INSERT INTO `papers` (`id`, `ano`, `journal`, `titulo`, `autores`, `afiliacao`, `pais`, `citacoes`, `palavra_chave`, `categorias`, `doi`, `pubmed`, `abstract`) VALUES
(87849, 2016, 'plos', 'Stochastic Simulation of Biomolecular Networks in Dynamic Environments', 'Voliotis, Margaritis|Thomas, Philipp|Grima, Ramon|Bowsher, Clive G', 'School of Mathematics, University of Bristol, Bristol, United Kingdom.|Department of Mathematics, Imperial College London, London, United Kingdom.|School of Biological Sciences, University of Edinburgh, Edinburgh, United Kingdom.|School of Mathematics, University of Bristol, Bristol, United Kingdom.', 'United Kingdom|United Kingdom|United Kingdom|United Kingdom', 24, 'Algorithms|Computational Biology|Computer Simulation|Metabolic Networks and Pathways|Models, Biological|Quorum Sensing|Stochastic Processes|Systems Biology', 'Journal Article', '10.1371/journal.pcbi.1004923', '27248512', 'Simulation of biomolecular networks is now indispensable for studying biological systems, from small reaction networks to large ensembles of cells. Here we present a novel approach for stochastic simulation of networks embedded in the dynamic environment of the cell and its surroundings. We thus sample trajectories of the stochastic process described by the chemical master equation with time-varying propensities. A comparative analysis shows that existing approaches can either fail dramatically, or else can impose impractical computational burdens due to numerical integration of reaction propensities, especially when cell ensembles are studied. Here we introduce the Extrande method which, given a simulated time course of dynamic network inputs, provides a conditionally exact and several orders-of-magnitude faster simulation solution. The new approach makes it feasible to demonstrate-using decision-making by a large population of quorum sensing bacteria-that robustness to fluctuations from upstream signaling places strong constraints on the design of networks determining cell fate. Our approach has the potential to significantly advance both understanding of molecular systems biology and design of synthetic circuits.'),
(87850, 2016, 'plos', 'Predicting Allosteric Effects from Orthosteric Binding in Hsp90-Ligand Interactions: Implications for Fragment-Based Drug Design', 'Chandramohan, Arun|Krishnamurthy, Srinath|Larsson, Andreas|Nordlund, Paer|Jansson, Anna|Anand, Ganesh S', 'Department of Biological Sciences, National University of Singapore, Singapore.|Department of Biological Sciences, National University of Singapore, Singapore.|School of Biological Sciences, Nanyang Technological University, Singapore.|School of Biological Sciences, Nanyang Technological University, Singapore.|School of Biological Sciences, Nanyang Technological University, Singapore.|Department of Biological Sciences, National University of Singapore, Singapore.', 'Singapore|Singapore|Singapore|Singapore|Singapore|Singapore', 15, 'Allosteric Site|Binding Sites|Deuterium Exchange Measurement|Drug Design|Enzyme Activation|HSP90 Heat-Shock Proteins|Ligands|Mass Spectrometry|Molecular Docking Simulation|Protein Binding|Protein Conformation|Protein Interaction Mapping|Substrate Specificity', 'Journal Article', '10.1371/journal.pcbi.1004840', '27253209', 'A key question in mapping dynamics of protein-ligand interactions is to distinguish changes at binding sites from those associated with long range conformational changes upon binding at distal sites. This assumes a greater challenge when considering the interactions of low affinity ligands (dissociation constants, KD, in the xcexbcM range or lower). Amide hydrogen deuterium Exchange mass spectrometry (HDXMS) is a robust method that can provide both structural insights and dynamics information on both high affinity and transient protein-ligand interactions. In this study, an application of HDXMS for probing the dynamics of low affinity ligands to proteins is described using the N-terminal ATPase domain of Hsp90. Comparison of Hsp90 dynamics between high affinity natural inhibitors (KD ~ nM) and fragment compounds reveal that HDXMS is highly sensitive in mapping the interactions of both high and low affinity ligands. HDXMS reports on changes that reflect both orthosteric effects and allosteric changes accompanying binding. Orthosteric sites can be identified by overlaying HDXMS onto structural information of protein-ligand complexes. Regions distal to orthosteric sites indicate long range conformational changes with implications for allostery. HDXMS, thus finds powerful utility as a high throughput method for compound library screening to identify binding sites and describe allostery with important implications for fragment-based ligand discovery (FBLD).'),
(87851, 2016, 'plos', 'Non-degradative Ubiquitination of Protein Kinases', 'Ball, K Aurelia|Johnson, Jeffrey R|Lewinski, Mary K|Guatelli, John|Verschueren, Erik|Krogan, Nevan J|Jacobson, Matthew P', 'Pharmaceutical Chemistry, University of California at San Francisco, San Francisco, California, United States of America.|Cellular and Molecular Pharmacology, University of California at San Francisco, San Francisco, California, United States of America.|Division of Infectious Diseases, University of California at San Diego School of Medicine, La Jolla, California, United States of America.|Division of Infectious Diseases, University of California at San Diego School of Medicine, La Jolla, California, United States of America.|Cellular and Molecular Pharmacology, University of California at San Francisco, San Francisco, California, United States of America.|Cellular and Molecular Pharmacology, University of California at San Francisco, San Francisco, California, United States of America.|Pharmaceutical Chemistry, University of California at San Francisco, San Francisco, California, United States of America.', 'United States|United States|United States|United States|United States|United States|United States', 12, 'Binding Sites|Enzyme Activation|HEK293 Cells|Humans|Jurkat Cells|Models, Chemical|Molecular Docking Simulation|Protein Binding|Protein Conformation|Protein Interaction Mapping|Protein Kinases|Substrate Specificity|Ubiquitinated Proteins', 'Journal Article', '10.1371/journal.pcbi.1004898', '27253329', 'Growing evidence supports other regulatory roles for protein ubiquitination in addition to serving as a tag for proteasomal degradation. In contrast to other common post-translational modifications, such as phosphorylation, little is known about how non-degradative ubiquitination modulates protein structure, dynamics, and function. Due to the wealth of knowledge concerning protein kinase structure and regulation, we examined kinase ubiquitination using ubiquitin remnant immunoaffinity enrichment and quantitative mass spectrometry to identify ubiquitinated kinases and the sites of ubiquitination in Jurkat and HEK293 cells. We find that, unlike phosphorylation, ubiquitination most commonly occurs in structured domains, and on the kinase domain, ubiquitination is concentrated in regions known to be important for regulating activity. We hypothesized that ubiquitination, like other post-translational modifications, may alter the conformational equilibrium of the modified protein. We chose one human kinase, ZAP-70, to simulate using molecular dynamics with and without a monoubiquitin modification. In Jurkat cells, ZAP-70 is ubiquitinated at several sites that are not sensitive to proteasome inhibition and thus may have other regulatory roles. Our simulations show that ubiquitination influences the conformational ensemble of ZAP-70 in a site-dependent manner. When monoubiquitinated at K377, near the C-helix, the active conformation of the ZAP-70 C-helix is disrupted. In contrast, when monoubiquitinated at K476, near the kinase hinge region, an active-like ZAP-70 C-helix conformation is stabilized. These results lead to testable hypotheses that ubiquitination directly modulates kinase activity, and that ubiquitination is likely to alter structure, dynamics, and function in other protein classes as well.'),
(87852, 2016, 'plos', 'EGFR Signal-Network Reconstruction Demonstrates Metabolic Crosstalk in EMT', 'Choudhary, Kumari Sonal|Rohatgi, Neha|Halldorsson, Skarphedinn|Briem, Eirikur|Gudjonsson, Thorarinn|Gudmundsson, Steinn|Rolfsson, Ottar', 'Center for Systems Biology, University of Iceland, Reykjavik, Iceland.|Center for Systems Biology, University of Iceland, Reykjavik, Iceland.|Center for Systems Biology, University of Iceland, Reykjavik, Iceland.|Biomedical Center, University of Iceland, Reykjavik, Iceland.|Biomedical Center, University of Iceland, Reykjavik, Iceland.|Center for Systems Biology, University of Iceland, Reykjavik, Iceland.|Center for Systems Biology, University of Iceland, Reykjavik, Iceland.', 'Iceland|Iceland|Iceland|Iceland|Iceland|Iceland|Iceland', 23, 'Cell Line|Computer Simulation|Epithelial Cells|Epithelial-Mesenchymal Transition|ErbB Receptors|Humans|Metabolic Networks and Pathways|Models, Biological|Receptor Cross-Talk|Signal Transduction', 'Journal Article', '10.1371/journal.pcbi.1004924', '27253373', 'Epithelial to mesenchymal transition (EMT) is an important event during development and cancer metastasis. There is limited understanding of the metabolic alterations that give rise to and take place during EMT. Dysregulation of signalling pathways that impact metabolism, including epidermal growth factor receptor (EGFR), are however a hallmark of EMT and metastasis. In this study, we report the investigation into EGFR signalling and metabolic crosstalk of EMT through constraint-based modelling and analysis of the breast epithelial EMT cell model D492 and its mesenchymal counterpart D492M. We built an EGFR signalling network for EMT based on stoichiometric coefficients and constrained the network with gene expression data to build epithelial (EGFR_E) and mesenchymal (EGFR_M) networks. Metabolic alterations arising from differential expression of EGFR genes was derived from a literature review of AKT regulated metabolic genes. Signaling flux differences between EGFR_E and EGFR_M models subsequently allowed metabolism in D492 and D492M cells to be assessed. Higher flux within AKT pathway in the D492 cells compared to D492M suggested higher glycolytic activity in D492 that we confirmed experimentally through measurements of glucose uptake and lactate secretion rates. The signaling genes from the AKT, RAS/MAPK and CaM pathways were predicted to revert D492M to D492 phenotype. Follow-up analysis of EGFR signaling metabolic crosstalk in three additional breast epithelial cell lines highlighted variability in in vitro cell models of EMT. This study shows that the metabolic phenotype may be predicted by in silico analyses of gene expression data of EGFR signaling genes, but this phenomenon is cell-specific and does not follow a simple trend.'),
(87853, 2016, 'plos', 'Program Bytes: Satellite Meetings, SIGs, and AKEs at ISMB 2016', 'Fogg, Christiana N|Kovats, Diane E', 'Freelance Science Writer, Kensington, Maryland, United States of America.|International Society for Computational Biology, Bethesda, Maryland, United States of America.', 'United States|United States', 0, 'Computational Biology|Congresses as Topic|Societies, Medical', 'Journal Article', '10.1371/journal.pcbi.1004944', '27253381', '-'),
(87854, 2016, 'plos', 'Theoretical Insights into the Biophysics of Protein Bi-stability and Evolutionary Switches', 'Sikosek, Tobias|Krobath, Heinrich|Chan, Hue Sun', 'Departments of Biochemistry and Molecular Genetics, University of Toronto, Toronto, Ontario, Canada.|Departments of Biochemistry and Molecular Genetics, University of Toronto, Toronto, Ontario, Canada.|Departments of Biochemistry and Molecular Genetics, University of Toronto, Toronto, Ontario, Canada.', 'Canada|Canada|Canada', 13, 'Computer Simulation|Evolution, Molecular|GTP-Binding Proteins|Genes, Switch|Genetic Variation|Genomic Instability|Models, Chemical|Models, Genetic|Models, Molecular|Protein Conformation|Protein Folding|Sequence Analysis, Protein', 'Journal Article', '10.1371/journal.pcbi.1004960', '27253392', 'Deciphering the effects of nonsynonymous mutations on protein structure is central to many areas of biomedical research and is of fundamental importance to the study of molecular evolution. Much of the investigation of protein evolution has focused on mutations that leave a proteins folded structure essentially unchanged. However, to evolve novel folds of proteins, mutations that lead to large conformational modifications have to be involved. Unraveling the basic biophysics of such mutations is a challenge to theory, especially when only one or two amino acid substitutions cause a large-scale conformational switch. Among the few such mutational switches identified experimentally, the one between the GA all-xcexb1 and GB xcexb1+xcexb2 folds is extensively characterized, but all-atom simulations using fully transferrable potentials have not been able to account for this striking switching behavior. Here we introduce an explicit-chain model that combines structure-based native biases for multiple alternative structures with a general physical atomic force field, and apply this construct to twelve mutants spanning the sequence variation between GA and GB. In agreement with experiment, we observe conformational switching from GA to GB upon a single L45Y substitution in the GA98 mutant. In line with the latent evolutionary potential concept, our model shows a gradual sequence-dependent change in fold preference in the mutants before this switch. Our analysis also indicates that a sharp GA/GB switch may arise from the orientation dependence of aromatic xcfx80-interactions. These findings provide physical insights toward rationalizing, predicting and designing evolutionary conformational switches.'),
(87855, 2016, 'plos', 'Allostery: An Overview of Its History, Concepts, Methods, and Applications', 'Liu, Jin|Nussinov, Ruth', 'Department of Pharmaceutical Sciences, University of North Texas Systems College of Pharmacy, University of North Texas Health Science Center, Fort Worth, Texas, United States of America.|Cancer and Inflammation Program, Leidos Biomedical Research, Inc., Frederick National Laboratory for Cancer Research, National Cancer Institute, Frederick, Maryland, United States of America.', 'United States|United States', 70, 'Allosteric Regulation|Biochemistry|Biomedical Research|History, 20th Century|History, 21st Century|Humans|Models, Biological', 'Editorial', '10.1371/journal.pcbi.1004966', '27253437', 'The concept of allostery has evolved in the past century. In this Editorial, we briefly overview the history of allostery, from the pre-allostery nomenclature era starting with the Bohr effect (1904) to the birth of allostery by Monod and Jacob (1961). We describe the evolution of the allostery concept, from a conformational change in a two-state model (1965, 1966) to dynamic allostery in the ensemble model (1999), from multi-subunit (1965) proteins to all proteins (2004). We highlight the current available methods to study allostery and their applications in studies of conformational mechanisms, disease, and allosteric drug discovery. We outline the challenges and future directions that we foresee. Altogether, this Editorial narrates the history of this fundamental concept in the life sciences, its significance, methodologies to detect and predict it, and its application in a broad range of living systems.'),
(87856, 2016, 'plos', 'Evolution-Based Functional Decomposition of Proteins', 'Rivoire, Olivier|Reynolds, Kimberly A|Ranganathan, Rama', 'Laboratoire Interdisciplinaire de Physique, CNRS and Université Grenoble Alpes, Grenoble, France.|The Green Center for Systems Biology, and Department of Biophysics, University of Texas Southwestern Medical Center, Dallas, Texas, United States of America.|The Green Center for Systems Biology, and Departments of Biophysics and Pharmacology, University of Texas Southwestern Medical Center, Dallas, Texas, United States of America.', 'France|United States|United States', 0, 'Algorithms|Binding Sites|Computer Simulation|Evolution, Molecular|GTP-Binding Proteins|Models, Chemical|Molecular Docking Simulation|Protein Binding|Sequence Alignment|Sequence Analysis, Protein', 'Journal Article', '10.1371/journal.pcbi.1004817', '27254668', 'The essential biological properties of proteins-folding, biochemical activities, and the capacity to adapt-arise from the global pattern of interactions between amino acid residues. The statistical coupling analysis (SCA) is an approach to defining this pattern that involves the study of amino acid coevolution in an ensemble of sequences comprising a protein family. This approach indicates a functional architecture within proteins in which the basic units are coupled networks of amino acids termed sectors. This evolution-based decomposition has potential for new understandings of the structural basis for protein function. To facilitate its usage, we present here the principles and practice of the SCA and introduce new methods for sector analysis in a python-based software package (pySCA). We show that the pattern of amino acid interactions within sectors is linked to the divergence of functional lineages in a multiple sequence alignment-a model for how sector properties might be differentially tuned in members of a protein family. This work provides new tools for studying proteins and for generally testing the concept of sectors as the principal units of function and adaptive variation.'),
(87857, 2016, 'plos', 'Implementation Considerations, Not Topological Differences, Are the Main Determinants of Noise Suppression Properties in Feedback and Incoherent Feedforward Circuits', 'Buzi, Gentian|Khammash, Mustafa', 'Control Theory and Systems Biology, Department of Biosystems Science and Engineering, ETH Zurich, Zurich, Switzerland.|Control Theory and Systems Biology, Department of Biosystems Science and Engineering, ETH Zurich, Zurich, Switzerland.', 'Switzerland|Switzerland', 0, 'Animals|Cell Physiological Phenomena|Computer Simulation|Feedback, Physiological|Humans|Models, Biological|Models, Statistical|Proteome|Signal Transduction|Signal-To-Noise Ratio', 'Journal Article', '10.1371/journal.pcbi.1004958', '27257684', 'Biological systems use a variety of mechanisms to deal with the uncertain nature of their external and internal environments. Two of the most common motifs employed for this purpose are the incoherent feedforward (IFF) and feedback (FB) topologies. Many theoretical and experimental studies suggest that these circuits play very different roles in providing robustness to uncertainty in the cellular environment. Here, we use a control theoretic approach to analyze two common FB and IFF architectures that make use of an intermediary species to achieve regulation. We show the equivalence of both circuits topologies in suppressing static cell-to-cell variations. While both circuits can suppress variations due to input noise, they are ineffective in suppressing inherent chemical reaction stochasticity. Indeed, these circuits realize comparable improvements limited to a modest 25% variance reduction in best case scenarios. Such limitations are attributed to the use of intermediary species in regulation, and as such, they persist even for circuit architectures that combine both IFF and FB features. Intriguingly, while the FB circuits are better suited in dealing with dynamic input variability, the most significant difference between the two topologies lies not in the structural features of the circuits, but in their practical implementation considerations.'),
(87858, 2016, 'plos', 'The Role of Adaptation in Bacterial Speed Races', 'Wong-Ng, Jérôme|Melbinger, Anna|Celani, Antonio|Vergassola, Massimo', 'University of California San Diego, Department of Physics, La Jolla, California, United States of America.|University of California San Diego, Department of Physics, La Jolla, California, United States of America.|The Abdus Salam International Centre for Theoretical Physics (ICTP), Trieste, Italy.|University of California San Diego, Department of Physics, La Jolla, California, United States of America.', 'United States|United States|Italy|United States', 0, 'Adaptation, Physiological|Aspartic Acid|Chemotactic Factors|Chemotaxis|Computational Biology|Escherichia coli|Models, Biological|Serine', 'Journal Article', '10.1371/journal.pcbi.1004974', '27257812', 'Evolution of biological sensory systems is driven by the need for efficient responses to environmental stimuli. A paradigm among prokaryotes is the chemotaxis system, which allows bacteria to navigate gradients of chemoattractants by biasing their run-and-tumble motion. A notable feature of chemotaxis is adaptation: after the application of a step stimulus, the bacterial running time relaxes to its pre-stimulus level. The response to the amino acid aspartate is precisely adapted whilst the response to serine is not, in spite of the same pathway processing the signals preferentially sensed by the two receptors Tar and Tsr, respectively. While the chemotaxis pathway in E. coli is well characterized, the role of adaptation, its functional significance and the ecological conditions where chemotaxis is selected, are largely unknown. Here, we investigate the role of adaptation in the climbing of gradients by E. coli. We first present theoretical arguments that highlight the mechanisms that control the efficiency of the chemotactic up-gradient motion. We discuss then the limitations of linear response theory, which motivate our subsequent experimental investigation of E. coli speed races in gradients of aspartate, serine and combinations thereof. By using microfluidic techniques, we engineer controlled gradients and demonstrate that bacterial fronts progress faster in equal-magnitude gradients of serine than aspartate. The effect is observed over an extended range of concentrations and is not due to differences in swimming velocities. We then show that adding a constant background of serine to gradients of aspartate breaks the adaptation to aspartate, which results in a sped-up progression of the fronts and directly illustrate the role of adaptation in chemotactic gradient-climbing.'),
(87859, 2016, 'plos', 'An Introduction to Programming for Bioscientists: A Python-Based Primer', 'Ekmekci, Berk|McAnany, Charles E|Mura, Cameron', 'Department of Chemistry, University of Virginia, Charlottesville, Virginia, United States of America.|Department of Chemistry, University of Virginia, Charlottesville, Virginia, United States of America.|Department of Chemistry, University of Virginia, Charlottesville, Virginia, United States of America.', 'United States|United States|United States', 0, 'Algorithms|Computational Biology|Computer Simulation|Models, Biological|Programming Languages|Semantics|Software', 'Journal Article', '10.1371/journal.pcbi.1004867', '27271528', 'Computing has revolutionized the biological sciences over the past several decades, such that virtually all contemporary research in molecular biology, biochemistry, and other biosciences utilizes computer programs. The computational advances have come on many fronts, spurred by fundamental developments in hardware, software, and algorithms. These advances have influenced, and even engendered, a phenomenal array of bioscience fields, including molecular evolution and bioinformatics, genome-, proteome-, transcriptome- and metabolome-wide experimental studies, structural genomics, and atomistic simulations of cellular-scale molecular assemblies as large as ribosomes and intact viruses. In short, much of post-genomic biology is increasingly becoming a form of computational biology. The ability to design and write computer programs is among the most indispensable skills that a modern researcher can cultivate. Python has become a popular programming language in the biosciences, largely because (i) its straightforward semantics and clean syntax make it a readily accessible first language, (ii) it is expressive and well-suited to object-oriented programming, as well as other modern paradigms, and (iii) the many available libraries and third-party toolkits extend the functionality of the core language into virtually every biological domain (sequence and structure analyses, phylogenomics, workflow management systems, etc.). This primer offers a basic introduction to coding, via Python, and it includes concrete examples and exercises to illustrate the languages usage and capabilities, the main text culminates with a final project in structural bioinformatics. A suite of Supplemental Chapters is also provided. Starting with basic concepts, such as that of a variable, the Chapters methodically advance the reader to the point of writing a graphical user interface to compute the Hamming distance between two DNA sequences.'),
(87860, 2016, 'plos', 'Towards Identifying and Reducing the Bias of Disease Information Extracted from Search Engine Data', 'Huang, Da-Cang|Wang, Jin-Feng|Huang, Ji-Xia|Sui, Daniel Z|Zhang, Hong-Yan|Hu, Mao-Gui|Xu, Cheng-Dong', 'State Key Laboratory of Resources and Environmental Information System, Institute of Geographic Science and Natural Resource Research, Chinese Academy of Sciences, Beijing, China.|State Key Laboratory of Resources and Environmental Information System, Institute of Geographic Science and Natural Resource Research, Chinese Academy of Sciences, Beijing, China.|College of Forestry, Beijing Forestry University, Beijing, China.|Department of Geography, The Ohio State University, Columbus, Ohio, United States of America.|School of Geographical Science, Northeast Normal University, Changchun, China.|State Key Laboratory of Resources and Environmental Information System, Institute of Geographic Science and Natural Resource Research, Chinese Academy of Sciences, Beijing, China.|State Key Laboratory of Resources and Environmental Information System, Institute of Geographic Science and Natural Resource Research, Chinese Academy of Sciences, Beijing, China.', 'China|China|China|United States|China|China|China', 0, 'Bias|Clinical Trials Data Monitoring Committees|Data Interpretation, Statistical|Databases, Factual|Hand, Foot and Mouth Disease|Humans|Prevalence|Reproducibility of Results|Risk Assessment|Search Engine|Sensitivity and Specificity|Sentinel Surveillance', 'Journal Article', '10.1371/journal.pcbi.1004876', '27271698', 'The estimation of disease prevalence in online search engine data (e.g., Google Flu Trends (GFT)) has received a considerable amount of scholarly and public attention in recent years. While the utility of search engine data for disease surveillance has been demonstrated, the scientific community still seeks ways to identify and reduce biases that are embedded in search engine data. The primary goal of this study is to explore new ways of improving the accuracy of disease prevalence estimations by combining traditional disease data with search engine data. A novel method, Biased Sentinel Hospital-based Area Disease Estimation (B-SHADE), is introduced to reduce search engine data bias from a geographical perspective. To monitor search trends on Hand, Foot and Mouth Disease (HFMD) in Guangdong Province, China, we tested our approach by selecting 11 keywords from the Baidu index platform, a Chinese big data analyst similar to GFT. The correlation between the number of real cases and the composite index was 0.8. After decomposing the composite index at the city level, we found that only 10 cities presented a correlation of close to 0.8 or higher. These cities were found to be more stable with respect to search volume, and they were selected as sample cities in order to estimate the search volume of the entire province. After the estimation, the correlation improved from 0.8 to 0.864. After fitting the revised search volume with historical cases, the mean absolute error was 11.19% lower than it was when the original search volume and historical cases were combined. To our knowledge, this is the first study to reduce search engine data bias levels through the use of rigorous spatial sampling strategies.'),
(87861, 2016, 'plos', 'Interplay between Graph Topology and Correlations of Third Order in Spiking Neuronal Networks', 'Jovanovixc4x87, Stojan|Rotter, Stefan', 'Bernstein Center Freiburg & Faculty of Biology, University of Freiburg, Freiburg, Germany.|Bernstein Center Freiburg & Faculty of Biology, University of Freiburg, Freiburg, Germany.', 'Germany|Germany', 5, 'Action Potentials|Animals|Computational Biology|Models, Neurological|Nerve Net|Neurons', 'Journal Article', '10.1371/journal.pcbi.1004963', '27271768', 'The study of processes evolving on networks has recently become a very popular research field, not only because of the rich mathematical theory that underpins it, but also because of its many possible applications, a number of them in the field of biology. Indeed, molecular signaling pathways, gene regulation, predator-prey interactions and the communication between neurons in the brain can be seen as examples of networks with complex dynamics. The properties of such dynamics depend largely on the topology of the underlying network graph. In this work, we want to answer the following question: Knowing network connectivity, what can be said about the level of third-order correlations that will characterize the network dynamics? We consider a linear point process as a model for pulse-coded, or spiking activity in a neuronal network. Using recent results from theory of such processes, we study third-order correlations between spike trains in such a system and explain which features of the network graph (i.e. which topological motifs) are responsible for their emergence. Comparing two different models of network topology-random networks of Erdxc5x91s-Rxc3xa9nyi type and networks with highly interconnected hubs-we find that, in random networks, the average measure of third-order correlations does not depend on the local connectivity properties, but rather on global parameters, such as the connection probability. This, however, ceases to be the case in networks with a geometric out-degree distribution, where topological specificities have a strong impact on average correlations.'),
(87862, 2016, 'plos', 'Accurate Automatic Detection of Densely Distributed Cell Nuclei in 3D Space', 'Toyoshima, Yu|Tokunaga, Terumasa|Hirose, Osamu|Kanamori, Manami|Teramoto, Takayuki|Jang, Moon Sun|Kuge, Sayuri|Ishihara, Takeshi|Yoshida, Ryo|Iino, Yuichi', 'Department of Biological Sciences, Graduate School of Science, The University of Tokyo, Bunkyo-ku, Tokyo, Japan.|Department of Systems Design and Informatics, Faculty of Computer Science and Systems Engineering, Kyushu Institute of Technology, Iizuka-shi, Fukuoka, Japan.|Faculty of Electrical and Computer Engineering, Institute of Science and Engineering, Kanazawa University, Kakuma, Kanazawa, Japan.|Department of Biological Sciences, Graduate School of Science, The University of Tokyo, Bunkyo-ku, Tokyo, Japan.|Department of Biology, Faculty of Sciences, Kyushu University, Higashi-ku, Fukuoka, Japan.|Department of Biological Sciences, Graduate School of Science, The University of Tokyo, Bunkyo-ku, Tokyo, Japan.|Department of Biology, Faculty of Sciences, Kyushu University, Higashi-ku, Fukuoka, Japan.|Department of Biology, Faculty of Sciences, Kyushu University, Higashi-ku, Fukuoka, Japan.|The Institute of Statistical Mathematics, Research Organization of Information and Systems, Tachikawa, Tokyo, Japan.|Department of Biological Sciences, Graduate School of Science, The University of Tokyo, Bunkyo-ku, Tokyo, Japan.', 'Japan|Japan|Japan|Japan|Japan|Japan|Japan|Japan|Japan|Japan', 13, 'Animals|Caenorhabditis elegans|Cell Nucleus|Computational Biology|Databases, Factual|Imaging, Three-Dimensional|Normal Distribution|Pattern Recognition, Automated', 'Journal Article', '10.1371/journal.pcbi.1004970', '27271939', 'To measure the activity of neurons using whole-brain activity imaging, precise detection of each neuron or its nucleus is required. In the head region of the nematode C. elegans, the neuronal cell bodies are distributed densely in three-dimensional (3D) space. However, no existing computational methods of image analysis can separate them with sufficient accuracy. Here we propose a highly accurate segmentation method based on the curvatures of the iso-intensity surfaces. To obtain accurate positions of nuclei, we also developed a new procedure for least squares fitting with a Gaussian mixture model. Combining these methods enables accurate detection of densely distributed cell nuclei in a 3D space. The proposed method was implemented as a graphical user interface program that allows visualization and correction of the results of automatic detection. Additionally, the proposed method was applied to time-lapse 3D calcium imaging data, and most of the nuclei in the images were successfully tracked and measured.'),
(87863, 2016, 'plos', 'FamPipe: An Automatic Analysis Pipeline for Analyzing Sequencing Data in Families for Disease Studies', 'Chung, Ren-Hua|Tsai, Wei-Yun|Kang, Chen-Yu|Yao, Po-Ju|Tsai, Hui-Ju|Chen, Chia-Hsiang', 'Division of Biostatistics and Bioinformatics, Institute of Population Health Sciences, National Health Research Institutes, Zhunan, Miaoli County, Taiwan.|Division of Biostatistics and Bioinformatics, Institute of Population Health Sciences, National Health Research Institutes, Zhunan, Miaoli County, Taiwan.|Division of Biostatistics and Bioinformatics, Institute of Population Health Sciences, National Health Research Institutes, Zhunan, Miaoli County, Taiwan.|Division of Biostatistics and Bioinformatics, Institute of Population Health Sciences, National Health Research Institutes, Zhunan, Miaoli County, Taiwan.|Division of Biostatistics and Bioinformatics, Institute of Population Health Sciences, National Health Research Institutes, Zhunan, Miaoli County, Taiwan.|Department of Psychiatry, Chang Gung Memorial Hospital-Linkou, Gueishan, Taoyuan, Taiwan.', '-|-|-|-|-|-', 0, 'Computational Biology|Computer Simulation|Genetic Association Studies|Genetic Predisposition to Disease|High-Throughput Nucleotide Sequencing|Humans|Internet|Sequence Analysis, DNA|Software', 'Journal Article', '10.1371/journal.pcbi.1004980', '27272119', 'In disease studies, family-based designs have become an attractive approach to analyzing next-generation sequencing (NGS) data for the identification of rare mutations enriched in families. Substantial research effort has been devoted to developing pipelines for automating sequence alignment, variant calling, and annotation. However, fewer pipelines have been designed specifically for disease studies. Most of the current analysis pipelines for family-based disease studies using NGS data focus on a specific function, such as identifying variants with Mendelian inheritance or identifying shared chromosomal regions among affected family members. Consequently, some other useful family-based analysis tools, such as imputation, linkage, and association tools, have yet to be integrated and automated. We developed FamPipe, a comprehensive analysis pipeline, which includes several family-specific analysis modules, including the identification of shared chromosomal regions among affected family members, prioritizing variants assuming a disease model, imputation of untyped variants, and linkage and association tests. We used simulation studies to compare properties of some modules implemented in FamPipe, and based on the results, we provided suggestions for the selection of modules to achieve an optimal analysis strategy. The pipeline is under the GNU GPL License and can be downloaded for free at http://fampipe.sourceforge.net.'),
(87864, 2016, 'plos', 'Computing Average Passive Forces in Sarcomeres in Length-Ramp Simulations', 'Schappacher-Tilp, Gudrun|Leonard, Timothy|Desch, Gertrud|Herzog, Walter', 'Department for Mathematics and Computational Sciences, University of Graz, Graz, Austria.|Human Performance Laboratory, University of Calgary, Calgary, Canada.|Department for Mathematics and Computational Sciences, University of Graz, Graz, Austria.|Human Performance Laboratory, University of Calgary, Calgary, Canada.', 'Austria|Canada|Austria|Canada', 0, 'Computer Simulation|Connectin|Models, Biological|Models, Chemical|Models, Molecular|Sarcomeres|Stress, Mechanical|Structure-Activity Relationship|Tensile Strength', 'Journal Article', '10.1371/journal.pcbi.1004904', '27276390', 'Passive forces in sarcomeres are mainly related to the giant protein titin. Titins extensible region consists of spring-like elements acting in series. In skeletal muscles these elements are the PEVK segment, two distinct immunoglobulin (Ig) domain regions (proximal and distal), and a N2A portion. While distal Ig domains are thought to form inextensible end filaments in intact sarcomeres, proximal Ig domains unfold in a force- and time-dependent manner. In length-ramp experiments of single titin strands, sequential unfolding of Ig domains leads to a typical saw-tooth pattern in force-elongation curves which can be simulated by Monte Carlo simulations. In sarcomeres, where more than a thousand titin strands are arranged in parallel, numerous Monte Carlo simulations are required to estimate the resultant force of all titin filaments based on the non-uniform titin elongations. To simplify calculations, the stochastic model of passive forces is often replaced by linear or non-linear deterministic and phenomenological functions. However, new theories of muscle contraction are based on the hypothesized binding of titin to the actin filament upon activation, and thereby on a prominent role of the structural properties of titin. Therefore, these theories necessitate a detailed analysis of titin forces in length-ramp experiments. In our study we present a simple and efficient alternative to Monte Carlo simulations. Based on a structural titin model, we calculate the exact probability distributions of unfolded Ig domains under length-ramp conditions needed for rigorous analysis of expected forces, distribution of unfolding forces, etc. Due to the generality of our model, the approach is applicable to a wide range of stochastic protein unfolding problems.'),
(87865, 2016, 'plos', 'The Evolutionary Origins of Hierarchy', 'Mengistu, Henok|Huizinga, Joost|Mouret, Jean-Baptiste|Clune, Jeff', 'Evolving AI Lab, Department of Computer Science, University of Wyoming, Laramie, Wyoming, United States of America.|Evolving AI Lab, Department of Computer Science, University of Wyoming, Laramie, Wyoming, United States of America.|LARSEN, Inria, Villers-lès-Nancy, France.|Evolving AI Lab, Department of Computer Science, University of Wyoming, Laramie, Wyoming, United States of America.', 'United States|United States|France|United States', 0, 'Animals|Biological Evolution|Computer Simulation|Gene Expression Regulation|Humans|Models, Genetic|Nerve Net|Proteome|Selection, Genetic|Signal Transduction', 'Journal Article', '10.1371/journal.pcbi.1004829', '27280881', 'Hierarchical organization-the recursive composition of sub-modules-is ubiquitous in biological networks, including neural, metabolic, ecological, and genetic regulatory networks, and in human-made systems, such as large organizations and the Internet. To date, most research on hierarchy in networks has been limited to quantifying this property. However, an open, important question in evolutionary biology is why hierarchical organization evolves in the first place. It has recently been shown that modularity evolves because of the presence of a cost for network connections. Here we investigate whether such connection costs also tend to cause a hierarchical organization of such modules. In computational simulations, we find that networks without a connection cost do not evolve to be hierarchical, even when the task has a hierarchical structure. However, with a connection cost, networks evolve to be both modular and hierarchical, and these networks exhibit higher overall performance and evolvability (i.e. faster adaptation to new environments). Additional analyses confirm that hierarchy independently improves adaptability after controlling for modularity. Overall, our results suggest that the same force-the cost of connections-promotes the evolution of both hierarchy and modularity, and that these properties are important drivers of network performance and adaptability. In addition to shedding light on the emergence of hierarchy across the many domains in which it appears, these findings will also accelerate future research into evolving more complex, intelligent computational brains in the fields of artificial intelligence and robotics.'),
(87866, 2016, 'plos', 'Continuing Education Workshops in Bioinformatics Positively Impact Research and Careers', 'Brazas, Michelle D|Ouellette, B F Francis', 'Ontario Institute for Cancer Research, Toronto, Ontario, Canada.|Ontario Institute for Cancer Research, Toronto, Ontario, Canada.', 'Canada|Canada', 5, 'Career Mobility|Computational Biology|Curriculum|Education|Education, Continuing|Research', 'Journal Article', '10.1371/journal.pcbi.1004916', '27281025', 'Bioinformatics.ca has been hosting continuing education programs in introductory and advanced bioinformatics topics in Canada since 1999 and has trained more than 2,000 participants to date. These workshops have been adapted over the years to keep pace with advances in both science and technology as well as the changing landscape in available learning modalities and the bioinformatics training needs of our audience. Post-workshop surveys have been a mandatory component of each workshop and are used to ensure appropriate adjustments are made to workshops to maximize learning. However, neither bioinformatics.ca nor others offering similar training programs have explored the long-term impact of bioinformatics continuing education training. Bioinformatics.ca recently initiated a look back on the impact its workshops have had on the career trajectories, research outcomes, publications, and collaborations of its participants. Using an anonymous online survey, bioinformatics.ca analyzed responses from those surveyed and discovered its workshops have had a positive impact on collaborations, research, publications, and career progression.'),
(87867, 2016, 'plos', 'Ten Simple Rules for Effective Statistical Practice', 'Kass, Robert E|Caffo, Brian S|Davidian, Marie|Meng, Xiao-Li|Yu, Bin|Reid, Nancy', 'Department of Statistics, Machine Learning Department, and Center for the Neural Basis of Cognition, Carnegie Mellon University, Pittsburgh, Pennsylvania, United States of America.|Department of Biostatistics, Bloomberg School of Public Health, Johns Hopkins University, Baltimore, Maryland, United States of America.|Department of Statistics, North Carolina State University, Raleigh, North Carolina, United States of America.|Department of Statistics, Harvard University, Cambridge, Massachusetts, United States of America.|Department of Statistics and Department of Electrical Engineering and Computer Science, University of California Berkeley, Berkeley, California, United States of America.|Department of Statistical Sciences, University of Toronto, Toronto, Ontario, Canada.', 'United States|United States|United States|United States|United States|Canada', 30, 'Algorithms|Computational Biology|Computer Simulation|Data Accuracy|Data Interpretation, Statistical|Information Dissemination|Models, Statistical', 'Editorial', '10.1371/journal.pcbi.1004961', '27281180', '-'),
(87868, 2016, 'plos', 'Revealing Atomic-Level Mechanisms of Protein Allostery with Molecular Dynamics Simulations', 'Hertig, Samuel|Latorraca, Naomi R|Dror, Ron O', 'Department of Computer Science, Stanford University, Stanford, California, United States of America.|Department of Computer Science, Stanford University, Stanford, California, United States of America.|Department of Computer Science, Stanford University, Stanford, California, United States of America.', 'United States|United States|United States', 51, 'Adhesins, Bacterial|Allosteric Regulation|Allosteric Site|Computational Biology|Computer Simulation|Drug Design|Fibronectins|Heterotrimeric GTP-Binding Proteins|Ligands|Molecular Dynamics Simulation|Protein Binding|Protein Conformation|Proteins|Receptor, Muscarinic M2|Receptors, Adrenergic, beta-2', 'Journal Article', '10.1371/journal.pcbi.1004746', '27285999', 'Molecular dynamics (MD) simulations have become a powerful and popular method for the study of protein allostery, the widespread phenomenon in which a stimulus at one site on a protein influences the properties of another site on the protein. By capturing the motions of a proteins constituent atoms, simulations can enable the discovery of allosteric binding sites and the determination of the mechanistic basis for allostery. These results can provide a foundation for applications including rational drug design and protein engineering. Here, we provide an introduction to the investigation of protein allostery using molecular dynamics simulation. We emphasize the importance of designing simulations that include appropriate perturbations to the molecular system, such as the addition or removal of ligands or the application of mechanical force. We also demonstrate how the bidirectional nature of allostery-the fact that the two sites involved influence one another in a symmetrical manner-can facilitate such investigations. Through a series of case studies, we illustrate how these concepts have been used to reveal the structural basis for allostery in several proteins and protein complexes of biological and pharmaceutical interest.'),
(87869, 2016, 'plos', 'Reservoir Computing Properties of Neural Dynamics in Prefrontal Cortex', 'Enel, Pierre|Procyk, Emmanuel|Quilodran, René|Dominey, Peter Ford', 'Univ Lyon, Université Lyon 1, Inserm, Stem Cell and Brain Research Institute U1208, Bron, France.|Univ Lyon, Université Lyon 1, Inserm, Stem Cell and Brain Research Institute U1208, Bron, France.|Univ Lyon, Université Lyon 1, Inserm, Stem Cell and Brain Research Institute U1208, Bron, France.|Univ Lyon, Université Lyon 1, Inserm, Stem Cell and Brain Research Institute U1208, Bron, France.', 'France|France|France|France', 51, 'Animals|Computational Biology|Models, Neurological|Nerve Net|Neurons|Prefrontal Cortex|Primates', 'Journal Article', '10.1371/journal.pcbi.1004967', '27286251', 'Primates display a remarkable ability to adapt to novel situations. Determining what is most pertinent in these situations is not always possible based only on the current sensory inputs, and often also depends on recent inputs and behavioral outputs that contribute to internal states. Thus, one can ask how cortical dynamics generate representations of these complex situations. It has been observed that mixed selectivity in cortical neurons contributes to represent diverse situations defined by a combination of the current stimuli, and that mixed selectivity is readily obtained in randomly connected recurrent networks. In this context, these reservoir networks reproduce the highly recurrent nature of local cortical connectivity. Recombining present and past inputs, random recurrent networks from the reservoir computing framework generate mixed selectivity which provides pre-coded representations of an essentially universal set of contexts. These representations can then be selectively amplified through learning to solve the task at hand. We thus explored their representational power and dynamical properties after training a reservoir to perform a complex cognitive task initially developed for monkeys. The reservoir model inherently displayed a dynamic form of mixed selectivity, key to the representation of the behavioral context over time. The pre-coded representation of context was amplified by training a feedback neuron to explicitly represent this context, thereby reproducing the effect of learning and allowing the model to perform more robustly. This second version of the model demonstrates how a hybrid dynamical regime combining spatio-temporal processing of reservoirs, and input driven attracting dynamics generated by the feedback neuron, can be used to solve a complex cognitive task. We compared reservoir activity to neural activity of dorsal anterior cingulate cortex of monkeys which revealed similar network dynamics. We argue that reservoir computing is a pertinent framework to model local cortical dynamics and their contribution to higher cognitive function.');
INSERT INTO `papers` (`id`, `ano`, `journal`, `titulo`, `autores`, `afiliacao`, `pais`, `citacoes`, `palavra_chave`, `categorias`, `doi`, `pubmed`, `abstract`) VALUES
(87870, 2016, 'plos', 'Theory and Experimental Validation of a Spatio-temporal Model of Chemotherapy Transport to Enhance Tumor Cell Kill', 'Wang, Zhihui|Kerketta, Romica|Chuang, Yao-Li|Dogra, Prashant|Butner, Joseph D|Brocato, Terisse A|Day, Armin|Xu, Rong|Shen, Haifa|Simbawa, Eman|Al-Fhaid, A S|Mahmoud, S R|Curley, Steven A|Ferrari, Mauro|Koay, Eugene J|Cristini, Vittorio', 'Department of NanoMedicine and Biomedical Engineering, University of Texas Medical School at Houston, Houston, Texas, United States of America.|Department of Pathology, University of New Mexico, Albuquerque, New Mexico, United States of America.|Department of Mathematics, California State University, Northridge, California, United States of America.|Department of Pathology, University of New Mexico, Albuquerque, New Mexico, United States of America.|Department of Chemical and Biological Engineering and Center for Biomedical Engineering, University of New Mexico, Albuquerque, New Mexico, United States of America.|Department of Chemical and Biological Engineering and Center for Biomedical Engineering, University of New Mexico, Albuquerque, New Mexico, United States of America.|Department of Pathology, University of New Mexico, Albuquerque, New Mexico, United States of America.|Department of Nanomedicine, Methodist Hospital Research Institute, Houston, Texas, United States of America.|Department of Nanomedicine, Methodist Hospital Research Institute, Houston, Texas, United States of America.|Department of Mathematics, Faculty of Science, King Abdulaziz University, Jeddah, Saudi Arabia.|Department of Mathematics, Faculty of Science, King Abdulaziz University, Jeddah, Saudi Arabia.|Department of Mathematics, Faculty of Science, King Abdulaziz University, Jeddah, Saudi Arabia.|Michael E. DeBakey Department of Surgery, Baylor College of Medicine, Houston, Texas, United States of America.|Department of Nanomedicine, Methodist Hospital Research Institute, Houston, Texas, United States of America.|Department of Radiation Oncology, University of Texas MD Anderson Cancer Center, Houston, Texas, United States of America.|Department of NanoMedicine and Biomedical Engineering, University of Texas Medical School at Houston, Houston, Texas, United States of America.', 'United States|Mexico|United States|Mexico|Mexico|Mexico|Mexico|United States|United States|Saudi Ara', 0, 'Animals|Antineoplastic Agents|Computational Biology|Computer Simulation|Drug Carriers|Female|Mice|Mice, Inbred BALB C|Models, Biological|Nanoparticles|Neoplasms|Spatio-Temporal Analysis', 'Journal Article', '10.1371/journal.pcbi.1004969', '27286441', 'Cancer treatment efficacy can be significantly enhanced through the elution of drug from nano-carriers that can temporarily stay in the tumor vasculature. Here we present a relatively simple yet powerful mathematical model that accounts for both spatial and temporal heterogeneities of drug dosing to help explain, examine, and prove this concept. We find that the delivery of systemic chemotherapy through a certain form of nano-carriers would have enhanced tumor kill by a factor of 2 to 4 over the standard therapy that the patients actually received. We also find that targeting blood volume fraction (a parameter of the model) through vascular normalization can achieve more effective drug delivery and tumor kill. More importantly, this model only requires a limited number of parameters which can all be readily assessed from standard clinical diagnostic measurements (e.g., histopathology and CT). This addresses an important challenge in current translational research and justifies further development of the model towards clinical translation.'),
(87871, 2016, 'plos', 'Phylogenetic Analysis Reveals That ERVs Die Young but HERV-H Is Unusually Conserved', 'Gemmell, Patrick|Hein, Jotun|Katzourakis, Aris', 'Department of Zoology, University of Oxford, Oxford, United Kingdom.|Department of Statistics, University of Oxford, Oxford, United Kingdom.|Department of Zoology, University of Oxford, Oxford, United Kingdom.', 'United Kingdom|United Kingdom|United Kingdom', 0, 'Animals|Base Sequence|Conserved Sequence|Endogenous Retroviruses|Evolution, Molecular|Genome, Human|Humans|Models, Genetic|Phylogeny|Primates', 'Journal Article', '10.1371/journal.pcbi.1004964', '27295277', 'About 8% of the human genome is made up of endogenous retroviruses (ERVs). Though most human endogenous retroviruses (HERVs) are thought to be irrelevant to our biology notable exceptions include members of the HERV-H family that are necessary for the correct functioning of stem cells. ERVs are commonly found in two forms, the full-length proviral form, and the more numerous solo-LTR form, thought to result from homologous recombination events. Here we introduce a phylogenetic framework to study ERV insertion and solo-LTR formation. We then apply the framework to site patterns sampled from a set of long alignments covering six primate genomes. Studying six categories of ERVs we quantitatively recapitulate patterns of insertional activity that are usually described in qualitative terms in the literature. A slowdown in most ERV groups is observed but we suggest that HERV-K activity may have increased in humans since they diverged from chimpanzees. We find that the rate of solo-LTR formation decreases rapidly as a function of ERV age and that an age dependent model of solo-LTR formation describes the history of ERVs more accurately than the commonly used exponential decay model. We also demonstrate that HERV-H loci are markedly less likely to form solo-LTRs than ERVs from other families. We conclude that the slower dynamics of HERV-H suggest a host role for the internal regions of these exapted elements and posit that in future it will be possible to use the relationship between full-length proviruses and solo-LTRs to help identify large scale co-options in distant vertebrate genomes.'),
(87872, 2016, 'plos', 'Deciphering Dimerization Modes of PAS Domains: Computational and Experimental Analyses of the AhR:ARNT Complex Reveal New Insights Into the Mechanisms of AhR Transformation', 'Corrada, Dario|Soshilov, Anatoly A|Denison, Michael S|Bonati, Laura', 'Department of Earth and Environmental Sciences, University of Milano-Bicocca, Milan, Italy.|Department of Environmental Toxicology, University of California, Davis, Davis, California, United States of America.|Department of Environmental Toxicology, University of California, Davis, Davis, California, United States of America.|Department of Earth and Environmental Sciences, University of Milano-Bicocca, Milan, Italy.', 'Italy|United States|United States|Italy', 11, 'Aryl Hydrocarbon Receptor Nuclear Translocator|Computational Biology|Humans|Models, Molecular|Mutation|Protein Domains|Receptors, Aryl Hydrocarbon', 'Journal Article', '10.1371/journal.pcbi.1004981', '27295348', 'The Aryl hydrocarbon Receptor (AhR) is a transcription factor that mediates the biochemical response to xenobiotics and the toxic effects of a number of environmental contaminants, including dioxins. Recently, endogenous regulatory roles for the AhR in normal physiology and development have also been reported, thus extending the interest in understanding its molecular mechanisms of activation. Since dimerization with the AhR Nuclear Translocator (ARNT) protein, occurring through the Helix-Loop-Helix (HLH) and PER-ARNT-SIM (PAS) domains, is needed to convert the AhR into its transcriptionally active form, deciphering the AhR:ARNT dimerization mode would provide insights into the mechanisms of AhR transformation. Here we present homology models of the murine AhR:ARNT PAS domain dimer developed using recently available X-ray structures of other bHLH-PAS protein dimers. Due to the different reciprocal orientation and interaction surfaces in the different template dimers, two alternative models were developed for both the PAS-A and PAS-B dimers and they were characterized by combining a number of computational evaluations. Both well-established hot spot prediction methods and new approaches to analyze individual residue and residue-pairwise contributions to the MM-GBSA binding free energies were adopted to predict residues critical for dimer stabilization. On this basis, a mutagenesis strategy for both the murine AhR and ARNT proteins was designed and ligand-dependent DNA binding ability of the AhR:ARNT heterodimer mutants was evaluated. While functional analysis disfavored the HIF2xcexb1:ARNT heterodimer-based PAS-B model, most mutants derived from the CLOCK:BMAL1-based AhR:ARNT dimer models of both the PAS-A and the PAS-B dramatically decreased the levels of DNA binding, suggesting this latter model as the most suitable for describing AhR:ARNT dimerization. These novel results open new research directions focused at elucidating basic molecular mechanisms underlying the functional activity of the AhR.'),
(87873, 2016, 'plos', 'Accuracy of Answers to Cell Lineage Questions Depends on Single-Cell Genomics Data Quality and Quantity', 'Spiro, Adam|Shapiro, Ehud', 'Department of Computer Science and Applied Mathematics and Department of Biological Chemistry, Weizmann Institute of Science, Rehovot, Israel.|Department of Computer Science and Applied Mathematics and Department of Biological Chemistry, Weizmann Institute of Science, Rehovot, Israel.', 'Israel|Israel', 1, 'Algorithms|Cell Lineage|Computer Simulation|Databases, Genetic|Genomics|Humans|Models, Genetic|Mutation|Single-Cell Analysis', 'Journal Article', '10.1371/journal.pcbi.1004983', '27295404', 'Advances in single-cell (SC) genomics enable commensurate improvements in methods for uncovering lineage relations among individual cells, as determined by phylogenetic analysis of the somatic mutations harbored by each cell. Theoretically, complete and accurate knowledge of the genome of each cell of an individual can produce an extremely accurate cell lineage tree of that individual. However, the reality of SC genomics is that such complete and accurate knowledge would be wanting, in quality and in quantity, for the foreseeable future. In this paper we offer a framework for systematically exploring the feasibility of answering cell lineage questions based on SC somatic mutational analysis, as a function of SC genomics data quality and quantity. We take into consideration the current limitations of SC genomics in terms of mutation data quality, most notably amplification bias and allele dropouts (ADO), as well as cost, which puts practical limits on mutation data quantity obtained from each cell as well as on cell sample density. We do so by generating in silico cell lineage trees using a dedicated formal language, eSTG, and show how the ability to answer correctly a cell lineage question depends on the quality and quantity of the SC mutation data. The presented framework can serve as a baseline for the potential of current SC genomics to unravel cell lineage dynamics, as well as the potential contributions of future advancement, both biochemical and computational, for the task.'),
(87874, 2016, 'plos', 'Large Scale Chromosome Folding Is Stable against Local Changes in Chromatin Structure', 'Florescu, Ana-Maria|Therizols, Pierre|Rosa, Angelo', 'SISSA - Scuola Internazionale Superiore di Studi Avanzati, Trieste, Italy.|INSERM UMR 944, Équipe Biologie et Dynamique des Chromosomes, Institut Universitaire dHématologie, Hôpital St. Louis, Paris, France.|SISSA - Scuola Internazionale Superiore di Studi Avanzati, Trieste, Italy.', 'Italy|France|Italy', 0, 'Animals|Biophysical Phenomena|Chromatin|Chromosomes|Models, Chemical|Molecular Dynamics Simulation|Nucleic Acid Conformation', 'Journal Article', '10.1371/journal.pcbi.1004987', '27295501', 'Characterizing the link between small-scale chromatin structure and large-scale chromosome folding during interphase is a prerequisite for understanding transcription. Yet, this link remains poorly investigated. Here, we introduce a simple biophysical model where interphase chromosomes are described in terms of the folding of chromatin sequences composed of alternating blocks of fibers with different thicknesses and flexibilities, and we use it to study the influence of sequence disorder on chromosome behaviors in space and time. By employing extensive computer simulations, we thus demonstrate that chromosomes undergo noticeable conformational changes only on length-scales smaller than 105 basepairs and time-scales shorter than a few seconds, and we suggest there might exist effective upper bounds to the detection of chromosome reorganization in eukaryotes. We prove the relevance of our framework by modeling recent experimental FISH data on murine chromosomes.'),
(87875, 2016, 'plos', 'Progression of Diabetic Capillary Occlusion: A Model', 'Fu, Xiao|Gens, John Scott|Glazier, James A|Burns, Stephen A|Gast, Thomas J', 'The Biocomplexity Institute, Indiana University, Bloomington, Indiana, United States of America.|The Biocomplexity Institute, Indiana University, Bloomington, Indiana, United States of America.|The Biocomplexity Institute, Indiana University, Bloomington, Indiana, United States of America.|School of Optometry, Indiana University, Bloomington, Indiana, United States of America.|School of Optometry, Indiana University, Bloomington, Indiana, United States of America.', 'India|India|India|India|India', 0, 'Blood Flow Velocity|Capillaries|Cell Adhesion|Computational Biology|Computer Simulation|Diabetic Retinopathy|Disease Progression|Endothelium, Vascular|Humans|Leukocytes|Macular Edema|Models, Biological|Retinal Artery Occlusion|Vascular Endothelial Growth Factor A', 'Journal Article', '10.1371/journal.pcbi.1004932', '27300722', 'An explanatory computational model is developed of the contiguous areas of retinal capillary loss which play a large role in diabetic maculapathy and diabetic retinal neovascularization. Strictly random leukocyte mediated capillary occlusion cannot explain the occurrence of large contiguous areas of retinal ischemia. Therefore occlusion of an individual capillary must increase the probability of occlusion of surrounding capillaries. A retinal perifoveal vascular sector as well as a peripheral retinal capillary network and a deleted hexagonal capillary network are modelled using Compucell3D. The perifoveal modelling produces a pattern of spreading capillary loss with associated macular edema. In the peripheral network, spreading ischemia results from the progressive loss of the ladder capillaries which connect peripheral arterioles and venules. System blood flow was elevated in the macular model before a later reduction in flow in cases with progression of capillary occlusions. Simulations differing only in initial vascular network structures but with identical dynamics for oxygen, growth factors and vascular occlusions, replicate key clinical observations of ischemia and macular edema in the posterior pole and ischemia in the retinal periphery. The simulation results also seem consistent with quantitative data on macular blood flow and qualitative data on venous oxygenation. One computational model applied to distinct capillary networks in different retinal regions yielded results comparable to clinical observations in those regions.'),
(87876, 2016, 'plos', 'Adaptive Spike Threshold Enables Robust and Temporally Precise Neuronal Encoding', 'Huang, Chao|Resnik, Andrey|Celikel, Tansu|Englitz, Bernhard', 'Department of Neurophysiology, Donders Institute for Brain, Cognition and Behaviour, Radboud University, Nijmegen, the Netherlands.|Laboratory of Neural Circuits and Plasticity, University of Southern California, Los Angeles, California, United States of America.|Department of Neurophysiology, Donders Institute for Brain, Cognition and Behaviour, Radboud University, Nijmegen, the Netherlands.|Department of Neurophysiology, Donders Institute for Brain, Cognition and Behaviour, Radboud University, Nijmegen, the Netherlands.', 'Netherlands|United States|Netherlands|Netherlands', 12, 'Action Potentials|Animals|Computational Biology|Female|Male|Mice|Models, Neurological|Neurons|Patch-Clamp Techniques', 'Journal Article', '10.1371/journal.pcbi.1004984', '27304526', 'Neural processing rests on the intracellular transformation of information as synaptic inputs are translated into action potentials. This transformation is governed by the spike threshold, which depends on the history of the membrane potential on many temporal scales. While the adaptation of the threshold after spiking activity has been addressed before both theoretically and experimentally, it has only recently been demonstrated that the subthreshold membrane state also influences the effective spike threshold. The consequences for neural computation are not well understood yet. We address this question here using neural simulations and whole cell intracellular recordings in combination with information theoretic analysis. We show that an adaptive spike threshold leads to better stimulus discrimination for tight input correlations than would be achieved otherwise, independent from whether the stimulus is encoded in the rate or pattern of action potentials. The time scales of input selectivity are jointly governed by membrane and threshold dynamics. Encoding information using adaptive thresholds further ensures robust information transmission across cortical states i.e. decoding from different states is less state dependent in the adaptive threshold case, if the decoding is performed in reference to the timing of the population response. Results from in vitro neural recordings were consistent with simulations from adaptive threshold neurons. In summary, the adaptive spike threshold reduces information loss during intracellular information transfer, improves stimulus discriminability and ensures robust decoding across membrane states in a regime of highly correlated inputs, similar to those seen in sensory nuclei during the encoding of sensory information.'),
(87877, 2016, 'plos', 'GRAbB: Selective Assembly of Genomic Regions, a New Niche for Genomic Research', 'Brankovics, Balázs|Zhang, Hao|van Diepeningen, Anne D|van der Lee, Theo A J|Waalwijk, Cees|de Hoog, G Sybren', 'CBS-KNAW Fungal Biodiversity Centre, Utrecht, the Netherlands.|State Key Laboratory for Biology of Plant Diseases and Insect Pests, Institute of Plant Protection, Chinese Academy of Agriculture Sciences, Beijing, China.|CBS-KNAW Fungal Biodiversity Centre, Utrecht, the Netherlands.|Wageningen University and Research Centre, Wageningen, the Netherlands.|Wageningen University and Research Centre, Wageningen, the Netherlands.|CBS-KNAW Fungal Biodiversity Centre, Utrecht, the Netherlands.', 'Netherlands|China|Netherlands|Netherlands|Netherlands|Netherlands', 16, 'Algorithms|Computational Biology|Computer Simulation|DNA, Fungal|DNA, Ribosomal|Fusarium|Genome, Fungal|Genome, Mitochondrial|Genomics|High-Throughput Nucleotide Sequencing|Software', 'Journal Article', '10.1371/journal.pcbi.1004753', '27308864', 'GRAbB (Genomic Region Assembly by Baiting) is a new program that is dedicated to assemble specific genomic regions from NGS data. This approach is especially useful when dealing with multi copy regions, such as mitochondrial genome and the rDNA repeat region, parts of the genome that are often neglected or poorly assembled, although they contain interesting information from phylogenetic or epidemiologic perspectives, but also single copy regions can be assembled. The program is capable of targeting multiple regions within a single run. Furthermore, GRAbB can be used to extract specific loci from NGS data, based on homology, like sequences that are used for barcoding. To make the assembly specific, a known part of the region, such as the sequence of a PCR amplicon or a homologous sequence from a related species must be specified. By assembling only the region of interest, the assembly process is computationally much less demanding and may lead to assemblies of better quality. In this study the different applications and functionalities of the program are demonstrated such as: exhaustive assembly (rDNA region and mitochondrial genome), extracting homologous regions or genes (IGS, RPB1, RPB2 and TEF1a), as well as extracting multiple regions within a single run. The program is also compared with MITObim, which is meant for the exhaustive assembly of a single target based on a similar query sequence. GRAbB is shown to be more efficient than MITObim in terms of speed, memory and disk usage. The other functionalities (handling multiple targets simultaneously and extracting homologous regions) of the new program are not matched by other programs. The program is available with explanatory documentation at https://github.com/b-brankovics/grabb. GRAbB has been tested on Ubuntu (12.04 and 14.04), Fedora (23), CentOS (7.1.1503) and Mac OS X (10.7). Furthermore, GRAbB is available as a docker repository: brankovics/grabb (https://hub.docker.com/r/brankovics/grabb/).'),
(87878, 2016, 'plos', 'Learning Universal Computations with Spikes', 'Thalmeier, Dominik|Uhlmann, Marvin|Kappen, Hilbert J|Memmesheimer, Raoul-Martin', 'Donders Institute, Department of Biophysics, Radboud University, Nijmegen, Netherlands.|Max Planck Institute for Psycholinguistics, Department for Neurobiology of Language, Nijmegen, Netherlands.|Donders Institute, Department of Biophysics, Radboud University, Nijmegen, Netherlands.|Donders Institute, Department for Neuroinformatics, Radboud University, Nijmegen, Netherlands.', 'Netherlands|Netherlands|Netherlands|Netherlands', 9, 'Action Potentials|Animals|Computational Biology|Humans|Learning|Memory, Long-Term|Models, Neurological|Nerve Net|Neural Networks (Computer)|Neurons|Nonlinear Dynamics|Synaptic Transmission', 'Journal Article', '10.1371/journal.pcbi.1004895', '27309381', 'Providing the neurobiological basis of information processing in higher animals, spiking neural networks must be able to learn a variety of complicated computations, including the generation of appropriate, possibly delayed reactions to inputs and the self-sustained generation of complex activity patterns, e.g. for locomotion. Many such computations require previous building of intrinsic world models. Here we show how spiking neural networks may solve these different tasks. Firstly, we derive constraints under which classes of spiking neural networks lend themselves to substrates of powerful general purpose computing. The networks contain dendritic or synaptic nonlinearities and have a constrained connectivity. We then combine such networks with learning rules for outputs or recurrent connections. We show that this allows to learn even difficult benchmark tasks such as the self-sustained generation of desired low-dimensional chaotic dynamics or memory-dependent computations. Furthermore, we show how spiking networks can build models of external world systems and use the acquired knowledge to control them.'),
(87879, 2016, 'plos', 'Predicting Achievable Fundamental Frequency Ranges in Vocalization Across Species', 'Titze, Ingo|Riede, Tobias|Mau, Ted', 'National Center for Voice and Speech, University of Utah, Salt Lake City, Utah, United States of America.|National Center for Voice and Speech, University of Utah, Salt Lake City, Utah, United States of America.|Department of Otolaryngology-Head and Neck Surgery, University of Texas Southwestern Medical Center, Dallas, Texas, United States of America.', 'United States|United States|United States', 8, 'Acoustics|Animals|Computational Biology|Female|Humans|Larynx|Male|Models, Biological|Species Specificity|Speech Acoustics|Vibration|Vocal Cords|Vocalization, Animal', 'Journal Article', '10.1371/journal.pcbi.1004907', '27309543', 'Vocal folds are used as sound sources in various species, but it is unknown how vocal fold morphologies are optimized for different acoustic objectives. Here we identify two main variables affecting range of vocal fold vibration frequency, namely vocal fold elongation and tissue fiber stress. A simple vibrating string model is used to predict fundamental frequency ranges across species of different vocal fold sizes. While average fundamental frequency is predominantly determined by vocal fold length (larynx size), range of fundamental frequency is facilitated by (1) laryngeal muscles that control elongation and by (2) nonlinearity in tissue fiber tension. One adaptation that would increase fundamental frequency range is greater freedom in joint rotation or gliding of two cartilages (thyroid and cricoid), so that vocal fold length change is maximized. Alternatively, tissue layers can develop to bear a disproportionate fiber tension (i.e., a ligament with high density collagen fibers), increasing the fundamental frequency range and thereby vocal versatility. The range of fundamental frequency across species is thus not simply one-dimensional, but can be conceptualized as the dependent variable in a multi-dimensional morphospace. In humans, this could allow for variations that could be clinically important for voice therapy and vocal fold repair. Alternative solutions could also have importance in vocal training for singing and other highly-skilled vocalizations.'),
(87880, 2016, 'plos', 'Training in High-Throughput Sequencing: Common Guidelines to Enable Material Sharing, Dissemination, and Reusability', 'Schiffthaler, Bastian|Kostadima, Myrto|NGS Trainer Consortium|Delhomme, Nicolas|Rustici, Gabriella', 'Department of Plant Physiology, Umeå Plant Science Centre, Umeå University, Umeå, Sweden.|Department of Haematology, University of Cambridge, Cambridge, United Kingdom.|Department of Haematology, University of Cambridge, Cambridge, United Kingdom.|Department of Plant Physiology, Umeå Plant Science Centre, Umeå University, Umeå, Sweden.|School of Biological Sciences, Department of Genetics, University of Cambridge, Cambridge, United Kingdom.', 'Sweden|United Kingdom|United Kingdom|Sweden|United Kingdom', 3, 'Algorithms|Computational Biology|Data Interpretation, Statistical|Education|High-Throughput Nucleotide Sequencing|Humans|Teaching', 'Journal Article', '10.1371/journal.pcbi.1004937', '27309738', 'The advancement of high-throughput sequencing (HTS) technologies and the rapid development of numerous analysis algorithms and pipelines in this field has resulted in an unprecedentedly high demand for training scientists in HTS data analysis. Embarking on developing new training materials is challenging for many reasons. Trainers often do not have prior experience in preparing or delivering such materials and struggle to keep them up to date. A repository of curated HTS training materials would support trainers in materials preparation, reduce the duplication of effort by increasing the usage of existing materials, and allow for the sharing of teaching experience among the HTS trainers community. To achieve this, we have developed a strategy for materials curation and dissemination. Standards for describing training materials have been proposed and applied to the curation of existing materials. A Git repository has been set up for sharing annotated materials that can now be reused, modified, or incorporated into new courses. This repository uses Git, hence, it is decentralized and self-managed by the community and can be forked/built-upon by all users. The repository is accessible at http://bioinformatics.upsc.se/htmr.'),
(87881, 2016, 'plos', 'Integration and Fixation Preferences of Human and Mouse Endogenous Retroviruses Uncovered with Functional Data Analysis', 'Campos-Sánchez, Rebeca|Cremona, Marzia A|Pini, Alessia|Chiaromonte, Francesca|Makova, Kateryna D', 'Genetics Graduate Program, The Huck Institutes of the Life Sciences, Penn State University, University Park, Pennsylvania, United States of America.|MOX-Modeling and Scientific Computing, Department of Mathematics, Politecnico di Milano, Milano, Italy.|MOX-Modeling and Scientific Computing, Department of Mathematics, Politecnico di Milano, Milano, Italy.|Department of Statistics, Penn State University, University Park, Pennsylvania, United States of America.|Center for Medical Genomics, The Huck Institutes of the Life Sciences, Penn State University, University Park, Pennsylvania, United States of America.', 'United States|Italy|Italy|United States|United States', 9, 'Animals|Chromosome Mapping|Computational Biology|DNA Replication|Data Interpretation, Statistical|Endogenous Retroviruses|Epigenesis, Genetic|Genome, Human|Humans|Logistic Models|Mice|Models, Biological|Recombination, Genetic|Repetitive Sequences, Nucleic Acid|Selection, Genetic|Virus Integration', 'Journal Article', '10.1371/journal.pcbi.1004956', '27309962', 'Endogenous retroviruses (ERVs), the remnants of retroviral infections in the germ line, occupy ~8% and ~10% of the human and mouse genomes, respectively, and affect their structure, evolution, and function. Yet we still have a limited understanding of how the genomic landscape influences integration and fixation of ERVs. Here we conducted a genome-wide study of the most recently active ERVs in the human and mouse genome. We investigated 826 fixed and 1,065 in vitro HERV-Ks in human, and 1,624 fixed and 242 polymorphic ETns, as well as 3,964 fixed and 1,986 polymorphic IAPs, in mouse. We quantitated >40 human and mouse genomic features (e.g., non-B DNA structure, recombination rates, and histone modifications) in ±32 kb of these ERVs integration sites and in control regions, and analyzed them using Functional Data Analysis (FDA) methodology. In one of the first applications of FDA in genomics, we identified genomic scales and locations at which these features display their influence, and how they work in concert, to provide signals essential for integration and fixation of ERVs. The investigation of ERVs of different evolutionary ages (young in vitro and polymorphic ERVs, older fixed ERVs) allowed us to disentangle integration vs. fixation preferences. As a result of these analyses, we built a comprehensive model explaining the uneven distribution of ERVs along the genome. We found that ERVs integrate in late-replicating AT-rich regions with abundant microsatellites, mirror repeats, and repressive histone marks. Regions favoring fixation are depleted of genes and evolutionarily conserved elements, and have low recombination rates, reflecting the effects of purifying selection and ectopic recombination removing ERVs from the genome. In addition to providing these biological insights, our study demonstrates the power of exploiting multiple scales and localization with FDA. These powerful techniques are expected to be applicable to many other genomic investigations.'),
(87882, 2016, 'plos', 'Mechanistic Mathematical Modeling Tests Hypotheses of the Neurovascular Coupling in fMRI', 'Lundengård, Karin|Cedersund, Gunnar|Sten, Sebastian|Leong, Felix|Smedberg, Alexander|Elinder, Fredrik|Engström, Maria', 'Department of Medical and Health Sciences, Linköping University, Linköping, Sweden.|Department of Biomedical Engineering, Linköping University, Linköping, Sweden.|Department of Medical and Health Sciences, Linköping University, Linköping, Sweden.|Department of Medical and Health Sciences, Linköping University, Linköping, Sweden.|Department of Medical and Health Sciences, Linköping University, Linköping, Sweden.|Department of Clinical and Experimental Medicine, Linköping University, Linköping, Sweden.|Department of Medical and Health Sciences, Linköping University, Linköping, Sweden.', 'Sweden|Sweden|Sweden|Sweden|Sweden|Sweden|Sweden', 4, 'Adult|Brain|Cerebrovascular Circulation|Female|Hemoglobins|Humans|Magnetic Resonance Imaging|Male|Models, Neurological|Neurovascular Coupling|Oxygen|Oxyhemoglobins|Signal Processing, Computer-Assisted|Young Adult', 'Journal Article', '10.1371/journal.pcbi.1004971', '27310017', 'Functional magnetic resonance imaging (fMRI) measures brain activity by detecting the blood-oxygen-level dependent (BOLD) response to neural activity. The BOLD response depends on the neurovascular coupling, which connects cerebral blood flow, cerebral blood volume, and deoxyhemoglobin level to neuronal activity. The exact mechanisms behind this neurovascular coupling are not yet fully investigated. There are at least three different ways in which these mechanisms are being discussed. Firstly, mathematical models involving the so-called Balloon model describes the relation between oxygen metabolism, cerebral blood volume, and cerebral blood flow. However, the Balloon model does not describe cellular and biochemical mechanisms. Secondly, the metabolic feedback hypothesis, which is based on experimental findings on metabolism associated with brain activation, and thirdly, the neurotransmitter feed-forward hypothesis which describes intracellular pathways leading to vasoactive substance release. Both the metabolic feedback and the neurotransmitter feed-forward hypotheses have been extensively studied, but only experimentally. These two hypotheses have never been implemented as mathematical models. Here we investigate these two hypotheses by mechanistic mathematical modeling using a systems biology approach, these methods have been used in biological research for many years but never been applied to the BOLD response in fMRI. In the current work, model structures describing the metabolic feedback and the neurotransmitter feed-forward hypotheses were applied to measured BOLD responses in the visual cortex of 12 healthy volunteers. Evaluating each hypothesis separately shows that neither hypothesis alone can describe the data in a biologically plausible way. However, by adding metabolism to the neurotransmitter feed-forward model structure, we obtained a new model structure which is able to fit the estimation data and successfully predict new, independent validation data. These results open the door to a new type of fMRI analysis that more accurately reflects the true neuronal activity.'),
(87883, 2016, 'plos', 'Graded, Dynamically Routable Information Processing with Synfire-Gated Synfire Chains', 'Wang, Zhuo|Sornborger, Andrew T|Tao, Louis', 'Center for Bioinformatics, National Laboratory of Protein Engineering and Plant Genetic Engineering, College of Life Sciences, Peking University, Beijing, Peoples Republic of China.|Department of Mathematics, University of California, Davis, Davis, California, United States of America.|Center for Bioinformatics, National Laboratory of Protein Engineering and Plant Genetic Engineering, College of Life Sciences, Peking University, Beijing, Peoples Republic of China.', 'China|United States|China', 9, 'Action Potentials|Animals|Cognition|Decision Making|Humans|Mammals|Models, Neurological|Neural Networks (Computer)|Synaptic Transmission', 'Journal Article', '10.1371/journal.pcbi.1004979', '27310184', 'Coherent neural spiking and local field potentials are believed to be signatures of the binding and transfer of information in the brain. Coherent activity has now been measured experimentally in many regions of mammalian cortex. Recently experimental evidence has been presented suggesting that neural information is encoded and transferred in packets, i.e., in stereotypical, correlated spiking patterns of neural activity. Due to their relevance to coherent spiking, synfire chains are one of the main theoretical constructs that have been appealed to in order to describe coherent spiking and information transfer phenomena. However, for some time, it has been known that synchronous activity in feedforward networks asymptotically either approaches an attractor with fixed waveform and amplitude, or fails to propagate. This has limited the classical synfire chains ability to explain graded neuronal responses. Recently, we have shown that pulse-gated synfire chains are capable of propagating graded information coded in mean population current or firing rate amplitudes. In particular, we showed that it is possible to use one synfire chain to provide gating pulses and a second, pulse-gated synfire chain to propagate graded information. We called these circuits synfire-gated synfire chains (SGSCs). Here, we present SGSCs in which graded information can rapidly cascade through a neural circuit, and show a correspondence between this type of transfer and a mean-field model in which gating pulses overlap in time. We show that SGSCs are robust in the presence of variability in population size, pulse timing and synaptic strength. Finally, we demonstrate the computational capabilities of SGSC-based information coding by implementing a self-contained, spike-based, modular neural circuit that is triggered by streaming input, processes the input, then makes a decision based on the processed information and shuts itself down.'),
(87884, 2016, 'plos', 'Formal Models of the Network Co-occurrence Underlying Mental Operations', 'Bzdok, Danilo|Varoquaux, Gaël|Grisel, Olivier|Eickenberg, Michael|Poupon, Cyril|Thirion, Bertrand', 'Department of Psychiatry, Psychotherapy and Psychosomatics, RWTH Aachen University, Aachen, Germany.|Parietal team, INRIA, Neurospin, bat 145, CEA Saclay, Gif-sur-Yvette, France.|Parietal team, INRIA, Neurospin, bat 145, CEA Saclay, Gif-sur-Yvette, France.|Parietal team, INRIA, Neurospin, bat 145, CEA Saclay, Gif-sur-Yvette, France.|NeuroSpin, CEA, bat 145, CEA Saclay, Gif-sur-Yvette, France.|Parietal team, INRIA, Neurospin, bat 145, CEA Saclay, Gif-sur-Yvette, France.', 'Germany|France|France|France|France|France', 0, 'Adult|Brain|Cognition|Female|Humans|Learning|Machine Learning|Male|Models, Neurological|Nerve Net|Neurons|Young Adult', 'Journal Article', '10.1371/journal.pcbi.1004994', '27310288', 'Systems neuroscience has identified a set of canonical large-scale networks in humans. These have predominantly been characterized by resting-state analyses of the task-unconstrained, mind-wandering brain. Their explicit relationship to defined task performance is largely unknown and remains challenging. The present work contributes a multivariate statistical learning approach that can extract the major brain networks and quantify their configuration during various psychological tasks. The method is validated in two extensive datasets (n = 500 and n = 81) by model-based generation of synthetic activity maps from recombination of shared network topographies. To study a use case, we formally revisited the poorly understood difference between neural activity underlying idling versus goal-directed behavior. We demonstrate that task-specific neural activity patterns can be explained by plausible combinations of resting-state networks. The possibility of decomposing a mental task into the relative contributions of major brain networks, the network co-occurrence architecture of a given task, opens an alternative access to the neural substrates of human cognition.'),
(87885, 2016, 'plos', 'Correction: Evolution of Self-Organized Task Specialization in Robot Swarms', 'PLOS Computational Biology Staff', 'Parietal team, INRIA, Neurospin, bat 145, CEA Saclay, Gif-sur-Yvette, France.', 'France', 0, '-', 'Published Erratum', '10.1371/journal.pcbi.1004996', '27310442', '[This corrects the article DOI: 10.1371/journal.pcbi.1004273.].'),
(87886, 2016, 'plos', 'Pervasive Selection for Cooperative Cross-Feeding in Bacterial Communities', 'Germerodt, Sebastian|Bohl, Katrin|Lück, Anja|Pande, Samay|Schröter, Anja|Kaleta, Christoph|Schuster, Stefan|Kost, Christian', 'Department of Bioinformatics, Friedrich Schiller University Jena, Germany.|Department of Bioinformatics, Friedrich Schiller University Jena, Germany.|Department of Bioinformatics, Friedrich Schiller University Jena, Germany.|Experimental Ecology and Evolution Research Group, Department of Bioorganic Chemistry, Max Planck Institute for Chemical Ecology, Jena, Germany.|Department of Bioinformatics, Friedrich Schiller University Jena, Germany.|Research Group Theoretical Systems Biology, Friedrich Schiller University Jena, Germany.|Department of Bioinformatics, Friedrich Schiller University Jena, Germany.|Experimental Ecology and Evolution Research Group, Department of Bioorganic Chemistry, Max Planck Institute for Chemical Ecology, Jena, Germany.', 'Germany|Germany|Germany|Germany|Germany|Germany|Germany|Germany', 35, 'Amino Acids|Bacteria|Computational Biology|Computer Simulation|Genotype|Microbial Consortia|Microbial Interactions', 'Journal Article', '10.1371/journal.pcbi.1004986', '27314840', 'Bacterial communities are taxonomically highly diverse, yet the mechanisms that maintain this diversity remain poorly understood. We hypothesized that an obligate and mutual exchange of metabolites, as is very common among bacterial cells, could stabilize different genotypes within microbial communities. To test this, we developed a cellular automaton to model interactions among six empirically characterized genotypes that differ in their ability and propensity to produce amino acids. By systematically varying intrinsic (i.e. benefit-to-cost ratio) and extrinsic parameters (i.e. metabolite diffusion level, environmental amino acid availability), we show that obligate cross-feeding of essential metabolites is selected for under a broad range of conditions. In spatially structured environments, positive assortment among cross-feeders resulted in the formation of cooperative clusters, which limited exploitation by non-producing auxotrophs, yet allowed them to persist at the clusters periphery. Strikingly, cross-feeding helped to maintain genotypic diversity within populations, while amino acid supplementation to the environment decoupled obligate interactions and favored auxotrophic cells that saved amino acid production costs over metabolically autonomous prototrophs. Together, our results suggest that spatially structured environments and limited nutrient availabilities should facilitate the evolution of metabolic interactions, which can help to maintain genotypic diversity within natural microbial populations.'),
(87887, 2016, 'plos', 'Filopodial-Tension Model of Convergent-Extension of Tissues', 'Belmonte, Julio M|Swat, Maciej H|Glazier, James A', 'Biocomplexity Institute and Department of Physics, Indiana University Bloomington, Bloomington, Indiana, United States of America.|Biocomplexity Institute and Department of Physics, Indiana University Bloomington, Bloomington, Indiana, United States of America.|Biocomplexity Institute and Department of Intelligent Systems Engineering, Indiana University Bloomington, Bloomington, Indiana, United States of America.', 'India|India|India', 0, 'Animals|Cell Adhesion|Cell Polarity|Computer Simulation|Elastic Modulus|Embryonic Development|Feedback, Physiological|Humans|Mechanotransduction, Cellular|Models, Biological|Pseudopodia|Stress, Mechanical|Tensile Strength', 'Journal Article', '10.1371/journal.pcbi.1004952', '27322528', 'In convergent-extension (CE), a planar-polarized epithelial tissue elongates (extends) in-plane in one direction while shortening (converging) in the perpendicular in-plane direction, with the cells both elongating and intercalating along the converging axis. CE occurs during the development of most multicellular organisms. Current CE models assume cell or tissue asymmetry, but neglect the preferential filopodial activity along the convergent axis observed in many tissues. We propose a cell-based CE model based on asymmetric filopodial tension forces between cells and investigate how cell-level filopodial interactions drive tissue-level CE. The final tissue geometry depends on the balance between external rounding forces and cell-intercalation traction. Filopodial-tension CE is robust to relatively high levels of planar cell polarity misalignment and to the presence of non-active cells. Addition of a simple mechanical feedback between cells fully rescues and even improves CE of tissues with high levels of polarity misalignments. Our model extends easily to three dimensions, with either one converging and two extending axes, or two converging and one extending axes, producing distinct tissue morphologies, as observed in vivo.'),
(87888, 2016, 'plos', 'The Computational Development of Reinforcement Learning during Adolescence', 'Palminteri, Stefano|Kilford, Emma J|Coricelli, Giorgio|Blakemore, Sarah-Jayne', 'Institute of Cognitive Neuroscience, University College London, London, United Kingdom.|Institute of Cognitive Neuroscience, University College London, London, United Kingdom.|Interdepartmental Centre for Mind/Brain Sciences, Università degli Studi di Trento, Trento, Italy.|Institute of Cognitive Neuroscience, University College London, London, United Kingdom.', 'United Kingdom|United Kingdom|Italy|United Kingdom', 29, 'Adolescent|Adolescent Behavior|Adult|Aging|Algorithms|Child|Computer Simulation|Decision Making|Decision Support Techniques|Female|Humans|Male|Models, Educational|Reward|Young Adult', 'Journal Article', '10.1371/journal.pcbi.1004953', '27322574', 'Adolescence is a period of life characterised by changes in learning and decision-making. Learning and decision-making do not rely on a unitary system, but instead require the coordination of different cognitive processes that can be mathematically formalised as dissociable computational modules. Here, we aimed to trace the developmental time-course of the computational modules responsible for learning from reward or punishment, and learning from counterfactual feedback. Adolescents and adults carried out a novel reinforcement learning paradigm in which participants learned the association between cues and probabilistic outcomes, where the outcomes differed in valence (reward versus punishment) and feedback was either partial or complete (either the outcome of the chosen option only, or the outcomes of both the chosen and unchosen option, were displayed). Computational strategies changed during development: whereas adolescents behaviour was better explained by a basic reinforcement learning algorithm, adults behaviour integrated increasingly complex computational features, namely a counterfactual learning module (enabling enhanced performance in the presence of complete feedback) and a value contextualisation module (enabling symmetrical reward and punishment learning). Unlike adults, adolescent performance did not benefit from counterfactual (complete) feedback. In addition, while adults learned symmetrically from both reward and punishment, adolescents learned from reward but were less likely to learn from punishment. This tendency to rely on rewards and not to consider alternative consequences of actions might contribute to our understanding of decision-making in adolescence.'),
(87889, 2016, 'plos', 'Roles for Coincidence Detection in Coding Amplitude-Modulated Sounds', 'Ashida, Go|Kretzberg, Jutta|Tollin, Daniel J', 'Cluster of Excellence Hearing4all, Department for Neuroscience, Faculty 6, University of Oldenburg, Oldenburg, Germany.|Cluster of Excellence Hearing4all, Department for Neuroscience, Faculty 6, University of Oldenburg, Oldenburg, Germany.|Department of Physiology and Biophysics, University of Colorado School of Medicine, Aurora, Colorado, United States of America.', 'Germany|Germany|United States', 15, 'Action Potentials|Animals|Auditory Pathways|Cats|Models, Neurological|Neurons|Olivary Nucleus|Sound Localization|Time Factors', 'Journal Article', '10.1371/journal.pcbi.1004997', '27322612', 'Many sensory neurons encode temporal information by detecting coincident arrivals of synaptic inputs. In the mammalian auditory brainstem, binaural neurons of the medial superior olive (MSO) are known to act as coincidence detectors, whereas in the lateral superior olive (LSO) roles of coincidence detection have remained unclear. LSO neurons receive excitatory and inhibitory inputs driven by ipsilateral and contralateral acoustic stimuli, respectively, and vary their output spike rates according to interaural level differences. In addition, LSO neurons are also sensitive to binaural phase differences of low-frequency tones and envelopes of amplitude-modulated (AM) sounds. Previous physiological recordings in vivo found considerable variations in monaural AM-tuning across neurons. To investigate the underlying mechanisms of the observed temporal tuning properties of LSO and their sources of variability, we used a simple coincidence counting model and examined how specific parameters of coincidence detection affect monaural and binaural AM coding. Spike rates and phase-locking of evoked excitatory and spontaneous inhibitory inputs had only minor effects on LSO output to monaural AM inputs. In contrast, the coincidence threshold of the model neuron affected both the overall spike rates and the half-peak positions of the AM-tuning curve, whereas the width of the coincidence window merely influenced the output spike rates. The duration of the refractory period affected only the low-frequency portion of the monaural AM-tuning curve. Unlike monaural AM coding, temporal factors, such as the coincidence window and the effective duration of inhibition, played a major role in determining the trough positions of simulated binaural phase-response curves. In addition, empirically-observed level-dependence of binaural phase-coding was reproduced in the framework of our minimalistic coincidence counting model. These modeling results suggest that coincidence detection of excitatory and inhibitory synaptic inputs is essential for LSO neurons to encode both monaural and binaural AM sounds.');
INSERT INTO `papers` (`id`, `ano`, `journal`, `titulo`, `autores`, `afiliacao`, `pais`, `citacoes`, `palavra_chave`, `categorias`, `doi`, `pubmed`, `abstract`) VALUES
(87890, 2016, 'plos', 'MEGAN Community Edition - Interactive Exploration and Analysis of Large-Scale Microbiome Sequencing Data', 'Huson, Daniel H|Beier, Sina|Flade, Isabell|Górska, Anna|El-Hadidi, Mohamed|Mitra, Suparna|Ruscheweyh, Hans-Joachim|Tappu, Rewati', 'Center for Bioinformatics, University of Tübingen, Tübingen, Germany.|Center for Bioinformatics, University of Tübingen, Tübingen, Germany.|CeMeT GmbH, Tübingen, Germany.|Center for Bioinformatics, University of Tübingen, Tübingen, Germany.|Center for Bioinformatics, University of Tübingen, Tübingen, Germany.|Norwich Medical School, University of East Anglia, Norwich, United Kingdom.|Center for Bioinformatics, University of Tübingen, Tübingen, Germany.|Center for Bioinformatics, University of Tübingen, Tübingen, Germany.', 'Germany|Germany|Germany|Germany|Germany|United Kingdom|Germany|Germany', 0, 'Genome, Bacterial|High-Throughput Nucleotide Sequencing|Metagenome|Microbiota|Sequence Analysis, DNA|Software|User-Computer Interface', 'Journal Article', '10.1371/journal.pcbi.1004957', '27327495', 'There is increasing interest in employing shotgun sequencing, rather than amplicon sequencing, to analyze microbiome samples. Typical projects may involve hundreds of samples and billions of sequencing reads. The comparison of such samples against a protein reference database generates billions of alignments and the analysis of such data is computationally challenging. To address this, we have substantially rewritten and extended our widely-used microbiome analysis tool MEGAN so as to facilitate the interactive analysis of the taxonomic and functional content of very large microbiome datasets. Other new features include a functional classifier called InterPro2GO, gene-centric read assembly, principal coordinate analysis of taxonomy and function, and support for metadata. The new program is called MEGAN Community Edition (CE) and is open source. By integrating MEGAN CE with our high-throughput DNA-to-protein alignment tool DIAMOND and by providing a new program MeganServer that allows access to metagenome analysis files hosted on a server, we provide a straightforward, yet powerful and complete pipeline for the analysis of metagenome shotgun sequences. We illustrate how to perform a full-scale computational analysis of a metagenomic sequencing project, involving 12 samples and 800 million reads, in less than three days on a single server. All source code is available here: https://github.com/danielhuson/megan-ce.'),
(87891, 2016, 'plos', 'Novel Computational Protocols for Functionally Classifying and Characterising Serine Beta-Lactamases', 'Lee, David|Das, Sayoni|Dawson, Natalie L|Dobrijevic, Dragana|Ward, John|Orengo, Christine', 'Institute of Structural and Molecular Biology, University College London, London, United Kingdom.|Institute of Structural and Molecular Biology, University College London, London, United Kingdom.|Institute of Structural and Molecular Biology, University College London, London, United Kingdom.|Department of Biochemical Engineering, University College London, London, United Kingdom.|Department of Biochemical Engineering, University College London, London, United Kingdom.|Institute of Structural and Molecular Biology, University College London, London, United Kingdom.', 'United Kingdom|United Kingdom|United Kingdom|United Kingdom|United Kingdom|United Kingdom', 0, 'Algorithms|Binding Sites|Computer Simulation|Drug Resistance, Bacterial|Enzyme Activation|Molecular Docking Simulation|Protein Binding|Sequence Analysis, Protein|Serine|Software|Structure-Activity Relationship|Substrate Specificity|beta-Lactam Resistance|beta-Lactamase Inhibitors|beta-Lactamases', 'Journal Article', '10.1371/journal.pcbi.1004926', '27332861', 'Beta-lactamases represent the main bacterial mechanism of resistance to beta-lactam antibiotics and are a significant challenge to modern medicine. We have developed an automated classification and analysis protocol that exploits structure- and sequence-based approaches and which allows us to propose a grouping of serine beta-lactamases that more consistently captures and rationalizes the existing three classification schemes: Classes, (A, C and D, which vary in their implementation of the mechanism of action), Types (that largely reflect evolutionary distance measured by sequence similarity), and Variant groups (which largely correspond with the Bush-Jacoby clinical groups). Our analysis platform exploits a suite of in-house and public tools to identify Functional Determinants (FDs), i.e. residue sites, responsible for conferring different phenotypes between different classes, different types and different variants. We focused on Class A beta-lactamases, the most highly populated and clinically relevant class, to identify FDs implicated in the distinct phenotypes associated with different Class A Types and Variants. We show that our FunFHMMer method can separate the known beta-lactamase classes and identify those positions likely to be responsible for the different implementations of the mechanism of action in these enzymes. Two novel algorithms, ASSP and SSPA, allow detection of FD sites likely to contribute to the broadening of the substrate profiles. Using our approaches, we recognise 151 Class A types in UniProt. Finally, we used our beta-lactamase FunFams and ASSP profiles to detect 4 novel Class A types in microbiome samples. Our platforms have been validated by literature studies, in silico analysis and some targeted experimental verification. Although developed for the serine beta-lactamases they could be used to classify and analyse any diverse protein superfamily where sub-families have diverged over both long and short evolutionary timescales.'),
(87892, 2016, 'plos', 'A Mathematical Model of Neonatal Rat Atrial Monolayers with Constitutively Active Acetylcholine-Mediated K+ Current', 'Majumder, Rupamanjari|Jangsangthong, Wanchana|Feola, Iolanda|Ypey, Dirk L|Pijnappels, Daniël A|Panfilov, Alexander V', 'Laboratory of Experimental Cardiology, Department of Cardiology, Heart Lung Center Leiden, Leiden University Medical Center, Leiden, the Netherlands.|Laboratory of Experimental Cardiology, Department of Cardiology, Heart Lung Center Leiden, Leiden University Medical Center, Leiden, the Netherlands.|Laboratory of Experimental Cardiology, Department of Cardiology, Heart Lung Center Leiden, Leiden University Medical Center, Leiden, the Netherlands.|Laboratory of Experimental Cardiology, Department of Cardiology, Heart Lung Center Leiden, Leiden University Medical Center, Leiden, the Netherlands.|Laboratory of Experimental Cardiology, Department of Cardiology, Heart Lung Center Leiden, Leiden University Medical Center, Leiden, the Netherlands.|Department of Physics and Astronomy, Ghent University, Ghent, Belgium.', 'Netherlands|Netherlands|Netherlands|Netherlands|Netherlands|Belgium', 0, 'Acetylcholine|Action Potentials|Animals|Animals, Newborn|Atrial Function|Computer Simulation|Ion Channel Gating|Models, Cardiovascular|Myocytes, Cardiac|Potassium|Rats|Sodium Channels', 'Journal Article', '10.1371/journal.pcbi.1004946', '27332890', 'Atrial fibrillation (AF) is the most frequent form of arrhythmia occurring in the industrialized world. Because of its complex nature, each identified form of AF requires specialized treatment. Thus, an in-depth understanding of the bases of these arrhythmias is essential for therapeutic development. A variety of experimental studies aimed at understanding the mechanisms of AF are performed using primary cultures of neonatal rat atrial cardiomyocytes (NRAMs). Previously, we have shown that the distinct advantage of NRAM cultures is that they allow standardized, systematic, robust re-entry induction in the presence of a constitutively-active acetylcholine-mediated K+ current (IKACh-c). Experimental studies dedicated to mechanistic explorations of AF, using these cultures, often use computer models for detailed electrophysiological investigations. However, currently, no mathematical model for NRAMs is available. Therefore, in the present study we propose the first model for the action potential (AP) of a NRAM with constitutively-active acetylcholine-mediated K+ current (IKACh-c). The descriptions of the ionic currents were based on patch-clamp data obtained from neonatal rats. Our monolayer model closely mimics the action potential duration (APD) restitution and conduction velocity (CV) restitution curves presented in our previous in vitro studies. In addition, the model reproduces the experimentally observed dynamics of spiral wave rotation, in the absence and in the presence of drug interventions, and in the presence of localized myofibroblast heterogeneities.'),
(87893, 2016, 'plos', 'QuIN: A Web Server for Querying and Visualizing Chromatin Interaction Networks', 'Thibodeau, Asa|Márquez, Eladio J|Luo, Oscar|Ruan, Yijun|Menghi, Francesca|Shin, Dong-Guk|Stitzel, Michael L|Vera-Licona, Paola|Ucar, Duygu', 'Department of Computer Science, University of Connecticut, Storrs, Connecticut, United States of America.|The Jackson Laboratory for Genomic Medicine, Farmington, Connecticut, United States of America.|The Jackson Laboratory for Genomic Medicine, Farmington, Connecticut, United States of America.|The Jackson Laboratory for Genomic Medicine, Farmington, Connecticut, United States of America.|The Jackson Laboratory for Genomic Medicine, Farmington, Connecticut, United States of America.|Department of Computer Science, University of Connecticut, Storrs, Connecticut, United States of America.|The Jackson Laboratory for Genomic Medicine, Farmington, Connecticut, United States of America.|Institute of Systems Genomics, University of Connecticut Health Center, Farmington, Connecticut, United States of America.|The Jackson Laboratory for Genomic Medicine, Farmington, Connecticut, United States of America.', 'United States|United States|United States|United States|United States|United States|United States|Un', 6, 'Binding Sites|Chromatin|Data Mining|Epigenesis, Genetic|Internet|Polymorphism, Single Nucleotide|Protein Binding|Protein Interaction Mapping|Regulatory Elements, Transcriptional|Signal Transduction|Software|User-Computer Interface', 'Journal Article', '10.1371/journal.pcbi.1004809', '27336171', 'Recent studies of the human genome have indicated that regulatory elements (e.g. promoters and enhancers) at distal genomic locations can interact with each other via chromatin folding and affect gene expression levels. Genomic technologies for mapping interactions between DNA regions, e.g., ChIA-PET and HiC, can generate genome-wide maps of interactions between regulatory elements. These interaction datasets are important resources to infer distal gene targets of non-coding regulatory elements and to facilitate prioritization of critical loci for important cellular functions. With the increasing diversity and complexity of genomic information and public ontologies, making sense of these datasets demands integrative and easy-to-use software tools. Moreover, network representation of chromatin interaction maps enables effective data visualization, integration, and mining. Currently, there is no software that can take full advantage of network theory approaches for the analysis of chromatin interaction datasets. To fill this gap, we developed a web-based application, QuIN, which enables: 1) building and visualizing chromatin interaction networks, 2) annotating networks with user-provided private and publicly available functional genomics and interaction datasets, 3) querying network components based on gene name or chromosome location, and 4) utilizing network based measures to identify and prioritize critical regulatory targets and their direct and indirect interactions.'),
(87894, 2016, 'plos', 'Electrophysiology of Heart Failure Using a Rabbit Model: From the Failing Myocyte to Ventricular Fibrillation', 'Ponnaluri, Aditya V S|Perotti, Luigi E|Liu, Michael|Qu, Zhilin|Weiss, James N|Ennis, Daniel B|Klug, William S|Garfinkel, Alan', 'Department of Mechanical and Aerospace Engineering, University of California Los Angeles, Los Angeles, California, United States of America.|Department of Radiological Sciences and Department of Bioengineering, University of California Los Angeles, Los Angeles, California, United States of America.|Department of Medicine - Division of Cardiology, University of California Los Angeles, Los Angeles, California, United States of America.|Department of Medicine - Division of Cardiology, University of California Los Angeles, Los Angeles, California, United States of America.|Department of Medicine - Division of Cardiology, University of California Los Angeles, Los Angeles, California, United States of America.|Department of Radiological Sciences and Department of Bioengineering, University of California Los Angeles, Los Angeles, California, United States of America.|Department of Mechanical and Aerospace Engineering, University of California Los Angeles, Los Angeles, California, United States of America.|Department of Medicine - Division of Cardiology, University of California Los Angeles, Los Angeles, California, United States of America.', 'United States|United States|United States|United States|United States|United States|United States|Un', 0, 'Animals|Electrophysiological Phenomena|Heart Conduction System|Heart Failure|Models, Cardiovascular|Myocytes, Cardiac|Rabbits|Ventricular Fibrillation', 'Journal Article', '10.1371/journal.pcbi.1004968', '27336310', 'Heart failure is a leading cause of death, yet its underlying electrophysiological (EP) mechanisms are not well understood. In this study, we use a multiscale approach to analyze a model of heart failure and connect its results to features of the electrocardiogram (ECG). The heart failure model is derived by modifying a previously validated electrophysiology model for a healthy rabbit heart. Specifically, in accordance with the heart failure literature, we modified the cell EP by changing both membrane currents and calcium handling. At the tissue level, we modeled the increased gap junction lateralization and lower conduction velocity due to downregulation of Connexin 43. At the biventricular level, we reduced the apex-to-base and transmural gradients of action potential duration (APD). The failing cell model was first validated by reproducing the longer action potential, slower and lower calcium transient, and earlier alternans characteristic of heart failure EP. Subsequently, we compared the electrical wave propagation in one dimensional cables of healthy and failing cells. The validated cell model was then used to simulate the EP of heart failure in an anatomically accurate biventricular rabbit model. As pacing cycle length decreases, both the normal and failing heart develop T-wave alternans, but only the failing heart shows QRS alternans (although moderate) at rapid pacing. Moreover, T-wave alternans is significantly more pronounced in the failing heart. At rapid pacing, APD maps show areas of conduction block in the failing heart. Finally, accelerated pacing initiated wave reentry and breakup in the failing heart. Further, the onset of VF was not observed with an upregulation of SERCA, a potential drug therapy, using the same protocol. The changes introduced at the cell and tissue level have increased the failing hearts susceptibility to dynamic instabilities and arrhythmias under rapid pacing. However, the observed increase in arrhythmogenic potential is not due to a steepening of the restitution curve (not present in our model), but rather to a novel blocking mechanism.'),
(87895, 2016, 'plos', 'Phylogeny Reconstruction with Alignment-Free Method That Corrects for Horizontal Gene Transfer', 'Bromberg, Raquel|Grishin, Nick V|Otwinowski, Zbyszek', 'Department of Biophysics and Department of Biochemistry, University of Texas Southwestern Medical Center at Dallas, Dallas, Texas, United States of America.|Department of Biophysics and Department of Biochemistry, University of Texas Southwestern Medical Center at Dallas, Dallas, Texas, United States of America.|Department of Biophysics and Department of Biochemistry, University of Texas Southwestern Medical Center at Dallas, Dallas, Texas, United States of America.', 'United States|United States|United States', 0, 'Algorithms|Archaea|Bacteria|Computational Biology|Evolution, Molecular|Gene Transfer, Horizontal|Genome, Archaeal|Genome, Bacterial|Phylogeny', 'Journal Article', '10.1371/journal.pcbi.1004985', '27336403', 'Advances in sequencing have generated a large number of complete genomes. Traditionally, phylogenetic analysis relies on alignments of orthologs, but defining orthologs and separating them from paralogs is a complex task that may not always be suited to the large datasets of the future. An alternative to traditional, alignment-based approaches are whole-genome, alignment-free methods. These methods are scalable and require minimal manual intervention. We developed SlopeTree, a new alignment-free method that estimates evolutionary distances by measuring the decay of exact substring matches as a function of match length. SlopeTree corrects for horizontal gene transfer, for composition variation and low complexity sequences, and for branch-length nonlinearity caused by multiple mutations at the same site. We tested SlopeTree on 495 bacteria, 73 archaea, and 72 strains of Escherichia coli and Shigella. We compared our trees to the NCBI taxonomy, to trees based on concatenated alignments, and to trees produced by other alignment-free methods. The results were consistent with current knowledge about prokaryotic evolution. We assessed differences in tree topology over different methods and settings and found that the majority of bacteria and archaea have a core set of proteins that evolves by descent. In trees built from complete genomes rather than sets of core genes, we observed some grouping by phenotype rather than phylogeny, for instance with a cluster of sulfur-reducing thermophilic bacteria coming together irrespective of their phyla. The source-code for SlopeTree is available at: http://prodata.swmed.edu/download/pub/slopetree_v1/slopetree.tar.gz.'),
(87896, 2016, 'plos', 'Using the Semantic Web for Rapid Integration of WikiPathways with Other Biological Online Data Resources', 'Waagmeester, Andra|Kutmon, Martina|Riutta, Anders|Miller, Ryan|Willighagen, Egon L|Evelo, Chris T|Pico, Alexander R', 'Department of Bioinformatics - BiGCaT, Maastricht University, Maastricht, The Netherlands.|Department of Bioinformatics - BiGCaT, Maastricht University, Maastricht, The Netherlands.|Gladstone Institutes, San Francisco, California, United States of America.|Department of Bioinformatics - BiGCaT, Maastricht University, Maastricht, The Netherlands.|Department of Bioinformatics - BiGCaT, Maastricht University, Maastricht, The Netherlands.|Department of Bioinformatics - BiGCaT, Maastricht University, Maastricht, The Netherlands.|Gladstone Institutes, San Francisco, California, United States of America.', 'Netherlands|Netherlands|United States|Netherlands|Netherlands|Netherlands|United States', 10, 'Biological Ontologies|Biomedical Research|Computational Biology|Humans|Information Storage and Retrieval|Internet|Semantics', 'Journal Article', '10.1371/journal.pcbi.1004989', '27336457', 'The diversity of online resources storing biological data in different formats provides a challenge for bioinformaticians to integrate and analyse their biological data. The semantic web provides a standard to facilitate knowledge integration using statements built as triples describing a relation between two objects. WikiPathways, an online collaborative pathway resource, is now available in the semantic web through a SPARQL endpoint at http://sparql.wikipathways.org. Having biological pathways in the semantic web allows rapid integration with data from other resources that contain information about elements present in pathways using SPARQL queries. In order to convert WikiPathways content into meaningful triples we developed two new vocabularies that capture the graphical representation and the pathway logic, respectively. Each gene, protein, and metabolite in a given pathway is defined with a standard set of identifiers to support linking to several other biological resources in the semantic web. WikiPathways triples were loaded into the Open PHACTS discovery platform and are available through its Web API (https://dev.openphacts.org/docs) to be used in various tools for drug development. We combined various semantic web resources with the newly converted WikiPathways content using a variety of SPARQL query types and third-party resources, such as the Open PHACTS API. The ability to use pathway information to form new links across diverse biological data highlights the utility of integrating WikiPathways in the semantic web.'),
(87897, 2016, 'plos', 'Ensembler: Enabling High-Throughput Molecular Simulations at the Superfamily Scale', 'Parton, Daniel L|Grinaway, Patrick B|Hanson, Sonya M|Beauchamp, Kyle A|Chodera, John D', 'Computational Biology Program, Sloan Kettering Institute, Memorial Sloan Kettering Cancer Center, New York, New York, United States of America.|Graduate Program in Physiology, Biophysics, and Systems Biology, Weill Cornell Medical College, 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.|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', 9, 'Algorithms|Binding Sites|Computer Simulation|Enzyme Activation|High-Throughput Screening Assays|Models, Chemical|Molecular Docking Simulation|Protein Binding|Protein-Tyrosine Kinases|Sequence Analysis, Protein|Software', 'Journal Article', '10.1371/journal.pcbi.1004728', '27337644', 'The rapidly expanding body of available genomic and protein structural data provides a rich resource for understanding protein dynamics with biomolecular simulation. While computational infrastructure has grown rapidly, simulations on an omics scale are not yet widespread, primarily because software infrastructure to enable simulations at this scale has not kept pace. It should now be possible to study protein dynamics across entire (super)families, exploiting both available structural biology data and conformational similarities across homologous proteins. Here, we present a new tool for enabling high-throughput simulation in the genomics era. Ensembler takes any set of sequences-from a single sequence to an entire superfamily-and shepherds them through various stages of modeling and refinement to produce simulation-ready structures. This includes comparative modeling to all relevant PDB structures (which may span multiple conformational states of interest), reconstruction of missing loops, addition of missing atoms, culling of nearly identical structures, assignment of appropriate protonation states, solvation in explicit solvent, and refinement and filtering with molecular simulation to ensure stable simulation. The output of this pipeline is an ensemble of structures ready for subsequent molecular simulations using computer clusters, supercomputers, or distributed computing projects like Folding@home. Ensembler thus automates much of the time-consuming process of preparing protein models suitable for simulation, while allowing scalability up to entire superfamilies. A particular advantage of this approach can be found in the construction of kinetic models of conformational dynamics-such as Markov state models (MSMs)-which benefit from a diverse array of initial configurations that span the accessible conformational states to aid sampling. We demonstrate the power of this approach by constructing models for all catalytic domains in the human tyrosine kinase family, using all available kinase catalytic domain structures from any organism as structural templates. Ensembler is free and open source software licensed under the GNU General Public License (GPL) v2. It is compatible with Linux and OS X. The latest release can be installed via the conda package manager, and the latest source can be downloaded from https://github.com/choderalab/ensembler.'),
(87898, 2016, 'plos', 'The Context-Dependence of Mutations: A Linkage of Formalisms', 'Poelwijk, Frank J|Krishna, Vinod|Ranganathan, Rama', 'Green Center for Systems Biology, University of Texas Southwestern Medical Center, Dallas, Texas, United States of America.|Green Center for Systems Biology, University of Texas Southwestern Medical Center, Dallas, Texas, United States of America.|Green Center for Systems Biology and Departments of Biophysics and Pharmacology, University of Texas Southwestern Medical Center, Dallas, Texas, United States of America.', 'United States|United States|United States', 20, 'Amino Acid Substitution|Base Sequence|Computer Simulation|Epistasis, Genetic|Models, Genetic|Molecular Sequence Data|Mutation|Protein Interaction Mapping|Proteins|Sequence Analysis, DNA', 'Journal Article', '10.1371/journal.pcbi.1004771', '27337695', '-'),
(87899, 2016, 'plos', 'Computationally Efficient Implementation of a Novel Algorithm for the General Unified Threshold Model of Survival (GUTS)', 'Albert, Carlo|Vogel, Sören|Ashauer, Roman', 'Eawag: Swiss Federal Institute of Aquatic Science and Technology, Dübendorf, Switzerland.|Eawag: Swiss Federal Institute of Aquatic Science and Technology, Dübendorf, Switzerland.|Environment Department, University of York, Heslington, York, United Kingdom.', 'Switzerland|Switzerland|United Kingdom', 4, 'Algorithms|Computational Biology|Humans|Markov Chains|Monte Carlo Method|Software|Survival Analysis', 'Journal Article', '10.1371/journal.pcbi.1004978', '27340823', 'The General Unified Threshold model of Survival (GUTS) provides a consistent mathematical framework for survival analysis. However, the calibration of GUTS models is computationally challenging. We present a novel algorithm and its fast implementation in our R package, GUTS, that help to overcome these challenges. We show a step-by-step application example consisting of model calibration and uncertainty estimation as well as making probabilistic predictions and validating the model with new data. Using self-defined wrapper functions, we show how to produce informative text printouts and plots without effort, for the inexperienced as well as the advanced user. The complete ready-to-run script is available as supplemental material. We expect that our software facilitates novel re-analysis of existing survival data as well as asking new research questions in a wide range of sciences. In particular the ability to quickly quantify stressor thresholds in conjunction with dynamic compensating processes, and their uncertainty, is an improvement that complements current survival analysis methods.'),
(87900, 2016, 'plos', 'How to Estimate Epidemic Risk from Incomplete Contact Diaries Data?', 'Mastrandrea, Rossana|Barrat, Alain', 'Aix Marseille Univ, Univ Toulon, CNRS, CPT, Marseille, France.|Aix Marseille Univ, Univ Toulon, CNRS, CPT, Marseille, France.', 'France|France', 6, 'Computational Biology|Computer Simulation|Contact Tracing|Epidemics|Humans|Interpersonal Relations|Models, Theoretical|Risk|Schools', 'Journal Article', '10.1371/journal.pcbi.1005002', '27341027', 'Social interactions shape the patterns of spreading processes in a population. Techniques such as diaries or proximity sensors allow to collect data about encounters and to build networks of contacts between individuals. The contact networks obtained from these different techniques are however quantitatively different. Here, we first show how these discrepancies affect the prediction of the epidemic risk when these data are fed to numerical models of epidemic spread: low participation rate, under-reporting of contacts and overestimation of contact durations in contact diaries with respect to sensor data determine indeed important differences in the outcomes of the corresponding simulations with for instance an enhanced sensitivity to initial conditions. Most importantly, we investigate if and how information gathered from contact diaries can be used in such simulations in order to yield an accurate description of the epidemic risk, assuming that data from sensors represent the ground truth. The contact networks built from contact sensors and diaries present indeed several structural similarities: this suggests the possibility to construct, using only the contact diary network information, a surrogate contact network such that simulations using this surrogate network give the same estimation of the epidemic risk as simulations using the contact sensor network. We present and compare several methods to build such surrogate data, and show that it is indeed possible to obtain a good agreement between the outcomes of simulations using surrogate and sensor data, as long as the contact diary information is complemented by publicly available data describing the heterogeneity of the durations of human contacts.'),
(87901, 2016, 'plos', 'Prospective Coding by Spiking Neurons', 'Brea, Johanni|Gaxc3xa1l, Alexisz Tamxc3xa1s|Urbanczik, Robert|Senn, Walter', 'Department of Physiology, University of Bern, Bern, Switzerland.|Department of Physiology, University of Bern, Bern, Switzerland.|Department of Physiology, University of Bern, Bern, Switzerland.|Department of Physiology, University of Bern, Bern, Switzerland.', 'Switzerland|Switzerland|Switzerland|Switzerland', 11, 'Action Potentials|Animals|Computational Biology|Dendrites|Macaca|Models, Neurological|Neuronal Plasticity|Neurons', 'Journal Article', '10.1371/journal.pcbi.1005003', '27341100', 'Animals learn to make predictions, such as associating the sound of a bell with upcoming feeding or predicting a movement that a motor command is eliciting. How predictions are realized on the neuronal level and what plasticity rule underlies their learning is not well understood. Here we propose a biologically plausible synaptic plasticity rule to learn predictions on a single neuron level on a timescale of seconds. The learning rule allows a spiking two-compartment neuron to match its current firing rate to its own expected future discounted firing rate. For instance, if an originally neutral event is repeatedly followed by an event that elevates the firing rate of a neuron, the originally neutral event will eventually also elevate the neurons firing rate. The plasticity rule is a form of spike timing dependent plasticity in which a presynaptic spike followed by a postsynaptic spike leads to potentiation. Even if the plasticity window has a width of 20 milliseconds, associations on the time scale of seconds can be learned. We illustrate prospective coding with three examples: learning to predict a time varying input, learning to predict the next stimulus in a delayed paired-associate task and learning with a recurrent network to reproduce a temporally compressed version of a sequence. We discuss the potential role of the learning mechanism in classical trace conditioning. In the special case that the signal to be predicted encodes reward, the neuron learns to predict the discounted future reward and learning is closely related to the temporal difference learning algorithm TD(xcexbb).'),
(87902, 2016, 'plos', 'Genes as Cues of Relatedness and Social Evolution in Heterogeneous Environments', 'Leimar, Olof|Dall, Sasha R X|Hammerstein, Peter|McNamara, John M', 'Department of Zoology, Stockholm University, Stockholm, Sweden.|Centre for Ecology and Conservation, University of Exeter, Penryn, United Kingdom.|Institute for Theoretical Biology, Humboldt University Berlin, Berlin, Germany.|School of Mathematics, University of Bristol, Bristol, United Kingdom.', 'Sweden|United Kingdom|Germany|United Kingdom', 4, 'Biological Evolution|Computational Biology|Cues|Ecosystem|Genetic Linkage|Models, Genetic|Polymorphism, Genetic|Social Behavior', 'Journal Article', '10.1371/journal.pcbi.1005006', '27341199', 'There are many situations where relatives interact while at the same time there is genetic polymorphism in traits influencing survival and reproduction. Examples include cheater-cooperator polymorphism and polymorphic microbial pathogens. Environmental heterogeneity, favoring different traits in nearby habitats, with dispersal between them, is one general reason to expect polymorphism. Currently, there is no formal framework of social evolution that encompasses genetic polymorphism. We develop such a framework, thus integrating theories of social evolution into the evolutionary ecology of heterogeneous environments. We allow for adaptively maintained genetic polymorphism by applying the concept of genetic cues. We analyze a model of social evolution in a two-habitat situation with limited dispersal between habitats, in which the average relatedness at the time of helping and other benefits of helping can differ between habitats. An important result from the analysis is that alleles at a polymorphic locus play the role of genetic cues, in the sense that the presence of a cue allele contains statistical information for an organism about its current environment, including information about relatedness. We show that epistatic modifiers of the cue polymorphism can evolve to make optimal use of the information in the genetic cue, in analogy with a Bayesian decision maker. Another important result is that the genetic linkage between a cue locus and modifier loci influences the evolutionary interest of modifiers, with tighter linkage leading to greater divergence between social traits induced by different cue alleles, and this can be understood in terms of genetic conflict.'),
(87903, 2016, 'plos', 'Competitive Dynamics in MSTd: A Mechanism for Robust Heading Perception Based on Optic Flow', 'Layton, Oliver W|Fajen, Brett R', 'Department of Cognitive Science, Rensselaer Polytechnic Institute, Troy, New York, United States of America.|Department of Cognitive Science, Rensselaer Polytechnic Institute, Troy, New York, United States of America.', 'United States|United States', 7, 'Computer Simulation|Humans|Models, Neurological|Motion Perception|Optic Flow|Orientation|Spatial Navigation|Visual Cortex', 'Journal Article', '10.1371/journal.pcbi.1004942', '27341686', 'Human heading perception based on optic flow is not only accurate, it is also remarkably robust and stable. These qualities are especially apparent when observers move through environments containing other moving objects, which introduce optic flow that is inconsistent with observer self-motion and therefore uninformative about heading direction. Moving objects may also occupy large portions of the visual field and occlude regions of the background optic flow that are most informative about heading perception. The fact that heading perception is biased by no more than a few degrees under such conditions attests to the robustness of the visual system and warrants further investigation. The aim of the present study was to investigate whether recurrent, competitive dynamics among MSTd neurons that serve to reduce uncertainty about heading over time offer a plausible mechanism for capturing the robustness of human heading perception. Simulations of existing heading models that do not contain competitive dynamics yield heading estimates that are far more erratic and unstable than human judgments. We present a dynamical model of primate visual areas V1, MT, and MSTd based on that of Layton, Mingolla, and Browning that is similar to the other models, except that the model includes recurrent interactions among model MSTd neurons. Competitive dynamics stabilize the models heading estimate over time, even when a moving object crosses the future path. Soft winner-take-all dynamics enhance units that code a heading direction consistent with the time history and suppress responses to transient changes to the optic flow field. Our findings support recurrent competitive temporal dynamics as a crucial mechanism underlying the robustness and stability of perception of heading.'),
(87904, 2016, 'plos', 'Model Constrained by Visual Hierarchy Improves Prediction of Neural Responses to Natural Scenes', 'Antolík, Ján|Hofer, Sonja B|Bednar, James A|Mrsic-Flogel, Thomas D', 'Unité de Neurosciences, Information et Complexité, CNRS UPR 3293, Gif-sur-Yvette, France.|Department of Neuroscience, Physiology and Pharmacology, University College London, London, United Kingdom.|Institute for Adaptive and Neural Computation, University of Edinburgh, Edinburgh, United Kingdom.|Department of Neuroscience, Physiology and Pharmacology, University College London, London, United Kingdom.', 'France|United Kingdom|United Kingdom|United Kingdom', 18, 'Animals|Computer Simulation|Mice|Models, Neurological|Nerve Net|Neural Pathways|Pattern Recognition, Visual|Thalamus|Visual Cortex|Visual Fields', 'Journal Article', '10.1371/journal.pcbi.1004927', '27348548', 'Accurate estimation of neuronal receptive fields is essential for understanding sensory processing in the early visual system. Yet a full characterization of receptive fields is still incomplete, especially with regard to natural visual stimuli and in complete populations of cortical neurons. While previous work has incorporated known structural properties of the early visual system, such as lateral connectivity, or imposing simple-cell-like receptive field structure, no study has exploited the fact that nearby V1 neurons share common feed-forward input from thalamus and other upstream cortical neurons. We introduce a new method for estimating receptive fields simultaneously for a population of V1 neurons, using a model-based analysis incorporating knowledge of the feed-forward visual hierarchy. We assume that a population of V1 neurons shares a common pool of thalamic inputs, and consists of two layers of simple and complex-like V1 neurons. When fit to recordings of a local population of mouse layer 2/3 V1 neurons, our model offers an accurate description of their response to natural images and significant improvement of prediction power over the current state-of-the-art methods. We show that the responses of a large local population of V1 neurons with locally diverse receptive fields can be described with surprisingly limited number of thalamic inputs, consistent with recent experimental findings. Our structural model not only offers an improved functional characterization of V1 neurons, but also provides a framework for studying the relationship between connectivity and function in visual cortical areas.'),
(87905, 2016, 'plos', 'Isofunctional Protein Subfamily Detection Using Data Integration and Spectral Clustering', 'Boari de Lima, Elisa|Meira, Wagner|Melo-Minardi, Raquel Cardoso de', 'Department of Biochemistry and Immunology, Universidade Federal de Minas Gerais, Belo Horizonte, Minas Gerais, Brazil.|Department of Computer Science, Universidade Federal de Minas Gerais, Belo Horizonte, Minas Gerais, Brazil.|Department of Computer Science, Universidade Federal de Minas Gerais, Belo Horizonte, Minas Gerais, Brazil.', 'Brazil|Brazil|Brazil', 3, 'Algorithms|Amino Acid Sequence|Cluster Analysis|Computational Biology|Databases, Protein|Proteins|Sequence Alignment|Sequence Analysis, Protein', 'Journal Article', '10.1371/journal.pcbi.1005001', '27348631', 'As increasingly more genomes are sequenced, the vast majority of proteins may only be annotated computationally, given experimental investigation is extremely costly. This highlights the need for computational methods to determine protein functions quickly and reliably. We believe dividing a protein family into subtypes which share specific functions uncommon to the whole family reduces the function annotation problems complexity. Hence, this works purpose is to detect isofunctional subfamilies inside a family of unknown function, while identifying differentiating residues. Similarity between protein pairs according to various properties is interpreted as functional similarity evidence. Data are integrated using genetic programming and provided to a spectral clustering algorithm, which creates clusters of similar proteins. The proposed framework was applied to well-known protein families and to a family of unknown function, then compared to ASMC. Results showed our fully automated technique obtained better clusters than ASMC for two families, besides equivalent results for other two, including one whose clusters were manually defined. Clusters produced by our framework showed great correspondence with the known subfamilies, besides being more contrasting than those produced by ASMC. Additionally, for the families whose specificity determining positions are known, such residues were among those our technique considered most important to differentiate a given group. When run with the crotonase and enolase SFLD superfamilies, the results showed great agreement with this gold-standard. Best results consistently involved multiple data types, thus confirming our hypothesis that similarities according to different knowledge domains may be used as functional similarity evidence. Our main contributions are the proposed strategy for selecting and integrating data types, along with the ability to work with noisy and incomplete data, domain knowledge usage for detecting subfamilies in a family with different specificities, thus reducing the complexity of the experimental function characterization problem, and the identification of residues responsible for specificity.'),
(87906, 2016, 'plos', 'Modeling Inter-trial Variability of Saccade Trajectories: Effects of Lesions of the Oculomotor Part of the Fastigial Nucleus', 'Eggert, Thomas|Robinson, Farrel R|Straube, Andreas', 'Department of Neurology, Ludwig-Maximilians University, Munich, Germany.|Department of Biological Structure, University of Washington, Seattle, Washington, United States of America.|Department of Neurology, Ludwig-Maximilians University, Munich, Germany.', 'Germany|United States|Germany', 7, 'Animals|Cerebellar Nuclei|Computer Simulation|Feedback, Sensory|Humans|Macaca mulatta|Models, Neurological|Motor Neurons|Reproducibility of Results|Saccades|Sensitivity and Specificity', 'Journal Article', '10.1371/journal.pcbi.1004866', '27351741', 'This study investigates the inter-trial variability of saccade trajectories observed in five rhesus macaques (Macaca mulatta). For each time point during a saccade, the inter-trial variance of eye position and its covariance with eye end position were evaluated. Data were modeled by a superposition of three noise components due to 1) planning noise, 2) signal-dependent motor noise, and 3) signal-dependent premotor noise entering within an internal feedback loop. Both planning noise and signal-dependent motor noise (together called accumulating noise) predict a simple S-shaped variance increase during saccades, which was not sufficient to explain the data. Adding noise within an internal feedback loop enabled the model to mimic variance/covariance structure in each monkey, and to estimate the noise amplitudes and the feedback gain. Feedback noise had little effect on end point noise, which was dominated by accumulating noise. This analysis was further extended to saccades executed during inactivation of the caudal fastigial nucleus (cFN) on one side of the cerebellum. Saccades ipsiversive to an inactivated cFN showed more end point variance than did normal saccades. During cFN inactivation, eye position during saccades was statistically more strongly coupled to eye position at saccade end. The proposed model could fit the variance/covariance structure of ipsiversive and contraversive saccades. Inactivation effects on saccade noise are explained by a decrease of the feedback gain and an increase of planning and/or signal-dependent motor noise. The decrease of the fitted feedback gain is consistent with previous studies suggesting a role for the cerebellum in an internal feedback mechanism. Increased end point variance did not result from impaired feedback but from the increase of accumulating noise. The effects of cFN inactivation on saccade noise indicate that the effects of cFN inactivation cannot be explained entirely with the cFNs direct connections to the saccade-related premotor centers in the brainstem.'),
(87907, 2016, 'plos', 'A Crowdsourcing Approach to Developing and Assessing Prediction Algorithms for AML Prognosis', 'Noren, David P|Long, Byron L|Norel, Raquel|Rrhissorrakrai, Kahn|Hess, Kenneth|Hu, Chenyue Wendy|Bisberg, Alex J|Schultz, Andre|Engquist, Erik|Liu, Li|Lin, Xihui|Chen, Gregory M|Xie, Honglei|Hunter, Geoffrey A M|Boutros, Paul C|Stepanov, Oleg|DREAM 9 AML-OPC Consortium|Norman, Thea|Friend, Stephen H|Stolovitzky, Gustavo|Kornblau, Steven|Qutub, Amina A', 'Rice University, Houston, Texas, United States of America.|Rice University, Houston, Texas, United States of America.|IBM Computational Biology Center, Yorktown Heights, New York, United States of America.|IBM Computational Biology Center, Yorktown Heights, New York, United States of America.|The University of Texas MD Anderson Cancer Center, Houston, Texas, United States of America.|Rice University, Houston, Texas, United States of America.|Rice University, Houston, Texas, United States of America.|Rice University, Houston, Texas, United States of America.|Rice University, Houston, Texas, United States of America.|Arizona State University, Tempe, Arizona, United States of America.|Ontario Institute for Cancer Research, Toronto, Ontario, Canada.|Ontario Institute for Cancer Research, Toronto, Ontario, Canada.|Ontario Institute for Cancer Research, Toronto, Ontario, Canada.|Ontario Institute for Cancer Research, Toronto, Ontario, Canada.|Ontario Institute for Cancer Research, Toronto, Ontario, Canada.|Institute for Systems Biology, Moscow, Russia.|Institute for Systems Biology, Moscow, Russia.|Sage Bionetworks, Seattle, Washington, United States of America.|Sage Bionetworks, Seattle, Washington, United States of America.|IBM Computational Biology Center, Yorktown Heights, New York, United States of America.|The University of Texas MD Anderson Cancer Center, Houston, Texas, United States of America.|Rice University, Houston, Texas, United States of America.', 'United States|United States|United States|United States|United States|United States|United States|Un', 14, 'Algorithms|Amyotrophic Lateral Sclerosis|Biomarkers|Crowdsourcing|Humans|Outcome and Process Assessment (Health Care)|Proteome|Reproducibility of Results|Risk Assessment|Sensitivity and Specificity|Treatment Outcome', 'Comparative Study', '10.1371/journal.pcbi.1004890', '27351836', 'Acute Myeloid Leukemia (AML) is a fatal hematological cancer. The genetic abnormalities underlying AML are extremely heterogeneous among patients, making prognosis and treatment selection very difficult. While clinical proteomics data has the potential to improve prognosis accuracy, thus far, the quantitative means to do so have yet to be developed. Here we report the results and insights gained from the DREAM 9 Acute Myeloid Prediction Outcome Prediction Challenge (AML-OPC), a crowdsourcing effort designed to promote the development of quantitative methods for AML prognosis prediction. We identify the most accurate and robust models in predicting patient response to therapy, remission duration, and overall survival. We further investigate patient response to therapy, a clinically actionable prediction, and find that patients that are classified as resistant to therapy are harder to predict than responsive patients across the 31 models submitted to the challenge. The top two performing models, which held a high sensitivity to these patients, substantially utilized the proteomics data to make predictions. Using these models, we also identify which signaling proteins were useful in predicting patient therapeutic response.');
INSERT INTO `papers` (`id`, `ano`, `journal`, `titulo`, `autores`, `afiliacao`, `pais`, `citacoes`, `palavra_chave`, `categorias`, `doi`, `pubmed`, `abstract`) VALUES
(87908, 2016, 'plos', 'Quantification and Classification of E coli Proteome Utilization and Unused Protein Costs across Environments', 'OBrien, Edward J|Utrilla, Jose|Palsson, Bernhard O', 'Department of Bioengineering, University of California, San Diego, La Jolla, California, United States of America.|Department of Bioengineering, University of California, San Diego, La Jolla, California, United States of America.|Department of Bioengineering, University of California, San Diego, La Jolla, California, United States of America.', 'United States|United States|United States', 46, 'Computational Biology|Databases, Protein|Escherichia coli|Escherichia coli Proteins|Models, Biological|Proteome', 'Journal Article', '10.1371/journal.pcbi.1004998', '27351952', 'The costs and benefits of protein expression are balanced through evolution. Expression of un-utilized protein (that have no benefits in the current environment) incurs a quantifiable fitness costs on cellular growth rates, however, the magnitude and variability of un-utilized protein expression in natural settings is unknown, largely due to the challenge in determining environment-specific proteome utilization. We address this challenge using absolute and global proteomics data combined with a recently developed genome-scale model of Escherichia coli that computes the environment-specific cost and utility of the proteome on a per gene basis. We show that nearly half of the proteome mass is unused in certain environments and accounting for the cost of this unused protein expression explains >95% of the variance in growth rates of Escherichia coli across 16 distinct environments. Furthermore, reduction in unused protein expression is shown to be a common mechanism to increase cellular growth rates in adaptive evolution experiments. Classification of the unused protein reveals that the unused protein encodes several nutrient- and stress- preparedness functions, which may convey fitness benefits in varying environments. Thus, unused protein expression is the source of large and pervasive fitness costs that may provide the benefit of hedging against environmental change.'),
(87909, 2016, 'plos', 'Constrained Allocation Flux Balance Analysis', 'Mori, Matteo|Hwa, Terence|Martin, Olivier C|De Martino, Andrea|Marinari, Enzo', 'Dipartimento di Fisica, Sapienza Università di Roma, Rome, Italy.|Department of Physics, University of California at San Diego, La Jolla, California, United States of America.|GQE - Le Moulon, INRA, Univ. Paris-Sud, CNRS, AgroParisTech, Université Paris-Saclay, Gif-sur-Yvette, France.|Dipartimento di Fisica, Sapienza Università di Roma, Rome, Italy.|Dipartimento di Fisica, Sapienza Università di Roma, Rome, Italy.', 'Italy|United States|France|Italy|Italy', 49, 'Acetates|Cell Proliferation|Computer Simulation|Escherichia coli|Escherichia coli Proteins|Metabolic Flux Analysis|Metabolome|Models, Biological|Proteome|Signal Transduction', 'Journal Article', '10.1371/journal.pcbi.1004913', '27355325', 'New experimental results on bacterial growth inspire a novel top-down approach to study cell metabolism, combining mass balance and proteomic constraints to extend and complement Flux Balance Analysis. We introduce here Constrained Allocation Flux Balance Analysis, CAFBA, in which the biosynthetic costs associated to growth are accounted for in an effective way through a single additional genome-wide constraint. Its roots lie in the experimentally observed pattern of proteome allocation for metabolic functions, allowing to bridge regulation and metabolism in a transparent way under the principle of growth-rate maximization. We provide a simple method to solve CAFBA efficiently and propose an ensemble averaging procedure to account for unknown protein costs. Applying this approach to modeling E. coli metabolism, we find that, as the growth rate increases, CAFBA solutions cross over from respiratory, growth-yield maximizing states (preferred at slow growth) to fermentative states with carbon overflow (preferred at fast growth). In addition, CAFBA allows for quantitatively accurate predictions on the rate of acetate excretion and growth yield based on only 3 parameters determined by empirical growth laws.'),
(87910, 2016, 'plos', 'Rare Variants Association Analysis in Large-Scale Sequencing Studies at the Single Locus Level', 'Jeng, Xinge Jessie|Daye, Zhongyin John|Lu, Wenbin|Tzeng, Jung-Ying', 'Department of Statistics, North Carolina State University, Raleigh, North Carolina, United States of America.|Epidemiology and Biostatistics, University of Arizona, Tucson, Arizona, United States of America.|Department of Statistics, North Carolina State University, Raleigh, North Carolina, United States of America.|Department of Statistics, North Carolina State University, Raleigh, North Carolina, United States of America.', 'United States|United States|United States|United States', 4, 'Cardiovascular Diseases|Computer Simulation|Databases, Factual|Drug Delivery Systems|Gene Frequency|Genetic Association Studies|Genetic Predisposition to Disease|Genomics|High-Throughput Nucleotide Sequencing|Humans|Models, Genetic', 'Journal Article', '10.1371/journal.pcbi.1004993', '27355347', 'Genetic association analyses of rare variants in next-generation sequencing (NGS) studies are fundamentally challenging due to the presence of a very large number of candidate variants at extremely low minor allele frequencies. Recent developments often focus on pooling multiple variants to provide association analysis at the gene instead of the locus level. Nonetheless, pinpointing individual variants is a critical goal for genomic researches as such information can facilitate the precise delineation of molecular mechanisms and functions of genetic factors on diseases. Due to the extreme rarity of mutations and high-dimensionality, significances of causal variants cannot easily stand out from those of noncausal ones. Consequently, standard false-positive control procedures, such as the Bonferroni and false discovery rate (FDR), are often impractical to apply, as a majority of the causal variants can only be identified along with a few but unknown number of noncausal variants. To provide informative analysis of individual variants in large-scale sequencing studies, we propose the Adaptive False-Negative Control (AFNC) procedure that can include a large proportion of causal variants with high confidence by introducing a novel statistical inquiry to determine those variants that can be confidently dispatched as noncausal. The AFNC provides a general framework that can accommodate for a variety of models and significance tests. The procedure is computationally efficient and can adapt to the underlying proportion of causal variants and quality of significance rankings. Extensive simulation studies across a plethora of scenarios demonstrate that the AFNC is advantageous for identifying individual rare variants, whereas the Bonferroni and FDR are exceedingly over-conservative for rare variants association studies. In the analyses of the CoLaus dataset, AFNC has identified individual variants most responsible for gene-level significances. Moreover, single-variant results using the AFNC have been successfully applied to infer related genes with annotation information.'),
(87911, 2016, 'plos', 'Conservation in Mammals of Genes Associated with Aggression-Related Behavioral Phenotypes in Honey Bees', 'Liu, Hui|Robinson, Gene E|Jakobsson, Eric', 'Center for Biophysics and Computational Biology, University of Illinois at Urbana-Champaign, Urbana, Illinois, United States of America.|Carl R. Woese Institute for Genomic Biology, University of Illinois at Urbana-Champaign, Urbana, Illinois, United States of America.|Center for Biophysics and Computational Biology, University of Illinois at Urbana-Champaign, Urbana, Illinois, United States of America.', 'United States|United States|United States', 7, 'Aggression|Animals|Bees|Behavior, Animal|Biological Evolution|Conserved Sequence|Gene Expression Regulation|Genetic Association Studies|Humans|Mammals|Phenotype|Proteome|Social Behavior', 'Journal Article', '10.1371/journal.pcbi.1004921', '27359102', 'The emerging field of sociogenomics explores the relations between social behavior and genome structure and function. An important question is the extent to which associations between social behavior and gene expression are conserved among the Metazoa. Prior experimental work in an invertebrate model of social behavior, the honey bee, revealed distinct brain gene expression patterns in African and European honey bees, and within European honey bees with different behavioral phenotypes. The present work is a computational study of these previous findings in which we analyze, by orthology determination, the extent to which genes that are socially regulated in honey bees are conserved across the Metazoa. We found that the differentially expressed gene sets associated with alarm pheromone response, the difference between old and young bees, and the colony influence on soldier bees, are enriched in widely conserved genes, indicating that these differences have genomic bases shared with many other metazoans. By contrast, the sets of differentially expressed genes associated with the differences between African and European forager and guard bees are depleted in widely conserved genes, indicating that the genomic basis for this social behavior is relatively specific to honey bees. For the alarm pheromone response gene set, we found a particularly high degree of conservation with mammals, even though the alarm pheromone itself is bee-specific. Gene Ontology identification of human orthologs to the strongly conserved honey bee genes associated with the alarm pheromone response shows overrepresentation of protein metabolism, regulation of protein complex formation, and protein folding, perhaps associated with remodeling of critical neural circuits in response to alarm pheromone. We hypothesize that such remodeling may be an adaptation of social animals to process and respond appropriately to the complex patterns of conspecific communication essential for social organization.'),
(87912, 2016, 'plos', 'Evolutionary and Topological Properties of Genes and Community Structures in Human Gene Regulatory Networks', 'Szedlak, Anthony|Smith, Nicholas|Liu, Li|Paternostro, Giovanni|Piermarocchi, Carlo', 'Department of Physics and Astronomy, Michigan State University, East Lansing, Michigan, United States of America.|Salgomed Inc., Del Mar, California, United States of America.|College of Health Solutions, Arizona State University, Tempe, Arizona, United States of America.|Sanford Burnham Prebys Medical Discovery Institute, La Jolla, California, United States of America.|Department of Physics and Astronomy, Michigan State University, East Lansing, Michigan, United States of America.', 'United States|United States|United States|United States|United States', 1, 'Computational Biology|Evolution, Molecular|Gene Regulatory Networks|Humans|Leukemia, Myeloid, Acute|Models, Genetic', 'Journal Article', '10.1371/journal.pcbi.1005009', '27359334', 'The diverse, specialized genes present in todays lifeforms evolved from a common core of ancient, elementary genes. However, these genes did not evolve individually: gene expression is controlled by a complex network of interactions, and alterations in one gene may drive reciprocal changes in its proteins binding partners. Like many complex networks, these gene regulatory networks (GRNs) are composed of communities, or clusters of genes with relatively high connectivity. A deep understanding of the relationship between the evolutionary history of single genes and the topological properties of the underlying GRN is integral to evolutionary genetics. Here, we show that the topological properties of an acute myeloid leukemia GRN and a general human GRN are strongly coupled with its genes evolutionary properties. Slowly evolving (cold), old genes tend to interact with each other, as do rapidly evolving (hot), young genes. This naturally causes genes to segregate into community structures with relatively homogeneous evolutionary histories. We argue that gene duplication placed old, cold genes and communities at the center of the networks, and young, hot genes and communities at the periphery. We demonstrate this with single-node centrality measures and two new measures of efficiency, the set efficiency and the interset efficiency. We conclude that these methods for studying the relationships between a GRNs community structures and its genes evolutionary properties provide new perspectives for understanding evolutionary genetics.'),
(87913, 2016, 'plos', 'Colony Expansion of Socially Motile Myxococcus xanthus Cells Is Driven by Growth, Motility, and Exopolysaccharide Production', 'Patra, Pintu|Kissoon, Kimberley|Cornejo, Isabel|Kaplan, Heidi B|Igoshin, Oleg A', 'Department of Bioengineering, Rice University, Houston, Texas, United States of America.|Department of Natural Sciences, Del Mar College, Corpus Christi, Texas, United States of America.|Department of Natural Sciences, University of Houston-Downtown, Houston, Texas, United States of America.|Department of Microbiology and Molecular Genetics, University of Texas Medical School, Houston, Texas, United States of America.|Department of Bioengineering, Rice University, Houston, Texas, United States of America.', 'United States|United States|United States|United States|United States', 6, 'Cell Proliferation|Fimbriae, Bacterial|Models, Biological|Myxococcus xanthus|Polysaccharides, Bacterial', 'Journal Article', '10.1371/journal.pcbi.1005010', '27362260', 'Myxococcus xanthus, a model organism for studies of multicellular behavior in bacteria, moves exclusively on solid surfaces using two distinct but coordinated motility mechanisms. One of these, social (S) motility is powered by the extension and retraction of type IV pili and requires the presence of exopolysaccharides (EPS) produced by neighboring cells. As a result, S motility requires close cell-to-cell proximity and isolated cells do not translocate. Previous studies measuring S motility by observing the colony expansion of cells deposited on agar have shown that the expansion rate increases with initial cell density, but the biophysical mechanisms involved remain largely unknown. To understand the dynamics of S motility-driven colony expansion, we developed a reaction-diffusion model describing the effects of cell density, EPS deposition and nutrient exposure on the expansion rate. Our results show that at steady state the population expands as a traveling wave with a speed determined by the interplay of cell motility and growth, a well-known characteristic of Fishers equation. The model explains the density-dependence of the colony expansion by demonstrating the presence of a lag phase-a transient period of very slow expansion with a duration dependent on the initial cell density. We propose that at a low initial density, more time is required for the cells to accumulate enough EPS to activate S-motility resulting in a longer lag period. Furthermore, our model makes the novel prediction that following the lag phase the population expands at a constant rate independent of the cell density. These predictions were confirmed by S motility experiments capturing long-term expansion dynamics.'),
(87914, 2016, 'plos', 'Inferring Strain Mixture within Clinical Plasmodium falciparum Isolates from Genomic Sequence Data', 'OBrien, John D|Iqbal, Zamin|Wendler, Jason|Amenga-Etego, Lucas', 'Mathematics Department, Bowdoin College, Brunswick, Maine, United States of America.|Wellcome Trust Centre for Human Genetics, University of Oxford, Oxford, Oxfordshire, United Kingdom.|Pacific Northwest National Laboratory, Richland, Washington, United States of America.|Wellcome Trust Centre for Human Genetics, University of Oxford, Oxford, Oxfordshire, United Kingdom.', 'United States|United Kingdom|United States|United Kingdom', 8, 'Algorithms|Bayes Theorem|Chromosome Mapping|DNA, Protozoan|Plasmodium falciparum|Polymorphism, Single Nucleotide|Sequence Analysis, DNA|Species Specificity', 'Journal Article', '10.1371/journal.pcbi.1004824', '27362949', 'We present a rigorous statistical model that infers the structure of P. falciparum mixtures-including the number of strains present, their proportion within the samples, and the amount of unexplained mixture-using whole genome sequence (WGS) data. Applied to simulation data, artificial laboratory mixtures, and field samples, the model provides reasonable inference with as few as 10 reads or 50 SNPs and works efficiently even with much larger data sets. Source code and example data for the model are provided in an open source fashion. We discuss the possible uses of this model as a window into within-host selection for clinical and epidemiological studies.'),
(87915, 2016, 'plos', 'Cellular Interrogation: Exploiting Cell-to-Cell Variability to Discriminate Regulatory Mechanisms in Oscillatory Signalling', 'Estrada, Javier|Andrew, Natalie|Gibson, Daniel|Chang, Frederick|Gnad, Florian|Gunawardena, Jeremy', 'Departamento de Física de la Materia Condensada and Instituto Nicolás Cabrera, Universidad Autónoma de Madrid, Madrid, Spain.|John A. Paulson School of Engineering and Applied Sciences, Harvard University, Cambridge, Massachusetts, United States of America.|Department of Systems Biology, Harvard Medical School, Boston, Massachusetts, United States of America.|Molecular and Cell Biology Graduate Program, Harvard University, Cambridge, Massachusetts, United States of America.|Department of Systems Biology, Harvard Medical School, Boston, Massachusetts, United States of America.|Department of Systems Biology, Harvard Medical School, Boston, Massachusetts, United States of America.', 'Spain|United States|United States|United States|United States|United States', 3, 'Calcium Signaling|Cell Physiological Phenomena|Computational Biology|Models, Biological|Nonlinear Dynamics|Signal Transduction|Single-Cell Analysis', 'Journal Article', '10.1371/journal.pcbi.1004995', '27367445', 'The molecular complexity within a cell may be seen as an evolutionary response to the external complexity of the cells environment. This suggests that the external environment may be harnessed to interrogate the cells internal molecular architecture. Cells, however, are not only nonlinear and non-stationary, but also exhibit heterogeneous responses within a clonal, isogenic population. In effect, each cell undertakes its own experiment. Here, we develop a method of cellular interrogation using programmable microfluidic devices which exploits the additional information present in cell-to-cell variation, without requiring model parameters to be fitted to data. We focussed on Ca2+ signalling in response to hormone stimulation, which exhibits oscillatory spiking in many cell types and chose eight models of Ca2+ signalling networks which exhibit similar behaviour in simulation. We developed a nonlinear frequency analysis for non-stationary responses, which could classify models into groups under parameter variation, but found that this question alone was unable to distinguish critical feedback loops. We further developed a nonlinear amplitude analysis and found that the combination of both questions ruled out six of the models as inconsistent with the experimentally-observed dynamics and heterogeneity. The two models that survived the double interrogation were mathematically different but schematically identical and yielded the same unexpected predictions that we confirmed experimentally. Further analysis showed that subtle mathematical details can markedly influence non-stationary responses under parameter variation, emphasising the difficulty of finding a correct model. By developing questions for the pathway being studied, and designing more versatile microfluidics, cellular interrogation holds promise as a systematic strategy that can complement direct intervention by genetics or pharmacology.'),
(87916, 2016, 'plos', 'Collective Signal Processing in Cluster Chemotaxis: Roles of Adaptation, Amplification, and Co-attraction in Collective Guidance', 'Camley, Brian A|Zimmermann, Juliane|Levine, Herbert|Rappel, Wouter-Jan', 'Department of Physics, University of California, San Diego, La Jolla, California, United States of America.|Center for Theoretical Biological Physics, Rice University, Houston, Texas, United States of America.|Center for Theoretical Biological Physics, Rice University, Houston, Texas, United States of America.|Department of Physics, University of California, San Diego, La Jolla, California, United States of America.', 'United States|United States|United States|United States', 21, 'Chemotactic Factors|Chemotaxis|Computational Biology|Computer Simulation|Models, Biological|Signal Transduction', 'Journal Article', '10.1371/journal.pcbi.1005008', '27367541', 'Single eukaryotic cells commonly sense and follow chemical gradients, performing chemotaxis. Recent experiments and theories, however, show that even when single cells do not chemotax, clusters of cells may, if their interactions are regulated by the chemoattractant. We study this general mechanism of collective guidance computationally with models that integrate stochastic dynamics for individual cells with biochemical reactions within the cells, and diffusion of chemical signals between the cells. We show that if clusters of cells use the well-known local excitation, global inhibition (LEGI) mechanism to sense chemoattractant gradients, the speed of the cell cluster becomes non-monotonic in the clusters size-clusters either larger or smaller than an optimal size will have lower speed. We argue that the cell cluster speed is a crucial readout of how the cluster processes chemotactic signals, both amplification and adaptation will alter the behavior of cluster speed as a function of size. We also show that, contrary to the assumptions of earlier theories, collective guidance does not require persistent cell-cell contacts and strong short range adhesion. If cell-cell adhesion is absent, and the cluster cohesion is instead provided by a co-attraction mechanism, e.g. chemotaxis toward a secreted molecule, collective guidance may still function. However, new behaviors, such as cluster rotation, may also appear in this case. Co-attraction and adaptation allow for collective guidance that is robust to varying chemoattractant concentrations while not requiring strong cell-cell adhesion.'),
(87917, 2016, 'plos', 'The Coda of the Transient Response in a Sensitive Cochlea: A Computational Modeling Study', 'Li, Yizeng|Grosh, Karl', 'Department of Mechanical Engineering, University of Michigan, Ann Arbor, Michigan, United States of America.|Department of Mechanical Engineering, University of Michigan, Ann Arbor, Michigan, United States of America.', 'United States|United States', 0, 'Acoustic Stimulation|Basilar Membrane|Cochlea|Computer Simulation|Ear Canal|Humans|Models, Biological|Signal Transduction|Time Factors', 'Journal Article', '10.1371/journal.pcbi.1005015', '27380177', 'In a sensitive cochlea, the basilar membrane response to transient excitation of any kind-normal acoustic or artificial intracochlear excitation-consists of not only a primary impulse but also a coda of delayed secondary responses with varying amplitudes but similar spectral content around the characteristic frequency of the measurement location. The coda, sometimes referred to as echoes or ringing, has been described as a form of local, short term memory which may influence the ability of the auditory system to detect gaps in an acoustic stimulus such as speech. Depending on the individual cochlea, the temporal gap between the primary impulse and the following coda ranges from once to thrice the group delay of the primary impulse (the group delay of the primary impulse is on the order of a few hundred microseconds). The coda is physiologically vulnerable, disappearing when the cochlea is compromised even slightly. The multicomponent sensitive response is not yet completely understood. We use a physiologically-based, mathematical model to investigate (i) the generation of the primary impulse response and the dependence of the group delay on the various stimulation methods, (ii) the effect of spatial perturbations in the properties of mechanically sensitive ion channels on the generation and separation of delayed secondary responses. The model suggests that the presence of the secondary responses depends on the wavenumber content of a perturbation and the activity level of the cochlea. In addition, the model shows that the varying temporal gaps between adjacent coda seen in experiments depend on the individual profiles of perturbations. Implications for non-invasive cochlear diagnosis are also discussed.'),
(87918, 2016, 'plos', 'Using Combined Diagnostic Test Results to Hindcast Trends of Infection from Cross-Sectional Data', 'Rydevik, Gustaf|Innocent, Giles T|Marion, Glenn|Davidson, Ross S|White, Piran C L|Billinis, Charalambos|Barrow, Paul|Mertens, Peter P C|Gavier-Widén, Dolores|Hutchings, Michael R', 'Biomathematics and Statistics Scotland (BIOSS), Edinburgh, United Kingdom.|Biomathematics and Statistics Scotland (BIOSS), Edinburgh, United Kingdom.|Biomathematics and Statistics Scotland (BIOSS), Edinburgh, United Kingdom.|SRUC, Edinburgh, United Kingdom.|Environment Department, University of York, York, United Kingdom.|Laboratory of Microbiology and Parasitology, Faculty of Veterinary Medicine, University of Thessaly, Karditsa, Greece.|School of Veterinary Medicine and Science, University of Nottingham, Nottingham, United Kingdom.|The Vector-Borne Viral Diseases Programme, The Pirbright Institute, Surrey, United Kingdom.|National Veterinary Institute (SVA), Uppsala, Sweden.|SRUC, Edinburgh, United Kingdom.', 'United Kingdom|United Kingdom|United Kingdom|United Kingdom|United Kingdom|Greece|United Kingdom|Uni', 3, 'Algorithms|Animals|Bluetongue|Cattle|Cattle Diseases|Computational Biology|Cross-Sectional Studies|Epidemics|Humans|Models, Statistical|Population Surveillance|Whooping Cough', 'Journal Article', '10.1371/journal.pcbi.1004901', '27384712', 'Infectious disease surveillance is key to limiting the consequences from infectious pathogens and maintaining animal and public health. Following the detection of a disease outbreak, a response in proportion to the severity of the outbreak is required. It is thus critical to obtain accurate information concerning the origin of the outbreak and its forward trajectory. However, there is often a lack of situational awareness that may lead to over- or under-reaction. There is a widening range of tests available for detecting pathogens, with typically different temporal characteristics, e.g. in terms of when peak test response occurs relative to time of exposure. We have developed a statistical framework that combines response level data from multiple diagnostic tests and is able to hindcast (infer the historical trend of) an infectious disease epidemic. Assuming diagnostic test data from a cross-sectional sample of individuals infected with a pathogen during an outbreak, we use a Bayesian Markov Chain Monte Carlo (MCMC) approach to estimate time of exposure, and the overall epidemic trend in the population prior to the time of sampling. We evaluate the performance of this statistical framework on simulated data from epidemic trend curves and show that we can recover the parameter values of those trends. We also apply the framework to epidemic trend curves taken from two historical outbreaks: a bluetongue outbreak in cattle, and a whooping cough outbreak in humans. Together, these results show that hindcasting can estimate the time since infection for individuals and provide accurate estimates of epidemic trends, and can be used to distinguish whether an outbreak is increasing or past its peak. We conclude that if temporal characteristics of diagnostics are known, it is possible to recover epidemic trends of both human and animal pathogens from cross-sectional data collected at a single point in time.'),
(87919, 2016, 'plos', 'The More the Tubular: Dynamic Bundling of Actin Filaments for Membrane Tube Formation', 'Weichsel, Julian|Geissler, Phillip L', 'Department of Chemistry, University of California, Berkeley, California, United States of America.|Department of Chemistry, University of California, Berkeley, California, United States of America.', 'United States|United States', 0, 'Actin Cytoskeleton|Actins|Cell Membrane|Computational Biology|Computer Simulation|Models, Biological|Monte Carlo Method|Protein Binding', 'Journal Article', '10.1371/journal.pcbi.1004982', '27384915', 'Tubular protrusions are a common feature of living cells, arising from polymerization of stiff protein filaments against a comparably soft membrane. Although this process involves many accessory proteins in cells, in vitro experiments indicate that similar tube-like structures can emerge without them, through spontaneous bundling of filaments mediated by the membrane. Using theory and simulation of physical models, we have elaborated how nonequilibrium fluctuations in growth kinetics and membrane shape can yield such protrusions. Enabled by a new grand canonical Monte Carlo method for membrane simulation, our work reveals a cascade of dynamical transitions from individually polymerizing filaments to highly cooperatively growing bundles as a dynamical bottleneck to tube formation. Filament network organization as well as adhesion points to the membrane, which bias filament bending and constrain membrane height fluctuations, screen the effective attractive interactions between filaments, significantly delaying bundling and tube formation.'),
(87920, 2016, 'plos', '2016 ISCB Innovator Award: Serafim Batzoglou', 'Fogg, Christiana N|Kovats, Diane E', 'Freelance Science Writer, Kensington, Maryland, United States of America.|Executive Director, International Society for Computational Biology, Bethesda, Maryland, United States of America.', 'United States|United States', 0, 'Awards and Prizes|Computational Biology|Genome|History, 21st Century|Societies, Scientific|United States', 'Biography', '10.1371/journal.pcbi.1004973', '27389680', '-'),
(87921, 2016, 'plos', 'Properties of Neurons in External Globus Pallidus Can Support Optimal Action Selection', 'Bogacz, Rafal|Martin Moraud, Eduardo|Abdi, Azzedine|Magill, Peter J|Baufreton, Jérôme', 'Medical Research Council Brain Network Dynamics Unit, Department of Pharmacology, University of Oxford, Oxford, United Kingdom.|Medical Research Council Brain Network Dynamics Unit, Department of Pharmacology, University of Oxford, Oxford, United Kingdom.|Univ. Bordeaux, Institut des Maladies Neurodégénératives, UMR 5293, Bordeaux, France.|Medical Research Council Brain Network Dynamics Unit, Department of Pharmacology, University of Oxford, Oxford, United Kingdom.|Univ. Bordeaux, Institut des Maladies Neurodégénératives, UMR 5293, Bordeaux, France.', 'United Kingdom|United Kingdom|France|United Kingdom|France', 8, 'Computational Biology|Feedback, Physiological|Globus Pallidus|Models, Neurological|Neurons', 'Journal Article', '10.1371/journal.pcbi.1005004', '27389780', 'The external globus pallidus (GPe) is a key nucleus within basal ganglia circuits that are thought to be involved in action selection. A class of computational models assumes that, during action selection, the basal ganglia compute for all actions available in a given context the probabilities that they should be selected. These models suggest that a network of GPe and subthalamic nucleus (STN) neurons computes the normalization term in Bayes equation. In order to perform such computation, the GPe needs to send feedback to the STN equal to a particular function of the activity of STN neurons. However, the complex form of this function makes it unlikely that individual GPe neurons, or even a single GPe cell type, could compute it. Here, we demonstrate how this function could be computed within a network containing two types of GABAergic GPe projection neuron, so-called prototypic and arkypallidal neurons, that have different response properties in vivo and distinct connections. We compare our model predictions with the experimentally-reported connectivity and input-output functions (f-I curves) of the two populations of GPe neurons. We show that, together, these dichotomous cell types fulfil the requirements necessary to compute the function needed for optimal action selection. We conclude that, by virtue of their distinct response properties and connectivities, a network of arkypallidal and prototypic GPe neurons comprises a neural substrate capable of supporting the computation of the posterior probabilities of actions.'),
(87922, 2016, 'plos', 'The Emergence of Synaesthesia in a Neuronal Network Model via Changes in Perceptual Sensitivity and Plasticity', 'Shriki, Oren|Sadeh, Yaniv|Ward, Jamie', 'Department of Cognitive and Brain Sciences, Ben-Gurion University, Beer-Sheva, Israel.|Israel Arts and Science Academy, Jerusalem, Israel.|School of Psychology, University of Sussex, Brighton, United Kingdom.', 'Israel|Israel|United Kingdom', 0, 'Computational Biology|Humans|Models, Neurological|Nerve Net|Neuronal Plasticity|Perception|Perceptual Disorders', 'Journal Article', '10.1371/journal.pcbi.1004959', '27392215', 'Synaesthesia is an unusual perceptual experience in which an inducer stimulus triggers a percept in a different domain in addition to its own. To explore the conditions under which synaesthesia evolves, we studied a neuronal network model that represents two recurrently connected neural systems. The interactions in the network evolve according to learning rules that optimize sensory sensitivity. We demonstrate several scenarios, such as sensory deprivation or heightened plasticity, under which synaesthesia can evolve even though the inputs to the two systems are statistically independent and the initial cross-talk interactions are zero. Sensory deprivation is the known causal mechanism for acquired synaesthesia and increased plasticity is implicated in developmental synaesthesia. The model unifies different causes of synaesthesia within a single theoretical framework and repositions synaesthesia not as some quirk of aberrant connectivity, but rather as a functional brain state that can emerge as a consequence of optimising sensory information processing.'),
(87923, 2016, 'plos', 'Correction: A Computational Framework for 3D Mechanical Modeling of Plant Morphogenesis with Cellular Resolution', 'PLOS Computational Biology Staff', 'School of Psychology, University of Sussex, Brighton, United Kingdom.', 'United Kingdom', 0, '-', 'Published Erratum', '10.1371/journal.pcbi.1005027', '27392250', '[This corrects the article DOI: 10.1371/journal.pcbi.1003950.].'),
(87924, 2016, 'plos', 'Dynamic Reweighting of Auditory Modulation Filters', 'Joosten, Eva R M|Shamma, Shihab A|Lorenzi, Christian|Neri, Peter', 'Laboratoire Psychologie de la Perception (CNRS UMR 8242) and Universitxc3xa9 Paris Descartes, Sorbonne Paris Citxc3xa9, Paris, France.|Laboratoire des Systxc3xa8mes Perceptifs (CNRS UMR 8248) and Dxc3xa9partement d\\xc3xa9tudes cognitives, Ecole Normale Supxc3xa9rieure, PSL Research University, Paris, France.|Laboratoire des Systxc3xa8mes Perceptifs (CNRS UMR 8248) and Dxc3xa9partement d\\xc3xa9tudes cognitives, Ecole Normale Supxc3xa9rieure, PSL Research University, Paris, France.|Laboratoire des Systxc3xa8mes Perceptifs (CNRS UMR 8248) and Dxc3xa9partement d\\xc3xa9tudes cognitives, Ecole Normale Supxc3xa9rieure, PSL Research University, Paris, France.', 'France|France|France|France', 4, 'Adult|Auditory Pathways|Auditory Perception|Computational Biology|Humans|Noise|Task Performance and Analysis|Young Adult', 'Journal Article', '10.1371/journal.pcbi.1005019', '27398600', 'Sound waveforms convey information largely via amplitude modulations (AM). A large body of experimental evidence has provided support for a modulation (bandpass) filterbank. Details of this model have varied over time partly reflecting different experimental conditions and diverse datasets from distinct task strategies, contributing uncertainty to the bandwidth measurements and leaving important issues unresolved. We adopt here a solely data-driven measurement approach in which we first demonstrate how different models can be subsumed within a common cascade framework, and then proceed to characterize the cascade via system identification analysis using a single stimulus/task specification and hence stable task rules largely unconstrained by any model or parameters. Observers were required to detect a brief change in level superimposed onto random level changes that served as AM noise, the relationship between trial-by-trial noisy fluctuations and corresponding human responses enables targeted identification of distinct cascade elements. The resulting measurements exhibit a dynamic complex picture in which human perception of auditory modulations appears adaptive in nature, evolving from an initial lowpass to bandpass modes (with broad tuning, Qxe2x88xbc1) following repeated stimulus exposure.'),
(87925, 2016, 'plos', 'Machine Learning Meta-analysis of Large Metagenomic Datasets: Tools and Biological Insights', 'Pasolli, Edoardo|Truong, Duy Tin|Malik, Faizan|Waldron, Levi|Segata, Nicola', 'Centre for Integrative Biology, University of Trento, Trento, Italy.|Centre for Integrative Biology, University of Trento, Trento, Italy.|Graduate School of Public Health and Health Policy, City University of New York, New York, New York, United States of America.|Graduate School of Public Health and Health Policy, City University of New York, New York, New York, United States of America.|Centre for Integrative Biology, University of Trento, Trento, Italy.', 'Italy|Italy|United States|United States|Italy', 116, 'Colorectal Neoplasms|Computational Biology|Gastrointestinal Microbiome|Humans|Inflammatory Bowel Diseases|Machine Learning|Metagenome|Metagenomics|Obesity|Software', 'Journal Article', '10.1371/journal.pcbi.1004977', '27400279', 'Shotgun metagenomic analysis of the human associated microbiome provides a rich set of microbial features for prediction and biomarker discovery in the context of human diseases and health conditions. However, the use of such high-resolution microbial features presents new challenges, and validated computational tools for learning tasks are lacking. Moreover, classification rules have scarcely been validated in independent studies, posing questions about the generality and generalization of disease-predictive models across cohorts. In this paper, we comprehensively assess approaches to metagenomics-based prediction tasks and for quantitative assessment of the strength of potential microbiome-phenotype associations. We develop a computational framework for prediction tasks using quantitative microbiome profiles, including species-level relative abundances and presence of strain-specific markers. A comprehensive meta-analysis, with particular emphasis on generalization across cohorts, was performed in a collection of 2424 publicly available metagenomic samples from eight large-scale studies. Cross-validation revealed good disease-prediction capabilities, which were in general improved by feature selection and use of strain-specific markers instead of species-level taxonomic abundance. In cross-study analysis, models transferred between studies were in some cases less accurate than models tested by within-study cross-validation. Interestingly, the addition of healthy (control) samples from other studies to training sets improved disease prediction capabilities. Some microbial species (most notably Streptococcus anginosus) seem to characterize general dysbiotic states of the microbiome rather than connections with a specific disease. Our results in modelling features of the healthy microbiome can be considered a first step toward defining general microbial dysbiosis. The software framework, microbiome profiles, and metadata for thousands of samples are publicly available at http://segatalab.cibio.unitn.it/tools/metaml.'),
(87926, 2016, 'plos', 'Metagenome and Metatranscriptome Analyses Using Protein Family Profiles', 'Zhong, Cuncong|Edlund, Anna|Yang, Youngik|McLean, Jeffrey S|Yooseph, Shibu', 'J. Craig Venter Institute, La Jolla, California, United States of America.|J. Craig Venter Institute, La Jolla, California, United States of America.|J. Craig Venter Institute, La Jolla, California, United States of America.|J. Craig Venter Institute, La Jolla, California, United States of America.|J. Craig Venter Institute, La Jolla, California, United States of America.', 'United States|United States|United States|United States|United States', 4, 'Algorithms|Anti-Bacterial Agents|Bacteria|Computational Biology|Computer Simulation|Databases, Genetic|Drug Resistance, Bacterial|Gene Expression Profiling|Humans|Metagenome|Metagenomics|Models, Theoretical|Proteins|Saliva|Transcriptome', 'Journal Article', '10.1371/journal.pcbi.1004991', '27400380', 'Analyses of metagenome data (MG) and metatranscriptome data (MT) are often challenged by a paucity of complete reference genome sequences and the uneven/low sequencing depth of the constituent organisms in the microbial community, which respectively limit the power of reference-based alignment and de novo sequence assembly. These limitations make accurate protein family classification and abundance estimation challenging, which in turn hamper downstream analyses such as abundance profiling of metabolic pathways, identification of differentially encoded/expressed genes, and de novo reconstruction of complete gene and protein sequences from the protein family of interest. The profile hidden Markov model (HMM) framework enables the construction of very useful probabilistic models for protein families that allow for accurate modeling of position specific matches, insertions, and deletions. We present a novel homology detection algorithm that integrates banded Viterbi algorithm for profile HMM parsing with an iterative simultaneous alignment and assembly computational framework. The algorithm searches a given profile HMM of a protein family against a database of fragmentary MG/MT sequencing data and simultaneously assembles complete or near-complete gene and protein sequences of the protein family. The resulting program, HMM-GRASPx, demonstrates superior performance in aligning and assembling homologs when benchmarked on both simulated marine MG and real human saliva MG datasets. On real supragingival plaque and stool MG datasets that were generated from healthy individuals, HMM-GRASPx accurately estimates the abundances of the antimicrobial resistance (AMR) gene families and enables accurate characterization of the resistome profiles of these microbial communities. For real human oral microbiome MT datasets, using the HMM-GRASPx estimated transcript abundances significantly improves detection of differentially expressed (DE) genes. Finally, HMM-GRASPx was used to reconstruct comprehensive sets of complete or near-complete protein and nucleotide sequences for the query protein families. HMM-GRASPx is freely available online from http://sourceforge.net/projects/hmm-graspx.'),
(87927, 2016, 'plos', 'Integrating Transcriptomic and Proteomic Data Using Predictive Regulatory Network Models of Host Response to Pathogens', 'Chasman, Deborah|Walters, Kevin B|Lopes, Tiago J S|Eisfeld, Amie J|Kawaoka, Yoshihiro|Roy, Sushmita', 'Wisconsin Institute for Discovery, University of Wisconsin-Madison, Madison, Wisconsin, United States of America.|Influenza Research Institute, Department of Pathobiological Sciences, School of Veterinary Medicine, University of Wisconsin-Madison, Madison, Wisconsin, United States of America.|Influenza Research Institute, Department of Pathobiological Sciences, School of Veterinary Medicine, University of Wisconsin-Madison, Madison, Wisconsin, United States of America.|Influenza Research Institute, Department of Pathobiological Sciences, School of Veterinary Medicine, University of Wisconsin-Madison, Madison, Wisconsin, United States of America.|Influenza Research Institute, Department of Pathobiological Sciences, School of Veterinary Medicine, University of Wisconsin-Madison, Madison, Wisconsin, United States of America.|Wisconsin Institute for Discovery, University of Wisconsin-Madison, Madison, Wisconsin, United States of America.', 'United States|United States|United States|United States|United States|United States', 11, 'Animals|Gene Expression Profiling|Gene Regulatory Networks|Host-Pathogen Interactions|Humans|Influenza, Human|Mice|Models, Biological|Proteome|Proteomics|Systems Biology|Transcriptome', 'Journal Article', '10.1371/journal.pcbi.1005013', '27403523', 'Mammalian host response to pathogenic infections is controlled by a complex regulatory network connecting regulatory proteins such as transcription factors and signaling proteins to target genes. An important challenge in infectious disease research is to understand molecular similarities and differences in mammalian host response to diverse sets of pathogens. Recently, systems biology studies have produced rich collections of omic profiles measuring host response to infectious agents such as influenza viruses at multiple levels. To gain a comprehensive understanding of the regulatory network driving host response to multiple infectious agents, we integrated host transcriptomes and proteomes using a network-based approach. Our approach combines expression-based regulatory network inference, structured-sparsity based regression, and network information flow to infer putative physical regulatory programs for expression modules. We applied our approach to identify regulatory networks, modules and subnetworks that drive host response to multiple influenza infections. The inferred regulatory network and modules are significantly enriched for known pathways of immune response and implicate apoptosis, splicing, and interferon signaling processes in the differential response of viral infections of different pathogenicities. We used the learned network to prioritize regulators and study virus and time-point specific networks. RNAi-based knockdown of predicted regulators had significant impact on viral replication and include several previously unknown regulators. Taken together, our integrated analysis identified novel module level patterns that capture strain and pathogenicity-specific patterns of expression and helped identify important regulators of host response to influenza infection.'),
(87928, 2016, 'plos', 'Computing Biology', 'Nussinov, Ruth|Papin, Jason A', 'Cancer and Inflammation Program, Leidos Biomedical Research, Inc., Frederick National Laboratory for Cancer Research, National Cancer Institute, Frederick, Maryland, United States of America.|Department of Biomedical Engineering, University of Virginia, Charlottesville, Virginia, United States of America.', 'United States|United States', 0, 'Computational Biology|Genetic Predisposition to Disease|Humans', 'Editorial', '10.1371/journal.pcbi.1005050', '27403659', '-'),
(87929, 2016, 'plos', 'Ancestral Reconstruction', 'Joy, Jeffrey B|Liang, Richard H|McCloskey, Rosemary M|Nguyen, T|Poon, Art F Y', 'BC Centre for Excellence in HIV/AIDS, Vancouver, British Columbia, Canada.|BC Centre for Excellence in HIV/AIDS, Vancouver, British Columbia, Canada.|BC Centre for Excellence in HIV/AIDS, Vancouver, British Columbia, Canada.|BC Centre for Excellence in HIV/AIDS, Vancouver, British Columbia, Canada.|BC Centre for Excellence in HIV/AIDS, Vancouver, British Columbia, Canada.', 'Canada|Canada|Canada|Canada|Canada', 37, 'Algorithms|Bayes Theorem|Family|Genealogy and Heraldry|Likelihood Functions|Phylogeny', 'Journal Article', '10.1371/journal.pcbi.1004763', '27404731', '-');
INSERT INTO `papers` (`id`, `ano`, `journal`, `titulo`, `autores`, `afiliacao`, `pais`, `citacoes`, `palavra_chave`, `categorias`, `doi`, `pubmed`, `abstract`) VALUES
(87930, 2016, 'plos', 'Modelling of Yeast Mating Reveals Robustness Strategies for Cell-Cell Interactions', 'Chen, Weitao|Nie, Qing|Yi, Tau-Mu|Chou, Ching-Shan', 'Department of Mathematics, University of California, Irvine, Irvine, California, United States of America.|Department of Mathematics, University of California, Irvine, Irvine, California, United States of America.|Molecular, Cellular, and Developmental Biology, University of California, Santa Barbara, Santa Barbara, California, United States of America.|Department of Mathematics, The Ohio State University, Columbus, Ohio, United States of America.', 'United States|United States|United States|United States', 5, 'Cell Communication|Computational Biology|Computer Simulation|Models, Biological|Saccharomyces cerevisiae|Saccharomyces cerevisiae Proteins|Stochastic Processes', 'Journal Article', '10.1371/journal.pcbi.1004988', '27404800', 'Mating of budding yeast cells is a model system for studying cell-cell interactions. Haploid yeast cells secrete mating pheromones that are sensed by the partner which responds by growing a mating projection toward the source. The two projections meet and fuse to form the diploid. Successful mating relies on precise coordination of dynamic extracellular signals, signaling pathways, and cell shape changes in a noisy background. It remains elusive how cells mate accurately and efficiently in a natural multi-cell environment. Here we present the first stochastic model of multiple mating cells whose morphologies are driven by pheromone gradients and intracellular signals. Our novel computational framework encompassed a moving boundary method for modeling both a-cells and xcexb1-cells and their cell shape changes, the extracellular diffusion of mating pheromones dynamically coupled with cell polarization, and both external and internal noise. Quantification of mating efficiency was developed and tested for different model parameters. Computer simulations revealed important robustness strategies for mating in the presence of noise. These strategies included the polarized secretion of pheromone, the presence of the xcexb1-factor protease Bar1, and the regulation of sensing sensitivity, all were consistent with data in the literature. In addition, we investigated mating discrimination, the ability of an a-cell to distinguish between xcexb1-cells either making or not making xcexb1-factor, and mating competition, in which multiple a-cells compete to mate with one xcexb1-cell. Our simulations were consistent with previous experimental results. Moreover, we performed a combination of simulations and experiments to estimate the diffusion rate of the pheromone a-factor. In summary, we constructed a framework for simulating yeast mating with multiple cells in a noisy environment, and used this framework to reproduce mating behaviors and to identify strategies for robust cell-cell interactions.'),
(87931, 2016, 'plos', 'A Computational Modeling and Simulation Approach to Investigate Mechanisms of Subcellular cAMP Compartmentation', 'Yang, Pei-Chi|Boras, Britton W|Jeng, Mao-Tsuen|Docken, Steffen S|Lewis, Timothy J|McCulloch, Andrew D|Harvey, Robert D|Clancy, Colleen E', 'Department of Pharmacology, University of California Davis, Davis, California, United States of America.|Department of Biomedical Engineering, University of California San Diego, La Jolla, California, United States of America.|Department of Pharmacology, University of California Davis, Davis, California, United States of America.|Department of Pharmacology, University of California Davis, Davis, California, United States of America.|Department of Mathematics, University of California Davis, Davis, California, United States of America.|Department of Biomedical Engineering, University of California San Diego, La Jolla, California, United States of America.|Department of Pharmacology, Center for Molecular Medicine, School of Medicine, University of Nevada Reno, Reno, Nevada, United States of America.|Department of Pharmacology, University of California Davis, Davis, California, United States of America.', 'United States|United States|United States|United States|United States|United States|United States|Un', 20, 'Animals|Cells, Cultured|Computational Biology|Computer Simulation|Cyclic AMP|Intracellular Space|Mice|Myocytes, Cardiac|Phosphoric Diester Hydrolases|Signal Transduction', 'Journal Article', '10.1371/journal.pcbi.1005005', '27409243', 'Subcellular compartmentation of the ubiquitous second messenger cAMP has been widely proposed as a mechanism to explain unique receptor-dependent functional responses. How exactly compartmentation is achieved, however, has remained a mystery for more than 40 years. In this study, we developed computational and mathematical models to represent a subcellular sarcomeric space in a cardiac myocyte with varying detail. We then used these models to predict the contributions of various mechanisms that establish subcellular cAMP microdomains. We used the models to test the hypothesis that phosphodiesterases act as functional barriers to diffusion, creating discrete cAMP signaling domains. We also used the models to predict the effect of a range of experimentally measured diffusion rates on cAMP compartmentation. Finally, we modeled the anatomical structures in a cardiac myocyte diad, to predict the effects of anatomical diffusion barriers on cAMP compartmentation. When we incorporated experimentally informed model parameters to reconstruct an in silico subcellular sarcomeric space with spatially distinct cAMP production sites linked to caveloar domains, the models predict that under realistic conditions phosphodiesterases alone were insufficient to generate significant cAMP gradients. This prediction persisted even when combined with slow cAMP diffusion. When we additionally considered the effects of anatomic barriers to diffusion that are expected in the cardiac myocyte dyadic space, cAMP compartmentation did occur, but only when diffusion was slow. Our model simulations suggest that additional mechanisms likely contribute to cAMP gradients occurring in submicroscopic domains. The difference between the physiological and pathological effects resulting from the production of cAMP may be a function of appropriate compartmentation of cAMP signaling. Therefore, understanding the contribution of factors that are responsible for coordinating the spatial and temporal distribution of cAMP at the subcellular level could be important for developing new strategies for the prevention or treatment of unfavorable responses associated with different disease states.'),
(87932, 2016, 'plos', 'Disease Surveillance on Complex Social Networks', 'Herrera, Jose L|Srinivasan, Ravi|Brownstein, John S|Galvani, Alison P|Meyers, Lauren Ancel', 'Department of Integrative Biology, The University of Texas at Austin, Austin, Texas, United States of America.|Applied Research Laboratories, The University of Texas at Austin, Austin, Texas, United States of America.|Department of Pediatrics, Harvard Medical School and Childrens Hospital Informatics Program, Boston Childrens Hospital, Boston, Massachusetts, United States of America.|Center for Infectious Disease Modeling and Analysis, Yale School of Public Health, New Haven, Connecticut, United States of America.|Department of Integrative Biology, The University of Texas at Austin, Austin, Texas, United States of America.', 'United States|United States|United States|United States|United States', 23, 'Computational Biology|Disease Outbreaks|Humans|Models, Biological|Models, Statistical|Public Health|Public Health Surveillance|Social Support', 'Journal Article', '10.1371/journal.pcbi.1004928', '27415615', 'As infectious disease surveillance systems expand to include digital, crowd-sourced, and social network data, public health agencies are gaining unprecedented access to high-resolution data and have an opportunity to selectively monitor informative individuals. Contact networks, which are the webs of interaction through which diseases spread, determine whether and when individuals become infected, and thus who might serve as early and accurate surveillance sensors. Here, we evaluate three strategies for selecting sensors-sampling the most connected, random, and friends of random individuals-in three complex social networks-a simple scale-free network, an empirical Venezuelan college student network, and an empirical Montreal wireless hotspot usage network. Across five different surveillance goals-early and accurate detection of epidemic emergence and peak, and general situational awareness-we find that the optimal choice of sensors depends on the public health goal, the underlying network and the reproduction number of the disease (R0). For diseases with a low R0, the most connected individuals provide the earliest and most accurate information about both the onset and peak of an outbreak. However, identifying network hubs is often impractical, and they can be misleading if monitored for general situational awareness, if the underlying network has significant community structure, or if R0 is high or unknown. Taking a theoretical approach, we also derive the optimal surveillance system for early outbreak detection but find that real-world identification of such sensors would be nearly impossible. By contrast, the friends-of-random strategy offers a more practical and robust alternative. It can be readily implemented without prior knowledge of the network, and by identifying sensors with higher than average, but not the highest, epidemiological risk, it provides reasonably early and accurate information.'),
(87933, 2016, 'plos', 'Ten Simple Rules for Writing a Postdoctoral Fellowship', 'Yuan, Ke|Cai, Lei|Ngok, Siu Ping|Ma, Li|Botham, Crystal M', 'Division of Pulmonary and Critical Care Medicine, Department of Medicine, Stanford University, Stanford, California, United States of America.|Department of Materials Science and Engineering, Stanford Neuroscience Institute, Stanford University, Stanford, California, United States of America.|Division of Hematology, Oncology, Stem Cell Transplantation, and Cancer Biology, Department of Pediatrics, Stanford University School of Medicine, Stanford, California, United States of America.|Asian Liver Center and Department of Surgery, Stanford University, Stanford, California, United States of America.|Stanford Biosciences Grant Writing Academy, Stanford University, Stanford, California, United States of America.', 'United States|United States|United States|United States|United States', 2, 'Education, Graduate|Fellowships and Scholarships|Guidelines as Topic|Writing', 'Editorial', '10.1371/journal.pcbi.1004934', '27415752', '-'),
(87934, 2016, 'plos', 'Ten Simple Rules for Taking Advantage of Git and GitHub', 'Perez-Riverol, Yasset|Gatto, Laurent|Wang, Rui|Sachsenberg, Timo|Uszkoreit, Julian|Leprevost, Felipe da Veiga|Fufezan, Christian|Ternent, Tobias|Eglen, Stephen J|Katz, Daniel S|Pollard, Tom J|Konovalov, Alexander|Flight, Robert M|Blin, Kai|Vizcaíno, Juan Antonio', 'European Molecular Biology Laboratory, European Bioinformatics Institute (EMBL-EBI), Wellcome Trust Genome Campus, Hinxton, Cambridge, United Kingdom.|Computational Proteomics Unit, Cambridge Systems Biology Centre, University of Cambridge, Cambridge, United Kingdom.|European Molecular Biology Laboratory, European Bioinformatics Institute (EMBL-EBI), Wellcome Trust Genome Campus, Hinxton, Cambridge, United Kingdom.|Applied Bioinformatics and Department of Computer Science, University of Tübingen, Tübingen, Germany.|Medizinisches Proteom-Center, Ruhr-Universität Bochum, Bochum, Germany.|Department of Pathology, University of Michigan, Ann Arbor, Michigan, United States of America.|Institute of Plant Biology and Biotechnology, University of Münster, Münster, Germany.|European Molecular Biology Laboratory, European Bioinformatics Institute (EMBL-EBI), Wellcome Trust Genome Campus, Hinxton, Cambridge, United Kingdom.|Centre for Mathematical Sciences, University of Cambridge, Cambridge, United Kingdom.|National Center for Supercomputing Applications and Graduate School of Library and Information Science, University of Illinois, Urbana, Illinois, United States of America.|MIT Laboratory for Computational Physiology, Institute for Medical Engineering and Science, Massachusetts Institute of Technology, Cambridge, Massachusetts, United States of America.|Centre for Interdisciplinary Research in Computational Algebra, University of St Andrews, St Andrews, United Kingdom.|Department of Molecular Biology and Biochemistry, Markey Cancer Center, Resource Center for Stable Isotope-Resolved Metabolomics, University of Kentucky, Lexington, Kentucky, United States of America.|The Novo Nordisk Foundation Center for Biosustainability, Technical University of Denmark, Hørsholm, Denmark.|European Molecular Biology Laboratory, European Bioinformatics Institute (EMBL-EBI), Wellcome Trust Genome Campus, Hinxton, Cambridge, United Kingdom.', 'United Kingdom|United Kingdom|United Kingdom|Germany|Germany|United States|Germany|United Kingdom|Un', 38, 'Computational Biology|Guidelines as Topic', 'Editorial', '10.1371/journal.pcbi.1004947', '27415786', '-'),
(87935, 2016, 'plos', 'NLLSS: Predicting Synergistic Drug Combinations Based on Semi-supervised Learning', 'Chen, Xing|Ren, Biao|Chen, Ming|Wang, Quanxin|Zhang, Lixin|Yan, Guiying', 'School of Information and Electrical Engineering, China University of Mining and Technology, Xuzhou, China.|Chinese Academy of Sciences Key Laboratory of Pathogenic Microbiology and Immunology, Institute of Microbiology, Chinese Academy of Sciences, Beijing, China.|Chinese Academy of Sciences Key Laboratory of Pathogenic Microbiology and Immunology, Institute of Microbiology, Chinese Academy of Sciences, Beijing, China.|Chinese Academy of Sciences Key Laboratory of Pathogenic Microbiology and Immunology, Institute of Microbiology, Chinese Academy of Sciences, Beijing, China.|Chinese Academy of Sciences Key Laboratory of Pathogenic Microbiology and Immunology, Institute of Microbiology, Chinese Academy of Sciences, Beijing, China.|Academy of Mathematics and Systems Science, Chinese Academy of Sciences, Beijing, China.', 'China|China|China|China|China|China', 120, 'Antifungal Agents|Candida albicans|Computational Biology|Drug Combinations|Drug Synergism|Humans|Models, Theoretical|Supervised Machine Learning', 'Journal Article', '10.1371/journal.pcbi.1004975', '27415801', 'Fungal infection has become one of the leading causes of hospital-acquired infections with high mortality rates. Furthermore, drug resistance is common for fungus-causing diseases. Synergistic drug combinations could provide an effective strategy to overcome drug resistance. Meanwhile, synergistic drug combinations can increase treatment efficacy and decrease drug dosage to avoid toxicity. Therefore, computational prediction of synergistic drug combinations for fungus-causing diseases becomes attractive. In this study, we proposed similar nature of drug combinations: principal drugs which obtain synergistic effect with similar adjuvant drugs are often similar and vice versa. Furthermore, we developed a novel algorithm termed Network-based Laplacian regularized Least Square Synergistic drug combination prediction (NLLSS) to predict potential synergistic drug combinations by integrating different kinds of information such as known synergistic drug combinations, drug-target interactions, and drug chemical structures. We applied NLLSS to predict antifungal synergistic drug combinations and showed that it achieved excellent performance both in terms of cross validation and independent prediction. Finally, we performed biological experiments for fungal pathogen Candida albicans to confirm 7 out of 13 predicted antifungal synergistic drug combinations. NLLSS provides an efficient strategy to identify potential synergistic antifungal combinations.'),
(87936, 2016, 'plos', 'Phasic Burst Stimulation: A Closed-Loop Approach to Tuning Deep Brain Stimulation Parameters for Parkinsons Disease', 'Holt, Abbey B|Wilson, Dan|Shinn, Max|Moehlis, Jeff|Netoff, Theoden I', 'Graduate Program in Neuroscience, University of Minnesota, Minneapolis, Minnesota, United States of America.|Department of Mechanical Engineering, University of California, Santa Barbara, California, United States of America.|Department of Neuroscience, University of Minnesota, Minneapolis, Minnesota, United States of America.|Department of Mechanical Engineering, University of California, Santa Barbara, California, United States of America.|Department of Biomedical Engineering, University of Minnesota, Minneapolis, Minnesota, United States of America.', 'United States|United States|United States|United States|United States', 31, 'Animals|Computational Biology|Deep Brain Stimulation|Electrophysiological Phenomena|Globus Pallidus|Humans|Models, Neurological|Neurons|Parkinson Disease|Primates', 'Journal Article', '10.1371/journal.pcbi.1005011', '27415832', 'We propose a novel, closed-loop approach to tuning deep brain stimulation (DBS) for Parkinsons disease (PD). The approach, termed Phasic Burst Stimulation (PhaBS), applies a burst of stimulus pulses over a range of phases predicted to disrupt pathological oscillations seen in PD. Stimulation parameters are optimized based on phase response curves (PRCs), which would be measured from each patient. This approach is tested in a computational model of PD with an emergent population oscillation. We show that the stimulus phase can be optimized using the PRC, and that PhaBS is more effective at suppressing the pathological oscillation than a single phasic stimulus pulse. PhaBS provides a closed-loop approach to DBS that can be optimized for each patient.'),
(87937, 2016, 'plos', 'Intrinsic Valuation of Information in Decision Making under Uncertainty', 'Bennett, Daniel|Bode, Stefan|Brydevall, Maja|Warren, Hayley|Murawski, Carsten', 'Melbourne School of Psychological Sciences, The University of Melbourne, Parkville, Victoria, Australia.|Melbourne School of Psychological Sciences, The University of Melbourne, Parkville, Victoria, Australia.|Melbourne School of Psychological Sciences, The University of Melbourne, Parkville, Victoria, Australia.|Melbourne School of Psychological Sciences, The University of Melbourne, Parkville, Victoria, Australia.|Department of Finance, The University of Melbourne, Parkville, Victoria, Australia.', 'Australia|Australia|Australia|Australia|Australia', 19, 'Adolescent|Adult|Algorithms|Computational Biology|Decision Making|Female|Humans|Information Seeking Behavior|Male|Risk-Taking|Uncertainty|Young Adult', 'Journal Article', '10.1371/journal.pcbi.1005020', '27416034', 'In a dynamic world, an accurate model of the environment is vital for survival, and agents ought regularly to seek out new information with which to update their world models. This aspect of behaviour is not captured well by classical theories of decision making, and the cognitive mechanisms of information seeking are poorly understood. In particular, it is not known whether information is valued only for its instrumental use, or whether humans also assign it a non-instrumental intrinsic value. To address this question, the present study assessed preference for non-instrumental information among 80 healthy participants in two experiments. Participants performed a novel information preference task in which they could choose to pay a monetary cost to receive advance information about the outcome of a monetary lottery. Importantly, acquiring information did not alter lottery outcome probabilities. We found that participants were willing to incur considerable monetary costs to acquire payoff-irrelevant information about the lottery outcome. This behaviour was well explained by a computational cognitive model in which information preference resulted from aversion to temporally prolonged uncertainty. These results strongly suggest that humans assign an intrinsic value to information in a manner inconsistent with normative accounts of decision making under uncertainty. This intrinsic value may be associated with adaptive behaviour in real-world environments by producing a bias towards exploratory and information-seeking behaviour.'),
(87938, 2016, 'plos', 'ASSET: Analysis of Sequences of Synchronous Events in Massively Parallel Spike Trains', 'Torre, Emiliano|Canova, Carlos|Denker, Michael|Gerstein, George|Helias, Moritz|Grün, Sonja', 'Institute of Neuroscience and Medicine (INM-6) and Institute for Advanced Simulation (IAS-6) and JARA BRAIN Institute I, Jülich Research Centre, Jülich, Germany.|Institute of Neuroscience and Medicine (INM-6) and Institute for Advanced Simulation (IAS-6) and JARA BRAIN Institute I, Jülich Research Centre, Jülich, Germany.|Institute of Neuroscience and Medicine (INM-6) and Institute for Advanced Simulation (IAS-6) and JARA BRAIN Institute I, Jülich Research Centre, Jülich, Germany.|Department of Neuroscience, University of Pennsylvania, Philadelphia, Pennsylvania, United States of America.|Institute of Neuroscience and Medicine (INM-6) and Institute for Advanced Simulation (IAS-6) and JARA BRAIN Institute I, Jülich Research Centre, Jülich, Germany.|Institute of Neuroscience and Medicine (INM-6) and Institute for Advanced Simulation (IAS-6) and JARA BRAIN Institute I, Jülich Research Centre, Jülich, Germany.', 'Germany|Germany|Germany|United States|Germany|Germany', 15, 'Action Potentials|Algorithms|Cerebral Cortex|Computational Biology|Humans|Models, Neurological|Neurons', 'Journal Article', '10.1371/journal.pcbi.1004939', '27420734', 'With the ability to observe the activity from large numbers of neurons simultaneously using modern recording technologies, the chance to identify sub-networks involved in coordinated processing increases. Sequences of synchronous spike events (SSEs) constitute one type of such coordinated spiking that propagates activity in a temporally precise manner. The synfire chain was proposed as one potential model for such network processing. Previous work introduced a method for visualization of SSEs in massively parallel spike trains, based on an intersection matrix that contains in each entry the degree of overlap of active neurons in two corresponding time bins. Repeated SSEs are reflected in the matrix as diagonal structures of high overlap values. The method as such, however, leaves the task of identifying these diagonal structures to visual inspection rather than to a quantitative analysis. Here we present ASSET (Analysis of Sequences of Synchronous EvenTs), an improved, fully automated method which determines diagonal structures in the intersection matrix by a robust mathematical procedure. The method consists of a sequence of steps that i) assess which entries in the matrix potentially belong to a diagonal structure, ii) cluster these entries into individual diagonal structures and iii) determine the neurons composing the associated SSEs. We employ parallel point processes generated by stochastic simulations as test data to demonstrate the performance of the method under a wide range of realistic scenarios, including different types of non-stationarity of the spiking activity and different correlation structures. Finally, the ability of the method to discover SSEs is demonstrated on complex data from large network simulations with embedded synfire chains. Thus, ASSET represents an effective and efficient tool to analyze massively parallel spike data for temporal sequences of synchronous activity.'),
(87939, 2016, 'plos', 'Near Equilibrium Calculus of Stem Cells in Application to the Airway Epithelium Lineage', 'Sun, Zheng|Plikus, Maksim V|Komarova, Natalia L', 'Department of Mathematics, University of California, Irvine, Irvine, California, United States of America.|Department of Developmental and Cell Biology, Sue and Bill Gross Stem Cell Research Center and Center for Complex Biological Systems, University of California, Irvine, Irvine, California, United States of America.|Department of Mathematics, University of California, Irvine, Irvine, California, United States of America.', 'United States|United States|United States', 4, 'Animals|Cell Lineage|Computational Biology|Epithelial Cells|Homeostasis|Mice|Models, Biological|Signal Transduction|Stem Cells|Stochastic Processes', 'Journal Article', '10.1371/journal.pcbi.1004990', '27427948', 'Homeostatic maintenance of tissues is orchestrated by well tuned networks of cellular signaling. Such networks regulate, in a stochastic manner, fates of all cells within the respective lineages. Processes such as symmetric and asymmetric divisions, differentiation, de-differentiation, and death have to be controlled in a dynamic fashion, such that the cell population is maintained at a stable equilibrium, has a sufficiently low level of stochastic variation, and is capable of responding efficiently to external damage. Cellular lineages in real tissues may consist of a number of different cell types, connected by hierarchical relationships, albeit not necessarily linear, and engaged in a number of different processes. Here we develop a general mathematical methodology for near equilibrium studies of arbitrarily complex hierarchical cell populations, under regulation by a control network. This methodology allows us to (1) determine stability properties of the network, (2) calculate the stochastic variance, and (3) predict how different control mechanisms affect stability and robustness of the system. We demonstrate the versatility of this tool by using the example of the airway epithelium lineage. Recent research shows that airway epithelium stem cells divide mostly asymmetrically, while the so-called secretory cells divide predominantly symmetrically. It further provides quantitative data on the recovery dynamics of the airway epithelium, which can include secretory cell de-differentiation. Using our new methodology, we demonstrate that while a number of regulatory networks can be compatible with the observed recovery behavior, the observed division patterns of cells are the most optimal from the viewpoint of homeostatic lineage stability and minimizing the variation of the cell population size. This not only explains the observed yet poorly understood features of airway tissue architecture, but also helps to deduce the information on the still largely hypothetical regulatory mechanisms governing tissue turnover, and lends insight into how different control loops influence the stability and variance properties of cell populations.'),
(87940, 2016, 'plos', 'The Integrated Role of Wnt/xcexb2-Catenin, N-Glycosylation, and E-Cadherin-Mediated Adhesion in Network Dynamics', 'Vargas, Diego A|Sun, Meng|Sadykov, Khikmet|Kukuruzinska, Maria A|Zaman, Muhammad H', 'Department of Biomedical Engineering, Boston University, Boston, Massachusetts, United States of America.|Department of Biomedical Engineering, Boston University, Boston, Massachusetts, United States of America.|Department of Molecular and Cell Biology, Boston University School of Dental Medicine, Boston, Massachusetts, United States of America.|Department of Molecular and Cell Biology, Boston University School of Dental Medicine, Boston, Massachusetts, United States of America.|Department of Biomedical Engineering, Boston University, Boston, Massachusetts, United States of America.', 'United States|United States|United States|United States|United States', 9, 'Animals|Cadherins|Cell Adhesion|Cell Line|Cell Movement|Computational Biology|Dogs|Glycosylation|Madin Darby Canine Kidney Cells|Models, Biological|N-Acetylglucosaminyltransferases|Wnt Proteins|Wnt Signaling Pathway|beta Catenin', 'Journal Article', '10.1371/journal.pcbi.1005007', '27427963', 'The cellular network composed of the evolutionarily conserved metabolic pathways of protein N-glycosylation, Wnt/xcexb2-catenin signaling pathway, and E-cadherin-mediated cell-cell adhesion plays pivotal roles in determining the balance between cell proliferation and intercellular adhesion during development and in maintaining homeostasis in differentiated tissues. These pathways share a highly conserved regulatory molecule, xcexb2-catenin, which functions as both a structural component of E-cadherin junctions and as a co-transcriptional activator of the Wnt/xcexb2-catenin signaling pathway, whose target is the N-glycosylation-regulating gene, DPAGT1. Whereas these pathways have been studied independently, little is known about the dynamics of their interaction. Here we present the first numerical model of this network in MDCK cells. Since the network comprises a large number of molecules with varying cell context and time-dependent levels of expression, it can give rise to a wide range of plausible cellular states that are difficult to track. Using known kinetic parameters for individual reactions in the component pathways, we have developed a theoretical framework and gained new insights into cellular regulation of the network. Specifically, we developed a mathematical model to quantify the fold-change in concentration of any molecule included in the mathematical representation of the network in response to a simulated activation of the Wnt/ xcexb2-catenin pathway with Wnt3a under different conditions. We quantified the importance of protein N-glycosylation and synthesis of the DPAGT1 encoded enzyme, GPT, in determining the abundance of cytoplasmic xcexb2-catenin. We confirmed the role of axin in xcexb2-catenin degradation. Finally, our data suggest that cell-cell adhesion is insensitive to E-cadherin recycling in the cell. We validate the model by inhibiting xcexb2-catenin-mediated activation of DPAGT1 expression and predicting changes in cytoplasmic xcexb2-catenin concentration and stability of E-cadherin junctions in response to DPAGT1 inhibition. We show the impact of pathway dysregulation through measurements of cell migration in scratch-wound assays. Collectively, our results highlight the importance of numerical analyses of cellular networks dynamics to gain insights into physiological processes and potential design of therapeutic strategies to prevent epithelial cell invasion in cancer.'),
(87941, 2016, 'plos', 'Robust Inference of Cell-to-Cell Expression Variations from Single- and K-Cell Profiling', 'Narayanan, Manikandan|Martins, Andrew J|Tsang, John S', 'Systems Genomics and Bioinformatics Unit, Laboratory of Systems Biology, National Institute of Allergy and Infectious Diseases, National Institutes of Health, Bethesda, Maryland, United States of America.|Systems Genomics and Bioinformatics Unit, Laboratory of Systems Biology, National Institute of Allergy and Infectious Diseases, National Institutes of Health, Bethesda, Maryland, United States of America.|Systems Genomics and Bioinformatics Unit, Laboratory of Systems Biology, National Institute of Allergy and Infectious Diseases, National Institutes of Health, Bethesda, Maryland, United States of America.', 'United States|United States|United States', 5, 'Computational Biology|Gene Expression Profiling|Humans|Macrophages|Models, Biological|Models, Statistical|RNA, Messenger|Single-Cell Analysis', 'Journal Article', '10.1371/journal.pcbi.1005016', '27438699', 'Quantifying heterogeneity in gene expression among single cells can reveal information inaccessible to cell-population averaged measurements. However, the expression level of many genes in single cells fall below the detection limit of even the most sensitive technologies currently available. One proposed approach to overcome this challenge is to measure random pools of k cells (e.g., 10) to increase sensitivity, followed by computational deconvolution of cellular heterogeneity parameters (CHPs), such as the biological variance of single-cell expression levels. Existing approaches infer CHPs using either single-cell or k-cell data alone, and typically within a single population of cells. However, integrating both single- and k-cell data may reap additional benefits, and quantifying differences in CHPs across cell populations or conditions could reveal novel biological information. Here we present a Bayesian approach that can utilize single-cell, k-cell, or both simultaneously to infer CHPs within a single condition or their differences across two conditions. Using simulated as well as experimentally generated single- and k-cell data, we found situations where each data type would offer advantages, but using both together can improve precision and better reconcile CHP information contained in single- and k-cell data. We illustrate the utility of our approach by applying it to jointly generated single- and k-cell data to reveal CHP differences in several key inflammatory genes between resting and inflammatory cytokine-activated human macrophages, delineating differences in the distribution of ON versus OFF cells and in continuous variation of expression level among cells. Our approach thus offers a practical and robust framework to assess and compare cellular heterogeneity within and across biological conditions using modern multiplexed technologies.'),
(87942, 2016, 'plos', 'Learning to Predict miRNA-mRNA Interactions from AGO CLIP Sequencing and CLASH Data', 'Lu, Yuheng|Leslie, Christina S', '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.', 'United States|United States', 12, 'Animals|Argonaute Proteins|Computational Biology|HEK293 Cells|Humans|Immunoprecipitation|Mice|MicroRNAs|Models, Statistical|Sequence Analysis, RNA|Ultraviolet Rays', 'Journal Article', '10.1371/journal.pcbi.1005026', '27438777', 'Recent technologies like AGO CLIP sequencing and CLASH enable direct transcriptome-wide identification of AGO binding and miRNA target sites, but the most widely used miRNA target prediction algorithms do not exploit these data. Here we use discriminative learning on AGO CLIP and CLASH interactions to train a novel miRNA target prediction model. Our method combines two SVM classifiers, one to predict miRNA-mRNA duplexes and a second to learn a binding model of AGOs local UTR sequence preferences and positional bias in 3UTR isoforms. The duplex SVM model enables the prediction of non-canonical target sites and more accurately resolves miRNA interactions from AGO CLIP data than previous methods. The binding model is trained using a multi-task strategy to learn context-specific and common AGO sequence preferences. The duplex and common AGO binding models together outperform existing miRNA target prediction algorithms on held-out binding data. Open source code is available at https://bitbucket.org/leslielab/chimiric.'),
(87943, 2016, 'plos', 'Reinforcement Learning Explains Conditional Cooperation and Its Moody Cousin', 'Ezaki, Takahiro|Horita, Yutaka|Takezawa, Masanori|Masuda, Naoki', 'Research Center for Advanced Science and Technology, The University of Tokyo, Meguro-ku, Tokyo, Japan.|National Institute of Informatics, Hitotsubashi, Chiyoda-ku, Tokyo, Japan.|Department of Behavioral Science, Hokkaido University, Kita-ku, Sapporo, Japan.|Department of Engineering Mathematics, University of Bristol, Clifton, Bristol, United Kingdom.', 'Japan|Japan|Japan|United Kingdom', 14, 'Affect|Computational Biology|Cooperative Behavior|Game Theory|Humans|Learning|Models, Psychological|Reinforcement (Psychology)|Social Behavior', 'Journal Article', '10.1371/journal.pcbi.1005034', '27438888', 'Direct reciprocity, or repeated interaction, is a main mechanism to sustain cooperation under social dilemmas involving two individuals. For larger groups and networks, which are probably more relevant to understanding and engineering our society, experiments employing repeated multiplayer social dilemma games have suggested that humans often show conditional cooperation behavior and its moody variant. Mechanisms underlying these behaviors largely remain unclear. Here we provide a proximate account for this behavior by showing that individuals adopting a type of reinforcement learning, called aspiration learning, phenomenologically behave as conditional cooperator. By definition, individuals are satisfied if and only if the obtained payoff is larger than a fixed aspiration level. They reinforce actions that have resulted in satisfactory outcomes and anti-reinforce those yielding unsatisfactory outcomes. The results obtained in the present study are general in that they explain extant experimental results obtained for both so-called moody and non-moody conditional cooperation, prisoners dilemma and public goods games, and well-mixed groups and networks. Different from the previous theory, individuals are assumed to have no access to information about what other individuals are doing such that they cannot explicitly use conditional cooperation rules. In this sense, myopic aspiration learning in which the unconditional propensity of cooperation is modulated in every discrete time step explains conditional behavior of humans. Aspiration learners showing (moody) conditional cooperation obeyed a noisy GRIM-like strategy. This is different from the Pavlov, a reinforcement learning strategy promoting mutual cooperation in two-player situations.'),
(87944, 2016, 'plos', 'Ten Simple Rules for Curating and Facilitating Small Workshops', 'McInerny, Greg J', 'Centre for Interdisciplinary Methodologies, Department of Social Sciences, University of Warwick, Coventry, United Kingdom.', 'United Kingdom', 6, 'Documentation|Education|Electronic Mail|Guidelines as Topic|Planning Techniques|Speech', 'Editorial', '10.1371/journal.pcbi.1004745', '27441642', '-'),
(87945, 2016, 'plos', 'Modeling of Kidney Hemodynamics: Probability-Based Topology of an Arterial Network', 'Postnov, Dmitry D|Marsh, Donald J|Postnov, Dmitry E|Braunstein, Thomas H|Holstein-Rathlou, Niels-Henrik|Martens, Erik A|Sosnovtseva, Olga', 'Department of Biomedical Sciences, University of Copenhagen, Copenhagen, Denmark.|Department of Molecular Pharmacology, Physiology, and Biotechnology, Brown University, Providence, Rhode Island.|Physics Department, Saratov State University, Saratov, Russian Federation.|Department of Biomedical Sciences, University of Copenhagen, Copenhagen, Denmark.|Department of Biomedical Sciences, University of Copenhagen, Copenhagen, Denmark.|Department of Biomedical Sciences, University of Copenhagen, Copenhagen, Denmark.|Department of Biomedical Sciences, University of Copenhagen, Copenhagen, Denmark.', 'Denmark|-|Russian Federation|Denmark|Denmark|Denmark|Denmark', 9, 'Algorithms|Animals|Arterioles|Computational Biology|Hemodynamics|Image Processing, Computer-Assisted|Kidney|Models, Biological|Nephrons|Rats|Renal Artery', 'Journal Article', '10.1371/journal.pcbi.1004922', '27447287', 'Through regulation of the extracellular fluid volume, the kidneys provide important long-term regulation of blood pressure. At the level of the individual functional unit (the nephron), pressure and flow control involves two different mechanisms that both produce oscillations. The nephrons are arranged in a complex branching structure that delivers blood to each nephron and, at the same time, provides a basis for an interaction between adjacent nephrons. The functional consequences of this interaction are not understood, and at present it is not possible to address this question experimentally. We provide experimental data and a new modeling approach to clarify this problem. To resolve details of microvascular structure, we collected 3D data from more than 150 afferent arterioles in an optically cleared rat kidney. Using these results together with published micro-computed tomography (xcexbcCT) data we develop an algorithm for generating the renal arterial network. We then introduce a mathematical model describing blood flow dynamics and nephron to nephron interaction in the network. The model includes an implementation of electrical signal propagation along a vascular wall. Simulation results show that the renal arterial architecture plays an important role in maintaining adequate pressure levels and the self-sustained dynamics of nephrons.'),
(87946, 2016, 'plos', 'How People Use Social Information to Find out What to Want in the Paradigmatic Case of Inter-temporal Preferences', 'Moutoussis, Michael|Dolan, Raymond J|Dayan, Peter', 'Wellcome Trust Centre for Neuroimaging, University College London, London, United Kingdom.|Wellcome Trust Centre for Neuroimaging, University College London, London, United Kingdom.|Gatsby Computational Neuroscience Unit, University College London, London, United Kingdom.', 'United Kingdom|United Kingdom|United Kingdom', 13, 'Adolescent|Adult|Bayes Theorem|Choice Behavior|Computational Biology|Female|Humans|Male|Models, Psychological|Social Behavior|Young Adult', 'Journal Article', '10.1371/journal.pcbi.1004965', '27447491', 'The weight with which a specific outcome feature contributes to preference quantifies a persons taste for that feature. However, far from being fixed personality characteristics, tastes are plastic. They tend to align, for example, with those of others even if such conformity is not rewarded. We hypothesised that people can be uncertain about their tastes. Personal tastes are therefore uncertain beliefs. People can thus learn about them by considering evidence, such as the preferences of relevant others, and then performing Bayesian updating. If a persons choice variability reflects uncertainty, as in random-preference models, then a signature of Bayesian updating is that the degree of taste change should correlate with that persons choice variability. Temporal discounting coefficients are an important example of taste-for patience. These coefficients quantify impulsivity, have good psychometric properties and can change upon observing others choices. We examined discounting preferences in a novel, large community study of 14-24 year olds. We assessed discounting behaviour, including decision variability, before and after participants observed another persons choices. We found good evidence for taste uncertainty and for Bayesian taste updating. First, participants displayed decision variability which was better accounted for by a random-taste than by a response-noise model. Second, apparent taste shifts were well described by a Bayesian model taking into account taste uncertainty and the relevance of social information. Our findings have important neuroscientific, clinical and developmental significance.'),
(87947, 2016, 'plos', 'Inference for Stochastic Chemical Kinetics Using Moment Equations and System Size Expansion', 'Fröhlich, Fabian|Thomas, Philipp|Kazeroonian, Atefeh|Theis, Fabian J|Grima, Ramon|Hasenauer, Jan', 'Helmholtz Zentrum München - German Research Center for Environmental Health, Institute of Computational Biology, Neuherberg, Germany.|Department of Mathematics, Imperial College London, London, United Kingdom.|Helmholtz Zentrum München - German Research Center for Environmental Health, Institute of Computational Biology, Neuherberg, Germany.|Helmholtz Zentrum München - German Research Center for Environmental Health, Institute of Computational Biology, Neuherberg, Germany.|School of Biological Sciences, University of Edinburgh, Edinburgh, United Kingdom.|Helmholtz Zentrum München - German Research Center for Environmental Health, Institute of Computational Biology, Neuherberg, Germany.', 'Germany|United Kingdom|Germany|Germany|United Kingdom|Germany', 35, 'Kinetics|Models, Biological|Models, Statistical|Signal Transduction|Single-Cell Analysis|Stochastic Processes|Systems Biology', 'Journal Article', '10.1371/journal.pcbi.1005030', '27447730', 'Quantitative mechanistic models are valuable tools for disentangling biochemical pathways and for achieving a comprehensive understanding of biological systems. However, to be quantitative the parameters of these models have to be estimated from experimental data. In the presence of significant stochastic fluctuations this is a challenging task as stochastic simulations are usually too time-consuming and a macroscopic description using reaction rate equations (RREs) is no longer accurate. In this manuscript, we therefore consider moment-closure approximation (MA) and the system size expansion (SSE), which approximate the statistical moments of stochastic processes and tend to be more precise than macroscopic descriptions. We introduce gradient-based parameter optimization methods and uncertainty analysis methods for MA and SSE. Efficiency and reliability of the methods are assessed using simulation examples as well as by an application to data for Epo-induced JAK/STAT signaling. The application revealed that even if merely population-average data are available, MA and SSE improve parameter identifiability in comparison to RRE. Furthermore, the simulation examples revealed that the resulting estimates are more reliable for an intermediate volume regime. In this regime the estimation error is reduced and we propose methods to determine the regime boundaries. These results illustrate that inference using MA and SSE is feasible and possesses a high sensitivity.'),
(87948, 2016, 'plos', 'Modeling Electrophysiological Coupling and Fusion between Human Mesenchymal Stem Cells and Cardiomyocytes', 'Mayourian, Joshua|Savizky, Ruben M|Sobie, Eric A|Costa, Kevin D', 'Cardiovascular Research Center, Icahn School of Medicine at Mount Sinai, New York, New York, United States of America.|Department of Chemistry, The Cooper Union, 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.|Cardiovascular Research Center, Icahn School of Medicine at Mount Sinai, New York, New York, United States of America.', 'United States|United States|United States|United States', 9, 'Computational Biology|Electrophysiological Phenomena|Humans|Mesenchymal Stem Cells|Models, Biological|Myocytes, Cardiac', 'Journal Article', '10.1371/journal.pcbi.1005014', '27454812', 'Human mesenchymal stem cell (hMSC) delivery has demonstrated promise in preclinical and clinical trials for myocardial infarction therapy, however, broad acceptance is hindered by limited understanding of hMSC-human cardiomyocyte (hCM) interactions. To better understand the electrophysiological consequences of direct heterocellular connections between hMSCs and hCMs, three original mathematical models were developed, representing an experimentally verified triad of hMSC families with distinct functional ion channel currents. The arrhythmogenic risk of such direct electrical interactions in the setting of healthy adult myocardium was predicted by coupling and fusing these hMSC models to the published ten Tusscher midcardial hCM model. Substantial variations in action potential waveform-such as decreased action potential duration (APD) and plateau height-were found when hCMs were coupled to the two hMSC models expressing functional delayed rectifier-like human ether à-go-go K+ channel 1 (hEAG1), the effects were exacerbated for fused hMSC-hCM hybrid cells. The third family of hMSCs (Type C), absent of hEAG1 activity, led to smaller single-cell action potential alterations during coupling and fusion, translating to longer tissue-level mean action potential wavelength. In a simulated 2-D monolayer of cardiac tissue, re-entry vulnerability with low (5%) hMSC insertion was approximately eight-fold lower with Type C hMSCs compared to hEAG1-functional hMSCs. A 20% decrease in APD dispersion by Type C hMSCs compared to hEAG1-active hMSCs supports the claim of reduced arrhythmogenic potential of this cell type with low hMSC insertion. However, at moderate (15%) and high (25%) hMSC insertion, the vulnerable window increased independent of hMSC type. In summary, this study provides novel electrophysiological models of hMSCs, predicts possible arrhythmogenic effects of hMSCs when directly coupled to healthy hCMs, and proposes that isolating a subset of hMSCs absent of hEAG1 activity may offer increased safety as a cell delivery cardiotherapy at low levels of hMSC-hCM coupling.');
INSERT INTO `papers` (`id`, `ano`, `journal`, `titulo`, `autores`, `afiliacao`, `pais`, `citacoes`, `palavra_chave`, `categorias`, `doi`, `pubmed`, `abstract`) VALUES
(87949, 2016, 'plos', 'Multiscale Simulations Suggest a Mechanism for the Association of the Dok7 PH Domain with PIP-Containing Membranes', 'Buyan, Amanda|Kalli, Antreas C|Sansom, Mark S P', 'Department of Biochemistry, University of Oxford, Oxford, United Kingdom.|Department of Biochemistry, University of Oxford, Oxford, United Kingdom.|Department of Biochemistry, University of Oxford, Oxford, United Kingdom.', 'United Kingdom|United Kingdom|United Kingdom', 15, 'Amino Acid Sequence|Animals|Binding Sites|Computational Biology|Molecular Dynamics Simulation|Muscle Proteins|Phosphatidylinositol Phosphates|Phosphotyrosine|Pleckstrin Homology Domains', 'Journal Article', '10.1371/journal.pcbi.1005028', '27459095', 'Dok7 is a peripheral membrane protein that is associated with the MuSK receptor tyrosine kinase. Formation of the Dok7/MuSK/membrane complex is required for the activation of MuSK. This is a key step in the complex exchange of signals between neuron and muscle, which lead to neuromuscular junction formation, dysfunction of which is associated with congenital myasthenic syndromes. The Dok7 structure consists of a Pleckstrin Homology (PH) domain and a Phosphotyrosine Binding (PTB) domain. The mechanism of the Dok7 association with the membrane remains largely unknown. Using multi-scale molecular dynamics simulations we have explored the formation of the Dok7 PH/membrane complex. Our simulations indicate that the PH domain of Dok7 associates with membranes containing phosphatidylinositol phosphates (PIPs) via interactions of the xcexb21/xcexb22, xcexb23/xcexb24, and xcexb25/xcexb26 loops, which together form a positively charged surface on the PH domain and interact with the negatively charged headgroups of PIP molecules. The initial encounter of the Dok7 PH domain is followed by formation of additional interactions with the lipid bilayer, and especially with PIP molecules, which stabilizes the Dok7 PH/membrane complex. We have quantified the binding of the PH domain to the model bilayers by calculating a density landscape for protein/membrane interactions. Detailed analysis of the PH/PIP interactions reveal both a canonical and an atypical site to be occupied by the anionic lipid. PH domain binding leads to local clustering of PIP molecules in the bilayer. Association of the Dok7 PH domain with PIP lipids is therefore seen as a key step in localization of Dok7 to the membrane and formation of a complex with MuSK.'),
(87950, 2016, 'plos', 'Model-Based Characterization of Inflammatory Gene Expression Patterns of Activated Macrophages', 'Rex, Julia|Albrecht, Ute|Ehlting, Christian|Thomas, Maria|Zanger, Ulrich M|Sawodny, Oliver|Häussinger, Dieter|Ederer, Michael|Feuer, Ronny|Bode, Johannes G', 'Institute for System Dynamics, University of Stuttgart, Stuttgart, Germany.|Clinic of Gastroenterology, Hepatology and Infectious Diseases, Heinrich-Heine-University, Düsseldorf, Germany.|Clinic of Gastroenterology, Hepatology and Infectious Diseases, Heinrich-Heine-University, Düsseldorf, Germany.|Dr. Margarete Fischer-Bosch Institute of Clinical Pharmacology, Stuttgart, and University of Tübingen, Tübingen, Germany.|Dr. Margarete Fischer-Bosch Institute of Clinical Pharmacology, Stuttgart, and University of Tübingen, Tübingen, Germany.|Institute for System Dynamics, University of Stuttgart, Stuttgart, Germany.|Clinic of Gastroenterology, Hepatology and Infectious Diseases, Heinrich-Heine-University, Düsseldorf, Germany.|Institute for System Dynamics, University of Stuttgart, Stuttgart, Germany.|Institute for System Dynamics, University of Stuttgart, Stuttgart, Germany.|Clinic of Gastroenterology, Hepatology and Infectious Diseases, Heinrich-Heine-University, Düsseldorf, Germany.', 'Germany|Germany|Germany|Germany|Germany|Germany|Germany|Germany|Germany|Germany', 9, 'Animals|Cells, Cultured|Computational Biology|Cytokines|Gene Expression|Gene Expression Profiling|Inflammation|Macrophage Activation|Macrophages|Mice|Reproducibility of Results', 'Journal Article', '10.1371/journal.pcbi.1005018', '27464342', 'Macrophages are cells with remarkable plasticity. They integrate signals from their microenvironment leading to context-dependent polarization into classically (M1) or alternatively (M2) activated macrophages, representing two extremes of a broad spectrum of divergent phenotypes. Thereby, macrophages deliver protective and pro-regenerative signals towards injured tissue but, depending on the eliciting damage, may also be responsible for the generation and aggravation of tissue injury. Although incompletely understood, there is emerging evidence that macrophage polarization is critical for these antagonistic roles. To identify activation-specific expression patterns of chemokines and cytokines that may confer these distinct effects a systems biology approach was applied. A comprehensive literature-based Boolean model was developed to describe the M1 (LPS-activated) and M2 (IL-4/13-activated) polarization types. The model was validated using high-throughput transcript expression data from murine bone marrow derived macrophages. By dynamic modeling of gene expression, the chronology of pathway activation and autocrine signaling was estimated. Our results provide a deepened understanding of the physiological balance leading to M1/M2 activation, indicating the relevance of co-regulatory signals at the level of Akt1 or Akt2 that may be important for directing macrophage polarization.'),
(87951, 2016, 'plos', 'Context Specific and Differential Gene Co-expression Networks via Bayesian Biclustering', 'Gao, Chuan|McDowell, Ian C|Zhao, Shiwen|Brown, Christopher D|Engelhardt, Barbara E', 'Department of Statistical Science, Duke University, Durham, North Carolina, United States of America.|Program in Computational Biology and Bioinformatics, Duke University, Durham, North Carolina, United States of America.|Program in Computational Biology and Bioinformatics, Duke University, Durham, North Carolina, United States of America.|Department of Genetics, University of Pennsylvania, Philadelphia, Pennsylvania, United States of America.|Department of Computer Science, Center for Statistics and Machine Learning, Princeton University, Princeton, New Jersey, United States of America.', 'United States|United States|United States|United States|Jersey', 0, 'Bayes Theorem|Breast Neoplasms|Cluster Analysis|Computational Biology|Female|Gene Expression Profiling|Gene Expression Regulation, Neoplastic|Gene Regulatory Networks|Humans|Male|Models, Genetic|Oligonucleotide Array Sequence Analysis', 'Journal Article', '10.1371/journal.pcbi.1004791', '27467526', 'Identifying latent structure in high-dimensional genomic data is essential for exploring biological processes. Here, we consider recovering gene co-expression networks from gene expression data, where each network encodes relationships between genes that are co-regulated by shared biological mechanisms. To do this, we develop a Bayesian statistical model for biclustering to infer subsets of co-regulated genes that covary in all of the samples or in only a subset of the samples. Our biclustering method, BicMix, allows overcomplete representations of the data, computational tractability, and joint modeling of unknown confounders and biological signals. Compared with related biclustering methods, BicMix recovers latent structure with higher precision across diverse simulation scenarios as compared to state-of-the-art biclustering methods. Further, we develop a principled method to recover context specific gene co-expression networks from the estimated sparse biclustering matrices. We apply BicMix to breast cancer gene expression data and to gene expression data from a cardiovascular study cohort, and we recover gene co-expression networks that are differential across ER+ and ER- samples and across male and female samples. We apply BicMix to the Genotype-Tissue Expression (GTEx) pilot data, and we find tissue specific gene networks. We validate these findings by using our tissue specific networks to identify trans-eQTLs specific to one of four primary tissues.'),
(87952, 2016, 'plos', 'A Multi-scale Computational Platform to Mechanistically Assess the Effect of Genetic Variation on Drug Responses in Human Erythrocyte Metabolism', 'Mih, Nathan|Brunk, Elizabeth|Bordbar, Aarash|Palsson, Bernhard O', 'Bioinformatics and Systems Biology Graduate Program, University of California, San Diego, La Jolla, California, United States of America.|Department of Bioengineering, University of California, San Diego, La Jolla, California, United States of America.|Department of Bioengineering, University of California, San Diego, La Jolla, California, United States of America.|Department of Bioengineering, University of California, San Diego, La Jolla, California, United States of America.', 'United States|United States|United States|United States', 0, 'Computational Biology|Erythrocytes|Genetic Variation|Humans|Molecular Dynamics Simulation|Pharmacogenetics|Protein Binding', 'Journal Article', '10.1371/journal.pcbi.1005039', '27467583', 'Progress in systems medicine brings promise to addressing patient heterogeneity and individualized therapies. Recently, genome-scale models of metabolism have been shown to provide insight into the mechanistic link between drug therapies and systems-level off-target effects while being expanded to explicitly include the three-dimensional structure of proteins. The integration of these molecular-level details, such as the physical, structural, and dynamical properties of proteins, notably expands the computational description of biochemical network-level properties and the possibility of understanding and predicting whole cell phenotypes. In this study, we present a multi-scale modeling framework that describes biological processes which range in scale from atomistic details to an entire metabolic network. Using this approach, we can understand how genetic variation, which impacts the structure and reactivity of a protein, influences both native and drug-induced metabolic states. As a proof-of-concept, we study three enzymes (catechol-O-methyltransferase, glucose-6-phosphate dehydrogenase, and glyceraldehyde-3-phosphate dehydrogenase) and their respective genetic variants which have clinically relevant associations. Using all-atom molecular dynamic simulations enables the sampling of long timescale conformational dynamics of the proteins (and their mutant variants) in complex with their respective native metabolites or drug molecules. We find that changes in a proteins structure due to a mutation influences protein binding affinity to metabolites and/or drug molecules, and inflicts large-scale changes in metabolism.'),
(87953, 2016, 'plos', 'The Differential Response of Proteins to Macromolecular Crowding', 'Candotti, Michela|Orozco, Modesto', 'Institute for Research in Biomedicine (IRB Barcelona), The Barcelona Institute of Science and Technology, Barcelona, Spain.|Institute for Research in Biomedicine (IRB Barcelona), The Barcelona Institute of Science and Technology, Barcelona, Spain.', 'Spain|Spain', 6, 'Computational Biology|Macromolecular Substances|Models, Molecular|Polyethylene Glycols|Protein Conformation|Protein Folding|Proteins|Water', 'Journal Article', '10.1371/journal.pcbi.1005040', '27471851', 'The habitat in which proteins exert their function contains up to 400 g/L of macromolecules, most of which are proteins. The repercussions of this dense environment on protein behavior are often overlooked or addressed using synthetic agents such as poly(ethylene glycol), whose ability to mimic protein crowders has not been demonstrated. Here we performed a comprehensive atomistic molecular dynamic analysis of the effect of protein crowders on the structure and dynamics of three proteins, namely an intrinsically disordered protein (ACTR), a molten globule conformation (NCBD), and a one-fold structure (IRF-3) protein. We found that crowding does not stabilize the native compact structure, and, in fact, often prevents structural collapse. Poly(ethylene glycol) PEG500 failed to reproduce many aspects of the physiologically-relevant protein crowders, thus indicating its unsuitability to mimic the cell interior. Instead, the impact of protein crowding on the structure and dynamics of a protein depends on its degree of disorder and results from two competing effects: the excluded volume, which favors compact states, and quinary interactions, which favor extended conformers. Such a viscous environment slows down protein flexibility and restricts the conformational landscape, often biasing it towards bioactive conformations but hindering biologically relevant protein-protein contacts. Overall, the protein crowders used here act as unspecific chaperons that modulate the protein conformational space, thus having relevant consequences for disordered proteins.'),
(87954, 2016, 'plos', 'PhyloBot: A Web Portal for Automated Phylogenetics, Ancestral Sequence Reconstruction, and Exploration of Mutational Trajectories', 'Hanson-Smith, Victor|Johnson, Alexander', 'Department of Microbiology and Immunology, University of California, San Francisco, San Francisco, California, United States of America.|Department of Microbiology and Immunology, University of California, San Francisco, San Francisco, California, United States of America.', 'United States|United States', 17, 'Animals|Computational Biology|Evolution, Molecular|Genetics|Humans|Internet|Phylogeny|Proteins|Sequence Alignment|Sequence Analysis, DNA|Software', 'Journal Article', '10.1371/journal.pcbi.1004976', '27472806', 'The method of phylogenetic ancestral sequence reconstruction is a powerful approach for studying evolutionary relationships among protein sequence, structure, and function. In particular, this approach allows investigators to (1) reconstruct and resurrect (that is, synthesize in vivo or in vitro) extinct proteins to study how they differ from modern proteins, (2) identify key amino acid changes that, over evolutionary timescales, have altered the function of the protein, and (3) order historical events in the evolution of protein function. Widespread use of this approach has been slow among molecular biologists, in part because the methods require significant computational expertise. Here we present PhyloBot, a web-based software tool that makes ancestral sequence reconstruction easy. Designed for non-experts, it integrates all the necessary software into a single user interface. Additionally, PhyloBot provides interactive tools to explore evolutionary trajectories between ancestors, enabling the rapid generation of hypotheses that can be tested using genetic or biochemical approaches. Early versions of this software were used in previous studies to discover genetic mechanisms underlying the functions of diverse protein families, including V-ATPase ion pumps, DNA-binding transcription regulators, and serine/threonine protein kinases. PhyloBot runs in a web browser, and is available at the following URL: http://www.phylobot.com. The software is implemented in Python using the Django web framework, and runs on elastic cloud computing resources from Amazon Web Services. Users can create and submit jobs on our free server (at the URL listed above), or use our open-source code to launch their own PhyloBot server.'),
(87955, 2016, 'plos', 'Improvement in Protein Domain Identification Is Reached by Breaking Consensus, with the Agreement of Many Profiles and Domain Co-occurrence', 'Bernardes, Juliana|Zaverucha, Gerson|Vaquero, Catherine|Carbone, Alessandra', 'Sorbonne Universités, UPMC Univ-Paris 6, CNRS, UMR 7238, Laboratoire de Biologie Computationnelle et Quantitative, Paris, France.|COPPE, Programa de Engenharia de Sistemas e Computação, Universidade Federal do Rio de Janeiro, Rio de Janeiro, Brazil.|Sorbonne Universités, UPMC Univ-Paris 6, INSERM U1135, CNRS ERL 8255, Centre dImmunologie et des Maladies Infectieuses (CIMI-Paris), Paris, France.|Sorbonne Universités, UPMC Univ-Paris 6, CNRS, UMR 7238, Laboratoire de Biologie Computationnelle et Quantitative, Paris, France.', 'France|Brazil|France|France', 17, 'Amino Acid Sequence|Computational Biology|Consensus Sequence|Databases, Protein|Plasmodium falciparum|Protein Domains|Proteins|Protozoan Proteins|Sequence Alignment|Sequence Analysis, Protein', 'Journal Article', '10.1371/journal.pcbi.1005038', '27472895', 'Traditional protein annotation methods describe known domains with probabilistic models representing consensus among homologous domain sequences. However, when relevant signals become too weak to be identified by a global consensus, attempts for annotation fail. Here we address the fundamental question of domain identification for highly divergent proteins. By using high performance computing, we demonstrate that the limits of state-of-the-art annotation methods can be bypassed. We design a new strategy based on the observation that many structural and functional protein constraints are not globally conserved through all species but might be locally conserved in separate clades. We propose a novel exploitation of the large amount of data available: 1. for each known protein domain, several probabilistic clade-centered models are constructed from a large and differentiated panel of homologous sequences, 2. a decision-making protocol combines outcomes obtained from multiple models, 3. a multi-criteria optimization algorithm finds the most likely protein architecture. The method is evaluated for domain and architecture prediction over several datasets and statistical testing hypotheses. Its performance is compared against HMMScan and HHblits, two widely used search methods based on sequence-profile and profile-profile comparison. Due to their closeness to actual protein sequences, clade-centered models are shown to be more specific and functionally predictive than the broadly used consensus models. Based on them, we improved annotation of Plasmodium falciparum protein sequences on a scale not previously possible. We successfully predict at least one domain for 72% of P. falciparum proteins against 63% achieved previously, corresponding to 30% of improvement over the total number of Pfam domain predictions on the whole genome. The method is applicable to any genome and opens new avenues to tackle evolutionary questions such as the reconstruction of ancient domain duplications, the reconstruction of the history of protein architectures, and the estimation of protein domain age. Website and software: http://www.lcqb.upmc.fr/CLADE.'),
(87956, 2016, 'plos', 'Impact of Heterogeneity in Sexual Behavior on Effectiveness in Reducing HIV Transmission with Test-and-Treat Strategy', 'Rozhnova, Ganna|van der Loeff, Maarten F Schim|Heijne, Janneke C M|Kretzschmar, Mirjam E', 'Julius Center for Health Sciences and Primary Care, University Medical Centre Utrecht, Utrecht, The Netherlands.|Department of Infectious Disease Control, Public Health Service Amsterdam, Amsterdam, The Netherlands.|Centre for Infectious Disease Control, National Institute of Public Health and the Environment, Bilthoven, The Netherlands.|Julius Center for Health Sciences and Primary Care, University Medical Centre Utrecht, Utrecht, The Netherlands.', 'Netherlands|Netherlands|Netherlands|Netherlands', 7, 'Anti-HIV Agents|HIV Infections|Homosexuality, Male|Humans|Male|Models, Statistical|Risk-Taking|Sexual Behavior', 'Journal Article', '10.1371/journal.pcbi.1005012', '27479074', 'The WHOs early-release guideline for antiretroviral treatment (ART) of HIV infection based on a recent trial conducted in 34 countries recommends starting treatment immediately upon an HIV diagnosis. Therefore, the test-and-treat strategy may become more widely used in an effort to scale up HIV treatment and curb further transmission. Here we examine behavioural determinants of HIV transmission and how heterogeneity in sexual behaviour influences the outcomes of this strategy. Using a deterministic model, we perform a systematic investigation into the effects of various mixing patterns in a population of men who have sex with men (MSM), stratified by partner change rates, on the elimination threshold and endemic HIV prevalence. We find that both the level of overdispersion in the distribution of the number of sexual partners and mixing between population subgroups have a large influence on endemic prevalence before introduction of ART and on possible long term effectiveness of ART. Increasing heterogeneity in risk behavior may lead to lower endemic prevalence levels, but requires higher coverage levels of ART for elimination. Elimination is only feasible for populations with a rather low degree of assortativeness of mixing and requires treatment coverage of almost 80% if rates of testing and treatment uptake by all population subgroups are equal. In this case, for fully assortative mixing and 80% coverage endemic prevalence is reduced by 57%. In the presence of heterogeneity in ART uptake, elimination is easier to achieve when the subpopulation with highest risk behavior is tested and treated more often than the rest of the population, and vice versa when it is less. The developed framework can be used to extract information on behavioral heterogeneity from existing data which is otherwise hard to determine from population surveys.'),
(87957, 2016, 'plos', 'Inference of Gene Regulatory Network Based on Local Bayesian Networks', 'Liu, Fei|Zhang, Shao-Wu|Guo, Wei-Feng|Wei, Ze-Gang|Chen, Luonan', 'Key Laboratory of Information Fusion Technology of Ministry of Education, School of Automation, Northwestern Polytechnical University, Xian, China.|Key Laboratory of Information Fusion Technology of Ministry of Education, School of Automation, Northwestern Polytechnical University, Xian, China.|Key Laboratory of Information Fusion Technology of Ministry of Education, School of Automation, Northwestern Polytechnical University, Xian, China.|Key Laboratory of Information Fusion Technology of Ministry of Education, School of Automation, Northwestern Polytechnical University, Xian, China.|Key Laboratory of Information Fusion Technology of Ministry of Education, School of Automation, Northwestern Polytechnical University, Xian, China.', 'China|China|China|China|China', 52, 'Algorithms|Bayes Theorem|Computational Biology|Escherichia coli|Gene Expression Profiling|Gene Regulatory Networks|Models, Genetic', 'Journal Article', '10.1371/journal.pcbi.1005024', '27479082', 'The inference of gene regulatory networks (GRNs) from expression data can mine the direct regulations among genes and gain deep insights into biological processes at a network level. During past decades, numerous computational approaches have been introduced for inferring the GRNs. However, many of them still suffer from various problems, e.g., Bayesian network (BN) methods cannot handle large-scale networks due to their high computational complexity, while information theory-based methods cannot identify the directions of regulatory interactions and also suffer from false positive/negative problems. To overcome the limitations, in this work we present a novel algorithm, namely local Bayesian network (LBN), to infer GRNs from gene expression data by using the network decomposition strategy and false-positive edge elimination scheme. Specifically, LBN algorithm first uses conditional mutual information (CMI) to construct an initial network or GRN, which is decomposed into a number of local networks or GRNs. Then, BN method is employed to generate a series of local BNs by selecting the k-nearest neighbors of each gene as its candidate regulatory genes, which significantly reduces the exponential search space from all possible GRN structures. Integrating these local BNs forms a tentative network or GRN by performing CMI, which reduces redundant regulations in the GRN and thus alleviates the false positive problem. The final network or GRN can be obtained by iteratively performing CMI and local BN on the tentative network. In the iterative process, the false or redundant regulations are gradually removed. When tested on the benchmark GRN datasets from DREAM challenge as well as the SOS DNA repair network in E.coli, our results suggest that LBN outperforms other state-of-the-art methods (ARACNE, GENIE3 and NARROMI) significantly, with more accurate and robust performance. In particular, the decomposition strategy with local Bayesian networks not only effectively reduce the computational cost of BN due to much smaller sizes of local GRNs, but also identify the directions of the regulations.'),
(87958, 2016, 'plos', 'Improved Metabolic Models for E coli and Mycoplasma genitalium from GlobalFit, an Algorithm That Simultaneously Matches Growth and Non-Growth Data Sets', 'Hartleb, Daniel|Jarre, Florian|Lercher, Martin J', 'Institute for Computer Science and Cluster of Excellence on Plant Sciences, Heinrich Heine University, Düsseldorf, Germany.|Institute for Mathematics, Heinrich Heine University, Düsseldorf, Germany.|Institute for Computer Science and Cluster of Excellence on Plant Sciences, Heinrich Heine University, Düsseldorf, Germany.', 'Germany|Germany|Germany', 11, 'Algorithms|Computational Biology|Computer Simulation|Escherichia coli|Gene Knockout Techniques|Metabolic Networks and Pathways|Models, Biological|Mycoplasma genitalium', 'Journal Article', '10.1371/journal.pcbi.1005036', '27482704', 'Constraint-based metabolic modeling methods such as Flux Balance Analysis (FBA) are routinely used to predict the effects of genetic changes and to design strains with desired metabolic properties. The major bottleneck in modeling genome-scale metabolic systems is the establishment and manual curation of reliable stoichiometric models. Initial reconstructions are typically refined through comparisons to experimental growth data from gene knockouts or nutrient environments. Existing methods iteratively correct one erroneous model prediction at a time, resulting in accumulating network changes that are often not globally optimal. We present GlobalFit, a bi-level optimization method that finds a globally optimal network, by identifying the minimal set of network changes needed to correctly predict all experimentally observed growth and non-growth cases simultaneously. When applied to the genome-scale metabolic model of Mycoplasma genitalium, GlobalFit decreases unexplained gene knockout phenotypes by 79%, increasing accuracy from 87.3% (according to the current state-of-the-art) to 97.3%. While currently available computers do not allow a global optimization of the much larger metabolic network of E. coli, the main strengths of GlobalFit are already played out when considering only one growth and one non-growth case simultaneously. Application of a corresponding strategy halves the number of unexplained cases for the already highly curated E. coli model, increasing accuracy from 90.8% to 95.4%.'),
(87959, 2016, 'plos', 'The Virtuous Cycle of a Data Ecosystem', 'Voytek, Bradley', 'Department of Cognitive Science, Neurosciences Graduate Program, Institute for Neural Computation, and Kavli Institute for Brain and Mind, University of California, San Diego, California, United States of America.', 'United States', 9, 'Computational Biology|Datasets as Topic', 'Journal Article', '10.1371/journal.pcbi.1005037', '27490108', '-'),
(87960, 2016, 'plos', 'Neuromotor Noise Is Malleable by Amplifying Perceived Errors', 'Hasson, Christopher J|Zhang, Zhaoran|Abe, Masaki O|Sternad, Dagmar', 'Department of Physical Therapy, Movement and Rehabilitation Sciences, Northeastern University, Boston, Massachusetts, United States of America.|Department of Bioengineering, Northeastern University, Boston, Massachusetts, United States of America.|Graduate School of Education, Hokkaido University, Sapporo, Hokkaido, Japan.|Departments of Biology, Electrical and Computer Engineering, and Physics, Northeastern University, Boston, Massachusetts, United States of America.', 'United States|United States|Japan|United States', 16, 'Adult|Algorithms|Computational Biology|Female|Humans|Male|Models, Neurological|Motor Skills|Task Performance and Analysis|Young Adult', 'Journal Article', '10.1371/journal.pcbi.1005044', '27490197', 'Variability in motor performance results from the interplay of error correction and neuromotor noise. This study examined whether visual amplification of error, previously shown to improve performance, affects not only error correction, but also neuromotor noise, typically regarded as inaccessible to intervention. Seven groups of healthy individuals, with six participants in each group, practiced a virtual throwing task for three days until reaching a performance plateau. Over three more days of practice, six of the groups received different magnitudes of visual error amplification, three of these groups also had noise added. An additional control group was not subjected to any manipulations for all six practice days. The results showed that the control group did not improve further after the first three practice days, but the error amplification groups continued to decrease their error under the manipulations. Analysis of the temporal structure of participants corrective actions based on stochastic learning models revealed that these performance gains were attained by reducing neuromotor noise and, to a considerably lesser degree, by increasing the size of corrective actions. Based on these results, error amplification presents a promising intervention to improve motor function by decreasing neuromotor noise after performance has reached an asymptote. These results are relevant for patients with neurological disorders and the elderly. More fundamentally, these results suggest that neuromotor noise may be accessible to practice interventions.'),
(87961, 2016, 'plos', 'The Representation of Prediction Error in Auditory Cortex', 'Rubin, Jonathan|Ulanovsky, Nachum|Nelken, Israel|Tishby, Naftali', 'Edmond and Lily Safra Center for Brain Sciences, Hebrew University, Jerusalem, Israel.|Department of Neurobiology, Weizmann Institute of Science, Rehovot, Israel.|Edmond and Lily Safra Center for Brain Sciences, Hebrew University, Jerusalem, Israel.|Edmond and Lily Safra Center for Brain Sciences, Hebrew University, Jerusalem, Israel.', 'Israel|Israel|Israel|Israel', 25, 'Animals|Auditory Cortex|Auditory Perception|Cats|Computational Biology|Models, Neurological|Neurons', 'Journal Article', '10.1371/journal.pcbi.1005058', '27490251', 'To survive, organisms must extract information from the past that is relevant for their future. How this process is expressed at the neural level remains unclear. We address this problem by developing a novel approach from first principles. We show here how to generate low-complexity representations of the past that produce optimal predictions of future events. We then illustrate this framework by studying the coding of oddball sequences in auditory cortex. We find that for many neurons in primary auditory cortex, trial-by-trial fluctuations of neuronal responses correlate with the theoretical prediction error calculated from the short-term past of the stimulation sequence, under constraints on the complexity of the representation of this past sequence. In some neurons, the effect of prediction error accounted for more than 50% of response variability. Reliable predictions often depended on a representation of the sequence of the last ten or more stimuli, although the representation kept only few details of that sequence.'),
(87962, 2016, 'plos', 'Strain Mediated Adaptation Is Key for Myosin Mechanochemistry: Discovering General Rules for Motor Activity', 'Jana, Biman|Onuchic, José N', 'Department of Physical Chemistry, Indian Association for the Cultivation of Science, Jadavpur, Kolkata, India.|Center for Theoretical Biological Physics, Rice University, Houston, Texas, United States of America.', 'India|United States', 6, 'Biomechanical Phenomena|Computational Biology|Molecular Dynamics Simulation|Molecular Motor Proteins|Myosins', 'Journal Article', '10.1371/journal.pcbi.1005035', '27494025', 'A structure-based model of myosin motor is built in the same spirit of our early work for kinesin-1 and Ncd towards physical understanding of its mechanochemical cycle. We find a structural adaptation of the motor head domain in post-powerstroke state that signals faster ADP release from it compared to the same from the motor head in the pre-powerstroke state. For dimeric myosin, an additional forward strain on the trailing head, originating from the postponed powerstroke state of the leading head in the waiting state of myosin, further increases the rate of ADP release. This coordination between the two heads is the essence of the processivity of the cycle. Our model provides a structural description of the powerstroke step of the cycle as an allosteric transition of the converter domain in response to the Pi release. Additionally, the variation in structural elements peripheral to catalytic motor domain is the deciding factor behind diverse directionalities of myosin motors (myosin V & VI). Finally, we observe that there are general rules for functional molecular motors across the different families. Allosteric structural adaptation of the catalytic motor head in different nucleotide states is crucial for mechanochemistry. Strain-mediated coordination between motor heads is essential for processivity and the variation of peripheral structural elements is essential for their diverse functionalities.'),
(87963, 2016, 'plos', 'Identification of Cell Type-Specific Differences in Erythropoietin Receptor Signaling in Primary Erythroid and Lung Cancer Cells', 'Merkle, Ruth|Steiert, Bernhard|Salopiata, Florian|Depner, Sofia|Raue, Andreas|Iwamoto, Nao|Schelker, Max|Hass, Helge|Wäsch, Marvin|Böhm, Martin E|Mücke, Oliver|Lipka, Daniel B|Plass, Christoph|Lehmann, Wolf D|Kreutz, Clemens|Timmer, Jens|Schilling, Marcel|Klingmüller, Ursula', 'Division Systems Biology of Signal Transduction, German Cancer Research Center (DKFZ), INF 280, Heidelberg, Germany.|Institute of Physics, University of Freiburg, Germany & BIOSS Centre for Biological Signalling Studies, University of Freiburg, Germany.|Division Systems Biology of Signal Transduction, German Cancer Research Center (DKFZ), INF 280, Heidelberg, Germany.|Division Systems Biology of Signal Transduction, German Cancer Research Center (DKFZ), INF 280, Heidelberg, Germany.|Institute of Physics, University of Freiburg, Germany & BIOSS Centre for Biological Signalling Studies, University of Freiburg, Germany.|Division Systems Biology of Signal Transduction, German Cancer Research Center (DKFZ), INF 280, Heidelberg, Germany.|Institute of Physics, University of Freiburg, Germany & BIOSS Centre for Biological Signalling Studies, University of Freiburg, Germany.|Institute of Physics, University of Freiburg, Germany & BIOSS Centre for Biological Signalling Studies, University of Freiburg, Germany.|Division Systems Biology of Signal Transduction, German Cancer Research Center (DKFZ), INF 280, Heidelberg, Germany.|Division Systems Biology of Signal Transduction, German Cancer Research Center (DKFZ), INF 280, Heidelberg, Germany.|Division Epigenomics and Cancer Risk Factors, German Cancer Research Center (DKFZ), INF 280, Heidelberg, Germany.|Regulation of Cellular Differentiation Group, Division Epigenomics and Cancer Risk Factors, German Cancer Research Center (DKFZ), INF 280, Heidelberg, Germany.|Division Epigenomics and Cancer Risk Factors, German Cancer Research Center (DKFZ), INF 280, Heidelberg, Germany.|Division Systems Biology of Signal Transduction, German Cancer Research Center (DKFZ), INF 280, Heidelberg, Germany.|Institute of Physics, University of Freiburg, Germany & BIOSS Centre for Biological Signalling Studies, University of Freiburg, Germany.|Institute of Physics, University of Freiburg, Germany & BIOSS Centre for Biological Signalling Studies, University of Freiburg, Germany.|Division Systems Biology of Signal Transduction, German Cancer Research Center (DKFZ), INF 280, Heidelberg, Germany.|Division Systems Biology of Signal Transduction, German Cancer Research Center (DKFZ), INF 280, Heidelberg, Germany.', 'Germany|Germany|Germany|Germany|Germany|Germany|Germany|Germany|Germany|Germany|Germany|Germany|Germ', 19, 'Carcinoma, Non-Small-Cell Lung|Cell Line, Tumor|Computational Biology|Erythroid Cells|Humans|Lung Neoplasms|Receptors, Erythropoietin|Signal Transduction', 'Journal Article', '10.1371/journal.pcbi.1005049', '27494133', 'Lung cancer, with its most prevalent form non-small-cell lung carcinoma (NSCLC), is one of the leading causes of cancer-related deaths worldwide, and is commonly treated with chemotherapeutic drugs such as cisplatin. Lung cancer patients frequently suffer from chemotherapy-induced anemia, which can be treated with erythropoietin (EPO). However, studies have indicated that EPO not only promotes erythropoiesis in hematopoietic cells, but may also enhance survival of NSCLC cells. Here, we verified that the NSCLC cell line H838 expresses functional erythropoietin receptors (EPOR) and that treatment with EPO reduces cisplatin-induced apoptosis. To pinpoint differences in EPO-induced survival signaling in erythroid progenitor cells (CFU-E, colony forming unit-erythroid) and H838 cells, we combined mathematical modeling with a method for feature selection, the L1 regularization. Utilizing an example model and simulated data, we demonstrated that this approach enables the accurate identification and quantification of cell type-specific parameters. We applied our strategy to quantitative time-resolved data of EPO-induced JAK/STAT signaling generated by quantitative immunoblotting, mass spectrometry and quantitative real-time PCR (qRT-PCR) in CFU-E and H838 cells as well as H838 cells overexpressing human EPOR (H838-HA-hEPOR). The established parsimonious mathematical model was able to simultaneously describe the data sets of CFU-E, H838 and H838-HA-hEPOR cells. Seven cell type-specific parameters were identified that included for example parameters for nuclear translocation of STAT5 and target gene induction. Cell type-specific differences in target gene induction were experimentally validated by qRT-PCR experiments. The systematic identification of pathway differences and sensitivities of EPOR signaling in CFU-E and H838 cells revealed potential targets for intervention to selectively inhibit EPO-induced signaling in the tumor cells but leave the responses in erythroid progenitor cells unaffected. Thus, the proposed modeling strategy can be employed as a general procedure to identify cell type-specific parameters and to recommend treatment strategies for the selective targeting of specific cell types.'),
(87964, 2016, 'plos', 'Flow-Based Network Analysis of the Caenorhabditis elegans Connectome', 'Bacik, Karol A|Schaub, Michael T|Beguerisse-Díaz, Mariano|Billeh, Yazan N|Barahona, Mauricio', 'Department of Mathematics, Imperial College London, London, United Kingdom.|Department of Mathematics, Imperial College London, London, United Kingdom.|Department of Mathematics, Imperial College London, London, United Kingdom.|Computation and Neural Systems Program, California Institute of Technology, Pasadena, California, United States of America.|Department of Mathematics, Imperial College London, London, United Kingdom.', 'United Kingdom|United Kingdom|United Kingdom|United States|United Kingdom', 14, 'Animals|Caenorhabditis elegans|Computational Biology|Connectome|Models, Neurological|Nerve Net', 'Journal Article', '10.1371/journal.pcbi.1005055', '27494178', 'We exploit flow propagation on the directed neuronal network of the nematode C. elegans to reveal dynamically relevant features of its connectome. We find flow-based groupings of neurons at different levels of granularity, which we relate to functional and anatomical constituents of its nervous system. A systematic in silico evaluation of the full set of single and double neuron ablations is used to identify deletions that induce the most severe disruptions of the multi-resolution flow structure. Such ablations are linked to functionally relevant neurons, and suggest potential candidates for further in vivo investigation. In addition, we use the directional patterns of incoming and outgoing network flows at all scales to identify flow profiles for the neurons in the connectome, without pre-imposing a priori categories. The four flow roles identified are linked to signal propagation motivated by biological input-response scenarios.'),
(87965, 2016, 'plos', 'Comparison of Detailed and Simplified Models of Human Atrial Myocytes to Recapitulate Patient Specific Properties', 'Lombardo, Daniel M|Fenton, Flavio H|Narayan, Sanjiv M|Rappel, Wouter-Jan', 'Department of Physics, University of California, San Diego, La Jolla, California, United States of America.|School of Physics, Georgia Tech University, Atlanta, Georgia, United States of America.|Department of Medicine, Stanford University, Palo Alto, California, United States of America.|Department of Physics, University of California, San Diego, La Jolla, California, United States of America.', 'United States|Georgia|United States|United States', 0, 'Aged|Atrial Fibrillation|Computer Simulation|Heart Atria|Humans|Middle Aged|Models, Cardiovascular|Myocytes, Cardiac|Precision Medicine', 'Journal Article', '10.1371/journal.pcbi.1005060', '27494252', 'Computer studies are often used to study mechanisms of cardiac arrhythmias, including atrial fibrillation (AF). A crucial component in these studies is the electrophysiological model that describes the membrane potential of myocytes. The models vary from detailed, describing numerous ion channels, to simplified, grouping ionic channels into a minimal set of variables. The parameters of these models, however, are determined across different experiments in varied species. Furthermore, a single set of parameters may not describe variations across patients, and models have rarely been shown to recapitulate critical features of AF in a given patient. In this study we develop physiologically accurate computational human atrial models by fitting parameters of a detailed and of a simplified model to clinical data for five patients undergoing ablation therapy. Parameters were simultaneously fitted to action potential (AP) morphology, action potential duration (APD) restitution and conduction velocity (CV) restitution curves in these patients. For both models, our fitting procedure generated parameter sets that accurately reproduced clinical data, but differed markedly from published sets and between patients, emphasizing the need for patient-specific adjustment. Both models produced two-dimensional spiral wave dynamics for that were similar for each patient. These results show that simplified, computationally efficient models are an attractive choice for simulations of human atrial electrophysiology in spatially extended domains. This study motivates the development and validation of patient-specific model-based mechanistic studies to target therapy.'),
(87966, 2016, 'plos', 'Modeling and Simulation of Mucus Flow in Human Bronchial Epithelial Cell Cultures - Part I: Idealized Axisymmetric Swirling Flow', 'Vasquez, Paula A|Jin, Yuan|Palmer, Erik|Hill, David|Forest, M Gregory', 'Department of Mathematics, University of South Carolina, Columbia, South Carolina, United States of America.|Department of Mathematics, University of North Carolina at Chapel Hill, Chapel Hill, North Carolina, United States of America.|Department of Mathematics, University of South Carolina, Columbia, South Carolina, United States of America.|Marsico Lung Institute & Cystic Fibrosis Pulmonary Research and Treatment Center, University of North Carolina at Chapel Hill, Chapel Hill, North Carolina, United States of America.|Department of Mathematics, University of North Carolina at Chapel Hill, Chapel Hill, North Carolina, United States of America.', 'United States|United States|United States|United States|United States', 0, 'Algorithms|Bronchi|Cells, Cultured|Cilia|Computational Biology|Computer Simulation|Elasticity|Epithelial Cells|Humans|Models, Biological|Mucus|Nonlinear Dynamics|Viscosity', 'Journal Article', '10.1371/journal.pcbi.1004872', '27494700', 'A multi-mode nonlinear constitutive model for mucus is constructed directly from micro- and macro-rheology experimental data on cell culture mucus, and a numerical algorithm is developed for the culture geometry and idealized cilia driving conditions. This study investigates the roles that mucus rheology, wall effects, and HBE culture geometry play in the development of flow profiles and the shape of the air-mucus interface. Simulations show that viscoelasticity captures normal stress generation in shear leading to a peak in the air-mucus interface at the middle of the culture and a depression at the walls. Linear and nonlinear viscoelastic regimes can be observed in cultures by varying the hurricane radius and mean rotational velocity. The advection-diffusion of a drug concentration dropped at the surface of the mucus flow is simulated as a function of Peclet number.'),
(87967, 2016, 'plos', 'The Complexity of Dynamics in Small Neural Circuits', 'Fasoli, Diego|Cattani, Anna|Panzeri, Stefano', 'Laboratory of Neural Computation, Center for Neuroscience and Cognitive Systems @UniTn, Istituto Italiano di Tecnologia, Rovereto, Italy.|Laboratory of Neural Computation, Center for Neuroscience and Cognitive Systems @UniTn, Istituto Italiano di Tecnologia, Rovereto, Italy.|Laboratory of Neural Computation, Center for Neuroscience and Cognitive Systems @UniTn, Istituto Italiano di Tecnologia, Rovereto, Italy.', 'Italy|Italy|Italy', 8, 'Action Potentials|Computational Biology|Models, Neurological|Nerve Net|Neurons', 'Journal Article', '10.1371/journal.pcbi.1004992', '27494737', 'Mean-field approximations are a powerful tool for studying large neural networks. However, they do not describe well the behavior of networks composed of a small number of neurons. In this case, major differences between the mean-field approximation and the real behavior of the network can arise. Yet, many interesting problems in neuroscience involve the study of mesoscopic networks composed of a few tens of neurons. Nonetheless, mathematical methods that correctly describe networks of small size are still rare, and this prevents us to make progress in understanding neural dynamics at these intermediate scales. Here we develop a novel systematic analysis of the dynamics of arbitrarily small networks composed of homogeneous populations of excitatory and inhibitory firing-rate neurons. We study the local bifurcations of their neural activity with an approach that is largely analytically tractable, and we numerically determine the global bifurcations. We find that for strong inhibition these networks give rise to very complex dynamics, caused by the formation of multiple branching solutions of the neural dynamics equations that emerge through spontaneous symmetry-breaking. This qualitative change of the neural dynamics is a finite-size effect of the network, that reveals qualitative and previously unexplored differences between mesoscopic cortical circuits and their mean-field approximation. The most important consequence of spontaneous symmetry-breaking is the ability of mesoscopic networks to regulate their degree of functional heterogeneity, which is thought to help reducing the detrimental effect of noise correlations on cortical information processing.');
INSERT INTO `papers` (`id`, `ano`, `journal`, `titulo`, `autores`, `afiliacao`, `pais`, `citacoes`, `palavra_chave`, `categorias`, `doi`, `pubmed`, `abstract`) VALUES
(87968, 2016, 'plos', 'Structure Prediction of RNA Loops with a Probabilistic Approach', 'Li, Jun|Zhang, Jian|Wang, Jun|Li, Wenfei|Wang, Wei', 'National Laboratory of Solid State Microstructures, School of Physics, Collaborative Innovation Center of Advanced Microstructures, Nanjing University, Nanjing, China.|National Laboratory of Solid State Microstructures, School of Physics, Collaborative Innovation Center of Advanced Microstructures, Nanjing University, Nanjing, China.|National Laboratory of Solid State Microstructures, School of Physics, Collaborative Innovation Center of Advanced Microstructures, Nanjing University, Nanjing, China.|National Laboratory of Solid State Microstructures, School of Physics, Collaborative Innovation Center of Advanced Microstructures, Nanjing University, Nanjing, China.|National Laboratory of Solid State Microstructures, School of Physics, Collaborative Innovation Center of Advanced Microstructures, Nanjing University, Nanjing, China.', 'China|China|China|China|China', 0, 'Computational Biology|Models, Molecular|Models, Statistical|Monte Carlo Method|Nucleic Acid Conformation|RNA', 'Journal Article', '10.1371/journal.pcbi.1005032', '27494763', 'The knowledge of the tertiary structure of RNA loops is important for understanding their functions. In this work we develop an efficient approach named RNApps, specifically designed for predicting the tertiary structure of RNA loops, including hairpin loops, internal loops, and multi-way junction loops. It includes a probabilistic coarse-grained RNA model, an all-atom statistical energy function, a sequential Monte Carlo growth algorithm, and a simulated annealing procedure. The approach is tested with a dataset including nine RNA loops, a 23S ribosomal RNA, and a large dataset containing 876 RNAs. The performance is evaluated and compared with a homology modeling based predictor and an ab initio predictor. It is found that RNApps has comparable performance with the former one and outdoes the latter in terms of structure predictions. The approach holds great promise for accurate and efficient RNA tertiary structure prediction.'),
(87969, 2016, 'plos', 'Modeling of Large-Scale Functional Brain Networks Based on Structural Connectivity from DTI: Comparison with EEG Derived Phase Coupling Networks and Evaluation of Alternative Methods along the Modeling Path', 'Finger, Holger|Bönstrup, Marlene|Cheng, Bastian|Messé, Arnaud|Hilgetag, Claus|Thomalla, Götz|Gerloff, Christian|König, Peter', 'Institute of Cognitive Science, University of Osnabrück, Osnabrück, Germany.|Department of Neurology, University Medical Center Hamburg-Eppendorf, Hamburg, Germany.|Department of Neurology, University Medical Center Hamburg-Eppendorf, Hamburg, Germany.|Department of Computational Neuroscience, University Medical Center Hamburg-Eppendorf, Hamburg, Germany.|Department of Computational Neuroscience, University Medical Center Hamburg-Eppendorf, Hamburg, Germany.|Department of Neurology, University Medical Center Hamburg-Eppendorf, Hamburg, Germany.|Department of Neurology, University Medical Center Hamburg-Eppendorf, Hamburg, Germany.|Institute of Cognitive Science, University of Osnabrück, Osnabrück, Germany.', 'Germany|Germany|Germany|Germany|Germany|Germany|Germany|Germany', 28, 'Algorithms|Computational Biology|Diffusion Tensor Imaging|Electroencephalography|Humans|Models, Neurological|Nerve Net', 'Journal Article', '10.1371/journal.pcbi.1005025', '27504629', 'In this study, we investigate if phase-locking of fast oscillatory activity relies on the anatomical skeleton and if simple computational models informed by structural connectivity can help further to explain missing links in the structure-function relationship. We use diffusion tensor imaging data and alpha band-limited EEG signal recorded in a group of healthy individuals. Our results show that about 23.4% of the variance in empirical networks of resting-state functional connectivity is explained by the underlying white matter architecture. Simulating functional connectivity using a simple computational model based on the structural connectivity can increase the match to 45.4%. In a second step, we use our modeling framework to explore several technical alternatives along the modeling path. First, we find that an augmentation of homotopic connections in the structural connectivity matrix improves the link to functional connectivity while a correction for fiber distance slightly decreases the performance of the model. Second, a more complex computational model based on Kuramoto oscillators leads to a slight improvement of the model fit. Third, we show that the comparison of modeled and empirical functional connectivity at source level is much more specific for the underlying structural connectivity. However, different source reconstruction algorithms gave comparable results. Of note, as the fourth finding, the model fit was much better if zero-phase lag components were preserved in the empirical functional connectome, indicating a considerable amount of functionally relevant synchrony taking place with near zero or zero-phase lag. The combination of the best performing alternatives at each stage in the pipeline results in a model that explains 54.4% of the variance in the empirical EEG functional connectivity. Our study shows that large-scale brain circuits of fast neural network synchrony strongly rely upon the structural connectome and simple computational models of neural activity can explain missing links in the structure-function relationship.'),
(87970, 2016, 'plos', 'The Impact of Cortical Lesions on Thalamo-Cortical Network Dynamics after Acute Ischaemic Stroke: A Combined Experimental and Theoretical Study', 'van Wijngaarden, Joeri B G|Zucca, Riccardo|Finnigan, Simon|Verschure, Paul F M J', 'Laboratory of Synthetic Perceptive, Emotive and Cognitive Systems (SPECS), Center for Autonomous Systems and Neuro-Robotics (N-RAS), Universitat Pompeu Fabra, Barcelona, Spain.|Laboratory of Synthetic Perceptive, Emotive and Cognitive Systems (SPECS), Center for Autonomous Systems and Neuro-Robotics (N-RAS), Universitat Pompeu Fabra, Barcelona, Spain.|UQ Centre for Clinical Research, The University of Queensland, Royal Brisbane and Womens Hospital, Brisbane, Australia.|Laboratory of Synthetic Perceptive, Emotive and Cognitive Systems (SPECS), Center for Autonomous Systems and Neuro-Robotics (N-RAS), Universitat Pompeu Fabra, Barcelona, Spain.', 'Spain|Spain|Australia|Spain', 9, 'Action Potentials|Adult|Aged|Aged, 80 and over|Calcium|Cerebral Cortex|Computational Biology|Electroencephalography|Female|Humans|Male|Middle Aged|Models, Neurological|Stroke|Thalamus', 'Journal Article', '10.1371/journal.pcbi.1005048', '27509209', 'The neocortex and thalamus provide a core substrate for perception, cognition, and action, and are interconnected through different direct and indirect pathways that maintain specific dynamics associated with functional states including wakefulness and sleep. It has been shown that a lack of excitation, or enhanced subcortical inhibition, can disrupt this system and drive thalamic nuclei into an attractor state of low-frequency bursting and further entrainment of thalamo-cortical circuits, also called thalamo-cortical dysrhythmia (TCD). The question remains however whether similar TCD-like phenomena can arise with a cortical origin. For instance, in stroke, a cortical lesion could disrupt thalamo-cortical interactions through an attenuation of the excitatory drive onto the thalamus, creating an imbalance between excitation and inhibition that can lead to a state of TCD. Here we tested this hypothesis by comparing the resting-state EEG recordings of acute ischaemic stroke patients (N = 21) with those of healthy, age-matched control-subjects (N = 17). We observed that these patients displayed the hallmarks of TCD: a characteristic downward shift of dominant xcexb1-peaks in the EEG power spectra, together with increased power over the lower frequencies (xcexb4 and xcexb8-range). Contrary to general observations in TCD, the patients also displayed a broad reduction in xcexb2-band activity. In order to explain the genesis of this stroke-induced TCD, we developed a biologically constrained model of a general thalamo-cortical module, allowing us to identify the specific cellular and network mechanisms involved. Our model showed that a lesion in the cortical component leads to sustained cell membrane hyperpolarization in the corresponding thalamic relay neurons, that in turn leads to the de-inactivation of voltage-gated T-type Ca2+-channels, switching neurons from tonic spiking to a pathological bursting regime. This thalamic bursting synchronises activity on a population level through divergent intrathalamic circuits, and entrains thalamo-cortical pathways by means of propagating low-frequency oscillations beyond the restricted region of the lesion. Hence, pathological stroke-induced thalamo-cortical dynamics can be the source of diaschisis, and account for the dissociation between lesion location and non-specific symptoms of stroke such as neuropathic pain and hemispatial neglect.'),
(87971, 2016, 'plos', 'Autonomous Optimization of Targeted Stimulation of Neuronal Networks', 'Kumar, Sreedhar S|Wülfing, Jan|Okujeni, Samora|Boedecker, Joschka|Riedmiller, Martin|Egert, Ulrich', 'Laboratory of Biomicrotechnology, IMTEK - Department of Microsystems Engineering, University of Freiburg, Freiburg, Germany.|Machine Learning Lab, Department of Computer Science, University of Freiburg, Freiburg, Germany.|Laboratory of Biomicrotechnology, IMTEK - Department of Microsystems Engineering, University of Freiburg, Freiburg, Germany.|Machine Learning Lab, Department of Computer Science, University of Freiburg, Freiburg, Germany.|Machine Learning Lab, Department of Computer Science, University of Freiburg, Freiburg, Germany.|Laboratory of Biomicrotechnology, IMTEK - Department of Microsystems Engineering, University of Freiburg, Freiburg, Germany.', 'Germany|Germany|Germany|Germany|Germany|Germany', 4, 'Animals|Brain|Computational Biology|Electric Stimulation|Machine Learning|Models, Neurological|Nerve Net|Rats', 'Journal Article', '10.1371/journal.pcbi.1005054', '27509295', 'Driven by clinical needs and progress in neurotechnology, targeted interaction with neuronal networks is of increasing importance. Yet, the dynamics of interaction between intrinsic ongoing activity in neuronal networks and their response to stimulation is unknown. Nonetheless, electrical stimulation of the brain is increasingly explored as a therapeutic strategy and as a means to artificially inject information into neural circuits. Strategies using regular or event-triggered fixed stimuli discount the influence of ongoing neuronal activity on the stimulation outcome and are therefore not optimal to induce specific responses reliably. Yet, without suitable mechanistic models, it is hardly possible to optimize such interactions, in particular when desired response features are network-dependent and are initially unknown. In this proof-of-principle study, we present an experimental paradigm using reinforcement-learning (RL) to optimize stimulus settings autonomously and evaluate the learned control strategy using phenomenological models. We asked how to (1) capture the interaction of ongoing network activity, electrical stimulation and evoked responses in a quantifiable state to formulate a well-posed control problem, (2) find the optimal state for stimulation, and (3) evaluate the quality of the solution found. Electrical stimulation of generic neuronal networks grown from rat cortical tissue in vitro evoked bursts of action potentials (responses). We show that the dynamic interplay of their magnitudes and the probability to be intercepted by spontaneous events defines a trade-off scenario with a network-specific unique optimal latency maximizing stimulus efficacy. An RL controller was set to find this optimum autonomously. Across networks, stimulation efficacy increased in 90% of the sessions after learning and learned latencies strongly agreed with those predicted from open-loop experiments. Our results show that autonomous techniques can exploit quantitative relationships underlying activity-response interaction in biological neuronal networks to choose optimal actions. Simple phenomenological models can be useful to validate the quality of the resulting controllers.'),
(87972, 2016, 'plos', 'Malaria Incidence Rates from Time Series of 2-Wave Panel Surveys', 'Castro, Marcia C|Maheu-Giroux, Mathieu|Chiyaka, Christinah|Singer, Burton H', 'Department of Global Health and Population, Harvard T. H. Chan School of Public Health, Boston, Massachusetts, United States of America.|Department of Infectious Disease Epidemiology, Imperial College London, London, United Kingdom.|Emerging Pathogens Institute, University of Florida, Gainesville, Florida, United States of America.|Emerging Pathogens Institute, University of Florida, Gainesville, Florida, United States of America.', 'United States|United Kingdom|United States|United States', 0, 'Computational Biology|Humans|Incidence|Longitudinal Studies|Malaria, Falciparum|Microscopy|Parasitology|Polymerase Chain Reaction|Tanzania', 'Journal Article', '10.1371/journal.pcbi.1005065', '27509368', 'Methodology to estimate malaria incidence rates from a commonly occurring form of interval-censored longitudinal parasitological data-specifically, 2-wave panel data-was first proposed 40 years ago based on the theory of continuous-time homogeneous Markov Chains. Assumptions of the methodology were suitable for settings with high malaria transmission in the absence of control measures, but are violated in areas experiencing fast decline or that have achieved very low transmission. No further developments that can accommodate such violations have been put forth since then. We extend previous work and propose a new methodology to estimate malaria incidence rates from 2-wave panel data, utilizing the class of 2-component mixtures of continuous-time Markov chains, representing two sub-populations with distinct behavior/attitude towards malaria prevention and treatment. Model identification, or even partial identification, requires context-specific a priori constraints on parameters. The method can be applied to scenarios of any transmission intensity. We provide an application utilizing data from Dar es Salaam, an area that experienced steady decline in malaria over almost five years after a larviciding intervention. We conducted sensitivity analysis to account for possible sampling variation in input data and model assumptions/parameters, and we considered differences in estimates due to submicroscopic infections. Results showed that, assuming defensible a priori constraints on model parameters, most of the uncertainty in the estimated incidence rates was due to sampling variation, not to partial identifiability of the mixture model for the case at hand. Differences between microscopy- and PCR-based rates depend on the transmission intensity. Leveraging on a method to estimate incidence rates from 2-wave panel data under any transmission intensity, and from the increasing availability of such data, there is an opportunity to foster further methodological developments, particularly focused on partial identifiability and the diversity of a priori parameter constraints associated with different human-ecosystem interfaces. As a consequence there can be more nuanced planning and evaluation of malaria control programs than heretofore.'),
(87973, 2016, 'plos', 'Evolutionary Games of Multiplayer Cooperation on Graphs', 'Peña, Jorge|Wu, Bin|Arranz, Jordi|Traulsen, Arne', 'Department of Evolutionary Theory, Max Planck Institute for Evolutionary Biology, Plön, Germany.|Department of Evolutionary Theory, Max Planck Institute for Evolutionary Biology, Plön, Germany.|Department of Evolutionary Theory, Max Planck Institute for Evolutionary Biology, Plön, Germany.|Department of Evolutionary Theory, Max Planck Institute for Evolutionary Biology, Plön, Germany.', 'Germany|Germany|Germany|Germany', 0, 'Biological Evolution|Computational Biology|Computer Simulation|Cooperative Behavior|Game Theory|Humans', 'Journal Article', '10.1371/journal.pcbi.1005059', '27513946', 'There has been much interest in studying evolutionary games in structured populations, often modeled as graphs. However, most analytical results so far have only been obtained for two-player or linear games, while the study of more complex multiplayer games has been usually tackled by computer simulations. Here we investigate evolutionary multiplayer games on graphs updated with a Moran death-Birth process. For cycles, we obtain an exact analytical condition for cooperation to be favored by natural selection, given in terms of the payoffs of the game and a set of structure coefficients. For regular graphs of degree three and larger, we estimate this condition using a combination of pair approximation and diffusion approximation. For a large class of cooperation games, our approximations suggest that graph-structured populations are stronger promoters of cooperation than populations lacking spatial structure. Computer simulations validate our analytical approximations for random regular graphs and cycles, but show systematic differences for graphs with many loops such as lattices. In particular, our simulation results show that these kinds of graphs can even lead to more stringent conditions for the evolution of cooperation than well-mixed populations. Overall, we provide evidence suggesting that the complexity arising from many-player interactions and spatial structure can be captured by pair approximation in the case of random graphs, but that it need to be handled with care for graphs with high clustering.'),
(87974, 2016, 'plos', 'Defining the Product Chemical Space of Monoterpenoid Synthases', 'Tian, Boxue|Poulter, C Dale|Jacobson, Matthew P', 'Department of Pharmaceutical Chemistry, School of Pharmacy, University of California, San Francisco, San Francisco, California, United States of America.|Department of Chemistry, University of Utah, Salt Lake City, Utah, United States of America.|Department of Pharmaceutical Chemistry, School of Pharmacy, University of California, San Francisco, San Francisco, California, United States of America.', 'United States|United States|United States', 11, 'Alkyl and Aryl Transferases|Chemistry, Pharmaceutical|Computational Biology|Models, Molecular|Molecular Conformation|Monoterpenes', 'Journal Article', '10.1371/journal.pcbi.1005053', '27517297', 'Terpenoid synthases create diverse carbon skeletons by catalyzing complex carbocation rearrangements, making them particularly challenging for enzyme function prediction. To begin to address this challenge, we have developed a computational approach for the systematic enumeration of terpenoid carbocations. Application of this approach allows us to systematically define a nearly complete chemical space for the potential carbon skeletons of products from monoterpenoid synthases. Specifically, 18758 carbocations were generated, which we cluster into 74 cyclic skeletons. Five of the 74 skeletons are found in known natural products, some of the others are plausible for new functions, either in nature or engineered. This work systematizes the description of function for this class of enzymes, and provides a basis for predicting functions of uncharacterized enzymes. To our knowledge, this is the first computational study to explore the complete product chemical space of this important class of enzymes.'),
(87975, 2016, 'plos', 'Shaping Neural Circuits by High Order Synaptic Interactions', 'Ravid Tannenbaum, Neta|Burak, Yoram', 'Edmond and Lily Safra Center for Brain Sciences, Hebrew University, Jerusalem, Israel.|Edmond and Lily Safra Center for Brain Sciences, Hebrew University, Jerusalem, Israel.', 'Israel|Israel', 16, 'Biophysical Phenomena|Computational Biology|Learning|Models, Neurological|Nerve Net|Neuronal Plasticity|Neurons|Synapses', 'Journal Article', '10.1371/journal.pcbi.1005056', '27517461', 'Spike timing dependent plasticity (STDP) is believed to play an important role in shaping the structure of neural circuits. Here we show that STDP generates effective interactions between synapses of different neurons, which were neglected in previous theoretical treatments, and can be described as a sum over contributions from structural motifs. These interactions can have a pivotal influence on the connectivity patterns that emerge under the influence of STDP. In particular, we consider two highly ordered forms of structure: wide synfire chains, in which groups of neurons project to each other sequentially, and self connected assemblies. We show that high order synaptic interactions can enable the formation of both structures, depending on the form of the STDP function and the time course of synaptic currents. Furthermore, within a certain regime of biophysical parameters, emergence of the ordered connectivity occurs robustly and autonomously in a stochastic network of spiking neurons, without a need to expose the neural network to structured inputs during learning.'),
(87976, 2016, 'plos', 'A Mechanistic Model for Cooperative Behavior of Co-transcribing RNA Polymerases', 'Heberling, Tamra|Davis, Lisa|Gedeon, Jakub|Morgan, Charles|Gedeon, Tomáš', 'Los Alamos National Laboratory, Los Alamos, New Mexico, United States of America.|Department of Mathematical Sciences, Montana State University, Bozeman, Montana, United States of America.|Computer Science Department, Montana State University, Bozeman, Montana, United States of America.|Department of Mathematical Sciences, Montana State University, Bozeman, Montana, United States of America.|Department of Mathematical Sciences, Montana State University, Bozeman, Montana, United States of America.', 'Mexico|United States|United States|United States|United States', 0, 'Algorithms|Computational Biology|Computer Simulation|DNA, Bacterial|DNA-Directed RNA Polymerases|Escherichia coli|Models, Theoretical|Stochastic Processes|Torque|Transcription, Genetic', 'Journal Article', '10.1371/journal.pcbi.1005069', '27517607', 'In fast-transcribing prokaryotic genes, such as an rrn gene in Escherichia coli, many RNA polymerases (RNAPs) transcribe the DNA simultaneously. Active elongation of RNAPs is often interrupted by pauses, which has been observed to cause RNAP traffic jams, yet some studies indicate that elongation seems to be faster in the presence of multiple RNAPs than elongation by a single RNAP. We propose that an interaction between RNAPs via the torque produced by RNAP motion on helically twisted DNA can explain this apparent paradox. We have incorporated the torque mechanism into a stochastic model and simulated transcription both with and without torque. Simulation results illustrate that the torque causes shorter pause durations and fewer collisions between polymerases. Our results suggest that the torsional interaction of RNAPs is an important mechanism in maintaining fast transcription times, and that transcription should be viewed as a cooperative group effort by multiple polymerases.'),
(87977, 2016, 'plos', 'Inference of Ancestral Recombination Graphs through Topological Data Analysis', 'Cámara, Pablo G|Levine, Arnold J|Rabadán, Raúl', 'Department of Systems Biology and Department of Biomedical Informatics, Columbia University College of Physicians and Surgeons, New York, New York, United States of America.|The Simons Center for Systems Biology, Institute for Advanced Study, Princeton, New Jersey, United States of America.|Department of Systems Biology and Department of Biomedical Informatics, Columbia University College of Physicians and Surgeons, New York, New York, United States of America.', 'United States|Jersey|United States', 18, 'Animals|Computational Biology|Evolution, Molecular|Finches|Gene Transfer, Horizontal|Humans|Models, Genetic|Phylogeny|Recombination, Genetic|Software', 'Journal Article', '10.1371/journal.pcbi.1005071', '27532298', 'The recent explosion of genomic data has underscored the need for interpretable and comprehensive analyses that can capture complex phylogenetic relationships within and across species. Recombination, reassortment and horizontal gene transfer constitute examples of pervasive biological phenomena that cannot be captured by tree-like representations. Starting from hundreds of genomes, we are interested in the reconstruction of potential evolutionary histories leading to the observed data. Ancestral recombination graphs represent potential histories that explicitly accommodate recombination and mutation events across orthologous genomes. However, they are computationally costly to reconstruct, usually being infeasible for more than few tens of genomes. Recently, Topological Data Analysis (TDA) methods have been proposed as robust and scalable methods that can capture the genetic scale and frequency of recombination. We build upon previous TDA developments for detecting and quantifying recombination, and present a novel framework that can be applied to hundreds of genomes and can be interpreted in terms of minimal histories of mutation and recombination events, quantifying the scales and identifying the genomic locations of recombinations. We implement this framework in a software package, called TARGet, and apply it to several examples, including small migration between different populations, human recombination, and horizontal evolution in finches inhabiting the Galápagos Islands.'),
(87978, 2016, 'plos', 'Intercellular Variability in Protein Levels from Stochastic Expression and Noisy Cell Cycle Processes', 'Soltani, Mohammad|Vargas-Garcia, Cesar A|Antunes, Duarte|Singh, Abhyudai', 'Electrical and Computer Engineering Department, University of Delaware, Newark, Delaware, United States of America.|Electrical and Computer Engineering Department, University of Delaware, Newark, Delaware, United States of America.|Mechanical Engineering Department, Eindhoven University of Technology, Eindhoven, Netherlands.|Electrical and Computer Engineering Department, University of Delaware, Newark, Delaware, United States of America.', 'United States|United States|Netherlands|United States', 0, 'Cell Cycle|Cell Division|Computational Biology|Gene Expression Regulation|Models, Biological|Protein Biosynthesis|Proteins|Stochastic Processes', 'Journal Article', '10.1371/journal.pcbi.1004972', '27536771', 'Inside individual cells, expression of genes is inherently stochastic and manifests as cell-to-cell variability or noise in protein copy numbers. Since proteins half-lives can be comparable to the cell-cycle length, randomness in cell-division times generates additional intercellular variability in protein levels. Moreover, as many mRNA/protein species are expressed at low-copy numbers, errors incurred in partitioning of molecules between two daughter cells are significant. We derive analytical formulas for the total noise in protein levels when the cell-cycle duration follows a general class of probability distributions. Using a novel hybrid approach the total noise is decomposed into components arising from i) stochastic expression, ii) partitioning errors at the time of cell division and iii) random cell-division events. These formulas reveal that random cell-division times not only generate additional extrinsic noise, but also critically affect the mean protein copy numbers and intrinsic noise components. Counter intuitively, in some parameter regimes, noise in protein levels can decrease as cell-division times become more stochastic. Computations are extended to consider genome duplication, where transcription rate is increased at a random point in the cell cycle. We systematically investigate how the timing of genome duplication influences different protein noise components. Intriguingly, results show that noise contribution from stochastic expression is minimized at an optimal genome-duplication time. Our theoretical results motivate new experimental methods for decomposing protein noise levels from synchronized and asynchronized single-cell expression data. Characterizing the contributions of individual noise mechanisms will lead to precise estimates of gene expression parameters and techniques for altering stochasticity to change phenotype of individual cells.'),
(87979, 2016, 'plos', 'Genome Landscapes of Disease: Strategies to Predict the Phenotypic Consequences of Human Germline and Somatic Variation', 'Karchin, Rachel|Nussinov, Ruth', 'Department of Biomedical Engineering and Institute for Computational Medicine, Department of Oncology, Cancer Biology Program, Johns Hopkins Institutions, Baltimore, Maryland, United States of America.|Cancer and Inflammation Program, Leidos Biomedical Research, Inc., Frederick National Laboratory for Cancer Research, National Cancer Institute, Frederick, Maryland, United States of America.', 'United States|United States', 0, 'Computational Biology|DNA Copy Number Variations|Disease|Germ Cells|Humans|Phenotype|Polymorphism, Single Nucleotide', 'Editorial', '10.1371/journal.pcbi.1005043', '27536867', '-'),
(87980, 2016, 'plos', 'Predicted Molecular Effects of Sequence Variants Link to System Level of Disease', 'Reeb, Jonas|Hecht, Maximilian|Mahlich, Yannick|Bromberg, Yana|Rost, Burkhard', 'Department of Informatics, Bioinformatics & Computational Biology-i12, Technische Universität München, Garching/Munich, Germany.|Department of Informatics, Bioinformatics & Computational Biology-i12, Technische Universität München, Garching/Munich, Germany.|Department of Informatics, Bioinformatics & Computational Biology-i12, Technische Universität München, Garching/Munich, Germany.|Department of Biochemistry and Microbiology, Rutgers University, New Brunswick, New Jersey, United States of America.|Department of Informatics, Bioinformatics & Computational Biology-i12, Technische Universität München, Garching/Munich, Germany.', 'Germany|Germany|Germany|Jersey|Germany', 0, 'Animals|Computational Biology|Databases, Protein|Disease Models, Animal|Genetic Predisposition to Disease|Humans|Mice|Polymorphism, Single Nucleotide|Proteins', 'Journal Article', '10.1371/journal.pcbi.1005047', '27536940', 'Developments in experimental and computational biology are advancing our understanding of how protein sequence variation impacts molecular protein function. However, the leap from the micro level of molecular function to the macro level of the whole organism, e.g. disease, remains barred. Here, we present new results emphasizing earlier work that suggested some links from molecular function to disease. We focused on non-synonymous single nucleotide variants, also referred to as single amino acid variants (SAVs). Building upon OMIA (Online Mendelian Inheritance in Animals), we introduced a curated set of 117 disease-causing SAVs in animals. Methods optimized to capture effects upon molecular function often correctly predict human (OMIM) and animal (OMIA) Mendelian disease-causing variants. We also predicted effects of human disease-causing variants in the mouse model, i.e. we put OMIM SAVs into mouse orthologs. Overall, fewer variants were predicted with effect in the model organism than in the original organism. Our results, along with other recent studies, demonstrate that predictions of molecular effects capture some important aspects of disease. Thus, in silico methods focusing on the micro level of molecular function can help to understand the macro system level of disease.'),
(87981, 2016, 'plos', 'metagene Profiles Analyses Reveal Regulatory Elements Factor-Specific Recruitment Patterns', 'Joly Beauparlant, Charles|Lamaze, Fabien C|Deschênes, Astrid|Samb, Rawane|Lemaçon, Audrey|Belleau, Pascal|Bilodeau, Steve|Droit, Arnaud', 'Centre de Recherche du CHU de Québec - Université Laval, Québec, Québec, Canada.|Centre de Recherche du CHU de Québec - Université Laval, Québec, Québec, Canada.|Centre de Recherche du CHU de Québec - Université Laval, Québec, Québec, Canada.|Centre de Recherche du CHU de Québec - Université Laval, Québec, Québec, Canada.|Centre de Recherche du CHU de Québec - Université Laval, Québec, Québec, Canada.|Centre de Recherche du CHU de Québec - Université Laval, Québec, Québec, Canada.|Centre de Recherche du CHU de Québec - Université Laval, Québec, Québec, Canada.|Centre de Recherche du CHU de Québec - Université Laval, Québec, Québec, Canada.', 'Canada|Canada|Canada|Canada|Canada|Canada|Canada|Canada', 0, 'Algorithms|B-Lymphocytes|Cell Line|Chromatin Immunoprecipitation|Gene Expression Profiling|High-Throughput Nucleotide Sequencing|Humans|Metagenomics|Regulatory Sequences, Nucleic Acid|Software|Transcription, Genetic', 'Journal Article', '10.1371/journal.pcbi.1004751', '27538250', 'ChIP-Sequencing (ChIP-Seq) provides a vast amount of information regarding the localization of proteins across the genome. The aggregation of ChIP-Seq enrichment signal in a metagene plot is an approach commonly used to summarize data complexity and to obtain a high level visual representation of the general occupancy pattern of a protein. Here we present the R package metagene, the graphical interface Imetagene and the companion package similaRpeak. Together, they provide a framework to integrate, summarize and compare the ChIP-Seq enrichment signal from complex experimental designs. Those packages identify and quantify similarities or dissimilarities in patterns between large numbers of ChIP-Seq profiles. We used metagene to investigate the differential occupancy of regulatory factors at noncoding regulatory regions (promoters and enhancers) in relation to transcriptional activity in GM12878 B-lymphocytes. The relationships between occupancy patterns and transcriptional activity suggest two different mechanisms of action for transcriptional control: i) a gradient effect where the regulatory factor occupancy levels follow transcription and ii) a threshold effect where the regulatory factor occupancy levels max out prior to reaching maximal transcription. metagene, Imetagene and similaRpeak are implemented in R under the Artistic license 2.0 and are available on Bioconductor.'),
(87982, 2016, 'plos', 'Vulnerability-Based Critical Neurons, Synapses, and Pathways in the Caenorhabditis elegans Connectome', 'Kim, Seongkyun|Kim, Hyoungkyu|Kralik, Jerald D|Jeong, Jaeseung', 'Department of Bio and Brain Engineering, Korea Advanced Institute of Science and Technology (KAIST), Daejeon, Republic of Korea.|Department of Bio and Brain Engineering, Korea Advanced Institute of Science and Technology (KAIST), Daejeon, Republic of Korea.|Department of Bio and Brain Engineering, Korea Advanced Institute of Science and Technology (KAIST), Daejeon, Republic of Korea.|Department of Bio and Brain Engineering, Korea Advanced Institute of Science and Technology (KAIST), Daejeon, Republic of Korea.', '-|-|-|-', 0, 'Animals|Caenorhabditis elegans|Computational Biology|Connectome|Models, Neurological|Nerve Net|Neurons|Synapses', 'Journal Article', '10.1371/journal.pcbi.1005084', '27540747', 'Determining the fundamental architectural design of complex nervous systems will lead to significant medical and technological advances. Yet it remains unclear how nervous systems evolved highly efficient networks with near optimal sharing of pathways that yet produce multiple distinct behaviors to reach the organisms goals. To determine this, the nematode roundworm Caenorhabditis elegans is an attractive model system. Progress has been made in delineating the behavioral circuits of the C. elegans, however, many details are unclear, including the specific functions of every neuron and synapse, as well as the extent the behavioral circuits are separate and parallel versus integrative and serial. Network analysis provides a normative approach to help specify the network design. We investigated the vulnerability of the Caenorhabditis elegans connectome by performing computational experiments that (a) attacked 279 individual neurons and 2,990 weighted synaptic connections (composed of 6,393 chemical synapses and 890 electrical junctions) and (b) quantified the effects of each removal on global network properties that influence information processing. The analysis identified 12 critical neurons and 29 critical synapses for establishing fundamental network properties. These critical constituents were found to be control elements-i.e., those with the most influence over multiple underlying pathways. Additionally, the critical synapses formed into circuit-level pathways. These emergent pathways provide evidence for (a) the importance of backward locomotion, avoidance behavior, and social feeding behavior to the organism, (b) the potential roles of specific neurons whose functions have been unclear, and'),
(87983, 2016, 'plos', 'Cortico-Cortical Interactions during Acquisition and Use of a Neuroprosthetic Skill', 'Wander, Jeremiah D|Sarma, Devapratim|Johnson, Lise A|Fetz, Eberhard E|Rao, Rajesh P N|Ojemann, Jeffrey G|Darvas, Felix', 'Department of Bioengineering, University of Washington, Seattle, Washington, United States of America.|Department of Bioengineering, University of Washington, Seattle, Washington, United States of America.|Department of Neurological Surgery, University of Washington, Seattle, Washington, United States of America.|Department of Physiology and Biophysics, University of Washington, Seattle, Washington, United States of America.|Department of Computer Science and Engineering, University of Washington, Seattle, Washington, United States of America.|Department of Neurological Surgery, University of Washington, Seattle, Washington, United States of America.|Department of Neurological Surgery, University of Washington, Seattle, Washington, United States of America.', 'United States|United States|United States|United States|United States|United States|United States', 0, 'Adolescent|Adult|Brain-Computer Interfaces|Child|Computational Biology|Electrocorticography|Female|Humans|Learning|Male|Middle Aged|Models, Neurological|Motor Cortex|Nerve Net|Task Performance and Analysis|Young Adult', 'Journal Article', '10.1371/journal.pcbi.1004931', '27541829', 'A motor cortex-based brain-computer interface (BCI) creates a novel real world output directly from cortical activity. Use of a BCI has been demonstrated to be a learned skill that involves recruitment of neural populations that are directly linked to BCI control as well as those that are not. The nature of interactions between these populations, however, remains largely unknown. Here, we employed a data-driven approach to assess the interaction between both local and remote cortical areas during the use of an electrocorticographic BCI, a method which allows direct sampling of cortical surface potentials. Comparing the area controlling the BCI with remote areas, we evaluated relationships between the amplitude envelopes of band limited powers as well as non-linear phase-phase interactions. We found amplitude-amplitude interactions in the high gamma (HG, 70-150 Hz) range that were primarily located in the posterior portion of the frontal lobe, near the controlling site, and non-linear phase-phase interactions involving multiple frequencies (cross-frequency coupling between 8-11 Hz and 70-90 Hz) taking place over larger cortical distances. Further, strength of the amplitude-amplitude interactions decreased with time, whereas the phase-phase interactions did not. These findings suggest multiple modes of cortical communication taking place during BCI use that are specialized for function and depend on interaction distance.'),
(87984, 2016, 'plos', 'Inverse Stochastic Resonance in Cerebellar Purkinje Cells', 'Buchin, Anatoly|Rieubland, Sarah|Häusser, Michael|Gutkin, Boris S|Roth, Arnd', 'Group for Neural Theory, Laboratoire des Neurosciences Cognitives, École Normale Supérieure, Paris, France.|Wolfson Institute for Biomedical Research and Department of Neuroscience, Physiology and Pharmacology, University College London, London, United Kingdom.|Wolfson Institute for Biomedical Research and Department of Neuroscience, Physiology and Pharmacology, University College London, London, United Kingdom.|Group for Neural Theory, Laboratoire des Neurosciences Cognitives, École Normale Supérieure, Paris, France.|Wolfson Institute for Biomedical Research and Department of Neuroscience, Physiology and Pharmacology, University College London, London, United Kingdom.', 'France|United Kingdom|United Kingdom|France|United Kingdom', 0, 'Action Potentials|Animals|Computational Biology|Models, Neurological|Purkinje Cells|Rats|Rats, Sprague-Dawley|Stochastic Processes', 'Journal Article', '10.1371/journal.pcbi.1005000', '27541958', 'Purkinje neurons play an important role in cerebellar computation since their axons are the only projection from the cerebellar cortex to deeper cerebellar structures. They have complex internal dynamics, which allow them to fire spontaneously, display bistability, and also to be involved in network phenomena such as high frequency oscillations and travelling waves. Purkinje cells exhibit type II excitability, which can be revealed by a discontinuity in their f-I curves. We show that this excitability mechanism allows Purkinje cells to be efficiently inhibited by noise of a particular variance, a phenomenon known as inverse stochastic resonance (ISR). While ISR has been described in theoretical models of single neurons, here we provide the first experimental evidence for this effect. We find that an adaptive exponential integrate-and-fire model fitted to the basic Purkinje cell characteristics using a modified dynamic IV method displays ISR and bistability between the resting state and a repetitive activity limit cycle. ISR allows the Purkinje cell to operate in different functional regimes: the all-or-none toggle or the linear filter mode, depending on the variance of the synaptic input. We propose that synaptic noise allows Purkinje cells to quickly switch between these functional regimes. Using mutual information analysis, we demonstrate that ISR can lead to a locally optimal information transfer between the input and output spike train of the Purkinje cell. These results provide the first experimental evidence for ISR and suggest a functional role for ISR in cerebellar information processing.'),
(87985, 2016, 'plos', 'Higher-Order Synaptic Interactions Coordinate Dynamics in Recurrent Networks', 'Chambers, Brendan|MacLean, Jason N', 'Committee on Computational Neuroscience, University of Chicago, Chicago, Illinois, United States of America.|Committee on Computational Neuroscience, University of Chicago, Chicago, Illinois, United States of America.', 'United States|United States', 7, 'Action Potentials|Algorithms|Animals|Computational Biology|Mice|Models, Neurological|Neocortex|Nerve Net|Neurons|Poisson Distribution|Synapses', 'Journal Article', '10.1371/journal.pcbi.1005078', '27542093', 'Linking synaptic connectivity to dynamics is key to understanding information processing in neocortex. Circuit dynamics emerge from complex interactions of interconnected neurons, necessitating that links between connectivity and dynamics be evaluated at the network level. Here we map propagating activity in large neuronal ensembles from mouse neocortex and compare it to a recurrent network model, where connectivity can be precisely measured and manipulated. We find that a dynamical feature dominates statistical descriptions of propagating activity for both neocortex and the model: convergent clusters comprised of fan-in triangle motifs, where two input neurons are themselves connected. Fan-in triangles coordinate the timing of presynaptic inputs during ongoing activity to effectively generate postsynaptic spiking. As a result, paradoxically, fan-in triangles dominate the statistics of spike propagation even in randomly connected recurrent networks. Interplay between higher-order synaptic connectivity and the integrative properties of neurons constrains the structure of network dynamics and shapes the routing of information in neocortex.'),
(87986, 2016, 'plos', 'A Robust Actin Filaments Image Analysis Framework', 'Alioscha-Perez, Mitchel|Benadiba, Carine|Goossens, Katty|Kasas, Sandor|Dietler, Giovanni|Willaert, Ronnie|Sahli, Hichem', 'Electronics and Informatics Dept (ETRO), AVSP Lab, Vrije Universiteit Brussel, Brussels, Belgium.|VUB-EPFL International Joint Research Group (IJRG) NanoBiotechnology and NanoMedicine (NANO), Brussels, Belgium.|VUB-EPFL International Joint Research Group (IJRG) NanoBiotechnology and NanoMedicine (NANO), Brussels, Belgium.|VUB-EPFL International Joint Research Group (IJRG) NanoBiotechnology and NanoMedicine (NANO), Brussels, Belgium.|VUB-EPFL International Joint Research Group (IJRG) NanoBiotechnology and NanoMedicine (NANO), Brussels, Belgium.|VUB-EPFL International Joint Research Group (IJRG) NanoBiotechnology and NanoMedicine (NANO), Brussels, Belgium.|Electronics and Informatics Dept (ETRO), AVSP Lab, Vrije Universiteit Brussel, Brussels, Belgium.', 'Belgium|Belgium|Belgium|Belgium|Belgium|Belgium|Belgium', 10, 'Actins|Algorithms|Animals|Cell Line|Cytoskeleton|Image Processing, Computer-Assisted|Mice|Microscopy, Fluorescence|Stress, Mechanical', 'Journal Article', '10.1371/journal.pcbi.1005063', '27551746', 'The cytoskeleton is a highly dynamical protein network that plays a central role in numerous cellular physiological processes, and is traditionally divided into three components according to its chemical composition, i.e. actin, tubulin and intermediate filament cytoskeletons. Understanding the cytoskeleton dynamics is of prime importance to unveil mechanisms involved in cell adaptation to any stress type. Fluorescence imaging of cytoskeleton structures allows analyzing the impact of mechanical stimulation in the cytoskeleton, but it also imposes additional challenges in the image processing stage, such as the presence of imaging-related artifacts and heavy blurring introduced by (high-throughput) automated scans. However, although there exists a considerable number of image-based analytical tools to address the image processing and analysis, most of them are unfit to cope with the aforementioned challenges. Filamentous structures in images can be considered as a piecewise composition of quasi-straight segments (at least in some finer or coarser scale). Based on this observation, we propose a three-steps actin filaments extraction methodology: (i) first the input image is decomposed into a cartoon part corresponding to the filament structures in the image, and a noise/texture part, (ii) on the cartoon image, we apply a multi-scale line detector coupled with a (iii) quasi-straight filaments merging algorithm for fiber extraction. The proposed robust actin filaments image analysis framework allows extracting individual filaments in the presence of noise, artifacts and heavy blurring. Moreover, it provides numerous parameters such as filaments orientation, position and length, useful for further analysis. Cell image decomposition is relatively under-exploited in biological images processing, and our study shows the benefits it provides when addressing such tasks. Experimental validation was conducted using publicly available datasets, and in osteoblasts grown in two different conditions: static (control) and fluid shear stress. The proposed methodology exhibited higher sensitivity values and similar accuracy compared to state-of-the-art methods.');
INSERT INTO `papers` (`id`, `ano`, `journal`, `titulo`, `autores`, `afiliacao`, `pais`, `citacoes`, `palavra_chave`, `categorias`, `doi`, `pubmed`, `abstract`) VALUES
(87987, 2016, 'plos', 'Determining Physical Mechanisms of Gene Expression Regulation from Single Cell Gene Expression Data', 'Ezer, Daphne|Moignard, Victoria|Göttgens, Berthold|Adryan, Boris', 'Department of Genetics, Systems Biology Centre, University of Cambridge, Cambridge, United Kingdom.|Department of Haematology, Wellcome Trust and MRC Cambridge Stem Cell Institute and Cambridge Institute for Medical Research, University of Cambridge, Cambridge, United Kingdom.|Department of Haematology, Wellcome Trust and MRC Cambridge Stem Cell Institute and Cambridge Institute for Medical Research, University of Cambridge, Cambridge, United Kingdom.|Department of Genetics, Systems Biology Centre, University of Cambridge, Cambridge, United Kingdom.', 'United Kingdom|United Kingdom|United Kingdom|United Kingdom', 0, 'Algorithms|Animals|Cell Line|Computational Biology|Computer Simulation|Gene Expression Profiling|Gene Expression Regulation|Hematopoiesis|Humans|Kinetics|Mice|Single-Cell Analysis|Transcription Factors', 'Journal Article', '10.1371/journal.pcbi.1005072', '27551778', 'Many genes are expressed in bursts, which can contribute to cell-to-cell heterogeneity. It is now possible to measure this heterogeneity with high throughput single cell gene expression assays (single cell qPCR and RNA-seq). These experimental approaches generate gene expression distributions which can be used to estimate the kinetic parameters of gene expression bursting, namely the rate that genes turn on, the rate that genes turn off, and the rate of transcription. We construct a complete pipeline for the analysis of single cell qPCR data that uses the mathematics behind bursty expression to develop more accurate and robust algorithms for analyzing the origin of heterogeneity in experimental samples, specifically an algorithm for clustering cells by their bursting behavior (Simulated Annealing for Bursty Expression Clustering, SABEC) and a statistical tool for comparing the kinetic parameters of bursty expression across populations of cells (Estimation of Parameter changes in Kinetics, EPiK). We applied these methods to hematopoiesis, including a new single cell dataset in which transcription factors (TFs) involved in the earliest branchpoint of blood differentiation were individually up- and down-regulated. We could identify two unique sub-populations within a seemingly homogenous group of hematopoietic stem cells. In addition, we could predict regulatory mechanisms controlling the expression levels of eighteen key hematopoietic transcription factors throughout differentiation. Detailed information about gene regulatory mechanisms can therefore be obtained simply from high throughput single cell gene expression data, which should be widely applicable given the rapid expansion of single cell genomics.'),
(87988, 2016, 'plos', 'Conflict Resolution as Near-Threshold Decision-Making: A Spiking Neural Circuit Model with Two-Stage Competition for Antisaccadic Task', 'Lo, Chung-Chuan|Wang, Xiao-Jing', 'Institute of Systems Neuroscience, National Tsing Hua University, Hsinchu, Taiwan.|Center for Neural Science, New York University, New York, New York, United States of America.', '-|United States', 10, 'Computational Biology|Decision Making|Humans|Models, Neurological|Nerve Net|Neurons|Reaction Time|Saccades', 'Journal Article', '10.1371/journal.pcbi.1005081', '27551824', 'Automatic responses enable us to react quickly and effortlessly, but they often need to be inhibited so that an alternative, voluntary action can take place. To investigate the brain mechanism of controlled behavior, we investigated a biologically-based network model of spiking neurons for inhibitory control. In contrast to a simple race between pro- versus anti-response, our model incorporates a sensorimotor remapping module, and an action-selection module endowed with a Stop process through tonic inhibition. Both are under the modulation of rule-dependent control. We tested the model by applying it to the well known antisaccade task in which one must suppress the urge to look toward a visual target that suddenly appears, and shift the gaze diametrically away from the target instead. We found that the two-stage competition is crucial for reproducing the complex behavior and neuronal activity observed in the antisaccade task across multiple brain regions. Notably, our model demonstrates two types of errors: fast and slow. Fast errors result from failing to inhibit the quick automatic responses and therefore exhibit very short response times. Slow errors, in contrast, are due to incorrect decisions in the remapping process and exhibit long response times comparable to those of correct antisaccade responses. The model thus reveals a circuit mechanism for the empirically observed slow errors and broad distributions of erroneous response times in antisaccade. Our work suggests that selecting between competing automatic and voluntary actions in behavioral control can be understood in terms of near-threshold decision-making, sharing a common recurrent (attractor) neural circuit mechanism with discrimination in perception.'),
(87989, 2016, 'plos', 'Characterization of Promiscuous Binding of Phosphor Ligands to Breast-Cancer-Gene 1 (BRCA1) C-Terminal (BRCT): Molecular Dynamics, Free Energy, Entropy and Inhibitor Design', 'You, Wanli|Huang, Yu-Ming M|Kizhake, Smitha|Natarajan, Amarnath|Chang, Chia-En A', 'Department of Chemistry, University of California, Riverside, Riverside, California, United States of America.|Department of Chemistry, University of California, Riverside, Riverside, California, United States of America.|Eppley Institute for Research in Cancer and Allied Diseases, University of Nebraska Medical Center, Omaha, Nebraska, United States of America.|Eppley Institute for Research in Cancer and Allied Diseases, University of Nebraska Medical Center, Omaha, Nebraska, United States of America.|Department of Chemistry, University of California, Riverside, Riverside, California, United States of America.', 'United States|United States|United States|United States|United States', 0, 'Antineoplastic Agents|BRCA1 Protein|Entropy|Humans|Ligands|Molecular Dynamics Simulation|Phosphopeptides|Protein Binding|Thermodynamics', 'Journal Article', '10.1371/journal.pcbi.1005057', '27560145', 'Inhibition of the protein-protein interaction (PPI) mediated by breast-cancer-gene 1 C-terminal (BRCT) is an attractive strategy to sensitize breast and ovarian cancers to chemotherapeutic agents that induce DNA damage. Such inhibitors could also be used for studies to understand the role of this PPI in DNA damage response. However, design of BRCT inhibitors is challenging because of the inherent flexibility associated with this domain. Several studies identified short phosphopeptides as tight BRCT binders. Here we investigated the thermodynamic properties of 18 phosphopeptides or peptide with phosphate mimic and three compounds with phosphate groups binding to BRCT to understand promiscuous molecular recognition and guide inhibitor design. We performed molecular dynamics (MD) simulations to investigate the interactions between inhibitors and BRCT and their dynamic behavior in the free and bound states. MD simulations revealed the key role of loops in altering the shape and size of the binding site to fit various ligands. The mining minima (M2) method was used for calculating binding free energy to explore the driving forces and the fine balance between configuration entropy loss and enthalpy gain. We designed a rigidified ligand, which showed unfavorable experimental binding affinity due to weakened enthalpy. This was because it lacked the ability to rearrange itself upon binding. Investigation of another phosphate group containing compound, C1, suggested that the entropy loss can be reduced by preventing significant narrowing of the energy well and introducing multiple new compound conformations in the bound states. From our computations, we designed an analog of C1 that introduced new intermolecular interactions to strengthen attractions while maintaining small entropic penalty. This study shows that flexible compounds do not always encounter larger entropy penalty, compared with other more rigid binders, and highlights a new strategy for inhibitor design.'),
(87990, 2016, 'plos', 'Leveraging Hypoxia-Activated Prodrugs to Prevent Drug Resistance in Solid Tumors', 'Lindsay, Danika|Garvey, Colleen M|Mumenthaler, Shannon M|Foo, Jasmine', 'School of Mathematics, University of Minnesota, Minneapolis, Minnesota, United States of America.|Lawrence J. Ellison Institute for Transformative Medicine, University of Southern California, Los Angeles, California, United States of America.|Lawrence J. Ellison Institute for Transformative Medicine, University of Southern California, Los Angeles, California, United States of America.|School of Mathematics, University of Minnesota, Minneapolis, Minnesota, United States of America.', 'United States|United States|United States|United States', 7, 'Antineoplastic Agents|Carcinoma, Non-Small-Cell Lung|Cell Line, Tumor|Computational Biology|Drug Resistance, Neoplasm|Erlotinib Hydrochloride|Humans|Hypoxia|Lung Neoplasms|Prodrugs|Tumor Microenvironment', 'Journal Article', '10.1371/journal.pcbi.1005077', '27560187', 'Experimental studies have shown that one key factor in driving the emergence of drug resistance in solid tumors is tumor hypoxia, which leads to the formation of localized environmental niches where drug-resistant cell populations can evolve and survive. Hypoxia-activated prodrugs (HAPs) are compounds designed to penetrate to hypoxic regions of a tumor and release cytotoxic or cytostatic agents, several of these HAPs are currently in clinical trial. However, preliminary results have not shown a survival benefit in several of these trials. We hypothesize that the efficacy of treatments involving these prodrugs depends heavily on identifying the correct treatment schedule, and that mathematical modeling can be used to help design potential therapeutic strategies combining HAPs with standard therapies to achieve long-term tumor control or eradication. We develop this framework in the specific context of EGFR-driven non-small cell lung cancer, which is commonly treated with the tyrosine kinase inhibitor erlotinib. We develop a stochastic mathematical model, parametrized using clinical and experimental data, to explore a spectrum of treatment regimens combining a HAP, evofosfamide, with erlotinib. We design combination toxicity constraint models and optimize treatment strategies over the space of tolerated schedules to identify specific combination schedules that lead to optimal tumor control. We find that (i) combining these therapies delays resistance longer than any monotherapy schedule with either evofosfamide or erlotinib alone, (ii) sequentially alternating single doses of each drug leads to minimal tumor burden and maximal reduction in probability of developing resistance, and (iii) strategies minimizing the length of time after an evofosfamide dose and before erlotinib confer further benefits in reduction of tumor burden. These results provide insights into how hypoxia-activated prodrugs may be used to enhance therapeutic effectiveness in the clinic.'),
(87991, 2016, 'plos', 'Noncommutative Biology: Sequential Regulation of Complex Networks', 'Letsou, William|Cai, Long', 'Division of Chemistry and Chemical Engineering, California Institute of Technology, Pasadena, California, United States of America.|Division of Chemistry and Chemical Engineering, California Institute of Technology, Pasadena, California, United States of America.', 'United States|United States', 0, 'Computational Biology|Gene Regulatory Networks|Models, Biological|Signal Transduction|Transcription Factors', 'Journal Article', '10.1371/journal.pcbi.1005089', '27560383', 'Single-cell variability in gene expression is important for generating distinct cell types, but it is unclear how cells use the same set of regulatory molecules to specifically control similarly regulated genes. While combinatorial binding of transcription factors at promoters has been proposed as a solution for cell-type specific gene expression, we found that such models resulted in substantial information bottlenecks. We sought to understand the consequences of adopting sequential logic wherein the time-ordering of factors informs the final outcome. We showed that with noncommutative control, it is possible to independently control targets that would otherwise be activated simultaneously using combinatorial logic. Consequently, sequential logic overcomes the information bottleneck inherent in complex networks. We derived scaling laws for two noncommutative models of regulation, motivated by phosphorylation/neural networks and chromosome folding, respectively, and showed that they scale super-exponentially in the number of regulators. We also showed that specificity in control is robust to the loss of a regulator. Lastly, we connected these theoretical results to real biological networks that demonstrate specificity in the context of promiscuity. These results show that achieving a desired outcome often necessitates roundabout steps.'),
(87992, 2016, 'plos', 'Efficient Reconstruction of Predictive Consensus Metabolic Network Models', 'van Heck, Ruben G A|Ganter, Mathias|Martins Dos Santos, Vitor A P|Stelling, Joerg', 'Department of Biosystems Science and Engineering and Swiss Institute of Bioinformatics, ETH Zurich, Basel, Switzerland.|Department of Biosystems Science and Engineering and Swiss Institute of Bioinformatics, ETH Zurich, Basel, Switzerland.|Laboratory of Systems and Synthetic Biology, Wageningen University, Wageningen, The Netherlands.|Department of Biosystems Science and Engineering and Swiss Institute of Bioinformatics, ETH Zurich, Basel, Switzerland.', 'Switzerland|Switzerland|Netherlands|Switzerland', 11, 'Algorithms|Bacteria|Computational Biology|Databases, Genetic|Metabolic Networks and Pathways|Models, Biological|Software|Yeasts', 'Journal Article', '10.1371/journal.pcbi.1005085', '27563720', 'Understanding cellular function requires accurate, comprehensive representations of metabolism. Genome-scale, constraint-based metabolic models (GSMs) provide such representations, but their usability is often hampered by inconsistencies at various levels, in particular for concurrent models. COMMGEN, our tool for COnsensus Metabolic Model GENeration, automatically identifies inconsistencies between concurrent models and semi-automatically resolves them, thereby contributing to consolidate knowledge of metabolic function. Tests of COMMGEN for four organisms showed that automatically generated consensus models were predictive and that they substantially increased coherence of knowledge representation. COMMGEN ought to be particularly useful for complex scenarios in which manual curation does not scale, such as for eukaryotic organisms, microbial communities, and host-pathogen interactions.'),
(87993, 2016, 'plos', 'When Does Model-Based Control Pay Off?', 'Kool, Wouter|Cushman, Fiery A|Gershman, Samuel J', 'Department of Psychology, Harvard University, Cambridge, Massachusetts, United States of America.|Department of Psychology, Harvard University, Cambridge, Massachusetts, United States of America.|Department of Psychology, Harvard University, Cambridge, Massachusetts, United States of America.', 'United States|United States|United States', 33, 'Adolescent|Adult|Aged|Algorithms|Computational Biology|Decision Making|Female|Humans|Learning|Male|Middle Aged|Models, Theoretical|Reinforcement (Psychology)|Task Performance and Analysis|Young Adult', 'Journal Article', '10.1371/journal.pcbi.1005090', '27564094', 'Many accounts of decision making and reinforcement learning posit the existence of two distinct systems that control choice: a fast, automatic system and a slow, deliberative system. Recent research formalizes this distinction by mapping these systems to model-free and model-based strategies in reinforcement learning. Model-free strategies are computationally cheap, but sometimes inaccurate, because action values can be accessed by inspecting a look-up table constructed through trial-and-error. In contrast, model-based strategies compute action values through planning in a causal model of the environment, which is more accurate but also more cognitively demanding. It is assumed that this trade-off between accuracy and computational demand plays an important role in the arbitration between the two strategies, but we show that the hallmark task for dissociating model-free and model-based strategies, as well as several related variants, do not embody such a trade-off. We describe five factors that reduce the effectiveness of the model-based strategy on these tasks by reducing its accuracy in estimating reward outcomes and decreasing the importance of its choices. Based on these observations, we describe a version of the task that formally and empirically obtains an accuracy-demand trade-off between model-free and model-based strategies. Moreover, we show that human participants spontaneously increase their reliance on model-based control on this task, compared to the original paradigm. Our novel task and our computational analyses may prove important in subsequent empirical investigations of how humans balance accuracy and demand.'),
(87994, 2016, 'plos', 'The Loss and Gain of Functional Amino Acid Residues Is a Common Mechanism Causing Human Inherited Disease', 'Lugo-Martinez, Jose|Pejaver, Vikas|Pagel, Kymberleigh A|Jain, Shantanu|Mort, Matthew|Cooper, David N|Mooney, Sean D|Radivojac, Predrag', 'Department of Computer Science and Informatics, Indiana University, Bloomington, Indiana, United States of America.|Department of Computer Science and Informatics, Indiana University, Bloomington, Indiana, United States of America.|Department of Computer Science and Informatics, Indiana University, Bloomington, Indiana, United States of America.|Department of Computer Science and Informatics, Indiana University, Bloomington, Indiana, United States of America.|Institute of Medical Genetics, School of Medicine, Cardiff University, Cardiff, United Kingdom.|Institute of Medical Genetics, School of Medicine, Cardiff University, Cardiff, United Kingdom.|Department of Biomedical Informatics and Medical Education, University of Washington, Seattle, Washington, United States of America.|Department of Computer Science and Informatics, Indiana University, Bloomington, Indiana, United States of America.', 'India|India|India|India|United Kingdom|United Kingdom|United States|India', 8, 'Amino Acid Sequence|Amino Acid Substitution|Computational Biology|Computer Simulation|Disease|Humans|Models, Molecular|Models, Statistical|Mutation|Protein Binding', 'Journal Article', '10.1371/journal.pcbi.1005091', '27564311', 'Elucidating the precise molecular events altered by disease-causing genetic variants represents a major challenge in translational bioinformatics. To this end, many studies have investigated the structural and functional impact of amino acid substitutions. Most of these studies were however limited in scope to either individual molecular functions or were concerned with functional effects (e.g. deleterious vs. neutral) without specifically considering possible molecular alterations. The recent growth of structural, molecular and genetic data presents an opportunity for more comprehensive studies to consider the structural environment of a residue of interest, to hypothesize specific molecular effects of sequence variants and to statistically associate these effects with genetic disease. In this study, we analyzed data sets of disease-causing and putatively neutral human variants mapped to protein 3D structures as part of a systematic study of the loss and gain of various types of functional attribute potentially underlying pathogenic molecular alterations. We first propose a formal model to assess probabilistically function-impacting variants. We then develop an array of structure-based functional residue predictors, evaluate their performance, and use them to quantify the impact of disease-causing amino acid substitutions on catalytic activity, metal binding, macromolecular binding, ligand binding, allosteric regulation and post-translational modifications. We show that our methodology generates actionable biological hypotheses for up to 41% of disease-causing genetic variants mapped to protein structures suggesting that it can be reliably used to guide experimental validation. Our results suggest that a significant fraction of disease-causing human variants mapping to protein structures are function-altering both in the presence and absence of stability disruption.'),
(87995, 2016, 'plos', 'On Expression Patterns and Developmental Origin of Human Brain Regions', 'Kirsch, Lior|Chechik, Gal', 'The Gonda Multidisciplinary Brain Research Center, Bar-Ilan University, Ramat Gan, Israel.|The Gonda Multidisciplinary Brain Research Center, Bar-Ilan University, Ramat Gan, Israel.', 'Israel|Israel', 10, 'Adolescent|Adult|Aged|Aged, 80 and over|Brain|Child|Child, Preschool|Computational Biology|Gene Expression Profiling|Gene Expression Regulation, Developmental|Humans|Infant|Infant, Newborn|Middle Aged|Neurons|Transcriptome|Young Adult', 'Journal Article', '10.1371/journal.pcbi.1005064', '27564987', 'Anatomical substructures of the human brain have characteristic cell-types, connectivity and local circuitry, which are reflected in area-specific transcriptome signatures, but the principles governing area-specific transcription and their relation to brain development are still being studied. In adult rodents, areal transcriptome patterns agree with the embryonic origin of brain regions, but the processes and genes that preserve an embryonic signature in regional expression profiles were not quantified. Furthermore, it is not clear how embryonic-origin signatures of adult-brain expression interplay with changes in expression patterns during development. Here we first quantify which genes have regional expression-patterns related to the developmental origin of brain regions, using genome-wide mRNA expression from post-mortem adult human brains. We find that almost all human genes (92%) exhibit an expression pattern that agrees with developmental brain-region ontology, but that this agreement changes at multiple phases during development. Agreement is particularly strong in neuron-specific genes, but also in genes that are not spatially correlated with neuron-specific or glia-specific markers. Surprisingly, agreement is also stronger in early-evolved genes. We further find that pairs of similar genes having high agreement to developmental region ontology tend to be more strongly correlated or anti-correlated, and that the strength of spatial correlation changes more strongly in gene pairs with stronger embryonic signatures. These results suggest that transcription regulation of most genes in the adult human brain is spatially tuned in a way that changes through life, but in agreement with development-determined brain regions.'),
(87996, 2016, 'plos', 'A Thalamocortical Neural Mass Model of the EEG during NREM Sleep and Its Response to Auditory Stimulation', 'Schellenberger Costa, Michael|Weigenand, Arne|Ngo, Hong-Viet V|Marshall, Lisa|Born, Jan|Martinetz, Thomas|Claussen, Jens Christian', 'Institute for Neuro- and Bioinformatics, University of Lübeck, Lübeck, Germany.|Institute for Neuro- and Bioinformatics, University of Lübeck, Lübeck, Germany.|Institute for Medical Psychology and Behavioral Neurobiology, University of Tübingen, Tübingen, Germany.|Graduate School for Computing in Medicine and Life Science, University of Lübeck, Lübeck, Germany.|Institute for Medical Psychology and Behavioral Neurobiology, University of Tübingen, Tübingen, Germany.|Institute for Neuro- and Bioinformatics, University of Lübeck, Lübeck, Germany.|Institute for Neuro- and Bioinformatics, University of Lübeck, Lübeck, Germany.', 'Germany|Germany|Germany|Germany|Germany|Germany|Germany', 11, 'Acoustic Stimulation|Cerebral Cortex|Electroencephalography|Humans|Models, Neurological|Sleep|Thalamus', 'Journal Article', '10.1371/journal.pcbi.1005022', '27584827', 'Few models exist that accurately reproduce the complex rhythms of the thalamocortical system that are apparent in measured scalp EEG and at the same time, are suitable for large-scale simulations of brain activity. Here, we present a neural mass model of the thalamocortical system during natural non-REM sleep, which is able to generate fast sleep spindles (12-15 Hz), slow oscillations (<1 Hz) and K-complexes, as well as their distinct temporal relations, and response to auditory stimuli. We show that with the inclusion of detailed calcium currents, the thalamic neural mass model is able to generate different firing modes, and validate the model with EEG-data from a recent sleep study in humans, where closed-loop auditory stimulation was applied. The model output relates directly to the EEG, which makes it a useful basis to develop new stimulation protocols.'),
(87997, 2016, 'plos', 'Role of DARPP-32 and ARPP-21 in the Emergence of Temporal Constraints on Striatal Calcium and Dopamine Integration', 'Nair, Anu G|Bhalla, Upinder S|Hellgren Kotaleski, Jeanette', 'Science for Life Laboratory, School of Computer Science and Communication, KTH Royal Institute of Technology, Stockholm, Sweden.|National Centre for Biological Sciences, Tata Institute of Fundamental Research, Bangalore, India.|Science for Life Laboratory, School of Computer Science and Communication, KTH Royal Institute of Technology, Stockholm, Sweden.', 'Sweden|India|Sweden', 14, 'Animals|Calcium|Computational Biology|Corpus Striatum|Dopamine|Dopamine and cAMP-Regulated Phosphoprotein 32|Models, Biological|Phosphoproteins|Signal Transduction', 'Journal Article', '10.1371/journal.pcbi.1005080', '27584878', 'In reward learning, the integration of NMDA-dependent calcium and dopamine by striatal projection neurons leads to potentiation of corticostriatal synapses through CaMKII/PP1 signaling. In order to elicit the CaMKII/PP1-dependent response, the calcium and dopamine inputs should arrive in temporal proximity and must follow a specific (dopamine after calcium) order. However, little is known about the cellular mechanism which enforces these temporal constraints on the signal integration. In this computational study, we propose that these temporal requirements emerge as a result of the coordinated signaling via two striatal phosphoproteins, DARPP-32 and ARPP-21. Specifically, DARPP-32-mediated signaling could implement an input-interval dependent gating function, via transient PP1 inhibition, thus enforcing the requirement for temporal proximity. Furthermore, ARPP-21 signaling could impose the additional input-order requirement of calcium and dopamine, due to its Ca2+/calmodulin sequestering property when dopamine arrives first. This highlights the possible role of phosphoproteins in the temporal aspects of striatal signal transduction.'),
(87998, 2016, 'plos', 'Learning Reward Uncertainty in the Basal Ganglia', 'Mikhael, John G|Bogacz, Rafal', 'Department of Experimental Psychology, University of Oxford, Oxford, United Kingdom.|MRC Brain Network Dynamics Unit, University of Oxford, Oxford, United Kingdom.', 'United Kingdom|United Kingdom', 0, 'Basal Ganglia|Choice Behavior|Computational Biology|Humans|Learning|Models, Neurological|Reward|Uncertainty', 'Journal Article', '10.1371/journal.pcbi.1005062', '27589489', 'Learning the reliability of different sources of rewards is critical for making optimal choices. However, despite the existence of detailed theory describing how the expected reward is learned in the basal ganglia, it is not known how reward uncertainty is estimated in these circuits. This paper presents a class of models that encode both the mean reward and the spread of the rewards, the former in the difference between the synaptic weights of D1 and D2 neurons, and the latter in their sum. In the models, the tendency to seek (or avoid) options with variable reward can be controlled by increasing (or decreasing) the tonic level of dopamine. The models are consistent with the physiology of and synaptic plasticity in the basal ganglia, they explain the effects of dopaminergic manipulations on choices involving risks, and they make multiple experimental predictions.'),
(87999, 2016, 'plos', 'Leukocyte Motility Models Assessed through Simulation and Multi-objective Optimization-Based Model Selection', 'Read, Mark N|Bailey, Jacqueline|Timmis, Jon|Chtanova, Tatyana', 'School of Life and Environmental Sciences, The University of Sydney, Sydney, New South Wales, Australia.|The Garvan Institute of Medical Research, Darlinghurst, New South Wales, Australia.|Department of Electronics, The University of York, York, United Kingdom.|The Garvan Institute of Medical Research, Darlinghurst, New South Wales, Australia.', 'Australia|Australia|United Kingdom|Australia', 9, 'Animals|Cell Movement|Computational Biology|Computer Simulation|Leukocytes|Mice|Mice, Inbred C57BL|Microscopy|Models, Biological', 'Journal Article', '10.1371/journal.pcbi.1005082', '27589606', 'The advent of two-photon microscopy now reveals unprecedented, detailed spatio-temporal data on cellular motility and interactions in vivo. Understanding cellular motility patterns is key to gaining insight into the development and possible manipulation of the immune response. Computational simulation has become an established technique for understanding immune processes and evaluating hypotheses in the context of experimental data, and there is clear scope to integrate microscopy-informed motility dynamics. However, determining which motility model best reflects in vivo motility is non-trivial: 3D motility is an intricate process requiring several metrics to characterize. This complicates model selection and parameterization, which must be performed against several metrics simultaneously. Here we evaluate Brownian motion, Lévy walk and several correlated random walks (CRWs) against the motility dynamics of neutrophils and lymph node T cells under inflammatory conditions by simultaneously considering cellular translational and turn speeds, and meandering indices. Heterogeneous cells exhibiting a continuum of inherent translational speeds and directionalities comprise both datasets, a feature significantly improving capture of in vivo motility when simulated as a CRW. Furthermore, translational and turn speeds are inversely correlated, and the corresponding CRW simulation again improves capture of our in vivo data, albeit to a lesser extent. In contrast, Brownian motion poorly reflects our data. Lévy walk is competitive in capturing some aspects of neutrophil motility, but T cell directional persistence only, therein highlighting the importance of evaluating models against several motility metrics simultaneously. This we achieve through novel application of multi-objective optimization, wherein each model is independently implemented and then parameterized to identify optimal trade-offs in performance against each metric. The resultant Pareto fronts of optimal solutions are directly contrasted to identify models best capturing in vivo dynamics, a technique that can aid model selection more generally. Our technique robustly determines our cell populations motility strategies, and paves the way for simulations that incorporate accurate immune cell motility dynamics.'),
(88000, 2016, 'plos', 'Direct Correlation between Motile Behavior and Protein Abundance in Single Cells', 'Dufour, Yann S|Gillet, Sébastien|Frankel, Nicholas W|Weibel, Douglas B|Emonet, Thierry', 'Department of Molecular, Cellular, and Developmental Biology, Yale University, New Haven, Connecticut, United States of America.|Department of Molecular, Cellular, and Developmental Biology, Yale University, New Haven, Connecticut, United States of America.|Department of Molecular, Cellular, and Developmental Biology, Yale University, New Haven, Connecticut, United States of America.|Department of Biochemistry, University of Wisconsin-Madison, Madison, Wisconsin, United States of America.|Department of Molecular, Cellular, and Developmental Biology, Yale University, New Haven, Connecticut, United States of America.', 'United States|United States|United States|United States|United States', 0, 'Chemotaxis|Computational Biology|Escherichia coli|Escherichia coli Proteins|Methyltransferases|Single-Cell Analysis', 'Journal Article', '10.1371/journal.pcbi.1005041', '27599206', 'Understanding how stochastic molecular fluctuations affect cell behavior requires the quantification of both behavior and protein numbers in the same cells. Here, we combine automated microscopy with in situ hydrogel polymerization to measure single-cell protein expression after tracking swimming behavior. We characterized the distribution of non-genetic phenotypic diversity in Escherichia coli motility, which affects single-cell exploration. By expressing fluorescently tagged chemotaxis proteins (CheR and CheB) at different levels, we quantitatively mapped motile phenotype (tumble bias) to protein numbers using thousands of single-cell measurements. Our results disagreed with established models until we incorporated the role of CheB in receptor deamidation and the slow fluctuations in receptor methylation. Beyond refining models, our central finding is that changes in numbers of CheR and CheB affect the population mean tumble bias and its variance independently. Therefore, it is possible to adjust the degree of phenotypic diversity of a population by adjusting the global level of expression of CheR and CheB while keeping their ratio constant, which, as shown in previous studies, confers functional robustness to the system. Since genetic control of protein expression is heritable, our results suggest that non-genetic diversity in motile behavior is selectable, supporting earlier hypotheses that such diversity confers a selective advantage.'),
(88001, 2016, 'plos', 'Qualitative Dynamical Modelling Can Formally Explain Mesoderm Specification and Predict Novel Developmental Phenotypes', 'Mbodj, Abibatou|Gustafson, E Hilary|Ciglar, Lucia|Junion, Guillaume|Gonzalez, Aitor|Girardot, Charles|Perrin, Laurent|Furlong, Eileen E M|Thieffry, Denis', 'Aix-Marseille Université, Marseille, France.|European Molecular Biology Laboratory (EMBL), Genome Biology Unit, Heidelberg, Germany.|European Molecular Biology Laboratory (EMBL), Genome Biology Unit, Heidelberg, Germany.|European Molecular Biology Laboratory (EMBL), Genome Biology Unit, Heidelberg, Germany.|Aix-Marseille Université, Marseille, France.|European Molecular Biology Laboratory (EMBL), Genome Biology Unit, Heidelberg, Germany.|Aix-Marseille Université, Marseille, France.|European Molecular Biology Laboratory (EMBL), Genome Biology Unit, Heidelberg, Germany.|Computational Systems Biology team, Institut de Biologie de lEcole Normale Supérieure (IBENS), INSERM, Ecole Normale Supérieure, PSL Research University, Paris, France.', 'France|Germany|Germany|Germany|France|Germany|France|Germany|France', 0, 'Animals|Computational Biology|Drosophila|Gene Expression Regulation, Developmental|Mesoderm|Models, Biological|Mutation|Phenotype|Signal Transduction', 'Journal Article', '10.1371/journal.pcbi.1005073', '27599298', 'Given the complexity of developmental networks, it is often difficult to predict the effect of genetic perturbations, even within coding genes. Regulatory factors generally have pleiotropic effects, exhibit partially redundant roles, and regulate highly interconnected pathways with ample cross-talk. Here, we delineate a logical model encompassing 48 components and 82 regulatory interactions involved in mesoderm specification during Drosophila development, thereby providing a formal integration of all available genetic information from the literature. The four main tissues derived from mesoderm correspond to alternative stable states. We demonstrate that the model can predict known mutant phenotypes and use it to systematically predict the effects of over 300 new, often non-intuitive, loss- and gain-of-function mutations, and combinations thereof. We further validated several novel predictions experimentally, thereby demonstrating the robustness of model. Logical modelling can thus contribute to formally explain and predict regulatory outcomes underlying cell fate decisions.'),
(88002, 2016, 'plos', 'Inhomogeneity Based Characterization of Distribution Patterns on the Plasma Membrane', 'Paparelli, Laura|Corthout, Nikky|Pavie, Benjamin|Wakefield, Devin L|Sannerud, Ragna|Jovanovic-Talisman, Tijana|Annaert, Wim|Munck, Sebastian', 'VIB Bio Imaging Core, Herestraat, Leuven, Belgium.|VIB Bio Imaging Core, Herestraat, Leuven, Belgium.|VIB Bio Imaging Core, Herestraat, Leuven, Belgium.|Department of Molecular Medicine, Beckman Research Institute of the City of Hope Comprehensive Cancer Center, Duarte, California, United States of America.|Laboratory of Membrane Trafficking, Department of Human Genetics, KU Leuven, Herestraat, Leuven, Belgium.|Department of Molecular Medicine, Beckman Research Institute of the City of Hope Comprehensive Cancer Center, Duarte, California, United States of America.|Laboratory of Membrane Trafficking, Department of Human Genetics, KU Leuven, Herestraat, Leuven, Belgium.|VIB Bio Imaging Core, Herestraat, Leuven, Belgium.', 'Belgium|Belgium|Belgium|United States|Belgium|United States|Belgium|Belgium', 0, 'Algorithms|Animals|Cell Membrane|Cells, Cultured|Computational Biology|Image Processing, Computer-Assisted|Lipids|Membrane Proteins|Mice|Microscopy, Fluorescence|Software', 'Journal Article', '10.1371/journal.pcbi.1005095', '27603951', 'Cell surface protein and lipid molecules are organized in various patterns: randomly, along gradients, or clustered when segregated into discrete micro- and nano-domains. Their distribution is tightly coupled to events such as polarization, endocytosis, and intracellular signaling, but challenging to quantify using traditional techniques. Here we present a novel approach to quantify the distribution of plasma membrane proteins and lipids. This approach describes spatial patterns in degrees of inhomogeneity and incorporates an intensity-based correction to analyze images with a wide range of resolutions, we have termed it Quantitative Analysis of the Spatial distributions in Images using Mosaic segmentation and Dual parameter Optimization in Histograms (QuASIMoDOH). We tested its applicability using simulated microscopy images and images acquired by widefield microscopy, total internal reflection microscopy, structured illumination microscopy, and photoactivated localization microscopy. We validated QuASIMoDOH, successfully quantifying the distribution of protein and lipid molecules detected with several labeling techniques, in different cell model systems. We also used this method to characterize the reorganization of cell surface lipids in response to disrupted endosomal trafficking and to detect dynamic changes in the global and local organization of epidermal growth factor receptors across the cell surface. Our findings demonstrate that QuASIMoDOH can be used to assess protein and lipid patterns, quantifying distribution changes and spatial reorganization at the cell surface. An ImageJ/Fiji plugin of this analysis tool is provided.'),
(88003, 2016, 'plos', 'The C elegans Connectome Consists of Homogenous Circuits with Defined Functional Roles', 'Azulay, Aharon|Itskovits, Eyal|Zaslaver, Alon', 'Department of Genetics, The Silberman Life Science Institute, Edmond J. Safra Campus, Hebrew University, Jerusalem, Israel.|Department of Genetics, The Silberman Life Science Institute, Edmond J. Safra Campus, Hebrew University, Jerusalem, Israel.|Department of Genetics, The Silberman Life Science Institute, Edmond J. Safra Campus, Hebrew University, Jerusalem, Israel.', 'Israel|Israel|Israel', 11, 'Animals|Caenorhabditis elegans|Computational Biology|Connectome|Models, Neurological|Nerve Net', 'Journal Article', '10.1371/journal.pcbi.1005021', '27606684', 'A major goal of systems neuroscience is to decipher the structure-function relationship in neural networks. Here we study network functionality in light of the common-neighbor-rule (CNR) in which a pair of neurons is more likely to be connected the more common neighbors it shares. Focusing on the fully-mapped neural network of C. elegans worms, we establish that the CNR is an emerging property in this connectome. Moreover, sets of common neighbors form homogenous structures that appear in defined layers of the network. Simulations of signal propagation reveal their potential functional roles: signal amplification and short-term memory at the sensory/inter-neuron layer, and synchronized activity at the motoneuron layer supporting coordinated movement. A coarse-grained view of the neural network based on homogenous connected sets alone reveals a simple modular network architecture that is intuitive to understand. These findings provide a novel framework for analyzing larger, more complex, connectomes once these become available.'),
(88004, 2016, 'plos', 'The Statistical Determinants of the Speed of Motor Learning', 'He, Kang|Liang, You|Abdollahi, Farnaz|Fisher Bittmann, Moria|Kording, Konrad|Wei, Kunlin', 'School of Psychological and Cognitive Sciences, Peking University, Beijing, China.|School of Psychological and Cognitive Sciences, Peking University, Beijing, China.|Rehabilitation Institute of Chicago, Chicago, Illinois, United States of America.|University of Wisconsin, Madison, Wisconsin, United States of America.|Rehabilitation Institute of Chicago, Chicago, Illinois, United States of America.|School of Psychological and Cognitive Sciences, Peking University, Beijing, China.', 'China|China|United States|United States|United States|China', 0, 'Computational Biology|Humans|Learning|Models, Statistical|Psychomotor Performance|Task Performance and Analysis', 'Journal Article', '10.1371/journal.pcbi.1005023', '27606808', 'It has recently been suggested that movement variability directly increases the speed of motor learning. Here we use computational modeling of motor adaptation to show that variability can have a broad range of effects on learning, both negative and positive. Experimentally, we also find contributing and decelerating effects. Lastly, through a meta-analysis of published papers, we verify that across a wide range of experiments, movement variability has no statistical relation with learning rate. While motor learning is a complex process that can be modeled, further research is needed to understand the relative importance of the involved factors.'),
(88005, 2016, 'plos', 'Stimulation-Based Control of Dynamic Brain Networks', 'Muldoon, Sarah Feldt|Pasqualetti, Fabio|Gu, Shi|Cieslak, Matthew|Grafton, Scott T|Vettel, Jean M|Bassett, Danielle S', 'Department of Bioengineering, University of Pennsylvania, Philadelphia, Pennsylvania, United States of America.|Department of Mechanical Engineering, University of California, Riverside, Riverside, California, United States of America.|Department of Bioengineering, University of Pennsylvania, Philadelphia, Pennsylvania, United States of America.|Department of Psychological and Brain Sciences, University of California, Santa Barbara, Santa Barbara, California, United States of America.|Department of Psychological and Brain Sciences, University of California, Santa Barbara, Santa Barbara, California, United States of America.|US Army Research Laboratory, Aberdeen Proving Ground, Maryland, United States of America.|Department of Bioengineering, University of Pennsylvania, Philadelphia, Pennsylvania, United States of America.', 'United States|United States|United States|United States|United States|United States|United States', 0, 'Adult|Brain|Brain Mapping|Computational Biology|Computer Simulation|Electric Stimulation Therapy|Female|Humans|Male|Models, Neurological|Nerve Net|Young Adult', 'Journal Article', '10.1371/journal.pcbi.1005076', '27611328', 'The ability to modulate brain states using targeted stimulation is increasingly being employed to treat neurological disorders and to enhance human performance. Despite the growing interest in brain stimulation as a form of neuromodulation, much remains unknown about the network-level impact of these focal perturbations. To study the system wide impact of regional stimulation, we employ a data-driven computational model of nonlinear brain dynamics to systematically explore the effects of targeted stimulation. Validating predictions from network control theory, we uncover the relationship between regional controllability and the focal versus global impact of stimulation, and we relate these findings to differences in the underlying network architecture. Finally, by mapping brain regions to cognitive systems, we observe that the default mode system imparts large global change despite being highly constrained by structural connectivity. This work forms an important step towards the development of personalized stimulation protocols for medical treatment or performance enhancement.'),
(88006, 2016, 'plos', 'The Computational Properties of a Simplified Cortical Column Model', 'Cain, Nicholas|Iyer, Ramakrishnan|Koch, Christof|Mihalas, Stefan', 'Allen Institute for Brain Science, Seattle, Washington, United States of America.|Allen Institute for Brain Science, Seattle, Washington, United States of America.|Allen Institute for Brain Science, Seattle, Washington, United States of America.|Allen Institute for Brain Science, Seattle, Washington, United States of America.', 'United States|United States|United States|United States', 0, 'Action Potentials|Animals|Computational Biology|Computer Simulation|Mammals|Models, Neurological|Neocortex|Neurons', 'Journal Article', '10.1371/journal.pcbi.1005045', '27617444', 'The mammalian neocortex has a repetitious, laminar structure and performs functions integral to higher cognitive processes, including sensory perception, memory, and coordinated motor output. What computations does this circuitry subserve that link these unique structural elements to their function? Potjans and Diesmann (2014) parameterized a four-layer, two cell type (i.e. excitatory and inhibitory) model of a cortical column with homogeneous populations and cell type dependent connection probabilities. We implement a version of their model using a displacement integro-partial differential equation (DiPDE) population density model. This approach, exact in the limit of large homogeneous populations, provides a fast numerical method to solve equations describing the full probability density distribution of neuronal membrane potentials. It lends itself to quickly analyzing the mean response properties of population-scale firing rate dynamics. We use this strategy to examine the input-output relationship of the Potjans and Diesmann cortical column model to understand its computational properties. When inputs are constrained to jointly and equally target excitatory and inhibitory neurons, we find a large linear regime where the effect of a multi-layer input signal can be reduced to a linear combination of component signals. One of these, a simple subtractive operation, can act as an error signal passed between hierarchical processing stages.');
INSERT INTO `papers` (`id`, `ano`, `journal`, `titulo`, `autores`, `afiliacao`, `pais`, `citacoes`, `palavra_chave`, `categorias`, `doi`, `pubmed`, `abstract`) VALUES
(88007, 2016, 'plos', 'Uncertainty-Dependent Extinction of Fear Memory in an Amygdala-mPFC Neural Circuit Model', 'Li, Yuzhe|Nakae, Ken|Ishii, Shin|Naoki, Honda', 'Graduate School of Biostudies, Kyoto University, Kyoto, Japan.|Graduate School of Informatics, Kyoto University, Kyoto, Japan.|Graduate School of Informatics, Kyoto University, Kyoto, Japan.|Imaging Platform of Spatio-temporal Information, Graduate School of Medicine, Kyoto University, Kyoto, Japan.', 'Japan|Japan|Japan|Japan', 7, 'Amygdala|Conditioning (Psychology)|Fear|Humans|Memory|Models, Neurological|Neural Pathways|Neurons|Prefrontal Cortex|Reinforcement (Psychology)|Uncertainty', 'Journal Article', '10.1371/journal.pcbi.1005099', '27617747', 'Uncertainty of fear conditioning is crucial for the acquisition and extinction of fear memory. Fear memory acquired through partial pairings of a conditioned stimulus (CS) and an unconditioned stimulus (US) is more resistant to extinction than that acquired through full pairings, this effect is known as the partial reinforcement extinction effect (PREE). Although the PREE has been explained by psychological theories, the neural mechanisms underlying the PREE remain largely unclear. Here, we developed a neural circuit model based on three distinct types of neurons (fear, persistent and extinction neurons) in the amygdala and medial prefrontal cortex (mPFC). In the model, the fear, persistent and extinction neurons encode predictions of net severity, of unconditioned stimulus (US) intensity, and of net safety, respectively. Our simulation successfully reproduces the PREE. We revealed that unpredictability of the US during extinction was represented by the combined responses of the three types of neurons, which are critical for the PREE. In addition, we extended the model to include amygdala subregions and the mPFC to address a recent finding that the ventral mPFC (vmPFC) is required for consolidating extinction memory but not for memory retrieval. Furthermore, model simulations led us to propose a novel procedure to enhance extinction learning through re-conditioning with a stronger US, strengthened fear memory up-regulates the extinction neuron, which, in turn, further inhibits the fear neuron during re-extinction. Thus, our models increased the understanding of the functional roles of the amygdala and vmPFC in the processing of uncertainty in fear conditioning and extinction.'),
(88008, 2016, 'plos', 'Statistical Analysis of Tract-Tracing Experiments Demonstrates a Dense, Complex Cortical Network in the Mouse', 'Ypma, Rolf J F|Bullmore, Edward T', 'Brain Mapping Unit, Department of Psychiatry, University of Cambridge, Cambridge, United Kingdom.|Brain Mapping Unit, Department of Psychiatry, University of Cambridge, Cambridge, United Kingdom.', 'United Kingdom|United Kingdom', 0, 'Animals|Computational Biology|Connectome|Databases, Factual|Mice|Models, Neurological|Models, Statistical|Nerve Net|Neural Pathways', 'Journal Article', '10.1371/journal.pcbi.1005104', '27617835', 'Anatomical tract tracing methods are the gold standard for estimating the weight of axonal connectivity between a pair of pre-defined brain regions. Large studies, comprising hundreds of experiments, have become feasible by automated methods. However, this comes at the cost of positive-mean noise making it difficult to detect weak connections, which are of particular interest as recent high resolution tract-tracing studies of the macaque have identified many more weak connections, adding up to greater connection density of cortical networks, than previously recognized. We propose a statistical framework that estimates connectivity weights and credibility intervals from multiple tract-tracing experiments. We model the observed signal as a log-normal distribution generated by a combination of tracer fluorescence and positive-mean noise, also accounting for injections into multiple regions. Using anterograde viral tract-tracing data provided by the Allen Institute for Brain Sciences, we estimate the connection density of the mouse intra-hemispheric cortical network to be 73% (95% credibility interval (CI): 71%, 75%), higher than previous estimates (40%). Inter-hemispheric density was estimated to be 59% (95% CI: 54%, 62%). The weakest estimable connections (about 6 orders of magnitude weaker than the strongest connections) are likely to represent only one or a few axons. These extremely weak connections are topologically more random and longer distance than the strongest connections, which are topologically more clustered and shorter distance (spatially clustered). Weak links do not substantially contribute to the global topology of a weighted brain graph, but incrementally increased topological integration of a binary graph. The topology of weak anatomical connections in the mouse brain, rigorously estimable down to the biological limit of a single axon between cortical areas in these data, suggests that they might confer functional advantages for integrative information processing and/or they might represent a stochastic factor in the development of the mouse connectome.'),
(88009, 2016, 'plos', 'Bipartite Community Structure of eQTLs', 'Platig, John|Castaldi, Peter J|DeMeo, Dawn|Quackenbush, John', 'Department of Biostatistics and Computational Biology, Dana-Farber Cancer Institute, Boston, Massachusetts, United States of America.|Channing Division of Network Medicine, Brigham and Womens Hospital, Boston, Massachusetts, United States of America.|Channing Division of Network Medicine, Brigham and Womens Hospital, Boston, Massachusetts, United States of America.|Department of Biostatistics and Computational Biology, Dana-Farber Cancer Institute, Boston, Massachusetts, United States of America.', 'United States|United States|United States|United States', 0, 'Algorithms|Genome-Wide Association Study|Humans|Models, Statistical|Polymorphism, Single Nucleotide|Pulmonary Disease, Chronic Obstructive|Quantitative Trait Loci', 'Journal Article', '10.1371/journal.pcbi.1005033', '27618581', 'Genome Wide Association Studies (GWAS) and expression quantitative trait locus (eQTL) analyses have identified genetic associations with a wide range of human phenotypes. However, many of these variants have weak effects and understanding their combined effect remains a challenge. One hypothesis is that multiple SNPs interact in complex networks to influence functional processes that ultimately lead to complex phenotypes, including disease states. Here we present CONDOR, a method that represents both cis- and trans-acting SNPs and the genes with which they are associated as a bipartite graph and then uses the modular structure of that graph to place SNPs into a functional context. In applying CONDOR to eQTLs in chronic obstructive pulmonary disease (COPD), we found the global network hub SNPs were devoid of disease associations through GWAS. However, the network was organized into 52 communities of SNPs and genes, many of which were enriched for genes in specific functional classes. We identified local hubs within each community (core SNPs) and these were enriched for GWAS SNPs for COPD and many other diseases. These results speak to our intuition: rather than single SNPs influencing single genes, we see groups of SNPs associated with the expression of families of functionally related genes and that disease SNPs are associated with the perturbation of those functions. These methods are not limited in their application to COPD and can be used in the analysis of a wide variety of disease processes and other phenotypic traits.'),
(88010, 2016, 'plos', 'The Contribution of High-Order Metabolic Interactions to the Global Activity of a Four-Species Microbial Community', 'Guo, Xiaokan|Boedicker, James Q', 'Department of Physics, University of Southern California, Los Angeles, California, United States of America.|Department of Physics, University of Southern California, Los Angeles, California, United States of America.', 'United States|United States', 0, 'Bacteria|Computational Biology|Microbial Consortia|Microbial Interactions|Models, Biological', 'Journal Article', '10.1371/journal.pcbi.1005079', '27623159', 'The activity of a biological community is the outcome of complex processes involving interactions between community members. It is often unclear how to accurately incorporate these interactions into predictive models. Previous work has shown a range of positive and negative metabolic pairwise interactions between species. Here we examine the ability of a modified general Lotka-Volterra model with cell-cell interaction coefficients to predict the overall metabolic rate of a well-mixed microbial community comprised of four heterotrophic natural isolates, experimentally quantifying the strengths of two, three, and four-species interactions. Within this community, interactions between any pair of microbial species were positive, while higher-order interactions, between 3 or more microbial species, slightly modulated community metabolism. For this simple community, the metabolic rate of can be well predicted only with taking into account pairwise interactions. Simulations using the experimentally determined interaction parameters revealed that spatial heterogeneity in the distribution of cells increased the importance of multispecies interactions in dictating function at both the local and global scales.'),
(88011, 2016, 'plos', 'Processing Oscillatory Signals by Incoherent Feedforward Loops', 'Zhang, Carolyn|Tsoi, Ryan|Wu, Feilun|You, Lingchong', 'Department of Biomedical Engineering, Duke University, Durham, North Carolina, United States of America.|Department of Biomedical Engineering, Duke University, Durham, North Carolina, United States of America.|Department of Biomedical Engineering, Duke University, Durham, North Carolina, United States of America.|Department of Biomedical Engineering, Duke University, Durham, North Carolina, United States of America.', 'United States|United States|United States|United States', 0, 'Biological Clocks|Computational Biology|Feedback, Physiological|Models, Biological|Signal Transduction', 'Journal Article', '10.1371/journal.pcbi.1005101', '27623175', 'From the timing of amoeba development to the maintenance of stem cell pluripotency, many biological signaling pathways exhibit the ability to differentiate between pulsatile and sustained signals in the regulation of downstream gene expression. While the networks underlying this signal decoding are diverse, many are built around a common motif, the incoherent feedforward loop (IFFL), where an input simultaneously activates an output and an inhibitor of the output. With appropriate parameters, this motif can exhibit temporal adaptation, where the system is desensitized to a sustained input. This property serves as the foundation for distinguishing input signals with varying temporal profiles. Here, we use quantitative modeling to examine another property of IFFLs-the ability to process oscillatory signals. Our results indicate that the systems ability to translate pulsatile dynamics is limited by two constraints. The kinetics of the IFFL components dictate the input range for which the network is able to decode pulsatile dynamics. In addition, a match between the network parameters and input signal characteristics is required for optimal counting. We elucidate one potential mechanism by which information processing occurs in natural networks, and our work has implications in the design of synthetic gene circuits for this purpose.'),
(88012, 2016, 'plos', 'A Model of the Spatio-temporal Dynamics of Drosophila Eye Disc Development', 'Fried, Patrick|Sánchez-Aragón, Máximo|Aguilar-Hidalgo, Daniel|Lehtinen, Birgitta|Casares, Fernando|Iber, Dagmar', 'Department of Biosystems, Science and Engineering (D-BSSE), ETH Zurich, Basel, Switzerland.|CABD, CSIC and Universidad Pablo de Olavide, Campus UPO, Seville, Spain.|CABD, CSIC and Universidad Pablo de Olavide, Campus UPO, Seville, Spain.|Department of Biosystems, Science and Engineering (D-BSSE), ETH Zurich, Basel, Switzerland.|CABD, CSIC and Universidad Pablo de Olavide, Campus UPO, Seville, Spain.|Department of Biosystems, Science and Engineering (D-BSSE), ETH Zurich, Basel, Switzerland.', 'Switzerland|Spain|Spain|Switzerland|Spain|Switzerland', 0, 'Animals|Cell Proliferation|Computational Biology|Computer Simulation|Drosophila|Drosophila Proteins|Eye|Morphogenesis|Signal Transduction|Spatio-Temporal Analysis', 'Journal Article', '10.1371/journal.pcbi.1005052', '27626238', 'Patterning and growth are linked during early development and have to be tightly controlled to result in a functional tissue or organ. During the development of the Drosophila eye, this linkage is particularly clear: the growth of the eye primordium mainly results from proliferating cells ahead of the morphogenetic furrow (MF), a moving signaling wave that sweeps across the tissue from the posterior to the anterior side, that induces proliferating cells anterior to it to differentiate and become cell cycle quiescent in its wake. Therefore, final eye disc size depends on the proliferation rate of undifferentiated cells and on the speed with which the MF sweeps across the eye disc. We developed a spatio-temporal model of the growing eye disc based on the regulatory interactions controlled by the signals Decapentaplegic (Dpp), Hedgehog (Hh) and the transcription factor Homothorax (Hth) and explored how the signaling patterns affect the movement of the MF and impact on eye disc growth. We used published and new quantitative data to parameterize the model. In particular, two crucial parameter values, the degradation rate of Hth and the diffusion coefficient of Hh, were measured. The model is able to reproduce the linear movement of the MF and the termination of growth of the primordium. We further show that the model can explain several mutant phenotypes, but fails to reproduce the previously observed scaling of the Dpp gradient in the anterior compartment.'),
(88013, 2016, 'plos', 'Including Thermal Fluctuations in Actomyosin Stable States Increases the Predicted Force per Motor and Macroscopic Efficiency in Muscle Modelling', 'Marcucci, Lorenzo|Washio, Takumi|Yanagida, Toshio', 'Department of Biomedical Sciences, Padova University, Padova, Italy.|Graduate School of Frontier Sciences, The University of Tokyo, Tokyo, Japan.|Quantitative Biology Center, RIKEN, Suita, Japan.', 'Italy|Japan|Japan', 10, 'Actomyosin|Animals|Anura|Computational Biology|Humans|Models, Biological|Muscle Contraction|Muscles', 'Journal Article', '10.1371/journal.pcbi.1005083', '27626630', 'Muscle contractions are generated by cyclical interactions of myosin heads with actin filaments to form the actomyosin complex. To simulate actomyosin complex stable states, mathematical models usually define an energy landscape with a corresponding number of wells. The jumps between these wells are defined through rate constants. Almost all previous models assign these wells an infinite sharpness by imposing a relatively simple expression for the detailed balance, i.e., the ratio of the rate constants depends exponentially on the sole myosin elastic energy. Physically, this assumption corresponds to neglecting thermal fluctuations in the actomyosin complex stable states. By comparing three mathematical models, we examine the extent to which this hypothesis affects muscle model predictions at the single cross-bridge, single fiber, and organ levels in a ceteris paribus analysis. We show that including fluctuations in stable states allows the lever arm of the myosin to easily and dynamically explore all possible minima in the energy landscape, generating several backward and forward jumps between states during the lifetime of the actomyosin complex, whereas the infinitely sharp minima case is characterized by fewer jumps between states. Moreover, the analysis predicts that thermal fluctuations enable a more efficient contraction mechanism, in which a higher force is sustained by fewer attached cross-bridges.'),
(88014, 2016, 'plos', 'SUMOFLUX: A Generalized Method for Targeted 13C Metabolic Flux Ratio Analysis', 'Kogadeeva, Maria|Zamboni, Nicola', 'Institute of Molecular Systems Biology, ETH Zürich, Zürich, Switzerland.|Institute of Molecular Systems Biology, ETH Zürich, Zürich, Switzerland.', 'Switzerland|Switzerland', 0, 'Algorithms|Carbon Isotopes|Computational Biology|Escherichia coli|Metabolic Flux Analysis|Models, Biological', 'Journal Article', '10.1371/journal.pcbi.1005109', '27626798', 'Metabolic fluxes are a cornerstone of cellular physiology that emerge from a complex interplay of enzymes, carriers, and nutrients. The experimental assessment of in vivo intracellular fluxes using stable isotopic tracers is essential if we are to understand metabolic function and regulation. Flux estimation based on 13C or 2H labeling relies on complex simulation and iterative fitting, processes that necessitate a level of expertise that ordinarily preclude the non-expert user. To overcome this, we have developed SUMOFLUX, a methodology that is broadly applicable to the targeted analysis of 13C-metabolic fluxes. By combining surrogate modeling and machine learning, we trained a predictor to specialize in estimating flux ratios from measurable 13C-data. SUMOFLUX targets specific flux features individually, which makes it fast, user-friendly, applicable to experimental design and robust in terms of experimental noise and exchange flux magnitude. Collectively, we predict that SUMOFLUXs properties realistically pave the way to high-throughput flux analyses.'),
(88015, 2016, 'plos', 'A Monte Carlo Study of Knots in Long Double-Stranded DNA Chains', 'Rieger, Florian C|Virnau, Peter', 'Institute of Physics, Johannes Gutenberg University Mainz, Mainz, Germany.|Institute of Physics, Johannes Gutenberg University Mainz, Mainz, Germany.', 'Germany|Germany', 11, 'Computational Biology|DNA|Molecular Dynamics Simulation|Monte Carlo Method|Nanopores|Nucleic Acid Conformation', 'Journal Article', '10.1371/journal.pcbi.1005029', '27631891', 'We determine knotting probabilities and typical sizes of knots in double-stranded DNA for chains of up to half a million base pairs with computer simulations of a coarse-grained bead-stick model: Single trefoil knots and composite knots which include at least one trefoil as a prime factor are shown to be common in DNA chains exceeding 250,000 base pairs, assuming physiologically relevant salt conditions. The analysis is motivated by the emergence of DNA nanopore sequencing technology, as knots are a potential cause of erroneous nucleotide reads in nanopore sequencing devices and may severely limit read lengths in the foreseeable future. Even though our coarse-grained model is only based on experimental knotting probabilities of short DNA strands, it reproduces the correct persistence length of DNA. This indicates that knots are not only a fine gauge for structural properties, but a promising tool for the design of polymer models.'),
(88016, 2016, 'plos', 'Systems Biology-Based Investigation of Cellular Antiviral Drug Targets Identified by Gene-Trap Insertional Mutagenesis', 'Cheng, Feixiong|Murray, James L|Zhao, Junfei|Sheng, Jinsong|Zhao, Zhongming|Rubin, Donald H', 'State Key Laboratory of Biotherapy/Collaborative Innovation Center for Biotherapy, West China Hospital, West China Medical School, Sichuan University, Chengdu 610041, Sichuan, China.|Zirus, Incorporated, Buford, Georgia, United States of America.|Center for Precision Health, School of Biomedical Informatics, The University of Texas Health Science Center at Houston, Houston, Texas, United States of America.|Division of Infectious Disease, Department of Medicine, Vanderbilt University School of Medicine, Nashville, Tennessee, United States of America.|Department of Biomedical Informatics, Vanderbilt University School of Medicine, Nashville, Tennessee, United States of America.|Division of Infectious Disease, Department of Medicine, Vanderbilt University School of Medicine, Nashville, Tennessee, United States of America.', 'China|Georgia|United States|United States|United States|United States', 0, 'Animals|Antiviral Agents|Cell Cycle|Cell Line|Dogs|Drug Delivery Systems|Drug Discovery|Hep G2 Cells|Host-Pathogen Interactions|Humans|Madin Darby Canine Kidney Cells|Mutagenesis, Insertional|Protein Interaction Maps|Systems Biology|Virus Replication', 'Journal Article', '10.1371/journal.pcbi.1005074', '27632082', 'Viruses require host cellular factors for successful replication. A comprehensive systems-level investigation of the virus-host interactome is critical for understanding the roles of host factors with the end goal of discovering new druggable antiviral targets. Gene-trap insertional mutagenesis is a high-throughput forward genetics approach to randomly disrupt (trap) host genes and discover host genes that are essential for viral replication, but not for host cell survival. In this study, we used libraries of randomly mutagenized cells to discover cellular genes that are essential for the replication of 10 distinct cytotoxic mammalian viruses, 1 gram-negative bacterium, and 5 toxins. We herein reported 712 candidate cellular genes, characterizing distinct topological network and evolutionary signatures, and occupying central hubs in the human interactome. Cell cycle phase-specific network analysis showed that host cell cycle programs played critical roles during viral replication (e.g. MYC and TAF4 regulating G0/1 phase). Moreover, the viral perturbation of host cellular networks reflected disease etiology in that host genes (e.g. CTCF, RHOA, and CDKN1B) identified were frequently essential and significantly associated with Mendelian and orphan diseases, or somatic mutations in cancer. Computational drug repositioning framework via incorporating drug-gene signatures from the Connectivity Map into the virus-host interactome identified 110 putative druggable antiviral targets and prioritized several existing drugs (e.g. ajmaline) that may be potential for antiviral indication (e.g. anti-Ebola). In summary, this work provides a powerful methodology with a tight integration of gene-trap insertional mutagenesis testing and systems biology to identify new antiviral targets and drugs for the development of broadly acting and targeted clinical antiviral therapeutics.'),
(88017, 2016, 'plos', 'A Computational Model of Hepatic Energy Metabolism: Understanding Zonated Damage and Steatosis in NAFLD', 'Ashworth, William B|Davies, Nathan A|Bogle, I David L', 'Institute of Liver and Digestive Health, University College London, London, United Kingdom.|Institute of Liver and Digestive Health, University College London, London, United Kingdom.|Department of Chemical Engineering, University College London, London, United Kingdom.', 'United Kingdom|United Kingdom|United Kingdom', 17, 'Animals|Computational Biology|Energy Metabolism|Glucose|Humans|Insulin Resistance|Lipid Metabolism|Liver|Models, Biological|Non-alcoholic Fatty Liver Disease', 'Journal Article', '10.1371/journal.pcbi.1005105', '27632189', 'In non-alcoholic fatty liver disease (NAFLD), lipid build-up and the resulting damage is known to occur more severely in pericentral cells. Due to the complexity of studying individual regions of the sinusoid, the causes of this zone specificity and its implications on treatment are largely ignored. In this study, a computational model of liver glucose and lipid metabolism is presented which treats the sinusoid as the repeating unit of the liver rather than the single hepatocyte. This allows for inclusion of zonated enzyme expression by splitting the sinusoid into periportal to pericentral compartments. By simulating insulin resistance (IR) and high intake diets leading to the development of steatosis in the model, we identify key differences between periportal and pericentral cells accounting for higher susceptibility to pericentral steatosis. Secondly, variation between individuals is seen in both susceptibility to steatosis and in its development across the sinusoid. Around 25% of obese individuals do not show excess liver fat, whilst 16% of lean individuals develop NAFLD. Furthermore, whilst pericentral cells tend to show higher lipid levels, variation is seen in the predominant location of steatosis from pericentral to pan-sinusoidal or azonal. Sensitivity analysis was used to identify the processes which have the largest effect on both total hepatic triglyceride levels and on the sinusoidal location of steatosis. As is seen in vivo, steatosis occurs when simulating IR in the model, predominantly due to increased uptake, along with an increase in de novo lipogenesis. Additionally, concentrations of glucose intermediates including glycerol-3-phosphate increased when simulating IR due to inhibited glycogen synthesis. Several differences between zones contributed to a higher susceptibility to steatosis in pericentral cells in the model simulations. Firstly, the periportal zonation of both glycogen synthase and the oxidative phosphorylation enzymes meant that the build-up of glucose intermediates was less severe in the periportal hepatocyte compartments. Secondly, the periportal zonation of the enzymes mediating xcexb2-oxidation and oxidative phosphorylation resulted in excess fats being metabolised more rapidly in the periportal hepatocyte compartments. Finally, the pericentral expression of de novo lipogenesis contributed to pericentral steatosis when additionally simulating the increase in sterol-regulatory element binding protein 1c (SREBP-1c) seen in NAFLD patients in vivo. The hepatic triglyceride concentration was predicted to be most sensitive to inter-individual variation in the activity of enzymes which, either directly or indirectly, determine the rate of free fatty acid (FFA) oxidation. The concentration was most strongly dependent on the rate constants for xcexb2-oxidation and oxidative phosphorylation. It also showed moderate sensitivity to the rate constants for processes which alter the allosteric inhibition of xcexb2-oxidation by acetyl-CoA. The predominant sinusoidal location of steatosis meanwhile was most sensitive variations in the zonation of proteins mediating FFA uptake or triglyceride release as very low density lipoproteins (VLDL). Neither the total hepatic concentration nor the location of steatosis showed strong sensitivity to variations in the lipogenic rate constants.'),
(88018, 2016, 'plos', 'Estimating Copy Number and Allelic Variation at the Immunoglobulin Heavy Chain Locus Using Short Reads', 'Luo, Shishi|Yu, Jane A|Song, Yun S', 'Computer Science Division, University of California, Berkeley, Berkeley, California, United States of America.|Computer Science Division, University of California, Berkeley, Berkeley, California, United States of America.|Computer Science Division, University of California, Berkeley, Berkeley, California, United States of America.', 'United States|United States|United States', 0, 'Cluster Analysis|Computational Biology|DNA Copy Number Variations|Databases, Genetic|Genetic Variation|Haplotypes|Humans|Immunoglobulin Heavy Chains|Immunoglobulin Variable Region|Sequence Alignment|Sequence Analysis, DNA', 'Journal Article', '10.1371/journal.pcbi.1005117', '27632220', 'The study of genomic regions that contain gene copies and structural variation is a major challenge in modern genomics. Unlike variation involving single nucleotide changes, data on the variation of copy number is difficult to collect and few tools exist for analyzing the variation between individuals. The immunoglobulin heavy variable (IGHV) locus, which plays an integral role in the adaptive immune response, is an example of a complex genomic region that varies in gene copy number. Lack of standard methods to genotype this region prevents it from being included in association studies and is holding back the growing field of antibody repertoire analysis. Here we develop a method that takes short reads from high-throughput sequencing and outputs a genetic profile of the IGHV locus with the read coverage depth and a putative nucleotide sequence for each operationally defined gene cluster. Our operationally defined gene clusters aim to address a major challenge in studying the IGHV locus: the high sequence similarity between gene segments in different genomic locations. Tests on simulated data demonstrate that our approach can accurately determine the presence or absence of a gene cluster from reads as short as 70 bp. More detailed resolution on the copy number of gene clusters can be obtained from read coverage depth using longer reads (e.g., xe2x89xa5 100 bp). Detail at the nucleotide resolution of single copy genes (genes present in one copy per haplotype) can be determined with 250 bp reads. For IGHV genes with more than one copy, accurate nucleotide-resolution reconstruction is currently beyond the means of our approach. When applied to a family of European ancestry, our pipeline outputs genotypes that are consistent with the family pedigree, confirms existing multigene variants and suggests new copy number variants. This study paves the way for analyzing population-level patterns of variation in IGHV gene clusters in larger diverse datasets and for quantitatively handling regions of copy number variation in other structurally varying and complex loci.'),
(88019, 2016, 'plos', 'How to Distinguish Conformational Selection and Induced Fit Based on Chemical Relaxation Rates', 'Paul, Fabian|Weikl, Thomas R', 'Max Planck Institute of Colloids and Interfaces, Department of Theory and Bio-Systems, Potsdam, Germany.|Max Planck Institute of Colloids and Interfaces, Department of Theory and Bio-Systems, Potsdam, Germany.', 'Germany|Germany', 16, 'Computational Biology|Models, Molecular|Protein Binding|Protein Conformation|Proteins', 'Journal Article', '10.1371/journal.pcbi.1005067', '27636092', 'Protein binding often involves conformational changes. Important questions are whether a conformational change occurs prior to a binding event (conformational selection) or after a binding event (induced fit), and how conformational transition rates can be obtained from experiments. In this article, we present general results for the chemical relaxation rates of conformational-selection and induced-fit binding processes that hold for all concentrations of proteins and ligands and, thus, go beyond the standard pseudo-first-order approximation of large ligand concentration. These results allow to distinguish conformational-selection from induced-fit processes-also in cases in which such a distinction is not possible under pseudo-first-order conditions-and to extract conformational transition rates of proteins from chemical relaxation data.'),
(88020, 2016, 'plos', 'Gamma Synchronization Influences Map Formation Time in a Topological Model of Spatial Learning', 'Basso, Edward|Arai, Mamiko|Dabaghian, Yuri', 'Department of Physics, Rice University, Houston, Texas, United States of America.|Department of Mathematics, Tokyo Womens Christian University, 2-6-1 Zempukuji, Suginami-ku, Tokyo, Japan.|Jan and Dan Duncan Neurological Research Institute, Baylor College of Medicine, Houston, Texas, United States of America.', 'United States|Japan|United States', 8, 'Animals|Computational Biology|Gamma Rhythm|Hippocampus|Models, Neurological|Rats|Spatial Learning', 'Journal Article', '10.1371/journal.pcbi.1005114', '27636199', 'The mammalian hippocampus plays a crucial role in producing a cognitive map of space-an internalized representation of the animals environment. We have previously shown that it is possible to model this map formation using a topological framework, in which information about the environment is transmitted through the temporal organization of neuronal spiking activity, particularly those occasions in which the firing of different place cells overlaps. In this paper, we discuss how gamma rhythm, one of the main components of the extracellular electrical field potential affects the efficiency of place cell map formation. Using methods of algebraic topology and the maximal entropy principle, we demonstrate that gamma modulation synchronizes the spiking of dynamical cell assemblies, which enables learning a spatial map at faster timescales.'),
(88021, 2016, 'plos', 'M-Track: A New Software for Automated Detection of Grooming Trajectories in Mice', 'Reeves, Sheldon L|Fleming, Kelsey E|Zhang, Lin|Scimemi, Annalisa', 'Department of Computer Science, State University of New York Polytechnic Institute, Utica, New York, United States of America.|Department of Biology, State University of New York Albany, Albany, New York, United States of America.|Department of Computer Science, State University of New York Albany, Albany, New York, United States of America.|Department of Biology, State University of New York Albany, Albany, New York, United States of America.', 'United States|United States|United States|United States', 0, 'Animals|Behavior, Animal|Computational Biology|Female|Grooming|Image Processing, Computer-Assisted|Male|Mice|Mice, Inbred C57BL|Movement|Software|Video Recording', 'Journal Article', '10.1371/journal.pcbi.1005115', '27636358', 'Grooming is a complex and robust innate behavior, commonly performed by most vertebrate species. In mice, grooming consists of a series of stereotyped patterned strokes, performed along the rostro-caudal axis of the body. The frequency and duration of each grooming episode is sensitive to changes in stress levels, social interactions and pharmacological manipulations, and is therefore used in behavioral studies to gain insights into the function of brain regions that control movement execution and anxiety. Traditional approaches to analyze grooming rely on manually scoring the time of onset and duration of each grooming episode, and are often performed on grooming episodes triggered by stress exposure, which may not be entirely representative of spontaneous grooming in freely-behaving mice. This type of analysis is time-consuming and provides limited information about finer aspects of grooming behaviors, which are important to understand movement stereotypy and bilateral coordination in mice. Currently available commercial and freeware video-tracking software allow automated tracking of the whole body of a mouse or of its head and tail, not of individual forepaws. Here we describe a simple experimental set-up and a novel open-source code, named M-Track, for simultaneously tracking the movement of individual forepaws during spontaneous grooming in multiple freely-behaving mice. This toolbox provides a simple platform to perform trajectory analysis of forepaw movement during distinct grooming episodes. By using M-track we show that, in C57BL/6 wild type mice, the speed and bilateral coordination of the left and right forepaws remain unaltered during the execution of distinct grooming episodes. Stress exposure induces a profound increase in the length of the forepaw grooming trajectories. M-Track provides a valuable and user-friendly interface to streamline the analysis of spontaneous grooming in biomedical research studies.'),
(88022, 2016, 'plos', 'Error Correction and the Structure of Inter-Trial Fluctuations in a Redundant Movement Task', 'John, Joby|Dingwell, Jonathan B|Cusumano, Joseph P', 'Department of Engineering Science and Mechanics, The Pennsylvania State University, University Park, Pennsylvania, United States of America.|Department of Kinesiology and Health Education, The University of Texas at Austin, Austin, Texas, United States of America.|Department of Engineering Science and Mechanics, The Pennsylvania State University, University Park, Pennsylvania, United States of America.', 'United States|United States|United States', 0, 'Adult|Cluster Analysis|Computational Biology|Humans|Linear Models|Male|Movement|Observer Variation|Psychomotor Performance|Task Performance and Analysis', 'Journal Article', '10.1371/journal.pcbi.1005118', '27643895', 'We study inter-trial movement fluctuations exhibited by human participants during the repeated execution of a virtual shuffleboard task. Focusing on skilled performance, theoretical analysis of a previously-developed general model of inter-trial error correction is used to predict the temporal and geometric structure of variability near a goal equivalent manifold (GEM). The theory also predicts that the goal-level error scales linearly with intrinsic body-level noise via the total body-goal sensitivity, a new derived quantity that illustrates how task performance arises from the interaction of active error correction and passive sensitivity properties along the GEM. Linear models estimated from observed fluctuations, together with a novel application of bootstrapping to the estimation of dynamical and correlation properties of the inter-trial dynamics, are used to experimentally confirm all predictions, thus validating our model. In addition, we show that, unlike static variability analyses, our dynamical approach yields results that are independent of the coordinates used to measure task execution and, in so doing, provides a new set of task coordinates that are intrinsic to the error-regulation process itself.'),
(88023, 2016, 'plos', 'Separating Timing, Movement Conditions and Individual Differences in the Analysis of Human Movement', 'Raket, Lars Lau|Grimme, Britta|Schöner, Gregor|Igel, Christian|Markussen, Bo', 'Department of Mathematical Sciences, University of Copenhagen, Copenhagen, Denmark.|Institut für Neuroinformatik, Ruhr-Universität Bochum, Bochum, Germany.|Institut für Neuroinformatik, Ruhr-Universität Bochum, Bochum, Germany.|Department of Computer Science, University of Copenhagen, Copenhagen, Denmark.|Department of Mathematical Sciences, University of Copenhagen, Copenhagen, Denmark.', 'Denmark|Germany|Germany|Denmark|Denmark', 6, '-', 'Journal Article', '10.1371/journal.pcbi.1005092', '27657545', 'A central task in the analysis of human movement behavior is to determine systematic patterns and differences across experimental conditions, participants and repetitions. This is possible because human movement is highly regular, being constrained by invariance principles. Movement timing and movement path, in particular, are linked through scaling laws. Separating variations of movement timing from the spatial variations of movements is a well-known challenge that is addressed in current approaches only through forms of preprocessing that bias analysis. Here we propose a novel nonlinear mixed-effects model for analyzing temporally continuous signals that contain systematic effects in both timing and path. Identifiability issues of path relative to timing are overcome by using maximum likelihood estimation in which the most likely separation of space and time is chosen given the variation found in data. The model is applied to analyze experimental data of human arm movements in which participants move a hand-held object to a target location while avoiding an obstacle. The model is used to classify movement data according to participant. Comparison to alternative approaches establishes nonlinear mixed-effects models as viable alternatives to conventional analysis frameworks. The model is then combined with a novel factor-analysis model that estimates the low-dimensional subspace within which movements vary when the task demands vary. Our framework enables us to visualize different dimensions of movement variation and to test hypotheses about the effect of obstacle placement and height on the movement path. We demonstrate that the approach can be used to uncover new properties of human movement.'),
(88024, 2016, 'plos', 'In Silico Oncology: Quantification of the In Vivo Antitumor Efficacy of Cisplatin-Based Doublet Therapy in Non-Small Cell Lung Cancer (NSCLC) through a Multiscale Mechanistic Model', 'Kolokotroni, Eleni|Dionysiou, Dimitra|Veith, Christian|Kim, Yoo-Jin|Sabczynski, Jörg|Franz, Astrid|Grgic, Aleksandar|Palm, Jan|Bohle, Rainer M|Stamatakos, Georgios', 'In Silico Oncology and In Silico Medicine Group, Institute of Communication and Computer Systems, National Technical University of Athens, Athens, Greece.|In Silico Oncology and In Silico Medicine Group, Institute of Communication and Computer Systems, National Technical University of Athens, Athens, Greece.|Institute of Pathology, University of Saarland, Homburg (Saar), Germany.|Institute of Pathology, University of Saarland, Homburg (Saar), Germany.|Philips Research, Hamburg, Germany.|Philips Research, Hamburg, Germany.|Department of Nuclear Medicine, University of Saarland, Homburg (Saar), Germany.|Department of Radiotherapy and Radiation Oncology, University of Saarland, Homburg (Saar), Germany.|Institute of Pathology, University of Saarland, Homburg (Saar), Germany.|In Silico Oncology and In Silico Medicine Group, Institute of Communication and Computer Systems, National Technical University of Athens, Athens, Greece.', 'Greece|Greece|Germany|Germany|Germany|Germany|Germany|Germany|Germany|Greece', 0, '-', 'Journal Article', '10.1371/journal.pcbi.1005093', '27657742', 'The 5-year survival of non-small cell lung cancer patients can be as low as 1% in advanced stages. For patients with resectable disease, the successful choice of preoperative chemotherapy is critical to eliminate micrometastasis and improve operability. In silico experimentations can suggest the optimal treatment protocol for each patient based on their own multiscale data. A determinant for reliable predictions is the a priori estimation of the drugs cytotoxic efficacy on cancer cells for a given treatment. In the present work a mechanistic model of cancer response to treatment is applied for the estimation of a plausible value range of the cell killing efficacy of various cisplatin-based doublet regimens. Among others, the model incorporates the cancer related mechanism of uncontrolled proliferation, population heterogeneity, hypoxia and treatment resistance. The methodology is based on the provision of tumor volumetric data at two time points, before and after or during treatment. It takes into account the effect of tumor microenvironment and cell repopulation on treatment outcome. A thorough sensitivity analysis based on one-factor-at-a-time and latin hypercube sampling/partial rank correlation coefficient approaches has established the volume growth rate and the growth fraction at diagnosis as key features for more accurate estimates. The methodology is applied on the retrospective data of thirteen patients with non-small cell lung cancer who received cisplatin in combination with gemcitabine, vinorelbine or docetaxel in the neoadjuvant context. The selection of model input values has been guided by a comprehensive literature survey on cancer-specific proliferation kinetics. The latin hypercube sampling has been recruited to compensate for patient-specific uncertainties. Concluding, the present work provides a quantitative framework for the estimation of the in-vivo cell-killing ability of various chemotherapies. Correlation studies of such estimates with the molecular profile of patients could serve as a basis for reliable personalized predictions.'),
(88025, 2016, 'plos', 'Forecasting Human African Trypanosomiasis Prevalences from Population Screening Data Using Continuous Time Models', 'de Vries, Harwin|Wagelmans, Albert P M|Hasker, Epco|Lumbala, Crispin|Lutumba, Pascal|de Vlas, Sake J|Klundert, Joris van de', 'Econometric Institute, Erasmus University Rotterdam, Rotterdam, The Netherlands.|Econometric Institute, Erasmus University Rotterdam, Rotterdam, The Netherlands.|Department of Public Health, Institute Of Tropical Medicine, Antwerp, Belgium.|Programme National de Lutte contre la Trypanosomiase Humaine Africain (PNLTHA), Kinshasa, Democratic Republic of Congo.|University of Kinshasa, Kinshasa, Democratic Republic of Congo.|Department of Public Health, Erasmus MC, University Medical Center Rotterdam, Rotterdam, The Netherlands.|Institute of Health Policy and Management, Erasmus University Rotterdam, Rotterdam, The Netherlands.', 'Netherlands|Netherlands|Belgium|Congo|Congo|Netherlands|Netherlands', 6, '-', 'Journal Article', '10.1371/journal.pcbi.1005103', '27657937', 'To eliminate and eradicate gambiense human African trypanosomiasis (HAT), maximizing the effectiveness of active case finding is of key importance. The progression of the epidemic is largely influenced by the planning of these operations. This paper introduces and analyzes five models for predicting HAT prevalence in a given village based on past observed prevalence levels and past screening activities in that village. Based on the quality of prevalence level predictions in 143 villages in Kwamouth (DRC), and based on the theoretical foundation underlying the models, we consider variants of the Logistic Model-a model inspired by the SIS epidemic model-to be most suitable for predicting HAT prevalence levels. Furthermore, we demonstrate the applicability of this model to predict the effects of planning policies for screening operations. Our analysis yields an analytical expression for the screening frequency required to reach eradication (zero prevalence) and a simple approach for determining the frequency required to reach elimination within a given time frame (one case per 10000). Furthermore, the model predictions suggest that annual screening is only expected to lead to eradication if at least half of the cases are detected during the screening rounds. This paper extends knowledge on control strategies for HAT and serves as a basis for further modeling and optimization studies.'),
(88026, 2016, 'plos', 'Immersed Boundary Models for Quantifying Flow-Induced Mechanical Stimuli on Stem Cells Seeded on 3D Scaffolds in Perfusion Bioreactors', 'Guyot, Yann|Smeets, Bart|Odenthal, Tim|Subramani, Ramesh|Luyten, Frank P|Ramon, Herman|Papantoniou, Ioannis|Geris, Liesbet', 'Prometheus, Division of Skeletal Tissue Engineering, KU Leuven, Leuven, Belgium.|Prometheus, Division of Skeletal Tissue Engineering, KU Leuven, Leuven, Belgium.|Division of Mechatronics, Biostatistics and Sensors (MeBioS), Leuven, Belgium.|Division of Mechatronics, Biostatistics and Sensors (MeBioS), Leuven, Belgium.|Prometheus, Division of Skeletal Tissue Engineering, KU Leuven, Leuven, Belgium.|Division of Mechatronics, Biostatistics and Sensors (MeBioS), Leuven, Belgium.|Prometheus, Division of Skeletal Tissue Engineering, KU Leuven, Leuven, Belgium.|Prometheus, Division of Skeletal Tissue Engineering, KU Leuven, Leuven, Belgium.', 'Belgium|Belgium|Belgium|Belgium|Belgium|Belgium|Belgium|Belgium', 15, '-', 'Journal Article', '10.1371/journal.pcbi.1005108', '27658116', 'Perfusion bioreactors regulate flow conditions in order to provide cells with oxygen, nutrients and flow-associated mechanical stimuli. Locally, these flow conditions can vary depending on the scaffold geometry, cellular confluency and amount of extra cellular matrix deposition. In this study, a novel application of the immersed boundary method was introduced in order to represent a detailed deformable cell attached to a 3D scaffold inside a perfusion bioreactor and exposed to microscopic flow. The immersed boundary model permits the prediction of mechanical effects of the local flow conditions on the cell. Incorporating stiffness values measured with atomic force microscopy and micro-flow boundary conditions obtained from computational fluid dynamics simulations on the entire scaffold, we compared cell deformation, cortical tension, normal and shear pressure between different cell shapes and locations. We observed a large effect of the precise cell location on the local shear stress and we predicted flow-induced cortical tensions in the order of 5 pN/xcexbcm, at the lower end of the range reported in literature. The proposed method provides an interesting tool to study perfusion bioreactors processes down to the level of the individual cells micro-environment, which can further aid in the achievement of robust bioprocess control for regenerative medicine applications.');
