INSERT INTO `papers` (`id`, `ano`, `journal`, `titulo`, `autores`, `afiliacao`, `pais`, `citacoes`, `palavra_chave`, `categorias`, `doi`, `pubmed`, `abstract`) VALUES
(86179, 2013, 'plos', 'Antimicrobial peptides design by evolutionary multiobjective optimization', 'Maccari, Giuseppe|Di Luca, Mariagrazia|Nifosí, Riccardo|Cardarelli, Francesco|Signore, Giovanni|Boccardi, Claudia|Bifone, Angelo', 'Center for Nanotechnology Innovation @NEST, Istituto Italiano di Tecnologia, Pisa, Italy.|Center for Nanotechnology Innovation @NEST, Istituto Italiano di Tecnologia, Pisa, Italy.|Center for Nanotechnology Innovation @NEST, Istituto Italiano di Tecnologia, Pisa, Italy.|Center for Nanotechnology Innovation @NEST, Istituto Italiano di Tecnologia, Pisa, Italy.|Center for Nanotechnology Innovation @NEST, Istituto Italiano di Tecnologia, Pisa, Italy.|Center for Nanotechnology Innovation @NEST, Istituto Italiano di Tecnologia, Pisa, Italy.|Center for Nanotechnology Innovation @NEST, Istituto Italiano di Tecnologia, Pisa, Italy.', 'Italy|Italy|Italy|Italy|Italy|Italy|Italy', 0, 'Anti-Infective Agents|Drug Design|Microscopy, Confocal|Molecular Dynamics Simulation|Peptides|Quantitative Structure-Activity Relationship', 'Journal Article', '10.1371/journal.pcbi.1003212', '24039565', 'Antimicrobial peptides (AMPs) are an abundant and wide class of molecules produced by many tissues and cell types in a variety of mammals, plant and animal species. Linear alpha-helical antimicrobial peptides are among the most widespread membrane-disruptive AMPs in nature, representing a particularly successful structural arrangement in innate defense. Recently, AMPs have received increasing attention as potential therapeutic agents, owing to their broad activity spectrum and their reduced tendency to induce resistance. The introduction of non-natural amino acids will be a key requisite in order to contrast host resistance and increase compounds life. In this work, the possibility to design novel AMP sequences with non-natural amino acids was achieved through a flexible computational approach, based on chemophysical profiles of peptide sequences. Quantitative structure-activity relationship (QSAR) descriptors were employed to code each peptide and train two statistical models in order to account for structural and functional properties of alpha-helical amphipathic AMPs. These models were then used as fitness functions for a multi-objective evolutional algorithm, together with a set of constraints for the design of a series of candidate AMPs. Two ab-initio natural peptides were synthesized and experimentally validated for antimicrobial activity, together with a series of control peptides. Furthermore, a well-known Cecropin-Mellitin alpha helical antimicrobial hybrid (CM18) was optimized by shortening its amino acid sequence while maintaining its activity and a peptide with non-natural amino acids was designed and tested, demonstrating the higher activity achievable with artificial residues. '),
(86180, 2013, 'plos', 'Mammalian rest/activity patterns explained by physiologically based modeling', 'Phillips, A J K|Fulcher, B D|Robinson, P A|Klerman, E B', 'Division of Sleep Medicine, Brigham & Womens Hospital, Harvard Medical School, Boston, Massachusetts, United States of America.|Division of Sleep Medicine, Brigham & Womens Hospital, Harvard Medical School, Boston, Massachusetts, United States of America.|Division of Sleep Medicine, Brigham & Womens Hospital, Harvard Medical School, Boston, Massachusetts, United States of America.|Division of Sleep Medicine, Brigham & Womens Hospital, Harvard Medical School, Boston, Massachusetts, United States of America.', 'United States|United States|United States|United States', 14, 'Animals|Circadian Rhythm|Models, Biological|Motor Activity|Suprachiasmatic Nucleus', 'Journal Article', '10.1371/journal.pcbi.1003213', '24039566', 'Circadian rhythms are fundamental to life. In mammals, these rhythms are generated by pacemaker neurons in the suprachiasmatic nucleus (SCN) of the hypothalamus. The SCN is remarkably consistent in structure and function between species, yet mammalian rest/activity patterns are extremely diverse, including diurnal, nocturnal, and crepuscular behaviors. Two mechanisms have been proposed to account for this diversity: (i) modulation of SCN output by downstream nuclei, and (ii) direct effects of light on activity. These two mechanisms are difficult to disentangle experimentally and their respective roles remain unknown. To address this, we developed a computational model to simulate the two mechanisms and their influence on temporal niche. In our model, SCN output is relayed via the subparaventricular zone (SPZ) to the dorsomedial hypothalamus (DMH), and thence to ventrolateral preoptic nuclei (VLPO) and lateral hypothalamus (LHA). Using this model, we generated rich phenotypes that closely resemble experimental data. Modulation of SCN output at the SPZ was found to generate a full spectrum of diurnal-to-nocturnal phenotypes. Intriguingly, we also uncovered a novel mechanism for crepuscular behavior: if DMH/VLPO and DMH/LHA projections act cooperatively, daily activity is unimodal, but if they act competitively, activity can become bimodal. In addition, we successfully reproduced diurnal/nocturnal switching in the rodent Octodon degu using coordinated inversions in both masking and circadian modulation. Finally, the model correctly predicted the SCN lesion phenotype in squirrel monkeys: loss of circadian rhythmicity and emergence of xe2x88xbc4-h sleep/wake cycles. In capturing these diverse phenotypes, the model provides a powerful new framework for understanding rest/activity patterns and relating them to underlying physiology. Given the ubiquitous effects of temporal organization on all aspects of animal behavior and physiology, this study sheds light on the physiological changes required to orchestrate adaptation to various temporal niches. '),
(86181, 2013, 'plos', 'The next generation of transcription factor binding site prediction', 'Mathelier, Anthony|Wasserman, Wyeth W', 'Centre for Molecular Medicine and Therapeutics at the Child and Family Research Institute, Department of Medical Genetics, University of British Columbia, Vancouver, British Columbia, Canada.|Centre for Molecular Medicine and Therapeutics at the Child and Family Research Institute, Department of Medical Genetics, University of British Columbia, Vancouver, British Columbia, Canada.', 'Canada|Canada', 92, 'Binding Sites|Chromatin Immunoprecipitation|DNA|Probability|Transcription Factors', 'Journal Article', '10.1371/journal.pcbi.1003214', '24039567', 'Finding where transcription factors (TFs) bind to the DNA is of key importance to decipher gene regulation at a transcriptional level. Classically, computational prediction of TF binding sites (TFBSs) is based on basic position weight matrices (PWMs) which quantitatively score binding motifs based on the observed nucleotide patterns in a set of TFBSs for the corresponding TF. Such models make the strong assumption that each nucleotide participates independently in the corresponding DNA-protein interaction and do not account for flexible length motifs. We introduce transcription factor flexible models (TFFMs) to represent TF binding properties. Based on hidden Markov models, TFFMs are flexible, and can model both position interdependence within TFBSs and variable length motifs within a single dedicated framework. The availability of thousands of experimentally validated DNA-TF interaction sequences from ChIP-seq allows for the generation of models that perform as well as PWMs for stereotypical TFs and can improve performance for TFs with flexible binding characteristics. We present a new graphical representation of the motifs that convey properties of position interdependence. TFFMs have been assessed on ChIP-seq data sets coming from the ENCODE project, revealing that they can perform better than both PWMs and the dinucleotide weight matrix extension in discriminating ChIP-seq from background sequences. Under the assumption that ChIP-seq signal values are correlated with the affinity of the TF-DNA binding, we find that TFFM scores correlate with ChIP-seq peak signals. Moreover, using available TF-DNA affinity measurements for the Max TF, we demonstrate that TFFMs constructed from ChIP-seq data correlate with published experimentally measured DNA-binding affinities. Finally, TFFMs allow for the straightforward computation of an integrated TF occupancy score across a sequence. These results demonstrate the capacity of TFFMs to accurately model DNA-protein interactions, while providing a single unified framework suitable for the next generation of TFBS prediction. '),
(86182, 2013, 'plos', 'From cellular characteristics to disease diagnosis: uncovering phenotypes with supercells', 'Candia, Julián|Maunu, Ryan|Driscoll, Meghan|Biancotto, Angélique|Dagur, Pradeep|McCoy, J Philip|Sen, H Nida|Wei, Lai|Maritan, Amos|Cao, Kan|Nussenblatt, Robert B|Banavar, Jayanth R|Losert, Wolfgang', 'Department of Physics, University of Maryland, College Park, Maryland, United States of America , School of Medicine, University of Maryland, Baltimore, Maryland, United States of America , IFLYSIB and CONICET, University of La Plata, La Plata, Argentina.candia@umd.edu          .|Department of Physics, University of Maryland, College Park, Maryland, United States of America.|Department of Physics, University of Maryland, College Park, Maryland, United States of America.|Center for Human Immunology, Autoimmunity and Inflammation, National Institutes of Health, Bethesda, Maryland, United States of America, Hematology Branch, National Heart Lung and Blood Institute, National Institutes of Health, Bethesda, Maryland, United States of America.|Hematology Branch, National Heart Lung and Blood Institute, National Institutes of Health, Bethesda, Maryland, United States of America.|Center for Human Immunology, Autoimmunity and Inflammation, National Institutes of Health, Bethesda, Maryland, United States of America,, Hematology Branch, National Heart Lung and Blood Institute, National Institutes of Health, Bethesda, Maryland, United States of America.|Laboratory of Immunology, National Eye Institute, National Institutes of Health, Bethesda, Maryland, United States of America.|Laboratory of Immunology, National Eye Institute, National Institutes of Health, Bethesda, Maryland, United States of America.|Dipartimento di Fisica “G. Galilei,” Università di Padova, Consorzio Nazionale Interuniversitario per le Scienze Fisiche della Materia and Istituto Nazionale di Fisica Nucleare, Padua, Italy.|Department of Cell Biology and Molecular Genetics, University of Maryland, College Park, Maryland, United States of America.|Laboratory of Immunology, National Eye Institute, National Institutes of Health, Bethesda, Maryland, United States of America.|Department of Physics, University of Maryland, College Park, Maryland, United States of America.|Department of Physics, University of Maryland, College Park, Maryland, United States of America.', 'Argentina|United States|United States|United States|United States|United States|United States|United', 23, 'Artificial Intelligence|Diagnosis|Humans', 'Journal Article', '10.1371/journal.pcbi.1003215', '24039568', 'Cell heterogeneity and the inherent complexity due to the interplay of multiple molecular processes within the cell pose difficult challenges for current single-cell biology. We introduce an approach that identifies a disease phenotype from multiparameter single-cell measurements, which is based on the concept of supercell statistics, a single-cell-based averaging procedure followed by a machine learning classification scheme. We are able to assess the optimal tradeoff between the number of single cells averaged and the number of measurements needed to capture phenotypic differences between healthy and diseased patients, as well as between different diseases that are difficult to diagnose otherwise. We apply our approach to two kinds of single-cell datasets, addressing the diagnosis of a premature aging disorder using images of cell nuclei, as well as the phenotypes of two non-infectious uveitides (the ocular manifestations of Behçets disease and sarcoidosis) based on multicolor flow cytometry. In the former case, one nuclear shape measurement taken over a group of 30 cells is sufficient to classify samples as healthy or diseased, in agreement with usual laboratory practice. In the latter, our method is able to identify a minimal set of 5 markers that accurately predict Behçets disease and sarcoidosis. This is the first time that a quantitative phenotypic distinction between these two diseases has been achieved. To obtain this clear phenotypic signature, about one hundred CD8(+) T cells need to be measured. Although the molecular markers identified have been reported to be important players in autoimmune disorders, this is the first report pointing out that CD8(+) T cells can be used to distinguish two systemic inflammatory diseases. Beyond these specific cases, the approach proposed here is applicable to datasets generated by other kinds of state-of-the-art and forthcoming single-cell technologies, such as multidimensional mass cytometry, single-cell gene expression, and single-cell full genome sequencing techniques. '),
(86183, 2013, 'plos', 'Characterizing changes in the rate of protein-protein dissociation upon interface mutation using hotspot energy and organization', 'Agius, Rudi|Torchala, Mieczyslaw|Moal, Iain H|Fernández-Recio, Juan|Bates, Paul A', 'Biomolecular Modelling Laboratory, Cancer Research UK London Research Institute, London, United Kingdom.|Biomolecular Modelling Laboratory, Cancer Research UK London Research Institute, London, United Kingdom.|Biomolecular Modelling Laboratory, Cancer Research UK London Research Institute, London, United Kingdom.|Biomolecular Modelling Laboratory, Cancer Research UK London Research Institute, London, United Kingdom.|Biomolecular Modelling Laboratory, Cancer Research UK London Research Institute, London, United Kingdom.', 'United Kingdom|United Kingdom|United Kingdom|United Kingdom|United Kingdom', 18, 'Alanine|Artificial Intelligence|Kinetics|Mutation|Proteins', 'Journal Article', '10.1371/journal.pcbi.1003216', '24039569', 'Predicting the effects of mutations on the kinetic rate constants of protein-protein interactions is central to both the modeling of complex diseases and the design of effective peptide drug inhibitors. However, while most studies have concentrated on the determination of association rate constants, dissociation rates have received less attention. In this work we take a novel approach by relating the changes in dissociation rates upon mutation to the energetics and architecture of hotspots and hotregions, by performing alanine scans pre- and post-mutation. From these scans, we design a set of descriptors that capture the change in hotspot energy and distribution. The method is benchmarked on 713 kinetically characterized mutations from the SKEMPI database. Our investigations show that, with the use of hotspot descriptors, energies from single-point alanine mutations may be used for the estimation of off-rate mutations to any residue type and also multi-point mutations. A number of machine learning models are built from a combination of molecular and hotspot descriptors, with the best models achieving a Pearsons Correlation Coefficient of 0.79 with experimental off-rates and a Matthews Correlation Coefficient of 0.6 in the detection of rare stabilizing mutations. Using specialized feature selection models we identify descriptors that are highly specific and, conversely, broadly important to predicting the effects of different classes of mutations, interface regions and complexes. Our results also indicate that the distribution of the critical stability regions across protein-protein interfaces is a function of complex size more strongly than interface area. In addition, mutations at the rim are critical for the stability of small complexes, but consistently harder to characterize. The relationship between hotregion size and the dissociation rate is also investigated and, using hotspot descriptors which model cooperative effects within hotregions, we show how the contribution of hotregions of different sizes, changes under different cooperative effects. '),
(86184, 2013, 'plos', 'Learning contrast-invariant cancellation of redundant signals in neural systems', 'Mejias, Jorge F|Marsat, Gary|Bol, Kieran|Maler, Leonard|Longtin, André', 'Department of Physics, University of Ottawa, Ottawa, Ontario, Canada.|Department of Physics, University of Ottawa, Ottawa, Ontario, Canada.|Department of Physics, University of Ottawa, Ottawa, Ontario, Canada.|Department of Physics, University of Ottawa, Ottawa, Ontario, Canada.|Department of Physics, University of Ottawa, Ottawa, Ontario, Canada.', 'Canada|Canada|Canada|Canada|Canada', 12, 'Action Potentials|Animals|Electric Fish|Learning|Models, Biological|Nervous System Physiological Phenomena', 'Journal Article', '10.1371/journal.pcbi.1003180', '24068898', 'Cancellation of redundant information is a highly desirable feature of sensory systems, since it would potentially lead to a more efficient detection of novel information. However, biologically plausible mechanisms responsible for such selective cancellation, and especially those robust to realistic variations in the intensity of the redundant signals, are mostly unknown. In this work, we study, via in vivo experimental recordings and computational models, the behavior of a cerebellar-like circuit in the weakly electric fish which is known to perform cancellation of redundant stimuli. We experimentally observe contrast invariance in the cancellation of spatially and temporally redundant stimuli in such a system. Our model, which incorporates heterogeneously-delayed feedback, bursting dynamics and burst-induced STDP, is in agreement with our in vivo observations. In addition, the model gives insight on the activity of granule cells and parallel fibers involved in the feedback pathway, and provides a strong prediction on the parallel fiber potentiation time scale. Finally, our model predicts the existence of an optimal learning contrast around 15% contrast levels, which are commonly experienced by interacting fish. '),
(86185, 2013, 'plos', 'Predicting odor perceptual similarity from odor structure', 'Snitz, Kobi|Yablonka, Adi|Weiss, Tali|Frumin, Idan|Khan, Rehan M|Sobel, Noam', 'Department of Neurobiology, Weizmann Institute of Science, Rehovot, Israel.|Department of Neurobiology, Weizmann Institute of Science, Rehovot, Israel.|Department of Neurobiology, Weizmann Institute of Science, Rehovot, Israel.|Department of Neurobiology, Weizmann Institute of Science, Rehovot, Israel.|Department of Neurobiology, Weizmann Institute of Science, Rehovot, Israel.|Department of Neurobiology, Weizmann Institute of Science, Rehovot, Israel.', 'Israel|Israel|Israel|Israel|Israel|Israel', 45, 'Brain|Humans|Odorants|Perception|Sensory Thresholds', 'Journal Article', '10.1371/journal.pcbi.1003184', '24068899', 'To understand the brain mechanisms of olfaction we must understand the rules that govern the link between odorant structure and odorant perception. Natural odors are in fact mixtures made of many molecules, and there is currently no method to look at the molecular structure of such odorant-mixtures and predict their smell. In three separate experiments, we asked 139 subjects to rate the pairwise perceptual similarity of 64 odorant-mixtures ranging in size from 4 to 43 mono-molecular components. We then tested alternative models to link odorant-mixture structure to odorant-mixture perceptual similarity. Whereas a model that considered each mono-molecular component of a mixture separately provided a poor prediction of mixture similarity, a model that represented the mixture as a single structural vector provided consistent correlations between predicted and actual perceptual similarity (rxe2x89xa50.49, p<0.001). An optimized version of this model yielded a correlation of rxe2x80x8a=xe2x80x8a0.85 (p<0.001) between predicted and actual mixture similarity. In other words, we developed an algorithm that can look at the molecular structure of two novel odorant-mixtures, and predict their ensuing perceptual similarity. That this goal was attained using a model that considers the mixtures as a single vector is consistent with a synthetic rather than analytical brain processing mechanism in olfaction. '),
(86186, 2013, 'plos', 'Specialization of gene expression during mouse brain development', 'Liscovitch, Noa|Chechik, Gal', 'Gonda Multidisiplinary Brain Research Center, Bar-Ilan University, Ramat Gan, Israel.|Gonda Multidisiplinary Brain Research Center, Bar-Ilan University, Ramat Gan, Israel.', 'Israel|Israel', 22, 'Animals|Brain|Gene Expression Profiling|Humans|In Situ Hybridization|Mice|Transcriptome', 'Comparative Study', '10.1371/journal.pcbi.1003185', '24068900', 'The transcriptome of the brain changes during development, reflecting processes that determine functional specialization of brain regions. We analyzed gene expression, measured using in situ hybridization across the full developing mouse brain, to quantify functional specialization of brain regions. Surprisingly, we found that during the time that the brain becomes anatomically regionalized in early development, transcription specialization actually decreases reaching a low, neurotypic, point around birth. This decrease of specialization is brain-wide, and mainly due to biological processes involved in constructing brain circuitry. Regional specialization rises again during post-natal development. This effect is largely due to specialization of plasticity and neural activity processes. Post-natal specialization is particularly significant in the cerebellum, whose expression signature becomes increasingly different from other brain regions. When comparing mouse and human expression patterns, the cerebellar post-natal specialization is also observed in human, but the regionalization of expression in the human Thalamus and Cortex follows a strikingly different profile than in mouse. '),
(86187, 2013, 'plos', 'Using biological pathway data with paxtools', 'Demir, Emek|Babur, Ozgün|Rodchenkov, Igor|Aksoy, Bülent Arman|Fukuda, Ken I|Gross, Benjamin|Sümer, Onur Selçuk|Bader, Gary D|Sander, Chris', 'Computational Biology Center, Memorial Sloan-Kettering Cancer Center, New York, New York, United States of America.|Computational Biology Center, Memorial Sloan-Kettering Cancer Center, New York, New York, United States of America.|Computational Biology Center, Memorial Sloan-Kettering Cancer Center, New York, New York, United States of America.|Computational Biology Center, Memorial Sloan-Kettering Cancer Center, New York, New York, United States of America.|Computational Biology Center, Memorial Sloan-Kettering Cancer Center, New York, New York, United States of America.|Computational Biology Center, Memorial Sloan-Kettering Cancer Center, New York, New York, United States of America.|Computational Biology Center, Memorial Sloan-Kettering Cancer Center, New York, New York, United States of America.|Computational Biology Center, Memorial Sloan-Kettering Cancer Center, New York, New York, United States of America.|Computational Biology Center, Memorial Sloan-Kettering Cancer Center, New York, New York, United States of America.', 'United States|United States|United States|United States|United States|United States|United States|Un', 33, 'Algorithms|Computational Biology|Programming Languages', 'Journal Article', '10.1371/journal.pcbi.1003194', '24068901', 'A rapidly growing corpus of formal, computable pathway information can be used to answer important biological questions including finding non-trivial connections between cellular processes, identifying significantly altered portions of the cellular network in a disease state and building predictive models that can be used for precision medicine. Due to its complexity and fragmented nature, however, working with pathway data is still difficult. We present Paxtools, a Java library that contains algorithms, software components and converters for biological pathways represented in the standard BioPAX language. Paxtools allows scientists to focus on their scientific problem by removing technical barriers to access and analyse pathway information. Paxtools can run on any platform that has a Java Runtime Environment and was tested on most modern operating systems. Paxtools is open source and is available under the Lesser GNU public license (LGPL), which allows users to freely use the code in their software systems with a requirement for attribution. Source code for the current release (4.2.0) can be found in Software S1. A detailed manual for obtaining and using Paxtools can be found in Protocol S1. The latest sources and release bundles can be obtained from biopax.org/paxtools. '),
(86188, 2013, 'plos', 'From birdsong to human speech recognition: bayesian inference on a hierarchy of nonlinear dynamical systems', 'Yildiz, Izzet B|von Kriegstein, Katharina|Kiebel, Stefan J', 'Max Planck Institute for Human Cognitive and Brain Sciences, Leipzig, Germany , Group for Neural Theory, Institute of Cognitive Studies, École Normale Supérieure, Paris, France.|Max Planck Institute for Human Cognitive and Brain Sciences, Leipzig, Germany , Group for Neural Theory, Institute of Cognitive Studies, École Normale Supérieure, Paris, France.|Max Planck Institute for Human Cognitive and Brain Sciences, Leipzig, Germany , Group for Neural Theory, Institute of Cognitive Studies, École Normale Supérieure, Paris, France.', 'Germany|Germany|Germany', 26, 'Animal Communication|Animals|Bayes Theorem|Birds|Humans|Speech', 'Journal Article', '10.1371/journal.pcbi.1003219', '24068902', 'Our knowledge about the computational mechanisms underlying human learning and recognition of sound sequences, especially speech, is still very limited. One difficulty in deciphering the exact means by which humans recognize speech is that there are scarce experimental findings at a neuronal, microscopic level. Here, we show that our neuronal-computational understanding of speech learning and recognition may be vastly improved by looking at an animal model, i.e., the songbird, which faces the same challenge as humans: to learn and decode complex auditory input, in an online fashion. Motivated by striking similarities between the human and songbird neural recognition systems at the macroscopic level, we assumed that the human brain uses the same computational principles at a microscopic level and translated a birdsong model into a novel human sound learning and recognition model with an emphasis on speech. We show that the resulting Bayesian model with a hierarchy of nonlinear dynamical systems can learn speech samples such as words rapidly and recognize them robustly, even in adverse conditions. In addition, we show that recognition can be performed even when words are spoken by different speakers and with different accents-an everyday situation in which current state-of-the-art speech recognition models often fail. The model can also be used to qualitatively explain behavioral data on human speech learning and derive predictions for future experiments. '),
(86189, 2013, 'plos', 'Computational optogenetics: empirically-derived voltage- and light-sensitive channelrhodopsin-2 model', 'Williams, John C|Xu, Jianjin|Lu, Zhongju|Klimas, Aleksandra|Chen, Xuxin|Ambrosi, Christina M|Cohen, Ira S|Entcheva, Emilia', 'Department of Biomedical Engineering, Stony Brook University, Stony Brook, New York, United States of America.|Department of Biomedical Engineering, Stony Brook University, Stony Brook, New York, United States of America.|Department of Biomedical Engineering, Stony Brook University, Stony Brook, New York, United States of America.|Department of Biomedical Engineering, Stony Brook University, Stony Brook, New York, United States of America.|Department of Biomedical Engineering, Stony Brook University, Stony Brook, New York, United States of America.|Department of Biomedical Engineering, Stony Brook University, Stony Brook, New York, United States of America.|Department of Biomedical Engineering, Stony Brook University, Stony Brook, New York, United States of America.|Department of Biomedical Engineering, Stony Brook University, Stony Brook, New York, United States of America.', 'United States|United States|United States|United States|United States|United States|United States|Un', 63, 'Channelrhodopsins|Humans|Light|Models, Biological|Myocytes, Cardiac|Optogenetics|Patch-Clamp Techniques', 'Journal Article', '10.1371/journal.pcbi.1003220', '24068903', 'Channelrhodospin-2 (ChR2), a light-sensitive ion channel, and its variants have emerged as new excitatory optogenetic tools not only in neuroscience, but also in other areas, including cardiac electrophysiology. An accurate quantitative model of ChR2 is necessary for in silico prediction of the response to optical stimulation in realistic tissue/organ settings. Such a model can guide the rational design of new ion channel functionality tailored to different cell types/tissues. Focusing on one of the most widely used ChR2 mutants (H134R) with enhanced current, we collected a comprehensive experimental data set of the response of this ion channel to different irradiances and voltages, and used these data to develop a model of ChR2 with empirically-derived voltage- and irradiance- dependence, where parameters were fine-tuned via simulated annealing optimization. This ChR2 model offers: 1) accurate inward rectification in the current-voltage response across irradiances, 2) empirically-derived voltage- and light-dependent kinetics (activation, deactivation and recovery from inactivation), and 3) accurate amplitude and morphology of the response across voltage and irradiance settings. Temperature-scaling factors (Q10) were derived and model kinetics was adjusted to physiological temperatures. Using optical action potential clamp, we experimentally validated model-predicted ChR2 behavior in guinea pig ventricular myocytes. The model was then incorporated in a variety of cardiac myocytes, including human ventricular, atrial and Purkinje cell models. We demonstrate the ability of ChR2 to trigger action potentials in human cardiomyocytes at relatively low light levels, as well as the differential response of these cells to light, with the Purkinje cells being most easily excitable and ventricular cells requiring the highest irradiance at all pulse durations. This new experimentally-validated ChR2 model will facilitate virtual experimentation in neural and cardiac optogenetics at the cell and organ level and provide guidance for the development of in vivo tools. '),
(86190, 2013, 'plos', 'Potential role of a bistable histidine kinase switch in the asymmetric division cycle of Caulobacter crescentus', 'Subramanian, Kartik|Paul, Mark R|Tyson, John J', 'Graduate Program in Genetics, Bioinformatics and Computational Biology, Virginia Polytechnic Institute and State University, Blacksburg, Virginia, United States of America.|Graduate Program in Genetics, Bioinformatics and Computational Biology, Virginia Polytechnic Institute and State University, Blacksburg, Virginia, United States of America.|Graduate Program in Genetics, Bioinformatics and Computational Biology, Virginia Polytechnic Institute and State University, Blacksburg, Virginia, United States of America.', 'United States|United States|United States', 11, 'Caulobacter crescentus|Cell Cycle|Enzyme Stability|Histidine Kinase|Protein Kinases|Substrate Specificity|Thermodynamics', 'Journal Article', '10.1371/journal.pcbi.1003221', '24068904', 'The free-living aquatic bacterium, Caulobacter crescentus, exhibits two different morphologies during its life cycle. The morphological change from swarmer cell to stalked cell is a result of changes of function of two bi-functional histidine kinases, PleC and CckA. Here, we describe a detailed molecular mechanism by which the function of PleC changes between phosphatase and kinase state. By mathematical modeling of our proposed molecular interactions, we derive conditions under which PleC, CckA and its response regulators exhibit bistable behavior, thus providing a scenario for robust switching between swarmer and stalked states. Our simulations are in reasonable agreement with in vitro and in vivo experimental observations of wild type and mutant phenotypes. According to our model, the kinase form of PleC is essential for the swarmer-to-stalked transition and to prevent premature development of the swarmer pole. Based on our results, we reconcile some published experimental observations and suggest novel mutants to test our predictions. '),
(86191, 2013, 'plos', 'Mechanistic model of natural killer cell proliferative response to IL-15 receptor stimulation', 'Zhao, Yun M|French, Anthony R', 'Division of Pediatric Rheumatology, Department of Pediatrics, Washington University School of Medicine, St Louis, Missouri, United States of America , Department of Biomedical Engineering, Washington University, St Louis, Missouri, United States of America.|Division of Pediatric Rheumatology, Department of Pediatrics, Washington University School of Medicine, St Louis, Missouri, United States of America , Department of Biomedical Engineering, Washington University, St Louis, Missouri, United States of America.', 'United States|United States', 0, 'Cell Proliferation|Humans|Killer Cells, Natural|Models, Biological|Receptors, Interleukin-15', 'Journal Article', '10.1371/journal.pcbi.1003222', '24068905', 'Natural killer (NK) cells are innate lymphocytes that provide early host defense against intracellular pathogens, such as viruses. Although NK cell development, homeostasis, and proliferation are regulated by IL-15, the influence of IL-15 receptor (IL-15R)-mediated signaling at the cellular level has not been quantitatively characterized. We developed a mathematical model to analyze the kinetic interactions that control the formation and localization of IL-15/IL-15R complexes. Our computational results demonstrated that IL-15/IL-15R complexes on the cell surface were a key determinant of the magnitude of the IL-15 proliferative signal and that IL-15R occupancy functioned as an effective surrogate measure of receptor signaling. Ligand binding and receptor internalization modulated IL-15R occupancy. Our work supports the hypothesis that the total number and duration of IL-15/IL-15R complexes on the cell surface crosses a quantitative threshold prior to the initiation of NK cell division. Furthermore, our model predicted that the upregulation of IL-15Rxcexb1 on NK cells substantially increased IL-15R complex formation and accelerated the expansion of dividing NK cells with the greatest impact at low IL-15 concentrations. Model predictions of the threshold requirement for NK cell recruitment to the cell cycle and the subsequent exponential proliferation correlated well with experimental data. In summary, our modeling analysis provides quantitative insight into the regulation of NK cell proliferation at the receptor level and provides a framework for the development of IL-15 based immunotherapies to modulate NK cell proliferation. '),
(86192, 2013, 'plos', 'Trial-type dependent frames of reference for value comparison', 'Hunt, Laurence T|Woolrich, Mark W|Rushworth, Matthew F S|Behrens, Timothy E J', 'Wellcome Trust Centre for Neuroimaging, University College London, London, United Kingdom , Centre for Functional MRI of the Brain (FMRIB), University of Oxford, Oxford, United Kingdom.|Wellcome Trust Centre for Neuroimaging, University College London, London, United Kingdom , Centre for Functional MRI of the Brain (FMRIB), University of Oxford, Oxford, United Kingdom.|Wellcome Trust Centre for Neuroimaging, University College London, London, United Kingdom , Centre for Functional MRI of the Brain (FMRIB), University of Oxford, Oxford, United Kingdom.|Wellcome Trust Centre for Neuroimaging, University College London, London, United Kingdom , Centre for Functional MRI of the Brain (FMRIB), University of Oxford, Oxford, United Kingdom.', 'United Kingdom|United Kingdom|United Kingdom|United Kingdom', 0, 'Brain Diseases|Decision Making|Humans|Models, Theoretical|Motor Cortex|Reference Values', 'Comparative Study', '10.1371/journal.pcbi.1003225', '24068906', 'A central question in cognitive neuroscience regards the means by which options are compared and decisions are resolved during value-guided choice. It is clear that several component processes are needed, these include identifying options, a value-based comparison, and implementation of actions to execute the decision. What is less clear is the temporal precedence and functional organisation of these component processes in the brain. Competing models of decision making have proposed that value comparison may occur in the space of alternative actions, or in the space of abstract goods. We hypothesized that the signals observed might in fact depend upon the framing of the decision. We recorded magnetoencephalographic data from humans performing value-guided choices in which two closely related trial types were interleaved. In the first trial type, each option was revealed separately, potentially causing subjects to estimate each actions value as it was revealed and perform comparison in action-space. In the second trial type, both options were presented simultaneously, potentially leading to comparison in abstract goods-space prior to commitment to a specific action. Distinct activity patterns (in distinct brain regions) on the two trial types demonstrated that the observed frame of reference used for decision making indeed differed, despite the information presented being formally identical, between the two trial types. This provides a potential reconciliation of conflicting accounts of value-guided choice. '),
(86193, 2013, 'plos', 'Target inhibition networks: predicting selective combinations of druggable targets to block cancer survival pathways', 'Tang, Jing|Karhinen, Leena|Xu, Tao|Szwajda, Agnieszka|Yadav, Bhagwan|Wennerberg, Krister|Aittokallio, Tero', 'Institute for Molecular Medicine Finland (FIMM), University of Helsinki, Helsinki, Finland.|Institute for Molecular Medicine Finland (FIMM), University of Helsinki, Helsinki, Finland.|Institute for Molecular Medicine Finland (FIMM), University of Helsinki, Helsinki, Finland.|Institute for Molecular Medicine Finland (FIMM), University of Helsinki, Helsinki, Finland.|Institute for Molecular Medicine Finland (FIMM), University of Helsinki, Helsinki, Finland.|Institute for Molecular Medicine Finland (FIMM), University of Helsinki, Helsinki, Finland.|Institute for Molecular Medicine Finland (FIMM), University of Helsinki, Helsinki, Finland.', 'Finland|Finland|Finland|Finland|Finland|Finland|Finland', 0, 'Antineoplastic Agents|Cell Line, Tumor|Cell Survival|Humans|Models, Theoretical|Neoplasms', 'Journal Article', '10.1371/journal.pcbi.1003226', '24068907', 'A recent trend in drug development is to identify drug combinations or multi-target agents that effectively modify multiple nodes of disease-associated networks. Such polypharmacological effects may reduce the risk of emerging drug resistance by means of attacking the disease networks through synergistic and synthetic lethal interactions. However, due to the exponentially increasing number of potential drug and target combinations, systematic approaches are needed for prioritizing the most potent multi-target alternatives on a global network level. We took a functional systems pharmacology approach toward the identification of selective target combinations for specific cancer cells by combining large-scale screening data on drug treatment efficacies and drug-target binding affinities. Our model-based prediction approach, named TIMMA, takes advantage of the polypharmacological effects of drugs and infers combinatorial drug efficacies through system-level target inhibition networks. Case studies in MCF-7 and MDA-MB-231 breast cancer and BxPC-3 pancreatic cancer cells demonstrated how the target inhibition modeling allows systematic exploration of functional interactions between drugs and their targets to maximally inhibit multiple survival pathways in a given cancer type. The TIMMA prediction results were experimentally validated by means of systematic siRNA-mediated silencing of the selected targets and their pairwise combinations, showing increased ability to identify not only such druggable kinase targets that are essential for cancer survival either individually or in combination, but also synergistic interactions indicative of non-additive drug efficacies. These system-level analyses were enabled by a novel model construction method utilizing maximization and minimization rules, as well as a model selection algorithm based on sequential forward floating search. Compared with an existing computational solution, TIMMA showed both enhanced prediction accuracies in cross validation as well as significant reduction in computation times. Such cost-effective computational-experimental design strategies have the potential to greatly speed-up the drug testing efforts by prioritizing those interventions and interactions warranting further study in individual cancer cases. '),
(86194, 2013, 'plos', 'Adaptation dynamics in densely clustered chemoreceptors', 'Pontius, William|Sneddon, Michael W|Emonet, Thierry', 'Department of Physics, 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 Physics, 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 Physics, 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.', 'United States|United States|United States', 11, 'Adaptation, Physiological|Chemoreceptor Cells|Chemotaxis|Escherichia coli|Kinetics|Methylation|Models, Theoretical', 'Journal Article', '10.1371/journal.pcbi.1003230', '24068908', 'In many sensory systems, transmembrane receptors are spatially organized in large clusters. Such arrangement may facilitate signal amplification and the integration of multiple stimuli. However, this organization likely also affects the kinetics of signaling since the cytoplasmic enzymes that modulate the activity of the receptors must localize to the cluster prior to receptor modification. Here we examine how these spatial considerations shape signaling dynamics at rest and in response to stimuli. As a model system, we use the chemotaxis pathway of Escherichia coli, a canonical system for the study of how organisms sense, respond, and adapt to environmental stimuli. In bacterial chemotaxis, adaptation is mediated by two enzymes that localize to the clustered receptors and modulate their activity through methylation-demethylation. Using a novel stochastic simulation, we show that distributive receptor methylation is necessary for successful adaptation to stimulus and also leads to large fluctuations in receptor activity in the steady state. These fluctuations arise from noise in the number of localized enzymes combined with saturated modification kinetics between the localized enzymes and the receptor substrate. An analytical model explains how saturated enzyme kinetics and large fluctuations can coexist with an adapted state robust to variation in the expression levels of the pathway constituents, a key requirement to ensure the functionality of individual cells within a population. This contrasts with the well-mixed covalent modification system studied by Goldbeter and Koshland in which mean activity becomes ultrasensitive to protein abundances when the enzymes operate at saturation. Large fluctuations in receptor activity have been quantified experimentally and may benefit the cell by enhancing its ability to explore empty environments and track shallow nutrient gradients. Here we clarify the mechanistic relationship of these large fluctuations to well-studied aspects of the chemotaxis system, precise adaptation and functional robustness. '),
(86195, 2013, 'plos', 'Predictive modeling of in vivo response to gemcitabine in pancreatic cancer', 'Lee, James J|Huang, Justin|England, Christopher G|McNally, Lacey R|Frieboes, Hermann B', 'School of Medicine, University of Louisville, Louisville, Kentucky, United States of America.|School of Medicine, University of Louisville, Louisville, Kentucky, United States of America.|School of Medicine, University of Louisville, Louisville, Kentucky, United States of America.|School of Medicine, University of Louisville, Louisville, Kentucky, United States of America.|School of Medicine, University of Louisville, Louisville, Kentucky, United States of America.', 'United States|United States|United States|United States|United States', 0, 'Animals|Antimetabolites, Antineoplastic|Deoxycytidine|Female|Humans|Mice|Mice, SCID|Pancreatic Neoplasms', 'Journal Article', '10.1371/journal.pcbi.1003231', '24068909', 'A clear contradiction exists between cytotoxic in-vitro studies demonstrating effectiveness of Gemcitabine to curtail pancreatic cancer and in-vivo studies failing to show Gemcitabine as an effective treatment. The outcome of chemotherapy in metastatic stages, where surgery is no longer viable, shows a 5-year survival <5%. It is apparent that in-vitro experiments, no matter how well designed, may fail to adequately represent the complex in-vivo microenvironmental and phenotypic characteristics of the cancer, including cell proliferation and apoptosis. We evaluate in-vitro cytotoxic data as an indicator of in-vivo treatment success using a mathematical model of tumor growth based on a dimensionless formulation describing tumor biology. Inputs to the model are obtained under optimal drug exposure conditions in-vitro. The model incorporates heterogeneous cell proliferation and death caused by spatial diffusion gradients of oxygen/nutrients due to inefficient vascularization and abundant stroma, and thus is able to simulate the effect of the microenvironment as a barrier to effective nutrient and drug delivery. Analysis of the mathematical model indicates the pancreatic tumors to be mostly resistant to Gemcitabine treatment in-vivo. The model results are confirmed with experiments in live mice, which indicate uninhibited tumor proliferation and metastasis with Gemcitabine treatment. By extracting mathematical model parameter values for proliferation and death from monolayer in-vitro cytotoxicity experiments with pancreatic cancer cells, and simulating the effects of spatial diffusion, we use the model to predict the drug response in-vivo, beyond what would have been expected from sole consideration of the cancer intrinsic resistance. We conclude that this integrated experimental/computational approach may enhance understanding of pancreatic cancer behavior and its response to various chemotherapies, and, further, that such an approach could predict resistance based on pharmacokinetic measurements with the goal to maximize effective treatment strategies. '),
(86196, 2013, 'plos', 'Collective dynamics underlying allosteric transitions in hemoglobin', 'Vesper, Martin D|de Groot, Bert L', 'Department of Theoretical and Computational Biophysics, Max Planck Institute for Biophysical Chemistry, Göttingen, Germany.|Department of Theoretical and Computational Biophysics, Max Planck Institute for Biophysical Chemistry, Göttingen, Germany.', 'Germany|Germany', 15, 'Allosteric Regulation|Hemoglobins|Histidine|Molecular Dynamics Simulation', 'Journal Article', '10.1371/journal.pcbi.1003232', '24068910', 'Hemoglobin is the prototypic allosteric protein. Still, its molecular allosteric mechanism is not fully understood. To elucidate the mechanism of cooperativity on an atomistic level, we developed a novel computational technique to analyse the coupling of tertiary and quaternary motions. From Molecular Dynamics simulations showing spontaneous quaternary transitions, we separated the transition trajectories into two orthogonal sets of motions: one consisting of intra-chain motions only (referred to as tertiary-only) and one consisting of global inter-chain motions only (referred to as quaternary-only). The two underlying subspaces are orthogonal by construction and their direct sum is the space of full motions. Using Functional Mode Analysis, we were able to identify a collective coordinate within the tertiary-only subspace that is correlated to the most dominant motion within the quaternary-only motions, hence providing direct insight into the allosteric coupling mechanism between tertiary and quaternary conformation changes. This coupling-motion is substantially different from tertiary structure changes between the crystallographic structures of the T- and R-state. We found that hemoglobins allosteric mechanism of communication between subunits is equally based on hydrogen bonds and steric interactions. In addition, we were able to affect the T-to-R transition rates by choosing different histidine protonation states, thereby providing a possible atomistic explanation for the Bohr effect. ');
INSERT INTO `papers` (`id`, `ano`, `journal`, `titulo`, `autores`, `afiliacao`, `pais`, `citacoes`, `palavra_chave`, `categorias`, `doi`, `pubmed`, `abstract`) VALUES
(86197, 2013, 'plos', 'Limited agreement of independent RNAi screens for virus-required host genes owes more to false-negative than false-positive factors', 'Hao, Linhui|He, Qiuling|Wang, Zhishi|Craven, Mark|Newton, Michael A|Ahlquist, Paul', 'Institute of Molecular Virology, University of Wisconsin-Madison, Madison, Wisconsin, United States of America , Howard Hughes Medical Institute, University of Wisconsin-Madison, Madison, Wisconsin, United States of America.|Institute of Molecular Virology, University of Wisconsin-Madison, Madison, Wisconsin, United States of America , Howard Hughes Medical Institute, University of Wisconsin-Madison, Madison, Wisconsin, United States of America.|Institute of Molecular Virology, University of Wisconsin-Madison, Madison, Wisconsin, United States of America , Howard Hughes Medical Institute, University of Wisconsin-Madison, Madison, Wisconsin, United States of America.|Institute of Molecular Virology, University of Wisconsin-Madison, Madison, Wisconsin, United States of America , Howard Hughes Medical Institute, University of Wisconsin-Madison, Madison, Wisconsin, United States of America.|Institute of Molecular Virology, University of Wisconsin-Madison, Madison, Wisconsin, United States of America , Howard Hughes Medical Institute, University of Wisconsin-Madison, Madison, Wisconsin, United States of America.|Institute of Molecular Virology, University of Wisconsin-Madison, Madison, Wisconsin, United States of America , Howard Hughes Medical Institute, University of Wisconsin-Madison, Madison, Wisconsin, United States of America.', 'United States|United States|United States|United States|United States|United States', 0, 'False Negative Reactions|False Positive Reactions|Gene Knockdown Techniques|Genes, Viral|Likelihood Functions|Orthomyxoviridae|RNA Interference|Virus Replication', 'Journal Article', '10.1371/journal.pcbi.1003235', '24068911', 'Systematic, genome-wide RNA interference (RNAi) analysis is a powerful approach to identify gene functions that support or modulate selected biological processes. An emerging challenge shared with some other genome-wide approaches is that independent RNAi studies often show limited agreement in their lists of implicated genes. To better understand this, we analyzed four genome-wide RNAi studies that identified host genes involved in influenza virus replication. These studies collectively identified and validated the roles of 614 cell genes, but pair-wise overlap among the four gene lists was only 3% to 15% (average 6.7%). However, a number of functional categories were overrepresented in multiple studies. The pair-wise overlap of these enriched-category lists was high, xe2x88xbc19%, implying more agreement among studies than apparent at the gene level. Probing this further, we found that the gene lists implicated by independent studies were highly connected in interacting networks by independent functional measures such as protein-protein interactions, at rates significantly higher than predicted by chance. We also developed a general, model-based approach to gauge the effects of false-positive and false-negative factors and to estimate, from a limited number of studies, the total number of genes involved in a process. For influenza virus replication, this novel statistical approach estimates the total number of cell genes involved to be xe2x88xbc2,800. This and multiple other aspects of our experimental and computational results imply that, when following good quality control practices, the low overlap between studies is primarily due to false negatives rather than false-positive gene identifications. These results and methods have implications for and applications to multiple forms of genome-wide analysis. '),
(86198, 2013, 'plos', 'Network signatures of survival in glioblastoma multiforme', 'Patel, Vishal N|Gokulrangan, Giridharan|Chowdhury, Salim A|Chen, Yanwen|Sloan, Andrew E|Koyutxc3xbcrk, Mehmet|Barnholtz-Sloan, Jill|Chance, Mark R', 'Center for Proteomics and Bioinformatics, Case Western Reserve University, Cleveland, Ohio, United States of America.|Center for Proteomics and Bioinformatics, Case Western Reserve University, Cleveland, Ohio, United States of America.|Center for Proteomics and Bioinformatics, Case Western Reserve University, Cleveland, Ohio, United States of America.|Center for Proteomics and Bioinformatics, Case Western Reserve University, Cleveland, Ohio, United States of America.|Center for Proteomics and Bioinformatics, Case Western Reserve University, Cleveland, Ohio, United States of America.|Center for Proteomics and Bioinformatics, Case Western Reserve University, Cleveland, Ohio, United States of America.|Center for Proteomics and Bioinformatics, Case Western Reserve University, Cleveland, Ohio, United States of America.|Center for Proteomics and Bioinformatics, Case Western Reserve University, Cleveland, Ohio, United States of America.', 'United States|United States|United States|United States|United States|United States|United States|Un', 0, 'Brain Neoplasms|Gene Expression Profiling|Gene Regulatory Networks|Glioblastoma|Humans|Protein Kinases|Proteomics|Survivors', 'Journal Article', '10.1371/journal.pcbi.1003237', '24068912', 'To determine a molecular basis for prognostic differences in glioblastoma multiforme (GBM), we employed a combinatorial network analysis framework to exhaustively search for molecular patterns in protein-protein interaction (PPI) networks. We identified a dysregulated molecular signature distinguishing short-term (survival<225 days) from long-term (survival>635 days) survivors of GBM using whole genome expression data from The Cancer Genome Atlas (TCGA). A 50-gene subnetwork signature achieved 80% prediction accuracy when tested against an independent gene expression dataset. Functional annotations for the subnetwork signature included protein kinase cascade, IxcexbaB kinase/NFxcexbaB cascade, and regulation of programmed cell death - all of which were not significant in signatures of existing subtypes. Finally, we used label-free proteomics to examine how our subnetwork signature predicted protein level expression differences in an independent GBM cohort of 16 patients. We found that the genes discovered using network biology had a higher probability of dysregulated protein expression than either genes exhibiting individual differential expression or genes derived from known GBM subtypes. In particular, the long-term survivor subtype was characterized by increased protein expression of DNM1 and MAPK1 and decreased expression of HSPA9, PSMD3, and CANX. Overall, we demonstrate that the combinatorial analysis of gene expression data constrained by PPIs outlines an approach for the discovery of robust and translatable molecular signatures in GBM. '),
(86199, 2013, 'plos', 'ISCB computational biology Wikipedia competition', 'Bateman, Alex|Kelso, Janet|Mietchen, Daniel|Macintyre, Geoff|Di Domenico, Tomás|Abeel, Thomas|Logan, Darren W|Radivojac, Predrag|Rost, Burkhard', 'European Molecular Biology Laboratory, European Bioinformatics Institute, Hinxton, United Kingdom.|European Molecular Biology Laboratory, European Bioinformatics Institute, Hinxton, United Kingdom.|European Molecular Biology Laboratory, European Bioinformatics Institute, Hinxton, United Kingdom.|European Molecular Biology Laboratory, European Bioinformatics Institute, Hinxton, United Kingdom.|European Molecular Biology Laboratory, European Bioinformatics Institute, Hinxton, United Kingdom.|European Molecular Biology Laboratory, European Bioinformatics Institute, Hinxton, United Kingdom.|European Molecular Biology Laboratory, European Bioinformatics Institute, Hinxton, United Kingdom.|European Molecular Biology Laboratory, European Bioinformatics Institute, Hinxton, United Kingdom.|European Molecular Biology Laboratory, European Bioinformatics Institute, Hinxton, United Kingdom.', 'United Kingdom|United Kingdom|United Kingdom|United Kingdom|United Kingdom|United Kingdom|United Kin', 5, 'Computational Biology|Internet|Societies, Scientific', 'Journal Article', '10.1371/journal.pcbi.1003242', '24068913', '-'),
(86200, 2013, 'plos', 'Task-based core-periphery organization of human brain dynamics', 'Bassett, Danielle S|Wymbs, Nicholas F|Rombach, M Puck|Porter, Mason A|Mucha, Peter J|Grafton, Scott T', 'Department of Physics, University of California, Santa Barbara, Santa Barbara, California, United States of America , Sage Center for the Study of the Mind, University of California, Santa Barbara, Santa Barbara, California, United States of America.|Department of Physics, University of California, Santa Barbara, Santa Barbara, California, United States of America , Sage Center for the Study of the Mind, University of California, Santa Barbara, Santa Barbara, California, United States of America.|Department of Physics, University of California, Santa Barbara, Santa Barbara, California, United States of America , Sage Center for the Study of the Mind, University of California, Santa Barbara, Santa Barbara, California, United States of America.|Department of Physics, University of California, Santa Barbara, Santa Barbara, California, United States of America , Sage Center for the Study of the Mind, University of California, Santa Barbara, Santa Barbara, California, United States of America.|Department of Physics, University of California, Santa Barbara, Santa Barbara, California, United States of America , Sage Center for the Study of the Mind, University of California, Santa Barbara, Santa Barbara, California, United States of America.|Department of Physics, University of California, Santa Barbara, Santa Barbara, California, United States of America , Sage Center for the Study of the Mind, University of California, Santa Barbara, Santa Barbara, California, United States of America.', 'United States|United States|United States|United States|United States|United States', 0, 'Brain|Humans|Learning|Task Performance and Analysis', 'Journal Article', '10.1371/journal.pcbi.1003171', '24086116', 'As a person learns a new skill, distinct synapses, brain regions, and circuits are engaged and change over time. In this paper, we develop methods to examine patterns of correlated activity across a large set of brain regions. Our goal is to identify properties that enable robust learning of a motor skill. We measure brain activity during motor sequencing and characterize network properties based on coherent activity between brain regions. Using recently developed algorithms to detect time-evolving communities, we find that the complex reconfiguration patterns of the brains putative functional modules that control learning can be described parsimoniously by the combined presence of a relatively stiff temporal core that is composed primarily of sensorimotor and visual regions whose connectivity changes little in time and a flexible temporal periphery that is composed primarily of multimodal association regions whose connectivity changes frequently. The separation between temporal core and periphery changes over the course of training and, importantly, is a good predictor of individual differences in learning success. The core of dynamically stiff regions exhibits dense connectivity, which is consistent with notions of core-periphery organization established previously in social networks. Our results demonstrate that core-periphery organization provides an insightful way to understand how putative functional modules are linked. This, in turn, enables the prediction of fundamental human capacities, including the production of complex goal-directed behavior. '),
(86201, 2013, 'plos', 'Modeling the effect of APC truncation on destruction complex function in colorectal cancer cells', 'Barua, Dipak|Hlavacek, William S', 'Theoretical Biology and Biophysics Group, Theoretical Division and Center for Nonlinear Studies, Los Alamos National Laboratory, Los Alamos, New Mexico, United States of America.|Theoretical Biology and Biophysics Group, Theoretical Division and Center for Nonlinear Studies, Los Alamos National Laboratory, Los Alamos, New Mexico, United States of America.', 'Mexico|Mexico', 15, 'Colorectal Neoplasms|Genes, APC|Humans|Hydrolysis|Mutation|Phosphorylation|Up-Regulation|beta Catenin', 'Journal Article', '10.1371/journal.pcbi.1003217', '24086117', 'In colorectal cancer cells, APC, a tumor suppressor protein, is commonly expressed in truncated form. Truncation of APC is believed to disrupt degradation of xcexb2-catenin, which is regulated by a multiprotein complex called the destruction complex. The destruction complex comprises APC, Axin, xcexb2-catenin, serine/threonine kinases, and other proteins. The kinases CK1xcexb1 and GSK -3xcexb2, which are recruited by Axin, mediate phosphorylation of xcexb2-catenin, which initiates its ubiquitination and proteosomal degradation. The mechanism of regulation of xcexb2-catenin degradation by the destruction complex and the role of truncation of APC in colorectal cancer are not entirely understood. Through formulation and analysis of a rule-based computational model, we investigated the regulation of xcexb2-catenin phosphorylation and degradation by APC and the effect of APC truncation on function of the destruction complex. The model integrates available mechanistic knowledge about site-specific interactions and phosphorylation of destruction complex components and is consistent with an array of published data. We find that the phosphorylated truncated form of APC can outcompete Axin for binding to xcexb2-catenin, provided that Axin is limiting, and thereby sequester xcexb2-catenin away from Axin and the Axin-recruited kinases CK1xcexb1 and GSK -3xcexb2. Full-length APC also competes with Axin for binding to xcexb2-catenin, however, full-length APC is able, through its SAMP repeats, which bind Axin and which are missing in truncated oncogenic forms of APC, to bring xcexb2-catenin into indirect association with Axin and Axin-recruited kinases. Because our model indicates that the positive effects of truncated APC on xcexb2-catenin levels depend on phosphorylation of APC, at the first 20-amino acid repeat, and because phosphorylation of this site is mediated by CK1xcexb5, we suggest that CK1xcexb5 is a potential target for therapeutic intervention in colorectal cancer. Specific inhibition of CK1xcexb5 is predicted to limit binding of xcexb2-catenin to truncated APC and thereby to reverse the effect of APC truncation.'),
(86202, 2013, 'plos', 'Analyzing and synthesizing phylogenies using tree alignment graphs', 'Smith, Stephen A|Brown, Joseph W|Hinchliff, Cody E', 'Department of Ecology and Evolutionary Biology, University of Michigan, Ann Arbor, Michigan, United States of America.|Department of Ecology and Evolutionary Biology, University of Michigan, Ann Arbor, Michigan, United States of America.|Department of Ecology and Evolutionary Biology, University of Michigan, Ann Arbor, Michigan, United States of America.', 'United States|United States|United States', 0, 'Phylogeny|Sequence Homology, Nucleic Acid', 'Journal Article', '10.1371/journal.pcbi.1003223', '24086118', 'Phylogenetic trees are used to analyze and visualize evolution. However, trees can be imperfect datatypes when summarizing multiple trees. This is especially problematic when accommodating for biological phenomena such as horizontal gene transfer, incomplete lineage sorting, and hybridization, as well as topological conflict between datasets. Additionally, researchers may want to combine information from sets of trees that have partially overlapping taxon sets. To address the problem of analyzing sets of trees with conflicting relationships and partially overlapping taxon sets, we introduce methods for aligning, synthesizing and analyzing rooted phylogenetic trees within a graph, called a tree alignment graph (TAG). The TAG can be queried and analyzed to explore uncertainty and conflict. It can also be synthesized to construct trees, presenting an alternative to supertrees approaches. We demonstrate these methods with two empirical datasets. In order to explore uncertainty, we constructed a TAG of the bootstrap trees from the Angiosperm Tree of Life project. Analysis of the resulting graph demonstrates that areas of the dataset that are unresolved in majority-rule consensus tree analyses can be understood in more detail within the context of a graph structure, using measures incorporating node degree and adjacency support. As an exercise in synthesis (i.e., summarization of a TAG constructed from the alignment trees), we also construct a TAG consisting of the taxonomy and source trees from a recent comprehensive bird study. We synthesized this graph into a tree that can be reconstructed in a repeatable fashion and where the underlying source information can be updated. The methods presented here are tractable for large scale analyses and serve as a basis for an alternative to consensus tree and supertree methods. Furthermore, the exploration of these graphs can expose structures and patterns within the dataset that are otherwise difficult to observe. '),
(86203, 2013, 'plos', 'Tunable stochastic pulsing in the Escherichia coli multiple antibiotic resistance network from interlinked positive and negative feedback loops', 'Garcia-Bernardo, Javier|Dunlop, Mary J', 'School of Engineering, University of Vermont, Burlington, Vermont, United States of America.|School of Engineering, University of Vermont, Burlington, Vermont, United States of America.', 'United States|United States', 21, 'Anti-Bacterial Agents|Drug Resistance, Multiple, Bacterial|Escherichia coli|Feedback|Stochastic Processes', 'Journal Article', '10.1371/journal.pcbi.1003229', '24086119', 'Cells live in uncertain, dynamic environments and have many mechanisms for sensing and responding to changes in their surroundings. However, sudden fluctuations in the environment can be catastrophic to a population if it relies solely on sensory responses, which have a delay associated with them. Cells can reconcile these effects by using a tunable stochastic response, where in the absence of a stressor they create phenotypic diversity within an isogenic population, but use a deterministic response when stressors are sensed. Here, we develop a stochastic model of the multiple antibiotic resistance network of Escherichia coli and show that it can produce tunable stochastic pulses in the activator MarA. In particular, we show that a combination of interlinked positive and negative feedback loops plays an important role in setting the dynamics of the stochastic pulses. Negative feedback produces a pulsatile response that is tunable, while positive feedback serves to amplify the effect. Our simulations show that the uninduced native network is in a parameter regime that is of low cost to the cell (taxing resistance mechanisms are expressed infrequently) and also elevated noise strength (phenotypic variability is high). The stochastic pulsing can be tuned by MarA induction such that variability is decreased once stresses are sensed, avoiding the detrimental effects of noise when an optimal MarA concentration is needed. We further show that variability in the expression of MarA can act as a bet hedging mechanism, allowing for survival in time-varying stress environments, however this effect is tunable to allow for a fully induced, deterministic response in the presence of a stressor. '),
(86204, 2013, 'plos', 'Whisker movements reveal spatial attention: a unified computational model of active sensing control in the rat', 'Mitchinson, Ben|Prescott, Tony J', 'Department Of Psychology, The University Of Sheffield, Sheffield, United Kingdom.|Department Of Psychology, The University Of Sheffield, Sheffield, United Kingdom.', 'United Kingdom|United Kingdom', 28, 'Animals|Attention|Behavior, Animal|Models, Biological|Rats|Vibrissae', 'Journal Article', '10.1371/journal.pcbi.1003236', '24086120', 'Spatial attention is most often investigated in the visual modality through measurement of eye movements, with primates, including humans, a widely-studied model. Its study in laboratory rodents, such as mice and rats, requires different techniques, owing to the lack of a visual fovea and the particular ethological relevance of orienting movements of the snout and the whiskers in these animals. In recent years, several reliable relationships have been observed between environmental and behavioural variables and movements of the whiskers, but the function of these responses, as well as how they integrate, remains unclear. Here, we propose a unifying abstract model of whisker movement control that has as its key variable the region of space that is the animals current focus of attention, and demonstrate, using computer-simulated behavioral experiments, that the model is consistent with a broad range of experimental observations. A core hypothesis is that the rat explicitly decodes the location in space of whisker contacts and that this representation is used to regulate whisker drive signals. This proposition stands in contrast to earlier proposals that the modulation of whisker movement during exploration is mediated primarily by reflex loops. We go on to argue that the superior colliculus is a candidate neural substrate for the siting of a head-centred map guiding whisker movement, in analogy to current models of visual attention. The proposed model has the potential to offer a more complete understanding of whisker control as well as to highlight the potential of the rodent and its whiskers as a tool for the study of mammalian attention. '),
(86205, 2013, 'plos', 'Frequency response of a protein to local conformational perturbations', 'Eren, Dilek|Alakent, Burak', 'Department of Chemical Engineering, Bogazici University, Bebek, Istanbul, Turkey.|Department of Chemical Engineering, Bogazici University, Bebek, Istanbul, Turkey.', 'Turkey|Turkey', 0, 'Cluster Analysis|Molecular Dynamics Simulation|Principal Component Analysis|Protein Conformation|Proteins', 'Journal Article', '10.1371/journal.pcbi.1003238', '24086121', 'Signals created by local perturbations are known to propagate long distances through proteins via backbone connectivity and nonbonded interactions. In the current study, signal propagation from the flexible ligand binding loop to the rest of Protein Tyrosine Phosphatase 1B (PTP1B) was investigated using frequency response techniques. Using restrained Targeted Molecular Dynamics (TMD) potential on WPD and R loops, PTP1B was driven between its crystal structure conformations at different frequencies. Propagation of the local perturbation signal was manifested via peaks at the fundamental frequency and upper harmonics of 1/f distributed spectral density of atomic variables, such as Cxcexb1 atoms, dihedral angles, or polar interaction distances. Frequency of perturbation was adjusted high enough (simulation length >xe2x88xbc10xc3x97period of a perturbation cycle) not to be clouded by random diffusional fluctuations, and low enough (<xe2x88xbc0.8 ns(-1)) not to attenuate the propagating signal and enhance the contribution of the side-chains to the dissipation of the signals. Employing Discrete Fourier Transform (DFT) to TMD simulation trajectories of 16 cycles of conformational transitions at periods of 1.2 to 5 ns yielded Cxcexb1 displacements consistent with those obtained from crystal structures. Identification of the perturbed atomic variables by statistical t-tests on log-log scale spectral densities revealed the extent of signal propagation in PTP1B, while phase angles of the filtered trajectories at the fundamental frequency were used to cluster collectively fluctuating elements. Hydrophobic interactions were found to have a higher contribution to signal transduction between side-chains compared to the role of polar interactions. Most of in-phase fluctuating residues on the signaling pathway were found to have high identity among PTP domains, and located over a wide region of PTP1B including the allosteric site. Due to its simplicity and efficiency, the suggested technique may find wide applications in identification of signaling pathways of different proteins. '),
(86206, 2013, 'plos', 'Polycation-xcfx80 interactions are a driving force for molecular recognition by an intrinsically disordered oncoprotein family', 'Song, Jianhui|Ng, Sheung Chun|Tompa, Peter|Lee, Kevin A W|Chan, Hue Sun', 'Departments of Biochemistry, Molecular Genetics, and Physics, University of Toronto, Toronto, Ontario, Canada.|Departments of Biochemistry, Molecular Genetics, and Physics, University of Toronto, Toronto, Ontario, Canada.|Departments of Biochemistry, Molecular Genetics, and Physics, University of Toronto, Toronto, Ontario, Canada.|Departments of Biochemistry, Molecular Genetics, and Physics, University of Toronto, Toronto, Ontario, Canada.|Departments of Biochemistry, Molecular Genetics, and Physics, University of Toronto, Toronto, Ontario, Canada.', 'Canada|Canada|Canada|Canada|Canada', 35, 'Intrinsically Disordered Proteins|Models, Chemical|Oncogene Proteins|Polyamines|Sarcoma, Ewing', 'Journal Article', '10.1371/journal.pcbi.1003239', '24086122', 'Molecular recognition by intrinsically disordered proteins (IDPs) commonly involves specific localized contacts and target-induced disorder to order transitions. However, some IDPs remain disordered in the bound state, a phenomenon coined fuzziness, often characterized by IDP polyvalency, sequence-insensitivity and a dynamic ensemble of disordered bound-state conformations. Besides the above general features, specific biophysical models for fuzzy interactions are mostly lacking. The transcriptional activation domain of the Ewings Sarcoma oncoprotein family (EAD) is an IDP that exhibits many features of fuzziness, with multiple EAD aromatic side chains driving molecular recognition. Considering the prevalent role of cation-xcfx80 interactions at various protein-protein interfaces, we hypothesized that EAD-target binding involves polycation- xcfx80 contacts between a disordered EAD and basic residues on the target. Herein we evaluated the polycation-xcfx80 hypothesis via functional and theoretical interrogation of EAD variants. The experimental effects of a range of EAD sequence variations, including aromatic number, aromatic density and charge perturbations, all support the cation-xcfx80 model. Moreover, the activity trends observed are well captured by a coarse-grained EAD chain model and a corresponding analytical model based on interaction between EAD aromatics and surface cations of a generic globular target. EAD-target binding, in the context of pathological Ewings Sarcoma oncoproteins, is thus seen to be driven by a balance between EAD conformational entropy and favorable EAD-target cation-xcfx80 contacts. Such a highly versatile mode of molecular recognition offers a general conceptual framework for promiscuous target recognition by polyvalent IDPs. '),
(86207, 2013, 'plos', 'Ten simple rules for cultivating open science and collaborative R&D', 'Masum, Hassan|Rao, Aarthi|Good, Benjamin M|Todd, Matthew H|Edwards, Aled M|Chan, Leslie|Bunin, Barry A|Su, Andrew I|Thomas, Zakir|Bourne, Philip E', 'Waterloo Institute for Complexity and Innovation, Waterloo, Ontario, Canada.|Waterloo Institute for Complexity and Innovation, Waterloo, Ontario, Canada.|Waterloo Institute for Complexity and Innovation, Waterloo, Ontario, Canada.|Waterloo Institute for Complexity and Innovation, Waterloo, Ontario, Canada.|Waterloo Institute for Complexity and Innovation, Waterloo, Ontario, Canada.|Waterloo Institute for Complexity and Innovation, Waterloo, Ontario, Canada.|Waterloo Institute for Complexity and Innovation, Waterloo, Ontario, Canada.|Waterloo Institute for Complexity and Innovation, Waterloo, Ontario, Canada.|Waterloo Institute for Complexity and Innovation, Waterloo, Ontario, Canada.|Waterloo Institute for Complexity and Innovation, Waterloo, Ontario, Canada.', 'Canada|Canada|Canada|Canada|Canada|Canada|Canada|Canada|Canada|Canada', 0, 'Cooperative Behavior|Research|Science', 'Editorial', '10.1371/journal.pcbi.1003244', '24086123', '-'),
(86208, 2013, 'plos', 'Barcoding T cell calcium response diversity with methods for automated and accurate analysis of cell signals (MAAACS)', 'Salles, Audrey|Billaudeau, Cyrille|Sergé, Arnauld|Bernard, Anne-Marie|Phélipot, Marie-Claire|Bertaux, Nicolas|Fallet, Mathieu|Grenot, Pierre|Marguet, Didier|He, Hai-Tao|Hamon, Yannick', 'Centre dImmunologie de Marseille-Luminy (CIML), Aix-Marseille University, UM2, Marseille, France , Institut National de la Santé et de la Recherche Médicale (Inserm), U1104, Marseille, France , Centre National de la Recherche Scientifique (CNRS) UMR7280, Marseille, France.|Centre dImmunologie de Marseille-Luminy (CIML), Aix-Marseille University, UM2, Marseille, France , Institut National de la Santé et de la Recherche Médicale (Inserm), U1104, Marseille, France , Centre National de la Recherche Scientifique (CNRS) UMR7280, Marseille, France.|Centre dImmunologie de Marseille-Luminy (CIML), Aix-Marseille University, UM2, Marseille, France , Institut National de la Santé et de la Recherche Médicale (Inserm), U1104, Marseille, France , Centre National de la Recherche Scientifique (CNRS) UMR7280, Marseille, France.|Centre dImmunologie de Marseille-Luminy (CIML), Aix-Marseille University, UM2, Marseille, France , Institut National de la Santé et de la Recherche Médicale (Inserm), U1104, Marseille, France , Centre National de la Recherche Scientifique (CNRS) UMR7280, Marseille, France.|Centre dImmunologie de Marseille-Luminy (CIML), Aix-Marseille University, UM2, Marseille, France , Institut National de la Santé et de la Recherche Médicale (Inserm), U1104, Marseille, France , Centre National de la Recherche Scientifique (CNRS) UMR7280, Marseille, France.|Centre dImmunologie de Marseille-Luminy (CIML), Aix-Marseille University, UM2, Marseille, France , Institut National de la Santé et de la Recherche Médicale (Inserm), U1104, Marseille, France , Centre National de la Recherche Scientifique (CNRS) UMR7280, Marseille, France.|Centre dImmunologie de Marseille-Luminy (CIML), Aix-Marseille University, UM2, Marseille, France , Institut National de la Santé et de la Recherche Médicale (Inserm), U1104, Marseille, France , Centre National de la Recherche Scientifique (CNRS) UMR7280, Marseille, France.|Centre dImmunologie de Marseille-Luminy (CIML), Aix-Marseille University, UM2, Marseille, France , Institut National de la Santé et de la Recherche Médicale (Inserm), U1104, Marseille, France , Centre National de la Recherche Scientifique (CNRS) UMR7280, Marseille, France.|Centre dImmunologie de Marseille-Luminy (CIML), Aix-Marseille University, UM2, Marseille, France , Institut National de la Santé et de la Recherche Médicale (Inserm), U1104, Marseille, France , Centre National de la Recherche Scientifique (CNRS) UMR7280, Marseille, France.|Centre dImmunologie de Marseille-Luminy (CIML), Aix-Marseille University, UM2, Marseille, France , Institut National de la Santé et de la Recherche Médicale (Inserm), U1104, Marseille, France , Centre National de la Recherche Scientifique (CNRS) UMR7280, Marseille, France.|Centre dImmunologie de Marseille-Luminy (CIML), Aix-Marseille University, UM2, Marseille, France , Institut National de la Santé et de la Recherche Médicale (Inserm), U1104, Marseille, France , Centre National de la Recherche Scientifique (CNRS) UMR7280, Marseille, France.', 'France|France|France|France|France|France|France|France|France|France|France', 14, 'Animals|COS Cells|Calcium|Cercopithecus aethiops|Humans|Molecular Probes|Signal Transduction|Software|T-Lymphocytes', 'Journal Article', '10.1371/journal.pcbi.1003245', '24086124', 'We introduce a series of experimental procedures enabling sensitive calcium monitoring in T cell populations by confocal video-microscopy. Tracking and post-acquisition analysis was performed using Methods for Automated and Accurate Analysis of Cell Signals (MAAACS), a fully customized program that associates a high throughput tracking algorithm, an intuitive reconnection routine and a statistical platform to provide, at a glance, the calcium barcode of a population of individual T-cells. Combined with a sensitive calcium probe, this method allowed us to unravel the heterogeneity in shape and intensity of the calcium response in T cell populations and especially in naive T cells, which display intracellular calcium oscillations upon stimulation by antigen presenting cells. '),
(86209, 2013, 'plos', 'Thermal adaptation of conformational dynamics in ribonuclease H', 'Stafford, Kate A|Robustelli, Paul|Palmer, Arthur G', 'Department of Biochemistry and Molecular Biophysics, Columbia University, New York, New York, United States of America.|Department of Biochemistry and Molecular Biophysics, Columbia University, New York, New York, United States of America.|Department of Biochemistry and Molecular Biophysics, Columbia University, New York, New York, United States of America.', 'United States|United States|United States', 16, 'Amino Acid Sequence|Bacterial Proteins|Computational Biology|Molecular Dynamics Simulation|Molecular Sequence Data|Principal Component Analysis|Protein Binding|Protein Conformation|Ribonuclease H|Thermodynamics', 'Journal Article', '10.1371/journal.pcbi.1003218', '24098095', 'The relationship between inherent internal conformational processes and enzymatic activity or thermodynamic stability of proteins has proven difficult to characterize. The study of homologous proteins with differing thermostabilities offers an especially useful approach for understanding the functional aspects of conformational dynamics. In particular, ribonuclease HI (RNase H), an 18 kD globular protein that hydrolyzes the RNA strand of RNA:DNA hybrid substrates, has been extensively studied by NMR spectroscopy to characterize the differences in dynamics between homologs from the mesophilic organism E. coli and the thermophilic organism T. thermophilus. Herein, molecular dynamics simulations are reported for five homologous RNase H proteins of varying thermostabilities and enzymatic activities from organisms of markedly different preferred growth temperatures. For the E. coli and T. thermophilus proteins, strong agreement is obtained between simulated and experimental values for NMR order parameters and for dynamically averaged chemical shifts, suggesting that these simulations can be a productive platform for predicting the effects of individual amino acid residues on dynamic behavior. Analyses of the simulations reveal that a single residue differentiates between two different and otherwise conserved dynamic processes in a region of the protein known to form part of the substrate-binding interface. Additional key residues within these two categories are identified through the temperature-dependence of these conformational processes. '),
(86210, 2013, 'plos', 'Swimming in light: a large-scale computational analysis of the metabolism of Dinoroseobacter shibae', 'Rex, Rene|Bill, Nelli|Schmidt-Hohagen, Kerstin|Schomburg, Dietmar', 'Department of Bioinformatics and Biochemistry, Technische Universitxc3xa4t Braunschweig, Braunschweig, Germany.|Department of Bioinformatics and Biochemistry, Technische Universitxc3xa4t Braunschweig, Braunschweig, Germany.|Department of Bioinformatics and Biochemistry, Technische Universitxc3xa4t Braunschweig, Braunschweig, Germany.|Department of Bioinformatics and Biochemistry, Technische Universitxc3xa4t Braunschweig, Braunschweig, Germany.', 'Germany|Germany|Germany|Germany', 0, 'Biomass|Computational Biology|Metabolic Flux Analysis|Metabolic Networks and Pathways|Rhodobacteraceae', 'Journal Article', '10.1371/journal.pcbi.1003224', '24098096', 'The Roseobacter clade is a ubiquitous group of marine xcexb1-proteobacteria. To gain insight into the versatile metabolism of this clade, we took a constraint-based approach and created a genome-scale metabolic model (iDsh827) of Dinoroseobacter shibae DFL12T. Our model is the first accounting for the energy demand of motility, the light-driven ATP generation and experimentally determined specific biomass composition. To cover a large variety of environmental conditions, as well as plasmid and single gene knock-out mutants, we simulated 391,560 different physiological states using flux balance analysis. We analyzed our results with regard to energy metabolism, validated them experimentally, and revealed a pronounced metabolic response to the availability of light. Furthermore, we introduced the energy demand of motility as an important parameter in genome-scale metabolic models. The results of our simulations also gave insight into the changing usage of the two degradation routes for dimethylsulfoniopropionate, an abundant compound in the ocean. A side product of dimethylsulfoniopropionate degradation is dimethyl sulfide, which seeds cloud formation and thus enhances the reflection of sunlight. By our exhaustive simulations, we were able to identify single-gene knock-out mutants, which show an increased production of dimethyl sulfide. In addition to the single-gene knock-out simulations we studied the effect of plasmid loss on the metabolism. Moreover, we explored the possible use of a functioning phosphofructokinase for D. shibae. '),
(86211, 2013, 'plos', 'Sensitive detection of viral transcripts in human tumor transcriptomes', 'Schelhorn, Sven-Eric|Fischer, Matthias|Tolosi, Laura|Altmüller, Janine|Nürnberg, Peter|Pfister, Herbert|Lengauer, Thomas|Berthold, Frank', 'Max-Planck-Institute for Informatics, Campus E1.4, Saarbrücken, Germany.|Max-Planck-Institute for Informatics, Campus E1.4, Saarbrücken, Germany.|Max-Planck-Institute for Informatics, Campus E1.4, Saarbrücken, Germany.|Max-Planck-Institute for Informatics, Campus E1.4, Saarbrücken, Germany.|Max-Planck-Institute for Informatics, Campus E1.4, Saarbrücken, Germany.|Max-Planck-Institute for Informatics, Campus E1.4, Saarbrücken, Germany.|Max-Planck-Institute for Informatics, Campus E1.4, Saarbrücken, Germany.|Max-Planck-Institute for Informatics, Campus E1.4, Saarbrücken, Germany.', 'Germany|Germany|Germany|Germany|Germany|Germany|Germany|Germany', 18, 'Cell Line, Tumor|Computational Biology|High-Throughput Nucleotide Sequencing|Humans|Neoplasms|Neuroblastoma|Phylogeny|RNA|RNA, Viral|Sequence Analysis, RNA|Sequence Homology, Nucleic Acid|Transcriptome|Viruses', 'Journal Article', '10.1371/journal.pcbi.1003228', '24098097', 'In excess of 12% of human cancer incidents have a viral cofactor. Epidemiological studies of idiopathic human cancers indicate that additional tumor viruses remain to be discovered. Recent advances in sequencing technology have enabled systematic screenings of human tumor transcriptomes for viral transcripts. However, technical problems such as low abundances of viral transcripts in large volumes of sequencing data, viral sequence divergence, and homology between viral and human factors significantly confound identification of tumor viruses. We have developed a novel computational approach for detecting viral transcripts in human cancers that takes the aforementioned confounding factors into account and is applicable to a wide variety of viruses and tumors. We apply the approach to conducting the first systematic search for viruses in neuroblastoma, the most common cancer in infancy. The diverse clinical progression of this disease as well as related epidemiological and virological findings are highly suggestive of a pathogenic cofactor. However, a viral etiology of neuroblastoma is currently contested. We mapped 14 transcriptomes of neuroblastoma as well as positive and negative controls to the human and all known viral genomes in order to detect both known and unknown viruses. Analysis of controls, comparisons with related methods, and statistical estimates demonstrate the high sensitivity of our approach. Detailed investigation of putative viral transcripts within neuroblastoma samples did not provide evidence for the existence of any known human viruses. Likewise, de-novo assembly and analysis of chimeric transcripts did not result in expression signatures associated with novel human pathogens. While confounding factors such as sample dilution or viral clearance in progressed tumors may mask viral cofactors in the data, in principle, this is rendered less likely by the high sensitivity of our approach and the number of biological replicates analyzed. Therefore, our results suggest that frequent viral cofactors of metastatic neuroblastoma are unlikely.'),
(86212, 2013, 'plos', 'ToPS: a framework to manipulate probabilistic models of sequence data', 'Kashiwabara, André Yoshiaki|Bonadio, Igor|Onuchic, Vitor|Amado, Felipe|Mathias, Rafael|Durham, Alan Mitchell', 'Graduate Program in Informatics, Federal University of Technology - Paraná, Cornélio Procópio, Paraná, Brazil.|Graduate Program in Informatics, Federal University of Technology - Paraná, Cornélio Procópio, Paraná, Brazil.|Graduate Program in Informatics, Federal University of Technology - Paraná, Cornélio Procópio, Paraná, Brazil.|Graduate Program in Informatics, Federal University of Technology - Paraná, Cornélio Procópio, Paraná, Brazil.|Graduate Program in Informatics, Federal University of Technology - Paraná, Cornélio Procópio, Paraná, Brazil.|Graduate Program in Informatics, Federal University of Technology - Paraná, Cornélio Procópio, Paraná, Brazil.', 'Brazil|Brazil|Brazil|Brazil|Brazil|Brazil', 1, 'Bayes Theorem|Computational Biology|CpG Islands|Markov Chains|Sequence Analysis', 'Journal Article', '10.1371/journal.pcbi.1003234', '24098098', 'Discrete Markovian models can be used to characterize patterns in sequences of values and have many applications in biological sequence analysis, including gene prediction, CpG island detection, alignment, and protein profiling. We present ToPS, a computational framework that can be used to implement different applications in bioinformatics analysis by combining eight kinds of models: (i) independent and identically distributed process, (ii) variable-length Markov chain, (iii) inhomogeneous Markov chain, (iv) hidden Markov model, (v) profile hidden Markov model, (vi) pair hidden Markov model, (vii) generalized hidden Markov model, and (viii) similarity based sequence weighting. The framework includes functionality for training, simulation and decoding of the models. Additionally, it provides two methods to help parameter setting: Akaike and Bayesian information criteria (AIC and BIC). The models can be used stand-alone, combined in Bayesian classifiers, or included in more complex, multi-model, probabilistic architectures using GHMMs. In particular the framework provides a novel, flexible, implementation of decoding in GHMMs that detects when the architecture can be traversed efficiently. '),
(86213, 2013, 'plos', 'Ligand clouds around protein clouds: a scenario of ligand binding with intrinsically disordered proteins', 'Jin, Fan|Yu, Chen|Lai, Luhua|Liu, Zhirong', 'BNLMS, State Key Laboratory for Structural Chemistry of Unstable and Stable Species, College of Chemistry and Molecular Engineering, Peking University, Beijing, China , Center for Quantitative Biology, Peking University, Beijing, China.|BNLMS, State Key Laboratory for Structural Chemistry of Unstable and Stable Species, College of Chemistry and Molecular Engineering, Peking University, Beijing, China , Center for Quantitative Biology, Peking University, Beijing, China.|BNLMS, State Key Laboratory for Structural Chemistry of Unstable and Stable Species, College of Chemistry and Molecular Engineering, Peking University, Beijing, China , Center for Quantitative Biology, Peking University, Beijing, China.|BNLMS, State Key Laboratory for Structural Chemistry of Unstable and Stable Species, College of Chemistry and Molecular Engineering, Peking University, Beijing, China , Center for Quantitative Biology, Peking University, Beijing, China.', 'China|China|China|China', 39, 'Computational Biology|Drug Design|Intrinsically Disordered Proteins|Ligands|Molecular Dynamics Simulation|Protein Binding|Protein Conformation|Proto-Oncogene Proteins c-myc|Thermodynamics', 'Journal Article', '10.1371/journal.pcbi.1003249', '24098099', 'Intrinsically disordered proteins (IDPs) were found to be widely associated with human diseases and may serve as potential drug design targets. However, drug design targeting IDPs is still in the very early stages. Progress in drug design is usually achieved using experimental screening, however, the structural disorder of IDPs makes it difficult to characterize their interaction with ligands using experiments alone. To better understand the structure of IDPs and their interactions with small molecule ligands, we performed extensive simulations on the c-Mycxe2x82x83xe2x82x87xe2x82x80xe2x82x8bxe2x82x84xe2x82x80xe2x82x89 peptide and its binding to a reported small molecule inhibitor, ligand 10074-A4. We found that the conformational space of the apo c-Mycxe2x82x83xe2x82x87xe2x82x80xe2x82x8bxe2x82x84xe2x82x80xe2x82x89 peptide was rather dispersed and that the conformations of the peptide were stabilized mainly by charge interactions and hydrogen bonds. Under the binding of the ligand, c-Mycxe2x82x83xe2x82x87xe2x82x80xe2x82x8bxe2x82x84xe2x82x80xe2x82x89 remained disordered. The ligand was found to bind to c-Mycxe2x82x83xe2x82x87xe2x82x80xe2x82x8bxe2x82x84xe2x82x80xe2x82x89 at different sites along the chain and behaved like a ligand cloud. In contrast to ligand binding to more rigid target proteins that usually results in a dominant bound structure, ligand binding to IDPs may better be described as ligand clouds around protein clouds. Nevertheless, the binding of the ligand and a non-ligand to the c-Mycxe2x82x83xe2x82x87xe2x82x80xe2x82x8bxe2x82x84xe2x82x80xe2x82x89 target could be clearly distinguished. The present study provides insights that will help improve rational drug design that targets IDPs.'),
(86214, 2013, 'plos', 'The lazy visual word form area: computational insights into location-sensitivity', 'Hannagan, Thomas|Grainger, Jonathan', 'Laboratoire de Psychologie Cognitive, CNRS & Aix-Marseille University, Marseille, France.|Laboratoire de Psychologie Cognitive, CNRS & Aix-Marseille University, Marseille, France.', 'France|France', 1, 'Computational Biology|Computer Simulation|Humans|Models, Neurological|Pattern Recognition, Visual', 'Journal Article', '10.1371/journal.pcbi.1003250', '24098100', 'In a recent study, Rauschecker et al. convincingly demonstrate that visual words evoke neural activation signals in the Visual Word Form Area that can be classified based on where they were presented in the visual fields. This result goes against the prevailing consensus, and begs an explanation. We show that one of the simplest possible models for word recognition, a multilayer feedforward network, will exhibit precisely the same behavior when trained to recognize words at different locations. The model suggests that the VWFA initially starts with information about location, which is not being suppressed during reading acquisition more than is needed to meet the requirements of location-invariant word recognition. Some new interpretations of Rauschecker et al.s results are proposed, and three specific predictions are derived to be tested in further studies. ');
INSERT INTO `papers` (`id`, `ano`, `journal`, `titulo`, `autores`, `afiliacao`, `pais`, `citacoes`, `palavra_chave`, `categorias`, `doi`, `pubmed`, `abstract`) VALUES
(86215, 2013, 'plos', 'Cellular adaptation facilitates sparse and reliable coding in sensory pathways', 'Farkhooi, Farzad|Froese, Anja|Muller, Eilif|Menzel, Randolf|Nawrot, Martin P', 'Neuroinformatics & Theoretical Neuroscience, Freie Universität Berlin, and Bernstein Center for Computational Neuroscience Berlin, Berlin, Germany.|Neuroinformatics & Theoretical Neuroscience, Freie Universität Berlin, and Bernstein Center for Computational Neuroscience Berlin, Berlin, Germany.|Neuroinformatics & Theoretical Neuroscience, Freie Universität Berlin, and Bernstein Center for Computational Neuroscience Berlin, Berlin, Germany.|Neuroinformatics & Theoretical Neuroscience, Freie Universität Berlin, and Bernstein Center for Computational Neuroscience Berlin, Berlin, Germany.|Neuroinformatics & Theoretical Neuroscience, Freie Universität Berlin, and Bernstein Center for Computational Neuroscience Berlin, Berlin, Germany.', 'Germany|Germany|Germany|Germany|Germany', 24, 'Action Potentials|Animals|Bees|Computer Simulation|Models, Neurological|Mushroom Bodies|Sensory Receptor Cells|Smell', 'Journal Article', '10.1371/journal.pcbi.1003251', '24098101', 'Most neurons in peripheral sensory pathways initially respond vigorously when a preferred stimulus is presented, but adapt as stimulation continues. It is unclear how this phenomenon affects stimulus coding in the later stages of sensory processing. Here, we show that a temporally sparse and reliable stimulus representation develops naturally in sequential stages of a sensory network with adapting neurons. As a modeling framework we employ a mean-field approach together with an adaptive population density treatment, accompanied by numerical simulations of spiking neural networks. We find that cellular adaptation plays a critical role in the dynamic reduction of the trial-by-trial variability of cortical spike responses by transiently suppressing self-generated fast fluctuations in the cortical balanced network. This provides an explanation for a widespread cortical phenomenon by a simple mechanism. We further show that in the insect olfactory system cellular adaptation is sufficient to explain the emergence of the temporally sparse and reliable stimulus representation in the mushroom body. Our results reveal a generic, biophysically plausible mechanism that can explain the emergence of a temporally sparse and reliable stimulus representation within a sequential processing architecture. '),
(86216, 2013, 'plos', 'Target prediction for an open access set of compounds active against Mycobacterium tuberculosis', 'Martínez-Jiménez, Francisco|Papadatos, George|Yang, Lun|Wallace, Iain M|Kumar, Vinod|Pieper, Ursula|Sali, Andrej|Brown, James R|Overington, John P|Marti-Renom, Marc A', 'Genome Biology Group, Centre Nacional dAnàlisi Genòmica (CNAG), Barcelona, Spain , Gene Regulation Stem Cells and Cancer Program, Centre for Genomic Regulation (CRG), Barcelona, Spain.|Genome Biology Group, Centre Nacional dAnàlisi Genòmica (CNAG), Barcelona, Spain , Gene Regulation Stem Cells and Cancer Program, Centre for Genomic Regulation (CRG), Barcelona, Spain.|Genome Biology Group, Centre Nacional dAnàlisi Genòmica (CNAG), Barcelona, Spain , Gene Regulation Stem Cells and Cancer Program, Centre for Genomic Regulation (CRG), Barcelona, Spain.|Genome Biology Group, Centre Nacional dAnàlisi Genòmica (CNAG), Barcelona, Spain , Gene Regulation Stem Cells and Cancer Program, Centre for Genomic Regulation (CRG), Barcelona, Spain.|Genome Biology Group, Centre Nacional dAnàlisi Genòmica (CNAG), Barcelona, Spain , Gene Regulation Stem Cells and Cancer Program, Centre for Genomic Regulation (CRG), Barcelona, Spain.|Genome Biology Group, Centre Nacional dAnàlisi Genòmica (CNAG), Barcelona, Spain , Gene Regulation Stem Cells and Cancer Program, Centre for Genomic Regulation (CRG), Barcelona, Spain.|Genome Biology Group, Centre Nacional dAnàlisi Genòmica (CNAG), Barcelona, Spain , Gene Regulation Stem Cells and Cancer Program, Centre for Genomic Regulation (CRG), Barcelona, Spain.|Genome Biology Group, Centre Nacional dAnàlisi Genòmica (CNAG), Barcelona, Spain , Gene Regulation Stem Cells and Cancer Program, Centre for Genomic Regulation (CRG), Barcelona, Spain.|Genome Biology Group, Centre Nacional dAnàlisi Genòmica (CNAG), Barcelona, Spain , Gene Regulation Stem Cells and Cancer Program, Centre for Genomic Regulation (CRG), Barcelona, Spain.|Genome Biology Group, Centre Nacional dAnàlisi Genòmica (CNAG), Barcelona, Spain , Gene Regulation Stem Cells and Cancer Program, Centre for Genomic Regulation (CRG), Barcelona, Spain.', 'Spain|Spain|Spain|Spain|Spain|Spain|Spain|Spain|Spain|Spain', 37, 'Amino Acid Sequence|Antitubercular Agents|Bacterial Proteins|Computational Biology|Databases, Chemical|Drug Discovery|Molecular Docking Simulation|Molecular Sequence Data|Mycobacterium tuberculosis|Protein Conformation|Sequence Alignment', 'Journal Article', '10.1371/journal.pcbi.1003253', '24098102', 'Mycobacterium tuberculosis, the causative agent of tuberculosis (TB), infects an estimated two billion people worldwide and is the leading cause of mortality due to infectious disease. The development of new anti-TB therapeutics is required, because of the emergence of multi-drug resistance strains as well as co-infection with other pathogens, especially HIV. Recently, the pharmaceutical company GlaxoSmithKline published the results of a high-throughput screen (HTS) of their two million compound library for anti-mycobacterial phenotypes. The screen revealed 776 compounds with significant activity against the M. tuberculosis H37Rv strain, including a subset of 177 prioritized compounds with high potency and low in vitro cytotoxicity. The next major challenge is the identification of the target proteins. Here, we use a computational approach that integrates historical bioassay data, chemical properties and structural comparisons of selected compounds to propose their potential targets in M. tuberculosis. We predicted 139 target--compound links, providing a necessary basis for further studies to characterize the mode of action of these compounds. The results from our analysis, including the predicted structural models, are available to the wider scientific community in the open source mode, to encourage further development of novel TB therapeutics.'),
(86217, 2013, 'plos', 'Lipid receptor S1Pxe2x82x81 activation scheme concluded from microsecond all-atom molecular dynamics simulations', 'Yuan, Shuguang|Wu, Rongliang|Latek, Dorota|Trzaskowski, Bartosz|Filipek, Slawomir', 'International Institute of Molecular and Cell Biology in Warsaw, Warsaw, Poland , Laboratory of Physical Chemistry of Polymers and Membranes, xc3x89cole Polytechnique Fxc3xa9dxc3xa9rale de Lausanne, SB ISIC LCPPM, Lausanne, Switzerland , Nencki Institute of Experimental Biology, Polish Academy of Sciences, Warsaw, Poland.|International Institute of Molecular and Cell Biology in Warsaw, Warsaw, Poland , Laboratory of Physical Chemistry of Polymers and Membranes, xc3x89cole Polytechnique Fxc3xa9dxc3xa9rale de Lausanne, SB ISIC LCPPM, Lausanne, Switzerland , Nencki Institute of Experimental Biology, Polish Academy of Sciences, Warsaw, Poland.|International Institute of Molecular and Cell Biology in Warsaw, Warsaw, Poland , Laboratory of Physical Chemistry of Polymers and Membranes, xc3x89cole Polytechnique Fxc3xa9dxc3xa9rale de Lausanne, SB ISIC LCPPM, Lausanne, Switzerland , Nencki Institute of Experimental Biology, Polish Academy of Sciences, Warsaw, Poland.|International Institute of Molecular and Cell Biology in Warsaw, Warsaw, Poland , Laboratory of Physical Chemistry of Polymers and Membranes, xc3x89cole Polytechnique Fxc3xa9dxc3xa9rale de Lausanne, SB ISIC LCPPM, Lausanne, Switzerland , Nencki Institute of Experimental Biology, Polish Academy of Sciences, Warsaw, Poland.|International Institute of Molecular and Cell Biology in Warsaw, Warsaw, Poland , Laboratory of Physical Chemistry of Polymers and Membranes, xc3x89cole Polytechnique Fxc3xa9dxc3xa9rale de Lausanne, SB ISIC LCPPM, Lausanne, Switzerland , Nencki Institute of Experimental Biology, Polish Academy of Sciences, Warsaw, Poland.', 'Switzerland|Switzerland|Switzerland|Switzerland|Switzerland', 22, 'DNA Mutational Analysis|Lysophospholipids|Molecular Dynamics Simulation|Receptors, Lysosphingolipid|Sphingosine|Water', 'Journal Article', '10.1371/journal.pcbi.1003261', '24098103', 'Sphingosine 1-phosphate (S1P) is a lysophospholipid mediator which activates G protein-coupled sphingosine 1-phosphate receptors and thus evokes a variety of cell and tissue responses including lymphocyte trafficking, endothelial development, integrity, and maturation. We performed five all-atom 700 ns molecular dynamics simulations of the sphingosine 1-phosphate receptor 1 (S1Pxe2x82x81) based on recently released crystal structure of that receptor with an antagonist. We found that the initial movements of amino acid residues occurred in the area of highly conserved W269xe2x81xb6xc2xb7xe2x81xb4xe2x81xb8 in TM6 which is close to the ligand binding location. Those residues located in the central part of the receptor and adjacent to kinks of TM helices comprise of a transmission switch. Side chains movements of those residues were coupled to the movements of water molecules inside the receptor which helped in the gradual opening of intracellular part of the receptor. The most stable parts of the protein were helices TM1 and TM2, while the largest movement was observed for TM7, possibly due to the short intracellular part starting with a helix kink at Pxe2x81xb7xc2xb7xe2x81xb5xe2x81xb0, which might be the first helix to move at the intracellular side. We show for the first time the detailed view of the concerted action of the transmission switch and Trp (Wxe2x81xb6xc2xb7xe2x81xb4xe2x81xb8) rotamer toggle switch leading to redirection of water molecules flow in the central part of the receptor. That event is a prerequisite for subsequent changes in intracellular part of the receptor involving water influx and opening of the receptor structure.'),
(86218, 2013, 'plos', 'How Can PLoS Computational Biology help the biological sciences?', 'Nussinov, Ruth', 'Basic Science Program, SAIC-Frederick, Inc., Cancer and Inflammation Program, National Cancer Institute, Frederick, Maryland, United States of America , Sackler Institute of Molecular Medicine, Department of Human Genetics and Molecular Medicine, Sackler School of Medicine, Tel Aviv University, Tel Aviv, Israel.', 'Israel', 0, 'Biological Science Disciplines|Computational Biology|Periodicals as Topic', 'Editorial', '10.1371/journal.pcbi.1003262', '24098104', '-'),
(86219, 2013, 'plos', 'Balanced excitatory and inhibitory synaptic currents promote efficient coding and metabolic efficiency', 'Sengupta, Biswa|Laughlin, Simon B|Niven, Jeremy E', 'Wellcome Trust Centre for Neuroimaging, University College London, London, United Kingdom , Centre for Neuroscience, Indian Institute of Science, Bangalore, India.|Wellcome Trust Centre for Neuroimaging, University College London, London, United Kingdom , Centre for Neuroscience, Indian Institute of Science, Bangalore, India.|Wellcome Trust Centre for Neuroimaging, University College London, London, United Kingdom , Centre for Neuroscience, Indian Institute of Science, Bangalore, India.', 'United Kingdom|United Kingdom|United Kingdom', 49, 'Action Potentials|Cerebral Cortex|Computer Simulation|Humans|Models, Neurological|Neurons|Synapses|Synaptic Transmission', 'Journal Article', '10.1371/journal.pcbi.1003263', '24098105', 'A balance between excitatory and inhibitory synaptic currents is thought to be important for several aspects of information processing in cortical neurons in vivo, including gain control, bandwidth and receptive field structure. These factors will affect the firing rate of cortical neurons and their reliability, with consequences for their information coding and energy consumption. Yet how balanced synaptic currents contribute to the coding efficiency and energy efficiency of cortical neurons remains unclear. We used single compartment computational models with stochastic voltage-gated ion channels to determine whether synaptic regimes that produce balanced excitatory and inhibitory currents have specific advantages over other input regimes. Specifically, we compared models with only excitatory synaptic inputs to those with equal excitatory and inhibitory conductances, and stronger inhibitory than excitatory conductances (i.e. approximately balanced synaptic currents). Using these models, we show that balanced synaptic currents evoke fewer spikes per second than excitatory inputs alone or equal excitatory and inhibitory conductances. However, spikes evoked by balanced synaptic inputs are more informative (bits/spike), so that spike trains evoked by all three regimes have similar information rates (bits/s). Consequently, because spikes dominate the energy consumption of our computational models, approximately balanced synaptic currents are also more energy efficient than other synaptic regimes. Thus, by producing fewer, more informative spikes approximately balanced synaptic currents in cortical neurons can promote both coding efficiency and energy efficiency. '),
(86220, 2013, 'plos', 'The regional student group program of the ISCB student council: stories from the road', 'Macintyre, Geoff|Michaut, Magali|Abeel, Thomas', 'NICTA Victoria Research Laboratory, University of Melbourne, Parkville, Victoria, Australia.|NICTA Victoria Research Laboratory, University of Melbourne, Parkville, Victoria, Australia.|NICTA Victoria Research Laboratory, University of Melbourne, Parkville, Victoria, Australia.', 'Australia|Australia|Australia', 10, 'Computational Biology|Humans|Societies, Scientific|Students', 'Journal Article', '10.1371/journal.pcbi.1003241', '24098107', 'The International Society for Computational Biology (ISCB) Student Council was launched in 2004 to facilitate interaction between young scientists in the fields of bioinformatics and computational biology. Since then, the Student Council has successfully run events and programs to promote the development of the next generation of computational biologists. However, in its early years, the Student Council faced a major challenge, in that students from different geographical regions had different needs, no single activity or event could address the needs of all students. To overcome this challenge, the Student Council created the Regional Student Group (RSG) program. The program consists of locally organised and run student groups that address the specific needs of students in their region. These groups usually encompass a given country, and, via affiliation with the international Student Council, are provided with financial support, organisational support, and the ability to share information with other RSGs. In the last five years, RSGs have been created all over the world and organised activities that have helped develop dynamic bioinformatics student communities. In this article series, we present common themes emerging from RSG initiatives, explain their goals, and highlight the challenges and rewards through specific examples. This article, the first in the series, introduces the Student Council and provides a high-level overview of RSG activities. Our hope is that the article series will be a valuable source of information and inspiration for initiating similar activities in other regions and scientific communities. '),
(86221, 2013, 'plos', 'GINI: from ISH images to gene interaction networks', 'Puniyani, Kriti|Xing, Eric P', 'School of Computer Science, Carnegie Mellon University, Pittsburgh, Pennsylvania, United States of America.|School of Computer Science, Carnegie Mellon University, Pittsburgh, Pennsylvania, United States of America.', 'United States|United States', 9, 'Animals|Computational Biology|Drosophila|Gene Expression Profiling|Gene Regulatory Networks|Image Processing, Computer-Assisted|In Situ Hybridization|Markov Chains', 'Journal Article', '10.1371/journal.pcbi.1003227', '24130465', 'Accurate inference of molecular and functional interactions among genes, especially in multicellular organisms such as Drosophila, often requires statistical analysis of correlations not only between the magnitudes of gene expressions, but also between their temporal-spatial patterns. The ISH (in-situ-hybridization)-based gene expression micro-imaging technology offers an effective approach to perform large-scale spatial-temporal profiling of whole-body mRNA abundance. However, analytical tools for discovering gene interactions from such data remain an open challenge due to various reasons, including difficulties in extracting canonical representations of gene activities from images, and in inference of statistically meaningful networks from such representations. In this paper, we present GINI, a machine learning system for inferring gene interaction networks from Drosophila embryonic ISH images. GINI builds on a computer-vision-inspired vector-space representation of the spatial pattern of gene expression in ISH images, enabled by our recently developed [Formula: see text] system, and a new multi-instance-kernel algorithm that learns a sparse Markov network model, in which, every gene (i.e., node) in the network is represented by a vector-valued spatial pattern rather than a scalar-valued gene intensity as in conventional approaches such as a Gaussian graphical model. By capturing the notion of spatial similarity of gene expression, and at the same time properly taking into account the presence of multiple images per gene via multi-instance kernels, GINI is well-positioned to infer statistically sound, and biologically meaningful gene interaction networks from image data. Using both synthetic data and a small manually curated data set, we demonstrate the effectiveness of our approach in network building. Furthermore, we report results on a large publicly available collection of Drosophila embryonic ISH images from the Berkeley Drosophila Genome Project, where GINI makes novel and interesting predictions of gene interactions. Software for GINI is available at http://sailing.cs.cmu.edu/Drosophila_ISH_images/ '),
(86222, 2013, 'plos', 'Human genome replication proceeds through four chromatin states', 'Julienne, Hanna|Zoufir, Azedine|Audit, Benjamin|Arneodo, Alain', 'Université de Lyon, Lyon, France , Laboratoire de Physique, CNRS UMR 5672, Ecole Normale Supérieure de Lyon, Lyon, France.|Université de Lyon, Lyon, France , Laboratoire de Physique, CNRS UMR 5672, Ecole Normale Supérieure de Lyon, Lyon, France.|Université de Lyon, Lyon, France , Laboratoire de Physique, CNRS UMR 5672, Ecole Normale Supérieure de Lyon, Lyon, France.|Université de Lyon, Lyon, France , Laboratoire de Physique, CNRS UMR 5672, Ecole Normale Supérieure de Lyon, Lyon, France.', 'France|France|France|France', 39, 'Chromatin|Cluster Analysis|Computational Biology|DNA Replication|Gene Expression|Genome, Human|Humans|K562 Cells|Principal Component Analysis|Statistics, Nonparametric', 'Journal Article', '10.1371/journal.pcbi.1003233', '24130466', 'Advances in genomic studies have led to significant progress in understanding the epigenetically controlled interplay between chromatin structure and nuclear functions. Epigenetic modifications were shown to play a key role in transcription regulation and genome activity during development and differentiation or in response to the environment. Paradoxically, the molecular mechanisms that regulate the initiation and the maintenance of the spatio-temporal replication program in higher eukaryotes, and in particular their links to epigenetic modifications, still remain elusive. By integrative analysis of the genome-wide distributions of thirteen epigenetic marks in the human cell line K562, at the 100 kb resolution of corresponding mean replication timing (MRT) data, we identify four major groups of chromatin marks with shared features. These states have different MRT, namely from early to late replicating, replication proceeds though a transcriptionally active euchromatin state (C1), a repressive type of chromatin (C2) associated with polycomb complexes, a silent state (C3) not enriched in any available marks, and a gene poor HP1-associated heterochromatin state (C4). When mapping these chromatin states inside the megabase-sized U-domains (U-shaped MRT profile) covering about 50% of the human genome, we reveal that the associated replication fork polarity gradient corresponds to a directional path across the four chromatin states, from C1 at U-domains borders followed by C2, C3 and C4 at centers. Analysis of the other genome half is consistent with early and late replication loci occurring in separate compartments, the former correspond to gene-rich, high-GC domains of intermingled chromatin states C1 and C2, whereas the latter correspond to gene-poor, low-GC domains of alternating chromatin states C3 and C4 or long C4 domains. This new segmentation sheds a new light on the epigenetic regulation of the spatio-temporal replication program in human and provides a framework for further studies in different cell types, in both health and disease. '),
(86223, 2013, 'plos', 'A genome-scale integration and analysis of Lactococcus lactis translation data', 'Racle, Julien|Picard, Flora|Girbal, Laurence|Cocaign-Bousquet, Muriel|Hatzimanikatis, Vassily', 'Laboratory of Computational Systems Biotechnology, Ecole Polytechnique Fédérale de Lausanne (EPFL), Lausanne, Switzerland , Swiss Institute of Bioinformatics (SIB), Lausanne, Switzerland.|Laboratory of Computational Systems Biotechnology, Ecole Polytechnique Fédérale de Lausanne (EPFL), Lausanne, Switzerland , Swiss Institute of Bioinformatics (SIB), Lausanne, Switzerland.|Laboratory of Computational Systems Biotechnology, Ecole Polytechnique Fédérale de Lausanne (EPFL), Lausanne, Switzerland , Swiss Institute of Bioinformatics (SIB), Lausanne, Switzerland.|Laboratory of Computational Systems Biotechnology, Ecole Polytechnique Fédérale de Lausanne (EPFL), Lausanne, Switzerland , Swiss Institute of Bioinformatics (SIB), Lausanne, Switzerland.|Laboratory of Computational Systems Biotechnology, Ecole Polytechnique Fédérale de Lausanne (EPFL), Lausanne, Switzerland , Swiss Institute of Bioinformatics (SIB), Lausanne, Switzerland.', 'Switzerland|Switzerland|Switzerland|Switzerland|Switzerland', 18, 'Bacterial Proteins|Computational Biology|Databases, Protein|Genome, Bacterial|Lactococcus lactis|Polyribosomes|Protein Biosynthesis', 'Journal Article', '10.1371/journal.pcbi.1003240', '24130467', 'Protein synthesis is a template polymerization process composed by three main steps: initiation, elongation, and termination. During translation, ribosomes are engaged into polysomes whose size is used for the quantitative characterization of translatome. However, simultaneous transcription and translation in the bacterial cytosol complicates the analysis of translatome data. We established a procedure for robust estimation of the ribosomal density in hundreds of genes from Lactococcus lactis polysome size measurements. We used a mechanistic model of translation to integrate the information about the ribosomal density and for the first time we estimated the protein synthesis rate for each gene and identified the rate limiting steps. Contrary to conventional considerations, we find significant number of genes to be elongation limited. This number increases during stress conditions compared to optimal growth and proteins synthesized at maximum rate are predominantly elongation limited. Consistent with bacterial physiology, we found proteins with similar rate and control characteristics belonging to the same functional categories. Under stress conditions, we found that synthesis rate of regulatory proteins is becoming comparable to proteins favored under optimal growth. These findings suggest that the coupling of metabolic states and protein synthesis is more important than previously thought.'),
(86224, 2013, 'plos', 'Simple topological features reflect dynamics and modularity in protein interaction networks', 'Pritykin, Yuri|Singh, Mona', 'Department of Computer Science, Princeton University, Princeton, New Jersey, United States of America , Lewis-Sigler Institute for Integrative Genomics, Princeton University, Princeton, New Jersey, United States of America.|Department of Computer Science, Princeton University, Princeton, New Jersey, United States of America , Lewis-Sigler Institute for Integrative Genomics, Princeton University, Princeton, New Jersey, United States of America.', 'Jersey|Jersey', 17, 'Animals|Cluster Analysis|Computational Biology|Databases, Protein|Drosophila melanogaster|Escherichia coli|Humans|Protein Interaction Mapping|Protein Interaction Maps|Proteins|Saccharomyces cerevisiae|Statistics, Nonparametric', 'Journal Article', '10.1371/journal.pcbi.1003243', '24130468', 'The availability of large-scale protein-protein interaction networks for numerous organisms provides an opportunity to comprehensively analyze whether simple properties of proteins are predictive of the roles they play in the functional organization of the cell. We begin by re-examining an influential but controversial characterization of the dynamic modularity of the S. cerevisiae interactome that incorporated gene expression data into network analysis. We analyse the protein-protein interaction networks of five organisms, S. cerevisiae, H. sapiens, D. melanogaster, A. thaliana, and E. coli, and confirm significant and consistent functional and structural differences between hub proteins that are co-expressed with their interacting partners and those that are not, and support the view that the former tend to be intramodular whereas the latter tend to be intermodular. However, we also demonstrate that in each of these organisms, simple topological measures are significantly correlated with the average co-expression of a hub with its partners, independent of any classification, and therefore also reflect protein intra- and inter- modularity. Further, cross-interactomic analysis demonstrates that these simple topological characteristics of hub proteins tend to be conserved across organisms. Overall, we give evidence that purely topological features of static interaction networks reflect aspects of the dynamics and modularity of interactomes as well as previous measures incorporating expression data, and are a powerful means for understanding the dynamic roles of hubs in interactomes. '),
(86225, 2013, 'plos', 'A horizontal alignment tool for numerical trend discovery in sequence data: application to protein hydropathy', 'Hadzipasic, Omar|Wrabl, James O|Hilser, Vincent J', 'Department of Biology, Johns Hopkins University, Baltimore, Maryland, United States of America.|Department of Biology, Johns Hopkins University, Baltimore, Maryland, United States of America.|Department of Biology, Johns Hopkins University, Baltimore, Maryland, United States of America.', 'United States|United States|United States', 0, 'Algorithms|Amino Acid Sequence|Bacterial Proteins|Chi-Square Distribution|Cluster Analysis|Computational Biology|Databases, Protein|Humans|Hydrophobic and Hydrophilic Interactions|Molecular Sequence Data|Protein Structure, Secondary|Proteins|Sequence Alignment|Sequence Analysis, Protein|Software', 'Journal Article', '10.1371/journal.pcbi.1003247', '24130469', 'An algorithm is presented that returns the optimal pairwise gapped alignment of two sets of signed numerical sequence values. One distinguishing feature of this algorithm is a flexible comparison engine (based on both relative shape and absolute similarity measures) that does not rely on explicit gap penalties. Additionally, an empirical probability model is developed to estimate the significance of the returned alignment with respect to randomized data. The algorithms utility for biological hypothesis formulation is demonstrated with test cases including database search and pairwise alignment of protein hydropathy. However, the algorithm and probability model could possibly be extended to accommodate other diverse types of protein or nucleic acid data, including positional thermodynamic stability and mRNA translation efficiency. The algorithm requires only numerical values as input and will readily compare data other than protein hydropathy. The tool is therefore expected to complement, rather than replace, existing sequence and structure based tools and may inform medical discovery, as exemplified by proposed similarity between a chlamydial ORFan protein and bacterial colicin pore-forming domain. The source code, documentation, and a basic web-server application are available. '),
(86226, 2013, 'plos', 'Feature selection methods for identifying genetic determinants of host species in RNA viruses', 'Aguas, Ricardo|Ferguson, Neil M', 'MRC Centre for Outbreak Analysis and Modelling, Department of Infectious Disease Epidemiology, Imperial College London, Faculty of Medicine, London, United Kingdom.|MRC Centre for Outbreak Analysis and Modelling, Department of Infectious Disease Epidemiology, Imperial College London, Faculty of Medicine, London, United Kingdom.', 'United Kingdom|United Kingdom', 10, 'Algorithms|Animals|Artificial Intelligence|Binding Sites|Chiroptera|Computational Biology|Evolution, Molecular|Genes, Viral|Host-Pathogen Interactions|Humans|Phenotype|Principal Component Analysis|RNA Viruses|Receptors, Cell Surface|Viral Proteins|Virus Diseases|Zoonoses', 'Journal Article', '10.1371/journal.pcbi.1003254', '24130470', 'Despite environmental, social and ecological dependencies, emergence of zoonotic viruses in human populations is clearly also affected by genetic factors which determine cross-species transmission potential. RNA viruses pose an interesting case study given their mutation rates are orders of magnitude higher than any other pathogen--as reflected by the recent emergence of SARS and Influenza for example. Here, we show how feature selection techniques can be used to reliably classify viral sequences by host species, and to identify the crucial minority of host-specific sites in pathogen genomic data. The variability in alleles at those sites can be translated into prediction probabilities that a particular pathogen isolate is adapted to a given host. We illustrate the power of these methods by: 1) identifying the sites explaining SARS coronavirus differences between human, bat and palm civet samples, 2) showing how cross species jumps of rabies virus among bat populations can be readily identified, and 3) de novo identification of likely functional influenza host discriminant markers.'),
(86227, 2013, 'plos', 'Inferring evolutionary histories of pathway regulation from transcriptional profiling data', 'Schraiber, Joshua G|Mostovoy, Yulia|Hsu, Tiffany Y|Brem, Rachel B', 'Department of Integrative Biology, University of California, Berkeley, Berkeley, California, United States of America.|Department of Integrative Biology, University of California, Berkeley, Berkeley, California, United States of America.|Department of Integrative Biology, University of California, Berkeley, Berkeley, California, United States of America.|Department of Integrative Biology, University of California, Berkeley, Berkeley, California, United States of America.', 'United States|United States|United States|United States', 21, 'Evolution, Molecular|Gene Expression Profiling|Genomics|Models, Genetic|Phylogeny|Saccharomyces', 'Journal Article', '10.1371/journal.pcbi.1003255', '24130471', 'One of the outstanding challenges in comparative genomics is to interpret the evolutionary importance of regulatory variation between species. Rigorous molecular evolution-based methods to infer evidence for natural selection from expression data are at a premium in the field, and to date, phylogenetic approaches have not been well-suited to address the question in the small sets of taxa profiled in standard surveys of gene expression. We have developed a strategy to infer evolutionary histories from expression profiles by analyzing suites of genes of common function. In a manner conceptually similar to molecular evolution models in which the evolutionary rates of DNA sequence at multiple loci follow a gamma distribution, we modeled expression of the genes of an a priori-defined pathway with rates drawn from an inverse gamma distribution. We then developed a fitting strategy to infer the parameters of this distribution from expression measurements, and to identify gene groups whose expression patterns were consistent with evolutionary constraint or rapid evolution in particular species. Simulations confirmed the power and accuracy of our inference method. As an experimental testbed for our approach, we generated and analyzed transcriptional profiles of four Saccharomyces yeasts. The results revealed pathways with signatures of constrained and accelerated regulatory evolution in individual yeasts and across the phylogeny, highlighting the prevalence of pathway-level expression change during the divergence of yeast species. We anticipate that our pathway-based phylogenetic approach will be of broad utility in the search to understand the evolutionary relevance of regulatory change. '),
(86228, 2013, 'plos', 'A simple rule for dendritic spine and axonal bouton formation can account for cortical reorganization after focal retinal lesions', 'Butz, Markus|van Ooyen, Arjen', 'Simulation Lab Neuroscience - Bernstein Facility for Simulation and Database Technology, Institute for Advanced Simulation, Jülich Aachen Research Alliance, Forschungszentrum Jülich, Jülich, Germany.|Simulation Lab Neuroscience - Bernstein Facility for Simulation and Database Technology, Institute for Advanced Simulation, Jülich Aachen Research Alliance, Forschungszentrum Jülich, Jülich, Germany.', 'Germany|Germany', 40, 'Axons|Dendritic Spines|Humans|Models, Neurological|Neurons|Optic Nerve|Retina|Visual Cortex', 'Journal Article', '10.1371/journal.pcbi.1003259', '24130472', 'Lasting alterations in sensory input trigger massive structural and functional adaptations in cortical networks. The principles governing these experience-dependent changes are, however, poorly understood. Here, we examine whether a simple rule based on the neurons need for homeostasis in electrical activity may serve as driving force for cortical reorganization. According to this rule, a neuron creates new spines and boutons when its level of electrical activity is below a homeostatic set-point and decreases the number of spines and boutons when its activity exceeds this set-point. In addition, neurons need a minimum level of activity to form spines and boutons. Spine and bouton formation depends solely on the neurons own activity level, and synapses are formed by merging spines and boutons independently of activity. Using a novel computational model, we show that this simple growth rule produces neuron and network changes as observed in the visual cortex after focal retinal lesions. In the model, as in the cortex, the turnover of dendritic spines was increased strongest in the center of the lesion projection zone, while axonal boutons displayed a marked overshoot followed by pruning. Moreover, the decrease in external input was compensated for by the formation of new horizontal connections, which caused a retinotopic remapping. Homeostatic regulation may provide a unifying framework for understanding cortical reorganization, including network repair in degenerative diseases or following focal stroke. '),
(86229, 2013, 'plos', 'Virus encoded MHC-like decoys diversify the inhibitory KIR repertoire', 'Carrillo-Bustamante, Paola|Kexc5x9fmir, Can|de Boer, Rob J', 'Theoretical Biology & Bioinformatics, Department of Biology, Utrecht University, Utrecht, The Netherlands.|Theoretical Biology & Bioinformatics, Department of Biology, Utrecht University, Utrecht, The Netherlands.|Theoretical Biology & Bioinformatics, Department of Biology, Utrecht University, Utrecht, The Netherlands.', 'Netherlands|Netherlands|Netherlands', 16, 'Animals|Computer Simulation|Evolution, Molecular|Genetic Variation|Haplotypes|Host-Pathogen Interactions|Humans|Killer Cells, Natural|Major Histocompatibility Complex|Mice|Models, Biological|Muromegalovirus|Receptors, KIR', 'Journal Article', '10.1371/journal.pcbi.1003264', '24130473', 'Natural killer (NK) cells are circulating lymphocytes that play an important role in the control of viral infections and tumors. Their functions are regulated by several activating and inhibitory receptors. A subset of these receptors in human NK cells are the killer immunoglobulin-like receptors (KIRs), which interact with the highly polymorphic MHC class I molecules. One important function of NK cells is to detect cells that have down-regulated MHC expression (missing-self). Because MHC molecules have non polymorphic regions, their expression could have been monitored with a limited set of monomorphic receptors. Surprisingly, the KIR family has a remarkable genetic diversity, the function of which remains poorly understood. The mouse cytomegalovirus (MCMV) is able to evade NK cell responses by coding decoy molecules that mimic MHC class I. This interaction was suggested to have driven the evolution of novel NK cell receptors. Inspired by the MCMV system, we develop an agent-based model of a host population infected with viruses that are able to evolve MHC down-regulation and decoy molecules. Our simulations show that specific recognition of MHC class I molecules by inhibitory KIRs provides excellent protection against viruses evolving decoys, and that the diversity of inhibitory KIRs will subsequently evolve as a result of the required discrimination between host MHC molecules and decoy molecules. '),
(86230, 2013, 'plos', 'A network approach to analyzing highly recombinant malaria parasite genes', 'Larremore, Daniel B|Clauset, Aaron|Buckee, Caroline O', 'Department of Epidemiology, Harvard School of Public Health, Boston, Massachusetts, United States of America , Center for Communicable Disease Dynamics, Harvard School of Public Health, Boston, Massachusetts, United States of America.|Department of Epidemiology, Harvard School of Public Health, Boston, Massachusetts, United States of America , Center for Communicable Disease Dynamics, Harvard School of Public Health, Boston, Massachusetts, United States of America.|Department of Epidemiology, Harvard School of Public Health, Boston, Massachusetts, United States of America , Center for Communicable Disease Dynamics, Harvard School of Public Health, Boston, Massachusetts, United States of America.', 'United States|United States|United States', 30, 'Amino Acid Sequence|Computational Biology|Computer Simulation|Genetic Variation|Humans|Malaria, Falciparum|Molecular Sequence Data|Plasmodium falciparum|Protozoan Proteins|Sequence Alignment|Sequence Analysis, DNA|Stochastic Processes', 'Journal Article', '10.1371/journal.pcbi.1003268', '24130474', 'The var genes of the human malaria parasite Plasmodium falciparum present a challenge to population geneticists due to their extreme diversity, which is generated by high rates of recombination. These genes encode a primary antigen protein called PfEMP1, which is expressed on the surface of infected red blood cells and elicits protective immune responses. Var gene sequences are characterized by pronounced mosaicism, precluding the use of traditional phylogenetic tools that require bifurcating tree-like evolutionary relationships. We present a new method that identifies highly variable regions (HVRs), and then maps each HVR to a complex network in which each sequence is a node and two nodes are linked if they share an exact match of significant length. Here, networks of var genes that recombine freely are expected to have a uniformly random structure, but constraints on recombination will produce network communities that we identify using a stochastic block model. We validate this method on synthetic data, showing that it correctly recovers populations of constrained recombination, before applying it to the Duffy Binding Like-xcexb1 (DBLxcexb1) domain of var genes. We find nine HVRs whose network communities map in distinctive ways to known DBLxcexb1 classifications and clinical phenotypes. We show that the recombinational constraints of some HVRs are correlated, while others are independent. These findings suggest that this micromodular structuring facilitates independent evolutionary trajectories of neighboring mosaic regions, allowing the parasite to retain protein function while generating enormous sequence diversity. Our approach therefore offers a rigorous method for analyzing evolutionary constraints in var genes, and is also flexible enough to be easily applied more generally to any highly recombinant sequences. '),
(86231, 2013, 'plos', 'Machines vs ensembles: effective MAPK signaling through heterogeneous sets of protein complexes', 'Suderman, Ryan|Deeds, Eric J', 'Center for Bioinformatics, University of Kansas, Lawrence, Kansas, United States of America.|Center for Bioinformatics, University of Kansas, Lawrence, Kansas, United States of America.', 'United States|United States', 0, 'Computer Simulation|Intracellular Signaling Peptides and Proteins|Least-Squares Analysis|MAP Kinase Signaling System|Models, Biological|Pheromones|Saccharomyces cerevisiae|Saccharomyces cerevisiae Proteins|Systems Biology', 'Journal Article', '10.1371/journal.pcbi.1003278', '24130475', 'Despite the importance of intracellular signaling networks, there is currently no consensus regarding the fundamental nature of the protein complexes such networks employ. One prominent view involves stable signaling machines with well-defined quaternary structures. The combinatorial complexity of signaling networks has led to an opposing perspective, namely that signaling proceeds via heterogeneous pleiomorphic ensembles of transient complexes. Since many hypotheses regarding network function rely on how we conceptualize signaling complexes, resolving this issue is a central problem in systems biology. Unfortunately, direct experimental characterization of these complexes has proven technologically difficult, while combinatorial complexity has prevented traditional modeling methods from approaching this question. Here we employ rule-based modeling, a technique that overcomes these limitations, to construct a model of the yeast pheromone signaling network. We found that this model exhibits significant ensemble character while generating reliable responses that match experimental observations. To contrast the ensemble behavior, we constructed a model that employs hierarchical assembly pathways to produce scaffold-based signaling machines. We found that this machine model could not replicate the experimentally observed combinatorial inhibition that arises when the scaffold is overexpressed. This finding provides evidence against the hierarchical assembly of machines in the pheromone signaling network and suggests that machines and ensembles may serve distinct purposes in vivo. In some cases, e.g. core enzymatic activities like protein synthesis and degradation, machines assembled via hierarchical energy landscapes may provide functional stability for the cell. In other cases, such as signaling, ensembles may represent a form of weak linkage, facilitating variation and plasticity in network evolution. The capacity of ensembles to signal effectively will ultimately shape how we conceptualize the function, evolution and engineering of signaling networks. '),
(86232, 2013, 'plos', 'dPeak: high resolution identification of transcription factor binding sites from PET and SET ChIP-Seq data', 'Chung, Dongjun|Park, Dan|Myers, Kevin|Grass, Jeffrey|Kiley, Patricia|Landick, Robert|Kelexc5x9f, Sxc3xbcndxc3xbcz', 'Department of Statistics, University of Wisconsin, Madison, Wisconsin, United States of America.|Department of Statistics, University of Wisconsin, Madison, Wisconsin, United States of America.|Department of Statistics, University of Wisconsin, Madison, Wisconsin, United States of America.|Department of Statistics, University of Wisconsin, Madison, Wisconsin, United States of America.|Department of Statistics, University of Wisconsin, Madison, Wisconsin, United States of America.|Department of Statistics, University of Wisconsin, Madison, Wisconsin, United States of America.|Department of Statistics, University of Wisconsin, Madison, Wisconsin, United States of America.', 'United States|United States|United States|United States|United States|United States|United States', 11, 'Binding Sites|Chromatin Immunoprecipitation|Computational Biology|DNA, Bacterial|Escherichia coli Proteins|Oligonucleotide Array Sequence Analysis|Sequence Analysis, DNA|Transcription Factors', 'Journal Article', '10.1371/journal.pcbi.1003246', '24146601', 'Chromatin immunoprecipitation followed by high throughput sequencing (ChIP-Seq) has been successfully used for genome-wide profiling of transcription factor binding sites, histone modifications, and nucleosome occupancy in many model organisms and humans. Because the compact genomes of prokaryotes harbor many binding sites separated by only few base pairs, applications of ChIP-Seq in this domain have not reached their full potential. Applications in prokaryotic genomes are further hampered by the fact that well studied data analysis methods for ChIP-Seq do not result in a resolution required for deciphering the locations of nearby binding events. We generated single-end tag (SET) and paired-end tag (PET) ChIP-Seq data for xcfx83xe2x81xb7xe2x81xb0 factor in Escherichia coli (E. coli). Direct comparison of these datasets revealed that although PET assay enables higher resolution identification of binding events, standard ChIP-Seq analysis methods are not equipped to utilize PET-specific features of the data. To address this problem, we developed dPeak as a high resolution binding site identification (deconvolution) algorithm. dPeak implements a probabilistic model that accurately describes ChIP-Seq data generation process for both the SET and PET assays. For SET data, dPeak outperforms or performs comparably to the state-of-the-art high-resolution ChIP-Seq peak deconvolution algorithms such as PICS, GPS, and GEM. When coupled with PET data, dPeak significantly outperforms SET-based analysis with any of the current state-of-the-art methods. Experimental validations of a subset of dPeak predictions from xcfx83xe2x81xb7xe2x81xb0 PET ChIP-Seq data indicate that dPeak can estimate locations of binding events with as high as 2 to 21 bp resolution. Applications of dPeak to xcfx83xe2x81xb7xe2x81xb0 ChIP-Seq data in E. coli under aerobic and anaerobic conditions reveal closely located promoters that are differentially occupied and further illustrate the importance of high resolution analysis of ChIP-Seq data.');
INSERT INTO `papers` (`id`, `ano`, `journal`, `titulo`, `autores`, `afiliacao`, `pais`, `citacoes`, `palavra_chave`, `categorias`, `doi`, `pubmed`, `abstract`) VALUES
(86233, 2013, 'plos', 'Integrated module and gene-specific regulatory inference implicates upstream signaling networks', 'Roy, Sushmita|Lagree, Stephen|Hou, Zhonggang|Thomson, James A|Stewart, Ron|Gasch, Audrey P', 'Department of Biostatistics and Medical Informatics, University of Wisconsin-Madison, Madison, Wisconsin, United States of America , Wisconsin Institute for Discovery, Madison, Wisconsin, United States of America.|Department of Biostatistics and Medical Informatics, University of Wisconsin-Madison, Madison, Wisconsin, United States of America , Wisconsin Institute for Discovery, Madison, Wisconsin, United States of America.|Department of Biostatistics and Medical Informatics, University of Wisconsin-Madison, Madison, Wisconsin, United States of America , Wisconsin Institute for Discovery, Madison, Wisconsin, United States of America.|Department of Biostatistics and Medical Informatics, University of Wisconsin-Madison, Madison, Wisconsin, United States of America , Wisconsin Institute for Discovery, Madison, Wisconsin, United States of America.|Department of Biostatistics and Medical Informatics, University of Wisconsin-Madison, Madison, Wisconsin, United States of America , Wisconsin Institute for Discovery, Madison, Wisconsin, United States of America.|Department of Biostatistics and Medical Informatics, University of Wisconsin-Madison, Madison, Wisconsin, United States of America , Wisconsin Institute for Discovery, Madison, Wisconsin, United States of America.', 'United States|United States|United States|United States|United States|United States', 30, 'Cluster Analysis|Computational Biology|Gene Regulatory Networks|Humans|Models, Genetic|Saccharomyces cerevisiae|Signal Transduction|Software|Transcription Factors', 'Journal Article', '10.1371/journal.pcbi.1003252', '24146602', 'Regulatory networks that control gene expression are important in diverse biological contexts including stress response and development. Each genes regulatory program is determined by module-level regulation (e.g. co-regulation via the same signaling system), as well as gene-specific determinants that can fine-tune expression. We present a novel approach, Modular regulatory network learning with per gene information (MERLIN), that infers regulatory programs for individual genes while probabilistically constraining these programs to reveal module-level organization of regulatory networks. Using edge-, regulator- and module-based comparisons of simulated networks of known ground truth, we find MERLIN reconstructs regulatory programs of individual genes as well or better than existing approaches of network reconstruction, while additionally identifying modular organization of the regulatory networks. We use MERLIN to dissect global transcriptional behavior in two biological contexts: yeast stress response and human embryonic stem cell differentiation. Regulatory modules inferred by MERLIN capture co-regulatory relationships between signaling proteins and downstream transcription factors thereby revealing the upstream signaling systems controlling transcriptional responses. The inferred networks are enriched for regulators with genetic or physical interactions, supporting the inference, and identify modules of functionally related genes bound by the same transcriptional regulators. Our method combines the strengths of per-gene and per-module methods to reveal new insights into transcriptional regulation in stress and development. '),
(86234, 2013, 'plos', 'Reassessing Google Flu Trends data for detection of seasonal and pandemic influenza: a comparative epidemiological study at three geographic scales', 'Olson, Donald R|Konty, Kevin J|Paladini, Marc|Viboud, Cecile|Simonsen, Lone', 'New York City Department of Health and Mental Hygiene, New York, New York, United States of America.|New York City Department of Health and Mental Hygiene, New York, New York, United States of America.|New York City Department of Health and Mental Hygiene, New York, New York, United States of America.|New York City Department of Health and Mental Hygiene, New York, New York, United States of America.|New York City Department of Health and Mental Hygiene, New York, New York, United States of America.', 'United States|United States|United States|United States|United States', 176, 'Algorithms|Computational Biology|Computer Simulation|Humans|Influenza, Human|Pandemics|Population Surveillance|Search Engine|Seasons|Sentinel Surveillance|United States', 'Journal Article', '10.1371/journal.pcbi.1003256', '24146603', 'The goal of influenza-like illness (ILI) surveillance is to determine the timing, location and magnitude of outbreaks by monitoring the frequency and progression of clinical case incidence. Advances in computational and information technology have allowed for automated collection of higher volumes of electronic data and more timely analyses than previously possible. Novel surveillance systems, including those based on internet search query data like Google Flu Trends (GFT), are being used as surrogates for clinically-based reporting of influenza-like-illness (ILI). We investigated the reliability of GFT during the last decade (2003 to 2013), and compared weekly public health surveillance with search query data to characterize the timing and intensity of seasonal and pandemic influenza at the national (United States), regional (Mid-Atlantic) and local (New York City) levels. We identified substantial flaws in the original and updated GFT models at all three geographic scales, including completely missing the first wave of the 2009 influenza A/H1N1 pandemic, and greatly overestimating the intensity of the A/H3N2 epidemic during the 2012/2013 season. These results were obtained for both the original (2008) and the updated (2009) GFT algorithms. The performance of both models was problematic, perhaps because of changes in internet search behavior and differences in the seasonality, geographical heterogeneity and age-distribution of the epidemics between the periods of GFT model-fitting and prospective use. We conclude that GFT data may not provide reliable surveillance for seasonal or pandemic influenza and should be interpreted with caution until the algorithm can be improved and evaluated. Current internet search query data are no substitute for timely local clinical and laboratory surveillance, or national surveillance based on local data collection. New generation surveillance systems such as GFT should incorporate the use of near-real time electronic health data and computational methods for continued model-fitting and ongoing evaluation and improvement. '),
(86235, 2013, 'plos', 'Prediction of the P falciparum target space relevant to malaria drug discovery', 'Spitzmüller, Andreas|Mestres, Jordi', 'Chemotargets SL and Systems Pharmacology, Research Programme on Biomedical Informatics (GRIB), IMIM Hospital del Mar Research Institute and Universitat Pompeu Fabra, Parc de Recerca Biomèdica, Barcelona, Catalonia, Spain.|Chemotargets SL and Systems Pharmacology, Research Programme on Biomedical Informatics (GRIB), IMIM Hospital del Mar Research Institute and Universitat Pompeu Fabra, Parc de Recerca Biomèdica, Barcelona, Catalonia, Spain.', 'Spain|Spain', 28, 'Antimalarials|Computational Biology|Computer Simulation|Databases, Protein|Drug Discovery|Plasmodium falciparum|Protozoan Proteins', 'Journal Article', '10.1371/journal.pcbi.1003257', '24146604', 'Malaria is still one of the most devastating infectious diseases, affecting hundreds of millions of patients worldwide. Even though there are several established drugs in clinical use for malaria treatment, there is an urgent need for new drugs acting through novel mechanisms of action due to the rapid development of resistance. Resistance emerges when the parasite manages to mutate the sequence of the drug targets to the extent that the protein can still perform its function in the parasite but can no longer be inhibited by the drug, which then becomes almost ineffective. The design of a new generation of malaria drugs targeting multiple essential proteins would make it more difficult for the parasite to develop full resistance without lethally disrupting some of its vital functions. The challenge is then to identify which set of Plasmodium falciparum proteins, among the millions of possible combinations, can be targeted at the same time by a given chemotype. To do that, we predicted first the targets of the close to 20,000 antimalarial hits identified recently in three independent phenotypic screening campaigns. All targets predicted were then projected onto the genome of P. falciparum using orthologous relationships. A total of 226 P. falciparum proteins were predicted to be hit by at least one compound, of which 39 were found to be significantly enriched by the presence and degree of affinity of phenotypically active compounds. The analysis of the chemically compatible target combinations containing at least one of those 39 targets led to the identification of a priority set of 64 multi-target profiles that can set the ground for a new generation of more robust malaria drugs. '),
(86236, 2013, 'plos', 'Analysis of initial cell spreading using mechanistic contact formulations for a deformable cell model', 'Odenthal, Tim|Smeets, Bart|Van Liedekerke, Paul|Tijskens, Engelbert|Van Oosterwyck, Hans|Ramon, Herman', 'MeBioS, KU Leuven, Leuven, Belgium.|MeBioS, KU Leuven, Leuven, Belgium.|MeBioS, KU Leuven, Leuven, Belgium.|MeBioS, KU Leuven, Leuven, Belgium.|MeBioS, KU Leuven, Leuven, Belgium.|MeBioS, KU Leuven, Leuven, Belgium.', 'Belgium|Belgium|Belgium|Belgium|Belgium|Belgium', 30, 'Biomechanical Phenomena|Cell Physiological Phenomena|Cell Shape|Computational Biology|Elasticity|Erythrocytes|Models, Biological', 'Journal Article', '10.1371/journal.pcbi.1003267', '24146605', 'Adhesion governs to a large extent the mechanical interaction between a cell and its microenvironment. As initial cell spreading is purely adhesion driven, understanding this phenomenon leads to profound insight in both cell adhesion and cell-substrate interaction. It has been found that across a wide variety of cell types, initial spreading behavior universally follows the same power laws. The simplest cell type providing this scaling of the radius of the spreading area with time are modified red blood cells (RBCs), whose elastic responses are well characterized. Using a mechanistic description of the contact interaction between a cell and its substrate in combination with a deformable RBC model, we are now able to investigate in detail the mechanisms behind this universal power law. The presented model suggests that the initial slope of the spreading curve with time results from a purely geometrical effect facilitated mainly by dissipation upon contact. Later on, the spreading rate decreases due to increasing tension and dissipation in the cells cortex as the cell spreads more and more. To reproduce this observed initial spreading, no irreversible deformations are required. Since the model created in this effort is extensible to more complex cell types and can cope with arbitrarily shaped, smooth mechanical microenvironments of the cells, it can be useful for a wide range of investigations where forces at the cell boundary play a decisive role. '),
(86237, 2013, 'plos', 'Dynamic change of global and local information processing in propofol-induced loss and recovery of consciousness', 'Monti, Martin M|Lutkenhoff, Evan S|Rubinov, Mikail|Boveroux, Pierre|Vanhaudenhuyse, Audrey|Gosseries, Olivia|Bruno, Marie-Aurélie|Noirhomme, Quentin|Boly, Mélanie|Laureys, Steven', 'Department of Psychology, University of California Los Angeles, Los Angeles, California, United States of America , Brain Injury Research Center (BIRC), Department of Neurosurgery, David Geffen School of Medicine at UCLA, Los Angeles, California, United States of America.|Department of Psychology, University of California Los Angeles, Los Angeles, California, United States of America , Brain Injury Research Center (BIRC), Department of Neurosurgery, David Geffen School of Medicine at UCLA, Los Angeles, California, United States of America.|Department of Psychology, University of California Los Angeles, Los Angeles, California, United States of America , Brain Injury Research Center (BIRC), Department of Neurosurgery, David Geffen School of Medicine at UCLA, Los Angeles, California, United States of America.|Department of Psychology, University of California Los Angeles, Los Angeles, California, United States of America , Brain Injury Research Center (BIRC), Department of Neurosurgery, David Geffen School of Medicine at UCLA, Los Angeles, California, United States of America.|Department of Psychology, University of California Los Angeles, Los Angeles, California, United States of America , Brain Injury Research Center (BIRC), Department of Neurosurgery, David Geffen School of Medicine at UCLA, Los Angeles, California, United States of America.|Department of Psychology, University of California Los Angeles, Los Angeles, California, United States of America , Brain Injury Research Center (BIRC), Department of Neurosurgery, David Geffen School of Medicine at UCLA, Los Angeles, California, United States of America.|Department of Psychology, University of California Los Angeles, Los Angeles, California, United States of America , Brain Injury Research Center (BIRC), Department of Neurosurgery, David Geffen School of Medicine at UCLA, Los Angeles, California, United States of America.|Department of Psychology, University of California Los Angeles, Los Angeles, California, United States of America , Brain Injury Research Center (BIRC), Department of Neurosurgery, David Geffen School of Medicine at UCLA, Los Angeles, California, United States of America.|Department of Psychology, University of California Los Angeles, Los Angeles, California, United States of America , Brain Injury Research Center (BIRC), Department of Neurosurgery, David Geffen School of Medicine at UCLA, Los Angeles, California, United States of America.|Department of Psychology, University of California Los Angeles, Los Angeles, California, United States of America , Brain Injury Research Center (BIRC), Department of Neurosurgery, David Geffen School of Medicine at UCLA, Los Angeles, California, United States of America.', 'United States|United States|United States|United States|United States|United States|United States|Un', 0, 'Adolescent|Adult|Brain|Female|Humans|Hypnotics and Sedatives|Magnetic Resonance Imaging|Male|Nerve Net|Neural Pathways|Propofol|Unconsciousness|Young Adult', 'Journal Article', '10.1371/journal.pcbi.1003271', '24146606', 'Whether unique to humans or not, consciousness is a central aspect of our experience of the world. The neural fingerprint of this experience, however, remains one of the least understood aspects of the human brain. In this paper we employ graph-theoretic measures and support vector machine classification to assess, in 12 healthy volunteers, the dynamic reconfiguration of functional connectivity during wakefulness, propofol-induced sedation and loss of consciousness, and the recovery of wakefulness. Our main findings, based on resting-state fMRI, are three-fold. First, we find that propofol-induced anesthesia does not bear differently on long-range versus short-range connections. Second, our multi-stage design dissociated an initial phase of thalamo-cortical and cortico-cortical hyperconnectivity, present during sedation, from a phase of cortico-cortical hypoconnectivity, apparent during loss of consciousness. Finally, we show that while clustering is increased during loss of consciousness, as recently suggested, it also remains significantly elevated during wakefulness recovery. Conversely, the characteristic path length of brain networks (i.e., the average functional distance between any two regions of the brain) appears significantly increased only during loss of consciousness, marking a decrease of global information-processing efficiency uniquely associated with unconsciousness. These findings suggest that propofol-induced loss of consciousness is mainly tied to cortico-cortical and not thalamo-cortical mechanisms, and that decreased efficiency of information flow is the main feature differentiating the conscious from the unconscious brain. '),
(86238, 2013, 'plos', 'Model of fission yeast cell shape driven by membrane-bound growth factors and the cytoskeleton', 'Drake, Tyler|Vavylonis, Dimitrios', 'Department of Physics, Lehigh University, Bethlehem, Pennsylvania, United States of America.|Department of Physics, Lehigh University, Bethlehem, Pennsylvania, United States of America.', 'United States|United States', 22, 'Cell Shape|Computer Simulation|Intercellular Signaling Peptides and Proteins|Membrane Proteins|Microtubules|Models, Biological|Schizosaccharomyces|Schizosaccharomyces pombe Proteins', 'Journal Article', '10.1371/journal.pcbi.1003287', '24146607', 'Fission yeast serves as a model for how cellular polarization machinery consisting of signaling molecules and the actin and microtubule cytoskeleton regulates cell shape. In this work, we develop mathematical models to investigate how these cells maintain a tubular shape of approximately constant diameter. Many studies identify active Cdc42, found in a cap at the inner membrane of growing cell tips, as an important regulator of local cell wall remodeling, likely through control of exocyst tethering and the targeting of other polarity-enhancing structures. First, we show that a computational model with Cdc42-dependent local cell wall remodeling under turgor pressure predicts a relationship between spatial extent of growth signal and cell diameter that is in agreement with prior experiments. Second, we model the consequences of feedback between cell shape and distribution of Cdc42 growth signal at cell tips. We show that stability of cell diameter over successive cell divisions places restrictions on their mutual dependence. We argue that simple models where the spatial extent of the tip growth signal relies solely on geometrical alignment of confined microtubules might lead to unstable width regulation. Third, we study a computational model that combines a growth signal distributed over a characteristic length scale (as, for example, by a reaction-diffusion mechanism) with an axis-sensing microtubules system that places landmarks at positions where microtubule tips touch the cortex. A two-dimensional implementation of this model leads to stable cell diameter for a wide range of parameters. Changes to the parameters of this model reproduce straight, bent, and bulged cell shapes, and we discuss how this model is consistent with other observed cell shapes in mutants. Our work provides an initial quantitative framework for understanding the regulation of cell shape in fission yeast, and a scaffold for understanding this process on a more molecular level in the future. '),
(86239, 2013, 'plos', 'On the role of aggregation prone regions in protein evolution, stability, and enzymatic catalysis: insights from diverse analyses', 'Buck, Patrick M|Kumar, Sandeep|Singh, Satish K', 'Pharmaceutical Research and Development, Biotherapeutics Pharmaceutical Sciences, Pfizer Inc., Chesterfield, Missouri, United States of America.|Pharmaceutical Research and Development, Biotherapeutics Pharmaceutical Sciences, Pfizer Inc., Chesterfield, Missouri, United States of America.|Pharmaceutical Research and Development, Biotherapeutics Pharmaceutical Sciences, Pfizer Inc., Chesterfield, Missouri, United States of America.', 'United States|United States|United States', 0, 'Databases, Protein|Evolution, Molecular|Models, Molecular|Protein Folding|Protein Stability|Protein Structure, Tertiary|Proteins|Sequence Analysis, Protein|Sequence Homology, Amino Acid', 'Journal Article', '10.1371/journal.pcbi.1003291', '24146608', 'The various roles that aggregation prone regions (APRs) are capable of playing in proteins are investigated here via comprehensive analyses of multiple non-redundant datasets containing randomly generated amino acid sequences, monomeric proteins, intrinsically disordered proteins (IDPs) and catalytic residues. Results from this study indicate that the aggregation propensities of monomeric protein sequences have been minimized compared to random sequences with uniform and natural amino acid compositions, as observed by a lower average aggregation propensity and fewer APRs that are shorter in length and more often punctuated by gate-keeper residues. However, evidence for evolutionary selective pressure to disrupt these sequence regions among homologous proteins is inconsistent. APRs are less conserved than average sequence identity among closely related homologues (xe2x89xa580% sequence identity with a parent) but APRs are more conserved than average sequence identity among homologues that have at least 50% sequence identity with a parent. Structural analyses of APRs indicate that APRs are three times more likely to contain ordered versus disordered residues and that APRs frequently contribute more towards stabilizing proteins than equal length segments from the same protein. Catalytic residues and APRs were also found to be in structural contact significantly more often than expected by random chance. Our findings suggest that proteins have evolved by optimizing their risk of aggregation for cellular environments by both minimizing aggregation prone regions and by conserving those that are important for folding and function. In many cases, these sequence optimizations are insufficient to develop recombinant proteins into commercial products. Rational design strategies aimed at improving protein solubility for biotechnological purposes should carefully evaluate the contributions made by candidate APRs, targeted for disruption, towards protein structure and activity.'),
(86240, 2013, 'plos', 'Reconstructing the genomic content of microbiome taxa through shotgun metagenomic deconvolution', 'Carr, Rogan|Shen-Orr, Shai S|Borenstein, Elhanan', 'Department of Genome Sciences, University of Washington, Seattle, Washington, United States of America.|Department of Genome Sciences, University of Washington, Seattle, Washington, United States of America.|Department of Genome Sciences, University of Washington, Seattle, Washington, United States of America.', 'United States|United States|United States', 34, 'Genome, Bacterial|Humans|Metagenomics|Microbiota|Models, Genetic|Sequence Analysis, DNA|Tongue', 'Journal Article', '10.1371/journal.pcbi.1003292', '24146609', 'Metagenomics has transformed our understanding of the microbial world, allowing researchers to bypass the need to isolate and culture individual taxa and to directly characterize both the taxonomic and gene compositions of environmental samples. However, associating the genes found in a metagenomic sample with the specific taxa of origin remains a critical challenge. Existing binning methods, based on nucleotide composition or alignment to reference genomes allow only a coarse-grained classification and rely heavily on the availability of sequenced genomes from closely related taxa. Here, we introduce a novel computational framework, integrating variation in gene abundances across multiple samples with taxonomic abundance data to deconvolve metagenomic samples into taxa-specific gene profiles and to reconstruct the genomic content of community members. This assembly-free method is not bounded by various factors limiting previously described methods of metagenomic binning or metagenomic assembly and represents a fundamentally different approach to metagenomic-based genome reconstruction. An implementation of this framework is available at http://elbo.gs.washington.edu/software.html. We first describe the mathematical foundations of our framework and discuss considerations for implementing its various components. We demonstrate the ability of this framework to accurately deconvolve a set of metagenomic samples and to recover the gene content of individual taxa using synthetic metagenomic samples. We specifically characterize determinants of prediction accuracy and examine the impact of annotation errors on the reconstructed genomes. We finally apply metagenomic deconvolution to samples from the Human Microbiome Project, successfully reconstructing genus-level genomic content of various microbial genera, based solely on variation in gene count. These reconstructed genera are shown to correctly capture genus-specific properties. With the accumulation of metagenomic data, this deconvolution framework provides an essential tool for characterizing microbial taxa never before seen, laying the foundation for addressing fundamental questions concerning the taxa comprising diverse microbial communities. '),
(86241, 2013, 'plos', 'Dynamic rendering of the heterogeneous cell response to anticancer treatments', 'Falcetta, Francesca|Lupi, Monica|Colombo, Valentina|Ubezio, Paolo', 'Biophysics Unit, Laboratory of Anticancer Pharmacology, Department of Oncology, IRCCS - Istituto di Ricerche Farmacologiche Mario Negri, Milano, Italy.|Biophysics Unit, Laboratory of Anticancer Pharmacology, Department of Oncology, IRCCS - Istituto di Ricerche Farmacologiche Mario Negri, Milano, Italy.|Biophysics Unit, Laboratory of Anticancer Pharmacology, Department of Oncology, IRCCS - Istituto di Ricerche Farmacologiche Mario Negri, Milano, Italy.|Biophysics Unit, Laboratory of Anticancer Pharmacology, Department of Oncology, IRCCS - Istituto di Ricerche Farmacologiche Mario Negri, Milano, Italy.', 'Italy|Italy|Italy|Italy', 0, 'Cell Cycle|Cell Line, Tumor|Cell Proliferation|Computer Simulation|Dose-Response Relationship, Radiation|Female|Humans|Microscopy, Video|Models, Biological|Ovarian Neoplasms|Time-Lapse Imaging', 'Journal Article', '10.1371/journal.pcbi.1003293', '24146610', 'The antiproliferative response to anticancer treatment is the result of concurrent responses in all cell cycle phases, extending over several cell generations, whose complexity is not captured by current methods. In the proposed experimental/computational approach, the contemporary use of time-lapse live cell microscopy and flow cytometric data supported the computer rendering of the proliferative process through the cell cycle and subsequent generations during/after treatment. The effects of treatments were modelled with modules describing the functional activity of the main pathways causing arrest, repair and cell death in each phase. A framework modelling environment was created, enabling us to apply different types of modules in each phase and test models at the complexity level justified by the available data. We challenged the method with time-course measures taken in parallel with flow cytometry and time-lapse live cell microscopy in X-ray-treated human ovarian cancer cells, spanning a wide range of doses. The most suitable model of the treatment, including the dose-response of each effect, was progressively built, combining modules with a rational strategy and fitting simultaneously all data of different doses and platforms. The final model gave for the first time the complete rendering in silico of the cycling process following X-ray exposure, providing separate and quantitative measures of the dose-dependence of G1, S and G2M checkpoint activities in subsequent generations, reconciling known effects of ionizing radiations and new insights in a unique scenario. '),
(86242, 2013, 'plos', 'The influence of synaptic weight distribution on neuronal population dynamics', 'Iyer, Ramakrishnan|Menon, Vilas|Buice, Michael|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.|Allen Institute for Brain Science, Seattle, Washington, United States of America.', 'United States|United States|United States|United States|United States', 28, 'Action Potentials|Computer Simulation|Models, Neurological|Neurons|Synapses', 'Journal Article', '10.1371/journal.pcbi.1003248', '24204219', 'The manner in which different distributions of synaptic weights onto cortical neurons shape their spiking activity remains open. To characterize a homogeneous neuronal population, we use the master equation for generalized leaky integrate-and-fire neurons with shot-noise synapses. We develop fast semi-analytic numerical methods to solve this equation for either current or conductance synapses, with and without synaptic depression. We show that its solutions match simulations of equivalent neuronal networks better than those of the Fokker-Planck equation and we compute bounds on the network response to non-instantaneous synapses. We apply these methods to study different synaptic weight distributions in feed-forward networks. We characterize the synaptic amplitude distributions using a set of measures, called tail weight numbers, designed to quantify the preponderance of very strong synapses. Even if synaptic amplitude distributions are equated for both the total current and average synaptic weight, distributions with sparse but strong synapses produce higher responses for small inputs, leading to a larger operating range. Furthermore, despite their small number, such synapses enable the network to respond faster and with more stability in the face of external fluctuations. '),
(86243, 2013, 'plos', 'A dendritic mechanism for decoding traveling waves: principles and applications to motor cortex', 'Heitmann, Stewart|Boonstra, Tjeerd|Breakspear, Michael', 'School of Psychiatry, The University of New South Wales, Sydney, Australia , The Black Dog Institute, Sydney, Australia.|School of Psychiatry, The University of New South Wales, Sydney, Australia , The Black Dog Institute, Sydney, Australia.|School of Psychiatry, The University of New South Wales, Sydney, Australia , The Black Dog Institute, Sydney, Australia.', 'Australia|Australia|Australia', 0, 'Algorithms|Computer Simulation|Dendrites|Humans|Models, Neurological|Motor Cortex|Motor Neurons|Pyramidal Tracts', 'Journal Article', '10.1371/journal.pcbi.1003260', '24204220', 'Traveling waves of neuronal oscillations have been observed in many cortical regions, including the motor and sensory cortex. Such waves are often modulated in a task-dependent fashion although their precise functional role remains a matter of debate. Here we conjecture that the cortex can utilize the direction and wavelength of traveling waves to encode information. We present a novel neural mechanism by which such information may be decoded by the spatial arrangement of receptors within the dendritic receptor field. In particular, we show how the density distributions of excitatory and inhibitory receptors can combine to act as a spatial filter of wave patterns. The proposed dendritic mechanism ensures that the neuron selectively responds to specific wave patterns, thus constituting a neural basis of pattern decoding. We validate this proposal in the descending motor system, where we model the large receptor fields of the pyramidal tract neurons - the principle outputs of the motor cortex - decoding motor commands encoded in the direction of traveling wave patterns in motor cortex. We use an existing model of field oscillations in motor cortex to investigate how the topology of the pyramidal cell receptor field acts to tune the cells responses to specific oscillatory wave patterns, even when those patterns are highly degraded. The model replicates key findings of the descending motor system during simple motor tasks, including variable interspike intervals and weak corticospinal coherence. By additionally showing how the nature of the wave patterns can be controlled by modulating the topology of local intra-cortical connections, we hence propose a novel integrated neuronal model of encoding and decoding motor commands. '),
(86244, 2013, 'plos', 'Attention-dependent modulation of cortical taste circuits revealed by Granger causality with signal-dependent noise', 'Luo, Qiang|Ge, Tian|Grabenhorst, Fabian|Feng, Jianfeng|Rolls, Edmund T', 'Shanghai Center for Mathematical Sciences, Fudan University, Shanghai, PR China , College of Information Systems and Management, National University of Defense Technology, Hunan, PR China.|Shanghai Center for Mathematical Sciences, Fudan University, Shanghai, PR China , College of Information Systems and Management, National University of Defense Technology, Hunan, PR China.|Shanghai Center for Mathematical Sciences, Fudan University, Shanghai, PR China , College of Information Systems and Management, National University of Defense Technology, Hunan, PR China.|Shanghai Center for Mathematical Sciences, Fudan University, Shanghai, PR China , College of Information Systems and Management, National University of Defense Technology, Hunan, PR China.|Shanghai Center for Mathematical Sciences, Fudan University, Shanghai, PR China , College of Information Systems and Management, National University of Defense Technology, Hunan, PR China.', 'China|China|China|China|China', 29, 'Adult|Cerebrovascular Circulation|Computer Simulation|Female|Humans|Magnetic Resonance Imaging|Male|Models, Statistical|Oxygen|Prefrontal Cortex|Signal Processing, Computer-Assisted|Taste|Young Adult', 'Journal Article', '10.1371/journal.pcbi.1003265', '24204221', 'We show, for the first time, that in cortical areas, for example the insular, orbitofrontal, and lateral prefrontal cortex, there is signal-dependent noise in the fMRI blood-oxygen level dependent (BOLD) time series, with the variance of the noise increasing approximately linearly with the square of the signal. Classical Granger causal models are based on autoregressive models with time invariant covariance structure, and thus do not take this signal-dependent noise into account. To address this limitation, here we describe a Granger causal model with signal-dependent noise, and a novel, likelihood ratio test for causal inferences. We apply this approach to the data from an fMRI study to investigate the source of the top-down attentional control of taste intensity and taste pleasantness processing. The Granger causality with signal-dependent noise analysis reveals effects not identified by classical Granger causal analysis. In particular, there is a top-down effect from the posterior lateral prefrontal cortex to the insular taste cortex during attention to intensity but not to pleasantness, and there is a top-down effect from the anterior and posterior lateral prefrontal cortex to the orbitofrontal cortex during attention to pleasantness but not to intensity. In addition, there is stronger forward effective connectivity from the insular taste cortex to the orbitofrontal cortex during attention to pleasantness than during attention to intensity. These findings indicate the importance of explicitly modeling signal-dependent noise in functional neuroimaging, and reveal some of the processes involved in a biased activation theory of selective attention. '),
(86245, 2013, 'plos', 'Properties of MHC class I presented peptides that enhance immunogenicity', 'Calis, Jorg J A|Maybeno, Matt|Greenbaum, Jason A|Weiskopf, Daniela|De Silva, Aruna D|Sette, Alessandro|Kexc5x9fmir, Can|Peters, Bjoern', 'Theoretical Biology & Bioinformatics, Utrecht University, Utrecht, The Netherlands.|Theoretical Biology & Bioinformatics, Utrecht University, Utrecht, The Netherlands.|Theoretical Biology & Bioinformatics, Utrecht University, Utrecht, The Netherlands.|Theoretical Biology & Bioinformatics, Utrecht University, Utrecht, The Netherlands.|Theoretical Biology & Bioinformatics, Utrecht University, Utrecht, The Netherlands.|Theoretical Biology & Bioinformatics, Utrecht University, Utrecht, The Netherlands.|Theoretical Biology & Bioinformatics, Utrecht University, Utrecht, The Netherlands.|Theoretical Biology & Bioinformatics, Utrecht University, Utrecht, The Netherlands.', 'Netherlands|Netherlands|Netherlands|Netherlands|Netherlands|Netherlands|Netherlands|Netherlands', 180, 'Amino Acid Sequence|Animals|Antigens, Viral|Databases, Protein|Epitopes|Histocompatibility Antigens Class I|Humans|Mice|Models, Immunological|Peptides|T-Lymphocytes', 'Journal Article', '10.1371/journal.pcbi.1003266', '24204222', 'T-cells have to recognize peptides presented on MHC molecules to be activated and elicit their effector functions. Several studies demonstrate that some peptides are more immunogenic than others and therefore more likely to be T-cell epitopes. We set out to determine which properties cause such differences in immunogenicity. To this end, we collected and analyzed a large set of data describing the immunogenicity of peptides presented on various MHC-I molecules. Two main conclusions could be drawn from this analysis: First, in line with previous observations, we showed that positions P4-6 of a presented peptide are more important for immunogenicity. Second, some amino acids, especially those with large and aromatic side chains, are associated with immunogenicity. This information was combined into a simple model that was used to demonstrate that immunogenicity is, to a certain extent, predictable. This model (made available at http://tools.iedb.org/immunogenicity/) was validated with data from two independent epitope discovery studies. Interestingly, with this model we could show that T-cells are equipped to better recognize viral than human (self) peptides. After the past successful elucidation of different steps in the MHC-I presentation pathway, the identification of variables that influence immunogenicity will be an important next step in the investigation of T-cell epitopes and our understanding of cellular immune responses. '),
(86246, 2013, 'plos', 'CAPE: an R package for combined analysis of pleiotropy and epistasis', 'Tyler, Anna L|Lu, Wei|Hendrick, Justin J|Philip, Vivek M|Carter, Gregory W', 'The Jackson Laboratory, Bar Harbor, Maine, United States of America.|The Jackson Laboratory, Bar Harbor, Maine, United States of America.|The Jackson Laboratory, Bar Harbor, Maine, United States of America.|The Jackson Laboratory, Bar Harbor, Maine, United States of America.|The Jackson Laboratory, Bar Harbor, Maine, United States of America.', 'United States|United States|United States|United States|United States', 21, 'Algorithms|Animals|Computational Biology|Diabetes Mellitus, Type 2|Disease Models, Animal|Epistasis, Genetic|Genetic Pleiotropy|Linear Models|Mice|Models, Genetic|Obesity|Software', 'Journal Article', '10.1371/journal.pcbi.1003270', '24204223', 'Contemporary genetic studies are revealing the genetic complexity of many traits in humans and model organisms. Two hallmarks of this complexity are epistasis, meaning gene-gene interaction, and pleiotropy, in which one gene affects multiple phenotypes. Understanding the genetic architecture of complex traits requires addressing these phenomena, but interpreting the biological significance of epistasis and pleiotropy is often difficult. While epistasis reveals dependencies between genetic variants, it is often unclear how the activity of one variant is specifically modifying the other. Epistasis found in one phenotypic context may disappear in another context, rendering the genetic interaction ambiguous. Pleiotropy can suggest either redundant phenotype measures or gene variants that affect multiple biological processes. Here we present an R package, R/cape, which addresses these interpretation ambiguities by implementing a novel method to generate predictive and interpretable genetic networks that influence quantitative phenotypes. R/cape integrates information from multiple related phenotypes to constrain models of epistasis, thereby enhancing the detection of interactions that simultaneously describe all phenotypes. The networks inferred by R/cape are readily interpretable in terms of directed influences that indicate suppressive and enhancing effects of individual genetic variants on other variants, which in turn account for the variance in quantitative traits. We demonstrate the utility of R/cape by analyzing a mouse backcross, thereby discovering novel epistatic interactions influencing phenotypes related to obesity and diabetes. R/cape is an easy-to-use, platform-independent R package and can be applied to data from both genetic screens and a variety of segregating populations including backcrosses, intercrosses, and natural populations. The package is freely available under the GPL-3 license at http://cran.r-project.org/web/packages/cape. '),
(86247, 2013, 'plos', 'The Convallis rule for unsupervised learning in cortical networks', 'Yger, Pierre|Harris, Kenneth D', 'UCL Institute of Neurology and UCL Department of Neuroscience, Physiology, and Pharmacology, London, United Kingdom.|UCL Institute of Neurology and UCL Department of Neuroscience, Physiology, and Pharmacology, London, United Kingdom.', 'United Kingdom|United Kingdom', 0, 'Action Potentials|Artificial Intelligence|Cochlea|Computational Biology|Computer Simulation|Humans|Models, Neurological|Neocortex|Neuronal Plasticity|Neurons|Speech Perception', 'Journal Article', '10.1371/journal.pcbi.1003272', '24204224', 'The phenomenology and cellular mechanisms of cortical synaptic plasticity are becoming known in increasing detail, but the computational principles by which cortical plasticity enables the development of sensory representations are unclear. Here we describe a framework for cortical synaptic plasticity termed the Convallis rule, mathematically derived from a principle of unsupervised learning via constrained optimization. Implementation of the rule caused a recurrent cortex-like network of simulated spiking neurons to develop rate representations of real-world speech stimuli, enabling classification by a downstream linear decoder. Applied to spike patterns used in in vitro plasticity experiments, the rule reproduced multiple results including and beyond STDP. However STDP alone produced poorer learning performance. The mathematical form of the rule is consistent with a dual coincidence detector mechanism that has been suggested by experiments in several synaptic classes of juvenile neocortex. Based on this confluence of normative, phenomenological, and mechanistic evidence, we suggest that the rule may approximate a fundamental computational principle of the neocortex. '),
(86248, 2013, 'plos', 'Molecular mechanical differences between isoforms of contractile actin in the presence of isoforms of smooth muscle tropomyosin', 'Hilbert, Lennart|Bates, Genevieve|Roman, Horia N|Blumenthal, Jenna L|Zitouni, Nedjma B|Sobieszek, Apolinary|Mackey, Michael C|Lauzon, Anne-Marie', 'Dept. Physiology, McGill University, Montréal, Québec, Canada , Centre for Applied Mathematics in Bioscience and Medicine, Montréal, Québec, Canada , Meakins-Christie Laboratories, McGill University, Montréal, Québec, Canada.|Dept. Physiology, McGill University, Montréal, Québec, Canada , Centre for Applied Mathematics in Bioscience and Medicine, Montréal, Québec, Canada , Meakins-Christie Laboratories, McGill University, Montréal, Québec, Canada.|Dept. Physiology, McGill University, Montréal, Québec, Canada , Centre for Applied Mathematics in Bioscience and Medicine, Montréal, Québec, Canada , Meakins-Christie Laboratories, McGill University, Montréal, Québec, Canada.|Dept. Physiology, McGill University, Montréal, Québec, Canada , Centre for Applied Mathematics in Bioscience and Medicine, Montréal, Québec, Canada , Meakins-Christie Laboratories, McGill University, Montréal, Québec, Canada.|Dept. Physiology, McGill University, Montréal, Québec, Canada , Centre for Applied Mathematics in Bioscience and Medicine, Montréal, Québec, Canada , Meakins-Christie Laboratories, McGill University, Montréal, Québec, Canada.|Dept. Physiology, McGill University, Montréal, Québec, Canada , Centre for Applied Mathematics in Bioscience and Medicine, Montréal, Québec, Canada , Meakins-Christie Laboratories, McGill University, Montréal, Québec, Canada.|Dept. Physiology, McGill University, Montréal, Québec, Canada , Centre for Applied Mathematics in Bioscience and Medicine, Montréal, Québec, Canada , Meakins-Christie Laboratories, McGill University, Montréal, Québec, Canada.|Dept. Physiology, McGill University, Montréal, Québec, Canada , Centre for Applied Mathematics in Bioscience and Medicine, Montréal, Québec, Canada , Meakins-Christie Laboratories, McGill University, Montréal, Québec, Canada.', 'Canada|Canada|Canada|Canada|Canada|Canada|Canada|Canada', 6, 'Actins|Animals|Biomechanical Phenomena|Computer Simulation|Kinetics|Models, Molecular|Muscle, Smooth|Protein Isoforms|Swine|Tropomyosin|Turkeys', 'Journal Article', '10.1371/journal.pcbi.1003273', '24204225', 'The proteins involved in smooth muscles molecular contractile mechanism - the anti-parallel motion of actin and myosin filaments driven by myosin heads interacting with actin - are found as different isoforms. While their expression levels are altered in disease states, their relevance to the mechanical interaction of myosin with actin is not sufficiently understood. Here, we analyzed in vitro actin filament propulsion by smooth muscle myosin for [Formula: see text]-actin ([Formula: see text]A), [Formula: see text]-actin-tropomyosin-[Formula: see text] ([Formula: see text]A-Tm[Formula: see text]), [Formula: see text]-actin-tropomyosin-[Formula: see text] ([Formula: see text]A-Tm[Formula: see text]), [Formula: see text]-actin ([Formula: see text]A), [Formula: see text]-actin-tropomyosin-[Formula: see text] ([Formula: see text]A-Tm[Formula: see text]), and [Formula: see text]-actin-tropomoysin-[Formula: see text] ([Formula: see text]A-Tm[Formula: see text]). Actin sliding analysis with our specifically developed video analysis software followed by statistical assessment (Bootstrapped Principal Component Analysis) indicated that the in vitro motility of [Formula: see text]A, [Formula: see text]A, and [Formula: see text]A-Tm[Formula: see text] is not distinguishable. Compared to these three baseline conditions, statistically significant differences ([Formula: see text]) were: [Formula: see text]A-Tm[Formula: see text] - actin sliding velocity increased 1.12-fold, [Formula: see text]A-Tm[Formula: see text] - motile fraction decreased to 0.96-fold, stop time elevated 1.6-fold, [Formula: see text]A-Tm[Formula: see text] - run time elevated 1.7-fold. We constructed a mathematical model, simulated actin sliding data, and adjusted the kinetic parameters so as to mimic the experimentally observed differences: [Formula: see text]A-Tm[Formula: see text] - myosin binding to actin, the main, and the secondary myosin power stroke are accelerated, [Formula: see text]A-Tm[Formula: see text] - mechanical coupling between myosins is stronger, [Formula: see text]A-Tm[Formula: see text] - the secondary power stroke is decelerated and mechanical coupling between myosins is weaker. In summary, our results explain the different regulatory effects that specific combinations of actin and smooth muscle tropomyosin have on smooth muscle actin-myosin interaction kinetics. ');
INSERT INTO `papers` (`id`, `ano`, `journal`, `titulo`, `autores`, `afiliacao`, `pais`, `citacoes`, `palavra_chave`, `categorias`, `doi`, `pubmed`, `abstract`) VALUES
(86249, 2013, 'plos', 'Keeping up with the Joneses: interpersonal prediction errors and the correlation of behavior in a tandem sequential choice task', 'Lohrenz, Terry|Bhatt, Meghana|Apple, Nathan|Montague, P Read', 'Virginia Tech Carilion Research Institute, Roanoke, Virginia, United States of America.|Virginia Tech Carilion Research Institute, Roanoke, Virginia, United States of America.|Virginia Tech Carilion Research Institute, Roanoke, Virginia, United States of America.|Virginia Tech Carilion Research Institute, Roanoke, Virginia, United States of America.', 'United States|United States|United States|United States', 6, 'Algorithms|Brain|Choice Behavior|Humans|Image Processing, Computer-Assisted|Investments|Magnetic Resonance Imaging|Models, Statistical|Regression Analysis|Reward|Task Performance and Analysis', 'Journal Article', '10.1371/journal.pcbi.1003275', '24204226', 'In many settings, copying, learning from or assigning value to group behavior is rational because such behavior can often act as a proxy for valuable returns. However, such herd behavior can also be pathologically misleading by coaxing individuals into behaviors that are otherwise irrational and it may be one source of the irrational behaviors underlying market bubbles and crashes. Using a two-person tandem investment game, we sought to examine the neural and behavioral responses of herd instincts in situations stripped of the incentive to be influenced by the choices of ones partner. We show that the investments of the two subjects correlate over time if they are made aware of their partners choices even though these choices have no impact on either players earnings. We computed an interpersonal prediction error, the difference between the investment decisions of the two subjects after each choice. BOLD responses in the striatum, implicated in valuation and action selection, were highly correlated with this interpersonal prediction error. The revelation of the partners investment occurred after all useful information about the market had already been revealed. This effect was confirmed in two separate experiments where the impact of the time of revelation of the partners choice was tested at 2 seconds and 6 seconds after a subjects choice, however, the effect was absent in a control condition with a computer partner. These findings strongly support the existence of mechanisms that drive correlated behavior even in contexts where there is no explicit advantage to do so. '),
(86250, 2013, 'plos', 'Novel methods for analysing bacterial tracks reveal persistence in Rhodobacter sphaeroides', 'Rosser, Gabriel|Fletcher, Alexander G|Wilkinson, David A|de Beyer, Jennifer A|Yates, Christian A|Armitage, Judith P|Maini, Philip K|Baker, Ruth E', 'Wolfson Centre for Mathematical Biology, Mathematical Institute, University of Oxford, Radcliffe Observatory Quarter, Oxford, United Kingdom.|Wolfson Centre for Mathematical Biology, Mathematical Institute, University of Oxford, Radcliffe Observatory Quarter, Oxford, United Kingdom.|Wolfson Centre for Mathematical Biology, Mathematical Institute, University of Oxford, Radcliffe Observatory Quarter, Oxford, United Kingdom.|Wolfson Centre for Mathematical Biology, Mathematical Institute, University of Oxford, Radcliffe Observatory Quarter, Oxford, United Kingdom.|Wolfson Centre for Mathematical Biology, Mathematical Institute, University of Oxford, Radcliffe Observatory Quarter, Oxford, United Kingdom.|Wolfson Centre for Mathematical Biology, Mathematical Institute, University of Oxford, Radcliffe Observatory Quarter, Oxford, United Kingdom.|Wolfson Centre for Mathematical Biology, Mathematical Institute, University of Oxford, Radcliffe Observatory Quarter, Oxford, United Kingdom.|Wolfson Centre for Mathematical Biology, Mathematical Institute, University of Oxford, Radcliffe Observatory Quarter, Oxford, United Kingdom.', 'United Kingdom|United Kingdom|United Kingdom|United Kingdom|United Kingdom|United Kingdom|United Kin', 0, 'Cell Movement|Computer Simulation|Image Processing, Computer-Assisted|Microscopy, Video|Reproducibility of Results|Rhodobacter sphaeroides|Single-Cell Analysis', 'Journal Article', '10.1371/journal.pcbi.1003276', '24204227', 'Tracking bacteria using video microscopy is a powerful experimental approach to probe their motile behaviour. The trajectories obtained contain much information relating to the complex patterns of bacterial motility. However, methods for the quantitative analysis of such data are limited. Most swimming bacteria move in approximately straight lines, interspersed with random reorientation phases. It is therefore necessary to segment observed tracks into swimming and reorientation phases to extract useful statistics. We present novel robust analysis tools to discern these two phases in tracks. Our methods comprise a simple and effective protocol for removing spurious tracks from tracking datasets, followed by analysis based on a two-state hidden Markov model, taking advantage of the availability of mutant strains that exhibit swimming-only or reorientating-only motion to generate an empirical prior distribution. Using simulated tracks with varying levels of added noise, we validate our methods and compare them with an existing heuristic method. To our knowledge this is the first example of a systematic assessment of analysis methods in this field. The new methods are substantially more robust to noise and introduce less systematic bias than the heuristic method. We apply our methods to tracks obtained from the bacterial species Rhodobacter sphaeroides and Escherichia coli. Our results demonstrate that R. sphaeroides exhibits persistence over the course of a tumbling event, which is a novel result with important implications in the study of this and similar species. '),
(86251, 2013, 'plos', 'Exploring Protein-Peptide Binding Specificity through Computational Peptide Screening', 'Bhattacherjee, Arnab|Wallin, Stefan', 'Department of Astronomy and Theoretical Physics, Computational Biology and Biological Physics group, Lund University, Lund, Sweden.|Department of Astronomy and Theoretical Physics, Computational Biology and Biological Physics group, Lund University, Lund, Sweden.', 'Sweden|Sweden', 0, 'Amino Acid Sequence|Computational Biology|Molecular Sequence Data|Monte Carlo Method|Peptides|Protein Binding|Protein Conformation|Proteins|Sequence Analysis, Protein|Thermodynamics', 'Journal Article', '10.1371/journal.pcbi.1003277', '24204228', 'The binding of short disordered peptide stretches to globular protein domains is important for a wide range of cellular processes, including signal transduction, protein transport, and immune response. The often promiscuous nature of these interactions and the conformational flexibility of the peptide chain, sometimes even when bound, make the binding specificity of this type of protein interaction a challenge to understand. Here we develop and test a Monte Carlo-based procedure for calculating protein-peptide binding thermodynamics for many sequences in a single run. The method explores both peptide sequence and conformational space simultaneously by simulating a joint probability distribution which, in particular, makes searching through peptide sequence space computationally efficient. To test our method, we apply it to 3 different peptide-binding protein domains and test its ability to capture the experimentally determined specificity profiles. Insight into the molecular underpinnings of the observed specificities is obtained by analyzing the peptide conformational ensembles of a large number of binding-competent sequences. We also explore the possibility of using our method to discover new peptide-binding pockets on protein structures. '),
(86252, 2013, 'plos', 'Comprehensive repertoire of foldable regions within whole genomes', 'Faure, Guilhem|Callebaut, Isabelle', 'CNRS, UPMC Univ Paris 6, IMPMC, UMR7590 - IUC, Paris, France.|CNRS, UPMC Univ Paris 6, IMPMC, UMR7590 - IUC, Paris, France.', 'France|France', 0, 'Amino Acid Sequence|Cluster Analysis|Fungal Proteins|Genome|Genomics|Humans|Hydrophobic and Hydrophilic Interactions|Models, Molecular|Models, Statistical|Molecular Sequence Data|Protein Folding|Protein Structure, Tertiary|Proteins|Proteome|Protozoan Proteins|Sequence Analysis, DNA|Sequence Analysis, Protein', 'Journal Article', '10.1371/journal.pcbi.1003280', '24204229', 'In order to get a comprehensive repertoire of foldable domains within whole proteomes, including orphan domains, we developed a novel procedure, called SEG-HCA. From only the information of a single amino acid sequence, SEG-HCA automatically delineates segments possessing high densities in hydrophobic clusters, as defined by Hydrophobic Cluster Analysis (HCA). These hydrophobic clusters mainly correspond to regular secondary structures, which together form structured or foldable regions. Genome-wide analyses revealed that SEG-HCA is opposite of disorder predictors, both addressing distinct structural states. Interestingly, there is however an overlap between the two predictions, including small segments of disordered sequences, which undergo coupled folding and binding. SEG-HCA thus gives access to these specific domains, which are generally poorly represented in domain databases. Comparison of the whole set of SEG-HCA predictions with the Conserved Domain Database (CDD) also highlighted a wide proportion of predicted large (length >50 amino acids) segments, which are CDD orphan. These orphan sequences may either correspond to highly divergent members of already known families or belong to new families of domains. Their comprehensive description thus opens new avenues to investigate new functional and/or structural features, which remained so far uncovered. Altogether, the data described here provide new insights into the protein architecture and organization throughout the three kingdoms of life. '),
(86253, 2013, 'plos', 'Reverse-engineering post-transcriptional regulation of gap genes in Drosophila melanogaster', 'Becker, Kolja|Balsa-Canto, Eva|Cicin-Sain, Damjan|Hoermann, Astrid|Janssens, Hilde|Banga, Julio R|Jaeger, Johannes', 'EMBL/CRG Research Unit in Systems Biology, Centre de Regulació Genòmica, and Universitat Pombeu Fabra (UPF), Barcelona, Spain , Institute of Genetics, Johannes Gutenberg University, Mainz, Germany.|EMBL/CRG Research Unit in Systems Biology, Centre de Regulació Genòmica, and Universitat Pombeu Fabra (UPF), Barcelona, Spain , Institute of Genetics, Johannes Gutenberg University, Mainz, Germany.|EMBL/CRG Research Unit in Systems Biology, Centre de Regulació Genòmica, and Universitat Pombeu Fabra (UPF), Barcelona, Spain , Institute of Genetics, Johannes Gutenberg University, Mainz, Germany.|EMBL/CRG Research Unit in Systems Biology, Centre de Regulació Genòmica, and Universitat Pombeu Fabra (UPF), Barcelona, Spain , Institute of Genetics, Johannes Gutenberg University, Mainz, Germany.|EMBL/CRG Research Unit in Systems Biology, Centre de Regulació Genòmica, and Universitat Pombeu Fabra (UPF), Barcelona, Spain , Institute of Genetics, Johannes Gutenberg University, Mainz, Germany.|EMBL/CRG Research Unit in Systems Biology, Centre de Regulació Genòmica, and Universitat Pombeu Fabra (UPF), Barcelona, Spain , Institute of Genetics, Johannes Gutenberg University, Mainz, Germany.|EMBL/CRG Research Unit in Systems Biology, Centre de Regulació Genòmica, and Universitat Pombeu Fabra (UPF), Barcelona, Spain , Institute of Genetics, Johannes Gutenberg University, Mainz, Germany.', 'Germany|Germany|Germany|Germany|Germany|Germany|Germany', 25, 'Animals|Drosophila Proteins|Drosophila melanogaster|Gene Expression Regulation, Developmental|Genetic Engineering|Models, Genetic|Protein Stability|RNA, Messenger|Repressor Proteins|Systems Biology', 'Journal Article', '10.1371/journal.pcbi.1003281', '24204230', 'Systems biology proceeds through repeated cycles of experiment and modeling. One way to implement this is reverse engineering, where models are fit to data to infer and analyse regulatory mechanisms. This requires rigorous methods to determine whether model parameters can be properly identified. Applying such methods in a complex biological context remains challenging. We use reverse engineering to study post-transcriptional regulation in pattern formation. As a case study, we analyse expression of the gap genes Krüppel, knirps, and giant in Drosophila melanogaster. We use detailed, quantitative datasets of gap gene mRNA and protein expression to solve and fit a model of post-transcriptional regulation, and establish its structural and practical identifiability. Our results demonstrate that post-transcriptional regulation is not required for patterning in this system, but is necessary for proper control of protein levels. Our work demonstrates that the uniqueness and specificity of a fitted model can be rigorously determined in the context of spatio-temporal pattern formation. This greatly increases the potential of reverse engineering for the study of development and other, similarly complex, biological processes. '),
(86254, 2013, 'plos', 'A brain-machine interface for control of medically-induced coma', 'Shanechi, Maryam M|Chemali, Jessica J|Liberman, Max|Solt, Ken|Brown, Emery N', 'School of Electrical and Computer Engineering, Cornell University, Ithaca, New York, United States of America , Department of Electrical Engineering and Computer Science, University of California, Berkeley, California, United States of America.|School of Electrical and Computer Engineering, Cornell University, Ithaca, New York, United States of America , Department of Electrical Engineering and Computer Science, University of California, Berkeley, California, United States of America.|School of Electrical and Computer Engineering, Cornell University, Ithaca, New York, United States of America , Department of Electrical Engineering and Computer Science, University of California, Berkeley, California, United States of America.|School of Electrical and Computer Engineering, Cornell University, Ithaca, New York, United States of America , Department of Electrical Engineering and Computer Science, University of California, Berkeley, California, United States of America.|School of Electrical and Computer Engineering, Cornell University, Ithaca, New York, United States of America , Department of Electrical Engineering and Computer Science, University of California, Berkeley, California, United States of America.', 'United States|United States|United States|United States|United States', 29, 'Animals|Bayes Theorem|Brain-Computer Interfaces|Coma|Computer Simulation|Electroencephalography|Feedback|Hypnotics and Sedatives|Propofol|Rats|Signal Processing, Computer-Assisted', 'Journal Article', '10.1371/journal.pcbi.1003284', '24204231', 'Medically-induced coma is a drug-induced state of profound brain inactivation and unconsciousness used to treat refractory intracranial hypertension and to manage treatment-resistant epilepsy. The state of coma is achieved by continually monitoring the patients brain activity with an electroencephalogram (EEG) and manually titrating the anesthetic infusion rate to maintain a specified level of burst suppression, an EEG marker of profound brain inactivation in which bursts of electrical activity alternate with periods of quiescence or suppression. The medical coma is often required for several days. A more rational approach would be to implement a brain-machine interface (BMI) that monitors the EEG and adjusts the anesthetic infusion rate in real time to maintain the specified target level of burst suppression. We used a stochastic control framework to develop a BMI to control medically-induced coma in a rodent model. The BMI controlled an EEG-guided closed-loop infusion of the anesthetic propofol to maintain precisely specified dynamic target levels of burst suppression. We used as the control signal the burst suppression probability (BSP), the brains instantaneous probability of being in the suppressed state. We characterized the EEG response to propofol using a two-dimensional linear compartment model and estimated the model parameters specific to each animal prior to initiating control. We derived a recursive Bayesian binary filter algorithm to compute the BSP from the EEG and controllers using a linear-quadratic-regulator and a model-predictive control strategy. Both controllers used the estimated BSP as feedback. The BMI accurately controlled burst suppression in individual rodents across dynamic target trajectories, and enabled prompt transitions between target levels while avoiding both undershoot and overshoot. The median performance error for the BMI was 3.6%, the median bias was -1.4% and the overall posterior probability of reliable control was 1 (95% Bayesian credibility interval of [0.87, 1.0]). A BMI can maintain reliable and accurate real-time control of medically-induced coma in a rodent model suggesting this strategy could be applied in patient care. '),
(86255, 2013, 'plos', 'Ten simple rules for reproducible computational research', 'Sandve, Geir Kjetil|Nekrutenko, Anton|Taylor, James|Hovig, Eivind', 'Department of Informatics, University of Oslo, Blindern, Oslo, Norway , Centre for Cancer Biomedicine, University of Oslo, Blindern, Oslo, Norway.|Department of Informatics, University of Oslo, Blindern, Oslo, Norway , Centre for Cancer Biomedicine, University of Oslo, Blindern, Oslo, Norway.|Department of Informatics, University of Oslo, Blindern, Oslo, Norway , Centre for Cancer Biomedicine, University of Oslo, Blindern, Oslo, Norway.|Department of Informatics, University of Oslo, Blindern, Oslo, Norway , Centre for Cancer Biomedicine, University of Oslo, Blindern, Oslo, Norway.', 'Norway|Norway|Norway|Norway', 282, 'Biomedical Research|Computational Biology|Reproducibility of Results', 'Journal Article', '10.1371/journal.pcbi.1003285', '24204232', '-'),
(86256, 2013, 'plos', 'The molecular mechanism of ion-dependent gating in secondary transporters', 'Zhao, Chunfeng|Noskov, Sergei Yu', 'Center for Molecular Simulations, Department of Biological Sciences, University of Calgary, Calgary, Canada.|Center for Molecular Simulations, Department of Biological Sciences, University of Calgary, Calgary, Canada.', 'Canada|Canada', 0, 'Bacterial Proteins|Computer Simulation|Ions|Models, Molecular|Plasma Membrane Neurotransmitter Transport Proteins|Protein Binding|Protein Conformation|Protein Stability|Sodium', 'Journal Article', '10.1371/journal.pcbi.1003296', '24204233', 'LeuT-like fold Na-dependent secondary active transporters form a large family of integral membrane proteins that transport various substrates against their concentration gradient across lipid membranes, using the free energy stored in the downhill concentration gradient of sodium ions. These transporters play an active role in synaptic transmission, the delivery of key nutrients, and the maintenance of osmotic pressure inside the cell. It is generally believed that binding of an ion and/or a substrate drives the conformational dynamics of the transporter. However, the exact mechanism for converting ion binding into useful work has yet to be established. Using a multi-dimensional path sampling (string-method) followed by all-atom free energy simulations, we established the principal thermodynamic and kinetic components governing the ion-dependent conformational dynamics of a LeuT-like fold transporter, the sodium/benzyl-hydantoin symporter Mhp1, for an entire conformational cycle. We found that inward-facing and outward-facing states of Mhp1 display nearly the same free energies with an ion absent from the Na2 site conserved across the LeuT-like fold transporters. The barrier separating an apo-state from inward-facing or outward-facing states of the transporter is very low, suggesting stochastic gating in the absence of ion/substrate bound. In contrast, the binding of a Na2 ion shifts the free energy stabilizing the outward-facing state and promoting substrate binding. Our results indicate that ion binding to the Na2 site may also play a key role in the intracellular thin gate dynamics modulation by altering its interactions with the transmembrane helix 5 (TM5). The Potential of Mean Force (PMF) computations for a substrate entrance displays two energy minima that correspond to the locations of the main binding site S1 and proposed allosteric S2 binding site. However, it was found that substrates binds to the site S1 xe2x88xbc5 kcal/mol more favorable than that to the site S2 for all studied bound combinations of ions and a substrate. '),
(86257, 2013, 'plos', 'An evolution-based approach to De Novo protein design and case study on Mycobacterium tuberculosis', 'Mitra, Pralay|Shultis, David|Brender, Jeffrey R|Czajka, Jeff|Marsh, David|Gray, Felicia|Cierpicki, Tomasz|Zhang, Yang', 'Department of Computational Medicine and Bioinformatics, University of Michigan, Ann Arbor, Michigan, United States of America.|Department of Computational Medicine and Bioinformatics, University of Michigan, Ann Arbor, Michigan, United States of America.|Department of Computational Medicine and Bioinformatics, University of Michigan, Ann Arbor, Michigan, United States of America.|Department of Computational Medicine and Bioinformatics, University of Michigan, Ann Arbor, Michigan, United States of America.|Department of Computational Medicine and Bioinformatics, University of Michigan, Ann Arbor, Michigan, United States of America.|Department of Computational Medicine and Bioinformatics, University of Michigan, Ann Arbor, Michigan, United States of America.|Department of Computational Medicine and Bioinformatics, University of Michigan, Ann Arbor, Michigan, United States of America.|Department of Computational Medicine and Bioinformatics, University of Michigan, Ann Arbor, Michigan, United States of America.', 'United States|United States|United States|United States|United States|United States|United States|Un', 28, 'Amino Acid Sequence|Bacterial Proteins|Computational Biology|Models, Molecular|Molecular Sequence Data|Mycobacterium tuberculosis|Protein Engineering|Protein Folding|Sequence Alignment', 'Journal Article', '10.1371/journal.pcbi.1003298', '24204234', 'Computational protein design is a reverse procedure of protein folding and structure prediction, where constructing structures from evolutionarily related proteins has been demonstrated to be the most reliable method for protein 3-dimensional structure prediction. Following this spirit, we developed a novel method to design new protein sequences based on evolutionarily related protein families. For a given target structure, a set of proteins having similar fold are identified from the PDB library by structural alignments. A structural profile is then constructed from the protein templates and used to guide the conformational search of amino acid sequence space, where physicochemical packing is accommodated by single-sequence based solvation, torsion angle, and secondary structure predictions. The method was tested on a computational folding experiment based on a large set of 87 protein structures covering different fold classes, which showed that the evolution-based design significantly enhances the foldability and biological functionality of the designed sequences compared to the traditional physics-based force field methods. Without using homologous proteins, the designed sequences can be folded with an average root-mean-square-deviation of 2.1 Å to the target. As a case study, the method is extended to redesign all 243 structurally resolved proteins in the pathogenic bacteria Mycobacterium tuberculosis, which is the second leading cause of death from infectious disease. On a smaller scale, five sequences were randomly selected from the design pool and subjected to experimental validation. The results showed that all the designed proteins are soluble with distinct secondary structure and three have well ordered tertiary structure, as demonstrated by circular dichroism and NMR spectroscopy. Together, these results demonstrate a new avenue in computational protein design that uses knowledge of evolutionary conservation from protein structural families to engineer new protein molecules of improved fold stability and biological functionality. '),
(86258, 2013, 'plos', 'Unraveling adaptation in eukaryotic pathways: lessons from protocells', 'De Palo, Giovanna|Endres, Robert G', 'Department of Life Sciences, Imperial College, London, United Kingdom , Centre for Integrative Systems Biology and Bioinformatics, Imperial College, London, United Kingdom.|Department of Life Sciences, Imperial College, London, United Kingdom , Centre for Integrative Systems Biology and Bioinformatics, Imperial College, London, United Kingdom.', 'United Kingdom|United Kingdom', 19, 'Adaptation, Physiological|Artificial Cells|Chemotaxis|Computational Biology|Dictyostelium|Escherichia coli|Eukaryota|Models, Biological|Signal Transduction', 'Journal Article', '10.1371/journal.pcbi.1003300', '24204235', 'Eukaryotic adaptation pathways operate within wide-ranging environmental conditions without stimulus saturation. Despite numerous differences in the adaptation mechanisms employed by bacteria and eukaryotes, all require energy consumption. Here, we present two minimal models showing that expenditure of energy by the cell is not essential for adaptation. Both models share important features with large eukaryotic cells: they employ small diffusible molecules and involve receptor subunits resembling highly conserved G-protein cascades. Analyzing the drawbacks of these models helps us understand the benefits of energy consumption, in terms of adjustability of response and adaptation times as well as separation of cell-external sensing and cell-internal signaling. Our work thus sheds new light on the evolution of adaptation mechanisms in complex systems. '),
(86259, 2013, 'plos', 'A complex-valued firing-rate model that approximates the dynamics of spiking networks', 'Schaffer, Evan S|Ostojic, Srdjan|Abbott, L F', 'Department of Neuroscience, Department of Physiology and Cellular Biophysics, Columbia University College of Physicians and Surgeons, New York, New York, United States of America.|Department of Neuroscience, Department of Physiology and Cellular Biophysics, Columbia University College of Physicians and Surgeons, New York, New York, United States of America.|Department of Neuroscience, Department of Physiology and Cellular Biophysics, Columbia University College of Physicians and Surgeons, New York, New York, United States of America.', 'United States|United States|United States', 0, 'Action Potentials|Algorithms|Computational Biology|Computer Simulation|Models, Neurological|Nerve Net|Neurons', 'Journal Article', '10.1371/journal.pcbi.1003301', '24204236', 'Firing-rate models provide an attractive approach for studying large neural networks because they can be simulated rapidly and are amenable to mathematical analysis. Traditional firing-rate models assume a simple form in which the dynamics are governed by a single time constant. These models fail to replicate certain dynamic features of populations of spiking neurons, especially those involving synchronization. We present a complex-valued firing-rate model derived from an eigenfunction expansion of the Fokker-Planck equation and apply it to the linear, quadratic and exponential integrate-and-fire models. Despite being almost as simple as a traditional firing-rate description, this model can reproduce firing-rate dynamics due to partial synchronization of the action potentials in a spiking model, and it successfully predicts the transition to spike synchronization in networks of coupled excitatory and inhibitory neurons. '),
(86260, 2013, 'plos', 'A comprehensive survey of small-molecule binding pockets in proteins', 'Gao, Mu|Skolnick, Jeffrey', 'Center for the Study of Systems Biology, School of Biology, Georgia Institute of Technology, Atlanta, Georgia, United States of America.|Center for the Study of Systems Biology, School of Biology, Georgia Institute of Technology, Atlanta, Georgia, United States of America.', 'Georgia|Georgia', 65, 'Binding Sites|Computational Biology|Databases, Protein|Ligands|Models, Molecular|Protein Binding|Protein Conformation|Proteins', 'Journal Article', '10.1371/journal.pcbi.1003302', '24204237', 'Many biological activities originate from interactions between small-molecule ligands and their protein targets. A detailed structural and physico-chemical characterization of these interactions could significantly deepen our understanding of protein function and facilitate drug design. Here, we present a large-scale study on a non-redundant set of about 20,000 known ligand-binding sites, or pockets, of proteins. We find that the structural space of protein pockets is crowded, likely complete, and may be represented by about 1,000 pocket shapes. Correspondingly, the growth rate of novel pockets deposited in the Protein Data Bank has been decreasing steadily over the recent years. Moreover, many protein pockets are promiscuous and interact with ligands of diverse scaffolds. Conversely, many ligands are promiscuous and interact with structurally different pockets. Through a physico-chemical and structural analysis, we provide insights into understanding both pocket promiscuity and ligand promiscuity. Finally, we discuss the implications of our study for the prediction of protein-ligand interactions based on pocket comparison. '),
(86261, 2013, 'plos', 'Emergence of metastable state dynamics in interconnected cortical networks with propagation delays', 'Kutchko, Katrina M|Fröhlich, Flavio', 'Department of Psychiatry, University of North Carolina at Chapel Hill, Chapel Hill, North Carolina, United States of America , Curriculum in Bioinformatics and Computational Biology, University of North Carolina at Chapel Hill, Chapel Hill, North Carolina, United States of America.|Department of Psychiatry, University of North Carolina at Chapel Hill, Chapel Hill, North Carolina, United States of America , Curriculum in Bioinformatics and Computational Biology, University of North Carolina at Chapel Hill, Chapel Hill, North Carolina, United States of America.', 'United States|United States', 0, 'Autistic Disorder|Brain|Computer Simulation|Cortical Synchronization|Deep Brain Stimulation|Humans|Models, Neurological|Nerve Net|Schizophrenia', 'Journal Article', '10.1371/journal.pcbi.1003304', '24204238', 'The importance of the large number of thin-diameter and unmyelinated axons that connect different cortical areas is unknown. The pronounced propagation delays in these axons may prevent synchronization of cortical networks and therefore hinder efficient information integration and processing. Yet, such global information integration across cortical areas is vital for higher cognitive function. We hypothesized that delays in communication between cortical areas can disrupt synchronization and therefore enhance the set of activity trajectories and computations interconnected networks can perform. To evaluate this hypothesis, we studied the effect of long-range cortical projections with propagation delays in interconnected large-scale cortical networks that exhibited spontaneous rhythmic activity. Long-range connections with delays caused the emergence of metastable, spatio-temporally distinct activity states between which the networks spontaneously transitioned. Interestingly, the observed activity patterns correspond to macroscopic network dynamics such as globally synchronized activity, propagating wave fronts, and spiral waves that have been previously observed in neurophysiological recordings from humans and animal models. Transient perturbations with simulated transcranial alternating current stimulation (tACS) confirmed the multistability of the interconnected networks by switching the networks between these metastable states. Our model thus proposes that slower long-range connections enrich the landscape of activity states and represent a parsimonious mechanism for the emergence of multistability in cortical networks. These results further provide a mechanistic link between the known deficits in connectivity and cortical state dynamics in neuropsychiatric illnesses such as schizophrenia and autism, as well as suggest non-invasive brain stimulation as an effective treatment for these illnesses. '),
(86262, 2013, 'plos', 'Explain bioinformatics to your grandmother!', 'Bernard, Virginie|Michaut, Magali', 'Next Generation Sequencing Platform - ICGex, Curie Institute, Paris, France.|Next Generation Sequencing Platform - ICGex, Curie Institute, Paris, France.', 'France|France', 1, 'Biomedical Research|Career Choice|Communication|Computational Biology|Humans', 'Journal Article', '10.1371/journal.pcbi.1003305', '24204239', 'What are you working on? You have certainly been asked that question many times, whether it be at a Saturday night party, during a discussion with your neighbors, or at a family gathering. Communicating with a lay audience about scientific subjects and making them attractive is a difficult task. But difficult or not, you will have to do it for many years, not only with your family and friends, but also with your colleagues and collaborators. So, better learn now! Although not usually taught, the ability to explain your work to others is an essential skill in science, where communication plays a key role. Using some examples of the French Regional Student Group activities, we discuss here (i) why it is important to have such communication skills, (ii) how you can get involved in these activities by using existing resources or working with people who have previous experience, and (iii) what you get out of this amazing experience. We aim to motivate you and provide you with tips and ideas to get involved in promoting scientific activities while getting all the benefits. '),
(86263, 2013, 'plos', 'Synaptic scaling enables dynamically distinct short- and long-term memory formation', 'Tetzlaff, Christian|Kolodziejski, Christoph|Timme, Marc|Tsodyks, Misha|Wörgötter, Florentin', 'Faculty of Physics - Biophysics, Georg August University Friedrich-Hund Platz 1, Göttingen, Germany , Network Dynamics Group, Max Planck Institute for Dynamics and Self-Organization, Göttingen, Germany , Bernstein Center for Computational Neuroscience, Georg-August-University Friedrich-Hund Platz 1, Göttingen, Germany.|Faculty of Physics - Biophysics, Georg August University Friedrich-Hund Platz 1, Göttingen, Germany , Network Dynamics Group, Max Planck Institute for Dynamics and Self-Organization, Göttingen, Germany , Bernstein Center for Computational Neuroscience, Georg-August-University Friedrich-Hund Platz 1, Göttingen, Germany.|Faculty of Physics - Biophysics, Georg August University Friedrich-Hund Platz 1, Göttingen, Germany , Network Dynamics Group, Max Planck Institute for Dynamics and Self-Organization, Göttingen, Germany , Bernstein Center for Computational Neuroscience, Georg-August-University Friedrich-Hund Platz 1, Göttingen, Germany.|Faculty of Physics - Biophysics, Georg August University Friedrich-Hund Platz 1, Göttingen, Germany , Network Dynamics Group, Max Planck Institute for Dynamics and Self-Organization, Göttingen, Germany , Bernstein Center for Computational Neuroscience, Georg-August-University Friedrich-Hund Platz 1, Göttingen, Germany.|Faculty of Physics - Biophysics, Georg August University Friedrich-Hund Platz 1, Göttingen, Germany , Network Dynamics Group, Max Planck Institute for Dynamics and Self-Organization, Göttingen, Germany , Bernstein Center for Computational Neuroscience, Georg-August-University Friedrich-Hund Platz 1, Göttingen, Germany.', 'Germany|Germany|Germany|Germany|Germany', 15, 'Computational Biology|Memory, Long-Term|Memory, Short-Term|Models, Neurological|Neuronal Plasticity|Neurons|Synapses', 'Journal Article', '10.1371/journal.pcbi.1003307', '24204240', 'Memory storage in the brain relies on mechanisms acting on time scales from minutes, for long-term synaptic potentiation, to days, for memory consolidation. During such processes, neural circuits distinguish synapses relevant for forming a long-term storage, which are consolidated, from synapses of short-term storage, which fade. How time scale integration and synaptic differentiation is simultaneously achieved remains unclear. Here we show that synaptic scaling - a slow process usually associated with the maintenance of activity homeostasis - combined with synaptic plasticity may simultaneously achieve both, thereby providing a natural separation of short- from long-term storage. The interaction between plasticity and scaling provides also an explanation for an established paradox where memory consolidation critically depends on the exact order of learning and recall. These results indicate that scaling may be fundamental for stabilizing memories, providing a dynamic link between early and late memory formation processes. '),
(86264, 2013, 'plos', 'Natural, persistent oscillations in a spatial multi-strain disease system with application to dengue', 'Lourenço, José|Recker, Mario', 'Department of Zoology, University of Oxford, Oxford, United Kingdom.|Department of Zoology, University of Oxford, Oxford, United Kingdom.', 'United Kingdom|United Kingdom', 0, 'Communicable Diseases|Dengue|Epidemics|Humans|Models, Biological', 'Journal Article', '10.1371/journal.pcbi.1003308', '24204241', 'Many infectious diseases are not maintained in a state of equilibrium but exhibit significant fluctuations in prevalence over time. For pathogens that consist of multiple antigenic types or strains, such as influenza, malaria or dengue, these fluctuations often take on the form of regular or irregular epidemic outbreaks in addition to oscillatory prevalence levels of the constituent strains. To explain the observed temporal dynamics and structuring in pathogen populations, epidemiological multi-strain models have commonly evoked strong immune interactions between strains as the predominant driver. Here, with specific reference to dengue, we show how spatially explicit, multi-strain systems can exhibit all of the described epidemiological dynamics even in the absence of immune competition. Instead, amplification of natural stochastic differences in disease transmission, can give rise to persistent oscillations comprising semi-regular epidemic outbreaks and sequential dominance of dengues four serotypes. Not only can this mechanism explain observed differences in serotype and disease distributions between neighbouring geographical areas, it also has important implications for inferring the nature and epidemiological consequences of immune mediated competition in multi-strain pathogen systems. '),
(86265, 2013, 'plos', 'Deciding not to decide: computational and neural evidence for hidden behavior in sequential choice', 'Gluth, Sebastian|Rieskamp, Jörg|Büchel, Christian', 'Department of Systems Neuroscience, University Medical Center Hamburg-Eppendorf, Hamburg, Germany , Department of Psychology, University of Basel, Basel, Switzerland.|Department of Systems Neuroscience, University Medical Center Hamburg-Eppendorf, Hamburg, Germany , Department of Psychology, University of Basel, Basel, Switzerland.|Department of Systems Neuroscience, University Medical Center Hamburg-Eppendorf, Hamburg, Germany , Department of Psychology, University of Basel, Basel, Switzerland.', 'Switzerland|Switzerland|Switzerland', 11, 'Adult|Brain|Choice Behavior|Computational Biology|Computer Simulation|Electroencephalography|Female|Humans|Magnetic Resonance Imaging|Male|Reaction Time|Young Adult', 'Journal Article', '10.1371/journal.pcbi.1003309', '24204242', 'Understanding the cognitive and neural processes that underlie human decision making requires the successful prediction of how, but also of when, people choose. Sequential sampling models (SSMs) have greatly advanced the decision sciences by assuming decisions to emerge from a bounded evidence accumulation process so that response times (RTs) become predictable. Here, we demonstrate a difficulty of SSMs that occurs when people are not forced to respond at once but are allowed to sample information sequentially: The decision maker might decide to delay the choice and terminate the accumulation process temporarily, a scenario not accounted for by the standard SSM approach. We developed several SSMs for predicting RTs from two independent samples of an electroencephalography (EEG) and a functional magnetic resonance imaging (fMRI) study. In these studies, participants bought or rejected fictitious stocks based on sequentially presented cues and were free to respond at any time. Standard SSM implementations did not describe RT distributions adequately. However, by adding a mechanism for postponing decisions to the model we obtained an accurate fit to the data. Time-frequency analysis of EEG data revealed alternating states of de- and increasing oscillatory power in beta-band frequencies (14-30 Hz), indicating that responses were repeatedly prepared and inhibited and thus lending further support for the existence of a decision not to decide. Finally, the extended model accounted for the results of an adapted version of our paradigm in which participants had to press a button for sampling more information. Our results show how computational modeling of decisions and RTs support a deeper understanding of the hidden dynamics in cognition. '),
(86266, 2013, 'plos', 'Conformational changes in talin on binding to anionic phospholipid membranes facilitate signaling by integrin transmembrane helices', 'Kalli, Antreas C|Campbell, Iain D|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', 0, 'Integrins|Molecular Dynamics Simulation|Phospholipids|Protein Structure, Tertiary|Talin', 'Journal Article', '10.1371/journal.pcbi.1003316', '24204243', 'Integrins are heterodimeric (xcexb1xcexb2) cell surface receptors that are activated to a high affinity state by the formation of a complex involving the xcexb1/xcexb2 integrin transmembrane helix dimer, the head domain of talin (a cytoplasmic protein that links integrins to actin), and the membrane. The talin head domain contains four sub-domains (F0, F1, F2 and F3) with a long cationic loop inserted in the F1 domain. Here, we model the binding and interactions of the complete talin head domain with a phospholipid bilayer, using multiscale molecular dynamics simulations. The role of the inserted F1 loop, which is missing from the crystal structure of the talin head, PDB:3IVF, is explored. The results show that the talin head domain binds to the membrane predominantly via cationic regions on the F2 and F3 subdomains and the F1 loop. Upon binding, the intact talin head adopts a novel V-shaped conformation which optimizes its interactions with the membrane. Simulations of the complex of talin with the integrin xcexb1/xcexb2 TM helix dimer in a membrane, show how this complex promotes a rearrangement, and eventual dissociation of, the integrin xcexb1 and xcexb2 transmembrane helices. A model for the talin-mediated integrin activation is proposed which describes how the mutual interplay of interactions between transmembrane helices, the cytoplasmic talin protein, and the lipid bilayer promotes integrin inside-out activation. '),
(86267, 2013, 'plos', 'APBioNet-transforming bioinformatics in the Asia-Pacific region', 'Khan, Asif M|Tan, Tin Wee|Schönbach, Christian|Ranganathan, Shoba', 'Perdana University Graduate School of Medicine, Selangor Darul Ehsan, Malaysia , Department of Pharmacology and Molecular Sciences, The Johns Hopkins University School of Medicine, Baltimore, Maryland, United States of America.|Perdana University Graduate School of Medicine, Selangor Darul Ehsan, Malaysia , Department of Pharmacology and Molecular Sciences, The Johns Hopkins University School of Medicine, Baltimore, Maryland, United States of America.|Perdana University Graduate School of Medicine, Selangor Darul Ehsan, Malaysia , Department of Pharmacology and Molecular Sciences, The Johns Hopkins University School of Medicine, Baltimore, Maryland, United States of America.|Perdana University Graduate School of Medicine, Selangor Darul Ehsan, Malaysia , Department of Pharmacology and Molecular Sciences, The Johns Hopkins University School of Medicine, Baltimore, Maryland, United States of America.', 'Malaysia|Malaysia|Malaysia|Malaysia', 3, 'Asia, Southeastern|Computational Biology|Cooperative Behavior|Databases, Genetic|Humans|Internet', 'Journal Article', '10.1371/journal.pcbi.1003317', '24204244', '-'),
(86268, 2013, 'plos', 'Predictive coding of dynamical variables in balanced spiking networks', 'Boerlin, Martin|Machens, Christian K|Denève, Sophie', 'Group for Neural Theory, Département dÉtudes Cognitives, École Normale Supérieure, Paris, France.|Group for Neural Theory, Département dÉtudes Cognitives, École Normale Supérieure, Paris, France.|Group for Neural Theory, Département dÉtudes Cognitives, École Normale Supérieure, Paris, France.', 'France|France|France', 0, 'Action Potentials|Algorithms|Computational Biology|Models, Neurological|Models, Statistical|Reproducibility of Results', 'Journal Article', '10.1371/journal.pcbi.1003258', '24244113', 'Two observations about the cortex have puzzled neuroscientists for a long time. First, neural responses are highly variable. Second, the level of excitation and inhibition received by each neuron is tightly balanced at all times. Here, we demonstrate that both properties are necessary consequences of neural networks that represent information efficiently in their spikes. We illustrate this insight with spiking networks that represent dynamical variables. Our approach is based on two assumptions: We assume that information about dynamical variables can be read out linearly from neural spike trains, and we assume that neurons only fire a spike if that improves the representation of the dynamical variables. Based on these assumptions, we derive a network of leaky integrate-and-fire neurons that is able to implement arbitrary linear dynamical systems. We show that the membrane voltage of the neurons is equivalent to a prediction error about a common population-level signal. Among other things, our approach allows us to construct an integrator network of spiking neurons that is robust against many perturbations. Most importantly, neural variability in our networks cannot be equated to noise. Despite exhibiting the same single unit properties as widely used population code models (e.g. tuning curves, Poisson distributed spike trains), balanced networks are orders of magnitudes more reliable. Our approach suggests that spikes do matter when considering how the brain computes, and that the reliability of cortical representations could have been strongly underestimated. '),
(86269, 2013, 'plos', 'Catalysis of protein folding by chaperones accelerates evolutionary dynamics in adapting cell populations', 'Cetinbaxc5x9f, Murat|Shakhnovich, Eugene I', 'Department of Chemistry and Chemical Biology, Harvard University, Cambridge, Massachusetts, United States of America.|Department of Chemistry and Chemical Biology, Harvard University, Cambridge, Massachusetts, United States of America.', 'United States|United States', 10, 'Adaptation, Physiological|Algorithms|Computational Biology|Evolution, Molecular|Models, Biological|Molecular Chaperones|Molecular Dynamics Simulation|Protein Folding|Protein Interaction Domains and Motifs|Proteins', 'Journal Article', '10.1371/journal.pcbi.1003269', '24244114', 'Although molecular chaperones are essential components of protein homeostatic machinery, their mechanism of action and impact on adaptation and evolutionary dynamics remain controversial. Here we developed a physics-based ab initio multi-scale model of a living cell for population dynamics simulations to elucidate the effect of chaperones on adaptive evolution. The 6-loci genomes of model cells encode model proteins, whose folding and interactions in cellular milieu can be evaluated exactly from their genome sequences. A genotype-phenotype relationship that is based on a simple yet non-trivially postulated protein-protein interaction (PPI) network determines the cell division rate. Model proteins can exist in native and molten globule states and participate in functional and all possible promiscuous non-functional PPIs. We find that an active chaperone mechanism, whereby chaperones directly catalyze protein folding, has a significant impact on the cellular fitness and the rate of evolutionary dynamics, while passive chaperones, which just maintain misfolded proteins in soluble complexes have a negligible effect on the fitness. We find that by partially releasing the constraint on protein stability, active chaperones promote a deeper exploration of sequence space to strengthen functional PPIs, and diminish the non-functional PPIs. A key experimentally testable prediction emerging from our analysis is that down-regulation of chaperones that catalyze protein folding significantly slows down the adaptation dynamics. ');
INSERT INTO `papers` (`id`, `ano`, `journal`, `titulo`, `autores`, `afiliacao`, `pais`, `citacoes`, `palavra_chave`, `categorias`, `doi`, `pubmed`, `abstract`) VALUES
(86270, 2013, 'plos', 'A tunable coarse-grained model for ligand-receptor interaction', 'Ruiz-Herrero, Teresa|Estrada, Javier|Guantes, Raúl|Miguez, David G', 'Departamento de Física Teórica de la Materia Condensada, Universidad Autónoma de Madrid, Madrid, España.|Departamento de Física Teórica de la Materia Condensada, Universidad Autónoma de Madrid, Madrid, España.|Departamento de Física Teórica de la Materia Condensada, Universidad Autónoma de Madrid, Madrid, España.|Departamento de Física Teórica de la Materia Condensada, Universidad Autónoma de Madrid, Madrid, España.', '-|-|-|-', 0, 'Computational Biology|Computer Simulation|Ligands|Models, Molecular|Protein Binding|Receptors, Cell Surface', 'Journal Article', '10.1371/journal.pcbi.1003274', '24244115', 'Cell-surface receptors are the most common target for therapeutic drugs. The design and optimization of next generation synthetic drugs require a detailed understanding of the interaction with their corresponding receptors. Mathematical approximations to study ligand-receptor systems based on reaction kinetics strongly simplify the spatial constraints of the interaction, while full atomistic ligand-receptor models do not allow for a statistical many-particle analysis, due to their high computational requirements. Here we present a generic coarse-grained model for ligand-receptor systems that accounts for the essential spatial characteristics of the interaction, while allowing statistical analysis. The model captures the main features of ligand-receptor kinetics, such as diffusion dependence of affinity and dissociation rates. Our model is used to characterize chimeric compounds, designed to take advantage of the receptor over-expression phenotype of certain diseases to selectively target unhealthy cells. Molecular dynamics simulations of chimeric ligands are used to study how selectivity can be optimized based on receptor abundance, ligand-receptor affinity and length of the linker between both ligand subunits. Overall, this coarse-grained model is a useful approximation in the study of systems with complex ligand-receptor interactions or spatial constraints. '),
(86271, 2013, 'plos', 'Communication and common interest', 'Godfrey-Smith, Peter|Martínez, Manolo', 'Philosophy Program, The Graduate Center CUNY, New York City, New York, United States of America.|Philosophy Program, The Graduate Center CUNY, New York City, New York, United States of America.', 'United States|United States', 18, 'Communication|Computational Biology|Game Theory|Humans|Models, Theoretical|Reward', 'Journal Article', '10.1371/journal.pcbi.1003282', '24244116', 'Explaining the maintenance of communicative behavior in the face of incentives to deceive, conceal information, or exaggerate is an important problem in behavioral biology. When the interests of agents diverge, some form of signal cost is often seen as essential to maintaining honesty. Here, novel computational methods are used to investigate the role of common interest between the sender and receiver of messages in maintaining cost-free informative signaling in a signaling game. Two measures of common interest are defined. These quantify the divergence between sender and receiver in their preference orderings over acts the receiver might perform in each state of the world. Sampling from a large space of signaling games finds that informative signaling is possible at equilibrium with zero common interest in both senses. Games of this kind are rare, however, and the proportion of games that include at least one equilibrium in which informative signals are used increases monotonically with common interest. Common interest as a predictor of informative signaling also interacts with the extent to which agents preferences vary with the state of the world. Our findings provide a quantitative description of the relation between common interest and informative signaling, employing exact measures of common interest, information use, and contingency of payoff under environmental variation that may be applied to a wide range of models and empirical systems. '),
(86272, 2013, 'plos', 'Evidence for finely-regulated asynchronous growth of Toxoplasma gondii cysts based on data-driven model selection', 'Sullivan, Adam M|Zhao, Xiaopeng|Suzuki, Yasuhiro|Ochiai, Eri|Crutcher, Stephen|Gilchrist, Michael A', 'Department of Mechanical, Aerospace, and Biomedical Engineering, University of Tennessee, Knoxville, Tennessee, United States of America , National Institute of Mathematical and Biological Synthesis, University of Tennessee, Knoxville, Tennessee, United States of America.|Department of Mechanical, Aerospace, and Biomedical Engineering, University of Tennessee, Knoxville, Tennessee, United States of America , National Institute of Mathematical and Biological Synthesis, University of Tennessee, Knoxville, Tennessee, United States of America.|Department of Mechanical, Aerospace, and Biomedical Engineering, University of Tennessee, Knoxville, Tennessee, United States of America , National Institute of Mathematical and Biological Synthesis, University of Tennessee, Knoxville, Tennessee, United States of America.|Department of Mechanical, Aerospace, and Biomedical Engineering, University of Tennessee, Knoxville, Tennessee, United States of America , National Institute of Mathematical and Biological Synthesis, University of Tennessee, Knoxville, Tennessee, United States of America.|Department of Mechanical, Aerospace, and Biomedical Engineering, University of Tennessee, Knoxville, Tennessee, United States of America , National Institute of Mathematical and Biological Synthesis, University of Tennessee, Knoxville, Tennessee, United States of America.|Department of Mechanical, Aerospace, and Biomedical Engineering, University of Tennessee, Knoxville, Tennessee, United States of America , National Institute of Mathematical and Biological Synthesis, University of Tennessee, Knoxville, Tennessee, United States of America.', 'United States|United States|United States|United States|United States|United States', 7, 'Animals|Brain|Computational Biology|Cysts|Female|Host-Pathogen Interactions|Mice|Models, Biological|Models, Statistical|Toxoplasma', 'Journal Article', '10.1371/journal.pcbi.1003283', '24244117', 'Toxoplasma gondii establishes a chronic infection by forming cysts preferentially in the brain. This chronic infection is one of the most common parasitic infections in humans and can be reactivated to develop life-threatening toxoplasmic encephalitis in immunocompromised patients. Host-pathogen interactions during the chronic infection include growth of the cysts and their removal by both natural rupture and elimination by the immune system. Analyzing these interactions is important for understanding the pathogenesis of this common infection. We developed a differential equation framework of cyst growth and employed Akaike Information Criteria (AIC) to determine the growth and removal functions that best describe the distribution of cyst sizes measured from the brains of chronically infected mice. The AIC strongly support models in which T. gondii cysts grow at a constant rate such that the per capita growth rate of the parasite is inversely proportional to the number of parasites within a cyst, suggesting finely-regulated asynchronous replication of the parasites. Our analyses were also able to reject the models where cyst removal rate increases linearly or quadratically in association with increase in cyst size. The modeling and analysis framework may provide a useful tool for understanding the pathogenesis of infections with other cyst producing parasites. '),
(86273, 2013, 'plos', 'A neurocomputational model of the mismatch negativity', 'Lieder, Falk|Stephan, Klaas E|Daunizeau, Jean|Garrido, Marta I|Friston, Karl J', 'Translational Neuromodeling Unit (TNU), Institute of Biomedical Engineering, University of Zurich & ETH Zurich, Zurich, Switzerland , Laboratory for Social and Neuronal Systems Research, Dept. of Economics, University of Zurich, Zurich, Switzerland , Helen Wills Neuroscience Institute, University of California at Berkeley, Berkeley, California, United States of America.|Translational Neuromodeling Unit (TNU), Institute of Biomedical Engineering, University of Zurich & ETH Zurich, Zurich, Switzerland , Laboratory for Social and Neuronal Systems Research, Dept. of Economics, University of Zurich, Zurich, Switzerland , Helen Wills Neuroscience Institute, University of California at Berkeley, Berkeley, California, United States of America.|Translational Neuromodeling Unit (TNU), Institute of Biomedical Engineering, University of Zurich & ETH Zurich, Zurich, Switzerland , Laboratory for Social and Neuronal Systems Research, Dept. of Economics, University of Zurich, Zurich, Switzerland , Helen Wills Neuroscience Institute, University of California at Berkeley, Berkeley, California, United States of America.|Translational Neuromodeling Unit (TNU), Institute of Biomedical Engineering, University of Zurich & ETH Zurich, Zurich, Switzerland , Laboratory for Social and Neuronal Systems Research, Dept. of Economics, University of Zurich, Zurich, Switzerland , Helen Wills Neuroscience Institute, University of California at Berkeley, Berkeley, California, United States of America.|Translational Neuromodeling Unit (TNU), Institute of Biomedical Engineering, University of Zurich & ETH Zurich, Zurich, Switzerland , Laboratory for Social and Neuronal Systems Research, Dept. of Economics, University of Zurich, Zurich, Switzerland , Helen Wills Neuroscience Institute, University of California at Berkeley, Berkeley, California, United States of America.', 'Switzerland|Switzerland|Switzerland|Switzerland|Switzerland', 0, 'Algorithms|Auditory Cortex|Bayes Theorem|Computational Biology|Computer Simulation|Electroencephalography|Evoked Potentials|Humans|Models, Neurological|Models, Statistical', 'Journal Article', '10.1371/journal.pcbi.1003288', '24244118', 'The mismatch negativity (MMN) is an event related potential evoked by violations of regularity. Here, we present a model of the underlying neuronal dynamics based upon the idea that auditory cortex continuously updates a generative model to predict its sensory inputs. The MMN is then modelled as the superposition of the electric fields evoked by neuronal activity reporting prediction errors. The process by which auditory cortex generates predictions and resolves prediction errors was simulated using generalised (Bayesian) filtering--a biologically plausible scheme for probabilistic inference on the hidden states of hierarchical dynamical models. The resulting scheme generates realistic MMN waveforms, explains the qualitative effects of deviant probability and magnitude on the MMN - in terms of latency and amplitude--and makes quantitative predictions about the interactions between deviant probability and magnitude. This work advances a formal understanding of the MMN and--more generally--illustrates the potential for developing computationally informed dynamic causal models of empirical electromagnetic responses.'),
(86274, 2013, 'plos', 'Dynamical adaptation in photoreceptors', 'Clark, Damon A|Benichou, Raphael|Meister, Markus|Azeredo da Silveira, Rava', 'Department of Physics, Ecole Normale Supxc3xa9rieure, Paris, France.|Department of Physics, Ecole Normale Supxc3xa9rieure, Paris, France.|Department of Physics, Ecole Normale Supxc3xa9rieure, Paris, France.|Department of Physics, Ecole Normale Supxc3xa9rieure, Paris, France.', 'France|France|France|France', 19, 'Adaptation, Physiological|Animals|Computational Biology|Humans|Light|Light Signal Transduction|Models, Biological|Photoreceptor Cells', 'Journal Article', '10.1371/journal.pcbi.1003289', '24244119', 'Adaptation is at the heart of sensation and nowhere is it more salient than in early visual processing. Light adaptation in photoreceptors is doubly dynamical: it depends upon the temporal structure of the input and it affects the temporal structure of the response. We introduce a non-linear dynamical adaptation model of photoreceptors. It is simple enough that it can be solved exactly and simulated with ease, analytical and numerical approaches combined provide both intuition on the behavior of dynamical adaptation and quantitative results to be compared with data. Yet the model is rich enough to capture intricate phenomenology. First, we show that it reproduces the known phenomenology of light response and short-term adaptation. Second, we present new recordings and demonstrate that the model reproduces cone response with great precision. Third, we derive a number of predictions on the response of photoreceptors to sophisticated stimuli such as periodic inputs, various forms of flickering inputs, and natural inputs. In particular, we demonstrate that photoreceptors undergo rapid adaptation of response gain and time scale, over xe2x88xbc 300[Formula: see text] ms-i. e., over the time scale of the response itself-and we confirm this prediction with data. For natural inputs, this fast adaptation can modulate the response gain more than tenfold and is hence physiologically relevant. '),
(86275, 2013, 'plos', 'In silico analysis of cell cycle synchronisation effects in radiotherapy of tumour spheroids', 'Kempf, Harald|Hatzikirou, Haralampos|Bleicher, Marcus|Meyer-Hermann, Michael', 'Department of Systems Immunology, Helmholtz Centre for Infection Research, Braunschweig, Germany , Frankfurt Institute for Advanced Studies, Frankfurt, Germany.|Department of Systems Immunology, Helmholtz Centre for Infection Research, Braunschweig, Germany , Frankfurt Institute for Advanced Studies, Frankfurt, Germany.|Department of Systems Immunology, Helmholtz Centre for Infection Research, Braunschweig, Germany , Frankfurt Institute for Advanced Studies, Frankfurt, Germany.|Department of Systems Immunology, Helmholtz Centre for Infection Research, Braunschweig, Germany , Frankfurt Institute for Advanced Studies, Frankfurt, Germany.', 'Germany|Germany|Germany|Germany', 26, 'Animals|Cell Cycle|Cell Line, Tumor|Computational Biology|Computer Simulation|Mice|Models, Biological|Radiotherapy|Spheroids, Cellular|Tumor Cells, Cultured', 'Journal Article', '10.1371/journal.pcbi.1003295', '24244120', 'Tumour cells show a varying susceptibility to radiation damage as a function of the current cell cycle phase. While this sensitivity is averaged out in an unperturbed tumour due to unsynchronised cell cycle progression, external stimuli such as radiation or drug doses can induce a resynchronisation of the cell cycle and consequently induce a collective development of radiosensitivity in tumours. Although this effect has been regularly described in experiments it is currently not exploited in clinical practice and thus a large potential for optimisation is missed. We present an agent-based model for three-dimensional tumour spheroid growth which has been combined with an irradiation damage and kinetics model. We predict the dynamic response of the overall tumour radiosensitivity to delivered radiation doses and describe corresponding time windows of increased or decreased radiation sensitivity. The degree of cell cycle resynchronisation in response to radiation delivery was identified as a main determinant of the transient periods of low and high radiosensitivity enhancement. A range of selected clinical fractionation schemes is examined and new triggered schedules are tested which aim to maximise the effect of the radiation-induced sensitivity enhancement. We find that the cell cycle resynchronisation can yield a strong increase in therapy effectiveness, if employed correctly. While the individual timing of sensitive periods will depend on the exact cell and radiation types, enhancement is a universal effect which is present in every tumour and accordingly should be the target of experimental investigation. Experimental observables which can be assessed non-invasively and with high spatio-temporal resolution have to be connected to the radiosensitivity enhancement in order to allow for a possible tumour-specific design of highly efficient treatment schedules based on induced cell cycle synchronisation. '),
(86276, 2013, 'plos', 'Comparing algorithms that reconstruct cell lineage trees utilizing information on microsatellite mutations', 'Chapal-Ilani, Noa|Maruvka, Yosef E|Spiro, Adam|Reizel, Yitzhak|Adar, Rivka|Shlush, Liran I|Shapiro, Ehud', 'Department of Computer Science and Applied Mathematics, Weizmann Institute of Science, Rehovot, Israel.|Department of Computer Science and Applied Mathematics, Weizmann Institute of Science, Rehovot, Israel.|Department of Computer Science and Applied Mathematics, Weizmann Institute of Science, Rehovot, Israel.|Department of Computer Science and Applied Mathematics, Weizmann Institute of Science, Rehovot, Israel.|Department of Computer Science and Applied Mathematics, Weizmann Institute of Science, Rehovot, Israel.|Department of Computer Science and Applied Mathematics, Weizmann Institute of Science, Rehovot, Israel.|Department of Computer Science and Applied Mathematics, Weizmann Institute of Science, Rehovot, Israel.', 'Israel|Israel|Israel|Israel|Israel|Israel|Israel', 0, 'Algorithms|Animals|Bone Marrow Cells|Cell Lineage|Cells, Cultured|Cluster Analysis|Computational Biology|Computer Simulation|Female|Humans|Male|Mice|Mice, Transgenic|Microsatellite Repeats|Models, Genetic|Mutation|Phylogeny', 'Journal Article', '10.1371/journal.pcbi.1003297', '24244121', 'Organism cells proliferate and die to build, maintain, renew and repair it. The cellular history of an organism up to any point in time can be captured by a cell lineage tree in which vertices represent all organism cells, past and present, and directed edges represent progeny relations among them. The root represents the fertilized egg, and the leaves represent extant and dead cells. Somatic mutations accumulated during cell division endow each organism cell with a genomic signature that is unique with a very high probability. Distances between such genomic signatures can be used to reconstruct an organisms cell lineage tree. Cell populations possess unique features that are absent or rare in organism populations (e.g., the presence of stem cells and a small number of generations since the zygote) and do not undergo sexual reproduction, hence the reconstruction of cell lineage trees calls for careful examination and adaptation of the standard tools of population genetics. Our lab developed a method for reconstructing cell lineage trees by examining only mutations in highly variable microsatellite loci (MS, also called short tandem repeats, STR). In this study we use experimental data on somatic mutations in MS of individual cells in human and mice in order to validate and quantify the utility of known lineage tree reconstruction algorithms in this context. We employed extensive measurements of somatic mutations in individual cells which were isolated from healthy and diseased tissues of mice and humans. The validation was done by analyzing the ability to infer known and clear biological scenarios. In general, we found that if the biological scenario is simple, almost all algorithms tested can infer it. Another somewhat surprising conclusion is that the best algorithm among those tested is Neighbor Joining where the distance measure used is normalized absolute distance. We include our full dataset in Tables S1, S2, S3, S4, S5 to enable further analysis of this data by others. '),
(86277, 2013, 'plos', 'A computational model of liver iron metabolism', 'Mitchell, Simon|Mendes, Pedro', 'School of Computer Science and Manchester Institute of Biotechnology, University of Manchester, Manchester, United Kingdom.|School of Computer Science and Manchester Institute of Biotechnology, University of Manchester, Manchester, United Kingdom.', 'United Kingdom|United Kingdom', 20, 'Computational Biology|Computer Simulation|Hemochromatosis|Hepcidins|Humans|Iron|Kinetics|Liver|Models, Biological|Transferrin', 'Journal Article', '10.1371/journal.pcbi.1003299', '24244122', 'Iron is essential for all known life due to its redox properties, however, these same properties can also lead to its toxicity in overload through the production of reactive oxygen species. Robust systemic and cellular control are required to maintain safe levels of iron, and the liver seems to be where this regulation is mainly located. Iron misregulation is implicated in many diseases, and as our understanding of iron metabolism improves, the list of iron-related disorders grows. Recent developments have resulted in greater knowledge of the fate of iron in the body and have led to a detailed map of its metabolism, however, a quantitative understanding at the systems level of how its components interact to produce tight regulation remains elusive. A mechanistic computational model of human liver iron metabolism, which includes the core regulatory components, is presented here. It was constructed based on known mechanisms of regulation and on their kinetic properties, obtained from several publications. The model was then quantitatively validated by comparing its results with previously published physiological data, and it is able to reproduce multiple experimental findings. A time course simulation following an oral dose of iron was compared to a clinical time course study and the simulation was found to recreate the dynamics and time scale of the systems response to iron challenge. A disease state simulation of haemochromatosis was created by altering a single reaction parameter that mimics a human haemochromatosis gene (HFE) mutation. The simulation provides a quantitative understanding of the liver iron overload that arises in this disease. This model supports and supplements understanding of the role of the liver as an iron sensor and provides a framework for further modelling, including simulations to identify valuable drug targets and design of experiments to improve further our knowledge of this system. '),
(86278, 2013, 'plos', 'Distribution of the fittest individuals and the rate of Mullers ratchet in a model with overlapping generations', 'Metzger, Jakob J|Eule, Stephan', 'Max Planck Institute for Dynamics and Self-Organization (MPIDS), Göttingen, Germany , Institute for Nonlinear Dynamics, Department of Physics, University of Göttingen, Göttingen, Germany.|Max Planck Institute for Dynamics and Self-Organization (MPIDS), Göttingen, Germany , Institute for Nonlinear Dynamics, Department of Physics, University of Göttingen, Göttingen, Germany.', 'Germany|Germany', 0, 'Computational Biology|Evolution, Molecular|Genetic Fitness|Models, Genetic|Mutation|Selection, Genetic', 'Journal Article', '10.1371/journal.pcbi.1003303', '24244123', 'Mullers ratchet is a paradigmatic model for the accumulation of deleterious mutations in a population of finite size. A click of the ratchet occurs when all individuals with the least number of deleterious mutations are lost irreversibly due to a stochastic fluctuation. In spite of the simplicity of the model, a quantitative understanding of the process remains an open challenge. In contrast to previous works, we here study a Moran model of the ratchet with overlapping generations. Employing an approximation which describes the fittest individuals as one class and the rest as a second class, we obtain closed analytical expressions of the ratchet rate in the rare clicking regime. As a click in this regime is caused by a rare, large fluctuation from a metastable state, we do not resort to a diffusion approximation but apply an approximation scheme which is especially well suited to describe extinction events from metastable states. This method also allows for a derivation of expressions for the quasi-stationary distribution of the fittest class. Additionally, we confirm numerically that the formulation with overlapping generations leads to the same results as the diffusion approximation and the corresponding Wright-Fisher model with non-overlapping generations. '),
(86279, 2013, 'plos', 'Modeling integrated cellular machinery using hybrid Petri-Boolean networks', 'Berestovsky, Natalie|Zhou, Wanding|Nagrath, Deepak|Nakhleh, Luay', 'Department of Computer Science, Rice University, Houston, Texas, United States of America.|Department of Computer Science, Rice University, Houston, Texas, United States of America.|Department of Computer Science, Rice University, Houston, Texas, United States of America.|Department of Computer Science, Rice University, Houston, Texas, United States of America.', 'United States|United States|United States|United States', 0, 'Computational Biology|Glucose|Humans|Metabolic Networks and Pathways|Models, Biological|Osmoregulation|Reproducibility of Results|Saccharomyces cerevisiae|Signal Transduction|Transcription, Genetic', 'Journal Article', '10.1371/journal.pcbi.1003306', '24244124', 'The behavior and phenotypic changes of cells are governed by a cellular circuitry that represents a set of biochemical reactions. Based on biological functions, this circuitry is divided into three types of networks, each encoding for a major biological process: signal transduction, transcription regulation, and metabolism. This division has generally enabled taming computational complexity dealing with the entire system, allowed for using modeling techniques that are specific to each of the components, and achieved separation of the different time scales at which reactions in each of the three networks occur. Nonetheless, with this division comes loss of information and power needed to elucidate certain cellular phenomena. Within the cell, these three types of networks work in tandem, and each produces signals and/or substances that are used by the others to process information and operate normally. Therefore, computational techniques for modeling integrated cellular machinery are needed. In this work, we propose an integrated hybrid model (IHM) that combines Petri nets and Boolean networks to model integrated cellular networks. Coupled with a stochastic simulation mechanism, the model simulates the dynamics of the integrated network, and can be perturbed to generate testable hypotheses. Our model is qualitative and is mostly built upon knowledge from the literature and requires fine-tuning of very few parameters. We validated our model on two systems: the transcriptional regulation of glucose metabolism in human cells, and cellular osmoregulation in S. cerevisiae. The model produced results that are in very good agreement with experimental data, and produces valid hypotheses. The abstract nature of our model and the ease of its construction makes it a very good candidate for modeling integrated networks from qualitative data. The results it produces can guide the practitioner to zoom into components and interconnections and investigate them using such more detailed mathematical models. '),
(86280, 2013, 'plos', 'Receptor concentration and diffusivity control multivalent binding of Sv40 to membrane bilayers', 'Szklarczyk, Oliwia M|González-Segredo, Nélido|Kukura, Philipp|Oppenheim, Ariella|Choquet, Daniel|Sandoghdar, Vahid|Helenius, Ari|Sbalzarini, Ivo F|Ewers, Helge', 'MOSAIC Group, Institute of Theoretical Computer Science and Swiss Institute of Bioinformatics, ETH Zurich, Zurich, Switzerland , Laboratory of Physical Chemistry, ETH Zurich, Zurich, Switzerland.|MOSAIC Group, Institute of Theoretical Computer Science and Swiss Institute of Bioinformatics, ETH Zurich, Zurich, Switzerland , Laboratory of Physical Chemistry, ETH Zurich, Zurich, Switzerland.|MOSAIC Group, Institute of Theoretical Computer Science and Swiss Institute of Bioinformatics, ETH Zurich, Zurich, Switzerland , Laboratory of Physical Chemistry, ETH Zurich, Zurich, Switzerland.|MOSAIC Group, Institute of Theoretical Computer Science and Swiss Institute of Bioinformatics, ETH Zurich, Zurich, Switzerland , Laboratory of Physical Chemistry, ETH Zurich, Zurich, Switzerland.|MOSAIC Group, Institute of Theoretical Computer Science and Swiss Institute of Bioinformatics, ETH Zurich, Zurich, Switzerland , Laboratory of Physical Chemistry, ETH Zurich, Zurich, Switzerland.|MOSAIC Group, Institute of Theoretical Computer Science and Swiss Institute of Bioinformatics, ETH Zurich, Zurich, Switzerland , Laboratory of Physical Chemistry, ETH Zurich, Zurich, Switzerland.|MOSAIC Group, Institute of Theoretical Computer Science and Swiss Institute of Bioinformatics, ETH Zurich, Zurich, Switzerland , Laboratory of Physical Chemistry, ETH Zurich, Zurich, Switzerland.|MOSAIC Group, Institute of Theoretical Computer Science and Swiss Institute of Bioinformatics, ETH Zurich, Zurich, Switzerland , Laboratory of Physical Chemistry, ETH Zurich, Zurich, Switzerland.|MOSAIC Group, Institute of Theoretical Computer Science and Swiss Institute of Bioinformatics, ETH Zurich, Zurich, Switzerland , Laboratory of Physical Chemistry, ETH Zurich, Zurich, Switzerland.', 'Switzerland|Switzerland|Switzerland|Switzerland|Switzerland|Switzerland|Switzerland|Switzerland|Swit', 27, 'Computational Biology|Computer Simulation|G(M1) Ganglioside|Lipid Bilayers|Models, Biological|Protein Binding|Simian virus 40|Stochastic Processes', 'Journal Article', '10.1371/journal.pcbi.1003310', '24244125', 'Incoming Simian Virus 40 particles bind to their cellular receptor, the glycolipid GM1, in the plasma membrane and thereby induce membrane deformation beneath the virion leading to endocytosis and infection. Efficient membrane deformation depends on receptor lipid structure and the organization of binding sites on the internalizing particle. To determine the role of receptor diffusion, concentration and the number of receptors required for stable binding in this interaction, we analyze the binding of SV40 to GM1 in supported membrane bilayers by computational modeling based on experimental data. We measure the diffusion rates of SV40 virions in solution by fluorescence correlation spectroscopy and of the receptor in bilayers by single molecule tracking. Quartz-crystal microbalance with dissipation (QCM-D) is used to measure binding of SV40 virus-like particles to bilayers containing the viral receptor GM1. We develop a phenomenological stochastic dynamics model calibrated against this data, and use it to investigate the early events of virus attachment to lipid membranes. Our results indicate that SV40 requires at least 4 attached receptors to achieve stable binding. We moreover find that receptor diffusion is essential for the establishment of stable binding over the physiological range of receptor concentrations and that receptor concentration controls the mode of viral motion on the target membrane. Our results provide quantitative insight into the initial events of virus-host interaction at the nanoscopic level. '),
(86281, 2013, 'plos', 'Stochastic computations in cortical microcircuit models', 'Habenschuss, Stefan|Jonke, Zeno|Maass, Wolfgang', 'Graz University of Technology, Institute for Theoretical Computer Science, Graz, Austria.|Graz University of Technology, Institute for Theoretical Computer Science, Graz, Austria.|Graz University of Technology, Institute for Theoretical Computer Science, Graz, Austria.', 'Austria|Austria|Austria', 0, 'Computational Biology|Humans|Markov Chains|Models, Neurological|Models, Statistical|Nerve Net|Neurons|Problem Solving|Stochastic Processes', 'Journal Article', '10.1371/journal.pcbi.1003311', '24244126', 'Experimental data from neuroscience suggest that a substantial amount of knowledge is stored in the brain in the form of probability distributions over network states and trajectories of network states. We provide a theoretical foundation for this hypothesis by showing that even very detailed models for cortical microcircuits, with data-based diverse nonlinear neurons and synapses, have a stationary distribution of network states and trajectories of network states to which they converge exponentially fast from any initial state. We demonstrate that this convergence holds in spite of the non-reversibility of the stochastic dynamics of cortical microcircuits. We further show that, in the presence of background network oscillations, separate stationary distributions emerge for different phases of the oscillation, in accordance with experimentally reported phase-specific codes. We complement these theoretical results by computer simulations that investigate resulting computation times for typical probabilistic inference tasks on these internally stored distributions, such as marginalization or marginal maximum-a-posteriori estimation. Furthermore, we show that the inherent stochastic dynamics of generic cortical microcircuits enables them to quickly generate approximate solutions to difficult constraint satisfaction problems, where stored knowledge and current inputs jointly constrain possible solutions. This provides a powerful new computing paradigm for networks of spiking neurons, that also throws new light on how networks of neurons in the brain could carry out complex computational tasks such as prediction, imagination, memory recall and problem solving. '),
(86282, 2013, 'plos', 'Improving the modeling of disease data from the government surveillance system: a case study on malaria in the Brazilian Amazon', 'Valle, Denis|Clark, James', 'School of Forest Resources and Conservation, Tropical Conservation and Development Program (Center for Latin American Studies), Emerging Pathogens Institute, University of Florida, Gainesville, Florida, United States of America.|School of Forest Resources and Conservation, Tropical Conservation and Development Program (Center for Latin American Studies), Emerging Pathogens Institute, University of Florida, Gainesville, Florida, United States of America.', 'United States|United States', 3, 'Algorithms|Brazil|Computational Biology|Computer Simulation|Humans|Incidence|Malaria|Markov Chains|Models, Biological|Monte Carlo Method|Prevalence|Public Health Surveillance|Reproducibility of Results|Spatial Analysis', 'Journal Article', '10.1371/journal.pcbi.1003312', '24244127', 'The study of the effect of large-scale drivers (e.g., climate) of human diseases typically relies on aggregate disease data collected by the government surveillance network. The usual approach to analyze these data, however, often ignores a) changes in the total number of individuals examined, b) the bias towards symptomatic individuals in routine government surveillance, and, c) the influence that observations can have on disease dynamics. Here, we highlight the consequences of ignoring the problems listed above and develop a novel modeling framework to circumvent them, which is illustrated using simulations and real malaria data. Our simulations reveal that trends in the number of disease cases do not necessarily imply similar trends in infection prevalence or incidence, due to the strong influence of concurrent changes in sampling effort. We also show that ignoring decreases in the pool of infected individuals due to the treatment of part of these individuals can hamper reliable inference on infection incidence. We propose a model that avoids these problems, being a compromise between phenomenological statistical models and mechanistic disease dynamics models, in particular, a cross-validation exercise reveals that it has better out-of-sample predictive performance than both of these alternative models. Our case study in the Brazilian Amazon reveals that infection prevalence was high in 2004-2008 (prevalence of 4% with 95% CI of 3-5%), with outbreaks (prevalence up to 18%) occurring during the dry season of the year. After this period, infection prevalence decreased substantially (0.9% with 95% CI of 0.8-1.1%), which is due to a large reduction in infection incidence (i.e., incidence in 2008-2010 was approximately one fifth of the incidence in 2004-2008).We believe that our approach to modeling government surveillance disease data will be useful to advance current understanding of large-scale drivers of several diseases. '),
(86283, 2013, 'plos', 'Computational protein design quantifies structural constraints on amino acid covariation', 'Ollikainen, Noah|Kortemme, Tanja', 'Graduate Program in Bioinformatics, University of California San Francisco, San Francisco, California, United States of America.|Graduate Program in Bioinformatics, University of California San Francisco, San Francisco, California, United States of America.', 'United States|United States', 22, 'Amino Acid Sequence|Amino Acids|Computational Biology|Evolution, Molecular|Models, Molecular|Molecular Sequence Data|Protein Structure, Tertiary|Proteins', 'Journal Article', '10.1371/journal.pcbi.1003313', '24244128', 'Amino acid covariation, where the identities of amino acids at different sequence positions are correlated, is a hallmark of naturally occurring proteins. This covariation can arise from multiple factors, including selective pressures for maintaining protein structure, requirements imposed by a specific function, or from phylogenetic sampling bias. Here we employed flexible backbone computational protein design to quantify the extent to which protein structure has constrained amino acid covariation for 40 diverse protein domains. We find significant similarities between the amino acid covariation in alignments of natural protein sequences and sequences optimized for their structures by computational protein design methods. These results indicate that the structural constraints imposed by protein architecture play a dominant role in shaping amino acid covariation and that computational protein design methods can capture these effects. We also find that the similarity between natural and designed covariation is sensitive to the magnitude and mechanism of backbone flexibility used in computational protein design. Our results thus highlight the necessity of including backbone flexibility to correctly model precise details of correlated amino acid changes and give insights into the pressures underlying these correlations. '),
(86284, 2013, 'plos', 'Systematically differentiating functions for alternatively spliced isoforms through integrating RNA-seq data', 'Eksi, Ridvan|Li, Hong-Dong|Menon, Rajasree|Wen, Yuchen|Omenn, Gilbert S|Kretzler, Matthias|Guan, Yuanfang', 'Department of Computational Medicine and Bioinformatics, University of Michigan, Ann Arbor, Michigan, United States of America.|Department of Computational Medicine and Bioinformatics, University of Michigan, Ann Arbor, Michigan, United States of America.|Department of Computational Medicine and Bioinformatics, University of Michigan, Ann Arbor, Michigan, United States of America.|Department of Computational Medicine and Bioinformatics, University of Michigan, Ann Arbor, Michigan, United States of America.|Department of Computational Medicine and Bioinformatics, University of Michigan, Ann Arbor, Michigan, United States of America.|Department of Computational Medicine and Bioinformatics, University of Michigan, Ann Arbor, Michigan, United States of America.|Department of Computational Medicine and Bioinformatics, University of Michigan, Ann Arbor, Michigan, United States of America.', 'United States|United States|United States|United States|United States|United States|United States', 0, 'Algorithms|Alternative Splicing|Animals|Cluster Analysis|Computational Biology|Databases, Protein|Humans|Mice|Models, Molecular|Protein Isoforms|RNA|Reproducibility of Results|Sequence Analysis, RNA', 'Journal Article', '10.1371/journal.pcbi.1003314', '24244129', 'Integrating large-scale functional genomic data has significantly accelerated our understanding of gene functions. However, no algorithm has been developed to differentiate functions for isoforms of the same gene using high-throughput genomic data. This is because standard supervised learning requires ground-truth functional annotations, which are lacking at the isoform level. To address this challenge, we developed a generic framework that interrogates public RNA-seq data at the transcript level to differentiate functions for alternatively spliced isoforms. For a specific function, our algorithm identifies the responsible isoform(s) of a gene and generates classifying models at the isoform level instead of at the gene level. Through cross-validation, we demonstrated that our algorithm is effective in assigning functions to genes, especially the ones with multiple isoforms, and robust to gene expression levels and removal of homologous gene pairs. We identified genes in the mouse whose isoforms are predicted to have disparate functionalities and experimentally validated the responsible isoforms using data from mammary tissue. With protein structure modeling and experimental evidence, we further validated the predicted isoform functional differences for the genes Cdkn2a and Anxa6. Our generic framework is the first to predict and differentiate functions for alternatively spliced isoforms, instead of genes, using genomic data. It is extendable to any base machine learner and other species with alternatively spliced isoforms, and shifts the current gene-centered function prediction to isoform-level predictions. '),
(86285, 2013, 'plos', 'Prediction of drug-target interactions for drug repositioning only based on genomic expression similarity', 'Wang, Kejian|Sun, Jiazhi|Zhou, Shufeng|Wan, Chunling|Qin, Shengying|Li, Can|He, Lin|Yang, Lun', 'Bio-X Institutes, Key Laboratory for the Genetics of Developmental and Neuropsychiatric Disorders, Shanghai Jiao Tong University, Shanghai, China.|Bio-X Institutes, Key Laboratory for the Genetics of Developmental and Neuropsychiatric Disorders, Shanghai Jiao Tong University, Shanghai, China.|Bio-X Institutes, Key Laboratory for the Genetics of Developmental and Neuropsychiatric Disorders, Shanghai Jiao Tong University, Shanghai, China.|Bio-X Institutes, Key Laboratory for the Genetics of Developmental and Neuropsychiatric Disorders, Shanghai Jiao Tong University, Shanghai, China.|Bio-X Institutes, Key Laboratory for the Genetics of Developmental and Neuropsychiatric Disorders, Shanghai Jiao Tong University, Shanghai, China.|Bio-X Institutes, Key Laboratory for the Genetics of Developmental and Neuropsychiatric Disorders, Shanghai Jiao Tong University, Shanghai, China.|Bio-X Institutes, Key Laboratory for the Genetics of Developmental and Neuropsychiatric Disorders, Shanghai Jiao Tong University, Shanghai, China.|Bio-X Institutes, Key Laboratory for the Genetics of Developmental and Neuropsychiatric Disorders, Shanghai Jiao Tong University, Shanghai, China.', 'China|China|China|China|China|China|China|China', 50, 'Drug Repositioning|Gene Expression|Genomics|Ligands|Pharmaceutical Preparations|Pharmacology', 'Journal Article', '10.1371/journal.pcbi.1003315', '24244130', 'Small drug molecules usually bind to multiple protein targets or even unintended off-targets. Such drug promiscuity has often led to unwanted or unexplained drug reactions, resulting in side effects or drug repositioning opportunities. So it is always an important issue in pharmacology to identify potential drug-target interactions (DTI). However, DTI discovery by experiment remains a challenging task, due to high expense of time and resources. Many computational methods are therefore developed to predict DTI with high throughput biological and clinical data. Here, we initiatively demonstrate that the on-target and off-target effects could be characterized by drug-induced in vitro genomic expression changes, e.g. the data in Connectivity Map (CMap). Thus, unknown ligands of a certain target can be found from the compounds showing high gene-expression similarity to the known ligands. Then to clarify the detailed practice of CMap based DTI prediction, we objectively evaluate how well each target is characterized by CMap. The results suggest that (1) some targets are better characterized than others, so the prediction models specific to these well characterized targets would be more accurate and reliable, (2) in some cases, a family of ligands for the same target tend to interact with common off-targets, which may help increase the efficiency of DTI discovery and explain the mechanisms of complicated drug actions. In the present study, CMap expression similarity is proposed as a novel indicator of drug-target interactions. The detailed strategies of improving data quality by decreasing the batch effect and building prediction models are also effectively established. We believe the success in CMap can be further translated into other public and commercial data of genomic expression, thus increasing research productivity towards valid drug repositioning and minimal side effects. '),
(86286, 2013, 'plos', 'Optimality conditions for cell-fate heterogeneity that maximize the effects of growth factors in PC12 cells', 'Mouri, Kazunari|Sako, Yasushi', 'Cellular Informatics Laboratory, RIKEN, 2-1 Hirosawa, Wako 351-0198, Saitama, Japan.|Cellular Informatics Laboratory, RIKEN, 2-1 Hirosawa, Wako 351-0198, Saitama, Japan.', 'Japan|Japan', 6, 'Animals|Bayes Theorem|Cell Differentiation|Computational Biology|Culture Media, Conditioned|Epidermal Growth Factor|Models, Biological|Nerve Growth Factor|PC12 Cells|Rats', 'Journal Article', '10.1371/journal.pcbi.1003320', '24244131', 'Recently, the heterogeneity that arises from stochastic fate decisions has been reported for several types of cancer-derived cell lines and several types of clonal cells grown under constant environmental conditions. However, the relation between this stochasticity and the responsiveness to extracellular stimuli remains largely unknown. Here we focused on the fate decisions of the PC12 cell line, which was derived from rat pheochromocytoma, and is a model system to study differentiation into sympathetic neurons. Whereas epidermal growth factor (EGF) stimulates the proliferation of populations of PC12 cells, nerve growth factor (NGF) promotes the differentiation of neurites to neuron-like cells. We found that phenotypic heterogeneity increased with time at several surrounding serum concentrations, suggesting stochastic cell-fate decisions in single cells. We made a simple mathematical model assuming Markovian transitions of the cell fates, and estimated the transition rates based on Bayes theorem. The model suggests that depending on the serum concentration, EGF (NGF) even directs differentiation (proliferation) at the single-cell level. The maximum effects of the growth factors were ensured when the transition rates were appropriately controlled by the serum concentration to produce a nonextremal, moderate amount of cell-fate heterogeneity. Our model was validated by the experimental finding that the means and variances of the local cell densities obey a power-law relationship. These results suggest that even when efficient responses to growth factors are observed at the population level, the growth factors stochastically direct the cell-fate decisions in different directions at the single-cell level. ');
INSERT INTO `papers` (`id`, `ano`, `journal`, `titulo`, `autores`, `afiliacao`, `pais`, `citacoes`, `palavra_chave`, `categorias`, `doi`, `pubmed`, `abstract`) VALUES
(86287, 2013, 'plos', 'Phosphorelays provide tunable signal processing capabilities for the cell', 'Kothamachu, Varun B|Feliu, Elisenda|Wiuf, Carsten|Cardelli, Luca|Soyer, Orkun S', 'Systems Biology Program, College of Engineering, Computing and Mathematics, University of Exeter, Exeter, United Kingdom.|Systems Biology Program, College of Engineering, Computing and Mathematics, University of Exeter, Exeter, United Kingdom.|Systems Biology Program, College of Engineering, Computing and Mathematics, University of Exeter, Exeter, United Kingdom.|Systems Biology Program, College of Engineering, Computing and Mathematics, University of Exeter, Exeter, United Kingdom.|Systems Biology Program, College of Engineering, Computing and Mathematics, University of Exeter, Exeter, United Kingdom.', 'United Kingdom|United Kingdom|United Kingdom|United Kingdom|United Kingdom', 12, 'Computational Biology|Hydrolysis|Models, Biological|Phosphorylation|Signal Transduction', 'Journal Article', '10.1371/journal.pcbi.1003322', '24244132', 'Achieving a complete understanding of cellular signal transduction requires deciphering the relation between structural and biochemical features of a signaling system and the shape of the signal-response relationship it embeds. Using explicit analytical expressions and numerical simulations, we present here this relation for four-layered phosphorelays, which are signaling systems that are ubiquitous in prokaryotes and also found in lower eukaryotes and plants. We derive an analytical expression that relates the shape of the signal-response relationship in a relay to the kinetic rates of forward, reverse phosphorylation and hydrolysis reactions. This reveals a set of mathematical conditions which, when satisfied, dictate the shape of the signal-response relationship. We find that a specific topology also observed in nature can satisfy these conditions in such a way to allow plasticity among hyperbolic and sigmoidal signal-response relationships. Particularly, the shape of the signal-response relationship of this relay topology can be tuned by altering kinetic rates and total protein levels at different parts of the relay. These findings provide an important step towards predicting response dynamics of phosphorelays, and the nature of subsequent physiological responses that they mediate, solely from topological features and few composite measurements, measuring the ratio of reverse and forward phosphorylation rate constants could be sufficient to determine the shape of the signal-response relationship the relay exhibits. Furthermore, they highlight the potential ways in which selective pressures on signal processing could have played a role in the evolution of the observed structural and biochemical characteristic in phosphorelays. '),
(86288, 2013, 'plos', 'Linking transcriptional changes over time in stimulated dendritic cells to identify gene networks activated during the innate immune response', 'Patil, Ashwini|Kumagai, Yutaro|Liang, Kuo-Ching|Suzuki, Yutaka|Nakai, Kenta', 'The Institute of Medical Science, The University of Tokyo, Tokyo, Japan.|The Institute of Medical Science, The University of Tokyo, Tokyo, Japan.|The Institute of Medical Science, The University of Tokyo, Tokyo, Japan.|The Institute of Medical Science, The University of Tokyo, Tokyo, Japan.|The Institute of Medical Science, The University of Tokyo, Tokyo, Japan.', 'Japan|Japan|Japan|Japan|Japan', 15, 'Adaptor Proteins, Vesicular Transport|Animals|Cells, Cultured|Computational Biology|Dendritic Cells|Gene Expression|Gene Knockout Techniques|Gene Regulatory Networks|Immunity, Innate|Lipopolysaccharides|Mice|Mice, Inbred C57BL|Myeloid Differentiation Factor 88|Protein Interaction Maps', 'Journal Article', '10.1371/journal.pcbi.1003323', '24244133', 'The innate immune response is primarily mediated by the Toll-like receptors functioning through the MyD88-dependent and TRIF-dependent pathways. Despite being widely studied, it is not yet completely understood and systems-level analyses have been lacking. In this study, we identified a high-probability network of genes activated during the innate immune response using a novel approach to analyze time-course gene expression profiles of activated immune cells in combination with a large gene regulatory and protein-protein interaction network. We classified the immune response into three consecutive time-dependent stages and identified the most probable paths between genes showing a significant change in expression at each stage. The resultant network contained several novel and known regulators of the innate immune response, many of which did not show any observable change in expression at the sampled time points. The response network shows the dominance of genes from specific functional classes during different stages of the immune response. It also suggests a role for the protein phosphatase 2a catalytic subunit xcexb1 in the regulation of the immunoproteasome during the late phase of the response. In order to clarify the differences between the MyD88-dependent and TRIF-dependent pathways in the innate immune response, time-course gene expression profiles from MyD88-knockout and TRIF-knockout dendritic cells were analyzed. Their response networks suggest the dominance of the MyD88-dependent pathway in the innate immune response, and an association of the circadian regulators and immunoproteasomal degradation with the TRIF-dependent pathway. The response network presented here provides the most probable associations between genes expressed in the early and the late phases of the innate immune response, while taking into account the intermediate regulators. We propose that the method described here can also be used in the identification of time-dependent gene sub-networks in other biological systems. '),
(86289, 2013, 'plos', 'Quantifying chaperone-mediated transitions in the proteostasis network of E coli', 'Dickson, Alex|Brooks, Charles L', 'Department of Chemistry, The University of Michigan, Ann Arbor, Michigan, United States of America.|Department of Chemistry, The University of Michigan, Ann Arbor, Michigan, United States of America.', 'United States|United States', 4, 'Computational Biology|Escherichia coli|Escherichia coli Proteins|Gene Knockout Techniques|Models, Biological|Molecular Chaperones|Protein Folding|Protein Interaction Maps', 'Journal Article', '10.1371/journal.pcbi.1003324', '24244134', 'For cells to function, the concentrations of all proteins in the cell must be maintained at the proper levels (proteostasis). This task--complicated by cellular stresses, protein misfolding, aggregation, and degradation--is performed by a collection of chaperones that alter the configurational landscape of a given client protein through the formation of protein-chaperone complexes. The set of all such complexes and the transitions between them form the proteostasis network. Recently, a computational model was introduced (FoldEco) that synthesizes experimental data into a system-wide description of the proteostasis network of E. coli. This model describes the concentrations over time of all the species in the system, which include different conformations of the client protein, as well as protein-chaperone complexes. We apply to this model a recently developed analysis tool to calculate mediation probabilities in complex networks. This allows us to determine the probability that a given chaperone system is used to mediate transitions between client protein conformations, such as folding, or the correction of misfolded conformations. We determine how these probabilities change both across different proteins, as well as with system parameters, such as the synthesis rate, and in each case reveal in detail which factors control the usage of one chaperone system over another. We find that the different chaperone systems do not operate orthogonally and can compensate for each other when one system is disabled or overworked, and that this can complicate the analysis of knockout experiments, where the concentration of native protein is compared both with and without the presence of a given chaperone system. This study also gives a general recipe for conducting a transition-path-based analysis on a network of coupled chemical reactions, which can be useful in other types of networks as well.'),
(86290, 2013, 'plos', 'Exploring fold space preferences of new-born and ancient protein superfamilies', 'Edwards, Hannah|Abeln, Sanne|Deane, Charlotte M', 'Department of Statistics, University of Oxford, Oxford, United Kingdom.|Department of Statistics, University of Oxford, Oxford, United Kingdom.|Department of Statistics, University of Oxford, Oxford, United Kingdom.', 'United Kingdom|United Kingdom|United Kingdom', 13, 'Algorithms|Amino Acid Sequence|Computational Biology|Databases, Protein|Disulfides|Evolution, Molecular|Hydrophobic and Hydrophilic Interactions|Phylogeny|Protein Conformation|Protein Folding|Proteins', 'Journal Article', '10.1371/journal.pcbi.1003325', '24244135', 'The evolution of proteins is one of the fundamental processes that has delivered the diversity and complexity of life we see around ourselves today. While we tend to define protein evolution in terms of sequence level mutations, insertions and deletions, it is hard to translate these processes to a more complete picture incorporating a polypeptides structure and function. By considering how protein structures change over time we can gain an entirely new appreciation of their long-term evolutionary dynamics. In this work we seek to identify how populations of proteins at different stages of evolution explore their possible structure space. We use an annotation of superfamily age to this space and explore the relationship between these ages and a diverse set of properties pertaining to a superfamilys sequence, structure and function. We note several marked differences between the populations of newly evolved and ancient structures, such as in their length distributions, secondary structure content and tertiary packing arrangements. In particular, many of these differences suggest a less elaborate structure for newly evolved superfamilies when compared with their ancient counterparts. We show that the structural preferences we report are not a residual effect of a more fundamental relationship with function. Furthermore, we demonstrate the robustness of our results, using significant variation in the algorithm used to estimate the ages. We present these age estimates as a useful tool to analyse protein populations. In particularly, we apply this in a comparison of domains containing greek key or jelly roll motifs. '),
(86291, 2013, 'plos', 'Practical guidelines for the comprehensive analysis of ChIP-seq data', 'Bailey, Timothy|Krajewski, Pawel|Ladunga, Istvan|Lefebvre, Celine|Li, Qunhua|Liu, Tao|Madrigal, Pedro|Taslim, Cenny|Zhang, Jie', 'Institute for Molecular Bioscience, The University of Queensland, Brisbane, Australia.|Institute for Molecular Bioscience, The University of Queensland, Brisbane, Australia.|Institute for Molecular Bioscience, The University of Queensland, Brisbane, Australia.|Institute for Molecular Bioscience, The University of Queensland, Brisbane, Australia.|Institute for Molecular Bioscience, The University of Queensland, Brisbane, Australia.|Institute for Molecular Bioscience, The University of Queensland, Brisbane, Australia.|Institute for Molecular Bioscience, The University of Queensland, Brisbane, Australia.|Institute for Molecular Bioscience, The University of Queensland, Brisbane, Australia.|Institute for Molecular Bioscience, The University of Queensland, Brisbane, Australia.', 'Australia|Australia|Australia|Australia|Australia|Australia|Australia|Australia|Australia', 123, 'Chromatin Immunoprecipitation|Computational Biology|High-Throughput Nucleotide Sequencing|Humans|Reproducibility of Results|Sequence Analysis, DNA', 'Journal Article', '10.1371/journal.pcbi.1003326', '24244136', 'Mapping the chromosomal locations of transcription factors, nucleosomes, histone modifications, chromatin remodeling enzymes, chaperones, and polymerases is one of the key tasks of modern biology, as evidenced by the Encyclopedia of DNA Elements (ENCODE) Project. To this end, chromatin immunoprecipitation followed by high-throughput sequencing (ChIP-seq) is the standard methodology. Mapping such protein-DNA interactions in vivo using ChIP-seq presents multiple challenges not only in sample preparation and sequencing but also for computational analysis. Here, we present step-by-step guidelines for the computational analysis of ChIP-seq data. We address all the major steps in the analysis of ChIP-seq data: sequencing depth selection, quality checking, mapping, data normalization, assessment of reproducibility, peak calling, differential binding analysis, controlling the false discovery rate, peak annotation, visualization, and motif analysis. At each step in our guidelines we discuss some of the software tools most frequently used. We also highlight the challenges and problems associated with each step in ChIP-seq data analysis. We present a concise workflow for the analysis of ChIP-seq data in Figure 1 that complements and expands on the recommendations of the ENCODE and modENCODE projects. Each step in the workflow is described in detail in the following sections. '),
(86292, 2013, 'plos', 'Mapping the structural and dynamical features of kinesin motor domains', 'Scarabelli, Guido|Grant, Barry J', 'Department of Computational Medicine and Bioinformatics, University of Michigan, Ann Arbor, Michigan, United States of America.|Department of Computational Medicine and Bioinformatics, University of Michigan, Ann Arbor, Michigan, United States of America.', 'United States|United States', 23, 'Adenosine Diphosphate|Adenosine Triphosphate|Binding Sites|Computational Biology|Humans|Hydrolysis|Kinesin|Microtubules|Molecular Dynamics Simulation|Mutation|Principal Component Analysis', 'Journal Article', '10.1371/journal.pcbi.1003329', '24244137', 'Kinesin motor proteins drive intracellular transport by coupling ATP hydrolysis to conformational changes that mediate directed movement along microtubules. Characterizing these distinct conformations and their interconversion mechanism is essential to determining an atomic-level model of kinesin action. Here we report a comprehensive principal component analysis of 114 experimental structures along with the results of conventional and accelerated molecular dynamics simulations that together map the structural dynamics of the kinesin motor domain. All experimental structures were found to reside in one of three distinct conformational clusters (ATP-like, ADP-like and Eg5 inhibitor-bound). These groups differ in the orientation of key functional elements, most notably the microtubule binding xcexb14-xcexb15, loop8 subdomain and xcexb12b-xcexb24-xcexb26-xcexb27 motor domain tip. Group membership was found not to correlate with the nature of the bound nucleotide in a given structure. However, groupings were coincident with distinct neck-linker orientations. Accelerated molecular dynamics simulations of ATP, ADP and nucleotide free Eg5 indicate that all three nucleotide states could sample the major crystallographically observed conformations. Differences in the dynamic coupling of distal sites were also evident. In multiple ATP bound simulations, the neck-linker, loop8 and the xcexb14-xcexb15 subdomain display correlated motions that are absent in ADP bound simulations. Further dissection of these couplings provides evidence for a network of dynamic communication between the active site, microtubule-binding interface and neck-linker via loop7 and loop13. Additional simulations indicate that the mutations G325A and G326A in loop13 reduce the flexibility of these regions and disrupt their couplings. Our combined results indicate that the reported ATP and ADP-like conformations of kinesin are intrinsically accessible regardless of nucleotide state and support a model where neck-linker docking leads to a tighter coupling of the microtubule and nucleotide binding regions. Furthermore, simulations highlight sites critical for large-scale conformational changes and the allosteric coupling between distal functional sites. '),
(86293, 2013, 'plos', 'Synaptic plasticity in neural networks needs homeostasis with a fast rate detector', 'Zenke, Friedemann|Hennequin, Guillaume|Gerstner, Wulfram', 'School of Computer and Communication Sciences and School of Life Sciences, Brain Mind Institute, Ecole polytechnique fédérale de Lausanne, Lausanne, Switzerland.|School of Computer and Communication Sciences and School of Life Sciences, Brain Mind Institute, Ecole polytechnique fédérale de Lausanne, Lausanne, Switzerland.|School of Computer and Communication Sciences and School of Life Sciences, Brain Mind Institute, Ecole polytechnique fédérale de Lausanne, Lausanne, Switzerland.', 'Switzerland|Switzerland|Switzerland', 70, 'Action Potentials|Computational Biology|Computer Simulation|Homeostasis|Models, Neurological|Neuronal Plasticity|Neurons|Synapses', 'Journal Article', '10.1371/journal.pcbi.1003330', '24244138', 'Hebbian changes of excitatory synapses are driven by and further enhance correlations between pre- and postsynaptic activities. Hence, Hebbian plasticity forms a positive feedback loop that can lead to instability in simulated neural networks. To keep activity at healthy, low levels, plasticity must therefore incorporate homeostatic control mechanisms. We find in numerical simulations of recurrent networks with a realistic triplet-based spike-timing-dependent plasticity rule (triplet STDP) that homeostasis has to detect rate changes on a timescale of seconds to minutes to keep the activity stable. We confirm this result in a generic mean-field formulation of network activity and homeostatic plasticity. Our results strongly suggest the existence of a homeostatic regulatory mechanism that reacts to firing rate changes on the order of seconds to minutes. '),
(86294, 2013, 'plos', 'Mechanical and assembly units of viral capsids identified via quasi-rigid domain decomposition', 'Polles, Guido|Indelicato, Giuliana|Potestio, Raffaello|Cermelli, Paolo|Twarock, Reidun|Micheletti, Cristian', 'International School for Advanced Studies (SISSA), Trieste, Italy.|International School for Advanced Studies (SISSA), Trieste, Italy.|International School for Advanced Studies (SISSA), Trieste, Italy.|International School for Advanced Studies (SISSA), Trieste, Italy.|International School for Advanced Studies (SISSA), Trieste, Italy.|International School for Advanced Studies (SISSA), Trieste, Italy.', 'Italy|Italy|Italy|Italy|Italy|Italy', 22, 'Capsid|Capsid Proteins|Computer Simulation|Models, Molecular|Reproducibility of Results|Viruses', 'Journal Article', '10.1371/journal.pcbi.1003331', '24244139', 'Key steps in a viral life-cycle, such as self-assembly of a protective protein container or in some cases also subsequent maturation events, are governed by the interplay of physico-chemical mechanisms involving various spatial and temporal scales. These salient aspects of a viral life cycle are hence well described and rationalised from a mesoscopic perspective. Accordingly, various experimental and computational efforts have been directed towards identifying the fundamental building blocks that are instrumental for the mechanical response, or constitute the assembly units, of a few specific viral shells. Motivated by these earlier studies we introduce and apply a general and efficient computational scheme for identifying the stable domains of a given viral capsid. The method is based on elastic network models and quasi-rigid domain decomposition. It is first applied to a heterogeneous set of well-characterized viruses (CCMV, MS2, STNV, STMV) for which the known mechanical or assembly domains are correctly identified. The validated method is next applied to other viral particles such as L-A, Pariacoto and polyoma viruses, whose fundamental functional domains are still unknown or debated and for which we formulate verifiable predictions. The numerical code implementing the domain decomposition strategy is made freely available. '),
(86295, 2013, 'plos', 'About dice, bouldering, and team empowerment: running the CompOmics group at VIB and Ghent University, Belgium', 'Martens, Lennart', 'Department of Medical Protein Research, VIB, Ghent, Belgium , Department of Biochemistry, Ghent University, Ghent, Belgium.', 'Belgium', 0, 'Belgium|Communication|Computational Biology|Humans|Laboratories|Universities', 'Journal Article', '10.1371/journal.pcbi.1003332', '24244140', '-'),
(86296, 2013, 'plos', 'Leading a statistical bioinformatics lab: its all about finding balance Interview with Olga Vitek', 'Vitek, Olga', 'Department of Statistics, Department of Computer Science, Purdue University, West Lafayette, Indiana, United States of America.', 'India', 0, 'Computational Biology|Cooperative Behavior|Humans|Indiana|Laboratories|Leadership|Universities', 'Interview', '10.1371/journal.pcbi.1003333', '24244141', '-'),
(86297, 2013, 'plos', 'Auditory frequency and intensity discrimination explained using a cortical population rate code', 'Micheyl, Christophe|Schrater, Paul R|Oxenham, Andrew J', 'Department of Psychology, University of Minnesota, Minneapolis, Minnesota, United States of America.|Department of Psychology, University of Minnesota, Minneapolis, Minnesota, United States of America.|Department of Psychology, University of Minnesota, Minneapolis, Minnesota, United States of America.', 'United States|United States|United States', 22, 'Action Potentials|Animals|Auditory Cortex|Computational Biology|Humans|Models, Neurological|Neurons|Primates', 'Journal Article', '10.1371/journal.pcbi.1003336', '24244142', 'The nature of the neural codes for pitch and loudness, two basic auditory attributes, has been a key question in neuroscience for over century. A currently widespread view is that sound intensity (subjectively, loudness) is encoded in spike rates, whereas sound frequency (subjectively, pitch) is encoded in precise spike timing. Here, using information-theoretic analyses, we show that the spike rates of a population of virtual neural units with frequency-tuning and spike-count correlation characteristics similar to those measured in the primary auditory cortex of primates, contain sufficient statistical information to account for the smallest frequency-discrimination thresholds measured in human listeners. The same population, and the same spike-rate code, can also account for the intensity-discrimination thresholds of humans. These results demonstrate the viability of a unified rate-based cortical population code for both sound frequency (pitch) and sound intensity (loudness), and thus suggest a resolution to a long-standing puzzle in auditory neuroscience. '),
(86298, 2013, 'plos', 'Conformational coupling between receptor and kinase binding sites through a conserved salt bridge in a signaling complex scaffold protein', 'Ortega, Davi R|Mo, Guoya|Lee, Kwangwoon|Zhou, Hongjun|Baudry, Jerome|Dahlquist, Frederick W|Zhulin, Igor B', 'Joint Institute for Computational Sciences, University of Tennessee - Oak Ridge National Laboratory, Oak Ridge, Tennessee, United States of America , Department of Physics, University of Tennessee, Knoxville, Tennessee, United States of America.|Joint Institute for Computational Sciences, University of Tennessee - Oak Ridge National Laboratory, Oak Ridge, Tennessee, United States of America , Department of Physics, University of Tennessee, Knoxville, Tennessee, United States of America.|Joint Institute for Computational Sciences, University of Tennessee - Oak Ridge National Laboratory, Oak Ridge, Tennessee, United States of America , Department of Physics, University of Tennessee, Knoxville, Tennessee, United States of America.|Joint Institute for Computational Sciences, University of Tennessee - Oak Ridge National Laboratory, Oak Ridge, Tennessee, United States of America , Department of Physics, University of Tennessee, Knoxville, Tennessee, United States of America.|Joint Institute for Computational Sciences, University of Tennessee - Oak Ridge National Laboratory, Oak Ridge, Tennessee, United States of America , Department of Physics, University of Tennessee, Knoxville, Tennessee, United States of America.|Joint Institute for Computational Sciences, University of Tennessee - Oak Ridge National Laboratory, Oak Ridge, Tennessee, United States of America , Department of Physics, University of Tennessee, Knoxville, Tennessee, United States of America.|Joint Institute for Computational Sciences, University of Tennessee - Oak Ridge National Laboratory, Oak Ridge, Tennessee, United States of America , Department of Physics, University of Tennessee, Knoxville, Tennessee, United States of America.', 'United States|United States|United States|United States|United States|United States|United States', 9, 'Binding Sites|Chemotaxis|Escherichia coli Proteins|Molecular Dynamics Simulation|Mutation|Protein Conformation|Protein Unfolding|Reproducibility of Results', 'Journal Article', '10.1371/journal.pcbi.1003337', '24244143', 'Bacterial chemotaxis is one of the best studied signal transduction pathways. CheW is a scaffold protein that mediates the association of the chemoreceptors and the CheA kinase in a ternary signaling complex. The effects of replacing conserved Arg62 of CheW with other residues suggested that the scaffold protein plays a more complex role than simply binding its partner proteins. Although R62A CheW had essentially the same affinity for chemoreceptors and CheA, cells expressing the mutant protein are impaired in chemotaxis. Using a combination of molecular dynamics simulations (MD), NMR spectroscopy, and circular dichroism (CD), we addressed the role of Arg62. Here we show that Arg62 forms a salt bridge with another highly conserved residue, Glu38. Although this interaction is unimportant for overall protein stability, it is essential to maintain the correct alignment of the chemoreceptor and kinase binding sites of CheW. Computational and experimental data suggest that the role of the salt bridge in maintaining the alignment of the two partner binding sites is fundamental to the function of the signaling complex but not to its assembly. We conclude that a key feature of CheW is to maintain the specific geometry between the two interaction sites required for its function as a scaffold. '),
(86299, 2013, 'plos', 'Structure-based function prediction of uncharacterized protein using binding sites comparison', 'Konc, Janez|Hodoxc5xa1xc4x8dek, Milan|Ogrizek, Mitja|Trykowska Konc, Joanna|Janexc5xbeixc4x8d, Duxc5xa1anka', 'National Institute of Chemistry, Ljubljana, Slovenia.|National Institute of Chemistry, Ljubljana, Slovenia.|National Institute of Chemistry, Ljubljana, Slovenia.|National Institute of Chemistry, Ljubljana, Slovenia.|National Institute of Chemistry, Ljubljana, Slovenia.', 'Slovenia|Slovenia|Slovenia|Slovenia|Slovenia', 23, 'Bacterial Proteins|Binding Sites|Computational Biology|DNA|Models, Statistical|Molecular Dynamics Simulation|Protein Conformation|Thermotoga maritima', 'Journal Article', '10.1371/journal.pcbi.1003341', '24244144', 'A challenge in structural genomics is prediction of the function of uncharacterized proteins. When proteins cannot be related to other proteins of known activity, identification of function based on sequence or structural homology is impossible and in such cases it would be useful to assess structurally conserved binding sites in connection with the proteins function. In this paper, we propose the function of a protein of unknown activity, the Tm1631 protein from Thermotoga maritima, by comparing its predicted binding site to a library containing thousands of candidate structures. The comparison revealed numerous similarities with nucleotide binding sites including specifically, a DNA-binding site of endonuclease IV. We constructed a model of this Tm1631 protein with a DNA-ligand from the newly found similar binding site using ProBiS, and validated this model by molecular dynamics. The interactions predicted by the Tm1631-DNA model corresponded to those known to be important in endonuclease IV-DNA complex model and the corresponding binding free energies, calculated from these models were in close agreement. We thus propose that Tm1631 is a DNA binding enzyme with endonuclease activity that recognizes DNA lesions in which at least two consecutive nucleotides are unpaired. Our approach is general, and can be applied to any protein of unknown function. It might also be useful to guide experimental determination of function of uncharacterized proteins. '),
(86300, 2013, 'plos', 'Ten quick tips for using the gene ontology', 'Blake, Judith A', 'Computational Biology and Bioinformatics, The Jackson Laboratory, Bar Harbor, Maine, United States of America.', 'United States', 24, 'Computational Biology|Gene Ontology|Humans', 'Journal Article', '10.1371/journal.pcbi.1003343', '24244145', '-'),
(86301, 2013, 'plos', 'Average is optimal: an inverted-U relationship between trial-to-trial brain activity and behavioral performance', 'He, Biyu J|Zempel, John M', 'National Institute of Neurological Disorders and Stroke, National Institutes of Health, Bethesda, Maryland, United States of America.|National Institute of Neurological Disorders and Stroke, National Institutes of Health, Bethesda, Maryland, United States of America.', 'United States|United States', 29, 'Adult|Behavior|Brain|Brain Mapping|Electroencephalography|Female|Humans|Male|Middle Aged|Photic Stimulation|Principal Component Analysis|Reaction Time|Task Performance and Analysis|Young Adult', 'Journal Article', '10.1371/journal.pcbi.1003348', '24244146', 'It is well known that even under identical task conditions, there is a tremendous amount of trial-to-trial variability in both brain activity and behavioral output. Thus far the vast majority of event-related potential (ERP) studies investigating the relationship between trial-to-trial fluctuations in brain activity and behavioral performance have only tested a monotonic relationship between them. However, it was recently found that across-trial variability can correlate with behavioral performance independent of trial-averaged activity. This finding predicts a U- or inverted-U- shaped relationship between trial-to-trial brain activity and behavioral output, depending on whether larger brain variability is associated with better or worse behavior, respectively. Using a visual stimulus detection task, we provide evidence from human electrocorticography (ECoG) for an inverted-U brain-behavior relationship: When the raw fluctuation in broadband ECoG activity is closer to the across-trial mean, hit rate is higher and reaction times faster. Importantly, we show that this relationship is present not only in the post-stimulus task-evoked brain activity, but also in the pre-stimulus spontaneous brain activity, suggesting anticipatory brain dynamics. Our findings are consistent with the presence of stochastic noise in the brain. They further support attractor network theories, which postulate that the brain settles into a more confined state space under task performance, and proximity to the targeted trajectory is associated with better performance. '),
(86302, 2013, 'plos', 'Learning how to run a lab: interviews with principal investigators', 'Alexandrov, Theodore|Bourne, Philip E', 'Departments of Biochemistry and Mathematics, University of Bremen, Bremen, Germany , SCiLS GmbH, Bremen, Germany , Steinbeis Innovation Center SCiLS Research, Bremen, Germany , Skaggs School of Pharmacy and Pharmaceutical Science, University of California San Diego, La Jolla, California, United States of America.|Departments of Biochemistry and Mathematics, University of Bremen, Bremen, Germany , SCiLS GmbH, Bremen, Germany , Steinbeis Innovation Center SCiLS Research, Bremen, Germany , Skaggs School of Pharmacy and Pharmaceutical Science, University of California San Diego, La Jolla, California, United States of America.', 'Germany|Germany', 0, 'Humans|Laboratories|Research Personnel', 'Editorial', '10.1371/journal.pcbi.1003349', '24244147', '-'),
(86303, 2013, 'plos', 'The young PI buzz: learning from the organizers of the Junior Principal Investigator Meeting at ISMB-ECCB 2013', 'de Ridder, Jeroen|Bromberg, Yana|Michaut, Magali|Satagopam, Venkata P|Corpas, Manuel|MacIntyre, Geoff|Alexandrov, Theodore', 'Delft Bioinformatics Lab, Faculty of Electrical Engineering, Mathematics and Computer Science, Delft University of Technology, Delft, The Netherlands.|Delft Bioinformatics Lab, Faculty of Electrical Engineering, Mathematics and Computer Science, Delft University of Technology, Delft, The Netherlands.|Delft Bioinformatics Lab, Faculty of Electrical Engineering, Mathematics and Computer Science, Delft University of Technology, Delft, The Netherlands.|Delft Bioinformatics Lab, Faculty of Electrical Engineering, Mathematics and Computer Science, Delft University of Technology, Delft, The Netherlands.|Delft Bioinformatics Lab, Faculty of Electrical Engineering, Mathematics and Computer Science, Delft University of Technology, Delft, The Netherlands.|Delft Bioinformatics Lab, Faculty of Electrical Engineering, Mathematics and Computer Science, Delft University of Technology, Delft, The Netherlands.|Delft Bioinformatics Lab, Faculty of Electrical Engineering, Mathematics and Computer Science, Delft University of Technology, Delft, The Netherlands.', 'Netherlands|Netherlands|Netherlands|Netherlands|Netherlands|Netherlands|Netherlands', 0, 'Computational Biology|Cooperative Behavior|Humans|Mentors|Research Personnel|Social Networking', 'Journal Article', '10.1371/journal.pcbi.1003350', '24244148', '-'),
(86304, 2013, 'plos', 'Substrate-driven mapping of the degradome by comparison of sequence logos', 'Fuchs, Julian E|von Grafenstein, Susanne|Huber, Roland G|Kramer, Christian|Liedl, Klaus R', 'Institute of General, Inorganic and Theoretical Chemistry, and Center for Molecular Biosciences Innsbruck (CMBI), University of Innsbruck, Innsbruck, Austria.|Institute of General, Inorganic and Theoretical Chemistry, and Center for Molecular Biosciences Innsbruck (CMBI), University of Innsbruck, Innsbruck, Austria.|Institute of General, Inorganic and Theoretical Chemistry, and Center for Molecular Biosciences Innsbruck (CMBI), University of Innsbruck, Innsbruck, Austria.|Institute of General, Inorganic and Theoretical Chemistry, and Center for Molecular Biosciences Innsbruck (CMBI), University of Innsbruck, Innsbruck, Austria.|Institute of General, Inorganic and Theoretical Chemistry, and Center for Molecular Biosciences Innsbruck (CMBI), University of Innsbruck, Innsbruck, Austria.', 'Austria|Austria|Austria|Austria|Austria', 21, 'Amino Acids|Binding Sites|Cluster Analysis|Drug Discovery|Peptide Hydrolases|Peptides|Principal Component Analysis|Proteins|Proteomics', 'Journal Article', '10.1371/journal.pcbi.1003353', '24244149', 'Sequence logos are frequently used to illustrate substrate preferences and specificity of proteases. Here, we employed the compiled substrates of the MEROPS database to introduce a novel metric for comparison of protease substrate preferences. The constructed similarity matrix of 62 proteases can be used to intuitively visualize similarities in protease substrate readout via principal component analysis and construction of protease specificity trees. Since our new metric is solely based on substrate data, we can engraft the protease tree including proteolytic enzymes of different evolutionary origin. Thereby, our analyses confirm pronounced overlaps in substrate recognition not only between proteases closely related on sequence basis but also between proteolytic enzymes of different evolutionary origin and catalytic type. To illustrate the applicability of our approach we analyze the distribution of targets of small molecules from the ChEMBL database in our substrate-based protease specificity trees. We observe a striking clustering of annotated targets in tree branches even though these grouped targets do not necessarily share similarity on protein sequence level. This highlights the value and applicability of knowledge acquired from peptide substrates in drug design of small molecules, e.g., for the prediction of off-target effects or drug repurposing. Consequently, our similarity metric allows to map the degradome and its associated drug target network via comparison of known substrate peptides. The substrate-driven view of protein-protein interfaces is not limited to the field of proteases but can be applied to any target class where a sufficient amount of known substrate data is available. '),
(86305, 2013, 'plos', 'Integrative modelling of the influence of MAPK network on cancer cell fate decision', 'Grieco, Luca|Calzone, Laurence|Bernard-Pierrot, Isabelle|Radvanyi, François|Kahn-Perlès, Brigitte|Thieffry, Denis', 'Aix-Marseille Université, Marseille, France , TAGC - Inserm U1090, Marseille, France , Institut de Biologie de lEcole Normale Supérieure (IBENS), Paris, France , UMR 8197 Centre National de la Recherche Scientifique (CNRS), Paris, France , Inserm 1024, Paris, France , Institut Curie, Paris, France.|Aix-Marseille Université, Marseille, France , TAGC - Inserm U1090, Marseille, France , Institut de Biologie de lEcole Normale Supérieure (IBENS), Paris, France , UMR 8197 Centre National de la Recherche Scientifique (CNRS), Paris, France , Inserm 1024, Paris, France , Institut Curie, Paris, France.|Aix-Marseille Université, Marseille, France , TAGC - Inserm U1090, Marseille, France , Institut de Biologie de lEcole Normale Supérieure (IBENS), Paris, France , UMR 8197 Centre National de la Recherche Scientifique (CNRS), Paris, France , Inserm 1024, Paris, France , Institut Curie, Paris, France.|Aix-Marseille Université, Marseille, France , TAGC - Inserm U1090, Marseille, France , Institut de Biologie de lEcole Normale Supérieure (IBENS), Paris, France , UMR 8197 Centre National de la Recherche Scientifique (CNRS), Paris, France , Inserm 1024, Paris, France , Institut Curie, Paris, France.|Aix-Marseille Université, Marseille, France , TAGC - Inserm U1090, Marseille, France , Institut de Biologie de lEcole Normale Supérieure (IBENS), Paris, France , UMR 8197 Centre National de la Recherche Scientifique (CNRS), Paris, France , Inserm 1024, Paris, France , Institut Curie, Paris, France.|Aix-Marseille Université, Marseille, France , TAGC - Inserm U1090, Marseille, France , Institut de Biologie de lEcole Normale Supérieure (IBENS), Paris, France , UMR 8197 Centre National de la Recherche Scientifique (CNRS), Paris, France , Inserm 1024, Paris, France , Institut Curie, Paris, France.', 'France|France|France|France|France|France', 0, 'Algorithms|Computational Biology|Computer Simulation|ErbB Receptors|Humans|Intracellular Space|MAP Kinase Signaling System|Models, Biological|Protein Interaction Maps|Receptor, Fibroblast Growth Factor, Type 3|Software|Urinary Bladder Neoplasms', 'Journal Article', '10.1371/journal.pcbi.1003286', '24250280', 'The Mitogen-Activated Protein Kinase (MAPK) network consists of tightly interconnected signalling pathways involved in diverse cellular processes, such as cell cycle, survival, apoptosis and differentiation. Although several studies reported the involvement of these signalling cascades in cancer deregulations, the precise mechanisms underlying their influence on the balance between cell proliferation and cell death (cell fate decision) in pathological circumstances remain elusive. Based on an extensive analysis of published data, we have built a comprehensive and generic reaction map for the MAPK signalling network, using CellDesigner software. In order to explore the MAPK responses to different stimuli and better understand their contributions to cell fate decision, we have considered the most crucial components and interactions and encoded them into a logical model, using the software GINsim. Our logical model analysis particularly focuses on urinary bladder cancer, where MAPK network deregulations have often been associated with specific phenotypes. To cope with the combinatorial explosion of the number of states, we have applied novel algorithms for model reduction and for the compression of state transition graphs, both implemented into the software GINsim. The results of systematic simulations for different signal combinations and network perturbations were found globally coherent with published data. In silico experiments further enabled us to delineate the roles of specific components, cross-talks and regulatory feedbacks in cell fate decision. Finally, tentative proliferative or anti-proliferative mechanisms can be connected with established bladder cancer deregulations, namely Epidermal Growth Factor Receptor (EGFR) over-expression and Fibroblast Growth Factor Receptor 3 (FGFR3) activating mutations. '),
(86306, 2013, 'plos', 'Identification of key hinge residues important for nucleotide-dependent allostery in E coli Hsp70/DnaK', 'Ung, Peter Man-Un|Thompson, Andrea D|Chang, Lyra|Gestwicki, Jason E|Carlson, Heather A', 'Department of Medicinal Chemistry, College of Pharmacy, University of Michigan, Ann Arbor, Michigan, United States of America.|Department of Medicinal Chemistry, College of Pharmacy, University of Michigan, Ann Arbor, Michigan, United States of America.|Department of Medicinal Chemistry, College of Pharmacy, University of Michigan, Ann Arbor, Michigan, United States of America.|Department of Medicinal Chemistry, College of Pharmacy, University of Michigan, Ann Arbor, Michigan, United States of America.|Department of Medicinal Chemistry, College of Pharmacy, University of Michigan, Ann Arbor, Michigan, United States of America.', 'United States|United States|United States|United States|United States', 15, 'Allosteric Regulation|Binding Sites|Escherichia coli Proteins|HSP70 Heat-Shock Proteins|Molecular Dynamics Simulation|Nucleotides|Point Mutation|Protein Structure, Tertiary', 'Journal Article', '10.1371/journal.pcbi.1003279', '24277995', 'DnaK is a molecular chaperone that has important roles in protein folding. The hydrolysis of ATP is essential to this activity, and the effects of nucleotides on the structure and function of DnaK have been extensively studied. However, the key residues that govern the conformational motions that define the apo, ATP-bound, and ADP-bound states are not entirely clear. Here, we used molecular dynamics simulations, mutagenesis, and enzymatic assays to explore the molecular basis of this process. Simulations of DnaKs nucleotide-binding domain (NBD) in the apo, ATP-bound, and ADP/Pi-bound states suggested that each state has a distinct conformation, consistent with available biochemical and structural information. The simulations further suggested that large shearing motions between subdomains I-A and II-A dominated the conversion between these conformations. We found that several evolutionally conserved residues, especially G228 and G229, appeared to function as a hinge for these motions, because they predominantly populated two distinct states depending on whether ATP or ADP/Pi was bound. Consistent with the importance of these hinge residues, alanine point mutations caused DnaK to have reduced chaperone activities in vitro and in vivo. Together, these results clarify how sub-domain motions communicate allostery in DnaK. '),
(86307, 2013, 'plos', 'Cell-based multi-parametric model of cleft progression during submandibular salivary gland branching morphogenesis', 'Ray, Shayoni|Yuan, Daniel|Dhulekar, Nimit|Oztan, Basak|Yener, Bülent|Larsen, Melinda', 'Department of Biological Sciences, University at Albany, State University of New York, Albany, New York, United States of America.|Department of Biological Sciences, University at Albany, State University of New York, Albany, New York, United States of America.|Department of Biological Sciences, University at Albany, State University of New York, Albany, New York, United States of America.|Department of Biological Sciences, University at Albany, State University of New York, Albany, New York, United States of America.|Department of Biological Sciences, University at Albany, State University of New York, Albany, New York, United States of America.|Department of Biological Sciences, University at Albany, State University of New York, Albany, New York, United States of America.', 'United States|United States|United States|United States|United States|United States', 11, 'Algorithms|Animals|Cell Adhesion|Embryo, Mammalian|Female|Mice|Models, Biological|Monte Carlo Method|Morphogenesis|Submandibular Gland', 'Journal Article', '10.1371/journal.pcbi.1003319', '24277996', 'Cleft formation during submandibular salivary gland branching morphogenesis is the critical step initiating the growth and development of the complex adult organ. Previous experimental studies indicated requirements for several epithelial cellular processes, such as proliferation, migration, cell-cell adhesion, cell-extracellular matrix (matrix) adhesion, and cellular contraction in cleft formation, however, the relative contribution of each of these processes is not fully understood since it is not possible to experimentally manipulate each factor independently. We present here a comprehensive analysis of several cellular parameters regulating cleft progression during branching morphogenesis in the epithelial tissue of an early embryonic salivary gland at a local scale using an on lattice Monte-Carlo simulation model, the Glazier-Graner-Hogeweg model. We utilized measurements from time-lapse images of mouse submandibular gland organ explants to construct a temporally and spatially relevant cell-based 2D model. Our model simulates the effect of cellular proliferation, actomyosin contractility, cell-cell and cell-matrix adhesions on cleft progression, and it was used to test specific hypotheses regarding the function of these parameters in branching morphogenesis. We use innovative features capturing several aspects of cleft morphology and quantitatively analyze clefts formed during functional modification of the cellular parameters. Our simulations predict that a low epithelial mitosis rate and moderate level of actomyosin contractility in the cleft cells promote cleft progression. Raising or lowering levels of contractility and mitosis rate resulted in non-progressive clefts. We also show that lowered cell-cell adhesion in the cleft region and increased cleft cell-matrix adhesions are required for cleft progression. Using a classifier-based analysis, the relative importance of these four contributing cellular factors for effective cleft progression was determined as follows: cleft cell contractility, cleft region cell-cell adhesion strength, epithelial cell mitosis rate, and cell-matrix adhesion strength. '),
(86308, 2013, 'plos', 'Exploring the composition of protein-ligand binding sites on a large scale', 'Khazanov, Nickolay A|Carlson, Heather A', 'Bioinformatics Graduate Program, University of Michigan, Ann Arbor, Michigan, United States of America.|Bioinformatics Graduate Program, University of Michigan, Ann Arbor, Michigan, United States of America.', 'United States|United States', 0, 'Amino Acid Sequence|Binding Sites|Computational Biology|Databases, Protein|Hydrogen Bonding|Ligands|Protein Binding|Proteins|Surface Properties', 'Journal Article', '10.1371/journal.pcbi.1003321', '24277997', 'The residue composition of a ligand binding site determines the interactions available for diffusion-mediated ligand binding, and understanding general composition of these sites is of great importance if we are to gain insight into the functional diversity of the proteome. Many structure-based drug design methods utilize such heuristic information for improving prediction or characterization of ligand-binding sites in proteins of unknown function. The Binding MOAD database if one of the largest curated sets of protein-ligand complexes, and provides a source of diverse, high-quality data for establishing general trends of residue composition from currently available protein structures. We present an analysis of 3,295 non-redundant proteins with 9,114 non-redundant binding sites to identify residues over-represented in binding regions versus the rest of the protein surface. The Binding MOAD database delineates biologically-relevant valid ligands from invalid small-molecule ligands bound to the protein. Invalids are present in the crystallization medium and serve no known biological function. Contacts are found to differ between these classes of ligands, indicating that residue composition of biologically relevant binding sites is distinct not only from the rest of the protein surface, but also from surface regions capable of opportunistic binding of non-functional small molecules. To confirm these trends, we perform a rigorous analysis of the variation of residue propensity with respect to the size of the dataset and the content bias inherent in structure sets obtained from a large protein structure database. The optimal size of the dataset for establishing general trends of residue propensities, as well as strategies for assessing the significance of such trends, are suggested for future studies of binding-site composition. ');
INSERT INTO `papers` (`id`, `ano`, `journal`, `titulo`, `autores`, `afiliacao`, `pais`, `citacoes`, `palavra_chave`, `categorias`, `doi`, `pubmed`, `abstract`) VALUES
(86309, 2013, 'plos', 'A data-driven mathematical model of CA-MRSA transmission among age groups: evaluating the effect of control interventions', 'Wang, Xiaoxia|Panchanathan, Sarada|Chowell, Gerardo', 'Mathematical, Computational and Modeling Sciences Center, School of Human Evolution and Social Change, Arizona State University, Tempe, Arizona, United States of America.|Mathematical, Computational and Modeling Sciences Center, School of Human Evolution and Social Change, Arizona State University, Tempe, Arizona, United States of America.|Mathematical, Computational and Modeling Sciences Center, School of Human Evolution and Social Change, Arizona State University, Tempe, Arizona, United States of America.', 'United States|United States|United States', 14, 'Adolescent|Adult|Child|Child, Preschool|Community-Acquired Infections|Humans|Infant|Methicillin-Resistant Staphylococcus aureus|Middle Aged|Models, Biological|Reproducibility of Results|Soft Tissue Infections|Staphylococcal Infections|Staphylococcal Skin Infections', 'Journal Article', '10.1371/journal.pcbi.1003328', '24277998', 'Community associated methicillin-resistant Staphylococcus aureus (CA-MRSA) has become a major cause of skin and soft tissue infections (SSTIs) in the US. We developed an age-structured compartmental model to study the spread of CA-MRSA at the population level and assess the effect of control intervention strategies. We used Monte-Carlo Markov Chain (MCMC) techniques to parameterize our model using monthly time series data on SSTIs incidence in children (xe2x89xa4 19 years) during January 2004 -December 2006 in Maricopa County, Arizona. Our model-based forecast for the period January 2007-December 2008 also provided a good fit to data. We also carried out an uncertainty and sensitivity analysis on the control reproduction number, Rc which we estimated at 1.3 (95% CI [1.2,1.4]) based on the model fit to data. Using our calibrated model, we evaluated the effect of typical intervention strategies namely reducing the contact rate of infected individuals owing to awareness of infection and decolonization strategies targeting symptomatic infected individuals on both [Formula: see text] and the long-term disease dynamics. We also evaluated the impact of hypothetical decolonization strategies targeting asymptomatic colonized individuals. We found that strategies focused on infected individuals were not capable of achieving disease control when implemented alone or in combination. In contrast, our results suggest that decolonization strategies targeting the pediatric population colonized with CA-MRSA have the potential of achieving disease elimination.'),
(86310, 2013, 'plos', 'Dread and the disvalue of future pain', 'Story, Giles W|Vlaev, Ivaylo|Seymour, Ben|Winston, Joel S|Darzi, Ara|Dolan, Raymond J', 'Centre for Health Policy, Institute of Global Health Innovation, Imperial College London, London, United Kingdom , Wellcome Trust Centre for Neuroimaging, University College London, London, United Kingdom.|Centre for Health Policy, Institute of Global Health Innovation, Imperial College London, London, United Kingdom , Wellcome Trust Centre for Neuroimaging, University College London, London, United Kingdom.|Centre for Health Policy, Institute of Global Health Innovation, Imperial College London, London, United Kingdom , Wellcome Trust Centre for Neuroimaging, University College London, London, United Kingdom.|Centre for Health Policy, Institute of Global Health Innovation, Imperial College London, London, United Kingdom , Wellcome Trust Centre for Neuroimaging, University College London, London, United Kingdom.|Centre for Health Policy, Institute of Global Health Innovation, Imperial College London, London, United Kingdom , Wellcome Trust Centre for Neuroimaging, University College London, London, United Kingdom.|Centre for Health Policy, Institute of Global Health Innovation, Imperial College London, London, United Kingdom , Wellcome Trust Centre for Neuroimaging, University College London, London, United Kingdom.', 'United Kingdom|United Kingdom|United Kingdom|United Kingdom|United Kingdom|United Kingdom', 31, 'Anticipation, Psychological|Bayes Theorem|Computational Biology|Decision Making|Female|Humans|Male|Models, Biological|Pain', 'Journal Article', '10.1371/journal.pcbi.1003335', '24277999', 'Standard theories of decision-making involving delayed outcomes predict that people should defer a punishment, whilst advancing a reward. In some cases, such as pain, people seem to prefer to expedite punishment, implying that its anticipation carries a cost, often conceptualized as dread. Despite empirical support for the existence of dread, whether and how it depends on prospective delay is unknown. Furthermore, it is unclear whether dread represents a stable component of value, or is modulated by biases such as framing effects. Here, we examine choices made between different numbers of painful shocks to be delivered faithfully at different time points up to 15 minutes in the future, as well as choices between hypothetical painful dental appointments at time points of up to approximately eight months in the future, to test alternative models for how future pain is disvalued. We show that future pain initially becomes increasingly aversive with increasing delay, but does so at a decreasing rate. This is consistent with a value model in which moment-by-moment dread increases up to the time of expected pain, such that dread becomes equivalent to the discounted expectation of pain. For a minority of individuals pain has maximum negative value at intermediate delay, suggesting that the dread function may itself be prospectively discounted in time. Framing an outcome as relief reduces the overall preference to expedite pain, which can be parameterized by reducing the rate of the dread-discounting function. Our data support an account of disvaluation for primary punishments such as pain, which differs fundamentally from existing models applied to financial punishments, in which dread exerts a powerful but time-dependent influence over choice. '),
(86311, 2013, 'plos', 'Genetic architecture promotes the evolution and maintenance of cooperation', 'Frénoy, Antoine|Taddei, François|Misevic, Dusan', 'INSERM U1001, Université Paris Descartes, Sorbonne Paris Cité, Faculté de Médecine Paris Descartes, Paris, France.|INSERM U1001, Université Paris Descartes, Sorbonne Paris Cité, Faculté de Médecine Paris Descartes, Paris, France.|INSERM U1001, Université Paris Descartes, Sorbonne Paris Cité, Faculté de Médecine Paris Descartes, Paris, France.', 'France|France|France', 0, 'Computational Biology|Computer Simulation|Cooperative Behavior|Evolution, Molecular|Genome|Metabolic Networks and Pathways|Microbial Interactions|Models, Biological|Mutation|Phenotype', 'Journal Article', '10.1371/journal.pcbi.1003339', '24278000', 'When cooperation has a direct cost and an indirect benefit, a selfish behavior is more likely to be selected for than an altruistic one. Kin and group selection do provide evolutionary explanations for the stability of cooperation in nature, but we still lack the full understanding of the genomic mechanisms that can prevent cheater invasion. In our study we used Aevol, an agent-based, in silico genomic platform to evolve populations of digital organisms that compete, reproduce, and cooperate by secreting a public good for tens of thousands of generations. We found that cooperating individuals may share a phenotype, defined as the amount of public good produced, but have very different abilities to resist cheater invasion. To understand the underlying genetic differences between cooperator types, we performed bio-inspired genomics analyses of our digital organisms by recording and comparing the locations of metabolic and secretion genes, as well as the relevant promoters and terminators. Association between metabolic and secretion genes (promoter sharing, overlap via frame shift or sense-antisense encoding) was characteristic for populations with robust cooperation and was more likely to evolve when secretion was costly. In mutational analysis experiments, we demonstrated the potential evolutionary consequences of the genetic association by performing a large number of mutations and measuring their phenotypic and fitness effects. The non-cooperating mutants arising from the individuals with genetic association were more likely to have metabolic deleterious mutations that eventually lead to selection eliminating such mutants from the population due to the accompanying fitness decrease. Effectively, cooperation evolved to be protected and robust to mutations through entangled genetic architecture. Our results confirm the importance of second-order selection on evolutionary outcomes, uncover an important genetic mechanism for the evolution and maintenance of cooperation, and suggest promising methods for preventing gene loss in synthetically engineered organisms. '),
(86312, 2013, 'plos', 'Ten simple rules for starting a regional student group', 'Shanmugam, Avinash Kumar|Macintyre, Geoff|Michaut, Magali|Abeel, Thomas', 'Department of Computational Medicine and Bioinformatics, University of Michigan Medical School, Ann Arbor, Michigan, United States of America.|Department of Computational Medicine and Bioinformatics, University of Michigan Medical School, Ann Arbor, Michigan, United States of America.|Department of Computational Medicine and Bioinformatics, University of Michigan Medical School, Ann Arbor, Michigan, United States of America.|Department of Computational Medicine and Bioinformatics, University of Michigan Medical School, Ann Arbor, Michigan, United States of America.', 'United States|United States|United States|United States', 7, 'Computational Biology|Humans|Societies|Students|Universities', 'Editorial', '10.1371/journal.pcbi.1003340', '24278001', '-'),
(86313, 2013, 'plos', 'Assessing computational methods for transcription factor target gene identification based on ChIP-seq data', 'Sikora-Wohlfeld, Weronika|Ackermann, Marit|Christodoulou, Eleni G|Singaravelu, Kalaimathy|Beyer, Andreas', 'Biotechnology Center, TU Dresden, Dresden, Germany.|Biotechnology Center, TU Dresden, Dresden, Germany.|Biotechnology Center, TU Dresden, Dresden, Germany.|Biotechnology Center, TU Dresden, Dresden, Germany.|Biotechnology Center, TU Dresden, Dresden, Germany.', 'Germany|Germany|Germany|Germany|Germany', 33, 'Algorithms|Animals|Binding Sites|Chromatin Immunoprecipitation|Databases, Genetic|Genome|Genomics|Mice|Models, Statistical|Reproducibility of Results|Sequence Analysis, DNA|Transcription Factors', 'Journal Article', '10.1371/journal.pcbi.1003342', '24278002', 'Chromatin immunoprecipitation coupled with deep sequencing (ChIP-seq) has great potential for elucidating transcriptional networks, by measuring genome-wide binding of transcription factors (TFs) at high resolution. Despite the precision of these experiments, identification of genes directly regulated by a TF (target genes) is not trivial. Numerous target gene scoring methods have been used in the past. However, their suitability for the task and their performance remain unclear, because a thorough comparative assessment of these methods is still lacking. Here we present a systematic evaluation of computational methods for defining TF targets based on ChIP-seq data. We validated predictions based on 68 ChIP-seq studies using a wide range of genomic expression data and functional information. We demonstrate that peak-to-gene assignment is the most crucial step for correct target gene prediction and propose a parameter-free method performing most consistently across the evaluation tests. '),
(86314, 2013, 'plos', 'Systematic analysis of compositional order of proteins reveals new characteristics of biological functions and a universal correlate of macroevolution', 'Persi, Erez|Horn, David', 'School of Physics and Astronomy, Tel Aviv University, Tel Aviv, Israel.|School of Physics and Astronomy, Tel Aviv University, Tel Aviv, Israel.', 'Israel|Israel', 4, 'Amino Acid Sequence|Animals|Biological Evolution|Cluster Analysis|Computational Biology|Databases, Protein|Humans|Models, Biological|Molecular Sequence Annotation|Molecular Sequence Data|Proteins|Saccharomyces cerevisiae|Sequence Analysis, Protein', 'Journal Article', '10.1371/journal.pcbi.1003346', '24278003', 'We present a novel analysis of compositional order (CO) based on the occurrence of Frequent amino-acid Triplets (FTs) that appear much more than random in protein sequences. The method captures all types of proteomic compositional order including single amino-acid runs, tandem repeats, periodic structure of motifs and otherwise low complexity amino-acid regions. We introduce new order measures, distinguishing between regularity, periodicity and vocabulary, to quantify these phenomena and to facilitate the identification of evolutionary effects. Detailed analysis of representative species across the tree-of-life demonstrates that CO proteins exhibit numerous functional enrichments, including a wide repertoire of particular patterns of dependencies on regularity and periodicity. Comparison between human and mouse proteomes further reveals the interplay of CO with evolutionary trends, such as faster substitution rate in mouse leading to decrease of periodicity, while innovation along the human lineage leads to larger regularity. Large-scale analysis of 94 proteomes leads to systematic ordering of all major taxonomic groups according to FT-vocabulary size. This is measured by the count of Different Frequent Triplets (DFT) in proteomes. The latter provides a clear hierarchical delineation of vertebrates, invertebrates, plants, fungi and prokaryotes, with thermophiles showing the lowest level of FT-vocabulary. Among eukaryotes, this ordering correlates with phylogenetic proximity. Interestingly, in all kingdoms CO accumulation in the proteome has universal characteristics. We suggest that CO is a genomic-information correlate of both macroevolution and various protein functions. The results indicate a mechanism of genomic innovation at the peptide level, involved in protein elongation, shaped in a universal manner by mutational and selective forces. '),
(86315, 2013, 'plos', 'MicroRNA-gene association as a prognostic biomarker in cancer exposes disease mechanisms', 'Ben-Hamo, Rotem|Efroni, Sol', 'The Mina and Everard Goodman Faculty of Life Science, Bar Ilan University, Ramat-Gan, Israel.|The Mina and Everard Goodman Faculty of Life Science, Bar Ilan University, Ramat-Gan, Israel.', 'Israel|Israel', 14, 'Algorithms|Biomarkers, Tumor|Databases, Genetic|Genomics|Humans|Kaplan-Meier Estimate|MicroRNAs|Neoplasms|Prognosis|Reproducibility of Results', 'Journal Article', '10.1371/journal.pcbi.1003351', '24278004', 'The transcriptional networks that regulate gene expression and modifications to this network are at the core of the cancer phenotype. MicroRNAs, a well-studied species of small non-coding RNA molecules, have been shown to have a central role in regulating gene expression as part of this transcriptional network. Further, microRNA deregulation is associated with cancer development and with tumor progression. Glioblastoma Multiform (GBM) is the most common, aggressive and malignant primary tumor of the brain and is associated with one of the worst 5-year survival rates among all human cancers. To study the transcriptional network and its modifications in GBM, we utilized gene expression, microRNA sequencing, whole genome sequencing and clinical data from hundreds of patients from different datasets. Using these data and a novel microRNA-gene association approach we introduce, we have identified unique microRNAs and their associated genes. This unique behavior is composed of the ability of the quantifiable association of the microRNA and the gene expression levels, which we show stratify patients into clinical subgroups of high statistical significance. Importantly, this stratification goes unobserved by other methods and is not affiliated by other subsets or phenotypes within the data. To investigate the robustness of the introduced approach, we demonstrate, in unrelated datasets, robustness of findings. Among the set of identified microRNA-gene associations, we closely study the example of MAF and hsa-miR-330-3p, and show how their co-behavior stratifies patients into prognosis clinical groups and how whole genome sequences tells us more about a specific genomic variation as a possible basis for patient variances. We argue that these identified associations may indicate previously unexplored specific disease control mechanisms and may be used as basis for further study and for possible therapeutic intervention. '),
(86316, 2013, 'plos', 'Understanding the connection between epigenetic DNA methylation and nucleosome positioning from computer simulations', 'Portella, Guillem|Battistini, Federica|Orozco, Modesto', 'Institute for Research in Biomedicine (IRB Barcelona), Barcelona, Spain , Joint IRB-BSC Program in Computational Biology, Barcelona, Spain.|Institute for Research in Biomedicine (IRB Barcelona), Barcelona, Spain , Joint IRB-BSC Program in Computational Biology, Barcelona, Spain.|Institute for Research in Biomedicine (IRB Barcelona), Barcelona, Spain , Joint IRB-BSC Program in Computational Biology, Barcelona, Spain.', 'Spain|Spain|Spain', 31, 'Computational Biology|Cytosine|DNA Methylation|Epigenesis, Genetic|Models, Genetic|Molecular Dynamics Simulation|Nucleosomes|Thermodynamics', 'Journal Article', '10.1371/journal.pcbi.1003354', '24278005', 'Cytosine methylation is one of the most important epigenetic marks that regulate the process of gene expression. Here, we have examined the effect of epigenetic DNA methylation on nucleosomal stability using molecular dynamics simulations and elastic deformation models. We found that methylation of CpG steps destabilizes nucleosomes, especially when these are placed in sites where the DNA minor groove faces the histone core. The larger stiffness of methylated CpG steps is a crucial factor behind the decrease in nucleosome stability. Methylation changes the positioning and phasing of the nucleosomal DNA, altering the accessibility of DNA to regulatory proteins, and accordingly gene functionality. Our theoretical calculations highlight a simple physical-based explanation on the foundations of epigenetic signaling. '),
(86317, 2013, 'plos', 'Beyond GLMs: a generative mixture modeling approach to neural system identification', 'Theis, Lucas|Chagas, Andrè Maia|Arnstein, Daniel|Schwarz, Cornelius|Bethge, Matthias', 'Werner Reichardt Centre for Integrative Neuroscience, Tübingen, Germany , Graduate School of Neural Information Processing, University of Tübingen, Tübingen, Germany.|Werner Reichardt Centre for Integrative Neuroscience, Tübingen, Germany , Graduate School of Neural Information Processing, University of Tübingen, Tübingen, Germany.|Werner Reichardt Centre for Integrative Neuroscience, Tübingen, Germany , Graduate School of Neural Information Processing, University of Tübingen, Tübingen, Germany.|Werner Reichardt Centre for Integrative Neuroscience, Tübingen, Germany , Graduate School of Neural Information Processing, University of Tübingen, Tübingen, Germany.|Werner Reichardt Centre for Integrative Neuroscience, Tübingen, Germany , Graduate School of Neural Information Processing, University of Tübingen, Tübingen, Germany.', 'Germany|Germany|Germany|Germany|Germany', 23, 'Action Potentials|Animals|Computational Biology|Linear Models|Models, Neurological|Neurons|Rats|Vibrissae', 'Journal Article', '10.1371/journal.pcbi.1003356', '24278006', 'Generalized linear models (GLMs) represent a popular choice for the probabilistic characterization of neural spike responses. While GLMs are attractive for their computational tractability, they also impose strong assumptions and thus only allow for a limited range of stimulus-response relationships to be discovered. Alternative approaches exist that make only very weak assumptions but scale poorly to high-dimensional stimulus spaces. Here we seek an approach which can gracefully interpolate between the two extremes. We extend two frequently used special cases of the GLM-a linear and a quadratic model-by assuming that the spike-triggered and non-spike-triggered distributions can be adequately represented using Gaussian mixtures. Because we derive the model from a generative perspective, its components are easy to interpret as they correspond to, for example, the spike-triggered distribution and the interspike interval distribution. The model is able to capture complex dependencies on high-dimensional stimuli with far fewer parameters than other approaches such as histogram-based methods. The added flexibility comes at the cost of a non-concave log-likelihood. We show that in practice this does not have to be an issue and the mixture-based model is able to outperform generalized linear and quadratic models. '),
(86318, 2013, 'plos', 'Harnessing diversity towards the reconstructing of large scale gene regulatory networks', 'Hase, Takeshi|Ghosh, Samik|Yamanaka, Ryota|Kitano, Hiroaki', 'The Systems Biology Institute, Shirokanedai, Minato, Tokyo, Japan , Laboratory of Disease Systems Modeling, Center for Integrative Medical Sciences, RIKEN, Suehiro-cho, Tsurumi-ku, Yokohama City, Kanagawa, Japan.|The Systems Biology Institute, Shirokanedai, Minato, Tokyo, Japan , Laboratory of Disease Systems Modeling, Center for Integrative Medical Sciences, RIKEN, Suehiro-cho, Tsurumi-ku, Yokohama City, Kanagawa, Japan.|The Systems Biology Institute, Shirokanedai, Minato, Tokyo, Japan , Laboratory of Disease Systems Modeling, Center for Integrative Medical Sciences, RIKEN, Suehiro-cho, Tsurumi-ku, Yokohama City, Kanagawa, Japan.|The Systems Biology Institute, Shirokanedai, Minato, Tokyo, Japan , Laboratory of Disease Systems Modeling, Center for Integrative Medical Sciences, RIKEN, Suehiro-cho, Tsurumi-ku, Yokohama City, Kanagawa, Japan.', 'Japan|Japan|Japan|Japan', 29, 'Algorithms|Computational Biology|Databases, Genetic|Gene Expression|Gene Expression Profiling|Gene Regulatory Networks', 'Journal Article', '10.1371/journal.pcbi.1003361', '24278007', 'Elucidating gene regulatory network (GRN) from large scale experimental data remains a central challenge in systems biology. Recently, numerous techniques, particularly consensus driven approaches combining different algorithms, have become a potentially promising strategy to infer accurate GRNs. Here, we develop a novel consensus inference algorithm, TopkNet that can integrate multiple algorithms to infer GRNs. Comprehensive performance benchmarking on a cloud computing framework demonstrated that (i) a simple strategy to combine many algorithms does not always lead to performance improvement compared to the cost of consensus and (ii) TopkNet integrating only high-performance algorithms provide significant performance improvement compared to the best individual algorithms and community prediction. These results suggest that a priori determination of high-performance algorithms is a key to reconstruct an unknown regulatory network. Similarity among gene-expression datasets can be useful to determine potential optimal algorithms for reconstruction of unknown regulatory networks, i.e., if expression-data associated with known regulatory network is similar to that with unknown regulatory network, optimal algorithms determined for the known regulatory network can be repurposed to infer the unknown regulatory network. Based on this observation, we developed a quantitative measure of similarity among gene-expression datasets and demonstrated that, if similarity between the two expression datasets is high, TopkNet integrating algorithms that are optimal for known dataset perform well on the unknown dataset. The consensus framework, TopkNet, together with the similarity measure proposed in this study provides a powerful strategy towards harnessing the wisdom of the crowds in reconstruction of unknown regulatory networks. '),
(86319, 2013, 'plos', 'Electrostatically accelerated encounter and folding for facile recognition of intrinsically disordered proteins', 'Ganguly, Debabani|Zhang, Weihong|Chen, Jianhan', 'Department of Biochemistry and Molecular Biophysics, Kansas State University, Manhattan, Kansas, United States of America.|Department of Biochemistry and Molecular Biophysics, Kansas State University, Manhattan, Kansas, United States of America.|Department of Biochemistry and Molecular Biophysics, Kansas State University, Manhattan, Kansas, United States of America.', 'United States|United States|United States', 57, 'Intrinsically Disordered Proteins|Kinetics|Molecular Dynamics Simulation|Protein Folding|Static Electricity|Surface Properties|Thermodynamics', 'Journal Article', '10.1371/journal.pcbi.1003363', '24278008', 'Achieving facile specific recognition is essential for intrinsically disordered proteins (IDPs) that are involved in cellular signaling and regulation. Consideration of the physical time scales of protein folding and diffusion-limited protein-protein encounter has suggested that the frequent requirement of protein folding for specific IDP recognition could lead to kinetic bottlenecks. How IDPs overcome such potential kinetic bottlenecks to viably function in signaling and regulation in general is poorly understood. Our recent computational and experimental study of cell-cycle regulator p27 (Ganguly et al., J. Mol. Biol. (2012)) demonstrated that long-range electrostatic forces exerted on enriched charges of IDPs could accelerate protein-protein encounter via electrostatic steering and at the same time promote folding-competent encounter topologies to enhance the efficiency of IDP folding upon encounter. Here, we further investigated the coupled binding and folding mechanisms and the roles of electrostatic forces in the formation of three IDP complexes with more complex folded topologies. The surface electrostatic potentials of these complexes lack prominent features like those observed for the p27/Cdk2/cyclin A complex to directly suggest the ability of electrostatic forces to facilitate folding upon encounter. Nonetheless, similar electrostatically accelerated encounter and folding mechanisms were consistently predicted for all three complexes using topology-based coarse-grained simulations. Together with our previous analysis of charge distributions in known IDP complexes, our results support a prevalent role of electrostatic interactions in promoting efficient coupled binding and folding for facile specific recognition. These results also suggest that there is likely a co-evolution of IDP folded topology, charge characteristics, and coupled binding and folding mechanisms, driven at least partially by the need to achieve fast association kinetics for cellular signaling and regulation. '),
(86320, 2013, 'plos', 'Multiscale modeling of influenza A virus infection supports the development of direct-acting antivirals', 'Heldt, Frank S|Frensing, Timo|Pflugmacher, Antje|Gröpler, Robin|Peschel, Britta|Reichl, Udo', 'Max Planck Institute for Dynamics of Complex Technical Systems, Magdeburg, Germany.|Max Planck Institute for Dynamics of Complex Technical Systems, Magdeburg, Germany.|Max Planck Institute for Dynamics of Complex Technical Systems, Magdeburg, Germany.|Max Planck Institute for Dynamics of Complex Technical Systems, Magdeburg, Germany.|Max Planck Institute for Dynamics of Complex Technical Systems, Magdeburg, Germany.|Max Planck Institute for Dynamics of Complex Technical Systems, Magdeburg, Germany.', 'Germany|Germany|Germany|Germany|Germany|Germany', 44, 'Animals|Antiviral Agents|Cell Death|Computational Biology|Dogs|Drug Discovery|Extracellular Space|Humans|Influenza A virus|Influenza, Human|Intracellular Space|Madin Darby Canine Kidney Cells|Models, Biological|Virus Internalization|Virus Replication', 'Journal Article', '10.1371/journal.pcbi.1003372', '24278009', 'Influenza A viruses are respiratory pathogens that cause seasonal epidemics with up to 500,000 deaths each year. Yet there are currently only two classes of antivirals licensed for treatment and drug-resistant strains are on the rise. A major challenge for the discovery of new anti-influenza agents is the identification of drug targets that efficiently interfere with viral replication. To support this step, we developed a multiscale model of influenza A virus infection which comprises both the intracellular level where the virus synthesizes its proteins, replicates its genome, and assembles new virions and the extracellular level where it spreads to new host cells. This integrated modeling approach recapitulates a wide range of experimental data across both scales including the time course of all three viral RNA species inside an infected cell and the infection dynamics in a cell population. It also allowed us to systematically study how interfering with specific steps of the viral life cycle affects virus production. We find that inhibitors of viral transcription, replication, protein synthesis, nuclear export, and assembly/release are most effective in decreasing virus titers whereas targeting virus entry primarily delays infection. In addition, our results suggest that for some antivirals therapy success strongly depends on the lifespan of infected cells and, thus, on the dynamics of virus-induced apoptosis or the hosts immune response. Hence, the proposed model provides a systems-level understanding of influenza A virus infection and therapy as well as an ideal platform to include further levels of complexity toward a comprehensive description of infectious diseases. '),
(86321, 2013, 'plos', 'Conserved substitution patterns around nucleosome footprints in eukaryotes and Archaea derive from frequent nucleosome repositioning through evolution', 'Warnecke, Tobias|Becker, Erin A|Facciotti, Marc T|Nislow, Corey|Lehner, Ben', 'Bioinformatics and Genomics Program, Centre for Genomic Regulation (CRG) and UPF, Barcelona, Spain , Universitat Pompeu Fabra (UPF), Barcelona, Spain.|Bioinformatics and Genomics Program, Centre for Genomic Regulation (CRG) and UPF, Barcelona, Spain , Universitat Pompeu Fabra (UPF), Barcelona, Spain.|Bioinformatics and Genomics Program, Centre for Genomic Regulation (CRG) and UPF, Barcelona, Spain , Universitat Pompeu Fabra (UPF), Barcelona, Spain.|Bioinformatics and Genomics Program, Centre for Genomic Regulation (CRG) and UPF, Barcelona, Spain , Universitat Pompeu Fabra (UPF), Barcelona, Spain.|Bioinformatics and Genomics Program, Centre for Genomic Regulation (CRG) and UPF, Barcelona, Spain , Universitat Pompeu Fabra (UPF), Barcelona, Spain.', 'Spain|Spain|Spain|Spain|Spain', 8, 'Archaea|Eukaryota|Evolution, Molecular|Genomics|Haloferax volcanii|Humans|Models, Genetic|Mutation|Nucleosomes|Phylogeny', 'Journal Article', '10.1371/journal.pcbi.1003373', '24278010', 'Nucleosomes, the basic repeat units of eukaryotic chromatin, have been suggested to influence the evolution of eukaryotic genomes, both by altering the propensity of DNA to mutate and by selection acting to maintain or exclude nucleosomes in particular locations. Contrary to the popular idea that nucleosomes are unique to eukaryotes, histone proteins have also been discovered in some archaeal genomes. Archaeal nucleosomes, however, are quite unlike their eukaryotic counterparts in many respects, including their assembly into tetramers (rather than octamers) from histone proteins that lack N- and C-terminal tails. Here, we show that despite these fundamental differences the association between nucleosome footprints and sequence evolution is strikingly conserved between humans and the model archaeon Haloferax volcanii. In light of this finding we examine whether selection or mutation can explain concordant substitution patterns in the two kingdoms. Unexpectedly, we find that neither the mutation nor the selection model are sufficient to explain the observed association between nucleosomes and sequence divergence. Instead, we demonstrate that nucleosome-associated substitution patterns are more consistent with a third model where sequence divergence results in frequent repositioning of nucleosomes during evolution. Indeed, we show that nucleosome repositioning is both necessary and largely sufficient to explain the association between current nucleosome positions and biased substitution patterns. This finding highlights the importance of considering the direction of causality between genetic and epigenetic change. '),
(86322, 2013, 'plos', 'Breaking the ice and forging links: the importance of socializing in research', 'Stobbe, Miranda|Mishra, Tarun|Macintyre, Geoff', 'Bioinformatics Laboratory, Department of Clinical Epidemiology, Biostatistics and Bioinformatics, Academic Medical Center, University of Amsterdam, Amsterdam, The Netherlands , Netherlands Bioinformatics Centre, Nijmegen, The Netherlands.|Bioinformatics Laboratory, Department of Clinical Epidemiology, Biostatistics and Bioinformatics, Academic Medical Center, University of Amsterdam, Amsterdam, The Netherlands , Netherlands Bioinformatics Centre, Nijmegen, The Netherlands.|Bioinformatics Laboratory, Department of Clinical Epidemiology, Biostatistics and Bioinformatics, Academic Medical Center, University of Amsterdam, Amsterdam, The Netherlands , Netherlands Bioinformatics Centre, Nijmegen, The Netherlands.', 'Netherlands|Netherlands|Netherlands', 8, 'Computational Biology|Humans|Research|Social Networking|Societies, Scientific|Students', 'Journal Article', '10.1371/journal.pcbi.1003355', '24282392', 'When meeting someone for the first time-whether another PhD student, or the Founding Editor-in-chief of PLOS Computational Biology-nothing breaks the ice like eating pancakes or having drinks together. A social atmosphere provides a relaxed, informal environment where people can connect, share ideas, and form collaborations. Being able to build a network and thrive in a social environment is crucial to a successful scientific career. This article highlights the importance of bringing people together who speak the same scientific language in an informal setting. Using examples of events held by Regional Student Groups of the ISCBs Student Council, this article shows that socializing is much more than simply sharing a drink. '),
(86323, 2013, 'plos', 'Sharpness of spike initiation in neurons explained by compartmentalization', 'Brette, Romain', 'Laboratoire Psychologie de la Perception, CNRS and Université Paris Descartes, Paris, France , Equipe Audition, Département dEtudes Cognitives, Ecole Normale Supérieure, Paris, France.', 'France', 0, 'Action Potentials|Models, Biological|Neurons|Sodium Channels', 'Journal Article', '10.1371/journal.pcbi.1003338', '24339755', 'In cortical neurons, spikes are initiated in the axon initial segment. Seen at the soma, they appear surprisingly sharp. A standard explanation is that the current coming from the axon becomes sharp as the spike is actively backpropagated to the soma. However, sharp initiation of spikes is also seen in the input-output properties of neurons, and not only in the somatic shape of spikes, for example, cortical neurons can transmit high frequency signals. An alternative hypothesis is that Na channels cooperate, but it is not currently supported by direct experimental evidence. I propose a simple explanation based on the compartmentalization of spike initiation. When Na channels are placed in the axon, the soma acts as a current sink for the Na current. I show that there is a critical distance to the soma above which an instability occurs, so that Na channels open abruptly rather than gradually as a function of somatic voltage. '),
(86324, 2013, 'plos', 'Transformation of stimulus correlations by the retina', 'Simmons, Kristina D|Prentice, Jason S|Tkaxc4x8dik, Gaxc5xa1per|Homann, Jan|Yee, Heather K|Palmer, Stephanie E|Nelson, Philip C|Balasubramanian, Vijay', 'Department of Neuroscience, University of Pennsylvania, Philadelphia, Pennsylvania, United States of America.|Department of Neuroscience, University of Pennsylvania, Philadelphia, Pennsylvania, United States of America.|Department of Neuroscience, University of Pennsylvania, Philadelphia, Pennsylvania, United States of America.|Department of Neuroscience, University of Pennsylvania, Philadelphia, Pennsylvania, United States of America.|Department of Neuroscience, University of Pennsylvania, Philadelphia, Pennsylvania, United States of America.|Department of Neuroscience, University of Pennsylvania, Philadelphia, Pennsylvania, United States of America.|Department of Neuroscience, University of Pennsylvania, Philadelphia, Pennsylvania, United States of America.|Department of Neuroscience, University of Pennsylvania, Philadelphia, Pennsylvania, United States of America.', 'United States|United States|United States|United States|United States|United States|United States|Un', 0, 'Animals|Guinea Pigs|Likelihood Functions|Linear Models|Nonlinear Dynamics|Photic Stimulation|Retinal Ganglion Cells', 'Journal Article', '10.1371/journal.pcbi.1003344', '24339756', 'Redundancies and correlations in the responses of sensory neurons may seem to waste neural resources, but they can also carry cues about structured stimuli and may help the brain to correct for response errors. To investigate the effect of stimulus structure on redundancy in retina, we measured simultaneous responses from populations of retinal ganglion cells presented with natural and artificial stimuli that varied greatly in correlation structure, these stimuli and recordings are publicly available online. Responding to spatio-temporally structured stimuli such as natural movies, pairs of ganglion cells were modestly more correlated than in response to white noise checkerboards, but they were much less correlated than predicted by a non-adapting functional model of retinal response. Meanwhile, responding to stimuli with purely spatial correlations, pairs of ganglion cells showed increased correlations consistent with a static, non-adapting receptive field and nonlinearity. We found that in response to spatio-temporally correlated stimuli, ganglion cells had faster temporal kernels and tended to have stronger surrounds. These properties of individual cells, along with gain changes that opposed changes in effective contrast at the ganglion cell input, largely explained the pattern of pairwise correlations across stimuli where receptive field measurements were possible. '),
(86325, 2013, 'plos', 'Membrane binding of MinE allows for a comprehensive description of Min-protein pattern formation', 'Bonny, Mike|Fischer-Friedrich, Elisabeth|Loose, Martin|Schwille, Petra|Kruse, Karsten', 'Theoretische Physik, Universität des Saarlandes, Saarbrücken, Germany.|Theoretische Physik, Universität des Saarlandes, Saarbrücken, Germany.|Theoretische Physik, Universität des Saarlandes, Saarbrücken, Germany.|Theoretische Physik, Universität des Saarlandes, Saarbrücken, Germany.|Theoretische Physik, Universität des Saarlandes, Saarbrücken, Germany.', 'Germany|Germany|Germany|Germany|Germany', 0, 'Cell Cycle Proteins|Escherichia coli Proteins|Molecular Dynamics Simulation|Protein Binding', 'Journal Article', '10.1371/journal.pcbi.1003347', '24339757', 'The rod-shaped bacterium Escherichia coli selects the cell center as site of division with the help of the proteins MinC, MinD, and MinE. This protein system collectively oscillates between the two cell poles by alternately binding to the membrane in one of the two cell halves. This dynamic behavior, which emerges from the interaction of the ATPase MinD and its activator MinE on the cell membrane, has become a paradigm for protein self-organization. Recently, it has been found that not only the binding of MinD to the membrane, but also interactions of MinE with the membrane contribute to Min-protein self-organization. Here, we show that by accounting for this finding in a computational model, we can comprehensively describe all observed Min-protein patterns in vivo and in vitro. Furthermore, by varying the systems geometry, our computations predict patterns that have not yet been reported. We confirm these predictions experimentally. '),
(86326, 2013, 'plos', 'Determinants of cell-to-cell variability in protein kinase signaling', 'Jeschke, Matthias|Baumgärtner, Stephan|Legewie, Stefan', 'Institute of Molecular Biology (IMB), Mainz, Germany.|Institute of Molecular Biology (IMB), Mainz, Germany.|Institute of Molecular Biology (IMB), Mainz, Germany.', 'Germany|Germany|Germany', 14, 'Feedback|Models, Biological|Protein Kinases|Signal Transduction', 'Journal Article', '10.1371/journal.pcbi.1003357', '24339758', 'Cells reliably sense environmental changes despite internal and external fluctuations, but the mechanisms underlying robustness remain unclear. We analyzed how fluctuations in signaling protein concentrations give rise to cell-to-cell variability in protein kinase signaling using analytical theory and numerical simulations. We characterized the dose-response behavior of signaling cascades by calculating the stimulus level at which a pathway responds (pathway sensitivity) and the maximal activation level upon strong stimulation. Minimal kinase cascades with gradual dose-response behavior show strong variability, because the pathway sensitivity and the maximal activation level cannot be simultaneously invariant. Negative feedback regulation resolves this trade-off and coordinately reduces fluctuations in the pathway sensitivity and maximal activation. Feedbacks acting at different levels in the cascade control different aspects of the dose-response curve, thereby synergistically reducing the variability. We also investigated more complex, ultrasensitive signaling cascades capable of switch-like decision making, and found that these can be inherently robust to protein concentration fluctuations. We describe how the cell-to-cell variability of ultrasensitive signaling systems can be actively regulated, e.g., by altering the expression of phosphatase(s) or by feedback/feedforward loops. Our calculations reveal that slow transcriptional negative feedback loops allow for variability suppression while maintaining switch-like decision making. Taken together, we describe design principles of signaling cascades that promote robustness. Our results may explain why certain signaling cascades like the yeast pheromone pathway show switch-like decision making with little cell-to-cell variability. '),
(86327, 2013, 'plos', 'Systems modeling of anti-apoptotic pathways in prostate cancer: psychological stress triggers a synergism pattern switch in drug combination therapy', 'Sun, Xiaoqiang|Bao, Jiguang|Nelson, Kyle C|Li, King Chuen|Kulik, George|Zhou, Xiaobo', 'Department of Radiology, Wake Forest School of Medicine, Winston-Salem, North Carolina, United States of America , School of Mathematical Science, Beijing Normal University, Beijing, P. R. China.|Department of Radiology, Wake Forest School of Medicine, Winston-Salem, North Carolina, United States of America , School of Mathematical Science, Beijing Normal University, Beijing, P. R. China.|Department of Radiology, Wake Forest School of Medicine, Winston-Salem, North Carolina, United States of America , School of Mathematical Science, Beijing Normal University, Beijing, P. R. China.|Department of Radiology, Wake Forest School of Medicine, Winston-Salem, North Carolina, United States of America , School of Mathematical Science, Beijing Normal University, Beijing, P. R. China.|Department of Radiology, Wake Forest School of Medicine, Winston-Salem, North Carolina, United States of America , School of Mathematical Science, Beijing Normal University, Beijing, P. R. China.|Department of Radiology, Wake Forest School of Medicine, Winston-Salem, North Carolina, United States of America , School of Mathematical Science, Beijing Normal University, Beijing, P. R. China.', 'China|China|China|China|China|China', 28, 'Antineoplastic Combined Chemotherapy Protocols|Apoptosis|Drug Synergism|Humans|Male|Models, Biological|Phosphorylation|Prostatic Neoplasms|Signal Transduction|Stress, Psychological|Systems Biology|bcl-Associated Death Protein', 'Journal Article', '10.1371/journal.pcbi.1003358', '24339759', 'Prostate cancer patients often have increased levels of psychological stress or anxiety, but the molecular mechanisms underlying the interaction between psychological stress and prostate cancer as well as therapy resistance have been rarely studied and remain poorly understood. Recent reports show that stress inhibits apoptosis in prostate cancer cells via epinephrine/beta2 adrenergic receptor/PKA/BAD pathway. In this study, we used experimental data on the signaling pathways that control BAD phosphorylation to build a dynamic network model of apoptosis regulation in prostate cancer cells. We then compared the predictive power of two different models with or without the role of Mcl-1, which justified the role of Mcl-1 stabilization in anti-apoptotic effects of emotional stress. Based on the selected model, we examined and quantitatively evaluated the induction of apoptosis by drug combination therapies. We predicted that the combination of PI3K inhibitor LY294002 and inhibition of BAD phosphorylation at S112 would produce the best synergistic effect among 8 interventions examined. Experimental validation confirmed the effectiveness of our predictive model. Moreover, we found that epinephrine signaling changes the synergism pattern and decreases efficacy of combination therapy. The molecular mechanisms responsible for therapeutic resistance and the switch in synergism were explored by analyzing a network model of signaling pathways affected by psychological stress. These results provide insights into the mechanisms of psychological stress signaling in therapy-resistant cancer, and indicate the potential benefit of reducing psychological stress in designing more effective therapies for prostate cancer patients. '),
(86328, 2013, 'plos', 'Dimensionality of carbon nanomaterials determines the binding and dynamics of amyloidogenic peptides: multiscale theoretical simulations', 'Todorova, Nevena|Makarucha, Adam J|Hine, Nicholas D M|Mostofi, Arash A|Yarovsky, Irene', 'Health Innovations Research Institute, Melbourne, Australia.|Health Innovations Research Institute, Melbourne, Australia.|Health Innovations Research Institute, Melbourne, Australia.|Health Innovations Research Institute, Melbourne, Australia.|Health Innovations Research Institute, Melbourne, Australia.', 'Australia|Australia|Australia|Australia|Australia', 0, 'Amyloid|Carbon|Models, Molecular|Models, Theoretical|Nanostructures|Peptides|Protein Binding|Protein Conformation|Thermodynamics', 'Journal Article', '10.1371/journal.pcbi.1003360', '24339760', 'Experimental studies have demonstrated that nanoparticles can affect the rate of protein self-assembly, possibly interfering with the development of protein misfolding diseases such as Alzheimers, Parkinsons and prion disease caused by aggregation and fibril formation of amyloid-prone proteins. We employ classical molecular dynamics simulations and large-scale density functional theory calculations to investigate the effects of nanomaterials on the structure, dynamics and binding of an amyloidogenic peptide apoC-II(60-70). We show that the binding affinity of this peptide to carbonaceous nanomaterials such as C60, nanotubes and graphene decreases with increasing nanoparticle curvature. Strong binding is facilitated by the large contact area available for xcfx80-stacking between the aromatic residues of the peptide and the extended surfaces of graphene and the nanotube. The highly curved fullerene surface exhibits reduced efficiency for xcfx80-stacking but promotes increased peptide dynamics. We postulate that the increase in conformational dynamics of the amyloid peptide can be unfavorable for the formation of fibril competent structures. In contrast, extended fibril forming peptide conformations are promoted by the nanotube and graphene surfaces which can provide a template for fibril-growth. ');
INSERT INTO `papers` (`id`, `ano`, `journal`, `titulo`, `autores`, `afiliacao`, `pais`, `citacoes`, `palavra_chave`, `categorias`, `doi`, `pubmed`, `abstract`) VALUES
(86329, 2013, 'plos', 'A sequential vesicle pool model with a single release sensor and a Ca(2+)-dependent priming catalyst effectively explains Ca(2+)-dependent properties of neurosecretion', 'Walter, Alexander M|Pinheiro, Paulo S|Verhage, Matthijs|Sørensen, Jakob B', 'Department of Functional Genomics and Department of Clinical Genetics, Center for Neurogenomics and Cognitive Research, Neuroscience Campus Amsterdam, VU University Amsterdam and VU University Medical Center, Amsterdam, The Netherlands , Department of Neuroscience and Pharmacology, Faculty of Health Sciences, University of Copenhagen, Copenhagen, Denmark.|Department of Functional Genomics and Department of Clinical Genetics, Center for Neurogenomics and Cognitive Research, Neuroscience Campus Amsterdam, VU University Amsterdam and VU University Medical Center, Amsterdam, The Netherlands , Department of Neuroscience and Pharmacology, Faculty of Health Sciences, University of Copenhagen, Copenhagen, Denmark.|Department of Functional Genomics and Department of Clinical Genetics, Center for Neurogenomics and Cognitive Research, Neuroscience Campus Amsterdam, VU University Amsterdam and VU University Medical Center, Amsterdam, The Netherlands , Department of Neuroscience and Pharmacology, Faculty of Health Sciences, University of Copenhagen, Copenhagen, Denmark.|Department of Functional Genomics and Department of Clinical Genetics, Center for Neurogenomics and Cognitive Research, Neuroscience Campus Amsterdam, VU University Amsterdam and VU University Medical Center, Amsterdam, The Netherlands , Department of Neuroscience and Pharmacology, Faculty of Health Sciences, University of Copenhagen, Copenhagen, Denmark.', 'Denmark|Denmark|Denmark|Denmark', 0, 'Animals|Calcium|Chromaffin Cells|Kinetics|Mice|Models, Biological|Neurosecretion|SNARE Proteins', 'Journal Article', '10.1371/journal.pcbi.1003362', '24339761', 'Neurotransmitter release depends on the fusion of secretory vesicles with the plasma membrane and the release of their contents. The final fusion step displays higher-order Ca(2+) dependence, but also upstream steps depend on Ca(2+). After deletion of the Ca(2+) sensor for fast release - synaptotagmin-1 - slower Ca(2+)-dependent release components persist. These findings have provoked working models involving parallel releasable vesicle pools (Parallel Pool Models, PPM) driven by alternative Ca(2+) sensors for release, but no slow release sensor acting on a parallel vesicle pool has been identified. We here propose a Sequential Pool Model (SPM), assuming a novel Ca(2+)-dependent action: a Ca(2+)-dependent catalyst that accelerates both forward and reverse priming reactions. While both models account for fast fusion from the Readily-Releasable Pool (RRP) under control of synaptotagmin-1, the origins of slow release differ. In the SPM the slow release component is attributed to the Ca(2+)-dependent refilling of the RRP from a Non-Releasable upstream Pool (NRP), whereas the PPM attributes slow release to a separate slowly-releasable vesicle pool. Using numerical integration we compared model predictions to data from mouse chromaffin cells. Like the PPM, the SPM explains biphasic release, Ca(2+)-dependence and pool sizes in mouse chromaffin cells. In addition, the SPM accounts for the rapid recovery of the fast component after strong stimulation, where the PPM fails. The SPM also predicts the simultaneous changes in release rate and amplitude seen when mutating the SNARE-complex. Finally, it can account for the loss of fast- and the persistence of slow release in the synaptotagmin-1 knockout by assuming that the RRP is depleted, leading to slow and Ca(2+)-dependent fusion from the NRP. We conclude that the elusive alternative Ca(2+) sensor for slow release might be the upstream priming catalyst, and that a sequential model effectively explains Ca(2+)-dependent properties of secretion without assuming parallel pools or sensors. '),
(86330, 2013, 'plos', 'Actions, action sequences and habits: evidence that goal-directed and habitual action control are hierarchically organized', 'Dezfouli, Amir|Balleine, Bernard W', 'Brain & Mind Research Institute, University of Sydney, Sydney, New South Wales, Australia.|Brain & Mind Research Institute, University of Sydney, Sydney, New South Wales, Australia.', 'Australia|Australia', 0, 'Bayes Theorem|Decision Making|Goals|Humans|Motivation|Reaction Time', 'Journal Article', '10.1371/journal.pcbi.1003364', '24339762', 'Behavioral evidence suggests that instrumental conditioning is governed by two forms of action control: a goal-directed and a habit learning process. Model-based reinforcement learning (RL) has been argued to underlie the goal-directed process, however, the way in which it interacts with habits and the structure of the habitual process has remained unclear. According to a flat architecture, the habitual process corresponds to model-free RL, and its interaction with the goal-directed process is coordinated by an external arbitration mechanism. Alternatively, the interaction between these systems has recently been argued to be hierarchical, such that the formation of action sequences underlies habit learning and a goal-directed process selects between goal-directed actions and habitual sequences of actions to reach the goal. Here we used a two-stage decision-making task to test predictions from these accounts. The hierarchical account predicts that, because they are tied to each other as an action sequence, selecting a habitual action in the first stage will be followed by a habitual action in the second stage, whereas the flat account predicts that the statuses of the first and second stage actions are independent of each other. We found, based on subjects choices and reaction times, that human subjects combined single actions to build action sequences and that the formation of such action sequences was sufficient to explain habitual actions. Furthermore, based on Bayesian model comparison, a family of hierarchical RL models, assuming a hierarchical interaction between habit and goal-directed processes, provided a better fit of the subjects behavior than a family of flat models. Although these findings do not rule out all possible model-free accounts of instrumental conditioning, they do show such accounts are not necessary to explain habitual actions and provide a new basis for understanding how goal-directed and habitual action control interact.'),
(86331, 2013, 'plos', 'Designing molecular dynamics simulations to shift populations of the conformational states of calmodulin', 'Aykut, Ayse Ozlem|Atilgan, Ali Rana|Atilgan, Canan', 'Faculty of Engineering & Natural Sciences, Sabanci University Tuzla, Istanbul, Turkey.|Faculty of Engineering & Natural Sciences, Sabanci University Tuzla, Istanbul, Turkey.|Faculty of Engineering & Natural Sciences, Sabanci University Tuzla, Istanbul, Turkey.', 'Turkey|Turkey|Turkey', 0, 'Calmodulin|Molecular Dynamics Simulation|Osmolar Concentration|Protein Binding|Protein Conformation|Static Electricity|X-Ray Diffraction', 'Journal Article', '10.1371/journal.pcbi.1003366', '24339763', 'We elucidate the mechanisms that lead to population shifts in the conformational states of calcium-loaded calmodulin (Ca(2+)-CaM). We design extensive molecular dynamics simulations to classify the effects that are responsible for adopting occupied conformations available in the ensemble of NMR structures. Electrostatic interactions amongst the different regions of the protein and with its vicinal water are herein mediated by lowering the ionic strength or the pH. Amino acid E31, which is one of the few charged residues whose ionization state is highly sensitive to pH differences in the physiological range, proves to be distinctive in its control of population shifts. E31A mutation at low ionic strength results in a distinct change from an extended to a compact Ca(2+)-CaM conformation within tens of nanoseconds, that otherwise occur on the time scales of microseconds. The kinked linker found in this particular compact form is observed in many of the target-bound forms of Ca(2+)-CaM, increasing the binding affinity. This mutation is unique in controlling C-lobe dynamics by affecting the fluctuations between the EF-hand motif helices. We also monitor the effect of the ionic strength on the conformational multiplicity of Ca(2+)-CaM. By lowering the ionic strength, the tendency of nonspecific anions in water to accumulate near the protein surface increases, especially in the vicinity of the linker. The change in the distribution of ions in the vicinal layer of water allows N- and C- lobes to span a wide variety of relative orientations that are otherwise not observed at physiological ionic strength. E31 protonation restores the conformations associated with physiological environmental conditions even at low ionic strength. '),
(86332, 2013, 'plos', 'Understanding variation in transcription factor binding by modeling transcription factor genome-epigenome interactions', 'Chen, Chieh-Chun|Xiao, Shu|Xie, Dan|Cao, Xiaoyi|Song, Chun-Xiao|Wang, Ting|He, Chuan|Zhong, Sheng', 'Department of Bioengineering, University of Illinois at Urbana-Champaign, Urbana, Illinois, United States of America.|Department of Bioengineering, University of Illinois at Urbana-Champaign, Urbana, Illinois, United States of America.|Department of Bioengineering, University of Illinois at Urbana-Champaign, Urbana, Illinois, United States of America.|Department of Bioengineering, University of Illinois at Urbana-Champaign, Urbana, Illinois, United States of America.|Department of Bioengineering, University of Illinois at Urbana-Champaign, Urbana, Illinois, United States of America.|Department of Bioengineering, University of Illinois at Urbana-Champaign, Urbana, Illinois, United States of America.|Department of Bioengineering, University of Illinois at Urbana-Champaign, Urbana, Illinois, United States of America.|Department of Bioengineering, University of Illinois at Urbana-Champaign, Urbana, Illinois, United States of America.', 'United States|United States|United States|United States|United States|United States|United States|Un', 21, '5-Methylcytosine|Animals|Cytosine|DNA|Embryonic Stem Cells|Epigenomics|Genome|Histones|Mice|Models, Biological|Protein Binding|Transcription Factors', 'Journal Article', '10.1371/journal.pcbi.1003367', '24339764', 'Despite explosive growth in genomic datasets, the methods for studying epigenomic mechanisms of gene regulation remain primitive. Here we present a model-based approach to systematically analyze the epigenomic functions in modulating transcription factor-DNA binding. Based on the first principles of statistical mechanics, this model considers the interactions between epigenomic modifications and a cis-regulatory module, which contains multiple binding sites arranged in any configurations. We compiled a comprehensive epigenomic dataset in mouse embryonic stem (mES) cells, including DNA methylation (MeDIP-seq and MRE-seq), DNA hydroxymethylation (5-hmC-seq), and histone modifications (ChIP-seq). We discovered correlations of transcription factors (TFs) for specific combinations of epigenomic modifications, which we term epigenomic motifs. Epigenomic motifs explained why some TFs appeared to have different DNA binding motifs derived from in vivo (ChIP-seq) and in vitro experiments. Theoretical analyses suggested that the epigenome can modulate transcriptional noise and boost the cooperativity of weak TF binding sites. ChIP-seq data suggested that epigenomic boost of binding affinities in weak TF binding sites can function in mES cells. We showed in theory that the epigenome should suppress the TF binding differences on SNP-containing binding sites in two people. Using personal data, we identified strong associations between H3K4me2/H3K9ac and the degree of personal differences in NFxcexbaB binding in SNP-containing binding sites, which may explain why some SNPs introduce much smaller personal variations on TF binding than other SNPs. In summary, this model presents a powerful approach to analyze the functions of epigenomic modifications. This model was implemented into an open source program APEG (Affinity Prediction by Epigenome and Genome, http://systemsbio.ucsd.edu/apeg). '),
(86333, 2013, 'plos', 'Protein-protein interactions in a crowded environment: an analysis via cross-docking simulations and evolutionary information', 'Lopes, Anne|Sacquin-Mora, Sophie|Dimitrova, Viktoriya|Laine, Elodie|Ponty, Yann|Carbone, Alessandra', 'Université Pierre et Marie Curie, UMR 7238, Equipe de Génomique Analytique, Paris, France , CNRS, UMR 7238, Laboratoire de Génomique des Microorganismes, Paris, France.|Université Pierre et Marie Curie, UMR 7238, Equipe de Génomique Analytique, Paris, France , CNRS, UMR 7238, Laboratoire de Génomique des Microorganismes, Paris, France.|Université Pierre et Marie Curie, UMR 7238, Equipe de Génomique Analytique, Paris, France , CNRS, UMR 7238, Laboratoire de Génomique des Microorganismes, Paris, France.|Université Pierre et Marie Curie, UMR 7238, Equipe de Génomique Analytique, Paris, France , CNRS, UMR 7238, Laboratoire de Génomique des Microorganismes, Paris, France.|Université Pierre et Marie Curie, UMR 7238, Equipe de Génomique Analytique, Paris, France , CNRS, UMR 7238, Laboratoire de Génomique des Microorganismes, Paris, France.|Université Pierre et Marie Curie, UMR 7238, Equipe de Génomique Analytique, Paris, France , CNRS, UMR 7238, Laboratoire de Génomique des Microorganismes, Paris, France.', 'France|France|France|France|France|France', 0, 'Binding Sites|Evolution, Molecular|Molecular Docking Simulation|Protein Binding|Proteins', 'Journal Article', '10.1371/journal.pcbi.1003369', '24339765', 'Large-scale analyses of protein-protein interactions based on coarse-grain molecular docking simulations and binding site predictions resulting from evolutionary sequence analysis, are possible and realizable on hundreds of proteins with variate structures and interfaces. We demonstrated this on the 168 proteins of the Mintseris Benchmark 2.0. On the one hand, we evaluated the quality of the interaction signal and the contribution of docking information compared to evolutionary information showing that the combination of the two improves partner identification. On the other hand, since protein interactions usually occur in crowded environments with several competing partners, we realized a thorough analysis of the interactions of proteins with true partners but also with non-partners to evaluate whether proteins in the environment, competing with the true partner, affect its identification. We found three populations of proteins: strongly competing, never competing, and interacting with different levels of strength. Populations and levels of strength are numerically characterized and provide a signature for the behavior of a protein in the crowded environment. We showed that partner identification, to some extent, does not depend on the competing partners present in the environment, that certain biochemical classes of proteins are intrinsically easier to analyze than others, and that small proteins are not more promiscuous than large ones. Our approach brings to light that the knowledge of the binding site can be used to reduce the high computational cost of docking simulations with no consequence in the quality of the results, demonstrating the possibility to apply coarse-grain docking to datasets made of thousands of proteins. Comparison with all available large-scale analyses aimed to partner predictions is realized. We release the complete decoys set issued by coarse-grain docking simulations of both true and false interacting partners, and their evolutionary sequence analysis leading to binding site predictions. Download site: http://www.lgm.upmc.fr/CCDMintseris/ '),
(86334, 2013, 'plos', 'Handling uncertainty in dynamic models: the pentose phosphate pathway in Trypanosoma brucei', 'Kerkhoven, Eduard J|Achcar, Fiona|Alibu, Vincent P|Burchmore, Richard J|Gilbert, Ian H|Trybixc5x82o, Maciej|Driessen, Nicole N|Gilbert, David|Breitling, Rainer|Bakker, Barbara M|Barrett, Michael P', 'Wellcome Trust Centre for Molecular Parasitology, Institute of Infection, Immunity and Inflammation and Glasgow Polyomics, College of Medical, Veterinary and Life Sciences, University of Glasgow, Glasgow, United Kingdom , Systems and Synthetic Biology Group, Department of Chemical and Biological Engineering, Chalmers University of Technology, Gothenburg, Sweden.|Wellcome Trust Centre for Molecular Parasitology, Institute of Infection, Immunity and Inflammation and Glasgow Polyomics, College of Medical, Veterinary and Life Sciences, University of Glasgow, Glasgow, United Kingdom , Systems and Synthetic Biology Group, Department of Chemical and Biological Engineering, Chalmers University of Technology, Gothenburg, Sweden.|Wellcome Trust Centre for Molecular Parasitology, Institute of Infection, Immunity and Inflammation and Glasgow Polyomics, College of Medical, Veterinary and Life Sciences, University of Glasgow, Glasgow, United Kingdom , Systems and Synthetic Biology Group, Department of Chemical and Biological Engineering, Chalmers University of Technology, Gothenburg, Sweden.|Wellcome Trust Centre for Molecular Parasitology, Institute of Infection, Immunity and Inflammation and Glasgow Polyomics, College of Medical, Veterinary and Life Sciences, University of Glasgow, Glasgow, United Kingdom , Systems and Synthetic Biology Group, Department of Chemical and Biological Engineering, Chalmers University of Technology, Gothenburg, Sweden.|Wellcome Trust Centre for Molecular Parasitology, Institute of Infection, Immunity and Inflammation and Glasgow Polyomics, College of Medical, Veterinary and Life Sciences, University of Glasgow, Glasgow, United Kingdom , Systems and Synthetic Biology Group, Department of Chemical and Biological Engineering, Chalmers University of Technology, Gothenburg, Sweden.|Wellcome Trust Centre for Molecular Parasitology, Institute of Infection, Immunity and Inflammation and Glasgow Polyomics, College of Medical, Veterinary and Life Sciences, University of Glasgow, Glasgow, United Kingdom , Systems and Synthetic Biology Group, Department of Chemical and Biological Engineering, Chalmers University of Technology, Gothenburg, Sweden.|Wellcome Trust Centre for Molecular Parasitology, Institute of Infection, Immunity and Inflammation and Glasgow Polyomics, College of Medical, Veterinary and Life Sciences, University of Glasgow, Glasgow, United Kingdom , Systems and Synthetic Biology Group, Department of Chemical and Biological Engineering, Chalmers University of Technology, Gothenburg, Sweden.|Wellcome Trust Centre for Molecular Parasitology, Institute of Infection, Immunity and Inflammation and Glasgow Polyomics, College of Medical, Veterinary and Life Sciences, University of Glasgow, Glasgow, United Kingdom , Systems and Synthetic Biology Group, Department of Chemical and Biological Engineering, Chalmers University of Technology, Gothenburg, Sweden.|Wellcome Trust Centre for Molecular Parasitology, Institute of Infection, Immunity and Inflammation and Glasgow Polyomics, College of Medical, Veterinary and Life Sciences, University of Glasgow, Glasgow, United Kingdom , Systems and Synthetic Biology Group, Department of Chemical and Biological Engineering, Chalmers University of Technology, Gothenburg, Sweden.|Wellcome Trust Centre for Molecular Parasitology, Institute of Infection, Immunity and Inflammation and Glasgow Polyomics, College of Medical, Veterinary and Life Sciences, University of Glasgow, Glasgow, United Kingdom , Systems and Synthetic Biology Group, Department of Chemical and Biological Engineering, Chalmers University of Technology, Gothenburg, Sweden.|Wellcome Trust Centre for Molecular Parasitology, Institute of Infection, Immunity and Inflammation and Glasgow Polyomics, College of Medical, Veterinary and Life Sciences, University of Glasgow, Glasgow, United Kingdom , Systems and Synthetic Biology Group, Department of Chemical and Biological Engineering, Chalmers University of Technology, Gothenburg, Sweden.', 'United Kingdom|United Kingdom|United Kingdom|United Kingdom|United Kingdom|United Kingdom|United Kin', 30, 'Animals|Glucose|Glycolysis|Models, Biological|Pentose Phosphate Pathway|RNA Interference|Trypanosoma brucei brucei|Uncertainty', 'Journal Article', '10.1371/journal.pcbi.1003371', '24339766', 'Dynamic models of metabolism can be useful in identifying potential drug targets, especially in unicellular organisms. A model of glycolysis in the causative agent of human African trypanosomiasis, Trypanosoma brucei, has already shown the utility of this approach. Here we add the pentose phosphate pathway (PPP) of T. brucei to the glycolytic model. The PPP is localized to both the cytosol and the glycosome and adding it to the glycolytic model without further adjustments leads to a draining of the essential bound-phosphate moiety within the glycosome. This phosphate leak must be resolved for the model to be a reasonable representation of parasite physiology. Two main types of theoretical solution to the problem could be identified: (i) including additional enzymatic reactions in the glycosome, or (ii) adding a mechanism to transfer bound phosphates between cytosol and glycosome. One example of the first type of solution would be the presence of a glycosomal ribokinase to regenerate ATP from ribose 5-phosphate and ADP. Experimental characterization of ribokinase in T. brucei showed that very low enzyme levels are sufficient for parasite survival, indicating that other mechanisms are required in controlling the phosphate leak. Examples of the second type would involve the presence of an ATP:ADP exchanger or recently described permeability pores in the glycosomal membrane, although the current absence of identified genes encoding such molecules impedes experimental testing by genetic manipulation. Confronted with this uncertainty, we present a modeling strategy that identifies robust predictions in the context of incomplete system characterization. We illustrate this strategy by exploring the mechanism underlying the essential function of one of the PPP enzymes, and validate it by confirming the model predictions experimentally. '),
(86335, 2013, 'plos', 'A network inference method for large-scale unsupervised identification of novel drug-drug interactions', 'Guimerà, Roger|Sales-Pardo, Marta', 'Institució Catalana de Recerca i Estudis Avançats (ICREA), Barcelona, Catalonia, Spain , Departament dEnginyeria Química, Universitat Rovira i Virgili, Tarragona, Catalonia, Spain.|Institució Catalana de Recerca i Estudis Avançats (ICREA), Barcelona, Catalonia, Spain , Departament dEnginyeria Química, Universitat Rovira i Virgili, Tarragona, Catalonia, Spain.', 'Spain|Spain', 29, 'Algorithms|Database Management Systems|Drug Discovery|Drug Interactions|Models, Theoretical', 'Journal Article', '10.1371/journal.pcbi.1003374', '24339767', 'Characterizing interactions between drugs is important to avoid potentially harmful combinations, to reduce off-target effects of treatments and to fight antibiotic resistant pathogens, among others. Here we present a network inference algorithm to predict uncharacterized drug-drug interactions. Our algorithm takes, as its only input, sets of previously reported interactions, and does not require any pharmacological or biochemical information about the drugs, their targets or their mechanisms of action. Because the models we use are abstract, our approach can deal with adverse interactions, synergistic/antagonistic/suppressing interactions, or any other type of drug interaction. We show that our method is able to accurately predict interactions, both in exhaustive pairwise interaction data between small sets of drugs, and in large-scale databases. We also demonstrate that our algorithm can be used efficiently to discover interactions of new drugs as part of the drug discovery process. '),
(86336, 2013, 'plos', 'Detecting genetic association of common human facial morphological variation using high density 3D image registration', 'Peng, Shouneng|Tan, Jingze|Hu, Sile|Zhou, Hang|Guo, Jing|Jin, Li|Tang, Kun', 'Human Functional Genetic Variation Group, CAS-MPG Partner Institute for Computational Biology, SIBS, Shanghai, China.|Human Functional Genetic Variation Group, CAS-MPG Partner Institute for Computational Biology, SIBS, Shanghai, China.|Human Functional Genetic Variation Group, CAS-MPG Partner Institute for Computational Biology, SIBS, Shanghai, China.|Human Functional Genetic Variation Group, CAS-MPG Partner Institute for Computational Biology, SIBS, Shanghai, China.|Human Functional Genetic Variation Group, CAS-MPG Partner Institute for Computational Biology, SIBS, Shanghai, China.|Human Functional Genetic Variation Group, CAS-MPG Partner Institute for Computational Biology, SIBS, Shanghai, China.|Human Functional Genetic Variation Group, CAS-MPG Partner Institute for Computational Biology, SIBS, Shanghai, China.', 'China|China|China|China|China|China|China', 40, 'Face|Humans|Imaging, Three-Dimensional|Models, Anatomic|Polymorphism, Single Nucleotide', 'Journal Article', '10.1371/journal.pcbi.1003375', '24339768', 'Human facial morphology is a combination of many complex traits. Little is known about the genetic basis of common facial morphological variation. Existing association studies have largely used simple landmark-distances as surrogates for the complex morphological phenotypes of the face. However, this can result in decreased statistical power and unclear inference of shape changes. In this study, we applied a new image registration approach that automatically identified the salient landmarks and aligned the sample faces using high density pixel points. Based on this high density registration, three different phenotype data schemes were used to test the association between the common facial morphological variation and 10 candidate SNPs, and their performances were compared. The first scheme used traditional landmark-distances, the second relied on the geometric analysis of 15 landmarks and the third used geometric analysis of a dense registration of xe2x88xbc30,000 3D points. We found that the two geometric approaches were highly consistent in their detection of morphological changes. The geometric method using dense registration further demonstrated superiority in the fine inference of shape changes and 3D face modeling. Several candidate SNPs showed potential associations with different facial features. In particular, one SNP, a known risk factor of non-syndromic cleft lips/palates, rs642961 in the IRF6 gene, was validated to strongly predict normal lip shape variation in female Han Chinese. This study further demonstrated that dense face registration may substantially improve the detection and characterization of genetic association in common facial variation. '),
(86337, 2013, 'plos', 'Extrapolating weak selection in evolutionary games', 'Wu, Bin|García, Julián|Hauert, Christoph|Traulsen, Arne', 'Evolutionary Theory Group, Max-Planck-Institute for Evolutionary Biology, Plön, Germany.|Evolutionary Theory Group, Max-Planck-Institute for Evolutionary Biology, Plön, Germany.|Evolutionary Theory Group, Max-Planck-Institute for Evolutionary Biology, Plön, Germany.|Evolutionary Theory Group, Max-Planck-Institute for Evolutionary Biology, Plön, Germany.', 'Germany|Germany|Germany|Germany', 0, 'Evolution, Molecular|Models, Theoretical|Reproduction|Selection, Genetic', 'Journal Article', '10.1371/journal.pcbi.1003381', '24339769', 'In evolutionary games, reproductive success is determined by payoffs. Weak selection means that even large differences in game outcomes translate into small fitness differences. Many results have been derived using weak selection approximations, in which perturbation analysis facilitates the derivation of analytical results. Here, we ask whether results derived under weak selection are also qualitatively valid for intermediate and strong selection. By qualitatively valid we mean that the ranking of strategies induced by an evolutionary process does not change when the intensity of selection increases. For two-strategy games, we show that the ranking obtained under weak selection cannot be carried over to higher selection intensity if the number of players exceeds two. For games with three (or more) strategies, previous examples for multiplayer games have shown that the ranking of strategies can change with the intensity of selection. In particular, rank changes imply that the most abundant strategy at one intensity of selection can become the least abundant for another. We show that this applies already to pairwise interactions for a broad class of evolutionary processes. Even when both weak and strong selection limits lead to consistent predictions, rank changes can occur for intermediate intensities of selection. To analyze how common such games are, we show numerically that for randomly drawn two-player games with three or more strategies, rank changes frequently occur and their likelihood increases rapidly with the number of strategies [Formula: see text]. In particular, rank changes are almost certain for [Formula: see text], which jeopardizes the predictive power of results derived for weak selection. '),
(86338, 2013, 'plos', 'Cortical and hippocampal correlates of deliberation during model-based decisions for rewards in humans', 'Bornstein, Aaron M|Daw, Nathaniel D', 'Department of Psychology, Program in Cognition and Perception, New York University, New York, New York, United States of America.|Department of Psychology, Program in Cognition and Perception, New York University, New York, New York, United States of America.', 'United States|United States', 0, 'Cerebral Cortex|Decision Making|Hippocampus|Humans|Magnetic Resonance Imaging|Models, Psychological|Motivation', 'Journal Article', '10.1371/journal.pcbi.1003387', '24339770', 'How do we use our memories of the past to guide decisions weve never had to make before? Although extensive work describes how the brain learns to repeat rewarded actions, decisions can also be influenced by associations between stimuli or events not directly involving reward - such as when planning routes using a cognitive map or chess moves using predicted countermoves - and these sorts of associations are critical when deciding among novel options. This process is known as model-based decision making. While the learning of environmental relations that might support model-based decisions is well studied, and separately this sort of information has been inferred to impact decisions, there is little evidence concerning the full cycle by which such associations are acquired and drive choices. Of particular interest is whether decisions are directly supported by the same mnemonic systems characterized for relational learning more generally, or instead rely on other, specialized representations. Here, building on our previous work, which isolated dual representations underlying sequential predictive learning, we directly demonstrate that one such representation, encoded by the hippocampal memory system and adjacent cortical structures, supports goal-directed decisions. Using interleaved learning and decision tasks, we monitor predictive learning directly and also trace its influence on decisions for reward. We quantitatively compare the learning processes underlying multiple behavioral and fMRI observables using computational model fits. Across both tasks, a quantitatively consistent learning process explains reaction times, choices, and both expectation- and surprise-related neural activity. The same hippocampal and ventral stream regions engaged in anticipating stimuli during learning are also engaged in proportion to the difficulty of decisions. These results support a role for predictive associations learned by the hippocampal memory system to be recalled during choice formation. '),
(86339, 2013, 'plos', 'Heterogeneity, mixing, and the spatial scales of mosquito-borne pathogen transmission', 'Perkins, T Alex|Scott, Thomas W|Le Menach, Arnaud|Smith, David L', 'Fogarty International Center, National Institutes of Health, Bethesda, Maryland, United States of America , Department of Entomology, University of California, Davis, California, United States of America.|Fogarty International Center, National Institutes of Health, Bethesda, Maryland, United States of America , Department of Entomology, University of California, Davis, California, United States of America.|Center for Disease Dynamics, Economics and Policy, Washington, D.C., United States of America.|Fogarty International Center, National Institutes of Health, Bethesda, Maryland, United States of America , Center for Disease Dynamics, Economics and Policy, Washington, D.C., United States of America , Department of Epidemiology, Johns Hopkins Bloomberg School of Public Health, Baltimore, Maryland, United States of America.', 'United States|United States|United States|United States', 83, 'Animals|Communicable Diseases|Culicidae|Disease Outbreaks|Host-Pathogen Interactions|Humans|Insect Vectors', 'Journal Article', '10.1371/journal.pcbi.1003327', '24348223', 'The Ross-Macdonald model has dominated theory for mosquito-borne pathogen transmission dynamics and control for over a century. The model, like many other basic population models, makes the mathematically convenient assumption that populations are well mixed, i.e., that each mosquito is equally likely to bite any vertebrate host. This assumption raises questions about the validity and utility of current theory because it is in conflict with preponderant empirical evidence that transmission is heterogeneous. Here, we propose a new dynamic framework that is realistic enough to describe biological causes of heterogeneous transmission of mosquito-borne pathogens of humans, yet tractable enough to provide a basis for developing and improving general theory. The framework is based on the ecological context of mosquito blood meals and the fine-scale movements of individual mosquitoes and human hosts that give rise to heterogeneous transmission. Using this framework, we describe pathogen dispersion in terms of individual-level analogues of two classical quantities: vectorial capacity and the basic reproductive number, R0. Importantly, this framework explicitly accounts for three key components of overall heterogeneity in transmission: heterogeneous exposure, poor mixing, and finite host numbers. Using these tools, we propose two ways of characterizing the spatial scales of transmission--pathogen dispersion kernels and the evenness of mixing across scales of aggregation--and demonstrate the consequences of a models choice of spatial scale for epidemic dynamics and for estimation of R0, both by a priori model formulas and by inference of the force of infection from time-series data.'),
(86340, 2013, 'plos', 'Next-generation sequence assembly: four stages of data processing and computational challenges', 'El-Metwally, Sara|Hamza, Taher|Zakaria, Magdi|Helmy, Mohamed', 'Computer Science Department, Faculty of Computers and Information, Mansoura University, Mansoura, Egypt.|Computer Science Department, Faculty of Computers and Information, Mansoura University, Mansoura, Egypt.|Computer Science Department, Faculty of Computers and Information, Mansoura University, Mansoura, Egypt.|Botany Department, Faculty of Agriculture, Al-Azhar University, Cairo, Egypt , Biotechnology Department, Faculty of Agriculture, Al-Azhar University, Cairo, Egypt.', 'Egypt|Egypt|Egypt|Egypt', 0, 'Algorithms|Base Sequence|DNA|Genome|Sequence Alignment|Sequence Analysis, DNA|Software', 'Journal Article', '10.1371/journal.pcbi.1003345', '24348224', 'Decoding DNA symbols using next-generation sequencers was a major breakthrough in genomic research. Despite the many advantages of next-generation sequencers, e.g., the high-throughput sequencing rate and relatively low cost of sequencing, the assembly of the reads produced by these sequencers still remains a major challenge. In this review, we address the basic framework of next-generation genome sequence assemblers, which comprises four basic stages: preprocessing filtering, a graph construction process, a graph simplification process, and postprocessing filtering. Here we discuss them as a framework of four stages for data analysis and processing and survey variety of techniques, algorithms, and software tools used during each stage. We also discuss the challenges that face current assemblers in the next-generation environment to determine the current state-of-the-art. We recommend a layered architecture approach for constructing a general assembler that can handle the sequences generated by different sequencing platforms. '),
(86341, 2013, 'plos', 'Epidemic spread on weighted networks', 'Kamp, Christel|Moslonka-Lefebvre, Mathieu|Alizon, Samuel', 'Paul-Ehrlich-Institut, Federal Institute for Vaccines and Biomedicines, Langen, Germany.|INRA, UR 0341 Mathématiques et Informatique Appliquées, Jouy-en-Josas, France , AgroParisTech, F-75005 Paris, France.|Laboratoire MIVEGEC (UMR CNRS 5290, IRD 224, UM1, UM2), Montpellier, France.', 'Germany|France|France', 37, 'Disease Outbreaks|Epidemiologic Studies|Humans|Models, Theoretical|Sexually Transmitted Diseases', 'Journal Article', '10.1371/journal.pcbi.1003352', '24348225', 'The contact structure between hosts shapes disease spread. Most network-based models used in epidemiology tend to ignore heterogeneity in the weighting of contacts between two individuals. However, this assumption is known to be at odds with the data for many networks (e.g. sexual contact networks) and to have a critical influence on epidemics behavior. One of the reasons why models usually ignore heterogeneity in transmission is that we currently lack tools to analyze weighted networks, such that most studies rely on numerical simulations. Here, we present a novel framework to estimate key epidemiological variables, such as the rate of early epidemic expansion (r0) and the basic reproductive ratio (R0), from joint probability distributions of number of partners (contacts) and number of interaction events through which contacts are weighted. These distributions are much easier to infer than the exact shape of the network, which makes the approach widely applicable. The framework also allows for a derivation of the full time course of epidemic prevalence and contact behaviour, which we validate with numerical simulations on networks. Overall, incorporating more realistic contact networks into epidemiological models can improve our understanding of the emergence and spread of infectious diseases.'),
(86342, 2013, 'plos', 'Metabolic constraint-based refinement of transcriptional regulatory networks', 'Chandrasekaran, Sriram|Price, Nathan D', 'Institute for Systems Biology, Seattle, Washington, United States of America , Center for Biophysics and Computational Biology, University of Illinois, Urbana-Champaign, Illinois, United States of America.|Institute for Systems Biology, Seattle, Washington, United States of America , Center for Biophysics and Computational Biology, University of Illinois, Urbana-Champaign, Illinois, United States of America.', 'United States|United States', 19, 'Gene Expression Regulation|Gene Regulatory Networks|Metabolism|Phenotype|Transcription, Genetic|Yeasts', 'Journal Article', '10.1371/journal.pcbi.1003370', '24348226', 'There is a strong need for computational frameworks that integrate different biological processes and data-types to unravel cellular regulation. Current efforts to reconstruct transcriptional regulatory networks (TRNs) focus primarily on proximal data such as gene co-expression and transcription factor (TF) binding. While such approaches enable rapid reconstruction of TRNs, the overwhelming combinatorics of possible networks limits identification of mechanistic regulatory interactions. Utilizing growth phenotypes and systems-level constraints to inform regulatory network reconstruction is an unmet challenge. We present our approach Gene Expression and Metabolism Integrated for Network Inference (GEMINI) that links a compendium of candidate regulatory interactions with the metabolic network to predict their systems-level effect on growth phenotypes. We then compare predictions with experimental phenotype data to select phenotype-consistent regulatory interactions. GEMINI makes use of the observation that only a small fraction of regulatory network states are compatible with a viable metabolic network, and outputs a regulatory network that is simultaneously consistent with the input genome-scale metabolic network model, gene expression data, and TF knockout phenotypes. GEMINI preferentially recalls gold-standard interactions (p-value = 10(-172)), significantly better than using gene expression alone. We applied GEMINI to create an integrated metabolic-regulatory network model for Saccharomyces cerevisiae involving 25,000 regulatory interactions controlling 1597 metabolic reactions. The model quantitatively predicts TF knockout phenotypes in new conditions (p-value = 10(-14)) and revealed potential condition-specific regulatory mechanisms. Our results suggest that a metabolic constraint-based approach can be successfully used to help reconstruct TRNs from high-throughput data, and highlights the potential of using a biochemically-detailed mechanistic framework to integrate and reconcile inconsistencies across different data-types. The algorithm and associated data are available at https://sourceforge.net/projects/gemini-data/'),
(86343, 2013, 'plos', 'Decipher the mechanisms of protein conformational changes induced by nucleotide binding through free-energy landscape analysis: ATP binding to Hsp70', 'Nicolaï, Adrien|Delarue, Patrice|Senet, Patrick', 'Laboratoire Interdisciplinaire Carnot de Bourgogne, UMR 6303 CNRS-Université de Bourgogne, Dijon, France.|Laboratoire Interdisciplinaire Carnot de Bourgogne, UMR 6303 CNRS-Université de Bourgogne, Dijon, France.|Laboratoire Interdisciplinaire Carnot de Bourgogne, UMR 6303 CNRS-Université de Bourgogne, Dijon, France.', 'France|France|France', 0, 'Adenosine Triphosphate|Escherichia coli Proteins|HSP70 Heat-Shock Proteins|Molecular Dynamics Simulation|Nuclear Magnetic Resonance, Biomolecular|Protein Binding|Protein Conformation', 'Journal Article', '10.1371/journal.pcbi.1003379', '24348227', 'ATP regulates the function of many proteins in the cell by transducing its binding and hydrolysis energies into protein conformational changes by mechanisms which are challenging to identify at the atomic scale. Based on molecular dynamics (MD) simulations, a method is proposed to analyze the structural changes induced by ATP binding to a protein by computing the effective free-energy landscape (FEL) of a subset of its coordinates along its amino-acid sequence. The method is applied to characterize the mechanism by which the binding of ATP to the nucleotide-binding domain (NBD) of Hsp70 propagates a signal to its substrate-binding domain (SBD). Unbiased MD simulations were performed for Hsp70-DnaK chaperone in nucleotide-free, ADP-bound and ATP-bound states. The simulations revealed that the SBD does not interact with the NBD for DnaK in its nucleotide-free and ADP-bound states whereas the docking of the SBD was found in the ATP-bound state. The docked state induced by ATP binding found in MD is an intermediate state between the initial nucleotide-free and final ATP-bound states of Hsp70. The analysis of the FEL projected along the amino-acid sequence permitted to identify a subset of 27 protein internal coordinates corresponding to a network of 91 key residues involved in the conformational change induced by ATP binding. Among the 91 residues, 26 are identified for the first time, whereas the others were shown relevant for the allosteric communication of Hsp70 s in several experiments and bioinformatics analysis. The FEL analysis revealed also the origin of the ATP-induced structural modifications of the SBD recently measured by Electron Paramagnetic Resonance. The pathway between the nucleotide-free and the intermediate state of DnaK was extracted by applying principal component analysis to the subset of internal coordinates describing the transition. The methodology proposed is general and could be applied to analyze allosteric communication in other proteins. '),
(86344, 2013, 'plos', 'Time scales in epigenetic dynamics and phenotypic heterogeneity of embryonic stem cells', 'Sasai, Masaki|Kawabata, Yudai|Makishi, Koh|Itoh, Kazuhito|Terada, Tomoki P', 'Department of Computational Science and Engineering, Nagoya University, Nagoya, Japan , Department of Applied Physics, Nagoya University, Nagoya, Japan , School of Computational Sciences, Korea Institute for Advanced Study, Seoul, Korea , Okazaki Institute for Integrative Bioscience, Okazaki, Japan.|Department of Applied Physics, Nagoya University, Nagoya, Japan.|Department of Computational Science and Engineering, Nagoya University, Nagoya, Japan.|Department of Computational Science and Engineering, Nagoya University, Nagoya, Japan.|Department of Computational Science and Engineering, Nagoya University, Nagoya, Japan , Department of Applied Physics, Nagoya University, Nagoya, Japan.', 'Japan|Japan|Japan|Japan|Japan', 32, 'Animals|Embryonic Stem Cells|Epigenesis, Genetic|Gene Regulatory Networks|Mice|Phenotype|Stochastic Processes', 'Journal Article', '10.1371/journal.pcbi.1003380', '24348228', 'A remarkable feature of the self-renewing population of embryonic stem cells (ESCs) is their phenotypic heterogeneity: Nanog and other marker proteins of ESCs show large cell-to-cell variation in their expression level, which should significantly influence the differentiation process of individual cells. The molecular mechanism and biological implication of this heterogeneity, however, still remain elusive. We address this problem by constructing a model of the core gene-network of mouse ESCs. The model takes account of processes of binding/unbinding of transcription factors, formation/dissolution of transcription apparatus, and modification of histone code at each locus of genes in the network. These processes are hierarchically interrelated to each other forming the dynamical feedback loops. By simulating stochastic dynamics of this model, we show that the phenotypic heterogeneity of ESCs can be explained when the chromatin at the Nanog locus undergoes the large scale reorganization in formation/dissolution of transcription apparatus, which should have the timescale similar to the cell cycle period. With this slow transcriptional switching of Nanog, the simulated ESCs fluctuate among multiple transient states, which can trigger the differentiation into the lineage-specific cell states. From the simulated transitions among cell states, the epigenetic landscape underlying transitions is calculated. The slow Nanog switching gives rise to the wide basin of ESC states in the landscape. The bimodal Nanog distribution arising from the kinetic flow running through this ESC basin prevents transdifferentiation and promotes the definite decision of the cell fate. These results show that the distribution of timescales of the regulatory processes is decisively important to characterize the fluctuation of cells and their differentiation process. The analyses through the epigenetic landscape and the kinetic flow on the landscape should provide a guideline to engineer cell differentiation. ');
