INSERT INTO `papers` (`id`, `ano`, `journal`, `titulo`, `autores`, `afiliacao`, `pais`, `citacoes`, `palavra_chave`, `categorias`, `doi`, `pubmed`, `abstract`) VALUES
(86345, 2013, 'plos', 'Amino acid changes in disease-associated variants differ radically from variants observed in the 1000 genomes project dataset', 'de Beer, Tjaart A P|Laskowski, Roman A|Parks, Sarah L|Sipos, Botond|Goldman, Nick|Thornton, Janet M', 'European Molecular Biology Laboratory, European Bioinformatics Institute (EMBL-EBI), Wellcome Trust Genomes Campus, Cambridge, Cambridgeshire, United Kingdom.|European Molecular Biology Laboratory, European Bioinformatics Institute (EMBL-EBI), Wellcome Trust Genomes Campus, Cambridge, Cambridgeshire, United Kingdom.|European Molecular Biology Laboratory, European Bioinformatics Institute (EMBL-EBI), Wellcome Trust Genomes Campus, Cambridge, Cambridgeshire, United Kingdom.|European Molecular Biology Laboratory, European Bioinformatics Institute (EMBL-EBI), Wellcome Trust Genomes Campus, Cambridge, Cambridgeshire, United Kingdom.|European Molecular Biology Laboratory, European Bioinformatics Institute (EMBL-EBI), Wellcome Trust Genomes Campus, Cambridge, Cambridgeshire, United Kingdom.|European Molecular Biology Laboratory, European Bioinformatics Institute (EMBL-EBI), Wellcome Trust Genomes Campus, Cambridge, Cambridgeshire, United Kingdom.', 'United Kingdom|United Kingdom|United Kingdom|United Kingdom|United Kingdom|United Kingdom', 36, 'Amino Acids|Databases, Genetic|Genome, Human|Humans|Mutation|Proteins', 'Journal Article', '10.1371/journal.pcbi.1003382', '24348229', 'The 1000 Genomes Project data provides a natural background dataset for amino acid germline mutations in humans. Since the direction of mutation is known, the amino acid exchange matrix generated from the observed nucleotide variants is asymmetric and the mutabilities of the different amino acids are very different. These differences predominantly reflect preferences for nucleotide mutations in the DNA (especially the high mutation rate of the CpG dinucleotide, which makes arginine mutability very much higher than other amino acids) rather than selection imposed by protein structure constraints, although there is evidence for the latter as well. The variants occur predominantly on the surface of proteins (82%), with a slight preference for sites which are more exposed and less well conserved than random. Mutations to functional residues occur about half as often as expected by chance. The disease-associated amino acid variant distributions in OMIM are radically different from those expected on the basis of the 1000 Genomes dataset. The disease-associated variants preferentially occur in more conserved sites, compared to 1000 Genomes mutations. Many of the amino acid exchange profiles appear to exhibit an anti-correlation, with common exchanges in one dataset being rare in the other. Disease-associated variants exhibit more extreme differences in amino acid size and hydrophobicity. More modelling of the mutational processes at the nucleotide level is needed, but these observations should contribute to an improved prediction of the effects of specific variants in humans. '),
(86346, 2013, 'plos', 'Forward and backward inference in spatial cognition', 'Penny, Will D|Zeidman, Peter|Burgess, Neil', 'Wellcome Trust Centre for Neuroimaging, University College, London, London, United Kingdom.|Wellcome Trust Centre for Neuroimaging, University College, London, London, United Kingdom.|Institute for Cognitive Neuroscience, University College, London, London, United Kingdom.', 'United Kingdom|United Kingdom|United Kingdom', 0, 'Algorithms|Animals|Cognition|Hippocampus|Humans|Models, Theoretical|Probability|Space Perception', 'Journal Article', '10.1371/journal.pcbi.1003383', '24348230', 'This paper shows that the various computations underlying spatial cognition can be implemented using statistical inference in a single probabilistic model. Inference is implemented using a common set of lower-level computations involving forward and backward inference over time. For example, to estimate where you are in a known environment, forward inference is used to optimally combine location estimates from path integration with those from sensory input. To decide which way to turn to reach a goal, forward inference is used to compute the likelihood of reaching that goal under each option. To work out which environment you are in, forward inference is used to compute the likelihood of sensory observations under the different hypotheses. For reaching sensory goals that require a chaining together of decisions, forward inference can be used to compute a state trajectory that will lead to that goal, and backward inference to refine the route and estimate control signals that produce the required trajectory. We propose that these computations are reflected in recent findings of pattern replay in the mammalian brain. Specifically, that theta sequences reflect decision making, theta flickering reflects model selection, and remote replay reflects route and motor planning. We also propose a mapping of the above computational processes onto lateral and medial entorhinal cortex and hippocampus. '),
(86347, 2013, 'plos', 'Modeling the afferent dynamics of the baroreflex control system', 'Mahdi, Adam|Sturdy, Jacob|Ottesen, Johnny T|Olufsen, Mette S', 'Department of Mathematics, North Carolina State University, Raleigh, North Carolina, United States of America.|Department of Mathematics, North Carolina State University, Raleigh, North Carolina, United States of America.|Department of Science, Systems, and Models, Roskilde University, Roskilde, Denmark.|Department of Mathematics, North Carolina State University, Raleigh, North Carolina, United States of America.', 'United States|United States|Denmark|United States', 21, 'Baroreflex|Humans|Models, Biological', 'Journal Article', '10.1371/journal.pcbi.1003384', '24348231', 'In this study we develop a modeling framework for predicting baroreceptor firing rate as a function of blood pressure. We test models within this framework both quantitatively and qualitatively using data from rats. The models describe three components: arterial wall deformation, stimulation of mechanoreceptors located in the BR nerve-endings, and modulation of the action potential frequency. The three sub-systems are modeled individually following well-established biological principles. The first submodel, predicting arterial wall deformation, uses blood pressure as an input and outputs circumferential strain. The mechanoreceptor stimulation model, uses circumferential strain as an input, predicting receptor deformation as an output. Finally, the neural model takes receptor deformation as an input predicting the BR firing rate as an output. Our results show that nonlinear dependence of firing rate on pressure can be accounted for by taking into account the nonlinear elastic properties of the artery wall. This was observed when testing the models using multiple experiments with a single set of parameters. We find that to model the response to a square pressure stimulus, giving rise to post-excitatory depression, it is necessary to include an integrate-and-fire model, which allows the firing rate to cease when the stimulus falls below a given threshold. We show that our modeling framework in combination with sensitivity analysis and parameter estimation can be used to test and compare models. Finally, we demonstrate that our preferred model can exhibit all known dynamics and that it is advantageous to combine qualitative and quantitative analysis methods. '),
(86348, 2013, 'plos', 'Ecological modeling from time-series inference: insight into dynamics and stability of intestinal microbiota', 'Stein, Richard R|Bucci, Vanni|Toussaint, Nora C|Buffie, Charlie G|Rätsch, Gunnar|Pamer, Eric G|Sander, Chris|Xavier, João B', 'Computational Biology Program, Sloan-Kettering Institute, Memorial Sloan-Kettering Cancer Center, New York, New York, United States of America.|Computational Biology Program, Sloan-Kettering Institute, Memorial Sloan-Kettering Cancer Center, New York, New York, United States of America.|Immunology Program, Sloan-Kettering Institute, Memorial Sloan-Kettering Cancer Center, New York, New York, United States of America.|Immunology Program, Sloan-Kettering Institute, Memorial Sloan-Kettering Cancer Center, New York, New York, United States of America.|Computational Biology Program, Sloan-Kettering Institute, Memorial Sloan-Kettering Cancer Center, New York, New York, United States of America.|Immunology Program, Sloan-Kettering Institute, Memorial Sloan-Kettering Cancer Center, New York, New York, United States of America.|Computational Biology Program, Sloan-Kettering Institute, Memorial Sloan-Kettering Cancer Center, New York, New York, United States of America.|Computational Biology Program, Sloan-Kettering Institute, Memorial Sloan-Kettering Cancer Center, New York, New York, United States of America.', 'United States|United States|United States|United States|United States|United States|United States|Un', 235, 'Animals|Clostridium difficile|Ecology|Intestines|Mice|Models, Animal|Models, Theoretical|Real-Time Polymerase Chain Reaction', 'Journal Article', '10.1371/journal.pcbi.1003388', '24348232', 'The intestinal microbiota is a microbial ecosystem of crucial importance to human health. Understanding how the microbiota confers resistance against enteric pathogens and how antibiotics disrupt that resistance is key to the prevention and cure of intestinal infections. We present a novel method to infer microbial community ecology directly from time-resolved metagenomics. This method extends generalized Lotka-Volterra dynamics to account for external perturbations. Data from recent experiments on antibiotic-mediated Clostridium difficile infection is analyzed to quantify microbial interactions, commensal-pathogen interactions, and the effect of the antibiotic on the community. Stability analysis reveals that the microbiota is intrinsically stable, explaining how antibiotic perturbations and C. difficile inoculation can produce catastrophic shifts that persist even after removal of the perturbations. Importantly, the analysis suggests a subnetwork of bacterial groups implicated in protection against C. difficile. Due to its generality, our method can be applied to any high-resolution ecological time-series data to infer community structure and response to external stimuli. '),
(86349, 2013, 'plos', 'Moving education forward, again!', 'Lewitter, Fran', 'Bioinformatics and Research Computing, Whitehead Institute, Cambridge, Massachusetts, United States of America.', 'United States', 0, 'Biology|Computational Biology|Education|Publishing', 'Editorial', '10.1371/journal.pcbi.1003390', '24348233', '-'),
(86350, 2013, 'plos', 'Education in computational biology today and tomorrow', 'Fox, Joanne A|Ouellette, B F Francis', 'Michael Smith Laboratories, University of British Columbia, Vancouver, British Columbia, Canada , Department of Microbiology & Immunology, University of British Columbia, Vancouver, British Columbia, Canada.|Ontario Institute for Cancer Research, Toronto, Canada , Department of Cell and Systems Biology, University of Toronto, Toronto, Canada.', 'Canada|Canada', 2, 'Computational Biology|Education|Forecasting', 'Editorial', '10.1371/journal.pcbi.1003391', '24348234', '-'),
(86351, 2013, 'plos', 'Inferring developmental stage composition from gene expression in human malaria', 'Joice, Regina|Narasimhan, Vagheesh|Montgomery, Jacqui|Sidhu, Amar Bir|Oh, Keunyoung|Meyer, Evan|Pierre-Louis, Willythssa|Seydel, Karl|Milner, Danny|Williamson, Kim|Wiegand, Roger|Ndiaye, Daouda|Daily, Johanna|Wirth, Dyann|Taylor, Terrie|Huttenhower, Curtis|Marti, Matthias', 'Department of Immunology and Infectious Diseases, Harvard School of Public Health, Boston, Massachusetts, United States of America.|Department of Biostatistics, Harvard School of Public Health, Boston, Massachusetts, United States of America.|Malawi-Liverpool-Wellcome Trust Clinical Research Programme, Blantyre, Malawi , Liverpool School of Tropical Medicine, Liverpool, United Kingdom.|The Broad Institute of Harvard and MIT, Cambridge, Massachusetts, United States of America.|Department of Biostatistics, Harvard School of Public Health, Boston, Massachusetts, United States of America.|Department of Immunology and Infectious Diseases, Harvard School of Public Health, Boston, Massachusetts, United States of America.|Department of Biostatistics, Harvard School of Public Health, Boston, Massachusetts, United States of America.|College of Osteopathic Medicine, Michigan State University, East Lansing, Michigan, United States of America , Blantyre Malaria Project, University of Malawi College of Medicine, Blantyre, Malawi.|Department of Immunology and Infectious Diseases, Harvard School of Public Health, Boston, Massachusetts, United States of America , Department of Pathology, Brigham and Womens Hospital, Boston, Massachusetts, United States of America.|Department of Biology, Loyola University Chicago, Chicago, Illinois, United States of America.|The Broad Institute of Harvard and MIT, Cambridge, Massachusetts, United States of America.|Faculty of Medicine and Pharmacy, Cheikh Anta Diop University, Dakar, Senegal.|Department of Immunology and Infectious Diseases, Harvard School of Public Health, Boston, Massachusetts, United States of America , Department of Medicine, Albert Einstein College of Medicine, Bronx, New York, New York, United States of America.|Department of Immunology and Infectious Diseases, Harvard School of Public Health, Boston, Massachusetts, United States of America , The Broad Institute of Harvard and MIT, Cambridge, Massachusetts, United States of America.|College of Osteopathic Medicine, Michigan State University, East Lansing, Michigan, United States of America , Blantyre Malaria Project, University of Malawi College of Medicine, Blantyre, Malawi.|Department of Biostatistics, Harvard School of Public Health, Boston, Massachusetts, United States of America , The Broad Institute of Harvard and MIT, Cambridge, Massachusetts, United States of America.|Department of Immunology and Infectious Diseases, Harvard School of Public Health, Boston, Massachusetts, United States of America.', 'United States|United States|United Kingdom|United States|United States|United States|United States|M', 34, 'Animals|Biomarkers|Gene Expression|Humans|Malaria, Falciparum|Models, Biological|Oligonucleotide Array Sequence Analysis|Plasmodium falciparum|Polymerase Chain Reaction|Real-Time Polymerase Chain Reaction|Selection, Genetic', 'Journal Article', '10.1371/journal.pcbi.1003392', '24348235', 'In the current era of malaria eradication, reducing transmission is critical. Assessment of transmissibility requires tools that can accurately identify the various developmental stages of the malaria parasite, particularly those required for transmission (sexual stages). Here, we present a method for estimating relative amounts of Plasmodium falciparum asexual and sexual stages from gene expression measurements. These are modeled using constrained linear regression to characterize stage-specific expression profiles within mixed-stage populations. The resulting profiles were analyzed functionally by gene set enrichment analysis (GSEA), confirming differentially active pathways such as increased mitochondrial activity and lipid metabolism during sexual development. We validated model predictions both from microarrays and from quantitative RT-PCR (qRT-PCR) measurements, based on the expression of a small set of key transcriptional markers. This sufficient marker set was identified by backward selection from the whole genome as available from expression arrays, targeting one sentinel marker per stage. The model as learned can be applied to any new microarray or qRT-PCR transcriptional measurement. We illustrate its use in vitro in inferring changes in stage distribution following stress and drug treatment and in vivo in identifying immature and mature sexual stage carriers within patient cohorts. We believe this approach will be a valuable resource for staging lab and field samples alike and will have wide applicability in epidemiological studies of malaria transmission. '),
(86352, 2013, 'plos', 'Exploring early stages of the chemical unfolding of proteins at the proteome scale', 'Candotti, Michela|Pxc3xa9rez, Alberto|Ferrer-Costa, Carles|Rueda, Manuel|Meyer, Tim|Gelpxc3xad, Josep Lluxc3xads|Orozco, Modesto', 'Institute for Research in Biomedicine (IRB Barcelona), Barcelona, Spain , Joint Research Program in Computational Biology, Institute for Research in Biomedicine and Barcelona Supercomputing Center, Barcelona, Spain.|Laufer Center, Stony Brook University, Stony Brook, New York, United States of America.|Joint Research Program in Computational Biology, Institute for Research in Biomedicine and Barcelona Supercomputing Center, Barcelona, Spain.|Skaggs School of Pharmacy and Pharmaceutical Sciences, University of California San Diego, La Jolla, California, United States of America.|Theoretische und Computergestxc3xbctzte Biophysik, Max-Planck-Institut fxc3xbcr Biophysikalische Chemie, Gxc3xb6ttingen, Germany.|Institute for Research in Biomedicine (IRB Barcelona), Barcelona, Spain , Department of Biochemistry and Molecular Biology, University of Barcelona, Barcelona, Spain.|Institute for Research in Biomedicine (IRB Barcelona), Barcelona, Spain , Joint Research Program in Computational Biology, Institute for Research in Biomedicine and Barcelona Supercomputing Center, Barcelona, Spain , Department of Biochemistry and Molecular Biology, University of Barcelona, Barcelona, Spain.', 'Spain|United States|Spain|United States|Germany|Spain|Spain', 0, 'Protein Unfolding|Proteome', 'Journal Article', '10.1371/journal.pcbi.1003393', '24348236', 'After decades of using urea as denaturant, the kinetic role of this molecule in the unfolding process is still undefined: does urea actively induce protein unfolding or passively stabilize the unfolded state? By analyzing a set of 30 proteins (representative of all native folds) through extensive molecular dynamics simulations in denaturant (using a range of force-fields), we derived robust rules for urea unfolding that are valid at the proteome level. Irrespective of the protein fold, presence or absence of disulphide bridges, and secondary structure composition, urea concentrates in the first solvation shell of quasi-native proteins, but with a density lower than that of the fully unfolded state. The presence of urea does not alter the spontaneous vibration pattern of proteins. In fact, it reduces the magnitude of such vibrations, leading to a counterintuitive slow down of the atomic-motions that opposes unfolding. Urea stickiness and slow diffusion is, however, crucial for unfolding. Long residence urea molecules placed around the hydrophobic core are crucial to stabilize partially open structures generated by thermal fluctuations. Our simulations indicate that although urea does not favor the formation of partially open microstates, it is not a mere spectator of unfolding that simply displaces to the right of the folded xe2x86x90xe2x86x92 unfolded equilibrium. On the contrary, urea actively favors unfolding: it selects and stabilizes partially unfolded microstates, slowly driving the protein conformational ensemble far from the native one and also from the conformations sampled during thermal unfolding.'),
(86353, 2013, 'plos', 'GDI-mediated cell polarization in yeast provides precise spatial and temporal control of Cdc42 signaling', 'Klünder, Ben|Freisinger, Tina|Wedlich-Söldner, Roland|Frey, Erwin', 'Arnold Sommerfeld Center for Theoretical Physics (ASC) and Center for NanoScience (CeNS), Department of Physics, Ludwig-Maximilians-Universität München, München, Germany.|Max Planck Institute of Biochemistry, Cellular Dynamics and Cell Patterning, Martinsried, Germany.|Max Planck Institute of Biochemistry, Cellular Dynamics and Cell Patterning, Martinsried, Germany.|Arnold Sommerfeld Center for Theoretical Physics (ASC) and Center for NanoScience (CeNS), Department of Physics, Ludwig-Maximilians-Universität München, München, Germany.', 'Germany|Germany|Germany|Germany', 0, 'Cell Polarity|Guanine Nucleotide Dissociation Inhibitors|Saccharomyces cerevisiae|Signal Transduction|cdc42 GTP-Binding Protein, Saccharomyces cerevisiae', 'Journal Article', '10.1371/journal.pcbi.1003396', '24348237', 'Cell polarization is a prerequisite for essential processes such as cell migration, proliferation or differentiation. The yeast Saccharomyces cerevisiae under control of the GTPase Cdc42 is able to polarize without the help of cytoskeletal structures and spatial cues through a pathway depending on its guanine nucleotide dissociation inhibitor (GDI) Rdi1. To develop a fundamental understanding of yeast polarization we establish a detailed mechanistic model of GDI-mediated polarization. We show that GDI-mediated polarization provides precise spatial and temporal control of Cdc42 signaling and give experimental evidence for our findings. Cell cycle induced changes of Cdc42 regulation enhance positive feedback loops of active Cdc42 production, and thereby allow simultaneous switch-like regulation of focused polarity and Cdc42 activation. This regulation drives the direct formation of a unique polarity cluster with characteristic narrowing dynamics, as opposed to the previously proposed competition between transient clusters. As the key components of the studied system are conserved among eukaryotes, we expect our findings also to apply to cell polarization in other organisms. '),
(86354, 2013, 'plos', 'A Petri net model of granulomatous inflammation: implications for IL-10 mediated control of Leishmania donovani infection', 'Albergante, Luca|Timmis, Jon|Beattie, Lynette|Kaye, Paul M', 'Department of Computer Science and Department of Electronics, University of York, York, United Kingdom.|Department of Computer Science and Department of Electronics, University of York, York, United Kingdom.|Center for Immunology and Infection, Department of Biology and Hull York Medical School, University of York, York, United Kingdom.|Center for Immunology and Infection, Department of Biology and Hull York Medical School, University of York, York, United Kingdom.', 'United Kingdom|United Kingdom|United Kingdom|United Kingdom', 26, 'Animals|Computer Simulation|Disease Models, Animal|Granuloma|Inflammation|Interleukin-10|Kupffer Cells|Leishmania donovani|Leishmaniasis, Visceral|Leukocytes|Liver|Mice|Models, Immunological|Parasite Load', 'Journal Article', '10.1371/journal.pcbi.1003334', '24363630', 'Experimental visceral leishmaniasis, caused by infection of mice with the protozoan parasite Leishmania donovani, is characterized by focal accumulation of inflammatory cells in the liver, forming discrete granulomas within which the parasite is eventually eliminated. To shed new light on fundamental aspects of granuloma formation and function, we have developed an in silico Petri net model that simulates hepatic granuloma development throughout the course of infection. The model was extensively validated by comparison with data derived from experimental studies in mice, and the model robustness was assessed by a sensitivity analysis. The model recapitulated the progression of disease as seen during experimental infection and also faithfully predicted many of the changes in cellular composition seen within granulomas over time. By conducting in silico experiments, we have identified a previously unappreciated level of inter-granuloma diversity in terms of the development of anti-leishmanial activity. Furthermore, by simulating the impact of IL-10 gene deficiency in a variety of lymphocyte and myeloid cell populations, our data suggest a dominant local regulatory role for IL-10 produced by infected Kupffer cells at the core of the granuloma. '),
(86355, 2013, 'plos', 'Flow cytometry bioinformatics', 'ONeill, Kieran|Aghaeepour, Nima|Spidlen, Josef|Brinkman, Ryan', 'Terry Fox Laboratory, BC Cancer Agency, Vancouver, British Columbia, Canada , Bioinformatics Graduate Program, University of British Columbia, Vancouver, British Columbia, Canada.|Terry Fox Laboratory, BC Cancer Agency, Vancouver, British Columbia, Canada , Bioinformatics Graduate Program, University of British Columbia, Vancouver, British Columbia, Canada.|Terry Fox Laboratory, BC Cancer Agency, Vancouver, British Columbia, Canada.|Terry Fox Laboratory, BC Cancer Agency, Vancouver, British Columbia, Canada , Department of Medical Genetics, University of British Columbia, Vancouver, British Columbia, Canada.', 'Canada|Canada|Canada|Canada', 0, 'Cell Separation|Computational Biology|Flow Cytometry', 'Journal Article', '10.1371/journal.pcbi.1003365', '24363631', 'Flow cytometry bioinformatics is the application of bioinformatics to flow cytometry data, which involves storing, retrieving, organizing, and analyzing flow cytometry data using extensive computational resources and tools. Flow cytometry bioinformatics requires extensive use of and contributes to the development of techniques from computational statistics and machine learning. Flow cytometry and related methods allow the quantification of multiple independent biomarkers on large numbers of single cells. The rapid growth in the multidimensionality and throughput of flow cytometry data, particularly in the 2000s, has led to the creation of a variety of computational analysis methods, data standards, and public databases for the sharing of results. Computational methods exist to assist in the preprocessing of flow cytometry data, identifying cell populations within it, matching those cell populations across samples, and performing diagnosis and discovery using the results of previous steps. For preprocessing, this includes compensating for spectral overlap, transforming data onto scales conducive to visualization and analysis, assessing data for quality, and normalizing data across samples and experiments. For population identification, tools are available to aid traditional manual identification of populations in two-dimensional scatter plots (gating), to use dimensionality reduction to aid gating, and to find populations automatically in higher dimensional space in a variety of ways. It is also possible to characterize data in more comprehensive ways, such as the density-guided binary space partitioning technique known as probability binning, or by combinatorial gating. Finally, diagnosis using flow cytometry data can be aided by supervised learning techniques, and discovery of new cell types of biological importance by high-throughput statistical methods, as part of pipelines incorporating all of the aforementioned methods. Open standards, data, and software are also key parts of flow cytometry bioinformatics. Data standards include the widely adopted Flow Cytometry Standard (FCS) defining how data from cytometers should be stored, but also several new standards under development by the International Society for Advancement of Cytometry (ISAC) to aid in storing more detailed information about experimental design and analytical steps. Open data is slowly growing with the opening of the CytoBank database in 2010 and FlowRepository in 2012, both of which allow users to freely distribute their data, and the latter of which has been recommended as the preferred repository for MIFlowCyt-compliant data by ISAC. Open software is most widely available in the form of a suite of Bioconductor packages, but is also available for web execution on the GenePattern platform. '),
(86356, 2013, 'plos', 'Perturbation biology: inferring signaling networks in cellular systems', 'Molinelli, Evan J|Korkut, Anil|Wang, Weiqing|Miller, Martin L|Gauthier, Nicholas P|Jing, Xiaohong|Kaushik, Poorvi|He, Qin|Mills, Gordon|Solit, David B|Pratilas, Christine A|Weigt, Martin|Braunstein, Alfredo|Pagnani, Andrea|Zecchina, Riccardo|Sander, Chris', 'Computational Biology Program, Memorial Sloan-Kettering Cancer Center, New York, New York, United States of America , Tri-Institutional Program for Computational Biology and Medicine, Weill Cornell Medical College, New York, New York, United States of America.|Computational Biology Program, Memorial Sloan-Kettering Cancer Center, New York, New York, United States of America.|Computational Biology Program, Memorial Sloan-Kettering Cancer Center, New York, New York, United States of America.|Computational Biology Program, Memorial Sloan-Kettering Cancer Center, New York, New York, United States of America.|Computational Biology Program, Memorial Sloan-Kettering Cancer Center, New York, New York, United States of America.|Computational Biology Program, Memorial Sloan-Kettering Cancer Center, New York, New York, United States of America.|Computational Biology Program, Memorial Sloan-Kettering Cancer Center, New York, New York, United States of America , Tri-Institutional Program for Computational Biology and Medicine, Weill Cornell Medical College, New York, New York, United States of America.|Computational Biology Program, Memorial Sloan-Kettering Cancer Center, New York, New York, United States of America.|Department of Systems Biology, The University of Texas MD Anderson Cancer Center, Houston, Texas, United States of America.|Program in Molecular Pharmacology, Memorial Sloan-Kettering Cancer Center, New York, New York, United States of America , Human Oncology and Pathogenesis Program, Memorial Sloan-Kettering Cancer Center, New York, New York, United States of America.|Program in Molecular Pharmacology, Memorial Sloan-Kettering Cancer Center, New York, New York, United States of America , Department of Pediatrics, Memorial Sloan-Kettering Cancer Center, New York, New York, United States of America.|Laboratoire de Génomique des Microorganismes, Université Pierre et Marie Curie, Paris, France.|Politecnico di Torino and Human Genetics Foundation, HuGeF, Torino, Italy.|Politecnico di Torino and Human Genetics Foundation, HuGeF, Torino, Italy.|Politecnico di Torino and Human Genetics Foundation, HuGeF, Torino, Italy.|Computational Biology Program, Memorial Sloan-Kettering Cancer Center, New York, New York, United States of America.', 'United States|United States|United States|United States|United States|United States|United States|Un', 74, 'Cell Line, Tumor|Humans|Models, Biological|Monte Carlo Method|Probability|Signal Transduction|Systems Biology', 'Journal Article', '10.1371/journal.pcbi.1003290', '24367245', 'We present a powerful experimental-computational technology for inferring network models that predict the response of cells to perturbations, and that may be useful in the design of combinatorial therapy against cancer. The experiments are systematic series of perturbations of cancer cell lines by targeted drugs, singly or in combination. The response to perturbation is quantified in terms of relative changes in the measured levels of proteins, phospho-proteins and cellular phenotypes such as viability. Computational network models are derived de novo, i.e., without prior knowledge of signaling pathways, and are based on simple non-linear differential equations. The prohibitively large solution space of all possible network models is explored efficiently using a probabilistic algorithm, Belief Propagation (BP), which is three orders of magnitude faster than standard Monte Carlo methods. Explicit executable models are derived for a set of perturbation experiments in SKMEL-133 melanoma cell lines, which are resistant to the therapeutically important inhibitor of RAF kinase. The resulting network models reproduce and extend known pathway biology. They empower potential discoveries of new molecular interactions and predict efficacious novel drug perturbations, such as the inhibition of PLK1, which is verified experimentally. This technology is suitable for application to larger systems in diverse areas of molecular biology. '),
(86357, 2013, 'plos', 'Structural control of metabolic flux', 'Sajitz-Hermstein, Max|Nikoloski, Zoran', 'Systems Biology and Mathematical Modeling Group, Max Planck Institute of Molecular Plant Physiology, Potsdam, Germany , System Regulation Group, Max Planck Institute of Molecular Plant Physiology, Potsdam, Germany.|Systems Biology and Mathematical Modeling Group, Max Planck Institute of Molecular Plant Physiology, Potsdam, Germany.', 'Germany|Germany', 7, 'Metabolism|Models, Theoretical', 'Journal Article', '10.1371/journal.pcbi.1003368', '24367246', 'Organisms have to continuously adapt to changing environmental conditions or undergo developmental transitions. To meet the accompanying change in metabolic demands, the molecular mechanisms of adaptation involve concerted interactions which ultimately induce a modification of the metabolic state, which is characterized by reaction fluxes and metabolite concentrations. These state transitions are the effect of simultaneously manipulating fluxes through several reactions. While metabolic control analysis has provided a powerful framework for elucidating the principles governing this orchestrated action to understand metabolic control, its applications are restricted by the limited availability of kinetic information. Here, we introduce structural metabolic control as a framework to examine individual reactions potential to control metabolic functions, such as biomass production, based on structural modeling. The capability to carry out a metabolic function is determined using flux balance analysis (FBA). We examine structural metabolic control on the example of the central carbon metabolism of Escherichia coli by the recently introduced framework of functional centrality (FC). This framework is based on the Shapley value from cooperative game theory and FBA, and we demonstrate its superior ability to assign share of control to individual reactions with respect to metabolic functions and environmental conditions. A comparative analysis of various scenarios illustrates the usefulness of FC and its relations to other structural approaches pertaining to metabolic control. We propose a Monte Carlo algorithm to estimate FCs for large networks, based on the enumeration of elementary flux modes. We further give detailed biological interpretation of FCs for production of lactate and ATP under various respiratory conditions. '),
(86358, 2013, 'plos', 'Electrodiffusive model for astrocytic and neuronal ion concentration dynamics', 'Halnes, Geir|Ostby, Ivar|Pettersen, Klas H|Omholt, Stig W|Einevoll, Gaute T', 'Department of Mathematical Sciences and Technology, Norwegian University of Life Sciences, Ås, Norway.|Department of Mathematical Sciences and Technology, Norwegian University of Life Sciences, Ås, Norway.|Centre for Integrative Genetics, Department of Mathematical Sciences and Technology, Norwegian University of Life Sciences, Ås, Norway.|Centre for Integrative Genetics, Department of Animal and Aqucultural Sciences, Norwegian University of Life Sciences, Ås, Norway.|Department of Mathematical Sciences and Technology, Norwegian University of Life Sciences, Ås, Norway.', 'Norway|Norway|Norway|Norway|Norway', 22, 'Astrocytes|Cations, Monovalent|Diffusion|Membrane Potentials|Models, Biological|Neurons|Potassium', 'Journal Article', '10.1371/journal.pcbi.1003386', '24367247', 'The cable equation is a proper framework for modeling electrical neural signalling that takes place at a timescale at which the ionic concentrations vary little. However, in neural tissue there are also key dynamic processes that occur at longer timescales. For example, endured periods of intense neural signaling may cause the local extracellular K(+)-concentration to increase by several millimolars. The clearance of this excess K(+) depends partly on diffusion in the extracellular space, partly on local uptake by astrocytes, and partly on intracellular transport (spatial buffering) within astrocytes. These processes, that take place at the time scale of seconds, demand a mathematical description able to account for the spatiotemporal variations in ion concentrations as well as the subsequent effects of these variations on the membrane potential. Here, we present a general electrodiffusive formalism for modeling of ion concentration dynamics in a one-dimensional geometry, including both the intra- and extracellular domains. Based on the Nernst-Planck equations, this formalism ensures that the membrane potential and ion concentrations are in consistency, it ensures global particle/charge conservation and it accounts for diffusion and concentration dependent variations in resistivity. We apply the formalism to a model of astrocytes exchanging ions with the extracellular space. The simulations show that K(+)-removal from high-concentration regions is driven by a local depolarization of the astrocyte membrane, which concertedly (i) increases the local astrocytic uptake of K(+), (ii) suppresses extracellular transport of K(+), (iii) increases axial transport of K(+) within astrocytes, and (iv) facilitates astrocytic relase of K(+) in regions where the extracellular concentration is low. Together, these mechanisms seem to provide a robust regulatory scheme for shielding the extracellular space from excess K(+). '),
(86359, 2013, 'plos', 'Utilizing a dynamical description of IspH to aid in the development of novel antimicrobial drugs', 'Blachly, Patrick G|de Oliveira, César A F|Williams, Sarah L|McCammon, J Andrew', 'Department of Chemistry & Biochemistry, University of California San Diego, La Jolla, California, United States of America.|Howard Hughes Medical Institute, University of California San Diego, La Jolla, California, United States of America.|Department of Chemistry & Biochemistry, University of California San Diego, La Jolla, California, United States of America.|Department of Chemistry & Biochemistry, University of California San Diego, La Jolla, California, United States of America , Howard Hughes Medical Institute, University of California San Diego, La Jolla, California, United States of America , Department of Pharmacology, University of California San Diego, La Jolla, California, United States of America.', 'United States|United States|United States|United States', 0, 'Anti-Infective Agents|Bacterial Proteins|Catalytic Domain|Drug Design|Ligands|Models, Theoretical|Molecular Dynamics Simulation|Principal Component Analysis|Protein Binding|Protein Conformation', 'Journal Article', '10.1371/journal.pcbi.1003395', '24367248', 'The nonmevalonate pathway is responsible for isoprenoid production in microbes, including H. pylori, M. tuberculosis and P. falciparum, but is nonexistent in humans, thus providing a desirable route for antibacterial and antimalarial drug discovery. We coordinate a structural study of IspH, a [4Fe-4S] protein responsible for converting HMBPP to IPP and DMAPP in the ultimate step in the nonmevalonate pathway. By performing accelerated molecular dynamics simulations on both substrate-free and HMBPP-bound [Fe4S4](2+) IspH, we elucidate how substrate binding alters the dynamics of the protein. Using principal component analysis, we note that while substrate-free IspH samples various open and closed conformations, the closed conformation observed experimentally for HMBPP-bound IspH is inaccessible in the absence of HMBPP. In contrast, simulations with HMBPP bound are restricted from accessing the open states sampled by the substrate-free simulations. Further investigation of the substrate-free simulations reveals large fluctuations in the HMBPP binding pocket, as well as allosteric pocket openings - both of which are achieved through the hinge motions of the individual domains in IspH. Coupling these findings with solvent mapping and various structural analyses reveals alternative druggable sites that may be exploited in future drug design efforts. '),
(86360, 2013, 'plos', 'Inferring the source of transmission with phylogenetic data', 'Volz, Erik M|Frost, Simon D W', 'Department of Infectious Disease Epidemiology, Imperial College London, London, United Kingdom.|Department of Veterinary Medicine, University of Cambridge, Cambridge, United Kingdom.', 'United Kingdom|United Kingdom', 39, 'Dengue|HIV Infections|Humans|Influenza, Human|Phylogeny|Probability', 'Journal Article', '10.1371/journal.pcbi.1003397', '24367249', 'Identifying the source of transmission using pathogen genetic data is complicated by numerous biological, immunological, and behavioral factors. A large source of error arises when there is incomplete or sparse sampling of cases. Unsampled cases may act as either a common source of infection or as an intermediary in a transmission chain for hosts infected with genetically similar pathogens. It is difficult to quantify the probability of common source or intermediate transmission events, which has made it difficult to develop statistical tests to either confirm or deny putative transmission pairs with genetic data. We present a method to incorporate additional information about an infectious disease epidemic, such as incidence and prevalence of infection over time, to inform estimates of the probability that one sampled host is the direct source of infection of another host in a pathogen gene genealogy. These methods enable forensic applications, such as source-case attribution, for infectious disease epidemics with incomplete sampling, which is usually the case for high-morbidity community-acquired pathogens like HIV, Influenza and Dengue virus. These methods also enable epidemiological applications such as the identification of factors that increase the risk of transmission. We demonstrate these methods in the context of the HIV epidemic in Detroit, Michigan, and we evaluate the suitability of current sequence databases for forensic and epidemiological investigations. We find that currently available sequences collected for drug resistance testing of HIV are unlikely to be useful in most forensic investigations, but are useful for identifying transmission risk factors. '),
(86361, 2013, 'plos', 'A latent Markov modelling approach to the evaluation of circulating cathodic antigen strips for schistosomiasis diagnosis pre- and post-praziquantel treatment in Uganda', 'Koukounari, Artemis|Donnelly, Christl A|Moustaki, Irini|Tukahebwa, Edridah M|Kabatereine, Narcis B|Wilson, Shona|Webster, Joanne P|Deelder, André M|Vennervald, Birgitte J|van Dam, Govert J', 'MRC Centre for Outbreak Analysis and Modelling, Department of Infectious Disease Epidemiology, Imperial College London, London, United Kingdom , Department of Statistics, London School of Economics and Political Science, London, United Kingdom.|MRC Centre for Outbreak Analysis and Modelling, Department of Infectious Disease Epidemiology, Imperial College London, London, United Kingdom.|Department of Statistics, London School of Economics and Political Science, London, United Kingdom.|Schistosomiasis Control Initiative at Vector Control Division - Ministry of Health, Kampala, Uganda.|Schistosomiasis Control Initiative at Vector Control Division - Ministry of Health, Kampala, Uganda.|Department of Pathology, University of Cambridge, Cambridge, United Kingdom.|Department of Infectious Disease Epidemiology, Imperial College London, London, United Kingdom.|Department of Parasitology, Leiden University Medical Center, Leiden, The Netherlands.|Section for Parasitology and Aquatic Diseases, University of Copenhagen, Copenhagen, Denmark.|Department of Parasitology, Leiden University Medical Center, Leiden, The Netherlands.', 'United Kingdom|United Kingdom|United Kingdom|Uganda|Uganda|United Kingdom|United Kingdom|Netherlands', 25, 'Anthelmintics|Antigens, Protozoan|Humans|Markov Chains|Praziquantel|Schistosomiasis|Sensitivity and Specificity|Uganda', 'Journal Article', '10.1371/journal.pcbi.1003402', '24367250', 'Regular treatment with praziquantel (PZQ) is the strategy for human schistosomiasis control aiming to prevent morbidity in later life. With the recent resolution on schistosomiasis elimination by the 65th World Health Assembly, appropriate diagnostic tools to inform interventions are keys to their success. We present a discrete Markov chains modelling framework that deals with the longitudinal study design and the measurement error in the diagnostic methods under study. A longitudinal detailed dataset from Uganda, in which one or two doses of PZQ treatment were provided, was analyzed through Latent Markov Models (LMMs). The aim was to evaluate the diagnostic accuracy of Circulating Cathodic Antigen (CCA) and of double Kato-Katz (KK) faecal slides over three consecutive days for Schistosoma mansoni infection simultaneously by age group at baseline and at two follow-up times post treatment. Diagnostic test sensitivities and specificities and the true underlying infection prevalence over time as well as the probabilities of transitions between infected and uninfected states are provided. The estimated transition probability matrices provide parsimonious yet important insights into the re-infection and cure rates in the two age groups. We show that the CCA diagnostic performance remained constant after PZQ treatment and that this test was overall more sensitive but less specific than single-day double KK for the diagnosis of S. mansoni infection. The probability of clearing infection from baseline to 9 weeks was higher among those who received two PZQ doses compared to one PZQ dose for both age groups, with much higher re-infection rates among children compared to adolescents and adults. We recommend LMMs as a useful methodology for monitoring and evaluation and treatment decision research as well as CCA for mapping surveys of S. mansoni infection, although additional diagnostic tools should be incorporated in schistosomiasis elimination programs. '),
(86362, 2013, 'plos', 'A disorder-induced domino-like destabilization mechanism governs the folding and functional dynamics of the repeat protein IxcexbaBxcexb1', 'Sivanandan, Srinivasan|Naganathan, Athi N', 'Department of Biotechnology, Indian Institute of Technology Kharagpur, Kharagpur, India.|Department of Biotechnology, Indian Institute of Technology Madras, Chennai, India.', 'India|India', 0, 'I-kappa B Proteins|Models, Molecular|NF-KappaB Inhibitor alpha|Protein Folding|Thermodynamics', 'Journal Article', '10.1371/journal.pcbi.1003403', '24367251', 'The stability of the repeat protein IxcexbaBxcexb1, a transcriptional inhibitor in mammalian cells, is critical in the functioning of the NF-xcexbaB signaling module implicated in an array of cellular processes, including cell growth, disease, immunity and apoptosis. Structurally, IxcexbaBxcexb1 is complex, with both ordered and disordered regions, thus posing a challenge to the available computational protocols to model its conformational behavior. Here, we introduce a simple procedure to model disorder in systems that undergo binding-induced folding that involves modulation of the contact map guided by equilibrium experimental observables in combination with an Ising-like Wako-Saitxc3xb4-Muxc3xb1oz-Eaton model. This one-step procedure alone is able to reproduce a variety of experimental observables, including ensemble thermodynamics (scanning calorimetry, pre-transitions, m-values) and kinetics (roll-over in chevron plot, intermediates and their identity), and is consistent with hydrogen-deuterium exchange measurements. We further capture the intricate distance-dynamics between the domains as measured by single-molecule FRET by combining the model predictions with simple polymer physics arguments. Our results reveal a unique mechanism at work in IxcexbaBxcexb1 folding, wherein disorder in one domain initiates a domino-like effect partially destabilizing neighboring domains, thus highlighting the effect of symmetry-breaking at the level of primary sequences. The offshoot is a multi-state and a dynamic conformational landscape that is populated by increasingly partially folded ensembles upon destabilization. Our results provide, in a straightforward fashion, a rationale to the promiscuous binding and short intracellular half-life of IxcexbaBxcexb1 evolutionarily engineered into it through repeats with variable stabilities and expand the functional repertoire of disordered regions in proteins. ');
INSERT INTO `papers` (`id`, `ano`, `journal`, `titulo`, `autores`, `afiliacao`, `pais`, `citacoes`, `palavra_chave`, `categorias`, `doi`, `pubmed`, `abstract`) VALUES
(86363, 2013, 'plos', 'Metabolic and demographic feedbacks shape the emergent spatial structure and function of microbial communities', 'Estrela, Sylvie|Brown, Sam P', 'Institute of Evolutionary Biology, School of Biological Sciences, University of Edinburgh, Edinburgh, United Kingdom , Centre for Immunity, Infection & Evolution, University of Edinburgh, Edinburgh, United Kingdom.|Institute of Evolutionary Biology, School of Biological Sciences, University of Edinburgh, Edinburgh, United Kingdom , Centre for Immunity, Infection & Evolution, University of Edinburgh, Edinburgh, United Kingdom.', 'United Kingdom|United Kingdom', 45, 'Feedback|Microbiota|Models, Biological', 'Journal Article', '10.1371/journal.pcbi.1003398', '24385891', 'Microbes are predominantly found in surface-attached and spatially structured polymicrobial communities. Within these communities, microbial cells excrete a wide range of metabolites, setting the stage for interspecific metabolic interactions. The links, however, between metabolic and ecological interactions (functional relationships), and species spatial organization (structural relationships) are still poorly understood. Here, we use an individual-based modelling framework to simulate the growth of a two-species surface-attached community where food (resource) is traded for detoxification (service) and investigate how metabolic constraints of individual species shape the emergent structural and functional relationships of the community. We show that strong metabolic interdependence drives the emergence of mutualism, robust interspecific mixing, and increased community productivity. Specifically, we observed a striking and highly stable emergent lineage branching pattern, generating a persistent lineage mixing that was absent when the metabolic exchange was removed. These emergent community properties are driven by demographic feedbacks, such that aid from neighbouring cells directly enhances focal cell growth, which in turn feeds back to neighbour fecundity. In contrast, weak metabolic interdependence drives conflict (exploitation or competition), and in turn greater interspecific segregation. Together, these results support the idea that species structural and functional relationships represent the net balance of metabolic interdependencies. '),
(86364, 2013, 'plos', 'Cortically-controlled population stochastic facilitation as a plausible substrate for guiding sensory transfer across the thalamic gateway', 'Béhuret, Sébastien|Deleuze, Charlotte|Gomez, Leonel|Frégnac, Yves|Bal, Thierry', 'Unité de Neurosciences, Information et Complexité (UNIC), CNRS UPR-3293, Gif-sur-Yvette, France.|Unité de Neurosciences, Information et Complexité (UNIC), CNRS UPR-3293, Gif-sur-Yvette, France.|Unité de Neurosciences, Information et Complexité (UNIC), CNRS UPR-3293, Gif-sur-Yvette, France , Laboratorio de Neurociencias, Facultad de Ciencias, Universidad de la República Oriental del Uruguay, Montevideo, Uruguay.|Unité de Neurosciences, Information et Complexité (UNIC), CNRS UPR-3293, Gif-sur-Yvette, France.|Unité de Neurosciences, Information et Complexité (UNIC), CNRS UPR-3293, Gif-sur-Yvette, France.', 'France|France|France|France|France', 9, 'Action Potentials|Cerebral Cortex|Humans|Stochastic Processes|Synapses|Thalamus', 'Journal Article', '10.1371/journal.pcbi.1003401', '24385892', 'The thalamus is the primary gateway that relays sensory information to the cerebral cortex. While a single recipient cortical cell receives the convergence of many principal relay cells of the thalamus, each thalamic cell in turn integrates a dense and distributed synaptic feedback from the cortex. During sensory processing, the influence of this functional loop remains largely ignored. Using dynamic-clamp techniques in thalamic slices in vitro, we combined theoretical and experimental approaches to implement a realistic hybrid retino-thalamo-cortical pathway mixing biological cells and simulated circuits. The synaptic bombardment of cortical origin was mimicked through the injection of a stochastic mixture of excitatory and inhibitory conductances, resulting in a gradable correlation level of afferent activity shared by thalamic cells. The study of the impact of the simulated cortical input on the global retinocortical signal transfer efficiency revealed a novel control mechanism resulting from the collective resonance of all thalamic relay neurons. We show here that the transfer efficiency of sensory input transmission depends on three key features: i) the number of thalamocortical cells involved in the many-to-one convergence from thalamus to cortex, ii) the statistics of the corticothalamic synaptic bombardment and iii) the level of correlation imposed between converging thalamic relay cells. In particular, our results demonstrate counterintuitively that the retinocortical signal transfer efficiency increases when the level of correlation across thalamic cells decreases. This suggests that the transfer efficiency of relay cells could be selectively amplified when they become simultaneously desynchronized by the cortical feedback. When applied to the intact brain, this network regulation mechanism could direct an attentional focus to specific thalamic subassemblies and select the appropriate input lines to the cortex according to the descending influence of cortically-defined priors. '),
(86365, 2013, 'plos', 'Phenome-wide association studies on a quantitative trait: application to TPMT enzyme activity and thiopurine therapy in pharmacogenomics', 'Neuraz, Antoine|Chouchana, Laurent|Malamut, Georgia|Le Beller, Christine|Roche, Denis|Beaune, Philippe|Degoulet, Patrice|Burgun, Anita|Loriot, Marie-Anne|Avillach, Paul', 'Biomedical Informatics and Public Health Department, University Hospital HEGP, AP-HP, Paris, France , INSERM UMR_S 872 Team 22: Information Sciences to support Personalized Medicine, Université Paris Descartes, Sorbonne Paris Cité, Faculté de Médecine, Paris, France.|INSERM UMR-S 775, Université Paris Descartes, Sorbonne Paris Cité, Paris, France.|Gastroenterology Department, University Hospital HEGP, AP-HP, Paris, France.|Pharmacovigilance Center, University Hospital HEGP, AP-HP, Paris, France.|Biochemistry, Pharmacogenetics and Molecular Oncology Unit, University Hospital HEGP, AP-HP, Paris, France.|INSERM UMR-S 775, Université Paris Descartes, Sorbonne Paris Cité, Paris, France , Biochemistry, Pharmacogenetics and Molecular Oncology Unit, University Hospital HEGP, AP-HP, Paris, France.|Biomedical Informatics and Public Health Department, University Hospital HEGP, AP-HP, Paris, France , INSERM UMR_S 872 Team 22: Information Sciences to support Personalized Medicine, Université Paris Descartes, Sorbonne Paris Cité, Faculté de Médecine, Paris, France.|Biomedical Informatics and Public Health Department, University Hospital HEGP, AP-HP, Paris, France , INSERM UMR_S 872 Team 22: Information Sciences to support Personalized Medicine, Université Paris Descartes, Sorbonne Paris Cité, Faculté de Médecine, Paris, France.|INSERM UMR-S 775, Université Paris Descartes, Sorbonne Paris Cité, Paris, France , Biochemistry, Pharmacogenetics and Molecular Oncology Unit, University Hospital HEGP, AP-HP, Paris, France.|Biomedical Informatics and Public Health Department, University Hospital HEGP, AP-HP, Paris, France , INSERM UMR_S 872 Team 22: Information Sciences to support Personalized Medicine, Université Paris Descartes, Sorbonne Paris Cité, Faculté de Médecine, Paris, France.', 'France|France|France|France|France|France|France|France|France|France', 31, 'Genome-Wide Association Study|Humans|International Classification of Diseases|Methyltransferases|Pharmacogenetics|Phenotype|Purines|Quantitative Trait Loci', 'Journal Article', '10.1371/journal.pcbi.1003405', '24385893', 'Phenome-Wide Association Studies (PheWAS) investigate whether genetic polymorphisms associated with a phenotype are also associated with other diagnoses. In this study, we have developed new methods to perform a PheWAS based on ICD-10 codes and biological test results, and to use a quantitative trait as the selection criterion. We tested our approach on thiopurine S-methyltransferase (TPMT) activity in patients treated by thiopurine drugs. We developed 2 aggregation methods for the ICD-10 codes: an ICD-10 hierarchy and a mapping to existing ICD-9-CM based PheWAS codes. Eleven biological test results were also analyzed using discretization algorithms. We applied these methods in patients having a TPMT activity assessment from the clinical data warehouse of a French academic hospital between January 2000 and July 2013. Data after initiation of thiopurine treatment were analyzed and patient groups were compared according to their TPMT activity level. A total of 442 patient records were analyzed representing 10,252 ICD-10 codes and 72,711 biological test results. The results from the ICD-9-CM based PheWAS codes and ICD-10 hierarchy codes were concordant. Cross-validation with the biological test results allowed us to validate the ICD phenotypes. Iron-deficiency anemia and diabetes mellitus were associated with a very high TPMT activity (p = 0.0004 and p = 0.0015, respectively). We describe here an original method to perform PheWAS on a quantitative trait using both ICD-10 diagnosis codes and biological test results to identify associated phenotypes. In the field of pharmacogenomics, PheWAS allow for the identification of new subgroups of patients who require personalized clinical and therapeutic management.'),
(86366, 2013, 'plos', 'The spirit of competition: to win or not to win', 'Szczepinska, Teresa|Iwasaki, Wataru|Abeel, Thomas', 'Institute of Genetics and Biotechnology, Faculty of Biology, University of Warsaw, Warsaw, Poland , Institute of Biochemistry and Biophysics, Polish Academy of Sciences, Warsaw, Poland.|Genetic Research Section, Center for Earth Surface System Dynamics, Atmosphere and Ocean Research Institute, the University of Tokyo, Kashiwa, Chiba, Japan.|Broad Institute of MIT and Harvard, Cambridge, Massachusetts, United States of America , VIB Department of Plant Systems Biology, Ghent University, Belgium.', 'Poland|Japan|Belgium', 0, 'Competitive Behavior|Computational Biology|Humans', 'Journal Article', '10.1371/journal.pcbi.1003413', '24385894', 'A competition is a contest between individuals or groups. The gain is often an award or recognition, which serves as a catalyst to motivate individuals to put forth their very best. Such events for recognition and success are part of many International Society for Computational Biology (ISCB) Student Council Regional Student Groups (RSGs) activities. These include a popular science article contest, a Wikipedia article competition, travel grants, poster and oral presentation awards during conferences, and quizzes at social events. Organizing competitions is no different than any other event, they require a lot of hard work to be successful. Each event gives remarkable organizational and social experience for students running it, while at the same time the participants of the competitions are rewarded by prizes and recognition. It gives everybody involved an opportunity to demonstrate their extraordinary talents and skills. Competitions are unique because they bring out both the best and worst in people. '),
(86367, 2014, 'plos', 'Speed controls in translating secretory proteins in eukaryotes--an evolutionary perspective', 'Mahlab, Shelly|Linial, Michal', 'School of Computer Science and Engineering, The Hebrew University of Jerusalem, Jerusalem, Israel.|Department of Biological Chemistry, Institute of Life Sciences, Sudarsky Center for Computational Biology, The Hebrew University of Jerusalem, Jerusalem, Israel.', 'Israel|Israel', 17, 'Animals|Caenorhabditis elegans|Cattle|Cell Membrane|Cluster Analysis|Codon|Computational Biology|Drosophila melanogaster|Endoplasmic Reticulum|Humans|Plants|Protein Biosynthesis|Protein Folding|Protein Sorting Signals|Protein Structure, Tertiary|Proteins|Proteome|RNA, Transfer|Ribosomes', 'Journal Article', '10.1371/journal.pcbi.1003294', '24391480', 'Protein translation is the most expensive operation in dividing cells from bacteria to humans. Therefore, managing the speed and allocation of resources is subject to tight control. From bacteria to humans, clusters of relatively rare tRNA codons at the N-terminal of mRNAs have been implicated in attenuating the process of ribosome allocation, and consequently the translation rate in a broad range of organisms. The current interpretation of slow tRNA codons does not distinguish between protein translations mediated by free- or endoplasmic reticulum (ER)-bound ribosomes. We demonstrate that proteins translated by free- or ER-bound ribosomes exhibit different overall properties in terms of their translation efficiency and speed in yeast, fly, plant, worm, bovine and human. We note that only secreted or membranous proteins with a Signal peptide (SP) are specified by segments of slow tRNA at the N-terminal, followed by abundant codons that are considered fast. Such profiles apply to 3100 proteins of the human proteome that are composed of secreted and signal peptide (SP)-assisted membranous proteins. Remarkably, the bulks of the proteins (12,000), or membranous proteins lacking SP (3400), do not have such a pattern. Alternation of fast and slow codons was found also in proteins that translocate to mitochondria through transit peptides (TP). The differential clusters of tRNA adapted codons is not restricted to the N-terminal of transcripts. Specifically, Glycosylphosphatidylinositol (GPI)-anchored proteins are unified by clusters of low adapted tRNAs codons at the C-termini. Furthermore, selection of amino acids types and specific codons was shown as the driving force which establishes the translation demands for the secretory proteome. We postulate that hard-coded signals within the secretory proteome assist the steps of protein maturation and folding. Specifically, speed control signals for delaying the translation of a nascent protein fulfill the co- and post-translational stages such as membrane translocation, proteins processing and folding. '),
(86368, 2014, 'plos', 'Enumeration of smallest intervention strategies in genome-scale metabolic networks', 'von Kamp, Axel|Klamt, Steffen', 'Max Planck Institute for Dynamics of Complex Technical Systems, Magdeburg, Germany.|Max Planck Institute for Dynamics of Complex Technical Systems, Magdeburg, Germany.', 'Germany|Germany', 65, 'Algorithms|Computational Biology|Computer Simulation|Escherichia coli|Ethanol|Fumarates|Genome|Genomics|Metabolic Engineering|Models, Theoretical|Serine|Software', 'Journal Article', '10.1371/journal.pcbi.1003378', '24391481', 'One ultimate goal of metabolic network modeling is the rational redesign of biochemical networks to optimize the production of certain compounds by cellular systems. Although several constraint-based optimization techniques have been developed for this purpose, methods for systematic enumeration of intervention strategies in genome-scale metabolic networks are still lacking. In principle, Minimal Cut Sets (MCSs, inclusion-minimal combinations of reaction or gene deletions that lead to the fulfilment of a given intervention goal) provide an exhaustive enumeration approach. However, their disadvantage is the combinatorial explosion in larger networks and the requirement to compute first the elementary modes (EMs) which itself is impractical in genome-scale networks. We present MCSEnumerator, a new method for effective enumeration of the smallest MCSs (with fewest interventions) in genome-scale metabolic network models. For this we combine two approaches, namely (i) the mapping of MCSs to EMs in a dual network, and (ii) a modified algorithm by which shortest EMs can be effectively determined in large networks. In this way, we can identify the smallest MCSs by calculating the shortest EMs in the dual network. Realistic application examples demonstrate that our algorithm is able to list thousands of the most efficient intervention strategies in genome-scale networks for various intervention problems. For instance, for the first time we could enumerate all synthetic lethals in E.coli with combinations of up to 5 reactions. We also applied the new algorithm exemplarily to compute strain designs for growth-coupled synthesis of different products (ethanol, fumarate, serine) by E.coli. We found numerous new engineering strategies partially requiring less knockouts and guaranteeing higher product yields (even without the assumption of optimal growth) than reported previously. The strength of the presented approach is that smallest intervention strategies can be quickly calculated and screened with neither network size nor the number of required interventions posing major challenges. '),
(86369, 2014, 'plos', 'Mathematical modeling of heterogeneous electrophysiological responses in human xcexb2-cells', 'Riz, Michela|Braun, Matthias|Pedersen, Morten Gram', 'Department of Information Engineering, University of Padua, Padua, Italy.|Alberta Diabetes Institute, Department of Pharmacology, University of Alberta, Edmonton, Alberta, Canada.|Department of Information Engineering, University of Padua, Padua, Italy.', 'Italy|Canada|Italy', 39, 'Action Potentials|Algorithms|Animals|Computational Biology|Electrophysiological Phenomena|Glucose|Glycolysis|Humans|Insulin|Insulin Secretion|Insulin-Secreting Cells|Mice|Models, Theoretical|Oscillometry|Pancreas|Potassium|Sodium Channels|Tetrodotoxin', 'Journal Article', '10.1371/journal.pcbi.1003389', '24391482', 'Electrical activity plays a pivotal role in glucose-stimulated insulin secretion from pancreatic xcexb2-cells. Recent findings have shown that the electrophysiological characteristics of human xcexb2-cells differ from their rodent counterparts. We show that the electrophysiological responses in human xcexb2-cells to a range of ion channels antagonists are heterogeneous. In some cells, inhibition of small-conductance potassium currents has no effect on action potential firing, while it increases the firing frequency dramatically in other cells. Sodium channel block can sometimes reduce action potential amplitude, sometimes abolish electrical activity, and in some cells even change spiking electrical activity to rapid bursting. We show that, in contrast to L-type Ca2+-channels, P/Q-type Ca2+-currents are not necessary for action potential generation, and, surprisingly, a P/Q-type Ca2+-channel antagonist even accelerates action potential firing. By including SK-channels and Ca2+ dynamics in a previous mathematical model of electrical activity in human xcexb2-cells, we investigate the heterogeneous and nonintuitive electrophysiological responses to ion channel antagonists, and use our findings to obtain insight in previously published insulin secretion measurements. Using our model we also study paracrine signals, and simulate slow oscillations by adding a glycolytic oscillatory component to the electrophysiological model. The heterogenous electrophysiological responses in human xcexb2-cells must be taken into account for a deeper understanding of the mechanisms underlying insulin secretion in health and disease, and as shown here, the interdisciplinary combination of experiments and modeling increases our understanding of human xcexb2-cell physiology.'),
(86370, 2014, 'plos', 'Environmental influence on the evolution of morphological complexity in machines', 'Auerbach, Joshua E|Bongard, Josh C', 'Laboratory of Intelligent Systems, École Polytechnique Fédérale de Lausanne (EPFL), Lausanne, Switzerland.|Department of Computer Science, University of Vermont, Burlington, Vermont, United States of America.', 'Switzerland|United States', 65, 'Biological Evolution|Computational Biology|Computer Simulation|Environment|Genome|Humans|Locomotion|Models, Biological|Models, Genetic|Neural Networks (Computer)', 'Journal Article', '10.1371/journal.pcbi.1003399', '24391483', 'Whether, when, how, and why increased complexity evolves in biological populations is a longstanding open question. In this work we combine a recently developed method for evolving virtual organisms with an information-theoretic metric of morphological complexity in order to investigate how the complexity of morphologies, which are evolved for locomotion, varies across different environments. We first demonstrate that selection for locomotion results in the evolution of organisms with morphologies that increase in complexity over evolutionary time beyond what would be expected due to random chance. This provides evidence that the increase in complexity observed is a result of a driven rather than a passive trend. In subsequent experiments we demonstrate that morphologies having greater complexity evolve in complex environments, when compared to a simple environment when a cost of complexity is imposed. This suggests that in some niches, evolution may act to complexify the body plans of organisms while in other niches selection favors simpler body plans. '),
(86371, 2014, 'plos', 'Optimal screening strategies for healthcare associated infections in a multi-institutional setting', 'Miller, Aaron C|Polgreen, Linnea A|Polgreen, Philip M', 'Department of Pharmacy Practice & Science, University of Iowa College of Pharmacy, Iowa City, Iowa, United States of America.|Department of Pharmacy Practice & Science, University of Iowa College of Pharmacy, Iowa City, Iowa, United States of America.|Division of Infectious Diseases, Department of Internal Medicine, University of Iowa Carver College of Medicine, Iowa City, Iowa, United States of America.', 'United States|United States|United States', 2, 'Algorithms|Communicable Disease Control|Communicable Diseases|Computational Biology|Cross Infection|Health Care Costs|Humans|Mass Screening|Medical Informatics|Models, Economic|Multivariate Analysis|Prevalence|Sensitivity and Specificity', 'Journal Article', '10.1371/journal.pcbi.1003407', '24391484', 'Health institutions may choose to screen newly admitted patients for the presence of disease in order to reduce disease prevalence within the institution. Screening is costly, and institutions must judiciously choose which patients they wish to screen based on the dynamics of disease transmission. Since potentially infected patients move between different health institutions, the screening and treatment decisions of one institution will affect the optimal decisions of others, an institution might choose to free-ride off the screening and treatment decisions of neighboring institutions. We develop a theoretical model of the strategic decision problem facing a health care institution choosing to screen newly admitted patients. The model incorporates an SIS compartmental model of disease transmission into a game theoretic model of strategic decision-making. Using this setup, we are able to analyze how optimal screening is influenced by disease parameters, such as the efficacy of treatment, the disease recovery rate and the movement of patients. We find that the optimal screening level is lower for diseases that have more effective treatments. Our model also allows us to analyze how the optimal screening level varies with the number of decision makers involved in the screening process. We show that when institutions are more autonomous in selecting whom to screen, they will choose to screen at a lower rate than when screening decisions are more centralized. Results also suggest that centralized screening decisions have a greater impact on disease prevalence when the availability or efficacy of treatment is low. Our model provides insight into the factors one should consider when choosing whether to set a mandated screening policy. We find that screening mandates set at a centralized level (i.e. state or national) will have a greater impact on the control of infectious disease. '),
(86372, 2014, 'plos', 'Searching for collective behavior in a large network of sensory neurons', 'Tkaxc4x8dik, Gaxc5xa1per|Marre, Olivier|Amodei, Dario|Schneidman, Elad|Bialek, William|Berry, Michael J', 'Institute of Science and Technology Austria, Klosterneuburg, Austria.|Institut de la Vision, INSERM U968, UPMC, CNRS U7210, CHNO Quinze-Vingts, Paris, France , Department of Molecular Biology, Princeton Neuroscience Institute, Princeton University, Princeton, New Jersey, United States of America.|Department of Molecular Biology, Princeton Neuroscience Institute, Princeton University, Princeton, New Jersey, United States of America , Joseph Henry Laboratories of Physics, Princeton University, Princeton, New Jersey, United States of America.|Department of Neurobiology, Weizmann Institute of Science, Rehovot, Israel.|Joseph Henry Laboratories of Physics, Princeton University, Princeton, New Jersey, United States of America , Lewis-Sigler Institute for Integrative Genomics, Princeton University, Princeton, New Jersey, United States of America.|Department of Molecular Biology, Princeton Neuroscience Institute, Princeton University, Princeton, New Jersey, United States of America.', 'Austria|France|Jersey|Israel|Jersey|Jersey', 111, 'Action Potentials|Animals|Computational Biology|Entropy|Fishes|Models, Neurological|Movement|Nerve Net|Probability|Retina|Sensory Receptor Cells|Urodela', 'Journal Article', '10.1371/journal.pcbi.1003408', '24391485', 'Maximum entropy models are the least structured probability distributions that exactly reproduce a chosen set of statistics measured in an interacting network. Here we use this principle to construct probabilistic models which describe the correlated spiking activity of populations of up to 120 neurons in the salamander retina as it responds to natural movies. Already in groups as small as 10 neurons, interactions between spikes can no longer be regarded as small perturbations in an otherwise independent system, for 40 or more neurons pairwise interactions need to be supplemented by a global interaction that controls the distribution of synchrony in the population. Here we show that such K-pairwise models--being systematic extensions of the previously used pairwise Ising models--provide an excellent account of the data. We explore the properties of the neural vocabulary by: 1) estimating its entropy, which constrains the populations capacity to represent visual information, 2) classifying activity patterns into a small set of metastable collective modes, 3) showing that the neural codeword ensembles are extremely inhomogenous, 4) demonstrating that the state of individual neurons is highly predictable from the rest of the population, allowing the capacity for error correction.'),
(86373, 2014, 'plos', 'Encoding of natural sounds at multiple spectral and temporal resolutions in the human auditory cortex', 'Santoro, Roberta|Moerel, Michelle|De Martino, Federico|Goebel, Rainer|Ugurbil, Kamil|Yacoub, Essa|Formisano, Elia', 'Department of Cognitive Neuroscience, Faculty of Psychology and Neuroscience, Maastricht University, Maastricht, The Netherlands , Maastricht Brain Imaging Center (MBIC), Maastricht, The Netherlands.|Department of Cognitive Neuroscience, Faculty of Psychology and Neuroscience, Maastricht University, Maastricht, The Netherlands , Maastricht Brain Imaging Center (MBIC), Maastricht, The Netherlands.|Department of Cognitive Neuroscience, Faculty of Psychology and Neuroscience, Maastricht University, Maastricht, The Netherlands , Maastricht Brain Imaging Center (MBIC), Maastricht, The Netherlands , Center for Magnetic Resonance Research, Department of Radiology, University of Minnesota, Minneapolis, Minnesota, United States of America.|Department of Cognitive Neuroscience, Faculty of Psychology and Neuroscience, Maastricht University, Maastricht, The Netherlands , Maastricht Brain Imaging Center (MBIC), Maastricht, The Netherlands , Department of Neuroimaging and Neuromodeling, Netherlands Institute for Neuroscience, Royal Netherlands Academy of Arts and Sciences (KNAW), Amsterdam, The Netherlands.|Center for Magnetic Resonance Research, Department of Radiology, University of Minnesota, Minneapolis, Minnesota, United States of America.|Center for Magnetic Resonance Research, Department of Radiology, University of Minnesota, Minneapolis, Minnesota, United States of America.|Department of Cognitive Neuroscience, Faculty of Psychology and Neuroscience, Maastricht University, Maastricht, The Netherlands , Maastricht Brain Imaging Center (MBIC), Maastricht, The Netherlands.', 'Netherlands|Netherlands|Netherlands|Netherlands|United States|United States|Netherlands', 90, 'Acoustic Stimulation|Auditory Cortex|Auditory Perception|Brain|Brain Mapping|Hearing|Humans|Image Processing, Computer-Assisted|Magnetic Resonance Imaging|Reproducibility of Results|Signal-To-Noise Ratio|Software|Sound|Speech|Time Factors', 'Journal Article', '10.1371/journal.pcbi.1003412', '24391486', 'Functional neuroimaging research provides detailed observations of the response patterns that natural sounds (e.g. human voices and speech, animal cries, environmental sounds) evoke in the human brain. The computational and representational mechanisms underlying these observations, however, remain largely unknown. Here we combine high spatial resolution (3 and 7 Tesla) functional magnetic resonance imaging (fMRI) with computational modeling to reveal how natural sounds are represented in the human brain. We compare competing models of sound representations and select the model that most accurately predicts fMRI response patterns to natural sounds. Our results show that the cortical encoding of natural sounds entails the formation of multiple representations of sound spectrograms with different degrees of spectral and temporal resolution. The cortex derives these multi-resolution representations through frequency-specific neural processing channels and through the combined analysis of the spectral and temporal modulations in the spectrogram. Furthermore, our findings suggest that a spectral-temporal resolution trade-off may govern the modulation tuning of neuronal populations throughout the auditory cortex. Specifically, our fMRI results suggest that neuronal populations in posterior/dorsal auditory regions preferably encode coarse spectral information with high temporal precision. Vice-versa, neuronal populations in anterior/ventral auditory regions preferably encode fine-grained spectral information with low temporal precision. We propose that such a multi-resolution analysis may be crucially relevant for flexible and behaviorally-relevant sound processing and may constitute one of the computational underpinnings of functional specialization in auditory cortex. '),
(86374, 2014, 'plos', 'Population decoding in rat barrel cortex: optimizing the linear readout of correlated population responses', 'Adibi, Mehdi|McDonald, James S|Clifford, Colin W G|Arabzadeh, Ehsan', 'School of Psychology, University of New South Wales, Sydney, New South Wales, Australia , Eccles Institute of Neuroscience, John Curtin School of Medical Research, The Australian National University, Canberra, Australian Capital Territory, Australia.|School of Psychology, University of New South Wales, Sydney, New South Wales, Australia.|School of Psychology & Australian Centre of Excellence in Vision Science, University of Sydney, Sydney, New South Wales, Australia.|School of Psychology, University of New South Wales, Sydney, New South Wales, Australia , Eccles Institute of Neuroscience, John Curtin School of Medical Research, The Australian National University, Canberra, Australian Capital Territory, Australia.', 'Australia|Australia|Australia|Australia', 18, 'Adaptation, Physiological|Algorithms|Animals|Cerebral Cortex|Electrophysiological Phenomena|Linear Models|Male|Neurons|ROC Curve|Rats|Rats, Wistar|Reproducibility of Results|Signal Processing, Computer-Assisted|Signal-To-Noise Ratio|Somatosensory Cortex', 'Journal Article', '10.1371/journal.pcbi.1003415', '24391487', 'Sensory information is encoded in the response of neuronal populations. How might this information be decoded by downstream neurons? Here we analyzed the responses of simultaneously recorded barrel cortex neurons to sinusoidal vibrations of varying amplitudes preceded by three adapting stimuli of 0, 6 and 12 µm in amplitude. Using the framework of signal detection theory, we quantified the performance of a linear decoder which sums the responses of neurons after applying an optimum set of weights. Optimum weights were found by the analytical solution that maximized the average signal-to-noise ratio based on Fisher linear discriminant analysis. This provided a biologically plausible decoder that took into account the neuronal variability, covariability, and signal correlations. The optimal decoder achieved consistent improvement in discrimination performance over simple pooling. Decorrelating neuronal responses by trial shuffling revealed that, unlike pooling, the performance of the optimal decoder was minimally affected by noise correlation. In the non-adapted state, noise correlation enhanced the performance of the optimal decoder for some populations. Under adaptation, however, noise correlation always degraded the performance of the optimal decoder. Nonetheless, sensory adaptation improved the performance of the optimal decoder mainly by increasing signal correlation more than noise correlation. Adaptation induced little systematic change in the relative direction of signal and noise. Thus, a decoder which was optimized under the non-adapted state generalized well across states of adaptation. '),
(86375, 2014, 'plos', 'A multi-scale model of hepcidin promoter regulation reveals factors controlling systemic iron homeostasis', 'Casanovas, Guillem|Banerji, Anashua|dAlessio, Flavia|Muckenthaler, Martina U|Legewie, Stefan', 'Department of Pediatric Oncology, Hematology and Immunology, University Hospital of Heidelberg, Heidelberg, Germany , Molecular Medicine Partnership Unit, Heidelberg, Germany , European Molecular Biology Laboratory, Heidelberg, Germany.|Institute of Molecular Biology (IMB), Mainz, Germany , BioQuant, Heidelberg, Germany.|Department of Pediatric Oncology, Hematology and Immunology, University Hospital of Heidelberg, Heidelberg, Germany , Molecular Medicine Partnership Unit, Heidelberg, Germany , European Molecular Biology Laboratory, Heidelberg, Germany.|Department of Pediatric Oncology, Hematology and Immunology, University Hospital of Heidelberg, Heidelberg, Germany , Molecular Medicine Partnership Unit, Heidelberg, Germany , European Molecular Biology Laboratory, Heidelberg, Germany.|Institute of Molecular Biology (IMB), Mainz, Germany , BioQuant, Heidelberg, Germany.', 'Germany|Germany|Germany|Germany|Germany', 15, 'Algorithms|Bone Morphogenetic Proteins|Cell Line, Tumor|Gene Expression Profiling|Gene Expression Regulation|Genes, Reporter|Hepcidins|Homeostasis|Humans|Inflammation|Interleukin-6|Iron|Models, Theoretical|Mutagenesis|Peptides|Phosphorylation|Promoter Regions, Genetic|Signal Transduction|Thermodynamics|Transcription Factors', 'Journal Article', '10.1371/journal.pcbi.1003421', '24391488', 'Systemic iron homeostasis involves a negative feedback circuit in which the expression level of the peptide hormone hepcidin depends on and controls the iron blood levels. Hepcidin expression is regulated by the BMP6/SMAD and IL6/STAT signaling cascades. Deregulation of either pathway causes iron-related diseases such as hemochromatosis or anemia of inflammation. We quantitatively analyzed how BMP6 and IL6 control hepcidin expression. Transcription factor (TF) phosphorylation and reporter gene expression were measured under co-stimulation conditions, and the promoter was perturbed by mutagenesis. Using mathematical modeling, we systematically analyzed potential mechanisms of cooperative and competitive promoter regulation by the transcription factors, and experimentally validated the model predictions. Our results reveal that hepcidin cross-regulation primarily occurs by combinatorial transcription factor binding to the promoter, whereas signaling crosstalk is insignificant. We find that the presence of two BMP-responsive elements enhances the steepness of the promoter response towards the iron-sensing BMP signaling axis, which promotes iron homeostasis in vivo. IL6 co-stimulation reduces the promoter sensitivity towards the BMP signal, because the SMAD and STAT transcription factors compete for recruiting RNA polymerase to the transcription start site. This may explain why inflammatory signals disturb iron homeostasis in anemia of inflammation. Taken together, our results reveal why the iron homeostasis circuit is sensitive to perturbations implicated in disease. '),
(86376, 2014, 'plos', 'The significance of the 2013 Nobel Prize in Chemistry and the challenges ahead', 'Nussinov, Ruth', '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.', 'Israel', 7, 'Algorithms|Chemistry|Computational Biology|Computer Simulation|Humans|Nobel Prize', 'Editorial', '10.1371/journal.pcbi.1003423', '24391489', '-'),
(86377, 2014, 'plos', 'Task-specific response strategy selection on the basis of recent training experience', 'Fulvio, Jacqueline M|Green, C Shawn|Schrater, Paul R', 'Department of Psychology, University of Wisconsin-Madison, Madison, Wisconsin, United States of America.|Department of Psychology, University of Wisconsin-Madison, Madison, Wisconsin, United States of America.|Department of Psychology, University of Minnesota, Minneapolis, Minnesota, United States of America , Center for Cognitive Sciences, University of Minnesota, Minneapolis, Minnesota, United States of America.', 'United States|United States|United States', 12, 'Algorithms|Computer Simulation|Decision Making|Feedback, Psychological|Humans|Learning|Models, Theoretical|Time Factors|Vision, Ocular', 'Journal Article', '10.1371/journal.pcbi.1003425', '24391490', 'The goal of training is to produce learning for a range of activities that are typically more general than the training task itself. Despite a century of research, predicting the scope of learning from the content of training has proven extremely difficult, with the same task producing narrowly focused learning strategies in some cases and broadly scoped learning strategies in others. Here we test the hypothesis that human subjects will prefer a decision strategy that maximizes performance and reduces uncertainty given the demands of the training task and that the strategy chosen will then predict the extent to which learning is transferable. To test this hypothesis, we trained subjects on a moving dot extrapolation task that makes distinct predictions for two types of learning strategy: a narrow model-free strategy that learns an input-output mapping for training stimuli, and a general model-based strategy that utilizes humans default predictive model for a class of trajectories. When the number of distinct training trajectories is low, we predict better performance for the mapping strategy, but as the number increases, a predictive model is increasingly favored. Consonant with predictions, subject extrapolations for test trajectories were consistent with using a mapping strategy when trained on a small number of training trajectories and a predictive model when trained on a larger number. The general framework developed here can thus be useful both in interpreting previous patterns of task-specific versus task-general learning, as well as in building future training paradigms with certain desired outcomes. '),
(86378, 2014, 'plos', 'Interference and shaping in sensorimotor adaptations with rewards', 'Darshan, Ran|Leblois, Arthur|Hansel, David', 'Edmond and Lily Safra Center for Brain Sciences, The Hebrew University, Jerusalem, Israel , Laboratoire de Neurophysique et Physiologie UMR8119-CNRS Université René Descartes, Paris, France , Interdisciplinary Center for Neural Computation, The Hebrew University, Jerusalem, Israel.|Laboratoire de Neurophysique et Physiologie UMR8119-CNRS Université René Descartes, Paris, France.|Laboratoire de Neurophysique et Physiologie UMR8119-CNRS Université René Descartes, Paris, France , Interdisciplinary Center for Neural Computation, The Hebrew University, Jerusalem, Israel , The Alexander Silberman Institute of Life Sciences, The Hebrew University of Jerusalem, Israel.', 'France|France|France', 11, 'Adaptation, Physiological|Algorithms|Biomechanical Phenomena|Brain|Computational Biology|Computer Simulation|Feedback, Sensory|Humans|Learning|Models, Neurological|Movement|Neuronal Plasticity|Neurons|Psychomotor Performance|Reproducibility of Results|Reward|Rotation|Synapses', 'Journal Article', '10.1371/journal.pcbi.1003377', '24415925', 'When a perturbation is applied in a sensorimotor transformation task, subjects can adapt and maintain performance by either relying on sensory feedback, or, in the absence of such feedback, on information provided by rewards. For example, in a classical rotation task where movement endpoints must be rotated to reach a fixed target, human subjects can successfully adapt their reaching movements solely on the basis of binary rewards, although this proves much more difficult than with visual feedback. Here, we investigate such a reward-driven sensorimotor adaptation process in a minimal computational model of the task. The key assumption of the model is that synaptic plasticity is gated by the reward. We study how the learning dynamics depend on the target size, the movement variability, the rotation angle and the number of targets. We show that when the movement is perturbed for multiple targets, the adaptation process for the different targets can interfere destructively or constructively depending on the similarities between the sensory stimuli (the targets) and the overlap in their neuronal representations. Destructive interferences can result in a drastic slowdown of the adaptation. As a result of interference, the time to adapt varies non-linearly with the number of targets. Our analysis shows that these interferences are weaker if the reward varies smoothly with the subjects performance instead of being binary. We demonstrate how shaping the reward or shaping the task can accelerate the adaptation dramatically by reducing the destructive interferences. We argue that experimentally investigating the dynamics of reward-driven sensorimotor adaptation for more than one sensory stimulus can shed light on the underlying learning rules. '),
(86379, 2014, 'plos', 'Stress and strain provide positional and directional cues in development', 'Bozorg, Behruz|Krupinski, Pawel|Jönsson, Henrik', 'Computational Biology & Biological Physics, Lund University, Lund, Sweden.|Computational Biology & Biological Physics, Lund University, Lund, Sweden.|Computational Biology & Biological Physics, Lund University, Lund, Sweden , Sainsbury Laboratory, Cambridge University, Cambridge, United Kingdom.', 'Sweden|Sweden|United Kingdom', 50, 'Anisotropy|Cellulose|Computational Biology|Computer Simulation|Finite Element Analysis|Meristem|Plant Development|Plant Physiological Phenomena|Poisson Distribution|Pressure|Programming Languages|Software|Stress, Mechanical', 'Journal Article', '10.1371/journal.pcbi.1003410', '24415926', 'The morphogenesis of organs necessarily involves mechanical interactions and changes in mechanical properties of a tissue. A long standing question is how such changes are directed on a cellular scale while being coordinated at a tissular scale. Growing evidence suggests that mechanical cues are participating in the control of growth and morphogenesis during development. We introduce a mechanical model that represents the deposition of cellulose fibers in primary plant walls. In the model both the degree of material anisotropy and the anisotropy direction are regulated by stress anisotropy. We show that the finite element shell model and the simpler triangular biquadratic springs approach provide equally adequate descriptions of cell mechanics in tissue pressure simulations of the epidermis. In a growing organ, where circumferentially organized fibers act as a main controller of longitudinal growth, we show that the fiber direction can be correlated with both the maximal stress direction and the direction orthogonal to the maximal strain direction. However, when dynamic updates of the fiber direction are introduced, the mechanical stress provides a robust directional cue for the circumferential organization of the fibers, whereas the orthogonal to maximal strain model leads to an unstable situation where the fibers reorient longitudinally. Our investigation of the more complex shape and growth patterns in the shoot apical meristem where new organs are initiated shows that a stress based feedback on fiber directions is capable of reproducing the main features of in vivo cellulose fiber directions, deformations and material properties in different regions of the shoot. In particular, we show that this purely mechanical model can create radially distinct regions such that cells expand slowly and isotropically in the central zone while cells at the periphery expand more quickly and in the radial direction, which is a well established growth pattern in the meristem. '),
(86380, 2014, 'plos', 'Intrinsic noise induces critical behavior in leaky Markovian networks leading to avalanching', 'Jenkinson, Garrett|Goutsias, John', 'Whitaker Biomedical Engineering Institute, The Johns Hopkins University, Baltimore, Maryland, United States of America.|Whitaker Biomedical Engineering Institute, The Johns Hopkins University, Baltimore, Maryland, United States of America.', 'United States|United States', 1, 'Algorithms|Bacterial Infections|Computational Biology|Computer Simulation|Entropy|Humans|Infectious Disease Medicine|Markov Chains|Models, Theoretical|Neurosciences|Normal Distribution|Stress, Mechanical|Thermodynamics', 'Journal Article', '10.1371/journal.pcbi.1003411', '24415927', 'The role intrinsic statistical fluctuations play in creating avalanches--patterns of complex bursting activity with scale-free properties--is examined in leaky Markovian networks. Using this broad class of models, we develop a probabilistic approach that employs a potential energy landscape perspective coupled with a macroscopic description based on statistical thermodynamics. We identify six important thermodynamic quantities essential for characterizing system behavior as a function of network size: the internal potential energy, entropy, free potential energy, internal pressure, pressure, and bulk modulus. In agreement with classical phase transitions, these quantities evolve smoothly as a function of the network size until a critical value is reached. At that value, a discontinuity in pressure is observed that leads to a spike in the bulk modulus demarcating loss of thermodynamic robustness. We attribute this novel result to a reallocation of the ground states (global minima) of the systems stationary potential energy landscape caused by a noise-induced deformation of its topographic surface. Further analysis demonstrates that appreciable levels of intrinsic noise can cause avalanching, a complex mode of operation that dominates system dynamics at near-critical or subcritical network sizes. Illustrative examples are provided using an epidemiological model of bacterial infection, where avalanching has not been characterized before, and a previously studied model of computational neuroscience, where avalanching was erroneously attributed to specific neural architectures. The general methods developed here can be used to study the emergence of avalanching (and other complex phenomena) in many biological, physical and man-made interaction networks.');
INSERT INTO `papers` (`id`, `ano`, `journal`, `titulo`, `autores`, `afiliacao`, `pais`, `citacoes`, `palavra_chave`, `categorias`, `doi`, `pubmed`, `abstract`) VALUES
(86381, 2014, 'plos', 'Competition for antigen between Th1 and Th2 responses determines the timing of the immune response switch during Mycobaterium avium subspecies paratuberulosis infection in ruminants', 'Magombedze, Gesham|Eda, Shigetoshi|Ganusov, Vitaly V', 'National Institute for Mathematical and Biological Synthesis, University of Tennessee, Knoxville, Tennesse, United States of America.|Department of Forestry, Wildlife, and Fisheries, University of Tennessee, Knoxville, Tennesse, United States of America.|National Institute for Mathematical and Biological Synthesis, University of Tennessee, Knoxville, Tennesse, United States of America , Department of Microbiology, University of Tennessee, Knoxville, Tennesse, United States of America , Department of Mathematics, University of Tennessee, Knoxville, Tennesse, United States of America.', 'United States|United States|United States', 29, 'Algorithms|Animals|Computer Simulation|Disease Progression|Immunity, Cellular|Macrophages|Models, Biological|Mycobacterium avium subsp. paratuberculosis|Paratuberculosis|Ruminants|Sheep|Th1 Cells|Th2 Cells', 'Journal Article', '10.1371/journal.pcbi.1003414', '24415928', 'Johnes disease (JD), a persistent and slow progressing infection of ruminants such as cows and sheep, is caused by slow replicating bacilli Mycobacterium avium subspecies paratuberculosis (MAP) infecting macrophages in the gut. Infected animals initially mount a cell-mediated CD4 T cell response against MAP which is characterized by the production of interferon gamma (Th1 response). Over time, Th1 response diminishes in most animals and antibody response to MAP antigens becomes dominant (Th2 response). The switch from Th1 to Th2 response occurs concomitantly with disease progression and shedding of the bacteria in feces. Mechanisms controlling this Th1/Th2 switch remain poorly understood. Because Th1 and Th2 responses are known to cross-inhibit each other, it is unclear why initially strong Th1 response is lost over time. Using a novel mathematical model of the immune response to MAP infection we show that the ability of extracellular bacteria to persist outside of macrophages naturally leads to switch of the cellular response to antibody production. Several additional mechanisms may also contribute to the timing of the Th1/Th2 switch including the rate of proliferation of Th1/Th2 responses at the site of infection, efficiency at which immune responses cross-inhibit each other, and the rate at which Th1 response becomes exhausted over time. Our basic model reasonably well explains four different kinetic patterns of the Th1/Th2 responses in MAP-infected sheep by variability in the initial bacterial dose and the efficiency of the MAP-specific T cell responses. Taken together, our novel mathematical model identifies factors of bacterial and host origin that drive kinetics of the immune response to MAP and provides the basis for testing the impact of vaccination or early treatment on the duration of infection.'),
(86382, 2014, 'plos', 'The free energy landscape of dimerization of a membrane protein, NanC', 'Dunton, Thomas A|Goose, Joseph E|Gavaghan, David J|Sansom, Mark S P|Osborne, James M', 'Department of Computer Science, University of Oxford, Oxford, United Kingdom.|Department of Biochemistry, University of Oxford, Oxford, United Kingdom.|Department of Computer Science, University of Oxford, Oxford, United Kingdom.|Department of Biochemistry, University of Oxford, Oxford, United Kingdom.|Department of Computer Science, University of Oxford, Oxford, United Kingdom.', 'United Kingdom|United Kingdom|United Kingdom|United Kingdom|United Kingdom', 0, 'Bacterial Outer Membrane Proteins|Escherichia coli|Escherichia coli Proteins|Lipid Bilayers|Models, Molecular|Molecular Dynamics Simulation|Phospholipids|Porins|Protein Conformation|Protein Multimerization', 'Journal Article', '10.1371/journal.pcbi.1003417', '24415929', 'Membrane proteins are frequently present in crowded environments, which favour lateral association and, on occasions, two-dimensional crystallization. To better understand the non-specific lateral association of a membrane protein we have characterized the free energy landscape for the dimerization of a bacterial outer membrane protein, NanC, in a phospholipid bilayer membrane. NanC is a member of the KdgM-family of bacterial outer membrane proteins and is responsible for sialic acid transport in E. coli. Umbrella sampling and coarse-grained molecular dynamics were employed to calculate the potentials of mean force (PMF) for a variety of restrained relative orientations of two NanC proteins as the separation of their centres of mass was varied. We found the free energy of dimerization for NanC to be in the range of -66 kJ mol(-1) to -45 kJ mol(-1). Differences in the depths of the PMFs for the various orientations are related to the shape of the proteins. This was quantified by calculating the lipid-inaccessible buried surface area of the proteins in the region around the minimum of each PMF. The depth of the potential well of the PMF was shown to depend approximately linearly on the buried surface area. We were able to resolve local minima in the restrained PMFs that would not be revealed using conventional umbrella sampling. In particular, these features reflected the local organization of the intervening lipids between the two interacting proteins. Through a comparison with the distribution of lipids around a single freely-diffusing NanC, we were able to predict the location of these restrained local minima for the orientational configuration in which they were most pronounced. Our ability to make this prediction highlights the important role that lipid organization plays in the association of two NanCs in a bilayer.'),
(86383, 2014, 'plos', 'The role of thalamic population synchrony in the emergence of cortical feature selectivity', 'Kelly, Sean T|Kremkow, Jens|Jin, Jianzhong|Wang, Yushi|Wang, Qi|Alonso, Jose-Manuel|Stanley, Garrett B', 'Coulter Dept. of Biomedical Engineering, Georgia Institute of Technology, Emory University, Atlanta, Georgia, United States of America.|Department of Biological Sciences, State University of New York, College of Optometry, New York, New York, United States of America.|Department of Biological Sciences, State University of New York, College of Optometry, New York, New York, United States of America.|Department of Biological Sciences, State University of New York, College of Optometry, New York, New York, United States of America.|Department of Biomedical Engineering, Columbia University, New York, New York, United States of America.|Department of Biological Sciences, State University of New York, College of Optometry, New York, New York, United States of America.|Coulter Dept. of Biomedical Engineering, Georgia Institute of Technology, Emory University, Atlanta, Georgia, United States of America.', 'Georgia|United States|United States|United States|United States|United States|Georgia', 10, 'Algorithms|Animals|Cats|Cerebral Cortex|Computer Simulation|Electrophysiological Phenomena|Geniculate Bodies|Male|Models, Neurological|Neural Inhibition|Neurons|Normal Distribution|Probability|Thalamus|Visual Cortex|Visual Pathways', 'Journal Article', '10.1371/journal.pcbi.1003418', '24415930', 'In a wide range of studies, the emergence of orientation selectivity in primary visual cortex has been attributed to a complex interaction between feed-forward thalamic input and inhibitory mechanisms at the level of cortex. Although it is well known that layer 4 cortical neurons are highly sensitive to the timing of thalamic inputs, the role of the stimulus-driven timing of thalamic inputs in cortical orientation selectivity is not well understood. Here we show that the synchronization of thalamic firing contributes directly to the orientation tuned responses of primary visual cortex in a way that optimizes the stimulus information per cortical spike. From the recorded responses of geniculate X-cells in the anesthetized cat, we synthesized thalamic sub-populations that would likely serve as the synaptic input to a common layer 4 cortical neuron based on anatomical constraints. We used this synchronized input as the driving input to an integrate-and-fire model of cortical responses and demonstrated that the tuning properties match closely to those measured in primary visual cortex. By modulating the overall level of synchronization at the preferred orientation, we show that efficiency of information transmission in the cortex is maximized for levels of synchronization which match those reported in thalamic recordings in response to naturalistic stimuli, a property which is relatively invariant to the orientation tuning width. These findings indicate evidence for a more prominent role of the feed-forward thalamic input in cortical feature selectivity based on thalamic synchronization. '),
(86384, 2014, 'plos', 'Communication efficiency and congestion of signal traffic in large-scale brain networks', 'Mixc5xa1ixc4x87, Bratislav|Sporns, Olaf|McIntosh, Anthony R', 'Rotman Research Institute, Baycrest Centre, Toronto, Canada , Department of Psychology, University of Toronto, Toronto, Canada.|Department of Psychological and Brain Sciences, Indiana University, Bloomington, Indiana, United States of America.|Rotman Research Institute, Baycrest Centre, Toronto, Canada , Department of Psychology, University of Toronto, Toronto, Canada.', 'Canada|India|Canada', 59, 'Algorithms|Animals|Brain|Brain Mapping|Cerebral Cortex|Computer Simulation|Macaca|Models, Neurological|Nerve Net|Neural Pathways|Signal Transduction', 'Journal Article', '10.1371/journal.pcbi.1003427', '24415931', 'The complex connectivity of the cerebral cortex suggests that inter-regional communication is a primary function. Using computational modeling, we show that anatomical connectivity may be a major determinant for global information flow in brain networks. A macaque brain network was implemented as a communication network in which signal units flowed between grey matter nodes along white matter paths. Compared to degree-matched surrogate networks, information flow on the macaque brain network was characterized by higher loss rates, faster transit times and lower throughput, suggesting that neural connectivity may be optimized for speed rather than fidelity. Much of global communication was mediated by a rich club of hub regions: a sub-graph comprised of high-degree nodes that are more densely interconnected with each other than predicted by chance. First, macaque communication patterns most closely resembled those observed for a synthetic rich club network, but were less similar to those seen in a synthetic small world network, suggesting that the former is a more fundamental feature of brain network topology. Second, rich club regions attracted the most signal traffic and likewise, connections between rich club regions carried more traffic than connections between non-rich club regions. Third, a number of rich club regions were significantly under-congested, suggesting that macaque connectivity actively shapes information flow, funneling traffic towards some nodes and away from others. Together, our results indicate a critical role of the rich club of hub nodes in dynamic aspects of global brain communication. '),
(86385, 2014, 'plos', 'Linkage of viral sequences among HIV-infected village residents in Botswana: estimation of linkage rates in the presence of missing data', 'Carnegie, Nicole Bohme|Wang, Rui|Novitsky, Vladimir|De Gruttola, Victor', 'Department of Biostatistics, Harvard School of Public Health, Boston, Massachusetts, United States of America.|Department of Biostatistics, Harvard School of Public Health, Boston, Massachusetts, United States of America , Division of Sleep Medicine, Brigham and Womens Hospital, Boston, Massachusetts, United States of America.|Department of Immunology and Infectious Diseases, Harvard School of Public Health, Boston, Massachusetts, United States of America.|Department of Biostatistics, Harvard School of Public Health, Boston, Massachusetts, United States of America.', 'United States|United States|United States|United States', 9, 'Algorithms|Anti-Retroviral Agents|Botswana|Communicable Disease Control|Computer Simulation|Genetic Linkage|Genotype|HIV|HIV Envelope Protein gp120|HIV Infections|Humans|Molecular Epidemiology|Probability|Randomized Controlled Trials as Topic', 'Journal Article', '10.1371/journal.pcbi.1003430', '24415932', 'Linkage analysis is useful in investigating disease transmission dynamics and the effect of interventions on them, but estimates of probabilities of linkage between infected people from observed data can be biased downward when missingness is informative. We investigate variation in the rates at which subjects viral genotypes link across groups defined by viral load (low/high) and antiretroviral treatment (ART) status using blood samples from household surveys in the Northeast sector of Mochudi, Botswana. The probability of obtaining a sequence from a sample varies with viral load, samples with low viral load are harder to amplify. Pairwise genetic distances were estimated from aligned nucleotide sequences of HIV-1C env gp120. It is first shown that the probability that randomly selected sequences are linked can be estimated consistently from observed data. This is then used to develop estimates of the probability that a sequence from one group links to at least one sequence from another group under the assumption of independence across pairs. Furthermore, a resampling approach is developed that accounts for the presence of correlation across pairs, with diagnostics for assessing the reliability of the method. Sequences were obtained for 65% of subjects with high viral load (HVL, nxe2x80x8a=xe2x80x8a117), 54% of subjects with low viral load but not on ART (LVL, nxe2x80x8a=xe2x80x8a180), and 45% of subjects on ART (ART, nxe2x80x8a=xe2x80x8a126). The probability of linkage between two individuals is highest if both have HVL, and lowest if one has LVL and the other has LVL or is on ART. Linkage across groups is high for HVL and lower for LVL and ART. Adjustment for missing data increases the group-wise linkage rates by 40-100%, and changes the relative rates between groups. Bias in inferences regarding HIV viral linkage that arise from differential ability to genotype samples can be reduced by appropriate methods for accommodating missing data. '),
(86386, 2014, 'plos', 'Induction of Wnt-inducible signaling protein-1 correlates with invasive breast cancer oncogenesis and reduced type 1 cell-mediated cytotoxic immunity: a retrospective study', 'Klinke, David J', 'Department of Chemical Engineering and Mary Babb Randolph Cancer Center, West Virginia University, Morgantown, West Virginia, United States of America , Department of Microbiology, Immunology, and Cell Biology, West Virginia University, Morgantown, West Virginia, United States of America.', 'United States', 30, 'Adult|Aged|Aged, 80 and over|Breast Neoplasms|CCN Intercellular Signaling Proteins|Carcinogenesis|Cell Transformation, Neoplastic|Cluster Analysis|Cohort Studies|Computational Biology|Female|Gene Expression Regulation, Neoplastic|Genetic Engineering|Humans|Immunity, Cellular|Interleukin-12|Middle Aged|Neoplasm Invasiveness|Proto-Oncogene Proteins|RNA, Messenger|Retrospective Studies|Signal Transduction', 'Journal Article', '10.1371/journal.pcbi.1003409', '24426833', 'Innate and type 1 cell-mediated cytotoxic immunity function as important extracellular control mechanisms that maintain cellular homeostasis. Interleukin-12 (IL12) is an important cytokine that links innate immunity with type 1 cell-mediated cytotoxic immunity. We recently observed in vitro that tumor-derived Wnt-inducible signaling protein-1 (WISP1) exerts paracrine action to suppress IL12 signaling. The objective of this retrospective study was three fold: 1) to determine whether a gene signature associated with type 1 cell-mediated cytotoxic immunity was correlated with overall survival, 2) to determine whether WISP1 expression is increased in invasive breast cancer, and 3) to determine whether a gene signature consistent with inhibition of IL12 signaling correlates with WISP1 expression. Clinical information and mRNA expression for genes associated with anti-tumor immunity were obtained from the invasive breast cancer arm of the Cancer Genome Atlas study. Patient cohorts were identified using hierarchical clustering. The immune signatures associated with the patient cohorts were interpreted using model-based inference of immune polarization. Reverse phase protein array, tissue microarray, and quantitative flow cytometry in breast cancer cell lines were used to validate observed differences in gene expression. We found that type 1 cell-mediated cytotoxic immunity was correlated with increased survival in patients with invasive breast cancer, especially in patients with invasive triple negative breast cancer. Oncogenic transformation in invasive breast cancer was associated with an increase in WISP1. The gene expression signature in invasive breast cancer was consistent with WISP1 as a paracrine inhibitor of type 1 cell-mediated immunity through inhibiting IL12 signaling and promoting type 2 immunity. Moreover, model-based inference helped identify appropriate immune signatures that can be used as design constraints in genetically engineering better pre-clinical models of breast cancer. '),
(86387, 2014, 'plos', 'Machine learning estimates of natural product conformational energies', 'Rupp, Matthias|Bauer, Matthias R|Wilcken, Rainer|Lange, Andreas|Reutlinger, Michael|Boeckler, Frank M|Schneider, Gisbert', 'Department of Chemistry and Applied Biosciences, Eidgenössische Technische Hochschule (ETH), Zürich, Switzerland.|Department of Pharmaceutical Chemistry, Eberhard Karls University, Tübingen, Germany.|Department of Pharmaceutical Chemistry, Eberhard Karls University, Tübingen, Germany.|Department of Pharmaceutical Chemistry, Eberhard Karls University, Tübingen, Germany.|Department of Chemistry and Applied Biosciences, Eidgenössische Technische Hochschule (ETH), Zürich, Switzerland.|Department of Pharmaceutical Chemistry, Eberhard Karls University, Tübingen, Germany.|Department of Chemistry and Applied Biosciences, Eidgenössische Technische Hochschule (ETH), Zürich, Switzerland.', 'Switzerland|Germany|Germany|Germany|Switzerland|Germany|Switzerland', 0, 'Adenosine Triphosphatases|Algorithms|Artificial Intelligence|Chemistry, Pharmaceutical|Computational Biology|Enzyme Inhibitors|Macrolides|Magnetic Resonance Spectroscopy|Models, Chemical|Molecular Dynamics Simulation|Molecular Structure|Myxococcales|Normal Distribution|Principal Component Analysis|Protein Conformation|Software|Stochastic Processes|Thiazoles', 'Journal Article', '10.1371/journal.pcbi.1003400', '24453952', 'Machine learning has been used for estimation of potential energy surfaces to speed up molecular dynamics simulations of small systems. We demonstrate that this approach is feasible for significantly larger, structurally complex molecules, taking the natural product Archazolid A, a potent inhibitor of vacuolar-type ATPase, from the myxobacterium Archangium gephyra as an example. Our model estimates energies of new conformations by exploiting information from previous calculations via Gaussian process regression. Predictive variance is used to assess whether a conformation is in the interpolation region, allowing a controlled trade-off between prediction accuracy and computational speed-up. For energies of relaxed conformations at the density functional level of theory (implicit solvent, DFT/BLYP-disp3/def2-TZVP), mean absolute errors of less than 1 kcal/mol were achieved. The study demonstrates that predictive machine learning models can be developed for structurally complex, pharmaceutically relevant compounds, potentially enabling considerable speed-ups in simulations of larger molecular structures. '),
(86388, 2014, 'plos', 'Fast reconstruction of compact context-specific metabolic network models', 'Vlassis, Nikos|Pacheco, Maria Pires|Sauter, Thomas', 'Luxembourg Centre for Systems Biomedicine, University of Luxembourg, Luxembourg City, Luxembourg.|Life Sciences Research Unit, University of Luxembourg, Luxembourg City, Luxembourg.|Life Sciences Research Unit, University of Luxembourg, Luxembourg City, Luxembourg.', 'Luxembourg|Luxembourg|Luxembourg', 85, 'Algorithms|Computational Biology|Computer Simulation|Genome|Humans|Linear Models|Metabolic Networks and Pathways|Software', 'Journal Article', '10.1371/journal.pcbi.1003424', '24453953', 'Systemic approaches to the study of a biological cell or tissue rely increasingly on the use of context-specific metabolic network models. The reconstruction of such a model from high-throughput data can routinely involve large numbers of tests under different conditions and extensive parameter tuning, which calls for fast algorithms. We present fastcore, a generic algorithm for reconstructing context-specific metabolic network models from global genome-wide metabolic network models such as Recon X. fastcore takes as input a core set of reactions that are known to be active in the context of interest (e.g., cell or tissue), and it searches for a flux consistent subnetwork of the global network that contains all reactions from the core set and a minimal set of additional reactions. Our key observation is that a minimal consistent reconstruction can be defined via a set of sparse modes of the global network, and fastcore iteratively computes such a set via a series of linear programs. Experiments on liver data demonstrate speedups of several orders of magnitude, and significantly more compact reconstructions, over a rival method. Given its simplicity and its excellent performance, fastcore can form the backbone of many future metabolic network reconstruction algorithms. '),
(86389, 2014, 'plos', 'PEX5 and ubiquitin dynamics on mammalian peroxisome membranes', 'Brown, Aidan I|Kim, Peter K|Rutenberg, Andrew D', 'Department of Physics and Atmospheric Science, Dalhousie University, Halifax, Nova Scotia, Canada.|Department of Biochemistry, University of Toronto, Toronto, Ontario, Canada , Cell Biology Program, Hospital for Sick Children, Toronto, Ontario, Canada.|Department of Physics and Atmospheric Science, Dalhousie University, Halifax, Nova Scotia, Canada.', 'Canada|Canada|Canada', 14, 'Animals|Computer Simulation|Cytosol|HeLa Cells|Humans|Intracellular Membranes|Mammals|Peroxisome-Targeting Signal 1 Receptor|Peroxisomes|Protein Transport|Receptors, Cytoplasmic and Nuclear|Signal Transduction|Stochastic Processes|Ubiquitin', 'Journal Article', '10.1371/journal.pcbi.1003426', '24453954', 'Peroxisomes are membrane-bound organelles within eukaryotic cells that post-translationally import folded proteins into their matrix. Matrix protein import requires a shuttle receptor protein, usually PEX5, that cycles through docking with the peroxisomal membrane, ubiquitination, and export back into the cytosol followed by deubiquitination. Matrix proteins associate with PEX5 in the cytosol and are translocated into the peroxisome lumen during the PEX5 cycle. This cargo translocation step is not well understood, and its energetics remain controversial. We use stochastic computational models to explore different ways the AAA ATPase driven removal of PEX5 may couple with cargo translocation in peroxisomal importers of mammalian cells. The first model considered is uncoupled, in which translocation is spontaneous, and does not immediately depend on PEX5 removal. The second is directly coupled, in which cargo translocation only occurs when its PEX5 is removed from the peroxisomal membrane. The third, novel, model is cooperatively coupled and requires two PEX5 on a given importomer for cargo translocation--one PEX5 with associated cargo and one with ubiquitin. We measure both the PEX5 and the ubiquitin levels on the peroxisomes as we vary the matrix protein cargo addition rate into the cytosol. We find that both uncoupled and directly coupled translocation behave identically with respect to PEX5 and ubiquitin, and the peroxisomal ubiquitin signal increases as the matrix protein traffic increases. In contrast, cooperatively coupled translocation behaves dramatically differently, with a ubiquitin signal that decreases with increasing matrix protein traffic. Recent work has shown that ubiquitin on mammalian peroxisome membranes can lead to selective degradation by autophagy, or pexophagy. Therefore, the high ubiquitin level for low matrix cargo traffic with cooperatively coupled protein translocation could be used as a disuse signal to mediate pexophagy. This mechanism may be one way that cells could regulate peroxisome numbers.'),
(86390, 2014, 'plos', 'The correlation structure of local neuronal networks intrinsically results from recurrent dynamics', 'Helias, Moritz|Tetzlaff, Tom|Diesmann, Markus', 'Institute of Neuroscience and Medicine (INM-6) and Institute for Advanced Simulation (IAS-6), Jülich Research Centre and JARA, Jülich, Germany.|Institute of Neuroscience and Medicine (INM-6) and Institute for Advanced Simulation (IAS-6), Jülich Research Centre and JARA, Jülich, Germany.|Institute of Neuroscience and Medicine (INM-6) and Institute for Advanced Simulation (IAS-6), Jülich Research Centre and JARA, Jülich, Germany , Medical Faculty, RWTH Aachen University, Aachen, Germany.', 'Germany|Germany|Germany', 46, 'Algorithms|Animals|Computer Simulation|Feedback, Physiological|Haplorhini|Models, Neurological|Nerve Net|Neuronal Plasticity|Neurons|Signal Transduction|Stochastic Processes|Synapses|Synaptic Transmission', 'Journal Article', '10.1371/journal.pcbi.1003428', '24453955', 'Correlated neuronal activity is a natural consequence of network connectivity and shared inputs to pairs of neurons, but the task-dependent modulation of correlations in relation to behavior also hints at a functional role. Correlations influence the gain of postsynaptic neurons, the amount of information encoded in the population activity and decoded by readout neurons, and synaptic plasticity. Further, it affects the power and spatial reach of extracellular signals like the local-field potential. A theory of correlated neuronal activity accounting for recurrent connectivity as well as fluctuating external sources is currently lacking. In particular, it is unclear how the recently found mechanism of active decorrelation by negative feedback on the population level affects the network response to externally applied correlated stimuli. Here, we present such an extension of the theory of correlations in stochastic binary networks. We show that (1) for homogeneous external input, the structure of correlations is mainly determined by the local recurrent connectivity, (2) homogeneous external inputs provide an additive, unspecific contribution to the correlations, (3) inhibitory feedback effectively decorrelates neuronal activity, even if neurons receive identical external inputs, and (4) identical synaptic input statistics to excitatory and to inhibitory cells increases intrinsically generated fluctuations and pairwise correlations. We further demonstrate how the accuracy of mean-field predictions can be improved by self-consistently including correlations. As a byproduct, we show that the cancellation of correlations between the summed inputs to pairs of neurons does not originate from the fast tracking of external input, but from the suppression of fluctuations on the population level by the local network. This suppression is a necessary constraint, but not sufficient to determine the structure of correlations, specifically, the structure observed at finite network size differs from the prediction based on perfect tracking, even though perfect tracking implies suppression of population fluctuations. '),
(86391, 2014, 'plos', 'Phylogenetic Gaussian process model for the inference of functionally important regions in protein tertiary structures', 'Huang, Yi-Fei|Golding, G Brian', 'Department of Biology, McMaster University, Hamilton, Ontario, Canada.|Department of Biology, McMaster University, Hamilton, Ontario, Canada.', 'Canada|Canada', 0, 'Algorithms|B7-1 Antigen|Computational Biology|Computer Simulation|Humans|Normal Distribution|Phylogeny|Protein Structure, Tertiary|Proteins|ROC Curve|Reproducibility of Results|Software', 'Journal Article', '10.1371/journal.pcbi.1003429', '24453956', 'A critical question in biology is the identification of functionally important amino acid sites in proteins. Because functionally important sites are under stronger purifying selection, site-specific substitution rates tend to be lower than usual at these sites. A large number of phylogenetic models have been developed to estimate site-specific substitution rates in proteins and the extraordinarily low substitution rates have been used as evidence of function. Most of the existing tools, e.g. Rate4Site, assume that site-specific substitution rates are independent across sites. However, site-specific substitution rates may be strongly correlated in the protein tertiary structure, since functionally important sites tend to be clustered together to form functional patches. We have developed a new model, GP4Rate, which incorporates the Gaussian process model with the standard phylogenetic model to identify slowly evolved regions in protein tertiary structures. GP4Rate uses the Gaussian process to define a nonparametric prior distribution of site-specific substitution rates, which naturally captures the spatial correlation of substitution rates. Simulations suggest that GP4Rate can potentially estimate site-specific substitution rates with a much higher accuracy than Rate4Site and tends to report slowly evolved regions rather than individual sites. In addition, GP4Rate can estimate the strength of the spatial correlation of substitution rates from the data. By applying GP4Rate to a set of mammalian B7-1 genes, we found a highly conserved region which coincides with experimental evidence. GP4Rate may be a useful tool for the in silico prediction of functionally important regions in the proteins with known structures. '),
(86392, 2014, 'plos', 'Integrated text mining and chemoinformatics analysis associates diet to health benefit at molecular level', 'Jensen, Kasper|Panagiotou, Gianni|Kouskoumvekaki, Irene', 'Center for Biological Sequence Analysis, Department of Systems Biology, Technical University of Denmark, Kemitorvet, Lyngby, Denmark.|School of Biological Sciences, The University of Hong Kong, Hong Kong.|School of Biological Sciences, The University of Hong Kong, Hong Kong.', 'Denmark|Hong Kong|Hong Kong', 0, 'Algorithms|Bayes Theorem|Colonic Neoplasms|Data Mining|Disease Progression|Disease Susceptibility|Food|Humans|Life Style|Lipids|Medical Informatics|Nutritional Sciences|Phenotype|Phytochemicals|Plants|Software|Systems Biology', 'Journal Article', '10.1371/journal.pcbi.1003432', '24453957', 'Awareness that disease susceptibility is not only dependent on genetic make up, but can be affected by lifestyle decisions, has brought more attention to the role of diet. However, food is often treated as a black box, or the focus is limited to few, well-studied compounds, such as polyphenols, lipids and nutrients. In this work, we applied text mining and Naïve Bayes classification to assemble the knowledge space of food-phytochemical and food-disease associations, where we distinguish between disease prevention/amelioration and disease progression. We subsequently searched for frequently occurring phytochemical-disease pairs and we identified 20,654 phytochemicals from 16,102 plants associated to 1,592 human disease phenotypes. We selected colon cancer as a case study and analyzed our results in three directions, i) one stop legacy knowledge-shop for the effect of food on disease, ii) discovery of novel bioactive compounds with drug-like properties, and iii) discovery of novel health benefits from foods. This works represents a systematized approach to the association of food with health effect, and provides the phytochemical layer of information for nutritional systems biology research. '),
(86393, 2014, 'plos', 'Microenvironmental variables must influence intrinsic phenotypic parameters of cancer stem cells to affect tumourigenicity', 'Scott, Jacob G|Hjelmeland, Anita B|Chinnaiyan, Prakash|Anderson, Alexander R A|Basanta, David', 'Integrated Mathematical Oncology, H. Lee Moffitt Cancer Center and Research Institute, Tampa, Florida, United States of America , Wolfson Centre for Mathematical Biology, Mathematical Institute, University of Oxford, Oxford, United Kingdom.|Department of Cell, Developmental and Integrative Biology, University of Alabama at Birmingham, Birmingham, Alabama, United States of America.|Department of Radiation Oncology, H. Lee Moffitt Cancer Center and Research Institute, Tampa, Florida, United States of America.|Integrated Mathematical Oncology, H. Lee Moffitt Cancer Center and Research Institute, Tampa, Florida, United States of America.|Integrated Mathematical Oncology, H. Lee Moffitt Cancer Center and Research Institute, Tampa, Florida, United States of America.', 'United Kingdom|United States|United States|United States|United States', 25, 'Algorithms|Brain|Cell Hypoxia|Cell Transformation, Neoplastic|Computer Simulation|Disease Progression|Humans|Models, Biological|Mutation|Neoplasms|Neoplastic Stem Cells|Phenotype|Tumor Microenvironment', 'Journal Article', '10.1371/journal.pcbi.1003433', '24453958', 'Since the discovery of tumour initiating cells (TICs) in solid tumours, studies focussing on their role in cancer initiation and progression have abounded. The biological interrogation of these cells continues to yield volumes of information on their pro-tumourigenic behaviour, but actionable generalised conclusions have been scarce. Further, new information suggesting a dependence of tumour composition and growth on the microenvironment has yet to be studied theoretically. To address this point, we created a hybrid, discrete/continuous computational cellular automaton model of a generalised stem-cell driven tissue with a simple microenvironment. Using the model we explored the phenotypic traits inherent to the tumour initiating cells and the effect of the microenvironment on tissue growth. We identify the regions in phenotype parameter space where TICs are able to cause a disruption in homeostasis, leading to tissue overgrowth and tumour maintenance. As our parameters and model are non-specific, they could apply to any tissue TIC and do not assume specific genetic mutations. Targeting these phenotypic traits could represent a generalizable therapeutic strategy across cancer types. Further, we find that the microenvironmental variable does not strongly affect the outcomes, suggesting a need for direct feedback from the microenvironment onto stem-cell behaviour in future modelling endeavours. '),
(86394, 2014, 'plos', 'Coarse-grained molecular simulation of epidermal growth factor receptor protein tyrosine kinase multi-site self-phosphorylation', 'Koland, John G', 'Departments of Pharmacology and Internal Medicine, University of Iowa, Carver College of Medicine, Iowa City, Iowa, United States of America.', 'United States', 0, 'Binding Sites|Catalytic Domain|Computational Biology|Computer Simulation|ErbB Receptors|Humans|Ligands|Models, Molecular|Phosphorylation|Protein Multimerization|Protein-Tyrosine Kinases|Static Electricity', 'Journal Article', '10.1371/journal.pcbi.1003435', '24453959', 'Upon the ligand-dependent dimerization of the epidermal growth factor receptor (EGFR), the intrinsic protein tyrosine kinase (PTK) activity of one receptor monomer is activated, and the dimeric receptor undergoes self-phosphorylation at any of eight candidate phosphorylation sites (P-sites) in either of the two C-terminal (CT) domains. While the structures of the extracellular ligand binding and intracellular PTK domains are known, that of the xe2x88xbc225-amino acid CT domain is not, presumably because it is disordered. Receptor phosphorylation on CT domain P-sites is critical in signaling because of the binding of specific signaling effector molecules to individual phosphorylated P-sites. To investigate how the combination of conventional substrate recognition and the unique topological factors involved in the CT domain self-phosphorylation reaction lead to selectivity in P-site phosphorylation, we performed coarse-grained molecular simulations of the P-site/catalytic site binding reactions that precede EGFR self-phosphorylation events. Our results indicate that self-phosphorylation of the dimeric EGFR, although generally believed to occur in trans, may well occur with a similar efficiency in cis, with the P-sites of both receptor monomers being phosphorylated to a similar extent. An exception was the case of the most kinase-proximal P-site-992, the catalytic site binding of which occurred exclusively in cis via an intramolecular reaction. We discovered that the in cis interaction of P-site-992 with the catalytic site was facilitated by a cleft between the N-terminal and C-terminal lobes of the PTK domain that allows the short CT domain sequence tethering P-site-992 to the PTK core to reach the catalytic site. Our work provides several new mechanistic insights into the EGFR self-phosphorylation reaction, and demonstrates the potential of coarse-grained molecular simulation approaches for investigating the complexities of self-phosphorylation in molecules such as EGFR (HER/ErbB) family receptors and growth factor receptor PTKs in general. '),
(86395, 2014, 'plos', 'The making of the Women in Biology forum (WiB) at Bioclues', 'Singhania, Reeta Rani|Madduru, Dhatri|Pappu, Pranathi|Panchangam, Sameera|Suravajhala, Renuka|Chandrasekharan, Mohanalatha', 'Bioclues Organization, IKP Knowledge Park, Picket, Secunderabad, India.|Bioclues Organization, IKP Knowledge Park, Picket, Secunderabad, India.|Bioclues Organization, IKP Knowledge Park, Picket, Secunderabad, India.|Bioclues Organization, IKP Knowledge Park, Picket, Secunderabad, India.|Bioclues Organization, IKP Knowledge Park, Picket, Secunderabad, India.|Bioclues Organization, IKP Knowledge Park, Picket, Secunderabad, India.', 'India|India|India|India|India|India', 0, 'Biology|Career Choice|Computational Biology|Congresses as Topic|Female|Humans|India|Mentors|Research|Science|Women|Workforce', 'Journal Article', '10.1371/journal.pcbi.1003436', '24453960', 'The Women in Biology forum (WiB) of Bioclues (India) began in 2009 to promote and support women pursuing careers in bioinformatics and computational biology. WiB was formed in order to help women scientists deprived of basic research, boost the prominence of women scientists particularly from developing countries, and bridge the gender gap to innovation. WiB has also served as a platform to highlight the work of established female scientists in these fields. Several award-winning women researchers have shared their experiences and provided valuable suggestions to WiB. Headed by Mohanalatha Chandrasekharan and supported by Dr. Reeta Rani Singhania and Renuka Suravajhala, WiB has seen major progress in the last couple of years particularly in the two avenues Mentoring and Research, off the four avenues in Bioclues: Mentoring, Outreach, Research and Entrepreneurship (MORE). In line with the Bioclues vision for bioinformatics in India, the WiB Journal Club (JoC) recognizes women scientists working on functional genomics and bioinformatics, and provides scientific mentorship and support for project design and hypothesis formulation. As a part of Bioclues, WiB members practice the groups open-desk policy and its belief that all members are free to express their own thoughts and opinions. The WiB forum appreciates suggestions and welcomes scientists from around the world to be a part of their mission to encourage women to pursue computational biology and bioinformatics. '),
(86396, 2014, 'plos', 'PredictSNP: robust and accurate consensus classifier for prediction of disease-related mutations', 'Bendl, Jaroslav|Stourac, Jan|Salanda, Ondrej|Pavelka, Antonin|Wieben, Eric D|Zendulka, Jaroslav|Brezovsky, Jan|Damborsky, Jiri', 'Loschmidt Laboratories, Department of Experimental Biology and Research Centre for Toxic Compounds in the Environment, Faculty of Science, Masaryk University, Brno, Czech Republic , Department of Information Systems, Faculty of Information Technology, Brno University of Technology, Brno, Czech Republic , Center of Biomolecular and Cellular Engineering, International Centre for Clinical Research, St. Annes University Hospital Brno, Brno, Czech Republic.|Loschmidt Laboratories, Department of Experimental Biology and Research Centre for Toxic Compounds in the Environment, Faculty of Science, Masaryk University, Brno, Czech Republic , Center of Biomolecular and Cellular Engineering, International Centre for Clinical Research, St. Annes University Hospital Brno, Brno, Czech Republic.|Department of Information Systems, Faculty of Information Technology, Brno University of Technology, Brno, Czech Republic.|Loschmidt Laboratories, Department of Experimental Biology and Research Centre for Toxic Compounds in the Environment, Faculty of Science, Masaryk University, Brno, Czech Republic.|Department of Biochemistry and Molecular Biology, Mayo Clinic, Rochester, New York, United States of America.|Department of Information Systems, Faculty of Information Technology, Brno University of Technology, Brno, Czech Republic.|Loschmidt Laboratories, Department of Experimental Biology and Research Centre for Toxic Compounds in the Environment, Faculty of Science, Masaryk University, Brno, Czech Republic.|Loschmidt Laboratories, Department of Experimental Biology and Research Centre for Toxic Compounds in the Environment, Faculty of Science, Masaryk University, Brno, Czech Republic , Center of Biomolecular and Cellular Engineering, International Centre for Clinical Research, St. Annes University Hospital Brno, Brno, Czech Republic.', '-|-|-|-|United States|-|-|-', 271, 'Algorithms|Computational Biology|Computer Simulation|Databases, Protein|Genetic Diseases, Inborn|Genetic Variation|Genome, Human|Humans|Internet|Mutation|Phylogeny|Polymorphism, Single Nucleotide|Software', 'Journal Article', '10.1371/journal.pcbi.1003440', '24453961', 'Single nucleotide variants represent a prevalent form of genetic variation. Mutations in the coding regions are frequently associated with the development of various genetic diseases. Computational tools for the prediction of the effects of mutations on protein function are very important for analysis of single nucleotide variants and their prioritization for experimental characterization. Many computational tools are already widely employed for this purpose. Unfortunately, their comparison and further improvement is hindered by large overlaps between the training datasets and benchmark datasets, which lead to biased and overly optimistic reported performances. In this study, we have constructed three independent datasets by removing all duplicities, inconsistencies and mutations previously used in the training of evaluated tools. The benchmark dataset containing over 43,000 mutations was employed for the unbiased evaluation of eight established prediction tools: MAPP, nsSNPAnalyzer, PANTHER, PhD-SNP, PolyPhen-1, PolyPhen-2, SIFT and SNAP. The six best performing tools were combined into a consensus classifier PredictSNP, resulting into significantly improved prediction performance, and at the same time returned results for all mutations, confirming that consensus prediction represents an accurate and robust alternative to the predictions delivered by individual tools. A user-friendly web interface enables easy access to all eight prediction tools, the consensus classifier PredictSNP and annotations from the Protein Mutant Database and the UniProt database. The web server and the datasets are freely available to the academic community at http://loschmidt.chemi.muni.cz/predictsnp. '),
(86397, 2014, 'plos', 'Current practice in software development for computational neuroscience and how to improve it', 'Gewaltig, Marc-Oliver|Cannon, Robert', 'Blue Brain Project, École Polytechnique Fédérale de Lausanne, Lausanne, Switzerland.|Textensor Ltd., Edinburgh, United Kingdom.', 'Switzerland|United Kingdom', 17, 'Algorithms|Computational Biology|Computer Simulation|Humans|Neurosciences|Publications|Quality Control|Reproducibility of Results|Software|Software Design', 'Journal Article', '10.1371/journal.pcbi.1003376', '24465191', 'Almost all research work in computational neuroscience involves software. As researchers try to understand ever more complex systems, there is a continual need for software with new capabilities. Because of the wide range of questions being investigated, new software is often developed rapidly by individuals or small groups. In these cases, it can be hard to demonstrate that the software gives the right results. Software developers are often open about the code they produce and willing to share it, but there is little appreciation among potential users of the great diversity of software development practices and end results, and how this affects the suitability of software tools for use in research projects. To help clarify these issues, we have reviewed a range of software tools and asked how the culture and practice of software development affects their validity and trustworthiness. We identified four key questions that can be used to categorize software projects and correlate them with the type of product that results. The first question addresses what is being produced. The other three concern why, how, and by whom the work is done. The answers to these questions show strong correlations with the nature of the software being produced, and its suitability for particular purposes. Based on our findings, we suggest ways in which current software development practice in computational neuroscience can be improved and propose checklists to help developers, reviewers, and scientists to assess the quality of software and whether particular pieces of software are ready for use in research. '),
(86398, 2014, 'plos', 'Bioinformatics projects supporting life-sciences learning in high schools', 'Marques, Isabel|Almeida, Paulo|Alves, Renato|Dias, Maria João|Godinho, Ana|Pereira-Leal, José B', 'Instituto Gulbenkian de Ciência, Oeiras, Portugal.|Instituto Gulbenkian de Ciência, Oeiras, Portugal.|Instituto Gulbenkian de Ciência, Oeiras, Portugal.|Escola Secundária Stuart de Carvalhais, Queluz, Portugal.|Instituto Gulbenkian de Ciência, Oeiras, Portugal.|Instituto Gulbenkian de Ciência, Oeiras, Portugal.', 'Portugal|Portugal|Portugal|Portugal|Portugal|Portugal', 6, 'Adolescent|Biology|Computational Biology|Curriculum|Humans|Internet|Learning|Portugal|Program Development|Schools|Surveys and Questionnaires', 'Journal Article', '10.1371/journal.pcbi.1003404', '24465192', 'The interdisciplinary nature of bioinformatics makes it an ideal framework to develop activities enabling enquiry-based learning. We describe here the development and implementation of a pilot project to use bioinformatics-based research activities in high schools, called Bioinformatics@school. It includes web-based research projects that students can pursue alone or under teacher supervision and a teacher training program. The project is organized so as to enable discussion of key results between students and teachers. After successful trials in two high schools, as measured by questionnaires, interviews, and assessment of knowledge acquisition, the project is expanding by the action of the teachers involved, who are helping us develop more content and are recruiting more teachers and schools. ');
INSERT INTO `papers` (`id`, `ano`, `journal`, `titulo`, `autores`, `afiliacao`, `pais`, `citacoes`, `palavra_chave`, `categorias`, `doi`, `pubmed`, `abstract`) VALUES
(86399, 2014, 'plos', 'Immune-mediated competition in rodent malaria is most likely caused by induced changes in innate immune clearance of merozoites', 'Santhanam, Jayanthi|Rxc3xa5berg, Lars|Read, Andrew F|Savill, Nicholas Jon', 'Institute of Immunology and Infection Research, University of Edinburgh, Ashworth Labs, Edinburgh, Scotland.|Department of Biology, Lund University, Lund, Sweden.|Center for Infectious Disease Dynamics, The Pennsylvania State University, University Park, Pennsylvania, United States of America.|Institute of Immunology and Infection Research, University of Edinburgh, Ashworth Labs, Edinburgh, Scotland.', '-|Sweden|United States|-', 6, 'Algorithms|Animals|Bayes Theorem|Computer Simulation|Disease Models, Animal|Erythrocytes|Female|Immunity, Innate|Likelihood Functions|Malaria|Merozoites|Mice|Mice, Inbred BALB C|Mice, Nude|Models, Theoretical|Parasitemia|Phenotype|Plasmodium chabaudi|Rats', 'Journal Article', '10.1371/journal.pcbi.1003416', '24465193', 'Malarial infections are often genetically diverse, leading to competitive interactions between parasites. A quantitative understanding of the competition between strains is essential to understand a wide range of issues, including the evolution of virulence and drug resistance. In this study, we use dynamical-model based Bayesian inference to investigate the cause of competitive suppression of an avirulent clone of Plasmodium chabaudi (AS) by a virulent clone (AJ) in immuno-deficient and competent mice. We test whether competitive suppression is caused by clone-specific differences in one or more of the following processes: adaptive immune clearance of merozoites and parasitised red blood cells (RBCs), background loss of merozoites and parasitised RBCs, RBC age preference, RBC infection rate, burst size, and within-RBC interference. These processes were parameterised in dynamical mathematical models and fitted to experimental data. We found that just one parameter xcexbc, the ratio of background loss rate of merozoites to invasion rate of mature RBCs, needed to be clone-specific to predict the data. Interestingly, xcexbc was found to be the same for both clones in single-clone infections, but different between the clones in mixed infections. The size of this difference was largest in immuno-competent mice and smallest in immuno-deficient mice. This explains why competitive suppression was alleviated in immuno-deficient mice. We found that competitive suppression acts early in infection, even before the day of peak parasitaemia. These results lead us to argue that the innate immune response clearing merozoites is the most likely, but not necessarily the only, mediator of competitive interactions between virulent and avirulent clones. Moreover, in mixed infections we predict there to be an interaction between the clones and the innate immune response which induces changes in the strength of its clearance of merozoites. What this interaction is unknown, but future refinement of the model, challenged with other datasets, may lead to its discovery.'),
(86400, 2014, 'plos', 'Combinatorial modeling of chromatin features quantitatively predicts DNA replication timing in Drosophila', 'Comoglio, Federico|Paro, Renato', 'Department of Biosystems Science and Engineering, ETH Zurich, Basel, Switzerland.|Department of Biosystems Science and Engineering, ETH Zurich, Basel, Switzerland , Faculty of Science, University of Basel, Basel, Switzerland.', 'Switzerland|Switzerland', 12, 'Animals|Cell Line|Chromatin|Cluster Analysis|Computer Simulation|DNA|DNA Replication Timing|Drosophila|Gene Expression Regulation|Genome|Histones|Models, Statistical', 'Journal Article', '10.1371/journal.pcbi.1003419', '24465194', 'In metazoans, each cell type follows a characteristic, spatio-temporally regulated DNA replication program. Histone modifications (HMs) and chromatin binding proteins (CBPs) are fundamental for a faithful progression and completion of this process. However, no individual HM is strictly indispensable for origin function, suggesting that HMs may act combinatorially in analogy to the histone code hypothesis for transcriptional regulation. In contrast to gene expression however, the relationship between combinations of chromatin features and DNA replication timing has not yet been demonstrated. Here, by exploiting a comprehensive data collection consisting of 95 CBPs and HMs we investigated their combinatorial potential for the prediction of DNA replication timing in Drosophila using quantitative statistical models. We found that while combinations of CBPs exhibit moderate predictive power for replication timing, pairwise interactions between HMs lead to accurate predictions genome-wide that can be locally further improved by CBPs. Independent feature importance and model analyses led us to derive a simplified, biologically interpretable model of the relationship between chromatin landscape and replication timing reaching 80% of the full model accuracy using six model terms. Finally, we show that pairwise combinations of HMs are able to predict differential DNA replication timing across different cell types. All in all, our work provides support to the existence of combinatorial HM patterns for DNA replication and reveal cell-type independent key elements thereof, whose experimental investigation might contribute to elucidate the regulatory mode of this fundamental cellular process. '),
(86401, 2014, 'plos', 'The brain ages optimally to model its environment: evidence from sensory learning over the adult lifespan', 'Moran, Rosalyn J|Symmonds, Mkael|Dolan, Raymond J|Friston, Karl J', 'Virginia Tech Carilion Research Institute and Bradley Department of Electrical & Computer Engineering, Roanoke, Virginia, United States of America.|Wellcome Trust Centre for Neuroimaging, Institute of Neurology, University College London, London, United Kingdom , Nuffield Department of Clinical Neurosciences, Oxford University, John Radcliffe Hospital, Oxford, United Kingdom.|Wellcome Trust Centre for Neuroimaging, Institute of Neurology, University College London, London, United Kingdom.|Wellcome Trust Centre for Neuroimaging, Institute of Neurology, University College London, London, United Kingdom.', 'United States|United Kingdom|United Kingdom|United Kingdom', 47, 'Adult|Aged|Aged, 80 and over|Aging|Algorithms|Auditory Cortex|Bayes Theorem|Brain|Brain Mapping|Cerebral Cortex|Cohort Studies|Female|Humans|Learning|Magnetoencephalography|Male|Middle Aged|Models, Theoretical|Neuronal Plasticity|Neurons|Reproducibility of Results|Young Adult', 'Journal Article', '10.1371/journal.pcbi.1003422', '24465195', 'The aging brain shows a progressive loss of neuropil, which is accompanied by subtle changes in neuronal plasticity, sensory learning and memory. Neurophysiologically, aging attenuates evoked responses--including the mismatch negativity (MMN). This is accompanied by a shift in cortical responsivity from sensory (posterior) regions to executive (anterior) regions, which has been interpreted as a compensatory response for cognitive decline. Theoretical neurobiology offers a simpler explanation for all of these effects--from a Bayesian perspective, as the brain is progressively optimized to model its world, its complexity will decrease. A corollary of this complexity reduction is an attenuation of Bayesian updating or sensory learning. Here we confirmed this hypothesis using magnetoencephalographic recordings of the mismatch negativity elicited in a large cohort of human subjects, in their third to ninth decade. Employing dynamic causal modeling to assay the synaptic mechanisms underlying these non-invasive recordings, we found a selective age-related attenuation of synaptic connectivity changes that underpin rapid sensory learning. In contrast, baseline synaptic connectivity strengths were consistently strong over the decades. Our findings suggest that the lifetime accrual of sensory experience optimizes functional brain architectures to enable efficient and generalizable predictions of the world.'),
(86402, 2014, 'plos', 'Modeling within-host effects of drugs on Plasmodium falciparum transmission and prospects for malaria elimination', 'Johnston, Geoffrey L|Gething, Peter W|Hay, Simon I|Smith, David L|Fidock, David A', 'Department of Microbiology and Immunology, Columbia University College of Physicians and Surgeons, New York, New York, United States of America , School of International and Public Affairs, Columbia University, New York, New York, United States of America , Bloomberg School of Public Health, John Hopkins University, Baltimore, Maryland, United States of America.|Spatial Ecology and Epidemiology Group, Department of Zoology, University of Oxford, Oxford, United Kingdom.|Spatial Ecology and Epidemiology Group, Department of Zoology, University of Oxford, Oxford, United Kingdom.|Bloomberg School of Public Health, John Hopkins University, Baltimore, Maryland, United States of America.|Department of Microbiology and Immunology, Columbia University College of Physicians and Surgeons, New York, New York, United States of America , Division of Infectious Diseases, Department of Medicine, Columbia University College of Physicians and Surgeons, New York, New York, United States of America.', 'United States|United Kingdom|United Kingdom|United States|United States', 0, 'Algorithms|Animals|Antimalarials|Asia, Southeastern|Communicable Disease Control|Computer Simulation|Culicidae|Geography|Humans|Malaria, Falciparum|Models, Theoretical|Plasmodium falciparum|Software', 'Journal Article', '10.1371/journal.pcbi.1003434', '24465196', 'Achieving a theoretical foundation for malaria elimination will require a detailed understanding of the quantitative relationships between patient treatment-seeking behavior, treatment coverage, and the effects of curative therapies that also block Plasmodium parasite transmission to mosquito vectors. Here, we report a mechanistic, within-host mathematical model that uses pharmacokinetic (PK) and pharmacodynamic (PD) data to simulate the effects of artemisinin-based combination therapies (ACTs) on Plasmodium falciparum transmission. To contextualize this model, we created a set of global maps of the fold reductions that would be necessary to reduce the malaria R C (i.e. its basic reproductive number under control) to below 1 and thus interrupt transmission. This modeling was applied to low-transmission settings, defined as having a R 0<10 based on 2010 data. Our modeling predicts that treating 93-98% of symptomatic infections with an ACT within five days of fever onset would interrupt malaria transmission for xe2x88xbc91% of the at-risk population of Southeast Asia and xe2x88xbc74% of the global at-risk population, and lead these populations towards malaria elimination. This level of treatment coverage corresponds to an estimated 81-85% of all infected individuals in these settings. At this coverage level with ACTs, the addition of the gametocytocidal agent primaquine affords no major gains in transmission reduction. Indeed, we estimate that it would require switching xe2x88xbc180 people from ACTs to ACTs plus primaquine to achieve the same transmission reduction as switching a single individual from untreated to treated with ACTs. Our model thus predicts that the addition of gametocytocidal drugs to treatment regimens provides very small population-wide benefits and that the focus of control efforts in Southeast Asia should be on increasing prompt ACT coverage. Prospects for elimination in much of Sub-Saharan Africa appear far less favorable currently, due to high rates of infection and less frequent and less rapid treatment. '),
(86403, 2014, 'plos', 'Consequences of converting graded to action potentials upon neural information coding and energy efficiency', 'Sengupta, Biswa|Laughlin, Simon Barry|Niven, Jeremy Edward', 'Wellcome Trust Centre for Neuroimaging, University College London, London, United Kingdom , Centre for Neuroscience, Indian Institute of Science, Bangalore, India.|Department of Zoology, University of Cambridge, Cambridge, United Kingdom.|School of Life Sciences and Centre for Computational Neuroscience and Robotics, University of Sussex, Falmer, Brighton, United Kingdom.', 'United Kingdom|United Kingdom|United Kingdom', 27, 'Action Potentials|Algorithms|Cell Size|Electrophysiological Phenomena|Energy Metabolism|Humans|Linear Models|Models, Neurological|Nerve Net|Neurons|Potassium Channels, Voltage-Gated|Stochastic Processes|Voltage-Gated Sodium Channels', 'Journal Article', '10.1371/journal.pcbi.1003439', '24465197', 'Information is encoded in neural circuits using both graded and action potentials, converting between them within single neurons and successive processing layers. This conversion is accompanied by information loss and a drop in energy efficiency. We investigate the biophysical causes of this loss of information and efficiency by comparing spiking neuron models, containing stochastic voltage-gated Na(+) and K(+) channels, with generator potential and graded potential models lacking voltage-gated Na(+) channels. We identify three causes of information loss in the generator potential that are the by-product of action potential generation: (1) the voltage-gated Na(+) channels necessary for action potential generation increase intrinsic noise and (2) introduce non-linearities, and (3) the finite duration of the action potential creates a footprint in the generator potential that obscures incoming signals. These three processes reduce information rates by xe2x88xbc50% in generator potentials, to xe2x88xbc3 times that of spike trains. Both generator potentials and graded potentials consume almost an order of magnitude less energy per second than spike trains. Because of the lower information rates of generator potentials they are substantially less energy efficient than graded potentials. However, both are an order of magnitude more efficient than spike trains due to the higher energy costs and low information content of spikes, emphasizing that there is a two-fold cost of converting analogue to digital, information loss and cost inflation. '),
(86404, 2014, 'plos', 'VBA: a probabilistic treatment of nonlinear models for neurobiological and behavioural data', 'Daunizeau, Jean|Adam, Vincent|Rigoux, Lionel', 'Brain and Spine Institute, Paris, France , Wellcome Trust Centre for Neuroimaging, University College London, London, United Kingdom.|Gatsby computational neuroscience Unit, University College London, London, United Kingdom.|Brain and Spine Institute, Paris, France.', 'France|United Kingdom|France', 96, 'Algorithms|Bayes Theorem|Cognition|Computational Biology|Computer Simulation|Decision Making|Humans|Models, Biological|Models, Neurological|Nerve Net|Normal Distribution|Probability|Software|Stochastic Processes', 'Journal Article', '10.1371/journal.pcbi.1003441', '24465198', 'This work is in line with an on-going effort tending toward a computational (quantitative and refutable) understanding of human neuro-cognitive processes. Many sophisticated models for behavioural and neurobiological data have flourished during the past decade. Most of these models are partly unspecified (i.e. they have unknown parameters) and nonlinear. This makes them difficult to peer with a formal statistical data analysis framework. In turn, this compromises the reproducibility of model-based empirical studies. This work exposes a software toolbox that provides generic, efficient and robust probabilistic solutions to the three problems of model-based analysis of empirical data: (i) data simulation, (ii) parameter estimation/model selection, and (iii) experimental design optimization. '),
(86405, 2014, 'plos', 'An allosteric signaling pathway of human 3-phosphoglycerate kinase from force distribution analysis', 'Palmai, Zoltan|Seifert, Christian|Gräter, Frauke|Balog, Erika', 'Department of Biophysics and Radiation Biology, Semmelweis University, Budapest, Hungary.|Molecular Biomechanics, Heidelberger Institut für Theoretische Studien gGmbH, Heidelberg, Germany.|Molecular Biomechanics, Heidelberger Institut für Theoretische Studien gGmbH, Heidelberg, Germany , MPG-CAS Partner Institute and Key Laboratory for Computational Biology, Shanghai, China.|Department of Biophysics and Radiation Biology, Semmelweis University, Budapest, Hungary.', 'Hungary|Germany|China|Hungary', 0, 'Algorithms|Allosteric Site|Binding Sites|DNA Mutational Analysis|Humans|Models, Molecular|Molecular Dynamics Simulation|Mutagenesis|Phosphoglycerate Kinase|Protein Binding|Protein Structure, Secondary|Protein Structure, Tertiary|Signal Transduction|Stress, Mechanical', 'Journal Article', '10.1371/journal.pcbi.1003444', '24465199', '3-Phosphogycerate kinase (PGK) is a two domain enzyme, which transfers a phosphate group between its two substrates, 1,3-bisphosphoglycerate bound to the N-domain and ADP bound to the C-domain. Indispensable for the phosphoryl transfer reaction is a large conformational change from an inactive open to an active closed conformation via a hinge motion that should bring substrates into close proximity. The allosteric pathway resulting in the active closed conformation has only been partially uncovered. Using Molecular Dynamics simulations combined with Force Distribution Analysis (FDA), we describe an allosteric pathway, which connects the substrate binding sites to the interdomain hinge region. Glu192 of alpha-helix 7 and Gly394 of loop L14 act as hinge points, at which these two secondary structure elements straighten, thereby moving the substrate-binding domains towards each other. The long-range allosteric pathway regulating hPGK catalytic activity, which is partially validated and can be further tested by mutagenesis, highlights the virtue of monitoring internal forces to reveal signal propagation, even if only minor conformational distortions, such as helix bending, initiate the large functional rearrangement of the macromolecule. '),
(86406, 2014, 'plos', 'Leadership and path characteristics during walks are linked to dominance order and individual traits in dogs', 'xc3x81kos, Zsuzsa|Beck, Rxc3xb3bert|Nagy, Mxc3xa1txc3xa9|Vicsek, Tamxc3xa1s|Kubinyi, Enikxc5x91', 'Department of Biological Physics, Exc3xb6tvxc3xb6s University, Budapest, Hungary.|Department of Biological Physics, Exc3xb6tvxc3xb6s University, Budapest, Hungary.|Department of Biological Physics, Exc3xb6tvxc3xb6s University, Budapest, Hungary , Statistical and Biological Physics Research Group of the Hungarian Academy of Sciences, Budapest, Hungary , Department of Zoology, University of Oxford, Oxford, United Kingdom.|Department of Biological Physics, Exc3xb6tvxc3xb6s University, Budapest, Hungary , Statistical and Biological Physics Research Group of the Hungarian Academy of Sciences, Budapest, Hungary.|Statistical and Biological Physics Research Group of the Hungarian Academy of Sciences, Budapest, Hungary , MTA-ELTE Comparative Ethological Research Group, Budapest, Hungary.', 'Hungary|Hungary|United Kingdom|Hungary|Hungary', 0, 'Aggression|Animals|Behavior, Animal|Dogs|Geography|Social Dominance', 'Journal Article', '10.1371/journal.pcbi.1003446', '24465200', 'Movement interactions and the underlying social structure in groups have relevance across many social-living species. Collective motion of groups could be based on an egalitarian decision system, but in practice it is often influenced by underlying social network structures and by individual characteristics. We investigated whether dominance rank and personality traits are linked to leader and follower roles during joint motion of family dogs. We obtained high-resolution spatio-temporal GPS trajectory data (823,148 data points) from six dogs belonging to the same household and their owner during 14 30-40 min unleashed walks. We identified several features of the dogs paths (e.g., running speed or distance from the owner) which are characteristic of a given dog. A directional correlation analysis quantifies interactions between pairs of dogs that run loops jointly. We found that dogs play the role of the leader about 50-85% of the time, i.e. the leader and follower roles in a given pair are dynamically interchangable. However, on a longer timescale tendencies to lead differ consistently. The network constructed from these loose leader-follower relations is hierarchical, and the dogs positions in the network correlates with the age, dominance rank, trainability, controllability, and aggression measures derived from personality questionnaires. We demonstrated the possibility of determining dominance rank and personality traits of an individual based only on its logged movement data. The collective motion of dogs is influenced by underlying social network structures and by characteristics such as personality differences. Our findings could pave the way for automated animal personality and human social interaction measurements. '),
(86407, 2014, 'plos', 'Correlation between oncogenic mutations and parameter sensitivity of the apoptosis pathway model', 'Chen, Jia|Yue, Haicen|Ouyang, Qi', 'Center for Quantitative Biology and Peking-Tsinghua Center for Life Sciences at Peking University, Beijing, China.|Center for Quantitative Biology and Peking-Tsinghua Center for Life Sciences at Peking University, Beijing, China , School of Physics and the State Key Laboratory for Artificial Microstructures and Mesoscopic Physics, Peking University, Beijing, China.|Center for Quantitative Biology and Peking-Tsinghua Center for Life Sciences at Peking University, Beijing, China , School of Physics and the State Key Laboratory for Artificial Microstructures and Mesoscopic Physics, Peking University, Beijing, China.', 'China|China|China', 0, 'Algorithms|Apoptosis|Caspase 3|Computer Simulation|DNA Damage|Gene Expression Profiling|Gene Regulatory Networks|Humans|Models, Biological|Mutation|Neoplasms|Proteins|Signal Transduction', 'Journal Article', '10.1371/journal.pcbi.1003451', '24465201', 'One of the major breakthroughs in oncogenesis research in recent years is the discovery that, in most patients, oncogenic mutations are concentrated in a few core biological functional pathways. This discovery indicates that oncogenic mechanisms are highly related to the dynamics of biologic regulatory networks, which govern the behaviour of functional pathways. Here, we propose that oncogenic mutations found in different biological functional pathways are closely related to parameter sensitivity of the corresponding networks. To test this hypothesis, we focus on the DNA damage-induced apoptotic pathway--the most important safeguard against oncogenesis. We first built the regulatory network that governs the apoptosis pathway, and then translated the network into dynamics equations. Using sensitivity analysis of the network parameters and comparing the results with cancer gene mutation spectra, we found that parameters that significantly affect the bifurcation point correspond to high-frequency oncogenic mutations. This result shows that the position of the bifurcation point is a better measure of the functionality of a biological network than gene expression levels of certain key proteins. It further demonstrates the suitability of applying systems-level analysis to biological networks as opposed to studying genes or proteins in isolation.'),
(86408, 2014, 'plos', 'Bayesian reconstruction of disease outbreaks by combining epidemiologic and genomic data', 'Jombart, Thibaut|Cori, Anne|Didelot, Xavier|Cauchemez, Simon|Fraser, Christophe|Ferguson, Neil', 'MRC Centre for Outbreak Analysis and Modelling, Department of Infectious Disease Epidemiology, School of Public Health, Imperial College London, London, United Kingdom.|MRC Centre for Outbreak Analysis and Modelling, Department of Infectious Disease Epidemiology, School of Public Health, Imperial College London, London, United Kingdom.|MRC Centre for Outbreak Analysis and Modelling, Department of Infectious Disease Epidemiology, School of Public Health, Imperial College London, London, United Kingdom.|MRC Centre for Outbreak Analysis and Modelling, Department of Infectious Disease Epidemiology, School of Public Health, Imperial College London, London, United Kingdom.|MRC Centre for Outbreak Analysis and Modelling, Department of Infectious Disease Epidemiology, School of Public Health, Imperial College London, London, United Kingdom.|MRC Centre for Outbreak Analysis and Modelling, Department of Infectious Disease Epidemiology, School of Public Health, Imperial College London, London, United Kingdom.', 'United Kingdom|United Kingdom|United Kingdom|United Kingdom|United Kingdom|United Kingdom', 0, 'Algorithms|Bayes Theorem|Communicable Disease Control|Computer Simulation|Disease Outbreaks|Entropy|Epidemics|Genome, Viral|Genomics|Humans|Mutation|Probability|Programming Languages|SARS Virus|Severe Acute Respiratory Syndrome|Singapore|Software', 'Journal Article', '10.1371/journal.pcbi.1003457', '24465202', 'Recent years have seen progress in the development of statistically rigorous frameworks to infer outbreak transmission trees (who infected whom) from epidemiological and genetic data. Making use of pathogen genome sequences in such analyses remains a challenge, however, with a variety of heuristic approaches having been explored to date. We introduce a statistical method exploiting both pathogen sequences and collection dates to unravel the dynamics of densely sampled outbreaks. Our approach identifies likely transmission events and infers dates of infections, unobserved cases and separate introductions of the disease. It also proves useful for inferring numbers of secondary infections and identifying heterogeneous infectivity and super-spreaders. After testing our approach using simulations, we illustrate the method with the analysis of the beginning of the 2003 Singaporean outbreak of Severe Acute Respiratory Syndrome (SARS), providing new insights into the early stage of this epidemic. Our approach is the first tool for disease outbreak reconstruction from genetic data widely available as free software, the R package outbreaker. It is applicable to various densely sampled epidemics, and improves previous approaches by detecting unobserved and imported cases, as well as allowing multiple introductions of the pathogen. Because of its generality, we believe this method will become a tool of choice for the analysis of densely sampled disease outbreaks, and will form a rigorous framework for subsequent methodological developments. '),
(86409, 2014, 'plos', 'Estimating the probability of polyreactive antibodies 4E10 and 2F5 disabling a gp41 trimer after T cell-HIV adhesion', 'Hu, Bin|Liao, Hua-Xin|Alam, S Munir|Goldstein, Byron', 'Theoretical Biology and Biophysics Group, Theoretical Division, Los Alamos National Laboratory, Los Alamos, New Mexico, United States of America.|Human Vaccine Institute, Duke University Medical Center, Durham, North Carolina, United States of America.|Human Vaccine Institute, Duke University Medical Center, Durham, North Carolina, United States of America.|Theoretical Biology and Biophysics Group, Theoretical Division, Los Alamos National Laboratory, Los Alamos, New Mexico, United States of America.', 'Mexico|United States|United States|Mexico', 3, 'Antibodies, Monoclonal|Antibodies, Neutralizing|Cell Adhesion|Epitopes|HIV Antibodies|HIV Envelope Protein gp41|HIV Infections|Humans|Immunoglobulin Fragments|Immunoglobulin G|Inhibitory Concentration 50|Probability|Protein Conformation|T-Lymphocytes|Virus Internalization', 'Journal Article', '10.1371/journal.pcbi.1003431', '24499928', 'A few broadly neutralizing antibodies, isolated from HIV-1 infected individuals, recognize epitopes in the membrane proximal external region (MPER) of gp41 that are transiently exposed during viral entry. The best characterized, 4E10 and 2F5, are polyreactive, binding to the viral membrane and their epitopes in the MPER. We present a model to calculate, for any antibody concentration, the probability that during the pre-hairpin intermediate, the transient period when the epitopes are first exposed, a bound antibody will disable a trivalent gp41 before fusion is complete. When 4E10 or 2F5 bind to the MPER, a conformational change is induced that results in a stably bound complex. The model predicts that for these antibodies to be effective at neutralization, the time to disable an epitope must be shorter than the time the antibody remains bound in this conformation, about five minutes or less for 4E10 and 2F5. We investigate the role of avidity in neutralization and show that 2F5 IgG, but not 4E10, is much more effective at neutralization than its Fab fragment. We attribute this to 2F5 interacting more stably than 4E10 with the viral membrane. We use the model to elucidate the parameters that determine the ability of these antibodies to disable epitopes and propose an extension of the model to analyze neutralization data. The extended model predicts the dependencies of IC50 for neutralization on the rate constants that characterize antibody binding, the rate of fusion of gp41, and the number of gp41 bridging the virus and target cell at the start of the pre-hairpin intermediate. Analysis of neutralization experiments indicate that only a small number of gp41 bridges must be disabled to prevent fusion. However, the model cannot determine the exact number from neutralization experiments alone.'),
(86410, 2014, 'plos', 'Timing over tuning: overcoming the shortcomings of a line attractor during a working memory task', 'Drover, Jonathan D', 'Brain and Mind Research Institute, Division of Systems Neurology and Neuroscience, Weill Cornell Medical College, New York, New York, United States of America.', 'United States', 2, 'Algorithms|Animals|Computational Biology|Computer Simulation|Discrimination Learning|Memory, Short-Term|Models, Neurological|Nerve Net|Time Factors|Touch|Vibration', 'Journal Article', '10.1371/journal.pcbi.1003437', '24499929', 'How the brain stores information about a sensory stimulus in working memory is not completely known. Clues about the mechanisms responsible for working memory can be gleaned by recording from neurons during the performance of a delayed response task. I focus on the data recorded during such an experiment, a classic tactile discrimination task. I describe how the observed variability in the firing rate during a trial suggests that the type of attractor that is responsible for holding the stimulus information is not a fixed-point type attractor. I propose an alternate mechanism to a line attractor that allows the network to hold the value of an analog stimulus variable for the duration of the delay period, but rather than maintain a constant level of activity, the cells firing rate varies throughout the delay period. I describe how my proposed mechanism offers a substantial advantage over a line attractor: The tuning requirements of cell to cell connections are greatly eased from that of a line attractor. To accommodate a change in the length of the delay period, I show that the network can be altered by changing a single parameter--the timing of an executive signal that originates outside of the network. To demonstrate the mechanism, as well as the tuning benefits, I use a well known model of propagation in neuronal networks.'),
(86411, 2014, 'plos', 'Robustness of DNA repair through collective rate control', 'Verbruggen, Paul|Heinemann, Tim|Manders, Erik|von Bornstaedt, Gesa|van Driel, Roel|Höfer, Thomas', 'Division of Theoretical Systems Biology, German Cancer Research Center (DKFZ), Heidelberg, Germany , Swammerdam Institute for Life Sciences, University of Amsterdam, Amsterdam, The Netherlands.|Division of Theoretical Systems Biology, German Cancer Research Center (DKFZ), Heidelberg, Germany , BioQuant Center, Heidelberg, Germany.|Swammerdam Institute for Life Sciences, University of Amsterdam, Amsterdam, The Netherlands.|Division of Theoretical Systems Biology, German Cancer Research Center (DKFZ), Heidelberg, Germany , BioQuant Center, Heidelberg, Germany.|Swammerdam Institute for Life Sciences, University of Amsterdam, Amsterdam, The Netherlands.|Division of Theoretical Systems Biology, German Cancer Research Center (DKFZ), Heidelberg, Germany , BioQuant Center, Heidelberg, Germany.', 'Germany|Germany|Netherlands|Germany|Netherlands|Germany', 10, 'Algorithms|Animals|Cell Cycle|Cell Line|Chromatin|DNA|DNA Repair|DNA Replication|DNA-Binding Proteins|Green Fluorescent Proteins|Humans|Kinetics|Models, Chemical|Time Factors|Transcription, Genetic|Urea|Xeroderma Pigmentosum Group A Protein', 'Journal Article', '10.1371/journal.pcbi.1003438', '24499930', 'DNA repair and other chromatin-associated processes are carried out by enzymatic macromolecular complexes that assemble at specific sites on the chromatin fiber. How the rate of these molecular machineries is regulated by their constituent parts is poorly understood. Here we quantify nucleotide-excision DNA repair in mammalian cells and find that, despite the pathways molecular complexity, repair effectively obeys slow first-order kinetics. Theoretical analysis and data-based modeling indicate that these kinetics are not due to a singular rate-limiting step. Rather, first-order kinetics emerge from the interplay of rapidly and reversibly assembling repair proteins, stochastically distributing DNA lesion repair over a broad time period. Based on this mechanism, the model predicts that the repair proteins collectively control the repair rate. Exploiting natural cell-to-cell variability, we corroborate this prediction for the lesion-recognition factor XPC and the downstream factor XPA. Our findings provide a rationale for the emergence of slow time scales in chromatin-associated processes from fast molecular steps and suggest that collective rate control might be a widespread mode of robust regulation in DNA repair and transcription. '),
(86412, 2014, 'plos', 'De novo prediction of PTBP1 binding and splicing targets reveals unexpected features of its RNA recognition and function', 'Han, Areum|Stoilov, Peter|Linares, Anthony J|Zhou, Yu|Fu, Xiang-Dong|Black, Douglas L', 'Department of Bioengineering, University of California at Los Angeles, Los Angeles, California, United States of America.|Department of Biochemistry, School of Medicine, West Virginia University, Morgantown, West Virginia, United States of America.|Molecular Biology Interdepartmental Graduate Program, University of California at Los Angeles, Los Angeles, California, United States of America , Medical Scientist Training Program, University of California at Los Angeles, Los Angeles, California, United States of America.|Department of Cellular and Molecular Medicine, University of California at San Diego, La Jolla, California, United States of America.|Department of Cellular and Molecular Medicine, University of California at San Diego, La Jolla, California, United States of America.|Department of Bioengineering, University of California at Los Angeles, Los Angeles, California, United States of America , Department of Microbiology, Immunology and Molecular Genetics, University of California at Los Angeles, Los Angeles, California, United States of America , Howard Hughes Medical Institute, University of California at Los Angeles, Los Angeles, California, United States of America.', 'United States|United States|United States|United States|United States|United States', 0, 'Algorithms|Animals|Binding Sites|Computational Biology|Exons|Guanosine|Heterogeneous-Nuclear Ribonucleoproteins|Humans|Logistic Models|Markov Chains|Mice|Polypyrimidine Tract-Binding Protein|Probability|Protein Binding|Protein Structure, Tertiary|Pyrimidines|RNA|Transcriptome', 'Journal Article', '10.1371/journal.pcbi.1003442', '24499931', 'The splicing regulator Polypyrimidine Tract Binding Protein (PTBP1) has four RNA binding domains that each binds a short pyrimidine element, allowing recognition of diverse pyrimidine-rich sequences. This variation makes it difficult to evaluate PTBP1 binding to particular sites based on sequence alone and thus to identify target RNAs. Conversely, transcriptome-wide binding assays such as CLIP identify many in vivo targets, but do not provide a quantitative assessment of binding and are informative only for the cells where the analysis is performed. A general method of predicting PTBP1 binding and possible targets in any cell type is needed. We developed computational models that predict the binding and splicing targets of PTBP1. A Hidden Markov Model (HMM), trained on CLIP-seq data, was used to score probable PTBP1 binding sites. Scores from this model are highly correlated (xcfx81xe2x80x8a=xe2x80x8a-0.9) with experimentally determined dissociation constants. Notably, we find that the protein is not strictly pyrimidine specific, as interspersed Guanosine residues are well tolerated within PTBP1 binding sites. This model identifies many previously unrecognized PTBP1 binding sites, and can score PTBP1 binding across the transcriptome in the absence of CLIP data. Using this model to examine the placement of PTBP1 binding sites in controlling splicing, we trained a multinomial logistic model on sets of PTBP1 regulated and unregulated exons. Applying this model to rank exons across the mouse transcriptome identifies known PTBP1 targets and many new exons that were confirmed as PTBP1-repressed by RT-PCR and RNA-seq after PTBP1 depletion. We find that PTBP1 dependent exons are diverse in structure and do not all fit previous descriptions of the placement of PTBP1 binding sites. Our study uncovers new features of RNA recognition and splicing regulation by PTBP1. This approach can be applied to other multi-RRM domain proteins to assess binding site degeneracy and multifactorial splicing regulation. '),
(86413, 2014, 'plos', 'Segregation and crosstalk of D1 receptor-mediated activation of ERK in striatal medium spiny neurons upon acute administration of psychostimulants', 'Gutierrez-Arenas, Omar|Eriksson, Olivia|Kotaleski, Jeanette Hellgren', 'School of Computer Science and Communication, KTH Royal Institute of Technology, Stockholm, Sweden.|Department of Numerical Analysis and Computer Science, Stockholm University, Stockholm, Sweden.|School of Computer Science and Communication, KTH Royal Institute of Technology, Stockholm, Sweden , Department of Numerical Analysis and Computer Science, Stockholm University, Stockholm, Sweden , Department of Neuroscience, Karolinska Institute, Stockholm, Sweden.', 'Sweden|Sweden|Sweden', 12, 'Adenylyl Cyclases|Algorithms|Behavior, Addictive|Calcium|Central Nervous System Stimulants|Corpus Striatum|Cyclic AMP|Cyclic AMP-Dependent Protein Kinases|Dopamine|Extracellular Signal-Regulated MAP Kinases|Humans|Kinetics|Models, Neurological|Neurons|Phenotype|Phosphorylation|Receptors, Dopamine D1|Reproducibility of Results|Signal Transduction', 'Journal Article', '10.1371/journal.pcbi.1003445', '24499932', 'The convergence of corticostriatal glutamate and dopamine from the midbrain in the striatal medium spiny neurons (MSN) triggers synaptic plasticity that underlies reinforcement learning and pathological conditions such as psychostimulant addiction. The increase in striatal dopamine produced by the acute administration of psychostimulants has been found to activate not only effectors of the AC5/cAMP/PKA signaling cascade such as GluR1, but also effectors of the NMDAR/Ca(2+)/RAS cascade such as ERK. The dopamine-triggered effects on both these cascades are mediated by D1R coupled to Golf but while the phosphorylation of GluR1 is affected by reductions in the available amount of Golf but not of D1R, the activation of ERK follows the opposite pattern. This segregation is puzzling considering that D1R-induced Golf activation monotonically increases with DA and that there is crosstalk from the AC5/cAMP/PKA cascade to the NMDAR/Ca(2+)/RAS cascade via a STEP (a tyrosine phosphatase). In this work, we developed a signaling model which accounts for this segregation based on the assumption that a common pool of D1R and Golf is distributed in two D1R/Golf signaling compartments. This model integrates a relatively large amount of experimental data for neurons in vivo and in vitro. We used it to explore the crosstalk topologies under which the sensitivities of the AC5/cAMP/PKA signaling cascade to reductions in D1R or Golf are transferred or not to the activation of ERK. We found that the sequestration of STEP by its substrate ERK together with the insensitivity of STEP activity on targets upstream of ERK (i.e. Fyn and NR2B) to PKA phosphorylation are able to explain the experimentally observed segregation. This model provides a quantitative framework for simulation based experiments to study signaling required for long term potentiation in MSNs. '),
(86414, 2014, 'plos', 'A division in PIN-mediated auxin patterning during organ initiation in grasses', 'OConnor, Devin L|Runions, Adam|Sluis, Aaron|Bragg, Jennifer|Vogel, John P|Prusinkiewicz, Przemyslaw|Hake, Sarah', 'Plant and Microbial Biology Department, University of California at Berkeley, Berkeley, California, United States of America , Plant Gene Expression Center, United States Department of Agriculture - Agricultural Research Service (USDA-ARS), Albany, California, United States of America.|Department of Computer Science, University of Calgary, Calgary, Alberta, Canada.|Plant and Microbial Biology Department, University of California at Berkeley, Berkeley, California, United States of America , Plant Gene Expression Center, United States Department of Agriculture - Agricultural Research Service (USDA-ARS), Albany, California, United States of America.|Western Regional Research Center, United States Department of Agriculture - Agriculture Research Service (USDA-ARS), Albany, California, United States of America.|Western Regional Research Center, United States Department of Agriculture - Agriculture Research Service (USDA-ARS), Albany, California, United States of America.|Department of Computer Science, University of Calgary, Calgary, Alberta, Canada.|Plant and Microbial Biology Department, University of California at Berkeley, Berkeley, California, United States of America , Plant Gene Expression Center, United States Department of Agriculture - Agricultural Research Service (USDA-ARS), Albany, California, United States of America.', 'United States|Canada|United States|United States|United States|Canada|United States', 64, 'Algorithms|Arabidopsis|Brachypodium|Computational Biology|Computer Simulation|Flowers|Gene Expression Regulation, Plant|Genes, Reporter|Image Processing, Computer-Assisted|Indoleacetic Acids|Meristem|Phylogeny|Plant Leaves|Poaceae|Software|Zea mays', 'Journal Article', '10.1371/journal.pcbi.1003447', '24499933', 'The hormone auxin plays a crucial role in plant morphogenesis. In the shoot apical meristem, the PIN-FORMED1 (PIN1) efflux carrier concentrates auxin into local maxima in the epidermis, which position incipient leaf or floral primordia. From these maxima, PIN1 transports auxin into internal tissues along emergent paths that pattern leaf and stem vasculature. In Arabidopsis thaliana, these functions are attributed to a single PIN1 protein. Using phylogenetic and gene synteny analysis we identified an angiosperm PIN clade sister to PIN1, here termed Sister-of-PIN1 (SoPIN1), which is present in all sampled angiosperms except for Brassicaceae, including Arabidopsis. Additionally, we identified a conserved duplication of PIN1 in the grasses: PIN1a and PIN1b. In Brachypodium distachyon, SoPIN1 is highly expressed in the epidermis and is consistently polarized toward regions of high expression of the DR5 auxin-signaling reporter, which suggests that SoPIN1 functions in the localization of new primordia. In contrast, PIN1a and PIN1b are highly expressed in internal tissues, suggesting a role in vascular patterning. PIN1b is expressed in broad regions spanning the space between new primordia and previously formed vasculature, suggesting a role in connecting new organs to auxin sinks in the older tissues. Within these regions, PIN1a forms narrow canals that likely pattern future veins. Using a computer model, we reproduced the observed spatio-temporal expression and localization patterns of these proteins by assuming that SoPIN1 is polarized up the auxin gradient, and PIN1a and PIN1b are polarized to different degrees with the auxin flux. Our results suggest that examination and modeling of PIN dynamics in plants outside of Brassicaceae will offer insights into auxin-driven patterning obscured by the loss of the SoPIN1 clade in Brassicaceae. '),
(86415, 2014, 'plos', 'Automated discovery of tissue-targeting enhancers and transcription factors from binding motif and gene function data', 'Tuteja, Geetu|Moreira, Karen Betancourt|Chung, Tisha|Chen, Jenny|Wenger, Aaron M|Bejerano, Gill', 'Department of Developmental Biology, Stanford University, Stanford, California, United States of America.|Department of Developmental Biology, Stanford University, Stanford, California, United States of America.|Department of Developmental Biology, Stanford University, Stanford, California, United States of America.|Biomedical Informatics Program, Stanford University, Stanford, California, United States of America.|Department of Computer Science, Stanford University, Stanford, California, United States of America.|Department of Developmental Biology, Stanford University, Stanford, California, United States of America , Department of Computer Science, Stanford University, Stanford, California, United States of America.', 'United States|United States|United States|United States|United States|United States', 6, 'Algorithms|Amino Acid Motifs|Animals|Automation|Binding Sites|Cluster Analysis|Computational Biology|Computer Simulation|Enhancer Elements, Genetic|Epigenomics|Female|Gene Expression Profiling|Gene Expression Regulation|Humans|Mice|Placenta|Pregnancy|Transcription Factors|Trophoblasts', 'Journal Article', '10.1371/journal.pcbi.1003449', '24499934', 'Identifying enhancers regulating gene expression remains an important and challenging task. While recent sequencing-based methods provide epigenomic characteristics that correlate well with enhancer activity, it remains onerous to comprehensively identify all enhancers across development. Here we introduce a computational framework to identify tissue-specific enhancers evolving under purifying selection. First, we incorporate high-confidence binding site predictions with target gene functional enrichment analysis to identify transcription factors (TFs) likely functioning in a particular context. We then search the genome for clusters of binding sites for these TFs, overcoming previous constraints associated with biased manual curation of TFs or enhancers. Applying our method to the placenta, we find 33 known and implicate 17 novel TFs in placental function, and discover 2,216 putative placenta enhancers. Using luciferase reporter assays, 31/36 (86%) tested candidates drive activity in placental cells. Our predictions agree well with recent epigenomic data in human and mouse, yet over half our loci, including 7/8 (87%) tested regions, are novel. Finally, we establish that our method is generalizable by applying it to 5 additional tissues: heart, pancreas, blood vessel, bone marrow, and liver. ');
INSERT INTO `papers` (`id`, `ano`, `journal`, `titulo`, `autores`, `afiliacao`, `pais`, `citacoes`, `palavra_chave`, `categorias`, `doi`, `pubmed`, `abstract`) VALUES
(86416, 2014, 'plos', 'Global patterns of protein domain gain and loss in superkingdoms', 'Nasir, Arshan|Kim, Kyung Mo|Caetano-Anollés, Gustavo', 'Evolutionary Bioinformatics Laboratory, Department of Crop Sciences, University of Illinois, Urbana, Illinois, United States of America , Illinois Informatics Institute, University of Illinois, Urbana, Illinois, United States of America.|Microbial Resource Center, Korea Research Institute of Bioscience and Biotechnology, Daejeon, Korea.|Evolutionary Bioinformatics Laboratory, Department of Crop Sciences, University of Illinois, Urbana, Illinois, United States of America , Illinois Informatics Institute, University of Illinois, Urbana, Illinois, United States of America.', 'United States|-|United States', 38, 'Algorithms|Archaea|Bacteria|Computational Biology|Evolution, Molecular|Genomics|Phylogeny|Protein Folding|Protein Structure, Tertiary|Proteome|Proteomics|Reproducibility of Results|Symbiosis', 'Journal Article', '10.1371/journal.pcbi.1003452', '24499935', 'Domains are modules within proteins that can fold and function independently and are evolutionarily conserved. Here we compared the usage and distribution of protein domain families in the free-living proteomes of Archaea, Bacteria and Eukarya and reconstructed species phylogenies while tracing the history of domain emergence and loss in proteomes. We show that both gains and losses of domains occurred frequently during proteome evolution. The rate of domain discovery increased approximately linearly in evolutionary time. Remarkably, gains generally outnumbered losses and the gain-to-loss ratios were much higher in akaryotes compared to eukaryotes. Functional annotations of domain families revealed that both Archaea and Bacteria gained and lost metabolic capabilities during the course of evolution while Eukarya acquired a number of diverse molecular functions including those involved in extracellular processes, immunological mechanisms, and cell regulation. Results also highlighted significant contemporary sharing of informational enzymes between Archaea and Eukarya and metabolic enzymes between Bacteria and Eukarya. Finally, the analysis provided useful insights into the evolution of species. The archaeal superkingdom appeared first in evolution by gradual loss of ancestral domains, bacterial lineages were the first to gain superkingdom-specific domains, and eukaryotes (likely) originated when an expanding proto-eukaryotic stem lineage gained organelles through endosymbiosis of already diversified bacterial lineages. The evolutionary dynamics of domain families in proteomes and the increasing number of domain gains is predicted to redefine the persistence strategies of organisms in superkingdoms, influence the make up of molecular functions, and enhance organismal complexity by the generation of new domain architectures. This dynamics highlights ongoing secondary evolutionary adaptations in akaryotic microbes, especially Archaea. '),
(86417, 2014, 'plos', 'Ten simple rules for writing research papers', 'Zhang, Weixiong', 'Department of Computer Science and Engineering, Department of Genetics, Washington University in St. Louis, St. Louis, Missouri, United States of America.', 'United States', 0, 'Computational Biology|Humans|Periodicals as Topic|Research|Research Design|Statistics as Topic|Writing', 'Journal Article', '10.1371/journal.pcbi.1003453', '24499936', '-'),
(86418, 2014, 'plos', 'A model for the epigenetic switch linking inflammation to cell transformation: deterministic and stochastic approaches', 'Gxc3xa9rard, Claude|Gonze, Didier|Lemaigre, Frxc3xa9dxc3xa9ric|Novxc3xa1k, Bxc3xa9la', 'Oxford Centre for Integrative Systems Biology, Department of Biochemistry, University of Oxford, Oxford, United Kingdom , de Duve Institute, Universitxc3xa9 Catholique de Louvain (UCL), Brussels, Belgium.|Facultxc3xa9 des Sciences, Universitxc3xa9 Libre de Bruxelles (ULB), Campus Plaine, Brussels, Belgium.|de Duve Institute, Universitxc3xa9 Catholique de Louvain (UCL), Brussels, Belgium.|Oxford Centre for Integrative Systems Biology, Department of Biochemistry, University of Oxford, Oxford, United Kingdom.', 'Belgium|Belgium|Belgium|United Kingdom', 11, 'Cell Transformation, Neoplastic|Computer Simulation|Epigenesis, Genetic|Genes, Tumor Suppressor|Humans|Inflammation|Kinetics|MicroRNAs|Models, Biological|NF-kappa B|Oncogenes|PTEN Phosphohydrolase|RNA-Binding Proteins|STAT3 Transcription Factor|Stochastic Processes', 'Journal Article', '10.1371/journal.pcbi.1003455', '24499937', 'Recently, a molecular pathway linking inflammation to cell transformation has been discovered. This molecular pathway rests on a positive inflammatory feedback loop between NF-xcexbaB, Lin28, Let-7 microRNA and IL6, which leads to an epigenetic switch allowing cell transformation. A transient activation of an inflammatory signal, mediated by the oncoprotein Src, activates NF-xcexbaB, which elicits the expression of Lin28. Lin28 decreases the expression of Let-7 microRNA, which results in higher level of IL6 than achieved directly by NF-xcexbaB. In turn, IL6 can promote NF-xcexbaB activation. Finally, IL6 also elicits the synthesis of STAT3, which is a crucial activator for cell transformation. Here, we propose a computational model to account for the dynamical behavior of this positive inflammatory feedback loop. By means of a deterministic model, we show that an irreversible bistable switch between a transformed and a non-transformed state of the cell is at the core of the dynamical behavior of the positive feedback loop linking inflammation to cell transformation. The model indicates that inhibitors (tumor suppressors) or activators (oncogenes) of this positive feedback loop regulate the occurrence of the epigenetic switch by modulating the threshold of inflammatory signal (Src) needed to promote cell transformation. Both stochastic simulations and deterministic simulations of a heterogeneous cell population suggest that random fluctuations (due to molecular noise or cell-to-cell variability) are able to trigger cell transformation. Moreover, the model predicts that oncogenes/tumor suppressors respectively decrease/increase the robustness of the non-transformed state of the cell towards random fluctuations. Finally, the model accounts for the potential effect of competing endogenous RNAs, ceRNAs, on the dynamics of the epigenetic switch. Depending on their microRNA targets, the model predicts that ceRNAs could act as oncogenes or tumor suppressors by regulating the occurrence of cell transformation. '),
(86419, 2014, 'plos', 'Building the future of bioinformatics through student-facilitated conferencing', 'Ramdayal, Kavisha|Stobbe, Miranda D|Mishra, Tarun|Michaut, Magali', 'South African National Bioinformatics Institute, University of the Western Cape, Cape Town, South Africa.|Bioinformatics Laboratory, Academic Medical Center, University of Amsterdam, Amsterdam, The Netherlands , Netherlands Bioinformatics Centre, Nijmegen, The Netherlands.|Bioinformatics Division, School of Bio Sciences and Technology, VIT University, Vellore, India.|Computational Cancer Biology, The Netherlands Cancer Institute, Amsterdam, The Netherlands.', 'South Africa|Netherlands|India|Netherlands', 0, 'Communication|Computational Biology|Congresses as Topic|Humans|Societies, Scientific|Students', 'Journal Article', '10.1371/journal.pcbi.1003458', '24499938', 'Sharing results, techniques, and challenges is paramount to advance our understanding of any field of science. In the scientific community this exchange of ideas is mainly made possible through national and international conferences. Scientists have the opportunity to showcase their work, receive feedback, and improve their presentation skills. However, conferences can be large and intimidating for young researchers. In addition, for many of the more prestigious conferences, the very high number of submissions and low selection rate are major limitations to aspiring young researchers aiming to present their work to the scientific community. To improve student participation and proliferation of information, regional student groups have successfully organized conferences and symposia specifically aimed at students. This gives more students the opportunity to present their work and receive valuable experience and insight from peers and leaders in the field. At the same time, it is an ideal way for students to gain familiarity with the conference experience. In this paper, we highlight some of the benefits of participating in such student conferences, and we review the challenges we have encountered when organizing them. Both topics are illustrated in detail with examples from different ISCB Student Council Regional Student Groups. '),
(86420, 2014, 'plos', 'A unified view of how allostery works', 'Tsai, Chung-Jung|Nussinov, Ruth', 'Cancer and Inflammation Program, Leidos Biomedical Research, Inc., Frederick National Laboratory, National Cancer Institute, Center for Cancer Research, Frederick, Maryland, United States of America.|Cancer and Inflammation Program, Leidos Biomedical Research, Inc., Frederick National Laboratory, National Cancer Institute, Center for Cancer Research, 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.', 'United States|Israel', 193, 'Allosteric Regulation|Allosteric Site|Computational Biology|Ligands|Models, Biological|Signal Transduction|Thermodynamics', 'Journal Article', '10.1371/journal.pcbi.1003394', '24516370', 'The question of how allostery works was posed almost 50 years ago. Since then it has been the focus of much effort. This is for two reasons: first, the intellectual curiosity of basic science and the desire to understand fundamental phenomena, and second, its vast practical importance. Allostery is at play in all processes in the living cell, and increasingly in drug discovery. Many models have been successfully formulated, and are able to describe allostery even in the absence of a detailed structural mechanism. However, conceptual schemes designed to qualitatively explain allosteric mechanisms usually lack a quantitative mathematical model, and are unable to link its thermodynamic and structural foundations. This hampers insight into oncogenic mutations in cancer progression and biased agonists actions. Here, we describe how allostery works from three different standpoints: thermodynamics, free energy landscape of population shift, and structure, all with exactly the same allosteric descriptors. This results in a unified view which not only clarifies the elusive allosteric mechanism but also provides structural grasp of agonist-mediated signaling pathways, and guides allosteric drug discovery. Of note, the unified view reasons that allosteric coupling (or communication) does not determine the allosteric efficacy, however, a communication channel is what makes potential binding sites allosteric. '),
(86421, 2014, 'plos', 'Compact modeling of allosteric multisite proteins: application to a cell size checkpoint', 'Enciso, Germán|Kellogg, Douglas R|Vargas, Arturo', 'Department of Mathematics, Department of Developmental and Cell Biology, University of California Irvine, Irvine, California, United States of America.|Department of Molecular, Cell and Developmental Biology, University of California Santa Cruz, Santa Cruz, California, United States of America.|Computational and Applied Mathematics Department, Rice University, Houston, Texas, United States of America.', 'United States|United States|United States', 6, 'Adaptor Proteins, Signal Transducing|Allosteric Site|Cell Growth Processes|Computational Biology|Models, Biological|Models, Molecular|Phosphorylation|Protein Kinase C|Protein Phosphatase 2|Protein Processing, Post-Translational|Proteins|Saccharomyces cerevisiae|Saccharomyces cerevisiae Proteins|Signal Transduction|rho GTP-Binding Proteins', 'Journal Article', '10.1371/journal.pcbi.1003443', '24516371', 'We explore a framework to model the dose response of allosteric multisite phosphorylation proteins using a single auxiliary variable. This reduction can closely replicate the steady state behavior of detailed multisite systems such as the Monod-Wyman-Changeux allosteric model or rule-based models. Optimal ultrasensitivity is obtained when the activation of an allosteric protein by its individual sites is concerted and redundant. The reduction makes this framework useful for modeling and analyzing biochemical systems in practical applications, where several multisite proteins may interact simultaneously. As an application we analyze a newly discovered checkpoint signaling pathway in budding yeast, which has been proposed to measure cell growth by monitoring signals generated at sites of plasma membrane growth. We show that the known components of this pathway can form a robust hysteretic switch. In particular, this system incorporates a signal proportional to bud growth or size, a mechanism to read the signal, and an all-or-none response triggered only when the signal reaches a threshold indicating that sufficient growth has occurred. '),
(86422, 2014, 'plos', 'VarWalker: personalized mutation network analysis of putative cancer genes from next-generation sequencing data', 'Jia, Peilin|Zhao, Zhongming', 'Department of Biomedical Informatics, Vanderbilt University School of Medicine, Nashville, Tennessee, United States of America , Center for Quantitative Sciences, Vanderbilt University Medical Center, Nashville, Tennessee, United States of America.|Department of Biomedical Informatics, Vanderbilt University School of Medicine, Nashville, Tennessee, United States of America , Center for Quantitative Sciences, Vanderbilt University Medical Center, Nashville, Tennessee, United States of America , Department of Cancer Biology, Vanderbilt University School of Medicine, Nashville, Tennessee, United States of America , Department of Psychiatry, Vanderbilt University School of Medicine, Nashville, Tennessee, United States of America.', 'United States|United States', 69, 'Adenocarcinoma|Adenocarcinoma of Lung|Algorithms|Computational Biology|Consensus Sequence|DNA Mutational Analysis|DNA, Neoplasm|Databases, Genetic|Gene Frequency|Gene Regulatory Networks|High-Throughput Nucleotide Sequencing|Humans|Lung Neoplasms|Melanoma|Models, Genetic|Molecular Sequence Annotation|Mutation|Neoplasms|Oncogenes', 'Journal Article', '10.1371/journal.pcbi.1003460', '24516372', 'A major challenge in interpreting the large volume of mutation data identified by next-generation sequencing (NGS) is to distinguish driver mutations from neutral passenger mutations to facilitate the identification of targetable genes and new drugs. Current approaches are primarily based on mutation frequencies of single-genes, which lack the power to detect infrequently mutated driver genes and ignore functional interconnection and regulation among cancer genes. We propose a novel mutation network method, VarWalker, to prioritize driver genes in large scale cancer mutation data. VarWalker fits generalized additive models for each sample based on sample-specific mutation profiles and builds on the joint frequency of both mutation genes and their close interactors. These interactors are selected and optimized using the Random Walk with Restart algorithm in a protein-protein interaction network. We applied the method in >300 tumor genomes in two large-scale NGS benchmark datasets: 183 lung adenocarcinoma samples and 121 melanoma samples. In each cancer, we derived a consensus mutation subnetwork containing significantly enriched consensus cancer genes and cancer-related functional pathways. These cancer-specific mutation networks were then validated using independent datasets for each cancer. Importantly, VarWalker prioritizes well-known, infrequently mutated genes, which are shown to interact with highly recurrently mutated genes yet have been ignored by conventional single-gene-based approaches. Utilizing VarWalker, we demonstrated that network-assisted approaches can be effectively adapted to facilitate the detection of cancer driver genes in NGS data. '),
(86423, 2014, 'plos', 'Mathematical modeling of the Phoenix Rising pathway', 'Liu, Chad|Li, Chuan-Yuan|Yuan, Fan', 'Department of Biomedical Engineering, Duke University, Durham, North Carolina, United States of America.|Department of Dermatology, Duke University Medical Center, Durham, North Carolina, United States of America.|Department of Biomedical Engineering, Duke University, Durham, North Carolina, United States of America.', 'United States|United States|United States', 6, 'Animals|Apoptosis|Caspase 3|Caspase 7|Cell Line, Tumor|Cell Proliferation|Cells, Cultured|Computational Biology|Computer Simulation|Cyclooxygenase 2|Cyclooxygenase 2 Inhibitors|Female|Mammary Neoplasms, Experimental|Mathematical Concepts|Mice|Models, Biological|NF-kappa B|Phospholipases A2|Prostaglandins E|Signal Transduction', 'Journal Article', '10.1371/journal.pcbi.1003461', '24516373', 'Apoptosis is a tightly controlled process in mammalian cells. It is important for embryogenesis, tissue homoeostasis, and cancer treatment. Apoptosis not only induces cell death, but also leads to the release of signals that promote rapid proliferation of surrounding cells through the Phoenix Rising (PR) pathway. To quantitatively understand the kinetics of interactions of different molecules in this pathway, we developed a mathematical model to simulate the effects of various changes in the PR pathway on the secretion of prostaglandin E2 (PGE2), a key factor for promoting cell proliferation. These changes include activation of caspase 3 (C3), caspase 7 (C7), and nuclear factor xcexbaB (NFxcexbaB). In addition, we simulated the effects of cyclooxygenase-2 (COX2) inhibition and C3 knockout on the level of secreted PGE2. The model predictions on PGE2 in MEF and 4T1 cells at 48 hours after 10-Gray radiation were quantitatively consistent with the experimental data in the literature. Compared to C7, the model predicted that C3 activation was more critical for PGE2 production. The model also predicted that PGE2 production could be significantly reduced when COX2 expression was blocked via either NFxcexbaB inactivation or treatment of cells with exogenous COX2 inhibitors, which led to a decrease in the rate of conversion from arachidonic acid to prostaglandin H2 in the PR pathway. In conclusion, the mathematical model developed in this study yielded new insights into the process of tissue regrowth stimulated by signals from apoptotic cells. In future studies, the model can be used for experimental data analysis and assisting development of novel strategies/drugs for improving cancer treatment or normal tissue regeneration. '),
(86424, 2014, 'plos', 'The free energy profile of tubulin straight-bent conformational changes, with implications for microtubule assembly and drug discovery', 'Peng, Lili X|Hsu, Monica T|Bonomi, Massimiliano|Agard, David A|Jacobson, Matthew P', 'Department of Pharmaceutical Chemistry, University of California, San Francisco, San Francisco, California, United States of America.|Graduate Group in Biophysics, University of California, San Francisco, San Francisco, California, United States of America.|Department of Bioengineering and Therapeutic Sciences, University of California, San Francisco, San Francisco, California, United States of America.|Howard Hughes Medical Institute and Department of Biochemistry and Biophysics, University of California, San Francisco, San Francisco, California, United States of America.|Department of Pharmaceutical Chemistry, University of California, San Francisco, San Francisco, California, United States of America , Department of Biochemistry and Biophysics, University of California, San Francisco, San Francisco, California, United States of America.', 'United States|United States|United States|United States|United States', 22, 'Animals|Binding Sites|Cattle|Colchicine|Computational Biology|Computer Simulation|Drug Discovery|Guanosine Diphosphate|Microtubules|Models, Molecular|Molecular Dynamics Simulation|Protein Conformation|Protein Multimerization|Protein Structure, Quaternary|Protein Subunits|Thermodynamics|Tubulin', 'Journal Article', '10.1371/journal.pcbi.1003464', '24516374', 'xcexb1xcexb2-tubulin dimers need to convert between a bent conformation observed for free dimers in solution and a straight conformation required for incorporation into the microtubule lattice. Here, we investigate the free energy landscape of xcexb1xcexb2-tubulin using molecular dynamics simulations, emphasizing implications for models of assembly, and modulation of the conformational landscape by colchicine, a tubulin-binding drug that inhibits microtubule polymerization. Specifically, we performed molecular dynamics, potential-of-mean force simulations to obtain the free energy profile for unpolymerized GDP-bound tubulin as a function of the xe2x88xbc12xc2xb0 intradimer rotation differentiating the straight and bent conformers. Our results predict that the unassembled GDP-tubulin heterodimer exists in a continuum of conformations ranging between straight and bent, but, in agreement with existing structural data, suggests that an intermediate bent state has a lower free energy (by xe2x88xbc1 kcal/mol) and thus dominates in solution. In agreement with predictions of the lattice model of microtubule assembly, lateral binding of two xcexb1xcexb2-tubulins strongly shifts the conformational equilibrium towards the straight state, which is then xe2x88xbc1 kcal/mol lower in free energy than the bent state. Finally, calculations of colchicine binding to a single xcexb1xcexb2-tubulin dimer strongly shifts the equilibrium toward the bent states, and disfavors the straight state to the extent that it is no longer thermodynamically populated. '),
(86425, 2014, 'plos', 'Comparative genome-scale reconstruction of gapless metabolic networks for present and ancestral species', 'Pitkänen, Esa|Jouhten, Paula|Hou, Jian|Syed, Muhammad Fahad|Blomberg, Peter|Kludas, Jana|Oja, Merja|Holm, Liisa|Penttilä, Merja|Rousu, Juho|Arvas, Mikko', 'Department of Computer Science, University of Helsinki, Helsinki, Finland , Department of Medical Genetics, Genome-Scale Biology Research Program, University of Helsinki, Helsinki, Finland.|VTT Technical Research Centre of Finland, Espoo, Finland.|Department of Computer Science, University of Helsinki, Helsinki, Finland , Department of Information and Computer Science, Aalto University, Espoo, Finland.|VTT Technical Research Centre of Finland, Espoo, Finland.|VTT Technical Research Centre of Finland, Espoo, Finland.|Department of Information and Computer Science, Aalto University, Espoo, Finland.|VTT Technical Research Centre of Finland, Espoo, Finland.|Institute of Biotechnology & Department of Biosciences, University of Helsinki, Helsinki, Finland.|VTT Technical Research Centre of Finland, Espoo, Finland.|Department of Information and Computer Science, Aalto University, Espoo, Finland.|VTT Technical Research Centre of Finland, Espoo, Finland.', 'Finland|Finland|Finland|Finland|Finland|Finland|Finland|Finland|Finland|Finland|Finland', 0, 'Algorithms|Biomass|Biotechnology|Computational Biology|Evolution, Molecular|Fungi|Gene Knockout Techniques|Genome, Fungal|Industrial Microbiology|Metabolic Networks and Pathways|Models, Biological|Models, Genetic|Models, Statistical|Phylogeny|Saccharomyces cerevisiae|Species Specificity', 'Comparative Study', '10.1371/journal.pcbi.1003465', '24516375', 'We introduce a novel computational approach, CoReCo, for comparative metabolic reconstruction and provide genome-scale metabolic network models for 49 important fungal species. Leveraging on the exponential growth in sequenced genome availability, our method reconstructs genome-scale gapless metabolic networks simultaneously for a large number of species by integrating sequence data in a probabilistic framework. High reconstruction accuracy is demonstrated by comparisons to the well-curated Saccharomyces cerevisiae consensus model and large-scale knock-out experiments. Our comparative approach is particularly useful in scenarios where the quality of available sequence data is lacking, and when reconstructing evolutionary distant species. Moreover, the reconstructed networks are fully carbon mapped, allowing their use in 13C flux analysis. We demonstrate the functionality and usability of the reconstructed fungal models with computational steady-state biomass production experiment, as these fungi include some of the most important production organisms in industrial biotechnology. In contrast to many existing reconstruction techniques, only minimal manual effort is required before the reconstructed models are usable in flux balance experiments. CoReCo is available at http://esaskar.github.io/CoReCo/. '),
(86426, 2014, 'plos', 'Overexpression of heat shock protein 72 attenuates NF-xcexbaB activation using a combination of regulatory mechanisms in microglia', 'Sheppard, Patrick W|Sun, Xiaoyun|Khammash, Mustafa|Giffard, Rona G', 'Department of Mechanical Engineering, University of California, Santa Barbara, Santa Barbara, California, United States of America , Department of Biosystems Science and Engineering, ETH-Zurich, Basel, Switzerland.|Department of Anesthesia, Stanford University, Stanford, California, United States of America.|Department of Biosystems Science and Engineering, ETH-Zurich, Basel, Switzerland.|Department of Anesthesia, Stanford University, Stanford, California, United States of America.', 'Switzerland|United States|Switzerland|United States', 26, 'Animals|Cell Line|Computational Biology|DNA|HSP72 Heat-Shock Proteins|I-kappa B Kinase|I-kappa B Proteins|Mathematical Concepts|Mice|Microglia|Models, Neurological|NF-KappaB Inhibitor alpha|NF-kappa B|RNA, Messenger|Signal Transduction|Transcription Factor RelA|Tumor Necrosis Factor-alpha|Up-Regulation', 'Journal Article', '10.1371/journal.pcbi.1003471', '24516376', 'Overexpression of the inducible heat shock protein 70, Hsp72, has broadly cytoprotective effects and improves outcome following stroke. A full understanding of how Hsp72 protects cells against injury is elusive, though several distinct mechanisms are implicated. One mechanism is its anti-inflammatory effects. We study the effects of Hsp72 overexpression on activation of the transcription factor NF-xcexbaB in microglia combining experimentation and mathematical modeling, using TNFxcexb1 to stimulate a microglial cell line stably overexpressing Hsp72. We find that Hsp72 overexpression reduces the amount of NF-xcexbaB DNA binding activity, activity of the upstream kinase IKK, and amount of IxcexbaBxcexb1 inhibitor phosphorylated following TNFxcexb1 application. Simulations evaluating several proposed mechanisms suggest that inhibition of IKK activation is an essential component of its regulatory activities. Unexpectedly we find that Hsp72 overexpression reduces the initial amount of the RelA/p65 NF-xcexbaB subunit in cells, contributing to the attenuated response. Neither mechanism in isolation, however, is sufficient to attenuate the response, providing evidence that Hsp72 relies upon multiple mechanisms to attenuate NF-xcexbaB activation. An additional observation from our study is that the induced expression of IxcexbaBxcexb1 is altered significantly in Hsp72 expressing cells. While the mechanism responsible for this observation is not known, it points to yet another means by which Hsp72 may alter the NF-xcexbaB response. This study illustrates the multi-faceted nature of Hsp72 regulation of NF-xcexbaB activation in microglia and offers further clues to a novel mechanism by which Hsp72 may protect cells against injury. '),
(86427, 2014, 'plos', 'Navigating the multilayered organization of eukaryotic signaling: a new trend in data integration', 'Santra, Tapesh|Kolch, Walter|Kholodenko, Boris N', 'Systems Biology Ireland, University College Dublin, Belfield, Dublin, Ireland.|Systems Biology Ireland, University College Dublin, Belfield, Dublin, Ireland , Conway Institute of Biomolecular and Biomedical Research, University College Dublin, Belfield, Dublin, Ireland , School of Medicine and Medical Science, University College Dublin, Belfield, Dublin, Ireland.|Systems Biology Ireland, University College Dublin, Belfield, Dublin, Ireland , Conway Institute of Biomolecular and Biomedical Research, University College Dublin, Belfield, Dublin, Ireland , School of Medicine and Medical Science, University College Dublin, Belfield, Dublin, Ireland.', 'Ireland|Ireland|Ireland', 0, 'Animals|Computational Biology|Databases, Factual|Drug Discovery|Humans|Models, Biological|Signal Transduction|Systems Integration', 'Journal Article', '10.1371/journal.pcbi.1003385', '24550716', 'The ever-increasing capacity of biological molecular data acquisition outpaces our ability to understand the meaningful relationships between molecules in a cell. Multiple databases were developed to store and organize these molecular data. However, emerging fundamental questions about concerted functions of these molecules in hierarchical cellular networks are poorly addressed. Here we review recent advances in the development of publically available databases that help us analyze the signal integration and processing by multilayered networks that specify biological responses in model organisms and human cells. '),
(86428, 2014, 'plos', 'Mathematical model of a telomerase transcriptional regulatory network developed by cell-based screening: analysis of inhibitor effects and telomerase expression mechanisms', 'Bilsland, Alan E|Stevenson, Katrina|Liu, Yu|Hoare, Stacey|Cairney, Claire J|Roffey, Jon|Keith, W Nicol', 'Institute of Cancer Sciences, University of Glasgow, Cancer Research UK Beatson Laboratories, Bearsden, Glasgow, United Kingdom.|Institute of Cancer Sciences, University of Glasgow, Cancer Research UK Beatson Laboratories, Bearsden, Glasgow, United Kingdom.|Institute of Cancer Sciences, University of Glasgow, Cancer Research UK Beatson Laboratories, Bearsden, Glasgow, United Kingdom.|Institute of Cancer Sciences, University of Glasgow, Cancer Research UK Beatson Laboratories, Bearsden, Glasgow, United Kingdom.|Institute of Cancer Sciences, University of Glasgow, Cancer Research UK Beatson Laboratories, Bearsden, Glasgow, United Kingdom.|Cancer Research Technology Ltd., Wolfson Institute for Biomedical Research, London, United Kingdom.|Institute of Cancer Sciences, University of Glasgow, Cancer Research UK Beatson Laboratories, Bearsden, Glasgow, United Kingdom.', 'United Kingdom|United Kingdom|United Kingdom|United Kingdom|United Kingdom|United Kingdom|United Kin', 12, 'Cell Line, Tumor|Computational Biology|Drug Discovery|Enzyme Inhibitors|Female|Gene Regulatory Networks|Genes, myc|Glycogen Synthase Kinase 3|Humans|Indoles|Mathematical Concepts|Models, Biological|Models, Genetic|Neoplasms|Ovarian Neoplasms|Proto-Oncogene Protein c-ets-2|Pyrazoles|Pyridazines|Signal Transduction|Sulfonamides|Telomerase|Transfection', 'Journal Article', '10.1371/journal.pcbi.1003448', '24550717', 'Cancer cells depend on transcription of telomerase reverse transcriptase (TERT). Many transcription factors affect TERT, though regulation occurs in context of a broader network. Network effects on telomerase regulation have not been investigated, though deeper understanding of TERT transcription requires a systems view. However, control over individual interactions in complex networks is not easily achievable. Mathematical modelling provides an attractive approach for analysis of complex systems and some models may prove useful in systems pharmacology approaches to drug discovery. In this report, we used transfection screening to test interactions among 14 TERT regulatory transcription factors and their respective promoters in ovarian cancer cells. The results were used to generate a network model of TERT transcription and to implement a dynamic Boolean model whose steady states were analysed. Modelled effects of signal transduction inhibitors successfully predicted TERT repression by Src-family inhibitor SU6656 and lack of repression by ERK inhibitor FR180204, results confirmed by RT-QPCR analysis of endogenous TERT expression in treated cells. Modelled effects of GSK3 inhibitor 6-bromoindirubin-3-oxime (BIO) predicted unstable TERT repression dependent on noise and expression of JUN, corresponding with observations from a previous study. MYC expression is critical in TERT activation in the model, consistent with its well known function in endogenous TERT regulation. Loss of MYC caused complete TERT suppression in our model, substantially rescued only by co-suppression of AR. Interestingly expression was easily rescued under modelled Ets-factor gain of function, as occurs in TERT promoter mutation. RNAi targeting AR, JUN, MXD1, SP3, or TP53, showed that AR suppression does rescue endogenous TERT expression following MYC knockdown in these cells and SP3 or TP53 siRNA also cause partial recovery. The model therefore successfully predicted several aspects of TERT regulation including previously unknown mechanisms. An extrapolation suggests that a dominant stimulatory system may programme TERT for transcriptional stability. '),
(86429, 2014, 'plos', 'A BMP-FGF morphogen toggle switch drives the ultrasensitive expression of multiple genes in the developing forebrain', 'Srinivasan, Shyam|Hu, Jia Sheng|Currle, D Spencer|Fung, Ernest S|Hayes, Wayne B|Lander, Arthur D|Monuki, Edwin S', 'Department of Developmental and Cell Biology, University of California, Irvine, California, United States of America , Center for Complex Biological Systems, University of California, Irvine, California, United States of America , Department of Computer Science, University of California, Irvine, California, United States of America.|Department of Developmental and Cell Biology, University of California, Irvine, California, United States of America.|Department of Developmental and Cell Biology, University of California, Irvine, California, United States of America , Department of Developmental Neurobiology, St Jude Childrens Research Hospital, Memphis, Tennessee, United States of America.|Department of Pathology and Laboratory Medicine, University of California, Irvine, California, United States of America.|Department of Computer Science, University of California, Irvine, California, United States of America.|Department of Developmental and Cell Biology, University of California, Irvine, California, United States of America , Center for Complex Biological Systems, University of California, Irvine, California, United States of America.|Department of Developmental and Cell Biology, University of California, Irvine, California, United States of America , Center for Complex Biological Systems, University of California, Irvine, California, United States of America , Department of Pathology and Laboratory Medicine, University of California, Irvine, California, United States of America.', 'United States|United States|United States|United States|United States|United States|United States', 0, 'Animals|Bone Morphogenetic Protein 4|Bone Morphogenetic Proteins|Computational Biology|Embryo Culture Techniques|Feedback, Physiological|Female|Fibroblast Growth Factors|Gene Expression Regulation, Developmental|MSX1 Transcription Factor|Mice|Mice, Transgenic|Models, Biological|Pregnancy|Prosencephalon|Receptors, Fibroblast Growth Factor|Signal Transduction|Telencephalon', 'Journal Article', '10.1371/journal.pcbi.1003463', '24550718', 'Borders are important as they demarcate developing tissue into distinct functional units. A key challenge is the discovery of mechanisms that can convert morphogen gradients into tissue borders. While mechanisms that produce ultrasensitive cellular responses provide a solution, how extracellular morphogens drive such mechanisms remains poorly understood. Here, we show how Bone Morphogenetic Protein (BMP) and Fibroblast Growth Factor (FGF) pathways interact to generate ultrasensitivity and borders in the dorsal telencephalon. BMP and FGF signaling manipulations in explants produced border defects suggestive of cross inhibition within single cells, which was confirmed in dissociated cultures. Using mathematical modeling, we designed experiments that ruled out alternative cross inhibition mechanisms and identified a cross-inhibitory positive feedback (CIPF) mechanism, or toggle switch, which acts upstream of transcriptional targets in dorsal telencephalic cells. CIPF explained several cellular phenomena important for border formation such as threshold tuning, ultrasensitivity, and hysteresis. CIPF explicitly links graded morphogen signaling in the telencephalon to switch-like cellular responses and has the ability to form multiple borders and scale pattern to size. These benefits may apply to other developmental systems. '),
(86430, 2014, 'plos', 'Modelling individual differences in the form of Pavlovian conditioned approach responses: a dual learning systems approach with factored representations', 'Lesaint, Florian|Sigaud, Olivier|Flagel, Shelly B|Robinson, Terry E|Khamassi, Mehdi', 'Institut des Systèmes Intelligents et de Robotique, UMR 7222, UPMC Univ Paris 06, Paris, France , Institut des Systèmes Intelligents et de Robotique, UMR 7222, CNRS, Paris, France.|Institut des Systèmes Intelligents et de Robotique, UMR 7222, UPMC Univ Paris 06, Paris, France , Institut des Systèmes Intelligents et de Robotique, UMR 7222, CNRS, Paris, France.|Department of Psychiatry, University of Michigan, Ann Arbor, Michigan, United States of America , Molecular and Behavioral Neuroscience Institute, University of Michigan, Ann Arbor, Michigan, United States of America , Department of Psychology, University of Michigan, Ann Arbor, Michigan, United States of America.|Department of Psychology, University of Michigan, Ann Arbor, Michigan, United States of America.|Institut des Systèmes Intelligents et de Robotique, UMR 7222, UPMC Univ Paris 06, Paris, France , Institut des Systèmes Intelligents et de Robotique, UMR 7222, CNRS, Paris, France.', 'France|France|United States|United States|France', 50, 'Algorithms|Animals|Behavior, Animal|Brain|Computational Biology|Conditioning (Psychology)|Dopamine|Dopamine Antagonists|Flupenthixol|Models, Neurological|Models, Psychological|Rats|Reinforcement (Psychology)|Systems Biology', 'Journal Article', '10.1371/journal.pcbi.1003466', '24550719', 'Reinforcement Learning has greatly influenced models of conditioning, providing powerful explanations of acquired behaviour and underlying physiological observations. However, in recent autoshaping experiments in rats, variation in the form of Pavlovian conditioned responses (CRs) and associated dopamine activity, have questioned the classical hypothesis that phasic dopamine activity corresponds to a reward prediction error-like signal arising from a classical Model-Free system, necessary for Pavlovian conditioning. Over the course of Pavlovian conditioning using food as the unconditioned stimulus (US), some rats (sign-trackers) come to approach and engage the conditioned stimulus (CS) itself - a lever - more and more avidly, whereas other rats (goal-trackers) learn to approach the location of food delivery upon CS presentation. Importantly, although both sign-trackers and goal-trackers learn the CS-US association equally well, only in sign-trackers does phasic dopamine activity show classical reward prediction error-like bursts. Furthermore, neither the acquisition nor the expression of a goal-tracking CR is dopamine-dependent. Here we present a computational model that can account for such individual variations. We show that a combination of a Model-Based system and a revised Model-Free system can account for the development of distinct CRs in rats. Moreover, we show that revising a classical Model-Free system to individually process stimuli by using factored representations can explain why classical dopaminergic patterns may be observed for some rats and not for others depending on the CR they develop. In addition, the model can account for other behavioural and pharmacological results obtained using the same, or similar, autoshaping procedures. Finally, the model makes it possible to draw a set of experimental predictions that may be verified in a modified experimental protocol. We suggest that further investigation of factored representations in computational neuroscience studies may be useful. '),
(86431, 2014, 'plos', 'The structural pathway of interleukin 1 (IL-1) initiated signaling reveals mechanisms of oncogenic mutations and SNPs in inflammation and cancer', 'Acuner Ozbabacan, Saliha Ece|Gursoy, Attila|Nussinov, Ruth|Keskin, Ozlem', 'Center for Computational Biology and Bioinformatics and College of Engineering, Koc University, Sariyer Istanbul, Turkey.|Center for Computational Biology and Bioinformatics and College of Engineering, Koc University, Sariyer Istanbul, Turkey.|Cancer and Inflammation Program, Leidos Biomedical Research, Inc., National Cancer Institute, Frederick National Laboratory, Frederick, Maryland, United States of America , Sackler Inst. of Molecular Medicine, Department of Human Genetics and Molecular Medicine, Sackler School of Medicine, Tel Aviv University, Tel Aviv, Israel.|Center for Computational Biology and Bioinformatics and College of Engineering, Koc University, Sariyer Istanbul, Turkey.', 'Turkey|Turkey|Israel|Turkey', 39, 'Computational Biology|Computer Simulation|Humans|Inflammation|Interleukin-1|Interleukin-1 Receptor Accessory Protein|MAP Kinase Kinase 4|MAP Kinase Kinase 7|Mitogen-Activated Protein Kinase 10|Mitogen-Activated Protein Kinase 9|Models, Biological|Models, Molecular|Mutagenesis|Mutation|Neoplasms|Oncogenes|Polymorphism, Single Nucleotide|Protein Interaction Maps|Receptors, Interleukin-1 Type I|Signal Transduction', 'Journal Article', '10.1371/journal.pcbi.1003470', '24550720', 'Interleukin-1 (IL-1) is a large cytokine family closely related to innate immunity and inflammation. IL-1 proteins are key players in signaling pathways such as apoptosis, TLR, MAPK, NLR and NF-xcexbaB. The IL-1 pathway is also associated with cancer, and chronic inflammation increases the risk of tumor development via oncogenic mutations. Here we illustrate that the structures of interfaces between proteins in this pathway bearing the mutations may reveal how. Proteins are frequently regulated via their interactions, which can turn them ON or OFF. We show that oncogenic mutations are significantly at or adjoining interface regions, and can abolish (or enhance) the protein-protein interaction, making the protein constitutively active (or inactive, if it is a repressor). We combine known structures of protein-protein complexes and those that we have predicted for the IL-1 pathway, and integrate them with literature information. In the reconstructed pathway there are 104 interactions between proteins whose three dimensional structures are experimentally identified, only 15 have experimentally-determined structures of the interacting complexes. By predicting the protein-protein complexes throughout the pathway via the PRISM algorithm, the structural coverage increases from 15% to 71%. In silico mutagenesis and comparison of the predicted binding energies reveal the mechanisms of how oncogenic and single nucleotide polymorphism (SNP) mutations can abrogate the interactions or increase the binding affinity of the mutant to the native partner. Computational mapping of mutations on the interface of the predicted complexes may constitute a powerful strategy to explain the mechanisms of activation/inhibition. It can also help explain how an oncogenic mutation or SNP works. '),
(86432, 2014, 'plos', 'A network characteristic that correlates environmental and genetic robustness', 'Shreif, Zeina|Periwal, Vipul', 'Laboratory of Biological Modeling, National Institutes of Diabetes and Digestive and Kidney Diseases, National Institutes of Health, Bethesda, Maryland, United States of America.|Laboratory of Biological Modeling, National Institutes of Diabetes and Digestive and Kidney Diseases, National Institutes of Health, Bethesda, Maryland, United States of America.', 'United States|United States', 3, 'Bacterial Proteins|Chemotactic Factors|Chemotaxis|Computational Biology|Escherichia coli|Escherichia coli Proteins|Gene-Environment Interaction|Mathematical Concepts|Models, Biological|Signal Transduction', 'Journal Article', '10.1371/journal.pcbi.1003474', '24550721', 'As scientific advances in perturbing biological systems and technological advances in data acquisition allow the large-scale quantitative analysis of biological function, the robustness of organisms to both transient environmental stresses and inter-generational genetic changes is a fundamental impediment to the identifiability of mathematical models of these functions. An approach to overcoming this impediment is to reduce the space of possible models to take into account both types of robustness. However, the relationship between the two is still controversial. This work uncovers a network characteristic, transient responsiveness, for a specific function that correlates environmental imperturbability and genetic robustness. We test this characteristic extensively for dynamic networks of ordinary differential equations ranging up to 30 interacting nodes and find that there is a power-law relating environmental imperturbability and genetic robustness that tends to linearity as the number of nodes increases. Using our methods, we refine the classification of known 3-node motifs in terms of their environmental and genetic robustness. We demonstrate our approach by applying it to the chemotaxis signaling network. In particular, we investigate plausible models for the role of CheV protein in biochemical adaptation via a phosphorylation pathway, testing modifications that could improve the robustness of the system to environmental and/or genetic perturbation. '),
(86433, 2014, 'plos', 'Optimal serotype compositions for Pneumococcal conjugate vaccination under serotype replacement', 'Nurhonen, Markku|Auranen, Kari', 'Department of Vaccination and Immune Protection, National Institute for Health and Welfare, Helsinki, Finland.|Department of Vaccination and Immune Protection, National Institute for Health and Welfare, Helsinki, Finland.', 'Finland|Finland', 17, 'Algorithms|Carrier State|Child|Child, Preschool|Computational Biology|Finland|Humans|Incidence|Models, Immunological|Pneumococcal Infections|Pneumococcal Vaccines|Serotyping|Streptococcus pneumoniae|Treatment Outcome|Vaccines, Conjugate', 'Journal Article', '10.1371/journal.pcbi.1003477', '24550722', 'Pneumococcal conjugate vaccination has proved highly effective in eliminating vaccine-type pneumococcal carriage and disease. However, the potential adverse effects of serotype replacement remain a major concern when implementing routine childhood pneumococcal conjugate vaccination programmes. Applying a concise predictive model, we present a ready-to-use quantitative tool to investigate the implications of serotype replacement on the net effectiveness of vaccination against invasive pneumococcal disease (IPD) and to guide in the selection of optimal vaccine serotype compositions. We utilise pre-vaccination data on pneumococcal carriage and IPD and assume partial or complete elimination of vaccine-type carriage, its replacement by non-vaccine-type carriage, and stable case-to-carrier ratios (probability of IPD per carriage episode). The model predicts that the post-vaccination IPD incidences in Finland for currently available vaccine serotype compositions can eventually decrease among the target age group of children <5 years of age by 75%. However, due to replacement through herd effects, the decrease among the older population is predicted to be much less (20-40%). We introduce a sequential algorithm for the search of optimal serotype compositions and assess the robustness of inferences to uncertainties in data and assumptions about carriage and IPD. The optimal serotype composition depends on the age group of interest and some serotypes may be highly beneficial vaccine types in one age category (e.g. 6B in children), while being disadvantageous in another. The net effectiveness will be improved only if the added serotype has a higher case-to-carrier ratio than the average case-to-carrier ratio of the current non-vaccine types and the degree of improvement in effectiveness depends on the carriage incidence of the serotype. The serotype compositions of currently available pneumococcal vaccines are not optimal and the effectiveness of vaccination in the population at large could be improved by including new serotypes in the vaccine (e.g. 22 and 9N). ');
INSERT INTO `papers` (`id`, `ano`, `journal`, `titulo`, `autores`, `afiliacao`, `pais`, `citacoes`, `palavra_chave`, `categorias`, `doi`, `pubmed`, `abstract`) VALUES
(86434, 2014, 'plos', 'Computational design of the affinity and specificity of a therapeutic T cell receptor', 'Pierce, Brian G|Hellman, Lance M|Hossain, Moushumi|Singh, Nishant K|Vander Kooi, Craig W|Weng, Zhiping|Baker, Brian M', 'Program in Bioinformatics and Integrative Biology, University of Massachusetts Medical School, Worcester, Massachusetts, United States of America.|Department of Chemistry and Biochemistry, University of Notre Dame, Notre Dame, Indiana, United States of America.|Department of Chemistry and Biochemistry, University of Notre Dame, Notre Dame, Indiana, United States of America.|Department of Chemistry and Biochemistry, University of Notre Dame, Notre Dame, Indiana, United States of America.|Department of Molecular and Cellular Biochemistry, University of Kentucky, Lexington, Kentucky, United States of America.|Program in Bioinformatics and Integrative Biology, University of Massachusetts Medical School, Worcester, Massachusetts, United States of America.|Department of Chemistry and Biochemistry, University of Notre Dame, Notre Dame, Indiana, United States of America , Harper Cancer Research Institute, University of Notre Dame, Notre Dame, Indiana, United States of America.', 'United States|India|India|India|United States|United States|India', 39, 'Antigen Presentation|Cancer Vaccines|Computational Biology|Computer Simulation|Crystallography, X-Ray|Epitopes, T-Lymphocyte|HLA-A2 Antigen|Humans|Ligands|MART-1 Antigen|Models, Molecular|Peptides|Point Mutation|Protein Engineering|Receptors, Antigen, T-Cell|Thermodynamics', 'Journal Article', '10.1371/journal.pcbi.1003478', '24550723', 'T cell receptors (TCRs) are key to antigen-specific immunity and are increasingly being explored as therapeutics, most visibly in cancer immunotherapy. As TCRs typically possess only low-to-moderate affinity for their peptide/MHC (pMHC) ligands, there is a recognized need to develop affinity-enhanced TCR variants. Previous in vitro engineering efforts have yielded remarkable improvements in TCR affinity, yet concerns exist about the maintenance of peptide specificity and the biological impacts of ultra-high affinity. As opposed to in vitro engineering, computational design can directly address these issues, in theory permitting the rational control of peptide specificity together with relatively controlled increments in affinity. Here we explored the efficacy of computational design with the clinically relevant TCR DMF5, which recognizes nonameric and decameric epitopes from the melanoma-associated Melan-A/MART-1 protein presented by the class I MHC HLA-A2. We tested multiple mutations selected by flexible and rigid modeling protocols, assessed impacts on affinity and specificity, and utilized the data to examine and improve algorithmic performance. We identified multiple mutations that improved binding affinity, and characterized the structure, affinity, and binding kinetics of a previously reported double mutant that exhibits an impressive 400-fold affinity improvement for the decameric pMHC ligand without detectable binding to non-cognate ligands. The structure of this high affinity mutant indicated very little conformational consequences and emphasized the high fidelity of our modeling procedure. Overall, our work showcases the capability of computational design to generate TCRs with improved pMHC affinities while explicitly accounting for peptide specificity, as well as its potential for generating TCRs with customized antigen targeting capabilities. '),
(86435, 2014, 'plos', 'Combining experiments and simulations using the maximum entropy principle', 'Boomsma, Wouter|Ferkinghoff-Borg, Jesper|Lindorff-Larsen, Kresten', 'Structural Biology and NMR Laboratory, Department of Biology, University of Copenhagen, Copenhagen, Denmark.|Cellular Signal Integration Group, Center for Biological Sequence Analysis, Technical University of Denmark, Lyngby, Denmark.|Structural Biology and NMR Laboratory, Department of Biology, University of Copenhagen, Copenhagen, Denmark.', 'Denmark|Denmark|Denmark', 98, 'Computational Biology|Computer Simulation|Entropy|Macromolecular Substances|Models, Biological|Models, Molecular|Molecular Dynamics Simulation|Uncertainty', 'Journal Article', '10.1371/journal.pcbi.1003406', '24586124', 'A key component of computational biology is to compare the results of computer modelling with experimental measurements. Despite substantial progress in the models and algorithms used in many areas of computational biology, such comparisons sometimes reveal that the computations are not in quantitative agreement with experimental data. The principle of maximum entropy is a general procedure for constructing probability distributions in the light of new data, making it a natural tool in cases when an initial model provides results that are at odds with experiments. The number of maximum entropy applications in our field has grown steadily in recent years, in areas as diverse as sequence analysis, structural modelling, and neurobiology. In this Perspectives article, we give a broad introduction to the method, in an attempt to encourage its further adoption. The general procedure is explained in the context of a simple example, after which we proceed with a real-world application in the field of molecular simulations, where the maximum entropy procedure has recently provided new insight. Given the limited accuracy of force fields, macromolecular simulations sometimes produce results that are at not in complete and quantitative accordance with experiments. A common solution to this problem is to explicitly ensure agreement between the two by perturbing the potential energy function towards the experimental data. So far, a general consensus for how such perturbations should be implemented has been lacking. Three very recent papers have explored this problem using the maximum entropy approach, providing both new theoretical and practical insights to the problem. We highlight each of these contributions in turn and conclude with a discussion on remaining challenges. '),
(86436, 2014, 'plos', 'Learning gene networks under SNP perturbations using eQTL datasets', 'Zhang, Lingxue|Kim, Seyoung', 'Lane Center for Computational Biology, School of Computer Science, Carnegie Mellon University, Pittsburgh, Pennsylvania, United States of America.|Lane Center for Computational Biology, School of Computer Science, Carnegie Mellon University, Pittsburgh, Pennsylvania, United States of America.', 'United States|United States', 32, 'Algorithms|Artificial Intelligence|Computational Biology|Computer Simulation|DNA, Fungal|Databases, Nucleic Acid|Gene Expression Profiling|Gene Regulatory Networks|Humans|Linear Models|Models, Genetic|Models, Statistical|Polymorphism, Single Nucleotide|Quantitative Trait Loci|Saccharomyces cerevisiae', 'Journal Article', '10.1371/journal.pcbi.1003420', '24586125', 'The standard approach for identifying gene networks is based on experimental perturbations of gene regulatory systems such as gene knock-out experiments, followed by a genome-wide profiling of differential gene expressions. However, this approach is significantly limited in that it is not possible to perturb more than one or two genes simultaneously to discover complex gene interactions or to distinguish between direct and indirect downstream regulations of the differentially-expressed genes. As an alternative, genetical genomics study has been proposed to treat naturally-occurring genetic variants as potential perturbants of gene regulatory system and to recover gene networks via analysis of population gene-expression and genotype data. Despite many advantages of genetical genomics data analysis, the computational challenge that the effects of multifactorial genetic perturbations should be decoded simultaneously from data has prevented a widespread application of genetical genomics analysis. In this article, we propose a statistical framework for learning gene networks that overcomes the limitations of experimental perturbation methods and addresses the challenges of genetical genomics analysis. We introduce a new statistical model, called a sparse conditional Gaussian graphical model, and describe an efficient learning algorithm that simultaneously decodes the perturbations of gene regulatory system by a large number of SNPs to identify a gene network along with expression quantitative trait loci (eQTLs) that perturb this network. While our statistical model captures direct genetic perturbations of gene network, by performing inference on the probabilistic graphical model, we obtain detailed characterizations of how the direct SNP perturbation effects propagate through the gene network to perturb other genes indirectly. We demonstrate our statistical method using HapMap-simulated and yeast eQTL datasets. In particular, the yeast gene network identified computationally by our method under SNP perturbations is well supported by the results from experimental perturbation studies related to DNA replication stress response. '),
(86437, 2014, 'plos', 'tRNA signatures reveal a polyphyletic origin of SAR11 strains among alphaproteobacteria', 'Amrine, Katherine C H|Swingley, Wesley D|Ardell, David H', 'Program in Quantitative and Systems Biology, University of California, Merced, Merced, California, United States of America.|Program in Quantitative and Systems Biology, University of California, Merced, Merced, California, United States of America.|Program in Quantitative and Systems Biology, University of California, Merced, Merced, California, United States of America.', 'United States|United States|United States', 5, 'Alphaproteobacteria|Bacterial Proteins|Computational Biology|Evolution, Molecular|Gene Regulatory Networks|Gene Transfer, Horizontal|Genome, Bacterial|Models, Genetic|Phylogeny|RNA, Bacterial|RNA, Transfer|Rhodospirillales', 'Journal Article', '10.1371/journal.pcbi.1003454', '24586126', 'Molecular phylogenetics and phylogenomics are subject to noise from horizontal gene transfer (HGT) and bias from convergence in macromolecular compositions. Extensive variation in size, structure and base composition of alphaproteobacterial genomes has complicated their phylogenomics, sparking controversy over the origins and closest relatives of the SAR11 strains. SAR11 are highly abundant, cosmopolitan aquatic Alphaproteobacteria with streamlined, A+T-biased genomes. A dominant view holds that SAR11 are monophyletic and related to both Rickettsiales and the ancestor of mitochondria. Other studies dispute this, finding evidence of a polyphyletic origin of SAR11 with most strains distantly related to Rickettsiales. Although careful evolutionary modeling can reduce bias and noise in phylogenomic inference, entirely different approaches may be useful to extract robust phylogenetic signals from genomes. Here we develop simple phyloclassifiers from bioinformatically derived tRNA Class-Informative Features (CIFs), features predicted to target tRNAs for specific interactions within the tRNA interaction network. Our tRNA CIF-based model robustly and accurately classifies alphaproteobacterial genomes into one of seven undisputed monophyletic orders or families, despite great variability in tRNA gene complement sizes and base compositions. Our model robustly rejects monophyly of SAR11, classifying all but one strain as Rhizobiales with strong statistical support. Yet remarkably, conventional phylogenetic analysis of tRNAs classifies all SAR11 strains identically as Rickettsiales. We attribute this discrepancy to convergence of SAR11 and Rickettsiales tRNA base compositions. Thus, tRNA CIFs appear more robust to compositional convergence than tRNA sequences generally. Our results suggest that tRNA-CIF-based phyloclassification is robust to HGT of components of the tRNA interaction network, such as aminoacyl-tRNA synthetases. We explain why tRNAs are especially advantageous for prediction of traits governing macromolecular interactions from genomic data, and why such traits may be advantageous in the search for robust signals to address difficult problems in classification and phylogeny. '),
(86438, 2014, 'plos', 'In silico single-molecule manipulation of DNA with rigid body dynamics', 'Carrivain, Pascal|Barbi, Maria|Victor, Jean-Marc', 'Laboratoire de Physique Théorique de la Matière Condensée, CNRS UMR 7600, Université Pierre et Marie Curie, Paris, France , Institut de Génétique Humaine (IGH), CNRS UPR 1142, Montpellier, France.|Laboratoire de Physique Théorique de la Matière Condensée, CNRS UMR 7600, Université Pierre et Marie Curie, Paris, France.|Laboratoire de Physique Théorique de la Matière Condensée, CNRS UMR 7600, Université Pierre et Marie Curie, Paris, France.', 'France|France|France', 8, 'Computational Biology|Computer Simulation|DNA|Models, Molecular|Molecular Dynamics Simulation|Nucleic Acid Conformation|Static Electricity', 'Journal Article', '10.1371/journal.pcbi.1003456', '24586127', 'We develop a new powerful method to reproduce in silico single-molecule manipulation experiments. We demonstrate that flexible polymers such as DNA can be simulated using rigid body dynamics thanks to an original implementation of Langevin dynamics in an open source library called Open Dynamics Engine. We moreover implement a global thermostat which accelerates the simulation sampling by two orders of magnitude. We reproduce force-extension as well as rotation-extension curves of reference experimental studies. Finally, we extend the model to simulations where the control parameter is no longer the torsional strain but instead the torque, and predict the expected behavior for this case which is particularly challenging theoretically and experimentally. '),
(86439, 2014, 'plos', 'The sign rule and beyond: boundary effects, flexibility, and noise correlations in neural population codes', 'Hu, Yu|Zylberberg, Joel|Shea-Brown, Eric', 'Department of Applied Mathematics, University of Washington, Seattle, Washington, United States of America.|Department of Applied Mathematics, University of Washington, Seattle, Washington, United States of America.|Department of Applied Mathematics, University of Washington, Seattle, Washington, United States of America , Program in Neurobiology and Behavior, University of Washington, Seattle, Washington, United States of America , Department of Physiology and Biophysics, University of Washington, Seattle, Washington, United States of America.', 'United States|United States|United States', 35, 'Animals|Brain|Computational Biology|Linear Models|Mathematical Concepts|Models, Neurological|Nerve Net|Normal Distribution|Sensory Receptor Cells|Signal-To-Noise Ratio', 'Journal Article', '10.1371/journal.pcbi.1003469', '24586128', 'Over repeat presentations of the same stimulus, sensory neurons show variable responses. This noise is typically correlated between pairs of cells, and a question with rich history in neuroscience is how these noise correlations impact the populations ability to encode the stimulus. Here, we consider a very general setting for population coding, investigating how information varies as a function of noise correlations, with all other aspects of the problem - neural tuning curves, etc. - held fixed. This work yields unifying insights into the role of noise correlations. These are summarized in the form of theorems, and illustrated with numerical examples involving neurons with diverse tuning curves. Our main contributions are as follows. (1) We generalize previous results to prove a sign rule (SR) - if noise correlations between pairs of neurons have opposite signs vs. their signal correlations, then coding performance will improve compared to the independent case. This holds for three different metrics of coding performance, and for arbitrary tuning curves and levels of heterogeneity. This generality is true for our other results as well. (2) As also pointed out in the literature, the SR does not provide a necessary condition for good coding. We show that a diverse set of correlation structures can improve coding. Many of these violate the SR, as do experimentally observed correlations. There is structure to this diversity: we prove that the optimal correlation structures must lie on boundaries of the possible set of noise correlations. (3) We provide a novel set of necessary and sufficient conditions, under which the coding performance (in the presence of noise) will be as good as it would be if there were no noise present at all. '),
(86440, 2014, 'plos', 'Escherichia coli peptidoglycan structure and mechanics as predicted by atomic-scale simulations', 'Gumbart, James C|Beeby, Morgan|Jensen, Grant J|Roux, Benoît', 'School of Physics, Georgia Institute of Technology, Atlanta, Georgia, United States of America.|Imperial College London, South Kensington Campus, London, United Kingdom.|California Institute of Technology and Howard Hughes Medical Institute, Pasadena, California, United States of America.|Department of Biochemistry and Molecular Biology and Gordon Center for Integrative Science, The University of Chicago, Chicago, Illinois, United States of America.', 'Georgia|United Kingdom|United States|United States', 42, 'Biophysical Phenomena|Cell Wall|Computational Biology|Computer Simulation|Escherichia coli|Models, Molecular|Molecular Conformation|Molecular Dynamics Simulation|Molecular Structure|Peptidoglycan', 'Journal Article', '10.1371/journal.pcbi.1003475', '24586129', 'Bacteria face the challenging requirement to maintain their shape and avoid rupture due to the high internal turgor pressure, but simultaneously permit the import and export of nutrients, chemical signals, and virulence factors. The bacterial cell wall, a mesh-like structure composed of cross-linked strands of peptidoglycan, fulfills both needs by being semi-rigid, yet sufficiently porous to allow diffusion through it. How the mechanical properties of the cell wall are determined by the molecular features and the spatial arrangement of the relatively thin strands in the larger cellular-scale structure is not known. To examine this issue, we have developed and simulated atomic-scale models of Escherichia coli cell walls in a disordered circumferential arrangement. The cell-wall models are found to possess an anisotropic elasticity, as known experimentally, arising from the orthogonal orientation of the glycan strands and of the peptide cross-links. Other features such as thickness, pore size, and disorder are also found to generally agree with experiments, further supporting the disordered circumferential model of peptidoglycan. The validated constructs illustrate how mesoscopic structure and behavior emerge naturally from the underlying atomic-scale properties and, furthermore, demonstrate the ability of all-atom simulations to reproduce a range of macroscopic observables for extended polymer meshes. '),
(86441, 2014, 'plos', 'A unified model of heading and path perception in primate MSTd', 'Layton, Oliver W|Browning, N Andrew', 'Center for Computational Neuroscience and Neural Technology, Boston University, Boston, Massachusetts, United States of America.|Center for Computational Neuroscience and Neural Technology, Boston University, Boston, Massachusetts, United States of America , Scientific Systems Company Inc. (SSCI), Woburn, Massachusetts, United Sates of America.', 'United States|United States', 10, 'Animals|Computational Biology|Haplorhini|Humans|Models, Neurological|Motion Perception|Photic Stimulation|Primates|Temporal Lobe|Visual Cortex|Visual Perception', 'Journal Article', '10.1371/journal.pcbi.1003476', '24586130', 'Self-motion, steering, and obstacle avoidance during navigation in the real world require humans to travel along curved paths. Many perceptual models have been proposed that focus on heading, which specifies the direction of travel along straight paths, but not on path curvature, which humans accurately perceive and is critical to everyday locomotion. In primates, including humans, dorsal medial superior temporal area (MSTd) has been implicated in heading perception. However, the majority of MSTd neurons respond optimally to spiral patterns, rather than to the radial expansion patterns associated with heading. No existing theory of curved path perception explains the neural mechanisms by which humans accurately assess path and no functional role for spiral-tuned cells has yet been proposed. Here we present a computational model that demonstrates how the continuum of observed cells (radial to circular) in MSTd can simultaneously code curvature and heading across the neural population. Curvature is encoded through the spirality of the most active cell, and heading is encoded through the visuotopic location of the center of the most active cells receptive field. Model curvature and heading errors fit those made by humans. Our model challenges the view that the function of MSTd is heading estimation, based on our analysis we claim that it is primarily concerned with trajectory estimation and the simultaneous representation of both curvature and heading. In our model, temporal dynamics afford time-history in the neural representation of optic flow, which may modulate its structure. This has far-reaching implications for the interpretation of studies that assume that optic flow is, and should be, represented as an instantaneous vector field. Our results suggest that spiral motion patterns that emerge in spatio-temporal optic flow are essential for guiding self-motion along complex trajectories, and that cells in MSTd are specifically tuned to extract complex trajectory estimation from flow. '),
(86442, 2014, 'plos', 'A virtual infection model quantifies innate effector mechanisms and Candida albicans immune escape in human blood', 'Hünniger, Kerstin|Lehnert, Teresa|Bieber, Kristin|Martin, Ronny|Figge, Marc Thilo|Kurzai, Oliver', 'Septomics Research Center, Friedrich Schiller University and Leibniz Institute for Natural Product Research and Infection Biology - Hans-Knöll-Institute (HKI), Jena, Germany.|Applied Systems Biology, Leibniz Institute for Natural Product Research and Infection Biology - Hans-Knöll-Institute (HKI), Jena, Germany , Friedrich Schiller University Jena, Jena, Germany.|Septomics Research Center, Friedrich Schiller University and Leibniz Institute for Natural Product Research and Infection Biology - Hans-Knöll-Institute (HKI), Jena, Germany.|Septomics Research Center, Friedrich Schiller University and Leibniz Institute for Natural Product Research and Infection Biology - Hans-Knöll-Institute (HKI), Jena, Germany.|Applied Systems Biology, Leibniz Institute for Natural Product Research and Infection Biology - Hans-Knöll-Institute (HKI), Jena, Germany , Friedrich Schiller University Jena, Jena, Germany.|Septomics Research Center, Friedrich Schiller University and Leibniz Institute for Natural Product Research and Infection Biology - Hans-Knöll-Institute (HKI), Jena, Germany.', 'Germany|Germany|Germany|Germany|Germany|Germany', 0, 'Candida albicans|Candidemia|Computational Biology|Computer Simulation|Cross Infection|Host-Pathogen Interactions|Humans|Immunity, Innate|Mathematical Concepts|Models, Immunological|Monocytes|Monte Carlo Method|Neutrophils|Phagocytosis|User-Computer Interface', 'Journal Article', '10.1371/journal.pcbi.1003479', '24586131', 'Candida albicans bloodstream infection is increasingly frequent and can result in disseminated candidiasis associated with high mortality rates. To analyze the innate immune response against C. albicans, fungal cells were added to human whole-blood samples. After inoculation, C. albicans started to filament and predominantly associate with neutrophils, whereas only a minority of fungal cells became attached to monocytes. While many parameters of host-pathogen interaction were accessible to direct experimental quantification in the whole-blood infection assay, others were not. To overcome these limitations, we generated a virtual infection model that allowed detailed and quantitative predictions on the dynamics of host-pathogen interaction. Experimental time-resolved data were simulated using a state-based modeling approach combined with the Monte Carlo method of simulated annealing to obtain quantitative predictions on a priori unknown transition rates and to identify the main axis of antifungal immunity. Results clearly demonstrated a predominant role of neutrophils, mediated by phagocytosis and intracellular killing as well as the release of antifungal effector molecules upon activation, resulting in extracellular fungicidal activity. Both mechanisms together account for almost [Formula: see text] of C. albicans killing, clearly proving that beside being present in larger numbers than other leukocytes, neutrophils functionally dominate the immune response against C. albicans in human blood. A fraction of C. albicans cells escaped phagocytosis and remained extracellular and viable for up to four hours. This immune escape was independent of filamentation and fungal activity and not linked to exhaustion or inactivation of innate immune cells. The occurrence of C. albicans cells being resistant against phagocytosis may account for the high proportion of dissemination in C. albicans bloodstream infection. Taken together, iterative experiment-model-experiment cycles allowed quantitative analyses of the interplay between host and pathogen in a complex environment like human blood. '),
(86443, 2014, 'plos', 'GAGA: a new algorithm for genomic inference of geographic ancestry reveals fine level population substructure in Europeans', 'Lao, Oscar|Liu, Fan|Wollstein, Andreas|Kayser, Manfred', 'Department of Forensic Molecular Biology, Erasmus MC University Medical Center Rotterdam, Rotterdam, The Netherlands.|Department of Forensic Molecular Biology, Erasmus MC University Medical Center Rotterdam, Rotterdam, The Netherlands.|Department of Forensic Molecular Biology, Erasmus MC University Medical Center Rotterdam, Rotterdam, The Netherlands , Department of Medical Statistics and Bioinformatics, Leiden University Medical Center, Leiden, The Netherlands.|Department of Forensic Molecular Biology, Erasmus MC University Medical Center Rotterdam, Rotterdam, The Netherlands.', 'Netherlands|Netherlands|Netherlands|Netherlands', 0, 'Algorithms|Analysis of Variance|Computational Biology|Computer Simulation|Databases, Genetic|Europe|European Continental Ancestry Group|Genetic Variation|Genetics, Population|Genome, Human|Humans|Models, Genetic|Multigene Family|Polymorphism, Single Nucleotide', 'Journal Article', '10.1371/journal.pcbi.1003480', '24586132', 'Attempts to detect genetic population substructure in humans are troubled by the fact that the vast majority of the total amount of observed genetic variation is present within populations rather than between populations. Here we introduce a new algorithm for transforming a genetic distance matrix that reduces the within-population variation considerably. Extensive computer simulations revealed that the transformed matrix captured the genetic population differentiation better than the original one which was based on the T1 statistic. In an empirical genomic data set comprising 2,457 individuals from 23 different European subpopulations, the proportion of individuals that were determined as a genetic neighbour to another individual from the same sampling location increased from 25% with the original matrix to 52% with the transformed matrix. Similarly, the percentage of genetic variation explained between populations by means of Analysis of Molecular Variance (AMOVA) increased from 1.62% to 7.98%. Furthermore, the first two dimensions of a classical multidimensional scaling (MDS) using the transformed matrix explained 15% of the variance, compared to 0.7% obtained with the original matrix. Application of MDS with Mclust, SPA with Mclust, and GemTools algorithms to the same dataset also showed that the transformed matrix gave a better association of the genetic clusters with the sampling locations, and particularly so when it was used in the AMOVA framework with a genetic algorithm. Overall, the new matrix transformation introduced here substantially reduces the within population genetic differentiation, and can be broadly applied to methods such as AMOVA to enhance their sensitivity to reveal population substructure. We herewith provide a publically available (http://www.erasmusmc.nl/fmb/resources/GAGA) model-free method for improved genetic population substructure detection that can be applied to human as well as any other species data in future studies relevant to evolutionary biology, behavioural ecology, medicine, and forensics. '),
(86444, 2014, 'plos', 'Differential adhesion between moving particles as a mechanism for the evolution of social groups', 'Garcia, Thomas|Brunnet, Leonardo Gregory|De Monte, Silvia', 'CNRS UMR 7625 Écologie et Évolution, École Normale Supérieure, Paris, France , CNRS UMR 7625 Écologie et Évolution, Université Pierre et Marie Curie-Paris 6, Paris, France.|Instituto de Física, Universidade Federal do Rio Grande do Sul, Porto Alegre, Brazil.|CNRS UMR 8197 INSERM U1024, Institut de Biologie de lÉcole Normale Supérieure (IBENS), Paris, France.', 'France|Brazil|France', 0, 'Algorithms|Bacterial Adhesion|Biological Evolution|Cell Adhesion|Computational Biology|Dictyosteliida|Game Theory|Humans|Models, Biological|Motion|Myxococcales|Selection, Genetic|Social Behavior', 'Journal Article', '10.1371/journal.pcbi.1003482', '24586133', 'The evolutionary stability of cooperative traits, that are beneficial to other individuals but costly to their carrier, is considered possible only through the establishment of a sufficient degree of assortment between cooperators. Chimeric microbial populations, characterized by simple interactions between unrelated individuals, restrain the applicability of standard mechanisms generating such assortment, in particular when cells disperse between successive reproductive events such as happens in Dicyostelids and Myxobacteria. In this paper, we address the evolutionary dynamics of a costly trait that enhances attachment to others as well as group cohesion. By modeling cells as self-propelled particles moving on a plane according to local interaction forces and undergoing cycles of aggregation, reproduction and dispersal, we show that blind differential adhesion provides a basis for assortment in the process of group formation. When reproductive performance depends on the social context of players, evolution by natural selection can lead to the success of the social trait, and to the concomitant emergence of sizeable groups. We point out the conditions on the microscopic properties of motion and interaction that make such evolutionary outcome possible, stressing that the advent of sociality by differential adhesion is restricted to specific ecological contexts. Moreover, we show that the aggregation process naturally implies the existence of non-aggregated particles, and highlight their crucial evolutionary role despite being largely neglected in theoretical models for the evolution of sociality. '),
(86445, 2014, 'plos', 'Pathway thermodynamics highlights kinetic obstacles in central metabolism', 'Noor, Elad|Bar-Even, Arren|Flamholz, Avi|Reznik, Ed|Liebermeister, Wolfram|Milo, Ron', 'Department of Plant Sciences, The Weizmann Institute of Science, Rehovot, Israel.|Department of Plant Sciences, The Weizmann Institute of Science, Rehovot, Israel.|Department of Plant Sciences, The Weizmann Institute of Science, Rehovot, Israel , Department of Molecular and Cellular Biology, University of California, Berkely, Berkely, California, United States of America.|Computational Biology Program, Memorial Sloan-Kettering Cancer Center, New York, New York, United States of America.|Institut fxc3xbcr Biochemie, Charitxc3xa9-Universitxc3xa4tsmedizin Berlin, Berlin, Germany.|Department of Plant Sciences, The Weizmann Institute of Science, Rehovot, Israel.', 'Israel|Israel|Israel|United States|Germany|Israel', 106, 'Citric Acid Cycle|Computational Biology|Enzymes|Escherichia coli|Fermentation|Kinetics|Malate Dehydrogenase|Metabolic Networks and Pathways|Models, Biological|Osmolar Concentration|Phosphorylation|Thermodynamics', 'Journal Article', '10.1371/journal.pcbi.1003483', '24586134', 'In metabolism research, thermodynamics is usually used to determine the directionality of a reaction or the feasibility of a pathway. However, the relationship between thermodynamic potentials and fluxes is not limited to questions of directionality: thermodynamics also affects the kinetics of reactions through the flux-force relationship, which states that the logarithm of the ratio between the forward and reverse fluxes is directly proportional to the change in Gibbs energy due to a reaction (xcex94rG). Accordingly, if an enzyme catalyzes a reaction with a xcex94rG of -5.7 kJ/mol then the forward flux will be roughly ten times the reverse flux. As xcex94rG approaches equilibrium (xcex94rGxe2x80x8a=xe2x80x8a0 kJ/mol), exponentially more enzyme counterproductively catalyzes the reverse reaction, reducing the net rate at which the reaction proceeds. Thus, the enzyme level required to achieve a given flux increases dramatically near equilibrium. Here, we develop a framework for quantifying the degree to which pathways suffer these thermodynamic limitations on flux. For each pathway, we calculate a single thermodynamically-derived metric (the Max-min Driving Force, MDF), which enables objective ranking of pathways by the degree to which their flux is constrained by low thermodynamic driving force. Our framework accounts for the effect of pH, ionic strength and metabolite concentration ranges and allows us to quantify how alterations to the pathway structure affect the pathways thermodynamics. Applying this methodology to pathways of central metabolism sheds light on some of their features, including metabolic bypasses (e.g., fermentation pathways bypassing substrate-level phosphorylation), substrate channeling (e.g., of oxaloacetate from malate dehydrogenase to citrate synthase), and use of alternative cofactors (e.g., quinone as an electron acceptor instead of NAD). The methods presented here place another arrow in metabolic engineers quiver, providing a simple means of evaluating the thermodynamic and kinetic quality of different pathway chemistries that produce the same molecules. '),
(86446, 2014, 'plos', 'Ten simple rules for running interactive workshops', 'Pavelin, Katrina|Pundir, Sangya|Cham, Jennifer A', 'European Bioinformatics Institute (EMBL-EBI), European Molecular Biology Laboratory, Wellcome Trust Genome Campus, Hinxton, Cambridge, United Kingdom.|European Bioinformatics Institute (EMBL-EBI), European Molecular Biology Laboratory, Wellcome Trust Genome Campus, Hinxton, Cambridge, United Kingdom.|European Bioinformatics Institute (EMBL-EBI), European Molecular Biology Laboratory, Wellcome Trust Genome Campus, Hinxton, Cambridge, United Kingdom.', 'United Kingdom|United Kingdom|United Kingdom', 0, 'Computational Biology|Congresses as Topic|Education', 'Editorial', '10.1371/journal.pcbi.1003485', '24586135', '-'),
(86447, 2014, 'plos', 'k-OptForce: integrating kinetics with flux balance analysis for strain design', 'Chowdhury, Anupam|Zomorrodi, Ali R|Maranas, Costas D', 'Department of Chemical Engineering, Pennsylvania State University, University Park, Pennsylvania, United States of America.|Department of Chemical Engineering, Pennsylvania State University, University Park, Pennsylvania, United States of America.|Department of Chemical Engineering, Pennsylvania State University, University Park, Pennsylvania, United States of America.', 'United States|United States|United States', 0, 'Algorithms|Computational Biology|Escherichia coli|Kinetics|Metabolic Networks and Pathways|Models, Biological|Pyrones|Saccharomyces cerevisiae|Serine', 'Journal Article', '10.1371/journal.pcbi.1003487', '24586136', 'Computational strain design protocols aim at the system-wide identification of intervention strategies for the enhanced production of biochemicals in microorganisms. Existing approaches relying solely on stoichiometry and rudimentary constraint-based regulation overlook the effects of metabolite concentrations and substrate-level enzyme regulation while identifying metabolic interventions. In this paper, we introduce k-OptForce, which integrates the available kinetic descriptions of metabolic steps with stoichiometric models to sharpen the prediction of intervention strategies for improving the bio-production of a chemical of interest. It enables identification of a minimal set of interventions comprised of both enzymatic parameter changes (for reactions with available kinetics) and reaction flux changes (for reactions with only stoichiometric information). Application of k-OptForce to the overproduction of L-serine in E. coli and triacetic acid lactone (TAL) in S. cerevisiae revealed that the identified interventions tend to cause less dramatic rearrangements of the flux distribution so as not to violate concentration bounds. In some cases the incorporation of kinetic information leads to the need for additional interventions as kinetic expressions render stoichiometry-only derived interventions infeasible by violating concentration bounds, whereas in other cases the kinetic expressions impart flux changes that favor the overproduction of the target product thereby requiring fewer direct interventions. A sensitivity analysis on metabolite concentrations shows that the required number of interventions can be significantly affected by changing the imposed bounds on metabolite concentrations. Furthermore, k-OptForce was capable of finding non-intuitive interventions aiming at alleviating the substrate-level inhibition of key enzymes in order to enhance the flux towards the product of interest, which cannot be captured by stoichiometry-alone analysis. This study paves the way for the integrated analysis of kinetic and stoichiometric models and enables elucidating system-wide metabolic interventions while capturing regulatory and kinetic effects. '),
(86448, 2014, 'plos', 'Optimal recall from bounded metaplastic synapses: predicting functional adaptations in hippocampal area CA3', 'Savin, Cristina|Dayan, Peter|Lengyel, Máté', 'Computational & Biological Learning Lab, Department of Engineering, University of Cambridge, Cambridge, United Kingdom.|Gatsby Computational Neuroscience Unit, University College London, London, United Kingdom.|Computational & Biological Learning Lab, Department of Engineering, University of Cambridge, Cambridge, United Kingdom.', 'United Kingdom|United Kingdom|United Kingdom', 13, 'Adaptation, Physiological|Algorithms|Animals|CA3 Region, Hippocampal|Computational Biology|Feedback, Physiological|Humans|Mental Recall|Models, Neurological|Models, Psychological|Models, Statistical|Neuronal Plasticity|Synapses', 'Journal Article', '10.1371/journal.pcbi.1003489', '24586137', 'A venerable history of classical work on autoassociative memory has significantly shaped our understanding of several features of the hippocampus, and most prominently of its CA3 area, in relation to memory storage and retrieval. However, existing theories of hippocampal memory processing ignore a key biological constraint affecting memory storage in neural circuits: the bounded dynamical range of synapses. Recent treatments based on the notion of metaplasticity provide a powerful model for individual bounded synapses, however, their implications for the ability of the hippocampus to retrieve memories well and the dynamics of neurons associated with that retrieval are both unknown. Here, we develop a theoretical framework for memory storage and recall with bounded synapses. We formulate the recall of a previously stored pattern from a noisy recall cue and limited-capacity (and therefore lossy) synapses as a probabilistic inference problem, and derive neural dynamics that implement approximate inference algorithms to solve this problem efficiently. In particular, for binary synapses with metaplastic states, we demonstrate for the first time that memories can be efficiently read out with biologically plausible network dynamics that are completely constrained by the synaptic plasticity rule, and the statistics of the stored patterns and of the recall cue. Our theory organises into a coherent framework a wide range of existing data about the regulation of excitability, feedback inhibition, and network oscillations in area CA3, and makes novel and directly testable predictions that can guide future experiments. '),
(86449, 2014, 'plos', 'A combination of transcriptional and microRNA regulation improves the stability of the relative concentrations of target genes', 'Riba, Andrea|Bosia, Carla|El Baroudi, Mariama|Ollino, Laura|Caselle, Michele', 'Department of Physics and INFN, University of Torino, Torino, Italy.|Department of Physics and INFN, University of Torino, Torino, Italy.|National Research Council (CNR), Institute of Informatics and Telematics (IIT) and Institute of Clinical Physiology (IFC), Laboratory for Integrative System Medicine (LISM), Pisa, Italy.|Department of Physics and INFN, University of Torino, Torino, Italy.|Department of Physics and INFN, University of Torino, Torino, Italy.', 'Italy|Italy|Italy|Italy|Italy', 0, 'Algorithms|Computational Biology|E2F1 Transcription Factor|Gene Regulatory Networks|Genes, Retinoblastoma|Genomic Instability|Humans|MicroRNAs|Models, Genetic|RNA Processing, Post-Transcriptional|Stochastic Processes|Transcription Factors', 'Journal Article', '10.1371/journal.pcbi.1003490', '24586138', 'It is well known that, under suitable conditions, microRNAs are able to fine tune the relative concentration of their targets to any desired value. We show that this function is particularly effective when one of the targets is a Transcription Factor (TF) which regulates the other targets. This combination defines a new class of feed-forward loops (FFLs) in which the microRNA plays the role of master regulator. Using both deterministic and stochastic equations, we show that these FFLs are indeed able not only to fine-tune the TF/target ratio to any desired value as a function of the miRNA concentration but also, thanks to the peculiar topology of the circuit, to ensure the stability of this ratio against stochastic fluctuations. These two effects are due to the interplay between the direct transcriptional regulation and the indirect TF/Target interaction due to competition of TF and target for miRNA binding (the so called sponge effect). We then perform a genome wide search of these FFLs in the human regulatory network and show that they are characterized by a very peculiar enrichment pattern. In particular, they are strongly enriched in all the situations in which the TF and its target have to be precisely kept at the same concentration notwithstanding the environmental noise. As an example we discuss the FFL involving E2F1 as Transcription Factor, RB1 as target and miR-17 family as master regulator. These FFLs ensure a tight control of the E2F/RB ratio which in turns ensures the stability of the transition from the G0/G1 to the S phase in quiescent cells. '),
(86450, 2014, 'plos', 'A novel Bayesian method for detection of APOBEC3-mediated hypermutation and its application to zoonotic transmission of simian foamy viruses', 'Matsen, Frederick A|Small, Christopher T|Soliven, Khanh|Engel, Gregory A|Feeroz, Mostafa M|Wang, Xiaoxing|Craig, Karen L|Hasan, M Kamrul|Emerman, Michael|Linial, Maxine L|Jones-Engel, Lisa', 'Fred Hutchinson Cancer Research Center, Seattle, Washington, United States of America.|Fred Hutchinson Cancer Research Center, Seattle, Washington, United States of America.|Fred Hutchinson Cancer Research Center, Seattle, Washington, United States of America.|University of Washington, Seattle, Washington, United States of America , Swedish Medical Center, Seattle, Washington, United States of America.|Jahangirnagar University, Savar, Dhaka, Bangladesh.|Fred Hutchinson Cancer Research Center, Seattle, Washington, United States of America.|Fred Hutchinson Cancer Research Center, Seattle, Washington, United States of America.|Jahangirnagar University, Savar, Dhaka, Bangladesh.|Fred Hutchinson Cancer Research Center, Seattle, Washington, United States of America.|Fred Hutchinson Cancer Research Center, Seattle, Washington, United States of America.|University of Washington, Seattle, Washington, United States of America.', 'United States|United States|United States|United States|Bangladesh|United States|United States|Bangl', 0, 'APOBEC-3G Deaminase|Animals|Bangladesh|Bayes Theorem|Codon, Terminator|Computational Biology|Cytidine Deaminase|Cytosine Deaminase|Host-Pathogen Interactions|Humans|Macaca|Models, Genetic|Mutation|RNA, Viral|Retroviridae Infections|Simian foamy virus|Species Specificity|Virus Replication|Zoonoses', 'Journal Article', '10.1371/journal.pcbi.1003493', '24586139', 'Simian Foamy Virus (SFV) can be transmitted from non-human primates (NHP) to humans. However, there are no documented cases of human to human transmission, and significant differences exist between infection in NHP and human hosts. The mechanism for these between-host differences is not completely understood. In this paper we develop a new Bayesian approach to the detection of APOBEC3-mediated hypermutation, and use it to compare SFV sequences from human and NHP hosts living in close proximity in Bangladesh. We find that human APOBEC3G can induce genetic changes that may prevent SFV replication in infected humans in vivo. '),
(86451, 2014, 'plos', 'Workshops: a great way to enhance and supplement a degree', 'Fatumo, Segun|Shome, Sayane|Macintyre, Geoff', 'H3Africa Bioinformatics Network (H3ABioNet) Node, National Biotechnology Development Agency (NABDA), Federal Ministry of Science and Technology (FMST), Abuja, Nigeria , International Health Research Group, Dept of Public Health and Primary Care, University of Cambridge, Cambridge, United Kingdom , Genetic Epidemiology Group, Wellcome Trust Sanger Institute, Hinxton, Cambridge, United Kingdom.|School of Biosciences and Technology, Vellore Institute of Technology, Vellore, Tamil Nadu, India.|NICTA Victoria Research Laboratory, Department of Electrical and Electronic Engineering, The University of Melbourne, Victoria, Australia , Department of Computing and Information Systems, The University of Melbourne, Victoria, Australia.', 'United Kingdom|India|Australia', 1, 'Computational Biology|Education|Societies, Scientific', 'Journal Article', '10.1371/journal.pcbi.1003497', '24586140', 'As part of the International Society for Computational Biology Student Council (ISCB-SC), Regional Student Groups (RSGs) have helped organise workshops in the emerging fields of bioinformatics and computational biology. Workshops are a great way for students to gain hands-on experience and rapidly acquire knowledge in advanced research topics where curriculum-based education is yet to be developed. RSG workshops have improved dissemination of knowledge of the latest bioinformatics techniques and resources among student communities and young scientists, especially in developing nations. This article highlights some of the benefits and challenges encountered while running RSG workshops. Examples cover a variety of subjects, including introductory bioinformatics and advanced bioinformatics, as well as soft skills such as networking, career development, and socializing. The collective experience condensed in this article is a useful starting point for students wishing to organise their own tailor-made workshops. '),
(86452, 2014, 'plos', 'Slowness and sparseness have diverging effects on complex cell learning', 'Lies, Jörn-Philipp|Häfner, Ralf M|Bethge, Matthias', 'Werner Reichardt Centre for Integrative Neuroscience, University of Tübingen, Tübingen, Germany.|Swartz Center for Theoretical Neurobiology, Brandeis University, Waltham, Massachusetts, United States of America.|Werner Reichardt Centre for Integrative Neuroscience, University of Tübingen, Tübingen, Germany, Bernstein Center for Computational Neuroscience, Tübingen, Germany, Max Planck Institute for Biological Cybernetics, Tübingen, Germany.', 'Germany|United States|Germany', 0, 'Algorithms|Animals|Computational Biology|Fourier Analysis|Humans|Models, Neurological|Neurons|Normal Distribution|Vision, Ocular|Visual Cortex', 'Journal Article', '10.1371/journal.pcbi.1003468', '24603197', 'Following earlier studies which showed that a sparse coding principle may explain the receptive field properties of complex cells in primary visual cortex, it has been concluded that the same properties may be equally derived from a slowness principle. In contrast to this claim, we here show that slowness and sparsity drive the representations towards substantially different receptive field properties. To do so, we present complete sets of basis functions learned with slow subspace analysis (SSA) in case of natural movies as well as translations, rotations, and scalings of natural images. SSA directly parallels independent subspace analysis (ISA) with the only difference that SSA maximizes slowness instead of sparsity. We find a large discrepancy between the filter shapes learned with SSA and ISA. We argue that SSA can be understood as a generalization of the Fourier transform where the power spectrum corresponds to the maximally slow subspace energies in SSA. Finally, we investigate the trade-off between slowness and sparseness when combined in one objective function. ');
INSERT INTO `papers` (`id`, `ano`, `journal`, `titulo`, `autores`, `afiliacao`, `pais`, `citacoes`, `palavra_chave`, `categorias`, `doi`, `pubmed`, `abstract`) VALUES
(86453, 2014, 'plos', 'Behavioral lateralization and optimal route choice in flying budgerigars', 'Bhagavatula, Partha S|Claudianos, Charles|Ibbotson, Michael R|Srinivasan, Mandyam V', 'ARC Centre of Excellence in Vision Science, Australian National University, Acton, Canberra, Australian Capital Territory, Australia, Research School of Biology, Australian National University, Acton, Canberra, Australian Capital Territory, Australia, Queensland Brain Institute, The University of Queensland, St Lucia, Brisbane, Queensland, Australia.|Queensland Brain Institute, The University of Queensland, St Lucia, Brisbane, Queensland, Australia.|ARC Centre of Excellence in Vision Science, Australian National University, Acton, Canberra, Australian Capital Territory, Australia, National Vision Research Institute, Australian College of Optometry, Carlton, Melbourne, Victoria, Australia.|ARC Centre of Excellence in Vision Science, Australian National University, Acton, Canberra, Australian Capital Territory, Australia, Queensland Brain Institute, The University of Queensland, St Lucia, Brisbane, Queensland, Australia, School of Information Technology and Electrical Engineering, The University of Queensland, St Lucia, Brisbane, Queensland, Australia.', 'Australia|Australia|Australia|Australia', 10, 'Animals|Behavior, Animal|Calibration|Choice Behavior|Computational Biology|Female|Flight, Animal|Male|Melopsittacus|Models, Theoretical|Probability|Video Recording', 'Journal Article', '10.1371/journal.pcbi.1003473', '24603285', 'Birds flying through a cluttered environment require the ability to choose routes that will take them through the environment safely and quickly. We have investigated some of the strategies by which they achieve this. We trained budgerigars to fly through a tunnel in which they encountered a barrier that offered two passages, positioned side by side, at the halfway point. When one of the passages was substantially wider than the other, the birds tended to fly through the wider passage to continue their transit to the end of the tunnel, regardless of whether this passage was on the right or the left. Evidently, the birds were selecting the safest and quickest route. However, when the two passages were of equal or nearly equal width, some individuals consistently preferred the left-hand passage, while others consistently preferred the passage on the right. Thus, the birds displayed idiosyncratic biases when choosing between alternative routes. Surprisingly--and unlike most of the instances in which behavioral lateralization has previously been discovered--the bias was found to vary from individual to individual, in its direction as well as its magnitude. This is very different from handedness in humans, where the majority of humans are right-handed, giving rise to a so-called population bias. Our experimental results and mathematical model of this behavior suggest that individually varying lateralization, working in concert with a tendency to choose the wider aperture, can expedite the passage of a flock of birds through a cluttered environment.'),
(86454, 2014, 'plos', 'Effect of dedifferentiation on time to mutation acquisition in stem cell-driven cancers', 'Jilkine, Alexandra|Gutenkunst, Ryan N', 'Department of Molecular and Cellular Biology, University of Arizona, Tucson, Arizona, United States of America, Department of Applied and Computational Mathematics and Statistics, University of Notre Dame, Notre Dame, Indiana, United States of America.|Department of Molecular and Cellular Biology, University of Arizona, Tucson, Arizona, United States of America.', 'India|United States', 36, 'Carcinogenesis|Cell Differentiation|Cell Division|Cell Proliferation|Computer Simulation|Homeostasis|Humans|Models, Theoretical|Mutation|Neoplasms|Neoplastic Stem Cells|Stochastic Processes', 'Journal Article', '10.1371/journal.pcbi.1003481', '24603301', 'Accumulating evidence suggests that many tumors have a hierarchical organization, with the bulk of the tumor composed of relatively differentiated short-lived progenitor cells that are maintained by a small population of undifferentiated long-lived cancer stem cells. It is unclear, however, whether cancer stem cells originate from normal stem cells or from dedifferentiated progenitor cells. To address this, we mathematically modeled the effect of dedifferentiation on carcinogenesis. We considered a hybrid stochastic-deterministic model of mutation accumulation in both stem cells and progenitors, including dedifferentiation of progenitor cells to a stem cell-like state. We performed exact computer simulations of the emergence of tumor subpopulations with two mutations, and we derived semi-analytical estimates for the waiting time distribution to fixation. Our results suggest that dedifferentiation may play an important role in carcinogenesis, depending on how stem cell homeostasis is maintained. If the stem cell population size is held strictly constant (due to all divisions being asymmetric), we found that dedifferentiation acts like a positive selective force in the stem cell population and thus speeds carcinogenesis. If the stem cell population size is allowed to vary stochastically with density-dependent reproduction rates (allowing both symmetric and asymmetric divisions), we found that dedifferentiation beyond a critical threshold leads to exponential growth of the stem cell population. Thus, dedifferentiation may play a crucial role, the common modeling assumption of constant stem cell population size may not be adequate, and further progress in understanding carcinogenesis demands a more detailed mechanistic understanding of stem cell homeostasis. '),
(86455, 2014, 'plos', 'Structural insights into E coli porphobilinogen deaminase during synthesis and exit of 1-hydroxymethylbilane', 'Bung, Navneet|Pradhan, Meenakshi|Srinivasan, Harini|Bulusu, Gopalakrishnan', 'TCS Innovation Labs-Hyderabad (Life Sciences Division), Tata Consultancy Services Limited, Hyderabad, India.|TCS Innovation Labs-Hyderabad (Life Sciences Division), Tata Consultancy Services Limited, Hyderabad, India.|TCS Innovation Labs-Hyderabad (Life Sciences Division), Tata Consultancy Services Limited, Hyderabad, India.|TCS Innovation Labs-Hyderabad (Life Sciences Division), Tata Consultancy Services Limited, Hyderabad, India.', 'India|India|India|India', 0, 'Catalysis|Catalytic Domain|Computational Biology|Diffusion|Escherichia coli|Heme|Hydroxymethylbilane Synthase|Molecular Conformation|Molecular Dynamics Simulation|Mutation|Pyrroles|Uroporphyrinogens', 'Journal Article', '10.1371/journal.pcbi.1003484', '24603363', 'Porphobilinogen deaminase (PBGD) catalyzes the formation of 1-hydroxymethylbilane (HMB), a crucial intermediate in tetrapyrrole biosynthesis, through a step-wise polymerization of four molecules of porphobilinogen (PBG), using a unique dipyrromethane (DPM) cofactor. Structural and biochemical studies have suggested residues with catalytic importance, but their specific role in the mechanism and the dynamic behavior of the protein with respect to the growing pyrrole chain remains unknown. Molecular dynamics simulations of the protein through the different stages of pyrrole chain elongation suggested that the compactness of the overall protein decreases progressively with addition of each pyrrole ring. Essential dynamics showed that domains move apart while the cofactor turn region moves towards the second domain, thus creating space for the pyrrole rings added at each stage. Residues of the flexible active site loop play a significant role in its modulation. Steered molecular dynamics was performed to predict the exit mechanism of HMB from PBGD at the end of the catalytic cycle. Based on the force profile and minimal structural changes the proposed path for the exit of HMB is through the space between the domains flanking the active site loop. Residues reported as catalytically important, also play an important role in the exit of HMB. Further, upon removal of HMB, the structure of PBGD gradually relaxes to resemble its initial stage structure, indicating its readiness to resume a new catalytic cycle. '),
(86456, 2014, 'plos', 'Universal count correction for high-throughput sequencing', 'Hashimoto, Tatsunori B|Edwards, Matthew D|Gifford, David K', 'Computer Science and Artificial Intelligence Laboratory, Massachusetts Institute of Technology, Cambridge, Massachusetts, United States of America.|Computer Science and Artificial Intelligence Laboratory, Massachusetts Institute of Technology, Cambridge, Massachusetts, United States of America.|Computer Science and Artificial Intelligence Laboratory, Massachusetts Institute of Technology, Cambridge, Massachusetts, United States of America.', 'United States|United States|United States', 8, 'Algorithms|Area Under Curve|Chromatin|Chromatin Immunoprecipitation|Computational Biology|Computer Simulation|DNA|High-Throughput Nucleotide Sequencing|Humans|K562 Cells|Likelihood Functions|Poisson Distribution|RNA|Sequence Analysis, DNA|Software|Transcription Factors', 'Journal Article', '10.1371/journal.pcbi.1003494', '24603409', 'We show that existing RNA-seq, DNase-seq, and ChIP-seq data exhibit overdispersed per-base read count distributions that are not matched to existing computational method assumptions. To compensate for this overdispersion we introduce a nonparametric and universal method for processing per-base sequencing read count data called FIXSEQ. We demonstrate that FIXSEQ substantially improves the performance of existing RNA-seq, DNase-seq, and ChIP-seq analysis tools when compared with existing alternatives.'),
(86457, 2014, 'plos', 'Bioinformatics curriculum guidelines: toward a definition of core competencies', 'Welch, Lonnie|Lewitter, Fran|Schwartz, Russell|Brooksbank, Cath|Radivojac, Predrag|Gaeta, Bruno|Schneider, Maria Victoria', 'School of Electrical Engineering and Computer Science, Ohio University, Athens, Ohio, United States of America.|Bioinformatics and Research Computing, Whitehead Institute, Cambridge, Massachusetts, United States of America.|Department of Biological Sciences and School of Computer Science, Carnegie Mellon University, Pittsburgh, Pennsylvania, United States of America.|European Molecular Biology Laboratory, European Bioinformatics Institute, Wellcome Trust Genome Campus, Hinxton, Cambridge, United Kingdom.|School of Informatics and Computing, Indiana University, Bloomington, Indiana, United States of America.|School of Computer Science and Engineering, The University of New South Wales, Sydney, New South Wales, Australia.|The Genome Analysis Centre, Norwich Research Park, Norwich, United Kingdom.', 'United States|United States|United States|United Kingdom|India|Australia|United Kingdom', 57, 'Computational Biology|Curriculum|Education, Graduate|Humans|Internationality|Software|User-Computer Interface', 'Journal Article', '10.1371/journal.pcbi.1003496', '24603430', '-'),
(86458, 2014, 'plos', 'Quantitative protein localization signatures reveal an association between spatial and functional divergences of proteins', 'Loo, Lit-Hsin|Laksameethanasan, Danai|Tung, Yi-Ling', 'Bioinformatics Institute, Agency for Science, Technology and Research, Singapore, Singapore, Department of Pharmacology, Yong Loo Lin School of Medicine, National University of Singapore, Singapore, Singapore.|Bioinformatics Institute, Agency for Science, Technology and Research, Singapore, Singapore.|Bioinformatics Institute, Agency for Science, Technology and Research, Singapore, Singapore.', 'Singapore|Singapore|Singapore', 0, 'Algorithms|Automation|Computational Biology|Databases, Protein|Green Fluorescent Proteins|Image Processing, Computer-Assisted|Internet|Microscopy, Fluorescence|Models, Statistical|Open Reading Frames|Proteins|Saccharomyces cerevisiae|Software', 'Journal Article', '10.1371/journal.pcbi.1003504', '24603469', 'Protein subcellular localization is a major determinant of protein function. However, this important protein feature is often described in terms of discrete and qualitative categories of subcellular compartments, and therefore it has limited applications in quantitative protein function analyses. Here, we present Protein Localization Analysis and Search Tools (PLAST), an automated analysis framework for constructing and comparing quantitative signatures of protein subcellular localization patterns based on microscopy images. PLAST produces human-interpretable protein localization maps that quantitatively describe the similarities in the localization patterns of proteins and major subcellular compartments, without requiring manual assignment or supervised learning of these compartments. Using the budding yeast Saccharomyces cerevisiae as a model system, we show that PLAST is more accurate than existing, qualitative protein localization annotations in identifying known co-localized proteins. Furthermore, we demonstrate that PLAST can reveal protein localization-function relationships that are not obvious from these annotations. First, we identified proteins that have similar localization patterns and participate in closely-related biological processes, but do not necessarily form stable complexes with each other or localize at the same organelles. Second, we found an association between spatial and functional divergences of proteins during evolution. Surprisingly, as proteins with common ancestors evolve, they tend to develop more diverged subcellular localization patterns, but still occupy similar numbers of compartments. This suggests that divergence of protein localization might be more frequently due to the development of more specific localization patterns over ancestral compartments than the occupation of new compartments. PLAST enables systematic and quantitative analyses of protein localization-function relationships, and will be useful to elucidate protein functions and how these functions were acquired in cells from different organisms or species. A public web interface of PLAST is available at http://plast.bii.a-star.edu.sg. '),
(86459, 2014, 'plos', 'Epigenetics decouples mutational from environmental robustness Did it also facilitate multicellularity?', 'Gombar, Saurabh|MacCarthy, Thomas|Bergman, Aviv', 'Department of Systems and Computational Biology, Albert Einstein College of Medicine, Bronx, New York, New York, United States of America.|Department of Systems and Computational Biology, Albert Einstein College of Medicine, Bronx, New York, New York, United States of America, Department of Applied Mathematics and Statistics, State University of New York, Stony Brook, New York, United States of America.|Department of Systems and Computational Biology, Albert Einstein College of Medicine, Bronx, New York, New York, United States of America.', 'United States|United States|United States', 4, 'Animals|Cell Differentiation|DNA Mutational Analysis|Drosophila melanogaster|Environment|Epigenesis, Genetic|Evolution, Molecular|Gene Regulatory Networks|Gene-Environment Interaction|Genetic Association Studies|Histones|Mutation|Polycomb-Group Proteins', 'Journal Article', '10.1371/journal.pcbi.1003450', '24604070', 'The evolution of ever increasing complex life forms has required innovations at the molecular level in order to overcome existing barriers. For example, evolving processes for cell differentiation, such as epigenetic mechanisms, facilitated the transition to multicellularity. At the same time, studies using gene regulatory network models, and corroborated in single-celled model organisms, have shown that mutational robustness and environmental robustness are correlated. Such correlation may constitute a barrier to the evolution of multicellularity since cell differentiation requires sensitivity to cues in the internal environment during development. To investigate how this barrier might be overcome, we used a gene regulatory network model which includes epigenetic control based on the mechanism of histone modification via Polycomb Group Proteins, which evolved in tandem with the transition to multicellularity. Incorporating the Polycomb mechanism allowed decoupling of mutational and environmental robustness, thus allowing the system to be simultaneously robust to mutations while increasing sensitivity to the environment. In turn, this decoupling facilitated cell differentiation which we tested by evaluating the capacity of the system for producing novel output states in response to altered initial conditions. In the absence of the Polycomb mechanism, the system was frequently incapable of adding new states, whereas with the Polycomb mechanism successful addition of new states was nearly certain. The Polycomb mechanism, which dynamically reshapes the network structure during development as a function of expression dynamics, decouples mutational and environmental robustness, thus providing a necessary step in the evolution of multicellularity. '),
(86460, 2014, 'plos', 'Quantitative modeling of a genes expression from its intergenic sequence', 'Samee, Md Abul Hassan|Sinha, Saurabh', 'Department of Computer Science, University of Illinois at Urbana-Champaign, Urbana, Illinois, United States of America.|Department of Computer Science, University of Illinois at Urbana-Champaign, Urbana, Illinois, United States of America, Institute for Genomic Biology, University of Illinois at Urbana-Champaign, Urbana, Illinois, United States of America.', 'United States|United States', 0, 'Algorithms|Animals|Computational Biology|Computer Simulation|DNA, Intergenic|Drosophila melanogaster|Enhancer Elements, Genetic|Gene Expression Profiling|Gene Expression Regulation|Markov Chains|Models, Genetic|Models, Statistical|Monte Carlo Method|Regulatory Sequences, Nucleic Acid|Thermodynamics|Transcription Factors', 'Journal Article', '10.1371/journal.pcbi.1003467', '24604095', 'Modeling a genes expression from its intergenic locus and trans-regulatory context is a fundamental goal in computational biology. Owing to the distributed nature of cis-regulatory information and the poorly understood mechanisms that integrate such information, gene locus modeling is a more challenging task than modeling individual enhancers. Here we report the first quantitative model of a genes expression pattern as a function of its locus. We model the expression readout of a locus in two tiers: 1) combinatorial regulation by transcription factors bound to each enhancer is predicted by a thermodynamics-based model and 2) independent contributions from multiple enhancers are linearly combined to fit the gene expression pattern. The model does not require any prior knowledge about enhancers contributing toward a genes expression. We demonstrate that the model captures the complex multi-domain expression patterns of anterior-posterior patterning genes in the early Drosophila embryo. Altogether, we model the expression patterns of 27 genes, these include several gap genes, pair-rule genes, and anterior, posterior, trunk, and terminal genes. We find that the model-selected enhancers for each gene overlap strongly with its experimentally characterized enhancers. Our findings also suggest the presence of sequence-segments in the locus that would contribute ectopic expression patterns and hence were shut down by the model. We applied our model to identify the transcription factors responsible for forming the stripe boundaries of the studied genes. The resulting network of regulatory interactions exhibits a high level of agreement with known regulatory influences on the target genes. Finally, we analyzed whether and why our assumption of enhancer independence was necessary for the genes we studied. We found a deterioration of expression when binding sites in one enhancer were allowed to influence the readout of another enhancer. Thus, interference between enhancer activities was a possible factor necessitating enhancer independence in our model. '),
(86461, 2014, 'plos', 'Spatio-temporal simulation of first pass drug perfusion in the liver', 'Schwen, Lars Ole|Krauss, Markus|Niederalt, Christoph|Gremse, Felix|Kiessling, Fabian|Schenk, Andrea|Preusser, Tobias|Kuepfer, Lars', 'Fraunhofer MEVIS, Bremen, Germany.|Computational Systems Biology, Bayer Technology Services, Leverkusen, Germany, Aachen Institute for Advanced Study in Computational Engineering Sciences, RWTH Aachen University, Aachen, Germany.|Computational Systems Biology, Bayer Technology Services, Leverkusen, Germany.|Experimental Molecular Imaging, RWTH Aachen University, Aachen, Germany.|Experimental Molecular Imaging, RWTH Aachen University, Aachen, Germany.|Fraunhofer MEVIS, Bremen, Germany.|Fraunhofer MEVIS, Bremen, Germany, School of Engineering and Science, Jacobs University, Bremen, Germany.|Computational Systems Biology, Bayer Technology Services, Leverkusen, Germany, Institute of Applied Microbiology, RWTH Aachen University, Aachen, Germany.', 'Germany|Germany|Germany|Germany|Germany|Germany|Germany|Germany', 0, 'Algorithms|Animals|Computer Simulation|Contrast Media|Fluoresceins|Inactivation, Metabolic|Liver|Mice|Midazolam|Perfusion|Permeability|Spatio-Temporal Analysis|Spiramycin|Succinimides|X-Ray Microtomography|Xenobiotics', 'Journal Article', '10.1371/journal.pcbi.1003499', '24625393', 'The liver is the central organ for detoxification of xenobiotics in the body. In pharmacokinetic modeling, hepatic metabolization capacity is typically quantified as hepatic clearance computed as degradation in well-stirred compartments. This is an accurate mechanistic description once a quasi-equilibrium between blood and surrounding tissue is established. However, this model structure cannot be used to simulate spatio-temporal distribution during the first instants after drug injection. In this paper, we introduce a new spatially resolved model to simulate first pass perfusion of compounds within the naive liver. The model is based on vascular structures obtained from computed tomography as well as physiologically based mass transfer descriptions obtained from pharmacokinetic modeling. The physiological architecture of hepatic tissue in our model is governed by both vascular geometry and the composition of the connecting hepatic tissue. In particular, we here consider locally distributed mass flow in liver tissue instead of considering well-stirred compartments. Experimentally, the model structure corresponds to an isolated perfused liver and provides an ideal platform to address first pass effects and questions of hepatic heterogeneity. The model was evaluated for three exemplary compounds covering key aspects of perfusion, distribution and metabolization within the liver. As pathophysiological states we considered the influence of steatosis and carbon tetrachloride-induced liver necrosis on total hepatic distribution and metabolic capacity. Notably, we found that our computational predictions are in qualitative agreement with previously published experimental data. The simulation results provide an unprecedented level of detail in compound concentration profiles during first pass perfusion, both spatio-temporally in liver tissue itself and temporally in the outflowing blood. We expect our model to be the foundation of further spatially resolved models of the liver in the future. '),
(86462, 2014, 'plos', 'Dynamic alignment models for neural coding', 'Kollmorgen, Sepp|Hahnloser, Richard H R', 'Institute of Neuroinformatics, University of Zurich/ETH Zurich, Zurich, Switzerland.|Institute of Neuroinformatics, University of Zurich/ETH Zurich, Zurich, Switzerland.', 'Switzerland|Switzerland', 0, 'Algorithms|Animals|Brain|Humans|Linear Models|Markov Chains|Models, Neurological|Neurons|Nonlinear Dynamics|Normal Distribution|Poisson Distribution|Probability|Rats|Songbirds|Time Factors', 'Journal Article', '10.1371/journal.pcbi.1003508', '24625448', 'Recently, there have been remarkable advances in modeling the relationships between the sensory environment, neuronal responses, and behavior. However, most models cannot encompass variable stimulus-response relationships such as varying response latencies and state or context dependence of the neural code. Here, we consider response modeling as a dynamic alignment problem and model stimulus and response jointly by a mixed pair hidden Markov model (MPH). In MPHs, multiple stimulus-response relationships (e.g., receptive fields) are represented by different states or groups of states in a Markov chain. Each stimulus-response relationship features temporal flexibility, allowing modeling of variable response latencies, including noisy ones. We derive algorithms for learning of MPH parameters and for inference of spike response probabilities. We show that some linear-nonlinear Poisson cascade (LNP) models are a special case of MPHs. We demonstrate the efficiency and usefulness of MPHs in simulations of both jittered and switching spike responses to white noise and natural stimuli. Furthermore, we apply MPHs to extracellular single and multi-unit data recorded in cortical brain areas of singing birds to showcase a novel method for estimating response lag distributions. MPHs allow simultaneous estimation of receptive fields, latency statistics, and hidden state dynamics and so can help to uncover complex stimulus response relationships that are subject to variable timing and involve diverse neural codes. '),
(86463, 2014, 'plos', 'An in-silico model of lipoprotein metabolism and kinetics for the evaluation of targets and biomarkers in the reverse cholesterol transport pathway', 'Lu, James|Hübner, Katrin|Nanjee, M Nazeem|Brinton, Eliot A|Mazer, Norman A', 'F. Hoffmann-La Roche AG, pRED, Pharma Research & Early Development, Clinical Pharmacology, Basel, Switzerland.|BioQuant, University of Heidelberg, Heidelberg, Germany.|Division of Cardiovascular Genetics, University of Utah, Salt Lake City, Utah, United States of America.|Utah Foundation for Biomedical Research, Salt Lake City, Utah, United States of America.|F. Hoffmann-La Roche AG, pRED, Pharma Research & Early Development, Clinical Pharmacology, Basel, Switzerland.', 'Switzerland|Germany|United States|United States|Switzerland', 27, 'ATP Binding Cassette Transporter 1|Algorithms|Bayes Theorem|Biological Transport|Biomarkers|Calibration|Cardiovascular Diseases|Cholesterol|Cholesterol Ester Transfer Proteins|Computational Biology|Female|Gene Expression Regulation|Humans|Lipoproteins|Male', 'Journal Article', '10.1371/journal.pcbi.1003509', '24625468', 'High-density lipoprotein (HDL) is believed to play an important role in lowering cardiovascular disease (CVD) risk by mediating the process of reverse cholesterol transport (RCT). Via RCT, excess cholesterol from peripheral tissues is carried back to the liver and hence should lead to the reduction of atherosclerotic plaques. The recent failures of HDL-cholesterol (HDL-C) raising therapies have initiated a re-examination of the link between CVD risk and the rate of RCT, and have brought into question whether all target modulations that raise HDL-C would be atheroprotective. To help address these issues, a novel in-silico model has been built to incorporate modern concepts of HDL biology, including: the geometric structure of HDL linking the core radius with the number of ApoA-I molecules on it, and the regeneration of lipid-poor ApoA-I from spherical HDL due to remodeling processes. The ODE model has been calibrated using data from the literature and validated by simulating additional experiments not used in the calibration. Using a virtual population, we show that the model provides possible explanations for a number of well-known relationships in cholesterol metabolism, including the epidemiological relationship between HDL-C and CVD risk and the correlations between some HDL-related lipoprotein markers. In particular, the model has been used to explore two HDL-C raising target modulations, Cholesteryl Ester Transfer Protein (CETP) inhibition and ATP-binding cassette transporter member 1 (ABCA1) up-regulation. It predicts that while CETP inhibition would not result in an increased RCT rate, ABCA1 up-regulation should increase both HDL-C and RCT rate. Furthermore, the model predicts the two target modulations result in distinct changes in the lipoprotein measures. Finally, the model also allows for an evaluation of two candidate biomarkers for in-vivo whole-body ABCA1 activity: the absolute concentration and the % lipid-poor ApoA-I. These findings illustrate the potential utility of the model in drug development. '),
(86464, 2014, 'plos', 'Environmental and state-level regulatory factors affect the incidence of autism and intellectual disability', 'Rzhetsky, Andrey|Bagley, Steven C|Wang, Kanix|Lyttle, Christopher S|Cook, Edwin H|Altman, Russ B|Gibbons, Robert D', 'Department of Medicine, the University of Chicago, Chicago, Illinois, United States of America, Institute for Genomics and Systems Biology, the University of Chicago, Chicago, Illinois, United States of America, Computation Institute, Department of Human Genetics, the University of Chicago, Chicago, Illinois, United States of America.|Department of Genetics, Stanford University, Stanford, California, United States of America.|Institute for Genomics and Systems Biology, the University of Chicago, Chicago, Illinois, United States of America, Committee on Genetics, Genomics, and Systems Biology, the University of Chicago, Chicago, Illinois, United States of America.|The Center for Health and the Social Sciences, the University of Chicago, Chicago, Illinois, United States of America.|Department of Psychiatry, Institute for Juvenile Research, University of Illinois at Chicago, Chicago, Illinois, United States of America.|Departments of Bioengineering, Genetics, Medicine, and Computer Science, Stanford University, Stanford, California, United States of America.|Departments of Medicine and Health Studies, the University of Chicago, Center for Health Statistics, Chicago, Illinois, United States of America.', 'United States|United States|United States|United States|United States|United States|United States', 33, 'Algorithms|Autistic Disorder|Cluster Analysis|Congenital Abnormalities|Environment|Female|Humans|Incidence|Insurance Claim Review|Intellectual Disability|Male|Markov Chains|Monte Carlo Method|Phenotype|Poisson Distribution|Risk Factors|United States', 'Journal Article', '10.1371/journal.pcbi.1003518', '24625521', 'Many factors affect the risks for neurodevelopmental maladies such as autism spectrum disorders (ASD) and intellectual disability (ID). To compare environmental, phenotypic, socioeconomic and state-policy factors in a unified geospatial framework, we analyzed the spatial incidence patterns of ASD and ID using an insurance claims dataset covering nearly one third of the US population. Following epidemiologic evidence, we used the rate of congenital malformations of the reproductive system as a surrogate for environmental exposure of parents to unmeasured developmental risk factors, including toxins. Adjusted for gender, ethnic, socioeconomic, and geopolitical factors, the ASD incidence rates were strongly linked to population-normalized rates of congenital malformations of the reproductive system in males (an increase in ASD incidence by 283% for every percent increase in incidence of malformations, 95% CI: [91%, 576%], p<6xc3x9710(-5)). Such congenital malformations were barely significant for ID (94% increase, 95% CI: [1%, 250%], pxe2x80x8a=xe2x80x8a0.0384). Other congenital malformations in males (excluding those affecting the reproductive system) appeared to significantly affect both phenotypes: 31.8% ASD rate increase (CI: [12%, 52%], p<6xc3x9710(-5)), and 43% ID rate increase (CI: [23%, 67%], p<6xc3x9710(-5)). Furthermore, the state-mandated rigor of diagnosis of ASD by a pediatrician or clinician for consideration in the special education system was predictive of a considerable decrease in ASD and ID incidence rates (98.6%, CI: [28%, 99.99%], pxe2x80x8a=xe2x80x8a0.02475 and 99% CI: [68%, 99.99%], pxe2x80x8a=xe2x80x8a0.00637 respectively). Thus, the observed spatial variability of both ID and ASD rates is associated with environmental and state-level regulatory factors, the magnitude of influence of compound environmental predictors was approximately three times greater than that of state-level incentives. The estimated county-level random effects exhibited marked spatial clustering, strongly indicating existence of as yet unidentified localized factors driving apparent disease incidence. Finally, we found that the rates of ASD and ID at the county level were weakly but significantly correlated (Pearson product-moment correlation 0.0589, pxe2x80x8a=xe2x80x8a0.00101), while for females the correlation was much stronger (0.197, p<2.26xc3x9710(-16)).'),
(86465, 2014, 'plos', 'Direct solution of the Chemical Master Equation using quantized tensor trains', 'Kazeev, Vladimir|Khammash, Mustafa|Nip, Michael|Schwab, Christoph', 'Seminar für Angewandte Mathematik, ETH Zürich, Zürich, Switzerland.|Department of Biosystems Science and Engineering, ETH Zürich, Basel, Switzerland.|Department of Mechanical Engineering, UC Santa Barbara, Santa Barbara, California, United States of America.|Seminar für Angewandte Mathematik, ETH Zürich, Zürich, Switzerland.', 'Switzerland|Switzerland|United States|Switzerland', 57, 'Algorithms|Biochemistry|Computational Biology|Computer Simulation|Models, Statistical|Monte Carlo Method|Probability|Stochastic Processes', 'Journal Article', '10.1371/journal.pcbi.1003359', '24626049', 'The Chemical Master Equation (CME) is a cornerstone of stochastic analysis and simulation of models of biochemical reaction networks. Yet direct solutions of the CME have remained elusive. Although several approaches overcome the infinite dimensional nature of the CME through projections or other means, a common feature of proposed approaches is their susceptibility to the curse of dimensionality, i.e. the exponential growth in memory and computational requirements in the number of problem dimensions. We present a novel approach that has the potential to lift this curse of dimensionality. The approach is based on the use of the recently proposed Quantized Tensor Train (QTT) formatted numerical linear algebra for the low parametric, numerical representation of tensors. The QTT decomposition admits both, algorithms for basic tensor arithmetics with complexity scaling linearly in the dimension (number of species) and sub-linearly in the mode size (maximum copy number), and a numerical tensor rounding procedure which is stable and quasi-optimal. We show how the CME can be represented in QTT format, then use the exponentially-converging hp-discontinuous Galerkin discretization in time to reduce the CME evolution problem to a set of QTT-structured linear equations to be solved at each time step using an algorithm based on Density Matrix Renormalization Group (DMRG) methods from quantum chemistry. Our method automatically adapts the basis of the solution at every time step guaranteeing that it is large enough to capture the dynamics of interest but no larger than necessary, as this would increase the computational complexity. Our approach is demonstrated by applying it to three different examples from systems biology: independent birth-death process, an example of enzymatic futile cycle, and a stochastic switch model. The numerical results on these examples demonstrate that the proposed QTT method achieves dramatic speedups and several orders of magnitude storage savings over direct approaches.'),
(86466, 2014, 'plos', 'The rise and fall of HIV in high-prevalence countries: a challenge for mathematical modeling', 'Nagelkerke, Nico J D|Arora, Paul|Jha, Prabhat|Williams, Brian|McKinnon, Lyle|de Vlas, Sake J', 'Institute of Public Health, College of Medicine and Health Science, United Arab Emirates University, Al Ain, United Arab Emirates, Department of Public Health, Erasmus MC, University Medical Center Rotterdam, Rotterdam, Netherlands, Department of Medical Microbiology and Infectious Diseases, University of Manitoba, Winnipeg, Canada.|Center for Global Health Research, St. Michaels Hospital, Dalla Lana School of Public Health, University of Toronto, Toronto, Canada.|Center for Global Health Research, St. Michaels Hospital, Dalla Lana School of Public Health, University of Toronto, Toronto, Canada.|South African Centre for Epidemiological Modelling and Analysis, University of Stellenbosch, Stellenbosch, South Africa.|Department of Medicine, University of Toronto, Toronto, Canada, Department of Medical Microbiology, University of Nairobi, Nairobi, Kenya.|Department of Public Health, Erasmus MC, University Medical Center Rotterdam, Rotterdam, Netherlands.', 'United Arab Emirates|Canada|Canada|South Africa|Canada|Netherlands', 0, 'Africa|Anti-Retroviral Agents|Computer Simulation|Epidemics|HIV Infections|Humans|Models, Theoretical|Prevalence|Risk-Taking|Sexual Behavior', 'Journal Article', '10.1371/journal.pcbi.1003459', '24626088', 'Several countries with generalized, high-prevalence HIV epidemics, mostly in sub-Saharan Africa, have experienced rapid declines in transmission. These HIV epidemics, often with rapid onsets, have generally been attributed to a combination of factors related to high-risk sexual behavior. The subsequent declines in these countries began prior to widespread therapy or implementation of any other major biomedical prevention. This change has been construed as evidence of behavior change, often on the basis of mathematical models, but direct evidence for behavior changes that would explain these declines is limited. Here, we look at the structure of current models and argue that the common fixed risk per sexual contact assumption favors the conclusion of substantial behavior changes. We argue that this assumption ignores reported non-linearities between exposure and risk. Taking this into account, we propose that some of the decline in HIV transmission may be part of the natural dynamics of the epidemic, and that several factors that have traditionally been ignored by modelers for lack of precise quantitative estimates may well hold the key to understanding epidemiologic trends. '),
(86467, 2014, 'plos', 'Modular composition of gene transcription networks', 'Gyorgy, Andras|Del Vecchio, Domitilla', 'Department of Electrical Engineering and Computer Science, Massachusetts Institute of Technology, Cambridge, Massachusetts, United States of America.|Department of Mechanical Engineering, Massachusetts Institute of Technology, Cambridge, Massachusetts, United States of America.', 'United States|United States', 40, 'Algorithms|Amino Acid Motifs|Bacteria|Computational Biology|Computer Simulation|Escherichia coli|Gene Regulatory Networks|Genes, Bacterial|Promoter Regions, Genetic|Signal Transduction|Transcription Factors|Transcription, Genetic', 'Journal Article', '10.1371/journal.pcbi.1003486', '24626132', 'Predicting the dynamic behavior of a large network from that of the composing modules is a central problem in systems and synthetic biology. Yet, this predictive ability is still largely missing because modules display context-dependent behavior. One cause of context-dependence is retroactivity, a phenomenon similar to loading that influences in non-trivial ways the dynamic performance of a module upon connection to other modules. Here, we establish an analysis framework for gene transcription networks that explicitly accounts for retroactivity. Specifically, a modules key properties are encoded by three retroactivity matrices: internal, scaling, and mixing retroactivity. All of them have a physical interpretation and can be computed from macroscopic parameters (dissociation constants and promoter concentrations) and from the modules topology. The internal retroactivity quantifies the effect of intramodular connections on an isolated modules dynamics. The scaling and mixing retroactivity establish how intermodular connections change the dynamics of connected modules. Based on these matrices and on the dynamics of modules in isolation, we can accurately predict how loading will affect the behavior of an arbitrary interconnection of modules. We illustrate implications of internal, scaling, and mixing retroactivity on the performance of recurrent network motifs, including negative autoregulation, combinatorial regulation, two-gene clocks, the toggle switch, and the single-input motif. We further provide a quantitative metric that determines how robust the dynamic behavior of a module is to interconnection with other modules. This metric can be employed both to evaluate the extent of modularity of natural networks and to establish concrete design guidelines to minimize retroactivity between modules in synthetic systems. '),
(86468, 2014, 'plos', 'Assembly of Nsp1 nucleoporins provides insight into nuclear pore complex gating', 'Gamini, Ramya|Han, Wei|Stone, John E|Schulten, Klaus', 'Beckman Institute, University of Illinois at Urbana-Champaign, Champaign, Illinois, United States of America, Center for Biophysics and Computational Biology, University of Illinois at Urbana-Champaign, Champaign, Illinois, United States of America.|Beckman Institute, University of Illinois at Urbana-Champaign, Champaign, Illinois, United States of America.|Beckman Institute, University of Illinois at Urbana-Champaign, Champaign, Illinois, United States of America.|Beckman Institute, University of Illinois at Urbana-Champaign, Champaign, Illinois, United States of America, Center for Biophysics and Computational Biology, University of Illinois at Urbana-Champaign, Champaign, Illinois, United States of America, Department of Physics, University of Illinois at Urbana-Champaign, Champaign, Illinois, United States of America.', 'United States|United States|United States|United States', 25, 'Computational Biology|Computer Simulation|Cross-Linking Reagents|Diffusion|Epitopes|Molecular Dynamics Simulation|Nuclear Pore|Nuclear Pore Complex Proteins|Nuclear Proteins|Protein Conformation|Saccharomyces cerevisiae|Saccharomyces cerevisiae Proteins|Software', 'Journal Article', '10.1371/journal.pcbi.1003488', '24626154', 'Nuclear pore complexes (NPCs) form gateways for material transfer across the nuclear envelope of eukaryotic cells. Disordered proteins, rich in phenylalanine-glycine repeat motifs (FG-nups), form the central transport channel. Understanding how nups are arranged in the interior of the NPC may explain how NPC functions as a selectivity filter for transport of large molecules and a sieve-like filter for diffusion of small molecules (<9 nm or 40 kDa). We employed molecular dynamics to model the structures formed by various assemblies of one kind of nup, namely the 609-aa-long FG domain of Nsp1 (Nsp1-FG). The simulations started from different initial conformations and geometrical arrangements of Nsp1-FGs. In all cases Nsp1-FGs collectively formed brush-like structures with bristles made of bundles of 2-27 nups, however, the bundles being cross-linked through single nups leaving one bundle and joining a nearby one. The degree of cross-linking varies with different initial nup conformations and arrangements. Structural analysis reveals that FG-repeats of the nups not only involve formation of bundle structures, but are abundantly present in cross-linking regions where the epitopes of FG-repeats are highly accessible. Large molecules that are assisted by transport factors (TFs) are selectively transported through NPC apparently by binding to FG-nups through populated FG-binding pockets on the TF surface. Therefore, our finding suggests that TFs bind concertedly to multiple FGs in cross-linking regions and break-up the bundles to create wide pores for themselves and their cargoes to pass. In addition, the cross-linking between Nsp1-FG bundles, arising from simulations, is found to set a molecular size limit of <9 nm (40 kDa) for passive diffusion of molecules. Our simulations suggest that the NPC central channel, near the periphery where tethering of nups is dominant, features brush-like moderately cross-linked bundles, but in the central region, where tethering loses its effect, features a sieve-like structure of bundles and frequent cross-links.'),
(86469, 2014, 'plos', 'Bidirectional control of absence seizures by the basal ganglia: a computational evidence', 'Chen, Mingming|Guo, Daqing|Wang, Tiebin|Jing, Wei|Xia, Yang|Xu, Peng|Luo, Cheng|Valdes-Sosa, Pedro A|Yao, Dezhong', 'Key Laboratory for NeuroInformation of Ministry of Education, School of Life Science and Technology, University of Electronic Science and Technology of China, Chengdu, Peoples Republic of China.|Key Laboratory for NeuroInformation of Ministry of Education, School of Life Science and Technology, University of Electronic Science and Technology of China, Chengdu, Peoples Republic of China.|Key Laboratory for NeuroInformation of Ministry of Education, School of Life Science and Technology, University of Electronic Science and Technology of China, Chengdu, Peoples Republic of China.|Key Laboratory for NeuroInformation of Ministry of Education, School of Life Science and Technology, University of Electronic Science and Technology of China, Chengdu, Peoples Republic of China.|Key Laboratory for NeuroInformation of Ministry of Education, School of Life Science and Technology, University of Electronic Science and Technology of China, Chengdu, Peoples Republic of China.|Key Laboratory for NeuroInformation of Ministry of Education, School of Life Science and Technology, University of Electronic Science and Technology of China, Chengdu, Peoples Republic of China.|Key Laboratory for NeuroInformation of Ministry of Education, School of Life Science and Technology, University of Electronic Science and Technology of China, Chengdu, Peoples Republic of China.|Key Laboratory for NeuroInformation of Ministry of Education, School of Life Science and Technology, University of Electronic Science and Technology of China, Chengdu, Peoples Republic of China, Cuban Neuroscience Center, Cubanacan, Playa, Cuba.|Key Laboratory for NeuroInformation of Ministry of Education, School of Life Science and Technology, University of Electronic Science and Technology of China, Chengdu, Peoples Republic of China.', 'China|China|China|China|China|China|China|China|China', 0, 'Algorithms|Basal Ganglia|Biophysics|Cerebral Cortex|Computer Simulation|Epilepsy, Absence|Humans|Models, Theoretical|Neural Pathways|Neurons|Software|Substantia Nigra|Thalamus', 'Journal Article', '10.1371/journal.pcbi.1003495', '24626189', 'Absence epilepsy is believed to be associated with the abnormal interactions between the cerebral cortex and thalamus. Besides the direct coupling, anatomical evidence indicates that the cerebral cortex and thalamus also communicate indirectly through an important intermediate bridge-basal ganglia. It has been thus postulated that the basal ganglia might play key roles in the modulation of absence seizures, but the relevant biophysical mechanisms are still not completely established. Using a biophysically based model, we demonstrate here that the typical absence seizure activities can be controlled and modulated by the direct GABAergic projections from the substantia nigra pars reticulata (SNr) to either the thalamic reticular nucleus (TRN) or the specific relay nuclei (SRN) of thalamus, through different biophysical mechanisms. Under certain conditions, these two types of seizure control are observed to coexist in the same network. More importantly, due to the competition between the inhibitory SNr-TRN and SNr-SRN pathways, we find that both decreasing and increasing the activation of SNr neurons from the normal level may considerably suppress the generation of spike-and-slow wave discharges in the coexistence region. Overall, these results highlight the bidirectional functional roles of basal ganglia in controlling and modulating absence seizures, and might provide novel insights into the therapeutic treatments of this brain disorder. ');
INSERT INTO `papers` (`id`, `ano`, `journal`, `titulo`, `autores`, `afiliacao`, `pais`, `citacoes`, `palavra_chave`, `categorias`, `doi`, `pubmed`, `abstract`) VALUES
(86470, 2014, 'plos', 'Model-based analysis for qualitative data: an application in Drosophila germline stem cell regulation', 'Pargett, Michael|Rundell, Ann E|Buzzard, Gregery T|Umulis, David M', 'Weldon School of Biomedical Engineering, Purdue University, West Lafayette, Indiana, United States of America.|Weldon School of Biomedical Engineering, Purdue University, West Lafayette, Indiana, United States of America.|Department of Mathematics, Purdue University, West Lafayette, Indiana, United States of America.|Agricultural and Biological Engineering, Purdue University, West Lafayette, Indiana, United States of America.', 'India|India|India|India', 10, 'Algorithms|Animals|Computational Biology|Drosophila|Endocytosis|Fluorescent Dyes|Gene Expression Profiling|Gene Expression Regulation|Immunohistochemistry|Models, Theoretical|Mutation|Phenotype|Stem Cells', 'Journal Article', '10.1371/journal.pcbi.1003498', '24626201', 'Discovery in developmental biology is often driven by intuition that relies on the integration of multiple types of data such as fluorescent images, phenotypes, and the outcomes of biochemical assays. Mathematical modeling helps elucidate the biological mechanisms at play as the networks become increasingly large and complex. However, the available data is frequently under-utilized due to incompatibility with quantitative model tuning techniques. This is the case for stem cell regulation mechanisms explored in the Drosophila germarium through fluorescent immunohistochemistry. To enable better integration of biological data with modeling in this and similar situations, we have developed a general parameter estimation process to quantitatively optimize models with qualitative data. The process employs a modified version of the Optimal Scaling method from social and behavioral sciences, and multi-objective optimization to evaluate the trade-off between fitting different datasets (e.g. wild type vs. mutant). Using only published imaging data in the germarium, we first evaluated support for a published intracellular regulatory network by considering alternative connections of the same regulatory players. Simply screening networks against wild type data identified hundreds of feasible alternatives. Of these, five parsimonious variants were found and compared by multi-objective analysis including mutant data and dynamic constraints. With these data, the current model is supported over the alternatives, but support for a biochemically observed feedback element is weak (i.e. these data do not measure the feedback effect well). When also comparing new hypothetical models, the available data do not discriminate. To begin addressing the limitations in data, we performed a model-based experiment design and provide recommendations for experiments to refine model parameters and discriminate increasingly complex hypotheses. '),
(86471, 2014, 'plos', 'If you cant measure it, you cant manage it', 'Peccoud, Jean', 'Virginia Bioinformatics Institute, Virginia Tech, Blacksburg, Virginia, United States of America.', 'United States', 2, 'Computational Biology|Computers|Humans|Models, Organizational|Research|Research Support as Topic|Social Media|Systems Biology', 'Journal Article', '10.1371/journal.pcbi.1003462', '24651311', '-'),
(86472, 2014, 'plos', 'Integrative computational and experimental approaches to establish a post-myocardial infarction knowledge map', 'Nguyen, Nguyen T|Zhang, Xiaolin|Wu, Cathy|Lange, Richard A|Chilton, Robert J|Lindsey, Merry L|Jin, Yu-Fang', 'Department of Electrical and Computer Engineering, University of Texas at San Antonio, San Antonio, Texas, United States of America, San Antonio Cardiovascular Proteomics Center, University of Texas Health Science Center at San Antonio, San Antonio, Texas, United States of America.|Department of Electrical and Computer Engineering, University of Texas at San Antonio, San Antonio, Texas, United States of America.|Center for Bioinformatics and Computational Biology and Protein Information Resource, University of Delaware, Newark, Delaware, United States of America.|San Antonio Cardiovascular Proteomics Center, University of Texas Health Science Center at San Antonio, San Antonio, Texas, United States of America, Department of Medicine, University of Texas Health Science Center at San Antonio, San Antonio, Texas, United States of America.|San Antonio Cardiovascular Proteomics Center, University of Texas Health Science Center at San Antonio, San Antonio, Texas, United States of America, Department of Medicine, University of Texas Health Science Center at San Antonio, San Antonio, Texas, United States of America.|San Antonio Cardiovascular Proteomics Center, University of Texas Health Science Center at San Antonio, San Antonio, Texas, United States of America, Mississippi Center for Heart Research, University of Mississippi Medical Center, Jackson, Mississippi, United States of America, Research Service, G.V. (Sonny) Montgomery Veterans Affairs Medical Center, Jackson, Mississippi, United States of America.|Department of Electrical and Computer Engineering, University of Texas at San Antonio, San Antonio, Texas, United States of America, San Antonio Cardiovascular Proteomics Center, University of Texas Health Science Center at San Antonio, San Antonio, Texas, United States of America.', 'United States|United States|United States|United States|United States|United States|United States', 8, 'Algorithms|Biomarkers|Cluster Analysis|Computer Simulation|Data Mining|Databases, Protein|Extracellular Matrix|Heart Ventricles|Humans|Medical Informatics|Models, Biological|Myocardial Infarction|Protein Interaction Mapping|Ventricular Remodeling', 'Journal Article', '10.1371/journal.pcbi.1003472', '24651374', 'Vast research efforts have been devoted to providing clinical diagnostic markers of myocardial infarction (MI), leading to over one million abstracts associated with MI and Cardiovascular Diseases in PubMed. Accumulation of the research results imposed a challenge to integrate and interpret these results. To address this problem and better understand how the left ventricle (LV) remodels post-MI at both the molecular and cellular levels, we propose here an integrative framework that couples computational methods and experimental data. We selected an initial set of MI-related proteins from published human studies and constructed an MI-specific protein-protein-interaction network (MIPIN). Structural and functional analysis of the MIPIN showed that the post-MI LV exhibited increased representation of proteins involved in transcriptional activity, inflammatory response, and extracellular matrix (ECM) remodeling. Known plasma or serum expression changes of the MIPIN proteins in patients with MI were acquired by data mining of the PubMed and UniProt knowledgebase, and served as a training set to predict unlabeled MIPIN protein changes post-MI. The predictions were validated with published results in PubMed, suggesting prognosticative capability of the MIPIN. Further, we established the first knowledge map related to the post-MI response, providing a major step towards enhancing our understanding of molecular interactions specific to MI and linking the molecular interaction, cellular responses, and biological processes to quantify LV remodeling. '),
(86473, 2014, 'plos', 'Spatiotemporal computations of an excitable and plastic brain: neuronal plasticity leads to noise-robust and noise-constructive computations', 'Toutounji, Hazem|Pipa, Gordon', 'Institute of Cognitive Science, University of Osnabrück, Osnabrück, Lower Saxony, Germany.|Institute of Cognitive Science, University of Osnabrück, Osnabrück, Lower Saxony, Germany.', 'Germany|Germany', 17, 'Algorithms|Animals|Brain|Computer Simulation|Homeostasis|Humans|Learning|Memory|Models, Neurological|Models, Statistical|Nerve Net|Neuronal Plasticity|Neurons|Spatio-Temporal Analysis|Synapses', 'Journal Article', '10.1371/journal.pcbi.1003512', '24651447', 'It is a long-established fact that neuronal plasticity occupies the central role in generating neural function and computation. Nevertheless, no unifying account exists of how neurons in a recurrent cortical network learn to compute on temporally and spatially extended stimuli. However, these stimuli constitute the norm, rather than the exception, of the brains input. Here, we introduce a geometric theory of learning spatiotemporal computations through neuronal plasticity. To that end, we rigorously formulate the problem of neural representations as a relation in space between stimulus-induced neural activity and the asymptotic dynamics of excitable cortical networks. Backed up by computer simulations and numerical analysis, we show that two canonical and widely spread forms of neuronal plasticity, that is, spike-timing-dependent synaptic plasticity and intrinsic plasticity, are both necessary for creating neural representations, such that these computations become realizable. Interestingly, the effects of these forms of plasticity on the emerging neural code relate to properties necessary for both combating and utilizing noise. The neural dynamics also exhibits features of the most likely stimulus in the networks spontaneous activity. These properties of the spatiotemporal neural code resulting from plasticity, having their grounding in nature, further consolidate the biological relevance of our findings. '),
(86474, 2014, 'plos', 'Probabilistic approach to predicting substrate specificity of methyltransferases', 'Szczepixc5x84ska, Teresa|Kutner, Jan|Kopczyxc5x84ski, Michaxc5x82|Pawxc5x82owski, Krzysztof|Dziembowski, Andrzej|Kudlicki, Andrzej|Ginalski, Krzysztof|Rowicka, Maga', 'Nencki Institute of Experimental Biology, Polish Academy of Sciences, Warsaw, Poland, Department of Biochemistry and Molecular Biology, University of Texas Medical Branch, Galveston, Texas, United States of America, Institute for Translational Sciences, University of Texas Medical Branch, Galveston, Texas, United States of America, Institute of Biochemistry and Biophysics, Polish Academy of Sciences, Warsaw, Poland, Institute of Genetics and Biotechnology, Faculty of Biology, University of Warsaw, Warsaw, Poland.|Laboratory of Bioinformatics and Systems Biology, Centre of New Technologies, University of Warsaw, Warsaw, Poland.|Laboratory of Bioinformatics and Systems Biology, Centre of New Technologies, University of Warsaw, Warsaw, Poland.|Nencki Institute of Experimental Biology, Polish Academy of Sciences, Warsaw, Poland, Warsaw University of Life Sciences, Warsaw, Poland.|Institute of Biochemistry and Biophysics, Polish Academy of Sciences, Warsaw, Poland, Institute of Genetics and Biotechnology, Faculty of Biology, University of Warsaw, Warsaw, Poland.|Department of Biochemistry and Molecular Biology, University of Texas Medical Branch, Galveston, Texas, United States of America, Institute for Translational Sciences, University of Texas Medical Branch, Galveston, Texas, United States of America, Sealy Center for Molecular Medicine, University of Texas Medical Branch, Galveston, Texas, United States of America.|Laboratory of Bioinformatics and Systems Biology, Centre of New Technologies, University of Warsaw, Warsaw, Poland.|Department of Biochemistry and Molecular Biology, University of Texas Medical Branch, Galveston, Texas, United States of America, Institute for Translational Sciences, University of Texas Medical Branch, Galveston, Texas, United States of America, Sealy Center for Molecular Medicine, University of Texas Medical Branch, Galveston, Texas, United States of America.', 'Poland|Poland|Poland|Poland|Poland|United States|Poland|United States', 12, 'Algorithms|Bayes Theorem|Binding Sites|Computational Biology|Fungal Proteins|Isoelectric Point|Likelihood Functions|Methyltransferases|Models, Theoretical|Probability|Protein Binding|Protein Folding|RNA|Saccharomyces cerevisiae|Substrate Specificity', 'Journal Article', '10.1371/journal.pcbi.1003514', '24651469', 'We present a general probabilistic framework for predicting the substrate specificity of enzymes. We designed this approach to be easily applicable to different organisms and enzymes. Therefore, our predictive models do not rely on species-specific properties and use mostly sequence-derived data. Maximum Likelihood optimization is used to fine-tune model parameters and the Akaike Information Criterion is employed to overcome the issue of correlated variables. As a proof-of-principle, we apply our approach to predicting general substrate specificity of yeast methyltransferases (MTases). As input, we use several physico-chemical and biological properties of MTases: structural fold, isoelectric point, expression pattern and cellular localization. Our method accurately predicts whether a yeast MTase methylates a protein, RNA or another molecule. Among our experimentally tested predictions, 89% were confirmed, including the surprising prediction that YOR021C is the first known MTase with a SPOUT fold that methylates a substrate other than RNA (protein). Our approach not only allows for highly accurate prediction of functional specificity of MTases, but also provides insight into general rules governing MTase substrate specificity. '),
(86475, 2014, 'plos', 'Long non-coding RNA and alternative splicing modulations in Parkinsons leukocytes identified by RNA sequencing', 'Soreq, Lilach|Guffanti, Alessandro|Salomonis, Nathan|Simchovitz, Alon|Israel, Zvi|Bergman, Hagai|Soreq, Hermona', 'Department of Medical Neurobiology, IMRIC, The Hebrew University-Hadassah Medical School, Jerusalem, Israel.|Department of Biological Chemistry, The Life Sciences Institute, The Hebrew University of Jerusalem, Jerusalem, Israel, Genomnia srl, Lainate, Milan, Italy.|Department of Pediatrics, Division of Biomedical Informatics, Cincinnati Childrens Hospital Medical Center, Cincinnati, Ohio, United States of America.|Genomnia srl, Lainate, Milan, Italy.|The Center for Functional and Restorative Neurosurgery, Department of Neurosurgery, Hadassah University Hospital, Jerusalem, Israel.|Department of Medical Neurobiology, IMRIC, The Hebrew University-Hadassah Medical School, Jerusalem, Israel, The Edmond and Lily Safra Center for Brain Sciences (ELSC), The Hebrew University of Jerusalem, Jerusalem, Israel.|Department of Biological Chemistry, The Life Sciences Institute, The Hebrew University of Jerusalem, Jerusalem, Israel, The Edmond and Lily Safra Center for Brain Sciences (ELSC), The Hebrew University of Jerusalem, Jerusalem, Israel.', 'Israel|Israel|United States|Italy|Israel|Israel|Israel', 97, 'Alternative Splicing|Amygdala|Brain Mapping|Deep Brain Stimulation|Female|Gene Expression Profiling|Humans|Leukocytes|Male|MicroRNAs|Oligonucleotide Array Sequence Analysis|Parkinson Disease|RNA, Long Noncoding|Sequence Analysis, RNA|Substantia Nigra', 'Journal Article', '10.1371/journal.pcbi.1003517', '24651478', 'The continuously prolonged human lifespan is accompanied by increase in neurodegenerative diseases incidence, calling for the development of inexpensive blood-based diagnostics. Analyzing blood cell transcripts by RNA-Seq is a robust means to identify novel biomarkers that rapidly becomes a commonplace. However, there is lack of tools to discover novel exons, junctions and splicing events and to precisely and sensitively assess differential splicing through RNA-Seq data analysis and across RNA-Seq platforms. Here, we present a new and comprehensive computational workflow for whole-transcriptome RNA-Seq analysis, using an updated version of the software AltAnalyze, to identify both known and novel high-confidence alternative splicing events, and to integrate them with both protein-domains and microRNA binding annotations. We applied the novel workflow on RNA-Seq data from Parkinsons disease (PD) patients leukocytes pre- and post- Deep Brain Stimulation (DBS) treatment and compared to healthy controls. Disease-mediated changes included decreased usage of alternative promoters and N-termini, 5-end variations and mutually-exclusive exons. The PD regulated FUS and HNRNP A/B included prion-like domains regulated regions. We also present here a workflow to identify and analyze long non-coding RNAs (lncRNAs) via RNA-Seq data. We identified reduced lncRNA expression and selective PD-induced changes in 13 of over 6,000 detected leukocyte lncRNAs, four of which were inversely altered post-DBS. These included the U1 spliceosomal lncRNA and RP11-462G22.1, each entailing sequence complementarity to numerous microRNAs. Analysis of RNA-Seq from PD and unaffected controls brains revealed over 7,000 brain-expressed lncRNAs, of which 3,495 were co-expressed in the leukocytes including U1, which showed both leukocyte and brain increases. Furthermore, qRT-PCR validations confirmed these co-increases in PD leukocytes and two brain regions, the amygdala and substantia-nigra, compared to controls. This novel workflow allows deep multi-level inspection of RNA-Seq datasets and provides a comprehensive new resource for understanding disease transcriptome modifications in PD and other neurodegenerative diseases. '),
(86476, 2014, 'plos', 'Computational analyses of synergism in small molecular network motifs', 'Zhang, Yili|Smolen, Paul|Baxter, Douglas A|Byrne, John H', 'Department of Neurobiology and Anatomy, The University of Texas Medical School at Houston, Houston, Texas, United States of America.|Department of Neurobiology and Anatomy, The University of Texas Medical School at Houston, Houston, Texas, United States of America.|Department of Neurobiology and Anatomy, The University of Texas Medical School at Houston, Houston, Texas, United States of America.|Department of Neurobiology and Anatomy, The University of Texas Medical School at Houston, Houston, Texas, United States of America.', 'United States|United States|United States|United States', 15, 'Amino Acid Motifs|Bacterial Proteins|CREB-Binding Protein|Computational Biology|Computer Simulation|Cyclic AMP Response Element-Binding Protein|Drug Therapy, Combination|Feedback, Physiological|Gene Regulatory Networks|Genes, Bacterial|Humans|Software|Systems Biology|Transcription, Genetic', 'Journal Article', '10.1371/journal.pcbi.1003524', '24651495', 'Cellular functions and responses to stimuli are controlled by complex regulatory networks that comprise a large diversity of molecular components and their interactions. However, achieving an intuitive understanding of the dynamical properties and responses to stimuli of these networks is hampered by their large scale and complexity. To address this issue, analyses of regulatory networks often focus on reduced models that depict distinct, reoccurring connectivity patterns referred to as motifs. Previous modeling studies have begun to characterize the dynamics of small motifs, and to describe ways in which variations in parameters affect their responses to stimuli. The present study investigates how variations in pairs of parameters affect responses in a series of ten common network motifs, identifying concurrent variations that act synergistically (or antagonistically) to alter the responses of the motifs to stimuli. Synergism (or antagonism) was quantified using degrees of nonlinear blending and additive synergism. Simulations identified concurrent variations that maximized synergism, and examined the ways in which it was affected by stimulus protocols and the architecture of a motif. Only a subset of architectures exhibited synergism following paired changes in parameters. The approach was then applied to a model describing interlocked feedback loops governing the synthesis of the CREB1 and CREB2 transcription factors. The effects of motifs on synergism for this biologically realistic model were consistent with those for the abstract models of single motifs. These results have implications for the rational design of combination drug therapies with the potential for synergistic interactions. '),
(86477, 2014, 'plos', 'Relating structure and function in the human brain: relative contributions of anatomy, stationary dynamics, and non-stationarities', 'Messé, Arnaud|Rudrauf, David|Benali, Habib|Marrelec, Guillaume', 'Laboratoire dImagerie Fonctionnelle, UMR678, Inserm/UPMC Univ Paris 06, Paris, France.|Laboratoire dImagerie Fonctionnelle, UMR678, Inserm/UPMC Univ Paris 06, Paris, France.|Laboratoire dImagerie Fonctionnelle, UMR678, Inserm/UPMC Univ Paris 06, Paris, France.|Laboratoire dImagerie Fonctionnelle, UMR678, Inserm/UPMC Univ Paris 06, Paris, France.', 'France|France|France|France', 103, 'Adult|Brain|Brain Mapping|Computer Simulation|Diffusion Magnetic Resonance Imaging|Female|Hemodynamics|Humans|Magnetic Resonance Imaging|Male|Models, Neurological|Nerve Net|Neural Pathways|Reproducibility of Results|Young Adult', 'Journal Article', '10.1371/journal.pcbi.1003530', '24651524', 'Investigating the relationship between brain structure and function is a central endeavor for neuroscience research. Yet, the mechanisms shaping this relationship largely remain to be elucidated and are highly debated. In particular, the existence and relative contributions of anatomical constraints and dynamical physiological mechanisms of different types remain to be established. We addressed this issue by systematically comparing functional connectivity (FC) from resting-state functional magnetic resonance imaging data with simulations from increasingly complex computational models, and by manipulating anatomical connectivity obtained from fiber tractography based on diffusion-weighted imaging. We hypothesized that FC reflects the interplay of at least three types of components: (i) a backbone of anatomical connectivity, (ii) a stationary dynamical regime directly driven by the underlying anatomy, and (iii) other stationary and non-stationary dynamics not directly related to the anatomy. We showed that anatomical connectivity alone accounts for up to 15% of FC variance, that there is a stationary regime accounting for up to an additional 20% of variance and that this regime can be associated to a stationary FC, that a simple stationary model of FC better explains FC than more complex models, and that there is a large remaining variance (around 65%), which must contain the non-stationarities of FC evidenced in the literature. We also show that homotopic connections across cerebral hemispheres, which are typically improperly estimated, play a strong role in shaping all aspects of FC, notably indirect connections and the topographic organization of brain networks. '),
(86478, 2014, 'plos', 'Comprehensive analyses of ventricular myocyte models identify targets exhibiting favorable rate dependence', 'Cummins, Megan A|Dalal, Pavan J|Bugana, Marco|Severi, Stefano|Sobie, Eric A', 'Department of Pharmacology and Systems Therapeutics, Icahn School of Medicine at Mount Sinai, New York, New York, United States of America.|Department of Pharmacology and Systems Therapeutics, Icahn School of Medicine at Mount Sinai, New York, New York, United States of America.|University of Bologna, Bologna, Italy.|University of Bologna, Bologna, Italy.|Department of Pharmacology and Systems Therapeutics, Icahn School of Medicine at Mount Sinai, New York, New York, United States of America.', 'United States|United States|Italy|Italy|United States', 28, 'Action Potentials|Animals|Arrhythmias, Cardiac|Computational Biology|Computer Simulation|Dogs|Guinea Pigs|Heart|Heart Ventricles|Humans|Linear Models|Models, Biological|Myocytes, Cardiac|Reproducibility of Results|Sodium-Potassium-Exchanging ATPase|Species Specificity|Ventricular Function', 'Journal Article', '10.1371/journal.pcbi.1003543', '24675446', 'Reverse rate dependence is a problematic property of antiarrhythmic drugs that prolong the cardiac action potential (AP). The prolongation caused by reverse rate dependent agents is greater at slow heart rates, resulting in both reduced arrhythmia suppression at fast rates and increased arrhythmia risk at slow rates. The opposite property, forward rate dependence, would theoretically overcome these parallel problems, yet forward rate dependent (FRD) antiarrhythmics remain elusive. Moreover, there is evidence that reverse rate dependence is an intrinsic property of perturbations to the AP. We have addressed the possibility of forward rate dependence by performing a comprehensive analysis of 13 ventricular myocyte models. By simulating populations of myocytes with varying properties and analyzing population results statistically, we simultaneously predicted the rate-dependent effects of changes in multiple model parameters. An average of 40 parameters were tested in each model, and effects on AP duration were assessed at slow (0.2 Hz) and fast (2 Hz) rates. The analysis identified a variety of FRD ionic current perturbations and generated specific predictions regarding their mechanisms. For instance, an increase in L-type calcium current is FRD when this is accompanied by indirect, rate-dependent changes in slow delayed rectifier potassium current. A comparison of predictions across models identified inward rectifier potassium current and the sodium-potassium pump as the two targets most likely to produce FRD AP prolongation. Finally, a statistical analysis of results from the 13 models demonstrated that models displaying minimal rate-dependent changes in AP shape have little capacity for FRD perturbations, whereas models with large shape changes have considerable FRD potential. This can explain differences between species and between ventricular cell types. Overall, this study provides new insights, both specific and general, into the determinants of AP duration rate dependence, and illustrates a strategy for the design of potentially beneficial antiarrhythmic drugs. '),
(86479, 2014, 'plos', 'Within-host bacterial diversity hinders accurate reconstruction of transmission networks from genomic distance data', 'Worby, Colin J|Lipsitch, Marc|Hanage, William P', 'Center for Communicable Disease Dynamics, Department of Epidemiology, Harvard School of Public Health, Boston, Massachusetts, United States of America.|Center for Communicable Disease Dynamics, Department of Epidemiology, Harvard School of Public Health, Boston, Massachusetts, United States of America.|Center for Communicable Disease Dynamics, Department of Epidemiology, Harvard School of Public Health, Boston, Massachusetts, United States of America.', 'United States|United States|United States', 81, 'Area Under Curve|Bacteria|Bacterial Infections|Computational Biology|Computer Simulation|Disease Outbreaks|Entropy|Epidemics|Genetic Variation|Genomics|Genotype|Humans|Mutation|Phylogeny|Polymorphism, Single Nucleotide|Population Density|Population Dynamics|ROC Curve|Staphylococcus aureus|Stochastic Processes', 'Journal Article', '10.1371/journal.pcbi.1003549', '24675511', 'The prospect of using whole genome sequence data to investigate bacterial disease outbreaks has been keenly anticipated in many quarters, and the large-scale collection and sequencing of isolates from cases is becoming increasingly feasible. While sequence data can provide many important insights into disease spread and pathogen adaptation, it remains unclear how successfully they may be used to estimate individual routes of transmission. Several studies have attempted to reconstruct transmission routes using genomic data, however, these have typically relied upon restrictive assumptions, such as a shared topology of the phylogenetic tree and a lack of within-host diversity. In this study, we investigated the potential for bacterial genomic data to inform transmission network reconstruction. We used simulation models to investigate the origins, persistence and onward transmission of genetic diversity, and examined the impact of such diversity on our estimation of the epidemiological relationship between carriers. We used a flexible distance-based metric to provide a weighted transmission network, and used receiver-operating characteristic (ROC) curves and network entropy to assess the accuracy and uncertainty of the inferred structure. Our results suggest that sequencing a single isolate from each case is inadequate in the presence of within-host diversity, and is likely to result in misleading interpretations of transmission dynamics--under many plausible conditions, this may be little better than selecting transmission links at random. Sampling more frequently improves accuracy, but much uncertainty remains, even if all genotypes are observed. While it is possible to discriminate between clusters of carriers, individual transmission routes cannot be resolved by sequence data alone. Our study demonstrates that bacterial genomic distance data alone provide only limited information on person-to-person transmission dynamics.'),
(86480, 2014, 'plos', 'Resolving structural variability in network models and the brain', 'Klimm, Florian|Bassett, Danielle S|Carlson, Jean M|Mucha, Peter J', 'Department of Physics, University of California, Santa Barbara, Santa Barbara, California, United States of America, Institut für Physik, Humboldt-Universität zu Berlin, Berlin, Germany, Department of Mathematics, University of North Carolina, Chapel Hill, Chapel Hill, North Carolina, United States of America.|Department of Physics, University of California, Santa Barbara, Santa Barbara, California, United States of America, Sage Center for the Study of the Mind, University of California, Santa Barbara, Santa Barbara, California, United States of America, Department of Bioengineering, University of Pennsylvania, Philadelphia, Pennsylvannia, United States of America.|Department of Physics, University of California, Santa Barbara, Santa Barbara, California, United States of America.|Department of Mathematics, University of North Carolina, Chapel Hill, Chapel Hill, North Carolina, United States of America, Department of Applied Physical Sciences, University of North Carolina, Chapel Hill, Chapel Hill, North Carolina, United States of America.', 'Germany|United States|United States|United States', 58, 'Algorithms|Brain|Brain Mapping|Cerebral Cortex|Cluster Analysis|Computational Biology|Fractals|Healthy Volunteers|Humans|Models, Neurological|Models, Statistical|Nerve Net|Neural Pathways|Probability|Software', 'Journal Article', '10.1371/journal.pcbi.1003491', '24675546', 'Large-scale white matter pathways crisscrossing the cortex create a complex pattern of connectivity that underlies human cognitive function. Generative mechanisms for this architecture have been difficult to identify in part because little is known in general about mechanistic drivers of structured networks. Here we contrast network properties derived from diffusion spectrum imaging data of the human brain with 13 synthetic network models chosen to probe the roles of physical network embedding and temporal network growth. We characterize both the empirical and synthetic networks using familiar graph metrics, but presented here in a more complete statistical form, as scatter plots and distributions, to reveal the full range of variability of each measure across scales in the network. We focus specifically on the degree distribution, degree assortativity, hierarchy, topological Rentian scaling, and topological fractal scaling--in addition to several summary statistics, including the mean clustering coefficient, the shortest path-length, and the network diameter. The models are investigated in a progressive, branching sequence, aimed at capturing different elements thought to be important in the brain, and range from simple random and regular networks, to models that incorporate specific growth rules and constraints. We find that synthetic models that constrain the network nodes to be physically embedded in anatomical brain regions tend to produce distributions that are most similar to the corresponding measurements for the brain. We also find that network models hardcoded to display one network property (e.g., assortativity) do not in general simultaneously display a second (e.g., hierarchy). This relative independence of network properties suggests that multiple neurobiological mechanisms might be at play in the development of human brain network architecture. Together, the network models that we develop and employ provide a potentially useful starting point for the statistical inference of brain network structure from neuroimaging data.'),
(86481, 2014, 'plos', 'MRFalign: protein homology detection through alignment of Markov random fields', 'Ma, Jianzhu|Wang, Sheng|Wang, Zhiyong|Xu, Jinbo', 'Toyota Technological Institute at Chicago, Chicago, Illinois, United States of America.|Toyota Technological Institute at Chicago, Chicago, Illinois, United States of America.|Toyota Technological Institute at Chicago, Chicago, Illinois, United States of America.|Toyota Technological Institute at Chicago, Chicago, Illinois, United States of America.', 'United States|United States|United States|United States', 31, 'Algorithms|Artificial Intelligence|Computational Biology|Computer Simulation|Computers|Imaging, Three-Dimensional|Markov Chains|Proteins|Reproducibility of Results|Sequence Alignment|Sequence Homology, Amino Acid', 'Journal Article', '10.1371/journal.pcbi.1003500', '24675572', 'Sequence-based protein homology detection has been extensively studied and so far the most sensitive method is based upon comparison of protein sequence profiles, which are derived from multiple sequence alignment (MSA) of sequence homologs in a protein family. A sequence profile is usually represented as a position-specific scoring matrix (PSSM) or an HMM (Hidden Markov Model) and accordingly PSSM-PSSM or HMM-HMM comparison is used for homolog detection. This paper presents a new homology detection method MRFalign, consisting of three key components: 1) a Markov Random Fields (MRF) representation of a protein family, 2) a scoring function measuring similarity of two MRFs, and 3) an efficient ADMM (Alternating Direction Method of Multipliers) algorithm aligning two MRFs. Compared to HMM that can only model very short-range residue correlation, MRFs can model long-range residue interaction pattern and thus, encode information for the global 3D structure of a protein family. Consequently, MRF-MRF comparison for remote homology detection shall be much more sensitive than HMM-HMM or PSSM-PSSM comparison. Experiments confirm that MRFalign outperforms several popular HMM or PSSM-based methods in terms of both alignment accuracy and remote homology detection and that MRFalign works particularly well for mainly beta proteins. For example, tested on the benchmark SCOP40 (8353 proteins) for homology detection, PSSM-PSSM and HMM-HMM succeed on 48% and 52% of proteins, respectively, at superfamily level, and on 15% and 27% of proteins, respectively, at fold level. In contrast, MRFalign succeeds on 57.3% and 42.5% of proteins at superfamily and fold level, respectively. This study implies that long-range residue interaction patterns are very helpful for sequence-based homology detection. The software is available for download at http://raptorx.uchicago.edu/download/. A summary of this paper appears in the proceedings of the RECOMB 2014 conference, April 2-5. '),
(86482, 2014, 'plos', 'An integrated model of multiple-condition ChIP-Seq data reveals predeterminants of Cdx2 binding', 'Mahony, Shaun|Edwards, Matthew D|Mazzoni, Esteban O|Sherwood, Richard I|Kakumanu, Akshay|Morrison, Carolyn A|Wichterle, Hynek|Gifford, David K', 'Center for Eukaryotic Gene Regulation, Department of Biochemistry & Molecular Biology, The Pennsylvania State University, University Park, Pennsylvania, United States of America.|Computer Science and Artificial Intelligence Laboratory, Massachusetts Institute of Technology, Cambridge, Massachusetts, United States of America.|Department of Biology, New York University, New York, New York, United States of America.|Division of Genetics, Department of Medicine, Brigham and Womens Hospital and Harvard Medical School, Boston, Massachusetts, United States of America.|Center for Eukaryotic Gene Regulation, Department of Biochemistry & Molecular Biology, The Pennsylvania State University, University Park, Pennsylvania, United States of America.|Departments of Pathology and Cell Biology, Neurology, and Neuroscience, Center for Motor Neuron Biology and Disease, Columbia Stem Cell Initiative, Columbia University Medical Center, New York, New York, United States of America.|Departments of Pathology and Cell Biology, Neurology, and Neuroscience, Center for Motor Neuron Biology and Disease, Columbia Stem Cell Initiative, Columbia University Medical Center, New York, New York, United States of America.|Computer Science and Artificial Intelligence Laboratory, Massachusetts Institute of Technology, Cambridge, Massachusetts, United States of America.', 'United States|United States|United States|United States|United States|United States|United States|Un', 36, 'Amino Acid Motifs|Animals|Artificial Intelligence|Bayes Theorem|Binding Sites|CDX2 Transcription Factor|Cell Line|Chromatin Immunoprecipitation|Cluster Analysis|Computational Biology|Embryonic Stem Cells|Genome|Homeodomain Proteins|Mice|Protein Binding|Sequence Analysis, DNA', 'Journal Article', '10.1371/journal.pcbi.1003501', '24675637', 'Regulatory proteins can bind to different sets of genomic targets in various cell types or conditions. To reliably characterize such condition-specific regulatory binding we introduce MultiGPS, an integrated machine learning approach for the analysis of multiple related ChIP-seq experiments. MultiGPS is based on a generalized Expectation Maximization framework that shares information across multiple experiments for binding event discovery. We demonstrate that our framework enables the simultaneous modeling of sparse condition-specific binding changes, sequence dependence, and replicate-specific noise sources. MultiGPS encourages consistency in reported binding event locations across multiple-condition ChIP-seq datasets and provides accurate estimation of ChIP enrichment levels at each event. MultiGPSs multi-experiment modeling approach thus provides a reliable platform for detecting differential binding enrichment across experimental conditions. We demonstrate the advantages of MultiGPS with an analysis of Cdx2 binding in three distinct developmental contexts. By accurately characterizing condition-specific Cdx2 binding, MultiGPS enables novel insight into the mechanistic basis of Cdx2 site selectivity. Specifically, the condition-specific Cdx2 sites characterized by MultiGPS are highly associated with pre-existing genomic context, suggesting that such sites are pre-determined by cell-specific regulatory architecture. However, MultiGPS-defined condition-independent sites are not predicted by pre-existing regulatory signals, suggesting that Cdx2 can bind to a subset of locations regardless of genomic environment. A summary of this paper appears in the proceedings of the RECOMB 2014 conference, April 2-5. '),
(86483, 2014, 'plos', 'HapTree: a novel Bayesian framework for single individual polyplotyping using NGS data', 'Berger, Emily|Yorukoglu, Deniz|Peng, Jian|Berger, Bonnie', 'Department of Mathematics, MIT, Cambridge, Massachusetts, United States of America, Computer Science and Artificial Intelligence Laboratory, MIT, Cambridge, Massachusetts, United States of America, Department of Mathematics, UC Berkeley, Berkeley, California, United States of America.|Computer Science and Artificial Intelligence Laboratory, MIT, Cambridge, Massachusetts, United States of America.|Department of Mathematics, MIT, Cambridge, Massachusetts, United States of America, Computer Science and Artificial Intelligence Laboratory, MIT, Cambridge, Massachusetts, United States of America.|Department of Mathematics, MIT, Cambridge, Massachusetts, United States of America, Computer Science and Artificial Intelligence Laboratory, MIT, Cambridge, Massachusetts, United States of America.', 'United States|United States|United States|United States', 38, 'Algorithms|Alleles|Animals|Bayes Theorem|Computational Biology|Epigenesis, Genetic|Fishes|Genes, Fungal|Genome|Genome, Human|Genotype|Haplotypes|High-Throughput Nucleotide Sequencing|Humans|Likelihood Functions|Mutation|Plants|Ploidies|Polymorphism, Single Nucleotide|Probability|Reproducibility of Results', 'Journal Article', '10.1371/journal.pcbi.1003502', '24675685', 'As the more recent next-generation sequencing (NGS) technologies provide longer read sequences, the use of sequencing datasets for complete haplotype phasing is fast becoming a reality, allowing haplotype reconstruction of a single sequenced genome. Nearly all previous haplotype reconstruction studies have focused on diploid genomes and are rarely scalable to genomes with higher ploidy. Yet computational investigations into polyploid genomes carry great importance, impacting plant, yeast and fish genomics, as well as the studies of the evolution of modern-day eukaryotes and (epi)genetic interactions between copies of genes. In this paper, we describe a novel maximum-likelihood estimation framework, HapTree, for polyploid haplotype assembly of an individual genome using NGS read datasets. We evaluate the performance of HapTree on simulated polyploid sequencing read data modeled after Illumina sequencing technologies. For triploid and higher ploidy genomes, we demonstrate that HapTree substantially improves haplotype assembly accuracy and efficiency over the state-of-the-art, moreover, HapTree is the first scalable polyplotyping method for higher ploidy. As a proof of concept, we also test our method on real sequencing data from NA12878 (1000 Genomes Project) and evaluate the quality of assembled haplotypes with respect to trio-based diplotype annotation as the ground truth. The results indicate that HapTree significantly improves the switch accuracy within phased haplotype blocks as compared to existing haplotype assembly methods, while producing comparable minimum error correction (MEC) values. A summary of this paper appears in the proceedings of the RECOMB 2014 conference, April 2-5. '),
(86484, 2014, 'plos', 'Modeling mutual exclusivity of cancer mutations', 'Szczurek, Ewa|Beerenwinkel, Niko', 'Department of Biosystems Science and Engineering, ETH Zurich, Basel, Switzerland, SIB Swiss Institute of Bioinformatics, Basel, Switzerland.|Department of Biosystems Science and Engineering, ETH Zurich, Basel, Switzerland, SIB Swiss Institute of Bioinformatics, Basel, Switzerland.', 'Switzerland|Switzerland', 47, 'Algorithms|Brain Neoplasms|Computational Biology|Computer Simulation|Databases, Genetic|False Positive Reactions|Genome, Human|Genomics|Glioblastoma|Humans|Models, Statistical|Mutation|Probability', 'Journal Article', '10.1371/journal.pcbi.1003503', '24675718', 'In large collections of tumor samples, it has been observed that sets of genes that are commonly involved in the same cancer pathways tend not to occur mutated together in the same patient. Such gene sets form mutually exclusive patterns of gene alterations in cancer genomic data. Computational approaches that detect mutually exclusive gene sets, rank and test candidate alteration patterns by rewarding the number of samples the pattern covers and by punishing its impurity, i.e., additional alterations that violate strict mutual exclusivity. However, the extant approaches do not account for possible observation errors. In practice, false negatives and especially false positives can severely bias evaluation and ranking of alteration patterns. To address these limitations, we develop a fully probabilistic, generative model of mutual exclusivity, explicitly taking coverage, impurity, as well as error rates into account, and devise efficient algorithms for parameter estimation and pattern ranking. Based on this model, we derive a statistical test of mutual exclusivity by comparing its likelihood to the null model that assumes independent gene alterations. Using extensive simulations, the new test is shown to be more powerful than a permutation test applied previously. When applied to detect mutual exclusivity patterns in glioblastoma and in pan-cancer data from twelve tumor types, we identify several significant patterns that are biologically relevant, most of which would not be detected by previous approaches. Our statistical modeling framework of mutual exclusivity provides increased flexibility and power to detect cancer pathways from genomic alteration data in the presence of noise. A summary of this paper appears in the proceedings of the RECOMB 2014 conference, April 2-5. '),
(86485, 2014, 'plos', 'Ten simple rules for effective computational research', 'Osborne, James M|Bernabeu, Miguel O|Bruna, Maria|Calderhead, Ben|Cooper, Jonathan|Dalchau, Neil|Dunn, Sara-Jane|Fletcher, Alexander G|Freeman, Robin|Groen, Derek|Knapp, Bernhard|McInerny, Greg J|Mirams, Gary R|Pitt-Francis, Joe|Sengupta, Biswa|Wright, David W|Yates, Christian A|Gavaghan, David J|Emmott, Stephen|Deane, Charlotte', 'Computational Biology Group, Department of Computer Science, University of Oxford, Wolfson Building, Oxford, United Kingdom, Computational Science Laboratory, Microsoft Research, Cambridge, United Kingdom.|CoMPLEX, Mathematical and Physical Sciences, University College London, Physics Building, London, United Kingdom, Centre for Computational Science, Department of Chemistry, University College London, London, United Kingdom.|Computational Biology Group, Department of Computer Science, University of Oxford, Wolfson Building, Oxford, United Kingdom, Computational Science Laboratory, Microsoft Research, Cambridge, United Kingdom.|CoMPLEX, Mathematical and Physical Sciences, University College London, Physics Building, London, United Kingdom.|Computational Biology Group, Department of Computer Science, University of Oxford, Wolfson Building, Oxford, United Kingdom.|Computational Science Laboratory, Microsoft Research, Cambridge, United Kingdom.|Computational Science Laboratory, Microsoft Research, Cambridge, United Kingdom.|Wolfson Centre for Mathematical Biology, Mathematical Institute, University of Oxford, Andrew Wiles Building, Radcliffe Observatory Quarter, Oxford, United Kingdom.|Computational Science Laboratory, Microsoft Research, Cambridge, United Kingdom, CoMPLEX, Mathematical and Physical Sciences, University College London, Physics Building, London, United Kingdom.|Centre for Computational Science, Department of Chemistry, University College London, London, United Kingdom.|Department of Statistics, University of Oxford, Oxford, United Kingdom.|Computational Biology Group, Department of Computer Science, University of Oxford, Wolfson Building, Oxford, United Kingdom, Computational Science Laboratory, Microsoft Research, Cambridge, United Kingdom.|Computational Biology Group, Department of Computer Science, University of Oxford, Wolfson Building, Oxford, United Kingdom.|Computational Biology Group, Department of Computer Science, University of Oxford, Wolfson Building, Oxford, United Kingdom.|The Wellcome Trust Centre for Neuroimaging, Institute of Neurology, University College London, London, United Kingdom.|CoMPLEX, Mathematical and Physical Sciences, University College London, Physics Building, London, United Kingdom, Centre for Computational Science, Department of Chemistry, University College London, London, United Kingdom.|Wolfson Centre for Mathematical Biology, Mathematical Institute, University of Oxford, Andrew Wiles Building, Radcliffe Observatory Quarter, Oxford, United Kingdom.|Computational Biology Group, Department of Computer Science, University of Oxford, Wolfson Building, Oxford, United Kingdom.|Computational Science Laboratory, Microsoft Research, Cambridge, 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, 'Computational Biology|Computer Simulation|Computers|Models, Statistical|Software', 'Editorial', '10.1371/journal.pcbi.1003506', '24675742', '-');
INSERT INTO `papers` (`id`, `ano`, `journal`, `titulo`, `autores`, `afiliacao`, `pais`, `citacoes`, `palavra_chave`, `categorias`, `doi`, `pubmed`, `abstract`) VALUES
(86486, 2014, 'plos', 'Investigation of inflammation and tissue patterning in the gut using a Spatially Explicit General-purpose Model of Enteric Tissue (SEGMEnT)', 'Cockrell, Chase|Christley, Scott|An, Gary', 'Department of Surgery, University of Chicago, Chicago, Illinois, United States of America.|Department of Surgery, University of Chicago, Chicago, Illinois, United States of America.|Department of Surgery, University of Chicago, Chicago, Illinois, United States of America.', 'United States|United States|United States', 0, 'Animals|Bone Morphogenetic Proteins|Computational Biology|Computer Simulation|Enterocytes|Gastrointestinal Tract|Humans|Inflammation|Intestinal Mucosa|Phosphatidylinositol 3-Kinases|Reperfusion Injury|Software', 'Journal Article', '10.1371/journal.pcbi.1003507', '24675765', 'The mucosa of the intestinal tract represents a finely tuned system where tissue structure strongly influences, and is turn influenced by, its function as both an absorptive surface and a defensive barrier. Mucosal architecture and histology plays a key role in the diagnosis, characterization and pathophysiology of a host of gastrointestinal diseases. Inflammation is a significant factor in the pathogenesis in many gastrointestinal diseases, and is perhaps the most clinically significant control factor governing the maintenance of the mucosal architecture by morphogenic pathways. We propose that appropriate characterization of the role of inflammation as a controller of enteric mucosal tissue patterning requires understanding the underlying cellular and molecular dynamics that determine the epithelial crypt-villus architecture across a range of conditions from health to disease. Towards this end we have developed the Spatially Explicit General-purpose Model of Enteric Tissue (SEGMEnT) to dynamically represent existing knowledge of the behavior of enteric epithelial tissue as influenced by inflammation with the ability to generate a variety of pathophysiological processes within a common platform and from a common knowledge base. In addition to reproducing healthy ileal mucosal dynamics as well as a series of morphogen knock-out/inhibition experiments, SEGMEnT provides insight into a range of clinically relevant cellular-molecular mechanisms, such as a putative role for Phosphotase and tensin homolog/phosphoinositide 3-kinase (PTEN/PI3K) as a key point of crosstalk between inflammation and morphogenesis, the protective role of enterocyte sloughing in enteric ischemia-reperfusion and chronic low level inflammation as a driver for colonic metaplasia. These results suggest that SEGMEnT can serve as an integrating platform for the study of inflammation in gastrointestinal disease. '),
(86487, 2014, 'plos', 'STDP installs in Winner-Take-All circuits an online approximation to hidden Markov model learning', 'Kappel, David|Nessler, Bernhard|Maass, Wolfgang', 'Institute for Theoretical Computer Science, Graz University of Technology, Graz, Austria.|Institute for Theoretical Computer Science, Graz University of Technology, Graz, Austria.|Institute for Theoretical Computer Science, Graz University of Technology, Graz, Austria.', 'Austria|Austria|Austria', 54, 'Bayes Theorem|Cerebral Cortex|Computer Simulation|Excitatory Postsynaptic Potentials|Humans|Language|Learning|Markov Chains|Models, Statistical|Nerve Net|Neuronal Plasticity|Neurons|Probability|Pyramidal Cells|Reward|Synapses', 'Journal Article', '10.1371/journal.pcbi.1003511', '24675787', 'In order to cross a street without being run over, we need to be able to extract very fast hidden causes of dynamically changing multi-modal sensory stimuli, and to predict their future evolution. We show here that a generic cortical microcircuit motif, pyramidal cells with lateral excitation and inhibition, provides the basis for this difficult but all-important information processing capability. This capability emerges in the presence of noise automatically through effects of STDP on connections between pyramidal cells in Winner-Take-All circuits with lateral excitation. In fact, one can show that these motifs endow cortical microcircuits with functional properties of a hidden Markov model, a generic model for solving such tasks through probabilistic inference. Whereas in engineering applications this model is adapted to specific tasks through offline learning, we show here that a major portion of the functionality of hidden Markov models arises already from online applications of STDP, without any supervision or rewards. We demonstrate the emergent computing capabilities of the model through several computer simulations. The full power of hidden Markov model learning can be attained through reward-gated STDP. This is due to the fact that these mechanisms enable a rejection sampling approximation to theoretically optimal learning. We investigate the possible performance gain that can be achieved with this more accurate learning method for an artificial grammar task. '),
(86488, 2014, 'plos', 'Viral quasispecies assembly via maximal clique enumeration', 'Töpfer, Armin|Marschall, Tobias|Bull, Rowena A|Luciani, Fabio|Schönhuth, Alexander|Beerenwinkel, Niko', 'Department of Biosystems Science and Engineering, ETH Zurich, Basel, Switzerland, SIB Swiss Institute of Bioinformatics, Basel, Switzerland.|Centrum Wiskunde & Informatica, Amsterdam, The Netherlands.|Inflammation and Infection Research Centre, School of Medical Sciences, UNSW, Sydney, Australia.|Inflammation and Infection Research Centre, School of Medical Sciences, UNSW, Sydney, Australia.|Centrum Wiskunde & Informatica, Amsterdam, The Netherlands.|Department of Biosystems Science and Engineering, ETH Zurich, Basel, Switzerland, SIB Swiss Institute of Bioinformatics, Basel, Switzerland.', 'Switzerland|Netherlands|Australia|Australia|Netherlands|Switzerland', 39, 'CD8-Positive T-Lymphocytes|Computational Biology|Gene Deletion|Genetic Variation|Genome, Viral|Haplotypes|Hepacivirus|High-Throughput Nucleotide Sequencing|Humans|Models, Statistical|Mutation|Probability|Sequence Alignment|Sequence Analysis, DNA|Software|Viruses', 'Journal Article', '10.1371/journal.pcbi.1003515', '24675810', 'Virus populations can display high genetic diversity within individual hosts. The intra-host collection of viral haplotypes, called viral quasispecies, is an important determinant of virulence, pathogenesis, and treatment outcome. We present HaploClique, a computational approach to reconstruct the structure of a viral quasispecies from next-generation sequencing data as obtained from bulk sequencing of mixed virus samples. We develop a statistical model for paired-end reads accounting for mutations, insertions, and deletions. Using an iterative maximal clique enumeration approach, read pairs are assembled into haplotypes of increasing length, eventually enabling global haplotype assembly. The performance of our quasispecies assembly method is assessed on simulated data for varying population characteristics and sequencing technology parameters. Owing to its paired-end handling, HaploClique compares favorably to state-of-the-art haplotype inference methods. It can reconstruct error-free full-length haplotypes from low coverage samples and detect large insertions and deletions at low frequencies. We applied HaploClique to sequencing data derived from a clinical hepatitis C virus population of an infected patient and discovered a novel deletion of length 357±167 bp that was validated by two independent long-read sequencing experiments. HaploClique is available at https://github.com/armintoepfer/haploclique. A summary of this paper appears in the proceedings of the RECOMB 2014 conference, April 2-5. '),
(86489, 2014, 'plos', 'Crossing borders for science', 'Schultheiss, Sebastian J|Yang, Joshua SungWoo|Iwasaki, Wataru|Lin, Shu-Hsi|Jean, Angela|Michaut, Magali', 'Computomics Molecular Data Analysis, Tuebingen, Germany.|Department of Physiology, Laboratory of System Medicine, School of Medicine, Ajou University, Suwon, Republic of Korea.|Atmosphere and Ocean Research Institute, University of Tokyo, Kashiwa, Chiba, Japan.|Biodiversity Research Center, Academia Sinica, Taipei, Taiwan.|School of Medicine, University of Queensland, Brisbane, Queensland, Australia.|Computational Cancer Biology, Netherlands Cancer Institute, Amsterdam, Netherlands.', 'Germany|-|Japan|-|Australia|Netherlands', 0, 'Communication|Computational Biology|Humans|International Cooperation|Science|Societies, Scientific|Students', 'Journal Article', '10.1371/journal.pcbi.1003519', '24675824', 'Exchanging ideas with like-minded, enthusiastic people interested in the same topic is crucial for the advancement of a scientists career. Several Regional Student Groups (RSGs) of the International Society for Computational Biology (ISCB) Student Council have cooperated in the last six years to organize scientific workshops and conferences. With motivated students, it is possible to create a memorable event for fellow scientists, in doing so, the organizers gain valuable experiences. While collaborating across borders and time zones can be difficult, feedback from event organizers was always positive. When limited resources are juxtaposed with great ideas and a network of contacts, the outcome is always an amazing experience, despite organizers being separated geographically across different countries. '),
(86490, 2014, 'plos', 'Global quantitative modeling of chromatin factor interactions', 'Zhou, Jian|Troyanskaya, Olga G', 'Lewis-Sigler Institute for Integrative Genomics, Princeton University, Princeton, New Jersey, United States of America, Graduate Program in Quantitative and Computational Biology, Princeton University, Princeton, New Jersey, United States of America.|Lewis-Sigler Institute for Integrative Genomics, Princeton University, Princeton, New Jersey, United States of America, Department of Computer Science, Princeton University, Princeton, New Jersey, United States of America.', 'Jersey|Jersey', 21, 'Algorithms|Animals|Area Under Curve|Chromatin|Computational Biology|Drosophila melanogaster|Entropy|Gene Expression Regulation|Histones|Models, Statistical|Normal Distribution|Probability|Reproducibility of Results|Systems Biology|Transcription Factors|Transcription, Genetic', 'Journal Article', '10.1371/journal.pcbi.1003525', '24675896', 'Chromatin is the driver of gene regulation, yet understanding the molecular interactions underlying chromatin factor combinatorial patterns (or the chromatin codes) remains a fundamental challenge in chromatin biology. Here we developed a global modeling framework that leverages chromatin profiling data to produce a systems-level view of the macromolecular complex of chromatin. Our model ultilizes maximum entropy modeling with regularization-based structure learning to statistically dissect dependencies between chromatin factors and produce an accurate probability distribution of chromatin code. Our unsupervised quantitative model, trained on genome-wide chromatin profiles of 73 histone marks and chromatin proteins from modENCODE, enabled making various data-driven inferences about chromatin profiles and interactions. We provided a highly accurate predictor of chromatin factor pairwise interactions validated by known experimental evidence, and for the first time enabled higher-order interaction prediction. Our predictions can thus help guide future experimental studies. The model can also serve as an inference engine for predicting unknown chromatin profiles--we demonstrated that with this approach we can leverage data from well-characterized cell types to help understand less-studied cell type or conditions.'),
(86491, 2014, 'plos', 'Neuronal spike timing adaptation described with a fractional leaky integrate-and-fire model', 'Teka, Wondimu|Marinov, Toma M|Santamaria, Fidel', 'UTSA Neurosciences Institute, The University of Texas at San Antonio, San Antonio, Texas, United States of America.|UTSA Neurosciences Institute, The University of Texas at San Antonio, San Antonio, Texas, United States of America.|UTSA Neurosciences Institute, The University of Texas at San Antonio, San Antonio, Texas, United States of America.', 'United States|United States|United States', 45, 'Action Potentials|Adaptation, Physiological|Algorithms|Animals|Biophysics|Computational Biology|Computer Simulation|Humans|Markov Chains|Membrane Potentials|Memory|Models, Neurological|Models, Statistical|Neurons|Pyramidal Cells|Rats', 'Journal Article', '10.1371/journal.pcbi.1003526', '24675903', 'The voltage trace of neuronal activities can follow multiple timescale dynamics that arise from correlated membrane conductances. Such processes can result in power-law behavior in which the membrane voltage cannot be characterized with a single time constant. The emergent effect of these membrane correlations is a non-Markovian process that can be modeled with a fractional derivative. A fractional derivative is a non-local process in which the value of the variable is determined by integrating a temporal weighted voltage trace, also called the memory trace. Here we developed and analyzed a fractional leaky integrate-and-fire model in which the exponent of the fractional derivative can vary from 0 to 1, with 1 representing the normal derivative. As the exponent of the fractional derivative decreases, the weights of the voltage trace increase. Thus, the value of the voltage is increasingly correlated with the trajectory of the voltage in the past. By varying only the fractional exponent, our model can reproduce upward and downward spike adaptations found experimentally in neocortical pyramidal cells and tectal neurons in vitro. The model also produces spikes with longer first-spike latency and high inter-spike variability with power-law distribution. We further analyze spike adaptation and the responses to noisy and oscillatory input. The fractional model generates reliable spike patterns in response to noisy input. Overall, the spiking activity of the fractional leaky integrate-and-fire model deviates from the spiking activity of the Markovian model and reflects the temporal accumulated intrinsic membrane dynamics that affect the response of the neuron to external stimulation. '),
(86492, 2014, 'plos', 'A discrete model of Drosophila eggshell patterning reveals cell-autonomous and juxtacrine effects', 'Fauré, Adrien|Vreede, Barbara M I|Sucena, Elio|Chaouiya, Claudine', 'Instituto Gulbenkian de Ciência, Oeiras, Portugal, Yamaguchi University, Faculty of Science, Yoshida, Yamaguchi City, Yamaguchi, Japan.|Instituto Gulbenkian de Ciência, Oeiras, Portugal.|Instituto Gulbenkian de Ciência, Oeiras, Portugal, Universidade de Lisboa, Faculdade de Ciências, Departamento de Biologia Animal, Campo Grande, Lisboa, Portugal.|Instituto Gulbenkian de Ciência, Oeiras, Portugal.', 'Japan|Portugal|Portugal|Portugal', 0, 'Animals|Bone Morphogenetic Proteins|Computational Biology|Computer Simulation|Drosophila melanogaster|Egg Proteins|Epidermal Growth Factor|Epithelium|Gene Expression Regulation, Developmental|Gene Regulatory Networks|Morphogenesis|Mutation|Oocytes|Oogenesis|Signal Transduction|Software|Vitelline Membrane', 'Journal Article', '10.1371/journal.pcbi.1003527', '24675973', 'The Drosophila eggshell constitutes a remarkable system for the study of epithelial patterning, both experimentally and through computational modeling. Dorsal eggshell appendages arise from specific regions in the anterior follicular epithelium that covers the oocyte: two groups of cells expressing broad (roof cells) bordered by rhomboid expressing cells (floor cells). Despite the large number of genes known to participate in defining these domains and the important modeling efforts put into this developmental system, key patterning events still lack a proper mechanistic understanding and/or genetic basis, and the literature appears to conflict on some crucial points. We tackle these issues with an original, discrete framework that considers single-cell models that are integrated to construct epithelial models. We first build a phenomenological model that reproduces wild type follicular epithelial patterns, confirming EGF and BMP signaling input as sufficient to establish the major features of this patterning system within the anterior domain. Importantly, this simple model predicts an instructive juxtacrine signal linking the roof and floor domains. To explore this prediction, we define a mechanistic model that integrates the combined effects of cellular genetic networks, cell communication and network adjustment through developmental events. Moreover, we focus on the anterior competence region, and postulate that early BMP signaling participates with early EGF signaling in its specification. This model accurately simulates wild type pattern formation and is able to reproduce, with unprecedented level of precision and completeness, various published gain-of-function and loss-of-function experiments, including perturbations of the BMP pathway previously seen as conflicting results. The result is a coherent model built upon rules that may be generalized to other epithelia and developmental systems. '),
(86493, 2014, 'plos', 'Identification of new IxcexbaBxcexb1 complexes by an iterative experimental and mathematical modeling approach', 'Konrath, Fabian|Witt, Johannes|Sauter, Thomas|Kulms, Dagmar', 'Institute of Cell Biology and Immunology, University of Stuttgart, Stuttgart, Germany, Institute for System Dynamics, University of Stuttgart, Stuttgart, Germany.|Institute for System Dynamics, University of Stuttgart, Stuttgart, Germany.|Life Sciences Research Unit, University of Luxembourg, Luxembourg, Luxembourg.|Institute of Cell Biology and Immunology, University of Stuttgart, Stuttgart, Germany, Experimental Dermatology, Department of Dermatology, TU-Dresden, Dresden, Germany.', 'Germany|Germany|Luxembourg|Germany', 7, 'Apoptosis|Biochemistry|Cell Line, Tumor|Cell Nucleus|Computational Biology|Cytosol|Humans|I-kappa B Proteins|Models, Theoretical|NF-KappaB Inhibitor alpha|NF-kappa B|Phosphorylation|Signal Transduction|Vanadates', 'Journal Article', '10.1371/journal.pcbi.1003528', '24675998', 'The transcription factor nuclear factor kappa-B (NFxcexbaB) is a key regulator of pro-inflammatory and pro-proliferative processes. Accordingly, uncontrolled NFxcexbaB activity may contribute to the development of severe diseases when the regulatory system is impaired. Since NFxcexbaB can be triggered by a huge variety of inflammatory, pro-and anti-apoptotic stimuli, its activation underlies a complex and tightly regulated signaling network that also includes multi-layered negative feedback mechanisms. Detailed understanding of this complex signaling network is mandatory to identify sensitive parameters that may serve as targets for therapeutic interventions. While many details about canonical and non-canonical NFxcexbaB activation have been investigated, less is known about cellular IxcexbaBxcexb1 pools that may tune the cellular NFxcexbaB levels. IxcexbaBxcexb1 has so far exclusively been described to exist in two different forms within the cell: stably bound to NFxcexbaB or, very transiently, as unbound protein. We created a detailed mathematical model to quantitatively capture and analyze the time-resolved network behavior. By iterative refinement with numerous biological experiments, we yielded a highly identifiable model with superior predictive power which led to the hypothesis of an NFxcexbaB-lacking IxcexbaBxcexb1 complex that contains stabilizing IKK subunits. We provide evidence that other but canonical pathways exist that may affect the cellular IxcexbaBxcexb1 status. This additional IxcexbaBxcexb1:IKKxcexb3 complex revealed may serve as storage for the inhibitor to antagonize undesired NFxcexbaB activation under physiological and pathophysiological conditions. '),
(86494, 2014, 'plos', 'Comparative analysis of the macroscale structural connectivity in the macaque and human brain', 'Goulas, Alexandros|Bastiani, Matteo|Bezgin, Gleb|Uylings, Harry B M|Roebroeck, Alard|Stiers, Peter', 'Department of Neuropsychology and Psychopharmacology, Maastricht University, Maastricht, The Netherlands.|Department of Cognitive Neuroscience, Maastricht University, Maastricht, The Netherlands, Institute of Neuroscience and Medicine - 4, Forschungszentrum Juelich GmbH, Juelich, Germany.|Rotman Research Institute of Baycrest Centre, University of Toronto, Toronto, Ontario, Canada.|Department of Anatomy and Neuroscience, VU University Medical Center, Graduate School Neurosciences Amsterdam, Amsterdam, The Netherlands.|Department of Cognitive Neuroscience, Maastricht University, Maastricht, The Netherlands.|Department of Neuropsychology and Psychopharmacology, Maastricht University, Maastricht, The Netherlands.', 'Netherlands|Germany|Canada|Netherlands|Netherlands|Netherlands', 43, 'Adult|Animals|Anisotropy|Brain|Brain Mapping|Cluster Analysis|Connectome|Diffusion|Diffusion Magnetic Resonance Imaging|Female|Humans|Macaca|Male|Nerve Net|Neural Pathways|Species Specificity', 'Comparative Study', '10.1371/journal.pcbi.1003529', '24676052', 'The macaque brain serves as a model for the human brain, but its suitability is challenged by unique human features, including connectivity reconfigurations, which emerged during primate evolution. We perform a quantitative comparative analysis of the whole brain macroscale structural connectivity of the two species. Our findings suggest that the human and macaque brain as a whole are similarly wired. A region-wise analysis reveals many interspecies similarities of connectivity patterns, but also lack thereof, primarily involving cingulate regions. We unravel a common structural backbone in both species involving a highly overlapping set of regions. This structural backbone, important for mediating information across the brain, seems to constitute a feature of the primate brain persevering evolution. Our findings illustrate novel evolutionary aspects at the macroscale connectivity level and offer a quantitative translational bridge between macaque and human research. '),
(86495, 2014, 'plos', 'Loads bias genetic and signaling switches in synthetic and natural systems', 'Lyons, Samanthe M|Xu, Wenlong|Medford, June|Prasad, Ashok', 'School of Biomedical Engineering, Colorado State University, Fort Collins, Colorado, United States of America.|Chemical and Biological Engineering Department, Colorado State University, Fort Collins, Colorado, United States of America.|Department of Biology, Colorado State University, Fort Collins, Colorado, United States of America.|School of Biomedical Engineering, Colorado State University, Fort Collins, Colorado, United States of America, Chemical and Biological Engineering Department, Colorado State University, Fort Collins, Colorado, United States of America.', 'United States|United States|United States|United States', 0, 'Algorithms|Animals|Bacterial Proteins|Computer Simulation|Feedback, Physiological|Gene Regulatory Networks|Humans|Models, Genetic|Probability|Signal Transduction|Stochastic Processes|Synthetic Biology|ras Proteins', 'Journal Article', '10.1371/journal.pcbi.1003533', '24676102', 'Biological protein interactions networks such as signal transduction or gene transcription networks are often treated as modular, allowing motifs to be analyzed in isolation from the rest of the network. Modularity is also a key assumption in synthetic biology, where it is similarly expected that when network motifs are combined together, they do not lose their essential characteristics. However, the interactions that a network module has with downstream elements change the dynamical equations describing the upstream module and thus may change the dynamic and static properties of the upstream circuit even without explicit feedback. In this work we analyze the behavior of a ubiquitous motif in gene transcription and signal transduction circuits: the switch. We show that adding an additional downstream component to the simple genetic toggle switch changes its dynamical properties by changing the underlying potential energy landscape, and skewing it in favor of the unloaded side, and in some situations adding loads to the genetic switch can also abrogate bistable behavior. We find that an additional positive feedback motif found in naturally occurring toggle switches could tune the potential energy landscape in a desirable manner. We also analyze autocatalytic signal transduction switches and show that a ubiquitous positive feedback switch can lose its switch-like properties when connected to a downstream load. Our analysis underscores the necessity of incorporating the effects of downstream components when understanding the physics of biochemical network motifs, and raises the question as to how these effects are managed in real biological systems. This analysis is particularly important when scaling synthetic networks to more complex organisms. '),
(86496, 2014, 'plos', 'Correction of distortion in flattened representations of the cortical surface allows prediction of V1-V3 functional organization from anatomy', 'Benson, Noah C|Butt, Omar H|Brainard, David H|Aguirre, Geoffrey K', 'Department of Neurology, University of Pennsylvania, Philadelphia, Pennsylvania, United States of America, Department of Psychology, University of Pennsylvania, Philadelphia, Pennsylvania, United States of America.|Department of Neurology, University of Pennsylvania, Philadelphia, Pennsylvania, United States of America.|Department of Psychology, University of Pennsylvania, Philadelphia, Pennsylvania, United States of America.|Department of Neurology, University of Pennsylvania, Philadelphia, Pennsylvania, United States of America.', 'United States|United States|United States|United States', 54, 'Adult|Algorithms|Brain Mapping|Computer Simulation|Female|Humans|Magnetic Resonance Imaging|Male|Models, Neurological|Models, Theoretical|Occipital Lobe|Reproducibility of Results|Surface Properties|Visual Cortex|Visual Fields|Visual Pathways|Young Adult', 'Journal Article', '10.1371/journal.pcbi.1003538', '24676149', 'Several domains of neuroscience offer map-like models that link location on the cortical surface to properties of sensory representation. Within cortical visual areas V1, V2, and V3, algebraic transformations can relate position in the visual field to the retinotopic representation on the flattened cortical sheet. A limit to the practical application of this structure-function model is that the cortex, while topologically a two-dimensional surface, is curved. Flattening of the curved surface to a plane unavoidably introduces local geometric distortions that are not accounted for in idealized models. Here, we show that this limitation is overcome by correcting the geometric distortion induced by cortical flattening. We use a mass-spring-damper simulation to create a registration between functional MRI retinotopic mapping data of visual areas V1, V2, and V3 and an algebraic model of retinotopy. This registration is then applied to the flattened cortical surface anatomy to create an anatomical template that is linked to the algebraic retinotopic model. This registered cortical template can be used to accurately predict the location and retinotopic organization of these early visual areas from cortical anatomy alone. Moreover, we show that prediction accuracy remains when extrapolating beyond the range of data used to inform the model, indicating that the registration reflects the retinotopic organization of visual cortex. We provide code for the mass-spring-damper technique, which has general utility for the registration of cortical structure and function beyond the visual cortex. '),
(86497, 2014, 'plos', 'The genealogical population dynamics of HIV-1 in a large transmission chain: bridging within and among host evolutionary rates', 'Vrancken, Bram|Rambaut, Andrew|Suchard, Marc A|Drummond, Alexei|Baele, Guy|Derdelinckx, Inge|Van Wijngaerden, Eric|Vandamme, Anne-Mieke|Van Laethem, Kristel|Lemey, Philippe', 'Department of Microbiology and Immunology, Rega Institute, KU Leuven, Leuven, Belgium.|Institute of Evolutionary Biology, University of Edinburgh, Edinburgh, United Kingdom, Fogarty International Center, National Institutes of Health, Bethesda, Maryland, United States of America.|Department of Biomathematics, David Geffen School of Medicine at UCLA, University of California, Los Angeles, Los Angeles, California, United States of America, Department of Human Genetics, David Geffen School of Medicine at UCLA, University of California, Los Angeles, Los Angeles, California, United States of America, Department of Biostatistics, UCLA Fielding School of Public Health, University of California, Los Angeles Los Angeles, California, United States of America.|Allan Wilson Centre for Molecular Ecology and Evolution, University of Auckland, Auckland, New Zealand.|Department of Microbiology and Immunology, Rega Institute, KU Leuven, Leuven, Belgium.|University Hospitals Leuven, Leuven, Belgium.|University Hospitals Leuven, Leuven, Belgium.|Department of Microbiology and Immunology, Rega Institute, KU Leuven, Leuven, Belgium, Centro de Malária e Outras Doenças Tropicais Instituto de Higiene e Medicina Tropical and Unidade de Microbiologia, Universidade Nova de Lisboa, Lisboa, Portugal.|Department of Microbiology and Immunology, Rega Institute, KU Leuven, Leuven, Belgium.|Department of Microbiology and Immunology, Rega Institute, KU Leuven, Leuven, Belgium.', 'Belgium|United Kingdom|United States|New Zealand|Belgium|Belgium|Belgium|Belgium|Belgium|Belgium', 49, 'Evolution, Molecular|HIV Infections|HIV-1|Host-Pathogen Interactions|Humans', 'Journal Article', '10.1371/journal.pcbi.1003505', '24699231', 'Transmission lies at the interface of human immunodeficiency virus type 1 (HIV-1) evolution within and among hosts and separates distinct selective pressures that impose differences in both the mode of diversification and the tempo of evolution. In the absence of comprehensive direct comparative analyses of the evolutionary processes at different biological scales, our understanding of how fast within-host HIV-1 evolutionary rates translate to lower rates at the between host level remains incomplete. Here, we address this by analyzing pol and env data from a large HIV-1 subtype C transmission chain for which both the timing and the direction is known for most transmission events. To this purpose, we develop a new transmission model in a Bayesian genealogical inference framework and demonstrate how to constrain the viral evolutionary history to be compatible with the transmission history while simultaneously inferring the within-host evolutionary and population dynamics. We show that accommodating a transmission bottleneck affords the best fit our data, but the sparse within-host HIV-1 sampling prevents accurate quantification of the concomitant loss in genetic diversity. We draw inference under the transmission model to estimate HIV-1 evolutionary rates among epidemiologically-related patients and demonstrate that they lie in between fast intra-host rates and lower rates among epidemiologically unrelated individuals infected with HIV subtype C. Using a new molecular clock approach, we quantify and find support for a lower evolutionary rate along branches that accommodate a transmission event or branches that represent the entire backbone of transmitted lineages in our transmission history. Finally, we recover the rate differences at the different biological scales for both synonymous and non-synonymous substitution rates, which is only compatible with the store and retrieve hypothesis positing that viruses stored early in latently infected cells preferentially transmit or establish new infections upon reactivation. '),
(86498, 2014, 'plos', 'Exploring the conformational transitions of biomolecular systems using a simple two-state anisotropic network model', 'Das, Avisek|Gur, Mert|Cheng, Mary Hongying|Jo, Sunhwan|Bahar, Ivet|Roux, Benoît', 'Department of Biochemistry and Molecular Biology, Gordon Center for Integrative Science, University of Chicago, Chicago, Illinois, United States of America.|Department of Computational & Systems Biology, School of Medicine, University of Pittsburgh, Pittsburgh, Pennsylvania, United States of America.|Department of Computational & Systems Biology, School of Medicine, University of Pittsburgh, Pittsburgh, Pennsylvania, United States of America.|Department of Biochemistry and Molecular Biology, Gordon Center for Integrative Science, University of Chicago, Chicago, Illinois, United States of America.|Department of Computational & Systems Biology, School of Medicine, University of Pittsburgh, Pittsburgh, Pennsylvania, United States of America.|Department of Biochemistry and Molecular Biology, Gordon Center for Integrative Science, University of Chicago, Chicago, Illinois, United States of America.', 'United States|United States|United States|United States|United States|United States', 0, 'Adenylate Kinase|Amino Acid Transport System X-AG|Carrier Proteins|Leucine|Models, Molecular|Protein Conformation|Sarcoplasmic Reticulum|Sarcoplasmic Reticulum Calcium-Transporting ATPases', 'Journal Article', '10.1371/journal.pcbi.1003521', '24699246', 'Biomolecular conformational transitions are essential to biological functions. Most experimental methods report on the long-lived functional states of biomolecules, but information about the transition pathways between these stable states is generally scarce. Such transitions involve short-lived conformational states that are difficult to detect experimentally. For this reason, computational methods are needed to produce plausible hypothetical transition pathways that can then be probed experimentally. Here we propose a simple and computationally efficient method, called ANMPathway, for constructing a physically reasonable pathway between two endpoints of a conformational transition. We adopt a coarse-grained representation of the protein and construct a two-state potential by combining two elastic network models (ENMs) representative of the experimental structures resolved for the endpoints. The two-state potential has a cusp hypersurface in the configuration space where the energies from both the ENMs are equal. We first search for the minimum energy structure on the cusp hypersurface and then treat it as the transition state. The continuous pathway is subsequently constructed by following the steepest descent energy minimization trajectories starting from the transition state on each side of the cusp hypersurface. Application to several systems of broad biological interest such as adenylate kinase, ATP-driven calcium pump SERCA, leucine transporter and glutamate transporter shows that ANMPathway yields results in good agreement with those from other similar methods and with data obtained from all-atom molecular dynamics simulations, in support of the utility of this simple and efficient approach. Notably the method provides experimentally testable predictions, including the formation of non-native contacts during the transition which we were able to detect in two of the systems we studied. An open-access web server has been created to deliver ANMPathway results. '),
(86499, 2014, 'plos', 'Waste not, want not: why rarefying microbiome data is inadmissible', 'McMurdie, Paul J|Holmes, Susan', 'Statistics Department, Stanford University, Stanford, California, United States of America.|Statistics Department, Stanford University, Stanford, California, United States of America.', 'United States|United States', 980, 'Microbiota|Models, Theoretical|Sequence Analysis, DNA|Sequence Analysis, RNA', 'Journal Article', '10.1371/journal.pcbi.1003531', '24699258', 'Current practice in the normalization of microbiome count data is inefficient in the statistical sense. For apparently historical reasons, the common approach is either to use simple proportions (which does not address heteroscedasticity) or to use rarefying of counts, even though both of these approaches are inappropriate for detection of differentially abundant species. Well-established statistical theory is available that simultaneously accounts for library size differences and biological variability using an appropriate mixture model. Moreover, specific implementations for DNA sequencing read count data (based on a Negative Binomial model for instance) are already available in RNA-Seq focused R packages such as edgeR and DESeq. Here we summarize the supporting statistical theory and use simulations and empirical data to demonstrate substantial improvements provided by a relevant mixture model framework over simple proportions or rarefying. We show how both proportions and rarefied counts result in a high rate of false positives in tests for species that are differentially abundant across sample classes. Regarding microbiome sample-wise clustering, we also show that the rarefying procedure often discards samples that can be accurately clustered by alternative methods. We further compare different Negative Binomial methods with a recently-described zero-inflated Gaussian mixture, implemented in a package called metagenomeSeq. We find that metagenomeSeq performs well when there is an adequate number of biological replicates, but it nevertheless tends toward a higher false positive rate. Based on these results and well-established statistical theory, we advocate that investigators avoid rarefying altogether. We have provided microbiome-specific extensions to these tools in the R package, phyloseq. '),
(86500, 2014, 'plos', 'Rates of CTL killing in persistent viral infection in vivo', 'Elemans, Marjet|Florins, Arnaud|Willems, Luc|Asquith, Becca', 'Section of Immunology, Imperial College London, London, United Kingdom.|Molecular and Cellular Biology, Université de Liège and GIGA, Gembloux Agro-Bio Tech, Liège, Belgium.|Molecular and Cellular Biology, Université de Liège and GIGA, Gembloux Agro-Bio Tech, Liège, Belgium.|Section of Immunology, Imperial College London, London, United Kingdom.', 'United Kingdom|Belgium|Belgium|United Kingdom', 20, 'Animals|CD8-Positive T-Lymphocytes|Cattle|Cytotoxicity, Immunologic|Enzootic Bovine Leukosis|HTLV-I Infections|Humans|Models, Biological|Sheep|Sheep Diseases', 'Journal Article', '10.1371/journal.pcbi.1003534', '24699260', 'The CD8+ cytotoxic T lymphocyte (CTL) response is an important defence against viral invasion. Although CTL-mediated cytotoxicity has been widely studied for many years, the rate at which virus-infected cells are killed in vivo by the CTL response is poorly understood. To date the rate of CTL killing in vivo has been estimated for three virus infections but the estimates differ considerably, and killing of HIV-1-infected cells was unexpectedly low. This raises questions about the typical anti-viral capability of CTL and whether CTL killing is abnormally low in HIV-1. We estimated the rate of killing of infected cells by CD8+ T cells in two distinct persistent virus infections: sheep infected with Bovine Leukemia Virus (BLV) and humans infected with Human T Lymphotropic Virus type 1 (HTLV-1) which together with existing data allows us to study a total of five viruses in parallel. Although both BLV and HTLV-1 infection are characterised by large expansions of chronically activated CTL with immediate effector function ex vivo and no evidence of overt immune suppression, our estimates are at the lower end of the reported range. This enables us to put current estimates into perspective and shows that CTL killing of HIV-infected cells may not be atypically low. The estimates at the higher end of the range are obtained in more manipulated systems and may thus represent the potential rather than the realised CTL efficiency. '),
(86501, 2014, 'plos', 'Leadership in moving human groups', 'Boos, Margarete|Pritz, Johannes|Lange, Simon|Belz, Michael', 'Courant Research Centre Evolution of Social Behaviour, University of Göttingen, Göttingen, Germany.|Courant Research Centre Evolution of Social Behaviour, University of Göttingen, Göttingen, Germany.|Economics Department & Centre for Statistics, University of Göttingen, Göttingen, Germany.|Courant Research Centre Evolution of Social Behaviour, University of Göttingen, Göttingen, Germany.', 'Germany|Germany|Germany|Germany', 16, 'Communication|Humans|Leadership|Movement|Social Behavior', 'Journal Article', '10.1371/journal.pcbi.1003541', '24699264', 'How is movement of individuals coordinated as a group? This is a fundamental question of social behaviour, encompassing phenomena such as bird flocking, fish schooling, and the innumerable activities in human groups that require people to synchronise their actions. We have developed an experimental paradigm, the HoneyComb computer-based multi-client game, to empirically investigate human movement coordination and leadership. Using economic games as a model, we set monetary incentives to motivate players on a virtual playfield to reach goals via players movements. We asked whether (I) humans coordinate their movements when information is limited to an individual group members observation of adjacent group member motion, (II) whether an informed group minority can lead an uninformed group majority to the minoritys goal, and if so, (III) how this minority exerts its influence. We showed that in a human group--on the basis of movement alone--a minority can successfully lead a majority. Minorities lead successfully when (a) their members choose similar initial steps towards their goal field and (b) they are among the first in the whole group to make a move. Using our approach, we empirically demonstrate that the rules of swarming behaviour apply to humans. Even complex human behaviour, such as leadership and directed group movement, follow simple rules that are based on visual perception of local movement.'),
(86502, 2014, 'plos', 'Exact hybrid particle/population simulation of rule-based models of biochemical systems', 'Hogg, Justin S|Harris, Leonard A|Stover, Lori J|Nair, Niketh S|Faeder, James R', 'Department of Computational and Systems Biology, University of Pittsburgh School of Medicine, Pittsburgh, Pennsylvania, United States of America.|Department of Computational and Systems Biology, University of Pittsburgh School of Medicine, Pittsburgh, Pennsylvania, United States of America.|Department of Computational and Systems Biology, University of Pittsburgh School of Medicine, Pittsburgh, Pennsylvania, United States of America.|Department of Computational and Systems Biology, University of Pittsburgh School of Medicine, Pittsburgh, Pennsylvania, United States of America.|Department of Computational and Systems Biology, University of Pittsburgh School of Medicine, Pittsburgh, Pennsylvania, United States of America.', 'United States|United States|United States|United States|United States', 25, 'Models, Biological|Models, Chemical|Monte Carlo Method', 'Journal Article', '10.1371/journal.pcbi.1003544', '24699269', 'Detailed modeling and simulation of biochemical systems is complicated by the problem of combinatorial complexity, an explosion in the number of species and reactions due to myriad protein-protein interactions and post-translational modifications. Rule-based modeling overcomes this problem by representing molecules as structured objects and encoding their interactions as pattern-based rules. This greatly simplifies the process of model specification, avoiding the tedious and error prone task of manually enumerating all species and reactions that can potentially exist in a system. From a simulation perspective, rule-based models can be expanded algorithmically into fully-enumerated reaction networks and simulated using a variety of network-based simulation methods, such as ordinary differential equations or Gillespies algorithm, provided that the network is not exceedingly large. Alternatively, rule-based models can be simulated directly using particle-based kinetic Monte Carlo methods. This network-free approach produces exact stochastic trajectories with a computational cost that is independent of network size. However, memory and run time costs increase with the number of particles, limiting the size of system that can be feasibly simulated. Here, we present a hybrid particle/population simulation method that combines the best attributes of both the network-based and network-free approaches. The method takes as input a rule-based model and a user-specified subset of species to treat as population variables rather than as particles. The model is then transformed by a process of partial network expansion into a dynamically equivalent form that can be simulated using a population-adapted network-free simulator. The transformation method has been implemented within the open-source rule-based modeling platform BioNetGen, and resulting hybrid models can be simulated using the particle-based simulator NFsim. Performance tests show that significant memory savings can be achieved using the new approach and a monetary cost analysis provides a practical measure of its utility. '),
(86503, 2014, 'plos', 'Influence of wiring cost on the large-scale architecture of human cortical connectivity', 'Samu, David|Seth, Anil K|Nowotny, Thomas', 'Sussex Neuroscience, CCNR, Informatics, University of Sussex, Falmer, Brighton, United Kingdom.|Sussex Neuroscience, CCNR, Informatics, University of Sussex, Falmer, Brighton, United Kingdom, Sackler Centre for Consciousness Science, Informatics, University of Sussex, Falmer, Brighton, United Kingdom.|Sussex Neuroscience, CCNR, Informatics, University of Sussex, Falmer, Brighton, United Kingdom.', 'United Kingdom|United Kingdom|United Kingdom', 41, 'Cerebral Cortex|Cluster Analysis|Humans|Models, Biological', 'Journal Article', '10.1371/journal.pcbi.1003557', '24699277', 'In the past two decades some fundamental properties of cortical connectivity have been discovered: small-world structure, pronounced hierarchical and modular organisation, and strong core and rich-club structures. A common assumption when interpreting results of this kind is that the observed structural properties are present to enable the brains function. However, the brain is also embedded into the limited space of the skull and its wiring has associated developmental and metabolic costs. These basic physical and economic aspects place separate, often conflicting, constraints on the brains connectivity, which must be characterized in order to understand the true relationship between brain structure and function. To address this challenge, here we ask which, and to what extent, aspects of the structural organisation of the brain are conserved if we preserve specific spatial and topological properties of the brain but otherwise randomise its connectivity. We perform a comparative analysis of a connectivity map of the cortical connectome both on high- and low-resolutions utilising three different types of surrogate networks: spatially unconstrained (random), connection length preserving (spatial), and connection length optimised (reduced) surrogates. We find that unconstrained randomisation markedly diminishes all investigated architectural properties of cortical connectivity. By contrast, spatial and reduced surrogates largely preserve most properties and, interestingly, often more so in the reduced surrogates. Specifically, our results suggest that the cortical network is less tightly integrated than its spatial constraints would allow, but more strongly segregated than its spatial constraints would necessitate. We additionally find that hierarchical organisation and rich-club structure of the cortical connectivity are largely preserved in spatial and reduced surrogates and hence may be partially attributable to cortical wiring constraints. In contrast, the high modularity and strong s-core of the high-resolution cortical network are significantly stronger than in the surrogates, underlining their potential functional relevance in the brain. ');
