initial encounter complex. We are able to reveal the binding mechanism in more detail than is possible using experimental data alone however, and in particular we uncover the role of non-native electrostatic interactions. We highlight the potential importance of such electrostatic interactions for describing the binding reactions of IDPs. Such approaches could be used to provide predictions for the results of mutational studies.'),
(88364, 2017, 'plos', 'The promiscuous enzyme medium-chain 3-keto-acyl-CoA thiolase triggers a vicious cycle in fatty-acid beta-oxidation', 'Martines, Anne-Claire M F|van Eunen, Karen|Reijngoud, Dirk-Jan|Bakker, Barbara M', 'Laboratory of Pediatrics, University of Groningen, University Medical Center Groningen, The Netherlands.|Laboratory of Pediatrics, University of Groningen, University Medical Center Groningen, The Netherlands.|Laboratory of Pediatrics, University of Groningen, University Medical Center Groningen, The Netherlands.|Laboratory of Pediatrics, University of Groningen, University Medical Center Groningen, The Netherlands.', 'Netherlands|Netherlands|Netherlands|Netherlands', 7, 'Acetyl-CoA C-Acyltransferase|Computational Biology|Computer Simulation|Fatty Acids|Kinetics|Metabolic Networks and Pathways|Oxidation-Reduction', 'Journal Article', '10.1371/journal.pcbi.1005461', '28369071', 'Mitochondrial fatty-acid beta-oxidation (mFAO) plays a central role in mammalian energy metabolism. Multiple severe diseases are associated with defects in this pathway. Its kinetic structure is characterized by a complex wiring of which the functional implications have hardly been explored. Repetitive cycles of reversible reactions, each cycle shortening the fatty acid by two carbon atoms, evoke competition between intermediates of different chain lengths for a common set of promiscuous enzymes (enzymes with activity towards multiple substrates). In our validated kinetic model of the pathway, substrate overload causes a steep and detrimental flux decline. Here, we unravel the underlying mechanism and the role of enzyme promiscuity in it. Comparison of alternative model versions elucidated the role of promiscuity of individual enzymes. Promiscuity of the last enzyme of the pathway, medium-chain ketoacyl-CoA thiolase (MCKAT), was both necessary and sufficient to elicit the flux decline. Subsequently, Metabolic Control Analysis revealed that MCKAT had insufficient capacity to cope with high substrate influx. Next, we quantified the internal metabolic regulation, revealing a vicious cycle around MCKAT. Upon substrate overload, MCKATs ketoacyl-CoA substrates started to accumulate. The unfavourable equilibrium constant of the preceding enzyme, medium/short-chain hydroxyacyl-CoA dehydrogenase, worked as an amplifier, leading to accumulation of upstream CoA esters, including acyl-CoA esters. These acyl-CoA esters are at the same time products of MCKAT and inhibited its already low activity further. Finally, the accumulation of CoA esters led to a sequestration of free CoA. CoA being a cofactor for MCKAT, its sequestration limited the MCKAT activity even further, thus completing the vicious cycle. Since CoA is also a substrate for distant enzymes, it efficiently communicated the traffic jam at MCKAT to the entire pathway. This novel mechanism provides a basis to explore the role of mFAO in disease and elucidate similar principles in other pathways of lipid metabolism.');
INSERT INTO `papers` (`id`, `ano`, `journal`, `titulo`, `autores`, `afiliacao`, `pais`, `citacoes`, `palavra_chave`, `categorias`, `doi`, `pubmed`, `abstract`) VALUES
(88365, 2017, 'plos', 'Transient chromatin properties revealed by polymer models and stochastic simulations constructed from Chromosomal Capture data', 'Shukron, Ofir|Holcman, David', 'Institute of Biology, Ecole Normale Supérieure, Paris, France.|Institute of Biology, Ecole Normale Supérieure, Paris, France.', 'France|France', 11, 'Biopolymers|Chromatin|Chromosomes|Empirical Research|Models, Chemical|Stochastic Processes', 'Journal Article', '10.1371/journal.pcbi.1005469', '28369076', 'Chromatin organization can be probed by Chromosomal Capture (5C) data, from which the encounter probability (EP) between genomic sites is presented in a large matrix. This matrix is averaged over a large cell population, revealing diagonal blocks called Topological Associating Domains (TADs) that represent a sub-chromatin organization. To study the relation between chromatin organization and gene regulation, we introduce a computational procedure to construct a bead-spring polymer model based on the EP matrix. The model permits exploring transient properties constrained by the statistics of the 5C data. To construct the polymer model, we proceed in two steps: first, we introduce a minimal number of random connectors inside restricted regions to account for diagonal blocks. Second, we account for long-range frequent specific genomic interactions. Using the constructed polymer, we compute the first encounter time distribution and the conditional probability of three key genomic sites. By simulating single particle trajectories of loci located on the constructed polymers from 5C data, we found a large variability of the anomalous exponent, used to interpret live cell imaging trajectories. The present polymer construction provides a generic tool to study steady-state and transient properties of chromatin constrained by some physical properties embedded in 5C data.'),
(88366, 2017, 'plos', 'Polarization and migration in the zebrafish posterior lateral line system', 'Knutsdottir, Hildur|Zmurchok, Cole|Bhaskar, Dhananjay|Palsson, Eirikur|Dalle Nogare, Damian|Chitnis, Ajay B|Edelstein-Keshet, Leah', 'Department of Mathematics, University of British Columbia, Vancouver, British Columbia, Canada.|Department of Mathematics, University of British Columbia, Vancouver, British Columbia, Canada.|Department of Mathematics, University of British Columbia, Vancouver, British Columbia, Canada.|Department of Biology, Simon Fraser University, Burnaby, British Columbia, Canada.|Division of Developmental Biology, Eunice Kennedy Shriver National Institute of Child Health and Human Development, Bethesda, Maryland, United States of America.|Division of Developmental Biology, Eunice Kennedy Shriver National Institute of Child Health and Human Development, Bethesda, Maryland, United States of America.|Department of Mathematics, University of British Columbia, Vancouver, British Columbia, Canada.', 'Canada|Canada|Canada|Canada|United States|United States|Canada', 0, 'Animals|Body Patterning|Cell Movement|Cell Polarity|Computational Biology|Models, Biological|Zebrafish', 'Journal Article', '10.1371/journal.pcbi.1005451', '28369079', 'Collective cell migration plays an important role in development. Here, we study the posterior lateral line primordium (PLLP) a group of about 100 cells, destined to form sensory structures, that migrates from head to tail in the zebrafish embryo. We model mutually inhibitory FGF-Wnt signalling network in the PLLP and link tissue subdivision (Wnt receptor and FGF receptor activity domains) to receptor-ligand parameters. We then use a 3D cell-based simulation with realistic cell-cell adhesion, interaction forces, and chemotaxis. Our model is able to reproduce experimentally observed motility with leading cells migrating up a gradient of CXCL12a, and trailing (FGF receptor active) cells moving actively by chemotaxis towards FGF ligand secreted by the leading cells. The 3D simulation framework, combined with experiments, allows an investigation of the role of cell division, chemotaxis, adhesion, and other parameters on the shape and speed of the PLLP. The 3D model demonstrates reasonable behaviour of control as well as mutant phenotypes.'),
(88367, 2017, 'plos', 'Quantifying the roles of host movement and vector dispersal in the transmission of vector-borne diseases of livestock', 'Sumner, Tom|Orton, Richard J|Green, Darren M|Kao, Rowland R|Gubbins, Simon', 'The Pirbright Institute, Pirbright, Surrey, United Kingdom.|Boyd Orr Centre for Population and Ecosystem Health, Institute of Biodiversity, Animal Health and Comparative Medicine, College of Medical, Veterinary and Life Sciences, University of Glasgow, Glasgow, United Kingdom.|Institute of Aquaculture, University of Stirling, Stirling, Stirlingshire, United Kingdom.|Boyd Orr Centre for Population and Ecosystem Health, Institute of Biodiversity, Animal Health and Comparative Medicine, College of Medical, Veterinary and Life Sciences, University of Glasgow, Glasgow, United Kingdom.|The Pirbright Institute, Pirbright, Surrey, United Kingdom.', 'United Kingdom|United Kingdom|United Kingdom|United Kingdom|United Kingdom', 13, 'Animals|Bayes Theorem|Bluetongue virus|Cattle|Cattle Diseases|Disease Outbreaks|Host-Pathogen Interactions|Insect Vectors|Livestock|Models, Theoretical|RNA Viruses|Sheep|Sheep Diseases', 'Journal Article', '10.1371/journal.pcbi.1005470', '28369082', 'The role of host movement in the spread of vector-borne diseases of livestock has been little studied. Here we develop a mathematical framework that allows us to disentangle and quantify the roles of vector dispersal and livestock movement in transmission between farms. We apply this framework to outbreaks of bluetongue virus (BTV) and Schmallenberg virus (SBV) in Great Britain, both of which are spread by Culicoides biting midges and have recently emerged in northern Europe. For BTV we estimate parameters by fitting the model to outbreak data using approximate Bayesian computation, while for SBV we use previously derived estimates. We find that around 90% of transmission of BTV between farms is a result of vector dispersal, while for SBV this proportion is 98%. This difference is a consequence of higher vector competence and shorter duration of viraemia for SBV compared with BTV. For both viruses we estimate that the mean number of secondary infections per infected farm is greater than one for vector dispersal, but below one for livestock movements. Although livestock movements account for a small proportion of transmission and cannot sustain an outbreak on their own, they play an important role in establishing new foci of infection. However, the impact of restricting livestock movements on the spread of both viruses depends critically on assumptions made about the distances over which vector dispersal occurs. If vector dispersal occurs primarily at a local scale (99% of transmission occurs <25 km), movement restrictions are predicted to be effective at reducing spread, but if dispersal occurs frequently over longer distances (99% of transmission occurs <50 km) they are not.'),
(88368, 2017, 'plos', 'Chemical Reaction Network Theory elucidates sources of multistability in interferon signaling', 'Otero-Muras, Irene|Yordanov, Pencho|Stelling, Joerg', 'Department of Biosystems Science and Engineering and Swiss Institute of Bioinformatics, ETH Zurich, Zurich, Switzerland.|Department of Biosystems Science and Engineering and Swiss Institute of Bioinformatics, ETH Zurich, Zurich, Switzerland.|Department of Biosystems Science and Engineering and Swiss Institute of Bioinformatics, ETH Zurich, Zurich, Switzerland.', 'Switzerland|Switzerland|Switzerland', 0, 'Cell Communication|Humans|Interferon Type I|Janus Kinases|Protein Interaction Maps|STAT Transcription Factors|Signal Transduction|Systems Biology', 'Journal Article', '10.1371/journal.pcbi.1005454', '28369103', 'Bistability has important implications in signaling pathways, since it indicates a potential cell decision between alternative outcomes. We present two approaches developed in the framework of the Chemical Reaction Network Theory for easy and efficient search of multiple steady state behavior in signaling networks (both with and without mass conservation), and apply them to search for sources of bistability at different levels of the interferon signaling pathway. Different type I interferon subtypes and/or doses are known to elicit differential bioactivities (ranging from antiviral, antiproliferative to immunomodulatory activities). How different signaling outcomes can be generated through the same receptor and activating the same JAK/STAT pathway is still an open question. Here, we detect bistability at the level of early STAT signaling, showing how two different cell outcomes are achieved under or above a threshold in ligand dose or ligand-receptor affinity. This finding could contribute to explain the differential signaling (antiviral vs apoptotic) depending on interferon dose and subtype (xcexb1 vs xcexb2) observed in type I interferons.'),
(88369, 2017, 'plos', 'Sequence dependency of canonical base pair opening in the DNA double helix', 'Lindahl, Viveca|Villa, Alessandra|Hess, Berk', 'Department of Physics and Swedish e-Science Research Center, KTH Royal Institute of Technology, Stockholm, Sweden.|Department of Biosciences and Nutrition, Karolinska Institutet, Huddinge, Sweden.|Department of Physics and Swedish e-Science Research Center, KTH Royal Institute of Technology, Stockholm, Sweden.', 'Sweden|Sweden|Sweden', 0, 'Base Pairing|Computational Biology|DNA|Nuclear Magnetic Resonance, Biomolecular', 'Journal Article', '10.1371/journal.pcbi.1005463', '28369121', 'The flipping-out of a DNA base from the double helical structure is a key step of many cellular processes, such as DNA replication, modification and repair. Base pair opening is the first step of base flipping and the exact mechanism is still not well understood. We investigate sequence effects on base pair opening using extensive classical molecular dynamics simulations targeting the opening of 11 different canonical base pairs in two DNA sequences. Two popular biomolecular force fields are applied. To enhance sampling and calculate free energies, we bias the simulation along a simple distance coordinate using a newly developed adaptive sampling algorithm. The simulation is guided back and forth along the coordinate, allowing for multiple opening pathways. We compare the calculated free energies with those from an NMR study and check assumptions of the model used for interpreting the NMR data. Our results further show that the neighboring sequence is an important factor for the opening free energy, but also indicates that other sequence effects may play a role. All base pairs are observed to have a propensity for opening toward the major groove. The preferred opening base is cytosine for GC base pairs, while for AT there is sequence dependent competition between the two bases. For AT opening, we identify two non-canonical base pair interactions contributing to a local minimum in the free energy profile. For both AT and CG we observe long-lived interactions with water and with sodium ions at specific sites on the open base pair.'),
(88370, 2017, 'plos', 'Geospatial characteristics of measles transmission in China during 2005-2014', 'Yang, Wan|Wen, Liang|Li, Shen-Long|Chen, Kai|Zhang, Wen-Yi|Shaman, Jeffrey', 'Department of Environmental Health Sciences, Mailman School of Public Health, Columbia University, New York, New York, United States.|Institute of Disease Control and Prevention, Academy of Military Medical Sciences, Beijing, P.R. China.|Institute of Disease Control and Prevention, Academy of Military Medical Sciences, Beijing, P.R. China.|State Key Laboratory of Pollution Control and Resource Reuse, School of the Environment, Nanjing University, Nanjing, P.R. China.|Institute of Disease Control and Prevention, Academy of Military Medical Sciences, Beijing, P.R. China.|Department of Environmental Health Sciences, Mailman School of Public Health, Columbia University, New York, New York, United States.', 'United States|China|China|China|China|United States', 8, 'China|Cluster Analysis|Disease Outbreaks|Humans|Incidence|Measles|Population Surveillance|Social Class', 'Journal Article', '10.1371/journal.pcbi.1005474', '28376097', 'Measles is a highly contagious and severe disease. Despite mass vaccination, it remains a leading cause of death in children in developing regions, killing 114,900 globally in 2014. In 2006, China committed to eliminating measles by 2012, to this end, the country enhanced its mandatory vaccination programs and achieved vaccination rates reported above 95% by 2008. However, in spite of these efforts, during the last 3 years (2013-2015) China documented 27,695, 52,656, and 42,874 confirmed measles cases. How measles manages to spread in China-the worlds largest population-in the mass vaccination era remains poorly understood. To address this conundrum and provide insights for future public health efforts, we analyze the geospatial pattern of measles transmission across China during 2005-2014. We map measles incidence and incidence rates for each of the 344 cities in mainland China, identify the key socioeconomic and demographic features associated with high disease burden, and identify transmission clusters based on the synchrony of outbreak cycles. Using hierarchical cluster analysis, we identify 21 epidemic clusters, of which 12 were cross-regional. The cross-regional clusters included more underdeveloped cities with large numbers of emigrants than would be expected by chance (p = 0.011, bootstrap sampling), indicating that cities in these clusters were likely linked by internal worker migration in response to uneven economic development. In contrast, cities in regional clusters were more likely to have high rates of minorities and high natural growth rates than would be expected by chance (p = 0.074, bootstrap sampling). Our findings suggest that multiple highly connected foci of measles transmission coexist in China and that migrant workers likely facilitate the transmission of measles across regions. This complex connection renders eradication of measles challenging in China despite its high overall vaccination coverage. Future immunization programs should therefore target these transmission foci simultaneously.'),
(88371, 2017, 'plos', 'Computation and measurement of cell decision making errors using single cell data', 'Habibi, Iman|Cheong, Raymond|Lipniacki, Tomasz|Levchenko, Andre|Emamian, Effat S|Abdi, Ali', 'Center for Wireless Information Processing, Department of Electrical and Computer Engineering, New Jersey Institute of Technology, Newark, NJ, United States of America.|Department of Biomedical Engineering, Johns Hopkins University, Baltimore, MD, United States of America.|Institute of Fundamental Technological Research, Polish Academy of Sciences, Pawinskiego 5B, Warsaw, Poland.|Yale Systems Biology Institute and Department of Biomedical Engineering, Yale University, New Haven, CT, United States of America.|Advanced Technologies for Novel Therapeutics, Enterprise Development Center, New Jersey Institute of Technology, Newark, NJ, United States of America.|Center for Wireless Information Processing, Department of Electrical and Computer Engineering, New Jersey Institute of Technology, Newark, NJ, United States of America.', 'Jersey|United States|Poland|United States|Jersey|Jersey', 9, 'Cell Communication|Computational Biology|Decision Theory|Models, Biological|Models, Statistical|NF-kappa B|Signal Processing, Computer-Assisted|Signal Transduction|Single-Cell Analysis|Tumor Necrosis Factor-alpha', 'Journal Article', '10.1371/journal.pcbi.1005436', '28379950', 'In this study a new computational method is developed to quantify decision making errors in cells, caused by noise and signaling failures. Analysis of tumor necrosis factor (TNF) signaling pathway which regulates the transcription factor Nuclear Factor xcexbaB (NF-xcexbaB) using this method identifies two types of incorrect cell decisions called false alarm and miss. These two events represent, respectively, declaring a signal which is not present and missing a signal that does exist. Using single cell experimental data and the developed method, we compute false alarm and miss error probabilities in wild-type cells and provide a formulation which shows how these metrics depend on the signal transduction noise level. We also show that in the presence of abnormalities in a cell, decision making processes can be significantly affected, compared to a wild-type cell, and the method is able to model and measure such effects. In the TNF-NF-xcexbaB pathway, the method computes and reveals changes in false alarm and miss probabilities in A20-deficient cells, caused by cells inability to inhibit TNF-induced NF-xcexbaB response. In biological terms, a higher false alarm metric in this abnormal TNF signaling system indicates perceiving more cytokine signals which in fact do not exist at the system input, whereas a higher miss metric indicates that it is highly likely to miss signals that actually exist. Overall, this study demonstrates the ability of the developed method for modeling cell decision making errors under normal and abnormal conditions, and in the presence of transduction noise uncertainty. Compared to the previously reported pathway capacity metric, our results suggest that the introduced decision error metrics characterize signaling failures more accurately. This is mainly because while capacity is a useful metric to study information transmission in signaling pathways, it does not capture the overlap between TNF-induced noisy response curves.'),
(88372, 2017, 'plos', 'Correction: Multiscale mutation clustering algorithm identifies pan-cancer mutational clusters associated with pathway-level changes in gene expression', 'PLOS Computational Biology Staff', 'Center for Wireless Information Processing, Department of Electrical and Computer Engineering, New Jersey Institute of Technology, Newark, NJ, United States of America.', 'Jersey', 0, '-', 'Journal Article', '10.1371/journal.pcbi.1005472', '28384155', '[This corrects the article DOI: 10.1371/journal.pcbi.1005347.].'),
(88373, 2017, 'plos', 'How evolution learns to generalise: Using the principles of learning theory to understand the evolution of developmental organisation', 'Kouvaris, Kostas|Clune, Jeff|Kounios, Loizos|Brede, Markus|Watson, Richard A', 'ECS, University of Southampton, Southampton, United Kingdom.|University of Wyoming, Laramie, Wyoming, United States of America.|ECS, University of Southampton, Southampton, United Kingdom.|ECS, University of Southampton, Southampton, United Kingdom.|ECS, University of Southampton, Southampton, United Kingdom.', 'United Kingdom|United States|United Kingdom|United Kingdom|United Kingdom', 21, 'Biological Evolution|Computational Biology|Environment|Humans|Learning|Machine Learning|Models, Biological|Phenotype|Selection, Genetic', 'Journal Article', '10.1371/journal.pcbi.1005358', '28384156', 'One of the most intriguing questions in evolution is how organisms exhibit suitable phenotypic variation to rapidly adapt in novel selective environments. Such variability is crucial for evolvability, but poorly understood. In particular, how can natural selection favour developmental organisations that facilitate adaptive evolution in previously unseen environments? Such a capacity suggests foresight that is incompatible with the short-sighted concept of natural selection. A potential resolution is provided by the idea that evolution may discover and exploit information not only about the particular phenotypes selected in the past, but their underlying structural regularities: new phenotypes, with the same underlying regularities, but novel particulars, may then be useful in new environments. If true, we still need to understand the conditions in which natural selection will discover such deep regularities rather than exploiting quick fixes (i.e., fixes that provide adaptive phenotypes in the short term, but limit future evolvability). Here we argue that the ability of evolution to discover such regularities is formally analogous to learning principles, familiar in humans and machines, that enable generalisation from past experience. Conversely, natural selection that fails to enhance evolvability is directly analogous to the learning problem of over-fitting and the subsequent failure to generalise. We support the conclusion that evolving systems and learning systems are different instantiations of the same algorithmic principles by showing that existing results from the learning domain can be transferred to the evolution domain. Specifically, we show that conditions that alleviate over-fitting in learning systems successfully predict which biological conditions (e.g., environmental variation, regularity, noise or a pressure for developmental simplicity) enhance evolvability. This equivalence provides access to a well-developed theoretical framework from learning theory that enables a characterisation of the general conditions for the evolution of evolvability.'),
(88374, 2017, 'plos', 'Dynamic compensation, parameter identifiability, and equivariances', 'Sontag, Eduardo D', 'Department of Mathematics and Center for Quantitative Biology, Hill Center, Rutgers University, Piscataway, New Jersey, United States of America.', 'Jersey', 10, 'Algorithms|Models, Biological|Systems Biology', 'Journal Article', '10.1371/journal.pcbi.1005447', '28384175', 'A recent paper by Karin et al. introduced a mathematical notion called dynamical compensation (DC) of biological circuits. DC was shown to play an important role in glucose homeostasis as well as other key physiological regulatory mechanisms. Karin et al. went on to provide a sufficient condition to test whether a given system has the DC property. Here, we show how DC can be formulated in terms of a well-known concept in systems biology, statistics, and control theory-that of parameter structural non-identifiability. Viewing DC as a parameter identification problem enables one to take advantage of powerful theoretical and computational tools to test a system for DC. We obtain as a special case the sufficient criterion discussed by Karin et al. We also draw connections to system equivalence and to the fold-change detection property.'),
(88375, 2017, 'plos', 'Functional asymmetry and plasticity of electrical synapses interconnecting neurons through a 36-state model of gap junction channel gating', 'Snipas, Mindaugas|Rimkute, Lina|Kraujalis, Tadas|Maciunas, Kestutis|Bukauskas, Feliksas F', 'Institute of Cardiology, Lithuanian University of Health Sciences, Kaunas, Lithuania.|Institute of Cardiology, Lithuanian University of Health Sciences, Kaunas, Lithuania.|Institute of Cardiology, Lithuanian University of Health Sciences, Kaunas, Lithuania.|Institute of Cardiology, Lithuanian University of Health Sciences, Kaunas, Lithuania.|Institute of Cardiology, Lithuanian University of Health Sciences, Kaunas, Lithuania.', 'Lithuania|Lithuania|Lithuania|Lithuania|Lithuania', 8, 'Action Potentials|Cell Communication|Connexins|Electrical Synapses|Gap Junctions|HeLa Cells|Humans|Magnesium|Models, Neurological|Neural Pathways|Neuronal Plasticity|Neurons', 'Journal Article', '10.1371/journal.pcbi.1005464', '28384220', 'We combined the Hodgkin-Huxley equations and a 36-state model of gap junction channel gating to simulate electrical signal transfer through electrical synapses. Differently from most previous studies, our model can account for dynamic modulation of junctional conductance during the spread of electrical signal between coupled neurons. The model of electrical synapse is based on electrical properties of the gap junction channel encompassing two fast and two slow gates triggered by the transjunctional voltage. We quantified the influence of a difference in input resistances of electrically coupled neurons and instantaneous conductance-voltage rectification of gap junctions on an asymmetry of cell-to-cell signaling. We demonstrated that such asymmetry strongly depends on junctional conductance and can lead to the unidirectional transfer of action potentials. The simulation results also revealed that voltage spikes, which develop between neighboring cells during the spread of action potentials, can induce a rapid decay of junctional conductance, thus demonstrating spiking activity-dependent short-term plasticity of electrical synapses. This conclusion was supported by experimental data obtained in HeLa cells transfected with connexin45, which is among connexin isoforms expressed in neurons. Moreover, the model allowed us to replicate the kinetics of junctional conductance under different levels of intracellular concentration of free magnesium ([Mg2+]i), which was experimentally recorded in cells expressing connexin36, a major neuronal connexin. We demonstrated that such [Mg2+]i-dependent long-term plasticity of the electrical synapse can be adequately reproduced through the changes of slow gate parameters of the 36-state model. This suggests that some types of chemical modulation of gap junctions can be executed through the underlying mechanisms of voltage gating. Overall, the developed model accounts for direction-dependent asymmetry, as well as for short- and long-term plasticity of electrical synapses. Our modeling results demonstrate that such complex behavior of the electrical synapse is important in shaping the response of coupled neurons.'),
(88376, 2017, 'plos', 'Dose-response relationships for environmentally mediated infectious disease transmission models', 'Brouwer, Andrew F|Weir, Mark H|Eisenberg, Marisa C|Meza, Rafael|Eisenberg, Joseph N S', 'Department of Epidemiology, University of Michigan, Ann Arbor, MI, United States of America.|Division of Environmental Health Sciences, The Ohio State University, Columbus, OH, United States of America.|Department of Epidemiology, University of Michigan, Ann Arbor, MI, United States of America.|Department of Epidemiology, University of Michigan, Ann Arbor, MI, United States of America.|Department of Epidemiology, University of Michigan, Ann Arbor, MI, United States of America.', 'United States|United States|United States|United States|United States', 0, 'Computational Biology|Cryptosporidiosis|Cryptosporidium|Disease Outbreaks|Disease Transmission, Infectious|Humans|Models, Biological', 'Journal Article', '10.1371/journal.pcbi.1005481', '28388665', 'Environmentally mediated infectious disease transmission models provide a mechanistic approach to examining environmental interventions for outbreaks, such as water treatment or surface decontamination. The shift from the classical SIR framework to one incorporating the environment requires codifying the relationship between exposure to environmental pathogens and infection, i.e. the dose-response relationship. Much of the work characterizing the functional forms of dose-response relationships has used statistical fit to experimental data. However, there has been little research examining the consequences of the choice of functional form in the context of transmission dynamics. To this end, we identify four properties of dose-response functions that should be considered when selecting a functional form: low-dose linearity, scalability, concavity, and whether it is a single-hit model. We find that i) middle- and high-dose data do not constrain the low-dose response, and different dose-response forms that are equally plausible given the data can lead to significant differences in simulated outbreak dynamics, ii) the choice of how to aggregate continuous exposure into discrete doses can impact the modeled force of infection, iii) low-dose linear, concave functions allow the basic reproduction number to control global dynamics, and iv) identifiability analysis offers a way to manage multiple sources of uncertainty and leverage environmental monitoring to make inference about infectivity. By applying an environmentally mediated infectious disease model to the 1993 Milwaukee Cryptosporidium outbreak, we demonstrate that environmental monitoring allows for inference regarding the infectivity of the pathogen and thus improves our ability to identify outbreak characteristics such as pathogen strain.'),
(88377, 2017, 'plos', 'Amino acid composition predicts prion activity', 'Afsar Minhas, Fayyaz Ul Amir|Ross, Eric D|Ben-Hur, Asa', 'Department of Computer and Information Sciences, Pakistan Institute of Engineering and Applied Sciences, Islamabad, Pakistan.|Department of Biochemistry and Molecular Biology, Colorado State University, Fort Collins, Colorado, United States of America.|Department of Computer Science, Colorado State University, Fort Collins, Colorado, United States of America.', 'Pakistan|United States|United States', 15, 'Amino Acid Sequence|Amyloid|Asparagine|Computational Biology|Glutamine|Humans|Machine Learning|Prions|Yeasts', 'Journal Article', '10.1371/journal.pcbi.1005465', '28394888', 'Many prion-forming proteins contain glutamine/asparagine (Q/N) rich domains, and there are conflicting opinions as to the role of primary sequence in their conversion to the prion form: is this phenomenon driven primarily by amino acid composition, or, as a recent computational analysis suggested, dependent on the presence of short sequence elements with high amyloid-forming potential. The argument for the importance of short sequence elements hinged on the relatively-high accuracy obtained using a method that utilizes a collection of length-six sequence elements with known amyloid-forming potential. We weigh in on this question and demonstrate that when those sequence elements are permuted, even higher accuracy is obtained, we also propose a novel multiple-instance machine learning method that uses sequence composition alone, and achieves better accuracy than all existing prion prediction approaches. While we expect there to be elements of primary sequence that affect the process, our experiments suggest that sequence composition alone is sufficient for predicting protein sequences that are likely to form prions. A web-server for the proposed method is available at http://faculty.pieas.edu.pk/fayyaz/prank.html, and the code for reproducing our experiments is available at http://doi.org/10.5281/zenodo.167136.'),
(88378, 2017, 'plos', 'Modeling disordered protein interactions from biophysical principles', 'Peterson, Lenna X|Roy, Amitava|Christoffer, Charles|Terashi, Genki|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 Biological Sciences, Purdue University, West Lafayette, Indiana, United States of America.', 'India|India|India|India|India', 18, 'Amino Acid Sequence|Animals|Binding Sites|Computational Biology|Humans|Intrinsically Disordered Proteins|Mice|Models, Molecular|Protein Binding|Sequence Analysis, Protein', 'Journal Article', '10.1371/journal.pcbi.1005485', '28394890', 'Disordered protein-protein interactions (PPIs), those involving a folded protein and an intrinsically disordered protein (IDP), are prevalent in the cell, including important signaling and regulatory pathways. IDPs do not adopt a single dominant structure in isolation but often become ordered upon binding. To aid understanding of the molecular mechanisms of disordered PPIs, it is crucial to obtain the tertiary structure of the PPIs. However, experimental methods have difficulty in solving disordered PPIs and existing protein-protein and protein-peptide docking methods are not able to model them. Here we present a novel computational method, IDP-LZerD, which models the conformation of a disordered PPI by considering the biophysical binding mechanism of an IDP to a structured protein, whereby a local segment of the IDP initiates the interaction and subsequently the remaining IDP regions explore and coalesce around the initial binding site. On a dataset of 22 disordered PPIs with IDPs up to 69 amino acids, successful predictions were made for 21 bound and 18 unbound receptors. The successful modeling provides additional support for biophysical principles. Moreover, the new technique significantly expands the capability of protein structure modeling and provides crucial insights into the molecular mechanisms of disordered PPIs.'),
(88379, 2017, 'plos', 'Correction: The missing link: Predicting connectomes from noisy and partially observed tract tracing data', 'Hinne, Max|Meijers, Annet|Bakker, Rembrandt|Tiesinga, Paul H E|Mørup, Morten|van Gerven, Marcel A J', '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.|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', 1, '-', 'Journal Article', '10.1371/journal.pcbi.1005478', '28399121', '[This corrects the article DOI: 10.1371/journal.pcbi.1005374.].'),
(88380, 2017, 'plos', 'Correction: Deciding Not to Decide: Computational and Neural Evidence for Hidden Behavior in Sequential Choice', 'Gluth, Sebastian|Rieskamp, Jörg|Büchel, Christian', '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', 0, '-', 'Journal Article', '10.1371/journal.pcbi.1005476', '28399130', '[This corrects the article DOI: 10.1371/journal.pcbi.1003309.].'),
(88381, 2017, 'plos', 'Correction: Order Under Uncertainty: Robust Differential Expression Analysis Using Probabilistic Models for Pseudotime Inference', 'PLOS Computational Biology Staff', 'Department of Biological Sciences, Purdue University, West Lafayette, Indiana, United States of America.', 'India', 0, '-', 'Journal Article', '10.1371/journal.pcbi.1005477', '28399131', '[This corrects the article DOI: 10.1371/journal.pcbi.1005212.].'),
(88382, 2017, 'plos', 'Increased decision thresholds enhance information gathering performance in juvenile Obsessive-Compulsive Disorder (OCD)', 'Hauser, Tobias U|Moutoussis, Michael|Iannaccone, Reto|Brem, Silvia|Walitza, Susanne|Drechsler, Renate|Dayan, Peter|Dolan, Raymond J', 'Wellcome Trust Centre for Neuroimaging, University College London, London, United Kingdom.|Wellcome Trust Centre for Neuroimaging, University College London, London, United Kingdom.|Department of Child and Adolescent Psychiatry and Psychotherapy, Psychiatric Hospital, University of Zurich, Zürich, Switzerland.|Department of Child and Adolescent Psychiatry and Psychotherapy, Psychiatric Hospital, University of Zurich, Zürich, Switzerland.|Department of Child and Adolescent Psychiatry and Psychotherapy, Psychiatric Hospital, University of Zurich, Zürich, Switzerland.|Department of Child and Adolescent Psychiatry and Psychotherapy, Psychiatric Hospital, University of Zurich, Zürich, Switzerland.|Gatsby Computational Neuroscience Unit, University College London, London, United Kingdom.|Wellcome Trust Centre for Neuroimaging, University College London, London, United Kingdom.', 'United Kingdom|United Kingdom|Switzerland|Switzerland|Switzerland|Switzerland|United Kingdom|United ', 17, 'Adolescent|Bayes Theorem|Decision Making|Female|Humans|Male|Models, Statistical|Neuropsychological Tests|Obsessive-Compulsive Disorder|Risk-Taking', 'Journal Article', '10.1371/journal.pcbi.1005440', '28403139', 'Patients with obsessive-compulsive disorder (OCD) can be described as cautious and hesitant, manifesting an excessive indecisiveness that hinders efficient decision making. However, excess caution in decision making may also lead to better performance in specific situations where the cost of extended deliberation is small. We compared 16 juvenile OCD patients with 16 matched healthy controls whilst they performed a sequential information gathering task under different external cost conditions. We found that patients with OCD outperformed healthy controls, winning significantly more points. The groups also differed in the number of draws required prior to committing to a decision, but not in decision accuracy. A novel Bayesian computational model revealed that subjective sampling costs arose as a non-linear function of sampling, closely resembling an escalating urgency signal. Group difference in performance was best explained by a later emergence of these subjective costs in the OCD group, also evident in an increased decision threshold. Our findings present a novel computational model and suggest that enhanced information gathering in OCD can be accounted for by a higher decision threshold arising out of an altered perception of costs that, in some specific contexts, may be advantageous.'),
(88383, 2017, 'plos', 'Inferring modulators of genetic interactions with epistatic nested effects models', 'Pirkl, Martin|Diekmann, Madeline|van der Wees, Marlies|Beerenwinkel, Niko|Fröhlich, Holger|Markowetz, Florian', 'ETH Zurich, Department of Biosystems Science and Engineering, Basel, Switzerland.|ETH Zurich, Department of Biosystems Science and Engineering, Basel, Switzerland.|University of Amsterdam, Amsterdam, The Netherlands.|ETH Zurich, Department of Biosystems Science and Engineering, Basel, Switzerland.|Bonn-Aachen International Center for IT (B-IT), University of Bonn, Bonn, Germany.|University of Cambridge, Cancer Research UK Cambridge Institute, Cambridge, United Kingdom.', 'Switzerland|Switzerland|Netherlands|Switzerland|Germany|United Kingdom', 6, 'Computational Biology|Epistasis, Genetic|Gene Regulatory Networks|Genes, Fungal|Models, Genetic|Saccharomyces cerevisiae', 'Journal Article', '10.1371/journal.pcbi.1005496', '28406896', 'Maps of genetic interactions can dissect functional redundancies in cellular networks. Gene expression profiles as high-dimensional molecular readouts of combinatorial perturbations provide a detailed view of genetic interactions, but can be hard to interpret if different gene sets respond in different ways (called mixed epistasis). Here we test the hypothesis that mixed epistasis between a gene pair can be explained by the action of a third gene that modulates the interaction. We have extended the framework of Nested Effects Models (NEMs), a type of graphical model specifically tailored to analyze high-dimensional gene perturbation data, to incorporate logical functions that describe interactions between regulators on downstream genes and proteins. We benchmark our approach in the controlled setting of a simulation study and show high accuracy in inferring the correct model. In an application to data from deletion mutants of kinases and phosphatases in S. cerevisiae we show that epistatic NEMs can point to modulators of genetic interactions. Our approach is implemented in the R-package epiNEM available from https://github.com/cbg-ethz/epiNEM and https://bioconductor.org/packages/epiNEM/.'),
(88384, 2017, 'plos', 'From elementary flux modes to elementary flux vectors: Metabolic pathway analysis with arbitrary linear flux constraints', 'Klamt, Steffen|Regensburger, Georg|Gerstl, Matthias P|Jungreuthmayer, Christian|Schuster, Stefan|Mahadevan, Radhakrishnan|Zanghellini, Jürgen|Müller, Stefan', 'Max Planck Institute for Dynamics of Complex Technical Systems, Magdeburg, Germany.|Institute for Algebra, Johannes Kepler University Linz (JKU), Linz, Austria.|Department of Biotechnology, University of Natural Resources and Life Sciences, Vienna, Austria.|Austrian Centre of Biotechnology, Vienna, Austria.|Department of Bioinformatics, Faculty of Biology and Pharmacy, Friedrich Schiller University Jena, Jena, Germany.|Department of Chemical Engineering & Applied Chemistry, Institute of Biomaterials and Biomedical Engineering, University of Toronto, Toronto, Ontario, Canada.|Department of Biotechnology, University of Natural Resources and Life Sciences, Vienna, Austria.|Radon Institute for Computational and Applied Mathematics (RICAM), Austrian Academy of Sciences, Linz, Austria.', 'Germany|Austria|Austria|Austria|Germany|Canada|Austria|Austria', 18, 'Metabolism|Models, Biological', 'Journal Article', '10.1371/journal.pcbi.1005409', '28406903', 'Elementary flux modes (EFMs) emerged as a formal concept to describe metabolic pathways and have become an established tool for constraint-based modeling and metabolic network analysis. EFMs are characteristic (support-minimal) vectors of the flux cone that contains all feasible steady-state flux vectors of a given metabolic network. EFMs account for (homogeneous) linear constraints arising from reaction irreversibilities and the assumption of steady state, however, other (inhomogeneous) linear constraints, such as minimal and maximal reaction rates frequently used by other constraint-based techniques (such as flux balance analysis [FBA]), cannot be directly integrated. These additional constraints further restrict the space of feasible flux vectors and turn the flux cone into a general flux polyhedron in which the concept of EFMs is not directly applicable anymore. For this reason, there has been a conceptual gap between EFM-based (pathway) analysis methods and linear optimization (FBA) techniques, as they operate on different geometric objects. One approach to overcome these limitations was proposed ten years ago and is based on the concept of elementary flux vectors (EFVs). Only recently has the community started to recognize the potential of EFVs for metabolic network analysis. In fact, EFVs exactly represent the conceptual development required to generalize the idea of EFMs from flux cones to flux polyhedra. This work aims to present a concise theoretical and practical introduction to EFVs that is accessible to a broad audience. We highlight the close relationship between EFMs and EFVs and demonstrate that almost all applications of EFMs (in flux cones) are possible for EFVs (in flux polyhedra) as well. In fact, certain properties can only be studied with EFVs. Thus, we conclude that EFVs provide a powerful and unifying framework for constraint-based modeling of metabolic networks.'),
(88385, 2017, 'plos', 'Human behavioral complexity peaks at age 25', 'Gauvrit, Nicolas|Zenil, Hector|Soler-Toscano, Fernando|Delahaye, Jean-Paul|Brugger, Peter', 'Algorithmic Nature Group, Laboratoire de Recherche Scientifique LABORES For the Natural and Digital Sciences, Paris, France.|Algorithmic Nature Group, Laboratoire de Recherche Scientifique LABORES For the Natural and Digital Sciences, Paris, France.|Algorithmic Nature Group, Laboratoire de Recherche Scientifique LABORES For the Natural and Digital Sciences, Paris, France.|Algorithmic Nature Group, Laboratoire de Recherche Scientifique LABORES For the Natural and Digital Sciences, Paris, France.|Algorithmic Nature Group, Laboratoire de Recherche Scientifique LABORES For the Natural and Digital Sciences, Paris, France.', 'France|France|France|France|France', 19, 'Adolescent|Adult|Aged|Aged, 80 and over|Behavior|Child|Child, Preschool|Humans|Middle Aged|Task Performance and Analysis|Young Adult', 'Journal Article', '10.1371/journal.pcbi.1005408', '28406953', 'Random Item Generation tasks (RIG) are commonly used to assess high cognitive abilities such as inhibition or sustained attention. They also draw upon our approximate sense of complexity. A detrimental effect of aging on pseudo-random productions has been demonstrated for some tasks, but little is as yet known about the developmental curve of cognitive complexity over the lifespan. We investigate the complexity trajectory across the lifespan of human responses to five common RIG tasks, using a large sample (n = 3429). Our main finding is that the developmental curve of the estimated algorithmic complexity of responses is similar to what may be expected of a measure of higher cognitive abilities, with a performance peak around 25 and a decline starting around 60, suggesting that RIG tasks yield good estimates of such cognitive abilities. Our study illustrates that very short strings of, i.e., 10 items, are sufficient to have their complexity reliably estimated and to allow the documentation of an age-dependent decline in the approximate sense of complexity.'),
(88386, 2017, 'plos', 'Peptide probes derived from pertuzumab by molecular dynamics modeling for HER2 positive tumor imaging', 'Yang, Xiaoliang|Wang, Zihua|Xiang, Zhichu|Li, Dan|Hu, Zhiyuan|Cui, Wei|Geng, Lingling|Fang, Qiaojun', 'CAS Key Laboratory for Biological Effects of Nanomaterials & Nanosafety, National Center for Nanoscience and Technology, Beijing, China.|CAS Key Laboratory for Biological Effects of Nanomaterials & Nanosafety, National Center for Nanoscience and Technology, Beijing, China.|CAS Key Laboratory for Biological Effects of Nanomaterials & Nanosafety, National Center for Nanoscience and Technology, Beijing, China.|CAS Key Laboratory for Biological Effects of Nanomaterials & Nanosafety, National Center for Nanoscience and Technology, Beijing, China.|CAS Key Laboratory for Biological Effects of Nanomaterials & Nanosafety, National Center for Nanoscience and Technology, Beijing, China.|School of Chemistry and Chemical Engineering, University of Chinese Academy of Sciences, Beijing, P.R. China.|CAS Key Laboratory for Biological Effects of Nanomaterials & Nanosafety, National Center for Nanoscience and Technology, Beijing, China.|CAS Key Laboratory for Biological Effects of Nanomaterials & Nanosafety, National Center for Nanoscience and Technology, Beijing, China.', 'China|China|China|China|China|China|China|China', 0, 'Amino Acid Sequence|Animals|Antibodies, Monoclonal, Humanized|Cell Line, Tumor|Genes, erbB-2|Heterografts|Humans|Mice|Mice, Nude|Molecular Dynamics Simulation|Molecular Probes|Mutation|Neoplasms|Peptides|Sequence Homology, Amino Acid|Surface Plasmon Resonance', 'Journal Article', '10.1371/journal.pcbi.1005441', '28406988', 'A high level of HER2 expression in breast cancer correlates with a higher tumor growth rate, high metastatic potential, and a poor long-term patient survival rate. Pertuzumab, a human monoclonal antibody, can reduce the effect of HER2 overexpression by preventing HER2 dimerization. In this study, a combination protocol of molecular dynamics modeling and MM/GBSA binding free energy calculations was applied to design peptides that interact with HER2 based on the HER2/pertuzumab crystal structure. Based on a xcexb2 hairpin in pertuzumab from Glu46 to Lys65-which plays a key role in interacting with HER2-mutations were carried out in silico to improve the binding free energy of the hairpin that interacts with the Phe256-Lys314 of the HER2 protein. Combined the use of one-bead-one-compound library screening, among all the mutations, a peptide (58F63Y) with the lowest binding free energy was confirmed experimentally to have the highest affinity, and it may be used as a new probe in diagnosing and treating HER2-positive breast cancer.'),
(88387, 2017, 'plos', 'Ten simple rules for making research software more robust', 'Taschuk, Morgan|Wilson, Greg', 'Genome Sequence Informatics, Ontario Institute for Cancer Research, Toronto, Ontario, Canada.|Software Carpentry Foundation, Austin, Texas, United States of America.', 'Canada|United States', 0, 'Computer Simulation|Software', 'Editorial', '10.1371/journal.pcbi.1005412', '28407023', 'Software produced for research, published and otherwise, suffers from a number of common problems that make it difficult or impossible to run outside the original institution or even off the primary developers computer. We present ten simple rules to make such software robust enough to be run by anyone, anywhere, and thereby delight your users and collaborators.');
