INSERT INTO `papers` (`id`, `ano`, `journal`, `titulo`, `autores`, `afiliacao`, `pais`, `citacoes`, `palavra_chave`, `categorias`, `doi`, `pubmed`, `abstract`) VALUES
(86504, 2014, 'plos', 'Chemical, target, and bioactive properties of allosteric modulation', 'van Westen, Gerard J P|Gaulton, Anna|Overington, John P', 'ChEMBL Group, European Molecular Biology Laboratory, European Bioinformatics Institute (EMBL-EBI), Hinxton, United Kingdom.|ChEMBL Group, European Molecular Biology Laboratory, European Bioinformatics Institute (EMBL-EBI), Hinxton, United Kingdom.|ChEMBL Group, European Molecular Biology Laboratory, European Bioinformatics Institute (EMBL-EBI), Hinxton, United Kingdom.', 'United Kingdom|United Kingdom|United Kingdom', 51, 'Allosteric Regulation|Databases, Chemical|Ligands|Models, Chemical|Molecular Weight', 'Journal Article', '10.1371/journal.pcbi.1003559', '24699297', 'Allosteric modulators are ligands for proteins that exert their effects via a different binding site than the natural (orthosteric) ligand site and hence form a conceptually distinct class of ligands for a target of interest. Here, the physicochemical and structural features of a large set of allosteric and non-allosteric ligands from the ChEMBL database of bioactive molecules are analyzed. In general allosteric modulators are relatively smaller, more lipophilic and more rigid compounds, though large differences exist between different targets and target classes. Furthermore, there are differences in the distribution of targets that bind these allosteric modulators. Allosteric modulators are over-represented in membrane receptors, ligand-gated ion channels and nuclear receptor targets, but are underrepresented in enzymes (primarily proteases and kinases). Moreover, allosteric modulators tend to bind to their targets with a slightly lower potency (5.96 log units versus 6.66 log units, p<0.01). However, this lower absolute affinity is compensated by their lower molecular weight and more lipophilic nature, leading to similar binding efficiency and surface efficiency indices. Subsequently a series of classifier models are trained, initially target class independent models followed by finer-grained target (architecture/functional class) based models using the target hierarchy of the ChEMBL database. Applications of these insights include the selection of likely allosteric modulators from existing compound collections, the design of novel chemical libraries biased towards allosteric regulators and the selection of targets potentially likely to yield allosteric modulators on screening. All data sets used in the paper are available for download. '),
(86505, 2014, 'plos', 'Use of long term molecular dynamics simulation in predicting cancer associated SNPs', 'Kumar, Ambuj|Purohit, Rituraj', 'Bioinformatics Division, School of Bio Sciences and Technology, Vellore Institute of Technology University, Vellore, Tamil Nadu, India.|Bioinformatics Division, School of Bio Sciences and Technology, Vellore Institute of Technology University, Vellore, Tamil Nadu, India.', 'India|India', 64, 'Carcinoma, Hepatocellular|Humans|Liver Neoplasms|Molecular Dynamics Simulation|Mutation|Polymorphism, Single Nucleotide', 'Journal Article', '10.1371/journal.pcbi.1003318', '24722014', 'Computational prediction of cancer associated SNPs from the large pool of SNP dataset is now being used as a tool for detecting the probable oncogenes, which are further examined in the wet lab experiments. The lack in prediction accuracy has been a major hurdle in relying on the computational results obtained by implementing multiple tools, platforms and algorithms for cancer associated SNP prediction. Our result obtained from the initial computational compilations suggests the strong chance of Aurora-A G325W mutation (rs11539196) to cause hepatocellular carcinoma. The implementation of molecular dynamics simulation (MDS) approaches has significantly aided in raising the prediction accuracy of these results, but measuring the difference in the convergence time of mutant protein structures has been a challenging task while setting the simulation timescale. The convergence time of most of the protein structures may vary from 10 ns to 100 ns or more, depending upon its size. Thus, in this work we have implemented 200 ns of MDS to aid the final results obtained from computational SNP prediction technique. The MDS results have significantly explained the atomic alteration related with the mutant protein and are useful in elaborating the change in structural conformations coupled with the computationally predicted cancer associated mutation. With further advancements in the computational techniques, it will become much easier to predict such mutations with higher accuracy level. '),
(86506, 2014, 'plos', 'A quick guide to genomics and bioinformatics training for clinical and public audiences', 'Brazas, Michelle D|Lewitter, Fran|Schneider, Maria Victoria|van Gelder, Celia W G|Palagi, Patricia M', 'Ontario Institute for Cancer Research, Toronto, Canada.|Whitehead Institute for Biomedical Research, Massachusetts Institute of Technology, Cambridge, United States of America.|The Genome Analysis Centre, Norwich, United Kingdom.|Netherlands Bioinformatics Centre and Department of Bioinformatics, Radboud Medical Center, Nijmegen, The Netherlands.|SIB Swiss Institute of Bioinformatics, Geneva, Switzerland.', 'Canada|United States|United Kingdom|Netherlands|Switzerland', 10, 'Community Participation|Computational Biology|Genomics|Guidelines as Topic|Health Personnel|Needs Assessment', 'Journal Article', '10.1371/journal.pcbi.1003510', '24722068', '-'),
(86507, 2014, 'plos', 'Dynamics of cellular responses to radiation', 'Wodarz, Dominik|Sorace, Ron|Komarova, Natalia L', 'Department of Ecology and Evolutionary Biology, University of California, Irvine, California, United States of America, Department of Mathematics, Rowland Hall, University of California, Irvine, California, United States of America.|Department of Mathematics, Rowland Hall, University of California, Irvine, California, United States of America.|Department of Ecology and Evolutionary Biology, University of California, Irvine, California, United States of America, Department of Mathematics, Rowland Hall, University of California, Irvine, California, United States of America.', 'United States|United States|United States', 10, 'Cell Communication|Cells|Dose-Response Relationship, Radiation|Models, Theoretical|Radiation Tolerance', 'Journal Article', '10.1371/journal.pcbi.1003513', '24722167', 'Understanding the consequences of exposure to low dose ionizing radiation is an important public health concern. While the risk of low dose radiation has been estimated by extrapolation from data at higher doses according to the linear non-threshold model, it has become clear that cellular responses can be very different at low compared to high radiation doses. Important phenomena in this respect include radioadaptive responses as well as low-dose hyper-radiosensitivity (HRS) and increased radioresistance (IRR). With radioadaptive responses, low dose exposure can protect against subsequent challenges, and two mechanisms have been suggested: an intracellular mechanism, inducing cellular changes as a result of the priming radiation, and induction of a protected state by inter-cellular communication. We use mathematical models to examine the effect of these mechanisms on cellular responses to low dose radiation. We find that the intracellular mechanism can account for the occurrence of radioadaptive responses. Interestingly, the same mechanism can also explain the existence of the HRS and IRR phenomena, and successfully describe experimentally observed dose-response relationships for a variety of cell types. This indicates that different, seemingly unrelated, low dose phenomena might be connected and driven by common core processes. With respect to the inter-cellular communication mechanism, we find that it can also account for the occurrence of radioadaptive responses, indicating redundancy in this respect. The model, however, also suggests that the communication mechanism can be vital for the long term survival of cell populations that are continuously exposed to relatively low levels of radiation, which cannot be achieved with the intracellular mechanism in our model. Experimental tests to address our model predictions are proposed. '),
(86508, 2014, 'plos', 'Optimal schedules of light exposure for rapidly correcting circadian misalignment', 'Serkh, Kirill|Forger, Daniel B', 'Department of Applied Mathematics, Graduate School of Arts & Sciences, Yale University, New Haven, Connecticut, United States of America, Department of Mathematics, University of Michigan, Ann Arbor, Michigan, United States of America.|Department of Mathematics, University of Michigan, Ann Arbor, Michigan, United States of America, Computational Medicine and Bioinformatics, University of Michigan, Ann Arbor, Michigan, United States of America.', 'United States|United States', 39, 'Chronobiology Disorders|Circadian Rhythm|Humans|Light|Phototherapy', 'Journal Article', '10.1371/journal.pcbi.1003523', '24722195', 'Jet lag arises from a misalignment of circadian biological timing with the timing of human activity, and is caused by rapid transmeridian travel. Jet lags symptoms, such as depressed cognitive alertness, also arise from work and social schedules misaligned with the timing of the circadian clock. Using experimentally validated mathematical models, we develop a new methodology to find mathematically optimal schedules of light exposure and avoidance for rapidly re-entraining the human circadian system. In simulations, our schedules are found to significantly outperform other recently proposed schedules. Moreover, our schedules appear to be significantly more robust to both noise in light and to inter-individual variations in endogenous circadian period than other proposed schedules. By comparing the optimal schedules for thousands of different situations, and by using general mathematical arguments, we are also able to translate our findings into general principles of optimal circadian re-entrainment. These principles include: 1) a class of schedules where circadian amplitude is only slightly perturbed, optimal for dim light and for small shifts 2) another class of schedules where shifting occurs along the shortest path in phase-space, optimal for bright light and for large shifts 3) the determination that short light pulses are less effective than sustained light if the goal is to re-entrain quickly, and 4) the determination that length of daytime should be significantly shorter when delaying the clock than when advancing it. '),
(86509, 2014, 'plos', 'Biophysical properties of intrinsically disordered p130Cas substrate domain--implication in mechanosensing', 'Hotta, Kinya|Ranganathan, Soumya|Liu, Ruchuan|Wu, Fei|Machiyama, Hiroaki|Gao, Rong|Hirata, Hiroaki|Soni, Neelesh|Ohe, Takashi|Hogue, Christopher W V|Madhusudhan, M S|Sawada, Yasuhiro', 'Department of Biological Sciences, National University of Singapore, Singapore, School of Biosciences, The University of Nottingham Malaysia Campus, Selangor, Malaysia.|Department of Biological Sciences, National University of Singapore, Singapore, Mechanobiology Institute, National University of Singapore, Singapore.|Mechanobiology Institute, National University of Singapore, Singapore, Department of Physics, National University of Singapore, Singapore.|Department of Physics, National University of Singapore, Singapore.|Department of Biological Sciences, National University of Singapore, Singapore, Mechanobiology Institute, National University of Singapore, Singapore.|Department of Biological Sciences, National University of Singapore, Singapore, Mechanobiology Institute, National University of Singapore, Singapore.|Mechanobiology Institute, National University of Singapore, Singapore.|Indian Institute of Science Education and Research, Pune, India.|Locomotive Syndrome Research Institute, Nadogaya Hospital, Kashiwa, Japan.|Department of Biological Sciences, National University of Singapore, Singapore, Mechanobiology Institute, National University of Singapore, Singapore.|Department of Biological Sciences, National University of Singapore, Singapore, Indian Institute of Science Education and Research, Pune, India, Bioinformatics Institute, Singapore.|Department of Biological Sciences, National University of Singapore, Singapore, Mechanobiology Institute, National University of Singapore, Singapore, Locomotive Syndrome Research Institute, Nadogaya Hospital, Kashiwa, Japan.', 'Malaysia|Singapore|Singapore|Singapore|Singapore|Singapore|Singapore|India|Japan|Singapore|India|Jap', 12, 'Biophysics|Crk-Associated Substrate Protein|Intrinsically Disordered Proteins|Mechanotransduction, Cellular|Microscopy, Atomic Force|Protein Unfolding', 'Journal Article', '10.1371/journal.pcbi.1003532', '24722239', 'Mechanical stretch-induced tyrosine phosphorylation in the proline-rich 306-residue substrate domain (CasSD) of p130Cas (or BCAR1) has eluded an experimentally validated structural understanding. Cellular p130Cas tyrosine phosphorylation is shown to function in areas without internal actomyosin contractility, sensing force at the leading edge of cell migration. Circular dichroism shows CasSD is intrinsically disordered with dominant polyproline type II conformations. Strongly conserved in placental mammals, the proline-rich sequence exhibits a pseudo-repeat unit with variation hotspots 2-9 residues before substrate tyrosine residues. Atomic-force microscopy pulling experiments show CasSD requires minimal extension force and exhibits infrequent, random regions of weak stability. Proteolysis, light scattering and ultracentrifugation results show that a monomeric intrinsically disordered form persists for CasSD in solution with an expanded hydrodynamic radius. All-atom 3D conformer sampling with the TraDES package yields ensembles in agreement with experiment when coil-biased sampling is used, matching the experimental radius of gyration. Increasing xcexb2-sampling propensities increases the number of prolate conformers. Combining the results, we conclude that CasSD has no stable compact structure and is unlikely to efficiently autoinhibit phosphorylation. Taking into consideration the structural propensity of CasSD and the fact that it is known to bind to LIM domains, we propose a model of how CasSD and LIM domain family of transcription factor proteins may function together to regulate phosphorylation of CasSD and effect machanosensing. '),
(86510, 2014, 'plos', 'BEAST 2: a software platform for Bayesian evolutionary analysis', 'Bouckaert, Remco|Heled, Joseph|Kühnert, Denise|Vaughan, Tim|Wu, Chieh-Hsi|Xie, Dong|Suchard, Marc A|Rambaut, Andrew|Drummond, Alexei J', 'Computational Evolution Group, Department of Computer Science, University of Auckland, Auckland, New Zealand.|Computational Evolution Group, Department of Computer Science, University of Auckland, Auckland, New Zealand.|Computational Evolution Group, Department of Computer Science, University of Auckland, Auckland, New Zealand, Department of Environmental Systems Science, ETH Zürich, Zürich, Switzerland.|Computational Evolution Group, Department of Computer Science, University of Auckland, Auckland, New Zealand, Allan Wilson Centre for Molecular Ecology and Evolution, Massey University, Palmerston North, New Zealand.|Computational Evolution Group, Department of Computer Science, University of Auckland, Auckland, New Zealand.|Computational Evolution Group, Department of Computer Science, University of Auckland, Auckland, New Zealand.|Departments of Biomathematics and Human Genetics, David Geffen School of Medicine, University of California, Los Angeles, Los Angeles, California, United States of America, Department of Biostatistics, School of Public Health, University of California, Los Angeles, Los Angeles, California, United States of America.|Institute of Evolutionary Biology, University of Edinburgh, Edinburgh, United Kingdom.|Computational Evolution Group, Department of Computer Science, University of Auckland, Auckland, New Zealand, Allan Wilson Centre for Molecular Ecology and Evolution, University of Auckland, Auckland, New Zealand.', 'New Zealand|New Zealand|Switzerland|New Zealand|New Zealand|New Zealand|United States|United Kingdom', 2623, 'Bayes Theorem|Biological Evolution|Programming Languages|Software', 'Journal Article', '10.1371/journal.pcbi.1003537', '24722319', 'We present a new open source, extensible and flexible software platform for Bayesian evolutionary analysis called BEAST 2. This software platform is a re-design of the popular BEAST 1 platform to correct structural deficiencies that became evident as the BEAST 1 software evolved. Key among those deficiencies was the lack of post-deployment extensibility. BEAST 2 now has a fully developed package management system that allows third party developers to write additional functionality that can be directly installed to the BEAST 2 analysis platform via a package manager without requiring a new software release of the platform. This package architecture is showcased with a number of recently published new models encompassing birth-death-sampling tree priors, phylodynamics and model averaging for substitution models and site partitioning. A second major improvement is the ability to read/write the entire state of the MCMC chain to/from disk allowing it to be easily shared between multiple instances of the BEAST software. This facilitates checkpointing and better support for multi-processor and high-end computing extensions. Finally, the functionality in new packages can be easily added to the user interface (BEAUti 2) by a simple XML template-based mechanism because BEAST 2 has been re-designed to provide greater integration between the analysis engine and the user interface so that, for example BEAST and BEAUti use exactly the same XML file format. '),
(86511, 2014, 'plos', 'Multiple model-informed open-loop control of uncertain intracellular signaling dynamics', 'Perley, Jeffrey P|Mikolajczak, Judith|Harrison, Marietta L|Buzzard, Gregery T|Rundell, Ann E', 'Weldon School of Biomedical Engineering, Purdue University, West Lafayette, Indiana, United States of America.|Department of Medicinal Chemistry & Molecular Pharmacology, Purdue University, West Lafayette, Indiana, United States of America.|Department of Medicinal Chemistry & Molecular Pharmacology, Purdue University, West Lafayette, Indiana, United States of America.|Department of Mathematics, Purdue University, West Lafayette, Indiana, United States of America.|Weldon School of Biomedical Engineering, Purdue University, West Lafayette, Indiana, United States of America.', 'India|India|India|India|India', 4, 'Computer Simulation|Humans|Jurkat Cells|Models, Theoretical|Signal Transduction|Uncertainty', 'Journal Article', '10.1371/journal.pcbi.1003546', '24722333', 'Computational approaches to tune the activation of intracellular signal transduction pathways both predictably and selectively will enable researchers to explore and interrogate cell biology with unprecedented precision. Techniques to control complex nonlinear systems typically involve the application of control theory to a descriptive mathematical model. For cellular processes, however, measurement assays tend to be too time consuming for real-time feedback control and models offer rough approximations of the biological reality, thus limiting their utility when considered in isolation. We overcome these problems by combining nonlinear model predictive control with a novel adaptive weighting algorithm that blends predictions from multiple models to derive a compromise open-loop control sequence. The proposed strategy uses weight maps to inform the controller of the tendency for models to differ in their ability to accurately reproduce the system dynamics under different experimental perturbations (i.e. control inputs). These maps, which characterize the changing model likelihoods over the admissible control input space, are constructed using preexisting experimental data and used to produce a model-based open-loop control framework. In effect, the proposed method designs a sequence of control inputs that force the signaling dynamics along a predefined temporal response without measurement feedback while mitigating the effects of model uncertainty. We demonstrate this technique on the well-known Erk/MAPK signaling pathway in T cells. In silico assessment demonstrates that this approach successfully reduces target tracking error by 52% or better when compared with single model-based controllers and non-adaptive multiple model-based controllers. In vitro implementation of the proposed approach in Jurkat cells confirms a 63% reduction in tracking error when compared with the best of the single-model controllers. This study provides an experimentally-corroborated control methodology that utilizes the knowledge encoded within multiple mathematical models of intracellular signaling to design control inputs that effectively direct cell behavior in open-loop. '),
(86512, 2014, 'plos', 'The evolution of multivariate maternal effects', 'Kuijper, Bram|Johnstone, Rufus A|Townley, Stuart', 'Environment and Sustainability Institute, University of Exeter, Penryn, United Kingdom, Behaviour and Evolution Group, Department of Zoology, University of Cambridge, Cambridge, United Kingdom, CoMPLEX, Centre for Mathematics and Physics in the Life Sciences and Experimental Biology, University College London, London, United Kingdom, Department of Genetics, Evolution and Environment, University College London, London, United Kingdom.|Behaviour and Evolution Group, Department of Zoology, University of Cambridge, Cambridge, United Kingdom.|Environment and Sustainability Institute, University of Exeter, Penryn, United Kingdom.', 'United Kingdom|United Kingdom|United Kingdom', 24, 'Female|Humans|Models, Theoretical|Mothers|Phenotype|Reproduction', 'Journal Article', '10.1371/journal.pcbi.1003550', '24722346', 'There is a growing interest in predicting the social and ecological contexts that favor the evolution of maternal effects. Most predictions focus, however, on maternal effects that affect only a single character, whereas the evolution of maternal effects is poorly understood in the presence of suites of interacting traits. To overcome this, we simulate the evolution of multivariate maternal effects (captured by the matrix M) in a fluctuating environment. We find that the rate of environmental fluctuations has a substantial effect on the properties of M: in slowly changing environments, offspring are selected to have a multivariate phenotype roughly similar to the maternal phenotype, so that M is characterized by positive dominant eigenvalues, by contrast, rapidly changing environments favor Ms with dominant eigenvalues that are negative, as offspring favor a phenotype which substantially differs from the maternal phenotype. Moreover, when fluctuating selection on one maternal character is temporally delayed relative to selection on other traits, we find a striking pattern of cross-trait maternal effects in which maternal characters influence not only the same character in offspring, but also other offspring characters. Additionally, when selection on one character contains more stochastic noise relative to selection on other traits, large cross-trait maternal effects evolve from those maternal traits that experience the smallest amounts of noise. The presence of these cross-trait maternal effects shows that individual maternal effects cannot be studied in isolation, and that their study in a multivariate context may provide important insights about the nature of past selection. Our results call for more studies that measure multivariate maternal effects in wild populations. '),
(86513, 2014, 'plos', 'Sensing membrane stresses by protein insertions', 'Campelo, Felix|Kozlov, Michael M', 'Cell and Developmental Biology Programme, Centre for Genomic Regulation (CRG), Barcelona, Spain, Universitat Pompeu Fabra (UPF), Barcelona, Spain.|Department of Physiology and Pharmacology, Sackler Faculty of Medicine, Tel Aviv University, Tel Aviv, Israel.', 'Spain|Israel', 29, 'Liposomes|Membrane Proteins|Models, Biological', 'Journal Article', '10.1371/journal.pcbi.1003556', '24722359', 'Protein domains shallowly inserting into the membrane matrix are ubiquitous in peripheral membrane proteins involved in various processes of intracellular membrane shaping and remodeling. It has been suggested that these domains sense membrane curvature through their preferable binding to strongly curved membranes, the binding mechanism being mediated by lipid packing defects. Here we make an alternative statement that shallow protein insertions are universal sensors of the intra-membrane stresses existing in the region of the insertion embedding rather than sensors of the curvature per se. We substantiate this proposal computationally by considering different independent ways of the membrane stress generation among which some include changes of the membrane curvature whereas others do not alter the membrane shape. Our computations show that the membrane-binding coefficient of shallow protein insertions is determined by the resultant stress independently of the way this stress has been produced. By contrast, consideration of the correlation between the insertion binding and the membrane curvature demonstrates that the binding coefficient either increases or decreases with curvature depending on the factors leading to the curvature generation. To validate our computational model, we treat quantitatively the experimental results on membrane binding by ALPS1 and ALPS2 motifs of ArfGAP1. '),
(86514, 2014, 'plos', 'Spike-threshold adaptation predicted by membrane potential dynamics in vivo', 'Fontaine, Bertrand|Peña, José Luis|Brette, Romain', 'Dominick P. Purpura Department of Neuroscience, Albert Einstein College of Medicine, Bronx, New York, United States of America.|Dominick P. Purpura Department of Neuroscience, Albert Einstein College of Medicine, Bronx, New York, United States of America.|Laboratoire Psychologie de la Perception, CNRS and Université Paris Descartes, Paris, France, Département dEtudes Cognitives, Ecole Normale Supérieure, Paris, France, Sorbonne Universités, UPMC Univ. Paris 06, UMR_S 968, Institut de la Vision, Paris, France, INSERM, U968, Paris, France, CNRS, UMR_7210, Paris, France.', 'United States|United States|France', 44, 'Action Potentials|Membrane Potentials|Models, Biological|Neurons', 'Journal Article', '10.1371/journal.pcbi.1003560', '24722397', 'Neurons encode information in sequences of spikes, which are triggered when their membrane potential crosses a threshold. In vivo, the spiking threshold displays large variability suggesting that threshold dynamics have a profound influence on how the combined input of a neuron is encoded in the spiking. Threshold variability could be explained by adaptation to the membrane potential. However, it could also be the case that most threshold variability reflects noise and processes other than threshold adaptation. Here, we investigated threshold variation in auditory neurons responses recorded in vivo in barn owls. We found that spike threshold is quantitatively predicted by a model in which the threshold adapts, tracking the membrane potential at a short timescale. As a result, in these neurons, slow voltage fluctuations do not contribute to spiking because they are filtered by threshold adaptation. More importantly, these neurons can only respond to input spikes arriving together on a millisecond timescale. These results demonstrate that fast adaptation to the membrane potential captures spike threshold variability in vivo. '),
(86515, 2014, 'plos', 'The spatial resolution of epidemic peaks', 'Mills, Harriet L|Riley, Steven', 'MRC Centre for Outbreak Analysis and Modelling, Department of Infectious Disease Epidemiology, Imperial College London, London, United Kingdom.|MRC Centre for Outbreak Analysis and Modelling, Department of Infectious Disease Epidemiology, Imperial College London, London, United Kingdom.', 'United Kingdom|United Kingdom', 13, 'Epidemics|Geography|Stochastic Processes', 'Journal Article', '10.1371/journal.pcbi.1003561', '24722420', 'The emergence of novel respiratory pathogens can challenge the capacity of key health care resources, such as intensive care units, that are constrained to serve only specific geographical populations. An ability to predict the magnitude and timing of peak incidence at the scale of a single large population would help to accurately assess the value of interventions designed to reduce that peak. However, current disease-dynamic theory does not provide a clear understanding of the relationship between: epidemic trajectories at the scale of interest (e.g. city), population mobility, and higher resolution spatial effects (e.g. transmission within small neighbourhoods). Here, we used a spatially-explicit stochastic meta-population model of arbitrary spatial resolution to determine the effect of resolution on model-derived epidemic trajectories. We simulated an influenza-like pathogen spreading across theoretical and actual population densities and varied our assumptions about mobility using Latin-Hypercube sampling. Even though, by design, cumulative attack rates were the same for all resolutions and mobilities, peak incidences were different. Clear thresholds existed for all tested populations, such that models with resolutions lower than the threshold substantially overestimated population-wide peak incidence. The effect of resolution was most important in populations which were of lower density and lower mobility. With the expectation of accurate spatial incidence datasets in the near future, our objective was to provide a framework for how to use these data correctly in a spatial meta-population model. Our results suggest that there is a fundamental spatial resolution for any pathogen-population pair. If underlying interactions between pathogens and spatially heterogeneous populations are represented at this resolution or higher, accurate predictions of peak incidence for city-scale epidemics are feasible. '),
(86516, 2014, 'plos', 'Atomistic picture for the folding pathway of a hybrid-1 type human telomeric DNA G-quadruplex', 'Bian, Yunqiang|Tan, Cheng|Wang, Jun|Sheng, Yuebiao|Zhang, Jian|Wang, Wei', 'National Laboratory of Solid State Microstructure and Department of Physics, Nanjing University, Nanjing, China.|National Laboratory of Solid State Microstructure and Department of Physics, Nanjing University, Nanjing, China.|National Laboratory of Solid State Microstructure and Department of Physics, Nanjing University, Nanjing, China.|High Performance Computing Center, Nanjing University, Nanjing, China.|National Laboratory of Solid State Microstructure and Department of Physics, Nanjing University, Nanjing, China.|National Laboratory of Solid State Microstructure and Department of Physics, Nanjing University, Nanjing, China.', 'China|China|China|China|China|China', 38, 'G-Quadruplexes|Humans|Models, Molecular|Nucleic Acid Conformation|Telomere', 'Journal Article', '10.1371/journal.pcbi.1003562', '24722458', 'In this work we studied the folding process of the hybrid-1 type human telomeric DNA G-quadruplex with solvent and K(+) ions explicitly modeled. Enabled by the powerful bias-exchange metadynamics and large-scale conventional molecular dynamic simulations, the free energy landscape of this G-DNA was obtained for the first time and four folding intermediates were identified, including a triplex and a basically formed quadruplex. The simulations also provided atomistic pictures for the structures and cation binding patterns of the intermediates. The results showed that the structure formation and cation binding are cooperative and mutually supporting each other. The syn/anti reorientation dynamics of the intermediates was also investigated. It was found that the nucleotides usually take correct syn/anti configurations when they form native and stable hydrogen bonds with the others, while fluctuating between two configurations when they do not. Misfolded intermediates with wrong syn/anti configurations were observed in the early intermediates but not in the later ones. Based on the simulations, we also discussed the roles of the non-native interactions. Besides, the formation process of the parallel conformation in the first two G-repeats and the associated reversal loop were studied. Based on the above results, we proposed a folding pathway for the hybrid-1 type G-quadruplex with atomistic details, which is new and more complete compared with previous ones. The knowledge gained for this type of G-DNA may provide a general insight for the folding of the other G-quadruplexes.'),
(86517, 2014, 'plos', 'rDock: a fast, versatile and open source program for docking ligands to proteins and nucleic acids', 'Ruiz-Carmona, Sergio|Alvarez-Garcia, Daniel|Foloppe, Nicolas|Garmendia-Doval, A Beatriz|Juhos, Szilveszter|Schmidtke, Peter|Barril, Xavier|Hubbard, Roderick E|Morley, S David', 'Departament de Fisicoquímica, Facultat de Farmàcia, Universitat de Barcelona, Barcelona, Spain, Institut de Biomedicina de la Universitat de Barcelona (IBUB), Barcelona, Spain.|Departament de Fisicoquímica, Facultat de Farmàcia, Universitat de Barcelona, Barcelona, Spain, Institut de Biomedicina de la Universitat de Barcelona (IBUB), Barcelona, Spain.|Vernalis (R&D) Ltd, Granta Park, Cambridge, United Kingdom.|Amper Programas, Madrid, Spain.|Omixon Biocomputing, Budapest, Hungary.|Discngine, Paris, France.|Departament de Fisicoquímica, Facultat de Farmàcia, Universitat de Barcelona, Barcelona, Spain, Institut de Biomedicina de la Universitat de Barcelona (IBUB), Barcelona, Spain, Catalan Institution for Research and Advanced Studies (ICREA), Barcelona, Spain.|Vernalis (R&D) Ltd, Granta Park, Cambridge, United Kingdom, YSBL, University of York, Heslington, York, United Kingdom.|Enspiral Discovery Limited, Cambridge, United Kingdom, Ariana Pharma, Paris, France.', 'Spain|Spain|United Kingdom|Spain|Hungary|France|Spain|United Kingdom|France', 147, 'Drug Discovery|Ligands|Nucleic Acids|Proteins', 'Journal Article', '10.1371/journal.pcbi.1003571', '24722481', 'Identification of chemical compounds with specific biological activities is an important step in both chemical biology and drug discovery. When the structure of the intended target is available, one approach is to use molecular docking programs to assess the chemical complementarity of small molecules with the target, such calculations provide a qualitative measure of affinity that can be used in virtual screening (VS) to rank order a list of compounds according to their potential to be active. rDock is a molecular docking program developed at Vernalis for high-throughput VS (HTVS) applications. Evolved from RiboDock, the program can be used against proteins and nucleic acids, is designed to be computationally very efficient and allows the user to incorporate additional constraints and information as a bias to guide docking. This article provides an overview of the program structure and features and compares rDock to two reference programs, AutoDock Vina (open source) and Schrödingers Glide (commercial). In terms of computational speed for VS, rDock is faster than Vina and comparable to Glide. For binding mode prediction, rDock and Vina are superior to Glide. The VS performance of rDock is significantly better than Vina, but inferior to Glide for most systems unless pharmacophore constraints are used, in that case rDock and Glide are of equal performance. The program is released under the Lesser General Public License and is freely available for download, together with the manuals, example files and the complete test sets, at http://rdock.sourceforge.net/ '),
(86518, 2014, 'plos', 'The influence of spatiotemporal structure of noisy stimuli in decision making', 'Insabato, Andrea|Dempere-Marco, Laura|Pannunzi, Mario|Deco, Gustavo|Romo, Ranulfo', 'Department of Information and Communication Technologies, Center for Brain and Cognition, Universitat Pompeu Fabra, Barcelona, Spain.|Department of Information and Communication Technologies, Center for Brain and Cognition, Universitat Pompeu Fabra, Barcelona, Spain.|Department of Information and Communication Technologies, Center for Brain and Cognition, Universitat Pompeu Fabra, Barcelona, Spain.|Department of Information and Communication Technologies, Center for Brain and Cognition, Universitat Pompeu Fabra, Barcelona, Spain, ICREA, Institució Catalana de Recerca i Estudis Avançats, Barcelona, Spain.|Instituto de Fisiología Celular-Neurociencias, Universidad Nacional Autónoma de México, México DF, México, El Colegio Nacional, México DF, México.', 'Spain|Spain|Spain|Spain|-', 10, 'Decision Making|Humans|Models, Theoretical|Noise', 'Journal Article', '10.1371/journal.pcbi.1003492', '24743140', 'Decision making is a process of utmost importance in our daily lives, the study of which has been receiving notable attention for decades. Nevertheless, the neural mechanisms underlying decision making are still not fully understood. Computational modeling has revealed itself as a valuable asset to address some of the fundamental questions. Biophysically plausible models, in particular, are useful in bridging the different levels of description that experimental studies provide, from the neural spiking activity recorded at the cellular level to the performance reported at the behavioral level. In this article, we have reviewed some of the recent progress made in the understanding of the neural mechanisms that underlie decision making. We have performed a critical evaluation of the available results and address, from a computational perspective, aspects of both experimentation and modeling that so far have eluded comprehension. To guide the discussion, we have selected a central theme which revolves around the following question: how does the spatiotemporal structure of sensory stimuli affect the perceptual decision-making process? This question is a timely one as several issues that still remain unresolved stem from this central theme. These include: (i) the role of spatiotemporal input fluctuations in perceptual decision making, (ii) how to extend the current results and models derived from two-alternative choice studies to scenarios with multiple competing evidences, and (iii) to establish whether different types of spatiotemporal input fluctuations affect decision-making outcomes in distinctive ways. And although we have restricted our discussion mostly to visual decisions, our main conclusions are arguably generalizable, hence, their possible extension to other sensory modalities is one of the points in our discussion. '),
(86519, 2014, 'plos', 'Phylogenetic quantification of intra-tumour heterogeneity', 'Schwarz, Roland F|Trinh, Anne|Sipos, Botond|Brenton, James D|Goldman, Nick|Markowetz, Florian', 'University of Cambridge, Cambridge, United Kingdom, Cancer Research UK Cambridge Institute, Cambridge, United Kingdom, European Molecular Biology Laboratory, European Bioinformatics Institute, Hinxton, United Kingdom.|University of Cambridge, Cambridge, United Kingdom, Cancer Research UK Cambridge Institute, Cambridge, United Kingdom.|European Molecular Biology Laboratory, European Bioinformatics Institute, Hinxton, United Kingdom.|University of Cambridge, Cambridge, United Kingdom, Cancer Research UK Cambridge Institute, Cambridge, United Kingdom, Department of Oncology, University of Cambridge, Cambridge, United Kingdom.|European Molecular Biology Laboratory, European Bioinformatics Institute, Hinxton, United Kingdom.|University of Cambridge, Cambridge, United Kingdom, Cancer Research UK Cambridge Institute, Cambridge, United Kingdom.', 'United Kingdom|United Kingdom|United Kingdom|United Kingdom|United Kingdom|United Kingdom', 70, 'Alleles|Biological Evolution|Humans|Neoplasms|Phylogeny', 'Journal Article', '10.1371/journal.pcbi.1003535', '24743184', 'Intra-tumour genetic heterogeneity is the result of ongoing evolutionary change within each cancer. The expansion of genetically distinct sub-clonal populations may explain the emergence of drug resistance, and if so, would have prognostic and predictive utility. However, methods for objectively quantifying tumour heterogeneity have been missing and are particularly difficult to establish in cancers where predominant copy number variation prevents accurate phylogenetic reconstruction owing to horizontal dependencies caused by long and cascading genomic rearrangements. To address these challenges, we present MEDICC, a method for phylogenetic reconstruction and heterogeneity quantification based on a Minimum Event Distance for Intra-tumour Copy-number Comparisons. Using a transducer-based pairwise comparison function, we determine optimal phasing of major and minor alleles, as well as evolutionary distances between samples, and are able to reconstruct ancestral genomes. Rigorous simulations and an extensive clinical study show the power of our method, which outperforms state-of-the-art competitors in reconstruction accuracy, and additionally allows unbiased numerical quantification of tumour heterogeneity. Accurate quantification and evolutionary inference are essential to understand the functional consequences of tumour heterogeneity. The MEDICC algorithms are independent of the experimental techniques used and are applicable to both next-generation sequencing and array CGH data. '),
(86520, 2014, 'plos', 'Prediction and prioritization of rare oncogenic mutations in the cancer Kinome using novel features and multiple classifiers', 'U, ManChon|Talevich, Eric|Katiyar, Samiksha|Rasheed, Khaled|Kannan, Natarajan', 'Department of Computer Science, University of Georgia, Athens, Georgia, United States of America.|Department of Dermatology, University of California San Francisco, San Francisco, California, United States of America.|Department of Biochemistry and Molecular Biology, University of Georgia, Athens, Georgia, United States of America.|Department of Computer Science, University of Georgia, Athens, Georgia, United States of America.|Department of Biochemistry and Molecular Biology, University of Georgia, Athens, Georgia, United States of America, Institute of Bioinformatics, University of Georgia, Athens, Georgia, United States of America.', 'Georgia|United States|Georgia|Georgia|Georgia', 0, 'Artificial Intelligence|Humans|Mutation|Neoplasms|Oncogenes|Protein Kinases', 'Journal Article', '10.1371/journal.pcbi.1003545', '24743239', 'Cancer is a genetic disease that develops through a series of somatic mutations, a subset of which drive cancer progression. Although cancer genome sequencing studies are beginning to reveal the mutational patterns of genes in various cancers, identifying the small subset of causative mutations from the large subset of non-causative mutations, which accumulate as a consequence of the disease, is a challenge. In this article, we present an effective machine learning approach for identifying cancer-associated mutations in human protein kinases, a class of signaling proteins known to be frequently mutated in human cancers. We evaluate the performance of 11 well known supervised learners and show that a multiple-classifier approach, which combines the performances of individual learners, significantly improves the classification of known cancer-associated mutations. We introduce several novel features related specifically to structural and functional characteristics of protein kinases and find that the level of conservation of the mutated residue at specific evolutionary depths is an important predictor of oncogenic effect. We consolidate the novel features and the multiple-classifier approach to prioritize and experimentally test a set of rare unconfirmed mutations in the epidermal growth factor receptor tyrosine kinase (EGFR). Our studies identify T725M and L861R as rare cancer-associated mutations inasmuch as these mutations increase EGFR activity in the absence of the activating EGF ligand in cell-based assays. '),
(86521, 2014, 'plos', 'A synergism between adaptive effects and evolvability drives whole genome duplication to fixation', 'Cuypers, Thomas D|Hogeweg, Paulien', 'Theoretical Biology and Bioinformatics Group, Utrecht University, Utrecht, the Netherlands.|Theoretical Biology and Bioinformatics Group, Utrecht University, Utrecht, the Netherlands.', 'Netherlands|Netherlands', 12, 'Adaptation, Physiological|Evolution, Molecular|Gene Duplication|Genome', 'Journal Article', '10.1371/journal.pcbi.1003547', '24743268', 'Whole genome duplication has shaped eukaryotic evolutionary history and has been associated with drastic environmental change and species radiation. While the most common fate of WGD duplicates is a return to single copy, retained duplicates have been found enriched for highly interacting genes. This pattern has been explained by a neutral process of subfunctionalization and more recently, dosage balance selection. However, much about the relationship between environmental change, WGD and adaptation remains unknown. Here, we study the duplicate retention pattern postWGD, by letting virtual cells adapt to environmental changes. The virtual cells have structured genomes that encode a regulatory network and simple metabolism. Populations are under selection for homeostasis and evolve by point mutations, small indels and WGD. After populations had initially adapted fully to fluctuating resource conditions re-adaptation to a broad range of novel environments was studied by tracking mutations in the line of descent. WGD was established in a minority (xe2x89x8830%) of lineages, yet, these were significantly more successful at re-adaptation. Unexpectedly, WGD lineages conserved more seemingly redundant genes, yet had higher per gene mutation rates. While WGD duplicates of all functional classes were significantly over-retained compared to a model of neutral losses, duplicate retention was clearly biased towards highly connected TFs. Importantly, no subfunctionalization occurred in conserved pairs, strongly suggesting that dosage balance shaped retention. Meanwhile, singles diverged significantly. WGD, therefore, is a powerful mechanism to cope with environmental change, allowing conservation of a core machinery, while adapting the peripheral network to accommodate change. '),
(86522, 2014, 'plos', 'A toolbox for representational similarity analysis', 'Nili, Hamed|Wingfield, Cai|Walther, Alexander|Su, Li|Marslen-Wilson, William|Kriegeskorte, Nikolaus', 'MRC Cognition and Brain Sciences Unit, Cambridge, United Kingdom.|Department of Computer Science, University of Bath, Bath, United Kingdom.|MRC Cognition and Brain Sciences Unit, Cambridge, United Kingdom.|MRC Cognition and Brain Sciences Unit, Cambridge, United Kingdom, Department of Experimental Psychology, University of Cambridge, Cambridge, United Kingdom.|Department of Experimental Psychology, University of Cambridge, Cambridge, United Kingdom.|MRC Cognition and Brain Sciences Unit, Cambridge, United Kingdom.', 'United Kingdom|United Kingdom|United Kingdom|United Kingdom|United Kingdom|United Kingdom', 0, 'Brain|Computer Simulation|Electronic Data Processing|Humans|Models, Theoretical', 'Journal Article', '10.1371/journal.pcbi.1003553', '24743308', 'Neuronal population codes are increasingly being investigated with multivariate pattern-information analyses. A key challenge is to use measured brain-activity patterns to test computational models of brain information processing. One approach to this problem is representational similarity analysis (RSA), which characterizes a representation in a brain or computational model by the distance matrix of the response patterns elicited by a set of stimuli. The representational distance matrix encapsulates what distinctions between stimuli are emphasized and what distinctions are de-emphasized in the representation. A model is tested by comparing the representational distance matrix it predicts to that of a measured brain region. RSA also enables us to compare representations between stages of processing within a given brain or model, between brain and behavioral data, and between individuals and species. Here, we introduce a Matlab toolbox for RSA. The toolbox supports an analysis approach that is simultaneously data- and hypothesis-driven. It is designed to help integrate a wide range of computational models into the analysis of multichannel brain-activity measurements as provided by modern functional imaging and neuronal recording techniques. Tools for visualization and inference enable the user to relate sets of models to sets of brain regions and to statistically test and compare the models using nonparametric inference methods. The toolbox supports searchlight-based RSA, to continuously map a measured brain volume in search of a neuronal population code with a specific geometry. Finally, we introduce the linear-discriminant t value as a measure of representational discriminability that bridges the gap between linear decoding analyses and RSA. In order to demonstrate the capabilities of the toolbox, we apply it to both simulated and real fMRI data. The key functions are equally applicable to other modalities of brain-activity measurement. The toolbox is freely available to the community under an open-source license agreement (http://www.mrc-cbu.cam.ac.uk/methods-and-resources/toolboxes/license/). ');
INSERT INTO `papers` (`id`, `ano`, `journal`, `titulo`, `autores`, `afiliacao`, `pais`, `citacoes`, `palavra_chave`, `categorias`, `doi`, `pubmed`, `abstract`) VALUES
(86523, 2014, 'plos', 'Enhanced methods for local ancestry assignment in sequenced admixed individuals', 'Brown, Robert|Pasaniuc, Bogdan', 'Bioinformatics Interdepartmental Program, University of California Los Angeles, Los Angeles, California, United States of America, Department of Pathology and Laboratory Medicine, Geffen School of Medicine, University of California Los Angeles, Los Angeles, California, United States of America.|Bioinformatics Interdepartmental Program, University of California Los Angeles, Los Angeles, California, United States of America, Department of Pathology and Laboratory Medicine, Geffen School of Medicine, University of California Los Angeles, Los Angeles, California, United States of America, Jonsson Comprehensive Cancer Center, University of California Los Angeles, Los Angeles, California, United States of America.', 'United States|United States', 16, 'Genealogy and Heraldry|Genome, Human|Haplotypes|Humans', 'Journal Article', '10.1371/journal.pcbi.1003555', '24743331', 'Inferring the ancestry at each locus in the genome of recently admixed individuals (e.g., Latino Americans) plays a major role in medical and population genetic inferences, ranging from finding disease-risk loci, to inferring recombination rates, to mapping missing contigs in the human genome. Although many methods for local ancestry inference have been proposed, most are designed for use with genotyping arrays and fail to make use of the full spectrum of data available from sequencing. In addition, current haplotype-based approaches are very computationally demanding, requiring large computational time for moderately large sample sizes. Here we present new methods for local ancestry inference that leverage continent-specific variants (CSVs) to attain increased performance over existing approaches in sequenced admixed genomes. A key feature of our approach is that it incorporates the admixed genomes themselves jointly with public datasets, such as 1000 Genomes, to improve the accuracy of CSV calling. We use simulations to show that our approach attains accuracy similar to widely used computationally intensive haplotype-based approaches with large decreases in runtime. Most importantly, we show that our method recovers comparable local ancestries, as the 1000 Genomes consensus local ancestry calls in the real admixed individuals from the 1000 Genomes Project. We extend our approach to account for low-coverage sequencing and show that accurate local ancestry inference can be attained at low sequencing coverage. Finally, we generalize CSVs to sub-continental population-specific variants (sCSVs) and show that in some cases it is possible to determine the sub-continental ancestry for short chromosomal segments on the basis of sCSVs. '),
(86524, 2014, 'plos', 'Continuous attractor network model for conjunctive position-by-velocity tuning of grid cells', 'Si, Bailu|Romani, Sandro|Tsodyks, Misha', 'Department of Neurobiology, Weizmann Institute of Science, Rehovot, Israel.|Center for Theoretical Neuroscience, Columbia University, New York, New York, United States of America.|Department of Neurobiology, Weizmann Institute of Science, Rehovot, Israel.', 'Israel|United States|Israel', 14, 'Animals|Models, Theoretical|Movement|Rodentia', 'Journal Article', '10.1371/journal.pcbi.1003558', '24743341', 'The spatial responses of many of the cells recorded in layer II of rodent medial entorhinal cortex (MEC) show a triangular grid pattern, which appears to provide an accurate population code for animal spatial position. In layer III, V and VI of the rat MEC, grid cells are also selective to head-direction and are modulated by the speed of the animal. Several putative mechanisms of grid-like maps were proposed, including attractor network dynamics, interactions with theta oscillations or single-unit mechanisms such as firing rate adaptation. In this paper, we present a new attractor network model that accounts for the conjunctive position-by-velocity selectivity of grid cells. Our network model is able to perform robust path integration even when the recurrent connections are subject to random perturbations. '),
(86525, 2014, 'plos', 'Active learning to understand infectious disease models and improve policy making', 'Willem, Lander|Stijven, Sean|Vladislavleva, Ekaterina|Broeckhove, Jan|Beutels, Philippe|Hens, Niel', 'Centre for Health Economics Research & Modeling of Infectious Diseases, Vaccine and Infectious Disease Institute, University of Antwerp, Antwerp, Belgium, Department of Mathematics and Computer Science, University of Antwerp, Antwerp, Belgium, Interuniversitary Institute for Biostatistics and statistical Bioinformatics, Hasselt University, Diepenbeek, Belgium.|Department of Mathematics and Computer Science, University of Antwerp, Antwerp, Belgium, Department of Information Technology, Gent University-iMinds, Gent, Belgium.|Evolved Analytics Europe BVBA, Beerse, Belgium.|Department of Mathematics and Computer Science, University of Antwerp, Antwerp, Belgium.|Centre for Health Economics Research & Modeling of Infectious Diseases, Vaccine and Infectious Disease Institute, University of Antwerp, Antwerp, Belgium, School of Public Health and Community Medicine, The University of New South Wales, Sydney, Australia.|Centre for Health Economics Research & Modeling of Infectious Diseases, Vaccine and Infectious Disease Institute, University of Antwerp, Antwerp, Belgium, Interuniversitary Institute for Biostatistics and statistical Bioinformatics, Hasselt University, Diepenbeek, Belgium.', 'Belgium|Belgium|Belgium|Belgium|Australia|Belgium', 11, 'Chickenpox|Chickenpox Vaccine|Communicable Diseases|Humans|Influenza Vaccines|Influenza, Human|Learning|Models, Theoretical|Policy Making|Stochastic Processes', 'Journal Article', '10.1371/journal.pcbi.1003563', '24743387', 'Modeling plays a major role in policy making, especially for infectious disease interventions but such models can be complex and computationally intensive. A more systematic exploration is needed to gain a thorough systems understanding. We present an active learning approach based on machine learning techniques as iterative surrogate modeling and model-guided experimentation to systematically analyze both common and edge manifestations of complex model runs. Symbolic regression is used for nonlinear response surface modeling with automatic feature selection. First, we illustrate our approach using an individual-based model for influenza vaccination. After optimizing the parameter space, we observe an inverse relationship between vaccination coverage and cumulative attack rate reinforced by herd immunity. Second, we demonstrate the use of surrogate modeling techniques on input-response data from a deterministic dynamic model, which was designed to explore the cost-effectiveness of varicella-zoster virus vaccination. We use symbolic regression to handle high dimensionality and correlated inputs and to identify the most influential variables. Provided insight is used to focus research, reduce dimensionality and decrease decision uncertainty. We conclude that active learning is needed to fully understand complex systems behavior. Surrogate models can be readily explored at no computational expense, and can also be used as emulator to improve rapid policy making in various settings. '),
(86526, 2014, 'plos', 'Timing of neuropeptide coupling determines synchrony and entrainment in the mammalian circadian clock', 'Ananthasubramaniam, Bharath|Herzog, Erik D|Herzel, Hanspeter', 'Institute for Theoretical Biology, Charité and Humboldt University Berlin, Berlin, Germany.|Department of Biology, Washington University in St. Louis, St. Louis, Missouri, United States of America.|Institute for Theoretical Biology, Charité and Humboldt University Berlin, Berlin, Germany.', 'Germany|United States|Germany', 0, 'Animals|Circadian Rhythm|Mammals|Neuropeptides', 'Journal Article', '10.1371/journal.pcbi.1003565', '24743470', 'Robust synchronization is a critical feature of several systems including the mammalian circadian clock. The master circadian clock in mammals consists of about 20000 sloppy neuronal oscillators within the hypothalamus that keep robust time by synchronization driven by inter-neuronal coupling. The complete understanding of this synchronization in the mammalian circadian clock and the mechanisms underlying it remain an open question. Experiments and computational studies have shown that coupling individual oscillators can achieve robust synchrony, despite heterogeneity and different network topologies. But, much less is known regarding the mechanisms and circuits involved in achieving this coupling, due to both system complexity and experimental limitations. Here, we computationally study the coupling mediated by the primary coupling neuropeptide, vasoactive intestinal peptide (VIP) and its canonical receptor, VPAC2R, using the transcriptional elements and generic mode of VIP-VPAC2R signaling. We find that synchrony is only possible if VIP (an inducer of Per expression) is released in-phase with activators of Per expression. Moreover, anti-phasic VIP release suppresses coherent rhythms by moving the network into a desynchronous state. Importantly, experimentally observed rhythms in VPAC2R have little effect on network synchronization, but can improve the amplitude of the SCN network rhythms while narrowing the network entrainment range. We further show that these findings are valid across several computational network models. Thus, we identified a general design principle to achieve robust synchronization: An activating coupling agent, such as VIP, must act in-phase with the activity of core-clock promoters. More generally, the phase of coupling is as critical as the strength of coupling from the viewpoint of synchrony and entrainment. '),
(86527, 2014, 'plos', 'ISMB 2014--the premier conference for the Worlds Computational Biologists', 'Fogg, Christiana N|Kovats, Diane E', 'Freelance Science Writer, Kensington, Maryland, United States of America.|Executive Director, International Society for Computational Biology, La Jolla, California, United States of America.', 'United States|United States', 0, 'Boston|Computational Biology', 'Congress', '10.1371/journal.pcbi.1003566', '24743524', '-'),
(86528, 2014, 'plos', 'Impact of different oseltamivir regimens on treating influenza A virus infection and resistance emergence: insights from a modelling study', 'Canini, Laetitia|Conway, Jessica M|Perelson, Alan S|Carrat, Fabrice', 'INSERM, UMR_S 1136, Institut Pierre Louis dEpidémiologie et de Santé Publique, Paris, France, Sorbonne Universités, UPMC Univ Paris 06, UMR_S 1136, Institut Pierre Louis dEpidémiologie et de Santé Publique, Paris, France, Theoretical Biology and Biophysics, Los Alamos National Laboratory, Los Alamos, New Mexico, United States of America.|Theoretical Biology and Biophysics, Los Alamos National Laboratory, Los Alamos, New Mexico, United States of America.|Theoretical Biology and Biophysics, Los Alamos National Laboratory, Los Alamos, New Mexico, United States of America.|INSERM, UMR_S 1136, Institut Pierre Louis dEpidémiologie et de Santé Publique, Paris, France, Sorbonne Universités, UPMC Univ Paris 06, UMR_S 1136, Institut Pierre Louis dEpidémiologie et de Santé Publique, Paris, France, Assistance Publique Hôpitaux de Paris, Hôpital Saint Antoine, Paris, France.', 'France|Mexico|Mexico|France', 37, 'Antiviral Agents|Drug Resistance, Viral|Humans|Influenza A virus|Influenza, Human|Models, Theoretical|Oseltamivir', 'Journal Article', '10.1371/journal.pcbi.1003568', '24743564', 'Several studies have proven oseltamivir to be efficient in reducing influenza viral titer and symptom intensity. However, the usefulness of oseltamivir can be compromised by the emergence and spread of drug-resistant virus. The selective pressure exerted by different oseltamivir therapy regimens have received little attention. Combining models of drug pharmacokinetics, pharmacodynamics, viral kinetics and symptom dynamics, we explored the efficacy of oseltamivir in reducing both symptoms (symptom efficacy) and viral load (virological efficacy). We simulated samples of 1000 subjects using previously estimated between-subject variability in viral and symptom dynamic parameters to describe the observed heterogeneity in a patient population. We simulated random mutations conferring resistance to oseltamivir. We explored the effect of therapy initiation time, dose, intake frequency and therapy duration on influenza infection, illness dynamics, and emergence of viral resistance. Symptom and virological efficacies were strongly associated with therapy initiation time. The proportion of subjects shedding resistant virus was 27-fold higher when prophylaxis was initiated during the incubation period compared with no treatment. It fell to below 1% when treatment was initiated after symptom onset for twice-a-day intakes. Lower doses and prophylaxis regimens led to lower efficacies and increased risk of resistance emergence. We conclude that prophylaxis initiated during the incubation period is the main factor leading to resistance emergence. '),
(86529, 2014, 'plos', 'Phylodynamic inference for structured epidemiological models', 'Rasmussen, David A|Volz, Erik M|Koelle, Katia', 'Biology Department, Duke University, Durham, North Carolina, United States of America.|Department of Infectious Disease Epidemiology, Imperial College London, London, United Kingdom.|Biology Department, Duke University, Durham, North Carolina, United States of America, Fogarty International Center, National Institutes of Health, Bethesda, Maryland, United States of America.', 'United States|United Kingdom|United States', 0, 'Algorithms|Bayes Theorem|Epidemiologic Studies|Likelihood Functions|Markov Chains|Models, Statistical|Monte Carlo Method|Phylogeny|Stochastic Processes', 'Journal Article', '10.1371/journal.pcbi.1003570', '24743590', 'Coalescent theory is routinely used to estimate past population dynamics and demographic parameters from genealogies. While early work in coalescent theory only considered simple demographic models, advances in theory have allowed for increasingly complex demographic scenarios to be considered. The success of this approach has lead to coalescent-based inference methods being applied to populations with rapidly changing population dynamics, including pathogens like RNA viruses. However, fitting epidemiological models to genealogies via coalescent models remains a challenging task, because pathogen populations often exhibit complex, nonlinear dynamics and are structured by multiple factors. Moreover, it often becomes necessary to consider stochastic variation in population dynamics when fitting such complex models to real data. Using recently developed structured coalescent models that accommodate complex population dynamics and population structure, we develop a statistical framework for fitting stochastic epidemiological models to genealogies. By combining particle filtering methods with Bayesian Markov chain Monte Carlo methods, we are able to fit a wide class of stochastic, nonlinear epidemiological models with different forms of population structure to genealogies. We demonstrate our framework using two structured epidemiological models: a model with disease progression between multiple stages of infection and a two-population model reflecting spatial structure. We apply the multi-stage model to HIV genealogies and show that the proposed method can be used to estimate the stage-specific transmission rates and prevalence of HIV. Finally, using the two-population model we explore how much information about population structure is contained in genealogies and what sample sizes are necessary to reliably infer parameters like migration rates. '),
(86530, 2014, 'plos', 'Wikipedia usage estimates prevalence of influenza-like illness in the United States in near real-time', 'McIver, David J|Brownstein, John S', 'Boston Childrens Hospital, Harvard Medical School, Boston, Massachusetts, United States of America.|Boston Childrens Hospital, Harvard Medical School, Boston, Massachusetts, United States of America.', 'United States|United States', 0, 'Centers for Disease Control and Prevention (U.S.)|Humans|Influenza, Human|Internet|Poisson Distribution|Prevalence|United States', 'Journal Article', '10.1371/journal.pcbi.1003581', '24743682', 'Circulating levels of both seasonal and pandemic influenza require constant surveillance to ensure the health and safety of the population. While up-to-date information is critical, traditional surveillance systems can have data availability lags of up to two weeks. We introduce a novel method of estimating, in near-real time, the level of influenza-like illness (ILI) in the United States (US) by monitoring the rate of particular Wikipedia article views on a daily basis. We calculated the number of times certain influenza- or health-related Wikipedia articles were accessed each day between December 2007 and August 2013 and compared these data to official ILI activity levels provided by the Centers for Disease Control and Prevention (CDC). We developed a Poisson model that accurately estimates the level of ILI activity in the American population, up to two weeks ahead of the CDC, with an absolute average difference between the two estimates of just 0.27% over 294 weeks of data. Wikipedia-derived ILI models performed well through both abnormally high media coverage events (such as during the 2009 H1N1 pandemic) as well as unusually severe influenza seasons (such as the 2012-2013 influenza season). Wikipedia usage accurately estimated the week of peak ILI activity 17% more often than Google Flu Trends data and was often more accurate in its measure of ILI intensity. With further study, this method could potentially be implemented for continuous monitoring of ILI activity in the US and to provide support for traditional influenza surveillance tools. '),
(86531, 2014, 'plos', 'How the brain decides when to work and when to rest: dissociation of implicit-reactive from explicit-predictive computational processes', 'Meyniel, Florent|Safra, Lou|Pessiglione, Mathias', 'Motivation, Brain & Behavior (MBB) team, Institut du Cerveau et de la Moelle épinière (ICM), Groupe Hospitalier Pitié-Salpêtrière, Université Pierre et Marie Curie (UPMC - Paris 6), Paris, France.|Motivation, Brain & Behavior (MBB) team, Institut du Cerveau et de la Moelle épinière (ICM), Groupe Hospitalier Pitié-Salpêtrière, Université Pierre et Marie Curie (UPMC - Paris 6), Paris, France.|Motivation, Brain & Behavior (MBB) team, Institut du Cerveau et de la Moelle épinière (ICM), Groupe Hospitalier Pitié-Salpêtrière, Université Pierre et Marie Curie (UPMC - Paris 6), Paris, France.', 'France|France|France', 10, 'Bayes Theorem|Brain|Decision Making|Electronic Data Processing|Humans', 'Journal Article', '10.1371/journal.pcbi.1003584', '24743711', 'A pervasive case of cost-benefit problem is how to allocate effort over time, i.e. deciding when to work and when to rest. An economic decision perspective would suggest that duration of effort is determined beforehand, depending on expected costs and benefits. However, the literature on exercise performance emphasizes that decisions are made on the fly, depending on physiological variables. Here, we propose and validate a general model of effort allocation that integrates these two views. In this model, a single variable, termed cost evidence, accumulates during effort and dissipates during rest, triggering effort cessation and resumption when reaching bounds. We assumed that such a basic mechanism could explain implicit adaptation, whereas the latent parameters (slopes and bounds) could be amenable to explicit anticipation. A series of behavioral experiments manipulating effort duration and difficulty was conducted in a total of 121 healthy humans to dissociate implicit-reactive from explicit-predictive computations. Results show 1) that effort and rest durations are adapted on the fly to variations in cost-evidence level, 2) that the cost-evidence fluctuations driving the behavior do not match explicit ratings of exhaustion, and 3) that actual difficulty impacts effort duration whereas expected difficulty impacts rest duration. Taken together, our findings suggest that cost evidence is implicitly monitored online, with an accumulation rate proportional to actual task difficulty. In contrast, cost-evidence bounds and dissipation rate might be adjusted in anticipation, depending on explicit task difficulty. '),
(86532, 2014, 'plos', 'Computational prediction of alanine scanning and ligand binding energetics in G-protein coupled receptors', 'Boukharta, Lars|Gutiérrez-de-Terán, Hugo|Aqvist, Johan', 'Department of Cell and Molecular Biology, Uppsala University, Biomedical Center, Uppsala, Sweden.|Department of Cell and Molecular Biology, Uppsala University, Biomedical Center, Uppsala, Sweden.|Department of Cell and Molecular Biology, Uppsala University, Biomedical Center, Uppsala, Sweden.', 'Sweden|Sweden|Sweden', 0, 'Alanine|Computational Biology|Ligands|Models, Molecular|Protein Binding|Receptors, G-Protein-Coupled', 'Journal Article', '10.1371/journal.pcbi.1003585', '24743773', 'Site-directed mutagenesis combined with binding affinity measurements is widely used to probe the nature of ligand interactions with GPCRs. Such experiments, as well as structure-activity relationships for series of ligands, are usually interpreted with computationally derived models of ligand binding modes. However, systematic approaches for accurate calculations of the corresponding binding free energies are still lacking. Here, we report a computational strategy to quantitatively predict the effects of alanine scanning and ligand modifications based on molecular dynamics free energy simulations. A smooth stepwise scheme for free energy perturbation calculations is derived and applied to a series of thirteen alanine mutations of the human neuropeptide Y1 receptor and series of eight analogous antagonists. The robustness and accuracy of the method enables univocal interpretation of existing mutagenesis and binding data. We show how these calculations can be used to validate structural models and demonstrate their ability to discriminate against suboptimal ones. '),
(86533, 2014, 'plos', 'Coupling of lever arm swing and biased Brownian motion in actomyosin', 'Nie, Qing-Miao|Togashi, Akio|Sasaki, Takeshi N|Takano, Mitsunori|Sasai, Masaki|Terada, Tomoki P', 'Department of Computational Science and Engineering, Nagoya University, Nagoya, Japan, Institute for Molecular Science, Okazaki, Japan, Department of Applied Physics, Zhejiang University of Technology, Hangzhou, P. R. China.|Department of Computational Science and Engineering, Nagoya University, Nagoya, Japan.|Department of Human Informatics, Aichi Shukutoku University, Aichi, Japan.|Department of Physics, Waseda University, Ohkubo, Shinjuku-ku, Tokyo, Japan.|Department of Computational Science and Engineering, Nagoya University, Nagoya, Japan, School of Computational Sciences, Korea Institute for Advanced Study, Seoul, Korea.|Department of Computational Science and Engineering, Nagoya University, Nagoya, Japan.', 'China|Japan|Japan|Japan|Japan|Japan', 8, 'Actomyosin|Colloids|Monte Carlo Method|Protein Conformation|Static Electricity', 'Journal Article', '10.1371/journal.pcbi.1003552', '24762409', 'An important unresolved problem associated with actomyosin motors is the role of Brownian motion in the process of force generation. On the basis of structural observations of myosins and actins, the widely held lever-arm hypothesis has been proposed, in which proteins are assumed to show sequential structural changes among observed and hypothesized structures to exert mechanical force. An alternative hypothesis, the Brownian motion hypothesis, has been supported by single-molecule experiments and emphasizes more on the roles of fluctuating protein movement. In this study, we address the long-standing controversy between the lever-arm hypothesis and the Brownian motion hypothesis through in silico observations of an actomyosin system. We study a system composed of myosin II and actin filament by calculating free-energy landscapes of actin-myosin interactions using the molecular dynamics method and by simulating transitions among dynamically changing free-energy landscapes using the Monte Carlo method. The results obtained by this combined multi-scale calculation show that myosin with inorganic phosphate (Pi) and ADP weakly binds to actin and that after releasing Pi and ADP, myosin moves along the actin filament toward the strong-binding site by exhibiting the biased Brownian motion, a behavior consistent with the observed single-molecular behavior of myosin. Conformational flexibility of loops at the actin-interface of myosin and the N-terminus of actin subunit is necessary for the distinct bias in the Brownian motion. Both the 5.5-11 nm displacement due to the biased Brownian motion and the 3-5 nm displacement due to lever-arm swing contribute to the net displacement of myosin. The calculated results further suggest that the recovery stroke of the lever arm plays an important role in enhancing the displacement of myosin through multiple cycles of ATP hydrolysis, suggesting a unified movement mechanism for various members of the myosin family. '),
(86534, 2014, 'plos', 'Evolutionary game dynamics in populations with heterogenous structures', 'Maciejewski, Wes|Fu, Feng|Hauert, Christoph', 'Department of Mathematics, The University of British Columbia, Vancouver, British Columbia, Canada.|Theoretical Biology, Institute of Integrative Biology, ETH Zürich, Zürich, Switzerland.|Department of Mathematics, The University of British Columbia, Vancouver, British Columbia, Canada.', 'Canada|Switzerland|Canada', 59, 'Biological Evolution|Game Theory|Social Behavior', 'Journal Article', '10.1371/journal.pcbi.1003567', '24762474', 'Evolutionary graph theory is a well established framework for modelling the evolution of social behaviours in structured populations. An emerging consensus in this field is that graphs that exhibit heterogeneity in the number of connections between individuals are more conducive to the spread of cooperative behaviours. In this article we show that such a conclusion largely depends on the individual-level interactions that take place. In particular, averaging payoffs garnered through game interactions rather than accumulating the payoffs can altogether remove the cooperative advantage of heterogeneous graphs while such a difference does not affect the outcome on homogeneous structures. In addition, the rate at which game interactions occur can alter the evolutionary outcome. Less interactions allow heterogeneous graphs to support more cooperation than homogeneous graphs, while higher rates of interactions make homogeneous and heterogeneous graphs virtually indistinguishable in their ability to support cooperation. Most importantly, we show that common measures of evolutionary advantage used in homogeneous populations, such as a comparison of the fixation probability of a rare mutant to that of the resident type, are no longer valid in heterogeneous populations. Heterogeneity causes a bias in where mutations occur in the population which affects the mutants fixation probability. We derive the appropriate measures for heterogeneous populations that account for this bias. '),
(86535, 2014, 'plos', 'A coarse-grained elastic network atom contact model and its use in the simulation of protein dynamics and the prediction of the effect of mutations', 'Frappier, Vincent|Najmanovich, Rafael J', 'Department of Biochemistry, Faculty of Medicine and Health Sciences, Universitxc3xa9 de Sherbrooke, Sherbrooke, Quebec, Canada.|Department of Biochemistry, Faculty of Medicine and Health Sciences, Universitxc3xa9 de Sherbrooke, Sherbrooke, Quebec, Canada.', 'Canada|Canada', 0, 'Crystallography|Elasticity|Models, Theoretical|Mutation|Proteins', 'Journal Article', '10.1371/journal.pcbi.1003569', '24762569', 'Normal mode analysis (NMA) methods are widely used to study dynamic aspects of protein structures. Two critical components of NMA methods are coarse-graining in the level of simplification used to represent protein structures and the choice of potential energy functional form. There is a trade-off between speed and accuracy in different choices. In one extreme one finds accurate but slow molecular-dynamics based methods with all-atom representations and detailed atom potentials. On the other extreme, fast elastic network model (ENM) methods with Cxcexb1-only representations and simplified potentials that based on geometry alone, thus oblivious to protein sequence. Here we present ENCoM, an Elastic Network Contact Model that employs a potential energy function that includes a pairwise atom-type non-bonded interaction term and thus makes it possible to consider the effect of the specific nature of amino-acids on dynamics within the context of NMA. ENCoM is as fast as existing ENM methods and outperforms such methods in the generation of conformational ensembles. Here we introduce a new application for NMA methods with the use of ENCoM in the prediction of the effect of mutations on protein stability. While existing methods are based on machine learning or enthalpic considerations, the use of ENCoM, based on vibrational normal modes, is based on entropic considerations. This represents a novel area of application for NMA methods and a novel approach for the prediction of the effect of mutations. We compare ENCoM to a large number of methods in terms of accuracy and self-consistency. We show that the accuracy of ENCoM is comparable to that of the best existing methods. We show that existing methods are biased towards the prediction of destabilizing mutations and that ENCoM is less biased at predicting stabilizing mutations. '),
(86536, 2014, 'plos', 'Contribution of network connectivity in determining the relationship between gene expression and metabolite concentration changes', 'Zelezniak, Aleksej|Sheridan, Steven|Patil, Kiran Raosaheb', 'European Molecular Biology Laboratory, Heidelberg, Germany, Technical University of Denmark, Kgs. Lyngby, Denmark.|European Molecular Biology Laboratory, Heidelberg, Germany.|European Molecular Biology Laboratory, Heidelberg, Germany.', 'Germany|Germany|Germany', 38, 'Gene Expression|Kinetics|Metabolic Networks and Pathways', 'Journal Article', '10.1371/journal.pcbi.1003572', '24762675', 'One of the primary mechanisms through which a cell exerts control over its metabolic state is by modulating expression levels of its enzyme-coding genes. However, the changes at the level of enzyme expression allow only indirect control over metabolite levels, for two main reasons. First, at the level of individual reactions, metabolite levels are non-linearly dependent on enzyme abundances as per the reaction kinetics mechanisms. Secondly, specific metabolite pools are tightly interlinked with the rest of the metabolic network through their production and consumption reactions. While the role of reaction kinetics in metabolite concentration control is well studied at the level of individual reactions, the contribution of network connectivity has remained relatively unclear. Here we report a modeling framework that integrates both reaction kinetics and network connectivity constraints for describing the interplay between metabolite concentrations and mRNA levels. We used this framework to investigate correlations between the gene expression and the metabolite concentration changes in Saccharomyces cerevisiae during its metabolic cycle, as well as in response to three fundamentally different biological perturbations, namely gene knockout, nutrient shock and nutrient change. While the kinetic constraints applied at the level of individual reactions were found to be poor descriptors of the mRNA-metabolite relationship, their use in the context of the network enabled us to correlate changes in the expression of enzyme-coding genes to the alterations in metabolite levels. Our results highlight the key contribution of metabolic network connectivity in mediating cellular control over metabolite levels, and have implications towards bridging the gap between genotype and metabolic phenotype. '),
(86537, 2014, 'plos', 'Constraint-based modeling of carbon fixation and the energetics of electron transfer in Geobacter metallireducens', 'Feist, Adam M|Nagarajan, Harish|Rotaru, Amelia-Elena|Tremblay, Pier-Luc|Zhang, Tian|Nevin, Kelly P|Lovley, Derek R|Zengler, Karsten', 'Department of Bioengineering, University of California San Diego, La Jolla, California, United States of America.|Department of Bioengineering, University of California San Diego, La Jolla, California, United States of America.|Department of Microbiology, University of Massachusetts, Amherst, Massachusetts, United States of America.|Department of Microbiology, University of Massachusetts, Amherst, Massachusetts, United States of America.|Department of Microbiology, University of Massachusetts, Amherst, Massachusetts, United States of America.|Department of Microbiology, University of Massachusetts, Amherst, Massachusetts, United States of America.|Department of Microbiology, University of Massachusetts, Amherst, Massachusetts, United States of America.|Department of Bioengineering, University of California San Diego, La Jolla, California, United States of America.', 'United States|United States|United States|United States|United States|United States|United States|Un', 19, 'Carbon|Electron Transport|Energy Metabolism|Genome, Bacterial|Geobacter|Models, Biological', 'Journal Article', '10.1371/journal.pcbi.1003575', '24762737', 'Geobacter species are of great interest for environmental and biotechnology applications as they can carry out direct electron transfer to insoluble metals or other microorganisms and have the ability to assimilate inorganic carbon. Here, we report on the capability and key enabling metabolic machinery of Geobacter metallireducens GS-15 to carry out CO2 fixation and direct electron transfer to iron. An updated metabolic reconstruction was generated, growth screens on targeted conditions of interest were performed, and constraint-based analysis was utilized to characterize and evaluate critical pathways and reactions in G. metallireducens. The novel capability of G. metallireducens to grow autotrophically with formate and Fe(III) was predicted and subsequently validated in vivo. Additionally, the energetic cost of transferring electrons to an external electron acceptor was determined through analysis of growth experiments carried out using three different electron acceptors (Fe(III), nitrate, and fumarate) by systematically isolating and examining different parts of the electron transport chain. The updated reconstruction will serve as a knowledgebase for understanding and engineering Geobacter and similar species. '),
(86538, 2014, 'plos', 'Systematic evaluation of methods for integration of transcriptomic data into constraint-based models of metabolism', 'Machado, Daniel|Herrgård, Markus', 'The Novo Nordisk Foundation Center for Biosustainability, Technical University of Denmark, Horsholm, Denmark.|The Novo Nordisk Foundation Center for Biosustainability, Technical University of Denmark, Horsholm, Denmark.', 'Denmark|Denmark', 0, 'Escherichia coli|Metabolism|Models, Biological|Saccharomyces cerevisiae|Transcriptome', 'Journal Article', '10.1371/journal.pcbi.1003580', '24762745', 'Constraint-based models of metabolism are a widely used framework for predicting flux distributions in genome-scale biochemical networks. The number of published methods for integration of transcriptomic data into constraint-based models has been rapidly increasing. So far the predictive capability of these methods has not been critically evaluated and compared. This work presents a survey of recently published methods that use transcript levels to try to improve metabolic flux predictions either by generating flux distributions or by creating context-specific models. A subset of these methods is then systematically evaluated using published data from three different case studies in E. coli and S. cerevisiae. The flux predictions made by different methods using transcriptomic data are compared against experimentally determined extracellular and intracellular fluxes (from 13C-labeling data). The sensitivity of the results to method-specific parameters is also evaluated, as well as their robustness to noise in the data. The results show that none of the methods outperforms the others for all cases. Also, it is observed that for many conditions, the predictions obtained by simple flux balance analysis using growth maximization and parsimony criteria are as good or better than those obtained using methods that incorporate transcriptomic data. We further discuss the differences in the mathematical formulation of the methods, and their relation to the results we have obtained, as well as the connection to the underlying biological principles of metabolic regulation. '),
(86539, 2014, 'plos', 'Comparison of filtering methods for the modeling and retrospective forecasting of influenza epidemics', 'Yang, Wan|Karspeck, Alicia|Shaman, Jeffrey', 'Department of Environmental Health Sciences, Mailman School of Public Health, Columbia University, New York, New York, United States of America.|Climate and Global Dynamics Division, National Center for Atmospheric Research, Boulder, Colorado, United States of America.|Department of Environmental Health Sciences, Mailman School of Public Health, Columbia University, New York, New York, United States of America.', 'United States|United States|United States', 0, 'Forecasting|Humans|Influenza, Human|Models, Theoretical|Retrospective Studies|United States', 'Comparative Study', '10.1371/journal.pcbi.1003583', '24762780', 'A variety of filtering methods enable the recursive estimation of system state variables and inference of model parameters. These methods have found application in a range of disciplines and settings, including engineering design and forecasting, and, over the last two decades, have been applied to infectious disease epidemiology. For any system of interest, the ideal filter depends on the nonlinearity and complexity of the model to which it is applied, the quality and abundance of observations being entrained, and the ultimate application (e.g. forecast, parameter estimation, etc.). Here, we compare the performance of six state-of-the-art filter methods when used to model and forecast influenza activity. Three particle filters--a basic particle filter (PF) with resampling and regularization, maximum likelihood estimation via iterated filtering (MIF), and particle Markov chain Monte Carlo (pMCMC)--and three ensemble filters--the ensemble Kalman filter (EnKF), the ensemble adjustment Kalman filter (EAKF), and the rank histogram filter (RHF)--were used in conjunction with a humidity-forced susceptible-infectious-recovered-susceptible (SIRS) model and weekly estimates of influenza incidence. The modeling frameworks, first validated with synthetic influenza epidemic data, were then applied to fit and retrospectively forecast the historical incidence time series of seven influenza epidemics during 2003-2012, for 115 cities in the United States. Results suggest that when using the SIRS model the ensemble filters and the basic PF are more capable of faithfully recreating historical influenza incidence time series, while the MIF and pMCMC do not perform as well for multimodal outbreaks. For forecast of the week with the highest influenza activity, the accuracies of the six model-filter frameworks are comparable, the three particle filters perform slightly better predicting peaks 1-5 weeks in the future, the ensemble filters are more accurate predicting peaks in the past.'),
(86540, 2014, 'plos', 'Bayesian analysis for inference of an emerging epidemic: citrus canker in urban landscapes', 'Neri, Franco M|Cook, Alex R|Gibson, Gavin J|Gottwald, Tim R|Gilligan, Christopher A', 'Department of Plant Sciences, University of Cambridge, Cambridge, United Kingdom.|Saw Swee Hock School of Public Health, National University of Singapore and National University Health System, Singapore, Department of Statistics and Applied Probability, National University of Singapore, Singapore, Program in Health Services and Systems Research, Duke-NUS Graduate Medical School Singapore, Singapore, Communicable Disease Centre, Tan Tock Seng Hospital, Singapore.|Department of Actuarial Mathematics and Statistics and the Maxwell Institute for Mathematical Sciences, Heriot-Watt University, Edinburgh, United Kingdom.|U.S. Dept. of Agriculture, Agricultural Research Service, U.S. Horticultural Research Laboratory, Fort Pierce, Florida, United States of America.|Department of Plant Sciences, University of Cambridge, Cambridge, United Kingdom.', 'United Kingdom|Singapore|United Kingdom|United States|United Kingdom', 0, 'Bayes Theorem|Citrus|Epidemics|Markov Chains|Monte Carlo Method|Plant Diseases|Weather', 'Journal Article', '10.1371/journal.pcbi.1003587', '24762851', 'Outbreaks of infectious diseases require a rapid response from policy makers. The choice of an adequate level of response relies upon available knowledge of the spatial and temporal parameters governing pathogen spread, affecting, amongst others, the predicted severity of the epidemic. Yet, when a new pathogen is introduced into an alien environment, such information is often lacking or of no use, and epidemiological parameters must be estimated from the first observations of the epidemic. This poses a challenge to epidemiologists: how quickly can the parameters of an emerging disease be estimated? How soon can the future progress of the epidemic be reliably predicted? We investigate these issues using a unique, spatially and temporally resolved dataset for the invasion of a plant disease, Asiatic citrus canker in urban Miami. We use epidemiological models, Bayesian Markov-chain Monte Carlo, and advanced spatial statistical methods to analyse rates and extent of spread of the disease. A rich and complex epidemic behaviour is revealed. The spatial scale of spread is approximately constant over time and can be estimated rapidly with great precision (although the evidence for long-range transmission is inconclusive). In contrast, the rate of infection is characterised by strong monthly fluctuations that we associate with extreme weather events. Uninformed predictions from the early stages of the epidemic, assuming complete ignorance of the future environmental drivers, fail because of the unpredictable variability of the infection rate. Conversely, predictions improve dramatically if we assume prior knowledge of either the main environmental trend, or the main environmental events. A contrast emerges between the high detail attained by modelling in the spatiotemporal description of the epidemic and the bottleneck imposed on epidemic prediction by the limits of meteorological predictability. We argue that identifying such bottlenecks will be a fundamental step in future modelling of weather-driven epidemics. '),
(86541, 2014, 'plos', 'Knowledge-based fragment binding prediction', 'Tang, Grace W|Altman, Russ B', 'Department of Bioengineering, Stanford University, Stanford, California, United States of America.|Department of Bioengineering, Stanford University, Stanford, California, United States of America, Department of Genetics, Stanford University, Stanford, California, United States of America.', 'United States|United States', 16, 'Knowledge|Models, Molecular|Protein Binding|Proteins', 'Journal Article', '10.1371/journal.pcbi.1003589', '24762971', 'Target-based drug discovery must assess many drug-like compounds for potential activity. Focusing on low-molecular-weight compounds (fragments) can dramatically reduce the chemical search space. However, approaches for determining protein-fragment interactions have limitations. Experimental assays are time-consuming, expensive, and not always applicable. At the same time, computational approaches using physics-based methods have limited accuracy. With increasing high-resolution structural data for protein-ligand complexes, there is now an opportunity for data-driven approaches to fragment binding prediction. We present FragFEATURE, a machine learning approach to predict small molecule fragments preferred by a target protein structure. We first create a knowledge base of protein structural environments annotated with the small molecule substructures they bind. These substructures have low-molecular weight and serve as a proxy for fragments. FragFEATURE then compares the structural environments within a target protein to those in the knowledge base to retrieve statistically preferred fragments. It merges information across diverse ligands with shared substructures to generate predictions. Our results demonstrate FragFEATUREs ability to rediscover fragments corresponding to the ligand bound with 74% precision and 82% recall on average. For many protein targets, it identifies high scoring fragments that are substructures of known inhibitors. FragFEATURE thus predicts fragments that can serve as inputs to fragment-based drug design or serve as refinement criteria for creating target-specific compound libraries for experimental or computational screening. '),
(86542, 2014, 'plos', 'Glutamate-bound NMDARs arising from in vivo-like network activity extend spatio-temporal integration in a L5 cortical pyramidal cell model', 'Farinella, Matteo|Ruedt, Daniel T|Gleeson, Padraig|Lanore, Frederic|Silver, R Angus', 'Department of Neuroscience, Physiology and Pharmacology, University College London, London, United Kingdom.|Department of Neuroscience, Physiology and Pharmacology, University College London, London, United Kingdom.|Department of Neuroscience, Physiology and Pharmacology, University College London, London, United Kingdom.|Department of Neuroscience, Physiology and Pharmacology, University College London, London, United Kingdom.|Department of Neuroscience, Physiology and Pharmacology, University College London, London, United Kingdom.', 'United Kingdom|United Kingdom|United Kingdom|United Kingdom|United Kingdom', 14, 'Cerebral Cortex|Dendrites|Glutamic Acid|Models, Biological|Pyramidal Cells|Receptors, N-Methyl-D-Aspartate|Synapses', 'Journal Article', '10.1371/journal.pcbi.1003590', '24763087', 'In vivo, cortical pyramidal cells are bombarded by asynchronous synaptic input arising from ongoing network activity. However, little is known about how such background synaptic input interacts with nonlinear dendritic mechanisms. We have modified an existing model of a layer 5 (L5) pyramidal cell to explore how dendritic integration in the apical dendritic tuft could be altered by the levels of network activity observed in vivo. Here we show that asynchronous background excitatory input increases neuronal gain and extends both temporal and spatial integration of stimulus-evoked synaptic input onto the dendritic tuft. Addition of fast and slow inhibitory synaptic conductances, with properties similar to those from dendritic targeting interneurons, that provided a balanced background configuration, partially counteracted these effects, suggesting that inhibition can tune spatio-temporal integration in the tuft. Excitatory background input lowered the threshold for NMDA receptor-mediated dendritic spikes, extended their duration and increased the probability of additional regenerative events occurring in neighbouring branches. These effects were also observed in a passive model where all the non-synaptic voltage-gated conductances were removed. Our results show that glutamate-bound NMDA receptors arising from ongoing network activity can provide a powerful spatially distributed nonlinear dendritic conductance. This may enable L5 pyramidal cells to change their integrative properties as a function of local network activity, potentially allowing both clustered and spatially distributed synaptic inputs to be integrated over extended timescales. ');
INSERT INTO `papers` (`id`, `ano`, `journal`, `titulo`, `autores`, `afiliacao`, `pais`, `citacoes`, `palavra_chave`, `categorias`, `doi`, `pubmed`, `abstract`) VALUES
(86543, 2014, 'plos', 'Ecological consistency of SSU rRNA-based operational taxonomic units at a global scale', 'Schmidt, Thomas S B|Matias Rodrigues, João F|von Mering, Christian', 'Institute for Molecular Life Sciences and Swiss Institute of Bioinformatics, University of Zurich, Zürich, Switzerland.|Institute for Molecular Life Sciences and Swiss Institute of Bioinformatics, University of Zurich, Zürich, Switzerland.|Institute for Molecular Life Sciences and Swiss Institute of Bioinformatics, University of Zurich, Zürich, Switzerland.', 'Switzerland|Switzerland|Switzerland', 0, 'Ecology|Phylogeny|RNA, Ribosomal', 'Journal Article', '10.1371/journal.pcbi.1003594', '24763141', 'Operational Taxonomic Units (OTUs), usually defined as clusters of similar 16S/18S rRNA sequences, are the most widely used basic diversity units in large-scale characterizations of microbial communities. However, it remains unclear how well the various proposed OTU clustering algorithms approximate true microbial taxa. Here, we explore the ecological consistency of OTUs--based on the assumption that, like true microbial taxa, they should show measurable habitat preferences (niche conservatism). In a global and comprehensive survey of available microbial sequence data, we systematically parse sequence annotations to obtain broad ecological descriptions of sampling sites. Based on these, we observe that sequence-based microbial OTUs generally show high levels of ecological consistency. However, different OTU clustering methods result in marked differences in the strength of this signal. Assuming that ecological consistency can serve as an objective external benchmark for cluster quality, we conclude that hierarchical complete linkage clustering, which provided the most ecologically consistent partitions, should be the default choice for OTU clustering. To our knowledge, this is the first approach to assess cluster quality using an external, biologically meaningful parameter as a benchmark, on a global scale.'),
(86544, 2014, 'plos', 'Agent-based modeling of oxygen-responsive transcription factors in Escherichia coli', 'Bai, Hao|Rolfe, Matthew D|Jia, Wenjing|Coakley, Simon|Poole, Robert K|Green, Jeffrey|Holcombe, Mike', 'Department of Computer Science, University of Sheffield, Sheffield, United Kingdom.|Department of Molecular Biology and Biotechnology, University of Sheffield, Sheffield, United Kingdom.|Department of Molecular Biology and Biotechnology, University of Sheffield, Sheffield, United Kingdom.|Department of Computer Science, University of Sheffield, Sheffield, United Kingdom.|Department of Molecular Biology and Biotechnology, University of Sheffield, Sheffield, United Kingdom.|Department of Molecular Biology and Biotechnology, University of Sheffield, Sheffield, United Kingdom.|Department of Computer Science, University of Sheffield, Sheffield, United Kingdom.', 'United Kingdom|United Kingdom|United Kingdom|United Kingdom|United Kingdom|United Kingdom|United Kin', 11, 'Escherichia coli|Genes, Bacterial|Operon|Oxygen|Transcription Factors', 'Journal Article', '10.1371/journal.pcbi.1003595', '24763195', 'In the presence of oxygen (O2) the model bacterium Escherichia coli is able to conserve energy by aerobic respiration. Two major terminal oxidases are involved in this process - Cyo has a relatively low affinity for O2 but is able to pump protons and hence is energetically efficient, Cyd has a high affinity for O2 but does not pump protons. When E. coli encounters environments with different O2 availabilities, the expression of the genes encoding the alternative terminal oxidases, the cydAB and cyoABCDE operons, are regulated by two O2-responsive transcription factors, ArcA (an indirect O2 sensor) and FNR (a direct O2 sensor). It has been suggested that O2-consumption by the terminal oxidases located at the cytoplasmic membrane significantly affects the activities of ArcA and FNR in the bacterial nucleoid. In this study, an agent-based modeling approach has been taken to spatially simulate the uptake and consumption of O2 by E. coli and the consequent modulation of ArcA and FNR activities based on experimental data obtained from highly controlled chemostat cultures. The molecules of O2, transcription factors and terminal oxidases are treated as individual agents and their behaviors and interactions are imitated in a simulated 3-D E. coli cell. The model implies that there are two barriers that dampen the response of FNR to O2, i.e. consumption of O2 at the membrane by the terminal oxidases and reaction of O2 with cytoplasmic FNR. Analysis of FNR variants suggested that the monomer-dimer transition is the key step in FNR-mediated repression of gene expression. '),
(86545, 2014, 'plos', 'Feedback signals in myelodysplastic syndromes: increased self-renewal of the malignant clone suppresses normal hematopoiesis', 'Walenda, Thomas|Stiehl, Thomas|Braun, Hanna|Fröbel, Julia|Ho, Anthony D|Schroeder, Thomas|Goecke, Tamme W|Rath, Björn|Germing, Ulrich|Marciniak-Czochra, Anna|Wagner, Wolfgang', 'Helmholtz Institute for Biomedical Engineering, RWTH Aachen University Medical School, Aachen, Germany.|Interdisciplinary Center of Scientific Computing (IWR), Institute of Applied Mathematics, University of Heidelberg, Heidelberg, Germany.|Helmholtz Institute for Biomedical Engineering, RWTH Aachen University Medical School, Aachen, Germany.|Department of Hematology, Oncology and Clinical Immunology, Heinrich-Heine-University Düsseldorf, Düsseldorf, Germany.|Department of Medicine V, Medical Center, University of Heidelberg, Heidelberg, Germany.|Department of Hematology, Oncology and Clinical Immunology, Heinrich-Heine-University Düsseldorf, Düsseldorf, Germany.|Department of Obstetrics and Gynecology, RWTH Aachen University Medical School, Aachen, Germany.|Department for Orthopedics, RWTH Aachen University Medical School, Aachen, Germany.|Department of Hematology, Oncology and Clinical Immunology, Heinrich-Heine-University Düsseldorf, Düsseldorf, Germany.|Interdisciplinary Center of Scientific Computing (IWR), Institute of Applied Mathematics, University of Heidelberg, Heidelberg, Germany.|Helmholtz Institute for Biomedical Engineering, RWTH Aachen University Medical School, Aachen, Germany.', 'Germany|Germany|Germany|Germany|Germany|Germany|Germany|Germany|Germany|Germany|Germany', 22, 'Case-Control Studies|Enzyme-Linked Immunosorbent Assay|Feedback|Hematopoiesis|Humans|Myelodysplastic Syndromes', 'Journal Article', '10.1371/journal.pcbi.1003599', '24763223', 'Myelodysplastic syndromes (MDS) are triggered by an aberrant hematopoietic stem cell (HSC). It is, however, unclear how this clone interferes with physiologic blood formation. In this study, we followed the hypothesis that the MDS clone impinges on feedback signals for self-renewal and differentiation and thereby suppresses normal hematopoiesis. Based on the theory that the MDS clone affects feedback signals for self-renewal and differentiation and hence suppresses normal hematopoiesis, we have developed a mathematical model to simulate different modifications in MDS-initiating cells and systemic feedback signals during disease development. These simulations revealed that the disease initiating cells must have higher self-renewal rates than normal HSCs to outcompete normal hematopoiesis. We assumed that self-renewal is the default pathway of stem and progenitor cells which is down-regulated by an increasing number of primitive cells in the bone marrow niche--including the premature MDS cells. Furthermore, the proliferative signal is up-regulated by cytopenia. Overall, our model is compatible with clinically observed MDS development, even though a single mutation scenario is unlikely for real disease progression which is usually associated with complex clonal hierarchy. For experimental validation of systemic feedback signals, we analyzed the impact of MDS patient derived serum on hematopoietic progenitor cells in vitro: in fact, MDS serum slightly increased proliferation, whereas maintenance of primitive phenotype was reduced. However, MDS serum did not significantly affect colony forming unit (CFU) frequencies indicating that regulation of self-renewal may involve local signals from the niche. Taken together, we suggest that initial mutations in MDS particularly favor aberrant high self-renewal rates. Accumulation of primitive MDS cells in the bone marrow then interferes with feedback signals for normal hematopoiesis--which then results in cytopenia.'),
(86546, 2014, 'plos', 'Computational biology and bioinformatics in Nigeria', 'Fatumo, Segun A|Adoga, Moses P|Ojo, Opeolu O|Oluwagbemi, Olugbenga|Adeoye, Tolulope|Ewejobi, Itunuoluwa|Adebiyi, Marion|Adebiyi, Ezekiel|Bewaji, Clement|Nashiru, Oyekanmi', 'H3Africa Bioinformatics Network (H3ABioNet) Node, National Biotechnology Development Agency (NABDA), Federal Ministry of Science and Technology (FMST), Abuja, Nigeria, Human Genetics Department, Wellcome Trust Sanger Institute, Cambridge, United Kingdom, International Health Research Group, Department of Public Health & Primary Care, University of Cambridge, Cambridge, United Kingdom.|Computational and Evolutionary Biology/Bioinformatics, Faculty of Life Sciences, University of Manchester, Manchester, United Kingdom, Microbiology Unit, Department of Biological Sciences, Nasarawa State University, Keffi, Nigeria.|Centre for Molecular Biosciences, University of Ulster, Coleraine, United Kingdom, Chevron Biotechnology Centre, Federal University of Technology, Yola, Nigeria.|Department of Computer and Information Sciences, Covenant University, Ota, Nigeria, H3ABioNet Node, Covenant University Bioinformatics Research (CUBRe), Ota, Nigeria.|University of Hradec Kralove, Kralove, Czech Republic.|Department of Computer and Information Sciences, Covenant University, Ota, Nigeria, H3ABioNet Node, Covenant University Bioinformatics Research (CUBRe), Ota, Nigeria.|Department of Computer and Information Sciences, Covenant University, Ota, Nigeria, H3ABioNet Node, Covenant University Bioinformatics Research (CUBRe), Ota, Nigeria.|Department of Computer and Information Sciences, Covenant University, Ota, Nigeria, H3ABioNet Node, Covenant University Bioinformatics Research (CUBRe), Ota, Nigeria.|Department of Biochemistry, University of Ilorin, Ilorin, Nigeria.|H3Africa Bioinformatics Network (H3ABioNet) Node, National Biotechnology Development Agency (NABDA), Federal Ministry of Science and Technology (FMST), Abuja, Nigeria.', 'United Kingdom|United Kingdom|United Kingdom|Niger|-|Niger|Niger|Niger|Niger|Niger', 16, 'Computational Biology|Nigeria', 'Journal Article', '10.1371/journal.pcbi.1003516', '24763310', 'Over the past few decades, major advances in the field of molecular biology, coupled with advances in genomic technologies, have led to an explosive growth in the biological data generated by the scientific community. The critical need to process and analyze such a deluge of data and turn it into useful knowledge has caused bioinformatics to gain prominence and importance. Bioinformatics is an interdisciplinary research area that applies techniques, methodologies, and tools in computer and information science to solve biological problems. In Nigeria, bioinformatics has recently played a vital role in the advancement of biological sciences. As a developing country, the importance of bioinformatics is rapidly gaining acceptance, and bioinformatics groups comprised of biologists, computer scientists, and computer engineers are being constituted at Nigerian universities and research institutes. In this article, we present an overview of bioinformatics education and research in Nigeria. We also discuss professional societies and academic and research institutions that play central roles in advancing the discipline in Nigeria. Finally, we propose strategies that can bolster bioinformatics education and support from policy makers in Nigeria, with potential positive implications for other developing countries. '),
(86547, 2014, 'plos', 'Fast protein loop sampling and structure prediction using distance-guided sequential chain-growth Monte Carlo method', 'Tang, Ke|Zhang, Jinfeng|Liang, Jie', 'Department of Bioengineering, University of Illinois at Chicago, Chicago, Illinois, United States of America.|Department of Statistics, Florida State University, Tallahassee, Florida, United States of America.|Department of Bioengineering, University of Illinois at Chicago, Chicago, Illinois, United States of America.', 'United States|United States|United States', 29, 'Monte Carlo Method|Protein Conformation|Proteins', 'Journal Article', '10.1371/journal.pcbi.1003539', '24763317', 'Loops in proteins are flexible regions connecting regular secondary structures. They are often involved in protein functions through interacting with other molecules. The irregularity and flexibility of loops make their structures difficult to determine experimentally and challenging to model computationally. Conformation sampling and energy evaluation are the two key components in loop modeling. We have developed a new method for loop conformation sampling and prediction based on a chain growth sequential Monte Carlo sampling strategy, called Distance-guided Sequential chain-Growth Monte Carlo (DISGRO). With an energy function designed specifically for loops, our method can efficiently generate high quality loop conformations with low energy that are enriched with near-native loop structures. The average minimum global backbone RMSD for 1,000 conformations of 12-residue loops is 1:53 A° , with a lowest energy RMSD of 2:99 A° , and an average ensembleRMSD of 5:23 A° . A novel geometric criterion is applied to speed up calculations. The computational cost of generating 1,000 conformations for each of the x loops in a benchmark dataset is only about 10 cpu minutes for 12-residue loops, compared to ca 180 cpu minutes using the FALCm method. Test results on benchmark datasets show that DISGRO performs comparably or better than previous successful methods, while requiring far less computing time. DISGRO is especially effective in modeling longer loops (10-17 residues).'),
(86548, 2014, 'plos', 'Ten simple rules for the care and feeding of scientific data', 'Goodman, Alyssa|Pepe, Alberto|Blocker, Alexander W|Borgman, Christine L|Cranmer, Kyle|Crosas, Merce|Di Stefano, Rosanne|Gil, Yolanda|Groth, Paul|Hedstrom, Margaret|Hogg, David W|Kashyap, Vinay|Mahabal, Ashish|Siemiginowska, Aneta|Slavkovic, Aleksandra', 'Harvard University, Cambridge, Massachusetts, United States of America.|Harvard University, Cambridge, Massachusetts, United States of America.|Harvard University, Cambridge, Massachusetts, United States of America.|University of California, Los Angeles, Los Angeles, California, United States of America.|New York University, New York, New York, United States of America.|Harvard University, Cambridge, Massachusetts, United States of America.|Harvard University, Cambridge, Massachusetts, United States of America.|University of Southern California, Los Angeles, Los Angeles, California, United States of America.|Vrije Universiteit Amsterdam, Amsterdam, The Netherlands.|University of Michigan, Ann Arbor, Michigan, United States of America.|New York University, New York, New York, United States of America.|Harvard University, Cambridge, Massachusetts, United States of America.|California Institute of Technology, Pasadena, California, United States of America.|Harvard University, Cambridge, Massachusetts, United States of America.|Pennsylvania State University, State College, Pennsylvania, United States of America.', 'United States|United States|United States|United States|United States|United States|United States|Un', 79, 'Data Interpretation, Statistical|Guidelines as Topic', 'Editorial', '10.1371/journal.pcbi.1003542', '24763340', '-'),
(86549, 2014, 'plos', 'Mechanisms of zero-lag synchronization in cortical motifs', 'Gollo, Leonardo L|Mirasso, Claudio|Sporns, Olaf|Breakspear, Michael', 'Systems Neuroscience Group, QIMR Berghofer Medical Research Institute, Brisbane, Queensland, Australia.|IFISC, Instituto de Fsica Interdisciplinar y Sistemas Complejos (CSIC-UIB), Campus Universitat de les Illes Balears, Palma de Mallorca, Spain.|Department of Psychological and Brain Sciences, Indiana University, Bloomington, Indiana, United States of America.|Systems Neuroscience Group, QIMR Berghofer Medical Research Institute, Brisbane, Queensland, Australia, School of Psychiatry, University of New South Wales and The Black Dog Institute, Sydney, New South Wales, Australia, The Royal Brisbane and Womans Hospital, Brisbane, Queensland, Australia.', 'Australia|Spain|India|Australia', 61, 'Cerebral Cortex|Humans|Models, Biological', 'Journal Article', '10.1371/journal.pcbi.1003548', '24763382', 'Zero-lag synchronization between distant cortical areas has been observed in a diversity of experimental data sets and between many different regions of the brain. Several computational mechanisms have been proposed to account for such isochronous synchronization in the presence of long conduction delays: Of these, the phenomenon of dynamical relaying--a mechanism that relies on a specific network motif--has proven to be the most robust with respect to parameter mismatch and system noise. Surprisingly, despite a contrary belief in the community, the common driving motif is an unreliable means of establishing zero-lag synchrony. Although dynamical relaying has been validated in empirical and computational studies, the deeper dynamical mechanisms and comparison to dynamics on other motifs is lacking. By systematically comparing synchronization on a variety of small motifs, we establish that the presence of a single reciprocally connected pair--a resonance pair--plays a crucial role in disambiguating those motifs that foster zero-lag synchrony in the presence of conduction delays (such as dynamical relaying) from those that do not (such as the common driving triad). Remarkably, minor structural changes to the common driving motif that incorporate a reciprocal pair recover robust zero-lag synchrony. The findings are observed in computational models of spiking neurons, populations of spiking neurons and neural mass models, and arise whether the oscillatory systems are periodic, chaotic, noise-free or driven by stochastic inputs. The influence of the resonance pair is also robust to parameter mismatch and asymmetrical time delays amongst the elements of the motif. We call this manner of facilitating zero-lag synchrony resonance-induced synchronization, outline the conditions for its occurrence, and propose that it may be a general mechanism to promote zero-lag synchrony in the brain.'),
(86550, 2014, 'plos', 'Bistable dynamics underlying excitability of ion homeostasis in neuron models', 'Hxc3xbcbel, Niklas|Schxc3xb6ll, Eckehard|Dahlem, Markus A', 'Department of Theoretical Physics, Technische Universitxc3xa4t Berlin, Berlin, Germany.|Department of Theoretical Physics, Technische Universitxc3xa4t Berlin, Berlin, Germany.|Department of Physics, Humboldt Universitxc3xa4t zu Berlin, Berlin, Germany.', 'Germany|Germany|Germany', 26, 'Action Potentials|Animals|Computer Simulation|Energy Metabolism|Homeostasis|Humans|Ion Channel Gating|Ions|Membrane Potentials|Models, Neurological|Neurons|Sodium-Potassium-Exchanging ATPase', 'Journal Article', '10.1371/journal.pcbi.1003551', '24784149', 'When neurons fire action potentials, dissipation of free energy is usually not directly considered, because the change in free energy is often negligible compared to the immense reservoir stored in neural transmembrane ion gradients and the long-term energy requirements are met through chemical energy, i.e., metabolism. However, these gradients can temporarily nearly vanish in neurological diseases, such as migraine and stroke, and in traumatic brain injury from concussions to severe injuries. We study biophysical neuron models based on the Hodgkin-Huxley (HH) formalism extended to include time-dependent ion concentrations inside and outside the cell and metabolic energy-driven pumps. We reveal the basic mechanism of a state of free energy-starvation (FES) with bifurcation analyses showing that ion dynamics is for a large range of pump rates bistable without contact to an ion bath. This is interpreted as a threshold reduction of a new fundamental mechanism of ionic excitability that causes a long-lasting but transient FES as observed in pathological states. We can in particular conclude that a coupling of extracellular ion concentrations to a large glial-vascular bath can take a role as an inhibitory mechanism crucial in ion homeostasis, while the Naxe2x81xba/Kxe2x81xba pumps alone are insufficient to recover from FES. Our results provide the missing link between the HH formalism and activator-inhibitor models that have been successfully used for modeling migraine phenotypes, and therefore will allow us to validate the hypothesis that migraine symptoms are explained by disturbed function in ion channel subunits, Naxe2x81xba/Kxe2x81xba pumps, and other proteins that regulate ion homeostasis.'),
(86551, 2014, 'plos', 'Interplay of intrinsic and synaptic conductances in the generation of high-frequency oscillations in interneuronal networks with irregular spiking', 'Baroni, Fabiano|Burkitt, Anthony N|Grayden, David B', 'NeuroEngineering Laboratory, Dept. of Electrical & Electronic Engineering, University of Melbourne, Parkville, Victoria, Australia, Centre for Neural Engineering, University of Melbourne, Parkville, Victoria, Australia.|NeuroEngineering Laboratory, Dept. of Electrical & Electronic Engineering, University of Melbourne, Parkville, Victoria, Australia, Centre for Neural Engineering, University of Melbourne, Parkville, Victoria, Australia, Bionics Institute, East Melbourne, Victoria, Australia.|NeuroEngineering Laboratory, Dept. of Electrical & Electronic Engineering, University of Melbourne, Parkville, Victoria, Australia, Centre for Neural Engineering, University of Melbourne, Parkville, Victoria, Australia, Bionics Institute, East Melbourne, Victoria, Australia.', 'Australia|Australia|Australia', 10, 'Action Potentials|Animals|Biological Clocks|Computer Simulation|Differential Threshold|Electric Conductivity|Humans|Interneurons|Models, Neurological|Nerve Net|Synapses|Synaptic Transmission', 'Journal Article', '10.1371/journal.pcbi.1003574', '24784237', 'High-frequency oscillations (above 30 Hz) have been observed in sensory and higher-order brain areas, and are believed to constitute a general hallmark of functional neuronal activation. Fast inhibition in interneuronal networks has been suggested as a general mechanism for the generation of high-frequency oscillations. Certain classes of interneurons exhibit subthreshold oscillations, but the effect of this intrinsic neuronal property on the population rhythm is not completely understood. We study the influence of intrinsic damped subthreshold oscillations in the emergence of collective high-frequency oscillations, and elucidate the dynamical mechanisms that underlie this phenomenon. We simulate neuronal networks composed of either Integrate-and-Fire (IF) or Generalized Integrate-and-Fire (GIF) neurons. The IF model displays purely passive subthreshold dynamics, while the GIF model exhibits subthreshold damped oscillations. Individual neurons receive inhibitory synaptic currents mediated by spiking activity in their neighbors as well as noisy synaptic bombardment, and fire irregularly at a lower rate than population frequency. We identify three factors that affect the influence of single-neuron properties on synchronization mediated by inhibition: i) the firing rate response to the noisy background input, ii) the membrane potential distribution, and iii) the shape of Inhibitory Post-Synaptic Potentials (IPSPs). For hyperpolarizing inhibition, the GIF IPSP profile (factor iii)) exhibits post-inhibitory rebound, which induces a coherent spike-mediated depolarization across cells that greatly facilitates synchronous oscillations. This effect dominates the network dynamics, hence GIF networks display stronger oscillations than IF networks. However, the restorative current in the GIF neuron lowers firing rates and narrows the membrane potential distribution (factors i) and ii), respectively), which tend to decrease synchrony. If inhibition is shunting instead of hyperpolarizing, post-inhibitory rebound is not elicited and factors i) and ii) dominate, yielding lower synchrony in GIF networks than in IF networks. '),
(86552, 2014, 'plos', 'A computational model for the analysis of lipoprotein distributions in the mouse: translating FPLC profiles to lipoprotein metabolism', 'Sips, Fianne L P|Tiemann, Christian A|Oosterveer, Maaike H|Groen, Albert K|Hilbers, Peter A J|van Riel, Natal A W', 'Department of Biomedical Engineering, Eindhoven University of Technology, Eindhoven, The Netherlands, Netherlands Consortium for Systems Biology, University of Amsterdam, Amsterdam, The Netherlands.|Department of Biomedical Engineering, Eindhoven University of Technology, Eindhoven, The Netherlands, Netherlands Consortium for Systems Biology, University of Amsterdam, Amsterdam, The Netherlands.|Department of Pediatrics, University Groningen, University Medical Center Groningen, Groningen, The Netherlands.|Netherlands Consortium for Systems Biology, University of Amsterdam, Amsterdam, The Netherlands, Department of Pediatrics, University Groningen, University Medical Center Groningen, Groningen, The Netherlands, Department of Laboratory Medicine, University Groningen, University Medical Center Groningen, Groningen, The Netherlands.|Department of Biomedical Engineering, Eindhoven University of Technology, Eindhoven, The Netherlands, Netherlands Consortium for Systems Biology, University of Amsterdam, Amsterdam, The Netherlands.|Department of Biomedical Engineering, Eindhoven University of Technology, Eindhoven, The Netherlands, Netherlands Consortium for Systems Biology, University of Amsterdam, Amsterdam, The Netherlands.', 'Netherlands|Netherlands|Netherlands|Netherlands|Netherlands|Netherlands', 11, 'Animals|Chromatography, Liquid|Computer Simulation|Gene Expression Profiling|Lipoproteins|Mice|Mice, Inbred C57BL|Mice, Knockout|Mice, Transgenic|Models, Biological|Peptide Mapping', 'Journal Article', '10.1371/journal.pcbi.1003579', '24784354', 'Disturbances of lipoprotein metabolism are recognized as indicators of cardiometabolic disease risk. Lipoprotein size and composition, measured in a lipoprotein profile, are considered to be disease risk markers. However, the measured profile is a collective result of complex metabolic interactions, which complicates the identification of changes in metabolism. In this study we aim to develop a method which quantitatively relates murine lipoprotein size, composition and concentration to the molecular mechanisms underlying lipoprotein metabolism. We introduce a computational framework which incorporates a novel kinetic model of murine lipoprotein metabolism. The model is applied to compute a distribution of plasma lipoproteins, which is then related to experimental lipoprotein profiles through the generation of an in silico lipoprotein profile. The model was first applied to profiles obtained from wild-type C57Bl/6J mice. The results provided insight into the interplay of lipoprotein production, remodelling and catabolism. Moreover, the concentration and metabolism of unmeasured lipoprotein components could be determined. The model was validated through the prediction of lipoprotein profiles of several transgenic mouse models commonly used in cardiovascular research. Finally, the framework was employed for longitudinal analysis of the profiles of C57Bl/6J mice following a pharmaceutical intervention with a liver X receptor (LXR) agonist. The multifaceted regulatory response to the administration of the compound is incompletely understood. The results explain the characteristic changes of the observed lipoprotein profile in terms of the underlying metabolic perturbation and resultant modifications of lipid fluxes in the body. The Murine Lipoprotein Profiler (MuLiP) presented here is thus a valuable tool to assess the metabolic origin of altered murine lipoprotein profiles and can be applied in preclinical research performed in mice for analysis of lipid fluxes and lipoprotein composition. '),
(86553, 2014, 'plos', 'Determining effects of non-synonymous SNPs on protein-protein interactions using supervised and semi-supervised learning', 'Zhao, Nan|Han, Jing Ginger|Shyu, Chi-Ren|Korkin, Dmitry', 'Informatics Institute, University of Missouri, Columbia, Missouri, United States of America.|Informatics Institute, University of Missouri, Columbia, Missouri, United States of America.|Informatics Institute, University of Missouri, Columbia, Missouri, United States of America, Department of Computer Science, University of Missouri, Columbia, Missouri, United States of America.|Informatics Institute, University of Missouri, Columbia, Missouri, United States of America, Department of Computer Science, University of Missouri, Columbia, Missouri, United States of America, Bond Life Science Center, University of Missouri, Columbia, Missouri, United States of America.', 'United States|United States|United States|United States', 46, 'Algorithms|Artificial Intelligence|Breast Neoplasms|Diabetes Mellitus|Genetic Association Studies|Genetic Predisposition to Disease|Humans|Pattern Recognition, Automated|Polymorphism, Single Nucleotide|Protein Interaction Mapping|Proteome', 'Journal Article', '10.1371/journal.pcbi.1003592', '24784581', 'Single nucleotide polymorphisms (SNPs) are among the most common types of genetic variation in complex genetic disorders. A growing number of studies link the functional role of SNPs with the networks and pathways mediated by the disease-associated genes. For example, many non-synonymous missense SNPs (nsSNPs) have been found near or inside the protein-protein interaction (PPI) interfaces. Determining whether such nsSNP will disrupt or preserve a PPI is a challenging task to address, both experimentally and computationally. Here, we present this task as three related classification problems, and develop a new computational method, called the SNP-IN tool (non-synonymous SNP INteraction effect predictor). Our method predicts the effects of nsSNPs on PPIs, given the interactions structure. It leverages supervised and semi-supervised feature-based classifiers, including our new Random Forest self-learning protocol. The classifiers are trained based on a dataset of comprehensive mutagenesis studies for 151 PPI complexes, with experimentally determined binding affinities of the mutant and wild-type interactions. Three classification problems were considered: (1) a 2-class problem (strengthening/weakening PPI mutations), (2) another 2-class problem (mutations that disrupt/preserve a PPI), and (3) a 3-class classification (detrimental/neutral/beneficial mutation effects). In total, 11 different supervised and semi-supervised classifiers were trained and assessed resulting in a promising performance, with the weighted f-measure ranging from 0.87 for Problem 1 to 0.70 for the most challenging Problem 3. By integrating prediction results of the 2-class classifiers into the 3-class classifier, we further improved its performance for Problem 3. To demonstrate the utility of SNP-IN tool, it was applied to study the nsSNP-induced rewiring of two disease-centered networks. The accurate and balanced performance of SNP-IN tool makes it readily available to study the rewiring of large-scale protein-protein interaction networks, and can be useful for functional annotation of disease-associated SNPs. SNIP-IN tool is freely accessible as a web-server at http://korkinlab.org/snpintool/. '),
(86554, 2014, 'plos', 'Paving the way towards a successful and fulfilling career in computational biology', 'Oluwagbemi, Olugbenga|Adebiyi, Marion|Fatumo, Segun|Macintyre, Geoff', 'Department of Computer and Information Sciences, College of Science and Technology, Bioinformatics Unit, Covenant University, Ota, Ogun State, Nigeria.|Department of Computer and Information Sciences, College of Science and Technology, Bioinformatics Unit, Covenant University, Ota, Ogun State, Nigeria.|H3Africa Bioinformatics Network (H3ABioNet) Node, National Biotechnology Development Agency (NABDA), Federal Ministry of Science and Technology (FMST), Abuja, Nigeria, Human Genetics Department, Wellcome Trust Sanger Institute, Cambridge, United Kingdom, International Health Research Group, Department of Public Health and Primary Care, University of Cambridge, Cambridge, United Kingdom.|Centre for Neural Engineering, The University of Melbourne, Carlton, Victoria, Australia, Department of Computing and Information Systems, The University of Melbourne, Parkville, Victoria, Australia.', 'Niger|Niger|United Kingdom|Australia', 1, 'Career Mobility|Computational Biology|Internationality|Societies|Workforce', 'Journal Article', '10.1371/journal.pcbi.1003593', '24784875', '-'),
(86555, 2014, 'plos', 'NbIT--a new information theory-based analysis of allosteric mechanisms reveals residues that underlie function in the leucine transporter LeuT', 'LeVine, Michael V|Weinstein, Harel', 'Department of Physiology and Biophysics, Weill Cornell Medical College of Cornell University (WCMC), New York, New York, United States of America.|Department of Physiology and Biophysics, Weill Cornell Medical College of Cornell University (WCMC), New York, New York, United States of America, HRH Prince Alwaleed Bin Talal Bin Abdulaziz Alsaud Institute of Computational Biomedicine, Weill Cornell Medical College of Cornell University, New York, New York, United States of America.', 'United States|United States', 56, 'Algorithms|Allosteric Regulation|Allosteric Site|Amino Acid Transport Systems|Bacterial Proteins|Binding Sites|Computer Simulation|Information Theory|Leucine|Models, Chemical|Molecular Dynamics Simulation|Protein Binding|Protein Conformation|Protein Structure, Tertiary', 'Journal Article', '10.1371/journal.pcbi.1003603', '24785005', 'Complex networks of interacting residues and microdomains in the structures of biomolecular systems underlie the reliable propagation of information from an input signal, such as the concentration of a ligand, to sites that generate the appropriate output signal, such as enzymatic activity. This information transduction often carries the signal across relatively large distances at the molecular scale in a form of allostery that is essential for the physiological functions performed by biomolecules. While allosteric behaviors have been documented from experiments and computation, the mechanism of this form of allostery proved difficult to identify at the molecular level. Here, we introduce a novel analysis framework, called N-body Information Theory (NbIT) analysis, which is based on information theory and uses measures of configurational entropy in a biomolecular system to identify microdomains and individual residues that act as (i)-channels for long-distance information sharing between functional sites, and (ii)-coordinators that organize dynamics within functional sites. Application of the new method to molecular dynamics (MD) trajectories of the occluded state of the bacterial leucine transporter LeuT identifies a channel of allosteric coupling between the functionally important intracellular gate and the substrate binding sites known to modulate it. NbIT analysis is shown also to differentiate residues involved primarily in stabilizing the functional sites, from those that contribute to allosteric couplings between sites. NbIT analysis of MD data thus reveals rigorous mechanistic elements of allostery underlying the dynamics of biomolecular systems. '),
(86556, 2014, 'plos', 'Linear superposition and prediction of bacterial promoter activity dynamics in complex conditions', 'Rothschild, Daphna|Dekel, Erez|Hausser, Jean|Bren, Anat|Aidelberg, Guy|Szekely, Pablo|Alon, Uri', 'Department of Molecular Cell Biology, Weizmann Institute of Science, Rehovot, Israel.|Department of Molecular Cell Biology, Weizmann Institute of Science, Rehovot, Israel.|Department of Molecular Cell Biology, Weizmann Institute of Science, Rehovot, Israel.|Department of Molecular Cell Biology, Weizmann Institute of Science, Rehovot, Israel.|Department of Molecular Cell Biology, Weizmann Institute of Science, Rehovot, Israel.|Department of Molecular Cell Biology, Weizmann Institute of Science, Rehovot, Israel.|Department of Molecular Cell Biology, Weizmann Institute of Science, Rehovot, Israel.', 'Israel|Israel|Israel|Israel|Israel|Israel|Israel', 13, 'Adaptation, Physiological|Bacterial Proteins|Cell Proliferation|Computer Simulation|Escherichia coli|Gene Expression Regulation, Bacterial|Linear Models|Models, Biological|Promoter Regions, Genetic|Stress, Physiological', 'Journal Article', '10.1371/journal.pcbi.1003602', '24809350', 'Bacteria often face complex environments. We asked how gene expression in complex conditions relates to expression in simpler conditions. To address this, we obtained accurate promoter activity dynamical measurements on 94 genes in E. coli in environments made up of all possible combinations of four nutrients and stresses. We find that the dynamics across conditions is well described by two principal component curves specific to each promoter. As a result, the promoter activity dynamics in a combination of conditions is a weighted average of the dynamics in each condition alone. The weights tend to sum up to approximately one. This weighted-average property, called linear superposition, allows predicting the promoter activity dynamics in a combination of conditions based on measurements of pairs of conditions. If these findings apply more generally, they can vastly reduce the number of experiments needed to understand how E. coli responds to the combinatorially huge space of possible environments. '),
(86557, 2014, 'plos', 'A simulated intermediate state for folding and aggregation provides insights into xcex94N6 xcexb22-microglobulin amyloidogenic behavior', 'Estxc3xa1cio, Sxc3xadlvia G|Krobath, Heinrich|Vila-Vixc3xa7osa, Diogo|Machuqueiro, Miguel|Shakhnovich, Eugene I|Faxc3xadsca, Patrxc3xadcia F N', 'Centro de Fxc3xadsica da Matxc3xa9ria Condensada & Departamento de Fxc3xadsica, Faculdade de Cixc3xaancias, Universidade de Lisboa, Lisboa, Portugal.|Centro de Fxc3xadsica da Matxc3xa9ria Condensada & Departamento de Fxc3xadsica, Faculdade de Cixc3xaancias, Universidade de Lisboa, Lisboa, Portugal.|Centro de Quxc3xadmica e Bioquxc3xadmica & Departamento de Quxc3xadmica e Bioquxc3xadmica, Faculdade de Cixc3xaancias, Universidade de Lisboa, Lisboa, Portugal.|Centro de Quxc3xadmica e Bioquxc3xadmica & Departamento de Quxc3xadmica e Bioquxc3xadmica, Faculdade de Cixc3xaancias, Universidade de Lisboa, Lisboa, Portugal.|Department of Chemistry and Chemical Biology, Harvard University, Cambridge, Massachusetts, United States of America.|Centro de Fxc3xadsica da Matxc3xa9ria Condensada & Departamento de Fxc3xadsica, Faculdade de Cixc3xaancias, Universidade de Lisboa, Lisboa, Portugal.', 'Portugal|Portugal|Portugal|Portugal|United States|Portugal', 24, 'Amyloidogenic Proteins|Binding Sites|Computer Simulation|Dimerization|Models, Chemical|Models, Molecular|Multiprotein Complexes|Protein Binding|Protein Conformation|Protein Folding|Protein Structure, Tertiary|beta 2-Microglobulin', 'Journal Article', '10.1371/journal.pcbi.1003606', '24809460', 'A major component of ex vivo amyloid plaques of patients with dialysis-related amyloidosis (DRA) is a cleaved variant of xcexb22-microglobulin (xcex94N6) lacking the first six N-terminal residues. Here we perform a computational study on xcex94N6, which provides clues to understand the amyloidogenicity of the full-length xcexb22-microglobulin. Contrary to the wild-type form, xcex94N6 is able to efficiently nucleate fibrillogenesis in vitro at physiological pH. This behavior is enhanced by a mild acidification of the medium such as that occurring in the synovial fluid of DRA patients. Results reported in this work, based on molecular simulations, indicate that deletion of the N-terminal hexapeptide triggers the formation of an intermediate state for folding and aggregation with an unstructured strand A and a native-like core. Strand A plays a pivotal role in aggregation by acting as a sticky hook in dimer assembly. This study further predicts that the detachment of strand A from the core is maximized at pH 6.2 resulting into higher aggregation efficiency. The structural mapping of the dimerization interface suggests that Tyr10, His13, Phe30 and His84 are hot-spot residues in xcex94N6 amyloidogenesis. '),
(86558, 2014, 'plos', 'Synonymous constraint elements show a tendency to encode intrinsically disordered protein segments', 'Macossay-Castillo, Mauricio|Kosol, Simone|Tompa, Peter|Pancsa, Rita', 'Vlaams Instituut voor Biotechnologie (VIB) Department of Structural Biology, Vrije Universiteit Brussel, Brussels, Belgium.|Vlaams Instituut voor Biotechnologie (VIB) Department of Structural Biology, Vrije Universiteit Brussel, Brussels, Belgium.|Vlaams Instituut voor Biotechnologie (VIB) Department of Structural Biology, Vrije Universiteit Brussel, Brussels, Belgium, Institute of Enzymology, Research Centre for Natural Sciences, Hungarian Academy of Sciences, Budapest, Hungary.|Vlaams Instituut voor Biotechnologie (VIB) Department of Structural Biology, Vrije Universiteit Brussel, Brussels, Belgium.', 'Belgium|Belgium|Belgium|Belgium', 15, 'Amino Acid Sequence|Base Sequence|Computer Simulation|Humans|Intrinsically Disordered Proteins|Models, Chemical|Models, Genetic|Models, Molecular|Molecular Sequence Data|Open Reading Frames|Structure-Activity Relationship', 'Journal Article', '10.1371/journal.pcbi.1003607', '24809503', 'Synonymous constraint elements (SCEs) are protein-coding genomic regions with very low synonymous mutation rates believed to carry additional, overlapping functions. Thousands of such potentially multi-functional elements were recently discovered by analyzing the levels and patterns of evolutionary conservation in human coding exons. These elements provide a good opportunity to improve our understanding of how the redundant nature of the genetic code is exploited in the cell. Our premise is that the protein segments encoded by such elements might better comply with the increased functional demands if they are structurally less constrained (i.e. intrinsically disordered). To test this idea, we investigated the protein segments encoded by SCEs with computational tools to describe the underlying structural properties. In addition to SCEs, we examined the level of disorder, secondary structure, and sequence complexity of protein regions overlapping with experimentally validated splice regulatory sites. We show that multi-functional gene regions translate into protein segments that are significantly enriched in structural disorder and compositional bias, while they are depleted in secondary structure and domain annotations compared to reference segments of similar lengths. This tendency suggests that relaxed protein structural constraints provide an advantage when accommodating multiple overlapping functions in coding regions. '),
(86559, 2014, 'plos', 'Predicting the responses of repetitively firing neurons to current noise', 'Wilson, Charles J|Barraza, David|Troyer, Todd|Farries, Michael A', 'Department of Biology, University of Texas at San Antonio, San Antonio, Texas, United States of America.|Department of Biology, University of Texas at San Antonio, San Antonio, Texas, United States of America.|Department of Biology, University of Texas at San Antonio, San Antonio, Texas, United States of America.|Department of Biology, University of Texas at San Antonio, San Antonio, Texas, United States of America.', 'United States|United States|United States|United States', 16, 'Action Potentials|Animals|Biological Clocks|Cells, Cultured|Computer Simulation|Membrane Potentials|Models, Neurological|Models, Statistical|Neurons|Rats|Rats, Sprague-Dawley|Signal-To-Noise Ratio|Subthalamic Nucleus', 'Journal Article', '10.1371/journal.pcbi.1003612', '24809636', 'We used phase resetting methods to predict firing patterns of rat subthalamic nucleus (STN) neurons when their rhythmic firing was densely perturbed by noise. We applied sequences of contiguous brief (0.5-2 ms) current pulses with amplitudes drawn from a Gaussian distribution (10-100 pA standard deviation) to autonomously firing STN neurons in slices. Current noise sequences increased the variability of spike times with little or no effect on the average firing rate. We measured the infinitesimal phase resetting curve (PRC) for each neuron using a noise-based method. A phase model consisting of only a firing rate and PRC was very accurate at predicting spike timing, accounting for more than 80% of spike time variance and reliably reproducing the spike-to-spike pattern of irregular firing. An approximation for the evolution of phase was used to predict the effect of firing rate and noise parameters on spike timing variability. It quantitatively predicted changes in variability of interspike intervals with variation in noise amplitude, pulse duration and firing rate over the normal range of STN spontaneous rates. When constant current was used to drive the cells to higher rates, the PRC was altered in size and shape and accurate predictions of the effects of noise relied on incorporating these changes into the prediction. Application of rate-neutral changes in conductance showed that changes in PRC shape arise from conductance changes known to accompany rate increases in STN neurons, rather than the rate increases themselves. Our results show that firing patterns of densely perturbed oscillators cannot readily be distinguished from those of neurons randomly excited to fire from the rest state. The spike timing of repetitively firing neurons may be quantitatively predicted from the input and their PRCs, even when they are so densely perturbed that they no longer fire rhythmically. '),
(86560, 2014, 'plos', 'Reciprocal regulation as a source of ultrasensitivity in two-component systems with a bifunctional sensor kinase', 'Straube, Ronny', 'Analysis and Redesign of Biological Networks Group, Max Planck Institute for Dynamics of Complex Technical Systems, Magdeburg, Germany.', 'Germany', 12, 'Bacterial Proteins|Computer Simulation|Enzyme Activation|Escherichia coli|Feedback, Physiological|Models, Biological|Models, Chemical|Multifunctional Enzymes|Phosphorylation|Phosphotransferases|Signal Transduction|Transcription Factors', 'Journal Article', '10.1371/journal.pcbi.1003614', '24809699', 'Two-component signal transduction systems, where the phosphorylation state of a regulator protein is modulated by a sensor kinase, are common in bacteria and other microbes. In many of these systems, the sensor kinase is bifunctional catalyzing both, the phosphorylation and the dephosphorylation of the regulator protein in response to input signals. Previous studies have shown that systems with a bifunctional enzyme can adjust the phosphorylation level of the regulator protein independently of the total protein concentrations--a property known as concentration robustness. Here, I argue that two-component systems with a bifunctional enzyme may also exhibit ultrasensitivity if the input signal reciprocally affects multiple activities of the sensor kinase. To this end, I consider the case where an allosteric effector inhibits autophosphorylation and, concomitantly, activates the enzymes phosphatase activity, as observed experimentally in the PhoQ/PhoP and NRII/NRI systems. A theoretical analysis reveals two operating regimes under steady state conditions depending on the effector affinity: If the affinity is low the system produces a graded response with respect to input signals and exhibits stimulus-dependent concentration robustness--consistent with previous experiments. In contrast, a high-affinity effector may generate ultrasensitivity by a similar mechanism as phosphorylation-dephosphorylation cycles with distinct converter enzymes. The occurrence of ultrasensitivity requires saturation of the sensor kinases phosphatase activity, but is restricted to low effector concentrations, which suggests that this mode of operation might be employed for the detection and amplification of low abundant input signals. Interestingly, the same mechanism also applies to covalent modification cycles with a bifunctional converter enzyme, which suggests that reciprocal regulation, as a mechanism to generate ultrasensitivity, is not restricted to two-component systems, but may apply more generally to bifunctional enzyme systems.');
INSERT INTO `papers` (`id`, `ano`, `journal`, `titulo`, `autores`, `afiliacao`, `pais`, `citacoes`, `palavra_chave`, `categorias`, `doi`, `pubmed`, `abstract`) VALUES
(86561, 2014, 'plos', 'Axonal noise as a source of synaptic variability', 'Neishabouri, Ali|Faisal, A Aldo', 'Department of Bioengineering, Imperial College London, London, United Kingdom.|Department of Bioengineering, Imperial College London, London, United Kingdom, Department of Computing, Imperial College London, London, United Kingdom, MRC Clinical Sciences Centre, London, United Kingdom.', 'United Kingdom|United Kingdom', 22, 'Action Potentials|Animals|Axons|Cells, Cultured|Computer Simulation|Humans|Models, Anatomic|Models, Neurological|Models, Statistical|Neural Conduction|Synapses|Synaptic Potentials|Synaptic Transmission', 'Journal Article', '10.1371/journal.pcbi.1003615', '24809823', 'Post-synaptic potential (PSP) variability is typically attributed to mechanisms inside synapses, yet recent advances in experimental methods and biophysical understanding have led us to reconsider the role of axons as highly reliable transmission channels. We show that in many thin axons of our brain, the action potential (AP) waveform and thus the Ca++ signal controlling vesicle release at synapses will be significantly affected by the inherent variability of ion channel gating. We investigate how and to what extent fluctuations in the AP waveform explain observed PSP variability. Using both biophysical theory and stochastic simulations of central and peripheral nervous system axons from vertebrates and invertebrates, we show that channel noise in thin axons (<1 µm diameter) causes random fluctuations in AP waveforms. AP height and width, both experimentally characterised parameters of post-synaptic response amplitude, vary e.g. by up to 20 mV and 0.5 ms while a single AP propagates in C-fibre axons. We show how AP height and width variabilities increase with a ¾ power-law as diameter decreases and translate these fluctuations into post-synaptic response variability using biophysical data and models of synaptic transmission. We find for example that for mammalian unmyelinated axons with 0.2 µm diameter (matching cerebellar parallel fibres) axonal noise alone can explain half of the PSP variability in cerebellar synapses. We conclude that axonal variability may have considerable impact on synaptic response variability. Thus, in many experimental frameworks investigating synaptic transmission through paired-cell recordings or extracellular stimulation of presynaptic neurons, causes of variability may have been confounded. We thereby show how bottom-up aggregation of molecular noise sources contributes to our understanding of variability observed at higher levels of biological organisation. '),
(86562, 2014, 'plos', 'Barriers to cooperation aid ideological rigidity and threaten societal collapse', 'Jusup, Marko|Matsuo, Tadasu|Iwasa, Yoh', 'Department of Biology, Kyushu University, Fukuoka, Japan.|Faculty of Economics, Ritsumeikan University, Kusatsu, Japan.|Department of Biology, Kyushu University, Fukuoka, Japan.', 'Japan|Japan|Japan', 9, 'Attitude|Choice Behavior|Computer Simulation|Conflict (Psychology)|Cooperative Behavior|Culture|Game Theory|Humans|Models, Theoretical|Social Networking|Social Values', 'Journal Article', '10.1371/journal.pcbi.1003618', '24809975', 'Understanding the factors that promote, disrupt, or shape the nature of cooperation is one of the main tasks of evolutionary biology. Here, we focus on attitudes and beliefs supportive of in-group favoritism and strict adherence to moral consensus, collectively known as ideological rigidity, that have been linked with both ends of the political spectrum. The presence among the political right and the left is likely to make ideological rigidity a major determinant of the political discourse with an important social function. To better understand this function, we equip the indirect reciprocity framework--widely used to explain evaluation-mediated social cooperation--with multiple stylized value systems, each corresponding to the different degree of ideological rigidity. By running game theoretical simulations, we observe the competitive evolution of these systems, map conditions that lead to more ideologically rigid societies, and identify potentially disastrous outcomes. In particular, we uncover that barriers to cooperation aid ideological rigidity. The society may even polarize to the extent where social parasites overrun the population and cause the complete collapse of the social structure. These results have implications for lawmakers globally, warning against restrictive or protectionist policies.'),
(86563, 2014, 'plos', 'Myxococcus xanthus gliding motors are elastically coupled to the substrate as predicted by the focal adhesion model of gliding motility', 'Balagam, Rajesh|Litwin, Douglas B|Czerwinski, Fabian|Sun, Mingzhai|Kaplan, Heidi B|Shaevitz, Joshua W|Igoshin, Oleg A', 'Department of Bioengineering, Rice University, Houston, Texas, United States of America.|Department of Microbiology and Molecular Genetics, University of Texas - Houston Medical School, Houston, Texas, United States of America.|Department of Physics and the Lewis-Sigler Institute of Integrative Genomics, Princeton University, Princeton, New Jersey, United States of America.|Department of Physics and the Lewis-Sigler Institute of Integrative Genomics, Princeton University, Princeton, New Jersey, United States of America.|Department of Microbiology and Molecular Genetics, University of Texas - Houston Medical School, Houston, Texas, United States of America.|Department of Physics and the Lewis-Sigler Institute of Integrative Genomics, Princeton University, Princeton, New Jersey, United States of America.|Department of Bioengineering, Rice University, Houston, Texas, United States of America.', 'United States|United States|Jersey|Jersey|United States|Jersey|United States', 25, 'Bacterial Adhesion|Bacterial Proteins|Computer Simulation|Elastic Modulus|Focal Adhesions|Friction|Models, Biological|Molecular Motor Proteins|Motion|Myxococcus xanthus|Viscosity', 'Journal Article', '10.1371/journal.pcbi.1003619', '24810164', 'Myxococcus xanthus is a model organism for studying bacterial social behaviors due to its ability to form complex multi-cellular structures. Knowledge of M. xanthus surface gliding motility and the mechanisms that coordinated it are critically important to our understanding of collective cell behaviors. Although the mechanism of gliding motility is still under investigation, recent experiments suggest that there are two possible mechanisms underlying force production for cell motility: the focal adhesion mechanism and the helical rotor mechanism, which differ in the biophysics of the cell-substrate interactions. Whereas the focal adhesion model predicts an elastic coupling, the helical rotor model predicts a viscous coupling. Using a combination of computational modeling, imaging, and force microscopy, we find evidence for elastic coupling in support of the focal adhesion model. Using a biophysical model of the M. xanthus cell, we investigated how the mechanical interactions between cells are affected by interactions with the substrate. Comparison of modeling results with experimental data for cell-cell collision events pointed to a strong, elastic attachment between the cell and substrate. These results are robust to variations in the mechanical and geometrical parameters of the model. We then directly measured the motor-substrate coupling by monitoring the motion of optically trapped beads and find that motor velocity decreases exponentially with opposing load. At high loads, motor velocity approaches zero velocity asymptotically and motors remain bound to beads indicating a strong, elastic attachment. '),
(86564, 2014, 'plos', 'Slow feature analysis on retinal waves leads to V1 complex cells', 'Dähne, Sven|Wilbert, Niko|Wiskott, Laurenz', 'Machine Learning Group, Department of Computer Science, Berlin Institute of Technology, Berlin, Germany, Institute for Theoretical Biology, Humboldt-University, Berlin, Germany, Bernstein Center for Computational Neuroscience, Berlin, Germany.|Institute for Theoretical Biology, Humboldt-University, Berlin, Germany, Bernstein Center for Computational Neuroscience, Berlin, Germany.|Institute for Theoretical Biology, Humboldt-University, Berlin, Germany, Bernstein Center for Computational Neuroscience, Berlin, Germany, Institute for Neural Computation, Ruhr-University Bochum, Bochum, Germany.', 'Germany|Germany|Germany', 5, 'Animals|Biological Clocks|Brain Waves|Computer Simulation|Humans|Models, Neurological|Nerve Net|Retinal Neurons|Visual Cortex|Visual Perception', 'Journal Article', '10.1371/journal.pcbi.1003564', '24810948', 'The developing visual system of many mammalian species is partially structured and organized even before the onset of vision. Spontaneous neural activity, which spreads in waves across the retina, has been suggested to play a major role in these prenatal structuring processes. Recently, it has been shown that when employing an efficient coding strategy, such as sparse coding, these retinal activity patterns lead to basis functions that resemble optimal stimuli of simple cells in primary visual cortex (V1). Here we present the results of applying a coding strategy that optimizes for temporal slowness, namely Slow Feature Analysis (SFA), to a biologically plausible model of retinal waves. Previously, SFA has been successfully applied to model parts of the visual system, most notably in reproducing a rich set of complex-cell features by training SFA with quasi-natural image sequences. In the present work, we obtain SFA units that share a number of properties with cortical complex-cells by training on simulated retinal waves. The emergence of two distinct properties of the SFA units (phase invariance and orientation tuning) is thoroughly investigated via control experiments and mathematical analysis of the input-output functions found by SFA. The results support the idea that retinal waves share relevant temporal and spatial properties with natural visual input. Hence, retinal waves seem suitable training stimuli to learn invariances and thereby shape the developing early visual system such that it is best prepared for coding input from the natural world. '),
(86565, 2014, 'plos', 'Effects of specular highlights on perceived surface convexity', 'Adams, Wendy J|Elder, James H', 'Psychology, University of Southampton, Southampton, United Kingdom.|Centre for Vision Research, York University, Toronto, Canada.', 'United Kingdom|Canada', 10, 'Animals|Computer Simulation|Contrast Sensitivity|Cues|Form Perception|Humans|Image Interpretation, Computer-Assisted|Lighting|Models, Biological|Vision Disparity', 'Journal Article', '10.1371/journal.pcbi.1003576', '24811069', 'Shading is known to produce vivid perceptions of depth. However, the influence of specular highlights on perceived shape is unclear: some studies have shown that highlights improve quantitative shape perception while others have shown no effect. Here we ask how specular highlights combine with Lambertian shading cues to determine perceived surface curvature, and to what degree this is based upon a coherent model of the scene geometry. Observers viewed ambiguous convex/concave shaded surfaces, with or without highlights. We show that the presence/absence of specular highlights has an effect on qualitative shape, their presence biasing perception toward convex interpretations of ambiguous shaded objects. We also find that the alignment of a highlight with the Lambertian shading modulates its effect on perceived shape, misaligned highlights are less likely to be perceived as specularities, and thus have less effect on shape perception. Increasing the depth of the surface or the slant of the illuminant also modulated the effect of the highlight, increasing the bias toward convexity. The effect of highlights on perceived shape can be understood probabilistically in terms of scene geometry: for deeper objects and/or highly slanted illuminants, highlights will occur on convex but not concave surfaces, due to occlusion of the illuminant. Given uncertainty about the exact object depth and illuminant direction, the presence of a highlight increases the probability that the surface is convex. '),
(86566, 2014, 'plos', 'From the phenomenology to the mechanisms of consciousness: Integrated Information Theory 30', 'Oizumi, Masafumi|Albantakis, Larissa|Tononi, Giulio', 'Department of Psychiatry, University of Wisconsin, Madison, Wisconsin, United States of America, RIKEN Brain Science Institute, Wako-shi, Saitama, Japan.|Department of Psychiatry, University of Wisconsin, Madison, Wisconsin, United States of America.|Department of Psychiatry, University of Wisconsin, Madison, Wisconsin, United States of America.', 'Japan|United States|United States', 0, 'Action Potentials|Animals|Brain|Computer Simulation|Consciousness|Humans|Information Theory|Models, Neurological|Nerve Net|Neurons|Synaptic Transmission', 'Journal Article', '10.1371/journal.pcbi.1003588', '24811198', 'This paper presents Integrated Information Theory (IIT) of consciousness 3.0, which incorporates several advances over previous formulations. IIT starts from phenomenological axioms: information says that each experience is specific--it is what it is by how it differs from alternative experiences, integration says that it is unified--irreducible to non-interdependent components, exclusion says that it has unique borders and a particular spatio-temporal grain. These axioms are formalized into postulates that prescribe how physical mechanisms, such as neurons or logic gates, must be configured to generate experience (phenomenology). The postulates are used to define intrinsic information as differences that make a difference within a system, and integrated information as information specified by a whole that cannot be reduced to that specified by its parts. By applying the postulates both at the level of individual mechanisms and at the level of systems of mechanisms, IIT arrives at an identity: an experience is a maximally irreducible conceptual structure (MICS, a constellation of concepts in qualia space), and the set of elements that generates it constitutes a complex. According to IIT, a MICS specifies the quality of an experience and integrated information xcexa6Max its quantity. From the theory follow several results, including: a system of mechanisms may condense into a major complex and non-overlapping minor complexes, the concepts that specify the quality of an experience are always about the complex itself and relate only indirectly to the external environment, anatomical connectivity influences complexes and associated MICS, a complex can generate a MICS even if its elements are inactive, simple systems can be minimally conscious, complicated systems can be unconscious, there can be true zombies--unconscious feed-forward systems that are functionally equivalent to conscious complexes.'),
(86567, 2014, 'plos', 'A computational framework for analyzing stochasticity in gene expression', 'Sherman, Marc S|Cohen, Barak A', 'Computational and Molecular Biophysics, Washington University in St. Louis, St. Louis, Missouri, United States of America, Center for Genome Sciences, Department of Genetics, Washington University in St. Louis, St. Louis, Missouri, United States of America.|Center for Genome Sciences, Department of Genetics, Washington University in St. Louis, St. Louis, Missouri, United States of America.', 'United States|United States', 0, 'Animals|Computer Simulation|Gene Expression Regulation|Humans|Models, Genetic|Models, Statistical|Protein Biosynthesis|Proteome|Stochastic Processes|Transcription, Genetic', 'Journal Article', '10.1371/journal.pcbi.1003596', '24811315', 'Stochastic fluctuations in gene expression give rise to distributions of protein levels across cell populations. Despite a mounting number of theoretical models explaining stochasticity in protein expression, we lack a robust, efficient, assumption-free approach for inferring the molecular mechanisms that underlie the shape of protein distributions. Here we propose a method for inferring sets of biochemical rate constants that govern chromatin modification, transcription, translation, and RNA and protein degradation from stochasticity in protein expression. We asked whether the rates of these underlying processes can be estimated accurately from protein expression distributions, in the absence of any limiting assumptions. To do this, we (1) derived analytical solutions for the first four moments of the protein distribution, (2) found that these four moments completely capture the shape of protein distributions, and (3) developed an efficient algorithm for inferring gene expression rate constants from the moments of protein distributions. Using this algorithm we find that most protein distributions are consistent with a large number of different biochemical rate constant sets. Despite this degeneracy, the solution space of rate constants almost always informs on underlying mechanism. For example, we distinguish between regimes where transcriptional bursting occurs from regimes reflecting constitutive transcript production. Our method agrees with the current standard approach, and in the restrictive regime where the standard method operates, also identifies rate constants not previously obtainable. Even without making any assumptions we obtain estimates of individual biochemical rate constants, or meaningful ratios of rate constants, in 91% of tested cases. In some cases our method identified all of the underlying rate constants. The framework developed here will be a powerful tool for deducing the contributions of particular molecular mechanisms to specific patterns of gene expression. '),
(86568, 2014, 'plos', 'Modelling negative feedback networks for activating transcription factor 3 predicts a dominant role for miRNAs in immediate early gene regulation', 'Tindall, Marcus J|Clerk, Angela', 'Department of Mathematics & Statistics, University of Reading, Reading, Berkshire, United Kingdom, School of Biological Sciences, University of Reading, Reading, Berkshire, United Kingdom.|School of Biological Sciences, University of Reading, Reading, Berkshire, United Kingdom.', 'United Kingdom|United Kingdom', 0, 'Activating Transcription Factor 3|Animals|Computer Simulation|Feedback, Physiological|Gene Expression Regulation|Humans|MicroRNAs|Models, Biological|Myocytes, Cardiac|Transcription Factors|Transcriptional Activation', 'Journal Article', '10.1371/journal.pcbi.1003597', '24811474', 'Activating transcription factor 3 (Atf3) is rapidly and transiently upregulated in numerous systems, and is associated with various disease states. Atf3 is required for negative feedback regulation of other genes, but is itself subject to negative feedback regulation possibly by autorepression. In cardiomyocytes, Atf3 and Egr1 mRNAs are upregulated via ERK1/2 signalling and Atf3 suppresses Egr1 expression. We previously developed a mathematical model for the Atf3-Egr1 system. Here, we adjusted and extended the model to explore mechanisms of Atf3 feedback regulation. Introduction of an autorepressive loop for Atf3 tuned down its expression and inhibition of Egr1 was lost, demonstrating that negative feedback regulation of Atf3 by Atf3 itself is implausible in this context. Experimentally, signals downstream from ERK1/2 suppress Atf3 expression. Mathematical modelling indicated that this cannot occur by phosphorylation of pre-existing inhibitory transcriptional regulators because the time delay is too short. De novo synthesis of an inhibitory transcription factor (ITF) with a high affinity for the Atf3 promoter could suppress Atf3 expression, but (as with the Atf3 autorepression loop) inhibition of Egr1 was lost. Developing the model to include newly-synthesised miRNAs very efficiently terminated Atf3 protein expression and, with a 4-fold increase in the rate of degradation of mRNA from the mRNA/miRNA complex, profiles for Atf3 mRNA, Atf3 protein and Egr1 mRNA approximated to the experimental data. Combining the ITF model with that of the miRNA did not improve the profiles suggesting that miRNAs are likely to play a dominant role in switching off Atf3 expression post-induction. '),
(86569, 2014, 'plos', 'Ten simple rules for internship in a pharmaceutical company', 'Chen, Bin', 'Division of Systems Medicine, Department of Pediatrics, Stanford University School of Medicine, Stanford, California, United States of America.', 'United States', 3, 'Algorithms|Computational Biology|Drug Industry|Employment|Job Application|Workforce', 'Editorial', '10.1371/journal.pcbi.1003600', '24811706', '-'),
(86570, 2014, 'plos', 'Combined role of seizure-induced dendritic morphology alterations and spine loss in newborn granule cells with mossy fiber sprouting on the hyperexcitability of a computer model of the dentate gyrus', 'Tejada, Julian|Garcia-Cairasco, Norberto|Roque, Antonio C', 'Departamento de Física, Faculdade de Filosofia, Ciências e Letras de Ribeirão Preto, Universidade de São Paulo, Ribeirão Preto, São Paulo, Brasil, Departamento de Fisiologia, Faculdade de Medicina de Ribeirão Preto, Ribeirão Preto, São Paulo, Brasil.|Departamento de Fisiologia, Faculdade de Medicina de Ribeirão Preto, Ribeirão Preto, São Paulo, Brasil.|Departamento de Física, Faculdade de Filosofia, Ciências e Letras de Ribeirão Preto, Universidade de São Paulo, Ribeirão Preto, São Paulo, Brasil.', '-|-|-', 0, 'Action Potentials|Animals|Animals, Newborn|Cells, Cultured|Cerebellar Nuclei|Computer Simulation|Dendritic Spines|Epilepsy|Models, Anatomic|Models, Neurological|Nerve Fibers|Neurogenesis|Rats', 'Journal Article', '10.1371/journal.pcbi.1003601', '24811867', 'Temporal lobe epilepsy strongly affects hippocampal dentate gyrus granule cells morphology. These cells exhibit seizure-induced anatomical alterations including mossy fiber sprouting, changes in the apical and basal dendritic tree and suffer substantial dendritic spine loss. The effect of some of these changes on the hyperexcitability of the dentate gyrus has been widely studied. For example, mossy fiber sprouting increases the excitability of the circuit while dendritic spine loss may have the opposite effect. However, the effect of the interplay of these different morphological alterations on the hyperexcitability of the dentate gyrus is still unknown. Here we adapted an existing computational model of the dentate gyrus by replacing the reduced granule cell models with morphologically detailed models coming from three-dimensional reconstructions of mature cells. The model simulates a network with 10% of the mossy fiber sprouting observed in the pilocarpine (PILO) model of epilepsy. Different fractions of the mature granule cell models were replaced by morphologically reconstructed models of newborn dentate granule cells from animals with PILO-induced Status Epilepticus, which have apical dendritic alterations and spine loss, and control animals, which do not have these alterations. This complex arrangement of cells and processes allowed us to study the combined effect of mossy fiber sprouting, altered apical dendritic tree and dendritic spine loss in newborn granule cells on the excitability of the dentate gyrus model. Our simulations suggest that alterations in the apical dendritic tree and dendritic spine loss in newborn granule cells have opposing effects on the excitability of the dentate gyrus after Status Epilepticus. Apical dendritic alterations potentiate the increase of excitability provoked by mossy fiber sprouting while spine loss curtails this increase. '),
(86571, 2014, 'plos', 'Towards structural systems pharmacology to study complex diseases and personalized medicine', 'Xie, Lei|Ge, Xiaoxia|Tan, Hepan|Xie, Li|Zhang, Yinliang|Hart, Thomas|Yang, Xiaowei|Bourne, Philip E', 'Department of Computer Science, Hunter College, The City University of New York, New York, New York, United States of America, Ph.D. Program in Computer Science, Biology, and Biochemistry, The Graduate Center, The City University of New York, New York, New York, United States of America.|Department of Computer Science, Hunter College, The City University of New York, New York, New York, United States of America.|Department of Computer Science, Hunter College, The City University of New York, New York, New York, United States of America.|Skaggs School of Pharmacy and Pharmaceutical Sciences, University of California San Diego, La Jolla, California, United States of America.|Skaggs School of Pharmacy and Pharmaceutical Sciences, University of California San Diego, La Jolla, California, United States of America.|Department of Biological Sciences, Hunter College, The City University of New York, New York, New York, United States of America.|School of Public Health, Hunter College, The City University of New York, New York, New York, United States of America.|Skaggs School of Pharmacy and Pharmaceutical Sciences, University of California San Diego, La Jolla, California, United States of America.', 'United States|United States|United States|United States|United States|United States|United States|Un', 43, 'Drug Design|Genome-Wide Association Study|Genomics|High-Throughput Nucleotide Sequencing|Pharmacogenetics|Precision Medicine|Systems Theory', 'Journal Article', '10.1371/journal.pcbi.1003554', '24830652', 'Genome-Wide Association Studies (GWAS), whole genome sequencing, and high-throughput omics techniques have generated vast amounts of genotypic and molecular phenotypic data. However, these data have not yet been fully explored to improve the effectiveness and efficiency of drug discovery, which continues along a one-drug-one-target-one-disease paradigm. As a partial consequence, both the cost to launch a new drug and the attrition rate are increasing. Systems pharmacology and pharmacogenomics are emerging to exploit the available data and potentially reverse this trend, but, as we argue here, more is needed. To understand the impact of genetic, epigenetic, and environmental factors on drug action, we must study the structural energetics and dynamics of molecular interactions in the context of the whole human genome and interactome. Such an approach requires an integrative modeling framework for drug action that leverages advances in data-driven statistical modeling and mechanism-based multiscale modeling and transforms heterogeneous data from GWAS, high-throughput sequencing, structural genomics, functional genomics, and chemical genomics into unified knowledge. This is not a small task, but, as reviewed here, progress is being made towards the final goal of personalized medicines for the treatment of complex diseases. '),
(86572, 2014, 'plos', 'Mathematical modeling reveals kinetics of lymphocyte recirculation in the whole organism', 'Ganusov, Vitaly V|Auerbach, Jeremy', 'Department of Microbiology, University of Tennessee, Knoxville, Tennessee, United States of America, Department of Mathematics, University of Tennessee, Knoxville, Tennessee, United States of America.|Department of Mathematics, University of Tennessee, Knoxville, Tennessee, United States of America.', 'United States|United States', 0, 'Animals|Blood Flow Velocity|Cell Movement|Computer Simulation|Lymphatic System|Lymphocytes|Microcirculation|Models, Cardiovascular|Rats', 'Journal Article', '10.1371/journal.pcbi.1003586', '24830705', 'The kinetics of recirculation of naive lymphocytes in the body has important implications for the speed at which local infections are detected and controlled by immune responses. With a help of a novel mathematical model, we analyze experimental data on migration of 51Cr-labeled thoracic duct lymphocytes (TDLs) via major lymphoid and nonlymphoid tissues of rats in the absence of systemic antigenic stimulation. We show that at any point of time, 95% of lymphocytes in the blood travel via capillaries in the lung or sinusoids of the liver and only 5% migrate to secondary lymphoid tissues such as lymph nodes, Peyers patches, or the spleen. Interestingly, our analysis suggests that lymphocytes travel via lung capillaries and liver sinusoids at an extremely rapid rate with the average residence time in these tissues being less than 1 minute. The model also predicts a relatively short average residence time of TDLs in the spleen (2.5 hours) and a longer average residence time of TDLs in major lymph nodes and Peyers patches (10 hours). Surprisingly, we find that the average residence time of lymphocytes is similar in lymph nodes draining the skin (subcutaneous LNs) or the gut (mesenteric LNs) or in Peyers patches. Applying our model to an additional dataset on lymphocyte migration via resting and antigen-stimulated lymph nodes we find that enlargement of antigen-stimulated lymph nodes occurs mainly due to increased entrance rate of TDLs into the nodes and not due to decreased exit rate as has been suggested in some studies. Taken together, our analysis for the first time provides a comprehensive, systems view of recirculation kinetics of thoracic duct lymphocytes in the whole organism. '),
(86573, 2014, 'plos', 'Structurally-constrained relationships between cognitive states in the human brain', 'Hermundstad, Ann M|Brown, Kevin S|Bassett, Danielle S|Aminoff, Elissa M|Frithsen, Amy|Johnson, Arianne|Tipper, Christine M|Miller, Michael B|Grafton, Scott T|Carlson, Jean M', 'Department of Physics, University of California, Santa Barbara, Santa Barbara, California, United States of America, Department of Physics and Astronomy, University of Pennsylvania, Philadelphia, Pennsylvania, United States of America.|Department of Biomedical Engineering, University of Connecticut, Storrs, Conneticutt, United States of America, Department of Physics, University of Connecticut, Storrs, Conneticutt, United States of America, Department of Chemical and Biomolecular Engineering, University of Connecticut, Storrs, Conneticutt, United States of America, Department of Marine Sciences, University of Connecticut, Groton, Conneticutt, United States of America.|Department of Physics, University of California, Santa Barbara, Santa Barbara, California, United States of America, Sage Center for the Study of the Mind, University of California, Santa Barbara, Santa Barbara, California, United States of America, Department of Bioengineering, University of Pennsylvania, Philadelphia, Pennsylvania, United States of America, Department of Electrical and Systems Engineering, University of Pennsylvania, Philadelphia, Pennsylvania, United States of America.|Center for the Neural Basis of Cognition, Carnegie Mellon University, Pittsburgh, Pennsylvania, United States of America.|Department of Psychological and Brain Sciences, University of California, Santa Barbara, Santa Barbara, California, United States of America.|Department of Psychological and Brain Sciences, University of California, Santa Barbara, Santa Barbara, California, United States of America.|Department of Psychiatry, Faculty of Medicine, University of British Columbia, Vancouver, British Columbia, Canada.|Department of Psychological and Brain Sciences, University of California, Santa Barbara, Santa Barbara, California, United States of America.|Department of Psychological and Brain Sciences, University of California, Santa Barbara, Santa Barbara, California, United States of America.|Department of Physics, University of California, Santa Barbara, Santa Barbara, California, United States of America.', 'United States|United States|United States|United States|United States|United States|Canada|United St', 0, 'Attention|Brain|Cognition|Computer Simulation|Connectome|Humans|Memory|Models, Anatomic|Models, Neurological|Nerve Net|White Matter', 'Journal Article', '10.1371/journal.pcbi.1003591', '24830758', 'The anatomical connectivity of the human brain supports diverse patterns of correlated neural activity that are thought to underlie cognitive function. In a manner sensitive to underlying structural brain architecture, we examine the extent to which such patterns of correlated activity systematically vary across cognitive states. Anatomical white matter connectivity is compared with functional correlations in neural activity measured via blood oxygen level dependent (BOLD) signals. Functional connectivity is separately measured at rest, during an attention task, and during a memory task. We assess these structural and functional measures within previously-identified resting-state functional networks, denoted task-positive and task-negative networks, that have been independently shown to be strongly anticorrelated at rest but also involve regions of the brain that routinely increase and decrease in activity during task-driven processes. We find that the density of anatomical connections within and between task-positive and task-negative networks is differentially related to strong, task-dependent correlations in neural activity. The space mapped out by the observed structure-function relationships is used to define a quantitative measure of separation between resting, attention, and memory states. We find that the degree of separation between states is related to both general measures of behavioral performance and relative differences in task-specific measures of attention versus memory performance. These findings suggest that the observed separation between cognitive states reflects underlying organizational principles of human brain structure and function. '),
(86574, 2014, 'plos', 'Inference of RNA polymerase II transcription dynamics from chromatin immunoprecipitation time course data', 'wa Maina, Ciira|Honkela, Antti|Matarese, Filomena|Grote, Korbinian|Stunnenberg, Hendrik G|Reid, George|Lawrence, Neil D|Rattray, Magnus', 'Department of Electrical and Electronic Engineering, Dedan Kimathi University of Technology, Nyeri, Kenya.|Helsinki Institute for Information Technology HIIT, Department of Computer Science, University of Helsinki, Helsinki, Finland.|Nijmegen Centre for Molecular Life Sciences, Radboud University Nijmegen, Nijmegen, The Netherlands.|Genomatix Software GmbH, Muenchen, Germany.|Nijmegen Centre for Molecular Life Sciences, Radboud University Nijmegen, Nijmegen, The Netherlands.|Institute for Molecular Biology, Mainz, Germany.|Department of Computer Science, University of Sheffield, Sheffield, United Kingdom.|Faculty of Life Sciences, University of Manchester, Manchester, United Kingdom.', 'Kenya|Finland|Netherlands|Germany|Netherlands|Germany|United Kingdom|United Kingdom', 13, 'Animals|Chromatin Immunoprecipitation|Computer Simulation|DNA-Directed RNA Polymerases|Humans|Models, Genetic|Models, Statistical|Promoter Regions, Genetic|Protein Binding|Transcription, Genetic|Transcriptional Activation', 'Journal Article', '10.1371/journal.pcbi.1003598', '24830797', 'Gene transcription mediated by RNA polymerase II (pol-II) is a key step in gene expression. The dynamics of pol-II moving along the transcribed region influence the rate and timing of gene expression. In this work, we present a probabilistic model of transcription dynamics which is fitted to pol-II occupancy time course data measured using ChIP-Seq. The model can be used to estimate transcription speed and to infer the temporal pol-II activity profile at the gene promoter. Model parameters are estimated using either maximum likelihood estimation or via Bayesian inference using Markov chain Monte Carlo sampling. The Bayesian approach provides confidence intervals for parameter estimates and allows the use of priors that capture domain knowledge, e.g. the expected range of transcription speeds, based on previous experiments. The model describes the movement of pol-II down the gene body and can be used to identify the time of induction for transcriptionally engaged genes. By clustering the inferred promoter activity time profiles, we are able to determine which genes respond quickly to stimuli and group genes that share activity profiles and may therefore be co-regulated. We apply our methodology to biological data obtained using ChIP-seq to measure pol-II occupancy genome-wide when MCF-7 human breast cancer cells are treated with estradiol (E2). The transcription speeds we obtain agree with those obtained previously for smaller numbers of genes with the advantage that our approach can be applied genome-wide. We validate the biological significance of the pol-II promoter activity clusters by investigating cluster-specific transcription factor binding patterns and determining canonical pathway enrichment. We find that rapidly induced genes are enriched for both estrogen receptor alpha (ERxcexb1) and FOXA1 binding in their proximal promoter regions.'),
(86575, 2014, 'plos', 'Slow noise in the period of a biological oscillator underlies gradual trends and abrupt transitions in phasic relationships in hybrid neural networks', 'Thounaojam, Umeshkanta S|Cui, Jianxia|Norman, Sharon E|Butera, Robert J|Canavier, Carmen C', 'Department of Cell Biology and Anatomy, Louisiana State University Health Sciences Center New Orleans, Louisiana, United States of America.|BioCircuits Institute, University of California, San Diego, La Jolla, California, United States of America, School of Electrical and Computer Engineering, Georgia Institute of Technology, Atlanta, Georgia, United States of America.|School of Electrical and Computer Engineering, Georgia Institute of Technology, Atlanta, Georgia, United States of America.|School of Electrical and Computer Engineering, Georgia Institute of Technology, Atlanta, Georgia, United States of America, Department of Biomedical Engineering, Georgia Institute of Technology and Emory University, Atlanta Georgia, United States of America.|Department of Cell Biology and Anatomy, Louisiana State University Health Sciences Center New Orleans, Louisiana, United States of America, Neuroscience Center of Excellence, Louisiana State University Health Sciences Center, New Orleans, Louisiana, United States of America.', 'United States|Georgia|Georgia|Georgia|United States', 8, 'Action Potentials|Animals|Aplysia|Biological Clocks|Cells, Cultured|Computer Simulation|Feedback, Physiological|Models, Neurological|Models, Statistical|Nerve Net|Neurons|Signal-To-Noise Ratio', 'Journal Article', '10.1371/journal.pcbi.1003622', '24830924', 'In order to study the ability of coupled neural oscillators to synchronize in the presence of intrinsic as opposed to synaptic noise, we constructed hybrid circuits consisting of one biological and one computational model neuron with reciprocal synaptic inhibition using the dynamic clamp. Uncoupled, both neurons fired periodic trains of action potentials. Most coupled circuits exhibited qualitative changes between one-to-one phase-locking with fairly constant phasic relationships and phase slipping with a constant progression in the phasic relationships across cycles. The phase resetting curve (PRC) and intrinsic periods were measured for both neurons, and used to construct a map of the firing intervals for both the coupled and externally forced (PRC measurement) conditions. For the coupled network, a stable fixed point of the map predicted phase locking, and its absence produced phase slipping. Repetitive application of the map was used to calibrate different noise models to simultaneously fit the noise level in the measurement of the PRC and the dynamics of the hybrid circuit experiments. Only a noise model that added history-dependent variability to the intrinsic period could fit both data sets with the same parameter values, as well as capture bifurcations in the fixed points of the map that cause switching between slipping and locking. We conclude that the biological neurons in our study have slowly-fluctuating stochastic dynamics that confer history dependence on the period. Theoretical results to date on the behavior of ensembles of noisy biological oscillators may require re-evaluation to account for transitions induced by slow noise dynamics. '),
(86576, 2014, 'plos', 'ATPase subdomain IA is a mediator of interdomain allostery in Hsp70 molecular chaperones', 'General, Ignacio J|Liu, Ying|Blackburn, Mandy E|Mao, Wenzhi|Gierasch, Lila M|Bahar, Ivet', 'Department of Computational and Systems Biology, School of Medicine, University of Pittsburgh, Pittsburgh, Pennsylvania, United States of America.|Department of Computational and Systems Biology, School of Medicine, University of Pittsburgh, Pittsburgh, Pennsylvania, United States of America.|Department of Biochemistry & Molecular Biology, University of Massachusetts Amherst, Amherst, Massachusetts, United States of America.|Department of Computational and Systems Biology, School of Medicine, University of Pittsburgh, Pittsburgh, Pennsylvania, United States of America, Department of Pharmacology, Tsinghua University, Beijing, China.|Department of Biochemistry & Molecular Biology, University of Massachusetts Amherst, Amherst, Massachusetts, United States of America, Department of Chemistry, University of Massachusetts Amherst, Amherst, Massachusetts, United States of America.|Department of Computational and Systems Biology, School of Medicine, University of Pittsburgh, Pittsburgh, Pennsylvania, United States of America.', 'United States|United States|United States|China|United States|United States', 50, 'Adenosine Triphosphatases|Binding Sites|Computer Simulation|HSP70 Heat-Shock Proteins|Models, Chemical|Models, Molecular|Molecular Chaperones|Protein Binding|Protein Conformation|Protein Structure, Tertiary', 'Journal Article', '10.1371/journal.pcbi.1003624', '24831085', 'The versatile functions of the heat shock protein 70 (Hsp70) family of molecular chaperones rely on allosteric interactions between their nucleotide-binding and substrate-binding domains, NBD and SBD. Understanding the mechanism of interdomain allostery is essential to rational design of Hsp70 modulators. Yet, despite significant progress in recent years, how the two Hsp70 domains regulate each others activity remains elusive. Covariance data from experiments and computations emerged in recent years as valuable sources of information towards gaining insights into the molecular events that mediate allostery. In the present study, conservation and covariance properties derived from both sequence and structural dynamics data are integrated with results from Perturbation Response Scanning and in vivo functional assays, so as to establish the dynamical basis of interdomain signal transduction in Hsp70s. Our study highlights the critical roles of SBD residues D481 and T417 in mediating the coupled motions of the two domains, as well as that of G506 in enabling the movements of the xcexb1-helical lid with respect to the xcexb2-sandwich. It also draws attention to the distinctive role of the NBD subdomains: Subdomain IA acts as a key mediator of signal transduction between the ATP- and substrate-binding sites, this function being achieved by a cascade of interactions predominantly involving conserved residues such as V139, D148, R167 and K155. Subdomain IIA, on the other hand, is distinguished by strong coevolutionary signals (with the SBD) exhibited by a series of residues (D211, E217, L219, T383) implicated in DnaJ recognition. The occurrence of coevolving residues at the DnaJ recognition region parallels the behavior recently observed at the nucleotide-exchange-factor recognition region of subdomain IIB. These findings suggest that Hsp70 tends to adapt to co-chaperone recognition and activity via coevolving residues, whereas interdomain allostery, critical to chaperoning, is robustly enabled by conserved interactions. '),
(86577, 2014, 'plos', 'In-vivo real-time control of protein expression from endogenous and synthetic gene networks', 'Menolascina, Filippo|Fiore, Gianfranco|Orabona, Emanuele|De Stefano, Luca|Ferry, Mike|Hasty, Jeff|di Bernardo, Mario|di Bernardo, Diego', 'TeleThon Institute of Genetics and Medicine (TIGEM), Naples, Italy, Department of Electrical Engineering and Information Technology, University of Naples Federico II, Naples, Italy.|TeleThon Institute of Genetics and Medicine (TIGEM), Naples, Italy, Department of Electrical Engineering and Information Technology, University of Naples Federico II, Naples, Italy.|Institute of Microelectronics and Microsystems (IMM), CNR, Naples, Italy.|Institute of Microelectronics and Microsystems (IMM), CNR, Naples, Italy.|Department of Bioengineering, University of California, San Diego, La Jolla, California, United States of America.|Department of Bioengineering, University of California, San Diego, La Jolla, California, United States of America.|Department of Electrical Engineering and Information Technology, University of Naples Federico II, Naples, Italy, Department of Engineering Mathematics, University of Bristol, Bristol, United Kingdom.|TeleThon Institute of Genetics and Medicine (TIGEM), Naples, Italy, Department of Electrical Engineering and Information Technology, University of Naples Federico II, Naples, Italy.', 'Italy|Italy|Italy|Italy|United States|United States|United Kingdom|Italy', 64, 'Computer Simulation|Computer Systems|Fungal Proteins|Gene Expression Regulation, Fungal|Genes, Synthetic|Metabolic Engineering|Models, Genetic|Yeasts', 'Journal Article', '10.1371/journal.pcbi.1003625', '24831205', 'We describe an innovative experimental and computational approach to control the expression of a protein in a population of yeast cells. We designed a simple control algorithm to automatically regulate the administration of inducer molecules to the cells by comparing the actual protein expression level in the cell population with the desired expression level. We then built an automated platform based on a microfluidic device, a time-lapse microscopy apparatus, and a set of motorized syringes, all controlled by a computer. We tested the platform to force yeast cells to express a desired fixed, or time-varying, amount of a reporter protein over thousands of minutes. The computer automatically switched the type of sugar administered to the cells, its concentration and its duration, according to the control algorithm. Our approach can be used to control expression of any protein, fused to a fluorescent reporter, provided that an external molecule known to (indirectly) affect its promoter activity is available. '),
(86578, 2014, 'plos', 'Genomic characterization of large heterochromatic gaps in the human genome assembly', 'Altemose, Nicolas|Miga, Karen H|Maggioni, Mauro|Willard, Huntington F', 'Genome Biology Group, Duke Institute for Genome Sciences & Policy, Duke University, Durham, North Carolina, United States of America.|Genome Biology Group, Duke Institute for Genome Sciences & Policy, Duke University, Durham, North Carolina, United States of America.|Department of Mathematics, Duke University, Durham, North Carolina, United States of America.|Genome Biology Group, Duke Institute for Genome Sciences & Policy, Duke University, Durham, North Carolina, United States of America.', 'United States|United States|United States|United States', 40, 'Base Sequence|Chromosome Mapping|Chromosomes, Human, Y|DNA, Satellite|Genome, Human|Heterochromatin|Humans|Molecular Sequence Data|Sequence Analysis, DNA', 'Journal Article', '10.1371/journal.pcbi.1003628', '24831296', 'The largest gaps in the human genome assembly correspond to multi-megabase heterochromatic regions composed primarily of two related families of tandem repeats, Human Satellites 2 and 3 (HSat2,3). The abundance of repetitive DNA in these regions challenges standard mapping and assembly algorithms, and as a result, the sequence composition and potential biological functions of these regions remain largely unexplored. Furthermore, existing genomic tools designed to predict consensus-based descriptions of repeat families cannot be readily applied to complex satellite repeats such as HSat2,3, which lack a consistent repeat unit reference sequence. Here we present an alignment-free method to characterize complex satellites using whole-genome shotgun read datasets. Utilizing this approach, we classify HSat2,3 sequences into fourteen subfamilies and predict their chromosomal distributions, resulting in a comprehensive satellite reference database to further enable genomic studies of heterochromatic regions. We also identify 1.3 Mb of non-repetitive sequence interspersed with HSat2,3 across 17 unmapped assembly scaffolds, including eight annotated gene predictions. Finally, we apply our satellite reference database to high-throughput sequence data from 396 males to estimate array size variation of the predominant HSat3 array on the Y chromosome, confirming that satellite array sizes can vary between individuals over an order of magnitude (7 to 98 Mb) and further demonstrating that array sizes are distributed differently within distinct Y haplogroups. In summary, we present a novel framework for generating initial reference databases for unassembled genomic regions enriched with complex satellite DNA, and we further demonstrate the utility of these reference databases for studying patterns of sequence variation within human populations. ');
INSERT INTO `papers` (`id`, `ano`, `journal`, `titulo`, `autores`, `afiliacao`, `pais`, `citacoes`, `palavra_chave`, `categorias`, `doi`, `pubmed`, `abstract`) VALUES
(86579, 2014, 'plos', 'An innovative influenza vaccination policy: targeting last seasons patients', 'Yamin, Dan|Gavious, Arieh|Solnik, Eyal|Davidovitch, Nadav|Balicer, Ran D|Galvani, Alison P|Pliskin, Joseph S', 'Department of Epidemiology of Microbial Diseases, Yale University, New Haven, Connecticut, United States of America, Department of Industrial Engineering and Management, Ben Gurion University of the Negev, Beersheba, Israel.|Department of Industrial Engineering and Management, Ben Gurion University of the Negev, Beersheba, Israel, Faculty of Business Administration, Ono Academic College, Kiryat Ono, Israel.|Department of Industrial Engineering and Management, Ben Gurion University of the Negev, Beersheba, Israel.|Department of Health Systems Management, Ben Gurion University of the Negev, Beersheba, Israel.|Clalit Research Institute, Clalit Health Services, Tel Aviv, Israel.|Department of Epidemiology of Microbial Diseases, Yale University, New Haven, Connecticut, United States of America.|Department of Industrial Engineering and Management, Ben Gurion University of the Negev, Beersheba, Israel, Department of Health Systems Management, Ben Gurion University of the Negev, Beersheba, Israel, Department of Health Policy and Management, Harvard School of Public Health, Boston, Massachusetts, United States of America.', 'Israel|Israel|Israel|Israel|Israel|United States|Israel', 7, 'Algorithms|Disease Outbreaks|Health Policy|Humans|Incidence|Influenza Vaccines|Influenza, Human|Israel|Mass Vaccination|Seasons|Treatment Outcome', 'Journal Article', '10.1371/journal.pcbi.1003643', '24851863', 'Influenza vaccination is the primary approach to prevent influenza annually. WHO/CDC recommendations prioritize vaccinations mainly on the basis of age and co-morbidities, but have never considered influenza infection history of individuals for vaccination targeting. We evaluated such influenza vaccination policies through small-world contact networks simulations. Further, to verify our findings we analyzed, independently, large-scale empirical data of influenza diagnosis from the two largest Health Maintenance Organizations in Israel, together covering more than 74% of the Israeli population. These longitudinal individual-level data include about nine million cases of influenza diagnosed over a decade. Through contact network epidemiology simulations, we found that individuals previously infected with influenza have a disproportionate probability of being highly connected within networks and transmitting to others. Therefore, we showed that prioritizing those previously infected for vaccination would be more effective than a random vaccination policy in reducing infection. The effectiveness of such a policy is robust over a range of epidemiological assumptions, including cross-reactivity between influenza strains conferring partial protection as high as 55%. Empirically, our analysis of the medical records confirms that in every age group, case definition for influenza, clinical diagnosis, and year tested, patients infected in the year prior had a substantially higher risk of becoming infected in the subsequent year. Accordingly, considering individual infection history in targeting and promoting influenza vaccination is predicted to be a highly effective supplement to the current policy. Our approach can also be generalized for other infectious disease, computer viruses, or ecological networks. '),
(86580, 2014, 'plos', 'The changing geometry of a fitness landscape along an adaptive walk', 'Greene, Devin|Crona, Kristina', 'University of California, Merced, Merced, California, United States of America.|University of California, Merced, Merced, California, United States of America.', 'United States|United States', 23, 'Adaptation, Physiological|Animals|Computer Simulation|Epistasis, Genetic|Evolution, Molecular|Genetic Fitness|Genetics, Population|Humans|Models, Genetic|Models, Statistical|Selection, Genetic', 'Journal Article', '10.1371/journal.pcbi.1003520', '24853069', 'It has recently been noted that the relative prevalence of the various kinds of epistasis varies along an adaptive walk. This has been explained as a result of mean regression in NK model fitness landscapes. Here we show that this phenomenon occurs quite generally in fitness landscapes. We propose a simple and general explanation for this phenomenon, confirming the role of mean regression. We provide support for this explanation with simulations, and discuss the empirical relevance of our findings. '),
(86581, 2014, 'plos', 'Optimism as a prior belief about the probability of future reward', 'Stankevicius, Aistis|Huys, Quentin J M|Kalra, Aditi|Seriès, Peggy', 'Institute for Adaptive and Neural Computation, University of Edinburgh, Edinburgh, United Kingdom.|Translational Neuromodeling Unit, Institute for Biomedical Engineering, University of Zürich and ETH Zürich, Zürich, Switzerland, Department of Psychiatry, Psychotherapy and Psychosomatics, University Hospital of Psychiatry Zurich, Zürich, Switzerland, Gatsby Computational Neuroscience Unit and Wellcome Trust Neuroimaging Centre, UCL, London, United Kingdom.|Institute for Adaptive and Neural Computation, University of Edinburgh, Edinburgh, United Kingdom.|Institute for Adaptive and Neural Computation, University of Edinburgh, Edinburgh, United Kingdom.', 'United Kingdom|Switzerland|United Kingdom|United Kingdom', 18, 'Adolescent|Adult|Anticipation, Psychological|Choice Behavior|Computer Simulation|Culture|Female|Humans|Male|Middle Aged|Models, Biological|Models, Statistical|Reward|Young Adult', 'Journal Article', '10.1371/journal.pcbi.1003605', '24853098', 'Optimists hold positive a priori beliefs about the future. In Bayesian statistical theory, a priori beliefs can be overcome by experience. However, optimistic beliefs can at times appear surprisingly resistant to evidence, suggesting that optimism might also influence how new information is selected and learned. Here, we use a novel Pavlovian conditioning task, embedded in a normative framework, to directly assess how trait optimism, as classically measured using self-report questionnaires, influences choices between visual targets, by learning about their association with reward progresses. We find that trait optimism relates to an a priori belief about the likelihood of rewards, but not losses, in our task. Critically, this positive belief behaves like a probabilistic prior, i.e. its influence reduces with increasing experience. Contrary to findings in the literature related to unrealistic optimism and self-beliefs, it does not appear to influence the iterative learning process directly. '),
(86582, 2014, 'plos', 'In silico screening of the key cellular remodeling targets in chronic atrial fibrillation', 'Koivumäki, Jussi T|Seemann, Gunnar|Maleckar, Mary M|Tavi, Pasi', 'Simula Research Laboratory, Center for Cardiological Innovation and Center for Biomedical Computing, Oslo, Norway, Department of Biotechnology and Molecular Medicine, A.I. Virtanen Institute for Molecular Sciences, University of Eastern Finland, Kuopio, Finland.|Institute of Biomedical Engineering, Karlsruhe Institute of Technology, Karlsruhe, Germany.|Simula Research Laboratory, Center for Cardiological Innovation and Center for Biomedical Computing, Oslo, Norway.|Department of Biotechnology and Molecular Medicine, A.I. Virtanen Institute for Molecular Sciences, University of Eastern Finland, Kuopio, Finland.', 'Finland|Germany|Norway|Finland', 33, 'Action Potentials|Atrial Fibrillation|Atrial Remodeling|Calcium|Calcium Channels|Calcium Signaling|Cells, Cultured|Computer Simulation|Heart Atria|Heart Conduction System|Humans|Ion Channel Gating|Models, Cardiovascular|Myocytes, Cardiac', 'Journal Article', '10.1371/journal.pcbi.1003620', '24853123', 'Chronic atrial fibrillation (AF) is a complex disease with underlying changes in electrophysiology, calcium signaling and the structure of atrial myocytes. How these individual remodeling targets and their emergent interactions contribute to cell physiology in chronic AF is not well understood. To approach this problem, we performed in silico experiments in a computational model of the human atrial myocyte. The remodeled function of cellular components was based on a broad literature review of in vitro findings in chronic AF, and these were integrated into the model to define a cohort of virtual cells. Simulation results indicate that while the altered function of calcium and potassium ion channels alone causes a pronounced decrease in action potential duration, remodeling of intracellular calcium handling also has a substantial impact on the chronic AF phenotype. We additionally found that the reduction in amplitude of the calcium transient in chronic AF as compared to normal sinus rhythm is primarily due to the remodeling of calcium channel function, calcium handling and cellular geometry. Finally, we found that decreased electrical resistance of the membrane together with remodeled calcium handling synergistically decreased cellular excitability and the subsequent inducibility of repolarization abnormalities in the human atrial myocyte in chronic AF. We conclude that the presented results highlight the complexity of both intrinsic cellular interactions and emergent properties of human atrial myocytes in chronic AF. Therefore, reversing remodeling for a single remodeled component does little to restore the normal sinus rhythm phenotype. These findings may have important implications for developing novel therapeutic approaches for chronic AF. '),
(86583, 2014, 'plos', '2014 ISCB Accomplishment by a Senior Scientist Award: Gene Myers', 'Fogg, Christiana N|Kovats, Diane E', 'Freelance Science Writer, Kensington, Maryland, United States of America.|Executive Director, International Society for Computational Biology, La Jolla, California, United States of America.', 'United States|United States', 0, 'Awards and Prizes|Germany|History, 20th Century|History, 21st Century|Molecular Biology|Societies|Systems Biology|United States', 'Biography', '10.1371/journal.pcbi.1003621', '24853264', '-'),
(86584, 2014, 'plos', 'Spatial generalization in operant learning: lessons from professional basketball', 'Neiman, Tal|Loewenstein, Yonatan', 'Edmond and Lily Safra Center for Brain Sciences, The Hebrew University, Jerusalem, Israel.|Edmond and Lily Safra Center for Brain Sciences, The Hebrew University, Jerusalem, Israel, Department of Neurobiology, The Alexander Silberman Institute of Life Sciences, Department of Cognitive Science and Center for the Study of Rationality, The Hebrew University, Jerusalem, Israel.', 'Israel|Israel', 5, 'Adaptation, Physiological|Athletic Performance|Basketball|Computer Simulation|Conditioning, Operant|Humans|Models, Biological|Models, Statistical|Space Perception', 'Journal Article', '10.1371/journal.pcbi.1003623', '24853373', 'In operant learning, behaviors are reinforced or inhibited in response to the consequences of similar actions taken in the past. However, because in natural environments the same situation never recurs, it is essential for the learner to decide what similar is so that he can generalize from experience in one state of the world to future actions in different states of the world. The computational principles underlying this generalization are poorly understood, in particular because natural environments are typically too complex to study quantitatively. In this paper we study the principles underlying generalization in operant learning of professional basketball players. In particular, we utilize detailed information about the spatial organization of shot locations to study how players adapt their attacking strategy in real time according to recent events in the game. To quantify this learning, we study how a makemiss from one location in the court affects the probabilities of shooting from different locations. We show that generalization is not a spatially-local process, nor is governed by the difficulty of the shot. Rather, to a first approximation, players use a simplified binary representation of the court into 2 pt and 3 pt zones. This result indicates that rather than using low-level features, generalization is determined by high-level cognitive processes that incorporate the abstract rules of the game.'),
(86585, 2014, 'plos', 'Quantifying and predicting the effect of exogenous interleukin-7 on CD4+ T cells in HIV-1 infection', 'Thixc3xa9baut, Rodolphe|Drylewicz, Julia|Prague, Mxc3xa9lanie|Lacabaratz, Christine|Beq, Stxc3xa9phanie|Jarne, Ana|Croughs, Thxc3xa9rxc3xa8se|Sekaly, Rafick-Pierre|Lederman, Michael M|Sereti, Irini|Commenges, Daniel|Lxc3xa9vy, Yves', 'INSERM, ISPED, Centre INSERM U897-Epidemiologie-Biostatistique, Bordeaux, France, Univ. Bordeaux, ISPED, Centre INSERM U897-Epidemiologie-Biostatistique, Bordeaux, France, INRIA, SISTM team, Bordeaux, France.|Laboratory for Translational Immunology, University Medical Center Utrecht, Utrecht, The Netherlands, Theoretical Biology and Bioinformatics, Department of Biology, Utrecht University, Utrecht, The Netherlands.|INSERM, ISPED, Centre INSERM U897-Epidemiologie-Biostatistique, Bordeaux, France, Univ. Bordeaux, ISPED, Centre INSERM U897-Epidemiologie-Biostatistique, Bordeaux, France, INRIA, SISTM team, Bordeaux, France.|INSERM, Unitxc3xa9 U955, Crxc3xa9teil, France, Universitxc3xa9 Paris-Est, Facultxc3xa9 de Mxc3xa9decine, UMR-S955 Creteil, France.|CYTHERIS, Issy Les Moulineaux, France.|INSERM, ISPED, Centre INSERM U897-Epidemiologie-Biostatistique, Bordeaux, France, Univ. Bordeaux, ISPED, Centre INSERM U897-Epidemiologie-Biostatistique, Bordeaux, France, INRIA, SISTM team, Bordeaux, France.|CYTHERIS, Issy Les Moulineaux, France.|Vaccine and Gene Therapy Institute-Florida, Port St. Lucie, Florida, United States of America.|Case Western Reserve University/University Hospitals/Case Medical Center, Cleveland, Ohio, United States of America.|National Institute of Allergy and Infectious Diseases, National Institutes of Health, Bethesda, Maryland, United States of America.|INSERM, ISPED, Centre INSERM U897-Epidemiologie-Biostatistique, Bordeaux, France, Univ. Bordeaux, ISPED, Centre INSERM U897-Epidemiologie-Biostatistique, Bordeaux, France, INRIA, SISTM team, Bordeaux, France.|INSERM, Unitxc3xa9 U955, Crxc3xa9teil, France, Universitxc3xa9 Paris-Est, Facultxc3xa9 de Mxc3xa9decine, UMR-S955 Creteil, France, AP-HP, Groupe Henri-Mondor Albert-Chenevier, Immunologie Clinique, Creteil, France.', 'France|Netherlands|France|France|France|France|France|United States|United States|United States|Fran', 15, 'CD4-Positive T-Lymphocytes|Cells, Cultured|Computer Simulation|HIV Infections|HIV-1|Humans|Interleukin-7|Ki-67 Antigen|Models, Immunological', 'Journal Article', '10.1371/journal.pcbi.1003630', '24853554', 'Exogenous Interleukin-7 (IL-7), in supplement to antiretroviral therapy, leads to a substantial increase of all CD4+ T cell subsets in HIV-1 infected patients. However, the quantitative contribution of the several potential mechanisms of action of IL-7 is unknown. We have performed a mathematical analysis of repeated measurements of total and naive CD4+ T cells and their Ki67 expression from HIV-1 infected patients involved in three phase I/II studies (Nxe2x80x8a=xe2x80x8a53 patients). We show that, besides a transient increase of peripheral proliferation, IL-7 exerts additional effects that play a significant role in CD4+ T cell dynamics up to 52 weeks. A decrease of the loss rate of the total CD4+ T cell is the most probable explanation. If this effect could be maintained during repeated administration of IL-7, our simulation study shows that such a strategy may allow maintaining CD4+ T cell counts above 500 cells/xc2xb5L with 4 cycles or fewer over a period of two years. This in-depth analysis of clinical data revealed the potential for IL-7 to achieve sustained CD4+ T cell restoration with limited IL-7 exposure in HIV-1 infected patients with immune failure despite antiretroviral therapy. '),
(86586, 2014, 'plos', 'Evolution of pathogen specialisation in a host metapopulation: joint effects of host and pathogen dispersal', 'Papaïx, Julien|Burdon, Jeremy J|Lannou, Christian|Thrall, Peter H', 'INRA, UMR 1290 BIOGER, Thiverval-Grignon, France, INRA, UR 341 MIA, Jouy-en-Josas, France, CSIRO Plant Industry, Canberra, Australia.|CSIRO Plant Industry, Canberra, Australia.|INRA, UMR 1290 BIOGER, Thiverval-Grignon, France.|CSIRO Plant Industry, Canberra, Australia.', 'Australia|Australia|France|Australia', 13, 'Biological Evolution|Computer Simulation|Genetics, Population|Host-Pathogen Interactions|Models, Genetic|Plant Dispersal|Plants', 'Journal Article', '10.1371/journal.pcbi.1003633', '24853675', 'Metapopulation processes are important determinants of epidemiological and evolutionary dynamics in host-pathogen systems, and are therefore central to explaining observed patterns of disease or genetic diversity. In particular, the spatial scale of interactions between pathogens and their hosts is of primary importance because migration rates of one species can affect both spatial and temporal heterogeneity of selection on the other. In this study we developed a stochastic and discrete time simulation model to specifically examine the joint effects of host and pathogen dispersal on the evolution of pathogen specialisation in a spatially explicit metapopulation. We consider a plant-pathogen system in which the host metapopulation is composed of two plant genotypes. The pathogen is dispersed by air-borne spores on the host metapopulation. The pathogen population is characterised by a single life-history trait under selection, the infection efficacy. We found that restricted host dispersal can lead to high amount of pathogen diversity and that the extent of pathogen specialisation varied according to the spatial scale of host-pathogen dispersal. We also discuss the role of population asynchrony in determining pathogen evolutionary outcomes. '),
(86587, 2014, 'plos', 'Arterial stiffening provides sufficient explanation for primary hypertension', 'Pettersen, Klas H|Bugenhagen, Scott M|Nauman, Javaid|Beard, Daniel A|Omholt, Stig W', 'Department of Mathematical and Technological Sciences, Norwegian University of Life Sciences, Ås, Norway.|Department of Physiology, Medical College of Wisconsin, Milwaukee, Wisconsin, United States of America.|Department of Circulation and Medical Imaging, Cardiac Exercise Research Group, NTNU Norwegian University of Science and Technology, Trondheim, Norway.|Department of Physiology, Medical College of Wisconsin, Milwaukee, Wisconsin, United States of America.|Department of Circulation and Medical Imaging, Cardiac Exercise Research Group, NTNU Norwegian University of Science and Technology, Trondheim, Norway.', 'Norway|United States|Norway|United States|Norway', 25, 'Animals|Arteries|Baroreflex|Blood Flow Velocity|Blood Pressure|Computer Simulation|Humans|Hypertension|Models, Cardiovascular|Vascular Resistance|Vascular Stiffness', 'Journal Article', '10.1371/journal.pcbi.1003634', '24853828', 'Hypertension is one of the most common age-related chronic disorders, and by predisposing individuals for heart failure, stroke, and kidney disease, it is a major source of morbidity and mortality. Its etiology remains enigmatic despite intense research efforts over many decades. By use of empirically well-constrained computer models describing the coupled function of the baroreceptor reflex and mechanics of the circulatory system, we demonstrate quantitatively that arterial stiffening seems sufficient to explain age-related emergence of hypertension. Specifically, the empirically observed chronic changes in pulse pressure with age and the impaired capacity of hypertensive individuals to regulate short-term changes in blood pressure arise as emergent properties of the integrated system. The results are consistent with available experimental data from chemical and surgical manipulation of the cardio-vascular system. In contrast to widely held opinions, the results suggest that primary hypertension can be attributed to a mechanogenic etiology without challenging current conceptions of renal and sympathetic nervous system function. '),
(86588, 2014, 'plos', 'High-resolution modeling of transmembrane helical protein structures from distant homologues', 'Chen, Kuang-Yui M|Sun, Jiaming|Salvo, Jason S|Baker, David|Barth, Patrick', 'Verna and Marrs McLean Department of Biochemistry and Molecular Biology, Baylor College of Medicine, Houston, Texas, United States of America.|Department of Pharmacology, Baylor College of Medicine, Houston, Texas, United States of America.|Structural and Computational Biology and Molecular Biophysics Graduate Program, Baylor College of Medicine, Houston, Texas, United States of America.|Howard Hughes Medical Institute and Department of Biochemistry, University of Washington, Seattle, Washington, United States of America.|Verna and Marrs McLean Department of Biochemistry and Molecular Biology, Baylor College of Medicine, Houston, Texas, United States of America, Department of Pharmacology, Baylor College of Medicine, Houston, Texas, United States of America, Structural and Computational Biology and Molecular Biophysics Graduate Program, Baylor College of Medicine, Houston, Texas, United States of America.', 'United States|United States|United States|United States|United States', 23, 'Amino Acid Sequence|Computer Simulation|Membrane Proteins|Models, Chemical|Molecular Docking Simulation|Molecular Sequence Data|Protein Conformation|Receptor, Adenosine A2A|Receptors, CXCR4|Sequence Homology, Amino Acid', 'Journal Article', '10.1371/journal.pcbi.1003636', '24854015', 'Eukaryotic transmembrane helical (TMH) proteins perform a wide diversity of critical cellular functions, but remain structurally largely uncharacterized and their high-resolution structure prediction is currently hindered by the lack of close structural homologues. To address this problem, we present a novel and generic method for accurately modeling large TMH protein structures from distant homologues exhibiting distinct loop and TMH conformations. Models of the adenosine A2AR and chemokine CXCR4 receptors were first ranked in GPCR-DOCK blind prediction contests in the receptor structure accuracy category. In a benchmark of 50 TMH protein homolog pairs of diverse topology (from 5 to 12 TMHs), size (from 183 to 420 residues) and sequence identity (from 15% to 70%), the method improves most starting templates, and achieves near-atomic accuracy prediction of membrane-embedded regions. Unlike starting templates, the models are of suitable quality for computer-based protein engineering: redesigned models and redesigned X-ray structures exhibit very similar native interactions. The method should prove useful for the atom-level modeling and design of a large fraction of structurally uncharacterized TMH proteins from a wide range of structural homologues. '),
(86589, 2014, 'plos', 'Essential plasticity and redundancy of metabolism unveiled by synthetic lethality analysis', 'Güell, Oriol|Sagués, Francesc|Serrano, M Ángeles', 'Departament de Química Física, Universitat de Barcelona, Barcelona, Spain.|Departament de Química Física, Universitat de Barcelona, Barcelona, Spain.|Departament de Física Fonamental, Universitat de Barcelona, Barcelona, Spain.', 'Spain|Spain|Spain', 22, 'Adaptation, Physiological|Apoptosis|Cell Membrane|Cell Survival|Computer Simulation|Escherichia coli|Escherichia coli Proteins|Lipid Metabolism|Models, Biological|Signal Transduction', 'Journal Article', '10.1371/journal.pcbi.1003637', '24854166', 'We unravel how functional plasticity and redundancy are essential mechanisms underlying the ability to survive of metabolic networks. We perform an exhaustive computational screening of synthetic lethal reaction pairs in Escherichia coli in a minimal medium and we find that synthetic lethal pairs divide in two different groups depending on whether the synthetic lethal interaction works as a backup or as a parallel use mechanism, the first corresponding to essential plasticity and the second to essential redundancy. In E. coli, the analysis of pathways entanglement through essential redundancy supports the view that synthetic lethality affects preferentially a single function or pathway. In contrast, essential plasticity, the dominant class, tends to be inter-pathway but strongly localized and unveils Cell Envelope Biosynthesis as an essential backup for Membrane Lipid Metabolism. When comparing E. coli and Mycoplasma pneumoniae, we find that the metabolic networks of the two organisms exhibit a large difference in the relative importance of plasticity and redundancy which is consistent with the conjecture that plasticity is a sophisticated mechanism that requires a complex organization. Finally, coessential reaction pairs are explored in different environmental conditions to uncover the interplay between the two mechanisms. We find that synthetic lethal interactions and their classification in plasticity and redundancy are basically insensitive to medium composition, and are highly conserved even when the environment is enriched with nonessential compounds or overconstrained to decrease maximum biomass formation. '),
(86590, 2014, 'plos', 'Are current atomistic force fields accurate enough to study proteins in crowded environments?', 'Petrov, Drazen|Zagrovic, Bojan', 'Max F. Perutz Laboratories, University of Vienna, Vienna, Austria.|Max F. Perutz Laboratories, University of Vienna, Vienna, Austria.', 'Austria|Austria', 82, 'Microfilament Proteins|Models, Chemical|Models, Molecular|Protein Conformation|Protein Folding|Stress, Mechanical', 'Journal Article', '10.1371/journal.pcbi.1003638', '24854339', 'The high concentration of macromolecules in the crowded cellular interior influences different thermodynamic and kinetic properties of proteins, including their structural stabilities, intermolecular binding affinities and enzymatic rates. Moreover, various structural biology methods, such as NMR or different spectroscopies, typically involve samples with relatively high protein concentration. Due to large sampling requirements, however, the accuracy of classical molecular dynamics (MD) simulations in capturing protein behavior at high concentration still remains largely untested. Here, we use explicit-solvent MD simulations and a total of 6.4 µs of simulated time to study wild-type (folded) and oxidatively damaged (unfolded) forms of villin headpiece at 6 mM and 9.2 mM protein concentration. We first perform an exhaustive set of simulations with multiple protein molecules in the simulation box using GROMOS 45a3 and 54a7 force fields together with different types of electrostatics treatment and solution ionic strengths. Surprisingly, the two villin headpiece variants exhibit similar aggregation behavior, despite the fact that their estimated aggregation propensities markedly differ. Importantly, regardless of the simulation protocol applied, wild-type villin headpiece consistently aggregates even under conditions at which it is experimentally known to be soluble. We demonstrate that aggregation is accompanied by a large decrease in the total potential energy, with not only hydrophobic, but also polar residues and backbone contributing substantially. The same effect is directly observed for two other major atomistic force fields (AMBER99SB-ILDN and CHARMM22-CMAP) as well as indirectly shown for additional two (AMBER94, OPLS-AAL), and is possibly due to a general overestimation of the potential energy of protein-protein interactions at the expense of water-water and water-protein interactions. Overall, our results suggest that current MD force fields may distort the picture of protein behavior in biologically relevant crowded environments. '),
(86591, 2014, 'plos', 'A signature of attractor dynamics in the CA3 region of the hippocampus', 'Rennó-Costa, César|Lisman, John E|Verschure, Paul F M J', 'Universitat Pompeu Fabra, Synthetic, Perceptive, Emotive and Cognitive Systems group (SPECS), Barcelona, Spain, Federal University of Rio Grande do Norte (UFRN), Brain Institute (ICe), Natal, Rio Grande do Norte, Brazil.|Brandeis University, Biology Department & Volen Center for Complex Systems, Waltham, Massachusetts, United States of America.|Universitat Pompeu Fabra, Synthetic, Perceptive, Emotive and Cognitive Systems group (SPECS), Barcelona, Spain, Catalan Institute of Advanced Research (ICREA), Passeig Lluís Companys 23, Barcelona, Spain, Universitat Pompeu Fabra, Center of Autonomous Systems and Neurorobotics (NRAS), Barcelona, Spain.', 'Brazil|United States|Spain', 30, 'Action Potentials|Animals|Biological Clocks|Computer Simulation|Hippocampus|Humans|Memory|Models, Neurological|Nerve Net|Neurons', 'Journal Article', '10.1371/journal.pcbi.1003641', '24854425', 'The notion of attractor networks is the leading hypothesis for how associative memories are stored and recalled. A defining anatomical feature of such networks is excitatory recurrent connections. These attract the firing pattern of the network to a stored pattern, even when the external input is incomplete (pattern completion). The CA3 region of the hippocampus has been postulated to be such an attractor network, however, the experimental evidence has been ambiguous, leading to the suggestion that CA3 is not an attractor network. In order to resolve this controversy and to better understand how CA3 functions, we simulated CA3 and its input structures. In our simulation, we could reproduce critical experimental results and establish the criteria for identifying attractor properties. Notably, under conditions in which there is continuous input, the output should be attracted to a stored pattern. However, contrary to previous expectations, as a pattern is gradually morphed from one stored pattern to another, a sharp transition between output patterns is not expected. The observed firing patterns of CA3 meet these criteria and can be quantitatively accounted for by our model. Notably, as morphing proceeds, the activity pattern in the dentate gyrus changes, in contrast, the activity pattern in the downstream CA3 network is attracted to a stored pattern and thus undergoes little change. We furthermore show that other aspects of the observed firing patterns can be explained by learning that occurs during behavioral testing. The CA3 thus displays both the learning and recall signatures of an attractor network. These observations, taken together with existing anatomical and behavioral evidence, make the strong case that CA3 constructs associative memories based on attractor dynamics. '),
(86592, 2014, 'plos', 'Finding novel molecular connections between developmental processes and disease', 'Park, Jisoo|Wick, Heather C|Kee, Daniel E|Noto, Keith|Maron, Jill L|Slonim, Donna K', 'Department of Computer Science, Tufts University, Medford, Massachussetts, United States of America.|Department of Computer Science, Tufts University, Medford, Massachussetts, United States of America.|Department of Computer Science, Tufts University, Medford, Massachussetts, United States of America.|Department of Computer Science, Tufts University, Medford, Massachussetts, United States of America.|Department of Pediatrics, The Floating Hospital for Children at Tufts Medical Center, Boston, Massachusetts, United States of America.|Department of Computer Science, Tufts University, Medford, Massachussetts, United States of America, Department of Pathology, Tufts University School of Medicine, Boston, Massachusetts, United States of America.', 'United States|United States|United States|United States|United States|United States', 9, 'Animals|Chromosome Mapping|Computer Simulation|Gene Expression Regulation, Developmental|Genetic Markers|Genetic Predisposition to Disease|Genome-Wide Association Study|Humans|Models, Genetic|Proteome', 'Journal Article', '10.1371/journal.pcbi.1003578', '24874013', 'Identifying molecular connections between developmental processes and disease can lead to new hypotheses about health risks at all stages of life. Here we introduce a new approach to identifying significant connections between gene sets and disease genes, and apply it to several gene sets related to human development. To overcome the limits of incomplete and imperfect information linking genes to disease, we pool genes within disease subtrees in the MeSH taxonomy, and we demonstrate that such pooling improves the power and accuracy of our approach. Significance is assessed through permutation. We created a web-based visualization tool to facilitate multi-scale exploration of this large collection of significant connections (http://gda.cs.tufts.edu/development). High-level analysis of the results reveals expected connections between tissue-specific developmental processes and diseases linked to those tissues, and widespread connections to developmental disorders and cancers. Yet interesting new hypotheses may be derived from examining the unexpected connections. We highlight and discuss the implications of three such connections, linking dementia with bone development, polycystic ovary syndrome with cardiovascular development, and retinopathy of prematurity with lung development. Our results provide additional evidence that TGFB lays a key role in the early pathogenesis of polycystic ovary syndrome. Our evidence also suggests that the VEGF pathway and downstream NFKB signaling may explain the complex relationship between bronchopulmonary dysplasia and retinopathy of prematurity, and may form a bridge between two currently-competing hypotheses about the molecular origins of bronchopulmonary dysplasia. Further data exploration and similar queries about other gene sets may generate a variety of new information about the molecular relationships between additional diseases.'),
(86593, 2014, 'plos', 'Inferring host gene subnetworks involved in viral replication', 'Chasman, Deborah|Gancarz, Brandi|Hao, Linhui|Ferris, Michael|Ahlquist, Paul|Craven, Mark', 'Department of Computer Sciences, University of Wisconsin-Madison, Madison, Wisconsin, United States of America, Department of Biostatistics and Medical Informatics, University of Wisconsin-Madison, Madison, Wisconsin, United States of America.|Luminex Corporation, Madison, Wisconsin, United States of America, Institute for Molecular Virology, University of Wisconsin-Madison, Madison, Wisconsin, United States of America.|Institute for 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.|Department of Computer Sciences, University of Wisconsin-Madison, Madison, Wisconsin, United States of America.|Institute for 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, Morgridge Institute for Research, University of Wisconsin-Madison, Madison, Wisconsin, United States of America.|Department of Computer Sciences, University of Wisconsin-Madison, Madison, Wisconsin, United States of America, Department of Biostatistics and Medical Informatics, University of Wisconsin-Madison, Madison, Wisconsin, United States of America.', 'United States|United States|United States|United States|United States|United States', 3, 'Cell Transformation, Viral|Fungal Proteins|Gene Expression Regulation, Fungal|Genes, Viral|RNA Viruses|Signal Transduction|Virus Replication|Yeasts', 'Journal Article', '10.1371/journal.pcbi.1003626', '24874113', 'Systematic, genome-wide loss-of-function experiments can be used to identify host factors that directly or indirectly facilitate or inhibit the replication of a virus in a host cell. We present an approach that combines an integer linear program and a diffusion kernel method to infer the pathways through which those host factors modulate viral replication. The inputs to the method are a set of viral phenotypes observed in single-host-gene mutants and a background network consisting of a variety of host intracellular interactions. The output is an ensemble of subnetworks that provides a consistent explanation for the measured phenotypes, predicts which unassayed host factors modulate the virus, and predicts which host factors are the most direct interfaces with the virus. We infer host-virus interaction subnetworks using data from experiments screening the yeast genome for genes modulating the replication of two RNA viruses. Because a gold-standard network is unavailable, we assess the predicted subnetworks using both computational and qualitative analyses. We conduct a cross-validation experiment in which we predict whether held-aside test genes have an effect on viral replication. Our approach is able to make high-confidence predictions more accurately than several baselines, and about as well as the best baseline, which does not infer mechanistic pathways. We also examine two kinds of predictions made by our method: which host factors are nearest to a direct interaction with a viral component, and which unassayed host genes are likely to be involved in viral replication. Multiple predictions are supported by recent independent experimental data, or are components or functional partners of confirmed relevant complexes or pathways. Integer program code, background network data, and inferred host-virus subnetworks are available at http://www.biostat.wisc.edu/~craven/chasman_host_virus/. '),
(86594, 2014, 'plos', 'A new tool to quantify receptor recruitment to cell contact sites during host-pathogen interaction', 'Graus, Matthew S|Pehlke, Carolyn|Wester, Michael J|Davidson, Lisa B|Steinberg, Stanly L|Neumann, Aaron K', 'Department of Pathology, University of New Mexico, Albuquerque, New Mexico, United States of America.|Center for Spatiotemporal Modeling of Cell Signaling, University of New Mexico, Albuquerque, New Mexico, United States of America.|Center for Spatiotemporal Modeling of Cell Signaling and Department of Mathematics and Statistics, University of New Mexico, Albuquerque, New Mexico, United States of America.|Department of Pathology, University of New Mexico, Albuquerque, New Mexico, United States of America.|Center for Spatiotemporal Modeling of Cell Signaling and Department of Mathematics and Statistics, University of New Mexico, Albuquerque, New Mexico, United States of America.|Department of Pathology, University of New Mexico, Albuquerque, New Mexico, United States of America.', 'Mexico|Mexico|Mexico|Mexico|Mexico|Mexico', 3, 'Cell Communication|Cells, Cultured|Computer Simulation|Dendritic Cells|Fungi|Host-Pathogen Interactions|Humans|Models, Immunological|Receptors, Cell Surface', 'Journal Article', '10.1371/journal.pcbi.1003639', '24874253', 'To understand the process of innate immune fungal recognition, we developed computational tools for the rigorous quantification and comparison of receptor recruitment and distribution at cell-cell contact sites. We used these tools to quantify pattern recognition receptor spatiotemporal distributions in contacts between primary human dendritic cells and the fungal pathogens C. albicans, C. parapsilosis and the environmental yeast S. cerevisiae, imaged using 3D multichannel laser scanning confocal microscopy. The detailed quantitative analysis of contact sites shows that, despite considerable biochemical similarity in the composition and structure of these species cell walls, the receptor spatiotemporal distribution in host-microbe contact sites varies significantly between these yeasts. Our findings suggest a model where innate immune cells discriminate fungal microorganisms based on differential mobilization and coordination of receptor networks. Our analysis methods are also broadly applicable to a range of cell-cell interactions central to many biological problems. '),
(86595, 2014, 'plos', 'The natural history of biocatalytic mechanisms', 'Nath, Neetika|Mitchell, John B O|Caetano-Anollxc3xa9s, Gustavo', 'Biomedical Sciences Research Complex and EaStCHEM School of Chemistry, University of St. Andrews, North Haugh, St. Andrews, Scotland, United Kingdom.|Biomedical Sciences Research Complex and EaStCHEM School of Chemistry, University of St. Andrews, North Haugh, St. Andrews, Scotland, United Kingdom.|Evolutionary Bioinformatics Laboratory, Department of Crop Sciences, University of Illinois, Urbana, Illinois, United States of America.', 'United Kingdom|United Kingdom|United States', 16, 'Catalysis|Enzymes|Evolution, Molecular|Protein Folding|Protein Structure, Tertiary|Structure-Activity Relationship', 'Journal Article', '10.1371/journal.pcbi.1003642', '24874434', 'Phylogenomic analysis of the occurrence and abundance of protein domains in proteomes has recently showed that the xcexb1/xcexb2 architecture is probably the oldest fold design. This holds important implications for the origins of biochemistry. Here we explore structure-function relationships addressing the use of chemical mechanisms by ancestral enzymes. We test the hypothesis that the oldest folds used the most mechanisms. We start by tracing biocatalytic mechanisms operating in metabolic enzymes along a phylogenetic timeline of the first appearance of homologous superfamilies of protein domain structures from CATH. A total of 335 enzyme reactions were retrieved from MACiE and were mapped over fold age. We define a mechanistic step type as one of the 51 mechanistic annotations given in MACiE, and each step of each of the 335 mechanisms was described using one or more of these annotations. We find that the first two folds, the P-loop containing nucleotide triphosphate hydrolase and the NAD(P)-binding Rossmann-like homologous superfamilies, were xcexb1/xcexb2 architectures responsible for introducing 35% (18/51) of the known mechanistic step types. We find that these two oldest structures in the phylogenomic analysis of protein domains introduced many mechanistic step types that were later combinatorially spread in catalytic history. The most common mechanistic step types included fundamental building blocks of enzyme chemistry: Proton transfer, Bimolecular nucleophilic addition, Bimolecular nucleophilic substitution, and Unimolecular elimination by the conjugate base. They were associated with the most ancestral fold structure typical of P-loop containing nucleotide triphosphate hydrolases. Over half of the mechanistic step types were introduced in the evolutionary timeline before the appearance of structures specific to diversified organisms, during a period of architectural diversification. The other half unfolded gradually after organismal diversification and during a period that spanned xe2x88xbc2 billion years of evolutionary history. '),
(86596, 2014, 'plos', 'Learn from the best', 'Bernard, Virginie|Schultheiss, Sebastian J|Michaut, Magali', 'Next Generation Sequencing Platform - ICGex, Curie Institute, Paris, France.|Computomics Molecular Data Analysis, Tuebingen, Germany.|Computational Cancer Biology, Netherlands Cancer Institute, Amsterdam, Netherlands.', 'France|Germany|Netherlands', 1, 'Education, Continuing|Mentors|Systems Biology', 'Journal Article', '10.1371/journal.pcbi.1003645', '24874540', 'What is more inspiring than a discussion with the leading scientists in your field? As a student or a young researcher, you have likely been influenced by mentors guiding you in your career and leading you to your current position. Any discussion with or advice from an expert is certainly very helpful for young people. But how often do we have the opportunity to meet experts? Do we make the most out of these situations? Meetings organized for young scientists are a great opportunity not only for the attendees: they are an opportunity for experts to meet bright students and learn from them in return. In this article, we introduce several successful events organized by Regional Student Groups all around the world, bridging the gap between experts and young scientists. We highlight how rewarding it is for all participants: young researchers, experts, and organizers. We then discuss the various benefits and emphasize the importance of organizing and attending such meetings. As a young researcher, seeking mentorship and additional skills training is a crucial step in career development. Keep in mind that one day, you may be an inspiring mentor, too. '),
(86597, 2014, 'plos', 'Exploration of the dynamic properties of protein complexes predicted from spatially constrained protein-protein interaction networks', 'Yen, Eric A|Tsay, Aaron|Waldispuhl, Jerome|Vogel, Jackie', 'Department of Biology, McGill University, Montreal, Quebec, Canada.|Department of Biology, McGill University, Montreal, Quebec, Canada.|School of Computer Science, McGill University, Montreal, Quebec, Canada.|Department of Biology, McGill University, Montreal, Quebec, Canada, School of Computer Science, McGill University, Montreal, Quebec, Canada.', 'Canada|Canada|Canada|Canada', 3, 'Binding Sites|Computer Simulation|Fungal Proteins|Models, Biological|Models, Chemical|Protein Binding|Protein Interaction Mapping|Saccharomycetales|Signal Transduction', 'Journal Article', '10.1371/journal.pcbi.1003654', '24874694', 'Protein complexes are not static, but rather highly dynamic with subunits that undergo 1-dimensional diffusion with respect to each other. Interactions within protein complexes are modulated through regulatory inputs that alter interactions and introduce new components and deplete existing components through exchange. While it is clear that the structure and function of any given protein complex is coupled to its dynamical properties, it remains a challenge to predict the possible conformations that complexes can adopt. Protein-fragment Complementation Assays detect physical interactions between protein pairs constrained to xe2x89xa48 nm from each other in living cells. This method has been used to build networks composed of 1000s of pair-wise interactions. Significantly, these networks contain a wealth of dynamic information, as the assay is fully reversible and the proteins are expressed in their natural context. In this study, we describe a method that extracts this valuable information in the form of predicted conformations, allowing the user to explore the conformational landscape, to search for structures that correlate with an activity state, and estimate the abundance of conformations in the living cell. The generator is based on a Markov Chain Monte Carlo simulation that uses the interaction dataset as input and is constrained by the physical resolution of the assay. We applied this method to an 18-member protein complex composed of the seven core proteins of the budding yeast Arp2/3 complex and 11 associated regulators and effector proteins. We generated 20,480 output structures and identified conformational states using principle component analysis. We interrogated the conformation landscape and found evidence of symmetry breaking, a mixture of likely active and inactive conformational states and dynamic exchange of the core protein Arc15 between core and regulatory components. Our method provides a novel tool for prediction and visualization of the hidden dynamics within protein interaction networks. '),
(86598, 2014, 'plos', 'Coiled-coil proteins facilitated the functional expansion of the centrosome', 'Kuhn, Michael|Hyman, Anthony A|Beyer, Andreas', 'Biotechnology Center, TU Dresden, Dresden, Germany, Max Planck Institute of Molecular Cell Biology and Genetics, Dresden, Germany.|Max Planck Institute of Molecular Cell Biology and Genetics, Dresden, Germany.|Biotechnology Center, TU Dresden, Dresden, Germany, University of Cologne, Cologne, Germany.', 'Germany|Germany|Germany', 20, 'Algorithms|Animals|Centrosome|Computational Biology|Fungi|Humans|Phylogeny|Protein Interaction Maps|Proteins', 'Journal Article', '10.1371/journal.pcbi.1003657', '24901223', 'Repurposing existing proteins for new cellular functions is recognized as a main mechanism of evolutionary innovation, but its role in organelle evolution is unclear. Here, we explore the mechanisms that led to the evolution of the centrosome, an ancestral eukaryotic organelle that expanded its functional repertoire through the course of evolution. We developed a refined sequence alignment technique that is more sensitive to coiled coil proteins, which are abundant in the centrosome. For proteins with high coiled-coil content, our algorithm identified 17% more reciprocal best hits than BLAST. Analyzing 108 eukaryotic genomes, we traced the evolutionary history of centrosome proteins. In order to assess how these proteins formed the centrosome and adopted new functions, we computationally emulated evolution by iteratively removing the most recently evolved proteins from the centrosomal protein interaction network. Coiled-coil proteins that first appeared in the animal-fungi ancestor act as scaffolds and recruit ancestral eukaryotic proteins such as kinases and phosphatases to the centrosome. This process created a signaling hub that is crucial for multicellular development. Our results demonstrate how ancient proteins can be co-opted to different cellular localizations, thereby becoming involved in novel functions. ');
INSERT INTO `papers` (`id`, `ano`, `journal`, `titulo`, `autores`, `afiliacao`, `pais`, `citacoes`, `palavra_chave`, `categorias`, `doi`, `pubmed`, `abstract`) VALUES
(86599, 2014, 'plos', 'The self-limiting dynamics of TGF-xcexb2 signaling in silico and in vitro, with negative feedback through PPM1A upregulation', 'Wang, Junjie|Tucker-Kellogg, Lisa|Ng, Inn Chuan|Jia, Ruirui|Thiagarajan, P S|White, Jacob K|Yu, Hanry', 'Computational and Systems Biology, Singapore-MIT Alliance, Singapore, Mechanobiology Institute, Singapore.|Computational and Systems Biology, Singapore-MIT Alliance, Singapore, Mechanobiology Institute, Singapore, Centre for Computational Biology, Duke-NUS Graduate Medical School, Singapore.|NUS Graduate School for Integrative Science and Engineering, National University of Singapore, Singapore.|Department of Physiology, National University of Singapore, Singapore.|NUS Graduate School for Integrative Science and Engineering, National University of Singapore, Singapore, School of Computing, National University of Singapore, Singapore.|Computational and Systems Biology, Singapore-MIT Alliance, Singapore, Department of Electrical Engineering and Computer Science, Massachusetts Institute of Technology, Cambridge, Massachusetts, United States of America.|Computational and Systems Biology, Singapore-MIT Alliance, Singapore, Mechanobiology Institute, Singapore, NUS Graduate School for Integrative Science and Engineering, National University of Singapore, Singapore, Department of Physiology, National University of Singapore, Singapore, Department of Biological Engineering, Massachusetts Institute of Technology, Cambridge, Massachusetts, United States of America.', 'Singapore|Singapore|Singapore|Singapore|Singapore|Singapore|Singapore', 0, 'Cell Line|Computational Biology|Computer Simulation|Feedback, Physiological|Humans|In Vitro Techniques|Intracellular Signaling Peptides and Proteins|Models, Theoretical|Phosphoprotein Phosphatases|Phosphorylation|Protein Phosphatase 2C|Proteolysis|Proto-Oncogene Proteins|Signal Transduction|Smad Proteins, Receptor-Regulated|Transforming Growth Factor beta|Up-Regulation', 'Journal Article', '10.1371/journal.pcbi.1003573', '24901250', 'The TGF-xcexb2/Smad signaling system decreases its activity through strong negative regulation. Several molecular mechanisms of negative regulation have been published, but the relative impact of each mechanism on the overall system is unknown. In this work, we used computational and experimental methods to assess multiple negative regulatory effects on Smad signaling in HaCaT cells. Previously reported negative regulatory effects were classified by time-scale: degradation of phosphorylated R-Smad and I-Smad-induced receptor degradation were slow-mode effects, and dephosphorylation of R-Smad was a fast-mode effect. We modeled combinations of these effects, but found no combination capable of explaining the observed dynamics of TGF-xcexb2/Smad signaling. We then proposed a negative feedback loop with upregulation of the phosphatase PPM1A. The resulting model was able to explain the dynamics of Smad signaling, under both short and long exposures to TGF-xcexb2. Consistent with this model, immuno-blots showed PPM1A levels to be significantly increased within 30 min after TGF-xcexb2 stimulation. Lastly, our model was able to resolve an apparent contradiction in the published literature, concerning the dynamics of phosphorylated R-Smad degradation. We conclude that the dynamics of Smad negative regulation cannot be explained by the negative regulatory effects that had previously been modeled, and we provide evidence for a new negative feedback loop through PPM1A upregulation. This work shows that tight coupling of computational and experiments approaches can yield improved understanding of complex pathways. '),
(86600, 2014, 'plos', 'Optimizing metabolite production using periodic oscillations', 'Sowa, Steven W|Baldea, Michael|Contreras, Lydia M', 'Microbiology Graduate Program, University of Texas at Austin, Austin, Texas, United States of America.|McKetta Department of Chemical Engineering, University of Texas at Austin, Austin, Texas, United States of America.|McKetta Department of Chemical Engineering, University of Texas at Austin, Austin, Texas, United States of America.', 'United States|United States|United States', 0, 'Enzymes|Escherichia coli|Metabolic Networks and Pathways|Models, Biological|Phosphoenolpyruvate|Systems Biology', 'Journal Article', '10.1371/journal.pcbi.1003658', '24901332', 'Methods for improving microbial strains for metabolite production remain the subject of constant research. Traditionally, metabolic tuning has been mostly limited to knockouts or overexpression of pathway genes and regulators. In this paper, we establish a new method to control metabolism by inducing optimally tuned time-oscillations in the levels of selected clusters of enzymes, as an alternative strategy to increase the production of a desired metabolite. Using an established kinetic model of the central carbon metabolism of Escherichia coli, we formulate this concept as a dynamic optimization problem over an extended, but finite time horizon. Total production of a metabolite of interest (in this case, phosphoenolpyruvate, PEP) is established as the objective function and time-varying concentrations of the cellular enzymes are used as decision variables. We observe that by varying, in an optimal fashion, levels of key enzymes in time, PEP production increases significantly compared to the unoptimized system. We demonstrate that oscillations can improve metabolic output in experimentally feasible synthetic circuits. '),
(86601, 2014, 'plos', 'Histone modifications are associated with transcript isoform diversity in normal and cancer cells', 'Podlaha, Ondrej|De, Subhajyoti|Gonen, Mithat|Michor, Franziska', 'Department of Biostatistics and Computational Biology, Dana-Farber Cancer Institute, and Department of Biostatistics, Harvard School of Public Health, Boston, Massachusetts, United States of America.|Department of Medicine, University of Colorado School of Medicine, Aurora, Colorado, United States of America, Department of Biostatistics and Informatics, Colorado School of Public Health, Aurora, Colorado, United States of America, Molecular Oncology Program, University of Colorado Cancer Center, Aurora, Colorado, United States of America.|Department of Epidemiology and Biostatistics, Memorial Sloan-Kettering Cancer Center, New York, New York, United States of America.|Department of Biostatistics and Computational Biology, Dana-Farber Cancer Institute, and Department of Biostatistics, Harvard School of Public Health, Boston, Massachusetts, United States of America.', 'United States|United States|United States|United States', 13, 'Alternative Splicing|Cell Line|Cell Line, Tumor|Computational Biology|Epigenesis, Genetic|Exons|Genetic Variation|Histones|Humans|Models, Genetic|Neoplasm Proteins|Neoplasms|RNA Isoforms|RNA, Messenger|RNA, Neoplasm|Transcription Initiation Site', 'Journal Article', '10.1371/journal.pcbi.1003611', '24901363', 'Mechanisms that generate transcript diversity are of fundamental importance in eukaryotes. Although a large fraction of human protein-coding genes and lincRNAs produce more than one mRNA isoform each, the regulation of this phenomenon is still incompletely understood. Much progress has been made in deciphering the role of sequence-specific features as well as DNA-and RNA-binding proteins in alternative splicing. Recently, however, several experimental studies of individual genes have revealed a direct involvement of epigenetic factors in alternative splicing and transcription initiation. While histone modifications are generally correlated with overall gene expression levels, it remains unclear how histone modification enrichment affects relative isoform abundance. Therefore, we sought to investigate the associations between histone modifications and transcript diversity levels measured by the rates of transcription start-site switching and alternative splicing on a genome-wide scale across protein-coding genes and lincRNAs. We found that the relationship between enrichment levels of epigenetic marks and transcription start-site switching is similar for protein-coding genes and lincRNAs. Furthermore, we found associations between splicing rates and enrichment levels of H2az, H3K4me1, H3K4me2, H3K4me3, H3K9ac, H3K9me3, H3K27ac, H3K27me3, H3K36me3, H3K79me2, and H4K20me, marks traditionally associated with enhancers, transcription initiation, transcriptional repression, and others. These patterns were observed in both normal and cancer cell lines. Additionally, we developed a novel computational method that identified 840 epigenetically regulated candidate genes and predicted transcription start-site switching and alternative exon splicing with up to 92% accuracy based on epigenetic patterning alone. Our results suggest that the epigenetic regulation of transcript isoform diversity may be a relatively common genome-wide phenomenon representing an avenue of deregulation in tumor development. '),
(86602, 2014, 'plos', 'AprioriGWAS, a new pattern mining strategy for detecting genetic variants associated with disease through interaction effects', 'Zhang, Qingrun|Long, Quan|Ott, Jurg', 'Department of Genetics and Genomic Sciences, Institute of Genomics and Multi-scale Biology, Icahn School of Medicine at Mount Sinai, New York, New York, United States of America.|Department of Genetics and Genomic Sciences, Institute of Genomics and Multi-scale Biology, Icahn School of Medicine at Mount Sinai, New York, New York, United States of America.|Institute of Psychology, Chinese Academy of Sciences, Chaoyang District, Beijing, PR China, Laboratory of Statistical Genetics, The Rockefeller University, New York, New York, United States of America.', 'United States|United States|China', 12, 'Algorithms|Bipolar Disorder|Complement Factor H|Computational Biology|Computer Simulation|Data Mining|Databases, Genetic|Epistasis, Genetic|Genetic Predisposition to Disease|Genetic Variation|Genome-Wide Association Study|Humans|Linkage Disequilibrium|Logistic Models|Macular Degeneration|Models, Genetic', 'Journal Article', '10.1371/journal.pcbi.1003627', '24901472', 'Identifying gene-gene interaction is a hot topic in genome wide association studies. Two fundamental challenges are: (1) how to smartly identify combinations of variants that may be associated with the trait from astronomical number of all possible combinations, and (2) how to test epistatic interaction when all potential combinations are available. We developed AprioriGWAS, which brings two innovations. (1) Based on Apriori, a successful method in field of Frequent Itemset Mining (FIM) in which a pattern growth strategy is leveraged to effectively and accurately reduce search space, AprioriGWAS can efficiently identify genetically associated genotype patterns. (2) To test the hypotheses of epistasis, we adopt a new conditional permutation procedure to obtain reliable statistical inference of Pearsons chi-square test for the [Formula: see text] contingency table generated by associated variants. By applying AprioriGWAS to age-related macular degeneration (AMD) data, we found that: (1) angiopoietin 1 (ANGPT1) and four retinal genes interact with Complement Factor H (CFH). (2) GO term glycosaminoglycan biosynthetic process was enriched in AMD interacting genes. The epistatic interactions newly found by AprioriGWAS on AMD data are likely true interactions, since genes interacting with CFH are retinal genes, and GO term enrichment also verified that interaction between glycosaminoglycans (GAGs) and CFH plays an important role in disease pathology of AMD. By applying AprioriGWAS on Bipolar disorder in WTCCC data, we found variants without marginal effect show significant interactions. For example, multiple-SNP genotype patterns inside gene GABRB2 and GRIA1 (AMPA subunit 1 receptor gene). AMPARs are found in many parts of the brain and are the most commonly found receptor in the nervous system. The GABRB2 mediates the fastest inhibitory synaptic transmission in the central nervous system. GRIA1 and GABRB2 are relevant to mental disorders supported by multiple evidences. '),
(86603, 2014, 'plos', 'Messages do diffuse faster than messengers: reconciling disparate estimates of the morphogen bicoid diffusion coefficient', 'Sigaut, Lorena|Pearson, John E|Colman-Lerner, Alejandro|Ponce Dawson, Silvina', 'Departamento de Física and IFIBA, FCEN-UBA - CONICET, Buenos Aires, Argentina.|Theoretical Biology and Biophysics, Los Alamos National Laboratory, Los Alamos, New Mexico, United States of America.|Departamento de Fisiología, Biología Molecular y Celular and IFIBYNE, CONICET, FCEN-UBA, Buenos Aires, Argentina.|Departamento de Física and IFIBA, FCEN-UBA - CONICET, Buenos Aires, Argentina.', 'Argentina|Mexico|Argentina|Argentina', 16, 'Active Transport, Cell Nucleus|Animals|Animals, Genetically Modified|Biophysical Phenomena|Body Patterning|Computational Biology|Computer Simulation|Diffusion|Drosophila Proteins|Drosophila melanogaster|Fluorescence Recovery After Photobleaching|Homeodomain Proteins|Models, Biological|Recombinant Fusion Proteins|Spectrometry, Fluorescence|Trans-Activators', 'Journal Article', '10.1371/journal.pcbi.1003629', '24901638', 'The gradient of Bicoid (Bcd) is key for the establishment of the anterior-posterior axis in Drosophila embryos. The gradient properties are compatible with the SDD model in which Bcd is synthesized at the anterior pole and then diffuses into the embryo and is degraded with a characteristic time. Within this model, the Bcd diffusion coefficient is critical to set the timescale of gradient formation. This coefficient has been measured using two optical techniques, Fluorescence Recovery After Photobleaching (FRAP) and Fluorescence Correlation Spectroscopy (FCS), obtaining estimates in which the FCS value is an order of magnitude larger than the FRAP one. This discrepancy raises the following questions: which estimate is correct, what is the reason for the disparity, and can the SDD model explain Bcd gradient formation within the experimentally observed times? In this paper, we use a simple biophysical model in which Bcd diffuses and interacts with binding sites to show that both the FRAP and the FCS estimates may be correct and compatible with the observed timescale of gradient formation. The discrepancy arises from the fact that FCS and FRAP report on different effective (concentration dependent) diffusion coefficients, one of which describes the spreading rate of the individual Bcd molecules (the messengers) and the other one that of their concentration (the message). The latter is the one that is more relevant for the gradient establishment and is compatible with its formation within the experimentally observed times. '),
(86604, 2014, 'plos', 'A novel cell traction force microscopy to study multi-cellular system', 'Tang, Xin|Tofangchi, Alireza|Anand, Sandeep V|Saif, Taher A', 'Department of Mechanical Science and Engineering (MechSE), College of Engineering, University of Illinois at Urbana-Champaign (UIUC), Urbana, Illinois, United States of America.|Department of Mechanical Science and Engineering (MechSE), College of Engineering, University of Illinois at Urbana-Champaign (UIUC), Urbana, Illinois, United States of America.|Department of Mechanical Science and Engineering (MechSE), College of Engineering, University of Illinois at Urbana-Champaign (UIUC), Urbana, Illinois, United States of America.|Department of Mechanical Science and Engineering (MechSE), College of Engineering, University of Illinois at Urbana-Champaign (UIUC), Urbana, Illinois, United States of America, Micro and Nanotechnology Laboratory (MNTL), University of Illinois at Urbana-Champaign (UIUC), Urbana, Illinois, United States of America.', 'United States|United States|United States|United States', 0, 'Animals|Biophysical Phenomena|Cell Adhesion|Cell Line, Tumor|Cells, Cultured|Cellular Microenvironment|Compressive Strength|Computational Biology|Finite Element Analysis|Humans|Mechanotransduction, Cellular|Microscopy|Models, Biological|Tensile Strength', 'Journal Article', '10.1371/journal.pcbi.1003631', '24901766', 'Traction forces exerted by adherent cells on their microenvironment can mediate many critical cellular functions. Accurate quantification of these forces is essential for mechanistic understanding of mechanotransduction. However, most existing methods of quantifying cellular forces are limited to single cells in isolation, whereas most physiological processes are inherently multi-cellular in nature where cell-cell and cell-microenvironment interactions determine the emergent properties of cell clusters. In the present study, a robust finite-element-method-based cell traction force microscopy technique is developed to estimate the traction forces produced by multiple isolated cells as well as cell clusters on soft substrates. The method accounts for the finite thickness of the substrate. Hence, cell cluster size can be larger than substrate thickness. The method allows computing the traction field from the substrate displacements within the cells and clusters boundaries. The displacement data outside these boundaries are not necessary. The utility of the method is demonstrated by computing the traction generated by multiple monkey kidney fibroblasts (MKF) and human colon cancerous (HCT-8) cells in close proximity, as well as by large clusters. It is found that cells act as individual contractile groups within clusters for generating traction. There may be multiple of such groups in the cluster, or the entire cluster may behave a single group. Individual cells do not form dipoles, but serve as a conduit of force (transmission lines) over long distances in the cluster. The cell-cell force can be either tensile or compressive depending on the cell-microenvironment interactions. '),
(86605, 2014, 'plos', 'A normative theory of forgetting: lessons from the fruit fly', 'Brea, Johanni|Urbanczik, Robert|Senn, Walter', 'Department of Physiology, University of Bern, Bern, Switzerland.|Department of Physiology, University of Bern, Bern, Switzerland.|Department of Physiology and Center for Cognition, Learning and Memory, University of Bern, Bern, Switzerland.', 'Switzerland|Switzerland|Switzerland', 13, 'Adaptation, Physiological|Adaptation, Psychological|Animals|Behavior, Animal|Computational Biology|Conditioning (Psychology)|Decision Making|Drosophila melanogaster|Environment|Learning|Memory|Models, Biological|Models, Psychological|Odorants|Reward|Stochastic Processes', 'Journal Article', '10.1371/journal.pcbi.1003640', '24901935', 'Recent experiments revealed that the fruit fly Drosophila melanogaster has a dedicated mechanism for forgetting: blocking the G-protein Rac leads to slower and activating Rac to faster forgetting. This active form of forgetting lacks a satisfactory functional explanation. We investigated optimal decision making for an agent adapting to a stochastic environment where a stimulus may switch between being indicative of reward or punishment. Like Drosophila, an optimal agent shows forgetting with a rate that is linked to the time scale of changes in the environment. Moreover, to reduce the odds of missing future reward, an optimal agent may trade the risk of immediate pain for information gain and thus forget faster after aversive conditioning. A simple neuronal network reproduces these features. Our theory shows that forgetting in Drosophila appears as an optimal adaptive behavior in a changing environment. This is in line with the view that forgetting is adaptive rather than a consequence of limitations of the memory system. '),
(86606, 2014, 'plos', 'Place cell rate remapping by CA3 recurrent collaterals', 'Solstad, Trygve|Yousif, Hosam N|Sejnowski, Terrence J', 'Howard Hughes Medical Institute, Computational Neurobiology Laboratory, Salk Institute for Biological Studies, La Jolla, California, United States of America, Kavli Institute for Systems Neuroscience and Centre for Neural Computation, Norwegian University of Science and Technology, MTFS, Trondheim, Norway.|Howard Hughes Medical Institute, Computational Neurobiology Laboratory, Salk Institute for Biological Studies, La Jolla, California, United States of America, Department of Physics, University of California at San Diego, La Jolla, California, United States of America.|Howard Hughes Medical Institute, Computational Neurobiology Laboratory, Salk Institute for Biological Studies, La Jolla, California, United States of America, Division of Biological Sciences, University of California at San Diego, La Jolla, California, United States of America.', 'Norway|United States|United States', 13, 'Action Potentials|Animals|Behavior, Animal|CA3 Region, Hippocampal|Computational Biology|Connectome|Feedback, Physiological|Memory|Memory, Episodic|Models, Neurological|Models, Psychological|Nerve Net|Spatial Behavior', 'Journal Article', '10.1371/journal.pcbi.1003648', '24902003', 'Episodic-like memory is thought to be supported by attractor dynamics in the hippocampus. A possible neural substrate for this memory mechanism is rate remapping, in which the spatial map of place cells encodes contextual information through firing rate variability. To test whether memories are stored as multimodal attractors in populations of place cells, recent experiments morphed one familiar context into another while observing the responses of CA3 cell ensembles. Average population activity in CA3 was reported to transition gradually rather than abruptly from one familiar context to the next, suggesting a lack of attractive forces associated with the two stored representations. On the other hand, individual CA3 cells showed a mix of gradual and abrupt transitions at different points along the morph sequence, and some displayed hysteresis which is a signature of attractor dynamics. To understand whether these seemingly conflicting results are commensurate with attractor network theory, we developed a neural network model of the CA3 with attractors for both position and discrete contexts. We found that for memories stored in overlapping neural ensembles within a single spatial map, position-dependent context attractors made transitions at different points along the morph sequence. Smooth transition curves arose from averaging across the population, while a heterogeneous set of responses was observed on the single unit level. In contrast, orthogonal memories led to abrupt and coherent transitions on both population and single unit levels as experimentally observed when remapping between two independent spatial maps. Strong recurrent feedback entailed a hysteretic effect on the network which diminished with the amount of overlap in the stored memories. These results suggest that context-dependent memory can be supported by overlapping local attractors within a spatial map of CA3 place cells. Similar mechanisms for context-dependent memory may also be found in other regions of the cerebral cortex. '),
(86607, 2014, 'plos', 'A unifying mechanistic model of selective attention in spiking neurons', 'Bobier, Bruce|Stewart, Terrence C|Eliasmith, Chris', 'Centre for Theoretical Neuroscience, University of Waterloo, Waterloo, Ontario, Canada.|Centre for Theoretical Neuroscience, University of Waterloo, Waterloo, Ontario, Canada.|Centre for Theoretical Neuroscience, University of Waterloo, Waterloo, Ontario, Canada.', 'Canada|Canada|Canada', 10, 'Action Potentials|Animals|Attention|Biofeedback, Psychology|Cerebral Cortex|Computational Biology|Macaca|Models, Neurological|Neural Pathways|Neurons|Photic Stimulation', 'Journal Article', '10.1371/journal.pcbi.1003577', '24921249', 'Visuospatial attention produces myriad effects on the activity and selectivity of cortical neurons. Spiking neuron models capable of reproducing a wide variety of these effects remain elusive. We present a model called the Attentional Routing Circuit (ARC) that provides a mechanistic description of selective attentional processing in cortex. The model is described mathematically and implemented at the level of individual spiking neurons, with the computations for performing selective attentional processing being mapped to specific neuron types and laminar circuitry. The model is used to simulate three studies of attention in macaque, and is shown to quantitatively match several observed forms of attentional modulation. Specifically, ARC demonstrates that with shifts of spatial attention, neurons may exhibit shifting and shrinking of receptive fields, increases in responses without changes in selectivity for non-spatial features (i.e. response gain), and, that the effect on contrast-response functions is better explained as a response-gain effect than as contrast-gain. Unlike past models, ARC embodies a single mechanism that unifies the above forms of attentional modulation, is consistent with a wide array of available data, and makes several specific and quantifiable predictions. '),
(86608, 2014, 'plos', 'A new online computational biology curriculum', 'Searls, David B', 'Independent Consultant, Philadelphia, Pennsylvania, United States of America.', 'United States', 0, 'Computational Biology|Computer-Assisted Instruction|Humans|Internet', 'Journal Article', '10.1371/journal.pcbi.1003662', '24921255', 'A recent proliferation of Massive Open Online Courses (MOOCs) and other web-based educational resources has greatly increased the potential for effective self-study in many fields. This article introduces a catalog of several hundred free video courses of potential interest to those wishing to expand their knowledge of bioinformatics and computational biology. The courses are organized into eleven subject areas modeled on university departments and are accompanied by commentary and career advice. '),
(86609, 2014, 'plos', 'Comparative analysis of human tissue interactomes reveals factors leading to tissue-specific manifestation of hereditary diseases', 'Barshir, Ruth|Shwartz, Omer|Smoly, Ilan Y|Yeger-Lotem, Esti', 'Department of Clinical Biochemistry and Pharmacology, Ben-Gurion University of the Negev, Beer-Sheva, Israel.|Department of Clinical Biochemistry and Pharmacology, Ben-Gurion University of the Negev, Beer-Sheva, Israel.|Department of Computer Science, Ben-Gurion University of the Negev, Beer-Sheva, Israel.|Department of Clinical Biochemistry and Pharmacology, Ben-Gurion University of the Negev, Beer-Sheva, Israel, National Institute for Biotechnology in the Negev, Ben-Gurion University of the Negev, Beer-Sheva, Israel.', 'Israel|Israel|Israel|Israel', 36, 'Computational Biology|Databases, Genetic|Gene Expression Profiling|Genetic Diseases, Inborn|Genetic Predisposition to Disease|Genomics|Humans|Protein Interaction Mapping|Protein Interaction Maps|Proteomics|Tissue Distribution', 'Comparative Study', '10.1371/journal.pcbi.1003632', '24921629', 'An open question in human genetics is what underlies the tissue-specific manifestation of hereditary diseases, which are caused by genomic aberrations that are present in cells across the human body. Here we analyzed this phenomenon for over 300 hereditary diseases by using comparative network analysis. We created an extensive resource of protein expression and interactions in 16 main human tissues, by integrating recent data of gene and protein expression across tissues with data of protein-protein interactions (PPIs). The resulting tissue interaction networks (interactomes) shared a large fraction of their proteins and PPIs, and only a small fraction of them were tissue-specific. Applying this resource to hereditary diseases, we first show that most of the disease-causing genes are widely expressed across tissues, yet, enigmatically, cause disease phenotypes in few tissues only. Upon testing for factors that could lead to tissue-specific vulnerability, we find that disease-causing genes tend to have elevated transcript levels and increased number of tissue-specific PPIs in their disease tissues compared to unaffected tissues. We demonstrate through several examples that these tissue-specific PPIs can highlight disease mechanisms, and thus, owing to their small number, provide a powerful filter for interrogating disease etiologies. As two thirds of the hereditary diseases are associated with these factors, comparative tissue analysis offers a meaningful and efficient framework for enhancing the understanding of the molecular basis of hereditary diseases. '),
(86610, 2014, 'plos', 'Augmenting microarray data with literature-based knowledge to enhance gene regulatory network inference', 'Chen, Guocai|Cairelli, Michael J|Kilicoglu, Halil|Shin, Dongwook|Rindflesch, Thomas C', 'Lister Hill National Center for Biomedical Communications, National Library of Medicine, Bethesda, Maryland, United States of America.|Lister Hill National Center for Biomedical Communications, National Library of Medicine, Bethesda, Maryland, United States of America.|Lister Hill National Center for Biomedical Communications, National Library of Medicine, Bethesda, Maryland, United States of America.|Lister Hill National Center for Biomedical Communications, National Library of Medicine, Bethesda, Maryland, United States of America.|Lister Hill National Center for Biomedical Communications, National Library of Medicine, Bethesda, Maryland, United States of America.', 'United States|United States|United States|United States|United States', 24, 'Computational Biology|Data Mining|Databases, Factual|Gene Expression Profiling|Gene Regulatory Networks|Knowledge Bases|Oligonucleotide Array Sequence Analysis', 'Journal Article', '10.1371/journal.pcbi.1003666', '24921649', 'Gene regulatory networks are a crucial aspect of systems biology in describing molecular mechanisms of the cell. Various computational models rely on random gene selection to infer such networks from microarray data. While incorporation of prior knowledge into data analysis has been deemed important, in practice, it has generally been limited to referencing genes in probe sets and using curated knowledge bases. We investigate the impact of augmenting microarray data with semantic relations automatically extracted from the literature, with the view that relations encoding gene/protein interactions eliminate the need for random selection of components in non-exhaustive approaches, producing a more accurate model of cellular behavior. A genetic algorithm is then used to optimize the strength of interactions using microarray data and an artificial neural network fitness function. The result is a directed and weighted network providing the individual contribution of each gene to its target. For testing, we used invasive ductile carcinoma of the breast to query the literature and a microarray set containing gene expression changes in these cells over several time points. Our model demonstrates significantly better fitness than the state-of-the-art model, which relies on an initial random selection of genes. Comparison to the component pathways of the KEGG Pathways in Cancer map reveals that the resulting networks contain both known and novel relationships. The p53 pathway results were manually validated in the literature. 60% of non-KEGG relationships were supported (74% for highly weighted interactions). The method was then applied to yeast data and our model again outperformed the comparison model. Our results demonstrate the advantage of combining gene interactions extracted from the literature in the form of semantic relations with microarray analysis in generating contribution-weighted gene regulatory networks. This methodology can make a significant contribution to understanding the complex interactions involved in cellular behavior and molecular physiology. '),
(86611, 2014, 'plos', 'Spatial Transmission of 2009 Pandemic Influenza in the US', 'Gog, Julia R|Ballesteros, Sébastien|Viboud, Cécile|Simonsen, Lone|Bjornstad, Ottar N|Shaman, Jeffrey|Chao, Dennis L|Khan, Farid|Grenfell, Bryan T', 'Department of Applied Mathematics and Theoretical Physics, University of Cambridge, Cambridge, United Kingdom, Fogarty International Center, National Institutes of Health, Bethesda, Maryland, United States of America.|Department of Ecology and Evolutionary Biology, Princeton University, Princeton, New Jersey, United States of America.|Fogarty International Center, National Institutes of Health, Bethesda, Maryland, United States of America.|Fogarty International Center, National Institutes of Health, Bethesda, Maryland, United States of America, Department of Global Health, George Washington University, Washington, D.C., United States of America.|Fogarty International Center, National Institutes of Health, Bethesda, Maryland, United States of America, Department of Entomology, Pennsylvania State University, State College, Pennsylvania, United States of America.|Department of Environmental Health Sciences, Mailman School of Public Health, Columbia University, New York, New York, United States of America.|Center for Statistics and Quantitative Infectious Diseases, Vaccine and Infectious Disease Division, Fred Hutchinson Cancer Research Center, Seattle, Washington, United States of America.|IMS Health, Plymouth Meeting, Pennsylvania, United States of America.|Fogarty International Center, National Institutes of Health, Bethesda, Maryland, United States of America, Department of Ecology and Evolutionary Biology, Princeton University, Princeton, New Jersey, United States of America.', 'United Kingdom|Jersey|United States|United States|United States|United States|United States|United S', 66, 'Adult|Child|Cities|Computational Biology|History, 21st Century|Humans|Humidity|Influenza A Virus, H1N1 Subtype|Influenza, Human|Likelihood Functions|Models, Biological|Pandemics|Schools|Seasons|United States', 'Historical Article', '10.1371/journal.pcbi.1003635', '24921923', 'The 2009 H1N1 influenza pandemic provides a unique opportunity for detailed examination of the spatial dynamics of an emerging pathogen. In the US, the pandemic was characterized by substantial geographical heterogeneity: the 2009 spring wave was limited mainly to northeastern cities while the larger fall wave affected the whole country. Here we use finely resolved spatial and temporal influenza disease data based on electronic medical claims to explore the spread of the fall pandemic wave across 271 US cities and associated suburban areas. We document a clear spatial pattern in the timing of onset of the fall wave, starting in southeastern cities and spreading outwards over a period of three months. We use mechanistic models to tease apart the external factors associated with the timing of the fall wave arrival: differential seeding events linked to demographic factors, school opening dates, absolute humidity, prior immunity from the spring wave, spatial diffusion, and their interactions. Although the onset of the fall wave was correlated with school openings as previously reported, models including spatial spread alone resulted in better fit. The best model had a combination of the two. Absolute humidity or prior exposure during the spring wave did not improve the fit and population size only played a weak role. In conclusion, the protracted spread of pandemic influenza in fall 2009 in the US was dominated by short-distance spatial spread partially catalysed by school openings rather than long-distance transmission events. This is in contrast to the rapid hierarchical transmission patterns previously described for seasonal influenza. The findings underline the critical role that school-age children play in facilitating the geographic spread of pandemic influenza and highlight the need for further information on the movement and mixing patterns of this age group. '),
(86612, 2014, 'plos', 'A computational model of the fetal circulation to quantify blood redistribution in intrauterine growth restriction', 'Garcia-Canadilla, Patricia|Rudenick, Paula A|Crispi, Fatima|Cruz-Lemini, Monica|Palau, Georgina|Camara, Oscar|Gratacos, Eduard|Bijnens, Bart H|Bijens, Bart H', 'BCNatal - Barcelona Center for Maternal-Fetal and Neonatal Medicine (Hospital Clínic and Hospital Sant Joan de Déu), IDIBAPS, University of Barcelona, and Centre for Biomedical Research on Rare Diseases (CIBER-ER), Barcelona, Spain, Physense, DTIC, Universitat Pompeu Fabra, Barcelona, Spain.|University Hospital and Research Institute Vall dHebron, Universitat Autònoma de Barcelona, Barcelona, Spain.|BCNatal - Barcelona Center for Maternal-Fetal and Neonatal Medicine (Hospital Clínic and Hospital Sant Joan de Déu), IDIBAPS, University of Barcelona, and Centre for Biomedical Research on Rare Diseases (CIBER-ER), Barcelona, Spain.|BCNatal - Barcelona Center for Maternal-Fetal and Neonatal Medicine (Hospital Clínic and Hospital Sant Joan de Déu), IDIBAPS, University of Barcelona, and Centre for Biomedical Research on Rare Diseases (CIBER-ER), Barcelona, Spain.|Physense, DTIC, Universitat Pompeu Fabra, Barcelona, Spain.|Physense, DTIC, Universitat Pompeu Fabra, Barcelona, Spain.|BCNatal - Barcelona Center for Maternal-Fetal and Neonatal Medicine (Hospital Clínic and Hospital Sant Joan de Déu), IDIBAPS, University of Barcelona, and Centre for Biomedical Research on Rare Diseases (CIBER-ER), Barcelona, Spain.|BCNatal - Barcelona Center for Maternal-Fetal and Neonatal Medicine (Hospital Clínic and Hospital Sant Joan de Déu), IDIBAPS, University of Barcelona, and Centre for Biomedical Research on Rare Diseases (CIBER-ER), Barcelona, Spain.|Physense, DTIC, Universitat Pompeu Fabra, Barcelona, Spain, ICREA, Barcelona, Spain.', 'Spain|Spain|Spain|Spain|Spain|Spain|Spain|Spain|Spain', 31, 'Aorta|Computer Simulation|Female|Fetal Growth Retardation|Fetus|Hemodynamics|Humans|Middle Cerebral Artery|Models, Cardiovascular|Placenta|Pregnancy|Pregnancy Trimester, Third', 'Journal Article', '10.1371/journal.pcbi.1003667', '24921933', 'Intrauterine growth restriction (IUGR) due to placental insufficiency is associated with blood flow redistribution in order to maintain delivery of oxygenated blood to the brain. Given that, in the fetus the aortic isthmus (AoI) is a key arterial connection between the cerebral and placental circulations, quantifying AoI blood flow has been proposed to assess this brain sparing effect in clinical practice. While numerous clinical studies have studied this parameter, fundamental understanding of its determinant factors and its quantitative relation with other aspects of haemodynamic remodeling has been limited. Computational models of the cardiovascular circulation have been proposed for exactly this purpose since they allow both for studying the contributions from isolated parameters as well as estimating properties that cannot be directly assessed from clinical measurements. Therefore, a computational model of the fetal circulation was developed, including the key elements related to fetal blood redistribution and using measured cardiac outflow profiles to allow personalization. The model was first calibrated using patient-specific Doppler data from a healthy fetus. Next, in order to understand the contributions of the main parameters determining blood redistribution, AoI and middle cerebral artery (MCA) flow changes were studied by variation of cerebral and peripheral-placental resistances. Finally, to study how this affects an individual fetus, the model was fitted to three IUGR cases with different degrees of severity. In conclusion, the proposed computational model provides a good approximation to assess blood flow changes in the fetal circulation. The results support that while MCA flow is mainly determined by a fall in brain resistance, the AoI is influenced by a balance between increased peripheral-placental and decreased cerebral resistances. Personalizing the model allows for quantifying the balance between cerebral and peripheral-placental remodeling, thus providing potentially novel information to aid clinical follow up. '),
(86613, 2014, 'plos', 'Negative example selection for protein function prediction: the NoGO database', 'Youngs, Noah|Penfold-Brown, Duncan|Bonneau, Richard|Shasha, Dennis', 'Department of Computer Science, New York University, New York, New York, United States of America.|Social Media and Political Participation Lab, New York University, New York, New York, United States of America.|Department of Computer Science, New York University, New York, New York, United States of America, Department of Biology, New York University, New York, New York, United States of America, Center for Genomics and Systems Biology, Department of Biology, New York University, New York, New York, United States of America.|Department of Computer Science, New York University, New York, New York, United States of America, Center for Genomics and Systems Biology, Department of Biology, New York University, New York, New York, United States of America.', 'United States|United States|United States|United States', 24, 'Algorithms|Animals|Arabidopsis Proteins|Artificial Intelligence|Computational Biology|Databases, Genetic|Gene Ontology|Genome|Humans|Mice|Molecular Sequence Annotation|Proteins|Proteome|Saccharomyces cerevisiae Proteins', 'Journal Article', '10.1371/journal.pcbi.1003644', '24922051', 'Negative examples - genes that are known not to carry out a given protein function - are rarely recorded in genome and proteome annotation databases, such as the Gene Ontology database. Negative examples are required, however, for several of the most powerful machine learning methods for integrative protein function prediction. Most protein function prediction efforts have relied on a variety of heuristics for the choice of negative examples. Determining the accuracy of methods for negative example prediction is itself a non-trivial task, given that the Open World Assumption as applied to gene annotations rules out many traditional validation metrics. We present a rigorous comparison of these heuristics, utilizing a temporal holdout, and a novel evaluation strategy for negative examples. We add to this comparison several algorithms adapted from Positive-Unlabeled learning scenarios in text-classification, which are the current state of the art methods for generating negative examples in low-density annotation contexts. Lastly, we present two novel algorithms of our own construction, one based on empirical conditional probability, and the other using topic modeling applied to genes and annotations. We demonstrate that our algorithms achieve significantly fewer incorrect negative example predictions than the current state of the art, using multiple benchmarks covering multiple organisms. Our methods may be applied to generate negative examples for any type of method that deals with protein function, and to this end we provide a database of negative examples in several well-studied organisms, for general use (The NoGO database, available at: bonneaulab.bio.nyu.edu/nogo.html). '),
(86614, 2014, 'plos', 'Comparison of REST cistromes across human cell types reveals common and context-specific functions', 'Rockowitz, Shira|Lien, Wen-Hui|Pedrosa, Erika|Wei, Gang|Lin, Mingyan|Zhao, Keji|Lachman, Herbert M|Fuchs, Elaine|Zheng, Deyou', 'Department of Genetics, Albert Einstein College of Medicine, Bronx, New York, New York, United States of America.|Howard Hughes Medical Institute, Laboratory of Mammalian Cell Biology & Development, The Rockefeller University, New York, New York, United States of America.|Department of Psychiatry and Behavioral Sciences, Albert Einstein College of Medicine, Bronx, New York, New York, United States of America.|Systems Biology Center, National Heart, Lung, and Blood Institute, National Institute of Health, Bethesda, Maryland, United States of America.|Department of Genetics, Albert Einstein College of Medicine, Bronx, New York, New York, United States of America.|Systems Biology Center, National Heart, Lung, and Blood Institute, National Institute of Health, Bethesda, Maryland, United States of America.|Department of Genetics, Albert Einstein College of Medicine, Bronx, New York, New York, United States of America, Department of Psychiatry and Behavioral Sciences, Albert Einstein College of Medicine, Bronx, New York, New York, United States of America, Department of Neuroscience, Albert Einstein College of Medicine, Bronx, New York, New York, United States of America.|Howard Hughes Medical Institute, Laboratory of Mammalian Cell Biology & Development, The Rockefeller University, New York, New York, United States of America.|Department of Genetics, Albert Einstein College of Medicine, Bronx, New York, New York, United States of America, Department of Neuroscience, Albert Einstein College of Medicine, Bronx, New York, New York, United States of America, The Saul R. Korey Department of Neurology, Albert Einstein College of Medicine, Bronx, New York, New York, United States of America.', 'United States|United States|United States|United States|United States|United States|United States|Un', 20, 'Animals|CD4-Positive T-Lymphocytes|Cell Line|Chromatin Immunoprecipitation|Gene Expression Regulation|Gene Silencing|Genomics|Histones|Humans|Mice|MicroRNAs|Neurons|Repressor Proteins', 'Comparative Study', '10.1371/journal.pcbi.1003671', '24922058', 'Recent studies have shown that the transcriptional functions of REST are much broader than repressing neuronal genes in non-neuronal systems. Whether REST occupies similar chromatin regions in different cell types and how it interacts with other transcriptional regulators to execute its functions in a context-dependent manner has not been adequately investigated. We have applied ChIP-seq analysis to identify the REST cistrome in human CD4+ T cells and compared it with published data from 15 other cell types. We found that REST cistromes were distinct among cell types, with REST binding to several tumor suppressors specifically in cancer cells, whereas 7% of the REST peaks in non-neuronal cells were ubiquitously called and <25% were identified for xe2x89xa5 5 cell types. Nevertheless, using a quantitative metric directly comparing raw ChIP-seq signals, we found the majority (xe2x88xbc80%) was shared by xe2x89xa5 2 cell types. Integration with RNA-seq data showed that REST binding was generally correlated with low gene expression. Close examination revealed that multiple contexts were correlated with reduced expression of REST targets, e.g., the presence of a cognate RE1 motif and cellular specificity of REST binding. These contexts were shown to play a role in differential corepressor recruitment. Furthermore, transcriptional outcome was highly influenced by REST cofactors, e.g., SIN3 and EZH2 co-occupancy marked higher and lower expression of REST targets, respectively. Unexpectedly, the REST cistrome in differentiated neurons exhibited unique features not observed in non-neuronal cells, e.g., the lack of RE1 motifs and an association with active gene expression. Finally, our analysis demonstrated how REST could differentially regulate a transcription network constituted of miRNAs, REST complex and neuronal factors. Overall, our findings of contexts playing critical roles in REST occupancy and regulatory outcome provide insights into the molecular interactions underlying RESTs diverse functions, and point to novel roles of REST in differentiated neurons.');
INSERT INTO `papers` (`id`, `ano`, `journal`, `titulo`, `autores`, `afiliacao`, `pais`, `citacoes`, `palavra_chave`, `categorias`, `doi`, `pubmed`, `abstract`) VALUES
(86615, 2014, 'plos', 'An HMM-based comparative genomic framework for detecting introgression in eukaryotes', 'Liu, Kevin J|Dai, Jingxuan|Truong, Kathy|Song, Ying|Kohn, Michael H|Nakhleh, Luay', 'Department of Computer Science, Rice University, Houston, Texas, United States of America, Department of Ecology and Evolutionary Biology, 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.|The State Key Laboratory for Biology of Plant Diseases and Insect Pests, Institute of Plant Protection, Chinese Academy of Agricultural Sciences, Beijing, China.|Department of Ecology and Evolutionary Biology, Rice University, Houston, Texas, United States of America.|Department of Computer Science, Rice University, Houston, Texas, United States of America, Department of Ecology and Evolutionary Biology, Rice University, Houston, Texas, United States of America.', 'United States|United States|United States|China|United States|United States', 25, 'Algorithms|Animals|Chromosome Mapping|Comparative Genomic Hybridization|Computational Biology|Computer Simulation|Databases, Genetic|Evolution, Molecular|Genetics, Population|Genomics|Markov Chains|Mice|Models, Genetic|Phylogeny', 'Journal Article', '10.1371/journal.pcbi.1003649', '24922281', 'One outcome of interspecific hybridization and subsequent effects of evolutionary forces is introgression, which is the integration of genetic material from one species into the genome of an individual in another species. The evolution of several groups of eukaryotic species has involved hybridization, and cases of adaptation through introgression have been already established. In this work, we report on PhyloNet-HMM-a new comparative genomic framework for detecting introgression in genomes. PhyloNet-HMM combines phylogenetic networks with hidden Markov models (HMMs) to simultaneously capture the (potentially reticulate) evolutionary history of the genomes and dependencies within genomes. A novel aspect of our work is that it also accounts for incomplete lineage sorting and dependence across loci. Application of our model to variation data from chromosome 7 in the mouse (Mus musculus domesticus) genome detected a recently reported adaptive introgression event involving the rodent poison resistance gene Vkorc1, in addition to other newly detected introgressed genomic regions. Based on our analysis, it is estimated that about 9% of all sites within chromosome 7 are of introgressive origin (these cover about 13 Mbp of chromosome 7, and over 300 genes). Further, our model detected no introgression in a negative control data set. We also found that our model accurately detected introgression and other evolutionary processes from synthetic data sets simulated under the coalescent model with recombination, isolation, and migration. Our work provides a powerful framework for systematic analysis of introgression while simultaneously accounting for dependence across sites, point mutations, recombination, and ancestral polymorphism. '),
(86616, 2014, 'plos', 'CGBayesNets: conditional Gaussian Bayesian network learning and inference with mixed discrete and continuous data', 'McGeachie, Michael J|Chang, Hsun-Hsien|Weiss, Scott T', 'Channing Division of Network Medicine, Brigham and Womens Hospital, Boston, Massachusetts, United States of America, Harvard Medical School, Boston, Massachusetts, United States of America.|Harvard Medical School, Boston, Massachusetts, United States of America, Childrens Hospital Informatics Program, Childrens Hospital Boston, Boston, Massachusetts, United States of America.|Channing Division of Network Medicine, Brigham and Womens Hospital, Boston, Massachusetts, United States of America, Harvard Medical School, Boston, Massachusetts, United States of America, Partners Health Care Center for Personalized Medicine, Boston, Massachusetts, United States of America.', 'United States|United States|United States', 38, 'Algorithms|Bayes Theorem|Gene Expression Profiling|Genomics|Humans|Intensive Care Units|Internet|Leukemia|Models, Biological|Normal Distribution|Phenotype|Software|Wood', 'Journal Article', '10.1371/journal.pcbi.1003676', '24922310', 'Bayesian Networks (BN) have been a popular predictive modeling formalism in bioinformatics, but their application in modern genomics has been slowed by an inability to cleanly handle domains with mixed discrete and continuous variables. Existing free BN software packages either discretize continuous variables, which can lead to information loss, or do not include inference routines, which makes prediction with the BN impossible. We present CGBayesNets, a BN package focused around prediction of a clinical phenotype from mixed discrete and continuous variables, which fills these gaps. CGBayesNets implements Bayesian likelihood and inference algorithms for the conditional Gaussian Bayesian network (CGBNs) formalism, one appropriate for predicting an outcome of interest from, e.g., multimodal genomic data. We provide four different network learning algorithms, each making a different tradeoff between computational cost and network likelihood. CGBayesNets provides a full suite of functions for model exploration and verification, including cross validation, bootstrapping, and AUC manipulation. We highlight several results obtained previously with CGBayesNets, including predictive models of wood properties from tree genomics, leukemia subtype classification from mixed genomic data, and robust prediction of intensive care unit mortality outcomes from metabolomic profiles. We also provide detailed example analysis on public metabolomic and gene expression datasets. CGBayesNets is implemented in MATLAB and available as MATLAB source code, under an Open Source license and anonymous download at http://www.cgbayesnets.com. '),
(86617, 2014, 'plos', 'Model selection in systems biology depends on experimental design', 'Silk, Daniel|Kirk, Paul D W|Barnes, Chris P|Toni, Tina|Stumpf, Michael P H', 'Centre for Integrative Systems Biology at Imperial College London, London, United Kingdom.|Centre for Integrative Systems Biology at Imperial College London, London, United Kingdom.|Centre for Integrative Systems Biology at Imperial College London, London, United Kingdom.|Centre for Integrative Systems Biology at Imperial College London, London, United Kingdom.|Centre for Integrative Systems Biology at Imperial College London, London, United Kingdom.', 'United Kingdom|United Kingdom|United Kingdom|United Kingdom|United Kingdom', 29, 'Computational Biology|Computer Simulation|Mathematical Concepts|Models, Biological|Monte Carlo Method|Signal Transduction|Systems Biology', 'Journal Article', '10.1371/journal.pcbi.1003650', '24922483', 'Experimental design attempts to maximise the information available for modelling tasks. An optimal experiment allows the inferred models or parameters to be chosen with the highest expected degree of confidence. If the true system is faithfully reproduced by one of the models, the merit of this approach is clear - we simply wish to identify it and the true parameters with the most certainty. However, in the more realistic situation where all models are incorrect or incomplete, the interpretation of model selection outcomes and the role of experimental design needs to be examined more carefully. Using a novel experimental design and model selection framework for stochastic state-space models, we perform high-throughput in-silico analyses on families of gene regulatory cascade models, to show that the selected model can depend on the experiment performed. We observe that experimental design thus makes confidence a criterion for model choice, but that this does not necessarily correlate with a models predictive power or correctness. Finally, in the special case of linear ordinary differential equation (ODE) models, we explore how wrong a model has to be before it influences the conclusions of a model selection analysis. '),
(86618, 2014, 'plos', 'Computational modeling of allosteric regulation in the hsp90 chaperones: a statistical ensemble analysis of protein structure networks and allosteric communications', 'Blacklock, Kristin|Verkhivker, Gennady M', 'School of Computational Sciences and Crean School of Health and Life Sciences, Schmid College of Science and Technology, Chapman University, Orange, California, United States of America.|School of Computational Sciences and Crean School of Health and Life Sciences, Schmid College of Science and Technology, Chapman University, Orange, California, United States of America, Department of Pharmacology, University of California San Diego, La Jolla, California, United States of America.', 'United States|United States', 50, 'Adenosine Triphosphatases|Adenosine Triphosphate|Allosteric Regulation|Bacterial Proteins|Fungal Proteins|HSP90 Heat-Shock Proteins|Molecular Chaperones|Molecular Dynamics Simulation|Protein Binding|Protein Conformation|Thermodynamics', 'Journal Article', '10.1371/journal.pcbi.1003679', '24922508', 'A fundamental role of the Hsp90 chaperone in regulating functional activity of diverse protein clients is essential for the integrity of signaling networks. In this work we have combined biophysical simulations of the Hsp90 crystal structures with the protein structure network analysis to characterize the statistical ensemble of allosteric interaction networks and communication pathways in the Hsp90 chaperones. We have found that principal structurally stable communities could be preserved during dynamic changes in the conformational ensemble. The dominant contribution of the inter-domain rigidity to the interaction networks has emerged as a common factor responsible for the thermodynamic stability of the active chaperone form during the ATPase cycle. Structural stability analysis using force constant profiling of the inter-residue fluctuation distances has identified a network of conserved structurally rigid residues that could serve as global mediating sites of allosteric communication. Mapping of the conformational landscape with the network centrality parameters has demonstrated that stable communities and mediating residues may act concertedly with the shifts in the conformational equilibrium and could describe the majority of functionally significant chaperone residues. The network analysis has revealed a relationship between structural stability, global centrality and functional significance of hotspot residues involved in chaperone regulation. We have found that allosteric interactions in the Hsp90 chaperone may be mediated by modules of structurally stable residues that display high betweenness in the global interaction network. The results of this study have suggested that allosteric interactions in the Hsp90 chaperone may operate via a mechanism that combines rapid and efficient communication by a single optimal pathway of structurally rigid residues and more robust signal transmission using an ensemble of suboptimal multiple communication routes. This may be a universal requirement encoded in protein structures to balance the inherent tension between resilience and efficiency of the residue interaction networks. '),
(86619, 2014, 'plos', 'Protein conservation and variation suggest mechanisms of cell type-specific modulation of signaling pathways', 'Schaefer, Martin H|Yang, Jae-Seong|Serrano, Luis|Kiel, Christina', 'EMBL/CRG Systems Biology Research Unit, Centre for Genomic Regulation (CRG), Barcelona, Spain, Universitat Pompeu Fabra (UPF), Barcelona, Spain.|EMBL/CRG Systems Biology Research Unit, Centre for Genomic Regulation (CRG), Barcelona, Spain, Universitat Pompeu Fabra (UPF), Barcelona, Spain.|EMBL/CRG Systems Biology Research Unit, Centre for Genomic Regulation (CRG), Barcelona, Spain, Universitat Pompeu Fabra (UPF), Barcelona, Spain, Institució Catalana de Recerca i Estudis Avançats (ICREA), Barcelona, Spain.|EMBL/CRG Systems Biology Research Unit, Centre for Genomic Regulation (CRG), Barcelona, Spain, Universitat Pompeu Fabra (UPF), Barcelona, Spain.', 'Spain|Spain|Spain|Spain', 18, 'Animals|Cell Line|Gene Expression Profiling|Humans|Mice|Models, Biological|Mutation|Organ Specificity|Proteins|Proteomics|Signal Transduction', 'Journal Article', '10.1371/journal.pcbi.1003659', '24922536', 'Many proteins and signaling pathways are present in most cell types and tissues and yet perform specialized functions. To elucidate mechanisms by which these ubiquitous pathways are modulated, we overlaid information about cross-cell line protein abundance and variability, and evolutionary conservation onto functional pathway components and topological layers in the pathway hierarchy. We found that the input (receptors) and the output (transcription factors) layers evolve more rapidly than proteins in the intermediary transmission layer. In contrast, protein expression variability decreases from the input to the output layer. We observed that the differences in protein variability between the input and transmission layer can be attributed to both the network position and the tendency of variable proteins to physically interact with constitutively expressed proteins. Differences in protein expression variability and conservation are also accompanied by the tendency of conserved and constitutively expressed proteins to acquire somatic mutations, while germline mutations tend to occur in cell type-specific proteins. Thus, conserved core proteins in the transmission layer could perform a fundamental role in most cell types and are therefore less tolerant to germline mutations. In summary, we propose that the core signal transmission machinery is largely modulated by a variable input layer through physical protein interactions. We hypothesize that the bow-tie organization of cellular signaling on the level of protein abundance variability contributes to the specificity of the signal response in different cell types. '),
(86620, 2014, 'plos', 'On the origins of suboptimality in human probabilistic inference', 'Acerbi, Luigi|Vijayakumar, Sethu|Wolpert, Daniel M', 'Institute of Perception, Action and Behaviour, School of Informatics, University of Edinburgh, Edinburgh, United Kingdom, Doctoral Training Centre in Neuroinformatics and Computational Neuroscience, School of Informatics, University of Edinburgh, Edinburgh, United Kingdom.|Institute of Perception, Action and Behaviour, School of Informatics, University of Edinburgh, Edinburgh, United Kingdom.|Computational and Biological Learning Lab, Department of Engineering, University of Cambridge, Cambridge, United Kingdom.', 'United Kingdom|United Kingdom|United Kingdom', 68, 'Adolescent|Adult|Algorithms|Computational Biology|Decision Making|Female|Humans|Male|Models, Statistical|Task Performance and Analysis|Young Adult', 'Journal Article', '10.1371/journal.pcbi.1003661', '24945142', 'Humans have been shown to combine noisy sensory information with previous experience (priors), in qualitative and sometimes quantitative agreement with the statistically-optimal predictions of Bayesian integration. However, when the prior distribution becomes more complex than a simple Gaussian, such as skewed or bimodal, training takes much longer and performance appears suboptimal. It is unclear whether such suboptimality arises from an imprecise internal representation of the complex prior, or from additional constraints in performing probabilistic computations on complex distributions, even when accurately represented. Here we probe the sources of suboptimality in probabilistic inference using a novel estimation task in which subjects are exposed to an explicitly provided distribution, thereby removing the need to remember the prior. Subjects had to estimate the location of a target given a noisy cue and a visual representation of the prior probability density over locations, which changed on each trial. Different classes of priors were examined (Gaussian, unimodal, bimodal). Subjects performance was in qualitative agreement with the predictions of Bayesian Decision Theory although generally suboptimal. The degree of suboptimality was modulated by statistical features of the priors but was largely independent of the class of the prior and level of noise in the cue, suggesting that suboptimality in dealing with complex statistical features, such as bimodality, may be due to a problem of acquiring the priors rather than computing with them. We performed a factorial model comparison across a large set of Bayesian observer models to identify additional sources of noise and suboptimality. Our analysis rejects several models of stochastic behavior, including probability matching and sample-averaging strategies. Instead we show that subjects response variability was mainly driven by a combination of a noisy estimation of the parameters of the priors, and by variability in the decision process, which we represent as a noisy or stochastic posterior. '),
(86621, 2014, 'plos', 'A digital framework to build, visualize and analyze a gene expression atlas with cellular resolution in zebrafish early embryogenesis', 'Castro-González, Carlos|Luengo-Oroz, Miguel A|Duloquin, Louise|Savy, Thierry|Rizzi, Barbara|Desnoulez, Sophie|Doursat, René|Kergosien, Yannick L|Ledesma-Carbayo, María J|Bourgine, Paul|Peyriéras, Nadine|Santos, Andrés', 'Biomedical Image Technologies, ETSIT, Universidad Politécnica de Madrid, CEIMoncloa, Madrid, Spain, Research Center in Bioengineering, Biomaterials and Nanomedicine (CIBER-BBN), Madrid, Spain, Madrid-MIT M+Visión Consortium, Massachusetts Institute of Technology, Cambridge, Massachusetts, United States of America.|Biomedical Image Technologies, ETSIT, Universidad Politécnica de Madrid, CEIMoncloa, Madrid, Spain, Research Center in Bioengineering, Biomaterials and Nanomedicine (CIBER-BBN), Madrid, Spain.|MDAM UPR3294, Institut de Neurobiologie Alfred Fessard, CNRS, Gif-sur-Yvette, France, Institut des Systèmes Complexes, Paris, France, BioEmergences-IBiSA, Institut de Neurobiologie Alfred Fessard, CNRS, Gif-sur-Yvette, France.|MDAM UPR3294, Institut de Neurobiologie Alfred Fessard, CNRS, Gif-sur-Yvette, France, Institut des Systèmes Complexes, Paris, France, BioEmergences-IBiSA, Institut de Neurobiologie Alfred Fessard, CNRS, Gif-sur-Yvette, France.|MDAM UPR3294, Institut de Neurobiologie Alfred Fessard, CNRS, Gif-sur-Yvette, France, Institut des Systèmes Complexes, Paris, France, BioEmergences-IBiSA, Institut de Neurobiologie Alfred Fessard, CNRS, Gif-sur-Yvette, France.|MDAM UPR3294, Institut de Neurobiologie Alfred Fessard, CNRS, Gif-sur-Yvette, France, BioEmergences-IBiSA, Institut de Neurobiologie Alfred Fessard, CNRS, Gif-sur-Yvette, France.|Institut des Systèmes Complexes, Paris, France, BioEmergences-IBiSA, Institut de Neurobiologie Alfred Fessard, CNRS, Gif-sur-Yvette, France, School of Biomedical Engineering, Drexel University, Philadelphia, Pennsylvania, United States of America.|MDAM UPR3294, Institut de Neurobiologie Alfred Fessard, CNRS, Gif-sur-Yvette, France, BioEmergences-IBiSA, Institut de Neurobiologie Alfred Fessard, CNRS, Gif-sur-Yvette, France, LIMICS-INSERM UMR 1142, UFR SMBH, Université Paris 13, Bobigny, France.|Biomedical Image Technologies, ETSIT, Universidad Politécnica de Madrid, CEIMoncloa, Madrid, Spain, Research Center in Bioengineering, Biomaterials and Nanomedicine (CIBER-BBN), Madrid, Spain.|MDAM UPR3294, Institut de Neurobiologie Alfred Fessard, CNRS, Gif-sur-Yvette, France, Institut des Systèmes Complexes, Paris, France, BioEmergences-IBiSA, Institut de Neurobiologie Alfred Fessard, CNRS, Gif-sur-Yvette, France.|MDAM UPR3294, Institut de Neurobiologie Alfred Fessard, CNRS, Gif-sur-Yvette, France, Institut des Systèmes Complexes, Paris, France, BioEmergences-IBiSA, Institut de Neurobiologie Alfred Fessard, CNRS, Gif-sur-Yvette, France.|Biomedical Image Technologies, ETSIT, Universidad Politécnica de Madrid, CEIMoncloa, Madrid, Spain, Research Center in Bioengineering, Biomaterials and Nanomedicine (CIBER-BBN), Madrid, Spain.', 'Spain|Spain|France|France|France|France|France|France|Spain|France|France|Spain', 15, 'Animals|Computational Biology|Databases, Factual|Embryo, Nonmammalian|Gene Expression Profiling|Transcriptome|Zebrafish', 'Journal Article', '10.1371/journal.pcbi.1003670', '24945246', 'A gene expression atlas is an essential resource to quantify and understand the multiscale processes of embryogenesis in time and space. The automated reconstruction of a prototypic 4D atlas for vertebrate early embryos, using multicolor fluorescence in situ hybridization with nuclear counterstain, requires dedicated computational strategies. To this goal, we designed an original methodological framework implemented in a software tool called Match-IT. With only minimal human supervision, our system is able to gather gene expression patterns observed in different analyzed embryos with phenotypic variability and map them onto a series of common 3D templates over time, creating a 4D atlas. This framework was used to construct an atlas composed of 6 gene expression templates from a cohort of zebrafish early embryos spanning 6 developmental stages from 4 to 6.3 hpf (hours post fertilization). They included 53 specimens, 181,415 detected cell nuclei and the segmentation of 98 gene expression patterns observed in 3D for 9 different genes. In addition, an interactive visualization software, Atlas-IT, was developed to inspect, supervise and analyze the atlas. Match-IT and Atlas-IT, including user manuals, representative datasets and video tutorials, are publicly and freely available online. We also propose computational methods and tools for the quantitative assessment of the gene expression templates at the cellular scale, with the identification, visualization and analysis of coexpression patterns, synexpression groups and their dynamics through developmental stages. '),
(86622, 2014, 'plos', 'Behaviors and strategies of bacterial navigation in chemical and nonchemical gradients', 'Hu, Bo|Tu, Yuhai', 'IBM T. J. Watson Research Center, Yorktown Heights, New York, United States of America.|IBM T. J. Watson Research Center, Yorktown Heights, New York, United States of America.', 'United States|United States', 15, 'Bacterial Load|Chemotaxis|Computational Biology|Escherichia coli|Models, Biological|Temperature', 'Journal Article', '10.1371/journal.pcbi.1003672', '24945282', 'Navigation of cells to the optimal environmental condition is critical for their survival and growth. Escherichia coli cells, for example, can detect various chemicals and move up or down those chemical gradients (i.e., chemotaxis). Using the same signaling machinery, they can also sense other external factors such as pH and temperature and navigate from both sides toward some intermediate levels of those stimuli. This mode of precision sensing is more sophisticated than the (unidirectional) chemotaxis strategy and requires distinctive molecular mechanisms to encode and track the preferred external conditions. To systematically study these different bacterial taxis behaviors, we develop a continuum model that incorporates microscopic signaling events in single cells into macroscopic population dynamics. A simple theoretical result is obtained for the steady state cell distribution in general. In particular, we find the cell distribution is controlled by the intracellular sensory dynamics as well as the dependence of the cells speed on external factors. The model is verified by available experimental data in various taxis behaviors (including bacterial chemotaxis, pH taxis, and thermotaxis), and it also leads to predictions that can be tested by future experiments. Our analysis help reveal the key conditions/mechanisms for bacterial precision-sensing behaviors and directly connects the cellular taxis performances with the underlying molecular parameters. It provides a unified framework to study bacterial navigation in complex environments with chemical and non-chemical stimuli. '),
(86623, 2014, 'plos', 'An HIV epidemic model based on viral load dynamics: value in assessing empirical trends in HIV virulence and community viral load', 'Herbeck, Joshua T|Mittler, John E|Gottlieb, Geoffrey S|Mullins, James I', 'Department of Microbiology, University of Washington, Seattle, Washington, United States of America.|Department of Microbiology, University of Washington, Seattle, Washington, United States of America.|Department of Medicine, University of Washington, Seattle, Washington, United States of America.|Department of Microbiology, University of Washington, Seattle, Washington, United States of America, Department of Medicine, University of Washington, Seattle, Washington, United States of America.', 'United States|United States|United States|United States', 18, 'Anti-HIV Agents|Computational Biology|Epidemics|HIV Infections|HIV-1|Humans|Models, Biological|RNA, Viral|Viral Load|Virulence', 'Journal Article', '10.1371/journal.pcbi.1003673', '24945322', 'Trends in HIV virulence have been monitored since the start of the AIDS pandemic, as studying HIV virulence informs our understanding of HIV epidemiology and pathogenesis. Here, we model changes in HIV virulence as a strictly evolutionary process, using set point viral load (SPVL) as a proxy, to make inferences about empirical SPVL trends from longitudinal HIV cohorts. We develop an agent-based epidemic model based on HIV viral load dynamics. The model contains functions for viral load and transmission, SPVL and disease progression, viral load trajectories in multiple stages of infection, and the heritability of SPVL across transmissions. We find that HIV virulence evolves to an intermediate level that balances infectiousness with longer infected lifespans, resulting in an optimal SPVLxe2x88xbc4.75 log10 viral RNA copies/mL. Adaptive viral evolution may explain observed HIV virulence trends: our model produces SPVL trends with magnitudes that are broadly similar to empirical trends. With regard to variation among studies in empirical SPVL trends, results from our model suggest that variation may be explained by the specific epidemic context, e.g. the mean SPVL of the founding lineage or the age of the epidemic, or improvements in HIV screening and diagnosis that results in sampling biases. We also use our model to examine trends in community viral load, a population-level measure of HIV viral load that is thought to reflect a populations overall transmission potential. We find that community viral load evolves in association with SPVL, in the absence of prevention programs such as antiretroviral therapy, and that the mean community viral load is not necessarily a strong predictor of HIV incidence. '),
(86624, 2014, 'plos', 'Identifying crucial parameter correlations maintaining bursting activity', 'Doloc-Mihu, Anca|Calabrese, Ronald L', 'Department of Biology, Emory University, Atlanta, Georgia, United States of America.|Department of Biology, Emory University, Atlanta, Georgia, United States of America.', 'Georgia|Georgia', 12, 'Animals|Central Pattern Generators|Computational Biology|Heart|Interneurons|Leeches|Models, Neurological|Principal Component Analysis', 'Journal Article', '10.1371/journal.pcbi.1003678', '24945358', 'Recent experimental and computational studies suggest that linearly correlated sets of parameters (intrinsic and synaptic properties of neurons) allow central pattern-generating networks to produce and maintain their rhythmic activity regardless of changing internal and external conditions. To determine the role of correlated conductances in the robust maintenance of functional bursting activity, we used our existing database of half-center oscillator (HCO) model instances of the leech heartbeat CPG. From the database, we identified functional activity groups of burster (isolated neuron) and half-center oscillator model instances and realistic subgroups of each that showed burst characteristics (principally period and spike frequency) similar to the animal. To find linear correlations among the conductance parameters maintaining functional leech bursting activity, we applied Principal Component Analysis (PCA) to each of these four groups. PCA identified a set of three maximal conductances (leak current, [Formula: see text]Leak, a persistent K current, [Formula: see text]K2, and of a persistent Na+ current, [Formula: see text]P) that correlate linearly for the two groups of burster instances but not for the HCO groups. Visualizations of HCO instances in a reduced space suggested that there might be non-linear relationships between these parameters for these instances. Experimental studies have shown that period is a key attribute influenced by modulatory inputs and temperature variations in heart interneurons. Thus, we explored the sensitivity of period to changes in maximal conductances of [Formula: see text]Leak, [Formula: see text]K2, and [Formula: see text]P, and we found that for our realistic bursters the effect of these parameters on period could not be assessed because when varied individually bursting activity was not maintained. '),
(86625, 2014, 'plos', 'A quantitative comparison of anti-HIV gene therapy delivered to hematopoietic stem cells versus CD4+ T cells', 'Savkovic, Borislav|Nichols, James|Birkett, Donald|Applegate, Tanya|Ledger, Scott|Symonds, Geoff|Murray, John M', 'School of Mathematics and Statistics, University of New South Wales, Sydney, Australia.|School of Mathematics and Statistics, University of New South Wales, Sydney, Australia.|Department of Clinical Pharmacology, Flinders University, Adelaide, Australia.|Kirby Institute, University of New South Wales, Sydney, Australia.|Faculty of Medicine, University of New South Wales, Sydney, Australia.|St Vincents Centre for Applied Medical Research, Darlinghurst, New South Wales, Sydney, Australia, Calimmune Pty Ltd, Darlinghurst, New South Wales, Australia.|School of Mathematics and Statistics, University of New South Wales, Sydney, Australia.', 'Australia|Australia|Australia|Australia|Australia|Australia|Australia', 11, 'Antigens, CD34|CD4-Positive T-Lymphocytes|Computational Biology|Computer Simulation|Disease Progression|Gene Transfer Techniques|Genetic Therapy|HIV Fusion Inhibitors|HIV Infections|HIV-1|Hematopoietic Stem Cells|Humans|Models, Biological|Receptors, CCR5|Recombinant Fusion Proteins', 'Journal Article', '10.1371/journal.pcbi.1003681', '24945407', 'Gene therapy represents an alternative and promising anti-HIV modality to highly active antiretroviral therapy. It involves the introduction of a protective gene into a cell, thereby conferring protection against HIV. While clinical trials to date have delivered gene therapy to CD4+T cells or to CD34+ hematopoietic stem cells (HSC), the relative benefits of each of these two cellular targets have not been conclusively determined. In the present analysis, we investigated the relative merits of delivering a dual construct (CCR5 entry inhibitor + C46 fusion inhibitor) to either CD4+T cells or to CD34+ HSC. Using mathematical modelling, we determined the impact of each scenario in terms of total CD4+T cell counts over a 10 year period, and also in terms of inhibition of CCR5 and CXCR4 tropic virus. Our modelling determined that therapy delivery to CD34+ HSC generally resulted in better outcomes than delivery to CD4+T cells. An early one-off therapy delivery to CD34+ HSC, assuming that 20% of CD34+ HSC in the bone marrow were gene-modified (G+), resulted in total CD4+T cell counts xe2x89xa5 180 cells/ xc2xb5L in peripheral blood after 10 years. If the uninfected G+ CD4+T cells (in addition to exhibiting lower likelihood of becoming productively infected) also exhibited reduced levels of bystander apoptosis (92.5% reduction) over non gene-modified (G-) CD4+T cells, then total CD4+T cell counts of xe2x89xa5 350 cells/ xc2xb5L were observed after 10 years, even if initially only 10% of CD34+ HSC in the bone marrow received the protective gene. Taken together our results indicate that: 1.) therapy delivery to CD34+ HSC will result in better outcomes than delivery to CD4+T cells, and 2.) a greater impact of gene therapy will be observed if G+ CD4+T cells exhibit reduced levels of bystander apoptosis over G- CD4+T cells.'),
(86626, 2014, 'plos', 'International Society for Computational Biology Honors Dana Peer with Top Bioinformatics/Computational Biology Award for 2014', 'Fogg, Christiana N|Kovats, Diane E', 'Freelance Science Writer, Kensington, Maryland, United States of America.|International Society for Computational Biology, La Jolla, California, United States of America.', 'United States|United States', 0, 'Awards and Prizes|Boston|Computational Biology|Female|Humans|Israel|Societies', 'Journal Article', '10.1371/journal.pcbi.1003682', '24945496', '-'),
(86627, 2014, 'plos', 'Understanding the sub-cellular dynamics of silicon transportation and synthesis in diatoms using population-level data and computational optimization', 'Javaheri, Narjes|Dries, Roland|Kaandorp, Jaap', 'Section Computational Science, University of Amsterdam, Amsterdam, The Netherlands.|Section Computational Science, University of Amsterdam, Amsterdam, The Netherlands, FOM Institute AMOLF, Amsterdam, The Netherlands.|Section Computational Science, University of Amsterdam, Amsterdam, The Netherlands.', 'Netherlands|Netherlands|Netherlands', 4, 'Computational Biology|Diatoms|Intracellular Space|Models, Biological|Proteins|Silicic Acid|Silicon', 'Journal Article', '10.1371/journal.pcbi.1003687', '24945622', 'Controlled synthesis of silicon is a major challenge in nanotechnology and material science. Diatoms, the unicellular algae, are an inspiring example of silica biosynthesis, producing complex and delicate nano-structures. This happens in several cell compartments, including cytoplasm and silica deposition vesicle (SDV). Considering the low concentration of silicic acid in oceans, cells have developed silicon transporter proteins (SIT). Moreover, cells change the level of active SITs during one cell cycle, likely as a response to the level of external nutrients and internal deposition rates. Despite this topic being of fundamental interest, the intracellular dynamics of nutrients and cell regulation strategies remain poorly understood. One reason is the difficulties in measurements and manipulation of these mechanisms at such small scales, and even when possible, data often contain large errors. Therefore, using computational techniques seems inevitable. We have constructed a mathematical model for silicon dynamics in the diatom Thalassiosira pseudonana in four compartments: external environment, cytoplasm, SDV and deposited silica. The model builds on mass conservation and Michaelis-Menten kinetics as mass transport equations. In order to find the free parameters of the model from sparse, noisy experimental data, an optimization technique (global and local search), together with enzyme related penalty terms, has been applied. We have connected population-level data to individual-cell-level quantities including the effect of early division of non-synchronized cells. Our model is robust, proven by sensitivity and perturbation analysis, and predicts dynamics of intracellular nutrients and enzymes in different compartments. The model produces different uptake regimes, previously recognized as surge, externally-controlled and internally-controlled uptakes. Finally, we imposed a flux of SITs to the model and compared it with previous classical kinetics. The model introduced can be generalized in order to analyze different biomineralizing organisms and to test different chemical pathways only by switching the system of mass transport equations. '),
(86628, 2014, 'plos', 'Historical pedigree reconstruction from extant populations using PArtitioning of RElatives (PREPARE)', 'Shem-Tov, Doron|Halperin, Eran', 'The Balvatnic School of Computer Science, Tel-Aviv University, Tel-Aviv, Israel.|The Balvatnic School of Computer Science, Tel-Aviv University, Tel-Aviv, Israel, International Computer Science Institute, Berkeley, California, United States of America, Molecular Microbiology and Biotechnology Department, Tel-Aviv University, Tel-Aviv, Israel.', 'Israel|Israel', 2, 'Algorithms|Computational Biology|Computer Graphics|Computer Simulation|Female|Genetics, Population|Genotype|Humans|Likelihood Functions|Male|Pedigree', 'Journal Article', '10.1371/journal.pcbi.1003610', '24945698', 'Recent technological improvements in the field of genetic data extraction give rise to the possibility of reconstructing the historical pedigrees of entire populations from the genotypes of individuals living today. Current methods are still not practical for real data scenarios as they have limited accuracy and assume unrealistic assumptions of monogamy and synchronized generations. In order to address these issues, we develop a new method for pedigree reconstruction, [Formula: see text], which is based on formulations of the pedigree reconstruction problem as variants of graph coloring. The new formulation allows us to consider features that were overlooked by previous methods, resulting in a reconstruction of up to 5 generations back in time, with an order of magnitude improvement of false-negatives rates over the state of the art, while keeping a lower level of false positive rates. We demonstrate the accuracy of [Formula: see text] compared to previous approaches using simulation studies over a range of population sizes, including inbred and outbred populations, monogamous and polygamous mating patterns, as well as synchronous and asynchronous mating. '),
(86629, 2014, 'plos', 'Pierced Lasso Bundles are a new class of knot-like motifs', 'Haglund, Ellinor|Sulkowska, Joanna I|Noel, Jeffrey K|Lammert, Heiko|Onuchic, José N|Jennings, Patricia A', 'Center for Theoretical Biological Physics (CTBP) and Department of Physics, University of California at San Diego (UCSD), La Jolla, California, United States of America, Center for Theoretical Biological Physics (CTBP) and Departments of Physics and Astronomy, Chemistry and Biochemistry and Cell Biology, Rice University, Houston, Texas, United States of America.|Laboratory of Theory of Biopolymers, University of Warsaw, Warsaw, Poland.|Center for Theoretical Biological Physics (CTBP) and Departments of Physics and Astronomy, Chemistry and Biochemistry and Cell Biology, Rice University, Houston, Texas, United States of America.|Center for Theoretical Biological Physics (CTBP) and Departments of Physics and Astronomy, Chemistry and Biochemistry and Cell Biology, Rice University, Houston, Texas, United States of America.|Center for Theoretical Biological Physics (CTBP) and Departments of Physics and Astronomy, Chemistry and Biochemistry and Cell Biology, Rice University, Houston, Texas, United States of America.|Departments of Chemistry and Biochemistry, University of California at San Diego (UCSD), La Jolla, California, United States of America.', 'United States|Poland|United States|United States|United States|United States', 26, 'Amino Acid Motifs|Animals|Computational Biology|Computer Simulation|Cysteine|Cytokines|Databases, Protein|Drug Design|Humans|Leptin|Models, Molecular|Molecular Dynamics Simulation|Multiprotein Complexes|Oxidation-Reduction|Protein Folding|Protein Structure, Secondary|Protein Structure, Tertiary|Proteins|Receptors, Leptin|Structural Homology, Protein', 'Journal Article', '10.1371/journal.pcbi.1003613', '24945798', 'A four-helix bundle is a well-characterized motif often used as a target for designed pharmaceutical therapeutics and nutritional supplements. Recently, we discovered a new structural complexity within this motif created by a disulphide bridge in the long-chain helical bundle cytokine leptin. When oxidized, leptin contains a disulphide bridge creating a covalent-loop through which part of the polypeptide chain is threaded (as seen in knotted proteins). We explored whether other proteins contain a similar intriguing knot-like structure as in leptin and discovered 11 structurally homologous proteins in the PDB. We call this new helical family class the Pierced Lasso Bundle (PLB) and the knot-like threaded structural motif a Pierced Lasso (PL). In the current study, we use structure-based simulation to investigate the threading/folding mechanisms for all the PLBs along with three unthreaded homologs as the covalent loop (or lasso) in leptin is important in folding dynamics and activity. We find that the presence of a small covalent loop leads to a mechanism where structural elements slipknot to thread through the covalent loop. Larger loops use a piercing mechanism where the free terminal plugs through the covalent loop. Remarkably, the position of the loop as well as its size influences the native state dynamics, which can impact receptor binding and biological activity. This previously unrecognized complexity of knot-like proteins within the helical bundle family comprises a completely new class within the knot family, and the hidden complexity we unraveled in the PLBs is expected to be found in other protein structures outside the four-helix bundles. The insights gained here provide critical new elements for future investigation of this emerging class of proteins, where function and the energetic landscape can be controlled by hidden topology, and should be take into account in ab initio predictions of newly identified protein targets. '),
(86630, 2014, 'plos', 'Quantification of HTLV-1 clonality and TCR diversity', 'Laydon, Daniel J|Melamed, Anat|Sim, Aaron|Gillet, Nicolas A|Sim, Kathleen|Darko, Sam|Kroll, J Simon|Douek, Daniel C|Price, David A|Bangham, Charles R M|Asquith, Becca', 'Section of Immunology, Wright-Fleming Institute, Imperial College School of Medicine, London, United Kingdom.|Section of Immunology, Wright-Fleming Institute, Imperial College School of Medicine, London, United Kingdom.|Centre for Integrative Systems Biology and Bioinformatics, South Kensington Campus, Imperial College, London, United Kingdom.|Section of Immunology, Wright-Fleming Institute, Imperial College School of Medicine, London, United Kingdom, Department of Molecular and Cellular Epigenetics, University of Liège, Liège, Belgium.|Section of Paediatrics, Wright-Fleming Institute, Imperial College School of Medicine, London, United Kingdom.|Vaccine Research Center, National Institutes of Health, Bethesda, Maryland, United States of America.|Section of Paediatrics, Wright-Fleming Institute, Imperial College School of Medicine, London, United Kingdom.|Vaccine Research Center, National Institutes of Health, Bethesda, Maryland, United States of America.|Vaccine Research Center, National Institutes of Health, Bethesda, Maryland, United States of America, Institute of Infection and Immunity, Cardiff University School of Medicine, Cardiff, Wales, United Kingdom.|Section of Immunology, Wright-Fleming Institute, Imperial College School of Medicine, London, United Kingdom.|Section of Immunology, Wright-Fleming Institute, Imperial College School of Medicine, London, United Kingdom.', 'United Kingdom|United Kingdom|United Kingdom|Belgium|United Kingdom|United States|United Kingdom|Uni', 50, 'Algorithms|Computational Biology|Databases, Genetic|Feces|Genetic Variation|HTLV-I Infections|Human T-lymphotropic virus 1|Humans|Infant|Microbiota|Models, Genetic|Receptors, Antigen, T-Cell|Seawater|Statistics, Nonparametric', 'Journal Article', '10.1371/journal.pcbi.1003646', '24945836', 'Estimation of immunological and microbiological diversity is vital to our understanding of infection and the immune response. For instance, what is the diversity of the T cell repertoire? These questions are partially addressed by high-throughput sequencing techniques that enable identification of immunological and microbiological species in a sample. Estimators of the number of unseen species are needed to estimate population diversity from sample diversity. Here we test five widely used non-parametric estimators, and develop and validate a novel method, DivE, to estimate species richness and distribution. We used three independent datasets: (i) viral populations from subjects infected with human T-lymphotropic virus type 1, (ii) T cell antigen receptor clonotype repertoires, and (iii) microbial data from infant faecal samples. When applied to datasets with rarefaction curves that did not plateau, existing estimators systematically increased with sample size. In contrast, DivE consistently and accurately estimated diversity for all datasets. We identify conditions that limit the application of DivE. We also show that DivE can be used to accurately estimate the underlying population frequency distribution. We have developed a novel method that is significantly more accurate than commonly used biodiversity estimators in microbiological and immunological populations. '),
(86631, 2014, 'plos', 'The effects of theta precession on spatial learning and simplicial complex dynamics in a topological model of the hippocampal spatial map', 'Arai, Mamiko|Brandt, Vicky|Dabaghian, Yuri', 'The Jan and Dan Duncan Neurological Research Institute, Baylor College of Medicine, Houston, Texas, United States of America.|The Jan and Dan Duncan Neurological Research Institute, Baylor College of Medicine, Houston, Texas, United States of America.|The Jan and Dan Duncan Neurological Research Institute, Baylor College of Medicine, Houston, Texas, United States of America, Department of Computational and Applied Mathematics, Rice University, Houston, Texas, United States of America.', 'United States|United States|United States', 22, 'Animals|Behavior, Animal|Computational Biology|Connectome|Hippocampus|Learning|Models, Neurological|Models, Psychological|Rats|Spatial Behavior|Theta Rhythm', 'Journal Article', '10.1371/journal.pcbi.1003651', '24945927', 'Learning arises through the activity of large ensembles of cells, yet most of the data neuroscientists accumulate is at the level of individual neurons, we need models that can bridge this gap. We have taken spatial learning as our starting point, computationally modeling the activity of place cells using methods derived from algebraic topology, especially persistent homology. We previously showed that ensembles of hundreds of place cells could accurately encode topological information about different environments (learn the space) within certain values of place cell firing rate, place field size, and cell population, we called this parameter space the learning region. Here we advance the model both technically and conceptually. To make the model more physiological, we explored the effects of theta precession on spatial learning in our virtual ensembles. Theta precession, which is believed to influence learning and memory, did in fact enhance learning in our model, increasing both speed and the size of the learning region. Interestingly, theta precession also increased the number of spurious loops during simplicial complex formation. We next explored how downstream readout neurons might define co-firing by grouping together cells within different windows of time and thereby capturing different degrees of temporal overlap between spike trains. Our models optimum coactivity window correlates well with experimental data, ranging from xe2x88xbc150-200 msec. We further studied the relationship between learning time, window width, and theta precession. Our results validate our topological model for spatial learning and open new avenues for connecting data at the level of individual neurons to behavioral outcomes at the neuronal ensemble level. Finally, we analyzed the dynamics of simplicial complex formation and loop transience to propose that the simplicial complex provides a useful working description of the spatial learning process. ');
INSERT INTO `papers` (`id`, `ano`, `journal`, `titulo`, `autores`, `afiliacao`, `pais`, `citacoes`, `palavra_chave`, `categorias`, `doi`, `pubmed`, `abstract`) VALUES
(86632, 2014, 'plos', 'An expanded Notch-Delta model exhibiting long-range patterning and incorporating MicroRNA regulation', 'Chen, Jerry S|Gumbayan, Abygail M|Zeller, Robert W|Mahaffy, Joseph M', 'Computational Science Research Center, San Diego State University, San Diego, California, United States of America, Department of Biology, San Diego State University, San Diego, California, United States of America.|Department of Biology, San Diego State University, San Diego, California, United States of America.|Computational Science Research Center, San Diego State University, San Diego, California, United States of America, Department of Biology, San Diego State University, San Diego, California, United States of America.|Computational Science Research Center, San Diego State University, San Diego, California, United States of America, Department of Mathematics and Statistics, San Diego State University, San Diego, California, United States of America.', 'United States|United States|United States|United States', 11, 'Animals|Animals, Genetically Modified|Body Patterning|Cell Communication|Ciona intestinalis|Computational Biology|Computer Simulation|Gene Expression Regulation, Developmental|Intracellular Signaling Peptides and Proteins|Membrane Proteins|MicroRNAs|Models, Neurological|Monte Carlo Method|Nervous System|Receptors, Notch|Sensory Receptor Cells|Signal Transduction', 'Journal Article', '10.1371/journal.pcbi.1003655', '24945987', 'Notch-Delta signaling is a fundamental cell-cell communication mechanism that governs the differentiation of many cell types. Most existing mathematical models of Notch-Delta signaling are based on a feedback loop between Notch and Delta leading to lateral inhibition of neighboring cells. These models result in a checkerboard spatial pattern whereby adjacent cells express opposing levels of Notch and Delta, leading to alternate cell fates. However, a growing body of biological evidence suggests that Notch-Delta signaling produces other patterns that are not checkerboard, and therefore a new model is needed. Here, we present an expanded Notch-Delta model that builds upon previous models, adding a local Notch activity gradient, which affects long-range patterning, and the activity of a regulatory microRNA. This model is motivated by our experiments in the ascidian Ciona intestinalis showing that the peripheral sensory neurons, whose specification is in part regulated by the coordinate activity of Notch-Delta signaling and the microRNA miR-124, exhibit a sparse spatial pattern whereby consecutive neurons may be spaced over a dozen cells apart. We perform rigorous stability and bifurcation analyses, and demonstrate that our model is able to accurately explain and reproduce the neuronal pattern in Ciona. Using Monte Carlo simulations of our model along with miR-124 transgene over-expression assays, we demonstrate that the activity of miR-124 can be incorporated into the Notch decay rate parameter of our model. Finally, we motivate the general applicability of our model to Notch-Delta signaling in other animals by providing evidence that microRNAs regulate Notch-Delta signaling in analogous cell types in other organisms, and by discussing evidence in other organisms of sparse spatial patterns in tissues where Notch-Delta signaling is active. '),
(86633, 2014, 'plos', 'Variability of metabolite levels is linked to differential metabolic pathways in Arabidopsiss responses to abiotic stresses', 'Töpfer, Nadine|Scossa, Federico|Fernie, Alisdair|Nikoloski, Zoran', 'Systems Biology and Mathematical Modeling Group, Max Planck Institute of Molecular Plant Physiology, Potsdam, Germany.|Central Metabolism Group, Max Planck Institute of Molecular Plant Physiology, Potsdam, Germany, Consiglio per la Ricerca e la Sperimentazione in Agricoltura, Centro di ricerca per lOrticoltura, Pontecagnano (Salerno), Italy.|Central Metabolism Group, Max Planck Institute of Molecular Plant Physiology, Potsdam, Germany.|Systems Biology and Mathematical Modeling Group, Max Planck Institute of Molecular Plant Physiology, Potsdam, Germany.', 'Germany|Germany|Germany|Germany', 13, 'Arabidopsis|Metabolic Flux Analysis|Metabolic Networks and Pathways|Metabolomics|Models, Biological|Stress, Physiological', 'Journal Article', '10.1371/journal.pcbi.1003656', '24946036', 'Constraint-based approaches have been used for integrating data in large-scale metabolic networks to obtain insights into metabolism of various organisms. Due to the underlying steady-state assumption, these approaches are usually not suited for making predictions about metabolite levels. Here, we ask whether we can make inferences about the variability of metabolite levels from a constraint-based analysis based on the integration of transcriptomics data. To this end, we analyze time-resolved transcriptomics and metabolomics data from Arabidopsis thaliana under a set of eight different light and temperature conditions. In a previous study, the gene expression data have already been integrated in a genome-scale metabolic network to predict pathways, termed modulators and sustainers, which are differentially regulated with respect to a biochemically meaningful data-driven null model. Here, we present a follow-up analysis which bridges the gap between flux- and metabolite-centric methods. One of our main findings demonstrates that under certain environmental conditions, the levels of metabolites acting as substrates in modulators or sustainers show significantly lower temporal variations with respect to the remaining measured metabolites. This observation is discussed within the context of a systems-view of plasticity and robustness of metabolite contents and pathway fluxes. Our study paves the way for investigating the existence of similar principles in other species for which both genome-scale networks and high-throughput metabolomics data of high quality are becoming increasingly available. '),
(86634, 2014, 'plos', 'Integrating diverse datasets improves developmental enhancer prediction', 'Erwin, Genevieve D|Oksenberg, Nir|Truty, Rebecca M|Kostka, Dennis|Murphy, Karl K|Ahituv, Nadav|Pollard, Katherine S|Capra, John A', 'Gladstone Institute of Cardiovascular Disease, San Francisco, California, United States of America, Institute for Human Genetics, University of California San Francisco, San Francisco, California, United States of America.|Institute for Human Genetics, University of California San Francisco, San Francisco, California, United States of America, Department of Bioengineering and Therapeutic Sciences, University of California San Francisco, San Francisco, California, United States of America.|Gladstone Institute of Cardiovascular Disease, San Francisco, California, United States of America.|Department of Developmental Biology and Department of Computational and Systems Biology, University of Pittsburgh, Pittsburgh, Pennsylvania, United States of America.|Institute for Human Genetics, University of California San Francisco, San Francisco, California, United States of America, Department of Bioengineering and Therapeutic Sciences, University of California San Francisco, San Francisco, California, United States of America.|Institute for Human Genetics, University of California San Francisco, San Francisco, California, United States of America, Department of Bioengineering and Therapeutic Sciences, University of California San Francisco, San Francisco, California, United States of America.|Gladstone Institute of Cardiovascular Disease, San Francisco, California, United States of America, Institute for Human Genetics, University of California San Francisco, San Francisco, California, United States of America, Department of Epidemiology and Biostatistics, University of California San Francisco, San Francisco, California, United States of America.|Center for Human Genetics Research and Department of Biomedical Informatics, Vanderbilt University, Nashville, Tennessee, United States of America.', 'United States|United States|United States|United States|United States|United States|United States|Un', 71, 'Animals|Artificial Intelligence|Databases, Genetic|Enhancer Elements, Genetic|Genome-Wide Association Study|Genomics|Histones|Humans|Mice|Mice, Transgenic|Models, Statistical|Organ Specificity', 'Journal Article', '10.1371/journal.pcbi.1003677', '24967590', 'Gene-regulatory enhancers have been identified using various approaches, including evolutionary conservation, regulatory protein binding, chromatin modifications, and DNA sequence motifs. To integrate these different approaches, we developed EnhancerFinder, a two-step method for distinguishing developmental enhancers from the genomic background and then predicting their tissue specificity. EnhancerFinder uses a multiple kernel learning approach to integrate DNA sequence motifs, evolutionary patterns, and diverse functional genomics datasets from a variety of cell types. In contrast with prediction approaches that define enhancers based on histone marks or p300 sites from a single cell line, we trained EnhancerFinder on hundreds of experimentally verified human developmental enhancers from the VISTA Enhancer Browser. We comprehensively evaluated EnhancerFinder using cross validation and found that our integrative method improves the identification of enhancers over approaches that consider a single type of data, such as sequence motifs, evolutionary conservation, or the binding of enhancer-associated proteins. We find that VISTA enhancers active in embryonic heart are easier to identify than enhancers active in several other embryonic tissues, likely due to their uniquely high GC content. We applied EnhancerFinder to the entire human genome and predicted 84,301 developmental enhancers and their tissue specificity. These predictions provide specific functional annotations for large amounts of human non-coding DNA, and are significantly enriched near genes with annotated roles in their predicted tissues and lead SNPs from genome-wide association studies. We demonstrate the utility of EnhancerFinder predictions through in vivo validation of novel embryonic gene regulatory enhancers from three developmental transcription factor loci. Our genome-wide developmental enhancer predictions are freely available as a UCSC Genome Browser track, which we hope will enable researchers to further investigate questions in developmental biology. '),
(86635, 2014, 'plos', 'Large-scale genomic analysis suggests a neutral punctuated dynamics of transposable elements in bacterial genomes', 'Iranzo, Jaime|Gómez, Manuel J|López de Saro, Francisco J|Manrubia, Susanna', 'Centro de Astrobiología (CAB), INTA-CSIC, Torrejón de Ardoz, Madrid, Spain.|Centro de Astrobiología (CAB), INTA-CSIC, Torrejón de Ardoz, Madrid, Spain.|Centro de Astrobiología (CAB), INTA-CSIC, Torrejón de Ardoz, Madrid, Spain.|Centro de Astrobiología (CAB), INTA-CSIC, Torrejón de Ardoz, Madrid, Spain, Grupo Interdisciplinar de Sistemas Complejos (GISC), Madrid, Spain.', 'Spain|Spain|Spain|Spain', 20, 'DNA Transposable Elements|Evolution, Molecular|Gene Duplication|Gene Transfer, Horizontal|Genome, Bacterial|Genomics|Models, Genetic', 'Journal Article', '10.1371/journal.pcbi.1003680', '24967627', 'Insertion sequences (IS) are the simplest and most abundant form of transposable DNA found in bacterial genomes. When present in multiple copies, it is thought that they can promote genomic plasticity and genetic exchange, thus being a major force of evolutionary change. The main processes that determine IS content in genomes are, though, a matter of debate. In this work, we take advantage of the large amount of genomic data currently available and study the abundance distributions of 33 IS families in 1811 bacterial chromosomes. This allows us to test simple models of IS dynamics and estimate their key parameters by means of a maximum likelihood approach. We evaluate the roles played by duplication, lateral gene transfer, deletion and purifying selection. We find that the observed IS abundances are compatible with a neutral scenario where IS proliferation is controlled by deletions instead of purifying selection. Even if there may be some cases driven by selection, neutral behavior dominates over large evolutionary scales. According to this view, IS and hosts tend to coexist in a dynamic equilibrium state for most of the time. Our approach also allows for a detection of recent IS expansions, and supports the hypothesis that rapid expansions constitute transient events-punctuations-during which the state of coexistence of IS and host becomes perturbated. '),
(86636, 2014, 'plos', 'Optimal reaction coordinate as a biomarker for the dynamics of recovery from kidney transplant', 'Krivov, Sergei V|Fenton, Hayley|Goldsmith, Paul J|Prasad, Rajendra K|Fisher, Julie|Paci, Emanuele', 'School of Molecular and Cellular Biology, University of Leeds, Leeds, United Kingdom, Astbury Centre for Structural Molecular Biology, University of Leeds, Leeds, United Kingdom.|School of Chemistry, University of Leeds, Leeds, United Kingdom.|Hepatopancreatobiliary Transplant Unit, St. Jamess University Hospital, Leeds, United Kingdom.|Hepatopancreatobiliary Transplant Unit, St. Jamess University Hospital, Leeds, United Kingdom.|Astbury Centre for Structural Molecular Biology, University of Leeds, Leeds, United Kingdom, School of Chemistry, University of Leeds, Leeds, United Kingdom.|School of Molecular and Cellular Biology, University of Leeds, Leeds, United Kingdom, Astbury Centre for Structural Molecular Biology, University of Leeds, Leeds, United Kingdom.', 'United Kingdom|United Kingdom|United Kingdom|United Kingdom|United Kingdom|United Kingdom', 8, 'Biomarkers|Computational Biology|Humans|Kidney|Kidney Transplantation|Magnetic Resonance Spectroscopy|Models, Biological|Recovery of Function', 'Journal Article', '10.1371/journal.pcbi.1003685', '24967678', 'The evolution of disease or the progress of recovery of a patient is a complex process, which depends on many factors. A quantitative description of this process in real-time by a single, clinically measurable parameter (biomarker) would be helpful for early, informed and targeted treatment. Organ transplantation is an eminent case in which the evolution of the post-operative clinical condition is highly dependent on the individual case. The quality of management and monitoring of patients after kidney transplant often determines the long-term outcome of the graft. Using NMR spectra of blood samples, taken at different time points from just before to a week after surgery, we have shown that a biomarker can be found that quantitatively monitors the evolution of a clinical condition. We demonstrate that this is possible if the dynamics of the process is considered explicitly: the biomarker is defined and determined as an optimal reaction coordinate that provides a quantitatively accurate description of the stochastic recovery dynamics. The method, originally developed for the analysis of protein folding dynamics, is rigorous, robust and general, i.e., it can be applied in principle to analyze any type of biological dynamics. Such predictive biomarkers will promote improvement of long-term graft survival after renal transplantation, and have potentially unlimited applications as diagnostic tools. '),
(86637, 2014, 'plos', 'Yeast mating and image-based quantification of spatial pattern formation', 'Diener, Christian|Schreiber, Gabriele|Giese, Wolfgang|del Rio, Gabriel|Schrxc3xb6der, Andreas|Klipp, Edda', 'Theoretische Biophysik, Humboldt-Universitxc3xa4t zu Berlin, Berlin, Germany, Instituto de Fisiologxc3xada Celular, Universidad Nacional Autxc3xb3noma de Mxc3xa9xico, Circuito Exterior S/N Ciudad Universitaria, Mxc3xa9xico D.F, Mxc3xa9xico.|Theoretische Biophysik, Humboldt-Universitxc3xa4t zu Berlin, Berlin, Germany.|Theoretische Biophysik, Humboldt-Universitxc3xa4t zu Berlin, Berlin, Germany.|Instituto de Fisiologxc3xada Celular, Universidad Nacional Autxc3xb3noma de Mxc3xa9xico, Circuito Exterior S/N Ciudad Universitaria, Mxc3xa9xico D.F, Mxc3xa9xico.|Institut fxc3xbcr Mathematik, Humboldt-Universitxc3xa4t zu Berlin, Berlin, Germany.|Theoretische Biophysik, Humboldt-Universitxc3xa4t zu Berlin, Berlin, Germany.', 'Germany|Germany|Germany|-|Germany|Germany', 13, 'Aspartic Acid Endopeptidases|Image Processing, Computer-Assisted|Microscopy, Confocal|Mutation|Pheromones|Saccharomyces cerevisiae|Saccharomyces cerevisiae Proteins', 'Journal Article', '10.1371/journal.pcbi.1003690', '24967739', 'Communication between cells is a ubiquitous feature of cell populations and is frequently realized by secretion and detection of signaling molecules. Direct visualization of the resulting complex gradients between secreting and receiving cells is often impossible due to the small size of diffusing molecules and because such visualization requires experimental perturbations such as attachment of fluorescent markers, which can change diffusion properties. We designed a method to estimate such extracellular concentration profiles in vivo by using spatiotemporal mathematical models derived from microscopic analysis. This method is applied to populations of thousands of haploid yeast cells during mating in order to quantify the extracellular distributions of the pheromone xcexb1-factor and the activity of the aspartyl protease Bar1. We demonstrate that Bar1 limits the range of the extracellular pheromone signal and is critical in establishing xcexb1-factor concentration gradients, which is crucial for effective mating. Moreover, haploid populations of wild type yeast cells, but not BAR1 deletion strains, create a pheromone pattern in which cells differentially grow and mate, with low pheromone regions where cells continue to bud and regions with higher pheromone levels and gradients where cells conjugate to form diploids. However, this effect seems to be exclusive to high-density cultures. Our results show a new role of Bar1 protease regulating the pheromone distribution within larger populations and not only locally inside an ascus or among few cells. As a consequence, wild type populations have not only higher mating efficiency, but also higher growth rates than mixed MATa bar1xcex94/MATxcexb1 cultures. We provide an explanation of how a rapidly diffusing molecule can be exploited by cells to provide spatial information that divides the population into different transcriptional programs and phenotypes. '),
(86638, 2014, 'plos', 'Mechanistic, mathematical model to predict the dynamics of tissue genesis in bone defects via mechanical feedback and mediation of biochemical factors', 'Moore, Shannon R|Saidel, Gerald M|Knothe, Ulf|Knothe Tate, Melissa L', 'Department of Biomedical Engineering, Case Western Reserve University, Cleveland, Ohio, United States of America.|Department of Biomedical Engineering, Case Western Reserve University, Cleveland, Ohio, United States of America.|Department of Orthopaedic Surgery, Cleveland Clinic, Cleveland, Ohio, United States of America.|Department of Biomedical Engineering, Case Western Reserve University, Cleveland, Ohio, United States of America, Department of Mechanical & Aerospace Engineering, Case Western Reserve University, Cleveland, Ohio, United States of America, Graduate School of Biomedical Engineering, University of New South Wales, Sydney, Australia.', 'United States|United States|United States|Australia', 15, 'Animals|Biomechanical Phenomena|Bone Morphogenetic Proteins|Bone Nails|Bone Regeneration|Chondrogenesis|Computational Biology|Computer Simulation|Feedback, Physiological|Finite Element Analysis|Fracture Healing|Humans|Mesenchymal Stem Cells|Models, Animal|Models, Biological|Osteogenesis|Periosteum|Sheep', 'Journal Article', '10.1371/journal.pcbi.1003604', '24967742', 'The link between mechanics and biology in the generation and the adaptation of bone has been well studied in context of skeletal development and fracture healing. Yet, the prediction of tissue genesis within - and the spatiotemporal healing of - postnatal defects, necessitates a quantitative evaluation of mechano-biological interactions using experimental and clinical parameters. To address this current gap in knowledge, this study aims to develop a mechanistic mathematical model of tissue genesis using bone morphogenetic protein (BMP) to represent of a class of factors that may coordinate bone healing. Specifically, we developed a mechanistic, mathematical model to predict the dynamics of tissue genesis by periosteal progenitor cells within a long bone defect surrounded by periosteum and stabilized via an intramedullary nail. The emergent material properties and mechanical environment associated with nascent tissue genesis influence the strain stimulus sensed by progenitor cells within the periosteum. Using a mechanical finite element model, periosteal surface strains are predicted as a function of emergent, nascent tissue properties. Strains are then input to a mechanistic mathematical model, where mechanical regulation of BMP-2 production mediates rates of cellular proliferation, differentiation and tissue production, to predict healing outcomes. A parametric approach enables the spatial and temporal prediction of endochondral tissue regeneration, assessed as areas of cartilage and mineralized bone, as functions of radial distance from the periosteum and time. Comparing model results to histological outcomes from two previous studies of periosteum-mediated bone regeneration in a common ovine model, it was shown that mechanistic models incorporating mechanical feedback successfully predict patterns (spatial) and trends (temporal) of bone tissue regeneration. The novel model framework presented here integrates a mechanistic feedback system based on the mechanosensitivity of periosteal progenitor cells, which allows for modeling and prediction of tissue regeneration on multiple length and time scales. Through combination of computational, physical and engineering science approaches, the model platform provides a means to test new hypotheses in silico and to elucidate conditions conducive to endogenous tissue genesis. Next generation models will serve to unravel intrinsic differences in bone genesis by endochondral and intramembranous mechanisms. '),
(86639, 2014, 'plos', 'Genome-wide prediction and validation of peptides that bind human prosurvival Bcl-2 proteins', 'DeBartolo, Joe|Taipale, Mikko|Keating, Amy E', 'MIT Department of Biology, Cambridge, Massachusetts, United States of America.|MIT Department of Biology, Cambridge, Massachusetts, United States of America.|MIT Department of Biology, Cambridge, Massachusetts, United States of America.', 'United States|United States|United States', 0, 'Amino Acid Sequence|Genomics|Humans|Models, Molecular|Molecular Sequence Data|Peptides|Proto-Oncogene Proteins c-bcl-2|Reproducibility of Results|Sequence Alignment', 'Journal Article', '10.1371/journal.pcbi.1003693', '24967846', 'Programmed cell death is regulated by interactions between pro-apoptotic and prosurvival members of the Bcl-2 family. Pro-apoptotic family members contain a weakly conserved BH3 motif that can adopt an alpha-helical structure and bind to a groove on prosurvival partners Bcl-xL, Bcl-w, Bcl-2, Mcl-1 and Bfl-1. Peptides corresponding to roughly 13 reported BH3 motifs have been verified to bind in this manner. Due to their short lengths and low sequence conservation, BH3 motifs are not detected using standard sequence-based bioinformatics approaches. Thus, it is possible that many additional proteins harbor BH3-like sequences that can mediate interactions with the Bcl-2 family. In this work, we used structure-based and data-based Bcl-2 interaction models to find new BH3-like peptides in the human proteome. We used peptide SPOT arrays to test candidate peptides for interaction with one or more of the prosurvival proteins Bcl-xL, Bcl-w, Bcl-2, Mcl-1 and Bfl-1. For the 36 most promising array candidates, we quantified binding to all five human receptors using direct and competition binding assays in solution. All 36 peptides showed evidence of interaction with at least one prosurvival protein, and 22 peptides bound at least one prosurvival protein with a dissociation constant between 1 and 500 nM, many peptides had specificity profiles not previously observed. We also screened the full-length parent proteins of a subset of array-tested peptides for binding to Bcl-xL and Mcl-1. Finally, we used the peptide binding data, in conjunction with previously reported interactions, to assess the affinity and specificity prediction performance of different models. '),
(86640, 2014, 'plos', 'Unsupervised learning of cone spectral classes from natural images', 'Benson, Noah C|Manning, Jeremy R|Brainard, David H', 'Department of Psychology, University of Pennsylvania, Philadelphia, Pennsylvania, United States of America, Department of Neurology, University of Pennsylvania, Philadelphia, Pennsylvania, United States of America.|Department of Psychology, University of Pennsylvania, Philadelphia, Pennsylvania, United States of America.|Department of Psychology, University of Pennsylvania, Philadelphia, Pennsylvania, United States of America.', 'United States|United States|United States', 10, 'Algorithms|Animals|Biological Evolution|Color Perception|Color Vision|Computational Biology|Computer Simulation|Humans|Learning|Models, Biological|Primates|Retinal Cone Photoreceptor Cells', 'Journal Article', '10.1371/journal.pcbi.1003652', '24967877', 'The first step in the evolution of primate trichromatic color vision was the expression of a third cone class not present in ancestral mammals. This observation motivates a fundamental question about the evolution of any sensory system: how is it possible to detect and exploit the presence of a novel sensory class? We explore this question in the context of primate color vision. We present an unsupervised learning algorithm capable of both detecting the number of spectral cone classes in a retinal mosaic and learning the class of each cone using the inter-cone correlations obtained in response to natural image input. The algorithms ability to classify cones is in broad agreement with experimental evidence about functional color vision for a wide range of mosaic parameters, including those characterizing dichromacy, typical trichromacy, anomalous trichromacy, and possible tetrachromacy. '),
(86641, 2014, 'plos', 'Limits of feedback control in bacterial chemotaxis', 'Dufour, Yann S|Fu, Xiongfei|Hernandez-Nunez, Luis|Emonet, Thierry', 'Department of Molecular, Cellular, and Developmental Biology, Yale University, New Haven, Connecticut, United States of America.|Department of Molecular, Cellular, and Developmental Biology, Yale University, New Haven, Connecticut, United States of America.|Department of Molecular, Cellular, and Developmental Biology, Yale University, New Haven, Connecticut, United States of America.|Department of 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.', 'United States|United States|United States|United States', 0, 'Bacterial Proteins|Chemotaxis|Computational Biology|Escherichia coli|Feedback, Physiological|Membrane Proteins|Methyl-Accepting Chemotaxis Proteins|Models, Biological|Phenotype|Signal Transduction', 'Journal Article', '10.1371/journal.pcbi.1003694', '24967937', 'Inputs to signaling pathways can have complex statistics that depend on the environment and on the behavioral response to previous stimuli. Such behavioral feedback is particularly important in navigation. Successful navigation relies on proper coupling between sensors, which gather information during motion, and actuators, which control behavior. Because reorientation conditions future inputs, behavioral feedback can place sensors and actuators in an operational regime different from the resting state. How then can organisms maintain proper information transfer through the pathway while navigating diverse environments? In bacterial chemotaxis, robust performance is often attributed to the zero integral feedback control of the sensor, which guarantees that activity returns to resting state when the input remains constant. While this property provides sensitivity over a wide range of signal intensities, it remains unclear how other parameters such as adaptation rate and adapted activity affect chemotactic performance, especially when considering that the swimming behavior of the cell determines the input signal. We examine this issue using analytical models and simulations that incorporate recent experimental evidences about behavioral feedback and flagellar motor adaptation. By focusing on how sensory information carried by the response regulator is best utilized by the motor, we identify an operational regime that maximizes drift velocity along chemical concentration gradients for a wide range of environments and sensor adaptation rates. This optimal regime is outside the dynamic range of the motor response, but maximizes the contrast between run duration up and down gradients. In steep gradients, the feedback from chemotactic drift can push the system through a bifurcation. This creates a non-chemotactic state that traps cells unless the motor is allowed to adapt. Although motor adaptation helps, we find that as the strength of the feedback increases individual phenotypes cannot maintain the optimal operational regime in all environments, suggesting that diversity could be beneficial. '),
(86642, 2014, 'plos', 'Ten simple rules for approaching a new job', 'Bourne, Philip E', 'Office of the Director, National Institutes of Health, Bethesda, Maryland, United States of America.', 'United States', 0, 'Career Choice|Employment|Goals|Humans|Interviews as Topic|Professional Competence', 'Editorial', '10.1371/journal.pcbi.1003660', '24967974', '-'),
(86643, 2014, 'plos', 'Optimal sampling strategies for detecting zoonotic disease epidemics', 'Ferguson, Jake M|Langebrake, Jessica B|Cannataro, Vincent L|Garcia, Andres J|Hamman, Elizabeth A|Martcheva, Maia|Osenberg, Craig W', 'Department of Biology, University of Florida, Gainesville, Florida, United States of America.|Department of Mathematics, University of Florida, Gainesville, Florida, United States of America.|Department of Biology, University of Florida, Gainesville, Florida, United States of America.|Emerging Pathogens Institute, University of Florida, Gainesville, Florida, United States of America, Department of Geography, University of Florida, Gainesville, Florida, United States of America.|Department of Biology, University of Florida, Gainesville, Florida, United States of America.|Department of Mathematics, University of Florida, Gainesville, Florida, United States of America.|Department of Biology, University of Florida, Gainesville, Florida, United States of America.', 'United States|United States|United States|United States|United States|United States|United States', 5, 'Animals|Computational Biology|Disease Vectors|Epidemics|Humans|Models, Biological|Models, Statistical|Population Surveillance|West Nile Fever|West Nile virus|Zoonoses', 'Journal Article', '10.1371/journal.pcbi.1003668', '24968100', 'The early detection of disease epidemics reduces the chance of successful introductions into new locales, minimizes the number of infections, and reduces the financial impact. We develop a framework to determine the optimal sampling strategy for disease detection in zoonotic host-vector epidemiological systems when a disease goes from below detectable levels to an epidemic. We find that if the time of disease introduction is known then the optimal sampling strategy can switch abruptly between sampling only from the vector population to sampling only from the host population. We also construct time-independent optimal sampling strategies when conducting periodic sampling that can involve sampling both the host and the vector populations simultaneously. Both time-dependent and -independent solutions can be useful for sampling design, depending on whether the time of introduction of the disease is known or not. We illustrate the approach with West Nile virus, a globally-spreading zoonotic arbovirus. Though our analytical results are based on a linearization of the dynamical systems, the sampling rules appear robust over a wide range of parameter space when compared to nonlinear simulation models. Our results suggest some simple rules that can be used by practitioners when developing surveillance programs. These rules require knowledge of transition rates between epidemiological compartments, which population was initially infected, and of the cost per sample for serological tests. '),
(86644, 2014, 'plos', 'A scalable computational framework for establishing long-term behavior of stochastic reaction networks', 'Gupta, Ankit|Briat, Corentin|Khammash, Mustafa', 'Department of Biosystems Science and Engineering (D-BSSE), Swiss Federal Institute of Technology-Zürich (ETH-Z), Basel, Switzerland.|Department of Biosystems Science and Engineering (D-BSSE), Swiss Federal Institute of Technology-Zürich (ETH-Z), Basel, Switzerland.|Department of Biosystems Science and Engineering (D-BSSE), Swiss Federal Institute of Technology-Zürich (ETH-Z), Basel, Switzerland.', 'Switzerland|Switzerland|Switzerland', 0, 'Circadian Rhythm|Feedback, Physiological|Models, Biological|Stochastic Processes|Systems Biology', 'Journal Article', '10.1371/journal.pcbi.1003669', '24968191', 'Reaction networks are systems in which the populations of a finite number of species evolve through predefined interactions. Such networks are found as modeling tools in many biological disciplines such as biochemistry, ecology, epidemiology, immunology, systems biology and synthetic biology. It is now well-established that, for small population sizes, stochastic models for biochemical reaction networks are necessary to capture randomness in the interactions. The tools for analyzing such models, however, still lag far behind their deterministic counterparts. In this paper, we bridge this gap by developing a constructive framework for examining the long-term behavior and stability properties of the reaction dynamics in a stochastic setting. In particular, we address the problems of determining ergodicity of the reaction dynamics, which is analogous to having a globally attracting fixed point for deterministic dynamics. We also examine when the statistical moments of the underlying process remain bounded with time and when they converge to their steady state values. The framework we develop relies on a blend of ideas from probability theory, linear algebra and optimization theory. We demonstrate that the stability properties of a wide class of biological networks can be assessed from our sufficient theoretical conditions that can be recast as efficient and scalable linear programs, well-known for their tractability. It is notably shown that the computational complexity is often linear in the number of species. We illustrate the validity, the efficiency and the wide applicability of our results on several reaction networks arising in biochemistry, systems biology, epidemiology and ecology. The biological implications of the results as well as an example of a non-ergodic biological network are also discussed. '),
(86645, 2014, 'plos', 'Interplay between chaperones and protein disorder promotes the evolution of protein networks', 'Pechmann, Sebastian|Frydman, Judith', 'Department of Biology, Stanford University, Stanford, California, United States of America.|Department of Biology, Stanford University, Stanford, California, United States of America.', 'United States|United States', 14, 'Computational Biology|Escherichia coli|Evolution, Molecular|Humans|Intrinsically Disordered Proteins|Molecular Chaperones|Mutation|Protein Interaction Maps|Saccharomyces cerevisiae', 'Journal Article', '10.1371/journal.pcbi.1003674', '24968255', 'Evolution is driven by mutations, which lead to new protein functions but come at a cost to protein stability. Non-conservative substitutions are of interest in this regard because they may most profoundly affect both function and stability. Accordingly, organisms must balance the benefit of accepting advantageous substitutions with the possible cost of deleterious effects on protein folding and stability. We here examine factors that systematically promote non-conservative mutations at the proteome level. Intrinsically disordered regions in proteins play pivotal roles in protein interactions, but many questions regarding their evolution remain unanswered. Similarly, whether and how molecular chaperones, which have been shown to buffer destabilizing mutations in individual proteins, generally provide robustness during proteome evolution remains unclear. To this end, we introduce an evolutionary parameter xcexbb that directly estimates the rate of non-conservative substitutions. Our analysis of xcexbb in Escherichia coli, Saccharomyces cerevisiae, and Homo sapiens sequences reveals how co- and post-translationally acting chaperones differentially promote non-conservative substitutions in their substrates, likely through buffering of their destabilizing effects. We further find that xcexbb serves well to quantify the evolution of intrinsically disordered proteins even though the unstructured, thus generally variable regions in proteins are often flanked by very conserved sequences. Crucially, we show that both intrinsically disordered proteins and highly re-wired proteins in protein interaction networks, which have evolved new interactions and functions, exhibit a higher xcexbb at the expense of enhanced chaperone assistance. Our findings thus highlight an intricate interplay of molecular chaperones and protein disorder in the evolvability of protein networks. Our results illuminate the role of chaperones in enabling protein evolution, and underline the importance of the cellular context and integrated approaches for understanding proteome evolution. We feel that the development of xcexbb may be a valuable addition to the toolbox applied to understand the molecular basis of evolution. '),
(86646, 2014, 'plos', 'Brain and behavior in decision-making', 'Cassey, Peter|Heathcote, Andrew|Brown, Scott D', 'School of Psychology, University of Newcastle, Newcastle, New South Wales, Australia.|School of Psychology, University of Newcastle, Newcastle, New South Wales, Australia.|School of Psychology, University of Newcastle, Newcastle, New South Wales, Australia.', 'Australia|Australia|Australia', 0, 'Animals|Behavior, Animal|Brain|Computational Biology|Decision Making|Haplorhini|Models, Neurological', 'Journal Article', '10.1371/journal.pcbi.1003700', '24991810', 'Speed-accuracy tradeoff (SAT) is an adaptive process balancing urgency and caution when making decisions. Computational cognitive theories, known as evidence accumulation models, have explained SATs via a manipulation of the amount of evidence necessary to trigger response selection. New light has been shed on these processes by single-cell recordings from monkeys who were adjusting their SAT settings. Those data have been interpreted as inconsistent with existing evidence accumulation theories, prompting the addition of new mechanisms to the models. We show that this interpretation was wrong, by demonstrating that the neural spiking data, and the behavioural data are consistent with existing evidence accumulation theories, without positing additional mechanisms. Our approach succeeds by using the neural data to provide constraints on the cognitive model. Open questions remain about the locus of the link between certain elements of the cognitive models and the neurophysiology, and about the relationship between activity in cortical neurons identified with decision-making vs. activity in downstream areas more closely linked with motor effectors. '),
(86647, 2014, 'plos', 'BiP clustering facilitates protein folding in the endoplasmic reticulum', 'Griesemer, Marc|Young, Carissa|Robinson, Anne S|Petzold, Linda', 'Department of Applied Mathematics, University of California, Merced, Merced, California, United States of America.|Department of Chemical Engineering, University of Delaware, Newark, Delaware, United States of America.|Department of Chemical Engineering, University of Delaware, Newark, Delaware, United States of America, Department of Chemical and Biomolecular Engineering, Tulane University, New Orleans, Louisiana, United States of America.|Department of Computer Science, University of California, Santa Barbara, Santa Barbara, California, United States of America.', 'United States|United States|United States|United States', 0, 'Computational Biology|Endoplasmic Reticulum|Heat-Shock Proteins|Models, Biological|Protein Folding|Saccharomyces cerevisiae|Saccharomyces cerevisiae Proteins', 'Journal Article', '10.1371/journal.pcbi.1003675', '24991821', 'The chaperone BiP participates in several regulatory processes within the endoplasmic reticulum (ER): translocation, protein folding, and ER-associated degradation. To facilitate protein folding, a cooperative mechanism known as entropic pulling has been proposed to demonstrate the molecular-level understanding of how multiple BiP molecules bind to nascent and unfolded proteins. Recently, experimental evidence revealed the spatial heterogeneity of BiP within the nuclear and peripheral ER of S. cerevisiae (commonly referred to as clusters). Here, we developed a model to evaluate the potential advantages of accounting for multiple BiP molecules binding to peptides, while proposing that BiPs spatial heterogeneity may enhance protein folding and maturation. Scenarios were simulated to gauge the effectiveness of binding multiple chaperone molecules to peptides. Using two metrics: folding efficiency and chaperone cost, we determined that the single binding site model achieves a higher efficiency than models characterized by multiple binding sites, in the absence of cooperativity. Due to entropic pulling, however, multiple chaperones perform in concert to facilitate the resolubilization and ultimate yield of folded proteins. As a result of cooperativity, multiple binding site models used fewer BiP molecules and maintained a higher folding efficiency than the single binding site model. These insilico investigations reveal that clusters of BiP molecules bound to unfolded proteins may enhance folding efficiency through cooperative action via entropic pulling. '),
(86648, 2014, 'plos', 'Computational modeling and analysis of iron release from macrophages', 'Potdar, Alka A|Sarkar, Joydeep|Das, Nupur K|Ghosh, Paroma|Gratzl, Miklos|Fox, Paul L|Saidel, Gerald M', 'Department of Biomedical Engineering, Case Western Reserve University, Cleveland, Ohio, United States of America, Department of Cellular and Molecular Medicine, Cleveland Clinic, Cleveland, Ohio, United States of America.|Department of Biomedical Engineering, Case Western Reserve University, Cleveland, Ohio, United States of America.|Department of Cellular and Molecular Medicine, Cleveland Clinic, Cleveland, Ohio, United States of America.|Department of Cellular and Molecular Medicine, Cleveland Clinic, Cleveland, Ohio, United States of America.|Department of Biomedical Engineering, Case Western Reserve University, Cleveland, Ohio, United States of America.|Department of Cellular and Molecular Medicine, Cleveland Clinic, Cleveland, Ohio, United States of America.|Department of Biomedical Engineering, Case Western Reserve University, Cleveland, Ohio, United States of America.', 'United States|United States|United States|United States|United States|United States|United States', 11, 'Computational Biology|Computer Simulation|Homeostasis|Humans|Intracellular Space|Iron|Macrophages|Models, Biological', 'Journal Article', '10.1371/journal.pcbi.1003701', '24991925', 'A major process of iron homeostasis in whole-body iron metabolism is the release of iron from the macrophages of the reticuloendothelial system. Macrophages recognize and phagocytose senescent or damaged erythrocytes. Then, they process the heme iron, which is returned to the circulation for reutilization by red blood cell precursors during erythropoiesis. The amount of iron released, compared to the amount shunted for storage as ferritin, is greater during iron deficiency. A currently accepted model of iron release assumes a passive-gradient with free diffusion of intracellular labile iron (Fe2+) through ferroportin (FPN), the transporter on the plasma membrane. Outside the cell, a multi-copper ferroxidase, ceruloplasmin (Cp), oxidizes ferrous to ferric ion. Apo-transferrin (Tf), the primary carrier of soluble iron in the plasma, binds ferric ion to form mono-ferric and di-ferric transferrin. According to the passive-gradient model, the removal of ferrous ion from the site of release sustains the gradient that maintains the iron release. Subcellular localization of FPN, however, indicates that the role of FPN may be more complex. By experiments and mathematical modeling, we have investigated the detailed mechanism of iron release from macrophages focusing on the roles of the Cp, FPN and apo-Tf. The passive-gradient model is quantitatively analyzed using a mathematical model for the first time. A comparison of experimental data with model simulations shows that the passive-gradient model cannot explain macrophage iron release. However, a facilitated-transport model associated with FPN can explain the iron release mechanism. According to the facilitated-transport model, intracellular FPN carries labile iron to the macrophage membrane. Extracellular Cp accelerates the oxidation of ferrous ion bound to FPN. Apo-Tf in the extracellular environment binds to the oxidized ferrous ion, completing the release process. Facilitated-transport model can correctly predict cellular iron efflux and is essential for physiologically relevant whole-body model of iron metabolism. '),
(86649, 2014, 'plos', 'Modeling higher-order correlations within cortical microcolumns', 'Köster, Urs|Sohl-Dickstein, Jascha|Gray, Charles M|Olshausen, Bruno A', 'Redwood Center for Theoretical Neuroscience, University of California, Berkeley, Berkeley, California, United States of America.|Department of Applied Physics, Stanford University and Khan Academy, Palo Alto, California, United States of America.|Department of Cell Biology and Neuroscience, Montana State University, Bozeman, Montana, United States of America.|Redwood Center for Theoretical Neuroscience, University of California, Berkeley, Berkeley, California, United States of America.', 'United States|United States|United States|United States', 0, 'Action Potentials|Algorithms|Animals|Cats|Cluster Analysis|Models, Neurological|Neurons|Photic Stimulation|Visual Cortex', 'Journal Article', '10.1371/journal.pcbi.1003684', '24991969', 'We statistically characterize the population spiking activity obtained from simultaneous recordings of neurons across all layers of a cortical microcolumn. Three types of models are compared: an Ising model which captures pairwise correlations between units, a Restricted Boltzmann Machine (RBM) which allows for modeling of higher-order correlations, and a semi-Restricted Boltzmann Machine which is a combination of Ising and RBM models. Model parameters were estimated in a fast and efficient manner using minimum probability flow, and log likelihoods were compared using annealed importance sampling. The higher-order models reveal localized activity patterns which reflect the laminar organization of neurons within a cortical column. The higher-order models also outperformed the Ising model in log-likelihood: On populations of 20 cells, the RBM had 10% higher log-likelihood (relative to an independent model) than a pairwise model, increasing to 45% gain in a larger network with 100 spatiotemporal elements, consisting of 10 neurons over 10 time steps. We further removed the need to model stimulus-induced correlations by incorporating a peri-stimulus time histogram term, in which case the higher order models continued to perform best. These results demonstrate the importance of higher-order interactions to describe the structure of correlated activity in cortical networks. Boltzmann Machines with hidden units provide a succinct and effective way to capture these dependencies without increasing the difficulty of model estimation and evaluation. ');
INSERT INTO `papers` (`id`, `ano`, `journal`, `titulo`, `autores`, `afiliacao`, `pais`, `citacoes`, `palavra_chave`, `categorias`, `doi`, `pubmed`, `abstract`) VALUES
(86650, 2014, 'plos', 'Alkylpurine glycosylase D employs DNA sculpting as a strategy to extrude and excise damaged bases', 'Kossmann, Bradley|Ivanov, Ivaylo', 'Department of Chemistry, Center for Diagnostics and Therapeutics, Georgia State University, Atlanta, Georgia, United States of America.|Department of Chemistry, Center for Diagnostics and Therapeutics, Georgia State University, Atlanta, Georgia, United States of America.', 'Georgia|Georgia', 0, 'Adenine|Bacillus cereus|Bacterial Proteins|DNA|DNA Glycosylases|DNA Repair|Models, Molecular|Nucleic Acid Conformation|Thermodynamics', 'Journal Article', '10.1371/journal.pcbi.1003704', '24992034', 'Alkylpurine glycosylase D (AlkD) exhibits a unique base excision strategy. Instead of interacting directly with the lesion, the enzyme engages the non-lesion DNA strand. AlkD induces flipping of the alkylated and opposing base accompanied by DNA stack compression. Since this strategy leaves the alkylated base solvent exposed, the means to achieve enzymatic cleavage had remained unclear. We determined a minimum energy path for flipping out a 3-methyl adenine by AlkD and computed a potential of mean force along this path to delineate the energetics of base extrusion. We show that AlkD acts as a scaffold to stabilize three distinct DNA conformations, including the final extruded state. These states are almost equivalent in free energy and separated by low barriers. Thus, AlkD acts by sculpting the global DNA conformation to achieve lesion expulsion from DNA. N-glycosidic bond scission is then facilitated by a backbone phosphate group proximal to the alkylated base. '),
(86651, 2014, 'plos', 'ODE constrained mixture modelling: a method for unraveling subpopulation structures and dynamics', 'Hasenauer, Jan|Hasenauer, Christine|Hucho, Tim|Theis, Fabian J', 'Institute of Computational Biology, Helmholtz Center Munich, Munich, Germany, Division of Mathematical Modeling of Biological Systems, Department of Mathematics, University of Technology Munich, Munich, Germany.|Max Planck Institute for Molecular Genetics, Berlin, Germany.|Max Planck Institute for Molecular Genetics, Berlin, Germany, Division of Experimental Anesthesiology and Pain Research, Department of Anesthesiology and Intensive Care Medicine, University Hospital Cologne, Cologne, Germany.|Institute of Computational Biology, Helmholtz Center Munich, Munich, Germany, Division of Mathematical Modeling of Biological Systems, Department of Mathematics, University of Technology Munich, Munich, Germany.', 'Germany|Germany|Germany|Germany', 24, 'Animals|Extracellular Signal-Regulated MAP Kinases|MAP Kinase Signaling System|Male|Models, Neurological|Nerve Growth Factor|Rats|Rats, Sprague-Dawley|Sensory Receptor Cells', 'Journal Article', '10.1371/journal.pcbi.1003686', '24992156', 'Functional cell-to-cell variability is ubiquitous in multicellular organisms as well as bacterial populations. Even genetically identical cells of the same cell type can respond differently to identical stimuli. Methods have been developed to analyse heterogeneous populations, e.g., mixture models and stochastic population models. The available methods are, however, either incapable of simultaneously analysing different experimental conditions or are computationally demanding and difficult to apply. Furthermore, they do not account for biological information available in the literature. To overcome disadvantages of existing methods, we combine mixture models and ordinary differential equation (ODE) models. The ODE models provide a mechanistic description of the underlying processes while mixture models provide an easy way to capture variability. In a simulation study, we show that the class of ODE constrained mixture models can unravel the subpopulation structure and determine the sources of cell-to-cell variability. In addition, the method provides reliable estimates for kinetic rates and subpopulation characteristics. We use ODE constrained mixture modelling to study NGF-induced Erk1/2 phosphorylation in primary sensory neurones, a process relevant in inflammatory and neuropathic pain. We propose a mechanistic pathway model for this process and reconstructed static and dynamical subpopulation characteristics across experimental conditions. We validate the model predictions experimentally, which verifies the capabilities of ODE constrained mixture models. These results illustrate that ODE constrained mixture models can reveal novel mechanistic insights and possess a high sensitivity. '),
(86652, 2014, 'plos', 'Soft skills: an important asset acquired from organizing regional student group activities', 'de Ridder, Jeroen|Meysman, Pieter|Oluwagbemi, Olugbenga|Abeel, Thomas', 'Delft Bioinformatics Lab, Delft University of Technology, Delft, The Netherlands.|Biomedical Informatics Research Center Antwerp (biomina), University of Antwerp/Antwerp University Hospital, Antwerp, Belgium, Department of Mathematics and Computer Sciences, University of Antwerp, Antwerp, Belgium.|Department of Computer and Information Sciences, School of Natural and Applied Sciences, Covenant University, Ota, Nigeria, West Africa.|Broad Institute of MIT and Harvard, Cambridge, Massachusetts, United States of America, VIB Department of Plant Systems Biology, Ghent University, Ghent, Belgium.', 'Netherlands|Belgium|Niger|Belgium', 6, 'Computational Biology|Humans|Leadership|Reward|Social Networking|Social Skills|Students', 'Journal Article', '10.1371/journal.pcbi.1003708', '24992198', 'Contributing to a student organization, such as the International Society for Computational Biology Student Council (ISCB-SC) and its Regional Student Group (RSG) program, takes time and energy. Both are scarce commodities, especially when you are trying to find your place in the world of computational biology as a graduate student. It comes as no surprise that organizing ISCB-SC-related activities sometimes interferes with day-to-day research and shakes up your priority list. However, we unanimously agree that the rewards, both in the short as well as the long term, make the time spent on these extracurricular activities more than worth it. In this article, we will explain what makes this so worthwhile: soft skills. '),
(86653, 2014, 'plos', 'Locating the route of entry and binding sites of benzocaine and phenytoin in a bacterial voltage gated sodium channel', 'Martin, Lewis J|Corry, Ben', 'Research School of Biology, Australian National University, Canberra, Australia.|Research School of Biology, Australian National University, Canberra, Australia.', 'Australia|Australia', 24, 'Bacterial Proteins|Benzocaine|Binding Sites|Computational Biology|Hydrophobic and Hydrophilic Interactions|Models, Biological|Molecular Dynamics Simulation|Phenytoin|Thermodynamics|Voltage-Gated Sodium Channels', 'Journal Article', '10.1371/journal.pcbi.1003688', '24992293', 'Sodium channel blockers are used to control electrical excitability in cells as a treatment for epileptic seizures and cardiac arrhythmia, and to provide short term control of pain. Development of the next generation of drugs that can selectively target one of the nine types of voltage-gated sodium channel expressed in the body requires a much better understanding of how current channel blockers work. Here we make use of the recently determined crystal structure of the bacterial voltage gated sodium channel NavAb in molecular dynamics simulations to elucidate the position at which the sodium channel blocking drugs benzocaine and phenytoin bind to the protein as well as to understand how these drugs find their way into resting channels. We show that both drugs have two likely binding sites in the pore characterised by nonspecific, hydrophobic interactions: one just above the activation gate, and one at the entrance to the the lateral lipid filled fenestrations. Three independent methods find the same sites and all suggest that binding to the activation gate is slightly more favourable than at the fenestration. Both drugs are found to be able to pass through the fenestrations into the lipid with only small energy barriers, suggesting that this can represent the long posited hydrophobic entrance route for neutral drugs. Our simulations highlight the importance of a number of residues in directing drugs into and through the fenestration, and in forming the drug binding sites. '),
(86654, 2014, 'plos', 'PolyUbiquitin chain linkage topology selects the functions from the underlying binding landscape', 'Wang, Yong|Tang, Chun|Wang, Erkang|Wang, Jin', 'State Key Laboratory of Electroanalytical Chemistry, Changchun Institute of Applied Chemistry, Chinese Academy of Sciences, Changchun, Jilin, P.R. China.|State Key Laboratory of Magnetic Resonance and Atomic and Molecular Physics, Wuhan Institute of Physics and Mathematics, Chinese Academy of Sciences, Wuhan, Hubei, China.|State Key Laboratory of Electroanalytical Chemistry, Changchun Institute of Applied Chemistry, Chinese Academy of Sciences, Changchun, Jilin, P.R. China.|State Key Laboratory of Electroanalytical Chemistry, Changchun Institute of Applied Chemistry, Chinese Academy of Sciences, Changchun, Jilin, P.R. China, College of Physics, Jilin University, Changchun, Jilin, P.R. China, Department of Chemistry, Physics and Applied Mathematics, State University of New York at Stony Brook, Stony Brook, New York, United States of America.', 'China|China|China|China', 0, 'Computational Biology|Hydrophobic and Hydrophilic Interactions|Molecular Dynamics Simulation|Polyubiquitin|Protein Binding|Protein Conformation|Static Electricity', 'Journal Article', '10.1371/journal.pcbi.1003691', '24992446', 'Ubiquitin (Ub) can generate versatile molecular signals and lead to different celluar fates. The functional poly-valence of Ub is believed to be resulted from its ability to form distinct polymerized chains with eight linkage types. To provide a full picture of ubiquitin code, we explore the binding landscape of two free Ub monomers and also the functional landscapes of of all eight linkage types by theoretical modeling. Remarkably, we found that most of the compact structures of covalently connected dimeric Ub chains (diUbs) pre-exist on the binding landscape. These compact functional states were subsequently validated by corresponding linkage models. This leads to the proposal that the folding architecture of Ub monomer has encoded all functional states into its binding landscape, which is further selected by different topologies of polymeric Ub chains. Moreover, our results revealed that covalent linkage leads to symmetry breaking of interfacial interactions. We further propose that topological constraint not only limits the conformational space for effective switching between functional states, but also selects the local interactions for realizing the corresponding biological function. Therefore, the topological constraint provides a way for breaking the binding symmetry and reaching the functional specificity. The simulation results also provide several predictions that qualitatively and quantitatively consistent with experiments. Importantly, the K48 linkage model successfully predicted intermediate states. The resulting multi-state energy landscape was further employed to reconcile the seemingly contradictory experimental data on the conformational equilibrium of K48-diUb. Our results further suggest that hydrophobic interactions are dominant in the functional landscapes of K6-, K11-, K33- and K48 diUbs, while electrostatic interactions play a more important role in the functional landscapes of K27, K29, K63 and linear linkages. '),
(86655, 2014, 'plos', 'A likelihood-based approach to identifying contaminated food products using sales data: performance and challenges', 'Kaufman, James|Lessler, Justin|Harry, April|Edlund, Stefan|Hu, Kun|Douglas, Judith|Thoens, Christian|Appel, Bernd|Käsbohrer, Annemarie|Filter, Matthias', 'IBM Almaden Research Center, San Jose, California, United States of America.|Department of Epidemiology, Johns Hopkins Bloomberg School of Public Health, Baltimore, Maryland, United States of America.|IBM Almaden Research Center, San Jose, California, United States of America.|IBM Almaden Research Center, San Jose, California, United States of America.|IBM Almaden Research Center, San Jose, California, United States of America.|IBM Almaden Research Center, San Jose, California, United States of America.|Federal Institute for Risk Assessment, Berlin, Germany.|Federal Institute for Risk Assessment, Berlin, Germany.|Federal Institute for Risk Assessment, Berlin, Germany.|Federal Institute for Risk Assessment, Berlin, Germany.', 'United States|United States|United States|United States|United States|United States|Germany|Germany|', 13, 'Cluster Analysis|Computational Biology|Disease Outbreaks|Food Industry|Foodborne Diseases|Humans|Likelihood Functions|Models, Biological|Public Health', 'Journal Article', '10.1371/journal.pcbi.1003692', '24992565', 'Foodborne disease outbreaks of recent years demonstrate that due to increasingly interconnected supply chains these type of crisis situations have the potential to affect thousands of people, leading to significant healthcare costs, loss of revenue for food companies, and--in the worst cases--death. When a disease outbreak is detected, identifying the contaminated food quickly is vital to minimize suffering and limit economic losses. Here we present a likelihood-based approach that has the potential to accelerate the time needed to identify possibly contaminated food products, which is based on exploitation of food products sales data and the distribution of foodborne illness case reports. Using a real world food sales data set and artificially generated outbreak scenarios, we show that this method performs very well for contamination scenarios originating from a single guilty food product. As it is neither always possible nor necessary to identify the single offending product, the method has been extended such that it can be used as a binary classifier. With this extension it is possible to generate a set of potentially guilty products that contains the real outbreak source with very high accuracy. Furthermore we explore the patterns of food distributions that lead to hard-to-identify foods, the possibility of identifying these food groups a priori, and the extent to which the likelihood-based method can be used to quantify uncertainty. We find that high spatial correlation of sales data between products may be a useful indicator for hard-to-identify products.'),
(86656, 2014, 'plos', 'Emergent biosynthetic capacity in simple microbial communities', 'Chiu, Hsuan-Chao|Levy, Roie|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, Department of Computer Science and Engineering, University of Washington, Seattle, Washington, United States of America, Santa Fe Institute, Santa Fe, New Mexico, United States of America.', 'United States|United States|Mexico', 52, 'Computational Biology|Ecosystem|Metabolism|Microbial Consortia|Models, Biological', 'Journal Article', '10.1371/journal.pcbi.1003695', '24992662', 'Microbes have an astonishing capacity to transform their environments. Yet, the metabolic capacity of a single species is limited and the vast majority of microorganisms form complex communities and join forces to exhibit capabilities far exceeding those achieved by any single species. Such enhanced metabolic capacities represent a promising route to many medical, environmental, and industrial applications and call for the development of a predictive, systems-level understanding of synergistic microbial capacity. Here we present a comprehensive computational framework, integrating high-quality metabolic models of multiple species, temporal dynamics, and flux variability analysis, to study the metabolic capacity and dynamics of simple two-species microbial ecosystems. We specifically focus on detecting emergent biosynthetic capacity--instances in which a community growing on some medium produces and secretes metabolites that are not secreted by any member species when growing in isolation on that same medium. Using this framework to model a large collection of two-species communities on multiple media, we demonstrate that emergent biosynthetic capacity is highly prevalent. We identify commonly observed emergent metabolites and metabolic reprogramming patterns, characterizing typical mechanisms of emergent capacity. We further find that emergent secretion tends to occur in two waves, the first as soon as the two organisms are introduced, and the second when the medium is depleted and nutrients become limited. Finally, aiming to identify global community determinants of emergent capacity, we find a marked association between the level of emergent biosynthetic capacity and the functional/phylogenetic distance between community members. Specifically, we demonstrate a Goldilocks principle, where high levels of emergent capacity are observed when the species comprising the community are functionally neither too close, nor too distant. Taken together, our results demonstrate the potential to design and engineer synthetic communities capable of novel metabolic activities and point to promising future directions in environmental and clinical bioengineering.'),
(86657, 2014, 'plos', 'Regulation of the nucleosome repeat length in vivo by the DNA sequence, protein concentrations and long-range interactions', 'Beshnova, Daria A|Cherstvy, Andrey G|Vainshtein, Yevhen|Teif, Vladimir B', 'Deutsches Krebsforschungszentrum (DKFZ) and BioQuant, Heidelberg, Germany.|Institute for Physics and Astronomy, University of Potsdam, Potsdam-Golm, Germany.|Deutsches Krebsforschungszentrum (DKFZ) and BioQuant, Heidelberg, Germany.|Deutsches Krebsforschungszentrum (DKFZ) and BioQuant, Heidelberg, Germany.', 'Germany|Germany|Germany|Germany', 0, 'Animals|Anura|Chromatin|Computational Biology|DNA|Histones|Mice|Models, Biological|Nucleosomes|Yeasts', 'Journal Article', '10.1371/journal.pcbi.1003698', '24992723', 'The nucleosome repeat length (NRL) is an integral chromatin property important for its biological functions. Recent experiments revealed several conflicting trends of the NRL dependence on the concentrations of histones and other architectural chromatin proteins, both in vitro and in vivo, but a systematic theoretical description of NRL as a function of DNA sequence and epigenetic determinants is currently lacking. To address this problem, we have performed an integrative biophysical and bioinformatics analysis in species ranging from yeast to frog to mouse where NRL was studied as a function of various parameters. We show that in simple eukaryotes such as yeast, a lower limit for the NRL value exists, determined by internucleosome interactions and remodeler action. For higher eukaryotes, also the upper limit exists since NRL is an increasing but saturating function of the linker histone concentration. Counterintuitively, smaller H1 variants or non-histone architectural proteins can initiate larger effects on the NRL due to entropic reasons. Furthermore, we demonstrate that different regimes of the NRL dependence on histone concentrations exist depending on whether DNA sequence-specific effects dominate over boundary effects or vice versa. We consider several classes of genomic regions with apparently different regimes of the NRL variation. As one extreme, our analysis reveals that the period of oscillations of the nucleosome density around bound RNA polymerase coincides with the period of oscillations of positioning sites of the corresponding DNA sequence. At another extreme, we show that although mouse major satellite repeats intrinsically encode well-defined nucleosome preferences, they have no unique nucleosome arrangement and can undergo a switch between two distinct types of nucleosome positioning. '),
(86658, 2014, 'plos', 'Biophysical fitness landscapes for transcription factor binding sites', 'Haldane, Allan|Manhart, Michael|Morozov, Alexandre V', 'Department of Physics and Astronomy, Rutgers University, Piscataway, New Jersey, United States of America.|Department of Physics and Astronomy, Rutgers University, Piscataway, New Jersey, United States of America.|Department of Physics and Astronomy, Rutgers University, Piscataway, New Jersey, United States of America, BioMaPS Institute for Quantitative Biology, Rutgers University, Piscataway, New Jersey, United States of America.', 'Jersey|Jersey|Jersey', 18, 'Binding Sites|Computational Biology|DNA|Models, Biological|Protein Binding|Saccharomyces cerevisiae Proteins|Transcription Factors', 'Journal Article', '10.1371/journal.pcbi.1003683', '25010228', 'Phenotypic states and evolutionary trajectories available to cell populations are ultimately dictated by complex interactions among DNA, RNA, proteins, and other molecular species. Here we study how evolution of gene regulation in a single-cell eukaryote S. cerevisiae is affected by interactions between transcription factors (TFs) and their cognate DNA sites. Our study is informed by a comprehensive collection of genomic binding sites and high-throughput in vitro measurements of TF-DNA binding interactions. Using an evolutionary model for monomorphic populations evolving on a fitness landscape, we infer fitness as a function of TF-DNA binding to show that the shape of the inferred fitness functions is in broad agreement with a simple functional form inspired by a thermodynamic model of two-state TF-DNA binding. However, the effective parameters of the model are not always consistent with physical values, indicating selection pressures beyond the biophysical constraints imposed by TF-DNA interactions. We find little statistical support for the fitness landscape in which each position in the binding site evolves independently, indicating that epistasis is common in the evolution of gene regulation. Finally, by correlating TF-DNA binding energies with biological properties of the sites or the genes they regulate, we are able to rule out several scenarios of site-specific selection, under which binding sites of the same TF would experience different selection pressures depending on their position in the genome. These findings support the existence of universal fitness landscapes which shape evolution of all sites for a given TF, and whose properties are determined in part by the physics of protein-DNA interactions. '),
(86659, 2014, 'plos', 'Inferring clonal composition from multiple sections of a breast cancer', 'Zare, Habil|Wang, Junfeng|Hu, Alex|Weber, Kris|Smith, Josh|Nickerson, Debbie|Song, ChaoZhong|Witten, Daniela|Blau, C Anthony|Noble, William Stafford', 'Department of Genome Sciences, University of Washington, Seattle, Washington, United States of America.|Division of Hematology, Department of Medicine, 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.|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.|Division of Hematology, Department of Medicine, University of Washington, Seattle, Washington, United States of America.|Department of Biostatistics, University of Washington, Seattle, Washington, United States of America.|Division of Hematology, Department of Medicine, University of Washington, Seattle, Washington, United States of America.|Department of Genome Sciences, University of Washington, Seattle, Washington, United States of America, Department of Computer Science and Engineering, University of Washington, Seattle, Washington, United States of America.', 'United States|United States|United States|United States|United States|United States|United States|Un', 0, 'Algorithms|Breast Neoplasms|Computational Biology|Computer Simulation|Female|Genotype|Humans|Phylogeny', 'Journal Article', '10.1371/journal.pcbi.1003703', '25010360', 'Cancers arise from successive rounds of mutation and selection, generating clonal populations that vary in size, mutational content and drug responsiveness. Ascertaining the clonal composition of a tumor is therefore important both for prognosis and therapy. Mutation counts and frequencies resulting from next-generation sequencing (NGS) potentially reflect a tumors clonal composition, however, deconvolving NGS data to infer a tumors clonal structure presents a major challenge. We propose a generative model for NGS data derived from multiple subsections of a single tumor, and we describe an expectation-maximization procedure for estimating the clonal genotypes and relative frequencies using this model. We demonstrate, via simulation, the validity of the approach, and then use our algorithm to assess the clonal composition of a primary breast cancer and associated metastatic lymph node. After dividing the tumor into subsections, we perform exome sequencing for each subsection to assess mutational content, followed by deep sequencing to precisely count normal and variant alleles within each subsection. By quantifying the frequencies of 17 somatic variants, we demonstrate that our algorithm predicts clonal relationships that are both phylogenetically and spatially plausible. Applying this method to larger numbers of tumors should cast light on the clonal evolution of cancers in space and time. '),
(86660, 2014, 'plos', 'Metagenomic data utilization and analysis (MEDUSA) and construction of a global gut microbial gene catalogue', 'Karlsson, Fredrik H|Nookaew, Intawat|Nielsen, Jens', 'Department of Chemical and Biological Engineering, Chalmers University of Technology, Gothenburg, Sweden.|Department of Chemical and Biological Engineering, Chalmers University of Technology, Gothenburg, Sweden.|Department of Chemical and Biological Engineering, Chalmers University of Technology, Gothenburg, Sweden.', 'Sweden|Sweden|Sweden', 32, 'Continental Population Groups|Databases, Genetic|Gastrointestinal Tract|Genome, Archaeal|Genome, Bacterial|Humans|Metagenomics', 'Journal Article', '10.1371/journal.pcbi.1003706', '25010449', 'Metagenomic sequencing has contributed important new knowledge about the microbes that live in a symbiotic relationship with humans. With modern sequencing technology it is possible to generate large numbers of sequencing reads from a metagenome but analysis of the data is challenging. Here we present the bioinformatics pipeline MEDUSA that facilitates analysis of metagenomic reads at the gene and taxonomic level. We also constructed a global human gut microbial gene catalogue by combining data from 4 studies spanning 3 continents. Using MEDUSA we mapped 782 gut metagenomes to the global gene catalogue and a catalogue of sequenced microbial species. Hereby we find that all studies share about half a million genes and that on average 300,000 genes are shared by half the studied subjects. The gene richness is higher in the European studies compared to Chinese and American and this is also reflected in the species richness. Even though it is possible to identify common species and a core set of genes, we find that there are large variations in abundance of species and genes.'),
(86661, 2014, 'plos', 'The dynamics of DNA methylation covariation patterns in carcinogenesis', 'Teschendorff, Andrew E|Liu, Xiaoping|Caren, Helena|Pollard, Steve M|Beck, Stephan|Widschwendter, Martin|Chen, Luonan', 'CAS-MPG Partner Institute for Computational Biology, Chinese Academy of Sciences, Shanghai Institute for Biological Sciences, Shanghai, China, Statistical Genomics Group, UCL Cancer Institute, University College London, London, United Kingdom.|Key Laboratory of Systems Biology, SIBS-Nordisk Translational Research Centre for PreDiabetes, Shanghai Institute for Biological Sciences, Chinese Academy of Sciences, Shanghai, China.|Sahlgrenska Cancer Center, Department of Pathology, University of Gothenburg, Gothenburg, Sweden.|Department of Cancer Biology, UCL Cancer Institute, University College London, London, United Kingdom.|Medical Genomics Group, UCL Cancer Institute, University College London, London, United Kingdom.|Department of Womens Cancer, UCL EGA Institute for Womens Health, University College London, London, United Kingdom.|Key Laboratory of Systems Biology, SIBS-Nordisk Translational Research Centre for PreDiabetes, Shanghai Institute for Biological Sciences, Chinese Academy of Sciences, Shanghai, China.', 'China|China|Sweden|United Kingdom|United Kingdom|United Kingdom|China', 29, 'Algorithms|Biomarkers, Tumor|Carcinogenesis|Computational Biology|DNA Methylation|Disease Progression|Female|Humans|Papillomavirus Infections|Uterine Cervical Neoplasms', 'Journal Article', '10.1371/journal.pcbi.1003709', '25010556', 'Recently it has been observed that cancer tissue is characterised by an increased variability in DNA methylation patterns. However, how the correlative patterns in genome-wide DNA methylation change during the carcinogenic progress has not yet been explored. Here we study genome-wide inter-CpG correlations in DNA methylation, in addition to single site variability, during cervical carcinogenesis. We demonstrate how the study of changes in DNA methylation covariation patterns across normal, intra-epithelial neoplasia and invasive cancer allows the identification of CpG sites that indicate the risk of neoplastic transformation in stages prior to neoplasia. Importantly, we show that the covariation in DNA methylation at these risk CpG loci is maximal immediately prior to the onset of cancer, supporting the view that high epigenetic diversity in normal cells increases the risk of cancer. Consistent with this, we observe that invasive cancers exhibit increased covariation in DNA methylation at the risk CpG sites relative to normal tissue, but lower levels relative to pre-cancerous lesions. We further show that the identified risk CpG sites undergo preferential DNA methylation changes in relation to human papilloma virus infection and age. Results are validated in independent data including prospectively collected samples prior to neoplastic transformation. Our data are consistent with a phase transition model of carcinogenesis, in which epigenetic diversity is maximal prior to the onset of cancer. The model and algorithm proposed here may allow, in future, network biomarkers predicting the risk of neoplastic transformation to be identified. '),
(86662, 2014, 'plos', 'Analysis of graph invariants in functional neocortical circuitry reveals generalized features common to three areas of sensory cortex', 'Gururangan, Suchin S|Sadovsky, Alexander J|MacLean, Jason N', 'Department of Neurobiology, University of Chicago, Chicago, Illinois, United States of America.|Committee on Computational Neuroscience, University of Chicago, Chicago, Illinois, United States of America.|Department of Neurobiology, University of Chicago, Chicago, Illinois, United States of America, Committee on Computational Neuroscience, University of Chicago, Chicago, Illinois, United States of America.', 'United States|United States|United States', 0, 'Animals|Computational Biology|Female|Male|Mice|Mice, Inbred C57BL|Models, Neurological|Neocortex|Nerve Net|Neurons|Sensorimotor Cortex', 'Journal Article', '10.1371/journal.pcbi.1003710', '25010654', 'Correlations in local neocortical spiking activity can provide insight into the underlying organization of cortical microcircuitry. However, identifying structure in patterned multi-neuronal spiking remains a daunting task due to the high dimensionality of the activity. Using two-photon imaging, we monitored spontaneous circuit dynamics in large, densely sampled neuronal populations within slices of mouse primary auditory, somatosensory, and visual cortex. Using the lagged correlation of spiking activity between neurons, we generated functional wiring diagrams to gain insight into the underlying neocortical circuitry. By establishing the presence of graph invariants, which are label-independent characteristics common to all circuit topologies, our study revealed organizational features that generalized across functionally distinct cortical regions. Regardless of sensory area, random and k-nearest neighbors null graphs failed to capture the structure of experimentally derived functional circuitry. These null models indicated that despite a bias in the data towards spatially proximal functional connections, functional circuit structure is best described by non-random and occasionally distal connections. Eigenvector centrality, which quantifies the importance of a neuron in the temporal flow of circuit activity, was highly related to feedforwardness in all functional circuits. The number of nodes participating in a functional circuit did not scale with the number of neurons imaged regardless of sensory area, indicating that circuit size is not tied to the sampling of neocortex. Local circuit flow comprehensively covered angular space regardless of the spatial scale that we tested, demonstrating that circuitry itself does not bias activity flow toward pia. Finally, analysis revealed that a minimal numerical sample size of neurons was necessary to capture at least 90 percent of functional circuit topology. These data and analyses indicated that functional circuitry exhibited rules of organization which generalized across three areas of sensory neocortex.'),
(86663, 2014, 'plos', 'On the use of human mobility proxies for modeling epidemics', 'Tizzoni, Michele|Bajardi, Paolo|Decuyper, Adeline|Kon Kam King, Guillaume|Schneider, Christian M|Blondel, Vincent|Smoreda, Zbigniew|González, Marta C|Colizza, Vittoria', 'Computational Epidemiology Laboratory, Institute for Scientific Interchange (ISI), Torino, Italy.|Department of Veterinary Science, University of Turin, Torino, Italy.|ICTEAM Institute, Université Catholique de Louvain, Louvain-la-Neuve, Belgium.|CNRS, UMR5558, F-69622 Villeurbanne, France.|Department of Civil and Environmental Engineering, Massachusetts Institute of Technology, Cambridge, Massachusetts, United States of America.|ICTEAM Institute, Université Catholique de Louvain, Louvain-la-Neuve, Belgium.|Sociology and Economics of Networks and Services Department, Orange Labs, Issy-les-Moulineaux, France.|Department of Civil and Environmental Engineering, Massachusetts Institute of Technology, Cambridge, Massachusetts, United States of America, Engineering Systems Division, Massachusetts Institute of Technology, Cambridge, Massachusetts, United States of America.|INSERM, U707, Paris, France, UPMC Université Paris 06, Faculté de Médecine Pierre et Marie Curie, UMR S 707, Paris, France, Institute for Scientific Interchange (ISI), Torino, Italy.', 'Italy|Italy|Belgium|France|United States|Belgium|France|United States|France', 98, 'Cell Phone|Communicable Diseases|Computational Biology|Computer Simulation|Databases, Factual|Epidemics|Europe|Humans|Influenza, Human|Models, Biological|Transportation', 'Journal Article', '10.1371/journal.pcbi.1003716', '25010676', 'Human mobility is a key component of large-scale spatial-transmission models of infectious diseases. Correctly modeling and quantifying human mobility is critical for improving epidemic control, but may be hindered by data incompleteness or unavailability. Here we explore the opportunity of using proxies for individual mobility to describe commuting flows and predict the diffusion of an influenza-like-illness epidemic. We consider three European countries and the corresponding commuting networks at different resolution scales, obtained from (i) official census surveys, (ii) proxy mobility data extracted from mobile phone call records, and (iii) the radiation model calibrated with census data. Metapopulation models defined on these countries and integrating the different mobility layers are compared in terms of epidemic observables. We show that commuting networks from mobile phone data capture the empirical commuting patterns well, accounting for more than 87% of the total fluxes. The distributions of commuting fluxes per link from mobile phones and census sources are similar and highly correlated, however a systematic overestimation of commuting traffic in the mobile phone data is observed. This leads to epidemics that spread faster than on census commuting networks, once the mobile phone commuting network is considered in the epidemic model, however preserving to a high degree the order of infection of newly affected locations. Proxies calibration affects the arrival times agreement across different models, and the observed topological and traffic discrepancies among mobility sources alter the resulting epidemic invasion patterns. Results also suggest that proxies perform differently in approximating commuting patterns for disease spread at different resolution scales, with the radiation model showing higher accuracy than mobile phone data when the seed is central in the network, the opposite being observed for peripheral locations. Proxies should therefore be chosen in light of the desired accuracy for the epidemic situation under study. '),
(86664, 2014, 'plos', 'De novo design and experimental characterization of ultrashort self-associating peptides', 'Smadbeck, James|Chan, Kiat Hwa|Khoury, George A|Xue, Bo|Robinson, Robert C|Hauser, Charlotte A E|Floudas, Christodoulos A', 'Department of Chemical and Biological Engineering, Princeton University, Princeton, New Jersey, United States of America.|Institute of Bioengineering and Nanotechnology, Singapore, Singapore.|Department of Chemical and Biological Engineering, Princeton University, Princeton, New Jersey, United States of America.|Institute of Molecular and Cell Biology, A*STAR (Agency of Science, Technology and Research), Biopolis, Singapore, Singapore.|Institute of Molecular and Cell Biology, A*STAR (Agency of Science, Technology and Research), Biopolis, Singapore, Singapore.|Institute of Bioengineering and Nanotechnology, Singapore, Singapore.|Department of Chemical and Biological Engineering, Princeton University, Princeton, New Jersey, United States of America.', 'Jersey|Singapore|Jersey|Singapore|Singapore|Singapore|Jersey', 0, 'Computational Biology|Crystallography, X-Ray|Hydrogel, Polyethylene Glycol Dimethacrylate|Molecular Dynamics Simulation|Peptides|Protein Aggregates|Protein Multimerization|Viscosity', 'Journal Article', '10.1371/journal.pcbi.1003718', '25010703', 'Self-association is a common phenomenon in biology and one that can have positive and negative impacts, from the construction of the architectural cytoskeleton of cells to the formation of fibrils in amyloid diseases. Understanding the nature and mechanisms of self-association is important for modulating these systems and in creating biologically-inspired materials. Here, we present a two-stage de novo peptide design framework that can generate novel self-associating peptide systems. The first stage uses a simulated multimeric template structure as input into the optimization-based Sequence Selection to generate low potential energy sequences. The second stage is a computational validation procedure that calculates Fold Specificity and/or Approximate Association Affinity (K*association) based on metrics that we have devised for multimeric systems. This framework was applied to the design of self-associating tripeptides using the known self-associating tripeptide, Ac-IVD, as a structural template. Six computationally predicted tripeptides (Ac-LVE, Ac-YYD, Ac-LLE, Ac-YLD, Ac-MYD, Ac-VIE) were chosen for experimental validation in order to illustrate the self-association outcomes predicted by the three metrics. Self-association and electron microscopy studies revealed that Ac-LLE formed bead-like microstructures, Ac-LVE and Ac-YYD formed fibrillar aggregates, Ac-VIE and Ac-MYD formed hydrogels, and Ac-YLD crystallized under ambient conditions. An X-ray crystallographic study was carried out on a single crystal of Ac-YLD, which revealed that each molecule adopts a xcexb2-strand conformation that stack together to form parallel xcexb2-sheets. As an additional validation of the approach, the hydrogel-forming sequences of Ac-MYD and Ac-VIE were shuffled. The shuffled sequences were computationally predicted to have lower K*association values and were experimentally verified to not form hydrogels. This illustrates the robustness of the framework in predicting self-associating tripeptides. We expect that this enhanced multimeric de novo peptide design framework will find future application in creating novel self-associating peptides based on unnatural amino acids, and inhibitor peptides of detrimental self-aggregating biological proteins. '),
(86665, 2014, 'plos', 'Electric imaging through evolution, a modeling study of commonalities and differences', 'Pedraja, Federico|Aguilera, Pedro|Caputi, Angel A|Budelli, Ruben', 'Departamento de Biología Celular y Molecular, Facultad de Ciencias, Universidad de la República, Montevideo, Uruguay.|Departamento de Neurociencias Integrativas y Computacionales, Instituto de Investigaciones Biológicas Clemente Estable, Montevideo, Uruguay.|Departamento de Neurociencias Integrativas y Computacionales, Instituto de Investigaciones Biológicas Clemente Estable, Montevideo, Uruguay.|Departamento de Biología Celular y Molecular, Facultad de Ciencias, Universidad de la República, Montevideo, Uruguay.', 'Uruguay|Uruguay|Uruguay|Uruguay', 0, 'Animals|Computational Biology|Electric Organ|Electricity|Gymnotiformes|Models, Biological', 'Journal Article', '10.1371/journal.pcbi.1003722', '25010765', 'Modeling the electric field and images in electric fish contributes to a better understanding of the pre-receptor conditioning of electric images. Although the boundary element method has been very successful for calculating images and fields, complex electric organ discharges pose a challenge for active electroreception modeling. We have previously developed a direct method for calculating electric images which takes into account the structure and physiology of the electric organ as well as the geometry and resistivity of fish tissues. The present article reports a general application of our simulator for studying electric images in electric fish with heterogeneous, extended electric organs. We studied three species of Gymnotiformes, including both wave-type (Apteronotus albifrons) and pulse-type (Gymnotus obscurus and Gymnotus coropinae) fish, with electric organs of different complexity. The results are compared with the African (Gnathonemus petersii) and American (Gymnotus omarorum) electric fish studied previously. We address the following issues: 1) how to calculate equivalent source distributions based on experimental measurements, 2) how the complexity of the electric organ discharge determines the features of the electric field and 3) how the basal field determines the characteristics of electric images. Our findings allow us to generalize the hypothesis (previously posed for G. omarorum) in which the perioral region and the rest of the body play different sensory roles. While the electrosensory fovea appears suitable for exploring objects in detail, the rest of the body is likened to a peripheral retina for detecting the presence and movement of surrounding objects. We discuss the commonalities and differences between species. Compared to African species, American electric fish show a weaker field. This feature, derived from the complexity of distributed electric organs, may endow Gymnotiformes with the ability to emit site-specific signals to be detected in the short range by a conspecific and the possibility to evolve predator avoidance strategies. '),
(86666, 2014, 'plos', 'Characterizing the impact of category uncertainty on human auditory categorization behavior', 'Gifford, Adam M|Cohen, Yale E|Stocker, Alan A', 'Neuroscience Graduate Group, University of Pennsylvania, Philadelphia, Pennsylvania, United States of America.|Neuroscience Graduate Group, University of Pennsylvania, Philadelphia, Pennsylvania, United States of America, Departments of Otorhinolaryngology, Neuroscience, and Bioengineering, University of Pennsylvania, Philadelphia, Pennsylvania, United States of America.|Neuroscience Graduate Group, University of Pennsylvania, Philadelphia, Pennsylvania, United States of America, Departments of Psychology and Electrical and Systems Engineering, University of Pennsylvania, Philadelphia, Pennsylvania, United States of America.', 'United States|United States|United States', 0, 'Acoustic Stimulation|Auditory Perception|Auditory Threshold|Bayes Theorem|Computational Biology|Decision Making|Female|Humans|Learning|Male|Models, Neurological|Task Performance and Analysis', 'Journal Article', '10.1371/journal.pcbi.1003715', '25032683', 'Categorization is an important cognitive process. However, the correct categorization of a stimulus is often challenging because categories can have overlapping boundaries. Whereas perceptual categorization has been extensively studied in vision, the analogous phenomenon in audition has yet to be systematically explored. Here, we test whether and how human subjects learn to use category distributions and prior probabilities, as well as whether subjects employ an optimal decision strategy when making auditory-category decisions. We asked subjects to classify the frequency of a tone burst into one of two overlapping, uniform categories according to the perceived tone frequency. We systematically varied the prior probability of presenting a tone burst with a frequency originating from one versus the other category. Most subjects learned these changes in prior probabilities early in testing and used this information to influence categorization. We also measured each subjects frequency-discrimination thresholds (i.e., their sensory uncertainty levels). We tested each subjects average behavior against variations of a Bayesian model that either led to optimal or sub-optimal decision behavior (i.e. probability matching). In both predicting and fitting each subjects average behavior, we found that probability matching provided a better account of human decision behavior. The model fits confirmed that subjects were able to learn category prior probabilities and approximate forms of the category distributions. Finally, we systematically explored the potential ways that additional noise sources could influence categorization behavior. We found that an optimal decision strategy can produce probability-matching behavior if it utilized non-stationary category distributions and prior probabilities formed over a short stimulus history. Our work extends previous findings into the auditory domain and reformulates the issue of categorization in a manner that can help to interpret the results of previous research within a generative framework. '),
(86667, 2014, 'plos', 'Poisson-like spiking in circuits with probabilistic synapses', 'Moreno-Bote, Rubén', 'Research Unit, Parc Sanitari Sant Joan de Déu and Universitat de Barcelona, Esplugues de Llobregat, Barcelona, Spain, Centro de Investigación Biomédica en Red de Salud Mental (CIBERSAM), Esplugues de Llobregat, Barcelona, Spain.', 'Spain', 30, 'Action Potentials|Cerebral Cortex|Electric Conductivity|Membrane Potentials|Models, Neurological|Models, Statistical|Neurons|Poisson Distribution|Synapses', 'Journal Article', '10.1371/journal.pcbi.1003522', '25032705', 'Neuronal activity in cortex is variable both spontaneously and during stimulation, and it has the remarkable property that it is Poisson-like over broad ranges of firing rates covering from virtually zero to hundreds of spikes per second. The mechanisms underlying cortical-like spiking variability over such a broad continuum of rates are currently unknown. We show that neuronal networks endowed with probabilistic synaptic transmission, a well-documented source of variability in cortex, robustly generate Poisson-like variability over several orders of magnitude in their firing rate without fine-tuning of the network parameters. Other sources of variability, such as random synaptic delays or spike generation jittering, do not lead to Poisson-like variability at high rates because they cannot be sufficiently amplified by recurrent neuronal networks. We also show that probabilistic synapses predict Fano factor constancy of synaptic conductances. Our results suggest that synaptic noise is a robust and sufficient mechanism for the type of variability found in cortex. ');
