INSERT INTO `papers` (`id`, `ano`, `journal`, `titulo`, `autores`, `afiliacao`, `pais`, `citacoes`, `palavra_chave`, `categorias`, `doi`, `pubmed`, `abstract`) VALUES
(86988, 2015, 'plos', 'DNA exit ramps are revealed in the binding landscapes obtained from simulations in helical coordinates', 'Echeverria, Ignacia|Papoian, Garegin A', 'Department of Chemistry and Biochemistry, University of Maryland, College Park, Maryland, United States of America, Institute for Physical Science and Technology, 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, Institute for Physical Science and Technology, University of Maryland, College Park, Maryland, United States of America.', 'United States|United States', 6, 'DNA|DNA Methylation|DNA-Binding Proteins|Methylguanidine|Molecular Dynamics Simulation|Nucleic Acid Conformation|Sodium|Thermodynamics|Transcription, Genetic', 'Journal Article', '10.1371/journal.pcbi.1003980', '25675216', 'DNA molecules are highly charged semi-flexible polymers that are involved in a wide variety of dynamical processes such as transcription and replication. Characterizing the binding landscapes around DNA molecules is essential to understanding the energetics and kinetics of various biological processes. We present a curvilinear coordinate system that fully takes into account the helical symmetry of a DNA segment. The latter naturally allows to characterize the spatial organization and motions of ligands tracking the minor or major grooves, in a motion reminiscent of sliding. Using this approach, we performed umbrella sampling (US) molecular dynamics (MD) simulations to calculate the three-dimensional potentials of mean force (3D-PMFs) for a Na+ cation and for methyl guanidinium, an arginine analog. The computed PMFs show that, even for small ligands, the free energy landscapes are complex. In general, energy barriers of up to ~5 kcal/mol were measured for removing the ligands from the minor groove, and of ~1.5 kcal/mol for sliding along the minor groove. We shed light on the way the minor groove geometry, defined mainly by the DNA sequence, shapes the binding landscape around DNA, providing heterogeneous environments for recognition by various ligands. For example, we identified the presence of dissociation points or exit ramps that naturally would terminate sliding. We discuss how our findings have important implications for understanding how proteins and ligands associate and slide along DNA. '),
(86989, 2015, 'plos', 'ClonalFrameML: efficient inference of recombination in whole bacterial genomes', 'Didelot, Xavier|Wilson, Daniel J', 'Department of Infectious Disease Epidemiology, Imperial College, London, United Kingdom.|Nuffield Department of Medicine, University of Oxford, John Radcliffe Hospital, Oxford, United Kingdom, Wellcome Trust Centre for Human Genetics, Oxford, United Kingdom.', 'United Kingdom|United Kingdom', 263, 'Clostridium difficile|Computer Simulation|Databases, Genetic|Evolution, Molecular|Genome, Bacterial|Genomics|Phylogeny|Recombination, Genetic|Sequence Analysis, DNA|Software|Staphylococcus aureus', 'Journal Article', '10.1371/journal.pcbi.1004041', '25675341', 'Recombination is an important evolutionary force in bacteria, but it remains challenging to reconstruct the imports that occurred in the ancestry of a genomic sample. Here we present ClonalFrameML, which uses maximum likelihood inference to simultaneously detect recombination in bacterial genomes and account for it in phylogenetic reconstruction. ClonalFrameML can analyse hundreds of genomes in a matter of hours, and we demonstrate its usefulness on simulated and real datasets. We find evidence for recombination hotspots associated with mobile elements in Clostridium difficile ST6 and a previously undescribed 310kb chromosomal replacement in Staphylococcus aureus ST582. ClonalFrameML is freely available at http://clonalframeml.googlecode.com/. '),
(86990, 2015, 'plos', 'Integrative multi-omics module network inference with Lemon-Tree', 'Bonnet, Eric|Calzone, Laurence|Michoel, Tom', 'Institut Curie, Paris, France, INSERM U900, Paris, France, Mines ParisTech, Fontainebleau, France.|Institut Curie, Paris, France, INSERM U900, Paris, France, Mines ParisTech, Fontainebleau, France.|Division of Genetics & Genomics, The Roslin Institute, The University of Edinburgh, Easter Bush, Midlothian, United Kingdom.', 'France|France|United Kingdom', 36, 'Cluster Analysis|Computational Biology|Databases, Genetic|Gene Expression Profiling|Glioblastoma|Humans|Internet|Kaplan-Meier Estimate|Signal Transduction|Software', 'Journal Article', '10.1371/journal.pcbi.1003983', '25679508', 'Module network inference is an established statistical method to reconstruct co-expression modules and their upstream regulatory programs from integrated multi-omics datasets measuring the activity levels of various cellular components across different individuals, experimental conditions or time points of a dynamic process. We have developed Lemon-Tree, an open-source, platform-independent, modular, extensible software package implementing state-of-the-art ensemble methods for module network inference. We benchmarked Lemon-Tree using large-scale tumor datasets and showed that Lemon-Tree algorithms compare favorably with state-of-the-art module network inference software. We also analyzed a large dataset of somatic copy-number alterations and gene expression levels measured in glioblastoma samples from The Cancer Genome Atlas and found that Lemon-Tree correctly identifies known glioblastoma oncogenes and tumor suppressors as master regulators in the inferred module network. Novel candidate driver genes predicted by Lemon-Tree were validated using tumor pathway and survival analyses. Lemon-Tree is available from http://lemon-tree.googlecode.com under the GNU General Public License version 2.0. '),
(86991, 2015, 'plos', 'Input-dependent frequency modulation of cortical gamma oscillations shapes spatial synchronization and enables phase coding', 'Lowet, Eric|Roberts, Mark|Hadjipapas, Avgis|Peter, Alina|van der Eerden, Jan|De Weerd, Peter', 'Psychology and Neuroscience, Maastricht University, Maastricht, The Netherlands, Donders Institute for Brain, Cognition and Behaviour, Radboud University Nijmegen, Nijmegen, The Netherlands.|Psychology and Neuroscience, Maastricht University, Maastricht, The Netherlands, Donders Institute for Brain, Cognition and Behaviour, Radboud University Nijmegen, Nijmegen, The Netherlands.|University of Nicosia Medical School, University of Nicosia, Cyprus, St Georges University of London, London, United Kingdom.|Ernst Strxc3xbcngmann Institute (ESI) for Neuroscience in Cooperation with Max Planck Society, Frankfurt, Germany, International Max Planck Research School for Neural Circuits, Frankfurt, Germany.|Donders Institute for Brain, Cognition and Behaviour, Radboud University Nijmegen, Nijmegen, The Netherlands.|Psychology and Neuroscience, Maastricht University, Maastricht, The Netherlands, Donders Institute for Brain, Cognition and Behaviour, Radboud University Nijmegen, Nijmegen, The Netherlands.', 'Netherlands|Netherlands|Cyprus|Germany|Netherlands|Netherlands', 25, 'Action Potentials|Animals|Computational Biology|Electric Conductivity|Electroencephalography Phase Synchronization|Gamma Rhythm|Humans|Macaca mulatta|Models, Neurological|Visual Cortex', 'Journal Article', '10.1371/journal.pcbi.1004072', '25679780', 'Fine-scale temporal organization of cortical activity in the gamma range (xe2x88xbc25-80Hz) may play a significant role in information processing, for example by neural grouping (binding) and phase coding. Recent experimental studies have shown that the precise frequency of gamma oscillations varies with input drive (e.g. visual contrast) and that it can differ among nearby cortical locations. This has challenged theories assuming widespread gamma synchronization at a fixed common frequency. In the present study, we investigated which principles govern gamma synchronization in the presence of input-dependent frequency modulations and whether they are detrimental for meaningful input-dependent gamma-mediated temporal organization. To this aim, we constructed a biophysically realistic excitatory-inhibitory network able to express different oscillation frequencies at nearby spatial locations. Similarly to cortical networks, the model was topographically organized with spatially local connectivity and spatially-varying input drive. We analyzed gamma synchronization with respect to phase-locking, phase-relations and frequency differences, and quantified the stimulus-related information represented by gamma phase and frequency. By stepwise simplification of our models, we found that the gamma-mediated temporal organization could be reduced to basic synchronization principles of weakly coupled oscillators, where input drive determines the intrinsic (natural) frequency of oscillators. The gamma phase-locking, the precise phase relation and the emergent (measurable) frequencies were determined by two principal factors: the detuning (intrinsic frequency difference, i.e. local input difference) and the coupling strength. In addition to frequency coding, gamma phase contained complementary stimulus information. Crucially, the phase code reflected input differences, but not the absolute input level. This property of relative input-to-phase conversion, contrasting with latency codes or slower oscillation phase codes, may resolve conflicting experimental observations on gamma phase coding. Our modeling results offer clear testable experimental predictions. We conclude that input-dependency of gamma frequencies could be essential rather than detrimental for meaningful gamma-mediated temporal organization of cortical activity. '),
(86992, 2015, 'plos', 'A biologically constrained, mathematical model of cortical wave propagation preceding seizure termination', 'González-Ramírez, Laura R|Ahmed, Omar J|Cash, Sydney S|Wayne, C Eugene|Kramer, Mark A', 'Department of Mathematics and Statistics, Boston University, Boston, Massachusetts, United States of America.|Department of Neurology, Massachusetts General Hospital, Boston, Massachusetts, United States of America, Harvard Medical School, Boston, Massachusetts, United States of America.|Department of Neurology, Massachusetts General Hospital, Boston, Massachusetts, United States of America, Harvard Medical School, Boston, Massachusetts, United States of America.|Department of Mathematics and Statistics, Boston University, Boston, Massachusetts, United States of America.|Department of Mathematics and Statistics, Boston University, Boston, Massachusetts, United States of America.', 'United States|United States|United States|United States|United States', 26, 'Adult|Cerebral Cortex|Electrodes, Implanted|Electroencephalography|Epilepsy|Humans|Male|Middle Aged|Models, Neurological|Seizures|Signal Processing, Computer-Assisted|Young Adult', 'Journal Article', '10.1371/journal.pcbi.1004065', '25689136', 'Epilepsy--the condition of recurrent, unprovoked seizures--manifests in brain voltage activity with characteristic spatiotemporal patterns. These patterns include stereotyped semi-rhythmic activity produced by aggregate neuronal populations, and organized spatiotemporal phenomena, including waves. To assess these spatiotemporal patterns, we develop a mathematical model consistent with the observed neuronal population activity and determine analytically the parameter configurations that support traveling wave solutions. We then utilize high-density local field potential data recorded in vivo from human cortex preceding seizure termination from three patients to constrain the model parameters, and propose basic mechanisms that contribute to the observed traveling waves. We conclude that a relatively simple and abstract mathematical model consisting of localized interactions between excitatory cells with slow adaptation captures the quantitative features of wave propagation observed in the human local field potential preceding seizure termination.'),
(86993, 2015, 'plos', 'Computer simulations suggest a key role of membranous nanodomains in biliary lipid secretion', 'Eckstein, Johannes|Berndt, Nikolaus|Holzhütter, Hermann-Georg', 'Charité-University Medicine Berlin, Institute of Biochemistry, Berlin, Germany.|Charité-University Medicine Berlin, Institute of Biochemistry, Berlin, Germany.|Charité-University Medicine Berlin, Institute of Biochemistry, Berlin, Germany.', 'Germany|Germany|Germany', 4, 'Animals|Bile|Cell Membrane|Cholesterol|Computer Simulation|Hepatocytes|Humans|Membrane Lipids|Mice|Models, Biological|Nanostructures|Phosphatidylcholines|Sphingomyelins', 'Journal Article', '10.1371/journal.pcbi.1004033', '25692493', 'The bile fluid contains various lipids that are secreted at the canalicular membrane of hepatocytes. As the secretion mechanism is still a matter of debate and a direct experimental observation of the secretion process is not possible so far, we used a mathematical model to simulate the extraction of the major bile lipids cholesterol, phosphatidylcholine and sphingomyelin from the outer leaflet of the canalicular membrane. Lipid diffusion was modeled as random movement on a triangular lattice governed by next-neighbor interaction energies. Phase separation in liquid-ordered and liquid-disordered domains was modeled by assigning two alternative ordering states to each lipid species and minimization of next-neighbor ordering energies. Parameterization of the model was performed such that experimentally determined diffusion rates and phases in ternary lipid mixtures of model membranes were correctly recapitulated. The model describes the spontaneous formation of nanodomains in the external leaflet of the canalicular membrane in a time window between 0.1 ms to 10 ms at varying lipid proportions. The extraction of lipid patches from the bile salt soluble nanodomain into the bile reproduced observed biliary phospholipid compositions for a physiological membrane composition. Comparing the outcome of model simulations with available experimental observations clearly favors the extraction of tiny membrane patches composed of about 100-400 lipids as the likely mechanism of biliary lipid secretion.'),
(86994, 2015, 'plos', 'A unified model of shoot tropism in plants: photo-, gravi- and Propio-ception', 'Bastien, Renaud|Douady, Stéphane|Moulia, Bruno', 'Institut Jean-Pierre Bourgin, UMR1318 INRA-AgroParisTech, 78026 Versailles, France, INRA, UMR 547 PIAF, F-63100 Clermont Fd Cedex 01, France, Clermont Université, Université Blaise Pascal, UMR 547 PIAF, BP 10448, F-63000 Clermont-Ferrand, France, School of Engineering and Applied Sciences, Harvard University, Cambridge, MA 02138, USA.|Matière et Systèmes Complexes, Université Paris-Diderot, 75025 Paris Cedex 13, France.|INRA, UMR 547 PIAF, F-63100 Clermont Fd Cedex 01, France, Clermont Université, Université Blaise Pascal, UMR 547 PIAF, BP 10448, F-63000 Clermont-Ferrand, France.', 'France|France|France', 21, 'Computational Biology|Gravitropism|Models, Biological|Phenotype|Phototropism|Plant Shoots', 'Journal Article', '10.1371/journal.pcbi.1004037', '25692607', 'Land plants rely mainly on gravitropism and phototropism to control their posture and spatial orientation. In natural conditions, these two major tropisms act concurrently to create a photogravitropic equilibrium in the responsive organ. Recently, a parsimonious model was developed that accurately predicted the complete gravitropic and proprioceptive control over the movement of different organs in different species in response to gravitational stimuli. Here we show that the framework of this unifying graviproprioceptive model can be readily extended to include phototropism. The interaction between gravitropism and phototropism results in an alignment of the apical part of the organ toward a photogravitropic set-point angle. This angle is determined by a combination of the two directional stimuli, gravity and light, weighted by the ratio between the gravi- and photo-sensitivities of the plant organ. In the model, two dimensionless numbers, the graviproprioceptive number B and the photograviceptive number M, control the dynamics and the shapes of the movement. The extended model agrees well with two sets of detailed quantitative data on photogravitropic equilibrium in oat coleoptiles. It is demonstrated that the influence of light intensity I can be included in the model in a power-law-dependent relationship M(I). The numbers B and M and the related photograviceptive number D are all quantitative genetic traits that can be measured in a straightforward manner, opening the way to the phenotyping of molecular and mechanical aspects of shoot tropism. '),
(86995, 2015, 'plos', 'The roles of post-translational modifications in the context of protein interaction networks', 'Duan, Guangyou|Walther, Dirk', 'Max Planck Institute for Molecular Plant Physiology, Potsdam-Golm, Germany.|Max Planck Institute for Molecular Plant Physiology, Potsdam-Golm, Germany.', 'Germany|Germany', 128, 'Animals|Cluster Analysis|Databases, Protein|Glycosylation|Humans|Phosphorylation|Protein Interaction Maps|Protein Processing, Post-Translational|Proteomics', 'Journal Article', '10.1371/journal.pcbi.1004049', '25692714', 'Among other effects, post-translational modifications (PTMs) have been shown to exert their function via the modulation of protein-protein interactions. For twelve different main PTM-types and associated subtypes and across 9 diverse species, we investigated whether particular PTM-types are associated with proteins with specific and possibly strategic placements in the network of all protein interactions by determining informative network-theoretic properties. Proteins undergoing a PTM were observed to engage in more interactions and positioned in more central locations than non-PTM proteins. Among the twelve considered PTM-types, phosphorylated proteins were identified most consistently as being situated in central network locations and with the broadest interaction spectrum to proteins carrying other PTM-types, while glycosylated proteins are preferentially located at the network periphery. For the human interactome, proteins undergoing sumoylation or proteolytic cleavage were found with the most characteristic network properties. PTM-type-specific protein interaction network (PIN) properties can be rationalized with regard to the function of the respective PTM-carrying proteins. For example, glycosylation sites were found enriched in proteins with plasma membrane localizations and transporter or receptor activity, which generally have fewer interacting partners. The involvement in disease processes of human proteins undergoing PTMs was also found associated with characteristic PIN properties. By integrating global protein interaction networks and specific PTMs, our study offers a novel approach to unraveling the role of PTMs in cellular processes. '),
(86996, 2015, 'plos', 'Heterogeneous CD8+ T cell migration in the lymph node in the absence of inflammation revealed by quantitative migration analysis', 'Banigan, Edward J|Harris, Tajie H|Christian, David A|Hunter, Christopher A|Liu, Andrea J', 'Department of Physics and Astronomy, School of Arts and Sciences, University of Pennsylvania, Philadelphia, Philadelphia, United States of America, Department of Physics and Astronomy, Northwestern University, Evanston, Illinois, United States of America.|Department of Pathobiology, School of Veterinary Medicine, University of Pennsylvania, Philadelphia, Philadelphia, United States of America, Department of Neuroscience, School of Medicine, University of Virginia, Charlottesville, Virginia, United States of America.|Department of Pathobiology, School of Veterinary Medicine, University of Pennsylvania, Philadelphia, Philadelphia, United States of America.|Department of Pathobiology, School of Veterinary Medicine, University of Pennsylvania, Philadelphia, Philadelphia, United States of America.|Department of Physics and Astronomy, School of Arts and Sciences, University of Pennsylvania, Philadelphia, Philadelphia, United States of America.', 'United States|United States|United States|United States|United States', 27, 'Animals|CD8-Positive T-Lymphocytes|Cell Movement|Cells, Cultured|Computational Biology|Computer Simulation|Lymph Nodes|Mice|Mice, Inbred C57BL|Mice, Transgenic|Models, Immunological|Spleen', 'Journal Article', '10.1371/journal.pcbi.1004058', '25692801', 'The three-dimensional positions of immune cells can be tracked in live tissues precisely as a function of time using two-photon microscopy. However, standard methods of analysis used in the field and experimental artifacts can bias interpretations and obscure important aspects of cell migration such as directional migration and non-Brownian walk statistics. Therefore, methods were developed for minimizing drift artifacts, identifying directional and anisotropic (asymmetric) migration, and classifying cell migration statistics. These methods were applied to describe the migration statistics of CD8+ T cells in uninflamed lymph nodes. Contrary to current models, CD8+ T cell statistics are not well described by a straightforward persistent random walk model. Instead, a model in which one population of cells moves via Brownian-like motion and another population follows variable persistent random walks with noise reproduces multiple statistical measures of CD8+ T cell migration in the lymph node in the absence of inflammation. '),
(86997, 2015, 'plos', 'Statistical mechanics provides novel insights into microtubule stability and mechanism of shrinkage', 'Jain, Ishutesh|Inamdar, Mandar M|Padinhateeri, Ranjith', '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 Biosciences and Bioengineering, Indian Institute of Technology Bombay, Mumbai, India.', 'India|India|India', 0, 'Biomechanical Phenomena|Computational Biology|Guanosine Diphosphate|Microtubules|Models, Molecular|Protein Stability|Thermodynamics|Tubulin', 'Journal Article', '10.1371/journal.pcbi.1004099', '25692909', 'Microtubules are nano-machines that grow and shrink stochastically, making use of the coupling between chemical kinetics and mechanics of its constituent protofilaments (PFs). We investigate the stability and shrinkage of microtubules taking into account inter-protofilament interactions and bending interactions of intrinsically curved PFs. Computing the free energy as a function of PF tip position, we show that the competition between curvature energy, inter-PF interaction energy and entropy leads to a rich landscape with a series of minima that repeat over a length-scale determined by the intrinsic curvature. Computing Langevin dynamics of the tip through the landscape and accounting for depolymerization, we calculate the average unzippering and shrinkage velocities of GDP protofilaments and compare them with the experimentally known results. Our analysis predicts that the strength of the inter-PF interaction (E(s)(m)) has to be comparable to the strength of the curvature energy (E(b)(m)) such that E(s)(m) - E(b)(m) xe2x89x88 1kBT, and questions the prevalent notion that unzippering results from the domination of bending energy of curved GDP PFs. Our work demonstrates how the shape of the free energy landscape is crucial in explaining the mechanism of MT shrinkage where the unzippered PFs will fluctuate in a set of partially peeled off states and subunit dissociation will reduce the length.'),
(86998, 2015, 'plos', 'Resting-state temporal synchronization networks emerge from connectivity topology and heterogeneity', 'Ponce-Alvarez, Adrián|Deco, Gustavo|Hagmann, Patric|Romani, Gian Luca|Mantini, Dante|Corbetta, Maurizio', 'Center for Brain and Cognition, Computational Neuroscience Group, Department of Information and Communication Technologies, Universitat Pompeu Fabra, Barcelona, Spain.|Center for Brain and Cognition, Computational Neuroscience Group, Department of Information and Communication Technologies, Universitat Pompeu Fabra, Barcelona, Spain, Institució Catalana de la Recerca i Estudis Avançats (ICREA), Universitat Pompeu Fabra, Barcelona, Spain.|Department of Radiology, Lausanne University Hospital and University of Lausanne (CHUV-UNIL), Lausanne, Switzerland, Signal Processing Lab 5, Ecole Polytechnique Fédérale de Lausanne (EPFL), Lausanne, Switzerland.|Institute of Advanced Biomedical Technologies-G. dAnnunzio University Foundation, Department of Neuroscience and Imaging, G. dAnnunzio University, Chieti, Italy.|Department of Health Sciences and Technology, ETH Zurich, Zurich, Switzerland, Department of Experimental Psychology, University of Oxford, Oxford, United Kingdom.|Department of Neurology, Radiology, Anatomy of Neurobiology, School of Medicine, Washington University in St. Louis, St. Louis, Missouri, United States of America.', 'Spain|Spain|Switzerland|Italy|Switzerland|United States', 99, 'Adult|Brain|Brain Mapping|Electroencephalography Phase Synchronization|Female|Humans|Magnetic Resonance Imaging|Male|Models, Neurological|Young Adult', 'Journal Article', '10.1371/journal.pcbi.1004100', '25692996', 'Spatial patterns of coherent activity across different brain areas have been identified during the resting-state fluctuations of the brain. However, recent studies indicate that resting-state activity is not stationary, but shows complex temporal dynamics. We were interested in the spatiotemporal dynamics of the phase interactions among resting-state fMRI BOLD signals from human subjects. We found that the global phase synchrony of the BOLD signals evolves on a characteristic ultra-slow (<0.01Hz) time scale, and that its temporal variations reflect the transient formation and dissolution of multiple communities of synchronized brain regions. Synchronized communities reoccurred intermittently in time and across scanning sessions. We found that the synchronization communities relate to previously defined functional networks known to be engaged in sensory-motor or cognitive function, called resting-state networks (RSNs), including the default mode network, the somato-motor network, the visual network, the auditory network, the cognitive control networks, the self-referential network, and combinations of these and other RSNs. We studied the mechanism originating the observed spatiotemporal synchronization dynamics by using a network model of phase oscillators connected through the brains anatomical connectivity estimated using diffusion imaging human data. The model consistently approximates the temporal and spatial synchronization patterns of the empirical data, and reveals that multiple clusters that transiently synchronize and desynchronize emerge from the complex topology of anatomical connections, provided that oscillators are heterogeneous. '),
(86999, 2015, 'plos', 'Potential benefits of cattle vaccination as a supplementary control for bovine tuberculosis', 'Conlan, Andrew J K|Brooks Pollock, Ellen|McKinley, Trevelyan J|Mitchell, Andrew P|Jones, Gareth J|Vordermeier, Martin|Wood, James L N', 'Disease Dynamics Unit (DDU), Department of Veterinary Medicine, University of Cambridge, Cambridge, United Kingdom.|Disease Dynamics Unit (DDU), Department of Veterinary Medicine, University of Cambridge, Cambridge, United Kingdom.|Disease Dynamics Unit (DDU), Department of Veterinary Medicine, University of Cambridge, Cambridge, United Kingdom.|Data Systems Group, Animal & Plant Health Agency Weybridge, New Haw, Addlestone, Surrey, United Kingdom.|Department of Bacteriology (TB Research), Animal & Plant Health Agency Weybridge, New Haw, Addlestone, Surrey, United Kingdom.|Department of Bacteriology (TB Research), Animal & Plant Health Agency Weybridge, New Haw, Addlestone, Surrey, United Kingdom.|Disease Dynamics Unit (DDU), Department of Veterinary Medicine, University of Cambridge, Cambridge, United Kingdom.', 'United Kingdom|United Kingdom|United Kingdom|United Kingdom|United Kingdom|United Kingdom|United Kin', 20, 'Animal Husbandry|Animals|Cattle|Computational Biology|Immunity, Herd|Legislation, Veterinary|Models, Immunological|Mycobacterium bovis|Tuberculosis Vaccines|Tuberculosis, Bovine|United Kingdom|Vaccination', 'Journal Article', '10.1371/journal.pcbi.1004038', '25695736', 'Vaccination for the control of bovine tuberculosis (bTB) in cattle is not currently used within any international control program, and is illegal within the EU. Candidate vaccines, based upon Mycobacterium bovis bacillus Calmette-Guérin (BCG) all interfere with the action of the tuberculin skin test, which is used to determine if animals, herds and countries are officially bTB-free. New diagnostic tests that Differentiate Infected from Vaccinated Animals (DIVA) offer the potential to introduce vaccination within existing eradication programs. We use within-herd transmission models estimated from historical data from Great Britain (GB) to explore the feasibility of such supplemental use of vaccination. The economic impact of bovine Tuberculosis for farmers is dominated by the costs associated with testing, and associated restrictions on animal movements. Farmers willingness to adopt vaccination will require vaccination to not only reduce the burden of infection, but also the risk of restrictions being imposed. We find that, under the intensive sequence of testing in GB, it is the specificity of the DIVA test, rather than the sensitivity, that is the greatest barrier to see a herd level benefit of vaccination. The potential negative effects of vaccination could be mitigated through relaxation of testing. However, this could potentially increase the hidden burden of infection within Officially TB Free herds. Using our models, we explore the range of the DIVA test characteristics necessary to see a protective herd level benefit of vaccination. We estimate that a DIVA specificity of at least 99.85% and sensitivity of >40% is required to see a protective benefit of vaccination with no increase in the risk of missed infection. Data from experimentally infected animals suggest that this target specificity could be achieved in vaccinates using a cocktail of three DIVA antigens while maintaining a sensitivity of 73.3% (95%CI: 61.9, 82.9%) relative to post-mortem detection. '),
(87000, 2015, 'plos', 'Data-driven prediction and design of bZIP coiled-coil interactions', 'Potapov, Vladimir|Kaplan, Jenifer B|Keating, Amy E', 'Department of Biology, Massachusetts Institute of Technology, Cambridge, Massachusetts, United States of America.|Department of Biology, Massachusetts Institute of Technology, Cambridge, Massachusetts, United States of America.|Department of Biology, Massachusetts Institute of Technology, Cambridge, Massachusetts, United States of America, Department of Biological Engineering, Massachusetts Institute of Technology, Cambridge, Massachusetts, United States of America.', 'United States|United States|United States', 0, 'Amino Acid Sequence|Basic-Leucine Zipper Transcription Factors|Computational Biology|Humans|Models, Molecular|Models, Statistical|Peptides|Protein Multimerization|Protein Structure, Secondary', 'Journal Article', '10.1371/journal.pcbi.1004046', '25695764', 'Selective dimerization of the basic-region leucine-zipper (bZIP) transcription factors presents a vivid example of how a high degree of interaction specificity can be achieved within a family of structurally similar proteins. The coiled-coil motif that mediates homo- or hetero-dimerization of the bZIP proteins has been intensively studied, and a variety of methods have been proposed to predict these interactions from sequence data. In this work, we used a large quantitative set of 4,549 bZIP coiled-coil interactions to develop a predictive model that exploits knowledge of structurally conserved residue-residue interactions in the coiled-coil motif. Our model, which expresses interaction energies as a sum of interpretable residue-pair and triplet terms, achieves a correlation with experimental binding free energies of R = 0.68 and significantly out-performs other scoring functions. To use our model in protein design applications, we devised a strategy in which synthetic peptides are built by assembling 7-residue native-protein heptad modules into new combinations. An integer linear program was used to find the optimal combination of heptads to bind selectively to a target human bZIP coiled coil, but not to target paralogs. Using this approach, we designed peptides to interact with the bZIP domains from human JUN, XBP1, ATF4 and ATF5. Testing more than 132 candidate protein complexes using a fluorescence resonance energy transfer assay confirmed the formation of tight and selective heterodimers between the designed peptides and their targets. This approach can be used to make inhibitors of native proteins, or to develop novel peptides for applications in synthetic biology or nanotechnology. '),
(87001, 2015, 'plos', 'Modulation of network excitability by persistent activity: how working memory affects the response to incoming stimuli', 'Tartaglia, Elisa M|Brunel, Nicolas|Mongillo, Gianluigi', 'Center for Neuroscience and Cognitive Systems @UniTn, Istituto Italiano di Tecnologia, Rovereto, Italy, Centre National de la Recherche Scientifique, Paris, France, Université Paris Descartes, Centre de Neurophysique, Physiologie et Pathologie, Paris, France, Departments of Statistics and Neurobiology, University of Chicago, Chicago, Illinois, United States of America.|Centre National de la Recherche Scientifique, Paris, France.|Université Paris Descartes, Centre de Neurophysique, Physiologie et Pathologie, Paris, France, Departments of Statistics and Neurobiology, University of Chicago, Chicago, Illinois, United States of America.', 'France|France|France', 1, 'Action Potentials|Computational Biology|Memory, Short-Term|Models, Neurological|Neurons|Physical Stimulation|Receptors, Neurotransmitter', 'Journal Article', '10.1371/journal.pcbi.1004059', '25695777', 'Persistent activity and match effects are widely regarded as neuronal correlates of short-term storage and manipulation of information, with the first serving active maintenance and the latter supporting the comparison between memory contents and incoming sensory information. The mechanistic and functional relationship between these two basic neurophysiological signatures of working memory remains elusive. We propose that match signals are generated as a result of transient changes in local network excitability brought about by persistent activity. Neurons more active will be more excitable, and thus more responsive to external inputs. Accordingly, network responses are jointly determined by the incoming stimulus and the ongoing pattern of persistent activity. Using a spiking model network, we show that this mechanism is able to reproduce most of the experimental phenomenology of match effects as exposed by single-cell recordings during delayed-response tasks. The model provides a unified, parsimonious mechanistic account of the main neuronal correlates of working memory, makes several experimentally testable predictions, and demonstrates a new functional role for persistent activity. '),
(87002, 2015, 'plos', 'Selectivity by small-molecule inhibitors of protein interactions can be driven by protein surface fluctuations', 'Johnson, David K|Karanicolas, John', 'Center for Computational Biology, University of Kansas, Lawrence, Kansas, United States of America.|Center for Computational Biology, University of Kansas, Lawrence, Kansas, United States of America, Department of Molecular Biosciences, University of Kansas, Lawrence, Kansas, United States of America.', 'United States|United States', 19, 'Animals|Binding Sites|Computational Biology|Computer Simulation|Drug Discovery|Humans|Mice|Models, Molecular|Protein Conformation|Proto-Oncogene Proteins c-bcl-2|Surface Properties|Thermodynamics', 'Journal Article', '10.1371/journal.pcbi.1004081', '25706586', 'Small-molecules that inhibit interactions between specific pairs of proteins have long represented a promising avenue for therapeutic intervention in a variety of settings. Structural studies have shown that in many cases, the inhibitor-bound protein adopts a conformation that is distinct from its unbound and its protein-bound conformations. This plasticity of the protein surface presents a major challenge in predicting which members of a protein family will be inhibited by a given ligand. Here, we use biased simulations of Bcl-2-family proteins to generate ensembles of low-energy conformations that contain surface pockets suitable for small molecule binding. We find that the resulting conformational ensembles include surface pockets that mimic those observed in inhibitor-bound crystal structures. Next, we find that the ensembles generated using different members of this protein family are overlapping but distinct, and that the activity of a given compound against a particular family member (ligand selectivity) can be predicted from whether the corresponding ensemble samples a complementary surface pocket. Finally, we find that each ensemble includes certain surface pockets that are not shared by any other family member: while no inhibitors have yet been identified to take advantage of these pockets, we expect that chemical scaffolds complementing these distinct pockets will prove highly selective for their targets. The opportunity to achieve target selectivity within a protein family by exploiting differences in surface fluctuations represents a new paradigm that may facilitate design of family-selective small-molecule inhibitors of protein-protein interactions. '),
(87003, 2015, 'plos', 'PathVisio 3: an extendable pathway analysis toolbox', 'Kutmon, Martina|van Iersel, Martijn P|Bohler, Anwesha|Kelder, Thomas|Nunes, Nuno|Pico, Alexander R|Evelo, Chris T', 'Department of Bioinformatics - BiGCaT, Maastricht University, Maastricht, The Netherlands, Maastricht Centre for Systems Biology (MaCSBio), Maastricht University, Maastricht, The Netherlands.|General Bioinformatics, Reading, United Kingdom.|Department of Bioinformatics - BiGCaT, Maastricht University, Maastricht, The Netherlands.|EdgeLeap B.V., Utrecht, The Netherlands.|Department of Bioinformatics - BiGCaT, Maastricht University, Maastricht, The Netherlands.|Gladstone Institutes, San Francisco, California, United States of America.|Department of Bioinformatics - BiGCaT, Maastricht University, Maastricht, The Netherlands.', 'Netherlands|United Kingdom|Netherlands|Netherlands|Netherlands|United States|Netherlands', 170, 'Animals|Computational Biology|Databases, Factual|Humans|Internet|Metabolomics|Mice|Signal Transduction|Software', 'Journal Article', '10.1371/journal.pcbi.1004085', '25706687', 'PathVisio is a commonly used pathway editor, visualization and analysis software. Biological pathways have been used by biologists for many years to describe the detailed steps in biological processes. Those powerful, visual representations help researchers to better understand, share and discuss knowledge. Since the first publication of PathVisio in 2008, the original paper was cited more than 170 times and PathVisio was used in many different biological studies. As an online editor PathVisio is also integrated in the community curated pathway database WikiPathways. Here we present the third version of PathVisio with the newest additions and improvements of the application. The core features of PathVisio are pathway drawing, advanced data visualization and pathway statistics. Additionally, PathVisio 3 introduces a new powerful extension systems that allows other developers to contribute additional functionality in form of plugins without changing the core application. PathVisio can be downloaded from http://www.pathvisio.org and in 2014 PathVisio 3 has been downloaded over 5,500 times. There are already more than 15 plugins available in the central plugin repository. PathVisio is a freely available, open-source tool published under the Apache 2.0 license (http://www.apache.org/licenses/LICENSE-2.0). It is implemented in Java and thus runs on all major operating systems. The code repository is available at http://svn.bigcat.unimaas.nl/pathvisio. The support mailing list for users is available on https://groups.google.com/forum/#!forum/wikipathways-discuss and for developers on https://groups.google.com/forum/#!forum/wikipathways-devel. '),
(87004, 2015, 'plos', 'Segment-specific adhesion as a driver of convergent extension', 'Vroomans, Renske M A|Hogeweg, Paulien|ten Tusscher, Kirsten H W J', 'Theoretical Biology and Bioinformatics, Utrecht University, Utrecht, The Netherlands.|Theoretical Biology and Bioinformatics, Utrecht University, Utrecht, The Netherlands.|Theoretical Biology and Bioinformatics, Utrecht University, Utrecht, The Netherlands.', 'Netherlands|Netherlands|Netherlands', 11, 'Animals|Body Patterning|Cell Adhesion|Computational Biology|Computer Simulation|Models, Biological', 'Journal Article', '10.1371/journal.pcbi.1004092', '25706823', 'Convergent extension, the simultaneous extension and narrowing of tissues, is a crucial event in the formation of the main body axis during embryonic development. It involves processes on multiple scales: the sub-cellular, cellular and tissue level, which interact via explicit or intrinsic feedback mechanisms. Computational modelling studies play an important role in unravelling the multiscale feedbacks underlying convergent extension. Convergent extension usually operates in tissue which has been patterned or is currently being patterned into distinct domains of gene expression. How such tissue patterns are maintained during the large scale tissue movements of convergent extension has thus far not been investigated. Intriguingly, experimental data indicate that in certain cases these tissue patterns may drive convergent extension rather than requiring safeguarding against convergent extension. Here we use a 2D Cellular Potts Model (CPM) of a tissue prepatterned into segments, to show that convergent extension tends to disrupt this pre-existing segmental pattern. However, when cells preferentially adhere to cells of the same segment type, segment integrity is maintained without any reduction in tissue extension. Strikingly, we demonstrate that this segment-specific adhesion is by itself sufficient to drive convergent extension. Convergent extension is enhanced when we endow our in silico cells with persistence of motion, which in vivo would naturally follow from cytoskeletal dynamics. Finally, we extend our model to confirm the generality of our results. We demonstrate a similar effect of differential adhesion on convergent extension in tissues that can only extend in a single direction (as often occurs due to the inertia of the head region of the embryo), and in tissues prepatterned into a sequence of domains resulting in two opposing adhesive gradients, rather than alternating segments. '),
(87005, 2015, 'plos', 'Critical slowing down governs the transition to neuron spiking', 'Meisel, Christian|Klaus, Andreas|Kuehn, Christian|Plenz, Dietmar', 'Section on Critical Brain Dynamics, National Institute of Mental Health, Bethesda, Maryland, United States of America, Department of Neurology, University Clinic Carl Gustav Carus, Dresden, Germany.|Section on Critical Brain Dynamics, National Institute of Mental Health, Bethesda, Maryland, United States of America.|Institute for Analysis and Scientific Computing, Vienna University of Technology, Vienna, Austria.|Section on Critical Brain Dynamics, National Institute of Mental Health, Bethesda, Maryland, United States of America.', 'Germany|United States|Austria|United States', 25, 'Action Potentials|Animals|Brain|Computational Biology|Models, Neurological|Neurons|Rats, Sprague-Dawley|Stochastic Processes', 'Journal Article', '10.1371/journal.pcbi.1004097', '25706912', 'Many complex systems have been found to exhibit critical transitions, or so-called tipping points, which are sudden changes to a qualitatively different system state. These changes can profoundly impact the functioning of a system ranging from controlled state switching to a catastrophic break-down, signals that predict critical transitions are therefore highly desirable. To this end, research efforts have focused on utilizing qualitative changes in markers related to a systems tendency to recover more slowly from a perturbation the closer it gets to the transition--a phenomenon called critical slowing down. The recently studied scaling of critical slowing down offers a refined path to understand critical transitions: to identify the transition mechanism and improve transition prediction using scaling laws. Here, we outline and apply this strategy for the first time in a real-world system by studying the transition to spiking in neurons of the mammalian cortex. The dynamical system approach has identified two robust mechanisms for the transition from subthreshold activity to spiking, saddle-node and Hopf bifurcation. Although theory provides precise predictions on signatures of critical slowing down near the bifurcation to spiking, quantitative experimental evidence has been lacking. Using whole-cell patch-clamp recordings from pyramidal neurons and fast-spiking interneurons, we show that 1) the transition to spiking dynamically corresponds to a critical transition exhibiting slowing down, 2) the scaling laws suggest a saddle-node bifurcation governing slowing down, and 3) these precise scaling laws can be used to predict the bifurcation point from a limited window of observation. To our knowledge this is the first report of scaling laws of critical slowing down in an experiment. They present a missing link for a broad class of neuroscience modeling and suggest improved estimation of tipping points by incorporating scaling laws of critical slowing down as a strategy applicable to other complex systems.'),
(87006, 2015, 'plos', 'Co-evolutionary dynamics of collective action with signaling for a quorum', 'Pacheco, Jorge M|Vasconcelos, Vítor V|Santos, Francisco C|Skyrms, Brian', 'Centro de Biologia Molecular e Ambiental, Universidade do Minho, Braga, Portugal, Departamento de Matemática e Aplicações, Universidade do Minho, Braga, Portugal, ATP-Group, CMAF, Instituto para a Investigação Interdisciplinar, Lisboa, Portugal.|ATP-Group, CMAF, Instituto para a Investigação Interdisciplinar, Lisboa, Portugal, Centro de Física da Universidade do Minho, Braga, Portugal, INESC-ID and Instituto Superior Técnico, Universidade de Lisboa, IST-Taguspark, Porto Salvo, Portugal.|INESC-ID and Instituto Superior Técnico, Universidade de Lisboa, IST-Taguspark, Porto Salvo, Portugal, ATP-Group, CMAF, Instituto para a Investigação Interdisciplinar, Lisboa, Portugal.|Logic and Philosophy of Science, School of Social Sciences, University of California at Irvine, Irvine, California, United States of America.', 'Portugal|Portugal|Portugal|United States', 16, 'Animals|Bacteria|Communication|Computational Biology|Decision Making|Game Theory|Humans|Models, Biological|Population Dynamics|Quorum Sensing', 'Journal Article', '10.1371/journal.pcbi.1004101', '25706984', 'Collective signaling for a quorum is found in a wide range of organisms that face collective action problems whose successful solution requires the participation of some quorum of the individuals present. These range from humans, to social insects, to bacteria. The mechanisms involved, the quorum required, and the size of the group may vary. Here we address the general question of the evolution of collective signaling at a high level of abstraction. We investigate the evolutionary dynamics of a population engaging in a signaling N-person game theoretic model. Parameter settings allow for loners and cheaters, and for costly or costless signals. We find a rich dynamics, showing how natural selection, operating on a population of individuals endowed with the simplest strategies, is able to evolve a costly signaling system that allows individuals to respond appropriately to different states of Nature. Signaling robustly promotes cooperative collective action, in particular when coordinated action is most needed and difficult to achieve. Two different signaling systems may emerge depending on Natures most prevalent states. ');
INSERT INTO `papers` (`id`, `ano`, `journal`, `titulo`, `autores`, `afiliacao`, `pais`, `citacoes`, `palavra_chave`, `categorias`, `doi`, `pubmed`, `abstract`) VALUES
(87007, 2015, 'plos', 'Membrane-mediated interaction between strongly anisotropic protein scaffolds', 'Schweitzer, Yonatan|Kozlov, Michael M', 'Department of Physiology and Pharmacology, Sackler Faculty of Medicine, Tel Aviv University, Tel Aviv, Israel.|Department of Physiology and Pharmacology, Sackler Faculty of Medicine, Tel Aviv University, Tel Aviv, Israel.', 'Israel|Israel', 39, 'Anisotropy|Biophysical Phenomena|Cell Membrane|Lipid Bilayers|Membrane Proteins|Models, Chemical', 'Journal Article', '10.1371/journal.pcbi.1004054', '25710602', 'Specialized proteins serve as scaffolds sculpting strongly curved membranes of intracellular organelles. Effective membrane shaping requires segregation of these proteins into domains and is, therefore, critically dependent on the protein-protein interaction. Interactions mediated by membrane elastic deformations have been extensively analyzed within approximations of large inter-protein distances, small extents of the protein-mediated membrane bending and small deviations of the protein shapes from isotropic spherical segments. At the same time, important classes of the realistic membrane-shaping proteins have strongly elongated shapes with large and highly anisotropic curvature. Here we investigated, computationally, the membrane mediated interaction between proteins or protein oligomers representing membrane scaffolds with strongly anisotropic curvature, and addressed, quantitatively, a specific case of the scaffold geometrical parameters characterizing BAR domains, which are crucial for membrane shaping in endocytosis. In addition to the previously analyzed contributions to the interaction, we considered a repulsive force stemming from the entropy of the scaffold orientation. We computed this interaction to be of the same order of magnitude as the well-known attractive force related to the entropy of membrane undulations. We demonstrated the scaffold shape anisotropy to cause a mutual aligning of the scaffolds and to generate a strong attractive interaction bringing the scaffolds close to each other to equilibrium distances much smaller than the scaffold size. We computed the energy of interaction between scaffolds of a realistic geometry to constitute tens of kBT, which guarantees a robust segregation of the scaffolds into domains. '),
(87008, 2015, 'plos', 'Correlations and functional connections in a population of grid cells', 'Dunn, Benjamin|Mørreaunet, Maria|Roudi, Yasser', 'Kavli Institute for Systems Neuroscience and Centre for Neural Computation, NTNU, Trondheim, Norway.|Kavli Institute for Systems Neuroscience and Centre for Neural Computation, NTNU, Trondheim, Norway.|Kavli Institute for Systems Neuroscience and Centre for Neural Computation, NTNU, Trondheim, Norway, Nordita, KTH and Stockholm University, Stockholm, Sweden.', 'Norway|Norway|Norway', 36, 'Action Potentials|Animals|Entorhinal Cortex|Male|Models, Neurological|Models, Statistical|Nerve Net|Neurons|Rats|Rats, Long-Evans', 'Journal Article', '10.1371/journal.pcbi.1004052', '25714908', 'We study the statistics of spike trains of simultaneously recorded grid cells in freely behaving rats. We evaluate pairwise correlations between these cells and, using a maximum entropy kinetic pairwise model (kinetic Ising model), study their functional connectivity. Even when we account for the covariations in firing rates due to overlapping fields, both the pairwise correlations and functional connections decay as a function of the shortest distance between the vertices of the spatial firing pattern of pairs of grid cells, i.e. their phase difference. They take positive values between cells with nearby phases and approach zero or negative values for larger phase differences. We find similar results also when, in addition to correlations due to overlapping fields, we account for correlations due to theta oscillations and head directional inputs. The inferred connections between neurons in the same module and those from different modules can be both negative and positive, with a mean close to zero, but with the strongest inferred connections found between cells of the same module. Taken together, our results suggest that grid cells in the same module do indeed form a local network of interconnected neurons with a functional connectivity that supports a role for attractor dynamics in the generation of grid pattern. '),
(87009, 2015, 'plos', 'A theoretical justification for single molecule peptide sequencing', 'Swaminathan, Jagannath|Boulgakov, Alexander A|Marcotte, Edward M', 'Center for Systems and Synthetic Biology, University of Texas at Austin, Austin, Texas, United States of America, Institute for Cellular and Molecular Biology, University of Texas at Austin, Austin, Texas, United States of America.|Center for Systems and Synthetic Biology, University of Texas at Austin, Austin, Texas, United States of America, Institute for Cellular and Molecular Biology, University of Texas at Austin, Austin, Texas, United States of America.|Center for Systems and Synthetic Biology, University of Texas at Austin, Austin, Texas, United States of America, Institute for Cellular and Molecular Biology, University of Texas at Austin, Austin, Texas, United States of America, Department of Molecular Biosciences, University of Texas at Austin, Austin, Texas, United States of America.', 'United States|United States|United States', 21, 'Amino Acids|Computational Biology|Computer Simulation|Databases, Protein|Fluorescent Dyes|Peptides|Sequence Analysis, Protein', 'Journal Article', '10.1371/journal.pcbi.1004080', '25714988', 'The proteomes of cells, tissues, and organisms reflect active cellular processes and change continuously in response to intracellular and extracellular cues. Deep, quantitative profiling of the proteome, especially if combined with mRNA and metabolite measurements, should provide an unprecedented view of cell state, better revealing functions and interactions of cell components. Molecular diagnostics and biomarker discovery should benefit particularly from the accurate quantification of proteomes, since complex diseases like cancer change protein abundances and modifications. Currently, shotgun mass spectrometry is the primary technology for high-throughput protein identification and quantification, while powerful, it lacks high sensitivity and coverage. We draw parallels with next-generation DNA sequencing and propose a strategy, termed fluorosequencing, for sequencing peptides in a complex protein sample at the level of single molecules. In the proposed approach, millions of individual fluorescently labeled peptides are visualized in parallel, monitoring changing patterns of fluorescence intensity as N-terminal amino acids are sequentially removed, and using the resulting fluorescence signatures (fluorosequences) to uniquely identify individual peptides. We introduce a theoretical foundation for fluorosequencing and, by using Monte Carlo computer simulations, we explore its feasibility, anticipate the most likely experimental errors, quantify their potential impact, and discuss the broad potential utility offered by a high-throughput peptide sequencing technology. '),
(87010, 2015, 'plos', 'Integrative analysis of circadian transcriptome and metabolic network reveals the role of de novo purine synthesis in circadian control of cell cycle', 'Li, Ying|Li, Guang|Görling, Benjamin|Luy, Burkhard|Du, Jiulin|Yan, Jun', 'CAS-MPG Partner Institute for Computational Biology, Chinese Academy of Sciences, Shanghai, China.|CAS-MPG Partner Institute for Computational Biology, Chinese Academy of Sciences, Shanghai, China.|Institute of Organic Chemistry, Karlsruhe Institute of Technology (KIT), Karlsruhe, Germany, Institute for Biological Interfaces, Karlsruhe Institute of Technology, Eggenstein-Leopoldshafen, Karlsruhe, Germany.|Institute of Organic Chemistry, Karlsruhe Institute of Technology (KIT), Karlsruhe, Germany, Institute for Biological Interfaces, Karlsruhe Institute of Technology, Eggenstein-Leopoldshafen, Karlsruhe, Germany.|Institute of Neuroscience, Shanghai Institutes of Biological Sciences, Chinese Academy of Sciences, Shanghai, China.|CAS-MPG Partner Institute for Computational Biology, Chinese Academy of Sciences, Shanghai, China.', 'China|China|Germany|Germany|China|China', 18, 'Animals|Brain|Cell Cycle|Circadian Rhythm|Cluster Analysis|Fish Proteins|Gene Knockdown Techniques|IMP Dehydrogenase|Larva|Metabolic Networks and Pathways|Purines|Transcriptome|Zebrafish', 'Journal Article', '10.1371/journal.pcbi.1004086', '25714999', 'Metabolism is the major output of the circadian clock in many organisms. We developed a computational method to integrate both circadian gene expression and metabolic network. Applying this method to zebrafish circadian transcriptome, we have identified large clusters of metabolic genes containing mostly genes in purine and pyrimidine metabolism in the metabolic network showing similar circadian phases. Our metabolomics analysis found that the level of inosine 5-monophosphate (IMP), an intermediate metabolite in de novo purine synthesis, showed significant circadian oscillation in larval zebrafish. We focused on IMP dehydrogenase (impdh), a rate-limiting enzyme in de novo purine synthesis, with three circadian oscillating gene homologs: impdh1a, impdh1b and impdh2. Functional analysis revealed that impdh2 contributes to the daily rhythm of S phase in the cell cycle while impdh1a contributes to ocular development and pigment synthesis. The three zebrafish homologs of impdh are likely regulated by different circadian transcription factors. We propose that the circadian regulation of de novo purine synthesis that supplies crucial building blocks for DNA replication is an important mechanism conferring circadian rhythmicity on the cell cycle. Our method is widely applicable to study the impact of circadian transcriptome on metabolism in complex organisms. '),
(87011, 2015, 'plos', 'Ten simple rules for lifelong learning, according to Hamming', 'Erren, Thomas C|Slanger, Tracy E|Groß, J Valérie|Bourne, Philip E|Cullen, Paul', 'Institute and Policlinic for Occupational Medicine, Environmental Medicine and Prevention Research, University Hospital of Cologne, Cologne, Germany.|Institute and Policlinic for Occupational Medicine, Environmental Medicine and Prevention Research, University Hospital of Cologne, Cologne, Germany.|Institute and Policlinic for Occupational Medicine, Environmental Medicine and Prevention Research, University Hospital of Cologne, Cologne, Germany.|Office of the Director, The National Institutes of Health, Bethesda, Maryland, United States of America.|Medizinisches Labor Münster, Münster, Germany.', 'Germany|Germany|Germany|United States|Germany', 2, 'Goals|Humans|Learning|Thinking', 'Editorial', '10.1371/journal.pcbi.1004020', '25719205', '-'),
(87012, 2015, 'plos', 'Multi-timescale modeling of activity-dependent metabolic coupling in the neuron-glia-vasculature ensemble', 'Jolivet, Renaud|Coggan, Jay S|Allaman, Igor|Magistretti, Pierre J', 'Department of Neuroscience, Physiology & Pharmacology, University College London, London, United Kingdom.|Brain Mind Institute, École Polytechnique Fédérale de Lausanne (EPFL), Lausanne, Switzerland, NeuroLinx Research Institute, La Jolla, California, United States of America.|Brain Mind Institute, École Polytechnique Fédérale de Lausanne (EPFL), Lausanne, Switzerland.|Brain Mind Institute, École Polytechnique Fédérale de Lausanne (EPFL), Lausanne, Switzerland, Biological and Environmental Sciences and Engineering Division, King Abdullah University of Science and Technology (KAUST), Thuwal, Kingdom of Saudi Arabia.', 'United Kingdom|Switzerland|Switzerland|Switzerland', 50, 'Animals|Astrocytes|Brain|Cerebrovascular Circulation|Computational Biology|Computer Simulation|Extracellular Space|Glucose|Humans|Lactic Acid|Models, Cardiovascular|Models, Neurological|NAD|Neurons|Oxygen Consumption|Rats|Sodium', 'Journal Article', '10.1371/journal.pcbi.1004036', '25719367', 'Glucose is the main energy substrate in the adult brain under normal conditions. Accumulating evidence, however, indicates that lactate produced in astrocytes (a type of glial cell) can also fuel neuronal activity. The quantitative aspects of this so-called astrocyte-neuron lactate shuttle (ANLS) are still debated. To address this question, we developed a detailed biophysical model of the brains metabolic interactions. Our model integrates three modeling approaches, the Buxton-Wang model of vascular dynamics, the Hodgkin-Huxley formulation of neuronal membrane excitability and a biophysical model of metabolic pathways. This approach provides a template for large-scale simulations of the neuron-glia-vasculature (NGV) ensemble, and for the first time integrates the respective timescales at which energy metabolism and neuronal excitability occur. The model is constrained by relative neuronal and astrocytic oxygen and glucose utilization, by the concentration of metabolites at rest and by the temporal dynamics of NADH upon activation. These constraints produced four observations. First, a transfer of lactate from astrocytes to neurons emerged in response to activity. Second, constrained by activity-dependent NADH transients, neuronal oxidative metabolism increased first upon activation with a subsequent delayed astrocytic glycolysis increase. Third, the model correctly predicted the dynamics of extracellular lactate and oxygen as observed in vivo in rats. Fourth, the model correctly predicted the temporal dynamics of tissue lactate, of tissue glucose and oxygen consumption, and of the BOLD signal as reported in human studies. These findings not only support the ANLS hypothesis but also provide a quantitative mathematical description of the metabolic activation in neurons and glial cells, as well as of the macroscopic measurements obtained during brain imaging. '),
(87013, 2015, 'plos', 'Quantifying two-dimensional filamentous and invasive growth spatial patterns in yeast colonies', 'Binder, Benjamin J|Sundstrom, Joanna F|Gardner, Jennifer M|Jiranek, Vladimir|Oliver, Stephen G', 'School of Mathematical Sciences, University of Adelaide, Adelaide, South Australia, Australia.|School of Agriculture, Food and Wine, Waite Campus, University of Adelaide, Adelaide, South Australia, Australia.|School of Agriculture, Food and Wine, Waite Campus, University of Adelaide, Adelaide, South Australia, Australia.|School of Agriculture, Food and Wine, Waite Campus, University of Adelaide, Adelaide, South Australia, Australia.|Cambridge Systems Biology Centre and Department of Biochemistry, University of Cambridge, Cambridge, United Kingdom.', 'Australia|Australia|Australia|Australia|United Kingdom', 11, 'Computational Biology|Image Processing, Computer-Assisted|Models, Biological|Saccharomyces cerevisiae', 'Journal Article', '10.1371/journal.pcbi.1004070', '25719406', 'The top-view, two-dimensional spatial patterning of non-uniform growth in a Saccharomyces cerevisiae yeast colony is considered. Experimental images are processed to obtain data sets that provide spatial information on the cell-area that is occupied by the colony. A method is developed that allows for the analysis of the spatial distribution with three metrics. The growth of the colony is quantified in both the radial direction from the centre of the colony and in the angular direction in a prescribed outer region of the colony. It is shown that during the period of 100-200 hours from the start of the growth of the colony there is an increasing amount of non-uniform growth. The statistical framework outlined in this work provides a platform for comparative quantitative assays of strain-specific mechanisms, with potential implementation in inferencing algorithms used for parameter-rate estimation. '),
(87014, 2015, 'plos', 'How to write a presubmission inquiry', 'Lengauer, Thomas|Nussinov, Ruth', 'Department of Computational Biology and Applied Algorithmics, Max Planck Institute for Informatics, Saarbrücken, Germany.|Cancer and Inflammation Program, Leidos Biomedical Research, Inc., Frederick National Laboratory for Cancer Research, National Cancer Institute, Frederick, Maryland, United States of America, Sackler Institute of Molecular Medicine, Department of Human Genetics and Molecular Medicine, Sackler School of Medicine, Tel Aviv University, Tel Aviv, Israel.', 'Germany|Israel', 0, 'Biomedical Research|Humans|Periodicals as Topic|Writing', 'Editorial', '10.1371/journal.pcbi.1004098', '25719491', '-'),
(87015, 2015, 'plos', 'The molecular clock of neutral evolution can be accelerated or slowed by asymmetric spatial structure', 'Allen, Benjamin|Sample, Christine|Dementieva, Yulia|Medeiros, Ruben C|Paoletti, Christopher|Nowak, Martin A', 'Department of Mathematics, Emmanuel College, Boston, Massachusetts, United States of America, Program for Evolutionary Dynamics, Harvard University, Cambridge, Massachusetts, United States of America, Center for Mathematical Sciences and Applications, Harvard University, Cambridge, Massachusetts, United States of America.|Department of Mathematics, Emmanuel College, Boston, Massachusetts, United States of America.|Department of Mathematics, Emmanuel College, Boston, Massachusetts, United States of America.|Department of Mathematics, Emmanuel College, Boston, Massachusetts, United States of America.|Department of Mathematics, Emmanuel College, Boston, Massachusetts, United States of America.|Program for Evolutionary Dynamics, Harvard University, Cambridge, Massachusetts, United States of America, Department of Mathematics, Department of Organismic and Evolutionary Biology, Harvard University, Cambridge, Massachusetts, United States of America.', 'United States|United States|United States|United States|United States|United States', 0, 'Computational Biology|Evolution, Molecular|Genetic Drift|Genetics, Population|Humans|Models, Genetic|Mutation', 'Journal Article', '10.1371/journal.pcbi.1004108', '25719560', 'Over time, a population acquires neutral genetic substitutions as a consequence of random drift. A famous result in population genetics asserts that the rate, K, at which these substitutions accumulate in the population coincides with the mutation rate, u, at which they arise in individuals: K = u. This identity enables genetic sequence data to be used as a molecular clock to estimate the timing of evolutionary events. While the molecular clock is known to be perturbed by selection, it is thought that K = u holds very generally for neutral evolution. Here we show that asymmetric spatial population structure can alter the molecular clock rate for neutral mutations, leading to either K<u or K>u. Our results apply to a general class of haploid, asexually reproducing, spatially structured populations. Deviations from K = u occur because mutations arise unequally at different sites and have different probabilities of fixation depending on where they arise. If birth rates are uniform across sites, then K xe2x89xa4 u. In general, K can take any value between 0 and Nu. Our model can be applied to a variety of population structures. In one example, we investigate the accumulation of genetic mutations in the small intestine. In another application, we analyze over 900 Twitter networks to study the effect of network topology on the fixation of neutral innovations in social evolution. '),
(87016, 2015, 'plos', 'Stochastic modeling of mouse motor activity under deep brain stimulation: the extraction of arousal information', 'Keenan, Daniel M|Quinkert, Amy W|Pfaff, Donald W', 'Department of Statistics, University of Virginia, Charlottesville, Virginia, United States of America, Laboratory of Neurobiology and Behavior, Rockefeller University, New York, New York, United States of America.|Laboratory of Neurobiology and Behavior, Rockefeller University, New York, New York, United States of America.|Laboratory of Neurobiology and Behavior, Rockefeller University, New York, New York, United States of America.', 'United States|United States|United States', 2, 'Animals|Arousal|Computational Biology|Deep Brain Stimulation|Mice|Motor Activity|Stochastic Processes', 'Journal Article', '10.1371/journal.pcbi.1003883', '25720000', 'In the present paper, we quantify, with a rigorous approach, the nature of motor activity in response to Deep Brain Stimulation (DBS), in the mouse. DBS is currently being used in the treatment of a broad range of diseases, but its underlying principles are still unclear. Because mouse movement involves rapidly repeated starting and stopping, one must statistically verify that the movement at a given stimulation time was not just coincidental, endogenously-driven movement. Moreover, the amount of activity changes significantly over the circadian rhythm, and hence the means, variances and autocorrelations are all time varying. A new methodology is presented. For example, to discern what is and what is not impacted by stimulation, velocity is classified (in a time-evolving manner) as being zero-, one- and two-dimensional movement. The most important conclusions of the paper are: (1) (DBS) stimulation is proven to be truly effective, (2) it is two-dimensional (2-D) movement that strongly differs between light and dark and responds to stimulation, and, (3) stimulation in the light initiates a manner of movement, 2-D movement, that is more commonly seen in the (non-stimulated) dark. Based upon these conclusions, it is conjectured that the above patterns of 2-D movement could be a straightforward, easy to calculate correlate of arousal. The above conclusions will aid in the systematic evaluation and understanding of how DBS in CNS arousal pathways leads to the activation of behavior. '),
(87017, 2015, 'plos', 'Protein complexes in bacteria', 'Caufield, J Harry|Abreu, Marco|Wimble, Christopher|Uetz, Peter', 'Center for the Study of Biological Complexity, Virginia Commonwealth University, Richmond, Virginia, United States of America.|Center for the Study of Biological Complexity, Virginia Commonwealth University, Richmond, Virginia, United States of America.|Center for the Study of Biological Complexity, Virginia Commonwealth University, Richmond, Virginia, United States of America.|Center for the Study of Biological Complexity, Virginia Commonwealth University, Richmond, Virginia, United States of America.', 'United States|United States|United States|United States', 0, 'Bacterial Proteins|Escherichia coli|Genome, Bacterial|Multiprotein Complexes|Mycoplasma pneumoniae|Proteomics', 'Journal Article', '10.1371/journal.pcbi.1004107', '25723151', 'Large-scale analyses of protein complexes have recently become available for Escherichia coli and Mycoplasma pneumoniae, yielding 443 and 116 heteromultimeric soluble protein complexes, respectively. We have coupled the results of these mass spectrometry-characterized protein complexes with the 285 gold standard protein complexes identified by EcoCyc. A comparison with databases of gene orthology, conservation, and essentiality identified proteins conserved or lost in complexes of other species. For instance, of 285 gold standard protein complexes in E. coli, less than 10% are fully conserved among a set of 7 distantly-related bacterial model species. Complex conservation follows one of three models: well-conserved complexes, complexes with a conserved core, and complexes with partial conservation but no conserved core. Expanding the comparison to 894 distinct bacterial genomes illustrates fractional conservation and the limits of co-conservation among components of protein complexes: just 14 out of 285 model protein complexes are perfectly conserved across 95% of the genomes used, yet we predict more than 180 may be partially conserved across at least half of the genomes. No clear relationship between gene essentiality and protein complex conservation is observed, as even poorly conserved complexes contain a significant number of essential proteins. Finally, we identify 183 complexes containing well-conserved components and uncharacterized proteins which will be interesting targets for future experimental studies. '),
(87018, 2015, 'plos', 'A human platelet calcium calculator trained by pairwise agonist scanning', 'Lee, Mei Yan|Diamond, Scott L', 'Institute for Medicine and Engineering, Department of Chemical and Biomolecular Engineering, University of Pennsylvania, Philadelphia, Pennsylvania, United States of America.|Institute for Medicine and Engineering, Department of Chemical and Biomolecular Engineering, University of Pennsylvania, Philadelphia, Pennsylvania, United States of America.', 'United States|United States', 13, 'Blood Coagulation Factors|Blood Platelets|Calcium|Computational Biology|Humans|Neural Networks (Computer)|Platelet Activation|Signal Processing, Computer-Assisted', 'Journal Article', '10.1371/journal.pcbi.1004118', '25723389', 'Since platelet intracellular calcium mobilization [Ca(t)]i controls granule release, cyclooxygenase-1 and integrin activation, and phosphatidylserine exposure, blood clotting simulations require prediction of platelet [Ca(t)]i in response to combinatorial agonists. Pairwise Agonist Scanning (PAS) deployed all single and pairwise combinations of six agonists (ADP, convulxin, thrombin, U46619, iloprost and GSNO used at 0.1, 1, and 10xEC50, 154 conditions including a null condition) to stimulate platelet P2Y1/P2Y12 GPVI, PAR1/PAR4, TP, IP receptors, and guanylate cyclase, respectively, in Factor Xa-inhibited (250 nM apixaban), diluted platelet rich plasma that had been loaded with the calcium dye Fluo-4 NW. PAS of 10 healthy donors provided [Ca(t)]i data for training 10 neural networks (NN, 2-layer/12-nodes) per donor. Trinary stimulations were then conducted at all 0.1x and 1xEC50 doses (160 conditions) as was a sampling of 45 higher ordered combinations (four to six agonists). The NN-ensemble average was a calcium calculator that accurately predicted [Ca (t)]i beyond the single and binary training set for trinary stimulations (R = 0.924). The 160 trinary synergy scores, a normalized metric of signaling crosstalk, were also well predicted (R = 0.850) as were the calcium dynamics (R = 0.871) and high-dimensional synergy scores (R = 0.695) for the 45 higher ordered conditions. The calculator even predicted sequential addition experiments (n = 54 conditions, R = 0.921). NN-ensemble is a fast calcium calculator, ideal for multiscale clotting simulations that include spatiotemporal concentrations of ADP, collagen, thrombin, thromboxane, prostacyclin, and nitric oxide. '),
(87019, 2015, 'plos', 'Cyclin and DNA distributed cell cycle model for GS-NS0 cells', 'García Münzer, David G|Kostoglou, Margaritis|Georgiadis, Michael C|Pistikopoulos, Efstratios N|Mantalaris, Athanasios', 'Biological Systems Engineering Laboratory, Centre for Process Systems Engineering, Department of Chemical Engineering, Imperial College London, London, United Kingdom.|Department of Chemistry, Aristotle University of Thessaloniki, Thessaloniki, Greece.|Department of Chemical Engineering, Aristotle University of Thessaloniki, Thessaloniki, Greece.|Biological Systems Engineering Laboratory, Centre for Process Systems Engineering, Department of Chemical Engineering, Imperial College London, London, United Kingdom.|Biological Systems Engineering Laboratory, Centre for Process Systems Engineering, Department of Chemical Engineering, Imperial College London, London, United Kingdom.', 'United Kingdom|Greece|Greece|United Kingdom|United Kingdom', 0, 'Animals|Cell Cycle|Cell Line|Cell Line, Tumor|Cell Survival|Cyclins|DNA|Mice|Models, Biological|Recombinant Proteins', 'Journal Article', '10.1371/journal.pcbi.1004062', '25723523', 'Mammalian cell cultures are intrinsically heterogeneous at different scales (molecular to bioreactor). The cell cycle is at the centre of capturing heterogeneity since it plays a critical role in the growth, death, and productivity of mammalian cell cultures. Current cell cycle models use biological variables (mass/volume/age) that are non-mechanistic, and difficult to experimentally determine, to describe cell cycle transition and capture culture heterogeneity. To address this problem, cyclins-key molecules that regulate cell cycle transition-have been utilized. Herein, a novel integrated experimental-modelling platform is presented whereby experimental quantification of key cell cycle metrics (cell cycle timings, cell cycle fractions, and cyclin expression determined by flow cytometry) is used to develop a cyclin and DNA distributed model for the industrially relevant cell line, GS-NS0. Cyclins/DNA synthesis rates were linked to stimulatory/inhibitory factors in the culture medium, which ultimately affect cell growth. Cell antibody productivity was characterized using cell cycle-specific production rates. The solution method delivered fast computational time that renders the models use suitable for model-based applications. Model structure was studied by global sensitivity analysis (GSA), which identified parameters with a significant effect on the model output, followed by re-estimation of its significant parameters from a control set of batch experiments. A good model fit to the experimental data, both at the cell cycle and viable cell density levels, was observed. The cell population heterogeneity of disturbed (after cell arrest) and undisturbed cell growth was captured proving the versatility of the modelling approach. Cell cycle models able to capture population heterogeneity facilitate in depth understanding of these complex systems and enable systematic formulation of culture strategies to improve growth and productivity. It is envisaged that this modelling approach will pave the model-based development of industrial cell lines and clinical studies. '),
(87020, 2015, 'plos', 'Protein sectors: statistical coupling analysis versus conservation', 'Texc5x9fileanu, Tiberiu|Colwell, Lucy J|Leibler, Stanislas', 'The Simons Center for Systems Biology and The School of Natural Sciences, Institute for Advanced Study, Einstein Drive, Princeton, New Jersey, United States of America, Initiative for the Theoretical Sciences, CUNY Graduate Center, 365 Fifth Avenue, New York, New York, United States of America.|The Simons Center for Systems Biology and The School of Natural Sciences, Institute for Advanced Study, Einstein Drive, Princeton, New Jersey, United States of America, Department of Chemistry, University of Cambridge, Lensfield Road, Cambridge, United Kingdom.|The Simons Center for Systems Biology and The School of Natural Sciences, Institute for Advanced Study, Einstein Drive, Princeton, New Jersey, United States of America, Center for Studies in Physics and Biology and Laboratory of Living Matter, The Rockefeller University, 1230 York Avenue, New York, New York, United States of America.', 'Jersey|United Kingdom|Jersey', 37, 'Algorithms|Amino Acid Sequence|Computational Biology|Conserved Sequence|PDZ Domains|Protein Interaction Domains and Motifs|Proteins|Sequence Alignment|Sequence Analysis, Protein|Tetrahydrofolate Dehydrogenase', 'Journal Article', '10.1371/journal.pcbi.1004091', '25723535', 'Statistical coupling analysis (SCA) is a method for analyzing multiple sequence alignments that was used to identify groups of coevolving residues termed sectors. The method applies spectral analysis to a matrix obtained by combining correlation information with sequence conservation. It has been asserted that the protein sectors identified by SCA are functionally significant, with different sectors controlling different biochemical properties of the protein. Here we reconsider the available experimental data and note that it involves almost exclusively proteins with a single sector. We show that in this case sequence conservation is the dominating factor in SCA, and can alone be used to make statistically equivalent functional predictions. Therefore, we suggest shifting the experimental focus to proteins for which SCA identifies several sectors. Correlations in protein alignments, which have been shown to be informative in a number of independent studies, would then be less dominated by sequence conservation. '),
(87021, 2015, 'plos', 'An integrated approach to reconstructing genome-scale transcriptional regulatory networks', 'Imam, Saheed|Noguera, Daniel R|Donohue, Timothy J', 'Program in Cellular and Molecular Biology, University of Wisconsin-Madison, Madison, Wisconsin, United States of America, Department of Bacteriology, University of Wisconsin-Madison, Madison, Wisconsin, United States of America, Wisconsin Energy Institute, University of Wisconsin-Madison, Madison, Wisconsin, United States of America, Great Lakes Bioenergy Research Center, University of Wisconsin-Madison, Madison, Wisconsin, United States of America.|Great Lakes Bioenergy Research Center, University of Wisconsin-Madison, Madison, Wisconsin, United States of America, Department of Civil and Environmental Engineering, University of Wisconsin-Madison, Wisconsin, United States of America.|Department of Bacteriology, University of Wisconsin-Madison, Madison, Wisconsin, United States of America, Great Lakes Bioenergy Research Center, University of Wisconsin-Madison, Madison, Wisconsin, United States of America.', 'United States|United States|United States', 15, 'Computational Biology|Gene Expression Regulation, Bacterial|Gene Regulatory Networks|Genome, Bacterial|Models, Genetic|Phylogeny|Rhodobacter sphaeroides', 'Journal Article', '10.1371/journal.pcbi.1004103', '25723545', 'Transcriptional regulatory networks (TRNs) program cells to dynamically alter their gene expression in response to changing internal or environmental conditions. In this study, we develop a novel workflow for generating large-scale TRN models that integrates comparative genomics data, global gene expression analyses, and intrinsic properties of transcription factors (TFs). An assessment of this workflow using benchmark datasets for the well-studied xcexb3-proteobacterium Escherichia coli showed that it outperforms expression-based inference approaches, having a significantly larger area under the precision-recall curve. Further analysis indicated that this integrated workflow captures different aspects of the E. coli TRN than expression-based approaches, potentially making them highly complementary. We leveraged this new workflow and observations to build a large-scale TRN model for the xcexb1-Proteobacterium Rhodobacter sphaeroides that comprises 120 gene clusters, 1211 genes (including 93 TFs), 1858 predicted protein-DNA interactions and 76 DNA binding motifs. We found that ~67% of the predicted gene clusters in this TRN are enriched for functions ranging from photosynthesis or central carbon metabolism to environmental stress responses. We also found that members of many of the predicted gene clusters were consistent with prior knowledge in R. sphaeroides and/or other bacteria. Experimental validation of predictions from this R. sphaeroides TRN model showed that high precision and recall was also obtained for TFs involved in photosynthesis (PpsR), carbon metabolism (RSP_0489) and iron homeostasis (RSP_3341). In addition, this integrative approach enabled generation of TRNs with increased information content relative to R. sphaeroides TRN models built via other approaches. We also show how this approach can be used to simultaneously produce TRN models for each related organism used in the comparative genomics analysis. Our results highlight the advantages of integrating comparative genomics of closely related organisms with gene expression data to assemble large-scale TRN models with high-quality predictions. '),
(87022, 2015, 'plos', 'Molecular dynamics simulations of the bacterial UraA H+-uracil symporter in lipid bilayers reveal a closed state and a selective interaction with cardiolipin', 'Kalli, Antreas C|Sansom, Mark S P|Reithmeier, Reinhart A F', 'Department of Biochemistry, University of Oxford, Oxford, United Kingdom.|Department of Biochemistry, University of Oxford, Oxford, United Kingdom.|Department of Biochemistry, University of Toronto, Toronto, Canada.', 'United Kingdom|United Kingdom|Canada', 0, 'Amino Acid Sequence|Cardiolipins|Escherichia coli Proteins|Lipid Bilayers|Membrane Transport Proteins|Molecular Dynamics Simulation|Molecular Sequence Data', 'Journal Article', '10.1371/journal.pcbi.1004123', '25729859', 'The Escherichia coli UraA H+-uracil symporter is a member of the nucleobase/ascorbate transporter (NAT) family of proteins, and is responsible for the proton-driven uptake of uracil. Multiscale molecular dynamics simulations of the UraA symporter in phospholipid bilayers consisting of: 1) 1-palmitoyl 2-oleoyl-phosphatidylcholine (POPC), 2) 1-palmitoyl 2-oleoyl-phosphatidylethanolamine (POPE), and 3) a mixture of 75% POPE, 20% 1-palmitoyl 2-oleoyl-phosphatidylglycerol (POPG), and 5% 1-palmitoyl 2-oleoyl-diphosphatidylglycerol/cardiolipin (CL) to mimic the lipid composition of the bacterial inner membrane, were performed using the MARTINI coarse-grained force field to self-assemble lipids around the crystal structure of this membrane transport protein, followed by atomistic simulations. The overall fold of the protein in lipid bilayers remained similar to the crystal structure in detergent on the timescale of our simulations. Simulations were performed in the absence of uracil, and resulted in a closed state of the transporter, due to relative movement of the gate and core domains. Anionic lipids, including POPG and especially CL, were found to associate with UraA, involving interactions between specific basic residues in loop regions and phosphate oxygens of the CL head group. In particular, three CL binding sites were identified on UraA: two in the inner leaflet and a single site in the outer leaflet. Mutation of basic residues in the binding sites resulted in the loss of CL binding in the simulations. CL may play a role as a proton trap that channels protons to and from this transporter within CL-enriched areas of the inner bacterial membrane. '),
(87023, 2015, 'plos', 'Highly loaded behavior of kinesins increases the robustness of transport under high resisting loads', 'Nam, Woochul|Epureanu, Bogdan I', 'Department of Mechanical Engineering, University of Michigan, Ann Arbor, Michigan, United States of America.|Department of Mechanical Engineering, University of Michigan, Ann Arbor, Michigan, United States of America.', 'United States|United States', 0, 'Adenosine Triphosphate|Biomechanical Phenomena|Computational Biology|Kinesin|Kinetics|Models, Molecular|Potassium|Protein Binding', 'Journal Article', '10.1371/journal.pcbi.1003981', '25734978', 'Kinesins are nano-sized biological motors which walk by repeating a mechanochemical cycle. A single kinesin molecule is able to transport its cargo about 1 xcexbcm in the absence of external loads. However, kinesins perform much longer range transport in cells by working collectively. This long range of transport by a team of kinesins is surprising because the motion of the cargo in cells can be hindered by other particles. To reveal how the kinesins are able to accomplish their tasks of transport in harsh intracellular circumstances, stochastic studies on the kinesin motion are performed by considering the binding and unbinding of kinesins to microtubules and their dependence on the force acting on kinesin molecules. The unbinding probabilities corresponding to each mechanochemical state of kinesin are modeled. The statistical characterization of the instants and locations of binding are captured by computing the probability of unbound kinesin being at given locations. It is predicted that a group of kinesins has a more efficient transport than a single kinesin from the perspective of velocity and run length. Particularly, when large loads are applied, the leading kinesin remains bound to the microtubule for long time which increases the chances of the other kinesins to bind to the microtubule. To predict effects of this behavior of the leading kinesin under large loads on the collective transport, the motion of the cargo is studied when the cargo confronts obstacles. The result suggests that the behavior of kinesins under large loads prevents the early termination of the transport which can be caused by the interference with the static or moving obstacles. '),
(87024, 2015, 'plos', 'PRIMAL: Fast and accurate pedigree-based imputation from sequence data in a founder population', 'Livne, Oren E|Han, Lide|Alkorta-Aranburu, Gorka|Wentworth-Sheilds, William|Abney, Mark|Ober, Carole|Nicolae, Dan L', 'Department of Human Genetics, The University of Chicago, Chicago, Illinois, United States of America.|Department of Human Genetics, The University of Chicago, Chicago, Illinois, United States of America.|Department of Human Genetics, The University of Chicago, Chicago, Illinois, United States of America.|Department of Human Genetics, The University of Chicago, Chicago, Illinois, United States of America.|Department of Human Genetics, The University of Chicago, Chicago, Illinois, United States of America.|Department of Human Genetics, The University of Chicago, Chicago, Illinois, United States of America.|Department of Human Genetics, The University of Chicago, Chicago, Illinois, United States of America, Departments of Medicine, and Statistics, The University of Chicago, Chicago, Illinois, United States of America.', 'United States|United States|United States|United States|United States|United States|United States', 21, 'Algorithms|European Continental Ancestry Group|Female|Founder Effect|Genome, Human|Genomics|Humans|Male|Models, Genetic|Pedigree|Polymorphism, Single Nucleotide|Sequence Analysis, DNA|Software|South Dakota', 'Journal Article', '10.1371/journal.pcbi.1004139', '25735005', 'Founder populations and large pedigrees offer many well-known advantages for genetic mapping studies, including cost-efficient study designs. Here, we describe PRIMAL (PedigRee IMputation ALgorithm), a fast and accurate pedigree-based phasing and imputation algorithm for founder populations. PRIMAL incorporates both existing and original ideas, such as a novel indexing strategy of Identity-By-Descent (IBD) segments based on clique graphs. We were able to impute the genomes of 1,317 South Dakota Hutterites, who had genome-wide genotypes for ~300,000 common single nucleotide variants (SNVs), from 98 whole genome sequences. Using a combination of pedigree-based and LD-based imputation, we were able to assign 87% of genotypes with >99% accuracy over the full range of allele frequencies. Using the IBD cliques we were also able to infer the parental origin of 83% of alleles, and genotypes of deceased recent ancestors for whom no genotype information was available. This imputed data set will enable us to better study the relative contribution of rare and common variants on human phenotypes, as well as parental origin effect of disease risk alleles in >1,000 individuals at minimal cost. '),
(87025, 2015, 'plos', 'Mining host-pathogen protein interactions to characterize Burkholderia mallei infectivity mechanisms', 'Memixc5xa1evixc4x87, Vesna|Zavaljevski, Nela|Rajagopala, Seesandra V|Kwon, Keehwan|Pieper, Rembert|DeShazer, David|Reifman, Jaques|Wallqvist, Anders', 'Department of Defense Biotechnology High Performance Computing Software Applications Institute, Telemedicine and Advanced Technology Research Center, U.S. Army Medical Research and Materiel Command, Fort Detrick, Maryland, United States of America.|Department of Defense Biotechnology High Performance Computing Software Applications Institute, Telemedicine and Advanced Technology Research Center, U.S. Army Medical Research and Materiel Command, Fort Detrick, Maryland, United States of America.|J. Craig Venter Institute, Rockville, Maryland, United States of America.|J. Craig Venter Institute, Rockville, Maryland, United States of America.|J. Craig Venter Institute, Rockville, Maryland, United States of America.|Bacteriology Division, U.S. Army Medical Research Institute of Infectious Diseases, Fort Detrick, Maryland, United States of America.|Department of Defense Biotechnology High Performance Computing Software Applications Institute, Telemedicine and Advanced Technology Research Center, U.S. Army Medical Research and Materiel Command, Fort Detrick, Maryland, United States of America.|Department of Defense Biotechnology High Performance Computing Software Applications Institute, Telemedicine and Advanced Technology Research Center, U.S. Army Medical Research and Materiel Command, Fort Detrick, Maryland, United States of America.', 'United States|United States|United States|United States|United States|United States|United States|Un', 0, 'Algorithms|Animals|Bacterial Proteins|Burkholderia mallei|Cluster Analysis|Computational Biology|Focal Adhesions|Glanders|Host-Pathogen Interactions|Humans|Mice|Protein Interaction Maps|Signal Transduction|Virulence Factors', 'Journal Article', '10.1371/journal.pcbi.1004088', '25738731', 'Burkholderia pathogenicity relies on protein virulence factors to control and promote bacterial internalization, survival, and replication within eukaryotic host cells. We recently used yeast two-hybrid (Y2H) screening to identify a small set of novel Burkholderia proteins that were shown to attenuate disease progression in an aerosol infection animal model using the virulent Burkholderia mallei ATCC 23344 strain. Here, we performed an extended analysis of primarily nine B. mallei virulence factors and their interactions with human proteins to map out how the bacteria can influence and alter host processes and pathways. Specifically, we employed topological analyses to assess the connectivity patterns of targeted host proteins, identify modules of pathogen-interacting host proteins linked to processes promoting infectivity, and evaluate the effect of crosstalk among the identified host protein modules. Overall, our analysis showed that the targeted host proteins generally had a large number of interacting partners and interacted with other host proteins that were also targeted by B. mallei proteins. We also introduced a novel Host-Pathogen Interaction Alignment (HPIA) algorithm and used it to explore similarities between host-pathogen interactions of B. mallei, Yersinia pestis, and Salmonella enterica. We inferred putative roles of B. mallei proteins based on the roles of their aligned Y. pestis and S. enterica partners and showed that up to 73% of the predicted roles matched existing annotations. A key insight into Burkholderia pathogenicity derived from these analyses of Y2H host-pathogen interactions is the identification of eukaryotic-specific targeted cellular mechanisms, including the ubiquitination degradation system and the use of the focal adhesion pathway as a fulcrum for transmitting mechanical forces and regulatory signals. This provides the mechanisms to modulate and adapt the host-cell environment for the successful establishment of host infections and intracellular spread. ');
INSERT INTO `papers` (`id`, `ano`, `journal`, `titulo`, `autores`, `afiliacao`, `pais`, `citacoes`, `palavra_chave`, `categorias`, `doi`, `pubmed`, `abstract`) VALUES
(87026, 2015, 'plos', 'Protein topology determines cysteine oxidation fate: the case of sulfenyl amide formation among protein families', 'Defelipe, Lucas A|Lanzarotti, Esteban|Gauto, Diego|Marti, Marcelo A|Turjanski, Adrián G', 'Departamento de Química Biológica, Facultad de Ciencias Exactas y Naturales, Universidad de Buenos Aires, Buenos Aires, Argentina, INQUIMAE/UBA-CONICET, Facultad de Ciencias Exactas y Naturales, Universidad de Buenos Aires. Buenos Aires, Argentina.|Departamento de Química Biológica, Facultad de Ciencias Exactas y Naturales, Universidad de Buenos Aires, Buenos Aires, Argentina.|INQUIMAE/UBA-CONICET, Facultad de Ciencias Exactas y Naturales, Universidad de Buenos Aires. Buenos Aires, Argentina.|Departamento de Química Biológica, Facultad de Ciencias Exactas y Naturales, Universidad de Buenos Aires, Buenos Aires, Argentina, INQUIMAE/UBA-CONICET, Facultad de Ciencias Exactas y Naturales, Universidad de Buenos Aires. Buenos Aires, Argentina.|Departamento de Química Biológica, Facultad de Ciencias Exactas y Naturales, Universidad de Buenos Aires, Buenos Aires, Argentina, INQUIMAE/UBA-CONICET, Facultad de Ciencias Exactas y Naturales, Universidad de Buenos Aires. Buenos Aires, Argentina.', 'Argentina|Argentina|Argentina|Argentina|Argentina', 0, 'Amides|Computational Biology|Cysteine|Models, Molecular|Oxidation-Reduction|Protein Conformation|Proteins|Sulfenic Acids', 'Journal Article', '10.1371/journal.pcbi.1004051', '25741692', 'Cysteine residues have a rich chemistry and play a critical role in the catalytic activity of a plethora of enzymes. However, cysteines are susceptible to oxidation by Reactive Oxygen and Nitrogen Species, leading to a loss of their catalytic function. Therefore, cysteine oxidation is emerging as a relevant physiological regulatory mechanism. Formation of a cyclic sulfenyl amide residue at the active site of redox-regulated proteins has been proposed as a protection mechanism against irreversible oxidation as the sulfenyl amide intermediate has been identified in several proteins. However, how and why only some specific cysteine residues in particular proteins react to form this intermediate is still unknown. In the present work using in-silico based tools, we have identified a constrained conformation that accelerates sulfenyl amide formation. By means of combined MD and QM/MM calculation we show that this conformation positions the NH backbone towards the sulfenic acid and promotes the reaction to yield the sulfenyl amide intermediate, in one step with the concomitant release of a water molecule. Moreover, in a large subset of the proteins we found a conserved beta sheet-loop-helix motif, which is present across different protein folds, that is key for sulfenyl amide production as it promotes the previous formation of sulfenic acid. For catalytic activity, in several cases, proteins need the Cysteine to be in the cysteinate form, i.e. a low pKa Cys. We found that the conserved motif stabilizes the cysteinate by hydrogen bonding to several NH backbone moieties. As cysteinate is also more reactive toward ROS we propose that the sheet-loop-helix motif and the constraint conformation have been selected by evolution for proteins that need a reactive Cys protected from irreversible oxidation. Our results also highlight how fold conservation can be correlated to redox chemistry regulation of protein function. '),
(87027, 2015, 'plos', 'How attention can create synaptic tags for the learning of working memories in sequential tasks', 'Rombouts, Jaldert O|Bohte, Sander M|Roelfsema, Pieter R', 'Department of Life Sciences, Centrum Wiskunde & Informatica, Amsterdam, The Netherlands.|Department of Life Sciences, Centrum Wiskunde & Informatica, Amsterdam, The Netherlands.|Department of Vision & Cognition, Netherlands Institute for Neurosciences, an institute of the Royal Netherlands Academy of Arts and Sciences (KNAW), Amsterdam, The Netherlands, Department of Integrative Neurophysiology, Centre for Neurogenomics and Cognitive Research, VU University, Amsterdam, The Netherlands, Psychiatry Department, Academic Medical Center, Amsterdam, The Netherlands.', 'Netherlands|Netherlands|Netherlands', 0, 'Animals|Attention|Computational Biology|Feedback, Sensory|Haplorhini|Memory, Short-Term|Models, Neurological|Models, Statistical|Neurons|Saccades|Synapses|Task Performance and Analysis', 'Journal Article', '10.1371/journal.pcbi.1004060', '25742003', 'Intelligence is our ability to learn appropriate responses to new stimuli and situations. Neurons in association cortex are thought to be essential for this ability. During learning these neurons become tuned to relevant features and start to represent them with persistent activity during memory delays. This learning process is not well understood. Here we develop a biologically plausible learning scheme that explains how trial-and-error learning induces neuronal selectivity and working memory representations for task-relevant information. We propose that the response selection stage sends attentional feedback signals to earlier processing levels, forming synaptic tags at those connections responsible for the stimulus-response mapping. Globally released neuromodulators then interact with tagged synapses to determine their plasticity. The resulting learning rule endows neural networks with the capacity to create new working memory representations of task relevant information as persistent activity. It is remarkably generic: it explains how association neurons learn to store task-relevant information for linear as well as non-linear stimulus-response mappings, how they become tuned to category boundaries or analog variables, depending on the task demands, and how they learn to integrate probabilistic evidence for perceptual decisions. '),
(87028, 2015, 'plos', 'Correction: Systems level analysis of systemic sclerosis shows a network of immune and profibrotic pathways connected with genetic polymorphisms', 'PLOS Computational Biology Staff', 'Department of Vision & Cognition, Netherlands Institute for Neurosciences, an institute of the Royal Netherlands Academy of Arts and Sciences (KNAW), Amsterdam, The Netherlands, Department of Integrative Neurophysiology, Centre for Neurogenomics and Cognitive Research, VU University, Amsterdam, The Netherlands, Psychiatry Department, Academic Medical Center, Amsterdam, The Netherlands.', 'Netherlands', 2, '-', 'Published Erratum', '10.1371/journal.pcbi.1004133', '25742131', '-'),
(87029, 2015, 'plos', 'Evolution and phenotypic selection of cancer stem cells', 'Poleszczuk, Jan|Hahnfeldt, Philip|Enderling, Heiko', 'Center of Cancer Systems Biology, GRI, Tufts University School of Medicine, Boston, Massachusetts, United States of America, College of Inter-faculty Individual Studies in Mathematics and Natural Sciences, University of Warsaw, Warsaw, Poland.|Center of Cancer Systems Biology, GRI, Tufts University School of Medicine, Boston, Massachusetts, United States of America.|Center of Cancer Systems Biology, GRI, Tufts University School of Medicine, Boston, Massachusetts, United States of America.', 'Poland|United States|United States', 38, 'Biopsy|Cell Proliferation|Computational Biology|Disease Progression|Humans|Models, Biological|Mutation|Neoplasms|Neoplastic Stem Cells|Phenotype', 'Journal Article', '10.1371/journal.pcbi.1004025', '25742563', 'Cells of different organs at different ages have an intrinsic set of kinetics that dictates their behavior. Transformation into cancer cells will inherit these kinetics that determine initial cell and tumor population progression dynamics. Subject to genetic mutation and epigenetic alterations, cancer cell kinetics can change, and favorable alterations that increase cellular fitness will manifest themselves and accelerate tumor progression. We set out to investigate the emerging intratumoral heterogeneity and to determine the evolutionary trajectories of the combination of cell-intrinsic kinetics that yield aggressive tumor growth. We develop a cellular automaton model that tracks the temporal evolution of the malignant subpopulation of so-called cancer stem cells(CSC), as these cells are exclusively able to initiate and sustain tumors. We explore orthogonal cell traits, including cell migration to facilitate invasion, spontaneous cell death due to genetic drift after accumulation of irreversible deleterious mutations, symmetric cancer stem cell division that increases the cancer stem cell pool, and telomere length and erosion as a mitotic counter for inherited non-stem cancer cell proliferation potential. Our study suggests that cell proliferation potential is the strongest modulator of tumor growth. Early increase in proliferation potential yields larger populations of non-stem cancer cells(CC) that compete with CSC and thus inhibit CSC division while a reduction in proliferation potential loosens such inhibition and facilitates frequent CSC division. The sub-population of cancer stem cells in itself becomes highly heterogeneous dictating population level dynamics that vary from long-term dormancy to aggressive progression. Our study suggests that the clonal diversity that is captured in single tumor biopsy samples represents only a small proportion of the total number of phenotypes. '),
(87030, 2015, 'plos', 'Model-based traction force microscopy reveals differential tension in cellular actin bundles', 'Soiné, Jérôme R D|Brand, Christoph A|Stricker, Jonathan|Oakes, Patrick W|Gardel, Margaret L|Schwarz, Ulrich S', 'Institute for Theoretical Physics and BioQuant, Heidelberg University, Heidelberg, Germany.|Institute for Theoretical Physics and BioQuant, Heidelberg University, Heidelberg, Germany.|Institute for Biophysical Dynamics, Department of Physics, and The James Franck Institute, University of Chicago, Chicago, United States of America.|Institute for Biophysical Dynamics, Department of Physics, and The James Franck Institute, University of Chicago, Chicago, United States of America.|Institute for Biophysical Dynamics, Department of Physics, and The James Franck Institute, University of Chicago, Chicago, United States of America.|Institute for Theoretical Physics and BioQuant, Heidelberg University, Heidelberg, Germany.', 'Germany|Germany|United States|United States|United States|Germany', 57, 'Actin Cytoskeleton|Actins|Cell Line, Tumor|Humans|Image Processing, Computer-Assisted|Microscopy, Atomic Force|Models, Biological|Stress Fibers|Stress, Mechanical', 'Journal Article', '10.1371/journal.pcbi.1004076', '25748431', 'Adherent cells use forces at the cell-substrate interface to sense and respond to the physical properties of their environment. These cell forces can be measured with traction force microscopy which inverts the equations of elasticity theory to calculate them from the deformations of soft polymer substrates. We introduce a new type of traction force microscopy that in contrast to traditional methods uses additional image data for cytoskeleton and adhesion structures and a biophysical model to improve the robustness of the inverse procedure and abolishes the need for regularization. We use this method to demonstrate that ventral stress fibers of U2OS-cells are typically under higher mechanical tension than dorsal stress fibers or transverse arcs. '),
(87031, 2015, 'plos', 'Predicting epidemic risk from past temporal contact data', 'Valdano, Eugenio|Poletto, Chiara|Giovannini, Armando|Palma, Diana|Savini, Lara|Colizza, Vittoria', 'INSERM, UMR-S 1136, Institut Pierre Louis dEpidémiologie et de Santé Publique, F-75013 56 bd Vincent Auriol-CS 81393-75646 Paris Cedex 13, France, Sorbonne Universités, UPMC Univ Paris 06, UMR-S 1136, Institut Pierre Louis dEpidémiologie et de Santé Publique, F-75013 56 bd Vincent Auriol-CS 81393 - 75646 Paris Cedex 13, France.|INSERM, UMR-S 1136, Institut Pierre Louis dEpidémiologie et de Santé Publique, F-75013 56 bd Vincent Auriol-CS 81393-75646 Paris Cedex 13, France, Sorbonne Universités, UPMC Univ Paris 06, UMR-S 1136, Institut Pierre Louis dEpidémiologie et de Santé Publique, F-75013 56 bd Vincent Auriol-CS 81393 - 75646 Paris Cedex 13, France.|Istituto Zooprofilattico Sperimentale Abruzzo-Molise G. Caporale Campo Boario, 64100 Teramo, Italy.|Istituto Zooprofilattico Sperimentale Abruzzo-Molise G. Caporale Campo Boario, 64100 Teramo, Italy.|Istituto Zooprofilattico Sperimentale Abruzzo-Molise G. Caporale Campo Boario, 64100 Teramo, Italy.|INSERM, UMR-S 1136, Institut Pierre Louis dEpidémiologie et de Santé Publique, F-75013 56 bd Vincent Auriol-CS 81393-75646 Paris Cedex 13, France, Sorbonne Universités, UPMC Univ Paris 06, UMR-S 1136, Institut Pierre Louis dEpidémiologie et de Santé Publique, F-75013 56 bd Vincent Auriol-CS 81393 - 75646 Paris Cedex 13, France, ISI Foundation Via Alassio 11/c, 10126 Torino, Italy.', 'France|France|Italy|Italy|Italy|France', 30, 'Animals|Cattle|Cattle Diseases|Communicable Diseases|Computational Biology|Contact Tracing|Databases, Factual|Epidemics|Humans|Models, Biological|Risk Assessment|Sex Work|Time Factors', 'Journal Article', '10.1371/journal.pcbi.1004152', '25763816', 'Understanding how epidemics spread in a system is a crucial step to prevent and control outbreaks, with broad implications on the systems functioning, health, and associated costs. This can be achieved by identifying the elements at higher risk of infection and implementing targeted surveillance and control measures. One important ingredient to consider is the pattern of disease-transmission contacts among the elements, however lack of data or delays in providing updated records may hinder its use, especially for time-varying patterns. Here we explore to what extent it is possible to use past temporal data of a systems pattern of contacts to predict the risk of infection of its elements during an emerging outbreak, in absence of updated data. We focus on two real-world temporal systems, a livestock displacements trade network among animal holdings, and a network of sexual encounters in high-end prostitution. We define the nodes loyalty as a local measure of its tendency to maintain contacts with the same elements over time, and uncover important non-trivial correlations with the nodes epidemic risk. We show that a risk assessment analysis incorporating this knowledge and based on past structural and temporal pattern properties provides accurate predictions for both systems. Its generalizability is tested by introducing a theoretical model for generating synthetic temporal networks. High accuracy of our predictions is recovered across different settings, while the amount of possible predictions is system-specific. The proposed method can provide crucial information for the setup of targeted intervention strategies. '),
(87032, 2015, 'plos', 'A neural mechanism for background information-gated learning based on axonal-dendritic overlaps', 'Mainetti, Matteo|Ascoli, Giorgio A', 'Krasnow Institute for Advanced Study, George Mason University, Fairfax, Virginia, United States of America.|Krasnow Institute for Advanced Study, George Mason University, Fairfax, Virginia, United States of America.', 'United States|United States', 5, 'Animals|Axons|Coleoptera|Computational Biology|Dendrites|Learning|Models, Neurological|Nerve Net|Wasps', 'Journal Article', '10.1371/journal.pcbi.1004155', '25767887', 'Experiencing certain events triggers the acquisition of new memories. Although necessary, however, actual experience is not sufficient for memory formation. One-trial learning is also gated by knowledge of appropriate background information to make sense of the experienced occurrence. Strong neurobiological evidence suggests that long-term memory storage involves formation of new synapses. On the short time scale, this form of structural plasticity requires that the axon of the pre-synaptic neuron be physically proximal to the dendrite of the post-synaptic neuron. We surmise that such axonal-dendritic overlap (ADO) constitutes the neural correlate of background information-gated (BIG) learning. The hypothesis is based on a fundamental neuroanatomical constraint: an axon must pass close to the dendrites that are near other neurons it contacts. The topographic organization of the mammalian cortex ensures that nearby neurons encode related information. Using neural network simulations, we demonstrate that ADO is a suitable mechanism for BIG learning. We model knowledge as associations between terms, concepts or indivisible units of thought via directed graphs. The simplest instantiation encodes each concept by single neurons. Results are then generalized to cell assemblies. The proposed mechanism results in learning real associations better than spurious co-occurrences, providing definitive cognitive advantages. '),
(87033, 2015, 'plos', 'Angiogenic activity of breast cancer patients monocytes reverted by combined use of systems modeling and experimental approaches', 'Guex, Nicolas|Crespo, Isaac|Bron, Sylvian|Ifticene-Treboux, Assia|Faes-Vant Hull, Eveline|Kharoubi, Solange|Liechti, Robin|Werffeli, Patricia|Ibberson, Mark|Majo, Francois|Nicolas, Michäel|Laurent, Julien|Garg, Abhishek|Zaman, Khalil|Lehr, Hans-Anton|Stevenson, Brian J|Rüegg, Curzio|Coukos, George|Delaloye, Jean-François|Xenarios, Ioannis|Doucey, Marie-Agnès', 'The Vital-IT, SIB (Swiss Institute of Bioinformatics), University of Lausanne, Lausanne, Switzerland.|The Vital-IT, SIB (Swiss Institute of Bioinformatics), University of Lausanne, Lausanne, Switzerland.|Ludwig Center for Cancer Research, University of Lausanne, Lausanne, Switzerland.|Centre du Sein, CHUV (Centre Hospitalier Universitaire Vaudois), University of Lausanne, Lausanne, Switzerland, Department of Gynecology and Obstetrics, CHUV (Centre Hospitalier Universitaire Vaudois), University of Lausanne, Lausanne, Switzerland.|Ludwig Center for Cancer Research, University of Lausanne, Lausanne, Switzerland.|Ludwig Center for Cancer Research, University of Lausanne, Lausanne, Switzerland.|The Vital-IT, SIB (Swiss Institute of Bioinformatics), University of Lausanne, Lausanne, Switzerland.|Department of Oncology, CHUV (Centre Hospitalier Universitaire Vaudois), University of Lausanne, Lausanne, Switzerland.|The Vital-IT, SIB (Swiss Institute of Bioinformatics), University of Lausanne, Lausanne, Switzerland.|Hopital Ophtalmique Jules-Gonin, Lausanne, Switzerland.|Hopital Ophtalmique Jules-Gonin, Lausanne, Switzerland.|Merck Group, Darmstadt, Germany.|Harvard Medical School, Boston, Massachusetts, United States of America.|Centre du Sein, CHUV (Centre Hospitalier Universitaire Vaudois), University of Lausanne, Lausanne, Switzerland.|Institute of Pathology, University of Lausanne, Switzerland and Institute of Pathology, Johannes Gutenberg University, Mainz, Germany.|The Vital-IT, SIB (Swiss Institute of Bioinformatics), University of Lausanne, Lausanne, Switzerland.|Department of Medicine, University of Fribourg, Fribourg, Switzerland.|Ludwig Center for Cancer Research, University of Lausanne, Lausanne, Switzerland.|Centre du Sein, CHUV (Centre Hospitalier Universitaire Vaudois), University of Lausanne, Lausanne, Switzerland, Department of Gynecology and Obstetrics, CHUV (Centre Hospitalier Universitaire Vaudois), University of Lausanne, Lausanne, Switzerland.|The Vital-IT, SIB (Swiss Institute of Bioinformatics), University of Lausanne, Lausanne, Switzerland.|Ludwig Center for Cancer Research, University of Lausanne, Lausanne, Switzerland.', 'Switzerland|Switzerland|Switzerland|Switzerland|Switzerland|Switzerland|Switzerland|Switzerland|Swit', 11, 'Animals|Breast Neoplasms|Cell Line|Computational Biology|Cytokines|Female|Humans|Kaplan-Meier Estimate|Mice|Mice, Transgenic|Middle Aged|Models, Biological|Monocytes|Neoplasms, Experimental|Neovascularization, Pathologic|Phenotype|Signal Transduction', 'Journal Article', '10.1371/journal.pcbi.1004050', '25768678', 'Angiogenesis plays a key role in tumor growth and cancer progression. TIE-2-expressing monocytes (TEM) have been reported to critically account for tumor vascularization and growth in mouse tumor experimental models, but the molecular basis of their pro-angiogenic activity are largely unknown. Moreover, differences in the pro-angiogenic activity between blood circulating and tumor infiltrated TEM in human patients has not been established to date, hindering the identification of specific targets for therapeutic intervention. In this work, we investigated these differences and the phenotypic reversal of breast tumor pro-angiogenic TEM to a weak pro-angiogenic phenotype by combining Boolean modelling and experimental approaches. Firstly, we show that in breast cancer patients the pro-angiogenic activity of TEM increased drastically from blood to tumor, suggesting that the tumor microenvironment shapes the highly pro-angiogenic phenotype of TEM. Secondly, we predicted in silico all minimal perturbations transitioning the highly pro-angiogenic phenotype of tumor TEM to the weak pro-angiogenic phenotype of blood TEM and vice versa. In silico predicted perturbations were validated experimentally using patient TEM. In addition, gene expression profiling of TEM transitioned to a weak pro-angiogenic phenotype confirmed that TEM are plastic cells and can be reverted to immunological potent monocytes. Finally, the relapse-free survival analysis showed a statistically significant difference between patients with tumors with high and low expression values for genes encoding transitioning proteins detected in silico and validated on patient TEM. In conclusion, the inferred TEM regulatory network accurately captured experimental TEM behavior and highlighted crosstalk between specific angiogenic and inflammatory signaling pathways of outstanding importance to control their pro-angiogenic activity. Results showed the successful in vitro reversion of such an activity by perturbation of in silico predicted target genes in tumor derived TEM, and indicated that targeting tumor TEM plasticity may constitute a novel valid therapeutic strategy in breast cancer. '),
(87034, 2015, 'plos', 'Physiology of layer 5 pyramidal neurons in mouse primary visual cortex: coincidence detection through bursting', 'Shai, Adam S|Anastassiou, Costas A|Larkum, Matthew E|Koch, Christof', 'California Institute of Technology, Pasadena, California, United States of America, Allen Institute for Brain Science, Seattle, Washington, United States of America.|Allen Institute for Brain Science, Seattle, Washington, United States of America.|Neurocure Cluster of Excellence, Department of Biology, Humboldt University of Berlin, Berlin, Germany.|Allen Institute for Brain Science, Seattle, Washington, United States of America.', 'United States|United States|Germany|United States', 40, 'Animals|Computational Biology|Dendrites|Mice|Models, Neurological|Pyramidal Cells|Synapses|Visual Cortex', 'Journal Article', '10.1371/journal.pcbi.1004090', '25768881', 'L5 pyramidal neurons are the only neocortical cell type with dendrites reaching all six layers of cortex, casting them as one of the main integrators in the cortical column. What is the nature and mode of computation performed in mouse primary visual cortex (V1) given the physiology of L5 pyramidal neurons? First, we experimentally establish active properties of the dendrites of L5 pyramidal neurons of mouse V1 using patch-clamp recordings. Using a detailed multi-compartmental model, we show this physiological setup to be well suited for coincidence detection between basal and apical tuft inputs by controlling the frequency of spike output. We further show how direct inhibition of calcium channels in the dendrites modulates such coincidence detection. To establish the singe-cell computation that this biophysics supports, we show that the combination of frequency-modulation of somatic output by tuft input and (simulated) calcium-channel blockage functionally acts as a composite sigmoidal function. Finally, we explore how this computation provides a mechanism whereby dendritic spiking contributes to orientation tuning in pyramidal neurons. '),
(87035, 2015, 'plos', 'Transcriptome sequencing reveals potential mechanism of cryptic 3 splice site selection in SF3B1-mutated cancers', 'DeBoever, Christopher|Ghia, Emanuela M|Shepard, Peter J|Rassenti, Laura|Barrett, Christian L|Jepsen, Kristen|Jamieson, Catriona H M|Carson, Dennis|Kipps, Thomas J|Frazer, Kelly A', 'Bioinformatics and Systems Biology, University of California San Diego, La Jolla, California, United States of America.|Moores Cancer Center, University of California San Diego, La Jolla, California, United States of America.|Moores Cancer Center, University of California San Diego, La Jolla, California, United States of America, Department of Pediatrics and Rady Childrens Hospital, University of California San Diego, La Jolla, California, United States of America.|Moores Cancer Center, University of California San Diego, La Jolla, California, United States of America.|Moores Cancer Center, University of California San Diego, La Jolla, California, United States of America, Department of Pediatrics and Rady Childrens Hospital, University of California San Diego, La Jolla, California, United States of America, Institute for Genomic Medicine, University of California San Diego, La Jolla, California, United States of America.|Institute for Genomic Medicine, University of California San Diego, La Jolla, California, United States of America.|Moores Cancer Center, University of California San Diego, La Jolla, California, United States of America, Department of Medicine, University of California San Diego, La Jolla, California, United States of America, Sanford Consortium for Regenerative Medicine, University of California San Diego, La Jolla, California, United States of America.|Moores Cancer Center, University of California San Diego, La Jolla, California, United States of America, Department of Medicine, University of California San Diego, La Jolla, California, United States of America, Sanford Consortium for Regenerative Medicine, University of California San Diego, La Jolla, California, United States of America.|Moores Cancer Center, University of California San Diego, La Jolla, California, United States of America.|Moores Cancer Center, University of California San Diego, La Jolla, California, United States of America, Department of Pediatrics and Rady Childrens Hospital, University of California San Diego, La Jolla, California, United States of America, Institute for Genomic Medicine, University of California San Diego, La Jolla, California, United States of America.', 'United States|United States|United States|United States|United States|United States|United States|Un', 108, 'Humans|Mutation|Neoplasms|Phosphoproteins|RNA Splice Sites|RNA Splicing Factors|Ribonucleoprotein, U2 Small Nuclear|Sequence Analysis, RNA|Transcriptome', 'Journal Article', '10.1371/journal.pcbi.1004105', '25768983', 'Mutations in the splicing factor SF3B1 are found in several cancer types and have been associated with various splicing defects. Using transcriptome sequencing data from chronic lymphocytic leukemia, breast cancer and uveal melanoma tumor samples, we show that hundreds of cryptic 3 splice sites (3SSs) are used in cancers with SF3B1 mutations. We define the necessary sequence context for the observed cryptic 3 SSs and propose that cryptic 3SS selection is a result of SF3B1 mutations causing a shift in the sterically protected region downstream of the branch point. While most cryptic 3SSs are present at low frequency (<10%) relative to nearby canonical 3SSs, we identified ten genes that preferred out-of-frame cryptic 3SSs. We show that cancers with mutations in the SF3B1 HEAT 5-9 repeats use cryptic 3SSs downstream of the branch point and provide both a mechanistic model consistent with published experimental data and affected targets that will guide further research into the oncogenic effects of SF3B1 mutation. '),
(87036, 2015, 'plos', 'HPV clearance and the neglected role of stochasticity', 'Ryser, Marc D|Myers, Evan R|Durrett, Rick', 'Department of Mathematics, Duke University, Durham, North Carolina, United States of America.|Department of Obstetrics and Gynecology, Duke University Medical School, Durham, North Carolina, United States of America.|Department of Mathematics, Duke University, Durham, North Carolina, United States of America.', 'United States|United States|United States', 17, 'Epithelium|Female|HIV Infections|Humans|Models, Biological|Models, Statistical|Papillomavirus Infections|Stochastic Processes|T-Lymphocytes', 'Journal Article', '10.1371/journal.pcbi.1004113', '25769112', 'Clearance of anogenital and oropharyngeal HPV infections is attributed primarily to a successful adaptive immune response. To date, little attention has been paid to the potential role of stochastic cell dynamics in the time it takes to clear an HPV infection. In this study, we combine mechanistic mathematical models at the cellular level with epidemiological data at the population level to disentangle the respective roles of immune capacity and cell dynamics in the clearing mechanism. Our results suggest that chance-in form of the stochastic dynamics of basal stem cells-plays a critical role in the elimination of HPV-infected cell clones. In particular, we find that in immunocompetent adolescents with cervical HPV infections, the immune response may contribute less than 20% to virus clearance-the rest is taken care of by the stochastic proliferation dynamics in the basal layer. In HIV-negative individuals, the contribution of the immune response may be negligible. '),
(87037, 2015, 'plos', 'Microbial forensics: predicting phenotypic characteristics and environmental conditions from large-scale gene expression profiles', 'Kim, Minseung|Zorraquino, Violeta|Tagkopoulos, Ilias', 'Department of Computer Science, University of California, Davis, Davis, California, United States of America, UC Davis Genome Center, University of California, Davis, Davis, California, United States of America.|UC Davis Genome Center, University of California, Davis, Davis, California, United States of America.|Department of Computer Science, University of California, Davis, Davis, California, United States of America, UC Davis Genome Center, University of California, Davis, Davis, California, United States of America.', 'United States|United States|United States', 11, 'Algorithms|Area Under Curve|Biomarkers|Environment|Escherichia coli|Forensic Sciences|Gene Expression Profiling|Metabolic Networks and Pathways|Phenotype', 'Journal Article', '10.1371/journal.pcbi.1004127', '25774498', 'A tantalizing question in cellular physiology is whether the cellular state and environmental conditions can be inferred by the expression signature of an organism. To investigate this relationship, we created an extensive normalized gene expression compendium for the bacterium Escherichia coli that was further enriched with meta-information through an iterative learning procedure. We then constructed an ensemble method to predict environmental and cellular state, including strain, growth phase, medium, oxygen level, antibiotic and carbon source presence. Results show that gene expression is an excellent predictor of environmental structure, with multi-class ensemble models achieving balanced accuracy between 70.0% (±3.5%) to 98.3% (±2.3%) for the various characteristics. Interestingly, this performance can be significantly boosted when environmental and strain characteristics are simultaneously considered, as a composite classifier that captures the inter-dependencies of three characteristics (medium, phase and strain) achieved 10.6% (±1.0%) higher performance than any individual models. Contrary to expectations, only 59% of the top informative genes were also identified as differentially expressed under the respective conditions. Functional analysis of the respective genetic signatures implicates a wide spectrum of Gene Ontology terms and KEGG pathways with condition-specific information content, including iron transport, transferases, and enterobactin synthesis. Further experimental phenotypic-to-genotypic mapping that we conducted for knock-out mutants argues for the information content of top-ranked genes. This work demonstrates the degree at which genome-scale transcriptional information can be predictive of latent, heterogeneous and seemingly disparate phenotypic and environmental characteristics, with far-reaching applications. '),
(87038, 2015, 'plos', 'Proportionality: a valid alternative to correlation for relative data', 'Lovell, David|Pawlowsky-Glahn, Vera|Egozcue, Juan Josxc3xa9|Marguerat, Samuel|Bxc3xa4hler, Jxc3xbcrg', 'Queensland University of Technology, Brisbane, Australia.|Dept. dInformxc3xa0tica, Matemxc3xa0tica Aplicada i Estadxc3xadstica. U. de Girona, Espaxc3xb1a.|Dept. Applied Mathematics III, U. Politxc3xa9cnica de Catalunya, Barcelona, Spain.|MRC Clinical Sciences Centre, Imperial College London, United Kingdom.|Research Department of Genetics, Evolution and Environment, University College London, United Kingdom.', 'Australia|-|Spain|United Kingdom|United Kingdom', 94, 'Computational Biology|Gene Expression Regulation, Fungal|Models, Genetic|Models, Statistical|RNA, Fungal|RNA, Messenger|Research Design|Yeasts', 'Journal Article', '10.1371/journal.pcbi.1004075', '25775355', 'In the life sciences, many measurement methods yield only the relative abundances of different components in a sample. With such relative-or compositional-data, differential expression needs careful interpretation, and correlation-a statistical workhorse for analyzing pairwise relationships-is an inappropriate measure of association. Using yeast gene expression data we show how correlation can be misleading and present proportionality as a valid alternative for relative data. We show how the strength of proportionality between two variables can be meaningfully and interpretably described by a new statistic xcfx95 which can be used instead of correlation as the basis of familiar analyses and visualisation methods, including co-expression networks and clustered heatmaps. While the main aim of this study is to present proportionality as a means to analyse relative data, it also raises intriguing questions about the molecular mechanisms underlying the proportional regulation of a range of yeast genes. '),
(87039, 2015, 'plos', 'On the firing rate dependency of the phase response curve of rat Purkinje neurons in vitro', 'Couto, João|Linaro, Daniele|De Schutter, E|Giugliano, Michele', 'Theoretical Neurobiology and Neuroengineering Laboratory, University of Antwerp, Antwerpen, Belgium, NeuroElectronics Research Flanders, Leuven, Belgium.|Theoretical Neurobiology and Neuroengineering Laboratory, University of Antwerp, Antwerpen, Belgium, NeuroElectronics Research Flanders, Leuven, Belgium.|Theoretical Neurobiology and Neuroengineering Laboratory, University of Antwerp, Antwerpen, Belgium, Computational Neuroscience Unit, Okinawa Institute of Science and Technology Graduate University, Onna, Okinawa, Japan.|Theoretical Neurobiology and Neuroengineering Laboratory, University of Antwerp, Antwerpen, Belgium, NeuroElectronics Research Flanders, Leuven, Belgium, Department of Computer Science, University of Sheffield, Sheffield, United Kingdom, Brain Mind Institute, EPFL, Lausanne, Switzerland.', 'Belgium|Belgium|Belgium|Belgium', 13, 'Action Potentials|Animals|Computational Biology|Computer Simulation|Models, Neurological|Purkinje Cells|Rats|Rats, Wistar', 'Journal Article', '10.1371/journal.pcbi.1004112', '25775448', 'Synchronous spiking during cerebellar tasks has been observed across Purkinje cells: however, little is known about the intrinsic cellular mechanisms responsible for its initiation, cessation and stability. The Phase Response Curve (PRC), a simple input-output characterization of single cells, can provide insights into individual and collective properties of neurons and networks, by quantifying the impact of an infinitesimal depolarizing current pulse on the time of occurrence of subsequent action potentials, while a neuron is firing tonically. Recently, the PRC theory applied to cerebellar Purkinje cells revealed that these behave as phase-independent integrators at low firing rates, and switch to a phase-dependent mode at high rates. Given the implications for computation and information processing in the cerebellum and the possible role of synchrony in the communication with its post-synaptic targets, we further explored the firing rate dependency of the PRC in Purkinje cells. We isolated key factors for the experimental estimation of the PRC and developed a closed-loop approach to reliably compute the PRC across diverse firing rates in the same cell. Our results show unambiguously that the PRC of individual Purkinje cells is firing rate dependent and that it smoothly transitions from phase independent integrator to a phase dependent mode. Using computational models we show that neither channel noise nor a realistic cell morphology are responsible for the rate dependent shift in the phase response curve. '),
(87040, 2015, 'plos', 'Correction: The pharmacodynamics of the p53-Mdm2 targeting drug nutlin: the role of gene-switching noise', 'PLOS Computational Biology Staff', 'Theoretical Neurobiology and Neuroengineering Laboratory, University of Antwerp, Antwerpen, Belgium, NeuroElectronics Research Flanders, Leuven, Belgium, Department of Computer Science, University of Sheffield, Sheffield, United Kingdom, Brain Mind Institute, EPFL, Lausanne, Switzerland.', 'Belgium', 0, '-', 'Published Erratum', '10.1371/journal.pcbi.1004215', '25781726', '-'),
(87041, 2015, 'plos', 'Within-host stochastic emergence dynamics of immune-escape mutants', 'Hartfield, Matthew|Alizon, Samuel', 'Laboratoire MIVEGEC (UMR CNRS 5290, IRD 224, UM1, UM2), 911 avenue Agropolis, Montpellier, France.|Laboratoire MIVEGEC (UMR CNRS 5290, IRD 224, UM1, UM2), 911 avenue Agropolis, Montpellier, France.', 'France|France', 3, 'Computational Biology|Host-Pathogen Interactions|Infection|Models, Biological|Models, Statistical|Mutation', 'Journal Article', '10.1371/journal.pcbi.1004149', '25785434', 'Predicting the emergence of new pathogenic strains is a key goal of evolutionary epidemiology. However, the majority of existing studies have focussed on emergence at the population level, and not within a host. In particular, the coexistence of pre-existing and mutated strains triggers a heightened immune response due to the larger total pathogen population, this feedback can smother mutated strains before they reach an ample size and establish. Here, we extend previous work for measuring emergence probabilities in non-equilibrium populations, to within-host models of acute infections. We create a mathematical model to investigate the emergence probability of a fitter strain if it mutates from a self-limiting strain that is guaranteed to go extinct in the long-term. We show that ongoing immune cell proliferation during the initial stages of infection causes a drastic reduction in the probability of emergence of mutated strains, we further outline how this effect can be accurately measured. Further analysis of the model shows that, in the short-term, mutant strains that enlarge their replication rate due to evolving an increased growth rate are more favoured than strains that suffer a lower immune-mediated death rate (immune tolerance), as the latter does not completely evade ongoing immune proliferation due to inter-parasitic competition. We end by discussing the model in relation to within-host evolution of human pathogens (including HIV, hepatitis C virus, and cancer), and how ongoing immune growth can affect their evolutionary dynamics. '),
(87042, 2015, 'plos', 'Prioritizing therapeutics for lung cancer: an integrative meta-analysis of cancer gene signatures and chemogenomic data', 'Fortney, Kristen|Griesman, Joshua|Kotlyar, Max|Pastrello, Chiara|Angeli, Marc|Sound-Tsao, Ming|Jurisica, Igor', 'Department of Medical Biophysics, University of Toronto, Toronto, Ontario, Canada.|Princess Margaret Cancer Centre, University Health Network, Toronto, Ontario, Canada.|Princess Margaret Cancer Centre, University Health Network, Toronto, Ontario, Canada.|Princess Margaret Cancer Centre, University Health Network, Toronto, Ontario, Canada.|Princess Margaret Cancer Centre, University Health Network, Toronto, Ontario, Canada.|Princess Margaret Cancer Centre, University Health Network, Toronto, Ontario, Canada.|Department of Medical Biophysics, University of Toronto, Toronto, Ontario, Canada, Princess Margaret Cancer Centre, University Health Network, Toronto, Ontario, Canada, Department of Computer Science, University of Toronto, Toronto, Ontario, Canada, Techna Institute, University Health Network, Toronto, Ontario, Canada.', 'Canada|Canada|Canada|Canada|Canada|Canada|Canada', 22, 'Antineoplastic Agents|Cell Line, Tumor|Computational Biology|Computer Simulation|Gene Expression Profiling|Gene Expression Regulation, Neoplastic|Humans|Lung Neoplasms|Pharmacogenetics|Pimozide', 'Journal Article', '10.1371/journal.pcbi.1004068', '25786242', 'Repurposing FDA-approved drugs with the aid of gene signatures of disease can accelerate the development of new therapeutics. A major challenge to developing reliable drug predictions is heterogeneity. Different gene signatures of the same disease or drug treatment often show poor overlap across studies, as a consequence of both biological and technical variability, and this can affect the quality and reproducibility of computational drug predictions. Existing algorithms for signature-based drug repurposing use only individual signatures as input. But for many diseases, there are dozens of signatures in the public domain. Methods that exploit all available transcriptional knowledge on a disease should produce improved drug predictions. Here, we adapt an established meta-analysis framework to address the problem of drug repurposing using an ensemble of disease signatures. Our computational pipeline takes as input a collection of disease signatures, and outputs a list of drugs predicted to consistently reverse pathological gene changes. We apply our method to conduct the largest and most systematic repurposing study on lung cancer transcriptomes, using 21 signatures. We show that scaling up transcriptional knowledge significantly increases the reproducibility of top drug hits, from 44% to 78%. We extensively characterize drug hits in silico, demonstrating that they slow growth significantly in nine lung cancer cell lines from the NCI-60 collection, and identify CALM1 and PLA2G4A as promising drug targets for lung cancer. Our meta-analysis pipeline is general, and applicable to any disease context, it can be applied to improve the results of signature-based drug repurposing by leveraging the large number of disease signatures in the public domain. '),
(87043, 2015, 'plos', 'Spatial heterogeneity in drug concentrations can facilitate the emergence of resistance to cancer therapy', 'Fu, Feng|Nowak, Martin A|Bonhoeffer, Sebastian', 'Theoretical Biology Group, Institute of Integrative Biology, ETH Zurich, Zurich, Switzerland.|Program for Evolutionary Dynamics, Department of Organismic and Evolutionary Biology, Department of Mathematics, Harvard University, Cambridge, Massachusetts, United States of America.|Theoretical Biology Group, Institute of Integrative Biology, ETH Zurich, Zurich, Switzerland.', 'Switzerland|United States|Switzerland', 55, 'Antineoplastic Agents|Cell Movement|Cell Proliferation|Computational Biology|Drug Resistance, Neoplasm|Humans|Neoplasms|Spatio-Temporal Analysis|Tumor Microenvironment', 'Journal Article', '10.1371/journal.pcbi.1004142', '25789469', 'Acquired resistance is one of the major barriers to successful cancer therapy. The development of resistance is commonly attributed to genetic heterogeneity. However, heterogeneity of drug penetration of the tumor microenvironment both on the microscopic level within solid tumors as well as on the macroscopic level across metastases may also contribute to acquired drug resistance. Here we use mathematical models to investigate the effect of drug heterogeneity on the probability of escape from treatment and the time to resistance. Specifically we address scenarios with sufficiently potent therapies that suppress growth of all preexisting genetic variants in the compartment with the highest possible drug concentration. To study the joint effect of drug heterogeneity, growth rate, and evolution of resistance, we analyze a multi-type stochastic branching process describing growth of cancer cells in multiple compartments with different drug concentrations and limited migration between compartments. We show that resistance is likely to arise first in the sanctuary compartment with poor drug penetrations and from there populate non-sanctuary compartments with high drug concentrations. Moreover, we show that only below a threshold rate of cell migration does spatial heterogeneity accelerate resistance evolution, otherwise deterring drug resistance with excessively high migration rates. Our results provide new insights into understanding why cancers tend to quickly become resistant, and that cell migration and the presence of sanctuary sites with little drug exposure are essential to this end. ');
INSERT INTO `papers` (`id`, `ano`, `journal`, `titulo`, `autores`, `afiliacao`, `pais`, `citacoes`, `palavra_chave`, `categorias`, `doi`, `pubmed`, `abstract`) VALUES
(87044, 2015, 'plos', 'Detailed contact data and the dissemination of Staphylococcus aureus in hospitals', 'Obadia, Thomas|Silhol, Romain|Opatowski, Lulla|Temime, Laura|Legrand, Judith|Thiébaut, Anne C M|Herrmann, Jean-Louis|Fleury, Éric|Guillemot, Didier|Boëlle, Pierre-Yves|I-Bird Study Group', 'Sorbonne Universités, UPMC Univ Paris 06, UMR_S 1136, Institut Pierre Louis dEpidémiologie et de Santé Publique, F-75013, Paris, France, INSERM, UMR_S 1136, Institut Pierre Louis dEpidémiologie et de Santé Publique, F-75013, Paris, France.|Department of Infectious Disease Epidemiology, Imperial College London, London, United Kingdom.|Inserm UMR 1181 Biostatistics, Biomathematics, Pharmacoepidemiology and Infectious Diseases (B2PHI), F-75015, Paris, France, Institut Pasteur, UMR 1181, B2PHI, F-75015, Paris, France, Univ. Versailles St Quentin, UMR 1181, B2PHI, F-78180 Montigny-le-Bretonneux.|Laboratoire MESuRS, Conservatoire National des Arts et Métiers, 75003, Paris, France.|Univ Paris-Sud, UMR 0320/UMR8120 Génétique Quantitative et Evolution-Le Moulon, F-91190, Gif-sur-Yvette, France.|Inserm UMR 1181 Biostatistics, Biomathematics, Pharmacoepidemiology and Infectious Diseases (B2PHI), F-75015, Paris, France, Institut Pasteur, UMR 1181, B2PHI, F-75015, Paris, France, Univ. Versailles St Quentin, UMR 1181, B2PHI, F-78180 Montigny-le-Bretonneux.|INSERM U1173, UFR Simone Veil, Versailles-Saint-Quentin University, 78180, Saint-Quentin en Yvelines, France, AP-HP, Hôpital Raymond Poincaré, Service de Microbiologie, F-92380, Garches, France.|ENS de Lyon, Université de Lyon, Laboratoire de lInformatique du Parallélisme (UMR CNRS 5668-ENS de Lyon-UCB Lyon 1), IXXI Rhône Alpes Complex Systems Institute, Lyon, France, Inria-Institut National de Recherche en Informatique et en Automatique, Montbonnet, France.|Inserm UMR 1181 Biostatistics, Biomathematics, Pharmacoepidemiology and Infectious Diseases (B2PHI), F-75015, Paris, France, Institut Pasteur, UMR 1181, B2PHI, F-75015, Paris, France, Univ. Versailles St Quentin, UMR 1181, B2PHI, F-78180 Montigny-le-Bretonneux, AP-HP, Raymond Poincare Hospital, F-92380 Garches, France.|Sorbonne Universités, UPMC Univ Paris 06, UMR_S 1136, Institut Pierre Louis dEpidémiologie et de Santé Publique, F-75013, Paris, France, INSERM, UMR_S 1136, Institut Pierre Louis dEpidémiologie et de Santé Publique, F-75013, Paris, France, AP-HP, Hôpital Saint-Antoine, Département de Santé Publique, F-75571, Paris, France.|Sorbonne Universités, UPMC Univ Paris 06, UMR_S 1136, Institut Pierre Louis dEpidémiologie et de Santé Publique, F-75013, Paris, France, INSERM, UMR_S 1136, Institut Pierre Louis dEpidémiologie et de Santé Publique, F-75013, Paris, France, AP-HP, Hôpital Saint-Antoine, Département de Santé Publique, F-75571, Paris, France.', 'France|United Kingdom|France|France|France|France|France|France|France|France|France', 41, 'Adolescent|Adult|Aged|Aged, 80 and over|Computational Biology|Cross Infection|Female|Hospitals|Humans|Male|Middle Aged|Models, Biological|Staphylococcal Infections|Staphylococcus aureus|Young Adult', 'Journal Article', '10.1371/journal.pcbi.1004170', '25789632', 'Close proximity interactions (CPIs) measured by wireless electronic devices are increasingly used in epidemiological models. However, no evidence supports that electronically collected CPIs inform on the contacts leading to transmission. Here, we analyzed Staphylococcus aureus carriage and CPIs recorded simultaneously in a long-term care facility for 4 months in 329 patients and 261 healthcare workers to test this hypothesis. In the broad diversity of isolated S. aureus strains, 173 transmission events were observed between participants. The joint analysis of carriage and CPIs showed that CPI paths linking incident cases to other individuals carrying the same strain (i.e. possible infectors) had fewer intermediaries than predicted by chance (P < 0.001), a feature that simulations showed to be the signature of transmission along CPIs. Additional analyses revealed a higher dissemination risk between patients via healthcare workers than via other patients. In conclusion, S. aureus transmission was consistent with contacts defined by electronically collected CPIs, illustrating their potential as a tool to control hospital-acquired infections and help direct surveillance. '),
(87045, 2015, 'plos', 'Integrating interactive computational modeling in biology curricula', 'Helikar, Tomáš|Cutucache, Christine E|Dahlquist, Lauren M|Herek, Tyler A|Larson, Joshua J|Rogers, Jim A', 'Department of Biochemistry, University of Nebraska-Lincoln, Lincoln, Nebraska, United States of America.|Department of Biology, University of Nebraska-Omaha, Omaha, Nebraska, United States of America.|Department of Biology, University of Nebraska-Omaha, Omaha, Nebraska, United States of America.|Department of Biology, University of Nebraska-Omaha, Omaha, Nebraska, United States of America.|Department of Biology, University of Nebraska-Omaha, Omaha, Nebraska, United States of America.|Department of Mathematics, University of Nebraska-Omaha, Omaha, Nebraska, United States of America.', 'United States|United States|United States|United States|United States|United States', 0, 'Biology|Computational Biology|Computer Simulation|Curriculum|Humans|Models, Immunological|Software', 'Journal Article', '10.1371/journal.pcbi.1004131', '25790483', 'While the use of computer tools to simulate complex processes such as computer circuits is normal practice in fields like engineering, the majority of life sciences/biological sciences courses continue to rely on the traditional textbook and memorization approach. To address this issue, we explored the use of the Cell Collective platform as a novel, interactive, and evolving pedagogical tool to foster student engagement, creativity, and higher-level thinking. Cell Collective is a Web-based platform used to create and simulate dynamical models of various biological processes. Students can create models of cells, diseases, or pathways themselves or explore existing models. This technology was implemented in both undergraduate and graduate courses as a pilot study to determine the feasibility of such software at the university level. First, a new (In Silico Biology) class was developed to enable students to learn biology by building and breaking it via computer models and their simulations. This class and technology also provide a non-intimidating way to incorporate mathematical and computational concepts into a class with students who have a limited mathematical background. Second, we used the technology to mediate the use of simulations and modeling modules as a learning tool for traditional biological concepts, such as T cell differentiation or cell cycle regulation, in existing biology courses. Results of this pilot application suggest that there is promise in the use of computational modeling and software tools such as Cell Collective to provide new teaching methods in biology and contribute to the implementation of the Vision and Change call to action in undergraduate biology education by providing a hands-on approach to biology. '),
(87046, 2015, 'plos', 'Anticipation and choice heuristics in the dynamic consumption of pain relief', 'Story, Giles W|Vlaev, Ivo|Dayan, Peter|Seymour, Ben|Darzi, Ara|Dolan, Raymond J', 'Centre for Health Policy, Institute of Global Health Innovation, Imperial College London, London, United Kingdom, Wellcome Trust Centre for Neuroimaging, University College London, London, United Kingdom.|Warwick Business School, University of Warwick, Coventry, United Kingdom.|Gatsby Computational Neuroscience Unit, University College London, London, United Kingdom.|Center for Information and Neural Networks, National Institute for Information and Communications Technology, Osaka, Japan, Computational and Biological Learning Laboratory, Department of Engineering, University of Cambridge, Cambridge, United Kingdom.|Centre for Health Policy, Institute of Global Health Innovation, Imperial College London, London, United Kingdom.|Wellcome Trust Centre for Neuroimaging, University College London, London, United Kingdom.', 'United Kingdom|United Kingdom|United Kingdom|United Kingdom|United Kingdom|United Kingdom', 0, 'Anticipation, Psychological|Choice Behavior|Computational Biology|Female|Heuristics|Humans|Male|Models, Neurological|Pain|Pain Management', 'Journal Article', '10.1371/journal.pcbi.1004030', '25793302', 'Humans frequently need to allocate resources across multiple time-steps. Economic theory proposes that subjects do so according to a stable set of intertemporal preferences, but the computational demands of such decisions encourage the use of formally less competent heuristics. Few empirical studies have examined dynamic resource allocation decisions systematically. Here we conducted an experiment involving the dynamic consumption over approximately 15 minutes of a limited budget of relief from moderately painful stimuli. We had previously elicited the participants time preferences for the same painful stimuli in one-off choices, allowing us to assess self-consistency. Participants exhibited three characteristic behaviors: saving relief until the end, spreading relief across time, and early spending, of which the last was markedly less prominent. The likelihood that behavior was heuristic rather than normative is suggested by the weak correspondence between one-off and dynamic choices. We show that the consumption choices are consistent with a combination of simple heuristics involving early-spending, spreading or saving of relief until the end, with subjects predominantly exhibiting the last two. '),
(87047, 2015, 'plos', 'On the number of neurons and time scale of integration underlying the formation of percepts in the brain', 'Wohrer, Adrien|Machens, Christian K', 'Group for Neural Theory, Laboratoire de Neurosciences Cognitives, INSERM U960, École Normale Supérieure, Paris, France.|Group for Neural Theory, Laboratoire de Neurosciences Cognitives, INSERM U960, École Normale Supérieure, Paris, France, Champalimaud Neuroscience Programme, Champalimaud Centre for the Unknown, Lisbon, Portugal.', 'France|France', 0, 'Animals|Brain|Computational Biology|Computer Simulation|Decision Making|Haplorhini|Models, Neurological|Neurons|Reproducibility of Results|Time Factors', 'Journal Article', '10.1371/journal.pcbi.1004082', '25793393', 'All of our perceptual experiences arise from the activity of neural populations. Here we study the formation of such percepts under the assumption that they emerge from a linear readout, i.e., a weighted sum of the neurons firing rates. We show that this assumption constrains the trial-to-trial covariance structure of neural activities and animal behavior. The predicted covariance structure depends on the readout parameters, and in particular on the temporal integration window w and typical number of neurons K used in the formation of the percept. Using these predictions, we show how to infer the readout parameters from joint measurements of a subjects behavior and neural activities. We consider three such scenarios: (1) recordings from the complete neural population, (2) recordings of neuronal sub-ensembles whose size exceeds K, and (3) recordings of neuronal sub-ensembles that are smaller than K. Using theoretical arguments and artificially generated data, we show that the first two scenarios allow us to recover the typical spatial and temporal scales of the readout. In the third scenario, we show that the readout parameters can only be recovered by making additional assumptions about the structure of the full population activity. Our work provides the first thorough interpretation of (feed-forward) percept formation from a population of sensory neurons. We discuss applications to experimental recordings in classic sensory decision-making tasks, which will hopefully provide new insights into the nature of perceptual integration. '),
(87048, 2015, 'plos', 'Improved statistical methods enable greater sensitivity in rhythm detection for genome-wide data', 'Hutchison, Alan L|Maienschein-Cline, Mark|Chiang, Andrew H|Tabei, S M Ali|Gudjonson, Herman|Bahroos, Neil|Allada, Ravi|Dinner, Aaron R', 'Medical Scientist Training Program, University of Chicago, Chicago, Illinois, United States of America, Graduate Program in the Biophysical Sciences, University of Chicago, Chicago, Illinois, United States of America, James Franck Institute, University of Chicago, Chicago, Illinois, United States of America.|Center for Research Informatics, University of Illinois at Chicago, Chicago, Illinois, United States of America.|James Franck Institute, University of Chicago, Chicago, Illinois, United States of America.|James Franck Institute, University of Chicago, Chicago, Illinois, United States of America.|Graduate Program in the Biophysical Sciences, University of Chicago, Chicago, Illinois, United States of America, James Franck Institute, University of Chicago, Chicago, Illinois, United States of America.|Center for Research Informatics, University of Illinois at Chicago, Chicago, Illinois, United States of America.|Department of Neurobiology, Northwestern University, Evanston, Illinois, United States of America.|Graduate Program in the Biophysical Sciences, University of Chicago, Chicago, Illinois, United States of America, James Franck Institute, University of Chicago, Chicago, Illinois, United States of America, Department of Chemistry, University of Chicago, Chicago, Illinois, United States of America.', 'United States|United States|United States|United States|United States|United States|United States|Un', 24, 'Animals|Circadian Rhythm|Computer Simulation|Drosophila melanogaster|Gene Expression Profiling|Genome, Insect|Genomics|Models, Genetic|Models, Statistical', 'Journal Article', '10.1371/journal.pcbi.1004094', '25793520', 'Robust methods for identifying patterns of expression in genome-wide data are important for generating hypotheses regarding gene function. To this end, several analytic methods have been developed for detecting periodic patterns. We improve one such method, JTK_CYCLE, by explicitly calculating the null distribution such that it accounts for multiple hypothesis testing and by including non-sinusoidal reference waveforms. We term this method empirical JTK_CYCLE with asymmetry search, and we compare its performance to JTK_CYCLE with Bonferroni and Benjamini-Hochberg multiple hypothesis testing correction, as well as to five other methods: cyclohedron test, address reduction, stable persistence, ANOVA, and F24. We find that ANOVA, F24, and JTK_CYCLE consistently outperform the other three methods when data are limited and noisy, empirical JTK_CYCLE with asymmetry search gives the greatest sensitivity while controlling for the false discovery rate. Our analysis also provides insight into experimental design and we find that, for a fixed number of samples, better sensitivity and specificity are achieved with higher numbers of replicates than with higher sampling density. Application of the methods to detecting circadian rhythms in a metadataset of microarrays that quantify time-dependent gene expression in whole heads of Drosophila melanogaster reveals annotations that are enriched among genes with highly asymmetric waveforms. These include a wide range of oxidation reduction and metabolic genes, as well as genes with transcripts that have multiple splice forms. '),
(87049, 2015, 'plos', 'Spatio-temporal model of endogenous ROS and raft-dependent WNT/beta-catenin signaling driving cell fate commitment in human neural progenitor cells', 'Haack, Fiete|Lemcke, Heiko|Ewald, Roland|Rharass, Tareck|Uhrmacher, Adelinde M', 'Modeling and Simulation Group, Institute of Computer Science, University of Rostock, Rostock, Germany.|Live Cell Imaging Center, Institute of Biological Sciences, University of Rostock, Rostock, Germany, Reference and Translation Center for Cardiac Stem Cell Therapy (RTC), University Medical Center Rostock, Rostock, Germany.|Modeling and Simulation Group, Institute of Computer Science, University of Rostock, Rostock, Germany.|Live Cell Imaging Center, Institute of Biological Sciences, University of Rostock, Rostock, Germany, Electrochemical Signaling in Development and Disease, Max-Delbrxc3xbcck-Center for Molecular Medicine (MDC) Berlin-Buch, Berlin-Buch, Germany.|Modeling and Simulation Group, Institute of Computer Science, University of Rostock, Rostock, Germany.', 'Germany|Germany|Germany|Germany|Germany', 30, 'Cell Line|Computational Biology|Computer Simulation|Humans|Neural Stem Cells|Reactive Oxygen Species|Reproducibility of Results|Spatio-Temporal Analysis|Wnt Proteins|Wnt Signaling Pathway|beta Catenin', 'Journal Article', '10.1371/journal.pcbi.1004106', '25793621', 'Canonical WNT/xcexb2-catenin signaling is a central pathway in embryonic development, but it is also connected to a number of cancers and developmental disorders. Here we apply a combined in-vitro and in-silico approach to investigate the spatio-temporal regulation of WNT/xcexb2-catenin signaling during the early neural differentiation process of human neural progenitors cells (hNPCs), which form a new prospect for replacement therapies in the context of neurodegenerative diseases. Experimental measurements indicate a second signal mechanism, in addition to canonical WNT signaling, being involved in the regulation of nuclear xcexb2-catenin levels during the cell fate commitment phase of neural differentiation. We find that the biphasic activation of xcexb2-catenin signaling observed experimentally can only be explained through a model that combines Reactive Oxygen Species (ROS) and raft dependent WNT/xcexb2-catenin signaling. Accordingly after initiation of differentiation endogenous ROS activates DVL in a redox-dependent manner leading to a transient activation of down-stream xcexb2-catenin signaling, followed by continuous auto/paracrine WNT signaling, which crucially depends on lipid rafts. Our simulation studies further illustrate the elaborate spatio-temporal regulation of DVL, which, depending on its concentration and localization, may either act as direct inducer of the transient ROS/xcexb2-catenin signal or as amplifier during continuous auto-/parcrine WNT/xcexb2-catenin signaling. In addition we provide the first stochastic computational model of WNT/xcexb2-catenin signaling that combines membrane-related and intracellular processes, including lipid rafts/receptor dynamics as well as WNT- and ROS-dependent xcexb2-catenin activation. The models predictive ability is demonstrated under a wide range of varying conditions for in-vitro and in-silico reference data sets. Our in-silico approach is realized in a multi-level rule-based language, that facilitates the extension and modification of the model. Thus, our results provide both new insights and means to further our understanding of canonical WNT/xcexb2-catenin signaling and the role of ROS as intracellular signaling mediator. '),
(87050, 2015, 'plos', 'Intra-tumour signalling entropy determines clinical outcome in breast and lung cancer', 'Banerji, Christopher R S|Severini, Simone|Caldas, Carlos|Teschendorff, Andrew E', 'Statistical Cancer Genomics, Paul OGorman Building, UCL Cancer Institute, University College London, London WC1E 6BT, UK, Department of Computer Science, University College London, London WC1E 6BT, UK, Centre of Mathematics and Physics in the Life Sciences and Experimental Biology, University College London, London WC1E 6BT, UK.|Department of Computer Science, University College London, London WC1E 6BT, UK.|Breast Cancer Functional Genomics Laboratory, Cancer Research UK, Cambridge Institute, University of Cambridge, Li Ka Shing Centre, Robinson Way, Cambridge, UK.|Statistical Cancer Genomics, Paul OGorman Building, UCL Cancer Institute, University College London, London WC1E 6BT, UK, CAS-MPG Partner Institute for Computational Biology, Chinese Academy of Sciences, Shanghai Institute for Biological Sciences, 320 Yue Yang Road, Shanghai 200031, China.', 'United Kingdom|United Kingdom|United Kingdom|China', 25, 'Breast Neoplasms|Computational Biology|Entropy|Female|Humans|Lung Neoplasms|Prognosis|Signal Transduction|Treatment Outcome', 'Journal Article', '10.1371/journal.pcbi.1004115', '25793737', 'The cancer stem cell hypothesis, that a small population of tumour cells are responsible for tumorigenesis and cancer progression, is becoming widely accepted and recent evidence has suggested a prognostic and predictive role for such cells. Intra-tumour heterogeneity, the diversity of the cancer cell population within the tumour of an individual patient, is related to cancer stem cells and is also considered a potential prognostic indicator in oncology. The measurement of cancer stem cell abundance and intra-tumour heterogeneity in a clinically relevant manner however, currently presents a challenge. Here we propose signalling entropy, a measure of signalling pathway promiscuity derived from a samples genome-wide gene expression profile, as an estimate of the stemness of a tumour sample. By considering over 500 mixtures of diverse cellular expression profiles, we reveal that signalling entropy also associates with intra-tumour heterogeneity. By analysing 3668 breast cancer and 1692 lung adenocarcinoma samples, we further demonstrate that signalling entropy correlates negatively with survival, outperforming leading clinical gene expression based prognostic tools. Signalling entropy is found to be a general prognostic measure, valid in different breast cancer clinical subgroups, as well as within stage I lung adenocarcinoma. We find that its prognostic power is driven by genes involved in cancer stem cells and treatment resistance. In summary, by approximating both stemness and intra-tumour heterogeneity, signalling entropy provides a powerful prognostic measure across different epithelial cancers. '),
(87051, 2015, 'plos', 'When can species abundance data reveal non-neutrality?', 'Al Hammal, Omar|Alonso, David|Etienne, Rampal S|Cornell, Stephen J', 'School of Biology, University of Leeds, Leeds, United Kingdom.|School of Biology, University of Leeds, Leeds, United Kingdom, Center for Advanced Studies (CEAB-CSIC), Blanes, Spain.|Groningen Institute for Evolutionary Life Sciences, University of Groningen, Groningen, Netherlands.|School of Biology, University of Leeds, Leeds, United Kingdom, Institute of Integrative Biology, University of Liverpool, Liverpool, United Kingdom (current address).', 'United Kingdom|Spain|Netherlands|United Kingdom', 10, 'Biodiversity|Computational Biology|Ecology|Forests|Models, Biological|Panama|Population Dynamics', 'Journal Article', '10.1371/journal.pcbi.1004134', '25793889', 'Species abundance distributions (SAD) are probably ecologys most well-known empirical pattern, and over the last decades many models have been proposed to explain their shape. There is no consensus over which model is correct, because the degree to which different processes can be discerned from SAD patterns has not yet been rigorously quantified. We present a power calculation to quantify our ability to detect deviations from neutrality using species abundance data. We study non-neutral stochastic community models, and show that the presence of non-neutral processes is detectable if sample size is large enough and/or the amplitude of the effect is strong enough. Our framework can be used for any candidate community model that can be simulated on a computer, and determines both the sampling effort required to distinguish between alternative processes, and a range for the strength of non-neutral processes in communities whose patterns are statistically consistent with neutral theory. We find that even data sets of the scale of the 50 Ha forest plot on Barro Colorado Island, Panama, are unlikely to be large enough to detect deviations from neutrality caused by competitive interactions alone, though the presence of multiple non-neutral processes with contrasting effects on abundance distributions may be detectable. '),
(87052, 2015, 'plos', 'Asymmetric genome organization in an RNA virus revealed via graph-theoretical analysis of tomographic data', 'Geraets, James A|Dykeman, Eric C|Stockley, Peter G|Ranson, Neil A|Twarock, Reidun', 'York Centre for Complex Systems Analysis, University of York, York, United Kingdom.|York Centre for Complex Systems Analysis, University of York, York, United Kingdom.|Astbury Centre for Structural Molecular Biology, University of Leeds, Leeds, United Kingdom.|Astbury Centre for Structural Molecular Biology, University of Leeds, Leeds, United Kingdom.|York Centre for Complex Systems Analysis, University of York, York, United Kingdom.', 'United Kingdom|United Kingdom|United Kingdom|United Kingdom|United Kingdom', 7, 'Computational Biology|Cryoelectron Microscopy|Genome, Viral|Levivirus|Models, Molecular|RNA Viruses|Tomography', 'Journal Article', '10.1371/journal.pcbi.1004146', '25793998', 'Cryo-electron microscopy permits 3-D structures of viral pathogens to be determined in remarkable detail. In particular, the protein containers encapsulating viral genomes have been determined to high resolution using symmetry averaging techniques that exploit the icosahedral architecture seen in many viruses. By contrast, structure determination of asymmetric components remains a challenge, and novel analysis methods are required to reveal such features and characterize their functional roles during infection. Motivated by the important, cooperative roles of viral genomes in the assembly of single-stranded RNA viruses, we have developed a new analysis method that reveals the asymmetric structural organization of viral genomes in proximity to the capsid in such viruses. The method uses geometric constraints on genome organization, formulated based on knowledge of icosahedrally-averaged reconstructions and the roles of the RNA-capsid protein contacts, to analyse cryo-electron tomographic data. We apply this method to the low-resolution tomographic data of a model virus and infer the unique asymmetric organization of its genome in contact with the protein shell of the capsid. This opens unprecedented opportunities to analyse viral genomes, revealing conserved structural features and mechanisms that can be targeted in antiviral drug design. '),
(87053, 2015, 'plos', 'Protein domain-level landscape of cancer-type-specific somatic mutations', 'Yang, Fan|Petsalaki, Evangelia|Rolland, Thomas|Hill, David E|Vidal, Marc|Roth, Frederick P', 'Department of Molecular Genetics, University of Toronto, Toronto, Ontario, Canada, Donnelly Centre, University of Toronto, Toronto, Ontario, Canada, Lunenfeld-Tanenbaum Research Institute, Mt. Sinai Hospital, Toronto, Ontario, Canada.|Donnelly Centre, University of Toronto, Toronto, Ontario, Canada, Lunenfeld-Tanenbaum Research Institute, Mt. Sinai Hospital, Toronto, Ontario, Canada.|Center for Cancer Systems Biology (CCSB), Dana-Farber Cancer Institute, Boston, Massachusetts, United States of America, Department of Genetics, Harvard Medical School, Boston, Massachusetts, United States of America.|Center for Cancer Systems Biology (CCSB), Dana-Farber Cancer Institute, Boston, Massachusetts, United States of America.|Center for Cancer Systems Biology (CCSB), Dana-Farber Cancer Institute, Boston, Massachusetts, United States of America.|Department of Molecular Genetics, University of Toronto, Toronto, Ontario, Canada, Donnelly Centre, University of Toronto, Toronto, Ontario, Canada, Lunenfeld-Tanenbaum Research Institute, Mt. Sinai Hospital, Toronto, Ontario, Canada, Center for Cancer Systems Biology (CCSB), Dana-Farber Cancer Institute, Boston, Massachusetts, United States of America, Canadian Institute for Advanced Research, Toronto, Ontario, Canada, Department of Computer Science, University of Toronto, Toronto, Ontario, Canada.', 'Canada|Canada|United States|United States|United States|Canada', 33, 'Cluster Analysis|Computational Biology|DNA Mutational Analysis|Humans|Models, Molecular|Mutation|Neoplasm Proteins|Neoplasms|Protein Structure, Tertiary|Sequence Analysis, Protein', 'Journal Article', '10.1371/journal.pcbi.1004147', '25794154', 'Identifying driver mutations and their functional consequences is critical to our understanding of cancer. Towards this goal, and because domains are the functional units of a protein, we explored the protein domain-level landscape of cancer-type-specific somatic mutations. Specifically, we systematically examined tumor genomes from 21 cancer types to identify domains with high mutational density in specific tissues, the positions of mutational hotspots within these domains, and the functional and structural context where possible. While hotspots corresponding to specific gain-of-function mutations are expected for oncoproteins, we found that tumor suppressor proteins also exhibit strong biases toward being mutated in particular domains. Within domains, however, we observed the expected patterns of mutation, with recurrently mutated positions for oncogenes and evenly distributed mutations for tumor suppressors. For example, we identified both known and new endometrial cancer hotspots in the tyrosine kinase domain of the FGFR2 protein, one of which is also a hotspot in breast cancer, and found new two hotspots in the Immunoglobulin I-set domain in colon cancer. Thus, to prioritize cancer mutations for further functional studies aimed at more precise cancer treatments, we have systematically correlated mutations and cancer types at the protein domain level. '),
(87054, 2015, 'plos', 'Energy landscape reveals that the budding yeast cell cycle is a robust and adaptive multi-stage process', 'Lv, Cheng|Li, Xiaoguang|Li, Fangting|Li, Tiejun', 'School of Physics, Peking University, Beijing, China.|LMAM and School of Mathematical Sciences, Peking University, Beijing, China.|School of Physics, Peking University, Beijing, China, Center of Quantitative Biology, Peking University, Beijing, China.|LMAM and School of Mathematical Sciences, Peking University, Beijing, China.', 'China|China|China|China', 22, 'Algorithms|Cell Cycle|Computational Biology|Energy Metabolism|Models, Biological|Saccharomycetales', 'Journal Article', '10.1371/journal.pcbi.1004156', '25794282', 'Quantitatively understanding the robustness, adaptivity and efficiency of cell cycle dynamics under the influence of noise is a fundamental but difficult question to answer for most eukaryotic organisms. Using a simplified budding yeast cell cycle model perturbed by intrinsic noise, we systematically explore these issues from an energy landscape point of view by constructing an energy landscape for the considered system based on large deviation theory. Analysis shows that the cell cycle trajectory is sharply confined by the ambient energy barrier, and the landscape along this trajectory exhibits a generally flat shape. We explain the evolution of the system on this flat path by incorporating its non-gradient nature. Furthermore, we illustrate how this global landscape changes in response to external signals, observing a nice transformation of the landscapes as the excitable system approaches a limit cycle system when nutrients are sufficient, as well as the formation of additional energy wells when the DNA replication checkpoint is activated. By taking into account the finite volume effect, we find additional pits along the flat cycle path in the landscape associated with the checkpoint mechanism of the cell cycle. The difference between the landscapes induced by intrinsic and extrinsic noise is also discussed. In our opinion, this meticulous structure of the energy landscape for our simplified model is of general interest to other cell cycle dynamics, and the proposed methods can be applied to study similar biological systems. '),
(87055, 2015, 'plos', 'Evolution of bow-tie architectures in biology', 'Friedlander, Tamar|Mayo, Avraham E|Tlusty, Tsvi|Alon, Uri', 'Department of Molecular Cell Biology, Weizmann Institute of Science, Rehovot, Israel, Institute of Science and Technology Austria, Klosterneuburg, Austria.|Department of Molecular Cell Biology, Weizmann Institute of Science, Rehovot, Israel.|Simons Center for Systems Biology, Institute for Advanced Study, Princeton, New Jersey, United States of America.|Department of Molecular Cell Biology, Weizmann Institute of Science, Rehovot, Israel.', 'Austria|Israel|Jersey|Israel', 52, 'Biological Evolution|Computational Biology|Computer Simulation|Metabolic Networks and Pathways|Models, Biological|Signal Transduction', 'Journal Article', '10.1371/journal.pcbi.1004055', '25798588', 'Bow-tie or hourglass structure is a common architectural feature found in many biological systems. A bow-tie in a multi-layered structure occurs when intermediate layers have much fewer components than the input and output layers. Examples include metabolism where a handful of building blocks mediate between multiple input nutrients and multiple output biomass components, and signaling networks where information from numerous receptor types passes through a small set of signaling pathways to regulate multiple output genes. Little is known, however, about how bow-tie architectures evolve. Here, we address the evolution of bow-tie architectures using simulations of multi-layered systems evolving to fulfill a given input-output goal. We find that bow-ties spontaneously evolve when the information in the evolutionary goal can be compressed. Mathematically speaking, bow-ties evolve when the rank of the input-output matrix describing the evolutionary goal is deficient. The maximal compression possible (the rank of the goal) determines the size of the narrowest part of the network-that is the bow-tie. A further requirement is that a process is active to reduce the number of links in the network, such as product-rule mutations, otherwise a non-bow-tie solution is found in the evolutionary simulations. This offers a mechanism to understand a common architectural principle of biological systems, and a way to quantitate the effective rank of the goals under which they evolved. '),
(87056, 2015, 'plos', 'A biologically plausible computational theory for value integration and action selection in decisions with competing alternatives', 'Christopoulos, Vassilios|Bonaiuto, James|Andersen, Richard A', 'Division of Biology and Biological Engineering, California Institute of Technology, Pasadena, California, United States of America.|Division of Biology and Biological Engineering, California Institute of Technology, Pasadena, California, United States of America, Sobell Department of Motor Neuroscience and Movement Disorders, University College London, London, United Kingdom.|Division of Biology and Biological Engineering, California Institute of Technology, Pasadena, California, United States of America.', 'United States|United Kingdom|United States', 26, 'Animals|Computational Biology|Decision Making|Eye Movements|Humans|Models, Neurological|Perception|Primates|Reward', 'Journal Article', '10.1371/journal.pcbi.1004104', '25803729', 'Decision making is a vital component of human and animal behavior that involves selecting between alternative options and generating actions to implement the choices. Although decisions can be as simple as choosing a goal and then pursuing it, humans and animals usually have to make decisions in dynamic environments where the value and the availability of an option change unpredictably with time and previous actions. A predator chasing multiple prey exemplifies how goals can dynamically change and compete during ongoing actions. Classical psychological theories posit that decision making takes place within frontal areas and is a separate process from perception and action. However, recent findings argue for additional mechanisms and suggest the decisions between actions often emerge through a continuous competition within the same brain regions that plan and guide action execution. According to these findings, the sensorimotor system generates concurrent action-plans for competing goals and uses online information to bias the competition until a single goal is pursued. This information is diverse, relating to both the dynamic value of the goal and the cost of acting, creating a challenging problem in integrating information across these diverse variables in real time. We introduce a computational framework for dynamically integrating value information from disparate sources in decision tasks with competing actions. We evaluated the framework in a series of oculomotor and reaching decision tasks and found that it captures many features of choice/motor behavior, as well as its neural underpinnings that previously have eluded a common explanation. '),
(87057, 2015, 'plos', 'Delayed response and biosonar perception explain movement coordination in trawling bats', 'Giuggioli, Luca|McKetterick, Thomas J|Holderied, Marc', 'Bristol Centre for Complexity Sciences, University of Bristol, Bristol, United Kingdom, School of Biological Sciences, University of Bristol, Bristol, United Kingdom, Department of Engineering Mathematics, University of Bristol, Bristol, United Kingdom.|Bristol Centre for Complexity Sciences, University of Bristol, Bristol, United Kingdom, School of Biological Sciences, University of Bristol, Bristol, United Kingdom.|Department of Engineering Mathematics, University of Bristol, Bristol, United Kingdom.', 'United Kingdom|United Kingdom|United Kingdom', 23, 'Animals|Appetitive Behavior|Chiroptera|Computational Biology|Echolocation|England|Models, Biological|Spatial Behavior', 'Journal Article', '10.1371/journal.pcbi.1004089', '25811627', 'Animal coordinated movement interactions are commonly explained by assuming unspecified social forces of attraction, repulsion and alignment with parameters drawn from observed movement data. Here we propose and test a biologically realistic and quantifiable biosonar movement interaction mechanism for echolocating bats based on spatial perceptual bias, i.e. actual sound field, a reaction delay, and observed motor constraints in speed and acceleration. We found that foraging pairs of bats flying over a water surface swapped leader-follower roles and performed chases or coordinated manoeuvres by copying the heading a nearby individual has had up to 500 ms earlier. Our proposed mechanism based on the interplay between sensory-motor constraints and delayed alignment was able to recreate the observed spatial actor-reactor patterns. Remarkably, when we varied model parameters (response delay, hearing threshold and echolocation directionality) beyond those observed in nature, the spatio-temporal interaction patterns created by the model only recreated the observed interactions, i.e. chases, and best matched the observed spatial patterns for just those response delays, hearing thresholds and echolocation directionalities found to be used by bats. This supports the validity of our sensory ecology approach of movement coordination, where interacting bats localise each other by active echolocation rather than eavesdropping. '),
(87058, 2015, 'plos', 'Variations in the binding pocket of an inhibitor of the bacterial division protein FtsZ across genotypes and species', 'Miguel, Amanda|Hsin, Jen|Liu, Tianyun|Tang, Grace|Altman, Russ B|Huang, Kerwyn Casey', 'Department of Bioengineering, Stanford University, Stanford, California, United States of America.|Department of Bioengineering, Stanford University, Stanford, California, United States of America.|Department of Bioengineering, Stanford University, Stanford, California, United States of America.|Department of Bioengineering, Stanford University, Stanford, California, United States of America.|Department of Bioengineering, Stanford University, Stanford, California, United States of America.|Department of Bioengineering, Stanford University, Stanford, California, United States of America, Department of Microbiology and Immunology, Stanford University School of Medicine, Stanford, California, United States of America.', 'United States|United States|United States|United States|United States|United States', 0, 'Bacterial Proteins|Binding Sites|Cytoskeletal Proteins|Drug Resistance, Bacterial|Molecular Dynamics Simulation|Pyridines|Staphylococcus aureus|Thiazoles', 'Journal Article', '10.1371/journal.pcbi.1004117', '25811761', 'The recent increase in antibiotic resistance in pathogenic bacteria calls for new approaches to drug-target selection and drug development. Targeting the mechanisms of action of proteins involved in bacterial cell division bypasses problems associated with increasingly ineffective variants of older antibiotics, to this end, the essential bacterial cytoskeletal protein FtsZ is a promising target. Recent work on its allosteric inhibitor, PC190723, revealed in vitro activity on Staphylococcus aureus FtsZ and in vivo antimicrobial activities. However, the mechanism of drug action and its effect on FtsZ in other bacterial species are unclear. Here, we examine the structural environment of the PC190723 binding pocket using PocketFEATURE, a statistical method that scores the similarity between pairs of small-molecule binding sites based on 3D structure information about the local microenvironment, and molecular dynamics (MD) simulations. We observed that species and nucleotide-binding state have significant impacts on the structural properties of the binding site, with substantially disparate microenvironments for bacterial species not from the Staphylococcus genus. Based on PocketFEATURE analysis of MD simulations of S. aureus FtsZ bound to GTP or with mutations that are known to confer PC190723 resistance, we predict that PC190723 strongly prefers to bind Staphylococcus FtsZ in the nucleotide-bound state. Furthermore, MD simulations of an FtsZ dimer indicated that polymerization may enhance PC190723 binding. Taken together, our results demonstrate that a drug-binding pocket can vary significantly across species, genetic perturbations, and in different polymerization states, yielding important information for the further development of FtsZ inhibitors. '),
(87059, 2015, 'plos', 'Speeding up ecological and evolutionary computations in R, essentials of high performance computing for biologists', 'Visser, Marco D|McMahon, Sean M|Merow, Cory|Dixon, Philip M|Record, Sydne|Jongejans, Eelke', 'Departments of Experimental Plant Ecology and Animal Ecology & Ecophysiology, Radboud University Nijmegen, Nijmegen, The Netherlands, Program for Applied Ecology, Centre for Tropical Forest Science, Smithsonian Tropical Research Institute, Balboa, Ancón, Panamá, Republic of Panamá|Smithsonian Environmental Research Center, Edgewater, Maryland, United States of America.|Smithsonian Environmental Research Center, Edgewater, Maryland, United States of America, Department of Ecology and Evolutionary Biology, University of Connecticut, Storrs, Connecticut, United States of America.|Department of Statistics, Iowa State University, Ames, Iowa, United States of America.|Harvard University, Harvard Forest, Petersham, Massachusetts, United States of America, Bryn Mawr College, Bryn Mawr, Pennsylvania, United States of America.|Departments of Experimental Plant Ecology and Animal Ecology & Ecophysiology, Radboud University Nijmegen, Nijmegen, The Netherlands.', 'Netherlands|United States|United States|United States|United States|Netherlands', 8, 'Cluster Analysis|Computational Biology|Computing Methodologies|Ecology|Genetics, Population|Humans', 'Journal Article', '10.1371/journal.pcbi.1004140', '25811842', 'Computation has become a critical component of research in biology. A risk has emerged that computational and programming challenges may limit research scope, depth, and quality. We review various solutions to common computational efficiency problems in ecological and evolutionary research. Our review pulls together material that is currently scattered across many sources and emphasizes those techniques that are especially effective for typical ecological and environmental problems. We demonstrate how straightforward it can be to write efficient code and implement techniques such as profiling or parallel computing. We supply a newly developed R package (aprof) that helps to identify computational bottlenecks in R code and determine whether optimization can be effective. Our review is complemented by a practical set of examples and detailed Supporting Information material (S1-S3 Texts) that demonstrate large improvements in computational speed (ranging from 10.5 times to 14,000 times faster). By improving computational efficiency, biologists can feasibly solve more complex tasks, ask more ambitious questions, and include more sophisticated analyses in their research. '),
(87060, 2015, 'plos', 'Theory of choice in bandit, information sampling and foraging tasks', 'Averbeck, Bruno B', 'Laboratory of Neuropsychology, National Institute of Mental Health, National Institutes of Health, Bethesda, Maryland, United States of America.', 'United States', 0, 'Choice Behavior|Decision Making|Humans|Models, Statistical|Task Performance and Analysis', 'Journal Article', '10.1371/journal.pcbi.1004164', '25815510', 'Decision making has been studied with a wide array of tasks. Here we examine the theoretical structure of bandit, information sampling and foraging tasks. These tasks move beyond tasks where the choice in the current trial does not affect future expected rewards. We have modeled these tasks using Markov decision processes (MDPs). MDPs provide a general framework for modeling tasks in which decisions affect the information on which future choices will be made. Under the assumption that agents are maximizing expected rewards, MDPs provide normative solutions. We find that all three classes of tasks pose choices among actions which trade-off immediate and future expected rewards. The tasks drive these trade-offs in unique ways, however. For bandit and information sampling tasks, increasing uncertainty or the time horizon shifts value to actions that pay-off in the future. Correspondingly, decreasing uncertainty increases the relative value of actions that pay-off immediately. For foraging tasks the time-horizon plays the dominant role, as choices do not affect future uncertainty in these tasks. '),
(87061, 2015, 'plos', 'Mapping shape to visuomotor mapping: learning and generalisation of sensorimotor behaviour based on contextual information', 'van Dam, Loes C J|Ernst, Marc O', 'Department of Cognitive Neuroscience, Universität Bielefeld, Bielefeld, Germany, Cognitive Interaction Technology (CITEC) Center of Excellence, Universität Bielefeld, Bielefeld, Germany.|Department of Cognitive Neuroscience, Universität Bielefeld, Bielefeld, Germany, Cognitive Interaction Technology (CITEC) Center of Excellence, Universität Bielefeld, Bielefeld, Germany, Bernstein Center for Computational Neuroscience, Tübingen, Germany.', 'Germany|Germany', 0, 'Algorithms|Bayes Theorem|Computational Biology|Feedback, Sensory|Humans|Models, Neurological|Psychomotor Performance', 'Journal Article', '10.1371/journal.pcbi.1004172', '25815787', 'Humans can learn and store multiple visuomotor mappings (dual-adaptation) when feedback for each is provided alternately. Moreover, learned context cues associated with each mapping can be used to switch between the stored mappings. However, little is known about the associative learning between cue and required visuomotor mapping, and how learning generalises to novel but similar conditions. To investigate these questions, participants performed a rapid target-pointing task while we manipulated the offset between visual feedback and movement end-points. The visual feedback was presented with horizontal offsets of different amounts, dependent on the targets shape. Participants thus needed to use different visuomotor mappings between target location and required motor response depending on the target shape in order to hit it. The target shapes were taken from a continuous set of shapes, morphed between spiky and circular shapes. After training we tested participants performance, without feedback, on different target shapes that had not been learned previously. We compared two hypotheses. First, we hypothesised that participants could (explicitly) extract the linear relationship between target shape and visuomotor mapping and generalise accordingly. Second, using previous findings of visuomotor learning, we developed a (implicit) Bayesian learning model that predicts generalisation that is more consistent with categorisation (i.e. use one mapping or the other). The experimental results show that, although learning the associations requires explicit awareness of the cues role, participants apply the mapping corresponding to the trained shape that is most similar to the current one, consistent with the Bayesian learning model. Furthermore, the Bayesian learning model predicts that learning should slow down with increased numbers of training pairs, which was confirmed by the present results. In short, we found a good correspondence between the Bayesian learning model and the empirical results indicating that this model poses a possible mechanism for simultaneously learning multiple visuomotor mappings. ');
INSERT INTO `papers` (`id`, `ano`, `journal`, `titulo`, `autores`, `afiliacao`, `pais`, `citacoes`, `palavra_chave`, `categorias`, `doi`, `pubmed`, `abstract`) VALUES
(87062, 2015, 'plos', '3-way networks: application of hypergraphs for modelling increased complexity in comparative genomics', 'Weighill, Deborah A|Jacobson, Daniel A', 'Institute for Wine Biotechnology, Stellenbosch University, Stellenbosch, South Africa, Comparative Genomics Group, Biosciences Division, Oak Ridge National Laboratory, Oak Ridge, Tennessee, United States of America, Bredesen Center for Interdisciplinary Research and Graduate Education, University of Tennessee, Knoxville, Tennessee, United States of America.|Institute for Wine Biotechnology, Stellenbosch University, Stellenbosch, South Africa, Comparative Genomics Group, Biosciences Division, Oak Ridge National Laboratory, Oak Ridge, Tennessee, United States of America.', 'United States|United States', 7, 'Bacteria|Genome, Bacterial|Genomics|Models, Genetic|Phylogeny', 'Journal Article', '10.1371/journal.pcbi.1004079', '25815802', 'We present and develop the theory of 3-way networks, a type of hypergraph in which each edge models relationships between triplets of objects as opposed to pairs of objects as done by standard network models. We explore approaches of how to prune these 3-way networks, illustrate their utility in comparative genomics and demonstrate how they find relationships which would be missed by standard 2-way network models using a phylogenomic dataset of 211 bacterial genomes. '),
(87063, 2015, 'plos', 'Explaining diversity in metagenomic datasets by phylogenetic-based feature weighting', 'Albanese, Davide|De Filippo, Carlotta|Cavalieri, Duccio|Donati, Claudio', 'Department of Computational Biology, Research and Innovation Centre, Fondazione Edmund Mach, San Michele allAdige, Italy.|Department of Food Quality and Nutrition, Research and Innovation Centre, Fondazione Edmund Mach, San Michele allAdige, Italy.|Department of Computational Biology, Research and Innovation Centre, Fondazione Edmund Mach, San Michele allAdige, Italy.|Department of Computational Biology, Research and Innovation Centre, Fondazione Edmund Mach, San Michele allAdige, Italy.', 'Italy|Italy|Italy|Italy', 0, 'Algorithms|Databases, Genetic|Gastrointestinal Microbiome|Genetic Variation|Humans|Metagenome|Metagenomics|Phylogeny', 'Journal Article', '10.1371/journal.pcbi.1004186', '25815895', 'Metagenomics is revolutionizing our understanding of microbial communities, showing that their structure and composition have profound effects on the ecosystem and in a variety of health and disease conditions. Despite the flourishing of new analysis methods, current approaches based on statistical comparisons between high-level taxonomic classes often fail to identify the microbial taxa that are differentially distributed between sets of samples, since in many cases the taxonomic schema do not allow an adequate description of the structure of the microbiota. This constitutes a severe limitation to the use of metagenomic data in therapeutic and diagnostic applications. To provide a more robust statistical framework, we introduce a class of feature-weighting algorithms that discriminate the taxa responsible for the classification of metagenomic samples. The method unambiguously groups the relevant taxa into clades without relying on pre-defined taxonomic categories, thus including in the analysis also those sequences for which a taxonomic classification is difficult. The phylogenetic clades are weighted and ranked according to their abundance measuring their contribution to the differentiation of the classes of samples, and a criterion is provided to define a reduced set of most relevant clades. Applying the method to public datasets, we show that the data-driven definition of relevant phylogenetic clades accomplished by our ranking strategy identifies features in the samples that are lost if phylogenetic relationships are not considered, improving our ability to mine metagenomic datasets. Comparison with supervised classification methods currently used in metagenomic data analysis highlights the advantages of using phylogenetic information. '),
(87064, 2015, 'plos', 'Evolving nutritional strategies in the presence of competition: a geometric agent-based model', 'Senior, Alistair M|Charleston, Michael A|Lihoreau, Mathieu|Buhl, Jerome|Raubenheimer, David|Simpson, Stephen J', 'Charles Perkins Centre, The University of Sydney, Sydney, New South Wales, Australia, School of Biological Sciences, The University of Sydney, Sydney, New South Wales, Australia.|School of Information Technologies, The University of Sydney, Sydney, New South Wales, Australia.|Centre National de la Recherche Scientifique (CNRS), Centre de Recherches sur la Cognition Animale, Toulouse, France, Université Paul Sabatier (UPS), Centre de Recherches sur la Cognition Animale, Toulouse, France.|Charles Perkins Centre, The University of Sydney, Sydney, New South Wales, Australia, School of Biological Sciences, The University of Sydney, Sydney, New South Wales, Australia, School of Agriculture, Food and Wine, The University of Adelaide, Adelaide South Australia, Australia.|Charles Perkins Centre, The University of Sydney, Sydney, New South Wales, Australia, School of Biological Sciences, The University of Sydney, Sydney, New South Wales, Australia, Faculty of Veterinary Science, The University of Sydney, Sydney, New South Wales, Australia.|Charles Perkins Centre, The University of Sydney, Sydney, New South Wales, Australia, School of Biological Sciences, The University of Sydney, Sydney, New South Wales, Australia.', 'Australia|Australia|France|Australia|Australia|Australia', 0, 'Animals|Competitive Behavior|Computational Biology|Feeding Behavior|Female|Insecta|Male|Models, Biological|Nutritional Physiological Phenomena', 'Journal Article', '10.1371/journal.pcbi.1004111', '25815976', 'Access to nutrients is a key factor governing development, reproduction and ultimately fitness. Within social groups, contest-competition can fundamentally affect nutrient access, potentially leading to reproductive asymmetry among individuals. Previously, agent-based models have been combined with the Geometric Framework of nutrition to provide insight into how nutrition and social interactions affect one another. Here, we expand this modelling approach by incorporating evolutionary algorithms to explore how contest-competition over nutrient acquisition might affect the evolution of animal nutritional strategies. Specifically, we model tolerance of nutrient excesses and deficits when ingesting nutritionally imbalanced foods, which we term nutritional latitude, a higher degree of nutritional latitude constitutes a higher tolerance of nutritional excess and deficit. Our results indicate that a transition between two alternative strategies occurs at moderate to high levels of competition. When competition is low, individuals display a low level of nutritional latitude and regularly switch foods in search of an optimum. When food is scarce and contest-competition is intense, high nutritional latitude appears optimal, and individuals continue to consume an imbalanced food for longer periods before attempting to switch to an alternative. However, the relative balance of nutrients within available foods also strongly influences at what levels of competition, if any, transitions between these two strategies occur. Our models imply that competition combined with reproductive skew in social groups can play a role in the evolution of diet breadth. We discuss how the integration of agent-based, nutritional and evolutionary modelling may be applied in future studies to further understand the evolution of nutritional strategies across social and ecological contexts. '),
(87065, 2015, 'plos', 'Behavioral modeling of human choices reveals dissociable effects of physical effort and temporal delay on reward devaluation', 'Klein-Flügge, Miriam C|Kennerley, Steven W|Saraiva, Ana C|Penny, Will D|Bestmann, Sven', 'Sobell Department of Motor Neuroscience and Movement Disorders, UCL Institute of Neurology, University College London (UCL), London, United Kingdom, Wellcome Trust Centre for Neuroimaging, University College London (UCL), London, United Kingdom, Department of Experimental Psychology, University of Oxford, Oxford, United Kingdom.|Sobell Department of Motor Neuroscience and Movement Disorders, UCL Institute of Neurology, University College London (UCL), London, United Kingdom.|Sobell Department of Motor Neuroscience and Movement Disorders, UCL Institute of Neurology, University College London (UCL), London, United Kingdom.|Wellcome Trust Centre for Neuroimaging, University College London (UCL), London, United Kingdom.|Sobell Department of Motor Neuroscience and Movement Disorders, UCL Institute of Neurology, University College London (UCL), London, United Kingdom.', 'United Kingdom|United Kingdom|United Kingdom|United Kingdom|United Kingdom', 0, 'Adult|Choice Behavior|Computational Biology|Female|Hand Strength|Humans|Male|Models, Biological|Reward|Task Performance and Analysis|Young Adult', 'Journal Article', '10.1371/journal.pcbi.1004116', '25816114', 'There has been considerable interest from the fields of biology, economics, psychology, and ecology about how decision costs decrease the value of rewarding outcomes. For example, formal descriptions of how reward value changes with increasing temporal delays allow for quantifying individual decision preferences, as in animal species populating different habitats, or normal and clinical human populations. Strikingly, it remains largely unclear how humans evaluate rewards when these are tied to energetic costs, despite the surge of interest in the neural basis of effort-guided decision-making and the prevalence of disorders showing a diminished willingness to exert effort (e.g., depression). One common assumption is that effort discounts reward in a similar way to delay. Here we challenge this assumption by formally comparing competing hypotheses about effort and delay discounting. We used a design specifically optimized to compare discounting behavior for both effort and delay over a wide range of decision costs (Experiment 1). We then additionally characterized the profile of effort discounting free of model assumptions (Experiment 2). Contrary to previous reports, in both experiments effort costs devalued reward in a manner opposite to delay, with small devaluations for lower efforts, and progressively larger devaluations for higher effort-levels (concave shape). Bayesian model comparison confirmed that delay-choices were best predicted by a hyperbolic model, with the largest reward devaluations occurring at shorter delays. In contrast, an altogether different relationship was observed for effort-choices, which were best described by a model of inverse sigmoidal shape that is initially concave. Our results provide a novel characterization of human effort discounting behavior and its first dissociation from delay discounting. This enables accurate modelling of cost-benefit decisions, a prerequisite for the investigation of the neural underpinnings of effort-guided choice and for understanding the deficits in clinical disorders characterized by behavioral inactivity. '),
(87066, 2015, 'plos', 'Kinetically-defined component actions in gene repression', 'Chow, Carson C|Finn, Kelsey K|Storchan, Geoffery B|Lu, Xinping|Sheng, Xiaoyan|Simons, S Stoney', 'Mathematical Biology Section, NIDDK/LBM, National Institutes of Health, Bethesda, Maryland, United States of America.|Steroid Hormones Section, NIDDK/LERB, National Institutes of Health, Bethesda, Maryland, United States of America.|Steroid Hormones Section, NIDDK/LERB, National Institutes of Health, Bethesda, Maryland, United States of America.|Steroid Hormones Section, NIDDK/LERB, National Institutes of Health, Bethesda, Maryland, United States of America.|Steroid Hormones Section, NIDDK/LERB, National Institutes of Health, Bethesda, Maryland, United States of America.|Steroid Hormones Section, NIDDK/LERB, National Institutes of Health, Bethesda, Maryland, United States of America.', 'United States|United States|United States|United States|United States|United States', 0, 'Computational Biology|Epigenetic Repression|Humans|Kinetics|Models, Genetic|Nitroso Compounds|Phenanthrolines|Pyrimidines|Receptors, Glucocorticoid|Reproducibility of Results|Transcription Factors', 'Journal Article', '10.1371/journal.pcbi.1004122', '25816223', 'Gene repression by transcription factors, and glucocorticoid receptors (GR) in particular, is a critical, but poorly understood, physiological response. Among the many unresolved questions is the difference between GR regulated induction and repression, and whether transcription cofactor action is the same in both. Because activity classifications based on changes in gene product level are mechanistically uninformative, we present a theory for gene repression in which the mechanisms of factor action are defined kinetically and are consistent for both gene repression and induction. The theory is generally applicable and amenable to predictions if the dose-response curve for gene repression is non-cooperative with a unit Hill coefficient, which is observed for GR-regulated repression of AP1LUC reporter induction by phorbol myristate acetate. The theory predicts the mechanism of GR and cofactors, and where they act with respect to each other, based on how each cofactor alters the plots of various kinetic parameters vs. cofactor. We show that the kinetically-defined mechanism of action of each of four factors (reporter gene, p160 coactivator TIF2, and two pharmaceuticals [NU6027 and phenanthroline]) is the same in GR-regulated repression and induction. What differs is the position of GR action. This insight should simplify clinical efforts to differentially modulate factor actions in gene induction vs. gene repression. '),
(87067, 2015, 'plos', 'An integrative approach for modeling and simulation of heterocyst pattern formation in cyanobacteria filaments', 'Torres-Sánchez, Alejandro|Gómez-Gardeñes, Jesús|Falo, Fernando', 'Departamento de Física de la Materia Condensada, Universidad de Zaragoza, Zaragoza, Spain, Laboratori de Càlcul Numèric, Universitat de Politècnica de Catalunya, Barcelona, Spain.|Departamento de Física de la Materia Condensada, Universidad de Zaragoza, Zaragoza, Spain, Instituto de Biocomputación y Física de Sistemas Complejos (BIFI), Universidad de Zaragoza, Zaragoza, Spain.|Departamento de Física de la Materia Condensada, Universidad de Zaragoza, Zaragoza, Spain, Instituto de Biocomputación y Física de Sistemas Complejos (BIFI), Universidad de Zaragoza, Zaragoza, Spain.', 'Spain|Spain|Spain', 8, 'Cell Differentiation|Computational Biology|Cyanobacteria|Models, Biological', 'Journal Article', '10.1371/journal.pcbi.1004129', '25816286', 'Heterocyst differentiation in cyanobacteria filaments is one of the simplest examples of cellular differentiation and pattern formation in multicellular organisms. Despite of the many experimental studies addressing the evolution and sustainment of heterocyst patterns and the knowledge of the genetic circuit underlying the behavior of single cyanobacterium under nitrogen deprivation, there is still a theoretical gap connecting these two macroscopic and microscopic processes. As an attempt to shed light on this issue, here we explore heterocyst differentiation under the paradigm of systems biology. This framework allows us to formulate the essential dynamical ingredients of the genetic circuit of a single cyanobacterium into a set of differential equations describing the time evolution of the concentrations of the relevant molecular products. As a result, we are able to study the behavior of a single cyanobacterium under different external conditions, emulating nitrogen deprivation, and simulate the dynamics of cyanobacteria filaments by coupling their respective genetic circuits via molecular diffusion. These two ingredients allow us to understand the principles by which heterocyst patterns can be generated and sustained. In particular, our results point out that, by including both diffusion and noisy external conditions in the computational model, it is possible to reproduce the main features of the formation and sustainment of heterocyst patterns in cyanobacteria filaments as observed experimentally. Finally, we discuss the validity and possible improvements of the model. '),
(87068, 2015, 'plos', 'Ligand-target prediction by structural network biology using nAnnoLyze', 'Martínez-Jiménez, Francisco|Marti-Renom, Marc A', 'Genome Biology Group, Centre Nacional dAanàlisi Genòmica (CNAG), Barcelona, Spain, Gene Regulation, Stem Cells and Cancer Program, Centre for Genomic Regulation (CRG), Barcelona, Spain.|Genome Biology Group, Centre Nacional dAanàlisi Genòmica (CNAG), Barcelona, Spain, Gene Regulation, Stem Cells and Cancer Program, Centre for Genomic Regulation (CRG), Barcelona, Spain, Institució Catalana de Recerca i Estudis Avançats (ICREA), Barcelona, Spain.', 'Spain|Spain', 14, 'Binding Sites|Computational Biology|Databases, Protein|Drug Discovery|Humans|Ligands|Protein Binding|Proteins|ROC Curve|Software', 'Journal Article', '10.1371/journal.pcbi.1004157', '25816344', 'Target identification is essential for drug design, drug-drug interaction prediction, dosage adjustment and side effect anticipation. Specifically, the knowledge of structural details is essential for understanding the mode of action of a compound on a target protein. Here, we present nAnnoLyze, a method for target identification that relies on the hypothesis that structurally similar binding sites bind similar ligands. nAnnoLyze integrates structural information into a bipartite network of interactions and similarities to predict structurally detailed compound-protein interactions at proteome scale. The method was benchmarked on a dataset of 6,282 pairs of known interacting ligand-target pairs reaching a 0.96 of area under the Receiver Operating Characteristic curve (AUC) when using the drug names as an input feature for the classifier, and a 0.70 of AUC for anonymous compounds or compounds not present in the training set. nAnnoLyze resulted in higher accuracies than its predecessor, AnnoLyze. We applied the method to predict interactions for all the compounds in the DrugBank database with each human protein structure and provide examples of target identification for known drugs against human diseases. The accuracy and applicability of our method to any compound indicate that a comparative docking approach such as nAnnoLyze enables large-scale annotation and analysis of compound-protein interactions and thus may benefit drug development. '),
(87069, 2015, 'plos', 'Hedging your bets: intermediate movements as optimal behavior in the context of an incomplete decision', 'Haith, Adrian M|Huberdeau, David M|Krakauer, John W', 'Department of Neurology, Johns Hopkins University, Baltimore, Maryland, United States of America.|Department of Biomedical Engineering, Johns Hopkins University, Baltimore, Maryland, United States of America.|Department of Neurology, Johns Hopkins University, Baltimore, Maryland, United States of America, Department of Neuroscience, Johns Hopkins University, Baltimore, Maryland, United States of America.', 'United States|United States|United States', 26, 'Adolescent|Adult|Decision Making|Female|Goals|Humans|Male|Movement|Reaction Time|Uncertainty|Young Adult', 'Journal Article', '10.1371/journal.pcbi.1004171', '25821964', 'Existing theories of movement planning suggest that it takes time to select and prepare the actions required to achieve a given goal. These theories often appeal to circumstances where planning apparently goes awry. For instance, if reaction times are forced to be very low, movement trajectories are often directed between two potential targets. These intermediate movements are generally interpreted as errors of movement planning, arising either from planning being incomplete or from parallel movement plans interfering with one another. Here we present an alternative view: that intermediate movements reflect uncertainty about movement goals. We show how intermediate movements are predicted by an optimal feedback control model that incorporates an ongoing decision about movement goals. According to this view, intermediate movements reflect an exploitation of compatibility between goals. Consequently, reducing the compatibility between goals should reduce the incidence of intermediate movements. In human subjects, we varied the compatibility between potential movement goals in two distinct ways: by varying the spatial separation between targets and by introducing a virtual barrier constraining trajectories to the target and penalizing intermediate movements. In both cases we found that decreasing goal compatibility led to a decreasing incidence of intermediate movements. Our results and theory suggest a more integrated view of decision-making and movement planning in which the primary bottleneck to generating a movement is deciding upon task goals. Determining how to move to achieve a given goal is rapid and automatic. '),
(87070, 2015, 'plos', 'Preferred supramolecular organization and dimer interfaces of opioid receptors from simulated self-association', 'Provasi, Davide|Boz, Mustafa Burak|Johnston, Jennifer M|Filizola, Marta', 'Department of Structural and Chemical Biology, Icahn School of Medicine at Mount Sinai, New York, New York, United States of America.|Department of Structural and Chemical Biology, Icahn School of Medicine at Mount Sinai, New York, New York, United States of America.|Department of Structural and Chemical Biology, Icahn School of Medicine at Mount Sinai, New York, New York, United States of America.|Department of Structural and Chemical Biology, Icahn School of Medicine at Mount Sinai, New York, New York, United States of America.', 'United States|United States|United States|United States', 48, 'Computational Biology|Humans|Lipids|Models, Molecular|Molecular Dynamics Simulation|Protein Multimerization|Protein Subunits|Receptors, Opioid', 'Journal Article', '10.1371/journal.pcbi.1004148', '25822938', 'Substantial evidence in support of the formation of opioid receptor (OR) di-/oligomers suggests previously unknown mechanisms used by these proteins to exert their biological functions. In an attempt to guide experimental assessment of the identity of the minimal signaling unit for ORs, we conducted extensive coarse-grained (CG) molecular dynamics (MD) simulations of different combinations of the three major OR subtypes, i.e., xcexbc-OR, xcexb4-OR, and xcexba-OR, in an explicit lipid bilayer. Specifically, we ran multiple, independent MD simulations of each homomeric xcexbc-OR/xcexbc-OR, xcexb4-OR/xcexb4-OR, and xcexba-OR/xcexba-OR complex, as well as two of the most studied heteromeric complexes, i.e., xcexb4-OR/xcexbc-OR and xcexb4-OR/xcexba-OR, to derive the preferred supramolecular organization and dimer interfaces of ORs in a cell membrane model. These simulations yielded over 250 microseconds of accumulated data, which correspond to approximately 1 millisecond of effective simulated dynamics according to established scaling factors of the CG model we employed. Analysis of these data indicates similar preferred supramolecular organization and dimer interfaces of ORs across the different receptor subtypes, but also important differences in the kinetics of receptor association at specific dimer interfaces. We also investigated the kinetic properties of interfacial lipids, and explored their possible role in modulating the rate of receptor association and in promoting the formation of filiform aggregates, thus supporting a distinctive role of the membrane in OR oligomerization and, possibly, signaling. '),
(87071, 2015, 'plos', 'Identifying and tracking simulated synaptic inputs from neuronal firing: insights from in vitro experiments', 'Volgushev, Maxim|Ilin, Vladimir|Stevenson, Ian H', 'Department of Psychology, University of Connecticut, Storrs, Connecticut, United States of America.|Department of Psychology, University of Connecticut, Storrs, Connecticut, United States of America.|Department of Psychology, University of Connecticut, Storrs, Connecticut, United States of America.', 'United States|United States|United States', 0, 'Action Potentials|Animals|Models, Neurological|Neurons|Rats|Rats, Wistar|Synapses|Visual Cortex', 'Journal Article', '10.1371/journal.pcbi.1004167', '25823000', 'Accurately describing synaptic interactions between neurons and how interactions change over time are key challenges for systems neuroscience. Although intracellular electrophysiology is a powerful tool for studying synaptic integration and plasticity, it is limited by the small number of neurons that can be recorded simultaneously in vitro and by the technical difficulty of intracellular recording in vivo. One way around these difficulties may be to use large-scale extracellular recording of spike trains and apply statistical methods to model and infer functional connections between neurons. These techniques have the potential to reveal large-scale connectivity structure based on the spike timing alone. However, the interpretation of functional connectivity is often approximate, since only a small fraction of presynaptic inputs are typically observed. Here we use in vitro current injection in layer 2/3 pyramidal neurons to validate methods for inferring functional connectivity in a setting where input to the neuron is controlled. In experiments with partially-defined input, we inject a single simulated input with known amplitude on a background of fluctuating noise. In a fully-defined input paradigm, we then control the synaptic weights and timing of many simulated presynaptic neurons. By analyzing the firing of neurons in response to these artificial inputs, we ask 1) How does functional connectivity inferred from spikes relate to simulated synaptic input? and 2) What are the limitations of connectivity inference? We find that individual current-based synaptic inputs are detectable over a broad range of amplitudes and conditions. Detectability depends on input amplitude and output firing rate, and excitatory inputs are detected more readily than inhibitory. Moreover, as we model increasing numbers of presynaptic inputs, we are able to estimate connection strengths more accurately and detect the presence of connections more quickly. These results illustrate the possibilities and outline the limits of inferring synaptic input from spikes. '),
(87072, 2015, 'plos', 'Improved estimation and interpretation of correlations in neural circuits', 'Yatsenko, Dimitri|Josixc4x87, Krexc5xa1imir|Ecker, Alexander S|Froudarakis, Emmanouil|Cotton, R James|Tolias, Andreas S', 'Department of Neuroscience, Baylor College of Medicine, Houston, Texas, United States of America.|Department of Mathematics and Department of Biology and Biochemistry, University of Houston, Houston, Texas, United States of America.|Department of Neuroscience, Baylor College of Medicine, Houston, Texas, United States of America, Werner Reichardt Center for Integrative Neuroscience and Institute for Theoretical Physics, University of Txc3xbcbingen, Germany, Bernstein Center for Computational Neuroscience, Txc3xbcbingen, Germany, Max Planck Institute for Biological Cybernetics, Txc3xbcbingen, Germany.|Department of Neuroscience, Baylor College of Medicine, Houston, Texas, United States of America.|Department of Neuroscience, Baylor College of Medicine, Houston, Texas, United States of America.|Department of Neuroscience, Baylor College of Medicine, Houston, Texas, United States of America, Department of Computational and Applied Mathematics, Rice University, Houston, Texas, United States of America.', 'United States|United States|Germany|United States|United States|United States', 0, 'Animals|Brain Mapping|Calcium|Calcium Signaling|Mice|Models, Neurological|Nerve Net|Neural Pathways|Neurons|Regression Analysis|Visual Cortex', 'Journal Article', '10.1371/journal.pcbi.1004083', '25826696', 'Ambitious projects aim to record the activity of ever larger and denser neuronal populations in vivo. Correlations in neural activity measured in such recordings can reveal important aspects of neural circuit organization. However, estimating and interpreting large correlation matrices is statistically challenging. Estimation can be improved by regularization, i.e. by imposing a structure on the estimate. The amount of improvement depends on how closely the assumed structure represents dependencies in the data. Therefore, the selection of the most efficient correlation matrix estimator for a given neural circuit must be determined empirically. Importantly, the identity and structure of the most efficient estimator informs about the types of dominant dependencies governing the system. We sought statistically efficient estimators of neural correlation matrices in recordings from large, dense groups of cortical neurons. Using fast 3D random-access laser scanning microscopy of calcium signals, we recorded the activity of nearly every neuron in volumes 200 xcexbcm wide and 100 xcexbcm deep (150-350 cells) in mouse visual cortex. We hypothesized that in these densely sampled recordings, the correlation matrix should be best modeled as the combination of a sparse graph of pairwise partial correlations representing local interactions and a low-rank component representing common fluctuations and external inputs. Indeed, in cross-validation tests, the covariance matrix estimator with this structure consistently outperformed other regularized estimators. The sparse component of the estimate defined a graph of interactions. These interactions reflected the physical distances and orientation tuning properties of cells: The density of positive excitatory interactions decreased rapidly with geometric distances and with differences in orientation preference whereas negative inhibitory interactions were less selective. Because of its superior performance, this sparse+latent estimator likely provides a more physiologically relevant representation of the functional connectivity in densely sampled recordings than the sample correlation matrix. '),
(87073, 2015, 'plos', 'The neuroglial potassium cycle during neurotransmission: role of Kir41 channels', 'Sibille, Jérémie|Dao Duc, Khanh|Holcman, David|Rouach, Nathalie', 'Neuroglial Interactions in Cerebral Physiopathology, Center for Interdisciplinary Research in Biology, Collège de France, INSERM U1050, CNRS UMR 7241, Labex Memolife, PSL Research University, Paris, France, Université Paris Diderot, Sorbonne Paris Cité, Paris, France.|IBENS, Ecole Normale Supérieure, INSERM U1024, CNRS UMR 8197, Paris, France, Université Paris 6, Paris, France.|IBENS, Ecole Normale Supérieure, INSERM U1024, CNRS UMR 8197, Paris, France.|Neuroglial Interactions in Cerebral Physiopathology, Center for Interdisciplinary Research in Biology, Collège de France, INSERM U1050, CNRS UMR 7241, Labex Memolife, PSL Research University, Paris, France.', 'France|France|France|France', 37, 'Action Potentials|Animals|Astrocytes|Mice|Mice, Inbred C57BL|Mice, Knockout|Models, Neurological|Neuroglia|Neurons|Potassium|Potassium Channels, Inwardly Rectifying|Synaptic Transmission', 'Journal Article', '10.1371/journal.pcbi.1004137', '25826753', 'Neuronal excitability relies on inward sodium and outward potassium fluxes during action potentials. To prevent neuronal hyperexcitability, potassium ions have to be taken up quickly. However, the dynamics of the activity-dependent potassium fluxes and the molecular pathways underlying extracellular potassium homeostasis remain elusive. To decipher the specific and acute contribution of astroglial Kir4.1 channels in controlling potassium homeostasis and the moment to moment neurotransmission, we built a tri-compartment model accounting for potassium dynamics between neurons, astrocytes and the extracellular space. We here demonstrate that astroglial Kir4.1 channels are sufficient to account for the slow membrane depolarization of hippocampal astrocytes and crucially contribute to extracellular potassium clearance during basal and high activity. By quantifying the dynamics of potassium levels in neuron-glia-extracellular space compartments, we show that astrocytes buffer within 6 to 9 seconds more than 80% of the potassium released by neurons in response to basal, repetitive and tetanic stimulations. Astroglial Kir4.1 channels directly lead to recovery of basal extracellular potassium levels and neuronal excitability, especially during repetitive stimulation, thereby preventing the generation of epileptiform activity. Remarkably, we also show that Kir4.1 channels strongly regulate neuronal excitability for slow 3 to 10 Hz rhythmic activity resulting from probabilistic firing activity induced by sub-firing stimulation coupled to Brownian noise. Altogether, these data suggest that astroglial Kir4.1 channels are crucially involved in extracellular potassium homeostasis regulating theta rhythmic activity. '),
(87074, 2015, 'plos', 'Large-scale chemical similarity networks for target profiling of compounds identified in cell-based chemical screens', 'Lo, Yu-Chen|Senese, Silvia|Li, Chien-Ming|Hu, Qiyang|Huang, Yong|Damoiseaux, Robert|Torres, Jorge Z', 'Department of Chemistry and Biochemistry, University of California, Los Angeles, Los Angeles, California, United States of America, Program in Bioengineering, University of California, Los Angeles, Los Angeles, California, United States of America.|Department of Chemistry and Biochemistry, University of California, Los Angeles, Los Angeles, California, United States of America.|Drug Studies Unit, Department of Bioengineering & Therapeutic Sciences, University of California, San Francisco, San Francisco, California, United States of America.|Institute for Digital Research and Education, University of California, Los Angeles, Los Angeles, California, United States of America.|Drug Studies Unit, Department of Bioengineering & Therapeutic Sciences, University of California, San Francisco, San Francisco, California, United States of America.|California NanoSystems Institute, University of California, Los Angeles, Los Angeles, California, United States of America.|Department of Chemistry and Biochemistry, University of California, Los Angeles, Los Angeles, California, United States of America, Jonsson Comprehensive Cancer Center, University of California, Los Angeles, Los Angeles, California, United States of America, Molecular Biology Institute, University of California, Los Angeles, Los Angeles, California, United States of America.', 'United States|United States|United States|United States|United States|United States|United States', 0, 'Algorithms|Binding Sites|Computational Biology|Databases, Factual|Drug Design|High-Throughput Screening Assays|Humans|Ligands', 'Journal Article', '10.1371/journal.pcbi.1004153', '25826798', 'Target identification is one of the most critical steps following cell-based phenotypic chemical screens aimed at identifying compounds with potential uses in cell biology and for developing novel disease therapies. Current in silico target identification methods, including chemical similarity database searches, are limited to single or sequential ligand analysis that have limited capabilities for accurate deconvolution of a large number of compounds with diverse chemical structures. Here, we present CSNAP (Chemical Similarity Network Analysis Pulldown), a new computational target identification method that utilizes chemical similarity networks for large-scale chemotype (consensus chemical pattern) recognition and drug target profiling. Our benchmark study showed that CSNAP can achieve an overall higher accuracy (>80%) of target prediction with respect to representative chemotypes in large (>200) compound sets, in comparison to the SEA approach (60-70%). Additionally, CSNAP is capable of integrating with biological knowledge-based databases (Uniprot, GO) and high-throughput biology platforms (proteomic, genetic, etc) for system-wise drug target validation. To demonstrate the utility of the CSNAP approach, we combined CSNAPs target prediction with experimental ligand evaluation to identify the major mitotic targets of hit compounds from a cell-based chemical screen and we highlight novel compounds targeting microtubules, an important cancer therapeutic target. The CSNAP method is freely available and can be accessed from the CSNAP web server (http://services.mbi.ucla.edu/CSNAP/). '),
(87075, 2015, 'plos', 'The equivalence of information-theoretic and likelihood-based methods for neural dimensionality reduction', 'Williamson, Ross S|Sahani, Maneesh|Pillow, Jonathan W', 'Gatsby Computational Neuroscience Unit, University College London, London, UK, Centre for Mathematics and Physics in the Life Sciences and Experimental Biology, University College London, London, UK.|Gatsby Computational Neuroscience Unit, University College London, London, UK.|Princeton Neuroscience Institute, Department of Psychology, Princeton University, Princeton, New Jersey, USA.', 'United Kingdom|United Kingdom|Jersey', 17, 'Action Potentials|Animals|Computer Simulation|Humans|Information Theory|Likelihood Functions|Models, Neurological|Models, Statistical|Neurons|Synaptic Transmission', 'Comparative Study', '10.1371/journal.pcbi.1004141', '25831448', 'Stimulus dimensionality-reduction methods in neuroscience seek to identify a low-dimensional space of stimulus features that affect a neurons probability of spiking. One popular method, known as maximally informative dimensions (MID), uses an information-theoretic quantity known as single-spike information to identify this space. Here we examine MID from a model-based perspective. We show that MID is a maximum-likelihood estimator for the parameters of a linear-nonlinear-Poisson (LNP) model, and that the empirical single-spike information corresponds to the normalized log-likelihood under a Poisson model. This equivalence implies that MID does not necessarily find maximally informative stimulus dimensions when spiking is not well described as Poisson. We provide several examples to illustrate this shortcoming, and derive a lower bound on the information lost when spiking is Bernoulli in discrete time bins. To overcome this limitation, we introduce model-based dimensionality reduction methods for neurons with non-Poisson firing statistics, and show that they can be framed equivalently in likelihood-based or information-theoretic terms. Finally, we show how to overcome practical limitations on the number of stimulus dimensions that MID can estimate by constraining the form of the non-parametric nonlinearity in an LNP model. We illustrate these methods with simulations and data from primate visual cortex. '),
(87076, 2015, 'plos', 'Ten simple rules to win a Nobel Prize', 'Roberts, Richard J', 'New England Biolabs, Ipswich, Massachusetts, United States of America.', 'United States', 0, 'Algorithms|Employment|Laboratories|Nobel Prize|Research|Science', 'Editorial', '10.1371/journal.pcbi.1004084', '25837678', '-'),
(87077, 2015, 'plos', 'Neural modularity helps organisms evolve to learn new skills without forgetting old skills', 'Ellefsen, Kai Olav|Mouret, Jean-Baptiste|Clune, Jeff', 'Department of Computer and Information Science, Norwegian University of Science and Technology, Trondheim, Norway.|Sorbonne Université UPMC Univ Paris 06, UMR 7222, ISIR, Paris, France, CNRS, UMR 7222, ISIR, Paris, France.|Computer Science Department, University of Wyoming, Laramie, Wyoming, United States of America.', 'Norway|France|United States', 0, 'Animals|Biomimetics|Computer Simulation|Humans|Inhibition (Psychology)|Learning|Mental Recall|Models, Neurological|Nerve Net|Neural Networks (Computer)|Retention (Psychology)|Task Performance and Analysis', 'Journal Article', '10.1371/journal.pcbi.1004128', '25837826', 'A long-standing goal in artificial intelligence is creating agents that can learn a variety of different skills for different problems. In the artificial intelligence subfield of neural networks, a barrier to that goal is that when agents learn a new skill they typically do so by losing previously acquired skills, a problem called catastrophic forgetting. That occurs because, to learn the new task, neural learning algorithms change connections that encode previously acquired skills. How networks are organized critically affects their learning dynamics. In this paper, we test whether catastrophic forgetting can be reduced by evolving modular neural networks. Modularity intuitively should reduce learning interference between tasks by separating functionality into physically distinct modules in which learning can be selectively turned on or off. Modularity can further improve learning by having a reinforcement learning module separate from sensory processing modules, allowing learning to happen only in response to a positive or negative reward. In this paper, learning takes place via neuromodulation, which allows agents to selectively change the rate of learning for each neural connection based on environmental stimuli (e.g. to alter learning in specific locations based on the task at hand). To produce modularity, we evolve neural networks with a cost for neural connections. We show that this connection cost technique causes modularity, confirming a previous result, and that such sparsely connected, modular networks have higher overall performance because they learn new skills faster while retaining old skills more and because they have a separate reinforcement learning module. Our results suggest (1) that encouraging modularity in neural networks may help us overcome the long-standing barrier of networks that cannot learn new skills without forgetting old ones, and (2) that one benefit of the modularity ubiquitous in the brains of natural animals might be to alleviate the problem of catastrophic forgetting.'),
(87078, 2015, 'plos', 'Hybrid spreading mechanisms and T cell activation shape the dynamics of HIV-1 infection', 'Zhang, Changwang|Zhou, Shi|Groppelli, Elisabetta|Pellegrino, Pierre|Williams, Ian|Borrow, Persephone|Chain, Benjamin M|Jolly, Clare', 'Department of Computer Science, University College London, London, United Kingdom, Security Science Doctoral Research Training Centre, University College London, London, United Kingdom, School of Computer Science, National University of Defense Technology, Changsha, China.|Department of Computer Science, University College London, London, United Kingdom.|Division of Infection and Immunity, University College London, London, United Kingdom.|Centre for Sexual Health & HIV Research, Mortimer Market Centre, London, United Kingdom.|Centre for Sexual Health & HIV Research, Mortimer Market Centre, London, United Kingdom.|Nuffield Department of Medicine, University of Oxford, Oxford, United Kingdom.|Division of Infection and Immunity, University College London, London, United Kingdom.|Division of Infection and Immunity, University College London, London, United Kingdom.', 'China|United Kingdom|United Kingdom|United Kingdom|United Kingdom|United Kingdom|United Kingdom|Unit', 25, 'CD4-Positive T-Lymphocytes|Computational Biology|Female|HIV Infections|HIV-1|Host-Pathogen Interactions|Humans|Male|Models, Immunological', 'Journal Article', '10.1371/journal.pcbi.1004179', '25837979', 'HIV-1 can disseminate between susceptible cells by two mechanisms: cell-free infection following fluid-phase diffusion of virions and by highly-efficient direct cell-to-cell transmission at immune cell contacts. The contribution of this hybrid spreading mechanism, which is also a characteristic of some important computer worm outbreaks, to HIV-1 progression in vivo remains unknown. Here we present a new mathematical model that explicitly incorporates the ability of HIV-1 to use hybrid spreading mechanisms and evaluate the consequences for HIV-1 pathogenenesis. The model captures the major phases of the HIV-1 infection course of a cohort of treatment naive patients and also accurately predicts the results of the Short Pulse Anti-Retroviral Therapy at Seroconversion (SPARTAC) trial. Using this model we find that hybrid spreading is critical to seed and establish infection, and that cell-to-cell spread and increased CD4+ T cell activation are important for HIV-1 progression. Notably, the model predicts that cell-to-cell spread becomes increasingly effective as infection progresses and thus may present a considerable treatment barrier. Deriving predictions of various treatments influence on HIV-1 progression highlights the importance of earlier intervention and suggests that treatments effectively targeting cell-to-cell HIV-1 spread can delay progression to AIDS. This study suggests that hybrid spreading is a fundamental feature of HIV infection, and provides the mathematical framework incorporating this feature with which to evaluate future therapeutic strategies. '),
(87079, 2015, 'plos', 'Survival kinetics of starving bacteria is biphasic and density-dependent', 'Phaiboun, Andy|Zhang, Yiming|Park, Boryung|Kim, Minsu', 'Department of Physics, Emory University, Atlanta, Georgia, United States of America.|Department of Physics, Emory University, Atlanta, Georgia, United States of America.|Department of Physics, Emory University, Atlanta, Georgia, United States of America.|Department of Physics, Emory University, Atlanta, Georgia, United States of America, Graduate Division of Biological and Biomedical Sciences, Emory University, Atlanta, Georgia, United States of America.', 'Georgia|Georgia|Georgia|Georgia', 0, 'Algorithms|Bacterial Physiological Phenomena|Bacterial Proteins|Computational Biology|Escherichia coli|Kinetics|Microbial Viability|Models, Biological|Sigma Factor', 'Journal Article', '10.1371/journal.pcbi.1004198', '25838110', 'In the lifecycle of microorganisms, prolonged starvation is prevalent and sustaining life during starvation periods is a vital task. In the literature, it is commonly assumed that survival kinetics of starving microbes follows exponential decay. This assumption, however, has not been rigorously tested. Currently, it is not clear under what circumstances this assumption is true. Also, it is not known when such survival kinetics deviates from exponential decay and if it deviates, what underlying mechanisms for the deviation are. Here, to address these issues, we quantitatively characterized dynamics of survival and death of starving E. coli cells. The results show that the assumption--starving cells die exponentially--is true only at high cell density. At low density, starving cells persevere for extended periods of time, before dying rapidly exponentially. Detailed analyses show intriguing quantitative characteristics of the density-dependent and biphasic survival kinetics, including that the period of the perseverance is inversely proportional to cell density. These characteristics further lead us to identification of key underlying processes relevant for the perseverance of starving cells. Then, using mathematical modeling, we show how these processes contribute to the density-dependent and biphasic survival kinetics observed. Importantly, our model reveals a thrifty strategy employed by bacteria, by which upon sensing impending depletion of a substrate, the limiting substrate is conserved and utilized later during starvation to delay cell death. These findings advance quantitative understanding of survival of microbes in oligotrophic environments and facilitate quantitative analysis and prediction of microbial dynamics in nature. Furthermore, they prompt revision of previous models used to analyze and predict population dynamics of microbes.');
INSERT INTO `papers` (`id`, `ano`, `journal`, `titulo`, `autores`, `afiliacao`, `pais`, `citacoes`, `palavra_chave`, `categorias`, `doi`, `pubmed`, `abstract`) VALUES
(87080, 2015, 'plos', 'Stepwise catalytic mechanism via short-lived intermediate inferred from combined QM/MM MERP and PES calculations on retaining glycosyltransferase ppGalNAcT2', 'Trnka, Tomxc3xa1xc5xa1|Kozmon, Stanislav|Tvaroxc5xa1ka, Igor|Koxc4x8da, Jaroslav', 'Central European Institute of Technology (CEITEC), Masaryk University, Brno, Czech Republic, Faculty of Science-National Centre for Biomolecular Research, Masaryk University, Brno, Czech Republic.|Central European Institute of Technology (CEITEC), Masaryk University, Brno, Czech Republic, Faculty of Science-National Centre for Biomolecular Research, Masaryk University, Brno, Czech Republic, On leave from the Institute of Chemistry, Slovak Academy of Sciences, Bratislava, Slovak Republic.|Central European Institute of Technology (CEITEC), Masaryk University, Brno, Czech Republic, Institute of Chemistry, Slovak Academy of Sciences, Bratislava, Slovak Republic.|Central European Institute of Technology (CEITEC), Masaryk University, Brno, Czech Republic, Faculty of Science-National Centre for Biomolecular Research, Masaryk University, Brno, Czech Republic.', '-|-|-|-', 11, 'Algorithms|Binding Sites|Catalysis|Computer Simulation|Glycosylation|Glycosyltransferases|Kinetics|Models, Chemical|Models, Molecular|Polysaccharides|Protein Binding|Protein Conformation', 'Journal Article', '10.1371/journal.pcbi.1004061', '25849117', 'The glycosylation of cell surface proteins plays a crucial role in a multitude of biological processes, such as cell adhesion and recognition. To understand the process of protein glycosylation, the reaction mechanisms of the participating enzymes need to be known. However, the reaction mechanism of retaining glycosyltransferases has not yet been sufficiently explained. Here we investigated the catalytic mechanism of human isoform 2 of the retaining glycosyltransferase polypeptide UDP-GalNAc transferase by coupling two different QM/MM-based approaches, namely a potential energy surface scan in two distance difference dimensions and a minimum energy reaction path optimisation using the Nudged Elastic Band method. Potential energy scan studies often suffer from inadequate sampling of reactive processes due to a predefined scan coordinate system. At the same time, path optimisation methods enable the sampling of a virtually unlimited number of dimensions, but their results cannot be unambiguously interpreted without knowledge of the potential energy surface. By combining these methods, we have been able to eliminate the most significant sources of potential errors inherent to each of these approaches. The structural model is based on the crystal structure of human isoform 2. In the QM/MM method, the QM region consists of 275 atoms, the remaining 5776 atoms were in the MM region. We found that ppGalNAcT2 catalyzes a same-face nucleophilic substitution with internal return (SNi). The optimized transition state for the reaction is 13.8 kcal/mol higher in energy than the reactant while the energy of the product complex is 6.7 kcal/mol lower. During the process of nucleophilic attack, a proton is synchronously transferred to the leaving phosphate. The presence of a short-lived metastable oxocarbenium intermediate is likely, as indicated by the reaction energy profiles obtained using high-level density functionals. '),
(87081, 2015, 'plos', 'Machine learning assisted design of highly active peptides for drug discovery', 'Giguère, Sébastien|Laviolette, François|Marchand, Mario|Tremblay, Denise|Moineau, Sylvain|Liang, Xinxia|Biron, Éric|Corbeil, Jacques', 'Department of Computer Science and Software Engineering, Université Laval, Québec, Canada.|Department of Computer Science and Software Engineering, Université Laval, Québec, Canada.|Department of Computer Science and Software Engineering, Université Laval, Québec, Canada.|Department of Biochemistry, Microbiology and Bioinformatics, Université Laval, Québec, Canada.|Department of Biochemistry, Microbiology and Bioinformatics, Université Laval, Québec, Canada.|Faculty of Pharmacy, Université Laval, Québec, Canada.|Faculty of Pharmacy, Université Laval, Québec, Canada.|Department of Molecular Medicine, Université Laval, Québec, Canada.', 'Canada|Canada|Canada|Canada|Canada|Canada|Canada|Canada', 23, 'Amino Acid Sequence|Antimicrobial Cationic Peptides|Bacterial Physiological Phenomena|Drug Discovery|Machine Learning|Molecular Sequence Data|Pattern Recognition, Automated|Peptides|Protein Interaction Mapping|Sequence Analysis, Protein|Structure-Activity Relationship', 'Journal Article', '10.1371/journal.pcbi.1004074', '25849257', 'The discovery of peptides possessing high biological activity is very challenging due to the enormous diversity for which only a minority have the desired properties. To lower cost and reduce the time to obtain promising peptides, machine learning approaches can greatly assist in the process and even partly replace expensive laboratory experiments by learning a predictor with existing data or with a smaller amount of data generation. Unfortunately, once the model is learned, selecting peptides having the greatest predicted bioactivity often requires a prohibitive amount of computational time. For this combinatorial problem, heuristics and stochastic optimization methods are not guaranteed to find adequate solutions. We focused on recent advances in kernel methods and machine learning to learn a predictive model with proven success. For this type of model, we propose an efficient algorithm based on graph theory, that is guaranteed to find the peptides for which the model predicts maximal bioactivity. We also present a second algorithm capable of sorting the peptides of maximal bioactivity. Extensive analyses demonstrate how these algorithms can be part of an iterative combinatorial chemistry procedure to speed up the discovery and the validation of peptide leads. Moreover, the proposed approach does not require the use of known ligands for the target protein since it can leverage recent multi-target machine learning predictors where ligands for similar targets can serve as initial training data. Finally, we validated the proposed approach in vitro with the discovery of new cationic antimicrobial peptides. Source code freely available at http://graal.ift.ulaval.ca/peptide-design/. '),
(87082, 2015, 'plos', 'Embodied choice: how action influences perceptual decision making', 'Lepora, Nathan F|Pezzulo, Giovanni', 'Department of Engineering Mathematics, University of Bristol, Bristol, United Kingdom, Bristol Robotics Laboratory (BRL), University of Bristol and University of the West of England, Bristol, United Kingdom.|Institute of Cognitive Sciences and Technologies, National Research Council, Rome, Italy.', 'United Kingdom|Italy', 64, 'Animals|Choice Behavior|Decision Making|Decision Support Techniques|Ecosystem|Mice|Models, Neurological|Motivation|Perception|Task Performance and Analysis', 'Journal Article', '10.1371/journal.pcbi.1004110', '25849349', 'Embodied Choice considers action performance as a proper part of the decision making process rather than merely as a means to report the decision. The central statement of embodied choice is the existence of bidirectional influences between action and decisions. This implies that for a decision expressed by an action, the action dynamics and its constraints (e.g. current trajectory and kinematics) influence the decision making process. Here we use a perceptual decision making task to compare three types of model: a serial decision-then-action model, a parallel decision-and-action model, and an embodied choice model where the action feeds back into the decision making. The embodied model incorporates two key mechanisms that together are lacking in the other models: action preparation and commitment. First, action preparation strategies alleviate delays in enacting a choice but also modify decision termination. Second, action dynamics change the prospects and create a commitment effect to the initially preferred choice. Our results show that these two mechanisms make embodied choice models better suited to combine decision and action appropriately to achieve suitably fast and accurate responses, as usually required in ecologically valid situations. Moreover, embodied choice models with these mechanisms give a better account of trajectory tracking experiments during decision making. In conclusion, the embodied choice framework offers a combined theory of decision and action that gives a clear case that embodied phenomena such as the dynamics of actions can have a causal influence on central cognition. '),
(87083, 2015, 'plos', 'Reconstructible phylogenetic networks: do not distinguish the indistinguishable', 'Pardi, Fabio|Scornavacca, Celine', 'Laboratoire dInformatique, de Robotique et de Microélectronique de Montpellier (LIRMM, UMR 5506) CNRS, Université de Montpellier, France, Institut de Biologie Computationnelle, Montpellier, France.|Institut des Sciences de lEvolution de Montpellier (ISE-M, UMR 5554) CNRS, IRD, Université de Montpellier, France, Institut de Biologie Computationnelle, Montpellier, France.', 'France|France', 28, 'Biological Evolution|Computer Simulation|Evolution, Molecular|Gene Expression Regulation|Gene Regulatory Networks|Models, Genetic|Phylogeny', 'Journal Article', '10.1371/journal.pcbi.1004135', '25849429', 'Phylogenetic networks represent the evolution of organisms that have undergone reticulate events, such as recombination, hybrid speciation or lateral gene transfer. An important way to interpret a phylogenetic network is in terms of the trees it displays, which represent all the possible histories of the characters carried by the organisms in the network. Interestingly, however, different networks may display exactly the same set of trees, an observation that poses a problem for network reconstruction: from the perspective of many inference methods such networks are indistinguishable. This is true for all methods that evaluate a phylogenetic network solely on the basis of how well the displayed trees fit the available data, including all methods based on input data consisting of clades, triples, quartets, or trees with any number of taxa, and also sequence-based approaches such as popular formalisations of maximum parsimony and maximum likelihood for networks. This identifiability problem is partially solved by accounting for branch lengths, although this merely reduces the frequency of the problem. Here we propose that network inference methods should only attempt to reconstruct what they can uniquely identify. To this end, we introduce a novel definition of what constitutes a uniquely reconstructible network. For any given set of indistinguishable networks, we define a canonical network that, under mild assumptions, is unique and thus representative of the entire set. Given data that underwent reticulate evolution, only the canonical form of the underlying phylogenetic network can be uniquely reconstructed. While on the methodological side this will imply a drastic reduction of the solution space in network inference, for the study of reticulate evolution this is a fundamental limitation that will require an important change of perspective when interpreting phylogenetic networks. '),
(87084, 2015, 'plos', 'Interplay between constraints, objectives, and optimality for genome-scale stoichiometric models', 'Maarleveld, Timo R|Wortel, Meike T|Olivier, Brett G|Teusink, Bas|Bruggeman, Frank J', 'Systems Bioinformatics, Amsterdam Institute for Molecules, Medicines and Systems, VU University, Amsterdam, The Netherlands, Life Sciences, Centrum Wiskunde & Informatica (CWI), Amsterdam, The Netherlands.|Systems Bioinformatics, Amsterdam Institute for Molecules, Medicines and Systems, VU University, Amsterdam, The Netherlands, Kluyver Centre for Genomics of Industrial Fermentation, Delft, The Netherlands.|Systems Bioinformatics, Amsterdam Institute for Molecules, Medicines and Systems, VU University, Amsterdam, The Netherlands.|Systems Bioinformatics, Amsterdam Institute for Molecules, Medicines and Systems, VU University, Amsterdam, The Netherlands, Kluyver Centre for Genomics of Industrial Fermentation, Delft, The Netherlands.|Systems Bioinformatics, Amsterdam Institute for Molecules, Medicines and Systems, VU University, Amsterdam, The Netherlands, Kluyver Centre for Genomics of Industrial Fermentation, Delft, The Netherlands.', 'Netherlands|Netherlands|Netherlands|Netherlands|Netherlands', 16, 'Escherichia coli|Genome, Bacterial|Genomics|Glucose|Models, Genetic|Systems Biology', 'Journal Article', '10.1371/journal.pcbi.1004166', '25849486', 'High-throughput data generation and genome-scale stoichiometric models have greatly facilitated the comprehensive study of metabolic networks. The computation of all feasible metabolic routes with these models, given stoichiometric, thermodynamic, and steady-state constraints, provides important insights into the metabolic capacities of a cell. How the feasible metabolic routes emerge from the interplay between flux constraints, optimality objectives, and the entire metabolic network of a cell is, however, only partially understood. We show how optimal metabolic routes, resulting from flux balance analysis computations, arise out of elementary flux modes, constraints, and optimization objectives. We illustrate our findings with a genome-scale stoichiometric model of Escherichia coli metabolism. In the case of one flux constraint, all feasible optimal flux routes can be derived from elementary flux modes alone. We found up to 120 million of such optimal elementary flux modes. We introduce a new computational method to compute the corner points of the optimal solution space fast and efficiently. Optimal flux routes no longer depend exclusively on elementary flux modes when we impose additional constraints, new optimal metabolic routes arise out of combinations of elementary flux modes. The solution space of feasible metabolic routes shrinks enormously when additional objectives---e.g. those related to pathway expression costs or pathway length---are introduced. In many cases, only a single metabolic route remains that is both feasible and optimal. This paper contributes to reaching a complete topological understanding of the metabolic capacity of organisms in terms of metabolic flux routes, one that is most natural to biochemists and biotechnologists studying and engineering metabolism. '),
(87085, 2015, 'plos', 'Metrics for assessing cytoskeletal orientational correlations and consistency', 'Drew, Nancy K|Eagleson, Mackenzie A|Baldo, Danny B|Parker, Kevin Kit|Grosberg, Anna', 'Department of Biomedical Engineering, University of California, Irvine, Irvine, California, United States of America.|Department of Biomedical Engineering, University of California, Irvine, Irvine, California, United States of America, School of Engineering and Applied Sciences, Harvard University, Cambridge, Massachusetts, United States of America.|Department of Biomedical Engineering, University of California, Irvine, Irvine, California, United States of America.|School of Engineering and Applied Sciences, Harvard University, Cambridge, Massachusetts, United States of America.|Department of Biomedical Engineering, University of California, Irvine, Irvine, California, United States of America, Department of Chemical Engineering, University of California, Irvine, Irvine, California, United States of America.', 'United States|United States|United States|United States|United States', 16, 'Actin Cytoskeleton|Animals|Computational Biology|Cytoskeleton|Image Processing, Computer-Assisted|Myocytes, Cardiac|Rats', 'Journal Article', '10.1371/journal.pcbi.1004190', '25849553', 'In biology, organization at multiple scales potentiates biological function. Current advances in staining and imaging of biological tissues provide a wealth of data, but there are few metrics to quantitatively describe these findings. In particular there is a need for a metric that would characterize the correlation and consistency of orientation of different biological constructs within a tissue. We aimed to create such a metric and to demonstrate its use with images of cardiac tissues. The co-orientational order parameter (COOP) was based on the mathematical framework of a classical parameter, the orientational order parameter (OOP). Theorems were proven to illustrate the properties and boundaries of the COOP, which was then applied to both synthetic and experimental data. We showed the COOP to be useful for quantifying the correlation of orientation of constructs such as actin filaments and sarcomeric Z-lines. As expected, cardiac tissues showed perfect correlation between actin filaments and Z-lines. We also demonstrated the use of COOP to quantify the consistency of construct orientation within cells of the same shape. The COOP provides a quantitative tool to characterize tissues beyond co-localization or single construct orientation distribution. In the future, this new parameter could be used to represent the quantitative changes during maturation of cardiac tissue, pathological malformation, and other processes. '),
(87086, 2015, 'plos', 'Cell fate reprogramming by control of intracellular network dynamics', 'Zañudo, Jorge G T|Albert, Réka', 'Department of Physics, The Pennsylvania State University, University Park, Pennsylvania, United States of America.|Department of Physics, The Pennsylvania State University, University Park, Pennsylvania, United States of America, Department of Biology, The Pennsylvania State University, University Park, Pennsylvania, United States of America.', 'United States|United States', 72, 'Algorithms|Cellular Reprogramming|Computational Biology|Humans|Leukemia|Models, Biological|Signal Transduction', 'Journal Article', '10.1371/journal.pcbi.1004193', '25849586', 'Identifying control strategies for biological networks is paramount for practical applications that involve reprogramming a cells fate, such as disease therapeutics and stem cell reprogramming. Here we develop a novel network control framework that integrates the structural and functional information available for intracellular networks to predict control targets. Formulated in a logical dynamic scheme, our approach drives any initial state to the target state with 100% effectiveness and needs to be applied only transiently for the network to reach and stay in the desired state. We illustrate our methods potential to find intervention targets for cancer treatment and cell differentiation by applying it to a leukemia signaling network and to the network controlling the differentiation of helper T cells. We find that the predicted control targets are effective in a broad dynamic framework. Moreover, several of the predicted interventions are supported by experiments. '),
(87087, 2015, 'plos', 'A Bayesian model of category-specific emotional brain responses', 'Wager, Tor D|Kang, Jian|Johnson, Timothy D|Nichols, Thomas E|Satpute, Ajay B|Barrett, Lisa Feldman', 'Department of Psychology and Neuroscience and the Institute for Cognitive Science, University of Colorado, Boulder, Colorado, United States of America.|Department of Biostatistics and Bioinformatics, Department of Radiology and Imaging Sciences, Emory University, Atlanta, Georgia, United States of America.|Department of Biostatistics, University of Michigan, Ann Arbor, Michigan, United States of America.|Department of Statistics and Warwick Manufacturing Group, University of Warwick, Coventry, United Kingdom, Functional Magnetic Resonance Imaging of the Brain (FMRIB) Centre, Nuffield Department of Clinical Neurosciences, University of Oxford, Oxford, United Kingdom.|Department of Psychology, Northeastern University, Boston, Massachusetts, United States of America.|Department of Psychology, Northeastern University, Boston, Massachusetts, United States of America, Massachusetts General Hospital/Harvard Medical School, Boston, Massachusetts, United States of America.', 'United States|Georgia|United States|United Kingdom|United States|United States', 93, 'Bayes Theorem|Brain|Computer Simulation|Emotions|Humans|Mental Recall|Models, Neurological|Models, Statistical|Nerve Net', 'Journal Article', '10.1371/journal.pcbi.1004066', '25853490', 'Understanding emotion is critical for a science of healthy and disordered brain function, but the neurophysiological basis of emotional experience is still poorly understood. We analyzed human brain activity patterns from 148 studies of emotion categories (2159 total participants) using a novel hierarchical Bayesian model. The model allowed us to classify which of five categories--fear, anger, disgust, sadness, or happiness--is engaged by a study with 66% accuracy (43-86% across categories). Analyses of the activity patterns encoded in the model revealed that each emotion category is associated with unique, prototypical patterns of activity across multiple brain systems including the cortex, thalamus, amygdala, and other structures. The results indicate that emotion categories are not contained within any one region or system, but are represented as configurations across multiple brain networks. The model provides a precise summary of the prototypical patterns for each emotion category, and demonstrates that a sufficient characterization of emotion categories relies on (a) differential patterns of involvement in neocortical systems that differ between humans and other species, and (b) distinctive patterns of cortical-subcortical interactions. Thus, these findings are incompatible with several contemporary theories of emotion, including those that emphasize emotion-dedicated brain systems and those that propose emotion is localized primarily in subcortical activity. They are consistent with componential and constructionist views, which propose that emotions are differentiated by a combination of perceptual, mnemonic, prospective, and motivational elements. Such brain-based models of emotion provide a foundation for new translational and clinical approaches.'),
(87088, 2015, 'plos', 'A DIseAse MOdule Detection (DIAMOnD) algorithm derived from a systematic analysis of connectivity patterns of disease proteins in the human interactome', 'Ghiassian, Susan Dina|Menche, Jörg|Barabási, Albert-László', 'Center for Complex Networks Research and Department of Physics, Northeastern University, Boston, Massachusetts, United States of America, Center for Cancer Systems Biology (CCSB) and Department of Cancer Biology, Dana-Farber Cancer Institute, Boston, Massachusetts, United States of America.|Center for Complex Networks Research and Department of Physics, Northeastern University, Boston, Massachusetts, United States of America, Center for Cancer Systems Biology (CCSB) and Department of Cancer Biology, Dana-Farber Cancer Institute, Boston, Massachusetts, United States of America, Center for Network Science, Central European University, Budapest, Hungary.|Center for Complex Networks Research and Department of Physics, Northeastern University, Boston, Massachusetts, United States of America, Center for Cancer Systems Biology (CCSB) and Department of Cancer Biology, Dana-Farber Cancer Institute, Boston, Massachusetts, United States of America, Center for Network Science, Central European University, Budapest, Hungary, Channing Division of Network Medicine, Department of Medicine, Brigham and Womens Hospital, Harvard Medical School, Boston, Massachusetts, United States of America.', 'United States|Hungary|Hungary', 125, 'Algorithms|Computer Simulation|Disease Susceptibility|Humans|Models, Statistical|Protein Interaction Mapping|Proteome|Signal Transduction', 'Journal Article', '10.1371/journal.pcbi.1004120', '25853560', 'The observation that disease associated proteins often interact with each other has fueled the development of network-based approaches to elucidate the molecular mechanisms of human disease. Such approaches build on the assumption that protein interaction networks can be viewed as maps in which diseases can be identified with localized perturbation within a certain neighborhood. The identification of these neighborhoods, or disease modules, is therefore a prerequisite of a detailed investigation of a particular pathophenotype. While numerous heuristic methods exist that successfully pinpoint disease associated modules, the basic underlying connectivity patterns remain largely unexplored. In this work we aim to fill this gap by analyzing the network properties of a comprehensive corpus of 70 complex diseases. We find that disease associated proteins do not reside within locally dense communities and instead identify connectivity significance as the most predictive quantity. This quantity inspires the design of a novel Disease Module Detection (DIAMOnD) algorithm to identify the full disease module around a set of known disease proteins. We study the performance of the algorithm using well-controlled synthetic data and systematically validate the identified neighborhoods for a large corpus of diseases. '),
(87089, 2015, 'plos', 'Quantification of diabetes comorbidity risks across life using nation-wide big claims data', 'Klimek, Peter|Kautzky-Willer, Alexandra|Chmiel, Anna|Schiller-Frühwirth, Irmgard|Thurner, Stefan', 'Section for Science of Complex Systems, Medical University of Vienna, Vienna, Austria.|Gender Medicine Unit, Medical University of Vienna, Vienna, Austria.|Section for Science of Complex Systems, Medical University of Vienna, Vienna, Austria.|Main Association of Austrian Social Security Institutions, Vienna, Austria.|Section for Science of Complex Systems, Medical University of Vienna, Vienna, Austria, Santa Fe Institute, Santa Fe, New Mexico, United States of America, IIASA, Laxenburg, Austria.', 'Austria|Austria|Austria|Austria|Austria', 26, 'Adolescent|Adult|Age Distribution|Aged|Aged, 80 and over|Austria|Causality|Child|Comorbidity|Data Interpretation, Statistical|Datasets as Topic|Diabetes Mellitus|Female|Heart Failure|Humans|Hyperlipidemias|Hypertension|Insurance Claim Review|Male|Middle Aged|National Health Programs|Parkinson Disease|Prevalence|Risk Factors|Sleep Wake Disorders|Young Adult', 'Journal Article', '10.1371/journal.pcbi.1004125', '25855969', 'Despite substantial progress in the study of diabetes, important questions remain about its comorbidities and clinical heterogeneity. To explore these issues, we develop a framework allowing for the first time to quantify nation-wide risks and their age- and sex-dependence for each diabetic comorbidity, and whether the association may be consequential or causal, in a sample of almost two million patients. This study is equivalent to nearly 40,000 single clinical measurements. We confirm the highly controversial relation of increased risk for Parkinsons disease in diabetics, using a 10 times larger cohort than previous studies on this relation. Detection of type 1 diabetes leads detection of depressions, whereas there is a strong comorbidity relation between type 2 diabetes and schizophrenia, suggesting similar pathogenic or medication-related mechanisms. We find significant sex differences in the progression of, for instance, sleep disorders and congestive heart failure in diabetic patients. Hypertension is a highly sex-sensitive comorbidity with females being at lower risk during fertile age, but at higher risk otherwise. These results may be useful to improve screening practices in the general population. Clinical management of diabetes must address age- and sex-dependence of multiple comorbid conditions. '),
(87090, 2015, 'plos', 'GOBLET: the Global Organisation for Bioinformatics Learning, Education and Training', 'Attwood, Teresa K|Atwood, Teresa K|Bongcam-Rudloff, Erik|Brazas, Michelle E|Corpas, Manuel|Gaudet, Pascale|Lewitter, Fran|Mulder, Nicola|Palagi, Patricia M|Schneider, Maria Victoria|van Gelder, Celia W G|GOBLET Consortium', 'Section for Science of Complex Systems, Medical University of Vienna, Vienna, Austria, Santa Fe Institute, Santa Fe, New Mexico, United States of America, IIASA, Laxenburg, Austria.|EMBnet, Nijmegen, The Netherlands.|SLU Global Bioinformatics Centre, Uppsala, Sweden.|Canadian Bioinformatics Workshops, Toronto, Canada.|ITICO, Cambridge, United Kingdom.|International Society for Biocuration, Geneva, Switzerland.|International Society for Computational Biology, San Diego, California, United States of America.|African Society for Bioinformatics & Computational Biology, Capetown, South Africa.|SIB Swiss Institute of Bioinformatics, Geneva, Switzerland.|The Genome Analysis Centre, Norwich, United Kingdom.|NBIC Netherlands Bioinformatics Centre, Nijmegen, The Netherlands.|NBIC Netherlands Bioinformatics Centre, Nijmegen, The Netherlands.', 'Austria|Netherlands|Sweden|Canada|United Kingdom|Switzerland|United States|South Africa|Switzerland|', 34, 'Computational Biology|Curriculum|Interinstitutional Relations|Internationality|Teaching', 'Journal Article', '10.1371/journal.pcbi.1004143', '25856076', 'In recent years, high-throughput technologies have brought big data to the life sciences. The march of progress has been rapid, leaving in its wake a demand for courses in data analysis, data stewardship, computing fundamentals, etc., a need that universities have not yet been able to satisfy--paradoxically, many are actually closing niche bioinformatics courses at a time of critical need. The impact of this is being felt across continents, as many students and early-stage researchers are being left without appropriate skills to manage, analyse, and interpret their data with confidence. This situation has galvanised a group of scientists to address the problems on an international scale. For the first time, bioinformatics educators and trainers across the globe have come together to address common needs, rising above institutional and international boundaries to cooperate in sharing bioinformatics training expertise, experience, and resources, aiming to put ad hoc training practices on a more professional footing for the benefit of all.'),
(87091, 2015, 'plos', 'What is the most realistic single-compartment model of spike initiation?', 'Brette, Romain', 'Institut dEtudes de la Cognition, Ecole Normale Supérieure, Paris, France, Sorbonne Universités, UPMC Univ. Paris 06, UMR_S 968, Institut de la Vision, Paris, France, INSERM, U968, Paris, France, CNRS, UMR_7210, Paris, France.', 'France', 29, 'Action Potentials|Animals|Computer Simulation|Differential Threshold|Humans|Ion Channel Gating|Ion Channels|Membrane Potentials|Models, Neurological|Models, Statistical|Synaptic Transmission', 'Comparative Study', '10.1371/journal.pcbi.1004114', '25856629', 'A large variety of neuron models are used in theoretical and computational neuroscience, and among these, single-compartment models are a popular kind. These models do not explicitly include the dendrites or the axon, and range from the Hodgkin-Huxley (HH) model to various flavors of integrate-and-fire (IF) models. The main classes of models differ in the way spikes are initiated. Which one is the most realistic? Starting with some general epistemological considerations, I show that the notion of realism comes in two dimensions: empirical content (the sort of predictions that a model can produce) and empirical accuracy (whether these predictions are correct). I then examine the realism of the main classes of single-compartment models along these two dimensions, in light of recent experimental evidence. '),
(87092, 2015, 'plos', 'Global mapping of DNA conformational flexibility on Saccharomyces cerevisiae', 'Menconi, Giulia|Bedini, Andrea|Barale, Roberto|Sbrana, Isabella', 'Dip. Informatica, Università di Pisa, Largo Pontecorvo, Pisa, Italy, Istituto Nazionale di Alta Matematica Francesco Severi, Piazzale Aldo Moro, Città Universitaria, Roma, Italy.|Dept. Mathematics and Statistics, The University of Melbourne Victoria, Australia.|Dip. Biologia, Università di Pisa, Via Derna, Pisa, Italy.|Dip. Biologia, Università di Pisa, Via Derna, Pisa, Italy.', 'France|Australia|Italy|Italy', 2, 'Base Sequence|Chromosome Mapping|Computer Simulation|DNA, Fungal|Genome, Fungal|Models, Genetic|Models, Molecular|Molecular Sequence Data|Nucleic Acid Conformation|Saccharomyces cerevisiae|Sequence Analysis, DNA', 'Journal Article', '10.1371/journal.pcbi.1004136', '25860149', 'In this study we provide the first comprehensive map of DNA conformational flexibility in Saccharomyces cerevisiae complete genome. Flexibility plays a key role in DNA supercoiling and DNA/protein binding, regulating DNA transcription, replication or repair. Specific interest in flexibility analysis concerns its relationship with human genome instability. Enrichment in flexible sequences has been detected in unstable regions of human genome defined fragile sites, where genes map and carry frequent deletions and rearrangements in cancer. Flexible sequences have been suggested to be the determinants of fragile gene proneness to breakage, however, their actual role and properties remain elusive. Our in silico analysis carried out genome-wide via the StabFlex algorithm, shows the conserved presence of highly flexible regions in budding yeast genome as well as in genomes of other Saccharomyces sensu stricto species. Flexibile peaks in S. cerevisiae identify 175 ORFs mapping on their 3UTR, a region affecting mRNA translation, localization and stability. (TA)n repeats of different extension shape the central structure of peaks and co-localize with polyadenylation efficiency element (EE) signals. ORFs with flexible peaks share common features. Transcripts are characterized by decreased half-life: this is considered peculiar of genes involved in regulatory systems with high turnover, consistently, their function affects biological processes such as cell cycle regulation or stress response. Our findings support the functional importance of flexibility peaks, suggesting that the flexible sequence may be derived by an expansion of canonical TAYRTA polyadenylation efficiency element. The flexible (TA)n repeat amplification could be the outcome of an evolutionary neofunctionalization leading to a differential 3-end processing and expression regulation in genes with peculiar function. Our study provides a new support to the functional role of flexibility in genomes and a strategy for its characterization inside human fragile sites. '),
(87093, 2015, 'plos', 'Characterizing the transmission potential of zoonotic infections from minor outbreaks', 'Kucharski, Adam J|Edmunds, W John', 'Centre for the Mathematical Modelling of Infectious Diseases, London School of Hygiene & Tropical Medicine, London, United Kingdom, Fogarty International Center, National Institutes of Health, Bethesda, Maryland, United States.|Centre for the Mathematical Modelling of Infectious Diseases, London School of Hygiene & Tropical Medicine, London, United Kingdom.', 'United Kingdom|United Kingdom', 11, 'Age Distribution|Animals|Communicable Diseases, Emerging|Computer Simulation|Disease Outbreaks|Disease Susceptibility|Humans|Incidence|Models, Statistical|Risk Assessment|Zoonoses', 'Journal Article', '10.1371/journal.pcbi.1004154', '25860289', 'The transmission potential of a novel infection depends on both the inherent transmissibility of a pathogen, and the level of susceptibility in the host population. However, distinguishing between these pathogen- and population-specific properties typically requires detailed serological studies, which are rarely available in the early stages of an outbreak. Using a simple transmission model that incorporates age-stratified social mixing patterns, we present a novel method for characterizing the transmission potential of subcritical infections, which have effective reproduction number R<1, from readily available data on the size of outbreaks. We show that the model can identify the extent to which outbreaks are driven by inherent pathogen transmissibility and pre-existing population immunity, and can generate unbiased estimates of the effective reproduction number. Applying the method to real-life infections, we obtained accurate estimates for the degree of age-specific immunity against monkeypox, influenza A(H5N1) and A(H7N9), and refined existing estimates of the reproduction number. Our results also suggest minimal pre-existing immunity to MERS-CoV in humans. The approach we describe can therefore provide crucial information about novel infections before serological surveys and other detailed analyses are available. The methods would also be applicable to data stratified by factors such as profession or location, which would make it possible to measure the transmission potential of emerging infections in a wide range of settings. '),
(87094, 2015, 'plos', 'Machine learning methods enable predictive modeling of antibody feature:function relationships in RV144 vaccinees', 'Choi, Ickwon|Chung, Amy W|Suscovich, Todd J|Rerks-Ngarm, Supachai|Pitisuttithum, Punnee|Nitayaphan, Sorachai|Kaewkungwal, Jaranit|OConnell, Robert J|Francis, Donald|Robb, Merlin L|Michael, Nelson L|Kim, Jerome H|Alter, Galit|Ackerman, Margaret E|Bailey-Kellogg, Chris', 'Department of Computer Science, Dartmouth College, Hanover, New Hampshire, United States of America.|Ragon Institute of Massachusetts General Hospital, Massachusetts Institute of Technology, and Harvard, Boston, Massachusetts, United States of America.|Ragon Institute of Massachusetts General Hospital, Massachusetts Institute of Technology, and Harvard, Boston, Massachusetts, United States of America.|Department of Disease Control, Ministry of Public Health, Nonthaburi, Thailand.|Faculty of Tropical Medicine, Mahidol University, Bangkok, Thailand.|Armed Forces Research Institute of Medical Sciences, Bangkok, Thailand.|Faculty of Tropical Medicine, Mahidol University, Bangkok, Thailand.|Department of Retrovirology, U.S. Army Medical Component, AFRIMS, Bangkok, Thailand.|Global Solutions for Infectious Diseases (GSID), South San Francisco, California, United States of America.|US Military HIV Research Program, Walter Reed Army Institute of Research, Silver Spring, Maryland, United States of America, Henry Jackson Foundation HIV Program, US Military HIV Research Program, Bethesda, Maryland, United States of America.|US Military HIV Research Program, Walter Reed Army Institute of Research, Silver Spring, Maryland, United States of America.|US Military HIV Research Program, Walter Reed Army Institute of Research, Silver Spring, Maryland, United States of America.|Ragon Institute of Massachusetts General Hospital, Massachusetts Institute of Technology, and Harvard, Boston, Massachusetts, United States of America.|Thayer School of Engineering, Dartmouth College, Hanover, New Hampshire, United States of America.|Department of Computer Science, Dartmouth College, Hanover, New Hampshire, United States of America.', 'United States|United States|United States|Thailand|Thailand|Thailand|Thailand|Thailand|United States', 29, 'AIDS Vaccines|Antibody-Dependent Cell Cytotoxicity|Computational Biology|Cytokines|HIV Antibodies|HIV Antigens|HIV Infections|HIV-1|Humans|Machine Learning|Models, Immunological', 'Journal Article', '10.1371/journal.pcbi.1004185', '25874406', 'The adaptive immune response to vaccination or infection can lead to the production of specific antibodies to neutralize the pathogen or recruit innate immune effector cells for help. The non-neutralizing role of antibodies in stimulating effector cell responses may have been a key mechanism of the protection observed in the RV144 HIV vaccine trial. In an extensive investigation of a rich set of data collected from RV144 vaccine recipients, we here employ machine learning methods to identify and model associations between antibody features (IgG subclass and antigen specificity) and effector function activities (antibody dependent cellular phagocytosis, cellular cytotoxicity, and cytokine release). We demonstrate via cross-validation that classification and regression approaches can effectively use the antibody features to robustly predict qualitative and quantitative functional outcomes. This integration of antibody feature and function data within a machine learning framework provides a new, objective approach to discovering and assessing multivariate immune correlates. '),
(87095, 2015, 'plos', 'A general framework for thermodynamically consistent parameterization and efficient sampling of enzymatic reactions', 'Saa, Pedro|Nielsen, Lars K', 'Australian Institute for Bioengineering and Nanotechnology, The University of Queensland, Brisbane, Queensland, Australia.|Australian Institute for Bioengineering and Nanotechnology, The University of Queensland, Brisbane, Queensland, Australia.', 'Australia|Australia', 16, 'Algorithms|Animals|Bacterial Proteins|Computational Biology|Enzymes|Escherichia coli|Mammals|Models, Biological|Thermodynamics', 'Journal Article', '10.1371/journal.pcbi.1004195', '25874556', 'Kinetic models provide the means to understand and predict the dynamic behaviour of enzymes upon different perturbations. Despite their obvious advantages, classical parameterizations require large amounts of data to fit their parameters. Particularly, enzymes displaying complex reaction and regulatory (allosteric) mechanisms require a great number of parameters and are therefore often represented by approximate formulae, thereby facilitating the fitting but ignoring many real kinetic behaviours. Here, we show that full exploration of the plausible kinetic space for any enzyme can be achieved using sampling strategies provided a thermodynamically feasible parameterization is used. To this end, we developed a General Reaction Assembly and Sampling Platform (GRASP) capable of consistently parameterizing and sampling accurate kinetic models using minimal reference data. The former integrates the generalized MWC model and the elementary reaction formalism. By formulating the appropriate thermodynamic constraints, our framework enables parameterization of any oligomeric enzyme kinetics without sacrificing complexity or using simplifying assumptions. This thermodynamically safe parameterization relies on the definition of a reference state upon which feasible parameter sets can be efficiently sampled. Uniform sampling of the kinetics space enabled dissecting enzyme catalysis and revealing the impact of thermodynamics on reaction kinetics. Our analysis distinguished three reaction elasticity regions for common biochemical reactions: a steep linear region (0> xcex94Gr >-2 kJ/mol), a transition region (-2> xcex94Gr >-20 kJ/mol) and a constant elasticity region (xcex94Gr <-20 kJ/mol). We also applied this framework to model more complex kinetic behaviours such as the monomeric cooperativity of the mammalian glucokinase and the ultrasensitive response of the phosphoenolpyruvate carboxylase of Escherichia coli. In both cases, our approach described appropriately not only the kinetic behaviour of these enzymes, but it also provided insights about the particular features underpinning the observed kinetics. Overall, this framework will enable systematic parameterization and sampling of enzymatic reactions. '),
(87096, 2015, 'plos', 'Optimising and communicating options for the control of invasive plant disease when there is epidemiological uncertainty', 'Cunniffe, Nik J|Stutt, Richard O J H|DeSimone, R Erik|Gottwald, Tim R|Gilligan, Christopher A', 'Department of Plant Sciences, University of Cambridge, Cambridge, United Kingdom.|Department of Plant Sciences, University of Cambridge, Cambridge, United Kingdom.|Department of Plant Sciences, University of Cambridge, Cambridge, United Kingdom.|United States Department of Agriculture, Agricultural Research Service, Fort Pierce, Florida, United States of America.|Department of Plant Sciences, University of Cambridge, Cambridge, United Kingdom.', 'United Kingdom|United Kingdom|United Kingdom|United States|United Kingdom', 30, 'Citrus|Computational Biology|Florida|Models, Biological|Models, Statistical|Plant Diseases|Xanthomonas', 'Journal Article', '10.1371/journal.pcbi.1004211', '25874622', 'Although local eradication is routinely attempted following introduction of disease into a new region, failure is commonplace. Epidemiological principles governing the design of successful control are not well-understood. We analyse factors underlying the effectiveness of reactive eradication of localised outbreaks of invading plant disease, using citrus canker in Florida as a case study, although our results are largely generic, and apply to other plant pathogens (as we show via our second case study, citrus greening). We demonstrate how to optimise control via removal of hosts surrounding detected infection (i.e. localised culling) using a spatially-explicit, stochastic epidemiological model. We show how to define optimal culling strategies that take account of stochasticity in disease spread, and how the effectiveness of disease control depends on epidemiological parameters determining pathogen infectivity, symptom emergence and spread, the initial level of infection, and the logistics and implementation of detection and control. We also consider how optimal culling strategies are conditioned on the levels of risk acceptance/aversion of decision makers, and show how to extend the analyses to account for potential larger-scale impacts of a small-scale outbreak. Control of local outbreaks by culling can be very effective, particularly when started quickly, but the optimum strategy and its performance are strongly dependent on epidemiological parameters (particularly those controlling dispersal and the extent of any cryptic infection, i.e. infectious hosts prior to symptoms), the logistics of detection and control, and the level of local and global risk that is deemed to be acceptable. A version of the model we developed to illustrate our methodology and results to an audience of stakeholders, including policy makers, regulators and growers, is available online as an interactive, user-friendly interface at http://www.webidemics.com/. This version of our model allows the complex epidemiological principles that underlie our results to be communicated to a non-specialist audience. '),
(87097, 2015, 'plos', 'General relationship of global topology, local dynamics, and directionality in large-scale brain networks', 'Moon, Joon-Young|Lee, UnCheol|Blain-Moraes, Stefanie|Mashour, George A', 'Department of Anesthesiology, University of Michigan Medical School, Ann Arbor, Michigan, United States of America.|Department of Anesthesiology and Center for Consciousness Science, University of Michigan Medical School, Ann Arbor, Michigan, United States of America.|Department of Anesthesiology, University of Michigan Medical School, Ann Arbor, Michigan, United States of America.|Department of Anesthesiology, Center for Consciousness Science and Neuroscience Graduate Program, University of Michigan Medical School, Ann Arbor, Michigan, United States of America.', 'United States|United States|United States|United States', 65, 'Adult|Brain|Computational Biology|Computer Simulation|Connectome|Female|Humans|Male|Models, Neurological|Nerve Net|Young Adult', 'Journal Article', '10.1371/journal.pcbi.1004225', '25874700', 'The balance of global integration and functional specialization is a critical feature of efficient brain networks, but the relationship of global topology, local node dynamics and information flow across networks has yet to be identified. One critical step in elucidating this relationship is the identification of governing principles underlying the directionality of interactions between nodes. Here, we demonstrate such principles through analytical solutions based on the phase lead/lag relationships of general oscillator models in networks. We confirm analytical results with computational simulations using general model networks and anatomical brain networks, as well as high-density electroencephalography collected from humans in the conscious and anesthetized states. Analytical, computational, and empirical results demonstrate that network nodes with more connections (i.e., higher degrees) have larger amplitudes and are directional targets (phase lag) rather than sources (phase lead). The relationship of node degree and directionality therefore appears to be a fundamental property of networks, with direct applicability to brain function. These results provide a foundation for a principled understanding of information transfer across networks and also demonstrate that changes in directionality patterns across states of human consciousness are driven by alterations of brain network topology. '),
(87098, 2015, 'plos', 'Correction: Data-driven prediction and design of bZIP coiled-coil interactions', 'PLOS Computational Biology Staff', 'Department of Anesthesiology, Center for Consciousness Science and Neuroscience Graduate Program, University of Michigan Medical School, Ann Arbor, Michigan, United States of America.', 'United States', 0, '-', 'Published Erratum', '10.1371/journal.pcbi.1004243', '25874775', '-');
INSERT INTO `papers` (`id`, `ano`, `journal`, `titulo`, `autores`, `afiliacao`, `pais`, `citacoes`, `palavra_chave`, `categorias`, `doi`, `pubmed`, `abstract`) VALUES
(87099, 2015, 'plos', 'Discovering anti-platelet drug combinations with an integrated model of activator-inhibitor relationships, activator-activator synergies and inhibitor-inhibitor synergies', 'Lombardi, Federica|Golla, Kalyan|Fitzpatrick, Darren J|Casey, Fergal P|Moran, Niamh|Shields, Denis C', 'Complex and Adaptive Systems Laboratory, University College Dublin, Dublin, Ireland, Molecular and Cellular Therapeutics, Royal College of Surgeons in Ireland, Dublin, Ireland, Conway Institute of Biomolecular and Biomedical Research, University College Dublin, Dublin, Ireland, School of Medicine and Medical Sciences, University College Dublin, Dublin, Ireland.|Molecular and Cellular Therapeutics, Royal College of Surgeons in Ireland, Dublin, Ireland.|Complex and Adaptive Systems Laboratory, University College Dublin, Dublin, Ireland, Conway Institute of Biomolecular and Biomedical Research, University College Dublin, Dublin, Ireland, School of Medicine and Medical Sciences, University College Dublin, Dublin, Ireland.|Complex and Adaptive Systems Laboratory, University College Dublin, Dublin, Ireland, Conway Institute of Biomolecular and Biomedical Research, University College Dublin, Dublin, Ireland, School of Medicine and Medical Sciences, University College Dublin, Dublin, Ireland.|Molecular and Cellular Therapeutics, Royal College of Surgeons in Ireland, Dublin, Ireland.|Complex and Adaptive Systems Laboratory, University College Dublin, Dublin, Ireland, Conway Institute of Biomolecular and Biomedical Research, University College Dublin, Dublin, Ireland, School of Medicine and Medical Sciences, University College Dublin, Dublin, Ireland.', 'Ireland|Ireland|Ireland|Ireland|Ireland|Ireland', 3, 'Blood Platelets|Cells, Cultured|Computer Simulation|Drug Antagonism|Drug Discovery|Drug Synergism|Drug Therapy, Combination|Humans|Models, Statistical|Platelet Activation|Platelet Aggregation Inhibitors', 'Journal Article', '10.1371/journal.pcbi.1004119', '25875950', 'Identifying effective therapeutic drug combinations that modulate complex signaling pathways in platelets is central to the advancement of effective anti-thrombotic therapies. However, there is no systems model of the platelet that predicts responses to different inhibitor combinations. We developed an approach which goes beyond current inhibitor-inhibitor combination screening to efficiently consider other signaling aspects that may give insights into the behaviour of the platelet as a system. We investigated combinations of platelet inhibitors and activators. We evaluated three distinct strands of information, namely: activator-inhibitor combination screens (testing a panel of inhibitors against a panel of activators), inhibitor-inhibitor synergy screens, and activator-activator synergy screens. We demonstrated how these analyses may be efficiently performed, both experimentally and computationally, to identify particular combinations of most interest. Robust tests of activator-activator synergy and of inhibitor-inhibitor synergy required combinations to show significant excesses over the double doses of each component. Modeling identified multiple effects of an inhibitor of the P2Y12 ADP receptor, and complementarity between inhibitor-inhibitor synergy effects and activator-inhibitor combination effects. This approach accelerates the mapping of combination effects of compounds to develop combinations that may be therapeutically beneficial. We integrated the three information sources into a unified model that predicted the benefits of a triple drug combination targeting ADP, thromboxane and thrombin signaling. '),
(87100, 2015, 'plos', 'Twisting right to left: A…A mismatch in a CAG trinucleotide repeat overexpansion provokes left-handed Z-DNA conformation', 'Khan, Noorain|Kolimi, Narendar|Rathinavelan, Thenmalarchelvi', 'Department of Biotechnology, Indian Institute of Technology Hyderabad, Kandi, Telangana State, India.|Department of Biotechnology, Indian Institute of Technology Hyderabad, Kandi, Telangana State, India.|Department of Biotechnology, Indian Institute of Technology Hyderabad, Kandi, Telangana State, India.', 'India|India|India', 0, 'Base Pair Mismatch|Computational Biology|DNA, Z-Form|Molecular Dynamics Simulation|Nucleic Acid Conformation|Trinucleotide Repeats', 'Journal Article', '10.1371/journal.pcbi.1004162', '25876062', 'Conformational polymorphism of DNA is a major causative factor behind several incurable trinucleotide repeat expansion disorders that arise from overexpansion of trinucleotide repeats located in coding/non-coding regions of specific genes. Hairpin DNA structures that are formed due to overexpansion of CAG repeat lead to Huntingtons disorder and spinocerebellar ataxias. Nonetheless, DNA hairpin stem structure that generally embraces B-form with canonical base pairs is poorly understood in the context of periodic noncanonical A…A mismatch as found in CAG repeat overexpansion. Molecular dynamics simulations on DNA hairpin stems containing A…A mismatches in a CAG repeat overexpansion show that A…A dictates local Z-form irrespective of starting glycosyl conformation, in sharp contrast to canonical DNA duplex. Transition from B-to-Z is due to the mechanistic effect that originates from its pronounced nonisostericity with flanking canonical base pairs facilitated by base extrusion, backbone and/or base flipping. Based on these structural insights we envisage that such an unusual DNA structure of the CAG hairpin stem may have a role in disease pathogenesis. As this is the first study that delineates the influence of a single A…A mismatch in reversing DNA helicity, it would further have an impact on understanding DNA mismatch repair. '),
(87101, 2015, 'plos', 'Correction: Contact-inhibited chemotaxis in de novo and sprouting blood-vessel growth', 'PLOS Computational Biology Staff', 'Department of Biotechnology, Indian Institute of Technology Hyderabad, Kandi, Telangana State, India.', 'India', 0, '-', 'Published Erratum', '10.1371/journal.pcbi.1004163', '25876177', '-'),
(87102, 2015, 'plos', 'Ten simple rules for effective online outreach', 'Bik, Holly M|Dove, Alistair D M|Goldstein, Miriam C|Helm, Rebecca R|MacPherson, Rick|Martini, Kim|Warneke, Alexandria|McClain, Craig', 'UC Davis Genome Center, University of California-Davis, Davis, California, United States of America, School of Biosciences, University of Birmingham, Birmingham, United Kingdom.|Georgia Aquarium Research Center, Atlanta, Georgia, United States of America.|California Sea Grant, La Jolla, California, United States of America.|Department of Ecology and Evolutionary Biology, Brown University, Providence, Rhode Island, United States of America.|Pelagia Consulting, San Francisco, California, United States of America.|Joint Institute for the Study of Atmosphere and Ocean, University of Washington, Seattle, Washington, United States of America, NOAA/Pacific Marine Environmental Laboratory, Seattle, Washington, United States of America.|Department of Biology, San Diego State University, San Diego, California, United States of America.|National Evolutionary Synthesis Center, Durham, North Carolina, United States of America.', 'United Kingdom|Georgia|United States|United States|United States|United States|United States|United ', 23, 'Algorithms|Communication|Information Dissemination|Models, Organizational|Online Systems|Publishing|Research Design|Science|Social Media', 'Editorial', '10.1371/journal.pcbi.1003906', '25879439', '-'),
(87103, 2015, 'plos', 'NEMix: single-cell nested effects models for probabilistic pathway stimulation', 'Siebourg-Polster, Juliane|Mudrak, Daria|Emmenlauer, Mario|Rämö, Pauli|Dehio, Christoph|Greber, Urs|Fröhlich, Holger|Beerenwinkel, Niko', 'Department of Biosystems Science and Engineering, ETH Zurich, Basel, Switzerland, SIB Swiss Institute of Bioinformatics, Basel, Switzerland.|Institute of Molecular Life Sciences, University of Zurich, Zurich, Switzerland.|Biozentrum, University of Basel, Basel, Switzerland.|Biozentrum, University of Basel, Basel, Switzerland.|Biozentrum, University of Basel, Basel, Switzerland.|Institute of Molecular Life Sciences, University of Zurich, Zurich, Switzerland.|Algorithmic Bioinformatics, Bonn-Aachen International Center for IT, University of Bonn, Bonn, Germany.|Department of Biosystems Science and Engineering, ETH Zurich, Basel, Switzerland, SIB Swiss Institute of Bioinformatics, Basel, Switzerland.', 'Switzerland|Switzerland|Switzerland|Switzerland|Switzerland|Switzerland|Germany|Switzerland', 13, 'Algorithms|Animals|Computer Simulation|Humans|Likelihood Functions|Models, Biological|Models, Statistical|Proteins|Signal Transduction|Software', 'Journal Article', '10.1371/journal.pcbi.1004078', '25879530', 'Nested effects models have been used successfully for learning subcellular networks from high-dimensional perturbation effects that result from RNA interference (RNAi) experiments. Here, we further develop the basic nested effects model using high-content single-cell imaging data from RNAi screens of cultured cells infected with human rhinovirus. RNAi screens with single-cell readouts are becoming increasingly common, and they often reveal high cell-to-cell variation. As a consequence of this cellular heterogeneity, knock-downs result in variable effects among cells and lead to weak average phenotypes on the cell population level. To address this confounding factor in network inference, we explicitly model the stimulation status of a signaling pathway in individual cells. We extend the framework of nested effects models to probabilistic combinatorial knock-downs and propose NEMix, a nested effects mixture model that accounts for unobserved pathway activation. We analyzed the identifiability of NEMix and developed a parameter inference scheme based on the Expectation Maximization algorithm. In an extensive simulation study, we show that NEMix improves learning of pathway structures over classical NEMs significantly in the presence of hidden pathway stimulation. We applied our model to single-cell imaging data from RNAi screens monitoring human rhinovirus infection, where limited infection efficiency of the assay results in uncertain pathway stimulation. Using a subset of genes with known interactions, we show that the inferred NEMix network has high accuracy and outperforms the classical nested effects model without hidden pathway activity. NEMix is implemented as part of the R/Bioconductor package nem and available at www.cbg.ethz.ch/software/NEMix. '),
(87104, 2015, 'plos', 'The presence of nuclear cactus in the early Drosophila embryo may extend the dynamic range of the dorsal gradient', 'OConnell, Michael D|Reeves, Gregory T', 'North Carolina State University Department of Chemical and Biomolecular Engineering, Raleigh, North Carolina, United States of America.|North Carolina State University Department of Chemical and Biomolecular Engineering, Raleigh, North Carolina, United States of America.', 'United States|United States', 0, 'Animals|Cell Nucleus|DNA-Binding Proteins|Drosophila|Drosophila Proteins|Embryo, Nonmammalian|Gene Expression Profiling|Morphogenesis|Phosphoproteins', 'Journal Article', '10.1371/journal.pcbi.1004159', '25879657', 'In a developing embryo, the spatial distribution of a signaling molecule, or a morphogen gradient, has been hypothesized to carry positional information to pattern tissues. Recent measurements of morphogen distribution have allowed us to subject this hypothesis to rigorous physical testing. In the early Drosophila embryo, measurements of the morphogen Dorsal, which is a transcription factor responsible for initiating the earliest zygotic patterns along the dorsal-ventral axis, have revealed a gradient that is too narrow to pattern the entire axis. In this study, we use a mathematical model of Dorsal dynamics, fit to experimental data, to determine the ability of the Dorsal gradient to regulate gene expression across the entire dorsal-ventral axis. We found that two assumptions are required for the model to match experimental data in both Dorsal distribution and gene expression patterns. First, we assume that Cactus, an inhibitor that binds to Dorsal and prevents it from entering the nuclei, must itself be present in the nuclei. And second, we assume that fluorescence measurements of Dorsal reflect both free Dorsal and Cactus-bound Dorsal. Our model explains the dynamic behavior of the Dorsal gradient at lateral and dorsal positions of the embryo, the ability of Dorsal to regulate gene expression across the entire dorsal-ventral axis, and the robustness of gene expression to stochastic effects. Our results have a general implication for interpreting fluorescence-based measurements of signaling molecules. '),
(87105, 2015, 'plos', 'The serotype distribution among healthy carriers before vaccination is essential for predicting the impact of pneumococcal conjugate vaccine on invasive disease', 'Flasche, Stefan|Le Polain de Waroux, Olivier|OBrien, Katherine L|Edmunds, W John', 'London School of Hygiene and Tropical Medicine, London, United Kingdom.|London School of Hygiene and Tropical Medicine, London, United Kingdom.|International Vaccine Access Center, Johns Hopkins Bloomberg School of Public Health, Baltimore, Maryland, United States of America.|London School of Hygiene and Tropical Medicine, London, United Kingdom.', 'United Kingdom|United Kingdom|United States|United Kingdom', 19, 'Carrier State|Computational Biology|Heptavalent Pneumococcal Conjugate Vaccine|Humans|Models, Biological|Pneumococcal Infections|Reproducibility of Results|Vaccination', 'Journal Article', '10.1371/journal.pcbi.1004173', '25879748', 'Pneumococcal conjugate vaccines (PCVs) have substantially reduced morbidity and mortality of pneumococcal disease. The impact of the 7-valent PCV on all-serotype invasive pneumococcal disease (IPD) among children was reported to vary between high-income countries. We investigate the ability to predict this heterogeneity from pre-vaccination data. We propose a parsimonious model that predicts the impact of PCVs from the odds of vaccine serotype (VT) among carriers and IPD cases in the pre-PCV period, assuming that VT are eliminated in a mature PCV programme, that full serotype replacement occurs in carriage and that invasiveness of the NVT group is unchanged. We test model performance against the reported impact of PCV7 on childhood IPD in high-income countries from a recent meta-analysis. The odds of pre-PCV7 VT IPD, PCV schedule, PCV coverage and whether a catch up campaign was used for introduction was gathered from the same analysis. We conducted a literature review and meta-analysis to obtain the odds of pre-PCV7 VT carriage in the respective settings. The model predicted the reported impact on childhood IPD of mature PCV programmes, the ratio of predicted and observed incidence risk ratios was close to 1 in all settings. In the high income settings studied differences in schedule, coverage, and catch up campaigns were not associated with the observed heterogeneity in impact of PCV7 on childhood all-serotype IPD. The pre-PCV7 proportion of VT IPD alone also had limited predictive value. The pre-PCV7 proportion of VT carriage and IPD are the main determinants for the impact of PCV7 on childhood IPD and can be combined in a simple model to provide predictions of the vaccine preventable burden of IPD. '),
(87106, 2015, 'plos', 'The role of inhibition in a computational model of an auditory cortical neuron during the encoding of temporal information', 'Bendor, Daniel', 'Institute of Behavioural Neuroscience, Department of Experimental Psychology, University College London, London, United Kingdom.', 'United Kingdom', 0, 'Acoustic Stimulation|Animals|Auditory Cortex|Callithrix|Computational Biology|Computer Simulation|Neurons|Time Factors', 'Journal Article', '10.1371/journal.pcbi.1004197', '25879843', 'In auditory cortex, temporal information within a sound is represented by two complementary neural codes: a temporal representation based on stimulus-locked firing and a rate representation, where discharge rate co-varies with the timing between acoustic events but lacks a stimulus-synchronized response. Using a computational neuronal model, we find that stimulus-locked responses are generated when sound-evoked excitation is combined with strong, delayed inhibition. In contrast to this, a non-synchronized rate representation is generated when the net excitation evoked by the sound is weak, which occurs when excitation is coincident and balanced with inhibition. Using single-unit recordings from awake marmosets (Callithrix jacchus), we validate several model predictions, including differences in the temporal fidelity, discharge rates and temporal dynamics of stimulus-evoked responses between neurons with rate and temporal representations. Together these data suggest that feedforward inhibition provides a parsimonious explanation of the neural coding dichotomy observed in auditory cortex. '),
(87107, 2015, 'plos', 'A power-law dependence of bacterial invasion on mammalian host receptors', 'Lee, Tae J|Wong, Jeffrey|Bae, Sena|Lee, Anna Jisu|Lopatkin, Allison|Yuan, Fan|You, Lingchong', 'Department of Biomedical Engineering, Duke University, Durham, North Carolina, United States of America, Center for Genomic and Computational Biology, Duke University, Durham, North Carolina, United States of America.|Department of Biomedical Engineering, Duke University, Durham, North Carolina, United States of America, Center for Genomic and Computational Biology, Duke University, Durham, North Carolina, United States of America.|Department of Biomedical Engineering, Duke University, Durham, North Carolina, United States of America, Center for Genomic and Computational Biology, 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, Center for Genomic and Computational Biology, Duke University, Durham, North Carolina, United States of America, Center for Systems Biology, Duke University, Durham, North Carolina, United States of America.', 'United States|United States|United States|United States|United States|United States|United States', 3, 'Bacteria|Bacterial Adhesion|Bacterial Infections|Bacterial Proteins|Computational Biology|HeLa Cells|Host-Pathogen Interactions|Humans|Membrane Proteins|Models, Biological', 'Journal Article', '10.1371/journal.pcbi.1004203', '25879937', 'Pathogenic bacteria such as Listeria and Yersinia gain initial entry by binding to host target cells and stimulating their internalization. Bacterial uptake entails successive, increasingly strong associations between receptors on the surface of bacteria and hosts. Even with genetically identical cells grown in the same environment, there are vast differences in the number of bacteria entering any given cell. To gain insight into this variability, we examined uptake dynamics of Escherichia coli engineered to express the invasin surface receptor from Yersinia, which enables uptake via mammalian host xcexb21-integrins. Surprisingly, we found that the uptake probability of a single bacterium follows a simple power-law dependence on the concentration of integrins. Furthermore, the value of a power-law parameter depends on the particular host-bacterium pair but not on bacterial concentration. This power-law captures the complex, variable processes underlying bacterial invasion while also enabling differentiation of cell lines. '),
(87108, 2015, 'plos', 'The quantitative methods boot camp: teaching quantitative thinking and computing skills to graduate students in the life sciences', 'Stefan, Melanie I|Gutlerner, Johanna L|Born, Richard T|Springer, Michael', 'Department of Neurobiology, Harvard Medical School, Boston, Massachusetts, United States of America.|Department of Biological Chemistry and Molecular Pharmacology, Harvard Medical School, Boston, Massachusetts, United States of America.|Department of Neurobiology, Harvard Medical School, Boston, Massachusetts, United States of America.|Department of Systems Biology, Harvard Medical School, Boston, Massachusetts, United States of America.', 'United States|United States|United States|United States', 0, 'Biological Science Disciplines|Computational Biology|Humans|Students|Thinking', 'Journal Article', '10.1371/journal.pcbi.1004208', '25880064', 'The past decade has seen a rapid increase in the ability of biologists to collect large amounts of data. It is therefore vital that research biologists acquire the necessary skills during their training to visualize, analyze, and interpret such data. To begin to meet this need, we have developed a boot camp in quantitative methods for biology graduate students at Harvard Medical School. The goal of this short, intensive course is to enable students to use computational tools to visualize and analyze data, to strengthen their computational thinking skills, and to simulate and thus extend their intuition about the behavior of complex biological systems. The boot camp teaches basic programming using biological examples from statistics, image processing, and data analysis. This integrative approach to teaching programming and quantitative reasoning motivates students engagement by demonstrating the relevance of these skills to their work in life science laboratories. Students also have the opportunity to analyze their own data or explore a topic of interest in more detail. The class is taught with a mixture of short lectures, Socratic discussion, and in-class exercises. Students spend approximately 40% of their class time working through both short and long problems. A high instructor-to-student ratio allows students to get assistance or additional challenges when needed, thus enhancing the experience for students at all levels of mastery. Data collected from end-of-course surveys from the last five offerings of the course (between 2012 and 2014) show that students report high learning gains and feel that the course prepares them for solving quantitative and computational problems they will encounter in their research. We outline our course here which, together with the course materials freely available online under a Creative Commons License, should help to facilitate similar efforts by others. '),
(87109, 2015, 'plos', 'ConPADE: genome assembly ploidy estimation from next-generation sequencing data', 'Margarido, Gabriel R A|Heckerman, David', 'Microsoft Research, Los Angeles, California, United States of America, Departamento de Genética, Escola Superior de Agricultura Luiz de Queiroz, Universidade de São Paulo, Piracicaba, Brazil.|Microsoft Research, Los Angeles, California, United States of America.', 'Brazil|United States', 11, 'Algorithms|Computer Simulation|DNA, Plant|Databases, Genetic|Genome, Plant|Genomics|High-Throughput Nucleotide Sequencing|Models, Genetic|Models, Statistical|Ploidies|Sequence Analysis, DNA', 'Journal Article', '10.1371/journal.pcbi.1004229', '25880203', 'As a result of improvements in genome assembly algorithms and the ever decreasing costs of high-throughput sequencing technologies, new high quality draft genome sequences are published at a striking pace. With well-established methodologies, larger and more complex genomes are being tackled, including polyploid plant genomes. Given the similarity between multiple copies of a basic genome in polyploid individuals, assembly of such data usually results in collapsed contigs that represent a variable number of homoeologous genomic regions. Unfortunately, such collapse is often not ideal, as keeping contigs separate can lead both to improved assembly and also insights about how haplotypes influence phenotype. Here, we describe a first step in avoiding inappropriate collapse during assembly. In particular, we describe ConPADE (Contig Ploidy and Allele Dosage Estimation), a probabilistic method that estimates the ploidy of any given contig/scaffold based on its allele proportions. In the process, we report findings regarding errors in sequencing. The method can be used for whole genome shotgun (WGS) sequencing data. We also show applicability of the method for variant calling and allele dosage estimation. Results for simulated and real datasets are discussed and provide evidence that ConPADE performs well as long as enough sequencing coverage is available, or the true contig ploidy is low. We show that ConPADE may also be used for related applications, such as the identification of duplicated genes in fragmented assemblies, although refinements are needed. '),
(87110, 2015, 'plos', 'Segmentation and tracking of adherens junctions in 3D for the analysis of epithelial tissue morphogenesis', 'Cilla, Rodrigo|Mechery, Vinodh|Hernandez de Madrid, Beatriz|Del Signore, Steven|Dotu, Ivan|Hatini, Victor', 'Department of Developmental, Molecular & Chemical Biology. Sackler School of Graduate Biomedical Sciences, Tufts University School of Medicine, Boston, Massachusetts, United States of America.|Department of Developmental, Molecular & Chemical Biology. Sackler School of Graduate Biomedical Sciences, Tufts University School of Medicine, Boston, Massachusetts, United States of America.|Department of Developmental, Molecular & Chemical Biology. Sackler School of Graduate Biomedical Sciences, Tufts University School of Medicine, Boston, Massachusetts, United States of America.|Department of Developmental, Molecular & Chemical Biology. Sackler School of Graduate Biomedical Sciences, Tufts University School of Medicine, Boston, Massachusetts, United States of America.|Department of Biology, Boston College, Boston, Massachusetts, United States of America.|Department of Developmental, Molecular & Chemical Biology. Sackler School of Graduate Biomedical Sciences, Tufts University School of Medicine, Boston, Massachusetts, United States of America.', 'United States|United States|United States|United States|United States|United States', 14, 'Adherens Junctions|Animals|Cell Adhesion|Cell Tracking|Drosophila|Epithelial Cells|Imaging, Three-Dimensional|Microscopy, Confocal|Morphogenesis|Reproducibility of Results|Sensitivity and Specificity', 'Journal Article', '10.1371/journal.pcbi.1004124', '25884654', 'Epithelial morphogenesis generates the shape of tissues, organs and embryos and is fundamental for their proper function. It is a dynamic process that occurs at multiple spatial scales from macromolecular dynamics, to cell deformations, mitosis and apoptosis, to coordinated cell rearrangements that lead to global changes of tissue shape. Using time lapse imaging, it is possible to observe these events at a system level. However, to investigate morphogenetic events it is necessary to develop computational tools to extract quantitative information from the time lapse data. Toward this goal, we developed an image-based computational pipeline to preprocess, segment and track epithelial cells in 4D confocal microscopy data. The computational pipeline we developed, for the first time, detects the adherens junctions of epithelial cells in 3D, without the need to first detect cell nuclei. We accentuate and detect cell outlines in a series of steps, symbolically describe the cells and their connectivity, and employ this information to track the cells. We validated the performance of the pipeline for its ability to detect vertices and cell-cell contacts, track cells, and identify mitosis and apoptosis in surface epithelia of Drosophila imaginal discs. We demonstrate the utility of the pipeline to extract key quantitative features of cell behavior with which to elucidate the dynamics and biomechanical control of epithelial tissue morphogenesis. We have made our methods and data available as an open-source multiplatform software tool called TTT (http://github.com/morganrcu/TTT). '),
(87111, 2015, 'plos', 'Neuroblastoma tyrosine kinase signaling networks involve FYN and LYN in endosomes and lipid rafts', 'Palacios-Moreno, Juan|Foltz, Lauren|Guo, Ailan|Stokes, Matthew P|Kuehn, Emily D|George, Lynn|Comb, Michael|Grimes, Mark L', 'Division of Biological Sciences, Center for Structural and Functional Neuroscience, University of Montana, Missoula, Montana, United States of America.|Division of Biological Sciences, Center for Structural and Functional Neuroscience, University of Montana, Missoula, Montana, United States of America.|Cell Signaling Technology, Inc., Danvers, Massachusetts, United States of America.|Cell Signaling Technology, Inc., Danvers, Massachusetts, United States of America.|Department of Neuroscience, Johns Hopkins University School of Medicine, Baltimore, Maryland, United States of America.|Department of Cell Biology and Neuroscience, Montana State University, Bozeman, Montana, United States of America.|Cell Signaling Technology, Inc., Danvers, Massachusetts, United States of America.|Division of Biological Sciences, Center for Structural and Functional Neuroscience, University of Montana, Missoula, Montana, United States of America.', 'United States|United States|United States|United States|United States|United States|United States|Un', 0, 'Adaptor Proteins, Signal Transducing|Cell Line, Tumor|Computer Simulation|Endosomes|Humans|Membrane Microdomains|Models, Biological|Neoplasm Proteins|Neuroblastoma|Phosphoproteins|Protein-Tyrosine Kinases|Signal Transduction|src-Family Kinases', 'Journal Article', '10.1371/journal.pcbi.1004130', '25884760', 'Protein phosphorylation plays a central role in creating a highly dynamic network of interacting proteins that reads and responds to signals from growth factors in the cellular microenvironment. Cells of the neural crest employ multiple signaling mechanisms to control migration and differentiation during development. It is known that defects in these mechanisms cause neuroblastoma, but how multiple signaling pathways interact to govern cell behavior is unknown. In a phosphoproteomic study of neuroblastoma cell lines and cell fractions, including endosomes and detergent-resistant membranes, 1622 phosphorylated proteins were detected, including more than half of the receptor tyrosine kinases in the human genome. Data were analyzed using a combination of graph theory and pattern recognition techniques that resolve data structure into networks that incorporate statistical relationships and protein-protein interaction data. Clusters of proteins in these networks are indicative of functional signaling pathways. The analysis indicates that receptor tyrosine kinases are functionally compartmentalized into distinct collaborative groups distinguished by activation and intracellular localization of SRC-family kinases, especially FYN and LYN. Changes in intracellular localization of activated FYN and LYN were observed in response to stimulation of the receptor tyrosine kinases, ALK and KIT. The results suggest a mechanism to distinguish signaling responses to activation of different receptors, or combinations of receptors, that govern the behavior of the neural crest, which gives rise to neuroblastoma. '),
(87112, 2015, 'plos', 'Loregic: a method to characterize the cooperative logic of regulatory factors', 'Wang, Daifeng|Yan, Koon-Kiu|Sisu, Cristina|Cheng, Chao|Rozowsky, Joel|Meyerson, William|Gerstein, Mark B', 'Program in Computational Biology and Bioinformatics, Yale University, New Haven, Connecticut, United States of America, Department of Molecular Biophysics and Biochemistry, Yale University, New Haven, Connecticut, United States of America.|Program in Computational Biology and Bioinformatics, Yale University, New Haven, Connecticut, United States of America, Department of Molecular Biophysics and Biochemistry, Yale University, New Haven, Connecticut, United States of America.|Program in Computational Biology and Bioinformatics, Yale University, New Haven, Connecticut, United States of America, Department of Molecular Biophysics and Biochemistry, Yale University, New Haven, Connecticut, United States of America.|Department of Genetics, Geisel School of Medicine at Dartmouth, Hanover, New Hampshire, United States of America.|Program in Computational Biology and Bioinformatics, Yale University, New Haven, Connecticut, United States of America, Department of Molecular Biophysics and Biochemistry, Yale University, New Haven, Connecticut, United States of America.|School of Medicine, Yale University, New Haven, Connecticut, United States of America.|Program in Computational Biology and Bioinformatics, Yale University, New Haven, Connecticut, United States of America, Department of Molecular Biophysics and Biochemistry, Yale University, New Haven, Connecticut, United States of America, Department of Computer Science, Yale University, New Haven, Connecticut, United States of America.', 'United States|United States|United States|United States|United States|United States|United States', 0, 'Algorithms|Animals|Computer Simulation|Gene Expression Regulation|Gene Regulatory Networks|Genes, Regulator|Humans|Leukemia|Logistic Models|MicroRNAs|Models, Genetic|Transcription Factors|Transcriptional Activation', 'Journal Article', '10.1371/journal.pcbi.1004132', '25884877', 'The topology of the gene-regulatory network has been extensively analyzed. Now, given the large amount of available functional genomic data, it is possible to go beyond this and systematically study regulatory circuits in terms of logic elements. To this end, we present Loregic, a computational method integrating gene expression and regulatory network data, to characterize the cooperativity of regulatory factors. Loregic uses all 16 possible two-input-one-output logic gates (e.g. AND or XOR) to describe triplets of two factors regulating a common target. We attempt to find the gate that best matches each triplets observed gene expression pattern across many conditions. We make Loregic available as a general-purpose tool (github.com/gersteinlab/loregic). We validate it with known yeast transcription-factor knockout experiments. Next, using human ENCODE ChIP-Seq and TCGA RNA-Seq data, we are able to demonstrate how Loregic characterizes complex circuits involving both proximally and distally regulating transcription factors (TFs) and also miRNAs. Furthermore, we show that MYC, a well-known oncogenic driving TF, can be modeled as acting independently from other TFs (e.g., using OR gates) but antagonistically with repressing miRNAs. Finally, we inter-relate Loregics gate logic with other aspects of regulation, such as indirect binding via protein-protein interactions, feed-forward loop motifs and global regulatory hierarchy. '),
(87113, 2015, 'plos', 'Simulation predicts IGFBP2-HIF1xcexb1 interaction drives glioblastoma growth', 'Lin, Ka Wai|Liao, Angela|Qutub, Amina A', 'Department of Bioengineering, Rice University, Houston, Texas, United States of America.|Department of Bioengineering, Rice University, Houston, Texas, United States of America.|Department of Bioengineering, Rice University, Houston, Texas, United States of America.', 'United States|United States|United States', 0, 'Adolescent|Adult|Aged|Algorithms|Child|Child, Preschool|Computational Biology|Computer Simulation|Feedback, Physiological|Glioblastoma|Humans|Hypoxia-Inducible Factor 1, alpha Subunit|Infant|Infant, Newborn|Insulin|Insulin-Like Growth Factor Binding Protein 2|Middle Aged|Models, Biological|Oxygen|Signal Transduction|Young Adult', 'Journal Article', '10.1371/journal.pcbi.1004169', '25884993', 'Tremendous strides have been made in improving patients survival from cancer with one glaring exception: brain cancer. Glioblastoma is the most common, aggressive and highly malignant type of primary brain tumor. The average overall survival remains less than 1 year. Notably, cancer patients with obesity and diabetes have worse outcomes and accelerated progression of glioblastoma. The root cause of this accelerated progression has been hypothesized to involve the insulin signaling pathway. However, while the process of invasive glioblastoma progression has been extensively studied macroscopically, it has not yet been well characterized with regards to intracellular insulin signaling. In this study we connect for the first time microscale insulin signaling activity with macroscale glioblastoma growth through the use of computational modeling. Results of the model suggest a novel observation: feedback from IGFBP2 to HIF1xcexb1 is integral to the sustained growth of glioblastoma. Our study suggests that downstream signaling from IGFI to HIF1xcexb1, which has been the target of many insulin signaling drugs in clinical trials, plays a smaller role in overall tumor growth. These predictions strongly suggest redirecting the focus of glioma drug candidates on controlling the feedback between IGFBP2 and HIF1xcexb1. '),
(87114, 2015, 'plos', 'Emergent systems energy laws for predicting myosin ensemble processivity', 'Egan, Paul|Moore, Jeffrey|Schunn, Christian|Cagan, Jonathan|LeDuc, Philip', 'Department of Mechanical Engineering, Carnegie Mellon University, Pittsburgh, Pennsylvania, United States of America.|Department of Physiology and Biophysics, Boston University School of Medicine, Boston, Massachusetts, United States of America.|Department of Psychology, University of Pittsburgh, Pittsburgh, Pennsylvania, United States of America.|Department of Mechanical Engineering, Carnegie Mellon University, Pittsburgh, Pennsylvania, United States of America.|Department of Mechanical Engineering, Carnegie Mellon University, Pittsburgh, Pennsylvania, United States of America.', 'United States|United States|United States|United States|United States', 13, 'Biomechanical Phenomena|Computational Biology|Computer Simulation|Models, Molecular|Myosins|Protein Isoforms|Reproducibility of Results|Stochastic Processes', 'Journal Article', '10.1371/journal.pcbi.1004177', '25885169', 'In complex systems with stochastic components, systems laws often emerge that describe higher level behavior regardless of lower level component configurations. In this paper, emergent laws for describing mechanochemical systems are investigated for processive myosin-actin motility systems. On the basis of prior experimental evidence that longer processive lifetimes are enabled by larger myosin ensembles, it is hypothesized that emergent scaling laws could coincide with myosin-actin contact probability or system energy consumption. Because processivity is difficult to predict analytically and measure experimentally, agent-based computational techniques are developed to simulate processive myosin ensembles and produce novel processive lifetime measurements. It is demonstrated that only systems energy relationships hold regardless of isoform configurations or ensemble size, and a unified expression for predicting processive lifetime is revealed. The finding of such laws provides insight for how patterns emerge in stochastic mechanochemical systems, while also informing understanding and engineering of complex biological systems. '),
(87115, 2015, 'plos', 'Interaction of the antimicrobial peptide polymyxin B1 with both membranes of E coli: a molecular dynamics study', 'Berglund, Nils A|Piggot, Thomas J|Jefferies, Damien|Sessions, Richard B|Bond, Peter J|Khalid, Syma', 'School of Chemistry, University of Southampton, Highfield, Southampton, United Kingdom, Bioinformatics Institute (A*STAR), Singapore.|School of Chemistry, University of Southampton, Highfield, Southampton, United Kingdom.|School of Chemistry, University of Southampton, Highfield, Southampton, United Kingdom.|School of Biochemistry, Bristol, United Kingdom.|Bioinformatics Institute (A*STAR), Singapore, Department of Biological Sciences, National University of Singapore, Singapore.|School of Chemistry, University of Southampton, Highfield, Southampton, United Kingdom.', 'United Kingdom|United Kingdom|United Kingdom|United Kingdom|Singapore|United Kingdom', 68, 'Cell Membrane|Computational Biology|Escherichia coli|Lipopolysaccharides|Molecular Dynamics Simulation|Polymyxins', 'Journal Article', '10.1371/journal.pcbi.1004180', '25885324', 'Antimicrobial peptides are small, cationic proteins that can induce lysis of bacterial cells through interaction with their membranes. Different mechanisms for cell lysis have been proposed, but these models tend to neglect the role of the chemical composition of the membrane, which differs between bacterial species and can be heterogeneous even within a single cell. Moreover, the cell envelope of Gram-negative bacteria such as E. coli contains two membranes with differing compositions. To this end, we report the first molecular dynamics simulation study of the interaction of the antimicrobial peptide, polymyxin B1 with complex models of both the inner and outer membranes of E. coli. The results of >16 microseconds of simulation predict that polymyxin B1 is likely to interact with the membranes via distinct mechanisms. The lipopeptides aggregate in the lipopolysaccharide headgroup region of the outer membrane with limited tendency for insertion within the lipid A tails. In contrast, the lipopeptides readily insert into the inner membrane core, and the concomitant increased hydration may be responsible for bilayer destabilization and antimicrobial function. Given the urgent need to develop novel, potent antibiotics, the results presented here reveal key mechanistic details that may be exploited for future rational drug development. '),
(87116, 2015, 'plos', 'The universal statistical distributions of the affinity, equilibrium constants, kinetics and specificity in biomolecular recognition', 'Zheng, Xiliang|Wang, Jin', 'State Key Laboratory of Electroanalytical Chemistry, Changchun Institute of Applied Chemistry, Chinese Academy of Sciences, ChangChun, Jilin, P.R. China.|Department of Chemistry and Physics, State University of New York at Stony Brook, Stony Brook, New York, United States of America.', 'China|United States', 0, 'Computational Biology|Kinetics|Ligands|Models, Theoretical|Protein Binding|Statistical Distributions|Thermodynamics', 'Journal Article', '10.1371/journal.pcbi.1004212', '25885453', 'We uncovered the universal statistical laws for the biomolecular recognition/binding process. We quantified the statistical energy landscapes for binding, from which we can characterize the distributions of the binding free energy (affinity), the equilibrium constants, the kinetics and the specificity by exploring the different ligands binding with a particular receptor. The results of the analytical studies are confirmed by the microscopic flexible docking simulations. The distribution of binding affinity is Gaussian around the mean and becomes exponential near the tail. The equilibrium constants of the binding follow a log-normal distribution around the mean and a power law distribution in the tail. The intrinsic specificity for biomolecular recognition measures the degree of discrimination of native versus non-native binding and the optimization of which becomes the maximization of the ratio of the free energy gap between the native state and the average of non-native states versus the roughness measured by the variance of the free energy landscape around its mean. The intrinsic specificity obeys a Gaussian distribution near the mean and an exponential distribution near the tail. Furthermore, the kinetics of binding follows a log-normal distribution near the mean and a power law distribution at the tail. Our study provides new insights into the statistical nature of thermodynamics, kinetics and function from different ligands binding with a specific receptor or equivalently specific ligand binding with different receptors. The elucidation of distributions of the kinetics and free energy has guiding roles in studying biomolecular recognition and function through small-molecule evolution and chemical genetics. '),
(87117, 2015, 'plos', 'Transcriptional dynamics reveal critical roles for non-coding RNAs in the immediate-early response', 'Aitken, Stuart|Magi, Shigeyuki|Alhendi, Ahmad M N|Itoh, Masayoshi|Kawaji, Hideya|Lassmann, Timo|Daub, Carsten O|Arner, Erik|Carninci, Piero|Forrest, Alistair R R|Hayashizaki, Yoshihide|FANTOM Consortium|Khachigian, Levon M|Okada-Hatakeyama, Mariko|Semple, Colin A', 'MRC Institute of Genetics and Molecular Medicine, University of Edinburgh, Edinburgh, United Kingdom.|Laboratory for Integrated Cellular Systems, RIKEN Center for Integrative Medical Sciences, IMS, W518, Suehiro-cho, Tsurumi-ku, Yokohama, Japan.|UNSW Centre for Vascular Research, University of New South Wales, Sydney, New South Wales, Australia.|RIKEN Center for Life Science Technologies, Division of Genomic Technologies, Yokohama, Kanagawa, Japan, RIKEN Preventive Medicine and Diagnosis Innovation Program, Wako, Saitama, Japan, RIKEN Omics Science Center, Yokohama, Kanagawa, Japan.|RIKEN Center for Life Science Technologies, Division of Genomic Technologies, Yokohama, Kanagawa, Japan, RIKEN Preventive Medicine and Diagnosis Innovation Program, Wako, Saitama, Japan, RIKEN Omics Science Center, Yokohama, Kanagawa, Japan.|RIKEN Center for Life Science Technologies, Division of Genomic Technologies, Yokohama, Kanagawa, Japan, RIKEN Omics Science Center, Yokohama, Kanagawa, Japan.|RIKEN Center for Life Science Technologies, Division of Genomic Technologies, Yokohama, Kanagawa, Japan, RIKEN Omics Science Center, Yokohama, Kanagawa, Japan.|RIKEN Center for Life Science Technologies, Division of Genomic Technologies, Yokohama, Kanagawa, Japan, RIKEN Omics Science Center, Yokohama, Kanagawa, Japan.|RIKEN Center for Life Science Technologies, Division of Genomic Technologies, Yokohama, Kanagawa, Japan, RIKEN Omics Science Center, Yokohama, Kanagawa, Japan.|RIKEN Center for Life Science Technologies, Division of Genomic Technologies, Yokohama, Kanagawa, Japan, RIKEN Omics Science Center, Yokohama, Kanagawa, Japan.|RIKEN Center for Life Science Technologies, Division of Genomic Technologies, Yokohama, Kanagawa, Japan, RIKEN Preventive Medicine and Diagnosis Innovation Program, Wako, Saitama, Japan.|RIKEN Center for Life Science Technologies, Division of Genomic Technologies, Yokohama, Kanagawa, Japan, RIKEN Preventive Medicine and Diagnosis Innovation Program, Wako, Saitama, Japan.|UNSW Centre for Vascular Research, University of New South Wales, Sydney, New South Wales, Australia.|Laboratory for Integrated Cellular Systems, RIKEN Center for Integrative Medical Sciences, IMS, W518, Suehiro-cho, Tsurumi-ku, Yokohama, Japan.|MRC Institute of Genetics and Molecular Medicine, University of Edinburgh, Edinburgh, United Kingdom.', 'United Kingdom|Japan|Australia|Japan|Japan|Japan|Japan|Japan|Japan|Japan|Japan|Japan|Australia|Japan', 0, 'Computational Biology|Humans|Immediate-Early Proteins|Kinetics|MCF-7 Cells|MicroRNAs|Models, Statistical|RNA, Untranslated|Transcription, Genetic', 'Journal Article', '10.1371/journal.pcbi.1004217', '25885578', 'The immediate-early response mediates cell fate in response to a variety of extracellular stimuli and is dysregulated in many cancers. However, the specificity of the response across stimuli and cell types, and the roles of non-coding RNAs are not well understood. Using a large collection of densely-sampled time series expression data we have examined the induction of the immediate-early response in unparalleled detail, across cell types and stimuli. We exploit cap analysis of gene expression (CAGE) time series datasets to directly measure promoter activities over time. Using a novel analysis method for time series data we identify transcripts with expression patterns that closely resemble the dynamics of known immediate-early genes (IEGs) and this enables a comprehensive comparative study of these genes and their chromatin state. Surprisingly, these data suggest that the earliest transcriptional responses often involve promoters generating non-coding RNAs, many of which are produced in advance of canonical protein-coding IEGs. IEGs are known to be capable of induction without de novo protein synthesis. Consistent with this, we find that the response of both protein-coding and non-coding RNA IEGs can be explained by their transcriptionally poised, permissive chromatin state prior to stimulation. We also explore the function of non-coding RNAs in the attenuation of the immediate early response in a small RNA sequencing dataset matched to the CAGE data: We identify a novel set of microRNAs responsible for the attenuation of the IEG response in an estrogen receptor positive cancer cell line. Our computational statistical method is well suited to meta-analyses as there is no requirement for transcripts to pass thresholds for significant differential expression between time points, and it is agnostic to the number of time points per dataset. ');
INSERT INTO `papers` (`id`, `ano`, `journal`, `titulo`, `autores`, `afiliacao`, `pais`, `citacoes`, `palavra_chave`, `categorias`, `doi`, `pubmed`, `abstract`) VALUES
(87118, 2015, 'plos', 'MAGMA: generalized gene-set analysis of GWAS data', 'de Leeuw, Christiaan A|Mooij, Joris M|Heskes, Tom|Posthuma, Danielle', 'Department of Complex Trait Genetics, Center for Neurogenomics and Cognitive Research, VU University Amsterdam, Amsterdam, The Netherlands, Institute for Computing and Information Sciences, Radboud University Nijmegen, Nijmegen, The Netherlands.|Informatics Institute, University of Amsterdam, Amsterdam, The Netherlands.|Institute for Computing and Information Sciences, Radboud University Nijmegen, Nijmegen, The Netherlands.|Department of Complex Trait Genetics, Center for Neurogenomics and Cognitive Research, VU University Amsterdam, Amsterdam, The Netherlands, Department of Clinical Genetics, VU University Medical Centre Amsterdam, Neuroscience Campus Amsterdam, The Netherlands.', 'Netherlands|Netherlands|Netherlands|Netherlands', 468, 'Computational Biology|Computer Simulation|Crohn Disease|Databases, Genetic|Genome-Wide Association Study|Humans|Models, Genetic|Software', 'Journal Article', '10.1371/journal.pcbi.1004219', '25885710', 'By aggregating data for complex traits in a biologically meaningful way, gene and gene-set analysis constitute a valuable addition to single-marker analysis. However, although various methods for gene and gene-set analysis currently exist, they generally suffer from a number of issues. Statistical power for most methods is strongly affected by linkage disequilibrium between markers, multi-marker associations are often hard to detect, and the reliance on permutation to compute p-values tends to make the analysis computationally very expensive. To address these issues we have developed MAGMA, a novel tool for gene and gene-set analysis. The gene analysis is based on a multiple regression model, to provide better statistical performance. The gene-set analysis is built as a separate layer around the gene analysis for additional flexibility. This gene-set analysis also uses a regression structure to allow generalization to analysis of continuous properties of genes and simultaneous analysis of multiple gene sets and other gene properties. Simulations and an analysis of Crohns Disease data are used to evaluate the performance of MAGMA and to compare it to a number of other gene and gene-set analysis tools. The results show that MAGMA has significantly more power than other tools for both the gene and the gene-set analysis, identifying more genes and gene sets associated with Crohns Disease while maintaining a correct type 1 error rate. Moreover, the MAGMA analysis of the Crohns Disease data was found to be considerably faster as well. '),
(87119, 2015, 'plos', 'Perturbation-expression analysis identifies RUNX1 as a regulator of human mammary stem cell differentiation', 'Sokol, Ethan S|Sanduja, Sandhya|Jin, Dexter X|Miller, Daniel H|Mathis, Robert A|Gupta, Piyush B', 'Whitehead Institute for Biomedical Research, Cambridge, Massachusetts, United States of America, Department of Biology, Massachusetts Institute of Technology, Cambridge, Massachusetts, United States of America.|Whitehead Institute for Biomedical Research, Cambridge, Massachusetts, United States of America.|Whitehead Institute for Biomedical Research, Cambridge, Massachusetts, United States of America, Department of Biology, Massachusetts Institute of Technology, Cambridge, Massachusetts, United States of America.|Whitehead Institute for Biomedical Research, Cambridge, Massachusetts, United States of America, Department of Biology, Massachusetts Institute of Technology, Cambridge, Massachusetts, United States of America.|Whitehead Institute for Biomedical Research, Cambridge, Massachusetts, United States of America, Department of Biology, Massachusetts Institute of Technology, Cambridge, Massachusetts, United States of America.|Whitehead Institute for Biomedical Research, Cambridge, Massachusetts, United States of America, Department of Biology, Massachusetts Institute of Technology, Cambridge, Massachusetts, United States of America, Koch Institute for Integrative Cancer Research at MIT, Cambridge, Massachusetts, United States of America, Harvard Stem Cell Institute, Cambridge, Massachusetts, United States of America.', 'United States|United States|United States|United States|United States|United States', 0, 'Cell Differentiation|Cells, Cultured|Core Binding Factor Alpha 2 Subunit|Gene Expression Profiling|Humans|Mammary Glands, Human|Organoids|Stem Cells|Systems Biology', 'Journal Article', '10.1371/journal.pcbi.1004161', '25894653', 'The search for genes that regulate stem cell self-renewal and differentiation has been hindered by a paucity of markers that uniquely label stem cells and early progenitors. To circumvent this difficulty we have developed a method that identifies cell-state regulators without requiring any markers of differentiation, termed Perturbation-Expression Analysis of Cell States (PEACS). We have applied this marker-free approach to screen for transcription factors that regulate mammary stem cell differentiation in a 3D model of tissue morphogenesis and identified RUNX1 as a stem cell regulator. Inhibition of RUNX1 expanded bipotent stem cells and blocked their differentiation into ductal and lobular tissue rudiments. Reactivation of RUNX1 allowed exit from the bipotent state and subsequent differentiation and mammary morphogenesis. Collectively, our findings show that RUNX1 is required for mammary stem cells to exit a bipotent state, and provide a new method for discovering cell-state regulators when markers are not available. '),
(87120, 2015, 'plos', 'Deep sequencing of protease inhibitor resistant HIV patient isolates reveals patterns of correlated mutations in Gag and protease', 'Flynn, William F|Chang, Max W|Tan, Zhiqiang|Oliveira, Glenn|Yuan, Jinyun|Okulicz, Jason F|Torbett, Bruce E|Levy, Ronald M', 'Department of Physics and Astronomy, Rutgers University, Piscataway, New Jersey, United States of America, Center for Biophysics and Computational Biology, Temple University, Philadelphia, Pennsylvania, United States of America.|Department of Molecular and Experimental Medicine, The Scripps Research Institute, La Jolla, California, United States of America.|Department of Statistics, Rutgers University, Piscataway, New Jersey, United States of America.|Department of Molecular and Experimental Medicine, The Scripps Research Institute, La Jolla, California, United States of America.|Department of Molecular and Experimental Medicine, The Scripps Research Institute, La Jolla, California, United States of America.|Infectious Disease Service, San Antonio Military Medical Center, San Antonio, Texas, United States of America.|Department of Molecular and Experimental Medicine, The Scripps Research Institute, La Jolla, California, United States of America.|Center for Biophysics and Computational Biology, Temple University, Philadelphia, Pennsylvania, United States of America, Department of Chemistry, and Institute for Computational Molecular Science, Temple University, Philadelphia, Pennsylvania, United States of America.', 'Jersey|United States|Jersey|United States|United States|United States|United States|United States', 18, 'Computational Biology|Drug Resistance, Viral|HIV Infections|HIV Protease|HIV Protease Inhibitors|HIV-1|High-Throughput Nucleotide Sequencing|Humans|Mutation|gag Gene Products, Human Immunodeficiency Virus', 'Journal Article', '10.1371/journal.pcbi.1004249', '25894830', 'While the role of drug resistance mutations in HIV protease has been studied comprehensively, mutations in its substrate, Gag, have not been extensively cataloged. Using deep sequencing, we analyzed a unique collection of longitudinal viral samples from 93 patients who have been treated with therapies containing protease inhibitors (PIs). Due to the high sequence coverage within each sample, the frequencies of mutations at individual positions were calculated with high precision. We used this information to characterize the variability in the Gag polyprotein and its effects on PI-therapy outcomes. To examine covariation of mutations between two different sites using deep sequencing data, we developed an approach to estimate the tight bounds on the two-site bivariate probabilities in each viral sample, and the mutual information between pairs of positions based on all the bounds. Utilizing the new methodology we found that mutations in the matrix and p6 proteins contribute to continued therapy failure and have a major role in the network of strongly correlated mutations in the Gag polyprotein, as well as between Gag and protease. Although covariation is not direct evidence of structural propensities, we found the strongest correlations between residues on capsid and matrix of the same Gag protein were often due to structural proximity. This suggests that some of the strongest inter-protein Gag correlations are the result of structural proximity. Moreover, the strong covariation between residues in matrix and capsid at the N-terminus with p1 and p6 at the C-terminus is consistent with residue-residue contacts between these proteins at some point in the viral life cycle. '),
(87121, 2015, 'plos', 'Modulation of the disordered conformational ensembles of the p53 transactivation domain by cancer-associated mutations', 'Ganguly, Debabani|Chen, Jianhan', 'Department of Biochemistry and Molecular Biophysics, Kansas State University, Manhattan, Kansas, United States of America, Indian Institute of Engineering Science and Technology, Shibpur Howrah, India.|Department of Biochemistry and Molecular Biophysics, Kansas State University, Manhattan, Kansas, United States of America.', 'India|United States', 22, 'Computational Biology|Molecular Dynamics Simulation|Mutation|Neoplasms|Protein Conformation|Protein Structure, Tertiary|Transcriptional Activation|Tumor Suppressor Protein p53', 'Journal Article', '10.1371/journal.pcbi.1004247', '25897952', 'Intrinsically disordered proteins (IDPs) are frequently associated with human diseases such as cancers, and about one-fourth of disease-associated missense mutations have been mapped into predicted disordered regions. Understanding how these mutations affect the structure-function relationship of IDPs is a formidable task that requires detailed characterization of the disordered conformational ensembles. Implicit solvent coupled with enhanced sampling has been proposed to provide a balance between accuracy and efficiency necessary for systematic and comparative assessments of the effects of mutations as well as post-translational modifications on IDP structure and interaction. Here, we utilize a recently developed replica exchange with guided annealing enhanced sampling technique to calculate well-converged atomistic conformational ensembles of the intrinsically disordered transactivation domain (TAD) of tumor suppressor p53 and several cancer-associated mutants in implicit solvent. The simulations are critically assessed by quantitative comparisons with several types of experimental data that provide structural information on both secondary and tertiary levels. The results show that the calculated ensembles reproduce local structural features of wild-type p53-TAD and the effects of K24N mutation quantitatively. On the tertiary level, the simulated ensembles are overly compact, even though they appear to recapitulate the overall features of transient long-range contacts qualitatively. A key finding is that, while p53-TAD and its cancer mutants sample a similar set of conformational states, cancer mutants could introduce both local and long-range structural modulations to potentially perturb the balance of p53 binding to various regulatory proteins and further alter how this balance is regulated by multisite phosphorylation of p53-TAD. The current study clearly demonstrates the promise of atomistic simulations for detailed characterization of IDP conformations, and at the same time reveals important limitations in the current implicit solvent protein force field that must be sufficiently addressed for reliable description of long-range structural features of the disordered ensembles. '),
(87122, 2015, 'plos', 'Power laws for heavy-tailed distributions: modeling allele and haplotype diversity for the national marrow donor program', 'Slater, Noa|Louzoun, Yoram|Gragert, Loren|Maiers, Martin|Chatterjee, Ansu|Albrecht, Mark', 'Gonda Brain Research Center, Bar-Ilan University, Ramat Gan, Israel.|Gonda Brain Research Center, Bar-Ilan University, Ramat Gan, Israel, Department of Mathematics, Bar-Ilan University, Ramat Gan, Israel.|National Marrow Donor Program, Minneapolis, Minnesota, United States of America.|National Marrow Donor Program, Minneapolis, Minnesota, United States of America.|School of Statistics, University of Minnesota, Minneapolis, Minnesota, United States of America.|National Marrow Donor Program, Minneapolis, Minnesota, United States of America.', 'Israel|Israel|United States|United States|United States|United States', 0, 'Algorithms|Alleles|Bone Marrow|Computational Biology|European Continental Ancestry Group|Gene Frequency|HLA Antigens|Haplotypes|Humans|Models, Statistical|Registries|Tissue Donors', 'Journal Article', '10.1371/journal.pcbi.1004204', '25901749', 'Measures of allele and haplotype diversity, which are fundamental properties in population genetics, often follow heavy tailed distributions. These measures are of particular interest in the field of hematopoietic stem cell transplant (HSCT). Donor/Recipient suitability for HSCT is determined by Human Leukocyte Antigen (HLA) similarity. Match predictions rely upon a precise description of HLA diversity, yet classical estimates are inaccurate given the heavy-tailed nature of the distribution. This directly affects HSCT matching and diversity measures in broader fields such as species richness. We, therefore, have developed a power-law based estimator to measure allele and haplotype diversity that accommodates heavy tails using the concepts of regular variation and occupancy distributions. Application of our estimator to 6.59 million donors in the Be The Match Registry revealed that haplotypes follow a heavy tail distribution across all ethnicities: for example, 44.65% of the European American haplotypes are represented by only 1 individual. Indeed, our discovery rate of all U.S. European American haplotypes is estimated at 23.45% based upon sampling 3.97% of the population, leaving a large number of unobserved haplotypes. Population coverage, however, is much higher at 99.4% given that 90% of European Americans carry one of the 4.5% most frequent haplotypes. Alleles were found to be less diverse suggesting the current registry represents most alleles in the population. Thus, for HSCT registries, haplotype discovery will remain high with continued recruitment to a very deep level of sampling, but population coverage will not. Finally, we compared the convergence of our power-law versus classical diversity estimators such as Capture recapture, Chao, ACE and Jackknife methods. When fit to the haplotype data, our estimator displayed favorable properties in terms of convergence (with respect to sampling depth) and accuracy (with respect to diversity estimates). This suggests that power-law based estimators offer a valid alternative to classical diversity estimators and may have broad applicability in the field of population genetics. '),
(87123, 2015, 'plos', 'Spatial and functional heterogeneities shape collective behavior of tumor-immune networks', 'Wells, Daniel K|Chuang, Yishan|Knapp, Louis M|Brockmann, Dirk|Kath, William L|Leonard, Joshua N', 'Department of Engineering Sciences and Applied Mathematics, Northwestern University, Evanston, Illinois, United States of America, Northwestern University Physical Sciences-Oncology Center, Evanston, Illinois, United States of America.|Department of Chemical and Biological Engineering, Northwestern University, Evanston, Illinois, United States of America.|Department of Chemical and Biological Engineering, Northwestern University, Evanston, Illinois, United States of America.|Department of Engineering Sciences and Applied Mathematics, Northwestern University, Evanston, Illinois, United States of America, Northwestern University Physical Sciences-Oncology Center, Evanston, Illinois, United States of America, Robert H. Lurie Comprehensive Cancer Center, Northwestern University, Evanston, Illinois, United States of America, Northwestern Institute on Complex Science, Northwestern University, Evanston, Illinois, United States of America, Institute for Theoretical Biology, Humboldt University Berlin, Berlin, Germany.|Department of Engineering Sciences and Applied Mathematics, Northwestern University, Evanston, Illinois, United States of America, Northwestern University Physical Sciences-Oncology Center, Evanston, Illinois, United States of America, Robert H. Lurie Comprehensive Cancer Center, Northwestern University, Evanston, Illinois, United States of America, Northwestern Institute on Complex Science, Northwestern University, Evanston, Illinois, United States of America, Chemistry of Life Processes Institute, Northwestern University, Evanston, Illinois, United States of America.|Northwestern University Physical Sciences-Oncology Center, Evanston, Illinois, United States of America, Department of Chemical and Biological Engineering, Northwestern University, Evanston, Illinois, United States of America, Robert H. Lurie Comprehensive Cancer Center, Northwestern University, Evanston, Illinois, United States of America, Chemistry of Life Processes Institute, Northwestern University, Evanston, Illinois, United States of America.', 'United States|United States|United States|Germany|United States|United States', 0, 'Algorithms|Cell- and Tissue-Based Therapy|Computational Biology|Computer Simulation|Cytokines|Humans|Macrophages|Models, Immunological|Neoplasms', 'Journal Article', '10.1371/journal.pcbi.1004181', '25905470', 'Tumor growth involves a dynamic interplay between cancer cells and host cells, which collectively form a tumor microenvironmental network that either suppresses or promotes tumor growth under different conditions. The transition from tumor suppression to tumor promotion is mediated by a tumor-induced shift in the local immune state, and despite the clinical challenge this shift poses, little is known about how such dysfunctional immune states are initiated. Clinical and experimental observations have indicated that differences in both the composition and spatial distribution of different cell types and/or signaling molecules within the tumor microenvironment can strongly impact tumor pathogenesis and ultimately patient prognosis. How such functional and spatial heterogeneities confer such effects, however, is not known. To investigate these phenomena at a level currently inaccessible by direct observation, we developed a computational model of a nascent metastatic tumor capturing salient features of known tumor-immune interactions that faithfully recapitulates key features of existing experimental observations. Surprisingly, over a wide range of model formulations, we observed that heterogeneity in both spatial organization and cell phenotype drove the emergence of immunosuppressive network states. We determined that this observation is general and robust to parameter choice by developing a systems-level sensitivity analysis technique, and we extended this analysis to generate other parameter-independent, experimentally testable hypotheses. Lastly, we leveraged this model as an in silico test bed to evaluate potential strategies for engineering cell-based therapies to overcome tumor associated immune dysfunction and thereby identified modes of immune modulation predicted to be most effective. Collectively, this work establishes a new integrated framework for investigating and modulating tumor-immune networks and provides insights into how such interactions may shape early stages of tumor formation. '),
(87124, 2015, 'plos', 'Ten simple rules for reducing overoptimistic reporting in methodological computational research', 'Boulesteix, Anne-Laure', 'Institute for Medical Informatics, Biometry and Epidemiology, Ludwig Maximilians University, Munich, Germany.', 'Germany', 23, 'Computational Biology|Databases, Factual|Humans|Research Design', 'Editorial', '10.1371/journal.pcbi.1004191', '25905639', '-'),
(87125, 2015, 'plos', 'Disentangling the Complexity of HGF Signaling by Combining Qualitative and Quantitative Modeling', 'DAlessandro, Lorenza A|Samaga, Regina|Maiwald, Tim|Rho, Seong-Hwan|Bonefas, Sandra|Raue, Andreas|Iwamoto, Nao|Kienast, Alexandra|Waldow, Katharina|Meyer, Rene|Schilling, Marcel|Timmer, Jens|Klamt, Steffen|Klingmüller, Ursula', 'Division Systems Biology of Signal Transduction, German Cancer Research Center (DKFZ), INF 280, Heidelberg, Germany.|Max Planck Institute for Dynamics of Complex Technical Systems, Magdeburg, Germany.|Institute of Physics, University of Freiburg, Freiburg, Germany, BIOSS Centre for Biological Signalling Studies, University of Freiburg, Freiburg, Germany.|Institute of Physics, University of Freiburg, Freiburg, Germany, BIOSS Centre for Biological Signalling Studies, University of Freiburg, Freiburg, Germany.|Division Systems Biology of Signal Transduction, German Cancer Research Center (DKFZ), INF 280, Heidelberg, Germany.|Institute of Physics, University of Freiburg, Freiburg, Germany, BIOSS Centre for Biological Signalling Studies, University of Freiburg, Freiburg, Germany, Merrimack Pharmaceuticals, Inc., Cambridge, Massachusetts, United States of America.|Division Systems Biology of Signal Transduction, German Cancer Research Center (DKFZ), INF 280, Heidelberg, Germany.|Division Systems Biology of Signal Transduction, German Cancer Research Center (DKFZ), INF 280, Heidelberg, Germany.|Division Systems Biology of Signal Transduction, German Cancer Research Center (DKFZ), INF 280, Heidelberg, Germany.|Division Systems Biology of Signal Transduction, German Cancer Research Center (DKFZ), INF 280, Heidelberg, Germany.|Division Systems Biology of Signal Transduction, German Cancer Research Center (DKFZ), INF 280, Heidelberg, Germany.|Institute of Physics, University of Freiburg, Freiburg, Germany, BIOSS Centre for Biological Signalling Studies, University of Freiburg, Freiburg, Germany.|Max Planck Institute for Dynamics of Complex Technical Systems, Magdeburg, Germany.|Division Systems Biology of Signal Transduction, German Cancer Research Center (DKFZ), INF 280, Heidelberg, Germany.', 'Germany|Germany|Germany|Germany|Germany|Germany|Germany|Germany|Germany|Germany|Germany|Germany|Germ', 0, 'Animals|Cells, Cultured|Computer Simulation|Hepatocyte Growth Factor|Hepatocytes|Liver Regeneration|MAP Kinase Signaling System|Mice|Models, Biological|Phosphatidylinositol 3-Kinases|Proto-Oncogene Proteins c-akt', 'Journal Article', '10.1371/journal.pcbi.1004192', '25905717', 'Signaling pathways are characterized by crosstalk, feedback and feedforward mechanisms giving rise to highly complex and cell-context specific signaling networks. Dissecting the underlying relations is crucial to predict the impact of targeted perturbations. However, a major challenge in identifying cell-context specific signaling networks is the enormous number of potentially possible interactions. Here, we report a novel hybrid mathematical modeling strategy to systematically unravel hepatocyte growth factor (HGF) stimulated phosphoinositide-3-kinase (PI3K) and mitogen activated protein kinase (MAPK) signaling, which critically contribute to liver regeneration. By combining time-resolved quantitative experimental data generated in primary mouse hepatocytes with interaction graph and ordinary differential equation modeling, we identify and experimentally validate a network structure that represents the experimental data best and indicates specific crosstalk mechanisms. Whereas the identified network is robust against single perturbations, combinatorial inhibition strategies are predicted that result in strong reduction of Akt and ERK activation. Thus, by capitalizing on the advantages of the two modeling approaches, we reduce the high combinatorial complexity and identify cell-context specific signaling networks. '),
(87126, 2015, 'plos', 'Bacterial temporal dynamics enable optimal design of antibiotic treatment', 'Meredith, Hannah R|Lopatkin, Allison J|Anderson, Deverick J|You, Lingchong', '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.|Division of Infectious Diseases, Department of Medicine, Duke University Medical Center, Durham, North Carolina, United States of America, Duke Infection Control Outreach Network, Duke University Medical Center, Durham, North Carolina, United States of America.|Department of Biomedical Engineering, Duke University, Durham, North Carolina, United States of America, Center for Systems Biology, Duke University, Durham, North Carolina, United States of America, Center for Genomic and Computational Biology, Duke University, Durham, North Carolina, United States of America.', 'United States|United States|United States|United States', 16, 'Bacterial Physiological Phenomena|Cell Survival|Computer Simulation|Dose-Response Relationship, Drug|Drug Administration Schedule|Drug Therapy, Computer-Assisted|Models, Biological|Time Factors|beta-Lactam Resistance|beta-Lactamases|beta-Lactams', 'Journal Article', '10.1371/journal.pcbi.1004201', '25905796', 'There is a critical need to better use existing antibiotics due to the urgent threat of antibiotic resistant bacteria coupled with the reduced effort in developing new antibiotics. xcexb2-lactam antibiotics represent one of the most commonly used classes of antibiotics to treat a broad spectrum of Gram-positive and -negative bacterial pathogens. However, the rise of extended spectrum xcexb2-lactamase (ESBL) producing bacteria has limited the use of xcexb2-lactams. Due to the concern of complex drug responses, many xcexb2-lactams are typically ruled out if ESBL-producing pathogens are detected, even if these pathogens test as susceptible to some xcexb2-lactams. Using quantitative modeling, we show that xcexb2-lactams could still effectively treat pathogens producing low or moderate levels of ESBLs when administered properly. We further develop a metric to guide the design of a dosing protocol to optimize treatment efficiency for any antibiotic-pathogen combination. Ultimately, optimized dosing protocols could allow reintroduction of a repertoire of first-line antibiotics with improved treatment outcomes and preserve last-resort antibiotics. '),
(87127, 2015, 'plos', 'Thermal stabilization of dihydrofolate reductase using monte carlo unfolding simulations and its functional consequences', 'Tian, Jian|Woodard, Jaie C|Whitney, Anna|Shakhnovich, Eugene I', 'Department of Chemistry and Chemical Biology, Harvard University, Cambridge, Massachusetts, United States of America, Biotechnology Research Institute, Chinese Academy of Agricultural Sciences, Beijing, China.|Graduate Program in Biophysics, Harvard University, Cambridge, Massachusetts, United States of America.|Department of Chemistry and Chemical Biology, Harvard University, Cambridge, Massachusetts, United States of America.|Department of Chemistry and Chemical Biology, Harvard University, Cambridge, Massachusetts, United States of America.', 'China|United States|United States|United States', 0, 'Computer Simulation|Enzyme Stability|Models, Chemical|Models, Molecular|Models, Statistical|Monte Carlo Method|Mutagenesis, Site-Directed|Protein Conformation|Protein Denaturation|Protein Folding|Structure-Activity Relationship|Tetrahydrofolate Dehydrogenase|Transition Temperature', 'Journal Article', '10.1371/journal.pcbi.1004207', '25905910', 'Design of proteins with desired thermal properties is important for scientific and biotechnological applications. Here we developed a theoretical approach to predict the effect of mutations on protein stability from non-equilibrium unfolding simulations. We establish a relative measure based on apparent simulated melting temperatures that is independent of simulation length and, under certain assumptions, proportional to equilibrium stability, and we justify this theoretical development with extensive simulations and experimental data. Using our new method based on all-atom Monte-Carlo unfolding simulations, we carried out a saturating mutagenesis of Dihydrofolate Reductase (DHFR), a key target of antibiotics and chemotherapeutic drugs. The method predicted more than 500 stabilizing mutations, several of which were selected for detailed computational and experimental analysis. We find a highly significant correlation of r=0.65-0.68 between predicted and experimentally determined melting temperatures and unfolding denaturant concentrations for WT DHFR and 42 mutants. The correlation between energy of the native state and experimental denaturation temperature was much weaker, indicating the important role of entropy in protein stability. The most stabilizing point mutation was D27F, which is located in the active site of the protein, rendering it inactive. However for the rest of mutations outside of the active site we observed a weak yet statistically significant positive correlation between thermal stability and catalytic activity indicating the lack of a stability-activity tradeoff for DHFR. By combining stabilizing mutations predicted by our method, we created a highly stable catalytically active E. coli DHFR mutant with measured denaturation temperature 7.2°C higher than WT. Prediction results for DHFR and several other proteins indicate that computational approaches based on unfolding simulations are useful as a general technique to discover stabilizing mutations.'),
(87128, 2015, 'plos', 'A change in vaccine efficacy and duration of protection explains recent rises in pertussis incidence in the United States', 'Gambhir, Manoj|Clark, Thomas A|Cauchemez, Simon|Tartof, Sara Y|Swerdlow, David L|Ferguson, Neil M', 'Department of Epidemiology and Preventive Medicine, Monash University, Melbourne, Australia, Modeling Unit, National Center for Immunization and Respiratory Diseases (NCIRD), Centers for Disease Control and Prevention (CDC), Atlanta, Georgia, United States of America, IHRC, Inc., Atlanta, Georgia, United States of America.|Meningitis and Vaccine Preventable Diseases Branch, Division of Bacterial Diseases, NCIRD, CDC, Atlanta, Georgia, United States of America.|Medical Research Council Centre for Outbreak Analysis and Modelling, Imperial College London, London, United Kingdom, Mathematical Modelling of Infectious Diseases Unit, Institut Pasteur, Paris, France.|Kaiser Permanente Southern California, Kaiser Permanente Research, Department of Research & Evaluation, Pasadena, California, United States of America.|Modeling Unit, National Center for Immunization and Respiratory Diseases (NCIRD), Centers for Disease Control and Prevention (CDC), Atlanta, Georgia, United States of America, Office of Science and Integrative Programs, NCIRD, CDC, Atlanta, Georgia, United States of America.|Medical Research Council Centre for Outbreak Analysis and Modelling, Imperial College London, London, United Kingdom.', 'Australia|Georgia|France|United States|Georgia|United Kingdom', 61, 'Adolescent|Adult|Age Distribution|Child|Child, Preschool|Computer Simulation|Diphtheria-Tetanus-Pertussis Vaccine|Female|Humans|Immunization Schedule|Incidence|Infant|Infant, Newborn|Male|Models, Statistical|Population Surveillance|Risk Assessment|Treatment Outcome|United States|Vaccination|Vaccine Potency|Whooping Cough|Young Adult', 'Journal Article', '10.1371/journal.pcbi.1004138', '25906150', 'Over the past ten years the incidence of pertussis in the United States (U.S.) has risen steadily, with 2012 seeing the highest case number since 1955. There has also been a shift over the same time period in the age group reporting the largest number of cases (aside from infants), from adolescents to 7-11 year olds. We use epidemiological modelling and a large case incidence dataset to explain the upsurge. We investigate several hypotheses for the upsurge in pertussis cases by fitting a suite of dynamic epidemiological models to incidence data from the National Notifiable Disease Surveillance System (NNDSS) between 1990-2009, as well as incidence data from a variety of sources from 1950-1989. We find that: the best-fitting model is one in which vaccine efficacy and duration of protection of the acellular pertussis (aP) vaccine is lower than that of the whole-cell (wP) vaccine, (efficacy of the first three doses 80% [95% CI: 78%, 82%] versus 90% [95% CI: 87%, 94%]), increasing the rate at which disease is reported to NNDSS is not sufficient to explain the upsurge and 3) 2010-2012 disease incidence is predicted well. In this study, we use all available U.S. surveillance data to: 1) fit a set of mathematical models and determine which best explains these data and 2) determine the epidemiological and vaccine-related parameter values of this model. We find evidence of a difference in efficacy and duration of protection between the two vaccine types, wP and aP (aP efficacy and duration lower than wP). Future refinement of the model presented here will allow for an exploration of alternative vaccination strategies such as different age-spacings, further booster doses, and cocooning. '),
(87129, 2015, 'plos', 'Ten simple rules for a community computational challenge', 'Friedberg, Iddo|Wass, Mark N|Mooney, Sean D|Radivojac, Predrag', 'Department of Microbiology, Miami University, Oxford, Ohio, United States of America, Department of Computer Science and Software Engineering, Miami University, Oxford, Ohio, United States of America.|Centre for Molecular Processing, School of Biosciences, University of Kent, Canterbury, Kent, United Kingdom.|The Buck Institute for Research on Aging, Novato, California, United States of America.|Department of Computer Science and Informatics, Indiana University, Bloomington, Indiana, United States of America.', 'United States|United Kingdom|United States|India', 5, 'Algorithms|Awards and Prizes|Computational Biology|Marketing|Problem Solving|Research|Societies, Scientific', 'Editorial', '10.1371/journal.pcbi.1004150', '25906249', '-'),
(87130, 2015, 'plos', 'Multiplex Eukaryotic Transcription (In)activation: Timing, Bursting and Cycling of a Ratchet Clock Mechanism', 'Rybakova, Katja N|Bruggeman, Frank J|Tomaszewska, Aleksandra|Moné, Martijn J|Carlberg, Carsten|Westerhoff, Hans V', 'Molecular Cell Physiology, VU University Amsterdam, Amsterdam, The Netherlands.|Systems Bioinformatics, VU University Amsterdam, Amsterdam, The Netherlands.|School of Medicine, Institute of Biomedicine, University of Eastern Finland, Kuopio, Finland.|Molecular Cell Physiology, VU University Amsterdam, Amsterdam, The Netherlands.|School of Medicine, Institute of Biomedicine, University of Eastern Finland, Kuopio, Finland.|Molecular Cell Physiology, VU University Amsterdam, Amsterdam, The Netherlands, Manchester Centre for Integrative Systems Biology, University of Manchester, Manchester, United Kingdom, Synthetic Systems Biology, Netherlands Institute for Systems Biology, University of Amsterdam, Amsterdam, The Netherlands.', 'Netherlands|Netherlands|Finland|Netherlands|Finland|United Kingdom', 0, 'Biological Clocks|Computer Simulation|Models, Genetic|Models, Statistical|RNA, Messenger|Transcription Factors|Transcription, Genetic|Transcriptional Activation', 'Journal Article', '10.1371/journal.pcbi.1004236', '25909187', 'Activation of eukaryotic transcription is an intricate process that relies on a multitude of regulatory proteins forming complexes on chromatin. Chromatin modifications appear to play a guiding role in protein-complex assembly on chromatin. Together, these processes give rise to stochastic, often bursting, transcriptional activity. Here we present a model of eukaryotic transcription that aims to integrate those mechanisms. We use stochastic and ordinary-differential-equation modeling frameworks to examine various possible mechanisms of gene regulation by multiple transcription factors. We find that the assembly of large transcription factor complexes on chromatin via equilibrium-binding mechanisms is highly inefficient and insensitive to concentration changes of single regulatory proteins. An alternative model that lacks these limitations is a cyclic ratchet mechanism. In this mechanism, small protein complexes assemble sequentially on the promoter. Chromatin modifications mark the completion of a protein complex assembly, and sensitize the local chromatin for the assembly of the next protein complex. In this manner, a strict order of protein complex assemblies is attained. Even though the individual assembly steps are highly stochastic in duration, a sequence of them gives rise to a remarkable precision of the transcription cycle duration. This mechanism explains how transcription activation cycles, lasting for tens of minutes, derive from regulatory proteins residing on chromatin for only tens of seconds. Transcriptional bursts are an inherent feature of such transcription activation cycles. Bursting transcription can cause individual cells to remain in synchrony transiently, offering an explanation of transcriptional cycling as observed in cell populations, both on promoter chromatin status and mRNA levels. '),
(87131, 2015, 'plos', 'Quantifying spike train oscillations: biases, distortions and solutions', 'Matzner, Ayala|Bar-Gad, Izhar', 'The Leslie & Susan Goldschmied (Gonda) Multidisciplinary Brain Research Center, Bar-Ilan University, Ramat-Gan, Israel.|The Leslie & Susan Goldschmied (Gonda) Multidisciplinary Brain Research Center, Bar-Ilan University, Ramat-Gan, Israel.', 'Israel|Israel', 7, 'Action Potentials|Algorithms|Animals|Artifacts|Biological Clocks|Brain|Electroencephalography|Macaca fascicularis|Parkinson Disease|Reproducibility of Results|Sensitivity and Specificity', 'Journal Article', '10.1371/journal.pcbi.1004252', '25909328', 'Estimation of the power spectrum is a common method for identifying oscillatory changes in neuronal activity. However, the stochastic nature of neuronal activity leads to severe biases in the estimation of these oscillations in single unit spike trains. Different biological and experimental factors cause the spike train to differentially reflect its underlying oscillatory rate function. We analyzed the effect of factors, such as the mean firing rate and the recording duration, on the detectability of oscillations and their significance, and tested these theoretical results on experimental data recorded in Parkinsonian non-human primates. The effect of these factors is dramatic, such that in some conditions, the detection of existing oscillations is impossible. Moreover, these biases impede the comparison of oscillations across brain regions, neuronal types, behavioral states and separate recordings with different underlying parameters, and lead inevitably to a gross misinterpretation of experimental results. We introduce a novel objective measure, the modulation index, which overcomes these biases, and enables reliable detection of oscillations from spike trains and a direct estimation of the oscillation magnitude. The modulation index detects a high percentage of oscillations over a wide range of parameters, compared to classical spectral analysis methods, and enables an unbiased comparison between spike trains recorded from different neurons and using different experimental protocols. '),
(87132, 2015, 'plos', 'Non-linear Membrane Properties in Entorhinal Cortical Stellate Cells Reduce Modulation of Input-Output Responses by Voltage Fluctuations', 'Fernandez, Fernando R|Malerba, Paola|White, John A', 'Department of Bioengineering, University of Utah, Salt Lake City, Utah, United States of America.|Department of Bioengineering, University of Utah, Salt Lake City, Utah, United States of America.|Department of Bioengineering, University of Utah, Salt Lake City, Utah, United States of America.', 'United States|United States|United States', 0, 'Action Potentials|Animals|Cell Membrane|Cells, Cultured|Computer Simulation|Entorhinal Cortex|Interneurons|Male|Membrane Potentials|Models, Neurological|Nonlinear Dynamics|Rats|Rats, Long-Evans|Synaptic Transmission', 'Journal Article', '10.1371/journal.pcbi.1004188', '25909971', 'The presence of voltage fluctuations arising from synaptic activity is a critical component in models of gain control, neuronal output gating, and spike rate coding. The degree to which individual neuronal input-output functions are modulated by voltage fluctuations, however, is not well established across different cortical areas. Additionally, the extent and mechanisms of input-output modulation through fluctuations have been explored largely in simplified models of spike generation, and with limited consideration for the role of non-linear and voltage-dependent membrane properties. To address these issues, we studied fluctuation-based modulation of input-output responses in medial entorhinal cortical (MEC) stellate cells of rats, which express strong sub-threshold non-linear membrane properties. Using in vitro recordings, dynamic clamp and modeling, we show that the modulation of input-output responses by random voltage fluctuations in stellate cells is significantly limited. In stellate cells, a voltage-dependent increase in membrane resistance at sub-threshold voltages mediated by Na+ conductance activation limits the ability of fluctuations to elicit spikes. Similarly, in exponential leaky integrate-and-fire models using a shallow voltage-dependence for the exponential term that matches stellate cell membrane properties, a low degree of fluctuation-based modulation of input-output responses can be attained. These results demonstrate that fluctuation-based modulation of input-output responses is not a universal feature of neurons and can be significantly limited by subthreshold voltage-gated conductances. '),
(87133, 2015, 'plos', 'Automated Processing of Imaging Data through Multi-tiered Classification of Biological Structures Illustrated Using Caenorhabditis elegans', 'Zhan, Mei|Crane, Matthew M|Entchev, Eugeni V|Caballero, Antonio|Fernandes de Abreu, Diana Andrea|Chng, QueeLim|Lu, Hang', 'Interdisciplinary Program in Bioengineering, Georgia Institute of Technology, Atlanta, Georgia, United States of America, Wallace H. Coulter Department of Biomedical Engineering, Georgia Institute of Technology, Atlanta, Georgia, United States of America.|Interdisciplinary Program in Bioengineering, Georgia Institute of Technology, Atlanta, Georgia, United States of America.|MRC Centre for Developmental Neurobiology, Kings College London, London, United Kingdom.|MRC Centre for Developmental Neurobiology, Kings College London, London, United Kingdom.|MRC Centre for Developmental Neurobiology, Kings College London, London, United Kingdom.|MRC Centre for Developmental Neurobiology, Kings College London, London, United Kingdom.|Interdisciplinary Program in Bioengineering, Georgia Institute of Technology, Atlanta, Georgia, United States of America, Wallace H. Coulter Department of Biomedical Engineering, Georgia Institute of Technology, Atlanta, Georgia, United States of America, School of Chemical & Biomolecular Engineering, Georgia Institute of Technology, Atlanta, Georgia, United States of America.', 'Georgia|Georgia|United Kingdom|United Kingdom|United Kingdom|United Kingdom|Georgia', 16, 'Algorithms|Animals|Caenorhabditis elegans|Cell Tracking|Head|Image Interpretation, Computer-Assisted|Machine Learning|Microscopy, Fluorescence|Multimodal Imaging|Pattern Recognition, Automated|Reproducibility of Results|Sensitivity and Specificity', 'Journal Article', '10.1371/journal.pcbi.1004194', '25910032', 'Quantitative imaging has become a vital technique in biological discovery and clinical diagnostics, a plethora of tools have recently been developed to enable new and accelerated forms of biological investigation. Increasingly, the capacity for high-throughput experimentation provided by new imaging modalities, contrast techniques, microscopy tools, microfluidics and computer controlled systems shifts the experimental bottleneck from the level of physical manipulation and raw data collection to automated recognition and data processing. Yet, despite their broad importance, image analysis solutions to address these needs have been narrowly tailored. Here, we present a generalizable formulation for autonomous identification of specific biological structures that is applicable for many problems. The process flow architecture we present here utilizes standard image processing techniques and the multi-tiered application of classification models such as support vector machines (SVM). These low-level functions are readily available in a large array of image processing software packages and programming languages. Our framework is thus both easy to implement at the modular level and provides specific high-level architecture to guide the solution of more complicated image-processing problems. We demonstrate the utility of the classification routine by developing two specific classifiers as a toolset for automation and cell identification in the model organism Caenorhabditis elegans. To serve a common need for automated high-resolution imaging and behavior applications in the C. elegans research community, we contribute a ready-to-use classifier for the identification of the head of the animal under bright field imaging. Furthermore, we extend our framework to address the pervasive problem of cell-specific identification under fluorescent imaging, which is critical for biological investigation in multicellular organisms or tissues. Using these examples as a guide, we envision the broad utility of the framework for diverse problems across different length scales and imaging methods. '),
(87134, 2015, 'plos', 'Bud-Localization of CLB2 mRNA Can Constitute a Growth Rate Dependent Daughter Sizer', 'Spiesser, Thomas W|Kühn, Clemens|Krantz, Marcus|Klipp, Edda', 'Theoretical Biophysics, Humboldt-Universität zu Berlin, Berlin, Germany.|Theoretical Biophysics, Humboldt-Universität zu Berlin, Berlin, Germany.|Theoretical Biophysics, Humboldt-Universität zu Berlin, Berlin, Germany.|Theoretical Biophysics, Humboldt-Universität zu Berlin, Berlin, Germany.', 'Germany|Germany|Germany|Germany', 6, 'Cell Cycle Checkpoints|Cell Enlargement|Computer Simulation|Cyclin B|Models, Biological|RNA, Messenger|Saccharomyces cerevisiae|Saccharomyces cerevisiae Proteins|Subcellular Fractions', 'Journal Article', '10.1371/journal.pcbi.1004223', '25910075', 'Maintenance of cellular size is a fundamental systems level process that requires balancing of cell growth with proliferation. This is achieved via the cell division cycle, which is driven by the sequential accumulation and destruction of cyclins. The regulatory network around these cyclins, particularly in G1, has been interpreted as a size control network in budding yeast, and cell size as being decisive for the START transition. However, it is not clear why disruptions in the G1 network may lead to altered size rather than loss of size control, or why the S-G2-M duration also depends on nutrients. With a mathematical population model comprised of individually growing cells, we show that cyclin translation would suffice to explain the observed growth rate dependence of cell volume at START. Moreover, we assess the impact of the observed bud-localisation of the G2 cyclin CLB2 mRNA, and find that localised cyclin translation could provide an efficient mechanism for measuring the biosynthetic capacity in specific compartments: The mother in G1, and the growing bud in G2. Hence, iteration of the same principle can ensure that the mother cell is strong enough to grow a bud, and that the bud is strong enough for independent life. Cell sizes emerge in the model, which predicts that a single CDK-cyclin pair per growth phase suffices for size control in budding yeast, despite the necessity of the cell cycle network around the cyclins to integrate other cues. Size control seems to be exerted twice, where the G2/M control affects bud size through bud-localized translation of CLB2 mRNA, explaining the dependence of the S-G2-M duration on nutrients. Taken together, our findings suggest that cell size is an emergent rather than a regulatory property of the network linking growth and proliferation. ');
INSERT INTO `papers` (`id`, `ano`, `journal`, `titulo`, `autores`, `afiliacao`, `pais`, `citacoes`, `palavra_chave`, `categorias`, `doi`, `pubmed`, `abstract`) VALUES
(87135, 2015, 'plos', 'Mixed signal learning by spike correlation propagation in feedback inhibitory circuits', 'Hiratani, Naoki|Fukai, Tomoki', 'Department of Complexity Science and Engineering, The University of Tokyo, Kashiwa, Chiba, Japan, Laboratory for Neural Circuit Theory, RIKEN Brain Science Institute, Wako, Saitama, Japan.|Laboratory for Neural Circuit Theory, RIKEN Brain Science Institute, Wako, Saitama, Japan.', 'Japan|Japan', 0, 'Action Potentials|Animals|Computer Simulation|Feedback, Physiological|Humans|Learning|Models, Neurological|Models, Statistical|Nerve Net|Neural Inhibition|Statistics as Topic|Synaptic Transmission', 'Journal Article', '10.1371/journal.pcbi.1004227', '25910189', 'The brain can learn and detect mixed input signals masked by various types of noise, and spike-timing-dependent plasticity (STDP) is the candidate synaptic level mechanism. Because sensory inputs typically have spike correlation, and local circuits have dense feedback connections, input spikes cause the propagation of spike correlation in lateral circuits, however, it is largely unknown how this secondary correlation generated by lateral circuits influences learning processes through STDP, or whether it is beneficial to achieve efficient spike-based learning from uncertain stimuli. To explore the answers to these questions, we construct models of feedforward networks with lateral inhibitory circuits and study how propagated correlation influences STDP learning, and what kind of learning algorithm such circuits achieve. We derive analytical conditions at which neurons detect minor signals with STDP, and show that depending on the origin of the noise, different correlation timescales are useful for learning. In particular, we show that non-precise spike correlation is beneficial for learning in the presence of cross-talk noise. We also show that by considering excitatory and inhibitory STDP at lateral connections, the circuit can acquire a lateral structure optimal for signal detection. In addition, we demonstrate that the model performs blind source separation in a manner similar to the sequential sampling approximation of the Bayesian independent component analysis algorithm. Our results provide a basic understanding of STDP learning in feedback circuits by integrating analyses from both dynamical systems and information theory. '),
(87136, 2015, 'plos', 'Existence and control of Go/No-Go decision transition threshold in the striatum', 'Bahuguna, Jyotika|Aertsen, Ad|Kumar, Arvind', 'Bernstein Center Freiburg and Faculty of Biology, University of Freiburg, Freiburg, Germany, Computational Biology, School of Computer Science and Communication, KTH Royal Institute of Technology, Stockholm, Sweden.|Bernstein Center Freiburg and Faculty of Biology, University of Freiburg, Freiburg, Germany.|Bernstein Center Freiburg and Faculty of Biology, University of Freiburg, Freiburg, Germany, Computational Biology, School of Computer Science and Communication, KTH Royal Institute of Technology, Stockholm, Sweden.', 'Germany|Germany|Germany', 0, 'Action Potentials|Animals|Computer Simulation|Corpus Striatum|Decision Making|Dopaminergic Neurons|Humans|Models, Neurological|Nerve Net|Receptors, Dopamine', 'Journal Article', '10.1371/journal.pcbi.1004233', '25910230', 'A typical Go/No-Go decision is suggested to be implemented in the brain via the activation of the direct or indirect pathway in the basal ganglia. Medium spiny neurons (MSNs) in the striatum, receiving input from cortex and projecting to the direct and indirect pathways express D1 and D2 type dopamine receptors, respectively. Recently, it has become clear that the two types of MSNs markedly differ in their mutual and recurrent connectivities as well as feedforward inhibition from FSIs. Therefore, to understand striatal function in action selection, it is of key importance to identify the role of the distinct connectivities within and between the two types of MSNs on the balance of their activity. Here, we used both a reduced firing rate model and numerical simulations of a spiking network model of the striatum to analyze the dynamic balance of spiking activities in D1 and D2 MSNs. We show that the asymmetric connectivity of the two types of MSNs renders the striatum into a threshold device, indicating the state of cortical input rates and correlations by the relative activity rates of D1 and D2 MSNs. Next, we describe how this striatal threshold can be effectively modulated by the activity of fast spiking interneurons, by the dopamine level, and by the activity of the GPe via pallidostriatal backprojections. We show that multiple mechanisms exist in the basal ganglia for biasing striatal output in favour of either the `Go or the `No-Go pathway. This new understanding of striatal network dynamics provides novel insights into the putative role of the striatum in various behavioral deficits in patients with Parkinsons disease, including increased reaction times, L-Dopa-induced dyskinesia, and deep brain stimulation-induced impulsivity. '),
(87137, 2015, 'plos', 'Dual dimensionality reduction reveals independent encoding of motor features in a muscle synergy for insect flight control', 'Sponberg, Simon|Daniel, Thomas L|Fairhall, Adrienne L', 'Department of Biology, Univ. of Washington, Seattle, Washington, United States of America, Department of Physiology & Biophysics, Univ. of Washington, Seattle, Washington, United States of America.|Department of Biology, Univ. of Washington, Seattle, Washington, United States of America, Institute for Neuroengineering, Univ. of Washington, Seattle, Washington, United States of America, Program in Neuroscience, Univ. of Washington, Seattle, Washington, United States of America.|Department of Physiology & Biophysics, Univ. of Washington, Seattle, Washington, United States of America, Institute for Neuroengineering, Univ. of Washington, Seattle, Washington, United States of America, Program in Neuroscience, Univ. of Washington, Seattle, Washington, United States of America.', 'United States|United States|United States', 0, 'Animals|Computer Simulation|Feedback, Physiological|Flight, Animal|Manduca|Models, Neurological|Models, Statistical|Muscle Contraction|Muscle, Skeletal|Postural Balance|Wings, Animal', 'Journal Article', '10.1371/journal.pcbi.1004168', '25919482', 'What are the features of movement encoded by changing motor commands? Do motor commands encode movement independently or can they be represented in a reduced set of signals (i.e. synergies)? Motor encoding poses a computational and practical challenge because many muscles typically drive movement, and simultaneous electrophysiology recordings of all motor commands are typically not available. Moreover, during a single locomotor period (a stride or wingstroke) the variation in movement may have high dimensionality, even if only a few discrete signals activate the muscles. Here, we apply the method of partial least squares (PLS) to extract the encoded features of movement based on the cross-covariance of motor signals and movement. PLS simultaneously decomposes both datasets and identifies only the variation in movement that relates to the specific muscles of interest. We use this approach to explore how the main downstroke flight muscles of an insect, the hawkmoth Manduca sexta, encode torque during yaw turns. We simultaneously record muscle activity and turning torque in tethered flying moths experiencing wide-field visual stimuli. We ask whether this pair of muscles acts as a muscle synergy (a single linear combination of activity) consistent with their hypothesized function of producing a left-right power differential. Alternatively, each muscle might individually encode variation in movement. We show that PLS feature analysis produces an efficient reduction of dimensionality in torque variation within a wingstroke. At first, the two muscles appear to behave as a synergy when we consider only their wingstroke-averaged torque. However, when we consider the PLS features, the muscles reveal independent encoding of torque. Using these features we can predictably reconstruct the variation in torque corresponding to changes in muscle activation. PLS-based feature analysis provides a general two-sided dimensionality reduction that reveals encoding in high dimensional sensory or motor transformations. '),
(87138, 2015, 'plos', 'Three-Dimensional Gradients of Cytokine Signaling between T Cells', 'Thurley, Kevin|Gerecht, Daniel|Friedmann, Elfriede|Hxc3xb6fer, Thomas', 'Division of Theoretical Systems Biology, German Cancer Research Center, Heidelberg, Germany, Institute for Theoretical Biology, Charitxc3xa9-Universitxc3xa4tsmedizin, Berlin, Germany, Department of Pharmaceutical Chemistry, University of California, San Francisco, San Francisco, California, United States of America.|Institute for Applied Mathematics, University of Heidelberg, Heidelberg, Germany.|Institute for Applied Mathematics, University of Heidelberg, Heidelberg, Germany.|Division of Theoretical Systems Biology, German Cancer Research Center, Heidelberg, Germany, Bioquant Center, University of Heidelberg, Heidelberg, Germany.', 'Germany|Germany|Germany|Germany', 34, 'Animals|Cells, Cultured|Computer Simulation|Diffusion|Humans|Immunological Synapses|Models, Immunological|Paracrine Communication|Receptors, Cytokine|T-Lymphocytes', 'Journal Article', '10.1371/journal.pcbi.1004206', '25923703', 'Immune responses are regulated by diffusible mediators, the cytokines, which act at sub-nanomolar concentrations. The spatial range of cytokine communication is a crucial, yet poorly understood, functional property. Both containment of cytokine action in narrow junctions between immune cells (immunological synapses) and global signaling throughout entire lymph nodes have been proposed, but the conditions under which they might occur are not clear. Here we analyze spatially three-dimensional reaction-diffusion models for the dynamics of cytokine signaling at two successive scales: in immunological synapses and in dense multicellular environments. For realistic parameter values, we observe local spatial gradients, with the cytokine concentration around secreting cells decaying sharply across only a few cell diameters. Focusing on the well-characterized T-cell cytokine interleukin-2, we show how cytokine secretion and competitive uptake determine this signaling range. Uptake is shaped locally by the geometry of the immunological synapse. However, even for narrow synapses, which favor intrasynaptic cytokine consumption, escape fluxes into the extrasynaptic space are expected to be substantial (xe2x89xa520% of secretion). Hence paracrine signaling will generally extend beyond the synapse but can be limited to cellular microenvironments through uptake by target cells or strong competitors, such as regulatory T cells. By contrast, long-range cytokine signaling requires a high density of cytokine producers or weak consumption (e.g., by sparsely distributed target cells). Thus in a physiological setting, cytokine gradients between cells, and not bulk-phase concentrations, are crucial for cell-to-cell communication, emphasizing the need for spatially resolved data on cytokine signaling. '),
(87139, 2015, 'plos', 'A Bayesian ensemble approach for epidemiological projections', 'Lindström, Tom|Tildesley, Michael|Webb, Colleen', 'Department of Physics, Chemistry and Biology, Linköping University, Linköping, Sweden, Department of Biology, Colorado State University, Fort Collins, Colorado, United States of America, US National Institute of Health, Bethesda, Maryland, United States of America, University of Exeter, Exeter, United Kingdom.|US National Institute of Health, Bethesda, Maryland, United States of America, School of Veterinary Medicine and Science, University of Nottingham, Leicestershire, United Kingdom.|Department of Biology, Colorado State University, Fort Collins, Colorado, United States of America, US National Institute of Health, Bethesda, Maryland, United States of America.', 'United Kingdom|United Kingdom|United States', 0, 'Algorithms|Animals|Bayes Theorem|Computer Simulation|Data Interpretation, Statistical|Disease Outbreaks|Foot-and-Mouth Disease|Humans|Incidence|Models, Statistical|Population Surveillance|Reproducibility of Results|Risk Factors|Sensitivity and Specificity|United Kingdom', 'Comparative Study', '10.1371/journal.pcbi.1004187', '25927892', 'Mathematical models are powerful tools for epidemiology and can be used to compare control actions. However, different models and model parameterizations may provide different prediction of outcomes. In other fields of research, ensemble modeling has been used to combine multiple projections. We explore the possibility of applying such methods to epidemiology by adapting Bayesian techniques developed for climate forecasting. We exemplify the implementation with single model ensembles based on different parameterizations of the Warwick model run for the 2001 United Kingdom foot and mouth disease outbreak and compare the efficacy of different control actions. This allows us to investigate the effect that discrepancy among projections based on different modeling assumptions has on the ensemble prediction. A sensitivity analysis showed that the choice of prior can have a pronounced effect on the posterior estimates of quantities of interest, in particular for ensembles with large discrepancy among projections. However, by using a hierarchical extension of the method we show that prior sensitivity can be circumvented. We further extend the method to include a priori beliefs about different modeling assumptions and demonstrate that the effect of this can have different consequences depending on the discrepancy among projections. We propose that the method is a promising analytical tool for ensemble modeling of disease outbreaks. '),
(87140, 2015, 'plos', 'Optimal Treatment Strategies in the Context of Treatment for Prevention against HIV-1 in Resource-Poor Settings', 'Duwal, Sulav|Winkelmann, Stefanie|Schütte, Christof|von Kleist, Max', 'Department of Mathematics and Computer Science, Freie Universität Berlin, Germany, Junior Research Group Systems Pharmacology & Disease Control|Department of Mathematics and Computer Science, Freie Universität Berlin, Germany.|Department of Mathematics and Computer Science, Freie Universität Berlin, Germany, Zuse Institute Berlin, Germany.|Department of Mathematics and Computer Science, Freie Universität Berlin, Germany, Junior Research Group Systems Pharmacology & Disease Control', 'Germany|Germany|Germany|Germany', 0, 'Computer Simulation|Decision Support Systems, Clinical|Disease Outbreaks|HIV Infections|HIV-1|Humans|Medically Underserved Area|Models, Statistical|South Africa|Stochastic Processes|Treatment Outcome', 'Journal Article', '10.1371/journal.pcbi.1004200', '25927964', 'An estimated 2.7 million new HIV-1 infections occurred in 2010. `Treatment-for-prevention may strongly prevent HIV-1 transmission. The basic idea is that immediate treatment initiation rapidly decreases virus burden, which reduces the number of transmittable viruses and thereby the probability of infection. However, HIV inevitably develops drug resistance, which leads to virus rebound and nullifies the effect of `treatment-for-prevention for the time it remains unrecognized. While timely conducted treatment changes may avert periods of viral rebound, necessary treatment options and diagnostics may be lacking in resource-constrained settings. Within this work, we provide a mathematical platform for comparing different treatment paradigms that can be applied to many medical phenomena. We use this platform to optimize two distinct approaches for the treatment of HIV-1: (i) a diagnostic-guided treatment strategy, based on infrequent and patient-specific diagnostic schedules and (ii) a pro-active strategy that allows treatment adaptation prior to diagnostic ascertainment. Both strategies are compared to current clinical protocols (standard of care and the HPTN052 protocol) in terms of patient health, economic means and reduction in HIV-1 onward transmission exemplarily for South Africa. All therapeutic strategies are assessed using a coarse-grained stochastic model of within-host HIV dynamics and pseudo-codes for solving the respective optimal control problems are provided. Our mathematical model suggests that both optimal strategies (i)-(ii) perform better than the current clinical protocols and no treatment in terms of economic means, life prolongation and reduction of HIV-transmission. The optimal diagnostic-guided strategy suggests rare diagnostics and performs similar to the optimal pro-active strategy. Our results suggest that treatment-for-prevention may be further improved using either of the two analyzed treatment paradigms. '),
(87141, 2015, 'plos', 'Ten simple (empirical) rules for writing science', 'Weinberger, Cody J|Evans, James A|Allesina, Stefano', 'Department of Ecology & Evolution, University of Chicago, Chicago, Illinois, United States of America.|Department of Sociology, University of Chicago, Chicago, Illinois, United States of America, Computation Institute, University of Chicago, Chicago, Illinois, United States of America.|Department of Ecology & Evolution, University of Chicago, Chicago, Illinois, United States of America, Computation Institute, University of Chicago, Chicago, Illinois, United States of America.', 'United States|United States|United States', 20, 'Algorithms|Manuscripts, Medical as Topic|Periodicals as Topic|Science|Writing', 'Editorial', '10.1371/journal.pcbi.1004205', '25928031', '-'),
(87142, 2015, 'plos', 'Short-range guiding can result in the formation of circular aggregates in myxobacteria populations', 'Janulevicius, Albertas|van Loosdrecht, Mark|Picioreanu, Cristian', 'Department of Biotechnology, Delft University of Technology, Delft, The Netherlands.|Department of Biotechnology, Delft University of Technology, Delft, The Netherlands.|Department of Biotechnology, Delft University of Technology, Delft, The Netherlands.', 'Netherlands|Netherlands|Netherlands', 0, 'Cell Communication|Computer Simulation|Models, Biological|Myxococcales', 'Journal Article', '10.1371/journal.pcbi.1004213', '25928112', 'Myxobacteria are social bacteria that upon starvation form multicellular fruiting bodies whose shape in different species can range from simple mounds to elaborate tree-like structures. The formation of fruiting bodies is a result of collective cell movement on a solid surface. In the course of development, groups of flexible rod-shaped cells form streams and move in circular or spiral patterns to form aggregation centers that can become sites of fruiting body formation. The mechanisms of such cell movement patterns are not well understood. It has been suggested that myxobacterial development depends on short-range contact-mediated interactions between individual cells, i.e. cell aggregation does not require long-range signaling in the population. In this study, by means of a computational mass-spring model, we investigate what types of short-range interactions between cells can result in the formation of streams and circular aggregates during myxobacterial development. We consider short-range head-to-tail guiding between individual cells, whereby movement direction of the head of one cell is affected by the nearby presence of the tail of another cell. We demonstrate that stable streams and circular aggregates can arise only when the trailing cell, in addition to being steered by the tail of the leading cell, is able to speed up to catch up with it. It is suggested that necessary head-to-tail interactions between cells can arise from physical adhesion, response to a diffusible substance or slime extruded by cells, or pulling by motility engine pili. Finally, we consider a case of long-range guiding between cells and show that circular aggregates are able to form without cells increasing speed. These findings present a possibility to discriminate between short-range and long-range guiding mechanisms in myxobacteria by experimentally measuring distribution of cell speeds in circular aggregates. '),
(87143, 2015, 'plos', 'Ten simple rules for a successful cross-disciplinary collaboration', 'Knapp, Bernhard|Bardenet, Rémi|Bernabeu, Miguel O|Bordas, Rafel|Bruna, Maria|Calderhead, Ben|Cooper, Jonathan|Fletcher, Alexander G|Groen, Derek|Kuijper, Bram|Lewis, Joanna|McInerny, Greg|Minssen, Timo|Osborne, James|Paulitschke, Verena|Pitt-Francis, Joe|Todoric, Jelena|Yates, Christian A|Gavaghan, David|Deane, Charlotte M', 'Department of Statistics, University of Oxford, Oxford, United Kingdom.|Department of Statistics, University of Oxford, Oxford, United Kingdom.|Centre for Computational Science, Department of Chemistry, University College London, London, United Kingdom, Centre for Mathematics, Physics and Engineering in the Life Sciences and Experimental Biology, University College London, London, United Kingdom.|Department of Computer Science, University of Oxford, Oxford, 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 Mathematics, Imperial College London, London, 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.|Centre for Computational Science, Department of Chemistry, University College London, London, United Kingdom.|Centre for Mathematics, Physics and Engineering in the Life Sciences and Experimental Biology, University College London, London, United Kingdom, Department of Genetics, Evolution and Environment, University College London, London, United Kingdom.|Centre for Mathematics, Physics and Engineering in the Life Sciences and Experimental Biology, University College London, London, United Kingdom.|Department of Computer Science, University of Oxford, Oxford, United Kingdom.|Centre for Information & Innovation Law, University of Copenhagen, Copenhagen, Denmark, Guest Scholar, Harvard Law School, Cambridge, Massachusetts, United States of America, Visiting Research Fellow, University of Oxford, Oxford, United Kingdom.|Department of Computer Science, University of Oxford, Oxford, United Kingdom.|Department of Dermatology, Medical University of Vienna, Vienna, Austria.|Department of Computer Science, University of Oxford, Oxford, United Kingdom.|Laboratory of Gene Regulation and Signal Transduction, Departments of Pharmacology and Pathology, University of California, California, San Diego, United States of America.|Department of Mathematical Sciences, University of Bath, Bath, United Kingdom.|Department of Computer Science, University of Oxford, Oxford, United Kingdom.|Department of Statistics, University of Oxford, Oxford, United Kingdom.', 'United Kingdom|United Kingdom|United Kingdom|United Kingdom|United Kingdom|United Kingdom|United Kin', 0, 'Algorithms|Cooperative Behavior|Interdisciplinary Communication|Interdisciplinary Studies|Leadership|Models, Organizational|Organizational Objectives|Science', 'Editorial', '10.1371/journal.pcbi.1004214', '25928184', '-'),
(87144, 2015, 'plos', 'Cell-specific cardiac electrophysiology models', 'Groenendaal, Willemijn|Ortega, Francis A|Kherlopian, Armen R|Zygmunt, Andrew C|Krogh-Madsen, Trine|Christini, David J', 'Greenberg Division of Cardiology, Weill Cornell Medical College, New York, New York, United States of America.|Department of Physiology and Biophysics, Weill Cornell Medical College, New York, New York, United States of America.|Department of Physiology and Biophysics, Weill Cornell Medical College, New York, New York, United States of America.|Consultant, New Hartford, New York, United States of America.|Greenberg Division of Cardiology, Weill Cornell Medical College, New York, New York, United States of America, Institute for Computational Biomedicine, Weill Cornell Medical College, New York, New York, United States of America.|Greenberg Division of Cardiology, Weill Cornell Medical College, New York, New York, United States of America, Department of Physiology and Biophysics, Weill Cornell Medical College, New York, New York, United States of America, Institute for Computational Biomedicine, Weill Cornell Medical College, New York, New York, United States of America.', 'United States|United States|United States|United States|United States|United States', 0, 'Action Potentials|Animals|Cells, Cultured|Computer Simulation|Heart Conduction System|Ion Channel Gating|Ion Channels|Membrane Potentials|Models, Cardiovascular|Models, Statistical|Myocytes, Cardiac|Swine', 'Journal Article', '10.1371/journal.pcbi.1004242', '25928268', 'The traditional cardiac model-building paradigm involves constructing a composite model using data collected from many cells. Equations are derived for each relevant cellular component (e.g., ion channel, exchanger) independently. After the equations for all components are combined to form the composite model, a subset of parameters is tuned, often arbitrarily and by hand, until the model output matches a target objective, such as an action potential. Unfortunately, such models often fail to accurately simulate behavior that is dynamically dissimilar (e.g., arrhythmia) to the simple target objective to which the model was fit. In this study, we develop a new approach in which data are collected via a series of complex electrophysiology protocols from single cardiac myocytes and then used to tune model parameters via a parallel fitting method known as a genetic algorithm (GA). The dynamical complexity of the electrophysiological data, which can only be fit by an automated method such as a GA, leads to more accurately parameterized models that can simulate rich cardiac dynamics. The feasibility of the method is first validated computationally, after which it is used to develop models of isolated guinea pig ventricular myocytes that simulate the electrophysiological dynamics significantly better than does a standard guinea pig model. In addition to improving model fidelity generally, this approach can be used to generate a cell-specific model. By so doing, the approach may be useful in applications ranging from studying the implications of cell-to-cell variability to the prediction of intersubject differences in response to pharmacological treatment. '),
(87145, 2015, 'plos', 'Estimating the In Vivo Killing Efficacy of Cytotoxic T Lymphocytes across Different Peptide-MHC Complex Densities', 'Garcia, Victor|Richter, Kirsten|Graw, Frederik|Oxenius, Annette|Regoes, Roland R', 'Institute of Integrative Biology, ETH Zurich, Universitätstr, Zurich, Switzerland.|Institute of Microbiology, ETH Zurich, Zurich, Switzerland.|Center for Modeling and Simulation in the Biosciences, Bio-Quant Center, Heidelberg University, Heidelberg, Germany.|Institute of Microbiology, ETH Zurich, Zurich, Switzerland.|Institute of Integrative Biology, ETH Zurich, Universitätstr, Zurich, Switzerland.', 'Switzerland|Switzerland|Germany|Switzerland|Switzerland', 0, 'Adoptive Transfer|Animals|Antigens, Viral|Computational Biology|Cytotoxicity, Immunologic|Epitopes|Host-Pathogen Interactions|Lymphocytic Choriomeningitis|Lymphocytic choriomeningitis virus|Major Histocompatibility Complex|Mice|Models, Immunological|Peptides|T-Lymphocytes, Cytotoxic|Viral Proteins', 'Journal Article', '10.1371/journal.pcbi.1004178', '25933039', 'Cytotoxic T lymphocytes (CTLs) are important agents in the control of intracellular pathogens, which specifically recognize and kill infected cells. Recently developed experimental methods allow the estimation of the CTLs efficacy in detecting and clearing infected host cells. One method, the in vivo killing assay, utilizes the adoptive transfer of antigen displaying target cells into the bloodstream of mice. Surprisingly, killing efficacies measured by this method are often much higher than estimates obtained by other methods based on, for instance, the dynamics of escape mutations. In this study, we investigated what fraction of this variation can be explained by differences in peptide loads employed in in vivo killing assays. We addressed this question in mice immunized with lymphocytic choriomeningitis virus (LCMV). We conducted in vivo killing assays varying the loads of the immunodominant epitope GP33 on target cells. Using a mathematical model, we determined the efficacy of effector and memory CTL, as well as CTL in chronically infected mice. We found that the killing efficacy is substantially reduced at lower peptide loads. For physiological peptide loads, our analysis predicts more than a factor 10 lower CTL efficacies than at maximum peptide loads. Assuming that the efficacy scales linearly with the frequency of CTL, a clear hierarchy emerges among the groups across all peptide antigen concentrations. The group of mice with chronic LCMV infections shows a consistently higher killing efficacy per CTL than the acutely infected mouse group, which in turn has a consistently larger efficacy than the memory mouse group. We conclude that CTL killing efficacy dependence on surface epitope frequencies can only partially explain the variation in in vivo killing efficacy estimates across experimental methods and viral systems, which vary about four orders of magnitude. In contrast, peptide load differences can explain at most two orders of magnitude. '),
(87146, 2015, 'plos', 'Quantification of Interactions between Dynamic Cellular Network Functionalities by Cascaded Layering', 'Prescott, Thomas P|Lang, Moritz|Papachristodoulou, Antonis', 'Department of Engineering Science, University of Oxford, Oxford, United Kingdom, Life Sciences Interface Doctoral Training Centre, University of Oxford, Oxford, United Kingdom.|Department of Biosystems Science and Engineering, ETH Zürich, Basel, Switzerland, Swiss Institute of Bioinformatics, Basel, Switzerland.|Department of Engineering Science, University of Oxford, Oxford, United Kingdom.', 'United Kingdom|Switzerland|United Kingdom', 8, 'Cells|Computational Biology|Models, Biological|Signal Transduction|Systems Biology', 'Journal Article', '10.1371/journal.pcbi.1004235', '25933116', 'Large, naturally evolved biomolecular networks typically fulfil multiple functions. When modelling or redesigning such systems, functional subsystems are often analysed independently first, before subsequent integration into larger-scale computational models. In the design and analysis process, it is therefore important to quantitatively analyse and predict the dynamics of the interactions between integrated subsystems, in particular, how the incremental effect of integrating a subsystem into a network depends on the existing dynamics of that network. In this paper we present a framework for simulating the contribution of any given functional subsystem when integrated together with one or more other subsystems. This is achieved through a cascaded layering of a network into functional subsystems, where each layer is defined by an appropriate subset of the reactions. We exploit symmetries in our formulation to exhaustively quantify each subsystems incremental effects with minimal computational effort. When combining subsystems, their isolated behaviour may be amplified, attenuated, or be subject to more complicated effects. We propose the concept of mutual dynamics to quantify such nonlinear phenomena, thereby defining the incompatibility and cooperativity between all pairs of subsystems when integrated into any larger network. We exemplify our theoretical framework by analysing diverse behaviours in three dynamic models of signalling and metabolic pathways: the effect of crosstalk mechanisms on the dynamics of parallel signal transduction pathways, reciprocal side-effects between several integral feedback mechanisms and the subsystems they stabilise, and consequences of nonlinear interactions between elementary flux modes in glycolysis for metabolic engineering strategies. Our analysis shows that it is not sufficient to just specify subsystems and analyse their pairwise interactions, the environment in which the interaction takes place must also be explicitly defined. Our framework provides a natural representation of nonlinear interaction phenomena, and will therefore be an important tool for modelling large-scale evolved or synthetic biomolecular networks. '),
(87147, 2015, 'plos', 'Predicting peptide-mediated interactions on a genome-wide scale', 'Chen, T Scott|Petrey, Donald|Garzon, Jose Ignacio|Honig, Barry', 'Howard Hughes Medical Institute, Columbia University, New York, New York, United States of America, Department of Systems Biology, Columbia University, New York, New York, United States of America, Department of Biochemistry and Molecular Biophysics, Columbia University, New York, New York, United States of America, Center for Computational Biology and Bioinformatics, Columbia University, New York, New York, United States of America.|Howard Hughes Medical Institute, Columbia University, New York, New York, United States of America, Department of Systems Biology, Columbia University, New York, New York, United States of America, Department of Biochemistry and Molecular Biophysics, Columbia University, New York, New York, United States of America, Center for Computational Biology and Bioinformatics, Columbia University, New York, New York, United States of America.|Howard Hughes Medical Institute, Columbia University, New York, New York, United States of America, Department of Systems Biology, Columbia University, New York, New York, United States of America, Department of Biochemistry and Molecular Biophysics, Columbia University, New York, New York, United States of America, Center for Computational Biology and Bioinformatics, Columbia University, New York, New York, United States of America.|Howard Hughes Medical Institute, Columbia University, New York, New York, United States of America, Department of Systems Biology, Columbia University, New York, New York, United States of America, Department of Biochemistry and Molecular Biophysics, Columbia University, New York, New York, United States of America, Center for Computational Biology and Bioinformatics, Columbia University, New York, New York, United States of America.', 'United States|United States|United States|United States', 11, 'Algorithms|Bayes Theorem|Computational Biology|Databases, Protein|Genome, Human|Humans|Likelihood Functions|Models, Biological|Protein Interaction Domains and Motifs|Protein Interaction Mapping|Proteomics|Support Vector Machine', 'Journal Article', '10.1371/journal.pcbi.1004248', '25938916', 'We describe a method to predict protein-protein interactions (PPIs) formed between structured domains and short peptide motifs. We take an integrative approach based on consensus patterns of known motifs in databases, structures of domain-motif complexes from the PDB and various sources of non-structural evidence. We combine this set of clues using a Bayesian classifier that reports the likelihood of an interaction and obtain significantly improved prediction performance when compared to individual sources of evidence and to previously reported algorithms. Our Bayesian approach was integrated into PrePPI, a structure-based PPI prediction method that, so far, has been limited to interactions formed between two structured domains. Around 80,000 new domain-motif mediated interactions were predicted, thus enhancing PrePPIs coverage of the human protein interactome. '),
(87148, 2015, 'plos', 'Dissecting the calcium-induced differentiation of human primary keratinocytes stem cells by integrative and structural network analyses', 'Toufighi, Kiana|Yang, Jae-Seong|Luis, Nuno Miguel|Aznar Benitah, Salvador|Lehner, Ben|Serrano, Luis|Kiel, Christina', 'EMBL/CRG Systems Biology Research Unit, Centre for Genomic Regulation (CRG), Barcelona, Spain, Universitat Pompeu Fabra, Barcelona, Spain.|EMBL/CRG Systems Biology Research Unit, Centre for Genomic Regulation (CRG), Barcelona, Spain, Universitat Pompeu Fabra, Barcelona, Spain.|EMBL/CRG Systems Biology Research Unit, Centre for Genomic Regulation (CRG), Barcelona, Spain, Universitat Pompeu Fabra, Barcelona, Spain.|EMBL/CRG Systems Biology Research Unit, Centre for Genomic Regulation (CRG), Barcelona, Spain, Universitat Pompeu Fabra, Barcelona, Spain, Institute for Research in Biomedicine, Parc Cientxc3xadfic de Barcelona, Barcelona, Spain.|EMBL/CRG Systems Biology Research Unit, Centre for Genomic Regulation (CRG), Barcelona, Spain, Universitat Pompeu Fabra, Barcelona, Spain, Institucixc3xb3 Catalana de Recerca i Estudis Avanxc3xa7ats, Barcelona, Spain.|EMBL/CRG Systems Biology Research Unit, Centre for Genomic Regulation (CRG), Barcelona, Spain, Universitat Pompeu Fabra, Barcelona, Spain, Institucixc3xb3 Catalana de Recerca i Estudis Avanxc3xa7ats, Barcelona, Spain.|EMBL/CRG Systems Biology Research Unit, Centre for Genomic Regulation (CRG), Barcelona, Spain, Universitat Pompeu Fabra, Barcelona, Spain.', 'Spain|Spain|Spain|Spain|Spain|Spain|Spain', 0, 'Calcium|Cell Differentiation|Cluster Analysis|Computational Biology|Epidermal Cells|Gene Expression Profiling|Humans|Keratinocytes|Models, Statistical|NF-kappa B|Oligonucleotide Array Sequence Analysis|Protein Interaction Mapping|Signal Transduction|Software|Stem Cells|Transcriptome|Tumor Necrosis Factor-alpha', 'Journal Article', '10.1371/journal.pcbi.1004256', '25946651', 'The molecular details underlying the time-dependent assembly of protein complexes in cellular networks, such as those that occur during differentiation, are largely unexplored. Focusing on the calcium-induced differentiation of primary human keratinocytes as a model system for a major cellular reorganization process, we look at the expression of genes whose products are involved in manually-annotated protein complexes. Clustering analyses revealed only moderate co-expression of functionally related proteins during differentiation. However, when we looked at protein complexes, we found that the majority (55%) are composed of non-dynamic and dynamic gene products (di-chromatic), 19% are non-dynamic, and 26% only dynamic. Considering three-dimensional protein structures to predict steric interactions, we found that proteins encoded by dynamic genes frequently interact with a common non-dynamic protein in a mutually exclusive fashion. This suggests that during differentiation, complex assemblies may also change through variation in the abundance of proteins that compete for binding to common proteins as found in some cases for paralogous proteins. Considering the example of the TNF-xcexb1/NFxcexbaB signaling complex, we suggest that the same core complex can guide signals into diverse context-specific outputs by addition of time specific expressed subunits, while keeping other cellular functions constant. Thus, our analysis provides evidence that complex assembly with stable core components and competition could contribute to cell differentiation. '),
(87149, 2015, 'plos', 'Accurate computation of survival statistics in genome-wide studies', 'Vandin, Fabio|Papoutsaki, Alexandra|Raphael, Benjamin J|Upfal, Eli', 'Department of Mathematics and Computer Science, University of Southern Denmark, Funen, Denmark, Department of Computer Science, Brown University, Providence, Rhode Island, United States of America, Center for Computational Molecular Biology, Brown University, Providence, Rhode Island, United States of America.|Department of Computer Science, Brown University, Providence, Rhode Island, United States of America, Center for Computational Molecular Biology, Brown University, Providence, Rhode Island, United States of America.|Department of Computer Science, Brown University, Providence, Rhode Island, United States of America, Center for Computational Molecular Biology, Brown University, Providence, Rhode Island, United States of America.|Department of Computer Science, Brown University, Providence, Rhode Island, United States of America.', 'Denmark|United States|United States|United States', 12, 'Algorithms|Computational Biology|Databases, Genetic|Female|Genetic Variation|Genome-Wide Association Study|Genomics|High-Throughput Nucleotide Sequencing|Humans|Male|Models, Statistical|Mutation|Neoplasms|Survival Analysis', 'Journal Article', '10.1371/journal.pcbi.1004071', '25950620', 'A key challenge in genomics is to identify genetic variants that distinguish patients with different survival time following diagnosis or treatment. While the log-rank test is widely used for this purpose, nearly all implementations of the log-rank test rely on an asymptotic approximation that is not appropriate in many genomics applications. This is because: the two populations determined by a genetic variant may have very different sizes, and the evaluation of many possible variants demands highly accurate computation of very small p-values. We demonstrate this problem for cancer genomics data where the standard log-rank test leads to many false positive associations between somatic mutations and survival time. We develop and analyze a novel algorithm, Exact Log-rank Test (ExaLT), that accurately computes the p-value of the log-rank statistic under an exact distribution that is appropriate for any size populations. We demonstrate the advantages of ExaLT on data from published cancer genomics studies, finding significant differences from the reported p-values. We analyze somatic mutations in six cancer types from The Cancer Genome Atlas (TCGA), finding mutations with known association to survival as well as several novel associations. In contrast, standard implementations of the log-rank test report dozens-hundreds of likely false positive associations as more significant than these known associations. '),
(87150, 2015, 'plos', 'A dynamical phyllotaxis model to determine floral organ number', 'Kitazawa, Miho S|Fujimoto, Koichi', 'Department of Biological Sciences, Osaka University, Toyonaka, Osaka, Japan, Japan Society for the Promotion of Science, Tokyo, Japan.|Department of Biological Sciences, Osaka University, Toyonaka, Osaka, Japan.', 'Japan|Japan', 0, 'Arabidopsis|Body Patterning|Computational Biology|Computer Simulation|Flowers|Genes, Plant|Indoleacetic Acids|Meristem|Models, Biological|Mutation|Plant Growth Regulators|Plant Leaves|Silene', 'Journal Article', '10.1371/journal.pcbi.1004145', '25950739', 'How organisms determine particular organ numbers is a fundamental key to the development of precise body structures, however, the developmental mechanisms underlying organ-number determination are unclear. In many eudicot plants, the primordia of sepals and petals (the floral organs) first arise sequentially at the edge of a circular, undifferentiated region called the floral meristem, and later transition into a concentric arrangement called a whorl, which includes four or five organs. The properties controlling the transition to whorls comprising particular numbers of organs is little explored. We propose a development-based model of floral organ-number determination, improving upon earlier models of plant phyllotaxis that assumed two developmental processes: the sequential initiation of primordia in the least crowded space around the meristem and the constant growth of the tip of the stem. By introducing mutual repulsion among primordia into the growth process, we numerically and analytically show that the whorled arrangement emerges spontaneously from the sequential initiation of primordia. Moreover, by allowing the strength of the inhibition exerted by each primordium to decrease as the primordium ages, we show that pentamerous whorls, in which the angular and radial positions of the primordia are consistent with those observed in sepal and petal primordia in Silene coeli-rosa, Caryophyllaceae, become the dominant arrangement. The organ number within the outmost whorl, corresponding to the sepals, takes a value of four or five in a much wider parameter space than that in which it takes a value of six or seven. These results suggest that mutual repulsion among primordia during growth and a temporal decrease in the strength of the inhibition during initiation are required for the development of the tetramerous and pentamerous whorls common in eudicots. '),
(87151, 2015, 'plos', 'Comment on Broadband Criticality of Human Brain Network Synchronization by Kitzbichler MG, Smith ML, Christensen SR, Bullmore E (2009) PLoS Comput Biol 5: e1000314', 'Farmer, Simon', 'Sobell Department of Motor Neuroscience and Movement Disorders, Institute of Neurology, University College London, Queen Square, London, United Kingdom.', 'United Kingdom', 0, 'Action Potentials|Animals|Biological Clocks|Brain|Cortical Synchronization|Humans|Models, Neurological|Nerve Net|Synaptic Transmission', 'Journal Article', '10.1371/journal.pcbi.1004174', '25950844', '-'),
(87152, 2015, 'plos', 'Sparse and compositionally robust inference of microbial ecological networks', 'Kurtz, Zachary D|Müller, Christian L|Miraldi, Emily R|Littman, Dan R|Blaser, Martin J|Bonneau, Richard A', 'Departments of Microbiology and Medicine, New York University School of Medicine, New York, New York, United States of America.|Department of Biology, Center for Genomics and Systems Biology, New York University, New York, New York, United States of America, Courant Institute of Mathematical Sciences, New York University, New York, New York, United States of America.|Departments of Microbiology and Medicine, New York University School of Medicine, New York, New York, United States of America, Department of Biology, Center for Genomics and Systems Biology, New York University, New York, New York, United States of America, Courant Institute of Mathematical Sciences, New York University, New York, New York, United States of America.|Departments of Microbiology and Medicine, New York University School of Medicine, New York, New York, United States of America.|Departments of Microbiology and Medicine, New York University School of Medicine, New York, New York, United States of America.|Department of Biology, Center for Genomics and Systems Biology, New York University, New York, New York, United States of America, Courant Institute of Mathematical Sciences, New York University, New York, New York, United States of America, Simons Center for Data Analysis, Simons Foundation, New York, New York, United States of America.', 'United States|United States|United States|United States|United States|United States', 0, 'Algorithms|Biota|Computational Biology|Gastrointestinal Microbiome|Humans|Metagenomics|Microbiota|Models, Biological|RNA, Ribosomal, 16S', 'Journal Article', '10.1371/journal.pcbi.1004226', '25950956', '16S ribosomal RNA (rRNA) gene and other environmental sequencing techniques provide snapshots of microbial communities, revealing phylogeny and the abundances of microbial populations across diverse ecosystems. While changes in microbial community structure are demonstrably associated with certain environmental conditions (from metabolic and immunological health in mammals to ecological stability in soils and oceans), identification of underlying mechanisms requires new statistical tools, as these datasets present several technical challenges. First, the abundances of microbial operational taxonomic units (OTUs) from amplicon-based datasets are compositional. Counts are normalized to the total number of counts in the sample. Thus, microbial abundances are not independent, and traditional statistical metrics (e.g., correlation) for the detection of OTU-OTU relationships can lead to spurious results. Secondly, microbial sequencing-based studies typically measure hundreds of OTUs on only tens to hundreds of samples, thus, inference of OTU-OTU association networks is severely under-powered, and additional information (or assumptions) are required for accurate inference. Here, we present SPIEC-EASI (SParse InversE Covariance Estimation for Ecological Association Inference), a statistical method for the inference of microbial ecological networks from amplicon sequencing datasets that addresses both of these issues. SPIEC-EASI combines data transformations developed for compositional data analysis with a graphical model inference framework that assumes the underlying ecological association network is sparse. To reconstruct the network, SPIEC-EASI relies on algorithms for sparse neighborhood and inverse covariance selection. To provide a synthetic benchmark in the absence of an experimentally validated gold-standard network, SPIEC-EASI is accompanied by a set of computational tools to generate OTU count data from a set of diverse underlying network topologies. SPIEC-EASI outperforms state-of-the-art methods to recover edges and network properties on synthetic data under a variety of scenarios. SPIEC-EASI also reproducibly predicts previously unknown microbial associations using data from the American Gut project. ');
