INSERT INTO `papers` (`id`, `ano`, `journal`, `titulo`, `autores`, `afiliacao`, `pais`, `citacoes`, `palavra_chave`, `categorias`, `doi`, `pubmed`, `abstract`) VALUES
(87488, 2015, 'plos', 'Identification of High-Impact cis-Regulatory Mutations Using Transcription Factor Specific Random Forest Models', 'Svetlichnyy, Dmitry|Imrichova, Hana|Fiers, Mark|Kalender Atak, Zeynep|Aerts, Stein', 'Laboratory of Computational Biology, KU Leuven Center for Human Genetics, Leuven, Belgium.|Laboratory of Computational Biology, KU Leuven Center for Human Genetics, Leuven, Belgium.|VIB Center for the Biology of Disease, Leuven, Belgium.|Laboratory of Computational Biology, KU Leuven Center for Human Genetics, Leuven, Belgium.|Laboratory of Computational Biology, KU Leuven Center for Human Genetics, Leuven, Belgium.', 'Belgium|Belgium|Belgium|Belgium|Belgium', 0, 'Algorithms|Binding Sites|Computational Biology|Genome|HeLa Cells|Humans|Machine Learning|Models, Statistical|Mutation|Neoplasms|Regulatory Sequences, Nucleic Acid|Transcription Factors', 'Journal Article', '10.1371/journal.pcbi.1004590', '26562774', 'Cancer genomes contain vast amounts of somatic mutations, many of which are passenger mutations not involved in oncogenesis. Whereas driver mutations in protein-coding genes can be distinguished from passenger mutations based on their recurrence, non-coding mutations are usually not recurrent at the same position. Therefore, it is still unclear how to identify cis-regulatory driver mutations, particularly when chromatin data from the same patient is not available, thus relying only on sequence and expression information. Here we use machine-learning methods to predict functional regulatory regions using sequence information alone, and compare the predicted activity of the mutated region with the reference sequence. This way we define the Predicted Regulatory Impact of a Mutation in an Enhancer (PRIME). We find that the recently identified driver mutation in the TAL1 enhancer has a high PRIME score, representing a gain-of-target for MYB, whereas the highly recurrent TERT promoter mutation has a surprisingly low PRIME score. We trained Random Forest models for 45 cancer-related transcription factors, and used these to score variations in the HeLa genome and somatic mutations across more than five hundred cancer genomes. Each model predicts only a small fraction of non-coding mutations with a potential impact on the function of the encompassing regulatory region. Nevertheless, as these few candidate driver mutations are often linked to gains in chromatin activity and gene expression, they may contribute to the oncogenic program by altering the expression levels of specific oncogenes and tumor suppressor genes. '),
(87489, 2015, 'plos', 'Automated and Accurate Estimation of Gene Family Abundance from Shotgun Metagenomes', 'Nayfach, Stephen|Bradley, Patrick H|Wyman, Stacia K|Laurent, Timothy J|Williams, Alex|Eisen, Jonathan A|Pollard, Katherine S|Sharpton, Thomas J', 'Gladstone Institute of Cardiovascular Disease, San Francisco, California, United States of America.|Gladstone Institute of Cardiovascular Disease, San Francisco, California, United States of America.|Gladstone Institute of Cardiovascular Disease, San Francisco, California, United States of America.|Gladstone Institute of Cardiovascular Disease, San Francisco, California, United States of America.|Gladstone Institute of Cardiovascular Disease, San Francisco, California, United States of America.|Department of Evolution and Ecology, Department of Medical Microbiology and Immunology, UC Davis Genome Center, University of California, Davis, Davis, California, United States of America.|Gladstone Institute of Cardiovascular Disease, San Francisco, California, United States of America.|Gladstone Institute of Cardiovascular Disease, San Francisco, California, United States of America.', 'United States|United States|United States|United States|United States|United States|United States|Un', 13, 'Chromosome Mapping|Computer Simulation|Crohn Disease|Genetic Markers|Humans|Metagenome|Metagenomics|Microbiota|Models, Genetic', 'Journal Article', '10.1371/journal.pcbi.1004573', '26565399', 'Shotgun metagenomic DNA sequencing is a widely applicable tool for characterizing the functions that are encoded by microbial communities. Several bioinformatic tools can be used to functionally annotate metagenomes, allowing researchers to draw inferences about the functional potential of the community and to identify putative functional biomarkers. However, little is known about how decisions made during annotation affect the reliability of the results. Here, we use statistical simulations to rigorously assess how to optimize annotation accuracy and speed, given parameters of the input data like read length and library size. We identify best practices in metagenome annotation and use them to guide the development of the Shotgun Metagenome Annotation Pipeline (ShotMAP). ShotMAP is an analytically flexible, end-to-end annotation pipeline that can be implemented either on a local computer or a cloud compute cluster. We use ShotMAP to assess how different annotation databases impact the interpretation of how marine metagenome and metatranscriptome functional capacity changes across seasons. We also apply ShotMAP to data obtained from a clinical microbiome investigation of inflammatory bowel disease. This analysis finds that gut microbiota collected from Crohns disease patients are functionally distinct from gut microbiota collected from either ulcerative colitis patients or healthy controls, with differential abundance of metabolic pathways related to host-microbiome interactions that may serve as putative biomarkers of disease. '),
(87490, 2015, 'plos', 'Improving Collective Estimations Using Resistance to Social Influence', 'Madirolas, Gabriel|de Polavieja, Gonzalo G', 'Instituto Cajal, Consejo Superior de Investigaciones Científicas, Madrid, Spain.|Instituto Cajal, Consejo Superior de Investigaciones Científicas, Madrid, Spain.', 'Spain|Spain', 10, 'Computational Biology|Decision Making|Group Processes|Humans|Interpersonal Relations|Models, Statistical', 'Journal Article', '10.1371/journal.pcbi.1004594', '26565619', 'Groups can make precise collective estimations in cases like the weight of an object or the number of items in a volume. However, in others tasks, for example those requiring memory or mental calculation, subjects often give estimations with large deviations from factual values. Allowing members of the group to communicate their estimations has the additional perverse effect of shifting individual estimations even closer to the biased collective estimation. Here we show that this negative effect of social interactions can be turned into a method to improve collective estimations. We first obtained a statistical model of how humans change their estimation when receiving the estimates made by other individuals. We confirmed using existing experimental data its prediction that individuals use the weighted geometric mean of private and social estimations. We then used this result and the fact that each individual uses a different value of the social weight to devise a method that extracts the subgroups resisting social influence. We found that these subgroups of individuals resisting social influence can make very large improvements in group estimations. This is in contrast to methods using the confidence that each individual declares, for which we find no improvement in group estimations. Also, our proposed method does not need to use historical data to weight individuals by performance. These results show the benefits of using the individual characteristics of the members in a group to better extract collective wisdom. '),
(87491, 2015, 'plos', 'Rich RNA Structure Landscapes Revealed by Mutate-and-Map Analysis', 'Cordero, Pablo|Das, Rhiju', 'Biomedical Informatics Program, Stanford University, Stanford, California, United States of America.|Biomedical Informatics Program, Stanford University, Stanford, California, United States of America.', 'United States|United States', 19, 'Algorithms|Computational Biology|Models, Molecular|Mutation|Nucleic Acid Conformation|RNA|Riboswitch|Sequence Analysis, RNA', 'Journal Article', '10.1371/journal.pcbi.1004473', '26566145', 'Landscapes exhibiting multiple secondary structures arise in natural RNA molecules that modulate gene expression, protein synthesis, and viral infection [corrected]. We report herein that high-throughput chemical experiments can isolate an RNAs multiple alternative secondary structures as they are stabilized by systematic mutagenesis (mutate-and-map, M2) and that a computational algorithm, REEFFIT, enables unbiased reconstruction of these states structures and populations. In an in silico benchmark on non-coding RNAs with complex landscapes, M2-REEFFIT recovers 95% of RNA helices present with at least 25% population while maintaining a low false discovery rate (10%) and conservative error estimates. In experimental benchmarks, M2-REEFFIT recovers the structure landscapes of a 35-nt MedLoop hairpin, a 110-nt 16S rRNA four-way junction with an excited state, a 25-nt bistable hairpin, and a 112-nt three-state adenine riboswitch with its expression platform, molecules whose characterization previously required expert mutational analysis and specialized NMR or chemical mapping experiments. With this validation, M2-REEFFIT enabled tests of whether artificial RNA sequences might exhibit complex landscapes in the absence of explicit design. An artificial flavin mononucleotide riboswitch and a randomly generated RNA sequence are found to interconvert between three or more states, including structures for which there was no design, but that could be stabilized through mutations. These results highlight the likely pervasiveness of rich landscapes with multiple secondary structures in both natural and artificial RNAs and demonstrate an automated chemical/computational route for their empirical characterization.'),
(87492, 2015, 'plos', 'Comparative Analysis of Yeast Metabolic Network Models Highlights Progress, Opportunities for Metabolic Reconstruction', 'Heavner, Benjamin D|Price, Nathan D', 'Institute for Systems Biology, Seattle, Washington, United States of America.|Institute for Systems Biology, Seattle, Washington, United States of America.', 'United States|United States', 17, 'Gene Knockout Techniques|Genome, Fungal|Metabolic Networks and Pathways|Models, Biological|Saccharomyces cerevisiae|Systems Biology', 'Comparative Study', '10.1371/journal.pcbi.1004530', '26566239', 'We have compared 12 genome-scale models of the Saccharomyces cerevisiae metabolic network published since 2003 to evaluate progress in reconstruction of the yeast metabolic network. We compared the genomic coverage, overlap of annotated metabolites, predictive ability for single gene essentiality with a selection of model parameters, and biomass production predictions in simulated nutrient-limited conditions. We have also compared pairwise gene knockout essentiality predictions for 10 of these models. We found that varying approaches to model scope and annotation reflected the involvement of multiple research groups in model development, that single-gene essentiality predictions were affected by simulated medium, objective function, and the reference list of essential genes, and that predictive ability for single-gene essentiality did not correlate well with predictive ability for our reference list of synthetic lethal gene interactions (R = 0.159). We conclude that the reconstruction of the yeast metabolic network is indeed gradually improving through the iterative process of model development, and there remains great opportunity for advancing our understanding of biology through continued efforts to reconstruct the full biochemical reaction network that constitutes yeast metabolism. Additionally, we suggest that there is opportunity for refining the process of deriving a metabolic model from a metabolic network reconstruction to facilitate mechanistic investigation and discovery. This comparative study lays the groundwork for developing improved tools and formalized methods to quantitatively assess metabolic network reconstructions independently of any particular model application, which will facilitate ongoing efforts to advance our understanding of the relationship between genotype and cellular phenotype. '),
(87493, 2015, 'plos', 'Inferring the Clonal Structure of Viral Populations from Time Series Sequencing', 'Chedom, Donatien F|Murcia, Pablo R|Greenman, Chris D', 'The Genome Analysis Centre, Norwich Research Park, Norwich, United Kingdom.|MRC-University of Glasgow Centre for Virus Research, United Kingdom.|The Genome Analysis Centre, Norwich Research Park, Norwich, United Kingdom.', 'United Kingdom|United Kingdom|United Kingdom', 0, 'Algorithms|Computational Biology|Evolution, Molecular|High-Throughput Nucleotide Sequencing|Models, Genetic|Mutation|Phylogeny|Polymerase Chain Reaction|RNA Viruses|RNA, Viral|Sequence Analysis, RNA', 'Journal Article', '10.1371/journal.pcbi.1004344', '26571026', 'RNA virus populations will undergo processes of mutation and selection resulting in a mixed population of viral particles. High throughput sequencing of a viral population subsequently contains a mixed signal of the underlying clones. We would like to identify the underlying evolutionary structures. We utilize two sources of information to attempt this, within segment linkage information, and mutation prevalence. We demonstrate that clone haplotypes, their prevalence, and maximum parsimony reticulate evolutionary structures can be identified, although the solutions may not be unique, even for complete sets of information. This is applied to a chain of influenza infection, where we infer evolutionary structures, including reassortment, and demonstrate some of the difficulties of interpretation that arise from deep sequencing due to artifacts such as template switching during PCR amplification. '),
(87494, 2015, 'plos', 'Beyond the E-Value: Stratified Statistics for Protein Domain Prediction', 'Ochoa, Alejandro|Storey, John D|Llinás, Manuel|Singh, Mona', 'Department of Molecular Biology, Princeton University, Princeton, New Jersey, United States of America.|Department of Molecular Biology, Princeton University, Princeton, New Jersey, United States of America.|Department of Biochemistry and Molecular Biology, and the Huck Institutes of the Life Sciences, Pennsylvania State University, University Park, Pennsylvania, United States of America.|Lewis-Sigler Institute for Integrative Genomics, Princeton University, Princeton, New Jersey, United States of America.', 'Jersey|Jersey|United States|Jersey', 10, 'Algorithms|Computational Biology|Databases, Protein|Models, Statistical|Protein Structure, Tertiary|Proteins', 'Journal Article', '10.1371/journal.pcbi.1004509', '26575353', 'E-values have been the dominant statistic for protein sequence analysis for the past two decades: from identifying statistically significant local sequence alignments to evaluating matches to hidden Markov models describing protein domain families. Here we formally show that for stratified multiple hypothesis testing problems-that is, those in which statistical tests can be partitioned naturally-controlling the local False Discovery Rate (lFDR) per stratum, or partition, yields the most predictions across the data at any given threshold on the FDR or E-value over all strata combined. For the important problem of protein domain prediction, a key step in characterizing protein structure, function and evolution, we show that stratifying statistical tests by domain family yields excellent results. We develop the first FDR-estimating algorithms for domain prediction, and evaluate how well thresholds based on q-values, E-values and lFDRs perform in domain prediction using five complementary approaches for estimating empirical FDRs in this context. We show that stratified q-value thresholds substantially outperform E-values. Contradicting our theoretical results, q-values also outperform lFDRs, however, our tests reveal a small but coherent subset of domain families, biased towards models for specific repetitive patterns, for which weaknesses in random sequence models yield notably inaccurate statistical significance measures. Usage of lFDR thresholds outperform q-values for the remaining families, which have as-expected noise, suggesting that further improvements in domain predictions can be achieved with improved modeling of random sequences. Overall, our theoretical and empirical findings suggest that the use of stratified q-values and lFDRs could result in improvements in a host of structured multiple hypothesis testing problems arising in bioinformatics, including genome-wide association studies, orthology prediction, and motif scanning. '),
(87495, 2015, 'plos', 'Random Wiring, Ganglion Cell Mosaics, and the Functional Architecture of the Visual Cortex', 'Schottdorf, Manuel|Keil, Wolfgang|Coppola, David|White, Leonard E|Wolf, Fred', 'Max Planck Institute for Dynamics and Self-Organization, Göttingen, Germany.|Max Planck Institute for Dynamics and Self-Organization, Göttingen, Germany.|Department of Biology, Randolph-Macon College, Ashland, Virginia, United States of America.|Department of Orthopaedic Surgery, Duke Institute for Brain Sciences, Duke University, Durham, North Carolina, United States of America.|Max Planck Institute for Dynamics and Self-Organization, Göttingen, Germany.', 'Germany|Germany|United States|United States|Germany', 6, 'Animals|Computational Biology|Mammals|Models, Neurological|Nerve Net|Retinal Ganglion Cells|Visual Cortex', 'Journal Article', '10.1371/journal.pcbi.1004602', '26575467', 'The architecture of iso-orientation domains in the primary visual cortex (V1) of placental carnivores and primates apparently follows species invariant quantitative laws. Dynamical optimization models assuming that neurons coordinate their stimulus preferences throughout cortical circuits linking millions of cells specifically predict these invariants. This might indicate that V1s intrinsic connectome and its functional architecture adhere to a single optimization principle with high precision and robustness. To validate this hypothesis, it is critical to closely examine the quantitative predictions of alternative candidate theories. Random feedforward wiring within the retino-cortical pathway represents a conceptually appealing alternative to dynamical circuit optimization because random dimension-expanding projections are believed to generically exhibit computationally favorable properties for stimulus representations. Here, we ask whether the quantitative invariants of V1 architecture can be explained as a generic emergent property of random wiring. We generalize and examine the stochastic wiring model proposed by Ringach and coworkers, in which iso-orientation domains in the visual cortex arise through random feedforward connections between semi-regular mosaics of retinal ganglion cells (RGCs) and visual cortical neurons. We derive closed-form expressions for cortical receptive fields and domain layouts predicted by the model for perfectly hexagonal RGC mosaics. Including spatial disorder in the RGC positions considerably changes the domain layout properties as a function of disorder parameters such as position scatter and its correlations across the retina. However, independent of parameter choice, we find that the model predictions substantially deviate from the layout laws of iso-orientation domains observed experimentally. Considering random wiring with the currently most realistic model of RGC mosaic layouts, a pairwise interacting point process, the predicted layouts remain distinct from experimental observations and resemble Gaussian random fields. We conclude that V1 layout invariants are specific quantitative signatures of visual cortical optimization, which cannot be explained by generic random feedforward-wiring models. '),
(87496, 2015, 'plos', 'SAAS-CNV: A Joint Segmentation Approach on Aggregated and Allele Specific Signals for the Identification of Somatic Copy Number Alterations with Next-Generation Sequencing Data', 'Zhang, Zhongyang|Hao, Ke', 'Department of Genetics and Genomic Sciences, Icahn School of Medicine at Mount Sinai, New York, New York, United States of America.|Department of Genetics and Genomic Sciences, Icahn School of Medicine at Mount Sinai, New York, New York, United States of America.', 'United States|United States', 12, 'Algorithms|Computational Biology|DNA Copy Number Variations|Databases, Genetic|High-Throughput Nucleotide Sequencing|Humans|Neoplasms|Sequence Analysis, DNA', 'Journal Article', '10.1371/journal.pcbi.1004618', '26583378', 'Cancer genomes exhibit profound somatic copy number alterations (SCNAs). Studying tumor SCNAs using massively parallel sequencing provides unprecedented resolution and meanwhile gives rise to new challenges in data analysis, complicated by tumor aneuploidy and heterogeneity as well as normal cell contamination. While the majority of read depth based methods utilize total sequencing depth alone for SCNA inference, the allele specific signals are undervalued. We proposed a joint segmentation and inference approach using both signals to meet some of the challenges. Our method consists of four major steps: 1) extracting read depth supporting reference and alternative alleles at each SNP/Indel locus and comparing the total read depth and alternative allele proportion between tumor and matched normal sample, 2) performing joint segmentation on the two signal dimensions, 3) correcting the copy number baseline from which the SCNA state is determined, 4) calling SCNA state for each segment based on both signal dimensions. The method is applicable to whole exome/genome sequencing (WES/WGS) as well as SNP array data in a tumor-control study. We applied the method to a dataset containing no SCNAs to test the specificity, created by pairing sequencing replicates of a single HapMap sample as normal/tumor pairs, as well as a large-scale WGS dataset consisting of 88 liver tumors along with adjacent normal tissues. Compared with representative methods, our method demonstrated improved accuracy, scalability to large cancer studies, capability in handling both sequencing and SNP array data, and the potential to improve the estimation of tumor ploidy and purity. '),
(87497, 2015, 'plos', 'A Bio-inspired Collision Avoidance Model Based on Spatial Information Derived from Motion Detectors Leads to Common Routes', 'Bertrand, Olivier J N|Lindemann, Jens P|Egelhaaf, Martin', 'Neurobiologie & CITEC, Bielefeld University, Bielefeld, Germany.|Neurobiologie & CITEC, Bielefeld University, Bielefeld, Germany.|Neurobiologie & CITEC, Bielefeld University, Bielefeld, Germany.', 'Germany|Germany|Germany', 18, 'Algorithms|Animals|Computational Biology|Computer Simulation|Flight, Animal|Insecta|Models, Biological|Motion Perception', 'Journal Article', '10.1371/journal.pcbi.1004339', '26583771', 'Avoiding collisions is one of the most basic needs of any mobile agent, both biological and technical, when searching around or aiming toward a goal. We propose a model of collision avoidance inspired by behavioral experiments on insects and by properties of optic flow on a spherical eye experienced during translation, and test the interaction of this model with goal-driven behavior. Insects, such as flies and bees, actively separate the rotational and translational optic flow components via behavior, i.e. by employing a saccadic strategy of flight and gaze control. Optic flow experienced during translation, i.e. during intersaccadic phases, contains information on the depth-structure of the environment, but this information is entangled with that on self-motion. Here, we propose a simple model to extract the depth structure from translational optic flow by using local properties of a spherical eye. On this basis, a motion direction of the agent is computed that ensures collision avoidance. Flying insects are thought to measure optic flow by correlation-type elementary motion detectors. Their responses depend, in addition to velocity, on the texture and contrast of objects and, thus, do not measure the velocity of objects veridically. Therefore, we initially used geometrically determined optic flow as input to a collision avoidance algorithm to show that depth information inferred from optic flow is sufficient to account for collision avoidance under closed-loop conditions. Then, the collision avoidance algorithm was tested with bio-inspired correlation-type elementary motion detectors in its input. Even then, the algorithm led successfully to collision avoidance and, in addition, replicated the characteristics of collision avoidance behavior of insects. Finally, the collision avoidance algorithm was combined with a goal direction and tested in cluttered environments. The simulated agent then showed goal-directed behavior reminiscent of components of the navigation behavior of insects. '),
(87498, 2015, 'plos', 'Broadband Bioinformatics Skills Transfer with the Knowledge Transfer Programme (KTP): Educational Model for Upliftment and Sustainable Development', 'Chimusa, Emile R|Mbiyavanga, Mamana|Masilela, Velaphi|Kumuthini, Judit', 'Computational Biology Group, Department of Integrative Biomedical Sciences, Institute of Infectious Disease and Molecular Medicine, University of Cape Town, Cape Town, South Africa.|Centre for Proteomic and Genomic Research, Cape Town, South Africa.|Centre for Proteomic and Genomic Research, Cape Town, South Africa.|Centre for Proteomic and Genomic Research, Cape Town, South Africa.', 'South Africa|South Africa|South Africa|South Africa', 5, 'Africa|Computational Biology|Conservation of Natural Resources|Humans|Internet|Models, Educational', 'Journal Article', '10.1371/journal.pcbi.1004512', '26583922', 'A shortage of practical skills and relevant expertise is possibly the primary obstacle to social upliftment and sustainable development in Africa. The omics fields, especially genomics, are increasingly dependent on the effective interpretation of large and complex sets of data. Despite abundant natural resources and population sizes comparable with many first-world countries from which talent could be drawn, countries in Africa still lag far behind the rest of the world in terms of specialized skills development. Moreover, there are serious concerns about disparities between countries within the continent. The multidisciplinary nature of the bioinformatics field, coupled with rare and depleting expertise, is a critical problem for the advancement of bioinformatics in Africa. We propose a formalized matchmaking system, which is aimed at reversing this trend, by introducing the Knowledge Transfer Programme (KTP). Instead of individual researchers travelling to other labs to learn, researchers with desirable skills are invited to join African research groups for six weeks to six months. Visiting researchers or trainers will pass on their expertise to multiple people simultaneously in their local environments, thus increasing the efficiency of knowledge transference. In return, visiting researchers have the opportunity to develop professional contacts, gain industry work experience, work with novel datasets, and strengthen and support their ongoing research. The KTP develops a network with a centralized hub through which groups and individuals are put into contact with one another and exchanges are facilitated by connecting both parties with potential funding sources. This is part of the PLOS Computational Biology Education collection. '),
(87499, 2015, 'plos', 'Untangling Brain-Wide Dynamics in Consciousness by Cross-Embedding', 'Tajima, Satohiro|Yanagawa, Toru|Fujii, Naotaka|Toyoizumi, Taro', 'RIKEN Brain Science Institute, Hirosawa, Wako, Saitama, Japan.|RIKEN Brain Science Institute, Hirosawa, Wako, Saitama, Japan.|RIKEN Brain Science Institute, Hirosawa, Wako, Saitama, Japan.|RIKEN Brain Science Institute, Hirosawa, Wako, Saitama, Japan.', 'Japan|Japan|Japan|Japan', 30, 'Algorithms|Animals|Brain|Computational Biology|Consciousness|Electroencephalography|Macaca|Wakefulness', 'Journal Article', '10.1371/journal.pcbi.1004537', '26584045', 'Brain-wide interactions generating complex neural dynamics are considered crucial for emergent cognitive functions. However, the irreducible nature of nonlinear and high-dimensional dynamical interactions challenges conventional reductionist approaches. We introduce a model-free method, based on embedding theorems in nonlinear state-space reconstruction, that permits a simultaneous characterization of complexity in local dynamics, directed interactions between brain areas, and how the complexity is produced by the interactions. We demonstrate this method in large-scale electrophysiological recordings from awake and anesthetized monkeys. The cross-embedding method captures structured interaction underlying cortex-wide dynamics that may be missed by conventional correlation-based analysis, demonstrating a critical role of time-series analysis in characterizing brain state. The method reveals a consciousness-related hierarchy of cortical areas, where dynamical complexity increases along with cross-area information flow. These findings demonstrate the advantages of the cross-embedding method in deciphering large-scale and heterogeneous neuronal systems, suggesting a crucial contribution by sensory-frontoparietal interactions to the emergence of complex brain dynamics during consciousness. '),
(87500, 2015, 'plos', 'Regulation of Early Steps of GPVI Signal Transduction by Phosphatases: A Systems Biology Approach', 'Dunster, Joanne L|Mazet, Francoise|Fry, Michael J|Gibbins, Jonathan M|Tindall, Marcus J', 'Department of Mathematics and Statistics, University of Reading, Reading, Berkshire, United Kingdom.|Institute for Cardiovascular and Metabolic Research and School of Biological Sciences, University of Reading, Reading, Berkshire, United Kingdom.|Institute for Cardiovascular and Metabolic Research and School of Biological Sciences, University of Reading, Reading, Berkshire, United Kingdom.|Institute for Cardiovascular and Metabolic Research and School of Biological Sciences, University of Reading, Reading, Berkshire, United Kingdom.|Department of Mathematics and Statistics, University of Reading, Reading, Berkshire, United Kingdom.', 'United Kingdom|United Kingdom|United Kingdom|United Kingdom|United Kingdom', 17, 'Blood Platelets|Humans|Phosphoric Monoester Hydrolases|Platelet Activation|Platelet Membrane Glycoproteins|Signal Transduction|Systems Biology', 'Journal Article', '10.1371/journal.pcbi.1004589', '26584182', 'We present a data-driven mathematical model of a key initiating step in platelet activation, a central process in the prevention of bleeding following Injury. In vascular disease, this process is activated inappropriately and causes thrombosis, heart attacks and stroke. The collagen receptor GPVI is the primary trigger for platelet activation at sites of injury. Understanding the complex molecular mechanisms initiated by this receptor is important for development of more effective antithrombotic medicines. In this work we developed a series of nonlinear ordinary differential equation models that are direct representations of biological hypotheses surrounding the initial steps in GPVI-stimulated signal transduction. At each stage model simulations were compared to our own quantitative, high-temporal experimental data that guides further experimental design, data collection and model refinement. Much is known about the linear forward reactions within platelet signalling pathways but knowledge of the roles of putative reverse reactions are poorly understood. An initial model, that includes a simple constitutively active phosphatase, was unable to explain experimental data. Model revisions, incorporating a complex pathway of interactions (and specifically the phosphatase TULA-2), provided a good description of the experimental data both based on observations of phosphorylation in samples from one donor and in those of a wider population. Our model was used to investigate the levels of proteins involved in regulating the pathway and the effect of low GPVI levels that have been associated with disease. Results indicate a clear separation in healthy and GPVI deficient states in respect of the signalling cascade dynamics associated with Syk tyrosine phosphorylation and activation. Our approach reveals the central importance of this negative feedback pathway that results in the temporal regulation of a specific class of protein tyrosine phosphatases in controlling the rate, and therefore extent, of GPVI-stimulated platelet activation. '),
(87501, 2015, 'plos', 'Learning of Chunking Sequences in Cognition and Behavior', 'Fonollosa, Jordi|Neftci, Emre|Rabinovich, Mikhail', 'Biocircuits Institute, University of California, San Diego, La Jolla, California, United States of America.|Biocircuits Institute, University of California, San Diego, La Jolla, California, United States of America.|Biocircuits Institute, University of California, San Diego, La Jolla, California, United States of America.', 'United States|United States|United States', 16, 'Algorithms|Cognition|Computational Biology|Computer Simulation|Humans|Learning|Mental Recall|Models, Neurological', 'Journal Article', '10.1371/journal.pcbi.1004592', '26584306', 'We often learn and recall long sequences in smaller segments, such as a phone number 858 534 22 30 memorized as four segments. Behavioral experiments suggest that humans and some animals employ this strategy of breaking down cognitive or behavioral sequences into chunks in a wide variety of tasks, but the dynamical principles of how this is achieved remains unknown. Here, we study the temporal dynamics of chunking for learning cognitive sequences in a chunking representation using a dynamical model of competing modes arranged to evoke hierarchical Winnerless Competition (WLC) dynamics. Sequential memory is represented as trajectories along a chain of metastable fixed points at each level of the hierarchy, and bistable Hebbian dynamics enables the learning of such trajectories in an unsupervised fashion. Using computer simulations, we demonstrate the learning of a chunking representation of sequences and their robust recall. During learning, the dynamics associates a set of modes to each information-carrying item in the sequence and encodes their relative order. During recall, hierarchical WLC guarantees the robustness of the sequence order when the sequence is not too long. The resulting patterns of activities share several features observed in behavioral experiments, such as the pauses between boundaries of chunks, their size and their duration. Failures in learning chunking sequences provide new insights into the dynamical causes of neurological disorders such as Parkinsons disease and Schizophrenia. '),
(87502, 2015, 'plos', 'Differences in Visual-Spatial Input May Underlie Different Compression Properties of Firing Fields for Grid Cell Modules in Medial Entorhinal Cortex', 'Raudies, Florian|Hasselmo, Michael E', 'Center for Systems Neuroscience and Department of Psychological and Brain Sciences, Boston University, Boston, Massachusetts, United States of America.|Center for Systems Neuroscience and Department of Psychological and Brain Sciences, Boston University, Boston, Massachusetts, United States of America.', 'United States|United States', 15, 'Action Potentials|Animals|Computational Biology|Entorhinal Cortex|Hippocampus|Models, Neurological|Rats|Spatial Navigation|Visual Cortex', 'Journal Article', '10.1371/journal.pcbi.1004596', '26584432', 'Firing fields of grid cells in medial entorhinal cortex show compression or expansion after manipulations of the location of environmental barriers. This compression or expansion could be selective for individual grid cell modules with particular properties of spatial scaling. We present a model for differences in the response of modules to barrier location that arise from different mechanisms for the influence of visual features on the computation of location that drives grid cell firing patterns. These differences could arise from differences in the position of visual features within the visual field. When location was computed from the movement of visual features on the ground plane (optic flow) in the ventral visual field, this resulted in grid cell spatial firing that was not sensitive to barrier location in modules modeled with small spacing between grid cell firing fields. In contrast, when location was computed from static visual features on walls of barriers, i.e. in the more dorsal visual field, this resulted in grid cell spatial firing that compressed or expanded based on the barrier locations in modules modeled with large spacing between grid cell firing fields. This indicates that different grid cell modules might have differential properties for computing location based on visual cues, or the spatial radius of sensitivity to visual cues might differ between modules. '),
(87503, 2015, 'plos', 'Parsimony, Exhaustivity and Balanced Detection in Neocortex', 'Romagnoni, Alberto|Ribot, Jérôme|Bennequin, Daniel|Touboul, Jonathan', 'Mathematical Neuroscience Team, CIRB-Collège de France (CNRS UMR 7241, INSERM U1050, Labex MEMOLIFE), PSL, Paris, France.|Mathematical Neuroscience Team, CIRB-Collège de France (CNRS UMR 7241, INSERM U1050, Labex MEMOLIFE), PSL, Paris, France.|Géométrie et dynamique, Université Paris Diderot (Paris VII), Paris, France.|Mathematical Neuroscience Team, CIRB-Collège de France (CNRS UMR 7241, INSERM U1050, Labex MEMOLIFE), PSL, Paris, France.', 'France|France|France|France', 3, 'Algorithms|Animals|Cats|Computational Biology|Neocortex|Optical Imaging|Photic Stimulation|Signal Processing, Computer-Assisted|Visual Cortex', 'Journal Article', '10.1371/journal.pcbi.1004623', '26587664', 'The layout of sensory brain areas is thought to subtend perception. The principles shaping these architectures and their role in information processing are still poorly understood. We investigate mathematically and computationally the representation of orientation and spatial frequency in cat primary visual cortex. We prove that two natural principles, local exhaustivity and parsimony of representation, would constrain the orientation and spatial frequency maps to display a very specific pinwheel-dipole singularity. This is particularly interesting since recent experimental evidences show a dipolar structures of the spatial frequency map co-localized with pinwheels in cat. These structures have important properties on information processing capabilities. In particular, we show using a computational model of visual information processing that this architecture allows a trade-off in the local detection of orientation and spatial frequency, but this property occurs for spatial frequency selectivity sharper than reported in the literature. We validated this sharpening on high-resolution optical imaging experimental data. These results shed new light on the principles at play in the emergence of functional architecture of cortical maps, as well as their potential role in processing information. '),
(87504, 2015, 'plos', 'Quantifying Stochastic Noise in Cultured Circadian Reporter Cells', 'St John, Peter C|Doyle, Francis J', 'Department of Chemical Engineering, University of California, Santa Barbara, Santa Barbara, California, United States of America.|Department of Chemical Engineering, University of California, Santa Barbara, Santa Barbara, California, United States of America.', 'United States|United States', 7, 'Animals|Cells, Cultured|Circadian Rhythm|Computational Biology|Computer Simulation|Gene Knockdown Techniques|Mice|Models, Biological|RNA Interference|RNA, Small Interfering|Stochastic Processes', 'Journal Article', '10.1371/journal.pcbi.1004451', '26588000', 'Stochastic noise at the cellular level has been shown to play a fundamental role in circadian oscillations, influencing how groups of cells entrain to external cues and likely serving as the mechanism by which cell-autonomous rhythms are generated. Despite this importance, few studies have investigated how clock perturbations affect stochastic noise-even as increasing numbers of high-throughput screens categorize how gene knockdowns or small molecules can change clock period and amplitude. This absence is likely due to the difficulty associated with measuring cell-autonomous stochastic noise directly, which currently requires the careful collection and processing of single-cell data. In this study, we show that the damping rate of population-level bioluminescence recordings can serve as an accurate measure of overall stochastic noise, and one that can be applied to future and existing high-throughput circadian screens. Using cell-autonomous fibroblast data, we first show directly that higher noise at the single-cell results in faster damping at the population level. Next, we show that the damping rate of cultured cells can be changed in a dose-dependent fashion by small molecule modulators, and confirm that such a change can be explained by single-cell noise using a mathematical model. We further demonstrate the insights that can be gained by applying our method to a genome-wide siRNA screen, revealing that stochastic noise is altered independently from period, amplitude, and phase. Finally, we hypothesize that the unperturbed clock is highly optimized for robust rhythms, as very few gene perturbations are capable of simultaneously increasing amplitude and lowering stochastic noise. Ultimately, this study demonstrates the importance of considering the effect of circadian perturbations on stochastic noise, particularly with regard to the development of small-molecule circadian therapeutics. '),
(87505, 2015, 'plos', 'Stochastic Regulation of her1/7 Gene Expression Is the Source of Noise in the Zebrafish Somite Clock Counteracted by Notch Signalling', 'Jenkins, Robert P|Hanisch, Anja|Soza-Ried, Cristian|Sahai, Erik|Lewis, Julian', 'Tumour Cell Biology Laboratory, The Francis Crick Institute Lincolns Inn Fields Laboratory, London, United Kingdom.|Vertebrate Development Laboratory, The Francis Crick Institute Lincolns Inn Fields Laboratory, London, United Kingdom.|Vertebrate Development Laboratory, The Francis Crick Institute Lincolns Inn Fields Laboratory, London, United Kingdom.|Tumour Cell Biology Laboratory, The Francis Crick Institute Lincolns Inn Fields Laboratory, London, United Kingdom.|Vertebrate Development Laboratory, The Francis Crick Institute Lincolns Inn Fields Laboratory, London, United Kingdom.', 'United Kingdom|United Kingdom|United Kingdom|United Kingdom|United Kingdom', 8, 'Animals|Basic Helix-Loop-Helix Transcription Factors|Biological Clocks|Computational Biology|Gene Expression Regulation, Developmental|Receptors, Notch|Somites|Transcription Factors|Zebrafish|Zebrafish Proteins', 'Journal Article', '10.1371/journal.pcbi.1004459', '26588097', 'The somite segmentation clock is a robust oscillator used to generate regularly-sized segments during early vertebrate embryogenesis. It has been proposed that the clocks of neighbouring cells are synchronised via inter-cellular Notch signalling, in order to overcome the effects of noisy gene expression. When Notch-dependent communication between cells fails, the clocks of individual cells operate erratically and lose synchrony over a period of about 5 to 8 segmentation clock cycles (2-3 hours in the zebrafish). Here, we quantitatively investigate the effects of stochasticity on cell synchrony, using mathematical modelling, to investigate the likely source of such noise. We find that variations in the transcription, translation and degradation rate of key Notch signalling regulators do not explain the in vivo kinetics of desynchronisation. Rather, the analysis predicts that clock desynchronisation, in the absence of Notch signalling, is due to the stochastic dissociation of Her1/7 repressor proteins from the oscillating her1/7 autorepressed target genes. Using in situ hybridisation to visualise sites of active her1 transcription, we measure an average delay of approximately three minutes between the times of activation of the two her1 alleles in a cell. Our model shows that such a delay is sufficient to explain the in vivo rate of clock desynchronisation in Notch pathway mutant embryos and also that Notch-mediated synchronisation is sufficient to overcome this stochastic variation. This suggests that the stochastic nature of repressor/DNA dissociation is the major source of noise in the segmentation clock. '),
(87506, 2015, 'plos', 'Finding New Order in Biological Functions from the Network Structure of Gene Annotations', 'Glass, Kimberly|Girvan, Michelle', 'Department of Biostatistics and Computational Biology, Dana-Farber Cancer Institute and Harvard T. H. Chan School of Public Health, Boston, Massachusetts, United States of America.|Physics Department, University of Maryland, College Park, Maryland, United States of America.', 'United States|United States', 0, 'Algorithms|Computational Biology|Genes|Humans|Models, Genetic|Molecular Sequence Annotation|Neoplasms', 'Journal Article', '10.1371/journal.pcbi.1004565', '26588252', 'The Gene Ontology (GO) provides biologists with a controlled terminology that describes how genes are associated with functions and how functional terms are related to one another. These term-term relationships encode how scientists conceive the organization of biological functions, and they take the form of a directed acyclic graph (DAG). Here, we propose that the network structure of gene-term annotations made using GO can be employed to establish an alternative approach for grouping functional terms that captures intrinsic functional relationships that are not evident in the hierarchical structure established in the GO DAG. Instead of relying on an externally defined organization for biological functions, our approach connects biological functions together if they are performed by the same genes, as indicated in a compendium of gene annotation data from numerous different sources. We show that grouping terms by this alternate scheme provides a new framework with which to describe and predict the functions of experimentally identified sets of genes. '),
(87507, 2015, 'plos', 'A Dual Model for Prioritizing Cancer Mutations in the Non-coding Genome Based on Germline and Somatic Events', 'Li, Jia|Poursat, Marie-Anne|Drubay, Damien|Motz, Arnaud|Saci, Zohra|Morillon, Antonin|Michiels, Stefan|Gautheret, Daniel', 'Institute for Integrative Biology of the Cell, CNRS, CEA, Université Paris-Sud, Gif-sur-Yvette, France.|Laboratoire de Mathématique, Université Paris-Sud, Paris, France.|Service de Biostatistique et dEpidémiologie, Gustave Roussy, Villejuif, France.|Institute for Integrative Biology of the Cell, CNRS, CEA, Université Paris-Sud, Gif-sur-Yvette, France.|RNA, epigenetics and genome fluidity, Institut Curie, PSL Research University, CNRS UMR3244, Université Pierre et Marie Curie, Paris, France.|RNA, epigenetics and genome fluidity, Institut Curie, PSL Research University, CNRS UMR3244, Université Pierre et Marie Curie, Paris, France.|Service de Biostatistique et dEpidémiologie, Gustave Roussy, Villejuif, France.|Institute for Integrative Biology of the Cell, CNRS, CEA, Université Paris-Sud, Gif-sur-Yvette, France.', 'France|France|France|France|France|France|France|France', 14, 'Computational Biology|Genome, Human|Humans|Models, Genetic|Mutation|Neoplasms|RNA, Untranslated|Sequence Analysis, DNA', 'Journal Article', '10.1371/journal.pcbi.1004583', '26588488', 'We address here the issue of prioritizing non-coding mutations in the tumoral genome. To this aim, we created two independent computational models. The first (germline) model estimates purifying selection based on population SNP data. The second (somatic) model estimates tumor mutation density based on whole genome tumor sequencing. We show that each model reflects a different set of constraints acting either on the normal or tumor genome, and we identify the specific genome features that most contribute to these constraints. Importantly, we show that the somatic mutation model carries independent functional information that can be used to narrow down the non-coding regions that may be relevant to cancer progression. On this basis, we identify positions in non-coding RNAs and the non-coding parts of mRNAs that are both under purifying selection in the germline and protected from mutation in tumors, thus introducing a new strategy for future detection of cancer driver elements in the expressed non-coding genome. ');
INSERT INTO `papers` (`id`, `ano`, `journal`, `titulo`, `autores`, `afiliacao`, `pais`, `citacoes`, `palavra_chave`, `categorias`, `doi`, `pubmed`, `abstract`) VALUES
(87508, 2015, 'plos', 'Computational Model of MicroRNA Control of HIF-VEGF Pathway: Insights into the Pathophysiology of Ischemic Vascular Disease and Cancer', 'Zhao, Chen|Popel, Aleksander S', 'Department of Biomedical Engineering, School of Medicine, Johns Hopkins University, Baltimore, Maryland, United States of America.|Department of Biomedical Engineering, School of Medicine, Johns Hopkins University, Baltimore, Maryland, United States of America.', 'United States|United States', 18, 'Cell Hypoxia|Cell Line, Tumor|Computational Biology|Computer Simulation|Humans|Hypoxia-Inducible Factor 1, alpha Subunit|MicroRNAs|Models, Biological|Neoplasms|Peripheral Arterial Disease|Reproducibility of Results|Signal Transduction|Vascular Endothelial Growth Factor A', 'Journal Article', '10.1371/journal.pcbi.1004612', '26588727', 'HRMs (hypoxia-responsive miRNAs) are a specific group of microRNAs that are regulated by hypoxia. Recent studies revealed that several HRMs including let-7 family miRNAs were highly induced in response to HIF (hypoxia-inducible factor) stabilization in hypoxia, and they potently participated in angiogenesis by targeting AGO1 (argonaute 1) and upregulating VEGF (vascular endothelial growth factor). Here we constructed a novel computational model of microRNA control of HIF-VEGF pathway in endothelial cells to quantitatively investigate the role of HRMs in modulating the cellular adaptation to hypoxia. The model parameters were optimized and the simulations based on these parameters were validated against several published in vitro experimental data. To advance the mechanistic understanding of oxygen sensing in hypoxia, we demonstrated that the rate of HIF-1xcexb1 nuclear import substantially influences its stabilization and the formation of HIF-1 transcription factor complex. We described the biological feedback loops involving let-7 and AGO1 in which the impact of external perturbations were minimized, as a pair of master regulators when low oxygen tension was sensed, they coordinated the critical process of VEGF desuppression in a controlled manner. Prompted by the model-motivated discoveries, we proposed and assessed novel pathway-specific therapeutics that modulate angiogenesis by adjusting VEGF synthesis in tumor and ischemic cardiovascular disease. Through simulations that capture the complex interactions between miRNAs and miRNA-processing molecules, this model explores an innovative perspective about the distinctive yet integrated roles of different miRNAs in angiogenesis, and it will help future research to elucidate the dysregulated miRNA profiles found in cancer and various cardiovascular diseases. '),
(87509, 2015, 'plos', 'Correction: Microbial Forensics: Predicting Phenotypic Characteristics and Environmental Conditions from Large-Scale Gene Expression Profiles', 'PLOS Computational Biology Staff', 'Department of Biomedical Engineering, School of Medicine, Johns Hopkins University, Baltimore, Maryland, United States of America.', 'United States', 1, '-', 'Published Erratum', '10.1371/journal.pcbi.1004617', '26588851', '-'),
(87510, 2015, 'plos', 'A Jump-from-Cavity Pyrophosphate Ion Release Assisted by a Key Lysine Residue in T7 RNA Polymerase Transcription Elongation', 'Da, Lin-Tai|E, Chao|Duan, Baogen|Zhang, Chuanbiao|Zhou, Xin|Yu, Jin', 'Department of Physics and Institute of Molecular Biophysics, Florida State University, Tallahassee, Florida, United States of America.|Beijing Computational Science Research Center, Beijing, China.|Beijing Computational Science Research Center, Beijing, China.|School of Physics, University of the Chinese Academy of Sciences, Beijing, China.|School of Physics, University of the Chinese Academy of Sciences, Beijing, China.|Beijing Computational Science Research Center, Beijing, China.', 'United States|China|China|China|China|China', 0, 'Amino Acid Sequence|Computational Biology|DNA-Directed RNA Polymerases|Diphosphates|Lysine|Molecular Dynamics Simulation|Molecular Sequence Data|Promoter Regions, Genetic|Sequence Alignment|Viral Proteins', 'Journal Article', '10.1371/journal.pcbi.1004624', '26599007', 'Pyrophosphate ion (PPi) release during transcription elongation is a signature step in each nucleotide addition cycle. The kinetics and energetics of the process as well as how it proceeds with substantial conformational changes of the polymerase complex determine the mechano-chemical coupling mechanism of the transcription elongation. Here we investigated detailed dynamics of the PPi release process in a single-subunit RNA polymerase (RNAP) from bacteriophage T7, implementing all-atom molecular dynamics (MD) simulations. We obtained a jump-from-cavity kinetic model of the PPi release utilizing extensive nanosecond MD simulations. We found that the PPi release in T7 RNAP is initiated by the PPi dissociation from two catalytic aspartic acids, followed by a comparatively slow jump-from-cavity activation process. Combining with a number of microsecond long MD simulations, we also found that the activation process is hindered by charged residue associations as well as by local steric and hydrogen bond interactions. On the other hand, the activation is greatly assisted by a highly flexible lysine residue Lys472 that swings its side chain to pull PPi out. The mechanism can apply in general to single subunit RNA and DNA polymerases with similar molecular structures and conserved key residues. Remarkably, the flexible lysine or arginine residue appears to be a universal module that assists the PPi release even in multi-subunit RNAPs with charge facilitated hopping mechanisms. We also noticed that the PPi release is not tightly coupled to opening motions of an O-helix on the fingers domain of T7 RNAP according to the microsecond MD simulations. Our study thus supports the Brownian ratchet scenario of the mechano-chemical coupling in the transcription elongation of the single-subunit polymerase. '),
(87511, 2015, 'plos', 'Computational Modelling of Metastasis Development in Renal Cell Carcinoma', 'Baratchart, Etienne|Benzekry, Sébastien|Bikfalvi, Andreas|Colin, Thierry|Cooley, Lindsay S|Pineau, Raphäel|Ribot, Emeline J|Saut, Olivier|Souleyreau, Wilfried', 'INRIA Bordeaux-Sud-Ouest team MONC, University of Bordeaux, IMB, UMR 5251, CNRS, IMB, UMR 5251, Bordeaux INP, IMB, UMR 5251,Talence, France.|INRIA Bordeaux-Sud-Ouest team MONC, University of Bordeaux, IMB, UMR 5251, CNRS, IMB, UMR 5251, Bordeaux INP, IMB, UMR 5251,Talence, France.|LAMC, INSERM U1029, University of Bordeaux, Pessac, France.|INRIA Bordeaux-Sud-Ouest team MONC, University of Bordeaux, IMB, UMR 5251, CNRS, IMB, UMR 5251, Bordeaux INP, IMB, UMR 5251,Talence, France.|LAMC, INSERM U1029, University of Bordeaux, Pessac, France.|LAMC, INSERM U1029, University of Bordeaux, Pessac, France.|Centre de Résonance Magnétique des Systèmes Biologiques, UMR 5536, CNRS/University of Bordeaux Segalen, Bordeaux, France.|INRIA Bordeaux-Sud-Ouest team MONC, University of Bordeaux, IMB, UMR 5251, CNRS, IMB, UMR 5251, Bordeaux INP, IMB, UMR 5251,Talence, France.|LAMC, INSERM U1029, University of Bordeaux, Pessac, France.', 'France|France|France|France|France|France|France|France|France', 13, 'Animals|Carcinoma, Renal Cell|Computational Biology|Computer Simulation|Female|Kidney Neoplasms|Mice|Models, Biological|Neoplasm Metastasis', 'Journal Article', '10.1371/journal.pcbi.1004626', '26599078', 'The biology of the metastatic colonization process remains a poorly understood phenomenon. To improve our knowledge of its dynamics, we conducted a modelling study based on multi-modal data from an orthotopic murine experimental system of metastatic renal cell carcinoma. The standard theory of metastatic colonization usually assumes that secondary tumours, once established at a distant site, grow independently from each other and from the primary tumour. Using a mathematical model that translates this assumption into equations, we challenged this theory against our data that included: 1) dynamics of primary tumour cells in the kidney and metastatic cells in the lungs, retrieved by green fluorescent protein tracking, and 2) magnetic resonance images (MRI) informing on the number and size of macroscopic lesions. Critically, when calibrated on the growth of the primary tumour and total metastatic burden, the predicted theoretical size distributions were not in agreement with the MRI observations. Moreover, tumour expansion only based on proliferation was not able to explain the volume increase of the metastatic lesions. These findings strongly suggested rejection of the standard theory, demonstrating that the time development of the size distribution of metastases could not be explained by independent growth of metastatic foci. This led us to investigate the effect of spatial interactions between merging metastatic tumours on the dynamics of the global metastatic burden. We derived a mathematical model of spatial tumour growth, confronted it with experimental data of single metastatic tumour growth, and used it to provide insights on the dynamics of multiple tumours growing in close vicinity. Together, our results have implications for theories of the metastatic process and suggest that global dynamics of metastasis development is dependent on spatial interactions between metastatic lesions. '),
(87512, 2015, 'plos', 'Red Queen Processes Drive Positive Selection on Major Histocompatibility Complex (MHC) Genes', 'Ejsmond, Maciej Jan|Radwan, Jacek', 'Institute of Environmental Sciences, Jagiellonian University, Krakxc3xb3w, Poland.|Evolutionary Biology Group, Faculty of Biology, Adam Mickiewicz University, Poznaxc5x84, Poland.', 'Poland|Poland', 24, 'Alleles|Computational Biology|Computer Simulation|Evolution, Molecular|Humans|Major Histocompatibility Complex|Models, Genetic|Mutation|Selection, Genetic', 'Journal Article', '10.1371/journal.pcbi.1004627', '26599213', 'Major Histocompatibility Complex (MHC) genes code for proteins involved in the incitation of the adaptive immune response in vertebrates, which is achieved through binding oligopeptides (antigens) of pathogenic origin. Across vertebrate species, substitutions of amino acids at sites responsible for the specificity of antigen binding (ABS) are positively selected. This is attributed to pathogen-driven balancing selection, which is also thought to maintain the high polymorphism of MHC genes, and to cause the sharing of allelic lineages between species. However, the nature of this selection remains controversial. We used individual-based computer simulations to investigate the roles of two phenomena capable of maintaining MHC polymorphism: heterozygote advantage and host-pathogen arms race (Red Queen process). Our simulations revealed that levels of MHC polymorphism were high and driven mostly by the Red Queen process at a high pathogen mutation rate, but were low and driven mostly by heterozygote advantage when the pathogen mutation rate was low. We found that novel mutations at ABSs are strongly favored by the Red Queen process, but not by heterozygote advantage, regardless of the pathogen mutation rate. However, while the strong advantage of novel alleles increased the allele turnover rate, under a high pathogen mutation rate, allelic lineages persisted for a comparable length of time under Red Queen and under heterozygote advantage. Thus, when pathogens evolve quickly, the Red Queen is capable of explaining both positive selection and long coalescence times, but the tension between the novel allele advantage and persistence of alleles deserves further investigation. '),
(87513, 2015, 'plos', 'Remodeling and Tenacity of Inhibitory Synapses: Relationships with Network Activity and Neighboring Excitatory Synapses', 'Rubinski, Anna|Ziv, Noam E', 'Rappaport Faculty of Medicine, Network Biology Research Laboratories, Technion, Haifa, Israel.|Rappaport Faculty of Medicine, Network Biology Research Laboratories, Technion, Haifa, Israel.', 'Israel|Israel', 14, 'Animals|Cells, Cultured|Computational Biology|Excitatory Postsynaptic Potentials|Hippocampus|Inhibitory Postsynaptic Potentials|Models, Neurological|Nerve Net|Rats', 'Journal Article', '10.1371/journal.pcbi.1004632', '26599330', 'Glutamatergic synapse size remodeling is governed not only by specific activity forms but also by apparently stochastic processes with well-defined statistics. These spontaneous remodeling processes can give rise to skewed and stable synaptic size distributions, underlie scaling of these distributions and drive changes in glutamatergic synapse size configurations. Where inhibitory synapses are concerned, however, little is known on spontaneous remodeling dynamics, their statistics, their activity dependence or their long-term consequences. Here we followed individual inhibitory synapses for days, and analyzed their size remodeling dynamics within the statistical framework previously developed for glutamatergic synapses. Similar to glutamatergic synapses, size distributions of inhibitory synapses were skewed and stable, at the same time, however, sizes of individual synapses changed considerably, leading to gradual changes in synaptic size configurations. The suppression of network activity only transiently affected spontaneous remodeling dynamics, did not affect synaptic size configuration change rates and was not followed by the scaling of inhibitory synapse size distributions. Comparisons with glutamatergic synapses within the same dendrites revealed a degree of coupling between nearby inhibitory and excitatory synapse remodeling, but also revealed that inhibitory synapse size configurations changed at considerably slower rates than those of their glutamatergic neighbors. These findings point to quantitative differences in spontaneous remodeling dynamics of inhibitory and excitatory synapses but also reveal deep qualitative similarities in the processes that control their sizes and govern their remodeling dynamics. '),
(87514, 2015, 'plos', 'A Systematic Bayesian Integration of Epidemiological and Genetic Data', 'Lau, Max S Y|Marion, Glenn|Streftaris, George|Gibson, Gavin', 'Department of Ecology and Evolutionary Biology, Princeton, New Jersey, United States of America.|Biomathematics and Statistics Scotland, Edinburgh, United Kingdom.|Department of Actuarial Mathematics and Statistics, Heriot-Watt University, Edinburgh, United Kingdom.|Department of Actuarial Mathematics and Statistics, Heriot-Watt University, Edinburgh, United Kingdom.', 'Jersey|United Kingdom|United Kingdom|United Kingdom', 29, 'Algorithms|Animals|Bayes Theorem|Computational Biology|Computer Simulation|Databases, Factual|Foot-and-Mouth Disease|Models, Biological|Molecular Epidemiology', 'Journal Article', '10.1371/journal.pcbi.1004633', '26599399', 'Genetic sequence data on pathogens have great potential to inform inference of their transmission dynamics ultimately leading to better disease control. Where genetic change and disease transmission occur on comparable timescales additional information can be inferred via the joint analysis of such genetic sequence data and epidemiological observations based on clinical symptoms and diagnostic tests. Although recently introduced approaches represent substantial progress, for computational reasons they approximate genuine joint inference of disease dynamics and genetic change in the pathogen population, capturing partially the joint epidemiological-evolutionary dynamics. Improved methods are needed to fully integrate such genetic data with epidemiological observations, for achieving a more robust inference of the transmission tree and other key epidemiological parameters such as latent periods. Here, building on current literature, a novel Bayesian framework is proposed that infers simultaneously and explicitly the transmission tree and unobserved transmitted pathogen sequences. Our framework facilitates the use of realistic likelihood functions and enables systematic and genuine joint inference of the epidemiological-evolutionary process from partially observed outbreaks. Using simulated data it is shown that this approach is able to infer accurately joint epidemiological-evolutionary dynamics, even when pathogen sequences and epidemiological data are incomplete, and when sequences are available for only a fraction of exposures. These results also characterise and quantify the value of incomplete and partial sequence data, which has important implications for sampling design, and demonstrate the abilities of the introduced method to identify multiple clusters within an outbreak. The framework is used to analyse an outbreak of foot-and-mouth disease in the UK, enhancing current understanding of its transmission dynamics and evolutionary process. '),
(87515, 2015, 'plos', 'SINCERA: A Pipeline for Single-Cell RNA-Seq Profiling Analysis', 'Guo, Minzhe|Wang, Hui|Potter, S Steven|Whitsett, Jeffrey A|Xu, Yan', 'The Perinatal Institute, Section of Neonatology, Perinatal and Pulmonary Biology, Cincinnati Childrens Hospital Medical Center, Cincinnati, Ohio, United States of America.|The Perinatal Institute, Section of Neonatology, Perinatal and Pulmonary Biology, Cincinnati Childrens Hospital Medical Center, Cincinnati, Ohio, United States of America.|Division of Developmental Biology, Cincinnati Childrens Hospital Medical Center, Cincinnati, Ohio, United States of America.|The Perinatal Institute, Section of Neonatology, Perinatal and Pulmonary Biology, Cincinnati Childrens Hospital Medical Center, Cincinnati, Ohio, United States of America.|The Perinatal Institute, Section of Neonatology, Perinatal and Pulmonary Biology, Cincinnati Childrens Hospital Medical Center, Cincinnati, Ohio, United States of America.', 'United States|United States|United States|United States|United States', 114, 'Animals|Cluster Analysis|Computational Biology|Gene Expression Profiling|High-Throughput Nucleotide Sequencing|Mice|RNA|Sequence Analysis, RNA|Single-Cell Analysis|Software', 'Journal Article', '10.1371/journal.pcbi.1004575', '26600239', 'A major challenge in developmental biology is to understand the genetic and cellular processes/programs driving organ formation and differentiation of the diverse cell types that comprise the embryo. While recent studies using single cell transcriptome analysis illustrate the power to measure and understand cellular heterogeneity in complex biological systems, processing large amounts of RNA-seq data from heterogeneous cell populations creates the need for readily accessible tools for the analysis of single-cell RNA-seq (scRNA-seq) profiles. The present study presents a generally applicable analytic pipeline (SINCERA: a computational pipeline for SINgle CEll RNA-seq profiling Analysis) for processing scRNA-seq data from a whole organ or sorted cells. The pipeline supports the analysis for: 1) the distinction and identification of major cell types, 2) the identification of cell type specific gene signatures, and 3) the determination of driving forces of given cell types. We applied this pipeline to the RNA-seq analysis of single cells isolated from embryonic mouse lung at E16.5. Through the pipeline analysis, we distinguished major cell types of fetal mouse lung, including epithelial, endothelial, smooth muscle, pericyte, and fibroblast-like cell types, and identified cell type specific gene signatures, bioprocesses, and key regulators. SINCERA is implemented in R, licensed under the GNU General Public License v3, and freely available from CCHMC PBGE website, https://research.cchmc.org/pbge/sincera.html. '),
(87516, 2015, 'plos', 'Fluctuation-Driven Neural Dynamics Reproduce Drosophila Locomotor Patterns', 'Maesani, Andrea|Ramdya, Pavan|Cruchet, Steeve|Gustafson, Kyle|Benton, Richard|Floreano, Dario', 'Institute of Microengineering, École Polytechnique Fédérale de Lausanne, Lausanne, Switzerland.|Institute of Microengineering, École Polytechnique Fédérale de Lausanne, Lausanne, Switzerland.|Center for Integrative Genomics, Faculty of Biology and Medicine, University of Lausanne, Lausanne, Switzerland.|The Institute of Bioengineering, School of Life Sciences, École Polytechnique Fédérale de Lausanne, Lausanne, Switzerland.|Center for Integrative Genomics, Faculty of Biology and Medicine, University of Lausanne, Lausanne, Switzerland.|Institute of Microengineering, École Polytechnique Fédérale de Lausanne, Lausanne, Switzerland.', 'Switzerland|Switzerland|Switzerland|Switzerland|Switzerland|Switzerland', 4, 'Animals|Behavior, Animal|Cluster Analysis|Computational Biology|Drosophila melanogaster|Locomotion|Models, Neurological|Neurons|Olfactory Perception', 'Journal Article', '10.1371/journal.pcbi.1004577', '26600381', 'The neural mechanisms determining the timing of even simple actions, such as when to walk or rest, are largely mysterious. One intriguing, but untested, hypothesis posits a role for ongoing activity fluctuations in neurons of central action selection circuits that drive animal behavior from moment to moment. To examine how fluctuating activity can contribute to action timing, we paired high-resolution measurements of freely walking Drosophila melanogaster with data-driven neural network modeling and dynamical systems analysis. We generated fluctuation-driven network models whose outputs-locomotor bouts-matched those measured from sensory-deprived Drosophila. From these models, we identified those that could also reproduce a second, unrelated dataset: the complex time-course of odor-evoked walking for genetically diverse Drosophila strains. Dynamical models that best reproduced both Drosophila basal and odor-evoked locomotor patterns exhibited specific characteristics. First, ongoing fluctuations were required. In a stochastic resonance-like manner, these fluctuations allowed neural activity to escape stable equilibria and to exceed a threshold for locomotion. Second, odor-induced shifts of equilibria in these models caused a depression in locomotor frequency following olfactory stimulation. Our models predict that activity fluctuations in action selection circuits cause behavioral output to more closely match sensory drive and may therefore enhance navigation in complex sensory environments. Together these data reveal how simple neural dynamics, when coupled with activity fluctuations, can give rise to complex patterns of animal behavior. '),
(87517, 2015, 'plos', 'A Model of Drosophila Larva Chemotaxis', 'Davies, Alex|Louis, Matthieu|Webb, Barbara', 'School of Informatics, University of Edinburgh, Edinburgh, United Kingdom.|Centre for Genomic Regulation (CRG), The Barcelona Institute of Science and Technology, Barcelona, Spain.|School of Informatics, University of Edinburgh, Edinburgh, United Kingdom.', 'United Kingdom|Spain|United Kingdom', 13, 'Animals|Behavior, Animal|Chemotaxis|Computational Biology|Drosophila|Larva|Models, Biological|Smell', 'Journal Article', '10.1371/journal.pcbi.1004606', '26600460', 'Detailed observations of larval Drosophila chemotaxis have characterised the relationship between the odour gradient and the runs, head casts and turns made by the animal. We use a computational model to test whether hypothesised sensorimotor control mechanisms are sufficient to account for larval behaviour. The model combines three mechanisms based on simple transformations of the recent history of odour intensity at the head location. The first is an increased probability of terminating runs in response to gradually decreasing concentration, the second an increased probability of terminating head casts in response to rapidly increasing concentration, and the third a biasing of run directions up concentration gradients through modulation of small head casts. We show that this model can be tuned to produce behavioural statistics comparable to those reported for the larva, and that this tuning results in similar chemotaxis performance to the larva. We demonstrate that each mechanism can enable odour approach but the combination of mechanisms is most effective, and investigate how these low-level control mechanisms relate to behavioural measures such as the preference indices used to investigate larval learning behaviour in group assays. '),
(87518, 2015, 'plos', 'VDJtools: Unifying Post-analysis of T Cell Receptor Repertoires', 'Shugay, Mikhail|Bagaev, Dmitriy V|Turchaninova, Maria A|Bolotin, Dmitriy A|Britanova, Olga V|Putintseva, Ekaterina V|Pogorelyy, Mikhail V|Nazarov, Vadim I|Zvyagin, Ivan V|Kirgizova, Vitalina I|Kirgizov, Kirill I|Skorobogatova, Elena V|Chudakov, Dmitriy M', 'Shemyakin-Ovchinnikov Institute of bioorganic chemistry RAS, Moscow, Russia.|Shemyakin-Ovchinnikov Institute of bioorganic chemistry RAS, Moscow, Russia.|Shemyakin-Ovchinnikov Institute of bioorganic chemistry RAS, Moscow, Russia.|Shemyakin-Ovchinnikov Institute of bioorganic chemistry RAS, Moscow, Russia.|Shemyakin-Ovchinnikov Institute of bioorganic chemistry RAS, Moscow, Russia.|Shemyakin-Ovchinnikov Institute of bioorganic chemistry RAS, Moscow, Russia.|Shemyakin-Ovchinnikov Institute of bioorganic chemistry RAS, Moscow, Russia.|Shemyakin-Ovchinnikov Institute of bioorganic chemistry RAS, Moscow, Russia.|Shemyakin-Ovchinnikov Institute of bioorganic chemistry RAS, Moscow, Russia.|Shemyakin-Ovchinnikov Institute of bioorganic chemistry RAS, Moscow, Russia.|Russian Childrens Hospital, Moscow, Russia.|Russian Childrens Hospital, Moscow, Russia.|Shemyakin-Ovchinnikov Institute of bioorganic chemistry RAS, Moscow, Russia.', '-|-|-|-|-|-|-|-|-|-|-|-|-', 152, 'Adolescent|Adult|Child|Cluster Analysis|Computational Biology|Hematopoietic Stem Cell Transplantation|Humans|Multiple Sclerosis|Receptors, Antigen, T-Cell|Sequence Analysis, DNA|Software|Twins|Young Adult', 'Journal Article', '10.1371/journal.pcbi.1004503', '26606115', 'Despite the growing number of immune repertoire sequencing studies, the field still lacks software for analysis and comprehension of this high-dimensional data. Here we report VDJtools, a complementary software suite that solves a wide range of T cell receptor (TCR) repertoires post-analysis tasks, provides a detailed tabular output and publication-ready graphics, and is built on top of a flexible API. Using TCR datasets for a large cohort of unrelated healthy donors, twins, and multiple sclerosis patients we demonstrate that VDJtools greatly facilitates the analysis and leads to sound biological conclusions. VDJtools software and documentation are available at https://github.com/mikessh/vdjtools. '),
(87519, 2015, 'plos', 'Reputation Effects in Public and Private Interactions', 'Ohtsuki, Hisashi|Iwasa, Yoh|Nowak, Martin A', 'Department of Evolutionary Studies of Biosystems, School of Advanced Sciences, SOKENDAI (The Graduate University for Advanced Studies), Hayama, Kanagawa, Japan.|Department of Biology, Faculty of Sciences, Kyushu University, Fukuoka, Japan.|Program for Evolutionary Dynamics, Harvard University, Cambridge, Massachusetts, United States of America.', 'Japan|Japan|United States', 26, 'Computational Biology|Cooperative Behavior|Humans|Interpersonal Relations|Models, Psychological|Observation|Privacy', 'Journal Article', '10.1371/journal.pcbi.1004527', '26606239', 'We study the evolution of cooperation in a model of indirect reciprocity where people interact in public and private situations. Public interactions have a high chance to be observed by others and always affect reputation. Private interactions have a lower chance to be observed and only occasionally affect reputation. We explore all second order social norms and study conditions for evolutionary stability of action rules. We observe the competition between honest and hypocritical strategies. The former cooperate both in public and in private. The later cooperate in public, where many others are watching, but try to get away with defection in private situations. The hypocritical idea is that in private situations it does not pay-off to cooperate, because there is a good chance that nobody will notice it. We find simple and intuitive conditions for the evolution of honest strategies. '),
(87520, 2015, 'plos', 'Towards a Molecular Understanding of the Link between Imatinib Resistance and Kinase Conformational Dynamics', 'Lovera, Silvia|Morando, Maria|Pucheta-Martinez, Encarna|Martinez-Torrecuadrada, Jorge L|Saladino, Giorgio|Gervasio, Francesco L', 'Department of Chemistry, University College London, London, United Kingdom.|Center of Technological Development in Health, Oswaldo Cruz Foundation (Fiocruz), Rio de Janeiro, Brazil.|Department of Chemistry, University College London, London, United Kingdom.|Proteomics Core Unit, Spanish National Cancer Research Centre (CNIO), Madrid, Spain.|Department of Chemistry, University College London, London, United Kingdom.|Department of Chemistry, University College London, London, United Kingdom.', 'United Kingdom|Brazil|United Kingdom|Spain|United Kingdom|United Kingdom', 38, 'Computational Biology|Drug Resistance, Neoplasm|Fusion Proteins, bcr-abl|Humans|Imatinib Mesylate|Leukemia, Myelogenous, Chronic, BCR-ABL Positive|Molecular Dynamics Simulation|Mutagenesis, Site-Directed|Thermodynamics', 'Journal Article', '10.1371/journal.pcbi.1004578', '26606374', 'Due to its inhibition of the Abl kinase domain in the BCR-ABL fusion protein, imatinib is strikingly effective in the initial stage of chronic myeloid leukemia with more than 90% of the patients showing complete remission. However, as in the case of most targeted anti-cancer therapies, the emergence of drug resistance is a serious concern. Several drug-resistant mutations affecting the catalytic domain of Abl and other tyrosine kinases are now known. But, despite their importance and the adverse effect that they have on the prognosis of the cancer patients harboring them, the molecular mechanism of these mutations is still debated. Here by using long molecular dynamics simulations and large-scale free energy calculations complemented by in vitro mutagenesis and microcalorimetry experiments, we model the effect of several widespread drug-resistant mutations of Abl. By comparing the conformational free energy landscape of the mutants with those of the wild-type tyrosine kinases we clarify their mode of action. It involves significant and complex changes in the inactive-to-active dynamics and entropy/enthalpy balance of two functional elements: the activation-loop and the conserved DFG motif. What is more the T315I gatekeeper mutant has a significant impact on the binding mechanism itself and on the binding kinetics. '),
(87521, 2015, 'plos', 'Integrated Modeling of Gene Regulatory and Metabolic Networks in Mycobacterium tuberculosis', 'Ma, Shuyi|Minch, Kyle J|Rustad, Tige R|Hobbs, Samuel|Zhou, Suk-Lin|Sherman, David R|Price, Nathan D', 'Department of Chemical and Biomolecular Engineering, University of Illinois, Urbana-Champaign, Illinois, United States of America.|Center for Infectious Disease Research, formerly Seattle Biomedical Research Institute, Seattle, Washington, United States of America.|Center for Infectious Disease Research, formerly Seattle Biomedical Research Institute, Seattle, Washington, United States of America.|Center for Infectious Disease Research, formerly Seattle Biomedical Research Institute, Seattle, Washington, United States of America.|Institute for Systems Biology, Seattle, Washington, United States of America.|Center for Infectious Disease Research, formerly Seattle Biomedical Research Institute, Seattle, Washington, United States of America.|Department of Chemical and Biomolecular Engineering, University of Illinois, Urbana-Champaign, Illinois, United States of America.', 'United States|United States|United States|United States|United States|United States|United States', 20, 'Gene Regulatory Networks|Genome, Bacterial|Metabolic Networks and Pathways|Models, Biological|Mycobacterium tuberculosis|Systems Biology', 'Journal Article', '10.1371/journal.pcbi.1004543', '26618656', 'Mycobacterium tuberculosis (MTB) is the causative bacterium of tuberculosis, a disease responsible for over a million deaths worldwide annually with a growing number of strains resistant to antibiotics. The development of better therapeutics would greatly benefit from improved understanding of the mechanisms associated with MTB responses to different genetic and environmental perturbations. Therefore, we expanded a genome-scale regulatory-metabolic model for MTB using the Probabilistic Regulation of Metabolism (PROM) framework. Our model, MTBPROM2.0, represents a substantial knowledge base update and extension of simulation capability. We incorporated a recent ChIP-seq based binding network of 2555 interactions linking to 104 transcription factors (TFs) (representing a 3.5-fold expansion of TF coverage). We integrated this expanded regulatory network with a refined genome-scale metabolic model that can correctly predict growth viability over 69 source metabolite conditions and predict metabolic gene essentiality more accurately than the original model. We used MTBPROM2.0 to simulate the metabolic consequences of knocking out and overexpressing each of the 104 TFs in the model. MTBPROM2.0 improves performance of knockout growth defect predictions compared to the original PROM MTB model, and it can successfully predict growth defects associated with TF overexpression. Moreover, condition-specific models of MTBPROM2.0 successfully predicted synergistic growth consequences of overexpressing the TF whiB4 in the presence of two standard anti-TB drugs. MTBPROM2.0 can screen in silico condition-specific transcription factor perturbations to generate putative targets of interest that can help prioritize future experiments for therapeutic development efforts. '),
(87522, 2015, 'plos', 'Multiscale Embedded Gene Co-expression Network Analysis', 'Song, Won-Min|Zhang, Bin', 'Department of Genetics and Genomic Sciences, Icahn Institute of Genomics and Multiscale Biology, Icahn School of Medicine at Mount Sinai, New York, New York, United States of America.|Department of Genetics and Genomic Sciences, Icahn Institute of Genomics and Multiscale Biology, Icahn School of Medicine at Mount Sinai, New York, New York, United States of America.', 'United States|United States', 58, 'Algorithms|Computational Biology|Gene Expression Profiling|Gene Expression Regulation, Neoplastic|Humans|Models, Genetic|Neoplasms|Software', 'Journal Article', '10.1371/journal.pcbi.1004574', '26618778', 'Gene co-expression network analysis has been shown effective in identifying functional co-expressed gene modules associated with complex human diseases. However, existing techniques to construct co-expression networks require some critical prior information such as predefined number of clusters, numerical thresholds for defining co-expression/interaction, or do not naturally reproduce the hallmarks of complex systems such as the scale-free degree distribution of small-worldness. Previously, a graph filtering technique called Planar Maximally Filtered Graph (PMFG) has been applied to many real-world data sets such as financial stock prices and gene expression to extract meaningful and relevant interactions. However, PMFG is not suitable for large-scale genomic data due to several drawbacks, such as the high computation complexity O(|V|3), the presence of false-positives due to the maximal planarity constraint, and the inadequacy of the clustering framework. Here, we developed a new co-expression network analysis framework called Multiscale Embedded Gene Co-expression Network Analysis (MEGENA) by: i) introducing quality control of co-expression similarities, ii) parallelizing embedded network construction, and iii) developing a novel clustering technique to identify multi-scale clustering structures in Planar Filtered Networks (PFNs). We applied MEGENA to a series of simulated data and the gene expression data in breast carcinoma and lung adenocarcinoma from The Cancer Genome Atlas (TCGA). MEGENA showed improved performance over well-established clustering methods and co-expression network construction approaches. MEGENA revealed not only meaningful multi-scale organizations of co-expressed gene clusters but also novel targets in breast carcinoma and lung adenocarcinoma. '),
(87523, 2015, 'plos', 'Inferring the Forces Controlling Metaphase Kinetochore Oscillations by Reverse Engineering System Dynamics', 'Armond, Jonathan W|Harry, Edward F|McAinsh, Andrew D|Burroughs, Nigel J', 'Warwick Systems Biology Centre and Mathematics Institute, University of Warwick, Coventry, United Kingdom.|Molecular Organisation and Assembly in Cells (MOAC) Doctoral Training Centre, University of Warwick, Coventry, United Kingdom.|Mechanochemical Cell Biology Building, Division of Biomedical Cell Biology, Warwick Medical School, University of Warwick, Coventry, United Kingdom.|Warwick Systems Biology Centre and Mathematics Institute, University of Warwick, Coventry, United Kingdom.', 'United Kingdom|United Kingdom|United Kingdom|United Kingdom', 8, 'Algorithms|Biomechanical Phenomena|Computational Biology|HeLa Cells|Humans|Kinetochores|Mitosis|Models, Biological', 'Journal Article', '10.1371/journal.pcbi.1004607', '26618929', 'Kinetochores are multi-protein complexes that mediate the physical coupling of sister chromatids to spindle microtubule bundles (called kinetochore (K)-fibres) from respective poles. These kinetochore-attached K-fibres generate pushing and pulling forces, which combine with polar ejection forces (PEF) and elastic inter-sister chromatin to govern chromosome movements. Classic experiments in meiotic cells using calibrated micro-needles measured an approximate stall force for a chromosome, but methods that allow the systematic determination of forces acting on a kinetochore in living cells are lacking. Here we report the development of mathematical models that can be fitted (reverse engineered) to high-resolution kinetochore tracking data, thereby estimating the model parameters and allowing us to indirectly compute the (relative) force components (K-fibre, spring force and PEF) acting on individual sister kinetochores in vivo. We applied our methodology to thousands of human kinetochore pair trajectories and report distinct signatures in temporal force profiles during directional switches. We found the K-fibre force to be the dominant force throughout oscillations, and the centromeric spring the smallest although it has the strongest directional switching signature. There is also structure throughout the metaphase plate, with a steeper PEF potential well towards the periphery and a concomitant reduction in plate thickness and oscillation amplitude. This data driven reverse engineering approach is sufficiently flexible to allow fitting of more complex mechanistic models, mathematical models of kinetochore dynamics can therefore be thoroughly tested on experimental data for the first time. Future work will now be able to map out how individual proteins contribute to kinetochore-based force generation and sensing. '),
(87524, 2015, 'plos', 'Correction: The Force at the Tip - Modelling Tension and Proliferation in Sprouting Angiogenesis', 'PLOS Computational Biology Staff', 'Warwick Systems Biology Centre and Mathematics Institute, University of Warwick, Coventry, United Kingdom.', 'United Kingdom', 0, '-', 'Published Erratum', '10.1371/journal.pcbi.1004616', '26619080', '-'),
(87525, 2015, 'plos', 'Maximizing Sensory Dynamic Range by Tuning the Cortical State to Criticality', 'Gautam, Shree Hari|Hoang, Thanh T|McClanahan, Kylie|Grady, Stephen K|Shew, Woodrow L', 'Department of Physics, University of Arkansas, Fayetteville, Arkansas, United States of America.|Department of Physics, University of Arkansas, Fayetteville, Arkansas, United States of America.|Department of Physics, University of Arkansas, Fayetteville, Arkansas, United States of America.|Department of Physics, University of Arkansas, Fayetteville, Arkansas, United States of America.|Department of Physics, University of Arkansas, Fayetteville, Arkansas, United States of America.', 'United States|United States|United States|United States|United States', 48, 'Animals|Computer Simulation|Male|Models, Neurological|Nerve Net|Neural Inhibition|Neuronal Plasticity|Rats|Rats, Sprague-Dawley|Sensory Receptor Cells|Sensory Thresholds|Somatosensory Cortex|Touch', 'Journal Article', '10.1371/journal.pcbi.1004576', '26623645', 'Modulation of interactions among neurons can manifest as dramatic changes in the state of population dynamics in cerebral cortex. How such transitions in cortical state impact the information processing performed by cortical circuits is not clear. Here we performed experiments and computational modeling to determine how somatosensory dynamic range depends on cortical state. We used microelectrode arrays to record ongoing and whisker stimulus-evoked population spiking activity in somatosensory cortex of urethane anesthetized rats. We observed a continuum of different cortical states, at one extreme population activity exhibited small scale variability and was weakly correlated, the other extreme had large scale fluctuations and strong correlations. In experiments, shifts along the continuum often occurred naturally, without direct manipulation. In addition, in both the experiment and the model we directly tuned the cortical state by manipulating inhibitory synaptic interactions. Our principal finding was that somatosensory dynamic range was maximized in a specific cortical state, called criticality, near the tipping point midway between the ends of the continuum. The optimal cortical state was uniquely characterized by scale-free ongoing population dynamics and moderate correlations, in line with theoretical predictions about criticality. However, to reproduce our experimental findings, we found that existing theory required modifications which account for activity-dependent depression. In conclusion, our experiments indicate that in vivo sensory dynamic range is maximized near criticality and our model revealed an unanticipated role for activity-dependent depression in this basic principle of cortical function. '),
(87526, 2015, 'plos', 'Automated Learning of Subcellular Variation among Punctate Protein Patterns and a Generative Model of Their Relation to Microtubules', 'Johnson, Gregory R|Li, Jieyue|Shariff, Aabid|Rohde, Gustavo K|Murphy, Robert F', 'Computational Biology Department, Carnegie Mellon University, Pittsburgh, Pennsylvania, United States of America.|Center for Bioimage Informatics, Carnegie Mellon University, Pittsburgh, Pennsylvania, United States of America.|Computational Biology Department, Carnegie Mellon University, Pittsburgh, Pennsylvania, United States of America.|Computational Biology Department, Carnegie Mellon University, Pittsburgh, Pennsylvania, United States of America.|Computational Biology Department, Carnegie Mellon University, Pittsburgh, Pennsylvania, United States of America.', 'United States|United States|United States|United States|United States', 0, 'Cell Line|Databases, Protein|Humans|Intracellular Space|Machine Learning|Microscopy, Fluorescence|Microtubules|Models, Biological|Proteins|Systems Biology', 'Journal Article', '10.1371/journal.pcbi.1004614', '26624011', 'Characterizing the spatial distribution of proteins directly from microscopy images is a difficult problem with numerous applications in cell biology (e.g. identifying motor-related proteins) and clinical research (e.g. identification of cancer biomarkers). Here we describe the design of a system that provides automated analysis of punctate protein patterns in microscope images, including quantification of their relationships to microtubules. We constructed the system using confocal immunofluorescence microscopy images from the Human Protein Atlas project for 11 punctate proteins in three cultured cell lines. These proteins have previously been characterized as being primarily located in punctate structures, but their images had all been annotated by visual examination as being simply vesicular. We were able to show that these patterns could be distinguished from each other with high accuracy, and we were able to assign to one of these subclasses hundreds of proteins whose subcellular localization had not previously been well defined. In addition to providing these novel annotations, we built a generative approach to modeling of punctate distributions that captures the essential characteristics of the distinct patterns. Such models are expected to be valuable for representing and summarizing each pattern and for constructing systems biology simulations of cell behaviors. '),
(87527, 2015, 'plos', 'Wham: Identifying Structural Variants of Biological Consequence', 'Kronenberg, Zev N|Osborne, Edward J|Cone, Kelsey R|Kennedy, Brett J|Domyan, Eric T|Shapiro, Michael D|Elde, Nels C|Yandell, Mark', 'Department of Human Genetics, Eccles Institute of Human Genetics, University of Utah, Salt Lake City, Utah, United States of America.|Department of Human Genetics, Eccles Institute of Human Genetics, University of Utah, Salt Lake City, Utah, United States of America.|Department of Human Genetics, Eccles Institute of Human Genetics, University of Utah, Salt Lake City, Utah, United States of America.|Department of Human Genetics, Eccles Institute of Human Genetics, University of Utah, Salt Lake City, Utah, United States of America.|Department of Biology, University of Utah, Salt Lake City, Utah, United States of America.|Department of Biology, University of Utah, Salt Lake City, Utah, United States of America.|Department of Human Genetics, Eccles Institute of Human Genetics, University of Utah, Salt Lake City, Utah, United States of America.|Department of Human Genetics, Eccles Institute of Human Genetics, University of Utah, Salt Lake City, Utah, United States of America.', 'United States|United States|United States|United States|United States|United States|United States|Un', 28, 'Algorithms|Base Sequence|Chromosome Mapping|Genetic Association Studies|Genetic Variation|Genome, Human|Genomic Structural Variation|Humans|Molecular Sequence Data|Software', 'Journal Article', '10.1371/journal.pcbi.1004572', '26625158', 'Existing methods for identifying structural variants (SVs) from short read datasets are inaccurate. This complicates disease-gene identification and efforts to understand the consequences of genetic variation. In response, we have created Wham (Whole-genome Alignment Metrics) to provide a single, integrated framework for both structural variant calling and association testing, thereby bypassing many of the difficulties that currently frustrate attempts to employ SVs in association testing. Here we describe Wham, benchmark it against three other widely used SV identification tools-Lumpy, Delly and SoftSearch-and demonstrate Whams ability to identify and associate SVs with phenotypes using data from humans, domestic pigeons, and vaccinia virus. Wham and all associated software are covered under the MIT License and can be freely downloaded from github (https://github.com/zeeev/wham), with documentation on a wiki (http://zeeev.github.io/wham/). For community support please post questions to https://www.biostars.org/. ');
INSERT INTO `papers` (`id`, `ano`, `journal`, `titulo`, `autores`, `afiliacao`, `pais`, `citacoes`, `palavra_chave`, `categorias`, `doi`, `pubmed`, `abstract`) VALUES
(87528, 2015, 'plos', 'A Functional Cartography of Cognitive Systems', 'Mattar, Marcelo G|Cole, Michael W|Thompson-Schill, Sharon L|Bassett, Danielle S', 'Department of Psychology, University of Pennsylvania, Philadelphia, Pennsylvania, United States of America.|Center for Molecular and Behavioral Neuroscience, Rutgers University, Newark, New Jersey, United States of America.|Department of Psychology, University of Pennsylvania, Philadelphia, Pennsylvania, United States of America.|Department of Bioengineering, University of Pennsylvania, Philadelphia, Pennsylvania, United States of America.', 'United States|Jersey|United States|United States', 42, 'Brain|Brain Mapping|Cognition|Computer Simulation|Executive Function|Humans|Magnetic Resonance Imaging|Models, Neurological|Nerve Net|Task Performance and Analysis', 'Journal Article', '10.1371/journal.pcbi.1004533', '26629847', 'One of the most remarkable features of the human brain is its ability to adapt rapidly and efficiently to external task demands. Novel and non-routine tasks, for example, are implemented faster than structural connections can be formed. The neural underpinnings of these dynamics are far from understood. Here we develop and apply novel methods in network science to quantify how patterns of functional connectivity between brain regions reconfigure as human subjects perform 64 different tasks. By applying dynamic community detection algorithms, we identify groups of brain regions that form putative functional communities, and we uncover changes in these groups across the 64-task battery. We summarize these reconfiguration patterns by quantifying the probability that two brain regions engage in the same network community (or putative functional module) across tasks. These tools enable us to demonstrate that classically defined cognitive systems-including visual, sensorimotor, auditory, default mode, fronto-parietal, cingulo-opercular and salience systems-engage dynamically in cohesive network communities across tasks. We define the network role that a cognitive system plays in these dynamics along the following two dimensions: (i) stability vs. flexibility and (ii) connected vs. isolated. The role of each system is therefore summarized by how stably that system is recruited over the 64 tasks, and how consistently that system interacts with other systems. Using this cartography, classically defined cognitive systems can be categorized as ephemeral integrators, stable loners, and anything in between. Our results provide a new conceptual framework for understanding the dynamic integration and recruitment of cognitive systems in enabling behavioral adaptability across both task and rest conditions. This work has important implications for understanding cognitive network reconfiguration during different task sets and its relationship to cognitive effort, individual variation in cognitive performance, and fatigue. '),
(87529, 2015, 'plos', 'AutoDockFR: Advances in Protein-Ligand Docking with Explicitly Specified Binding Site Flexibility', 'Ravindranath, Pradeep Anand|Forli, Stefano|Goodsell, David S|Olson, Arthur J|Sanner, Michel F', 'Department of Integrative Structural and Computational Biology, The Scripps Research Institute, La Jolla, California, United States of America.|Department of Integrative Structural and Computational Biology, The Scripps Research Institute, La Jolla, California, United States of America.|Department of Integrative Structural and Computational Biology, The Scripps Research Institute, La Jolla, California, United States of America.|Department of Integrative Structural and Computational Biology, The Scripps Research Institute, La Jolla, California, United States of America.|Department of Integrative Structural and Computational Biology, The Scripps Research Institute, La Jolla, California, United States of America.', 'United States|United States|United States|United States|United States', 9, 'Algorithms|Binding Sites|Drug Design|Ligands|Models, Chemical|Molecular Docking Simulation|Protein Binding|Protein Interaction Mapping|Proteins|Software', 'Journal Article', '10.1371/journal.pcbi.1004586', '26629955', 'Automated docking of drug-like molecules into receptors is an essential tool in structure-based drug design. While modeling receptor flexibility is important for correctly predicting ligand binding, it still remains challenging. This work focuses on an approach in which receptor flexibility is modeled by explicitly specifying a set of receptor side-chains a-priori. The challenges of this approach include the: 1) exponential growth of the search space, demanding more efficient search methods, and 2) increased number of false positives, calling for scoring functions tailored for flexible receptor docking. We present AutoDockFR-AutoDock for Flexible Receptors (ADFR), a new docking engine based on the AutoDock4 scoring function, which addresses the aforementioned challenges with a new Genetic Algorithm (GA) and customized scoring function. We validate ADFR using the Astex Diverse Set, demonstrating an increase in efficiency and reliability of its GA over the one implemented in AutoDock4. We demonstrate greatly increased success rates when cross-docking ligands into apo receptors that require side-chain conformational changes for ligand binding. These cross-docking experiments are based on two datasets: 1) SEQ17 -a receptor diversity set containing 17 pairs of apo-holo structures, and 2) CDK2 -a ligand diversity set composed of one CDK2 apo structure and 52 known bound inhibitors. We show that, when cross-docking ligands into the apo conformation of the receptors with up to 14 flexible side-chains, ADFR reports more correctly cross-docked ligands than AutoDock Vina on both datasets with solutions found for 70.6% vs. 35.3% systems on SEQ17, and 76.9% vs. 61.5% on CDK2. ADFR also outperforms AutoDock Vina in number of top ranking solutions on both datasets. Furthermore, we show that correctly docked CDK2 complexes re-create on average 79.8% of all pairwise atomic interactions between the ligand and moving receptor atoms in the holo complexes. Finally, we show that down-weighting the receptor internal energy improves the ranking of correctly docked poses and that runtime for AutoDockFR scales linearly when side-chain flexibility is added. '),
(87530, 2015, 'plos', 'Mathematical Modeling of Interacting Glucose-Sensing Mechanisms and Electrical Activity Underlying Glucagon-Like Peptide 1 Secretion', 'Riz, Michela|Pedersen, Morten Gram', 'Department of Information Engineering, University of Padua, Padua, Italy.|Department of Information Engineering, University of Padua, Padua, Italy.', 'Italy|Italy', 5, 'Action Potentials|Animals|Computer Simulation|Enteroendocrine Cells|Glucagon-Like Peptide 1|Glucose|Humans|Intestines|Models, Biological', 'Journal Article', '10.1371/journal.pcbi.1004600', '26630068', 'Intestinal L-cells sense glucose and other nutrients, and in response release glucagon-like peptide 1 (GLP-1), peptide YY and other hormones with anti-diabetic and weight-reducing effects. The stimulus-secretion pathway in L-cells is still poorly understood, although it is known that GLP-1 secreting cells use sodium-glucose co-transporters (SGLT) and ATP-sensitive K+-channels (K(ATP)-channels) to sense intestinal glucose levels. Electrical activity then transduces glucose sensing to Ca2+-stimulated exocytosis. This particular glucose-sensing arrangement with glucose triggering both a depolarizing SGLT current as well as leading to closure of the hyperpolarizing K(ATP) current is of more general interest for our understanding of glucose-sensing cells. To dissect the interactions of these two glucose-sensing mechanisms, we build a mathematical model of electrical activity underlying GLP-1 secretion. Two sets of model parameters are presented: one set represents primary mouse colonic L-cells, the other set is based on data from the GLP-1 secreting GLUTag cell line. The model is then used to obtain insight into the differences in glucose-sensing between primary L-cells and GLUTag cells. Our results illuminate how the two glucose-sensing mechanisms interact, and suggest that the depolarizing effect of SGLT currents is modulated by K(ATP)-channel activity. Based on our simulations, we propose that primary L-cells encode the glucose signal as changes in action potential amplitude, whereas GLUTag cells rely mainly on frequency modulation. The model should be useful for further basic, pharmacological and theoretical investigations of the cellular signals underlying endogenous GLP-1 and peptide YY release. '),
(87531, 2015, 'plos', 'Cerebellar Nuclear Neurons Use Time and Rate Coding to Transmit Purkinje Neuron Pauses', 'Sudhakar, Shyam Kumar|Torben-Nielsen, Benjamin|De Schutter, Erik', 'Computational Neuroscience Unit, Okinawa Institute of Science and Technology, Onna-son, Okinawa, Japan.|Computational Neuroscience Unit, Okinawa Institute of Science and Technology, Onna-son, Okinawa, Japan.|Computational Neuroscience Unit, Okinawa Institute of Science and Technology, Onna-son, Okinawa, Japan.', 'Japan|Japan|Japan', 10, 'Animals|Cerebellar Nuclei|Computer Simulation|Humans|Models, Neurological|Nerve Net|Neural Inhibition|Neural Pathways|Neurons|Purkinje Cells|Synaptic Potentials|Synaptic Transmission', 'Journal Article', '10.1371/journal.pcbi.1004641', '26630202', 'Neurons of the cerebellar nuclei convey the final output of the cerebellum to their targets in various parts of the brain. Within the cerebellum their direct upstream connections originate from inhibitory Purkinje neurons. Purkinje neurons have a complex firing pattern of regular spikes interrupted by intermittent pauses of variable length. How can the cerebellar nucleus process this complex input pattern? In this modeling study, we investigate different forms of Purkinje neuron simple spike pause synchrony and its influence on candidate coding strategies in the cerebellar nuclei. That is, we investigate how different alignments of synchronous pauses in synthetic Purkinje neuron spike trains affect either time-locking or rate-changes in the downstream nuclei. We find that Purkinje neuron synchrony is mainly represented by changes in the firing rate of cerebellar nuclei neurons. Pause beginning synchronization produced a unique effect on nuclei neuron firing, while the effect of pause ending and pause overlapping synchronization could not be distinguished from each other. Pause beginning synchronization produced better time-locking of nuclear neurons for short length pauses. We also characterize the effect of pause length and spike jitter on the nuclear neuron firing. Additionally, we find that the rate of rebound responses in nuclear neurons after a synchronous pause is controlled by the firing rate of Purkinje neurons preceding it. '),
(87532, 2015, 'plos', 'Computational Identification of Mechanistic Factors That Determine the Timing and Intensity of the Inflammatory Response', 'Nagaraja, Sridevi|Reifman, Jaques|Mitrophanov, Alexander Y', 'Department of Defense Biotechnology High Performance Computing Software Applications Institute, Telemedicine and Advanced Technology Research Center, U.S. Army Medical Research and Materiel Command, Fort Detrick, Maryland, United States of America.|Department of Defense Biotechnology High Performance Computing Software Applications Institute, Telemedicine and Advanced Technology Research Center, U.S. Army Medical Research and Materiel Command, Fort Detrick, Maryland, United States of America.|Department of Defense Biotechnology High Performance Computing Software Applications Institute, Telemedicine and Advanced Technology Research Center, U.S. Army Medical Research and Materiel Command, Fort Detrick, Maryland, United States of America.', 'United States|United States|United States', 0, 'Animals|Computer Simulation|Humans|Immunity, Innate|Inflammation|Interleukin-8|Macrophage Activation|Macrophages|Models, Immunological|Severity of Illness Index|Transforming Growth Factor beta|Tumor Necrosis Factor-alpha', 'Journal Article', '10.1371/journal.pcbi.1004460', '26633296', 'Timely resolution of inflammation is critical for the restoration of homeostasis in injured or infected tissue. Chronic inflammation is often characterized by a persistent increase in the concentrations of inflammatory cells and molecular mediators, whose distinct amount and timing characteristics offer an opportunity to identify effective therapeutic regulatory targets. Here, we used our recently developed computational model of local inflammation to identify potential targets for molecular interventions and to investigate the effects of individual and combined inhibition of such targets. This was accomplished via the development and application of computational strategies involving the simulation and analysis of thousands of inflammatory scenarios. We found that modulation of macrophage influx and efflux is an effective potential strategy to regulate the amount of inflammatory cells and molecular mediators in both normal and chronic inflammatory scenarios. We identified three molecular mediators - tumor necrosis factor-xcexb1 (TNF-xcexb1), transforming growth factor-xcexb2 (TGF-xcexb2), and the chemokine CXCL8 - as potential molecular targets whose individual or combined inhibition may robustly regulate both the amount and timing properties of the kinetic trajectories for neutrophils and macrophages in chronic inflammation. Modulation of macrophage flux, as well as of the abundance of TNF-xcexb1, TGF-xcexb2, and CXCL8, may improve the resolution of chronic inflammation. '),
(87533, 2015, 'plos', 'Mirrored STDP Implements Autoencoder Learning in a Network of Spiking Neurons', 'Burbank, Kendra S', 'Department of Statistics, University of Chicago, Chicago, Illinois, United States of America.', 'United States', 0, 'Action Potentials|Biomimetics|Computer Simulation|Humans|Information Storage and Retrieval|Learning|Machine Learning|Models, Neurological|Nerve Net|Neural Networks (Computer)|Neuronal Plasticity|Neurons|Signal Processing, Computer-Assisted', 'Journal Article', '10.1371/journal.pcbi.1004566', '26633645', 'The autoencoder algorithm is a simple but powerful unsupervised method for training neural networks. Autoencoder networks can learn sparse distributed codes similar to those seen in cortical sensory areas such as visual area V1, but they can also be stacked to learn increasingly abstract representations. Several computational neuroscience models of sensory areas, including Olshausen & Fields Sparse Coding algorithm, can be seen as autoencoder variants, and autoencoders have seen extensive use in the machine learning community. Despite their power and versatility, autoencoders have been difficult to implement in a biologically realistic fashion. The challenges include their need to calculate differences between two neuronal activities and their requirement for learning rules which lead to identical changes at feedforward and feedback connections. Here, we study a biologically realistic network of integrate-and-fire neurons with anatomical connectivity and synaptic plasticity that closely matches that observed in cortical sensory areas. Our choice of synaptic plasticity rules is inspired by recent experimental and theoretical results suggesting that learning at feedback connections may have a different form from learning at feedforward connections, and our results depend critically on this novel choice of plasticity rules. Specifically, we propose that plasticity rules at feedforward versus feedback connections are temporally opposed versions of spike-timing dependent plasticity (STDP), leading to a symmetric combined rule we call Mirrored STDP (mSTDP). We show that with mSTDP, our network follows a learning rule that approximately minimizes an autoencoder loss function. When trained with whitened natural image patches, the learned synaptic weights resemble the receptive fields seen in V1. Our results use realistic synaptic plasticity rules to show that the powerful autoencoder learning algorithm could be within the reach of real biological networks. '),
(87534, 2015, 'plos', 'Correction: Efficient Shotgun Inference of Neural Connectivity from Highly Sub-sampled Activity Data', 'PLOS Computational Biology Staff', 'Department of Statistics, University of Chicago, Chicago, Illinois, United States of America.', 'United States', 0, '-', 'Published Erratum', '10.1371/journal.pcbi.1004657', '26633800', '-'),
(87535, 2015, 'plos', 'Gene Expression Switching of Receptor Subunits in Human Brain Development', 'Bar-Shira, Ossnat|Maor, Ronnie|Chechik, Gal', 'Gonda Brain Research Center, Bar-Ilan University, Ramat Gan, Israel.|Gonda Brain Research Center, Bar-Ilan University, Ramat Gan, Israel.|Gonda Brain Research Center, Bar-Ilan University, Ramat Gan, Israel.', 'Israel|Israel|Israel', 15, 'Aging|Brain|Chromosome Mapping|Gene Expression Regulation, Developmental|Genes, Switch|Humans|Protein Subunits|Receptors, GABA|Receptors, N-Methyl-D-Aspartate|Receptors, Neurotransmitter|Synaptic Transmission', 'Journal Article', '10.1371/journal.pcbi.1004559', '26636753', 'Synaptic receptors in the human brain consist of multiple protein subunits, many of which have multiple variants, coded by different genes, and are differentially expressed across brain regions and developmental stages. The brain can tune the electrophysiological properties of synapses to regulate plasticity and information processing by switching from one protein variant to another. Such condition-dependent variant switch during development has been demonstrated in several neurotransmitter systems including NMDA and GABA. Here we systematically detect pairs of receptor-subunit variants that switch during the lifetime of the human brain by analyzing postmortem expression data collected in a population of donors at various ages and brain regions measured using microarray and RNA-seq. To further detect variant pairs that co-vary across subjects, we present a method to quantify age-corrected expression correlation in face of strong temporal trends. This is achieved by computing the correlations in the residual expression beyond a cubic-spline model of the population temporal trend, and can be seen as a nonlinear version of partial correlations. Using these methods, we detect multiple new pairs of context dependent variants. For instance, we find a switch from GLRA2 to GLRA3 that differs from the known switch in the rat. We also detect an early switch from HTR1A to HTR5A whose trends are negatively correlated and find that their age-corrected expression is strongly positively correlated. Finally, we observe that GRIN2B switch to GRIN2A occurs mostly during embryonic development, presumably earlier than observed in rodents. These results provide a systematic map of developmental switching in the neurotransmitter systems of the human brain. '),
(87536, 2015, 'plos', 'Melanoma Cell Colony Expansion Parameters Revealed by Approximate Bayesian Computation', 'Vo, Brenda N|Drovandi, Christopher C|Pettitt, Anthony N|Pettet, Graeme J', 'School of Mathematical Sciences, Queensland University of Technology (QUT), Brisbane, Australia.|School of Mathematical Sciences, Queensland University of Technology (QUT), Brisbane, Australia.|School of Mathematical Sciences, Queensland University of Technology (QUT), Brisbane, Australia.|School of Mathematical Sciences, Queensland University of Technology (QUT), Brisbane, Australia.', 'Australia|Australia|Australia|Australia', 8, 'Bayes Theorem|Cell Adhesion|Cell Line, Tumor|Cell Movement|Cell Proliferation|Computer Simulation|Humans|Image Interpretation, Computer-Assisted|Melanoma|Models, Biological|Models, Statistical|Neoplasm Invasiveness|Skin Neoplasms', 'Journal Article', '10.1371/journal.pcbi.1004635', '26642072', 'In vitro studies and mathematical models are now being widely used to study the underlying mechanisms driving the expansion of cell colonies. This can improve our understanding of cancer formation and progression. Although much progress has been made in terms of developing and analysing mathematical models, far less progress has been made in terms of understanding how to estimate model parameters using experimental in vitro image-based data. To address this issue, a new approximate Bayesian computation (ABC) algorithm is proposed to estimate key parameters governing the expansion of melanoma cell (MM127) colonies, including cell diffusivity, D, cell proliferation rate, xcexbb, and cell-to-cell adhesion, q, in two experimental scenarios, namely with and without a chemical treatment to suppress cell proliferation. Even when little prior biological knowledge about the parameters is assumed, all parameters are precisely inferred with a small posterior coefficient of variation, approximately 2-12%. The ABC analyses reveal that the posterior distributions of D and q depend on the experimental elapsed time, whereas the posterior distribution of xcexbb does not. The posterior mean values of D and q are in the ranges 226-268 xc2xb5m2h-1, 311-351 xc2xb5m2h-1 and 0.23-0.39, 0.32-0.61 for the experimental periods of 0-24 h and 24-48 h, respectively. Furthermore, we found that the posterior distribution of q also depends on the initial cell density, whereas the posterior distributions of D and xcexbb do not. The ABC approach also enables information from the two experiments to be combined, resulting in greater precision for all estimates of D and xcexbb. '),
(87537, 2015, 'plos', 'The Characteristics of Heterozygous Protein Truncating Variants in the Human Genome', 'Bartha, István|Rausell, Antonio|McLaren, Paul J|Mohammadi, Pejman|Tardaguila, Manuel|Chaturvedi, Nimisha|Fellay, Jacques|Telenti, Amalio', 'SIB Swiss Institute of Bioinformatics, Lausanne and Basel, Switzerland.|SIB Swiss Institute of Bioinformatics, Lausanne and Basel, Switzerland.|SIB Swiss Institute of Bioinformatics, Lausanne and Basel, Switzerland.|SIB Swiss Institute of Bioinformatics, Lausanne and Basel, Switzerland.|SIB Swiss Institute of Bioinformatics, Lausanne and Basel, Switzerland.|SIB Swiss Institute of Bioinformatics, Lausanne and Basel, Switzerland.|SIB Swiss Institute of Bioinformatics, Lausanne and Basel, Switzerland.|J. Craig Venter Institute, La Jolla, California, United States of America.', 'Switzerland|Switzerland|Switzerland|Switzerland|Switzerland|Switzerland|Switzerland|United States', 0, 'Base Sequence|Chromosome Mapping|Codon, Nonsense|Genetic Variation|Genome, Human|Humans|Molecular Sequence Data|Proteins', 'Journal Article', '10.1371/journal.pcbi.1004647', '26642228', 'Sequencing projects have identified large numbers of rare stop-gain and frameshift variants in the human genome. As most of these are observed in the heterozygous state, they test a genes tolerance to haploinsufficiency and dominant loss of function. We analyzed the distribution of truncating variants across 16,260 autosomal protein coding genes in 11,546 individuals. We observed 39,893 truncating variants affecting 12,062 genes, which significantly differed from an expectation of 12,916 genes under a model of neutral de novo mutation (p<10-4). Extrapolating this to increasing numbers of sequenced individuals, we estimate that 10.8% of human genes do not tolerate heterozygous truncating variants. An additional 10 to 15% of truncated genes may be rescued by incomplete penetrance or compensatory mutations, or because the truncating variants are of limited functional impact. The study of protein truncating variants delineates the essential genome and, more generally, identifies rare heterozygous variants as an unexplored source of diversity of phenotypic traits and diseases. '),
(87538, 2015, 'plos', 'MiR-192-Mediated Positive Feedback Loop Controls the Robustness of Stress-Induced p53 Oscillations in Breast Cancer Cells', 'Moore, Richard|Ooi, Hsu Kiang|Kang, Taek|Bleris, Leonidas|Ma, Lan', 'Bioengineering Department, University of Texas at Dallas, Richardson, Texas, United States of America.|Bioengineering Department, University of Texas at Dallas, Richardson, Texas, United States of America.|Bioengineering Department, University of Texas at Dallas, Richardson, Texas, United States of America.|Bioengineering Department, University of Texas at Dallas, Richardson, Texas, United States of America.|Bioengineering Department, University of Texas at Dallas, Richardson, Texas, United States of America.', 'United States|United States|United States|United States|United States', 0, 'Biological Clocks|Breast Neoplasms|Computer Simulation|DNA Damage|Feedback, Physiological|Gene Expression Regulation|Humans|MCF-7 Cells|MicroRNAs|Models, Biological|Stress, Physiological|Tumor Suppressor Protein p53', 'Journal Article', '10.1371/journal.pcbi.1004653', '26642352', 'The p53 tumor suppressor protein plays a critical role in cellular stress and cancer prevention. A number of post-transcriptional regulators, termed microRNAs, are closely connected with the p53-mediated cellular networks. While the molecular interactions among p53 and microRNAs have emerged, a systems-level understanding of the regulatory mechanism and the role of microRNAs-forming feedback loops with the p53 core remains elusive. Here we have identified from literature that there exist three classes of microRNA-mediated feedback loops revolving around p53, all with the nature of positive feedback coincidentally. To explore the relationship between the cellular performance of p53 with the microRNA feedback pathways, we developed a mathematical model of the core p53-MDM2 module coupled with three microRNA-mediated positive feedback loops involving miR-192, miR-34a, and miR-29a. Simulations and bifurcation analysis in relationship to extrinsic noise reproduce the oscillatory behavior of p53 under DNA damage in single cells, and notably show that specific microRNA abrogation can disrupt the wild-type cellular phenotype when the ubiquitous cell-to-cell variability is taken into account. To assess these in silico results we conducted microRNA-perturbation experiments in MCF7 breast cancer cells. Time-lapse microscopy of cell-population behavior in response to DNA double-strand breaks, together with image classification of single-cell phenotypes across a population, confirmed that the cellular p53 oscillations are compromised after miR-192 perturbations, matching well with the model predictions. Our study via modeling in combination with quantitative experiments provides new evidence on the role of microRNA-mediated positive feedback loops in conferring robustness to the system performance of stress-induced response of p53. '),
(87539, 2015, 'plos', 'Biases in Visual, Auditory, and Audiovisual Perception of Space', 'Odegaard, Brian|Wozny, David R|Shams, Ladan', 'Department of Psychology, University of California, Los Angeles, Los Angeles, California, United States of America.|Department of Psychology, University of California, Los Angeles, Los Angeles, California, United States of America.|Department of Psychology, University of California, Los Angeles, Los Angeles, California, United States of America.', 'United States|United States|United States', 0, 'Acoustic Stimulation|Adolescent|Adult|Auditory Perception|Computer Simulation|Female|Humans|Male|Middle Aged|Models, Neurological|Models, Statistical|Physical Stimulation|Reproducibility of Results|Sensitivity and Specificity|Sound Localization|Space Perception|Task Performance and Analysis|Young Adult', 'Journal Article', '10.1371/journal.pcbi.1004649', '26646312', 'Localization of objects and events in the environment is critical for survival, as many perceptual and motor tasks rely on estimation of spatial location. Therefore, it seems reasonable to assume that spatial localizations should generally be accurate. Curiously, some previous studies have reported biases in visual and auditory localizations, but these studies have used small sample sizes and the results have been mixed. Therefore, it is not clear (1) if the reported biases in localization responses are real (or due to outliers, sampling bias, or other factors), and (2) whether these putative biases reflect a bias in sensory representations of space or a priori expectations (which may be due to the experimental setup, instructions, or distribution of stimuli). Here, to address these questions, a dataset of unprecedented size (obtained from 384 observers) was analyzed to examine presence, direction, and magnitude of sensory biases, and quantitative computational modeling was used to probe the underlying mechanism(s) driving these effects. Data revealed that, on average, observers were biased towards the center when localizing visual stimuli, and biased towards the periphery when localizing auditory stimuli. Moreover, quantitative analysis using a Bayesian Causal Inference framework suggests that while pre-existing spatial biases for central locations exert some influence, biases in the sensory representations of both visual and auditory space are necessary to fully explain the behavioral data. How are these opposing visual and auditory biases reconciled in conditions in which both auditory and visual stimuli are produced by a single event? Potentially, the bias in one modality could dominate, or the biases could interact/cancel out. The data revealed that when integration occurred in these conditions, the visual bias dominated, but the magnitude of this bias was reduced compared to unisensory conditions. Therefore, multisensory integration not only improves the precision of perceptual estimates, but also the accuracy. '),
(87540, 2015, 'plos', 'Protein Connectivity in Chemotaxis Receptor Complexes', 'Eismann, Stephan|Endres, Robert G', 'Department of Physics and Astronomy, University of Heidelberg, Heidelberg, Germany.|Department of Life Sciences and Centre for Integrative Systems Biology and Bioinformatics, Imperial College London, London, United Kingdom.', 'Germany|United Kingdom', 3, 'Bacterial Proteins|Chemotaxis|Computer Simulation|Escherichia coli|Escherichia coli Proteins|Histidine Kinase|Membrane Proteins|Methyl-Accepting Chemotaxis Proteins|Models, Biological|Models, Chemical|Models, Statistical|Protein Interaction Mapping', 'Journal Article', '10.1371/journal.pcbi.1004650', '26646441', 'The chemotaxis sensory system allows bacteria such as Escherichia coli to swim towards nutrients and away from repellents. The underlying pathway is remarkably sensitive in detecting chemical gradients over a wide range of ambient concentrations. Interactions among receptors, which are predominantly clustered at the cell poles, are crucial to this sensitivity. Although it has been suggested that the kinase CheA and the adapter protein CheW are integral for receptor connectivity, the exact coupling mechanism remains unclear. Here, we present a statistical-mechanics approach to model the receptor linkage mechanism itself, building on nanodisc and electron cryotomography experiments. Specifically, we investigate how the sensing behavior of mixed receptor clusters is affected by variations in the expression levels of CheA and CheW at a constant receptor density in the membrane. Our model compares favorably with dose-response curves from in vivo Förster resonance energy transfer (FRET) measurements, demonstrating that the receptor-methylation level has only minor effects on receptor cooperativity. Importantly, our model provides an explanation for the non-intuitive conclusion that the receptor cooperativity decreases with increasing levels of CheA, a core signaling protein associated with the receptors, whereas the receptor cooperativity increases with increasing levels of CheW, a key adapter protein. Finally, we propose an evolutionary advantage as explanation for the recently suggested CheW-only linker structures. '),
(87541, 2015, 'plos', 'Text Mining for Protein Docking', 'Badal, Varsha D|Kundrotas, Petras J|Vakser, Ilya A', 'Center for Computational Biology, The University of Kansas, Lawrence, Kansas, United States of America.|Center for Computational Biology, The University of Kansas, Lawrence, Kansas, United States of America.|Center for Computational Biology, The University of Kansas, Lawrence, Kansas, United States of America.', 'United States|United States|United States', 0, '-', 'Journal Article', '10.1371/journal.pcbi.1004630', '26650466', 'The rapidly growing amount of publicly available information from biomedical research is readily accessible on the Internet, providing a powerful resource for predictive biomolecular modeling. The accumulated data on experimentally determined structures transformed structure prediction of proteins and protein complexes. Instead of exploring the enormous search space, predictive tools can simply proceed to the solution based on similarity to the existing, previously determined structures. A similar major paradigm shift is emerging due to the rapidly expanding amount of information, other than experimentally determined structures, which still can be used as constraints in biomolecular structure prediction. Automated text mining has been widely used in recreating protein interaction networks, as well as in detecting small ligand binding sites on protein structures. Combining and expanding these two well-developed areas of research, we applied the text mining to structural modeling of protein-protein complexes (protein docking). Protein docking can be significantly improved when constraints on the docking mode are available. We developed a procedure that retrieves published abstracts on a specific protein-protein interaction and extracts information relevant to docking. The procedure was assessed on protein complexes from Dockground (http://dockground.compbio.ku.edu). The results show that correct information on binding residues can be extracted for about half of the complexes. The amount of irrelevant information was reduced by conceptual analysis of a subset of the retrieved abstracts, based on the bag-of-words (features) approach. Support Vector Machine models were trained and validated on the subset. The remaining abstracts were filtered by the best-performing models, which decreased the irrelevant information for ~ 25% complexes in the dataset. The extracted constraints were incorporated in the docking protocol and tested on the Dockground unbound benchmark set, significantly increasing the docking success rate.'),
(87542, 2015, 'plos', 'Anxiety-Like Behavioural Inhibition Is Normative under Environmental Threat-Reward Correlations', 'Bach, Dominik R', 'Department of Psychiatry, Psychotherapy, and Psychosomatics, University of Zurich, Zurich, Switzerland.', 'Switzerland', 24, '-', 'Journal Article', '10.1371/journal.pcbi.1004646', '26650585', 'Behavioural inhibition is a key anxiety-like behaviour in rodents and humans, distinct from avoidance of danger, and reduced by anxiolytic drugs. In some situations, it is not clear how behavioural inhibition minimises harm or maximises benefit for the agent, and can even appear counterproductive. Extant explanations of this phenomenon make use of descriptive models but do not provide a formal assessment of its adaptive value. This hampers a better understanding of the neural computations underlying anxiety behaviour. Here, we analyse a standard rodent anxiety model, the operant conflict test. We harvest Bayesian Decision Theory to show that behavioural inhibition normatively arises as cost-minimising strategy in temporally correlated environments. Importantly, only if behavioural inhibition is aimed at minimising cost, it depends on probability and magnitude of threat. Harnessing a virtual computer game, we test model predictions in four experiments with human participants. Humans exhibit behavioural inhibition with a strong linear dependence on threat probability and magnitude. Strikingly, inhibition occurs before motor execution and depends on the virtual environment, thus likely resulting from a neural optimisation process rather than a pre-programmed mechanism. Individual trait anxiety scores predict behavioural inhibition, underlining the validity of this anxiety model. These findings put anxiety behaviour into the context of cost-minimisation and optimal inference, and may ultimately pave the way towards a mechanistic understanding of the neural computations gone awry in human anxiety disorder.'),
(87543, 2015, 'plos', 'Morphological and Stress Vulnerability Indices for Human Coronary Plaques and Their Correlations with Cap Thickness and Lipid Percent: An IVUS-Based Fluid-Structure Interaction Multi-patient Study', 'Wang, Liang|Zheng, Jie|Maehara, Akiko|Yang, Chun|Billiar, Kristen L|Wu, Zheyang|Bach, Richard|Muccigrosso, David|Mintz, Gary S|Tang, Dalin', 'Mathematical Sciences Department, Worcester Polytechnic Institute, Massachusetts, United States of America.|Mallinckrodt Institute of Radiology, Washington University, St. Louis, Missouri, United States of America.|The Cardiovascular Research Foundation, New York, New York, United States of America.|Mathematical Sciences Department, Worcester Polytechnic Institute, Massachusetts, United States of America.|Biomedical Engineering Department, Worcester Polytechnic Institute, Worcester, Massachusetts, United States of America.|Mathematical Sciences Department, Worcester Polytechnic Institute, Massachusetts, United States of America.|Cardiovascular Division, Washington University School of Medicine, St. Louis, Missouri, United States of America.|Mallinckrodt Institute of Radiology, Washington University, St. Louis, Missouri, United States of America.|The Cardiovascular Research Foundation, New York, New York, United States of America.|Mathematical Sciences Department, Worcester Polytechnic Institute, Massachusetts, United States of America.', 'United States|United States|United States|United States|United States|United States|United States|Un', 15, '-', 'Journal Article', '10.1371/journal.pcbi.1004652', '26650721', 'Plaque vulnerability, defined as the likelihood that a plaque would rupture, is difficult to quantify due to lack of in vivo plaque rupture data. Morphological and stress-based plaque vulnerability indices were introduced as alternatives to obtain quantitative vulnerability assessment. Correlations between these indices and key plaque features were investigated. In vivo intravascular ultrasound (IVUS) data were acquired from 14 patients and IVUS-based 3D fluid-structure interaction (FSI) coronary plaque models with cyclic bending were constructed to obtain plaque wall stress/strain and flow shear stress for analysis. For the 617 slices from the 14 patients, lipid percentage, min cap thickness, critical plaque wall stress (CPWS), strain (CPWSn) and flow shear stress (CFSS) were recorded, and cap index, lipid index and morphological index were assigned to each slice using methods consistent with American Heart Association (AHA) plaque classification schemes. A stress index was introduced based on CPWS. Linear Mixed-Effects (LME) models were used to analyze the correlations between the mechanical and morphological indices and key morphological factors associated with plaque rupture. Our results indicated that for all 617 slices, CPWS correlated with min cap thickness, cap index, morphological index with r = -0.6414, 0.7852, and 0.7411 respectively (p<0.0001). The correlation between CPWS and lipid percentage, lipid index were weaker (r = 0.2445, r = 0.2338, p<0.0001). Stress index correlated with cap index, lipid index, morphological index positively with r = 0.8185, 0.3067, and 0.7715, respectively, all with p<0.0001. For all 617 slices, the stress index has 66.77% agreement with morphological index. Morphological and stress indices may serve as quantitative plaque vulnerability assessment supported by their strong correlations with morphological features associated with plaque rupture. Differences between the two indices may lead to better plaque assessment schemes when both indices were jointly used with further validations from clinical studies.'),
(87544, 2015, 'plos', 'Locust Collective Motion and Its Modeling', 'Ariel, Gil|Ayali, Amir', 'Department of Mathematics, Bar Ilan University, Ramat-Gan, Israel.|Department of Zoology, Faculty of Life Sciences, and Sagol School of Neuroscience, Tel Aviv University, Tel Aviv, Israel.', 'Israel|Israel', 0, 'Animal Distribution|Animal Migration|Animals|Behavior, Animal|Computer Simulation|Crowding|Grasshoppers|Locomotion|Mass Behavior|Models, Biological|Models, Statistical|Nymph', 'Journal Article', '10.1371/journal.pcbi.1004522', '26656851', 'Over the past decade, technological advances in experimental and animal tracking techniques have motivated a renewed theoretical interest in animal collective motion and, in particular, locust swarming. This review offers a comprehensive biological background followed by comparative analysis of recent models of locust collective motion, in particular locust marching, their settings, and underlying assumptions. We describe a wide range of recent modeling and simulation approaches, from discrete agent-based models of self-propelled particles to continuous models of integro-differential equations, aimed at describing and analyzing the fascinating phenomenon of locust collective motion. These modeling efforts have a dual role: The first views locusts as a quintessential example of animal collective motion. As such, they aim at abstraction and coarse-graining, often utilizing the tools of statistical physics. The second, which originates from a more biological perspective, views locust swarming as a scientific problem of its own exceptional merit. The main goal should, thus, be the analysis and prediction of natural swarm dynamics. We discuss the properties of swarm dynamics using the tools of statistical physics, as well as the implications for laboratory experiments and natural swarms. Finally, we stress the importance of a combined-interdisciplinary, biological-theoretical effort in successfully confronting the challenges that locusts pose at both the theoretical and practical levels. '),
(87545, 2015, 'plos', 'Computing the Local Field Potential (LFP) from Integrate-and-Fire Network Models', 'Mazzoni, Alberto|Lindén, Henrik|Cuntz, Hermann|Lansner, Anders|Panzeri, Stefano|Einevoll, Gaute T', 'The Biorobotics Institute, Scuola Superiore SantAnna, Pontedera, Pisa, Italy.|Department of Neuroscience and Pharmacology, University of Copenhagen, Copenhagen, Denmark.|Ernst Strüngmann Institute (ESI) for Neuroscience in Cooperation with Max Planck Society, Frankfurt/Main, Germany.|Department of Computational Biology, School of Computer Science and Communication, Royal Institute of Technology-KTH, Stockholm, Sweden.|Neural Computation Laboratory, Center for Neuroscience and Cognitive Systems @UniTn, Istituto Italiano di Tecnologia, Rovereto, Italy.|Department of Mathematical Sciences and Technology, Norwegian University of Life Sciences, Ås, Norway.', 'Italy|Denmark|Germany|Sweden|Italy|Norway', 48, 'Action Potentials|Brain|Brain Mapping|Computer Simulation|Electromagnetic Fields|Humans|Membrane Potentials|Models, Neurological|Nerve Net|Neurons|Synaptic Transmission', 'Journal Article', '10.1371/journal.pcbi.1004584', '26657024', 'Leaky integrate-and-fire (LIF) network models are commonly used to study how the spiking dynamics of neural networks changes with stimuli, tasks or dynamic network states. However, neurophysiological studies in vivo often rather measure the mass activity of neuronal microcircuits with the local field potential (LFP). Given that LFPs are generated by spatially separated currents across the neuronal membrane, they cannot be computed directly from quantities defined in models of point-like LIF neurons. Here, we explore the best approximation for predicting the LFP based on standard output from point-neuron LIF networks. To search for this best LFP proxy, we compared LFP predictions from candidate proxies based on LIF network output (e.g, firing rates, membrane potentials, synaptic currents) with ground-truth LFP obtained when the LIF network synaptic input currents were injected into an analogous three-dimensional (3D) network model of multi-compartmental neurons with realistic morphology, spatial distributions of somata and synapses. We found that a specific fixed linear combination of the LIF synaptic currents provided an accurate LFP proxy, accounting for most of the variance of the LFP time course observed in the 3D network for all recording locations. This proxy performed well over a broad set of conditions, including substantial variations of the neuronal morphologies. Our results provide a simple formula for estimating the time course of the LFP from LIF network simulations in cases where a single pyramidal population dominates the LFP generation, and thereby facilitate quantitative comparison between computational models and experimental LFP recordings in vivo. '),
(87546, 2015, 'plos', 'Simulations Meet Experiment to Reveal New Insights into DNA Intrinsic Mechanics', 'Ben Imeddourene, Akli|Elbahnsi, Ahmad|Guxc3xa9roult, Marc|Oguey, Christophe|Foloppe, Nicolas|Hartmann, Brigitte', 'LBPA, CNRS, ENS Cachan, Universitxc3xa9 Paris-Saclay, Cachan, France.|LBPA, CNRS, ENS Cachan, Universitxc3xa9 Paris-Saclay, Cachan, France.|UMR S665, INSERM, Universitxc3xa9 Paris Diderot, INTS, Paris, France.|LPTM, UMR 8089, Universitxc3xa9 de Cergy-Pontoise, Cergy-Pontoise, France.|Cambridge, United Kingdom.|LBPA, CNRS, ENS Cachan, Universitxc3xa9 Paris-Saclay, Cachan, France.', 'France|France|France|France|United Kingdom|France', 13, 'Base Sequence|Models, Chemical|Molecular Dynamics Simulation|Molecular Sequence Data|Nucleic Acid Conformation|Sequence Analysis, Protein|Structure-Activity Relationship', 'Journal Article', '10.1371/journal.pcbi.1004631', '26657165', 'The accurate prediction of the structure and dynamics of DNA remains a major challenge in computational biology due to the dearth of precise experimental information on DNA free in solution and limitations in the DNA force-fields underpinning the simulations. A new generation of force-fields has been developed to better represent the sequence-dependent B-DNA intrinsic mechanics, in particular with respect to the BI xe2x86x94 BII backbone equilibrium, which is essential to understand the B-DNA properties. Here, the performance of MD simulations with the newly updated force-fields Parmbsc0xcexb5xcexb6OLI and CHARMM36 was tested against a large ensemble of recent NMR data collected on four DNA dodecamers involved in nucleosome positioning. We find impressive progress towards a coherent, realistic representation of B-DNA in solution, despite residual shortcomings. This improved representation allows new and deeper interpretation of the experimental observables, including regarding the behavior of facing phosphate groups in complementary dinucleotides, and their modulation by the sequence. It also provides the opportunity to extensively revisit and refine the coupling between backbone states and inter base pair parameters, which emerges as a common theme across all the complementary dinucleotides. In sum, the global agreement between simulations and experiment reveals new aspects of intrinsic DNA mechanics, a key component of DNA-protein recognition. ');
INSERT INTO `papers` (`id`, `ano`, `journal`, `titulo`, `autores`, `afiliacao`, `pais`, `citacoes`, `palavra_chave`, `categorias`, `doi`, `pubmed`, `abstract`) VALUES
(87547, 2015, 'plos', 'MIiSR: Molecular Interactions in Super-Resolution Imaging Enables the Analysis of Protein Interactions, Dynamics and Formation of Multi-protein Structures', 'Caetano, Fabiana A|Dirk, Brennan S|Tam, Joshua H K|Cavanagh, P Craig|Goiko, Maria|Ferguson, Stephen S G|Pasternak, Stephen H|Dikeakos, Jimmy D|de Bruyn, John R|Heit, Bryan', 'The J. Allyn Taylor Centre for Cell Biology, Robarts Research Institute and the Department of Physiology and Pharmacology, The University of Western Ontario, London, Ontario, Canada.|Department of Microbiology and Immunology, The University of Western Ontario, London, Ontario, Canada.|The J. Allyn Taylor Centre for Cell Biology, Robarts Research Institute and the Department of Physiology and Pharmacology, The University of Western Ontario, London, Ontario, Canada.|Department of Microbiology and Immunology, The University of Western Ontario, London, Ontario, Canada.|Department of Microbiology and Immunology, The University of Western Ontario, London, Ontario, Canada.|Cellular and Molecular Medicine, University of Ottawa, Ottawa, Ontario, Canada.|The J. Allyn Taylor Centre for Cell Biology, Robarts Research Institute and the Department of Physiology and Pharmacology, The University of Western Ontario, London, Ontario, Canada.|Department of Microbiology and Immunology, The University of Western Ontario, London, Ontario, Canada.|Department of Physics and Astronomy, The University of Western Ontario, London, Ontario, Canada.|Department of Microbiology and Immunology, The University of Western Ontario, London, Ontario, Canada.', 'Canada|Canada|Canada|Canada|Canada|Canada|Canada|Canada|Canada|Canada', 19, 'Algorithms|Computer Graphics|Computer Simulation|Image Interpretation, Computer-Assisted|Models, Biological|Models, Chemical|Molecular Imaging|Multiprotein Complexes|Protein Interaction Mapping|Reproducibility of Results|Sensitivity and Specificity|Software|User-Computer Interface', 'Journal Article', '10.1371/journal.pcbi.1004634', '26657340', 'Our current understanding of the molecular mechanisms which regulate cellular processes such as vesicular trafficking has been enabled by conventional biochemical and microscopy techniques. However, these methods often obscure the heterogeneity of the cellular environment, thus precluding a quantitative assessment of the molecular interactions regulating these processes. Herein, we present Molecular Interactions in Super Resolution (MIiSR) software which provides quantitative analysis tools for use with super-resolution images. MIiSR combines multiple tools for analyzing intermolecular interactions, molecular clustering and image segmentation. These tools enable quantification, in the native environment of the cell, of molecular interactions and the formation of higher-order molecular complexes. The capabilities and limitations of these analytical tools are demonstrated using both modeled data and examples derived from the vesicular trafficking system, thereby providing an established and validated experimental workflow capable of quantitatively assessing molecular interactions and molecular complex formation within the heterogeneous environment of the cell. '),
(87548, 2015, 'plos', 'Predicting Surgery Targets in Temporal Lobe Epilepsy through Structural Connectome Based Simulations', 'Hutchings, Frances|Han, Cheol E|Keller, Simon S|Weber, Bernd|Taylor, Peter N|Kaiser, Marcus', 'Interdisciplinary Computing and Complex BioSystems, School of Computing Science, Newcastle University, Newcastle upon Tyne, United Kingdom.|Department of Biomedical Engineering, Korea University, Seoul, Republic of Korea.|Department of Molecular and Clinical Pharmacology, Institute of Translational Medicine, University of Liverpool, Liverpool, United Kingdom.|Center for Economics and Neuroscience, University of Bonn, Bonn, Germany.|Interdisciplinary Computing and Complex BioSystems, School of Computing Science, Newcastle University, Newcastle upon Tyne, United Kingdom.|Interdisciplinary Computing and Complex BioSystems, School of Computing Science, Newcastle University, Newcastle upon Tyne, United Kingdom.', 'United Kingdom|-|United Kingdom|Germany|United Kingdom|United Kingdom', 35, 'Adult|Aged|Computer Simulation|Connectome|Diffusion Tensor Imaging|Epilepsy, Temporal Lobe|Female|Hippocampus|Humans|Male|Middle Aged|Models, Anatomic|Models, Neurological|Monitoring, Intraoperative|Neurophysiological Monitoring|Patient-Specific Modeling|Preoperative Care|Surgery, Computer-Assisted|Treatment Outcome', 'Clinical Trial', '10.1371/journal.pcbi.1004642', '26657566', 'Temporal lobe epilepsy (TLE) is a prevalent neurological disorder resulting in disruptive seizures. In the case of drug resistant epilepsy resective surgery is often considered. This is a procedure hampered by unpredictable success rates, with many patients continuing to have seizures even after surgery. In this study we apply a computational model of epilepsy to patient specific structural connectivity derived from diffusion tensor imaging (DTI) of 22 individuals with left TLE and 39 healthy controls. We validate the model by examining patient-control differences in simulated seizure onset time and network location. We then investigate the potential of the model for surgery prediction by performing in silico surgical resections, removing nodes from patient networks and comparing seizure likelihood post-surgery to pre-surgery simulations. We find that, first, patients tend to transit from non-epileptic to epileptic states more often than controls in the model. Second, regions in the left hemisphere (particularly within temporal and subcortical regions) that are known to be involved in TLE are the most frequent starting points for seizures in patients in the model. In addition, our analysis also implicates regions in the contralateral and frontal locations which may play a role in seizure spreading or surgery resistance. Finally, the model predicts that patient-specific surgery (resection areas chosen on an individual, model-prompted, basis and not following a predefined procedure) may lead to better outcomes than the currently used routine clinical procedure. Taken together this work provides a first step towards patient specific computational modelling of epilepsy surgery in order to inform treatment strategies in individuals. '),
(87549, 2015, 'plos', 'Simple Plans or Sophisticated Habits? State, Transition and Learning Interactions in the Two-Step Task', 'Akam, Thomas|Costa, Rui|Dayan, Peter', 'Champalimaud Neuroscience Program, Champalimaud Centre for the Unknown, Lisbon, Portugal.|Champalimaud Neuroscience Program, Champalimaud Centre for the Unknown, Lisbon, Portugal.|Gatsby Computational Neuroscience Unit, UCL, London, United Kingdom.', 'Portugal|Portugal|United Kingdom', 0, 'Choice Behavior|Computer Simulation|Habits|Humans|Models, Neurological|Models, Statistical|Reinforcement (Psychology)|Reversal Learning|Task Performance and Analysis', 'Journal Article', '10.1371/journal.pcbi.1004648', '26657806', 'The recently developed two-step behavioural task promises to differentiate model-based from model-free reinforcement learning, while generating neurophysiologically-friendly decision datasets with parametric variation of decision variables. These desirable features have prompted its widespread adoption. Here, we analyse the interactions between a range of different strategies and the structure of transitions and outcomes in order to examine constraints on what can be learned from behavioural performance. The task involves a trade-off between the need for stochasticity, to allow strategies to be discriminated, and a need for determinism, so that it is worth subjects investment of effort to exploit the contingencies optimally. We show through simulation that under certain conditions model-free strategies can masquerade as being model-based. We first show that seemingly innocuous modifications to the task structure can induce correlations between action values at the start of the trial and the subsequent trial events in such a way that analysis based on comparing successive trials can lead to erroneous conclusions. We confirm the power of a suggested correction to the analysis that can alleviate this problem. We then consider model-free reinforcement learning strategies that exploit correlations between where rewards are obtained and which actions have high expected value. These generate behaviour that appears model-based under these, and also more sophisticated, analyses. Exploiting the full potential of the two-step task as a tool for behavioural neuroscience requires an understanding of these issues. '),
(87550, 2015, 'plos', 'The siRNA Non-seed Region and Its Target Sequences Are Auxiliary Determinants of Off-Target Effects', 'Kamola, Piotr J|Nakano, Yuko|Takahashi, Tomoko|Wilson, Paul A|Ui-Tei, Kumiko', 'Department of Surgery and Cancer, Imperial College London, London, United Kingdom.|Department of Biological Sciences, University of Tokyo, Bunkyo, Tokyo, Japan.|Department of Biological Sciences, University of Tokyo, Bunkyo, Tokyo, Japan.|Computational Biology, GlaxoSmithKline R&D, Stevenage, Hertfordshire, United Kingdom.|Department of Biological Sciences, University of Tokyo, Bunkyo, Tokyo, Japan.', 'United Kingdom|Japan|Japan|United Kingdom|Japan', 17, 'Base Pair Mismatch|Base Pairing|Base Sequence|Binding Sites|Gene Silencing|Gene Targeting|HeLa Cells|Humans|Molecular Sequence Data|RNA, Small Interfering|RNA-Induced Silencing Complex|Sequence Analysis, RNA|Transcription, Genetic', 'Journal Article', '10.1371/journal.pcbi.1004656', '26657993', 'RNA interference (RNAi) is a powerful tool for post-transcriptional gene silencing. However, the siRNA guide strand may bind unintended off-target transcripts via partial sequence complementarity by a mechanism closely mirroring micro RNA (miRNA) silencing. To better understand these off-target effects, we investigated the correlation between sequence features within various subsections of siRNA guide strands, and its corresponding target sequences, with off-target activities. Our results confirm previous reports that strength of base-pairing in the siRNA seed region is the primary factor determining the efficiency of off-target silencing. However, the degree of downregulation of off-target transcripts with shared seed sequence is not necessarily similar, suggesting that there are additional auxiliary factors that influence the silencing potential. Here, we demonstrate that both the melting temperature (Tm) in a subsection of siRNA non-seed region, and the GC contents of its corresponding target sequences, are negatively correlated with the efficiency of off-target effect. Analysis of experimentally validated miRNA targets demonstrated a similar trend, indicating a putative conserved mechanistic feature of seed region-dependent targeting mechanism. These observations may prove useful as parameters for off-target prediction algorithms and improve siRNA specificity design rules. '),
(87551, 2015, 'plos', 'Model-Based Evaluation of Spontaneous Tumor Regression in Pilocytic Astrocytoma', 'Buder, Thomas|Deutsch, Andreas|Klink, Barbara|Voss-Bxc3xb6hme, Anja', 'Zentrum fxc3xbcr Informationsdienste und Hochleistungsrechnen (ZIH), Technische Universitxc3xa4t Dresden, Dresden, Germany.|Zentrum fxc3xbcr Informationsdienste und Hochleistungsrechnen (ZIH), Technische Universitxc3xa4t Dresden, Dresden, Germany.|Institut fxc3xbcr Klinische Genetik, Medizinische Fakultxc3xa4t Carl Gustav Carus, Technische Universitxc3xa4t Dresden, Dresden, Germany.|Zentrum fxc3xbcr Informationsdienste und Hochleistungsrechnen (ZIH), Technische Universitxc3xa4t Dresden, Dresden, Germany.', 'Germany|Germany|Germany|Germany', 10, 'Apoptosis|Astrocytoma|Brain Neoplasms|Cell Proliferation|Computer Simulation|Humans|Models, Biological|Models, Statistical|Mutation|Neoplasm Regression, Spontaneous|Neoplasm, Residual', 'Journal Article', '10.1371/journal.pcbi.1004662', '26658166', 'Pilocytic astrocytoma (PA) is the most common brain tumor in children. This tumor is usually benign and has a good prognosis. Total resection is the treatment of choice and will cure the majority of patients. However, often only partial resection is possible due to the location of the tumor. In that case, spontaneous regression, regrowth, or progression to a more aggressive form have been observed. The dependency between the residual tumor size and spontaneous regression is not understood yet. Therefore, the prognosis is largely unpredictable and there is controversy regarding the management of patients for whom complete resection cannot be achieved. Strategies span from pure observation (wait and see) to combinations of surgery, adjuvant chemotherapy, and radiotherapy. Here, we introduce a mathematical model to investigate the growth and progression behavior of PA. In particular, we propose a Markov chain model incorporating cell proliferation and death as well as mutations. Our model analysis shows that the tumor behavior after partial resection is essentially determined by a risk coefficient xcexb3, which can be deduced from epidemiological data about PA. Our results quantitatively predict the regression probability of a partially resected benign PA given the residual tumor size and lead to the hypothesis that this dependency is linear, implying that removing any amount of tumor mass will improve prognosis. This finding stands in contrast to diffuse malignant glioma where an extent of resection threshold has been experimentally shown, below which no benefit for survival is expected. These results have important implications for future therapeutic studies in PA that should include residual tumor volume as a prognostic factor. '),
(87552, 2015, 'plos', 'Operational Principles for the Dynamics of the In Vitro ParA-ParB System', 'Jindal, Lavisha|Emberly, Eldon', 'Physics Department, Simon Fraser University, Burnaby, British Columbia, Canada.|Physics Department, Simon Fraser University, Burnaby, British Columbia, Canada.', 'Canada|Canada', 0, 'Bacterial Proteins|Binding Sites|DNA|Diffusion|Immunomagnetic Separation|Models, Chemical|Models, Statistical|Molecular Dynamics Simulation|Protein Binding|Spatio-Temporal Analysis', 'Journal Article', '10.1371/journal.pcbi.1004651', '26670738', 'In many bacteria the ParA-ParB protein system is responsible for actively segregating DNA during replication. ParB proteins move by interacting with DNA bound ParA-ATP, stimulating their unbinding by catalyzing hydrolysis, that leads to rectified motion due to the creation of a wake of depleted ParA. Recent in vitro experiments have shown that a ParB covered magnetic bead can move with constant speed over a DNA covered substrate that is bound by ParA. It has been suggested that the formation of a gradient in ParA leads to diffusion-ratchet like motion of the ParB bead but how it forms and generates a force is still a matter of exploration. Here we develop a deterministic model for the in vitro ParA-ParB system and show that a ParA gradient can spontaneously form due to any amount of initial spatial noise in bound ParA. The speed of the bead is independent of this noise but depends on the ratio of the range of ParA-ParB force on the bead to that of removal of surface bound ParA by ParB. We find that at a particular ratio the speed attains a maximal value. We also consider ParA rebinding (including cooperativity) and ParA surface diffusion independently as mechanisms for ParA recovery on the surface. Depending on whether the DNA covered surface is undersaturated or saturated with ParA, we find that the bead can accelerate persistently or potentially stall. Our model highlights key requirements of the ParA-ParB driving force that are necessary for directed motion in the in vitro system that may provide insight into the in vivo dynamics of the ParA-ParB system. '),
(87553, 2015, 'plos', 'Modeling Fatty Acid Transfer from Artery to Cardiomyocyte', 'Arts, Theo|Reneman, Robert S|Bassingthwaighte, James B|van der Vusse, Ger J', 'Department of Biomedical Engineering, CARIM, Maastricht University, Maastricht, the Netherlands.|Department of Physiology, CARIM, Maastricht University, Maastricht, the Netherlands.|Department of Bioengineering, University of Washington, Seattle, Washington, United States of America.|Department of Physiology, CARIM, Maastricht University, Maastricht, the Netherlands.', 'Netherlands|Netherlands|United States|Netherlands', 1, 'Biological Transport, Active|Computer Simulation|Coronary Vessels|Fatty Acid-Binding Proteins|Fatty Acids|Humans|Models, Cardiovascular|Myocytes, Cardiac|Serum Albumin', 'Journal Article', '10.1371/journal.pcbi.1004666', '26675003', 'Despite the importance of oxidation of blood-borne long-chain fatty acids (Fa) in the cardiomyocytes for contractile energy of the heart, the mechanisms underlying the transfer of Fa from the coronary plasma to the cardiomyocyte is still incompletely understood. To obtain detailed insight into this transfer process, we designed a novel model of Fa transfer dynamics from coronary plasma through the endothelial cells and interstitium to the cardiomyocyte, applying standard physicochemical principles on diffusion and on the chemical equilibrium of Fa binding to carrier proteins Cp, like albumin in plasma and interstitium and Fatty Acid-Binding Proteins within endothelium and cardiomyocytes. Applying these principles, the present model strongly suggests that in the heart, binding and release of Fa to and from Cp in the aqueous border zones on both sides of the cell membranes form the major hindrance to Fa transfer. Although often considered, the membrane itself appears not to be a significant hindrance to diffusion of Fa. Proteins, residing in the cellular membrane, may facilitate transfer of Fa between Cp and membrane. The model is suited to simulate multiple tracer dilution experiments performed on isolated rabbit hearts administrating albumin and Fa as tracer substances into the coronary arterial perfusion line. Using parameter values on myocardial ultrastructure and physicochemical properties of Fa and Cp as reported in literature, simulated washout curves appear to be similar to the experimentally determined ones. We conclude therefore that the model is realistic and, hence, can be considered as a useful tool to better understand Fa transfer by evaluation of experimentally determined tracer washout curves. '),
(87554, 2015, 'plos', 'Dynamic Network Drivers of Seizure Generation, Propagation and Termination in Human Neocortical Epilepsy', 'Khambhati, Ankit N|Davis, Kathryn A|Oommen, Brian S|Chen, Stephanie H|Lucas, Timothy H|Litt, Brian|Bassett, Danielle S', 'Department of Bioengineering, University of Pennsylvania, Philadelphia, Pennsylvania, United States of America.|Penn Center for Neuroengineering and Therapeutics, University of Pennsylvania, Philadelphia, Pennsylvania, United States of America.|Penn Center for Neuroengineering and Therapeutics, University of Pennsylvania, Philadelphia, Pennsylvania, United States of America.|Penn Center for Neuroengineering and Therapeutics, University of Pennsylvania, Philadelphia, Pennsylvania, United States of America.|Penn Center for Neuroengineering and Therapeutics, University of Pennsylvania, Philadelphia, Pennsylvania, United States of America.|Department of Bioengineering, University of Pennsylvania, Philadelphia, Pennsylvania, United States of America.|Department of Bioengineering, University of Pennsylvania, Philadelphia, Pennsylvania, United States of America.', 'United States|United States|United States|United States|United States|United States|United States', 83, 'Action Potentials|Computer Simulation|Epilepsy|Humans|Models, Neurological|Neocortex|Nerve Net|Neural Inhibition|Seizures|Synaptic Transmission', 'Journal Article', '10.1371/journal.pcbi.1004608', '26680762', 'The epileptic network is characterized by pathologic, seizure-generating foci embedded in a web of structural and functional connections. Clinically, seizure foci are considered optimal targets for surgery. However, poor surgical outcome suggests a complex relationship between foci and the surrounding network that drives seizure dynamics. We developed a novel technique to objectively track seizure states from dynamic functional networks constructed from intracranial recordings. Each dynamical state captures unique patterns of network connections that indicate synchronized and desynchronized hubs of neural populations. Our approach suggests that seizures are generated when synchronous relationships near foci work in tandem with rapidly changing desynchronous relationships from the surrounding epileptic network. As seizures progress, topographical and geometrical changes in network connectivity strengthen and tighten synchronous connectivity near foci-a mechanism that may aid seizure termination. Collectively, our observations implicate distributed cortical structures in seizure generation, propagation and termination, and may have practical significance in determining which circuits to modulate with implantable devices. '),
(87555, 2015, 'plos', 'A Large-Scale Assessment of Nucleic Acids Binding Site Prediction Programs', 'Miao, Zhichao|Westhof, Eric', 'Architecture et Réactivité de lARN, Université de Strasbourg, Institut de Biologie Moléculaire et Cellulaire du CNRS, Strasbourg, France.|Architecture et Réactivité de lARN, Université de Strasbourg, Institut de Biologie Moléculaire et Cellulaire du CNRS, Strasbourg, France.', 'France|France', 0, 'Amino Acid Sequence|Binding Sites|Models, Chemical|Molecular Docking Simulation|Molecular Sequence Data|Nucleic Acids|Protein Binding|Protein Interaction Mapping|Proteins|Sequence Analysis, Protein', 'Journal Article', '10.1371/journal.pcbi.1004639', '26681179', 'Computational prediction of nucleic acid binding sites in proteins are necessary to disentangle functional mechanisms in most biological processes and to explore the binding mechanisms. Several strategies have been proposed, but the state-of-the-art approaches display a great diversity in i) the definition of nucleic acid binding sites, ii) the training and test datasets, iii) the algorithmic methods for the prediction strategies, iv) the performance measures and v) the distribution and availability of the prediction programs. Here we report a large-scale assessment of 19 web servers and 3 stand-alone programs on 41 datasets including more than 5000 proteins derived from 3D structures of protein-nucleic acid complexes. Well-defined binary assessment criteria (specificity, sensitivity, precision, accuracy…) are applied. We found that i) the tools have been greatly improved over the years, ii) some of the approaches suffer from theoretical defects and there is still room for sorting out the essential mechanisms of binding, iii) RNA binding and DNA binding appear to follow similar driving forces and iv) dataset bias may exist in some methods. '),
(87556, 2015, 'plos', 'High-Specificity Targeted Functional Profiling in Microbial Communities with ShortBRED', 'Kaminski, James|Gibson, Molly K|Franzosa, Eric A|Segata, Nicola|Dantas, Gautam|Huttenhower, Curtis', 'Department of Biostatistics, Harvard T.H. Chan School of Public Health, Boston, Massachusetts, United States of America.|Center for Genome Sciences and Systems Biology, Washington University School of Medicine, St. Louis, Missouri, United States of America.|Department of Biostatistics, Harvard T.H. Chan School of Public Health, Boston, Massachusetts, United States of America.|Centre for Integrative Biology (CIBIO), University of Trento, Trento, Trentino, Italy.|Center for Genome Sciences and Systems Biology, Washington University School of Medicine, St. Louis, Missouri, United States of America.|Department of Biostatistics, Harvard T.H. Chan School of Public Health, Boston, Massachusetts, United States of America.', 'United States|United States|United States|Italy|United States|United States', 0, 'Algorithms|Bacterial Proteins|Genetic Markers|High-Throughput Nucleotide Sequencing|Humans|Microbiota|Open Reading Frames|Reproducibility of Results|Sensitivity and Specificity|Sequence Alignment|Software', 'Journal Article', '10.1371/journal.pcbi.1004557', '26682918', 'Profiling microbial community function from metagenomic sequencing data remains a computationally challenging problem. Mapping millions of DNA reads from such samples to reference protein databases requires long run-times, and short read lengths can result in spurious hits to unrelated proteins (loss of specificity). We developed ShortBRED (Short, Better Representative Extract Dataset) to address these challenges, facilitating fast, accurate functional profiling of metagenomic samples. ShortBRED consists of two components: (i) a method that reduces reference proteins of interest to short, highly representative amino acid sequences (markers) and (ii) a search step that maps reads to these markers to quantify the relative abundance of their associated proteins. After evaluating ShortBRED on synthetic data, we applied it to profile antibiotic resistance protein families in the gut microbiomes of individuals from the United States, China, Malawi, and Venezuela. Our results support antibiotic resistance as a core function in the human gut microbiome, with tetracycline-resistant ribosomal protection proteins and Class A beta-lactamases being the most widely distributed resistance mechanisms worldwide. ShortBRED markers are applicable to other homology-based search tasks, which we demonstrate here by identifying phylogenetic signatures of antibiotic resistance across more than 3,000 microbial isolate genomes. ShortBRED can be applied to profile a wide variety of protein families of interest, the software, source code, and documentation are available for download at http://huttenhower.sph.harvard.edu/shortbred. '),
(87557, 2015, 'plos', 'Network-Based Integration of Disparate Omic Data To Identify Silent Players in Cancer', 'Ruffalo, Matthew|Koyutürk, Mehmet|Sharan, Roded', 'Department of Electrical Engineering and Computer Science, Case Western Reserve University, Cleveland, Ohio, United States of America.|Department of Electrical Engineering and Computer Science, Case Western Reserve University, Cleveland, Ohio, United States of America.|School of Computer Science, Tel Aviv University, Tel Aviv, Israel.', 'United States|United States|Israel', 0, 'Algorithms|Chromosome Mapping|Data Mining|Databases, Genetic|Gene Expression Profiling|Genes, Neoplasm|Genetic Association Studies|Genetic Markers|Genomics|Humans|Neoplasm Proteins|Neoplasms|Signal Transduction|Silent Mutation', 'Journal Article', '10.1371/journal.pcbi.1004595', '26683094', 'Development of high-throughput monitoring technologies enables interrogation of cancer samples at various levels of cellular activity. Capitalizing on these developments, various public efforts such as The Cancer Genome Atlas (TCGA) generate disparate omic data for large patient cohorts. As demonstrated by recent studies, these heterogeneous data sources provide the opportunity to gain insights into the molecular changes that drive cancer pathogenesis and progression. However, these insights are limited by the vast search space and as a result low statistical power to make new discoveries. In this paper, we propose methods for integrating disparate omic data using molecular interaction networks, with a view to gaining mechanistic insights into the relationship between molecular changes at different levels of cellular activity. Namely, we hypothesize that genes that play a role in cancer development and progression may be implicated by neither frequent mutation nor differential expression, and that network-based integration of mutation and differential expression data can reveal these silent players. For this purpose, we utilize network-propagation algorithms to simulate the information flow in the cell at a sample-specific resolution. We then use the propagated mutation and expression signals to identify genes that are not necessarily mutated or differentially expressed genes, but have an essential role in tumor development and patient outcome. We test the proposed method on breast cancer and glioblastoma multiforme data obtained from TCGA. Our results show that the proposed method can identify important proteins that are not readily revealed by molecular data, providing insights beyond what can be gleaned by analyzing different types of molecular data in isolation. '),
(87558, 2015, 'plos', 'Computer Simulations Imply Forelimb-Dominated Underwater Flight in Plesiosaurs', 'Liu, Shiqiu|Smith, Adam S|Gu, Yuting|Tan, Jie|Liu, C Karen|Turk, Greg', 'School of Interactive Computing, Georgia Institute of Technology, Atlanta, Georgia, United States of America.|Nottingham Natural History Museum, Wollaton Hall, Nottingham, United Kingdom.|School of Interactive Computing, Georgia Institute of Technology, Atlanta, Georgia, United States of America.|School of Interactive Computing, Georgia Institute of Technology, Atlanta, Georgia, United States of America.|School of Interactive Computing, Georgia Institute of Technology, Atlanta, Georgia, United States of America.|School of Interactive Computing, Georgia Institute of Technology, Atlanta, Georgia, United States of America.', 'Georgia|United Kingdom|Georgia|Georgia|Georgia|Georgia', 12, 'Animals|Computer Simulation|Dinosaurs|Flight, Animal|Forelimb|Hindlimb|Models, Biological|Rheology|Swimming|Wings, Animal', 'Journal Article', '10.1371/journal.pcbi.1004605', '26683221', 'Plesiosaurians are an extinct group of highly derived Mesozoic marine reptiles with a global distribution that spans 135 million years from the Early Jurassic to the Late Cretaceous. During their long evolutionary history they maintained a unique body plan with two pairs of large wing-like flippers, but their locomotion has been a topic of debate for almost 200 years. Key areas of controversy have concerned the most efficient biologically possible limb stroke, e.g. whether it consisted of rowing, underwater flight, or modified underwater flight, and how the four limbs moved in relation to each other: did they move in or out of phase? Previous studies have investigated plesiosaur swimming using a variety of methods, including skeletal analysis, human swimmers, and robotics. We adopt a novel approach using a digital, three-dimensional, articulated, free-swimming plesiosaur in a simulated fluid. We generated a large number of simulations under various joint degrees of freedom to investigate how the locomotory repertoire changes under different parameters. Within the biologically possible range of limb motion, the simulated plesiosaur swims primarily with its forelimbs using an unmodified underwater flight stroke, essentially the same as turtles and penguins. In contrast, the hindlimbs provide relatively weak thrust in all simulations. We conclude that plesiosaurs were forelimb-dominated swimmers that used their hind limbs mainly for maneuverability and stability. '),
(87559, 2015, 'plos', 'Computational Models Describing Possible Mechanisms for Generation of Excessive Beta Oscillations in Parkinsons Disease', 'Pavlides, Alex|Hogan, S John|Bogacz, Rafal', 'MRC Unit for Brain Network Dynamics, University of Oxford, Oxford, United Kingdom.|Faculty of Engineering, University of Bristol, Bristol, United Kingdom.|MRC Unit for Brain Network Dynamics, University of Oxford, Oxford, United Kingdom.', 'United Kingdom|United Kingdom|United Kingdom', 0, 'Action Potentials|Beta Rhythm|Biological Clocks|Brain|Computer Simulation|Humans|Models, Neurological|Nerve Net|Oscillometry|Parkinson Disease', 'Journal Article', '10.1371/journal.pcbi.1004609', '26683341', 'In Parkinsons disease, an increase in beta oscillations within the basal ganglia nuclei has been shown to be associated with difficulty in movement initiation. An important role in the generation of these oscillations is thought to be played by the motor cortex and by a network composed of the subthalamic nucleus (STN) and the external segment of globus pallidus (GPe). Several alternative models have been proposed to describe the mechanisms for generation of the Parkinsonian beta oscillations. However, a recent experimental study of Tachibana and colleagues yielded results which are challenging for all published computational models of beta generation. That study investigated how the presence of beta oscillations in a primate model of Parkinsons disease is affected by blocking different connections of the STN-GPe circuit. Due to a large number of experimental conditions, the study provides strong constraints that any mechanistic model of beta generation should satisfy. In this paper we present two models consistent with the data of Tachibana et al. The first model assumes that Parkinsonian beta oscillation are generated in the cortex and the STN-GPe circuits resonates at this frequency. The second model additionally assumes that the feedback from STN-GPe circuit to cortex is important for maintaining the oscillations in the network. Predictions are made about experimental evidence that is required to differentiate between the two models, both of which are able to reproduce firing rates, oscillation frequency and effects of lesions carried out by Tachibana and colleagues. Furthermore, an analysis of the models reveals how the amplitude and frequency of the generated oscillations depend on parameters. '),
(87560, 2015, 'plos', 'The Essential Complexity of Auditory Receptive Fields', 'Thorson, Ivar L|Liénard, Jean|David, Stephen V', 'Oregon Hearing Research Center, Oregon Health & Science University, Portland, Oregon, United States of America.|Department of Mathematics, Washington State University, Vancouver, Washington, United States of America.|Oregon Hearing Research Center, Oregon Health & Science University, Portland, Oregon, United States of America.', 'United States|United States|United States', 0, 'Acoustic Stimulation|Action Potentials|Algorithms|Animals|Auditory Cortex|Auditory Perception|Computer Simulation|Ferrets|Models, Neurological|Nerve Net|Sensory Receptor Cells|Signal Processing, Computer-Assisted', 'Journal Article', '10.1371/journal.pcbi.1004628', '26683490', 'Encoding properties of sensory neurons are commonly modeled using linear finite impulse response (FIR) filters. For the auditory system, the FIR filter is instantiated in the spectro-temporal receptive field (STRF), often in the framework of the generalized linear model. Despite widespread use of the FIR STRF, numerous formulations for linear filters are possible that require many fewer parameters, potentially permitting more efficient and accurate model estimates. To explore these alternative STRF architectures, we recorded single-unit neural activity from auditory cortex of awake ferrets during presentation of natural sound stimuli. We compared performance of > 1000 linear STRF architectures, evaluating their ability to predict neural responses to a novel natural stimulus. Many were able to outperform the FIR filter. Two basic constraints on the architecture lead to the improved performance: (1) factorization of the STRF matrix into a small number of spectral and temporal filters and (2) low-dimensional parameterization of the factorized filters. The best parameterized model was able to outperform the full FIR filter in both primary and secondary auditory cortex, despite requiring fewer than 30 parameters, about 10% of the number required by the FIR filter. After accounting for noise from finite data sampling, these STRFs were able to explain an average of 40% of A1 response variance. The simpler models permitted more straightforward interpretation of sensory tuning properties. They also showed greater benefit from incorporating nonlinear terms, such as short term plasticity, that provide theoretical advances over the linear model. Architectures that minimize parameter count while maintaining maximum predictive power provide insight into the essential degrees of freedom governing auditory cortical function. They also maximize statistical power available for characterizing additional nonlinear properties that limit current auditory models. '),
(87561, 2015, 'plos', 'Local Geometry and Evolutionary Conservation of Protein Surfaces Reveal the Multiple Recognition Patches in Protein-Protein Interactions', 'Laine, Elodie|Carbone, Alessandra', 'Sorbonne Universités, UPMC-Univ P6, CNRS, Laboratoire de Biologie Computationnelle et Quantitative-UMR 7238, Paris, France.|Sorbonne Universités, UPMC-Univ P6, CNRS, Laboratoire de Biologie Computationnelle et Quantitative-UMR 7238, Paris, France.', 'France|France', 0, 'Algorithms|Amino Acid Sequence|Binding Sites|Computer Simulation|Evolution, Molecular|Models, Chemical|Models, Genetic|Models, Molecular|Molecular Sequence Data|Protein Binding|Protein Conformation|Protein Interaction Mapping|Proteins|Sequence Analysis, Protein', 'Journal Article', '10.1371/journal.pcbi.1004580', '26690684', 'Protein-protein interactions (PPIs) are essential to all biological processes and they represent increasingly important therapeutic targets. Here, we present a new method for accurately predicting protein-protein interfaces, understanding their properties, origins and binding to multiple partners. Contrary to machine learning approaches, our method combines in a rational and very straightforward way three sequence- and structure-based descriptors of protein residues: evolutionary conservation, physico-chemical properties and local geometry. The implemented strategy yields very precise predictions for a wide range of protein-protein interfaces and discriminates them from small-molecule binding sites. Beyond its predictive power, the approach permits to dissect interaction surfaces and unravel their complexity. We show how the analysis of the predicted patches can foster new strategies for PPIs modulation and interaction surface redesign. The approach is implemented in JET2, an automated tool based on the Joint Evolutionary Trees (JET) method for sequence-based protein interface prediction. JET2 is freely available at www.lcqb.upmc.fr/JET2. '),
(87562, 2015, 'plos', 'Cultured Cortical Neurons Can Perform Blind Source Separation According to the Free-Energy Principle', 'Isomura, Takuya|Kotani, Kiyoshi|Jimbo, Yasuhiko', 'Department of Human and Engineered Environmental Studies, Graduate School of Frontier Sciences, The University of Tokyo, Hongo, Bunkyo-ku, Tokyo, Japan.|Research Center for Advanced Science and Technology, The University of Tokyo, Komaba, Meguro-ku, Tokyo, Japan.|Department of Precision Engineering, School of Engineering, The University of Tokyo, Hongo, Bunkyo-ku, Tokyo, Japan.', 'Japan|Japan|Japan', 0, 'Action Potentials|Animals|Cells, Cultured|Cerebral Cortex|Energy Transfer|Machine Learning|Models, Neurological|Models, Statistical|Nerve Net|Neurons|Pattern Recognition, Physiological|Principal Component Analysis|Rats', 'Journal Article', '10.1371/journal.pcbi.1004643', '26690814', 'Blind source separation is the computation underlying the cocktail party effect--a partygoer can distinguish a particular talkers voice from the ambient noise. Early studies indicated that the brain might use blind source separation as a signal processing strategy for sensory perception and numerous mathematical models have been proposed, however, it remains unclear how the neural networks extract particular sources from a complex mixture of inputs. We discovered that neurons in cultures of dissociated rat cortical cells could learn to represent particular sources while filtering out other signals. Specifically, the distinct classes of neurons in the culture learned to respond to the distinct sources after repeating training stimulation. Moreover, the neural network structures changed to reduce free energy, as predicted by the free-energy principle, a candidate unified theory of learning and memory, and by Jaynes principle of maximum entropy. This implicit learning can only be explained by some form of Hebbian plasticity. These results are the first in vitro (as opposed to in silico) demonstration of neural networks performing blind source separation, and the first formal demonstration of neuronal self-organization under the free energy principle. '),
(87563, 2015, 'plos', 'Defectors Can Create Conditions That Rescue Cooperation', 'Waite, Adam James|Cannistra, Caroline|Shou, Wenying', 'Molecular and Cellular Biology Program, University of Washington, Seattle, Washington, United States of America.|Division of Basic Sciences, Fred Hutchinson Cancer Research Center, Seattle, Washington, United States of America.|Division of Basic Sciences, Fred Hutchinson Cancer Research Center, Seattle, Washington, United States of America.', 'United States|United States|United States', 0, 'Altruism|Biological Evolution|Cooperative Behavior|Ecosystem|Game Theory|Genetic Fitness|Genetics, Population|Models, Genetic|Models, Statistical|Mutation|Population Density', 'Journal Article', '10.1371/journal.pcbi.1004645', '26690946', 'Cooperation based on the production of costly common goods is observed throughout nature. This is puzzling, as cooperation is vulnerable to exploitation by defectors which enjoy a fitness advantage by consuming the common good without contributing fairly. Depletion of the common good can lead to population collapse and the destruction of cooperation. However, population collapse implies small population size, which, in a structured population, is known to favor cooperation. This happens because small population size increases variability in cooperator frequency across different locations. Since individuals in cooperator-dominated locations (which are most likely cooperators) will grow more than those in defector-dominated locations (which are most likely defectors), cooperators can outgrow defectors globally despite defectors outgrowing cooperators in each location. This raises the possibility that defectors can lead to conditions that sometimes rescue cooperation from defector-induced destruction. We demonstrate multiple mechanisms through which this can occur, using an individual-based approach to model stochastic birth, death, migration, and mutation events. First, during defector-induced population collapse, defectors occasionally go extinct before cooperators by chance, which allows cooperators to grow. Second, empty locations, either preexisting or created by defector-induced population extinction, can favor cooperation because they allow cooperator but not defector migrants to grow. These factors lead to the counterintuitive result that the initial presence of defectors sometimes allows better survival of cooperation compared to when defectors are initially absent. Finally, we find that resource limitation, inducible by defectors, can select for mutations adaptive to resource limitation. When these mutations are initially present at low levels or continuously generated at a moderate rate, they can favor cooperation by further reducing local population size. We predict that in a structured population, small population sizes precipitated by defectors provide a built-in mechanism for the persistence of cooperation. '),
(87564, 2015, 'plos', 'Structural and Energetic Characterization of the Ankyrin Repeat Protein Family', 'Parra, R Gonzalo|Espada, Rocío|Verstraete, Nina|Ferreiro, Diego U', 'Protein Physiology Lab, Dep de Química Biológica, Facultad de Ciencias Exactas y Naturales, UBA-CONICET-IQUIBICEN, Buenos Aires, Argentina.|Protein Physiology Lab, Dep de Química Biológica, Facultad de Ciencias Exactas y Naturales, UBA-CONICET-IQUIBICEN, Buenos Aires, Argentina.|Protein Physiology Lab, Dep de Química Biológica, Facultad de Ciencias Exactas y Naturales, UBA-CONICET-IQUIBICEN, Buenos Aires, Argentina.|Protein Physiology Lab, Dep de Química Biológica, Facultad de Ciencias Exactas y Naturales, UBA-CONICET-IQUIBICEN, Buenos Aires, Argentina.', 'Argentina|Argentina|Argentina|Argentina', 21, 'Amino Acid Sequence|Ankyrin Repeat|Ankyrins|Computer Simulation|Energy Transfer|Models, Chemical|Models, Molecular|Molecular Sequence Data|Sequence Analysis, Protein', 'Journal Article', '10.1371/journal.pcbi.1004659', '26691182', 'Ankyrin repeat containing proteins are one of the most abundant solenoid folds. Usually implicated in specific protein-protein interactions, these proteins are readily amenable for design, with promising biotechnological and biomedical applications. Studying repeat protein families presents technical challenges due to the high sequence divergence among the repeating units. We developed and applied a systematic method to consistently identify and annotate the structural repetitions over the members of the complete Ankyrin Repeat Protein Family, with increased sensitivity over previous studies. We statistically characterized the number of repeats, the folding of the repeat-arrays, their structural variations, insertions and deletions. An energetic analysis of the local frustration patterns reveal the basic features underlying fold stability and its relation to the functional binding regions. We found a strong linear correlation between the conservation of the energetic features in the repeat arrays and their sequence variations, and discuss new insights into the organization and function of these ubiquitous proteins. '),
(87565, 2015, 'plos', 'Coherent Motion of Monolayer Sheets under Confinement and Its Pathological Implications', 'Soumya, S S|Gupta, Animesh|Cugno, Andrea|Deseri, Luca|Dayal, Kaushik|Das, Dibyendu|Sen, Shamik|Inamdar, Mandar M', 'Department of Civil Engineering, Indian Institute of Technology Bombay, Mumbai, India.|Department of Physics, Indian Institute of Technology Bombay, Mumbai, India.|DICAM-Department of Civil, Environmental and Mechanical Engineering, University of Trento, Trento, Italy.|DICAM-Department of Civil, Environmental and Mechanical Engineering, University of Trento, Trento, Italy.|Department of Civil and Environmental Engineering, Carnegie Mellon University, Pittsburgh, Pennsylvania, United States of America.|Department of Physics, Indian Institute of Technology Bombay, Mumbai, India.|Department of Biosciences and Bioengineering, Indian Institute of Technology Bombay, Mumbai, India.|Department of Civil Engineering, Indian Institute of Technology Bombay, Mumbai, India.', 'India|India|Italy|Italy|United States|India|India|India', 5, 'Animals|Cell Aggregation|Cell Communication|Cell Movement|Computer Simulation|Elasticity|Epithelial Cells|Focal Adhesions|Humans|Mechanotransduction, Cellular|Models, Biological|Neoplasm Invasiveness', 'Journal Article', '10.1371/journal.pcbi.1004670', '26691341', 'Coherent angular rotation of epithelial cells is thought to contribute to many vital physiological processes including tissue morphogenesis and glandular formation. However, factors regulating this motion, and the implications of this motion if perturbed, remain incompletely understood. In the current study, we address these questions using a cell-center based model in which cells are polarized, motile, and interact with the neighboring cells via harmonic forces. We demonstrate that, a simple evolution rule in which the polarization of any cell tends to orient with its velocity vector can induce coherent motion in geometrically confined environments. In addition to recapitulating coherent rotational motion observed in experiments, our results also show the presence of radial movements and tissue behavior that can vary between solid-like and fluid-like. We show that the pattern of coherent motion is dictated by the combination of different physical parameters including number density, cell motility, system size, bulk cell stiffness and stiffness of cell-cell adhesions. We further observe that perturbations in the form of cell division can induce a reversal in the direction of motion when cell division occurs synchronously. Moreover, when the confinement is removed, we see that the existing coherent motion leads to cell scattering, with bulk cell stiffness and stiffness of cell-cell contacts dictating the invasion pattern. In summary, our study provides an in-depth understanding of the origin of coherent rotation in confined tissues, and extracts useful insights into the influence of various physical parameters on the pattern of such movements. ');
INSERT INTO `papers` (`id`, `ano`, `journal`, `titulo`, `autores`, `afiliacao`, `pais`, `citacoes`, `palavra_chave`, `categorias`, `doi`, `pubmed`, `abstract`) VALUES
(87566, 2015, 'plos', 'Recombination Enhances HIV-1 Envelope Diversity by Facilitating the Survival of Latent Genomic Fragments in the Plasma Virus Population', 'Immonen, Taina T|Conway, Jessica M|Romero-Severson, Ethan O|Perelson, Alan S|Leitner, Thomas', 'Theoretical Biology and Biophysics, Los Alamos National Laboratory, Los Alamos, New Mexico, United States of America.|Department of Mathematics, The Pennsylvania State University, University Park, Pennsylvania, 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.|Theoretical Biology and Biophysics, Los Alamos National Laboratory, Los Alamos, New Mexico, United States of America.', 'Mexico|United States|Mexico|Mexico|Mexico', 9, 'Cell Survival|Evolution, Molecular|Genetic Fitness|Genetic Variation|Genome, Viral|HIV-1|Humans|Plasma|Recombination, Genetic|Viral Envelope Proteins|Virus Latency', 'Journal Article', '10.1371/journal.pcbi.1004625', '26693708', 'HIV-1 is subject to immune pressure exerted by the host, giving variants that escape the immune response an advantage. Virus released from activated latent cells competes against variants that have continually evolved and adapted to host immune pressure. Nevertheless, there is increasing evidence that virus displaying a signal of latency survives in patient plasma despite having reduced fitness due to long-term immune memory. We investigated the survival of virus with latent envelope genomic fragments by simulating within-host HIV-1 sequence evolution and the cycling of viral lineages in and out of the latent reservoir. Our model incorporates a detailed mutation process including nucleotide substitution, recombination, latent reservoir dynamics, diversifying selection pressure driven by the immune response, and purifying selection pressure asserted by deleterious mutations. We evaluated the ability of our model to capture sequence evolution in vivo by comparing our simulated sequences to HIV-1 envelope sequence data from 16 HIV-infected untreated patients. Empirical sequence divergence and diversity measures were qualitatively and quantitatively similar to those of our simulated HIV-1 populations, suggesting that our model invokes realistic trends of HIV-1 genetic evolution. Moreover, reconstructed phylogenies of simulated and patient HIV-1 populations showed similar topological structures. Our simulation results suggest that recombination is a key mechanism facilitating the persistence of virus with latent envelope genomic fragments in the productively infected cell population. Recombination increased the survival probability of latent virus forms approximately 13-fold. Prevalence of virus with latent fragments in productively infected cells was observed in only 2% of simulations when we ignored recombination, while the proportion increased to 27% of simulations when we allowed recombination. We also found that the selection pressures exerted by different fitness landscapes influenced the shape of phylogenies, diversity trends, and survival of virus with latent genomic fragments. Our model predicts that the persistence of latent genomic fragments from multiple different ancestral origins increases sequence diversity in plasma for reasonable fitness landscapes. '),
(87567, 2015, 'plos', 'Sources of Variability in a Synthetic Gene Oscillator', 'Veliz-Cuba, Alan|Hirning, Andrew J|Atanas, Adam A|Hussain, Faiza|Vancia, Flavia|Josixc4x87, Krexc5xa1imir|Bennett, Matthew R', 'Department of Biosciences, Rice University, Houston, Texas, United States of America.|Department of Biosciences, Rice University, Houston, Texas, United States of America.|Department of Biosciences, Rice University, Houston, Texas, United States of America.|Department of Biosciences, Rice University, Houston, Texas, United States of America.|Department of Mathematics, University of Houston, Houston, Texas, United States of America.|Department of Mathematics, University of Houston, Houston, Texas, United States of America.|Department of Biosciences, Rice University, Houston, Texas, United States of America.', 'United States|United States|United States|United States|United States|United States|United States', 9, 'Biological Clocks|Computer Simulation|Gene Expression Regulation|Gene Regulatory Networks|Genes, Synthetic|Genetic Variation|Humans|Male|Models, Genetic|Oscillometry', 'Journal Article', '10.1371/journal.pcbi.1004674', '26693906', 'Synthetic gene oscillators are small, engineered genetic circuits that produce periodic variations in target protein expression. Like other gene circuits, synthetic gene oscillators are noisy and exhibit fluctuations in amplitude and period. Understanding the origins of such variability is key to building predictive models that can guide the rational design of synthetic circuits. Here, we developed a method for determining the impact of different sources of noise in genetic oscillators by measuring the variability in oscillation amplitude and correlations between sister cells. We first used a combination of microfluidic devices and time-lapse fluorescence microscopy to track oscillations in cell lineages across many generations. We found that oscillation amplitude exhibited high cell-to-cell variability, while sister cells remained strongly correlated for many minutes after cell division. To understand how such variability arises, we constructed a computational model that identified the impact of various noise sources across the lineage of an initial cell. When each source of noise was appropriately tuned the model reproduced the experimentally observed amplitude variability and correlations, and accurately predicted outcomes under novel experimental conditions. Our combination of computational modeling and time-lapse data analysis provides a general way to examine the sources of variability in dynamic gene circuits. '),
(87568, 2015, 'plos', 'How Obstacles Perturb Population Fronts and Alter Their Genetic Structure', 'Möbius, Wolfram|Murray, Andrew W|Nelson, David R', 'Department of Physics, Harvard University, Cambridge, Massachusetts, United States of America.|FAS Center for Systems Biology, Harvard University, Cambridge, Massachusetts, United States of America.|Department of Physics, Harvard University, Cambridge, Massachusetts, United States of America.', 'United States|United States|United States', 11, 'Bacteriophage T7|Cell Movement|Ecosystem|Founder Effect|Gene Pool|Genetic Drift|Genetic Variation|Genetics, Population|Models, Genetic|Mutation', 'Journal Article', '10.1371/journal.pcbi.1004615', '26696601', 'As populations spread into new territory, environmental heterogeneities can shape the population front and genetic composition. We focus here on the effects of an important building block of heterogeneous environments, isolated obstacles. With a combination of experiments, theory, and simulation, we show how isolated obstacles both create long-lived distortions of the front shape and amplify the effect of genetic drift. A system of bacteriophage T7 spreading on a spatially heterogeneous Escherichia coli lawn serves as an experimental model system to study population expansions. Using an inkjet printer, we create well-defined replicates of the lawn and quantitatively study the population expansion of phage T7. The transient perturbations of the population front found in the experiments are well described by a model in which the front moves with constant speed. Independent of the precise details of the expansion, we show that obstacles create a kink in the front that persists over large distances and is insensitive to the details of the obstacles shape. The small deviations between experimental findings and the predictions of the constant speed model can be understood with a more general reaction-diffusion model, which reduces to the constant speed model when the obstacle size is large compared to the front width. Using this framework, we demonstrate that frontier genotypes just grazing the side of an isolated obstacle increase in abundance, a phenomenon we call geometry-enhanced genetic drift, complementary to the founder effect associated with spatial bottlenecks. Bacterial range expansions around nutrient-poor barriers and stochastic simulations confirm this prediction. The effect of the obstacle on the genealogy of individuals at the front is characterized by simulations and rationalized using the constant speed model. Lastly, we consider the effect of two obstacles on front shape and genetic composition of the population illuminating the effects expected from complex environments with many obstacles. '),
(87569, 2015, 'plos', 'Network-Based Isoform Quantification with RNA-Seq Data for Cancer Transcriptome Analysis', 'Zhang, Wei|Chang, Jae-Woong|Lin, Lilong|Minn, Kay|Wu, Baolin|Chien, Jeremy|Yong, Jeongsik|Zheng, Hui|Kuang, Rui', 'Department of Computer Science and Engineering, University of Minnesota Twin Cities, Minneapolis, Minnesota, United States of America.|Department of Biochemistry, Molecular Biology and Biophysics, University of Minnesota Twin Cities, Minneapolis, Minnesota, United States of America.|Guangzhou Institutes of Biomedicine and Health, Chinese Academy of Sciences, Guangzhou, Peoples Republic of China.|Department of Cancer Biology, University of Kansas Medical Center, Kansas City, Kansas, United States of America.|Division of Biostatistics, School of Public Health, University of Minnesota Twin Cities, Minneapolis, Minnesota, United States of America.|Department of Cancer Biology, University of Kansas Medical Center, Kansas City, Kansas, United States of America.|Department of Biochemistry, Molecular Biology and Biophysics, University of Minnesota Twin Cities, Minneapolis, Minnesota, United States of America.|Guangzhou Institutes of Biomedicine and Health, Chinese Academy of Sciences, Guangzhou, Peoples Republic of China.|Department of Computer Science and Engineering, University of Minnesota Twin Cities, Minneapolis, Minnesota, United States of America.', 'United States|United States|China|United States|United States|United States|United States|China|Unit', 6, 'Algorithms|Base Sequence|High-Throughput Nucleotide Sequencing|Humans|Molecular Sequence Data|Neoplasm Proteins|Neoplasms|Protein Interaction Mapping|Protein Isoforms|RNA, Neoplasm|Signal Transduction|Software|Transcriptome', 'Journal Article', '10.1371/journal.pcbi.1004465', '26699225', 'High-throughput mRNA sequencing (RNA-Seq) is widely used for transcript quantification of gene isoforms. Since RNA-Seq data alone is often not sufficient to accurately identify the read origins from the isoforms for quantification, we propose to explore protein domain-domain interactions as prior knowledge for integrative analysis with RNA-Seq data. We introduce a Network-based method for RNA-Seq-based Transcript Quantification (Net-RSTQ) to integrate protein domain-domain interaction network with short read alignments for transcript abundance estimation. Based on our observation that the abundances of the neighboring isoforms by domain-domain interactions in the network are positively correlated, Net-RSTQ models the expression of the neighboring transcripts as Dirichlet priors on the likelihood of the observed read alignments against the transcripts in one gene. The transcript abundances of all the genes are then jointly estimated with alternating optimization of multiple EM problems. In simulation Net-RSTQ effectively improved isoform transcript quantifications when isoform co-expressions correlate with their interactions. qRT-PCR results on 25 multi-isoform genes in a stem cell line, an ovarian cancer cell line, and a breast cancer cell line also showed that Net-RSTQ estimated more consistent isoform proportions with RNA-Seq data. In the experiments on the RNA-Seq data in The Cancer Genome Atlas (TCGA), the transcript abundances estimated by Net-RSTQ are more informative for patient sample classification of ovarian cancer, breast cancer and lung cancer. All experimental results collectively support that Net-RSTQ is a promising approach for isoform quantification. Net-RSTQ toolbox is available at http://compbio.cs.umn.edu/Net-RSTQ/. '),
(87570, 2015, 'plos', 'Elastohydrodynamics and Kinetics of Protein Patterning in the Immunological Synapse', 'Carlson, Andreas|Mahadevan, L', 'School of Engineering and Applied Sciences, Kavli Institute for Bionano Science and Technology, and Wyss Institute, Harvard University, Cambridge, United States of America.|School of Engineering and Applied Sciences, Kavli Institute for Bionano Science and Technology, and Wyss Institute, Harvard University, Cambridge, United States of America.', 'United States|United States', 12, 'Antigen-Presenting Cells|Computer Simulation|Elastic Modulus|Humans|Hydrodynamics|Immunological Synapses|Lipid Bilayers|Mechanotransduction, Cellular|Membrane Fluidity|Membrane Proteins|Models, Chemical|Models, Immunological|Models, Molecular|Protein Binding|T-Lymphocytes|Tensile Strength', 'Journal Article', '10.1371/journal.pcbi.1004481', '26699430', 'We propose a minimal mathematical model for the physical basis of membrane protein patterning in the immunological synapse (IS), which encompass membrane mechanics, protein binding kinetics and motion, and fluid flow in the synaptic cleft. Our theory leads to simple predictions for the spatial and temporal scales of protein cluster formation, growth and arrest as a function of membrane stiffness, rigidity and kinetics of the adhesive proteins, and the fluid flow in the synaptic cleft. Numerical simulations complement these scaling laws by quantifying the nucleation, growth and stabilization of proteins domains on the size of the cell. Direct comparison with experiment shows that passive elastohydrodynamics and kinetics of protein binding in the synaptic cleft can describe the short-time formation and organization of protein clusters, without evoking any active processes in the cytoskeleton. Despite the apparent complexity of the process, our analysis shows that just two dimensionless parameters characterize the spatial and temporal evolution of the protein pattern: a ratio of membrane elasticity to protein stiffness, and the ratio of a hydrodynamic time scale for fluid flow relative to the protein binding rate. A simple phase diagram encompasses the variety of patterns that can arise. '),
(87571, 2015, 'plos', 'Mechanism of Iron-Dependent Repressor (IdeR) Activation and DNA Binding: A Molecular Dynamics and Protein Structure Network Study', 'Ghosh, Soma|Chandra, Nagasuma|Vishveshwara, Saraswathi', 'Molecular Biophysics Unit, Indian Institute of Science, Bangalore, Karnataka, India.|I.I.Sc. Mathematics Initiative, Indian Institute of Science, Bangalore, Karnataka, India.|Molecular Biophysics Unit, Indian Institute of Science, Bangalore, Karnataka, India.', 'India|India|India', 8, 'Bacterial Proteins|Binding Sites|DNA|Enzyme Activation|Kinetics|Models, Chemical|Molecular Dynamics Simulation|Nucleic Acid Conformation|Protein Binding|Protein Conformation|Repressor Proteins|Substrate Specificity', 'Journal Article', '10.1371/journal.pcbi.1004500', '26699663', 'Metalloproteins form a major class of enzymes in the living system that are involved in crucial biological functions such as catalysis, redox reactions and as switches in signal transductions. Iron dependent repressor (IdeR) is a metal-sensing transcription factor that regulates free iron concentration in Mycobacterium tuberculosis. IdeR is also known to promote bacterial virulence, making it an important target in the field of therapeutics. Mechanistic details of how iron ions modulate IdeR such that it dimerizes and binds to DNA is not understood clearly. In this study, we have performed molecular dynamic simulations and integrated it with protein structure networks to study the influence of iron on IdeR structure and function. A significant structural variation between the metallated and the non-metallated system is observed. Our simulations clearly indicate the importance of iron in stabilizing its monomeric subunit, which in turn promotes dimerization. However, the most striking results are obtained from the simulations of IdeR-DNA complex in the absence of metals, where at the end of 100ns simulations, the protein subunits are seen to rapidly dissociate away from the DNA, thereby forming an excellent resource to investigate the mechanism of DNA binding. We have also investigated the role of iron as an allosteric regulator of IdeR that positively induces IdeR-DNA complex formation. Based on this study, a mechanistic model of IdeR activation and DNA binding has been proposed. '),
(87572, 2015, 'plos', 'Distinctive Behaviors of Druggable Proteins in Cellular Networks', 'Mitsopoulos, Costas|Schierz, Amanda C|Workman, Paul|Al-Lazikani, Bissan', 'Cancer Research UK Cancer Therapeutics Unit, The Institute of Cancer Research, London, United Kingdom.|Cancer Research UK Cancer Therapeutics Unit, The Institute of Cancer Research, London, United Kingdom.|Cancer Research UK Cancer Therapeutics Unit, The Institute of Cancer Research, London, United Kingdom.|Cancer Research UK Cancer Therapeutics Unit, The Institute of Cancer Research, London, United Kingdom.', 'United Kingdom|United Kingdom|United Kingdom|United Kingdom', 29, 'Algorithms|Antineoplastic Agents|Computer Simulation|Drug Delivery Systems|Drug Discovery|Drug Therapy, Computer-Assisted|Humans|Models, Biological|Molecular Targeted Therapy|Neoplasm Proteins|Neoplasms|Protein Interaction Mapping|Signal Transduction', 'Journal Article', '10.1371/journal.pcbi.1004597', '26699810', 'The interaction environment of a protein in a cellular network is important in defining the role that the protein plays in the system as a whole, and thus its potential suitability as a drug target. Despite the importance of the network environment, it is neglected during target selection for drug discovery. Here, we present the first systematic, comprehensive computational analysis of topological, community and graphical network parameters of the human interactome and identify discriminatory network patterns that strongly distinguish drug targets from the interactome as a whole. Importantly, we identify striking differences in the network behavior of targets of cancer drugs versus targets from other therapeutic areas and explore how they may relate to successful drug combinations to overcome acquired resistance to cancer drugs. We develop, computationally validate and provide the first public domain predictive algorithm for identifying druggable neighborhoods based on network parameters. We also make available full predictions for 13,345 proteins to aid target selection for drug discovery. All target predictions are available through canSAR.icr.ac.uk. Underlying data and tools are available at https://cansar.icr.ac.uk/cansar/publications/druggable_network_neighbourhoods/. '),
(87573, 2015, 'plos', 'Tamping Ramping: Algorithmic, Implementational, and Computational Explanations of Phasic Dopamine Signals in the Accumbens', 'Lloyd, Kevin|Dayan, Peter', 'Gatsby Computational Neuroscience Unit, London, United Kingdom.|Gatsby Computational Neuroscience Unit, London, United Kingdom.', 'United Kingdom|United Kingdom', 14, 'Algorithms|Animals|Computer Simulation|Decision Making|Dopamine|Humans|Metabolic Clearance Rate|Models, Neurological|Models, Statistical|Neurotransmitter Agents|Nucleus Accumbens|Reaction Time|Reward|Synaptic Transmission', 'Journal Article', '10.1371/journal.pcbi.1004622', '26699940', 'Substantial evidence suggests that the phasic activity of dopamine neurons represents reinforcement learnings temporal difference prediction error. However, recent reports of ramp-like increases in dopamine concentration in the striatum when animals are about to act, or are about to reach rewards, appear to pose a challenge to established thinking. This is because the implied activity is persistently predictable by preceding stimuli, and so cannot arise as this sort of prediction error. Here, we explore three possible accounts of such ramping signals: (a) the resolution of uncertainty about the timing of action, (b) the direct influence of dopamine over mechanisms associated with making choices, and (c) a new model of discounted vigour. Collectively, these suggest that dopamine ramps may be explained, with only minor disturbance, by standard theoretical ideas, though urgent questions remain regarding their proximal cause. We suggest experimental approaches to disentangling which of the proposed mechanisms are responsible for dopamine ramps. '),
(87574, 2015, 'plos', 'The Role of Symmetric Stem Cell Divisions in Tissue Homeostasis', 'Yang, Jienian|Plikus, Maksim V|Komarova, Natalia L', 'Department of Mathematics, University of California, Irvine, Irvine, California, United States of America.|Department of Developmental and Cell Biology, Sue and Bill Gross Stem Cell Research Center and Center for Complex Biological Systems, University of California, Irvine, Irvine, California, United States of America.|Department of Mathematics, University of California, Irvine, Irvine, California, United States of America.', 'United States|United States|United States', 21, 'Animals|Cell Differentiation|Cell Division|Cells, Cultured|Computer Simulation|Epidermal Cells|Epidermis|Feedback, Physiological|Homeostasis|Humans|Models, Biological|Stem Cells', 'Journal Article', '10.1371/journal.pcbi.1004629', '26700130', 'Successful maintenance of cellular lineages critically depends on the fate decision dynamics of stem cells (SCs) upon division. There are three possible strategies with respect to SC fate decision symmetry: (a) asymmetric mode, when each and every SC division produces one SC and one non-SC progeny, (b) symmetric mode, when 50% of all divisions produce two SCs and another 50%-two non-SC progeny, (c) mixed mode, when both the asymmetric and two types of symmetric SC divisions co-exist and are partitioned so that long-term net balance of the lineage output stays constant. Theoretically, either of these strategies can achieve lineage homeostasis. However, it remains unclear which strategy(s) are more advantageous and under what specific circumstances, and what minimal control mechanisms are required to operate them. Here we used stochastic modeling to analyze and quantify the ability of different types of divisions to maintain long-term lineage homeostasis, in the context of different control networks. Using the example of a two-component lineage, consisting of SCs and one type of non-SC progeny, we show that its tight homeostatic control is not necessarily associated with purely asymmetric divisions. Through stochastic analysis and simulations we show that asymmetric divisions can either stabilize or destabilize the lineage system, depending on the underlying control network. We further apply our computational model to biological observations in the context of a two-component lineage of mouse epidermis, where autonomous lineage control has been proposed and notable regional differences, in terms of symmetric division ratio, have been noted-higher in thickened epidermis of the paw skin as compared to ear and tail skin. By using our model we propose a possible explanation for the regional differences in epidermal lineage control strategies. We demonstrate how symmetric divisions can work to stabilize paw epidermis lineage, which experiences high level of micro-injuries and a lack of hair follicles as a back-up source of SCs. '),
(87575, 2015, 'plos', 'Correction: Cell Fate Reprogramming by Control of Intracellular Network Dynamics', 'PLOS Computational Biology Staff', 'Department of Mathematics, University of California, Irvine, Irvine, California, United States of America.', 'United States', 0, '-', 'Published Erratum', '10.1371/journal.pcbi.1004672', '26700269', '-'),
(87576, 2015, 'plos', 'Topological Phenotypes Constitute a New Dimension in the Phenotypic Space of Leaf Venation Networks', 'Ronellenfitsch, Henrik|Lasser, Jana|Daly, Douglas C|Katifori, Eleni', 'Max Planck Institute for Dynamics and Self-Organization, Göttingen, Germany.|Max Planck Institute for Dynamics and Self-Organization, Göttingen, Germany.|New York Botanical Garden, Bronx, New York, United States of America.|Department of Physics and Astronomy, University of Pennsylvania, Philadelphia, Pennsylvania, United States of America.', 'Germany|Germany|United States|United States', 16, 'Computer Simulation|Magnoliopsida|Models, Anatomic|Models, Biological|Phenotype|Plant Leaves|Plant Vascular Bundle', 'Journal Article', '10.1371/journal.pcbi.1004680', '26700471', 'The leaves of angiosperms contain highly complex venation networks consisting of recursively nested, hierarchically organized loops. We describe a new phenotypic trait of reticulate vascular networks based on the topology of the nested loops. This phenotypic trait encodes information orthogonal to widely used geometric phenotypic traits, and thus constitutes a new dimension in the leaf venation phenotypic space. We apply our metric to a database of 186 leaves and leaflets representing 137 species, predominantly from the Burseraceae family, revealing diverse topological network traits even within this single family. We show that topological information significantly improves identification of leaves from fragments by calculating a leaf venation fingerprint from topology and geometry. Further, we present a phenomenological model suggesting that the topological traits can be explained by noise effects unique to specimen during development of each leaf which leave their imprint on the final network. This work opens the path to new quantitative identification techniques for leaves which go beyond simple geometric traits such as vein density and is directly applicable to other planar or sub-planar networks such as blood vessels in the brain. '),
(87577, 2015, 'plos', 'Multistability in Large Scale Models of Brain Activity', 'Golos, Mathieu|Jirsa, Viktor|Daucé, Emmanuel', 'Aix-Marseille Université, Inserm, INS UMR_S 1106, Marseille, France.|Aix-Marseille Université, Inserm, INS UMR_S 1106, Marseille, France.|Aix-Marseille Université, Inserm, INS UMR_S 1106, Marseille, France.', 'France|France|France', 16, 'Action Potentials|Animals|Biological Clocks|Brain|Computer Simulation|Connectome|Humans|Models, Neurological|Models, Statistical|Nerve Net', 'Journal Article', '10.1371/journal.pcbi.1004644', '26709852', 'Noise driven exploration of a brain networks dynamic repertoire has been hypothesized to be causally involved in cognitive function, aging and neurodegeneration. The dynamic repertoire crucially depends on the networks capacity to store patterns, as well as their stability. Here we systematically explore the capacity of networks derived from human connectomes to store attractor states, as well as various network mechanisms to control the brains dynamic repertoire. Using a deterministic graded response Hopfield model with connectome-based interactions, we reconstruct the systems attractor space through a uniform sampling of the initial conditions. Large fixed-point attractor sets are obtained in the low temperature condition, with a bigger number of attractors than ever reported so far. Different variants of the initial model, including (i) a uniform activation threshold or (ii) a global negative feedback, produce a similarly robust multistability in a limited parameter range. A numerical analysis of the distribution of the attractors identifies spatially-segregated components, with a centro-medial core and several well-delineated regional patches. Those different modes share similarity with the fMRI independent components observed in the resting state condition. We demonstrate non-stationary behavior in noise-driven generalizations of the models, with different meta-stable attractors visited along the same time course. Only the model with a global dynamic density control is found to display robust and long-lasting non-stationarity with no tendency toward either overactivity or extinction. The best fit with empirical signals is observed at the edge of multistability, a parameter region that also corresponds to the highest entropy of the attractors. '),
(87578, 2015, 'plos', 'Modeling the Slow CD4+ T Cell Decline in HIV-Infected Individuals', 'Wang, Sunpeng|Hottz, Patricia|Schechter, Mauro|Rong, Libin', 'Department of Biology, New York University, New York, New York, United States of America.|Departamento de Medicina Preventiva, Faculdade de Medicina, Universidade Federal do Rio de Janeiro, Rio de Janeiro, Brazil.|Departamento de Medicina Preventiva, Faculdade de Medicina, Universidade Federal do Rio de Janeiro, Rio de Janeiro, Brazil.|Department of Mathematics and Statistics, and Center for Biomedical Research, Oakland University, Rochester, Michigan, United States of America.', 'United States|Brazil|Brazil|United States', 21, 'CD4 Lymphocyte Count|CD4-Positive T-Lymphocytes|Cell Proliferation|Computer Simulation|Cytokines|Disease Progression|HIV Infections|Humans|Immunologic Memory|Models, Immunological', 'Journal Article', '10.1371/journal.pcbi.1004665', '26709961', 'The progressive loss of CD4+ T cell population is the hallmark of HIV-1 infection but the mechanism underlying the slow T cell decline remains unclear. Some recent studies suggested that pyroptosis, a form of programmed cell death triggered during abortive HIV infection, is associated with the release of inflammatory cytokines, which can attract more CD4+ T cells to be infected. In this paper, we developed mathematical models to study whether this mechanism can explain the time scale of CD4+ T cell decline during HIV infection. Simulations of the models showed that cytokine induced T cell movement can explain the very slow decline of CD4+ T cells within untreated patients. The long-term CD4+ T cell dynamics predicted by the models were shown to be consistent with available data from patients in Rio de Janeiro, Brazil. Highly active antiretroviral therapy has the potential to restore the CD4+ T cell population but CD4+ response depends on the effectiveness of the therapy, when the therapy is initiated, and whether there are drug sanctuary sites. The model also showed that chronic inflammation induced by pyroptosis may facilitate persistence of the HIV latent reservoir by promoting homeostatic proliferation of memory CD4+ cells. These results improve our understanding of the long-term T cell dynamics in HIV-1 infection, and support that new treatment strategies, such as the use of caspase-1 inhibitors that inhibit pyroptosis, may maintain the CD4+ T cell population and reduce the latent reservoir size. '),
(87579, 2015, 'plos', 'Combining Evolutionary Information and an Iterative Sampling Strategy for Accurate Protein Structure Prediction', 'Braun, Tatjana|Koehler Leman, Julia|Lange, Oliver F', 'Biomolecular NMR and Munich Center for Integrated Protein Science, Department Chemie, Technische Universität München, Garching, Germany.|Department of Chemical and Biomolecular Engineering, Johns Hopkins University, Baltimore, Maryland, United States of America.|Biomolecular NMR and Munich Center for Integrated Protein Science, Department Chemie, Technische Universität München, Garching, Germany.', 'Germany|United States|Germany', 12, 'Amino Acid Sequence|Computational Biology|Databases, Protein|Evolution, Molecular|Models, Molecular|Protein Conformation|Proteins|Sequence Analysis, Protein|Software', 'Journal Article', '10.1371/journal.pcbi.1004661', '26713437', 'Recent work has shown that the accuracy of ab initio structure prediction can be significantly improved by integrating evolutionary information in form of intra-protein residue-residue contacts. Following this seminal result, much effort is put into the improvement of contact predictions. However, there is also a substantial need to develop structure prediction protocols tailored to the type of restraints gained by contact predictions. Here, we present a structure prediction protocol that combines evolutionary information with the resolution-adapted structural recombination approach of Rosetta, called RASREC. Compared to the classic Rosetta ab initio protocol, RASREC achieves improved sampling, better convergence and higher robustness against incorrect distance restraints, making it the ideal sampling strategy for the stated problem. To demonstrate the accuracy of our protocol, we tested the approach on a diverse set of 28 globular proteins. Our method is able to converge for 26 out of the 28 targets and improves the average TM-score of the entire benchmark set from 0.55 to 0.72 when compared to the top ranked models obtained by the EVFold web server using identical contact predictions. Using a smaller benchmark, we furthermore show that the prediction accuracy of our method is only slightly reduced when the contact prediction accuracy is comparatively low. This observation is of special interest for protein sequences that only have a limited number of homologs. '),
(87580, 2015, 'plos', 'Clustered Desynchronization from High-Frequency Deep Brain Stimulation', 'Wilson, Dan|Moehlis, Jeff', 'Department of Mechanical Engineering, University of California, Santa Barbara, Santa Barbara, Calfornia, United States of America.|Department of Mechanical Engineering, University of California, Santa Barbara, Santa Barbara, Calfornia, United States of America.', 'United States|United States', 20, 'Animals|Cluster Analysis|Computational Biology|Computer Simulation|Cortical Synchronization|Deep Brain Stimulation|Humans|Models, Neurological|Neurons|Parkinson Disease|Thalamus', 'Journal Article', '10.1371/journal.pcbi.1004673', '26713619', 'While high-frequency deep brain stimulation is a well established treatment for Parkinsons disease, its underlying mechanisms remain elusive. Here, we show that two competing hypotheses, desynchronization and entrainment in a population of model neurons, may not be mutually exclusive. We find that in a noisy group of phase oscillators, high frequency perturbations can separate the population into multiple clusters, each with a nearly identical proportion of the overall population. This phenomenon can be understood by studying maps of the underlying deterministic system and is guaranteed to be observed for small noise strengths. When we apply this framework to populations of Type I and Type II neurons, we observe clustered desynchronization at many pulsing frequencies. '),
(87581, 2015, 'plos', 'Capabilities and Limitations of Tissue Size Control through Passive Mechanical Forces', 'Kursawe, Jochen|Brodskiy, Pavel A|Zartman, Jeremiah J|Baker, Ruth E|Fletcher, Alexander G', 'Mathematical Institute, University of Oxford, Oxford, United Kingdom.|Department of Chemical and Biomolecular Engineering, University of Notre Dame, Notre Dame, Indiana, United States of America.|Department of Chemical and Biomolecular Engineering, University of Notre Dame, Notre Dame, Indiana, United States of America.|Mathematical Institute, University of Oxford, Oxford, United Kingdom.|Mathematical Institute, University of Oxford, Oxford, United Kingdom.', 'United Kingdom|India|India|United Kingdom|United Kingdom', 22, 'Animals|Biomechanical Phenomena|Cell Death|Cell Proliferation|Cell Shape|Computational Biology|Drosophila|Embryonic Development|Models, Biological', 'Journal Article', '10.1371/journal.pcbi.1004679', '26713738', 'Embryogenesis is an extraordinarily robust process, exhibiting the ability to control tissue size and repair patterning defects in the face of environmental and genetic perturbations. The size and shape of a developing tissue is a function of the number and size of its constituent cells as well as their geometric packing. How these cellular properties are coordinated at the tissue level to ensure developmental robustness remains a mystery, understanding this process requires studying multiple concurrent processes that make up morphogenesis, including the spatial patterning of cell fates and apoptosis, as well as cell intercalations. In this work, we develop a computational model that aims to understand aspects of the robust pattern repair mechanisms of the Drosophila embryonic epidermal tissues. Size control in this system has previously been shown to rely on the regulation of apoptosis rather than proliferation, however, to date little work has been done to understand the role of cellular mechanics in this process. We employ a vertex model of an embryonic segment to test hypotheses about the emergence of this size control. Comparing the model to previously published data across wild type and genetic perturbations, we show that passive mechanical forces suffice to explain the observed size control in the posterior (P) compartment of a segment. However, observed asymmetries in cell death frequencies across the segment are demonstrated to require patterning of cellular properties in the model. Finally, we show that distinct forms of mechanical regulation in the model may be distinguished by differences in cell shapes in the P compartment, as quantified through experimentally accessible summary statistics, as well as by the tissue recoil after laser ablation experiments. '),
(87582, 2015, 'plos', 'Formation and Maintenance of Robust Long-Term Information Storage in the Presence of Synaptic Turnover', 'Fauth, Michael|Wörgötter, Florentin|Tetzlaff, Christian', 'Third Physics Institute, Georg-August University, Göttingen, Germany.|Third Physics Institute, Georg-August University, Göttingen, Germany.|Max-Planck Institute for Dynamics and Self-Organization, Göttingen, Germany.', 'Germany|Germany|Germany', 15, 'Computational Biology|Dendritic Spines|Learning|Memory|Models, Neurological|Neuronal Plasticity|Synapses', 'Journal Article', '10.1371/journal.pcbi.1004684', '26713858', 'A long-standing problem is how memories can be stored for very long times despite the volatility of the underlying neural substrate, most notably the high turnover of dendritic spines and synapses. To address this problem, here we are using a generic and simple probabilistic model for the creation and removal of synapses. We show that information can be stored for several months when utilizing the intrinsic dynamics of multi-synapse connections. In such systems, single synapses can still show high turnover, which enables fast learning of new information, but this will not perturb prior stored information (slow forgetting), which is represented by the compound state of the connections. The model matches the time course of recent experimental spine data during learning and memory in mice supporting the assumption of multi-synapse connections as the basis for long-term storage. '),
(87583, 2015, 'plos', 'A Boolean Function for Neural Induction Reveals a Critical Role of Direct Intercellular Interactions in Patterning the Ectoderm of the Ascidian Embryo', 'Ohta, Naoyuki|Waki, Kana|Mochizuki, Atsushi|Satou, Yutaka', 'Department of Zoology, Graduate School of Science, Kyoto University, Sakyo, Kyoto, Japan.|Department of Zoology, Graduate School of Science, Kyoto University, Sakyo, Kyoto, Japan.|RIKEN Advanced Science Institute, Wako, Saitama, Japan.|Department of Zoology, Graduate School of Science, Kyoto University, Sakyo, Kyoto, Japan.', 'Japan|Japan|Japan|Japan', 8, 'Animals|Body Patterning|Computational Biology|Ectoderm|Embryo, Nonmammalian|Gene Expression Regulation, Developmental|Models, Biological|Signal Transduction|Urochordata', 'Journal Article', '10.1371/journal.pcbi.1004687', '26714026', 'A complex system of multiple signaling molecules often produce differential gene expression patterns in animal embryos. In the ascidian embryo, four signaling ligands, Ephrin-A.d (Efna.d), Fgf9/16/20, Admp, and Gdf1/3-r, coordinately induce Otx expression in the neural lineage at the 32-cell stage. However, it has not been determined whether differential inputs of all of these signaling pathways are really necessary. It is possible that differential activation of one of these signaling pathways is sufficient and the remaining signaling pathways are activated in all cells at similar levels. To address this question, we developed a parameter-free method for determining a Boolean function for Otx expression in the present study. We treated activities of signaling pathways as Boolean values, and we also took all possible patterns of signaling gradients into consideration. We successfully determined a Boolean function that explains Otx expression in the animal hemisphere of wild-type and morphant embryos at the 32-cell stage. This Boolean function was not inconsistent with three sensing patterns, which represented whether or not individual cells received sufficient amounts of the signaling molecules. These sensing patterns all indicated that differential expression of Otx in the neural lineage is primarily determined by Efna.d, but not by differential inputs of Fgf9/16/20, Admp, and Gdf1/3-r signaling. To confirm this hypothesis experimentally, we simultaneously knocked-down Admp, Gdf1/3-r, and Fgf9/16/20, and treated this triple morphant with recombinant bFGF and BMP4 proteins, which mimic Fgf9/16/20 and Admp/Gdf1/3-r activity, respectively. Although no differential inputs of Admp, Gdf1/3-r and Fgf9/16/20 signaling were expected under this experimental condition, Otx was expressed specifically in the neural lineage. Thus, direct cell-cell interactions through Efna.d play a critical role in patterning the ectoderm of the early ascidian embryo. '),
(87584, 2015, 'plos', 'Wheres the Noise? Key Features of Spontaneous Activity and Neural Variability Arise through Learning in a Deterministic Network', 'Hartmann, Christoph|Lazar, Andreea|Nessler, Bernhard|Triesch, Jochen', 'Frankfurt Institute for Advanced Studies, Johann Wolfgang Goethe University, Frankfurt am Main, Germany.|Frankfurt Institute for Advanced Studies, Johann Wolfgang Goethe University, Frankfurt am Main, Germany.|Frankfurt Institute for Advanced Studies, Johann Wolfgang Goethe University, Frankfurt am Main, Germany.|Frankfurt Institute for Advanced Studies, Johann Wolfgang Goethe University, Frankfurt am Main, Germany.', 'Germany|Germany|Germany|Germany', 16, 'Computational Biology|Humans|Learning|Models, Neurological|Models, Statistical|Neural Networks (Computer)|Neuronal Plasticity', 'Journal Article', '10.1371/journal.pcbi.1004640', '26714277', 'Even in the absence of sensory stimulation the brain is spontaneously active. This background noise seems to be the dominant cause of the notoriously high trial-to-trial variability of neural recordings. Recent experimental observations have extended our knowledge of trial-to-trial variability and spontaneous activity in several directions: 1. Trial-to-trial variability systematically decreases following the onset of a sensory stimulus or the start of a motor act. 2. Spontaneous activity states in sensory cortex outline the region of evoked sensory responses. 3. Across development, spontaneous activity aligns itself with typical evoked activity patterns. 4. The spontaneous brain activity prior to the presentation of an ambiguous stimulus predicts how the stimulus will be interpreted. At present it is unclear how these observations relate to each other and how they arise in cortical circuits. Here we demonstrate that all of these phenomena can be accounted for by a deterministic self-organizing recurrent neural network model (SORN), which learns a predictive model of its sensory environment. The SORN comprises recurrently coupled populations of excitatory and inhibitory threshold units and learns via a combination of spike-timing dependent plasticity (STDP) and homeostatic plasticity mechanisms. Similar to balanced network architectures, units in the network show irregular activity and variable responses to inputs. Additionally, however, the SORN exhibits sequence learning abilities matching recent findings from visual cortex and the networks spontaneous activity reproduces the experimental findings mentioned above. Intriguingly, the networks behaviour is reminiscent of sampling-based probabilistic inference, suggesting that correlates of sampling-based inference can develop from the interaction of STDP and homeostasis in deterministic networks. We conclude that key observations on spontaneous brain activity and the variability of neural responses can be accounted for by a simple deterministic recurrent neural network which learns a predictive model of its sensory environment via a combination of generic neural plasticity mechanisms. '),
(87585, 2015, 'plos', 'Epidemic Reconstruction in a Phylogenetics Framework: Transmission Trees as Partitions of the Node Set', 'Hall, Matthew|Woolhouse, Mark|Rambaut, Andrew', 'Institute of Evolutionary Biology, University of Edinburgh, Edinburgh, United Kingdom.|Institute of Evolutionary Biology, University of Edinburgh, Edinburgh, United Kingdom.|Institute of Evolutionary Biology, University of Edinburgh, Edinburgh, United Kingdom.', 'United Kingdom|United Kingdom|United Kingdom', 37, 'Algorithms|Animals|Computational Biology|Epidemics|Influenza A Virus, H7N7 Subtype|Influenza in Birds|Markov Chains|Models, Biological|Monte Carlo Method|Phylogeny|Poultry|Software', 'Journal Article', '10.1371/journal.pcbi.1004613', '26717515', 'The use of genetic data to reconstruct the transmission tree of infectious disease epidemics and outbreaks has been the subject of an increasing number of studies, but previous approaches have usually either made assumptions that are not fully compatible with phylogenetic inference, or, where they have based inference on a phylogeny, have employed a procedure that requires this tree to be fixed. At the same time, the coalescent-based models of the pathogen population that are employed in the methods usually used for time-resolved phylogeny reconstruction are a considerable simplification of epidemic process, as they assume that pathogen lineages mix freely. Here, we contribute a new method that is simultaneously a phylogeny reconstruction method for isolates taken from an epidemic, and a procedure for transmission tree reconstruction. We observe that, if one or more samples is taken from each host in an epidemic or outbreak and these are used to build a phylogeny, a transmission tree is equivalent to a partition of the set of nodes of this phylogeny, such that each partition element is a set of nodes that is connected in the full tree and contains all the tips corresponding to samples taken from one and only one host. We then implement a Monte Carlo Markov Chain (MCMC) procedure for simultaneous sampling from the spaces of both trees, utilising a newly-designed set of phylogenetic tree proposals that also respect node partitions. We calculate the posterior probability of these partitioned trees based on a model that acknowledges the population structure of an epidemic by employing an individual-based disease transmission model and a coalescent process taking place within each host. We demonstrate our method, first using simulated data, and then with sequences taken from the H7N7 avian influenza outbreak that occurred in the Netherlands in 2003. We show that it is superior to established coalescent methods for reconstructing the topology and node heights of the phylogeny and performs well for transmission tree reconstruction when the phylogeny is well-resolved by the genetic data, but caution that this will often not be the case in practice and that existing genetic and epidemiological data should be used to configure such analyses whenever possible. This method is available for use by the research community as part of BEAST, one of the most widely-used packages for reconstruction of dated phylogenies. ');
INSERT INTO `papers` (`id`, `ano`, `journal`, `titulo`, `autores`, `afiliacao`, `pais`, `citacoes`, `palavra_chave`, `categorias`, `doi`, `pubmed`, `abstract`) VALUES
(87586, 2015, 'plos', 'The Effect of Farmers Decisions on Pest Control with Bt Crops: A Billion Dollar Game of Strategy', 'Milne, Alice E|Bell, James R|Hutchison, William D|van den Bosch, Frank|Mitchell, Paul D|Crowder, David|Parnell, Stephen|Whitmore, Andrew P', 'Computational and Systems Biology, Rothamsted Research, Harpenden, United Kingdom.|Rothamsted Insect Survey, Rothamsted Research, Harpenden, United Kingdom.|Department of Entomology, University of Minnesota, St. Paul, Minnesota, United States of America.|Computational and Systems Biology, Rothamsted Research, Harpenden, United Kingdom.|Department of Agricultural and Applied Economics, University of Wisconsin, Madison, Wisconsin, United States of America.|Department of Entomology, Washington State University, Pullman, Washington, United States of America.|Computational and Systems Biology, Rothamsted Research, Harpenden, United Kingdom.|Sustainable Soils and Grassland Systems, Rothamsted Research, Harpenden, United Kingdom.', 'United Kingdom|United Kingdom|United States|United Kingdom|United States|United States|United Kingdo', 13, 'Animals|Computational Biology|Crops, Agricultural|Decision Making|Farmers|Health Knowledge, Attitudes, Practice|Humans|Lepidoptera|Models, Biological|Nosema|Pest Control, Biological|Plants, Genetically Modified|United States|Zea mays', 'Journal Article', '10.1371/journal.pcbi.1004483', '26720851', 'A farmers decision on whether to control a pest is usually based on the perceived threat of the pest locally and the guidance of commercial advisors. Therefore, farmers in a region are often influenced by similar circumstances, and this can create a coordinated response for pest control that is effective at a landscape scale. This coordinated response is not intentional, but is an emergent property of the system. We propose a framework for understanding the intrinsic feedback mechanisms between the actions of humans and the dynamics of pest populations and demonstrate this framework using the European corn borer, a serious pest in maize crops. We link a model of the European corn borer and a parasite in a landscape with a model that simulates the decisions of individual farmers on what type of maize to grow. Farmers chose whether to grow Bt-maize, which is toxic to the corn borer, or conventional maize for which the seed is cheaper. The problem is akin to the snow-drift problem in game theory, that is to say, if enough farmers choose to grow Bt maize then because the pest is suppressed an individual may benefit from growing conventional maize. We show that the communication network between farmers and their perceptions of profit and loss affects landscape scale patterns in pest dynamics. We found that although adoption of Bt maize often brings increased financial returns, these rewards oscillate in response to the prevalence of pests. '),
(87587, 2015, 'plos', 'Complete Firing-Rate Response of Neurons with Complex Intrinsic Dynamics', 'Puelma Touzel, Maximilian|Wolf, Fred', 'Department for Nonlinear Dynamics, Max Planck Institute for Dynamics and Self-Organization, Goettingen, Germany.|Department for Nonlinear Dynamics, Max Planck Institute for Dynamics and Self-Organization, Goettingen, Germany.', 'Germany|Germany', 5, 'Action Potentials|Computational Biology|Computer Simulation|Membrane Potentials|Models, Neurological|Neurons', 'Journal Article', '10.1371/journal.pcbi.1004636', '26720924', 'The response of a neuronal population over a space of inputs depends on the intrinsic properties of its constituent neurons. Two main modes of single neuron dynamics-integration and resonance-have been distinguished. While resonator cell types exist in a variety of brain areas, few models incorporate this feature and fewer have investigated its effects. To understand better how a resonators frequency preference emerges from its intrinsic dynamics and contributes to its local areas population firing rate dynamics, we analyze the dynamic gain of an analytically solvable two-degree of freedom neuron model. In the Fokker-Planck approach, the dynamic gain is intractable. The alternative Gauss-Rice approach lifts the resetting of the voltage after a spike. This allows us to derive a complete expression for the dynamic gain of a resonator neuron model in terms of a cascade of filters on the input. We find six distinct response types and use them to fully characterize the routes to resonance across all values of the relevant timescales. We find that resonance arises primarily due to slow adaptation with an intrinsic frequency acting to sharpen and adjust the location of the resonant peak. We determine the parameter regions for the existence of an intrinsic frequency and for subthreshold and spiking resonance, finding all possible intersections of the three. The expressions and analysis presented here provide an account of how intrinsic neuron dynamics shape dynamic population response properties and can facilitate the construction of an exact theory of correlations and stability of population activity in networks containing populations of resonator neurons. '),
(87588, 2016, 'plos', 'Coordinating Role of RXRxcexb1 in Downregulating Hepatic Detoxification during Inflammation Revealed by Fuzzy-Logic Modeling', 'Keller, Roland|Klein, Marcus|Thomas, Maria|Drxc3xa4ger, Andreas|Metzger, Ute|Templin, Markus F|Joos, Thomas O|Thasler, Wolfgang E|Zell, Andreas|Zanger, Ulrich M', 'Center for Bioinformatics Tuebingen (ZBIT), University of Tuebingen, Tuebingen, Germany.|Dr. Margarete Fischer Bosch-Institute of Clinical Pharmacology, Stuttgart.|Dr. Margarete Fischer Bosch-Institute of Clinical Pharmacology, Stuttgart.|Center for Bioinformatics Tuebingen (ZBIT), University of Tuebingen, Tuebingen, Germany.|NMI Institute of Natural and Medical Sciences, Reutlingen, Germany.|NMI Institute of Natural and Medical Sciences, Reutlingen, Germany.|NMI Institute of Natural and Medical Sciences, Reutlingen, Germany.|Department of General, Visceral, Transplantation, Vascular and Thoracic Surgery, Hospital of the University of Munich, Munich, Germany.|Center for Bioinformatics Tuebingen (ZBIT), University of Tuebingen, Tuebingen, Germany.|Dr. Margarete Fischer Bosch-Institute of Clinical Pharmacology, Stuttgart.', 'Germany|-|-|Germany|Germany|Germany|Germany|Germany|Germany|-', 12, 'Adult|Aged|Aged, 80 and over|Computational Biology|Down-Regulation|Female|Fuzzy Logic|Hepatocytes|Humans|Inactivation, Metabolic|Inflammation|Male|Middle Aged|Models, Biological|Retinoid X Receptor alpha|Signal Transduction|Young Adult', 'Journal Article', '10.1371/journal.pcbi.1004431', '26727233', 'During various inflammatory processes circulating cytokines including IL-6, IL-1xcexb2, and TNFxcexb1 elicit a broad and clinically relevant impairment of hepatic detoxification that is based on the simultaneous downregulation of many drug metabolizing enzymes and transporter genes. To address the question whether a common mechanism is involved we treated human primary hepatocytes with IL-6, the major mediator of the acute phase response in liver, and characterized acute phase and detoxification responses in quantitative gene expression and (phospho-)proteomics data sets. Selective inhibitors were used to disentangle the roles of JAK/STAT, MAPK, and PI3K signaling pathways. A prior knowledge-based fuzzy logic model comprising signal transduction and gene regulation was established and trained with perturbation-derived gene expression data from five hepatocyte donors. Our model suggests a greater role of MAPK/PI3K compared to JAK/STAT with the orphan nuclear receptor RXRxcexb1 playing a central role in mediating transcriptional downregulation. Validation experiments revealed a striking similarity of RXRxcexb1 gene silencing versus IL-6 induced negative gene regulation (rs = 0.79, P<0.0001). These results concur with RXRxcexb1 functioning as obligatory heterodimerization partner for several nuclear receptors that regulate drug and lipid metabolism. '),
(87589, 2016, 'plos', 'K+ Block Is the Mechanism of Functional Asymmetry in Bacterial Na(v) Channels', 'Ngo, Van|Wang, Yibo|Haas, Stephan|Noskov, Sergei Y|Farley, Robert A', 'Department of Physics and Astronomy, University of Southern California, Los Angeles, California, United States of America.|Department of Biological Sciences, Centre for Molecular Simulations, University of Calgary, Calgary, Alberta, Canada.|Department of Physics and Astronomy, University of Southern California, Los Angeles, California, United States of America.|Department of Biological Sciences, Centre for Molecular Simulations, University of Calgary, Calgary, Alberta, Canada.|Department of Physiology and Biophysics, and Department of Biochemistry and Molecular Biology, Keck School of Medicine, University of Southern California, Los Angeles, California, United States of America.', 'United States|Canada|United States|Canada|United States', 0, 'Bacterial Proteins|Computational Biology|Computer Simulation|Models, Molecular|Potassium|Thermodynamics|Voltage-Gated Sodium Channels', 'Journal Article', '10.1371/journal.pcbi.1004482', '26727271', 'Crystal structures of several bacterial Na(v) channels have been recently published and molecular dynamics simulations of ion permeation through these channels are consistent with many electrophysiological properties of eukaryotic channels. Bacterial Na(v) channels have been characterized as functionally asymmetric, and the mechanism of this asymmetry has not been clearly understood. To address this question, we combined non-equilibrium simulation data with two-dimensional equilibrium unperturbed landscapes generated by umbrella sampling and Weighted Histogram Analysis Methods for multiple ions traversing the selectivity filter of bacterial Na(v)Ab channel. This approach provided new insight into the mechanism of selective ion permeation in bacterial Na(v) channels. The non-equilibrium simulations indicate that two or three extracellular K+ ions can block the entrance to the selectivity filter of Na(v)Ab in the presence of applied forces in the inward direction, but not in the outward direction. The block state occurs in an unstable local minimum of the equilibrium unperturbed free-energy landscape of two K+ ions that can be locked in place by modest applied forces. In contrast to K+, three Na+ ions move favorably through the selectivity filter together as a unit in a loose knock-on mechanism of permeation in both inward and outward directions, and there is no similar local minimum in the two-dimensional free-energy landscape of two Na+ ions for a block state. The useful work predicted by the non-equilibrium simulations that is required to break the K+ block is equivalent to large applied potentials experimentally measured for two bacterial Na(v) channels to induce inward currents of K+ ions. These results illustrate how inclusion of non-equilibrium factors in the simulations can provide detailed information about mechanisms of ion selectivity that is missing from mechanisms derived from either crystal structures or equilibrium unperturbed free-energy landscapes.'),
(87590, 2016, 'plos', 'Pore Structure and Synergy in Antimicrobial Peptides of the Magainin Family', 'Pino-Angeles, Almudena|Leveritt, John M|Lazaridis, Themis', 'Department of Chemistry, The City College of New York, New York, New York, United States of America.|Department of Chemistry, The City College of New York, New York, New York, United States of America.|Department of Chemistry, The City College of New York, New York, New York, United States of America.', 'United States|United States|United States', 29, 'Anti-Bacterial Agents|Antimicrobial Cationic Peptides|Computational Biology|Magainins|Molecular Dynamics Simulation|Nuclear Magnetic Resonance, Biomolecular|Porosity|Protein Conformation', 'Journal Article', '10.1371/journal.pcbi.1004570', '26727376', 'Magainin 2 and PGLa are among the best-studied cationic antimicrobial peptides. They bind preferentially to negatively charged membranes and apparently cause their disruption by the formation of transmembrane pores, whose detailed structure is still unclear. Here we report the results of 5-9 xcexbcs all-atom molecular dynamics simulations starting from tetrameric transmembrane helical bundles of these two peptides, as well as their stoichiometric mixture, and the analog MG-H2 in DMPC or 3:1 DMPC/DMPG membranes. The simulations produce pore structures that appear converged, although some effect of the starting peptide arrangement (parallel vs. antiparallel) is still observed on this timescale. The peptides remain mostly helical and adopt tilted orientations. The calculated tilt angles for PGLa are in excellent agreement with recent solid state NMR experiments. The antiparallel dimer structure in the magainin 2 simulations resembles previously determined NMR and crystal structures. More transmembrane orientations and a larger and more ordered pore are seen in the 1:1 heterotetramer with an antiparallel helix arrangement. Insights into the mechanism of synergy between these two peptides are obtained via implicit solvent modeling of homo- and heterodimers and analysis of interactions in the atomistic simulations. This analysis suggests stronger pairwise interactions in the heterodimer than in the two homodimers. '),
(87591, 2016, 'plos', 'Hydrodynamic Radii of Intrinsically Disordered Proteins Determined from Experimental Polyproline II Propensities', 'Tomasso, Maria E|Tarver, Micheal J|Devarajan, Deepa|Whitten, Steven T', 'Department of Chemistry and Biochemistry, Texas State University, San Marcos, Texas, United States of America.|Department of Chemistry and Biochemistry, Texas State University, San Marcos, Texas, United States of America.|Department of Chemistry and Biochemistry, Texas State University, San Marcos, Texas, United States of America.|Department of Chemistry and Biochemistry, Texas State University, San Marcos, Texas, United States of America.', 'United States|United States|United States|United States', 13, 'Computational Biology|Computer Simulation|Hydrodynamics|Intrinsically Disordered Proteins|Models, Molecular|Peptides|Protein Structure, Secondary', 'Journal Article', '10.1371/journal.pcbi.1004686', '26727467', 'The properties of disordered proteins are thought to depend on intrinsic conformational propensities for polyproline II (PPII) structure. While intrinsic PPII propensities have been measured for the common biological amino acids in short peptides, the ability of these experimentally determined propensities to quantitatively reproduce structural behavior in intrinsically disordered proteins (IDPs) has not been established. Presented here are results from molecular simulations of disordered proteins showing that the hydrodynamic radius (Rh) can be predicted from experimental PPII propensities with good agreement, even when charge-based considerations are omitted. The simulations demonstrate that Rh and chain propensity for PPII structure are linked via a simple power-law scaling relationship, which was tested using the experimental Rh of 22 IDPs covering a wide range of peptide lengths, net charge, and sequence composition. Charge effects on Rh were found to be generally weak when compared to PPII effects on Rh. Results from this study indicate that the hydrodynamic dimensions of IDPs are evidence of considerable sequence-dependent backbone propensities for PPII structure that qualitatively, if not quantitatively, match conformational propensities measured in peptides. '),
(87592, 2016, 'plos', 'Long-Lasting Sparks: Multi-Metastability and Release Competition in the Calcium Release Unit Network', 'Song, Zhen|Karma, Alain|Weiss, James N|Qu, Zhilin', 'The UCLA Cardiovascular Research Laboratory, David Geffen School of Medicine, University of California, Los Angeles, Los Angeles, California, United States of America.|Department of Physics, Northeastern University, Boston, Massachusetts, United States of America.|The UCLA Cardiovascular Research Laboratory, David Geffen School of Medicine, University of California, Los Angeles, Los Angeles, California, United States of America.|The UCLA Cardiovascular Research Laboratory, David Geffen School of Medicine, University of California, Los Angeles, Los Angeles, California, United States of America.', 'United States|United States|United States|United States', 0, 'Calcium|Calcium Signaling|Computational Biology|Models, Biological|Ryanodine Receptor Calcium Release Channel|Sarcoplasmic Reticulum', 'Journal Article', '10.1371/journal.pcbi.1004671', '26730593', 'Calcium (Ca) sparks are elementary events of biological Ca signaling. A normal Ca spark has a brief duration in the range of 10 to 100 ms, but long-lasting sparks with durations of several hundred milliseconds to seconds are also widely observed. Experiments have shown that the transition from normal to long-lasting sparks can occur when ryanodine receptor (RyR) open probability is either increased or decreased. Here, we demonstrate theoretically and computationally that long-lasting sparks emerge as a collective dynamical behavior of the network of diffusively coupled Ca release units (CRUs). We show that normal sparks occur when the CRU network is monostable and excitable, while long-lasting sparks occur when the network dynamics possesses multiple metastable attractors, each attractor corresponding to a different spatial firing pattern of sparks. We further highlight the mechanisms and conditions that produce long-lasting sparks, demonstrating the existence of an optimal range of RyR open probability favoring long-lasting sparks. We find that when CRU firings are sparse and sarcoplasmic reticulum (SR) Ca load is high, increasing RyR open probability promotes long-lasting sparks by potentiating Ca-induced Ca release (CICR). In contrast, when CICR is already strong enough to produce frequent firings, decreasing RyR open probability counter-intuitively promotes long-lasting sparks by decreasing spark frequency. The decrease in spark frequency promotes intra-SR Ca diffusion from neighboring non-firing CRUs to the firing CRUs, which helps to maintain the local SR Ca concentration of the firing CRUs above a critical level to sustain firing. In this setting, decreasing RyR open probability further suppresses long-lasting sparks by weakening CICR. Since a long-lasting spark terminates via the Kramers escape process over a potential barrier, its duration exhibits an exponential distribution determined by the barrier height and noise strength, which is modulated differently by different ways of altering the Ca release flux strength. '),
(87593, 2016, 'plos', 'Neurally Encoding Time for Olfactory Navigation', 'Park, In Jun|Hein, Andrew M|Bobkov, Yuriy V|Reidenbach, Matthew A|Ache, Barry W|Principe, Jose C', 'Department of Electrical and Computer Engineering, University of Florida, Gainesville, Florida, United States of America.|Department of Ecology and Evolutionary Biology, Princeton University, Princeton, New Jersey, United States of America.|Whitney Laboratory for Marine Bioscience, University of Florida, St. Augustine, Florida, United States of America.|Department of Environmental Sciences, University of Virginia, Charlottesville, Virginia, United States of America.|Whitney Laboratory for Marine Bioscience, University of Florida, St. Augustine, Florida, United States of America.|Department of Electrical and Computer Engineering, University of Florida, Gainesville, Florida, United States of America.', 'United States|Jersey|United States|United States|United States|United States', 5, 'Animals|Appetitive Behavior|Computational Biology|Models, Neurological|Odorants|Olfactory Receptor Neurons|Smell', 'Journal Article', '10.1371/journal.pcbi.1004682', '26730727', 'Accurately encoding time is one of the fundamental challenges faced by the nervous system in mediating behavior. We recently reported that some animals have a specialized population of rhythmically active neurons in their olfactory organs with the potential to peripherally encode temporal information about odor encounters. If these neurons do indeed encode the timing of odor arrivals, it should be possible to demonstrate that this capacity has some functional significance. Here we show how this sensory input can profoundly influence an animals ability to locate the source of odor cues in realistic turbulent environments-a common task faced by species that rely on olfactory cues for navigation. Using detailed data from a turbulent plume created in the laboratory, we reconstruct the spatiotemporal behavior of a real odor field. We use recurrence theory to show that information about position relative to the source of the odor plume is embedded in the timing between odor pulses. Then, using a parameterized computational model, we show how an animal can use populations of rhythmically active neurons to capture and encode this temporal information in real time, and use it to efficiently navigate to an odor source. Our results demonstrate that the capacity to accurately encode temporal information about sensory cues may be crucial for efficient olfactory navigation. More generally, our results suggest a mechanism for extracting and encoding temporal information from the sensory environment that could have broad utility for neural information processing. '),
(87594, 2016, 'plos', 'Transient Accumulation of NO2- and N2O during Denitrification Explained by Assuming Cell Diversification by Stochastic Transcription of Denitrification Genes', 'Hassan, Junaid|Qu, Zhi|Bergaust, Linda L|Bakken, Lars R', 'Department of Environmental Sciences, Norwegian University of Life Sciences, Ås, Norway.|Department of Environmental Sciences, Norwegian University of Life Sciences, Ås, Norway.|Chemistry, Biotechnology and Food Science, Norwegian University of Life Sciences, Ås, Norway.|Department of Environmental Sciences, Norwegian University of Life Sciences, Ås, Norway.', 'Norway|Norway|Norway|Norway', 23, 'Bacterial Proteins|Cell Hypoxia|Computational Biology|Denitrification|Metabolic Networks and Pathways|Models, Biological|Nitrogen Dioxide|Nitrous Oxide|Oxidoreductases|Paracoccus denitrificans|Phenotype', 'Journal Article', '10.1371/journal.pcbi.1004621', '26731685', 'Denitrifying bacteria accumulate [Formula: see text], NO, and N2O, the amounts depending on transcriptional regulation of core denitrification genes in response to O2-limiting conditions. The genes include nar, nir, nor and nosZ, encoding [Formula: see text]-, [Formula: see text]-, NO- and N2O reductase, respectively. We previously constructed a dynamic model to simulate growth and respiration in batch cultures of Paracoccus denitrificans. The observed denitrification kinetics were adequately simulated by assuming a stochastic initiation of nir-transcription in each cell with an extremely low probability (0.5% h-1), leading to product- and substrate-induced transcription of nir and nor, respectively, via NO. Thus, the model predicted cell diversification: after O2 depletion, only a small fraction was able to grow by reducing [Formula: see text]. Here we have extended the model to simulate batch cultivation with [Formula: see text], i.e., [Formula: see text], NO, N2O, and N2 kinetics, measured in a novel experiment including frequent measurements of [Formula: see text]. Pa. denitrificans reduced practically all [Formula: see text] to [Formula: see text] before initiating gas production. The [Formula: see text] production is adequately simulated by assuming stochastic nar-transcription, as that for nirS, but with a higher probability (0.035 h-1) and initiating at a higher O2 concentration. Our model assumes that all cells express nosZ, thus predicting that a majority of cells have only N2O-reductase (A), while a minority (B) has [Formula: see text]-, NO- and N2O-reductase. Population B has a higher cell-specific respiration rate than A because the latter can only use N2O produced by B. Thus, the ratio [Formula: see text] is low immediately after O2 depletion, but increases throughout the anoxic phase because B grows faster than A. As a result, the model predicts initially low but gradually increasing N2O concentration throughout the anoxic phase, as observed. The modelled cell diversification neatly explains the observed denitrification kinetics and transient intermediate accumulations. The result has major implications for understanding the relationship between genotype and phenotype in denitrification research. '),
(87595, 2016, 'plos', 'Coarse-Grained Simulations of Topology-Dependent Mechanisms of Protein Unfolding and Translocation Mediated by ClpY ATPase Nanomachines', 'Kravats, Andrea N|Tonddast-Navaei, Sam|Stan, George', 'Department of Chemistry, University of Cincinnati, Cincinnati, Ohio, United States of America.|Department of Chemistry, University of Cincinnati, Cincinnati, Ohio, United States of America.|Department of Chemistry, University of Cincinnati, Cincinnati, Ohio, United States of America.', 'United States|United States|United States', 3, 'Computers, Molecular|Endopeptidase Clp|Molecular Dynamics Simulation|Nanostructures|Protein Folding|Protein Unfolding', 'Journal Article', '10.1371/journal.pcbi.1004675', '26734937', 'Clp ATPases are powerful ring shaped nanomachines which participate in the degradation pathway of the protein quality control system, coupling the energy from ATP hydrolysis to threading substrate proteins (SP) through their narrow central pore. Repetitive cycles of sequential intra-ring ATP hydrolysis events induce axial excursions of diaphragm-forming central pore loops that effect the application of mechanical forces onto SPs to promote unfolding and translocation. We perform Langevin dynamics simulations of a coarse-grained model of the ClpY ATPase-SP system to elucidate the molecular details of unfolding and translocation of an xcexb1/xcexb2 model protein. We contrast this mechanism with our previous studies which used an all-xcexb1 SP. We find conserved aspects of unfolding and translocation mechanisms by allosteric ClpY, including unfolding initiated at the tagged C-terminus and translocation via a power stroke mechanism. Topology-specific aspects include the time scales, the rate limiting steps in the degradation pathway, the effect of force directionality, and the translocase efficacy. Mechanisms of ClpY-assisted unfolding and translocation are distinct from those resulting from non-allosteric mechanical pulling. Bulk unfolding simulations, which mimic Atomic Force Microscopy-type pulling, reveal multiple unfolding pathways initiated at the C-terminus, N-terminus, or simultaneously from both termini. In a non-allosteric ClpY ATPase pore, mechanical pulling with constant velocity yields larger effective forces for SP unfolding, while pulling with constant force results in simultaneous unfolding and translocation. '),
(87596, 2016, 'plos', 'Residual Viremia in Treated HIV+ Individuals', 'Conway, Jessica M|Perelson, Alan S', 'Department of Mathematics and Center for Infectious Disease Dynamics (CIDD), The Pennsylvania State University, University Park, Pennsylvania, United States of America.|Theoretical Biology and Biophysics, Los Alamos National Laboratory, Los Alamos, New Mexico, United States of America.', 'United States|Mexico', 28, 'Anti-Retroviral Agents|Computational Biology|HIV Infections|HIV-1|Humans|Models, Biological|RNA, Viral|Viral Load|Viremia|Virus Replication', 'Journal Article', '10.1371/journal.pcbi.1004677', '26735135', 'Antiretroviral therapy (ART) effectively controls HIV infection, suppressing HIV viral loads. However, some residual virus remains, below the level of detection, in HIV-infected patients on ART. The source of this viremia is an area of debate: does it derive primarily from activation of infected cells in the latent reservoir, or from ongoing viral replication? Observations seem to be contradictory: there is evidence of short term evolution, implying that there must be ongoing viral replication, and viral strains should thus evolve. However, phylogenetic analyses, and rare emergent drug resistance, suggest no long-term viral evolution, implying that virus derived from activated latent cells must dominate. We use simple deterministic and stochastic models to gain insight into residual viremia dynamics in HIV-infected patients. Our modeling relies on two underlying assumptions for patients on suppressive ART: that latent cell activation drives viral dynamics and that the reproductive ratio of treated infection is less than 1. Nonetheless, the contribution of viral replication to residual viremia in patients on ART may be non-negligible. However, even if the portion of viremia attributable to viral replication is significant, our model predicts (1) that latent reservoir re-seeding remains negligible, and (2) some short-term viral evolution is permitted, but long-term evolution can still be limited: stochastic analysis of our model shows that de novo emergence of drug resistance is rare. Thus, our simple models reconcile the seemingly contradictory observations on residual viremia and, with relatively few parameters, recapitulates HIV viral dynamics observed in patients on suppressive therapy. '),
(87597, 2016, 'plos', 'Correction: Improving Collective Estimations Using Resistance to Social Influence', 'PLOS Computational Biology Staff', 'Theoretical Biology and Biophysics, Los Alamos National Laboratory, Los Alamos, New Mexico, United States of America.', 'Mexico', 0, '-', 'Published Erratum', '10.1371/journal.pcbi.1004713', '26735304', '[This corrects the article DOI: 10.1371/journal.pcbi.1004594.]. '),
(87598, 2016, 'plos', 'Model-Based Analysis of Cell Cycle Responses to Dynamically Changing Environments', 'Seaton, Daniel D|Krishnan, J', 'Department of Chemical Engineering, Centre for Process Systems Engineering, Institute for Systems and Synthetic Biology, Imperial College London, London, United Kingdom.|Department of Chemical Engineering, Centre for Process Systems Engineering, Institute for Systems and Synthetic Biology, Imperial College London, London, United Kingdom.', 'United Kingdom|United Kingdom', 0, 'Cell Cycle|Glucose|Models, Biological|Saccharomyces cerevisiae|Signal Transduction|Systems Biology', 'Journal Article', '10.1371/journal.pcbi.1004604', '26741131', 'Cell cycle progression is carefully coordinated with a cells intra- and extracellular environment. While some pathways have been identified that communicate information from the environment to the cell cycle, a systematic understanding of how this information is dynamically processed is lacking. We address this by performing dynamic sensitivity analysis of three mathematical models of the cell cycle in Saccharomyces cerevisiae. We demonstrate that these models make broadly consistent qualitative predictions about cell cycle progression under dynamically changing conditions. For example, it is shown that the models predict anticorrelated changes in cell size and cell cycle duration under different environments independently of the growth rate. This prediction is validated by comparison to available literature data. Other consistent patterns emerge, such as widespread nonmonotonic changes in cell size down generations in response to parameter changes. We extend our analysis by investigating glucose signalling to the cell cycle, showing that known regulation of Cln3 translation and Cln1,2 transcription by glucose is sufficient to explain the experimentally observed changes in cell cycle dynamics at different glucose concentrations. Together, these results provide a framework for understanding the complex responses the cell cycle is capable of producing in response to dynamic environments. '),
(87599, 2016, 'plos', 'Faster Adaptation in Smaller Populations: Counterintuitive Evolution of HIV during Childhood Infection', 'Raghwani, Jayna|Bhatt, Samir|Pybus, Oliver G', 'Department of Zoology, University of Oxford, South Parks Road, Oxford, United Kingdom.|Department of Zoology, University of Oxford, South Parks Road, Oxford, United Kingdom.|Department of Zoology, University of Oxford, South Parks Road, Oxford, United Kingdom.', 'United Kingdom|United Kingdom|United Kingdom', 4, 'Child|Computational Biology|Evolution, Molecular|HIV Infections|HIV-1|Host-Pathogen Interactions|Humans|Models, Biological', 'Journal Article', '10.1371/journal.pcbi.1004694', '26741359', 'Analysis of HIV-1 gene sequences sampled longitudinally from infected individuals can reveal the evolutionary dynamics that underlie associations between disease outcome and viral genetic diversity and divergence. Here we extend a statistical framework to estimate rates of viral molecular adaptation by considering sampling error when computing nucleotide site-frequencies. This is particularly beneficial when analyzing viral sequences from within-host viral infections if the number of sequences per time point is limited. To demonstrate the utility of this approach, we apply our method to a cohort of 24 patients infected with HIV-1 at birth. Our approach finds that viral adaptation arising from recurrent positive natural selection is associated with the rate of HIV-1 disease progression, in contrast to previous analyses of these data that found no significant association. Most surprisingly, we discover a strong negative correlation between viral population size and the rate of viral adaptation, the opposite of that predicted by standard molecular evolutionary theory. We argue that this observation is most likely due to the existence of a confounding third variable, namely variation in selective pressure among hosts. A conceptual non-linear model of virus adaptation that incorporates the two opposing effects of host immunity on the virus population can explain this counterintuitive result. '),
(87600, 2016, 'plos', 'Evidence for Functional Groupings of Vibrissae across the Rodent Mystacial Pad', 'Hobbs, Jennifer A|Towal, R Blythe|Hartmann, Mitra J Z', 'Department of Physics and Astronomy, Northwestern University, Evanston, Illinois, United States of America.|Department of Biomedical Engineering, Northwestern University, Evanston, Illinois, United States of America.|Department of Biomedical Engineering, Northwestern University, Evanston, Illinois, United States of America.', 'United States|United States|United States', 8, 'Animals|Behavior, Animal|Computational Biology|Exploratory Behavior|Female|Models, Biological|Posture|Rats|Rats, Long-Evans|Rats, Sprague-Dawley|Touch|Vibrissae', 'Journal Article', '10.1371/journal.pcbi.1004109', '26745501', 'During natural exploration, rats exhibit two particularly conspicuous vibrissal-mediated behaviors: they follow along walls, and dab their snouts on the ground at frequencies related to the whisking cycle. In general, the walls and ground may be located at any distance from, and at any orientation relative to, the rats head, which raises the question of how the rat might determine the position and orientation of these surfaces. Previous studies have compellingly demonstrated that rats can accurately determine the horizontal angle at which a vibrissa first touches an object, and we therefore asked whether this parameter could provide the rat with information about the pitch, distance, and yaw of a surface relative to its head. We used a three-dimensional model of the whisker array to construct mappings between the horizontal angle of contact of each vibrissa and every possible (pitch, distance, and yaw) configuration of the head relative to a flat surface. The mappings revealed striking differences in the patterns of contact for vibrissae in different regions of the array. The exterior (A, D, E) rows provide information about the relative pitch of the surface regardless of distance. The interior (B, C) rows provide distance cues regardless of head pitch. Yaw is linearly correlated with the difference between the number of right and left whiskers touching the surface. Compared to the long reaches that whiskers can make to the side and below the rat, the reachable distance in front of the rats nose is relatively small. We confirmed key predictions of these functional groupings in a behavioral experiment that monitored the contact patterns that the vibrissae made with a flat vertical surface. These results suggest that vibrissae in different regions of the array are not interchangeable sensors, but rather functionally grouped to acquire particular types of information about the environment. '),
(87601, 2016, 'plos', 'Josephin Domain Structural Conformations Explored by Metadynamics in Essential Coordinates', 'Deriu, Marco A|Grasso, Gianvito|Tuszynski, Jack A|Gallo, Diego|Morbiducci, Umberto|Danani, Andrea', 'Istituto Dalle Molle di studi sullIntelligenza Artificiale (IDSIA), Scuola universitaria professionale della Svizzera italiana (SUPSI), Università della Svizzera italiana (USI), Manno, Switzerland.|Istituto Dalle Molle di studi sullIntelligenza Artificiale (IDSIA), Scuola universitaria professionale della Svizzera italiana (SUPSI), Università della Svizzera italiana (USI), Manno, Switzerland.|Department of Physics, University of Alberta, Edmonton, Alberta, Canada.|Department of Mechanical and Aerospace Engineering, Politecnico di Torino, Torino, Italy.|Department of Mechanical and Aerospace Engineering, Politecnico di Torino, Torino, Italy.|Istituto Dalle Molle di studi sullIntelligenza Artificiale (IDSIA), Scuola universitaria professionale della Svizzera italiana (SUPSI), Università della Svizzera italiana (USI), Manno, Switzerland.', 'Switzerland|Switzerland|Canada|Italy|Italy|Switzerland', 15, 'Ataxin-3|Computational Biology|Models, Chemical|Molecular Dynamics Simulation|Principal Component Analysis|Protein Structure, Tertiary|Thermodynamics', 'Journal Article', '10.1371/journal.pcbi.1004699', '26745628', 'The Josephin Domain (JD), i.e. the N-terminal domain of Ataxin 3 (At3) protein, is an interesting example of competition between physiological function and aggregation risk. In fact, the fibrillogenesis of Ataxin 3, responsible for the spinocerebbellar ataxia 3, is strictly related to the JD thermodynamic stability. Whereas recent NMR studies have demonstrated that different JD conformations exist, the likelihood of JD achievable conformational states in solution is still an open issue. Marked differences in the available NMR models are located in the hairpin region, supporting the idea that JD has a flexible hairpin in dynamic equilibrium between open and closed states. In this work we have carried out an investigation on the JD conformational arrangement by means of both classical molecular dynamics (MD) and Metadynamics employing essential coordinates as collective variables. We provide a representation of the free energy landscape characterizing the transition pathway from a JD open-like structure to a closed-like conformation. Findings of our in silico study strongly point to the closed-like conformation as the most likely for a Josephin Domain in water. '),
(87602, 2016, 'plos', 'Consistency of VDJ Rearrangement and Substitution Parameters Enables Accurate B Cell Receptor Sequence Annotation', 'Ralph, Duncan K|Matsen, Frederick A', 'Fred Hutchinson Cancer Research Center, Seattle, Washington, United States of America.|Fred Hutchinson Cancer Research Center, Seattle, Washington, United States of America.', 'United States|United States', 45, 'Computational Biology|Computer Simulation|Databases, Genetic|Gene Rearrangement, B-Lymphocyte|Humans|Models, Genetic|Molecular Sequence Annotation|Sequence Analysis, DNA|VDJ Exons', 'Journal Article', '10.1371/journal.pcbi.1004409', '26751373', 'VDJ rearrangement and somatic hypermutation work together to produce antibody-coding B cell receptor (BCR) sequences for a remarkable diversity of antigens. It is now possible to sequence these BCRs in high throughput, analysis of these sequences is bringing new insight into how antibodies develop, in particular for broadly-neutralizing antibodies against HIV and influenza. A fundamental step in such sequence analysis is to annotate each base as coming from a specific one of the V, D, or J genes, or from an N-addition (a.k.a. non-templated insertion). Previous work has used simple parametric distributions to model transitions from state to state in a hidden Markov model (HMM) of VDJ recombination, and assumed that mutations occur via the same process across sites. However, codon frame and other effects have been observed to violate these parametric assumptions for such coding sequences, suggesting that a non-parametric approach to modeling the recombination process could be useful. In our paper, we find that indeed large modern data sets suggest a model using parameter-rich per-allele categorical distributions for HMM transition probabilities and per-allele-per-position mutation probabilities, and that using such a model for inference leads to significantly improved results. We present an accurate and efficient BCR sequence annotation software package using a novel HMM factorization strategy. This package, called partis (https://github.com/psathyrella/partis/), is built on a new general-purpose HMM compiler that can perform efficient inference given a simple text description of an HMM. '),
(87603, 2016, 'plos', 'A Network Model to Describe the Terminal Differentiation of B Cells', 'Méndez, Akram|Mendoza, Luis', 'Programa de Doctorado en Ciencias Bioquímicas, Universidad Nacional Autónoma de México, Ciudad de México, México.|Instituto de Investigaciones Biomédicas, Universidad Nacional Autónoma de México, Ciudad de México, México.', '-|-', 23, 'Animals|B-Lymphocytes|Cell Differentiation|Cells, Cultured|Computational Biology|Intracellular Signaling Peptides and Proteins|Mice|Models, Immunological|Signal Transduction|T-Lymphocytes, Helper-Inducer', 'Journal Article', '10.1371/journal.pcbi.1004696', '26751566', 'Terminal differentiation of B cells is an essential process for the humoral immune response in vertebrates and is achieved by the concerted action of several transcription factors in response to antigen recognition and extracellular signals provided by T-helper cells. While there is a wealth of experimental data regarding the molecular and cellular signals involved in this process, there is no general consensus regarding the structure and dynamical properties of the underlying regulatory network controlling this process. We developed a dynamical model of the regulatory network controlling terminal differentiation of B cells. The structure of the network was inferred from experimental data available in the literature, and its dynamical behavior was analyzed by modeling the network both as a discrete and a continuous dynamical systems. The steady states of these models are consistent with the patterns of activation reported for the Naive, GC, Mem, and PC cell types. Moreover, the models are able to describe the patterns of differentiation from the precursor Naive to any of the GC, Mem, or PC cell types in response to a specific set of extracellular signals. We simulated all possible single loss- and gain-of-function mutants, corroborating the importance of Pax5, Bcl6, Bach2, Irf4, and Blimp1 as key regulators of B cell differentiation process. The model is able to represent the directional nature of terminal B cell differentiation and qualitatively describes key differentiation events from a precursor cell to terminally differentiated B cells. '),
(87604, 2016, 'plos', 'The Molecular Basis of Polyunsaturated Fatty Acid Interactions with the Shaker Voltage-Gated Potassium Channel', 'Yazdi, Samira|Stein, Matthias|Elinder, Fredrik|Andersson, Magnus|Lindahl, Erik', 'Max Planck Institute for Dynamics of Complex Technical Systems, Molecular Simulations and Design Group, Magdeburg, Germany.|Max Planck Institute for Dynamics of Complex Technical Systems, Molecular Simulations and Design Group, Magdeburg, Germany.|Department of Clinical and Experimental Medicine, Linköping University, Linköping, Sweden.|Science for Life Laboratory, Stockholm and Uppsala, Stockholm, Sweden.|Science for Life Laboratory, Stockholm and Uppsala, Stockholm, Sweden.', 'Germany|Germany|Sweden|Sweden|Sweden', 30, 'Binding Sites|Computational Biology|Fatty Acids, Unsaturated|Models, Molecular|Shaker Superfamily of Potassium Channels', 'Journal Article', '10.1371/journal.pcbi.1004704', '26751683', 'Voltage-gated potassium (KV) channels are membrane proteins that respond to changes in membrane potential by enabling K+ ion flux across the membrane. Polyunsaturated fatty acids (PUFAs) induce channel opening by modulating the voltage-sensitivity, which can provide effective treatment against refractory epilepsy by means of a ketogenic diet. While PUFAs have been reported to influence the gating mechanism by electrostatic interactions to the voltage-sensor domain (VSD), the exact PUFA-protein interactions are still elusive. In this study, we report on the interactions between the Shaker KV channel in open and closed states and a PUFA-enriched lipid bilayer using microsecond molecular dynamics simulations. We determined a putative PUFA binding site in the open state of the channel located at the protein-lipid interface in the vicinity of the extracellular halves of the S3 and S4 helices of the VSD. In particular, the lipophilic PUFA tail covered a wide range of non-specific hydrophobic interactions in the hydrophobic central core of the protein-lipid interface, while the carboxylic head group displayed more specific interactions to polar/charged residues at the extracellular regions of the S3 and S4 helices, encompassing the S3-S4 linker. Moreover, by studying the interactions between saturated fatty acids (SFA) and the Shaker KV channel, our study confirmed an increased conformational flexibility in the polyunsaturated carbon tails compared to saturated carbon chains, which may explain the specificity of PUFA action on channel proteins. '),
(87605, 2016, 'plos', 'Asymmetrical Damage Partitioning in Bacteria: A Model for the Evolution of Stochasticity, Determinism, and Genetic Assimilation', 'Chao, Lin|Rang, Camilla Ulla|Proenca, Audrey Menegaz|Chao, Jasper Ubirajara', 'Section of Ecology, Behavior and Evolution, Division of Biological Sciences, University of California, San Diego, La Jolla, California, United States of America.|Section of Ecology, Behavior and Evolution, Division of Biological Sciences, University of California, San Diego, La Jolla, California, United States of America.|Section of Ecology, Behavior and Evolution, Division of Biological Sciences, University of California, San Diego, La Jolla, California, United States of America.|Section of Ecology, Behavior and Evolution, Division of Biological Sciences, University of California, San Diego, La Jolla, California, United States of America.', 'United States|United States|United States|United States', 15, 'Biological Evolution|Cell Polarity|Computational Biology|Escherichia coli|Genetic Fitness|Models, Biological|Selection, Genetic|Stochastic Processes', 'Journal Article', '10.1371/journal.pcbi.1004700', '26761487', 'Non-genetic phenotypic variation is common in biological organisms. The variation is potentially beneficial if the environment is changing. If the benefit is large, selection can favor the evolution of genetic assimilation, the process by which the expression of a trait is transferred from environmental to genetic control. Genetic assimilation is an important evolutionary transition, but it is poorly understood because the fitness costs and benefits of variation are often unknown. Here we show that the partitioning of damage by a mother bacterium to its two daughters can evolve through genetic assimilation. Bacterial phenotypes are also highly variable. Because gene-regulating elements can have low copy numbers, the variation is attributed to stochastic sampling. Extant Escherichia coli partition asymmetrically and deterministically more damage to the old daughter, the one receiving the mothers old pole. By modeling in silico damage partitioning in a population, we show that deterministic asymmetry is advantageous because it increases fitness variance and hence the efficiency of natural selection. However, we find that symmetrical but stochastic partitioning can be similarly beneficial. To examine why bacteria evolved deterministic asymmetry, we modeled the effect of damage anchored to the mothers old pole. While anchored damage strengthens selection for asymmetry by creating additional fitness variance, it has the opposite effect on symmetry. The difference results because anchored damage reinforces the polarization of partitioning in asymmetric bacteria. In symmetric bacteria, it dilutes the polarization. Thus, stochasticity alone may have protected early bacteria from damage, but deterministic asymmetry has evolved to be equally important in extant bacteria. We estimate that 47% of damage partitioning is deterministic in E. coli. We suggest that the evolution of deterministic asymmetry from stochasticity offers an example of Waddingtons genetic assimilation. Our model is able to quantify the evolution of the assimilation because it characterizes the fitness consequences of variation. ');
INSERT INTO `papers` (`id`, `ano`, `journal`, `titulo`, `autores`, `afiliacao`, `pais`, `citacoes`, `palavra_chave`, `categorias`, `doi`, `pubmed`, `abstract`) VALUES
(87606, 2016, 'plos', 'Brain Connectivity Dissociates Responsiveness from Drug Exposure during Propofol-Induced Transitions of Consciousness', 'Chennu, Srivas|OConnor, Stuart|Adapa, Ram|Menon, David K|Bekinschtein, Tristan A', 'Department of Clinical Neurosciences, University of Cambridge, Cambridge, United Kingdom.|Warwick Medical School, University of Warwick, Coventry, United Kingdom.|Division of Anaesthesia, University of Cambridge, Cambridge, United Kingdom.|Division of Anaesthesia, University of Cambridge, Cambridge, United Kingdom.|Medical Research Council, Cognition and Brain Sciences Unit, Cambridge, United Kingdom.', 'United Kingdom|United Kingdom|United Kingdom|United Kingdom|United Kingdom', 45, 'Adult|Brain Waves|Computational Biology|Consciousness|Electroencephalography|Female|Humans|Hypnotics and Sedatives|Male|Propofol|Young Adult', 'Journal Article', '10.1371/journal.pcbi.1004669', '26764466', 'Accurately measuring the neural correlates of consciousness is a grand challenge for neuroscience. Despite theoretical advances, developing reliable brain measures to track the loss of reportable consciousness during sedation is hampered by significant individual variability in susceptibility to anaesthetics. We addressed this challenge using high-density electroencephalography to characterise changes in brain networks during propofol sedation. Assessments of spectral connectivity networks before, during and after sedation were combined with measurements of behavioural responsiveness and drug concentrations in blood. Strikingly, we found that participants who had weaker alpha band networks at baseline were more likely to become unresponsive during sedation, despite registering similar levels of drug in blood. In contrast, phase-amplitude coupling between slow and alpha oscillations correlated with drug concentrations in blood. Our findings highlight novel markers that prognosticate individual differences in susceptibility to propofol and track drug exposure. These advances could inform accurate drug titration and brain state monitoring during anaesthesia. '),
(87607, 2016, 'plos', 'Optimal Population-Level Infection Detection Strategies for Malaria Control and Elimination in a Spatial Model of Malaria Transmission', 'Gerardin, Jaline|Bever, Caitlin A|Hamainza, Busiku|Miller, John M|Eckhoff, Philip A|Wenger, Edward A', 'Institute for Disease Modeling, Bellevue, Washington, United States of America.|Institute for Disease Modeling, Bellevue, Washington, United States of America.|National Malaria Control Centre, Lusaka, Zambia.|PATH Malaria Control and Elimination Partnership in Africa (MACEPA), Lusaka, Zambia.|Institute for Disease Modeling, Bellevue, Washington, United States of America.|Institute for Disease Modeling, Bellevue, Washington, United States of America.', 'United States|United States|Zambia|Zambia|United States|United States', 20, 'Antimalarials|Computational Biology|Disease Eradication|Humans|Malaria|Population Surveillance', 'Journal Article', '10.1371/journal.pcbi.1004707', '26764905', 'Mass campaigns with antimalarial drugs are potentially a powerful tool for local elimination of malaria, yet current diagnostic technologies are insufficiently sensitive to identify all individuals who harbor infections. At the same time, overtreatment of uninfected individuals increases the risk of accelerating emergence of drug resistance and losing community acceptance. Local heterogeneity in transmission intensity may allow campaign strategies that respond to index cases to successfully target subpatent infections while simultaneously limiting overtreatment. While selective targeting of hotspots of transmission has been proposed as a strategy for malaria control, such targeting has not been tested in the context of malaria elimination. Using household locations, demographics, and prevalence data from a survey of four health facility catchment areas in southern Zambia and an agent-based model of malaria transmission and immunity acquisition, a transmission intensity was fit to each household based on neighborhood age-dependent malaria prevalence. A set of individual infection trajectories was constructed for every household in each catchment area, accounting for heterogeneous exposure and immunity. Various campaign strategies-mass drug administration, mass screen and treat, focal mass drug administration, snowball reactive case detection, pooled sampling, and a hypothetical serological diagnostic-were simulated and evaluated for performance at finding infections, minimizing overtreatment, reducing clinical case counts, and interrupting transmission. For malaria control, presumptive treatment leads to substantial overtreatment without additional morbidity reduction under all but the highest transmission conditions. Compared with untargeted approaches, selective targeting of hotspots with drug campaigns is an ineffective tool for elimination due to limited sensitivity of available field diagnostics. Serological diagnosis is potentially an effective tool for malaria elimination but requires higher coverage to achieve similar results to mass distribution of presumptive treatment. '),
(87608, 2016, 'plos', 'Discovery of Influenza A Virus Sequence Pairs and Their Combinations for Simultaneous Heterosubtypic Targeting that Hedge against Antiviral Resistance', 'Wee, Keng Boon|Lee, Raphael Tze Chuen|Lin, Jing|Pramono, Zacharias Aloysius Dwi|Maurer-Stroh, Sebastian', 'Fluid Dynamics Department, Institute of High Performance Computing (IHPC), A*STAR (Agency for Science, Technology and Research), Singapore, Singapore.|Biomolecular Function Discovery Division, Bioinformatics Institute (BII), A*STAR (Agency for Science, Technology and Research), Singapore, Singapore.|Fluid Dynamics Department, Institute of High Performance Computing (IHPC), A*STAR (Agency for Science, Technology and Research), Singapore, Singapore.|Department of Research, National Skin Centre, Singapore, Singapore.|Biomolecular Function Discovery Division, Bioinformatics Institute (BII), A*STAR (Agency for Science, Technology and Research), Singapore, Singapore.', 'Singapore|Singapore|Singapore|Singapore|Singapore', 1, 'Animals|Antiviral Agents|Base Sequence|Chickens|Computational Biology|Computer Simulation|Conserved Sequence|Drug Resistance, Viral|Gene Expression Profiling|Host-Pathogen Interactions|Humans|Influenza A virus|Influenza, Human|Orthomyxoviridae Infections|Swine', 'Journal Article', '10.1371/journal.pcbi.1004663', '26771381', 'The multiple circulating human influenza A virus subtypes coupled with the perpetual genomic mutations and segment reassortment events challenge the development of effective therapeutics. The capacity to drug most RNAs motivates the investigation on viral RNA targets. 123,060 segment sequences from 35,938 strains of the most prevalent subtypes also infecting humans-H1N1, 2009 pandemic H1N1, H3N2, H5N1 and H7N9, were used to identify 1,183 conserved RNA target sequences (xe2x89xa515-mer) in the internal segments. 100% theoretical coverage in simultaneous heterosubtypic targeting is achieved by pairing specific sequences from the same segment (Duals) or from two segments (Doubles), 1,662 Duals and 28,463 Doubles identified. By combining specific Duals and/or Doubles to form a target graph wherein an edge connecting two vertices (target sequences) represents a Dual or Double, it is possible to hedge against antiviral resistance besides maintaining 100% heterosubtypic coverage. To evaluate the hedging potential, we define the hedge-factor as the minimum number of resistant target sequences that will render the graph to become resistant i.e. eliminate all the edges therein, a target sequence or a graph is considered resistant when it cannot achieve 100% heterosubtypic coverage. In an n-vertices graph (n xe2x89xa5 3), the hedge-factor is maximal (= n- 1) when it is a complete graph i.e. every distinct pair in a graph is either a Dual or Double. Computational analyses uncover an extensive number of complete graphs of different sizes. Monte Carlo simulations show that the mutation counts and time elapsed for a target graph to become resistant increase with the hedge-factor. Incidentally, target sequences which were reported to reduce virus titre in experiments are included in our target graphs. The identity of target sequence pairs for heterosubtypic targeting and their combinations for hedging antiviral resistance are useful toolkits to construct target graphs for different therapeutic objectives. '),
(87609, 2016, 'plos', 'Correction: Depletion of the Chromatin Looping Proteins CTCF and Cohesin Causes Chromatin Compaction: Insight into Chromatin Folding by Polymer Modelling', 'PLOS Computational Biology Staff', 'Biomolecular Function Discovery Division, Bioinformatics Institute (BII), A*STAR (Agency for Science, Technology and Research), Singapore, Singapore.', 'Singapore', 0, '-', 'Published Erratum', '10.1371/journal.pcbi.1004716', '26771514', '[This corrects the article DOI: 10.1371/journal.pcbi.1003877.]. '),
(87610, 2016, 'plos', 'A Quick Introduction to Version Control with Git and GitHub', 'Blischak, John D|Davenport, Emily R|Wilson, Greg', 'Committee on Genetics, Genomics, and Systems Biology, University of Chicago, Chicago, Illinois, United States of America.|Department of Molecular Biology and Genetics, Cornell University, Ithaca, New York, United States of America.|Software Carpentry Foundation, Toronto, Ontario, Canada.', 'United States|United States|Canada', 43, 'Computational Biology|Humans|Programming Languages|Software', 'Journal Article', '10.1371/journal.pcbi.1004668', '26785377', '-'),
(87611, 2016, 'plos', 'Evolutionary and Functional Relationships in the Truncated Hemoglobin Family', 'Bustamante, Juan P|Radusky, Leandro|Boechi, Leonardo|Estrin, Darío A|Ten Have, Arjen|Martí, Marcelo A', 'Departamento de Química Inorgánica, Analítica y Química Física, INQUIMAE-CONICET, Facultad de Ciencias Exactas y Naturales, Universidad de Buenos Aires, Buenos Aires, Argentina.|Departamento de Química Biológica e Instituto de Química Biológica de la Facultad de Ciencias Exactas y Naturales (IQUIBICEN), Universidad de Buenos Aires, Buenos Aires, Argentina.|Instituto de Cálculo, Facultad de Ciencias Exactas y Naturales, Universidad de Buenos Aires, Buenos Aires, Argentina.|Departamento de Química Inorgánica, Analítica y Química Física, INQUIMAE-CONICET, Facultad de Ciencias Exactas y Naturales, Universidad de Buenos Aires, Buenos Aires, Argentina.|Instituto de Investigación Biológica, CONICET, Universidad Nacional de Mar del Plata. Buenos Aires, Argentina.|Instituto de Cálculo, Facultad de Ciencias Exactas y Naturales, Universidad de Buenos Aires, Buenos Aires, Argentina.', 'Argentina|Argentina|Argentina|Argentina|Argentina|Argentina', 19, 'Amino Acid Sequence|Computational Biology|Evolution, Molecular|Linear Models|Models, Molecular|Molecular Sequence Data|Oxygen|Phylogeny|Sequence Alignment|Truncated Hemoglobins', 'Journal Article', '10.1371/journal.pcbi.1004701', '26788940', 'Predicting function from sequence is an important goal in current biological research, and although, broad functional assignment is possible when a protein is assigned to a family, predicting functional specificity with accuracy is not straightforward. If function is provided by key structural properties and the relevant properties can be computed using the sequence as the starting point, it should in principle be possible to predict function in detail. The truncated hemoglobin family presents an interesting benchmark study due to their ubiquity, sequence diversity in the context of a conserved fold and the number of characterized members. Their functions are tightly related to O2 affinity and reactivity, as determined by the association and dissociation rate constants, both of which can be predicted and analyzed using in-silico based tools. In the present work we have applied a strategy, which combines homology modeling with molecular based energy calculations, to predict and analyze function of all known truncated hemoglobins in an evolutionary context. Our results show that truncated hemoglobins present conserved family features, but that its structure is flexible enough to allow the switch from high to low affinity in a few evolutionary steps. Most proteins display moderate to high oxygen affinities and multiple ligand migration paths, which, besides some minor trends, show heterogeneous distributions throughout the phylogenetic tree, again suggesting fast functional adaptation. Our data not only deepens our comprehension of the structural basis governing ligand affinity, but they also highlight some interesting functional evolutionary trends. '),
(87612, 2016, 'plos', 'Computational Modeling, Formal Analysis, and Tools for Systems Biology', 'Bartocci, Ezio|Lió, Pietro', 'Faculty of Informatics, Technische Universität Wien, Vienna, Austria.|Computer Laboratory, University of Cambridge, Cambridge, United Kingdom.', 'Austria|United Kingdom', 68, 'Computer Simulation|Models, Biological|Software|Systems Biology', 'Journal Article', '10.1371/journal.pcbi.1004591', '26795950', 'As the amount of biological data in the public domain grows, so does the range of modeling and analysis techniques employed in systems biology. In recent years, a number of theoretical computer science developments have enabled modeling methodology to keep pace. The growing interest in systems biology in executable models and their analysis has necessitated the borrowing of terms and methods from computer science, such as formal analysis, model checking, static analysis, and runtime verification. Here, we discuss the most important and exciting computational methods and tools currently available to systems biologists. We believe that a deeper understanding of the concepts and theory highlighted in this review will produce better software practice, improved investigation of complex biological processes, and even new ideas and better feedback into computer science. '),
(87613, 2016, 'plos', 'Measuring Integrated Information from the Decoding Perspective', 'Oizumi, Masafumi|Amari, Shun-ichi|Yanagawa, Toru|Fujii, Naotaka|Tsuchiya, Naotsugu', 'RIKEN Brain Science Institute, Wako, Saitama, Japan.|RIKEN Brain Science Institute, Wako, Saitama, Japan.|RIKEN Brain Science Institute, Wako, Saitama, Japan.|RIKEN Brain Science Institute, Wako, Saitama, Japan.|School of Psychological Sciences, Faculty of Biomedical and Psychological Sciences, Monash University, Clayton, Victoria, Australia.', 'Japan|Japan|Japan|Japan|Australia', 48, 'Animals|Cerebral Cortex|Computational Biology|Consciousness|Electrocorticography|Information Theory|Macaca|Models, Neurological|Normal Distribution', 'Journal Article', '10.1371/journal.pcbi.1004654', '26796119', 'Accumulating evidence indicates that the capacity to integrate information in the brain is a prerequisite for consciousness. Integrated Information Theory (IIT) of consciousness provides a mathematical approach to quantifying the information integrated in a system, called integrated information, xcexa6. Integrated information is defined theoretically as the amount of information a system generates as a whole, above and beyond the amount of information its parts independently generate. IIT predicts that the amount of integrated information in the brain should reflect levels of consciousness. Empirical evaluation of this theory requires computing integrated information from neural data acquired from experiments, although difficulties with using the original measure xcexa6 precludes such computations. Although some practical measures have been previously proposed, we found that these measures fail to satisfy the theoretical requirements as a measure of integrated information. Measures of integrated information should satisfy the lower and upper bounds as follows: The lower bound of integrated information should be 0 and is equal to 0 when the system does not generate information (no information) or when the system comprises independent parts (no integration). The upper bound of integrated information is the amount of information generated by the whole system. Here we derive the novel practical measure xcexa6* by introducing a concept of mismatched decoding developed from information theory. We show that xcexa6* is properly bounded from below and above, as required, as a measure of integrated information. We derive the analytical expression of xcexa6* under the Gaussian assumption, which makes it readily applicable to experimental data. Our novel measure xcexa6* can generally be used as a measure of integrated information in research on consciousness, and also as a tool for network analysis on diverse areas of biology. '),
(87614, 2016, 'plos', 'Model-Based Comprehensive Analysis of School Closure Policies for Mitigating Influenza Epidemics and Pandemics', 'Fumanelli, Laura|Ajelli, Marco|Merler, Stefano|Ferguson, Neil M|Cauchemez, Simon', 'Bruno Kessler Foundation, Trento, Italy.|Bruno Kessler Foundation, Trento, Italy.|Bruno Kessler Foundation, Trento, Italy.|MRC Centre for Outbreak Analysis and Modelling, School of Public Health, Imperial College London, London, United Kingdom.|Mathematical Modelling of Infectious Diseases Unit, Institut Pasteur, Paris, France.', 'Italy|Italy|Italy|United Kingdom|France', 20, 'Absenteeism|Computational Biology|Computer Simulation|Humans|Influenza, Human|Models, Biological|Pandemics|Schools|Students', 'Journal Article', '10.1371/journal.pcbi.1004681', '26796333', 'School closure policies are among the non-pharmaceutical measures taken into consideration to mitigate influenza epidemics and pandemics spread. However, a systematic review of the effectiveness of alternative closure policies has yet to emerge. Here we perform a model-based analysis of four types of school closure, ranging from the nationwide closure of all schools at the same time to reactive gradual closure, starting from class-by-class, then grades and finally the whole school. We consider policies based on triggers that are feasible to monitor, such as school absenteeism and national ILI surveillance system. We found that, under specific constraints on the average number of weeks lost per student, reactive school-by-school, gradual, and county-wide closure give comparable outcomes in terms of optimal infection attack rate reduction, peak incidence reduction or peak delay. Optimal implementations generally require short closures of one week each, this duration is long enough to break the transmission chain without leading to unnecessarily long periods of class interruption. Moreover, we found that gradual and county closures may be slightly more easily applicable in practice as they are less sensitive to the value of the excess absenteeism threshold triggering the start of the intervention. These findings suggest that policy makers could consider school closure policies more diffusely as response strategy to influenza epidemics and pandemics, and the fact that some countries already have some experience of gradual or regional closures for seasonal influenza outbreaks demonstrates that logistic and feasibility challenges of school closure strategies can be to some extent overcome. '),
(87615, 2016, 'plos', 'Spatial Metrics of Tumour Vascular Organisation Predict Radiation Efficacy in a Computational Model', 'Scott, Jacob G|Fletcher, Alexander G|Anderson, Alexander R A|Maini, Philip K', 'Department of Integrated Mathematical Oncology, H. Lee Moffitt Cancer Center and Research Institute, Tampa, Florida, United States of America.|Wolfson Centre for Mathematical Biology, Mathematical Institute, University of Oxford, Oxford, United Kingdom.|Department of Integrated Mathematical Oncology, H. Lee Moffitt Cancer Center and Research Institute, Tampa, Florida, United States of America.|Wolfson Centre for Mathematical Biology, Mathematical Institute, University of Oxford, Oxford, United Kingdom.', 'United States|United Kingdom|United States|United Kingdom', 23, 'Apoptosis|Computational Biology|Humans|Models, Biological|Neoplasm Invasiveness|Neoplasms|Neovascularization, Pathologic', 'Journal Article', '10.1371/journal.pcbi.1004712', '26800503', 'Intratumoural heterogeneity is known to contribute to poor therapeutic response. Variations in oxygen tension in particular have been correlated with changes in radiation response in vitro and at the clinical scale with overall survival. Heterogeneity at the microscopic scale in tumour blood vessel architecture has been described, and is one source of the underlying variations in oxygen tension. We seek to determine whether histologic scale measures of the erratic distribution of blood vessels within a tumour can be used to predict differing radiation response. Using a two-dimensional hybrid cellular automaton model of tumour growth, we evaluate the effect of vessel distribution on cell survival outcomes of simulated radiation therapy. Using the standard equations for the oxygen enhancement ratio for cell survival probability under differing oxygen tensions, we calculate average radiation effect over a range of different vessel densities and organisations. We go on to quantify the vessel distribution heterogeneity and measure spatial organization using Ripleys L function, a measure designed to detect deviations from complete spatial randomness. We find that under differing regimes of vessel density the correlation coefficient between the measure of spatial organization and radiation effect changes sign. This provides not only a useful way to understand the differences seen in radiation effect for tissues based on vessel architecture, but also an alternate explanation for the vessel normalization hypothesis. '),
(87616, 2016, 'plos', 'A Computational Model for the AMPA Receptor Phosphorylation Master Switch Regulating Cerebellar Long-Term Depression', 'Gallimore, Andrew R|Aricescu, A Radu|Yuzaki, Michisuke|Calinescu, Radu', 'Department of Computer Science, University of York, York, United Kingdom.|Division of Structural Biology, Wellcome Trust Centre for Human Genetics, University of Oxford, Oxford, United Kingdom.|Department of Physiology, Graduate School of Medicine, Keio University, Tokyo, Japan.|Department of Computer Science, University of York, York, United Kingdom.', 'United Kingdom|United Kingdom|Japan|United Kingdom', 9, 'Cerebellum|Computational Biology|Computer Simulation|Dendritic Spines|Long-Term Synaptic Depression|Models, Neurological|Phosphorylation|Receptors, AMPA|Synapses', 'Journal Article', '10.1371/journal.pcbi.1004664', '26807999', 'The expression of long-term depression (LTD) in cerebellar Purkinje cells results from the internalisation of xcexb1-amino-3-hydroxy-5-methylisoxazole-4-propionic acid receptors (AMPARs) from the postsynaptic membrane. This process is regulated by a complex signalling pathway involving sustained protein kinase C (PKC) activation, inhibition of serine/threonine phosphatase, and an active protein tyrosine phosphatase, PTPMEG. In addition, two AMPAR-interacting proteins-glutamate receptor-interacting protein (GRIP) and protein interacting with C kinase 1 (PICK1)-regulate the availability of AMPARs for trafficking between the postsynaptic membrane and the endosome. Here we present a new computational model of these overlapping signalling pathways. The model reveals how PTPMEG cooperates with PKC to drive LTD expression by facilitating the effect of PKC on the dissociation of AMPARs from GRIP and thus their availability for trafficking. Model simulations show that LTD expression is increased by serine/threonine phosphatase inhibition, and negatively regulated by Src-family tyrosine kinase activity, which restricts the dissociation of AMPARs from GRIP under basal conditions. We use the model to expose the dynamic balance between AMPAR internalisation and reinsertion, and the phosphorylation switch responsible for the perturbation of this balance and for the rapid plasticity initiation and regulation. Our model advances the understanding of PF-PC LTD regulation and induction, and provides a validated extensible platform for more detailed studies of this fundamental synaptic process. '),
(87617, 2016, 'plos', 'Coenzyme Q Biosynthesis: Evidence for a Substrate Access Channel in the FAD-Dependent Monooxygenase Coq6', 'Ismail, Alexandre|Leroux, Vincent|Smadja, Myriam|Gonzalez, Lucie|Lombard, Murielle|Pierrel, Fabien|Mellot-Draznieks, Caroline|Fontecave, Marc', 'Laboratoire de Chimie des Processus Biologiques, UMR 8229 CNRS, UPMC Univ Paris 06, Collège de France, Paris, France.|Paris Sciences et Lettres (PSL*), Collège de France, Center for Interdisciplinary Research in Biology (CIRB), INSERM U1050, Paris, France.|Laboratoire de Chimie des Processus Biologiques, UMR 8229 CNRS, UPMC Univ Paris 06, Collège de France, Paris, France.|Laboratoire de Chimie des Processus Biologiques, UMR 8229 CNRS, UPMC Univ Paris 06, Collège de France, Paris, France.|Laboratoire de Chimie des Processus Biologiques, UMR 8229 CNRS, UPMC Univ Paris 06, Collège de France, Paris, France.|Université Grenoble Alpes, Laboratoire Adaptation et Pathogénie des Microorganismes, Grenoble, France.|Laboratoire de Chimie des Processus Biologiques, UMR 8229 CNRS, UPMC Univ Paris 06, Collège de France, Paris, France.|Laboratoire de Chimie des Processus Biologiques, UMR 8229 CNRS, UPMC Univ Paris 06, Collège de France, Paris, France.', 'France|France|France|France|France|France|France|France', 3, 'Amino Acid Sequence|Binding Sites|Computational Biology|Computer Simulation|Escherichia coli|Flavin-Adenine Dinucleotide|Mixed Function Oxygenases|Models, Molecular|Molecular Sequence Data|Mutagenesis|Protein Conformation|Recombinant Proteins|Saccharomyces cerevisiae Proteins|Sequence Alignment|Ubiquinone', 'Journal Article', '10.1371/journal.pcbi.1004690', '26808124', 'Coq6 is an enzyme involved in the biosynthesis of coenzyme Q, a polyisoprenylated benzoquinone lipid essential to the function of the mitochondrial respiratory chain. In the yeast Saccharomyces cerevisiae, this putative flavin-dependent monooxygenase is proposed to hydroxylate the benzene ring of coenzyme Q (ubiquinone) precursor at position C5. We show here through biochemical studies that Coq6 is a flavoprotein using FAD as a cofactor. Homology models of the Coq6-FAD complex are constructed and studied through molecular dynamics and substrate docking calculations of 3-hexaprenyl-4-hydroxyphenol (4-HP6), a bulky hydrophobic model substrate. We identify a putative access channel for Coq6 in a wild type model and propose in silico mutations positioned at its entrance capable of partially (G248R and L382E single mutations) or completely (a G248R-L382E double-mutation) blocking access to the channel for the substrate. Further in vivo assays support the computational predictions, thus explaining the decreased activities or inactivation of the mutated enzymes. This work provides the first detailed structural information of an important and highly conserved enzyme of ubiquinone biosynthesis. '),
(87618, 2016, 'plos', 'Social Norms of Cooperation in Small-Scale Societies', 'Santos, Fernando P|Santos, Francisco C|Pacheco, Jorge M', 'INESC-ID and Instituto Superior Técnico, Universidade de Lisboa, IST-Tagusparque, Porto Salvo, Portugal.|INESC-ID and Instituto Superior Técnico, Universidade de Lisboa, IST-Tagusparque, Porto Salvo, Portugal.|ATP-Group, Lisboa, Portugal.', 'Portugal|Portugal|Portugal', 29, 'Computational Biology|Cooperative Behavior|Humans|Models, Psychological|Social Norms', 'Journal Article', '10.1371/journal.pcbi.1004709', '26808261', 'Indirect reciprocity, besides providing a convenient framework to address the evolution of moral systems, offers a simple and plausible explanation for the prevalence of cooperation among unrelated individuals. By helping someone, an individual may increase her/his reputation, which may change the pre-disposition of others to help her/him in the future. This, however, depends on what is reckoned as a good or a bad action, i.e., on the adopted social norm responsible for raising or damaging a reputation. In particular, it remains an open question which social norms are able to foster cooperation in small-scale societies, while enduring the wide plethora of stochastic affects inherent to finite populations. Here we address this problem by studying the stochastic dynamics of cooperation under distinct social norms, showing that the leading norms capable of promoting cooperation depend on the community size. However, only a single norm systematically leads to the highest cooperative standards in small communities. That simple norm dictates that only whoever cooperates with good individuals, and defects against bad ones, deserves a good reputation, a pattern that proves robust to errors, mutations and variations in the intensity of selection. '),
(87619, 2016, 'plos', 'Adaptive Landscape by Environment Interactions Dictate Evolutionary Dynamics in Models of Drug Resistance', 'Ogbunugafor, C Brandon|Wylie, C Scott|Diakite, Ibrahim|Weinreich, Daniel M|Hartl, Daniel L', 'Department of Organismic and Evolutionary Biology, Harvard University, Cambridge, Massachusetts, United States of America.|Department of Ecology and Evolutionary Biology, Brown University, Providence, Rhode Island, United States of America.|Department of Global Health and Social Medicine, Harvard Medical School, Boston, Massachusetts, United States of America.|Department of Ecology and Evolutionary Biology, Brown University, Providence, Rhode Island, United States of America.|Department of Organismic and Evolutionary Biology, Harvard University, Cambridge, Massachusetts, United States of America.', 'United States|United States|United States|United States|United States', 14, 'Antimalarials|Computational Biology|Drug Resistance|Evolution, Molecular|Humans|Inhibitory Concentration 50|Malaria, Falciparum|Models, Biological|Mutation|Plasmodium falciparum|Proguanil|Pyrimethamine|Triazines', 'Journal Article', '10.1371/journal.pcbi.1004710', '26808374', 'The adaptive landscape analogy has found practical use in recent years, as many have explored how their understanding can inform therapeutic strategies that subvert the evolution of drug resistance. A major barrier to applications of these concepts is a lack of detail concerning how the environment affects adaptive landscape topography, and consequently, the outcome of drug treatment. Here we combine empirical data, evolutionary theory, and computer simulations towards dissecting adaptive landscape by environment interactions for the evolution of drug resistance in two dimensions-drug concentration and drug type. We do so by studying the resistance mediated by Plasmodium falciparum dihydrofolate reductase (DHFR) to two related inhibitors-pyrimethamine and cycloguanil-across a breadth of drug concentrations. We first examine whether the adaptive landscapes for the two drugs are consistent with common definitions of cross-resistance. We then reconstruct all accessible pathways across the landscape, observing how their structure changes with drug environment. We offer a mechanism for non-linearity in the topography of accessible pathways by calculating of the interaction between mutation effects and drug environment, which reveals rampant patterns of epistasis. We then simulate evolution in several different drug environments to observe how these individual mutation effects (and patterns of epistasis) influence paths taken at evolutionary forks in the road that dictate adaptive dynamics in silico. In doing so, we reveal how classic metrics like the IC50 and minimal inhibitory concentration (MIC) are dubious proxies for understanding how evolution will occur across drug environments. We also consider how the findings reveal ambiguities in the cross-resistance concept, as subtle differences in adaptive landscape topography between otherwise equivalent drugs can drive drastically different evolutionary outcomes. Summarizing, we discuss the results with regards to their basic contribution to the study of empirical adaptive landscapes, and in terms of how they inform new models for the evolution of drug resistance. '),
(87620, 2016, 'plos', 'Fast and Rigorous Computation of Gene and Pathway Scores from SNP-Based Summary Statistics', 'Lamparter, David|Marbach, Daniel|Rueedi, Rico|Kutalik, Zoltán|Bergmann, Sven', 'Department of Medical Genetics, University of Lausanne, Lausanne, Switzerland.|Department of Medical Genetics, University of Lausanne, Lausanne, Switzerland.|Department of Medical Genetics, University of Lausanne, Lausanne, Switzerland.|Department of Medical Genetics, University of Lausanne, Lausanne, Switzerland.|Department of Medical Genetics, University of Lausanne, Lausanne, Switzerland.', 'Switzerland|Switzerland|Switzerland|Switzerland|Switzerland', 111, 'Algorithms|Computational Biology|Genome-Wide Association Study|HapMap Project|Humans|Phenotype|Polymorphism, Single Nucleotide|Software', 'Journal Article', '10.1371/journal.pcbi.1004714', '26808494', 'Integrating single nucleotide polymorphism (SNP) p-values from genome-wide association studies (GWAS) across genes and pathways is a strategy to improve statistical power and gain biological insight. Here, we present Pascal (Pathway scoring algorithm), a powerful tool for computing gene and pathway scores from SNP-phenotype association summary statistics. For gene score computation, we implemented analytic and efficient numerical solutions to calculate test statistics. We examined in particular the sum and the maximum of chi-squared statistics, which measure the strongest and the average association signals per gene, respectively. For pathway scoring, we use a modified Fisher method, which offers not only significant power improvement over more traditional enrichment strategies, but also eliminates the problem of arbitrary threshold selection inherent in any binary membership based pathway enrichment approach. We demonstrate the marked increase in power by analyzing summary statistics from dozens of large meta-studies for various traits. Our extensive testing indicates that our method not only excels in rigorous type I error control, but also results in more biologically meaningful discoveries. '),
(87621, 2016, 'plos', 'Probing the Limits to MicroRNA-Mediated Control of Gene Expression', 'Martirosyan, Araks|Figliuzzi, Matteo|Marinari, Enzo|De Martino, Andrea', 'Dipartimento di Fisica, Sapienza Università di Roma, Rome, Italy.|Sorbonne Universités, UPMC, Institut de Calcul et de la Simulation, Paris, France.|Dipartimento di Fisica, Sapienza Università di Roma, Rome, Italy.|Dipartimento di Fisica, Sapienza Università di Roma, Rome, Italy.', 'Italy|France|Italy|Italy', 8, 'Algorithms|Computational Biology|Gene Expression Regulation|MicroRNAs|Models, Genetic|Transcription Factors', 'Journal Article', '10.1371/journal.pcbi.1004715', '26812364', 'According to the ceRNA hypothesis, microRNAs (miRNAs) may act as mediators of an effective positive interaction between long coding or non-coding RNA molecules, carrying significant potential implications for a variety of biological processes. Here, inspired by recent work providing a quantitative description of small regulatory elements as information-conveying channels, we characterize the effectiveness of miRNA-mediated regulation in terms of the optimal information flow achievable between modulator (transcription factors) and target nodes (long RNAs). Our findings show that, while a sufficiently large degree of target derepression is needed to activate miRNA-mediated transmission, (a) in case of differential mechanisms of complex processing and/or transcriptional capabilities, regulation by a post-transcriptional miRNA-channel can outperform that achieved through direct transcriptional control, moreover, (b) in the presence of large populations of weakly interacting miRNA molecules the extra noise coming from titration disappears, allowing the miRNA-channel to process information as effectively as the direct channel. These observations establish the limits of miRNA-mediated post-transcriptional cross-talk and suggest that, besides providing a degree of noise buffering, this type of control may be effectively employed in cells both as a failsafe mechanism and as a preferential fine tuner of gene expression, pointing to the specific situations in which each of these functionalities is maximized. '),
(87622, 2016, 'plos', 'Correction: Comprehensive Sieve Analysis of Breakthrough HIV-1 Sequences in the RV144 Vaccine Efficacy Trial', 'PLOS Computational Biology Staff', 'Dipartimento di Fisica, Sapienza Università di Roma, Rome, Italy.', 'Italy', 1, '-', 'Published Erratum', '10.1371/journal.pcbi.1004733', '26812465', '[This corrects the article DOI: 10.1371/journal.pcbi.1003973.]. '),
(87623, 2016, 'plos', 'Binding Site Identification and Flexible Docking of Single Stranded RNA to Proteins Using a Fragment-Based Approach', 'Chauvot de Beauchene, Isaure|de Vries, Sjoerd J|Zacharias, Martin', 'Physik-Department T38, Technische Universität München, Garching, Germany.|Physik-Department T38, Technische Universität München, Garching, Germany.|Physik-Department T38, Technische Universität München, Garching, Germany.', 'Germany|Germany|Germany', 0, 'Binding Sites|Computational Biology|Molecular Docking Simulation|Protein Binding|Protein Conformation|RNA|RNA-Binding Proteins', 'Journal Article', '10.1371/journal.pcbi.1004697', '26815409', 'Protein-RNA docking is hampered by the high flexibility of RNA, and particularly single-stranded RNA (ssRNA). Yet, ssRNA regions typically carry the specificity of protein recognition. The lack of methodology for modeling such regions limits the accuracy of current protein-RNA docking methods. We developed a fragment-based approach to model protein-bound ssRNA, based on the structure of the protein and the sequence of the RNA, without any prior knowledge of the RNA binding site or the RNA structure. The conformational diversity of each fragment is sampled by an exhaustive RNA fragment library that was created from all the existing experimental structures of protein-ssRNA complexes. A systematic and detailed analysis of fragment-based ssRNA docking was performed which constitutes a proof-of-principle for the fragment-based approach. The method was tested on two 8-homo-nucleotide ssRNA-protein complexes and was able to identify the binding site on the protein within 10 Å. Moreover, a structure of each bound ssRNA could be generated in close agreement with the crystal structure with a mean deviation of ~1.5 Å except for a terminal nucleotide. This is the first time a bound ssRNA could be modeled from sequence with high precision. '),
(87624, 2016, 'plos', 'A Thermodynamic Model of Monovalent Cation Homeostasis in the Yeast Saccharomyces cerevisiae', 'Gerber, Susanne|Fröhlich, Martina|Lichtenberg-Fraté, Hella|Shabala, Sergey|Shabala, Lana|Klipp, Edda', 'Faculty of Biology, Johannes Gutenberg-Universität Mainz, Germany.|Theoretical Biophysics, Humboldt-Universität zu Berlin, Germany.|Molecular Bioenergetics, University of Bonn, Bonn, Germany.|School of Land and Food, University of Tasmania, Hobart, Australia.|School of Land and Food, University of Tasmania, Hobart, Australia.|Theoretical Biophysics, Humboldt-Universität zu Berlin, Germany.', 'Germany|Germany|Germany|Australia|Australia|Germany', 3, 'Algorithms|Cations|Computational Biology|Homeostasis|Ion Channels|Models, Biological|Saccharomyces cerevisiae|Thermodynamics', 'Journal Article', '10.1371/journal.pcbi.1004703', '26815455', 'Cationic and heavy metal toxicity is involved in a substantial number of diseases in mammals and crop plants. Therefore, the understanding of tightly regulated transporter activities, as well as conceiving the interplay of regulatory mechanisms, is of substantial interest. A generalized thermodynamic description is developed for the complex interplay of the plasma membrane ion transporters, membrane potential and the consumption of energy for maintaining and restoring specific intracellular cation concentrations. This concept is applied to the homeostasis of cation concentrations in the yeast cells of S. cerevisiae. The thermodynamic approach allows to model passive ion fluxes driven by the electrochemical potential differences, but also primary or secondary active transport processes driven by the inter- play of different ions (symport, antiport) or by ATP consumption (ATPases). The model-confronted with experimental data-reproduces the experimentally observed potassium and proton fluxes induced by the external stimuli KCl and glucose. The estimated phenomenological constants combine kinetic parameters and transport coefficients. These are in good agreement with the biological understanding of the transporters thus providing a better understanding of the control exerted by the coupled fluxes. The model predicts the flux of additional ion species, like e.g. chloride, as a potential candidate for counterbalancing positive charges. Furthermore, the effect of a second KCl stimulus is simulated, predicting a reduced cellular response for cells that were first exposed to a high KCl stimulus compared to cells pretreated with a mild KCl stimulus. By describing the generalized forces that are responsible for a given flow, the model provides information and suggestions for new experiments. Furthermore, it can be extended to other systems such as e.g. Candida albicans, or selected plant cells. '),
(87625, 2016, 'plos', 'Correction: Neurally Encoding Time for Olfactory Navigation', 'PLOS Computational Biology Staff', 'Theoretical Biophysics, Humboldt-Universität zu Berlin, Germany.', 'Germany', 0, '-', 'Published Erratum', '10.1371/journal.pcbi.1004742', '26815555', '[This corrects the article DOI: 10.1371/journal.pcbi.1004682.]. '),
(87626, 2016, 'plos', 'Ten Simple Rules for a Bioinformatics Journal Club', 'Lonsdale, Andrew|Sietsma Penington, Jocelyn|Rice, Timothy|Walker, Michael|Dashnow, Harriet', 'ARC Centre of Excellence in Plant Cell Walls, School of BioSciences, University of Melbourne, Parkville, Victoria, Australia.|Bioinformatics, Walter and Eliza Hall Institute of Medical Research, Parkville, Victoria, Australia.|School of Mathematics and Statistics, University of Melbourne, Parkville, Victoria, Australia.|School of BioSciences, University of Melbourne, Parkville, Victoria, Australia.|School of BioSciences, University of Melbourne, Parkville, Victoria, Australia.', 'Australia|Australia|Australia|Australia|Australia', 0, 'Coffee|Computational Biology|Humans|Peer Group|Periodicals as Topic|Time Factors', 'Editorial', '10.1371/journal.pcbi.1004526', '26820645', '-'),
(87627, 2016, 'plos', 'NINJA-OPS: Fast Accurate Marker Gene Alignment Using Concatenated Ribosomes', 'Al-Ghalith, Gabriel A|Montassier, Emmanuel|Ward, Henry N|Knights, Dan', 'Biomedical Informatics and Computational Biology, University of Minnesota, Minneapolis, Minnesota, United States of America.|University of Nantes, Nantes, France.|Lawrence University, Appleton, Wisconsin, United States of America.|Biomedical Informatics and Computational Biology, University of Minnesota, Minneapolis, Minnesota, United States of America.', 'United States|France|United States|United States', 0, 'Chromosome Mapping|Computational Biology|High-Throughput Nucleotide Sequencing|Humans|Metagenome|Microbiota|Ribosomes|Software', 'Journal Article', '10.1371/journal.pcbi.1004658', '26820746', 'The explosion of bioinformatics technologies in the form of next generation sequencing (NGS) has facilitated a massive influx of genomics data in the form of short reads. Short read mapping is therefore a fundamental component of next generation sequencing pipelines which routinely match these short reads against reference genomes for contig assembly. However, such techniques have seldom been applied to microbial marker gene sequencing studies, which have mostly relied on novel heuristic approaches. We propose NINJA Is Not Just Another OTU-Picking Solution (NINJA-OPS, or NINJA for short), a fast and highly accurate novel method enabling reference-based marker gene matching (picking Operational Taxonomic Units, or OTUs). NINJA takes advantage of the Burrows-Wheeler (BW) alignment using an artificial reference chromosome composed of concatenated reference sequences, the concatesome, as the BW input. Other features include automatic support for paired-end reads with arbitrary insert sizes. NINJA is also free and open source and implements several pre-filtering methods that elicit substantial speedup when coupled with existing tools. We applied NINJA to several published microbiome studies, obtaining accuracy similar to or better than previous reference-based OTU-picking methods while achieving an order of magnitude or more speedup and using a fraction of the memory footprint. NINJA is a complete pipeline that takes a FASTA-formatted input file and outputs a QIIME-formatted taxonomy-annotated BIOM file for an entire MiSeq run of human gut microbiome 16S genes in under 10 minutes on a dual-core laptop. '),
(87628, 2016, 'plos', 'Spontaneous Decoding of the Timing and Content of Human Object Perception from Cortical Surface Recordings Reveals Complementary Information in the Event-Related Potential and Broadband Spectral Change', 'Miller, Kai J|Schalk, Gerwin|Hermes, Dora|Ojemann, Jeffrey G|Rao, Rajesh P N', 'Departments of Neurosurgery, Stanford University, Stanford, California, United States of America.|National Center for Adaptive Neurotechnologies, Wadsworth Center, New York State Department of Health, Albany, New York, United States of America.|Psychology, Stanford University, Stanford, California, United States of America.|Program in Neurobiology and Behavior, University of Washington, Seattle, Washington, United States of America.|Program in Neurobiology and Behavior, University of Washington, Seattle, Washington, United States of America.', 'United States|United States|United States|United States|United States', 31, 'Brain Mapping|Computational Biology|Electroencephalography|Epilepsy|Evoked Potentials|Humans|Signal Processing, Computer-Assisted|Temporal Lobe|Visual Perception', 'Journal Article', '10.1371/journal.pcbi.1004660', '26820899', 'The link between object perception and neural activity in visual cortical areas is a problem of fundamental importance in neuroscience. Here we show that electrical potentials from the ventral temporal cortical surface in humans contain sufficient information for spontaneous and near-instantaneous identification of a subjects perceptual state. Electrocorticographic (ECoG) arrays were placed on the subtemporal cortical surface of seven epilepsy patients. Grayscale images of faces and houses were displayed rapidly in random sequence. We developed a template projection approach to decode the continuous ECoG data stream spontaneously, predicting the occurrence, timing and type of visual stimulus. In this setting, we evaluated the independent and joint use of two well-studied features of brain signals, broadband changes in the frequency power spectrum of the potential and deflections in the raw potential trace (event-related potential, ERP). Our ability to predict both the timing of stimulus onset and the type of image was best when we used a combination of both the broadband response and ERP, suggesting that they capture different and complementary aspects of the subjects perceptual state. Specifically, we were able to predict the timing and type of 96% of all stimuli, with less than 5% false positive rate and a ~20ms error in timing. '),
(87629, 2016, 'plos', 'Does High-Dose Antimicrobial Chemotherapy Prevent the Evolution of Resistance?', 'Day, Troy|Read, Andrew F', 'Department of Mathematics and Statistics, Jeffery Hall, Queens University, Kingston, Ontario, Canada.|The Fogarty International Center, National Institutes of Health, Bethesda, Maryland, United States of America.', 'Canada|United States', 61, 'Animals|Anti-Infective Agents|Biological Evolution|Communicable Diseases|Computational Biology|Drug Resistance|Drug Therapy|Humans|Mice|Models, Biological', 'Journal Article', '10.1371/journal.pcbi.1004689', '26820986', 'High-dose chemotherapy has long been advocated as a means of controlling drug resistance in infectious diseases but recent empirical studies have begun to challenge this view. We develop a very general framework for modeling and understanding resistance emergence based on principles from evolutionary biology. We use this framework to show how high-dose chemotherapy engenders opposing evolutionary processes involving the mutational input of resistant strains and their release from ecological competition. Whether such therapy provides the best approach for controlling resistance therefore depends on the relative strengths of these processes. These opposing processes typically lead to a unimodal relationship between drug pressure and resistance emergence. As a result, the optimal drug dose lies at either end of the therapeutic window of clinically acceptable concentrations. We illustrate our findings with a simple model that shows how a seemingly minor change in parameter values can alter the outcome from one where high-dose chemotherapy is optimal to one where using the smallest clinically effective dose is best. A review of the available empirical evidence provides broad support for these general conclusions. Our analysis opens up treatment options not currently considered as resistance management strategies, and it also simplifies the experiments required to determine the drug doses which best retard resistance emergence in patients. ');
INSERT INTO `papers` (`id`, `ano`, `journal`, `titulo`, `autores`, `afiliacao`, `pais`, `citacoes`, `palavra_chave`, `categorias`, `doi`, `pubmed`, `abstract`) VALUES
(87630, 2016, 'plos', 'Systems-Wide Prediction of Enzyme Promiscuity Reveals a New Underground Alternative Route for Pyridoxal 5-Phosphate Production in E coli', 'Oberhardt, Matthew A|Zarecki, Raphy|Reshef, Leah|Xia, Fangfang|Duran-Frigola, Miquel|Schreiber, Rachel|Henry, Christopher S|Ben-Tal, Nir|Dwyer, Daniel J|Gophna, Uri|Ruppin, Eytan', 'School of Computer Sciences and Sackler School of Medicine, Tel Aviv University, Tel Aviv, Israel.|School of Computer Sciences and Sackler School of Medicine, Tel Aviv University, Tel Aviv, Israel.|Department of Molecular Microbiology and Biotechnology, Faculty of Life Sciences, Tel Aviv University, Tel Aviv, Israel.|Mathematics and Computer Science Division, Argonne National Laboratory, Argonne, Illinois, United States of America.|Joint IRB-BSC-CRG Program in Computational Biology, Institute for Research in Biomedicine (IRB Barcelona), Barcelona, Spain.|Department of Molecular Microbiology and Biotechnology, Faculty of Life Sciences, Tel Aviv University, Tel Aviv, Israel.|Mathematics and Computer Science Division, Argonne National Laboratory, Argonne, Illinois, United States of America.|Department of Biochemistry and Molecular Biology, George S. Wise Faculty of Life Sciences, Tel Aviv University, Tel Aviv, Israel.|Department of Cell Biology and Molecular Genetics, Institute for Physical Science and Technology, Department of Bioengineering, Maryland Pathogen Research Institute, University of Maryland, College Park, Maryland, United States of America.|Department of Molecular Microbiology and Biotechnology, Faculty of Life Sciences, Tel Aviv University, Tel Aviv, Israel.|School of Computer Sciences and Sackler School of Medicine, Tel Aviv University, Tel Aviv, Israel.', 'Israel|Israel|Israel|United States|Spain|Israel|United States|Israel|United States|Israel|Israel', 12, 'Carbohydrate Dehydrogenases|Computational Biology|Escherichia coli|Escherichia coli Proteins|Models, Molecular|Pyridoxal Phosphate', 'Journal Article', '10.1371/journal.pcbi.1004705', '26821166', 'Recent insights suggest that non-specific and/or promiscuous enzymes are common and active across life. Understanding the role of such enzymes is an important open question in biology. Here we develop a genome-wide method, PROPER, that uses a permissive PSI-BLAST approach to predict promiscuous activities of metabolic genes. Enzyme promiscuity is typically studied experimentally using multicopy suppression, in which over-expression of a promiscuous replacer gene rescues lethality caused by inactivation of a target gene. We use PROPER to predict multicopy suppression in Escherichia coli, achieving highly significant overlap with published cases (hypergeometric p = 4.4e-13). We then validate three novel predicted target-replacer gene pairs in new multicopy suppression experiments. We next go beyond PROPER and develop a network-based approach, GEM-PROPER, that integrates PROPER with genome-scale metabolic modeling to predict promiscuous replacements via alternative metabolic pathways. GEM-PROPER predicts a new indirect replacer (thiG) for an essential enzyme (pdxB) in production of pyridoxal 5-phosphate (the active form of Vitamin B6), which we validate experimentally via multicopy suppression. We perform a structural analysis of thiG to determine its potential promiscuous active site, which we validate experimentally by inactivating the pertaining residues and showing a loss of replacer activity. Thus, this study is a successful example where a computational investigation leads to a network-based identification of an indirect promiscuous replacement of a key metabolic enzyme, which would have been extremely difficult to identify directly. '),
(87631, 2016, 'plos', 'Fluctuating Nonlinear Spring Model of Mechanical Deformation of Biological Particles', 'Kononova, Olga|Snijder, Joost|Kholodov, Yaroslav|Marx, Kenneth A|Wuite, Gijs J L|Roos, Wouter H|Barsegov, Valeri', 'Department of Chemistry, University of Massachusetts, Lowell, Massachusetts, United States of America.|Natuur- en Sterrenkunde and LaserLab, Vrije Universiteit, Amsterdam, The Netherlands.|Moscow Institute of Physics and Technology, Moscow Region, Russia.|Department of Chemistry, University of Massachusetts, Lowell, Massachusetts, United States of America.|Natuur- en Sterrenkunde and LaserLab, Vrije Universiteit, Amsterdam, The Netherlands.|Moleculaire Biofysica, Zernike instituut, Rijksuniversiteit Groningen, Groningen, The Netherlands.|Department of Chemistry, University of Massachusetts, Lowell, Massachusetts, United States of America.', 'United States|Netherlands|-|United States|Netherlands|Netherlands|United States', 0, 'Biomechanical Phenomena|Capsid Proteins|Computational Biology|Molecular Dynamics Simulation|Nonlinear Dynamics|Protein Conformation|Virion', 'Journal Article', '10.1371/journal.pcbi.1004729', '26821264', 'The mechanical properties of virus capsids correlate with local conformational dynamics in the capsid structure. They also reflect the required stability needed to withstand high internal pressures generated upon genome loading and contribute to the success of important events in viral infectivity, such as capsid maturation, genome uncoating and receptor binding. The mechanical properties of biological nanoparticles are often determined from monitoring their dynamic deformations in Atomic Force Microscopy nanoindentation experiments, but a comprehensive theory describing the full range of observed deformation behaviors has not previously been described. We present a new theory for modeling dynamic deformations of biological nanoparticles, which considers the non-linear Hertzian deformation, resulting from an indenter-particle physical contact, and the bending of curved elements (beams) modeling the particle structure. The beams deformation beyond the critical point triggers a dynamic transition of the particle to the collapsed state. This extreme event is accompanied by a catastrophic force drop as observed in the experimental or simulated force (F)-deformation (X) spectra. The theory interprets fine features of the spectra, including the nonlinear components of the FX-curves, in terms of the Youngs moduli for Hertzian and bending deformations, and the structural damage dependent beams survival probability, in terms of the maximum strength and the cooperativity parameter. The theory is exemplified by successfully describing the deformation dynamics of natural nanoparticles through comparing theoretical curves with experimental force-deformation spectra for several virus particles. This approach provides a comprehensive description of the dynamic structural transitions in biological and artificial nanoparticles, which is essential for their optimal use in nanotechnology and nanomedicine applications. '),
(87632, 2016, 'plos', 'Modelling Feedback Excitation, Pacemaker Properties and Sensory Switching of Electrically Coupled Brainstem Neurons Controlling Rhythmic Activity', 'Hull, Michael J|Soffe, Stephen R|Willshaw, David J|Roberts, Alan', 'Institute for Adaptive and Neural Computation, University of Edinburgh, Edinburgh, United Kingdom.|School of Biological Sciences, University of Bristol, Bristol, United Kingdom.|Institute for Adaptive and Neural Computation, University of Edinburgh, Edinburgh, United Kingdom.|School of Biological Sciences, University of Bristol, Bristol, United Kingdom.', 'United Kingdom|United Kingdom|United Kingdom|United Kingdom', 5, 'Animals|Brain Stem|Computational Biology|Feedback, Physiological|Models, Biological|N-Methylaspartate|Neurons|Xenopus', 'Journal Article', '10.1371/journal.pcbi.1004702', '26824331', 'What cellular and network properties allow reliable neuronal rhythm generation or firing that can be started and stopped by brief synaptic inputs? We investigate rhythmic activity in an electrically-coupled population of brainstem neurons driving swimming locomotion in young frog tadpoles, and how activity is switched on and off by brief sensory stimulation. We build a computational model of 30 electrically-coupled conditional pacemaker neurons on one side of the tadpole hindbrain and spinal cord. Based on experimental estimates for neuron properties, population sizes, synapse strengths and connections, we show that: long-lasting, mutual, glutamatergic excitation between the neurons allows the network to sustain rhythmic pacemaker firing at swimming frequencies following brief synaptic excitation, activity persists but rhythm breaks down without electrical coupling, NMDA voltage-dependency doubles the range of synaptic feedback strengths generating sustained rhythm. The network can be switched on and off at short latency by brief synaptic excitation and inhibition. We demonstrate that a population of generic Hodgkin-Huxley type neurons coupled by glutamatergic excitatory feedback can generate sustained asynchronous firing switched on and off synaptically. We conclude that networks of neurons with NMDAR mediated feedback excitation can generate self-sustained activity following brief synaptic excitation. The frequency of activity is limited by the kinetics of the neuron membrane channels and can be stopped by brief inhibitory input. Network activity can be rhythmic at lower frequencies if the neurons are electrically coupled. Our key finding is that excitatory synaptic feedback within a population of neurons can produce switchable, stable, sustained firing without synaptic inhibition. '),
(87633, 2016, 'plos', 'A Biophysical Model of CRISPR/Cas9 Activity for Rational Design of Genome Editing and Gene Regulation', 'Farasat, Iman|Salis, Howard M', 'Department of Chemical Engineering, Pennsylvania State University, University Park, Pennsylvania, United States of America.|Department of Chemical Engineering, Pennsylvania State University, University Park, Pennsylvania, United States of America.', 'United States|United States', 45, 'Bacteriophage lambda|CRISPR-Associated Proteins|Computer Simulation|DNA|Gene Expression Regulation|Genome|Models, Genetic|Protein Binding|RNA, Guide', 'Journal Article', '10.1371/journal.pcbi.1004724', '26824432', 'The ability to precisely modify genomes and regulate specific genes will greatly accelerate several medical and engineering applications. The CRISPR/Cas9 (Type II) system binds and cuts DNA using guide RNAs, though the variables that control its on-target and off-target activity remain poorly characterized. Here, we develop and parameterize a system-wide biophysical model of Cas9-based genome editing and gene regulation to predict how changing guide RNA sequences, DNA superhelical densities, Cas9 and crRNA expression levels, organisms and growth conditions, and experimental conditions collectively control the dynamics of dCas9-based binding and Cas9-based cleavage at all DNA sites with both canonical and non-canonical PAMs. We combine statistical thermodynamics and kinetics to model Cas9:crRNA complex formation, diffusion, site selection, reversible R-loop formation, and cleavage, using large amounts of structural, biochemical, expression, and next-generation sequencing data to determine kinetic parameters and develop free energy models. Our results identify DNA supercoiling as a novel mechanism controlling Cas9 binding. Using the model, we predict Cas9 off-target binding frequencies across the lambdaphage and human genomes, and explain why Cas9s off-target activity can be so high. With this improved understanding, we propose several rules for designing experiments for minimizing off-target activity. We also discuss the implications for engineering dCas9-based genetic circuits. '),
(87634, 2016, 'plos', 'The Emotional Gatekeeper: A Computational Model of Attentional Selection and Suppression through the Pathway from the Amygdala to the Inhibitory Thalamic Reticular Nucleus', 'John, Yohan J|Zikopoulos, Basilis|Bullock, Daniel|Barbas, Helen', 'Neural Systems Laboratory, Department of Health Sciences, Boston University, Boston, Massachusetts, United States of America.|Human Systems Neuroscience Laboratory, Department of Health Sciences, Boston University, Boston, Massachusetts, United States of America.|Graduate Program for Neuroscience, Boston University and School of Medicine, Boston, Massachusetts, United States of America.|Neural Systems Laboratory, Department of Health Sciences, Boston University, Boston, Massachusetts, United States of America.', 'United States|United States|United States|United States', 0, 'Amygdala|Animals|Computational Biology|Computer Simulation|Emotions|Humans|Models, Neurological|Neural Pathways|Thalamic Nuclei', 'Journal Article', '10.1371/journal.pcbi.1004722', '26828203', 'In a complex environment that contains both opportunities and threats, it is important for an organism to flexibly direct attention based on current events and prior plans. The amygdala, the hub of the brains emotional system, is involved in forming and signaling affective associations between stimuli and their consequences. The inhibitory thalamic reticular nucleus (TRN) is a hub of the attentional system that gates thalamo-cortical signaling. In the primate brain, a recently discovered pathway from the amygdala sends robust projections to TRN. Here we used computational modeling to demonstrate how the amygdala-TRN pathway, embedded in a wider neural circuit, can mediate selective attention guided by emotions. Our Emotional Gatekeeper model demonstrates how this circuit enables focused top-down, and flexible bottom-up, allocation of attention. The model suggests that the amygdala-TRN projection can serve as a unique mechanism for emotion-guided selection of signals sent to cortex for further processing. This inhibitory selection mechanism can mediate a powerful affective framing effect that may lead to biased decision-making in highly charged emotional situations. The model also supports the idea that the amygdala can serve as a relevance detection system. Further, the model demonstrates how abnormal top-down drive and dysregulated local inhibition in the amygdala and in the cortex can contribute to the attentional symptoms that accompany several neuropsychiatric disorders. '),
(87635, 2016, 'plos', 'Food Web Assembly Rules for Generalized Lotka-Volterra Equations', 'Haerter, Jan O|Mitarai, Namiko|Sneppen, Kim', 'Center for Models of Life, Niels Bohr Institute, University of Copenhagen, Copenhagen, Denmark.|Center for Models of Life, Niels Bohr Institute, University of Copenhagen, Copenhagen, Denmark.|Center for Models of Life, Niels Bohr Institute, University of Copenhagen, Copenhagen, Denmark.', 'Denmark|Denmark|Denmark', 0, 'Animals|Computational Biology|Computer Simulation|Ecosystem|Food Chain|Models, Biological', 'Journal Article', '10.1371/journal.pcbi.1004727', '26828363', 'In food webs, many interacting species coexist despite the restrictions imposed by the competitive exclusion principle and apparent competition. For the generalized Lotka-Volterra equations, sustainable coexistence necessitates nonzero determinant of the interaction matrix. Here we show that this requirement is equivalent to demanding that each species be part of a non-overlapping pairing, which substantially constrains the food web structure. We demonstrate that a stable food web can always be obtained if a non-overlapping pairing exists. If it does not, the matrix rank can be used to quantify the lack of niches, corresponding to unpaired species. For the species richness at each trophic level, we derive the food web assembly rules, which specify sustainable combinations. In neighboring levels, these rules allow the higher level to avert competitive exclusion at the lower, thereby incorporating apparent competition. In agreement with data, the assembly rules predict high species numbers at intermediate levels and thinning at the top and bottom. Using comprehensive food web data, we demonstrate how omnivores or parasites with hosts at multiple trophic levels can loosen the constraints and help obtain coexistence in food webs. Hence, omnivory may be the glue that keeps communities intact even under extinction or ecological release of species. '),
(87636, 2016, 'plos', 'Quantifying Clonal and Subclonal Passenger Mutations in Cancer Evolution', 'Bozic, Ivana|Gerold, Jeffrey M|Nowak, Martin A', 'Program for Evolutionary Dynamics, Harvard University, Cambridge, Massachusetts, United States of America.|Program for Evolutionary Dynamics, Harvard University, Cambridge, Massachusetts, United States of America.|Program for Evolutionary Dynamics, Harvard University, Cambridge, Massachusetts, United States of America.', 'United States|United States|United States', 57, 'Computational Biology|Evolution, Molecular|Humans|Models, Genetic|Models, Statistical|Mutation|Neoplasms', 'Journal Article', '10.1371/journal.pcbi.1004731', '26828429', 'The vast majority of mutations in the exome of cancer cells are passengers, which do not affect the reproductive rate of the cell. Passengers can provide important information about the evolutionary history of an individual cancer, and serve as a molecular clock. Passengers can also become targets for immunotherapy or confer resistance to treatment. We study the stochastic expansion of a population of cancer cells describing the growth of primary tumors or metastatic lesions. We first analyze the process by looking forward in time and calculate the fixation probabilities and frequencies of successive passenger mutations ordered by their time of appearance. We compute the likelihood of specific evolutionary trees, thereby informing the phylogenetic reconstruction of cancer evolution in individual patients. Next, we derive results looking backward in time: for a given subclonal mutation we estimate the number of cancer cells that were present at the time when that mutation arose. We derive exact formulas for the expected numbers of subclonal mutations of any frequency. Fitting this formula to cancer sequencing data leads to an estimate for the ratio of birth and death rates of cancer cells during the early stages of clonal expansion. '),
(87637, 2016, 'plos', 'PSAMM: A Portable System for the Analysis of Metabolic Models', 'Steffensen, Jon Lund|Dufault-Thompson, Keith|Zhang, Ying', 'Department of Cell and Molecular Biology, College of the Environment and Life Sciences, University of Rhode Island, Kingston, Rhode Island, United States of America.|Department of Cell and Molecular Biology, College of the Environment and Life Sciences, University of Rhode Island, Kingston, Rhode Island, United States of America.|Department of Cell and Molecular Biology, College of the Environment and Life Sciences, University of Rhode Island, Kingston, Rhode Island, United States of America.', 'United States|United States|United States', 15, 'Computational Biology|Genome, Bacterial|Internet|Metabolic Engineering|Metabolic Networks and Pathways|Models, Biological|Reproducibility of Results|Software', 'Journal Article', '10.1371/journal.pcbi.1004732', '26828591', 'The genome-scale models of metabolic networks have been broadly applied in phenotype prediction, evolutionary reconstruction, community functional analysis, and metabolic engineering. Despite the development of tools that support individual steps along the modeling procedure, it is still difficult to associate mathematical simulation results with the annotation and biological interpretation of metabolic models. In order to solve this problem, here we developed a Portable System for the Analysis of Metabolic Models (PSAMM), a new open-source software package that supports the integration of heterogeneous metadata in model annotations and provides a user-friendly interface for the analysis of metabolic models. PSAMM is independent of paid software environments like MATLAB, and all its dependencies are freely available for academic users. Compared to existing tools, PSAMM significantly reduced the running time of constraint-based analysis and enabled flexible settings of simulation parameters using simple one-line commands. The integration of heterogeneous, model-specific annotation information in PSAMM is achieved with a novel format of YAML-based model representation, which has several advantages, such as providing a modular organization of model components and simulation settings, enabling model version tracking, and permitting the integration of multiple simulation problems. PSAMM also includes a number of quality checking procedures to examine stoichiometric balance and to identify blocked reactions. Applying PSAMM to 57 models collected from current literature, we demonstrated how the software can be used for managing and simulating metabolic models. We identified a number of common inconsistencies in existing models and constructed an updated model repository to document the resolution of these inconsistencies. '),
(87638, 2016, 'plos', 'Kernel Architecture of the Genetic Circuitry of the Arabidopsis Circadian System', 'Foo, Mathias|Somers, David E|Kim, Pan-Jun', 'Asia Pacific Center for Theoretical Physics, Pohang, Gyeongbuk, Republic of Korea.|Department of Molecular Genetics, The Ohio State University, Columbus, Ohio, United States of America.|Asia Pacific Center for Theoretical Physics, Pohang, Gyeongbuk, Republic of Korea.', '-|United States|-', 11, 'Algorithms|Arabidopsis|Circadian Clocks|Computational Biology|Gene Regulatory Networks|Genes, Plant|Models, Genetic', 'Journal Article', '10.1371/journal.pcbi.1004748', '26828650', 'A wide range of organisms features molecular machines, circadian clocks, which generate endogenous oscillations with ~24 h periodicity and thereby synchronize biological processes to diurnal environmental fluctuations. Recently, it has become clear that plants harbor more complex gene regulatory circuits within the core circadian clocks than other organisms, inspiring a fundamental question: are all these regulatory interactions between clock genes equally crucial for the establishment and maintenance of circadian rhythms? Our mechanistic simulation for Arabidopsis thaliana demonstrates that at least half of the total regulatory interactions must be present to express the circadian molecular profiles observed in wild-type plants. A set of those essential interactions is called herein a kernel of the circadian system. The kernel structure unbiasedly reveals four interlocked negative feedback loops contributing to circadian rhythms, and three feedback loops among them drive the autonomous oscillation itself. Strikingly, the kernel structure, as well as the whole clock circuitry, is overwhelmingly composed of inhibitory, rather than activating, interactions between genes. We found that this tendency underlies plant circadian molecular profiles which often exhibit sharply-shaped, cuspidate waveforms. Through the generation of these cuspidate profiles, inhibitory interactions may facilitate the global coordination of temporally-distant clock events that are markedly peaked at very specific times of day. Our systematic approach resulting in experimentally-testable predictions provides insights into a design principle of biological clockwork, with implications for synthetic biology. '),
(87639, 2016, 'plos', 'ClassTR: Classifying Within-Host Heterogeneity Based on Tandem Repeats with Application to Mycobacterium tuberculosis Infections', 'Chindelevitch, Leonid|Colijn, Caroline|Moodley, Prashini|Wilson, Douglas|Cohen, Ted', 'Department of Epidemiology of Microbial Diseases, Yale School of Public Health, New Haven, Connecticut, United States of America.|Department of Mathematics, Imperial College, London, United Kingdom.|School of Laboratory Medicine and Medical Sciences, Nelson R Mandela School of Medicine, University of KwaZulu-Natal, Durban, South Africa.|Department of Medicine, Edendale Hospital, Pietermaritzberg, South Africa.|Department of Epidemiology of Microbial Diseases, Yale School of Public Health, New Haven, Connecticut, United States of America.', 'United States|United Kingdom|South Africa|South Africa|United States', 8, 'Algorithms|Computational Biology|Databases, Genetic|Humans|Minisatellite Repeats|Mycobacterium tuberculosis|Reproducibility of Results|Tuberculosis', 'Journal Article', '10.1371/journal.pcbi.1004475', '26829497', 'Genomic tools have revealed genetically diverse pathogens within some hosts. Within-host pathogen diversity, which we refer to as complex infection, is increasingly recognized as a determinant of treatment outcome for infections like tuberculosis. Complex infection arises through two mechanisms: within-host mutation (which results in clonal heterogeneity) and reinfection (which results in mixed infections). Estimates of the frequency of within-host mutation and reinfection in populations are critical for understanding the natural history of disease. These estimates influence projections of disease trends and effects of interventions. The genotyping technique MLVA (multiple loci variable-number tandem repeats analysis) can identify complex infections, but the current method to distinguish clonal heterogeneity from mixed infections is based on a rather simple rule. Here we describe ClassTR, a method which leverages MLVA information from isolates collected in a population to distinguish mixed infections from clonal heterogeneity. We formulate the resolution of complex infections into their constituent strains as an optimization problem, and show its NP-completeness. We solve it efficiently by using mixed integer linear programming and graph decomposition. Once the complex infections are resolved into their constituent strains, ClassTR probabilistically classifies isolates as clonally heterogeneous or mixed by using a model of tandem repeat evolution. We first compare ClassTR with the standard rule-based classification on 100 simulated datasets. ClassTR outperforms the standard method, improving classification accuracy from 48% to 80%. We then apply ClassTR to a sample of 436 strains collected from tuberculosis patients in a South African community, of which 92 had complex infections. We find that ClassTR assigns an alternate classification to 18 of the 92 complex infections, suggesting important differences in practice. By explicitly modeling tandem repeat evolution, ClassTR helps to improve our understanding of the mechanisms driving within-host diversity of pathogens like Mycobacterium tuberculosis. '),
(87640, 2016, 'plos', 'Implementation of Complex Biological Logic Circuits Using Spatially Distributed Multicellular Consortia', 'Macia, Javier|Manzoni, Romilde|Conde, Núria|Urrios, Arturo|de Nadal, Eulàlia|Solé, Ricard|Posas, Francesc', 'ICREA-Complex Systems Laboratory, Universitat Pompeu Fabra (UPF), Barcelona, Spain.|Cell Signaling Research Group, Departament de Ciències Experimentals i de la Salut, Universitat Pompeu Fabra (UPF), Barcelona, Spain.|ICREA-Complex Systems Laboratory, Universitat Pompeu Fabra (UPF), Barcelona, Spain.|Cell Signaling Research Group, Departament de Ciències Experimentals i de la Salut, Universitat Pompeu Fabra (UPF), Barcelona, Spain.|Cell Signaling Research Group, Departament de Ciències Experimentals i de la Salut, Universitat Pompeu Fabra (UPF), Barcelona, Spain.|ICREA-Complex Systems Laboratory, Universitat Pompeu Fabra (UPF), Barcelona, Spain.|Cell Signaling Research Group, Departament de Ciències Experimentals i de la Salut, Universitat Pompeu Fabra (UPF), Barcelona, Spain.', 'Spain|Spain|Spain|Spain|Spain|Spain|Spain', 20, 'Flow Cytometry|Genetic Engineering|Logic|Models, Biological|Synthetic Biology|Yeasts', 'Journal Article', '10.1371/journal.pcbi.1004685', '26829588', 'Engineered synthetic biological devices have been designed to perform a variety of functions from sensing molecules and bioremediation to energy production and biomedicine. Notwithstanding, a major limitation of in vivo circuit implementation is the constraint associated to the use of standard methodologies for circuit design. Thus, future success of these devices depends on obtaining circuits with scalable complexity and reusable parts. Here we show how to build complex computational devices using multicellular consortia and space as key computational elements. This spatial modular design grants scalability since its general architecture is independent of the circuits complexity, minimizes wiring requirements and allows component reusability with minimal genetic engineering. The potential use of this approach is demonstrated by implementation of complex logical functions with up to six inputs, thus demonstrating the scalability and flexibility of this method. The potential implications of our results are outlined. '),
(87641, 2016, 'plos', 'Recovery of Dynamics and Function in Spiking Neural Networks with Closed-Loop Control', 'Vlachos, Ioannis|Deniz, Taxc5x9fkin|Aertsen, Ad|Kumar, Arvind', 'Bernstein Center Freiburg and Faculty of Biology, University of Freiburg, Freiburg, Germany.|Bernstein Center Freiburg and Faculty of Biology, University of Freiburg, Freiburg, Germany.|Bernstein Center Freiburg and Faculty of Biology, University of Freiburg, Freiburg, Germany.|Bernstein Center Freiburg and Faculty of Biology, University of Freiburg, Freiburg, Germany.', 'Germany|Germany|Germany|Germany', 7, 'Action Potentials|Computational Biology|Computer Simulation|Deep Brain Stimulation|Feedback, Physiological|Humans|Models, Neurological|Nerve Net', 'Journal Article', '10.1371/journal.pcbi.1004720', '26829673', 'There is a growing interest in developing novel brain stimulation methods to control disease-related aberrant neural activity and to address basic neuroscience questions. Conventional methods for manipulating brain activity rely on open-loop approaches that usually lead to excessive stimulation and, crucially, do not restore the original computations performed by the network. Thus, they are often accompanied by undesired side-effects. Here, we introduce delayed feedback control (DFC), a conceptually simple but effective method, to control pathological oscillations in spiking neural networks (SNNs). Using mathematical analysis and numerical simulations we show that DFC can restore a wide range of aberrant network dynamics either by suppressing or enhancing synchronous irregular activity. Importantly, DFC, besides steering the system back to a healthy state, also recovers the computations performed by the underlying network. Finally, using our theory we identify the role of single neuron and synapse properties in determining the stability of the closed-loop system. '),
(87642, 2016, 'plos', 'Investigating the Consequences of Interference between Multiple CD8+ T Cell Escape Mutations in Early HIV Infection', 'Garcia, Victor|Feldman, Marcus W|Regoes, Roland R', 'Institute of Integrative Biology, ETH Zurich, Zurich, Switzerland.|Department of Biological Sciences, Stanford University, Stanford, California, United States of America.|Institute of Integrative Biology, ETH Zurich, Zurich, Switzerland.', 'Switzerland|United States|Switzerland', 8, 'CD8-Positive T-Lymphocytes|Computational Biology|Epitopes, T-Lymphocyte|Evolution, Molecular|HIV Infections|HIV-1|Humans|Immune Evasion', 'Journal Article', '10.1371/journal.pcbi.1004721', '26829720', 'During early human immunodeficiency virus (HIV) infection multiple CD8+ T cell responses are elicited almost simultaneously. These responses exert strong selective pressures on different parts of HIVs genome, and select for mutations that escape recognition and are thus beneficial to the virus. Some studies reveal that the later these escape mutations emerge, the more slowly they go to fixation. This pattern of escape rate decrease(ERD) can arise by distinct mechanisms. In particular, in large populations with high beneficial mutation rates interference among different escape strains--an effect that can emerge in evolution with asexual reproduction and results in delayed fixation times of beneficial mutations compared to sexual reproduction--could significantly impact the escape rates of mutations. In this paper, we investigated how interference between these concurrent escape mutations affects their escape rates in systems with multiple epitopes, and whether it could be a source of the ERD pattern. To address these issues, we developed a multilocus Wright-Fisher model of HIV dynamics with selection, mutation and recombination, serving as a null-model for interference. We also derived an interference-free null model assuming initial neutral evolution before immune response elicitation. We found that interference between several equally selectively advantageous mutations can generate the observed ERD pattern. We also found that the number of loci, as well as recombination rates substantially affect ERD. These effects can be explained by the underexponential decline of escape rates over time. Lastly, we found that the observed ERD pattern in HIV infected individuals is consistent with both independent, interference-free mutations as well as interference effects. Our results confirm that interference effects should be considered when analyzing HIV escape mutations. The challenge in estimating escape rates and mutation-associated selective coefficients posed by interference effects cannot simply be overcome by improved sampling frequencies or sizes. This problem is a consequence of the fundamental shortcomings of current estimation techniques under interference regimes. Hence, accounting for the stochastic nature of competition between mutations demands novel estimation methodologies based on the analysis of HIV strains, rather than mutation frequencies.'),
(87643, 2016, 'plos', 'Molecular Mechanisms of Glutamine Synthetase Mutations that Lead to Clinically Relevant Pathologies', 'Frieg, Benedikt|Görg, Boris|Homeyer, Nadine|Keitel, Verena|Häussinger, Dieter|Gohlke, Holger', 'Institute for Pharmaceutical and Medicinal Chemistry, Heinrich-Heine-University, Düsseldorf, Germany.|Clinic for Gastroenterology, Hepatology, and Infectious Diseases, Heinrich-Heine-University, Düsseldorf, Germany.|Institute for Pharmaceutical and Medicinal Chemistry, Heinrich-Heine-University, Düsseldorf, Germany.|Clinic for Gastroenterology, Hepatology, and Infectious Diseases, Heinrich-Heine-University, Düsseldorf, Germany.|Clinic for Gastroenterology, Hepatology, and Infectious Diseases, Heinrich-Heine-University, Düsseldorf, Germany.|Institute for Pharmaceutical and Medicinal Chemistry, Heinrich-Heine-University, Düsseldorf, Germany.', 'Germany|Germany|Germany|Germany|Germany|Germany', 14, 'Adenosine Triphosphate|Amino Acid Metabolism, Inborn Errors|Glutamate-Ammonia Ligase|HEK293 Cells|Humans|Molecular Dynamics Simulation|Mutation|Protein Binding', 'Journal Article', '10.1371/journal.pcbi.1004693', '26836257', 'Glutamine synthetase (GS) catalyzes ATP-dependent ligation of ammonia and glutamate to glutamine. Two mutations of human GS (R324C and R341C) were connected to congenital glutamine deficiency with severe brain malformations resulting in neonatal death. Another GS mutation (R324S) was identified in a neurologically compromised patient. However, the molecular mechanisms underlying the impairment of GS activity by these mutations have remained elusive. Molecular dynamics simulations, free energy calculations, and rigidity analyses suggest that all three mutations influence the first step of GS catalytic cycle. The R324S and R324C mutations deteriorate GS catalytic activity due to loss of direct interactions with ATP. As to R324S, indirect, water-mediated interactions reduce this effect, which may explain the suggested higher GS residual activity. The R341C mutation weakens ATP binding by destabilizing the interacting residue R340 in the apo state of GS. Additionally, the mutation is predicted to result in a significant destabilization of helix H8, which should negatively affect glutamate binding. This prediction was tested in HEK293 cells overexpressing GS by dot-blot analysis: Structural stability of H8 was impaired through mutation of amino acids interacting with R341, as indicated by a loss of masking of an epitope in the glutamate binding pocket for a monoclonal anti-GS antibody by L-methionine-S-sulfoximine, in contrast, cells transfected with wild type GS showed the masking. Our analyses reveal complex molecular effects underlying impaired GS catalytic activity in three clinically relevant mutants. Our findings could stimulate the development of ATP binding-enhancing molecules by which the R324S mutant can be repaired extrinsically. '),
(87644, 2016, 'plos', 'Somato-dendritic Synaptic Plasticity and Error-backpropagation in Active Dendrites', 'Schiess, Mathieu|Urbanczik, Robert|Senn, Walter', 'Department of Physiology, University of Bern, Bern, Switzerland.|Department of Physiology, University of Bern, Bern, Switzerland.|Department of Physiology, University of Bern, Bern, Switzerland.', 'Switzerland|Switzerland|Switzerland', 27, 'Action Potentials|Algorithms|Computational Biology|Dendrites|Models, Neurological|Neuronal Plasticity', 'Journal Article', '10.1371/journal.pcbi.1004638', '26841235', 'In the last decade dendrites of cortical neurons have been shown to nonlinearly combine synaptic inputs by evoking local dendritic spikes. It has been suggested that these nonlinearities raise the computational power of a single neuron, making it comparable to a 2-layer network of point neurons. But how these nonlinearities can be incorporated into the synaptic plasticity to optimally support learning remains unclear. We present a theoretically derived synaptic plasticity rule for supervised and reinforcement learning that depends on the timing of the presynaptic, the dendritic and the postsynaptic spikes. For supervised learning, the rule can be seen as a biological version of the classical error-backpropagation algorithm applied to the dendritic case. When modulated by a delayed reward signal, the same plasticity is shown to maximize the expected reward in reinforcement learning for various coding scenarios. Our framework makes specific experimental predictions and highlights the unique advantage of active dendrites for implementing powerful synaptic plasticity rules that have access to downstream information via backpropagation of action potentials. '),
(87645, 2016, 'plos', 'Correction: Random Wiring, Ganglion Cell Mosaics, and the Functional Architecture of the Visual Cortex', 'PLOS Computational Biology Staff', 'Department of Physiology, University of Bern, Bern, Switzerland.', 'Switzerland', 0, '-', 'Published Erratum', '10.1371/journal.pcbi.1004758', '26841304', '-'),
(87646, 2016, 'plos', 'Evolutionary Genomics Suggests That CheV Is an Additional Adaptor for Accommodating Specific Chemoreceptors within the Chemotaxis Signaling Complex', 'Ortega, Davi R|Zhulin, Igor B', 'Computer Science and Mathematics Division, Oak Ridge National Laboratory, Oak Ridge, Tennessee, United States of America.|Computer Science and Mathematics Division, Oak Ridge National Laboratory, Oak Ridge, Tennessee, United States of America.', 'United States|United States', 14, 'Amino Acid Sequence|Bacillus subtilis|Bacterial Proteins|Chemotactic Factors|Chemotaxis|Evolution, Molecular|Genome, Bacterial|Genomics|Helicobacter pylori|Models, Molecular|Molecular Sequence Data', 'Journal Article', '10.1371/journal.pcbi.1004723', '26844549', 'Escherichia coli and Salmonella enterica are models for many experiments in molecular biology including chemotaxis, and most of the results obtained with one organism have been generalized to another. While most components of the chemotaxis pathway are strongly conserved between the two species, Salmonella genomes contain some chemoreceptors and an additional protein, CheV, that are not found in E. coli. The role of CheV was examined in distantly related species Bacillus subtilis and Helicobacter pylori, but its role in bacterial chemotaxis is still not well understood. We tested a hypothesis that in enterobacteria CheV functions as an additional adaptor linking the CheA kinase to certain types of chemoreceptors that cannot be effectively accommodated by the universal adaptor CheW. Phylogenetic profiling, genomic context and comparative protein sequence analyses suggested that CheV interacts with specific domains of CheA and chemoreceptors from an orthologous group exemplified by the Salmonella McpC protein. Structural consideration of the conservation patterns suggests that CheV and CheW share the same binding spot on the chemoreceptor structure, but have some affinity bias towards chemoreceptors from different orthologous groups. Finally, published experimental results and data newly obtained via comparative genomics support the idea that CheV functions as a phosphate sink possibly to off-set the over-stimulation of the kinase by certain types of chemoreceptors. Overall, our results strongly suggest that CheV is an additional adaptor for accommodating specific chemoreceptors within the chemotaxis signaling complex. '),
(87647, 2016, 'plos', 'MicroRNAs Form Triplexes with Double Stranded DNA at Sequence-Specific Binding Sites, a Eukaryotic Mechanism via which microRNAs Could Directly Alter Gene Expression', 'Paugh, Steven W|Coss, David R|Bao, Ju|Laudermilk, Lucas T|Grace, Christy R|Ferreira, Antonio M|Waddell, M Brett|Ridout, Granger|Naeve, Deanna|Leuze, Michael|LoCascio, Philip F|Panetta, John C|Wilkinson, Mark R|Pui, Ching-Hon|Naeve, Clayton W|Uberbacher, Edward C|Bonten, Erik J|Evans, William E', 'Hematological Malignancies Program, St. Jude Childrens Research Hospital, Memphis, Tennessee, United States of America.|High Performance Computing Facility, St. Jude Childrens Research Hospital, Memphis, Tennessee, United States of America.|Department of Pharmaceutical Sciences, St. Jude Childrens Research Hospital, Memphis, Tennessee, United States of America.|Hematological Malignancies Program, St. Jude Childrens Research Hospital, Memphis, Tennessee, United States of America.|Department of Structural Biology, St. Jude Childrens Research Hospital, Memphis, Tennessee, United States of America.|High Performance Computing Facility, St. Jude Childrens Research Hospital, Memphis, Tennessee, United States of America.|Molecular Interaction Analysis Laboratory, St. Jude Childrens Research Hospital, Memphis, Tennessee, United States of America.|Functional Genomics Laboratory, Hartwell Center for Bioinformatics & Biotechnology, St. Jude Childrens Research Hospital, Memphis, Tennessee, United States of America.|Functional Genomics Laboratory, Hartwell Center for Bioinformatics & Biotechnology, St. Jude Childrens Research Hospital, Memphis, Tennessee, United States of America.|Computer Science and Mathematics Division, Oak Ridge National Laboratory, Oak Ridge, Tennessee, United States of America.|Doctoral Training Centre, University of Oxford, Oxford, United Kingdom.|Department of Pharmaceutical Sciences, St. Jude Childrens Research Hospital, Memphis, Tennessee, United States of America.|Hematological Malignancies Program, St. Jude Childrens Research Hospital, Memphis, Tennessee, United States of America.|Hematological Malignancies Program, St. Jude Childrens Research Hospital, Memphis, Tennessee, United States of America.|Department of Information Sciences, St. Jude Childrens Research Hospital, Memphis, Tennessee, United States of America.|Computer Science and Mathematics Division, Oak Ridge National Laboratory, Oak Ridge, Tennessee, United States of America.|Hematological Malignancies Program, St. Jude Childrens Research Hospital, Memphis, Tennessee, United States of America.|Hematological Malignancies Program, St. Jude Childrens Research Hospital, Memphis, Tennessee, United States of America.', 'Mali|United States|United States|Mali|United States|United States|United States|United States|United', 33, 'Algorithms|Base Composition|Base Sequence|Binding Sites|Computational Biology|DNA|Gene Expression Regulation|Humans|Leukemia|MicroRNAs', 'Journal Article', '10.1371/journal.pcbi.1004744', '26844769', 'MicroRNAs are important regulators of gene expression, acting primarily by binding to sequence-specific locations on already transcribed messenger RNAs (mRNA) and typically down-regulating their stability or translation. Recent studies indicate that microRNAs may also play a role in up-regulating mRNA transcription levels, although a definitive mechanism has not been established. Double-helical DNA is capable of forming triple-helical structures through Hoogsteen and reverse Hoogsteen interactions in the major groove of the duplex, and we show physical evidence (i.e., NMR, FRET, SPR) that purine or pyrimidine-rich microRNAs of appropriate length and sequence form triple-helical structures with purine-rich sequences of duplex DNA, and identify microRNA sequences that favor triplex formation. We developed an algorithm (Trident) to search genome-wide for potential triplex-forming sites and show that several mammalian and non-mammalian genomes are enriched for strong microRNA triplex binding sites. We show that those genes containing sequences favoring microRNA triplex formation are markedly enriched (3.3 fold, p<2.2 × 10(-16)) for genes whose expression is positively correlated with expression of microRNAs targeting triplex binding sequences. This work has thus revealed a new mechanism by which microRNAs could interact with gene promoter regions to modify gene transcription.'),
(87648, 2016, 'plos', 'The Development of Computational Biology in South Africa: Successes Achieved and Lessons Learnt', 'Mulder, Nicola J|Christoffels, Alan|de Oliveira, Tulio|Gamieldien, Junaid|Hazelhurst, Scott|Joubert, Fourie|Kumuthini, Judit|Pillay, Ché S|Snoep, Jacky L|Tastan Bishop, Özlem|Tiffin, Nicki', 'Computational Biology Division, Department of Integrative Biomedical Sciences, Institute of Infectious Disease and Molecular Medicine, Faculty of Health Sciences, University of Cape Town, Cape Town, South Africa.|South African National Bioinformatics Institute/Medical Research Council of South Africa Bioinformatics Unit, University of the Western Cape, Bellville, South Africa.|Africa Centre for Health and Population Studies, School of Laboratory Medicine and Medical Sciences, University of KwaZulu-Natal, Durban, South Africa.|South African National Bioinformatics Institute/Medical Research Council of South Africa Bioinformatics Unit, University of the Western Cape, Bellville, South Africa.|School of Electrical & Information Engineering, and Sydney Brenner Institute for Molecular Bioscience, University of the Witwatersrand, Johannesburg, South Africa.|Centre for Bioinformatics and Computational Biology, University of Pretoria, Pretoria, South Africa.|Centre for Proteomic and Genomic Research, Cape Town, South Africa.|School of Life Sciences, University of KwaZulu-Natal, Pietermaritzburg, South Africa.|Department of Biochemistry, Stellenbosch University, Stellenbosch, South Africa.|Research Unit in Bioinformatics (RUBi), Department of Biochemistry and Microbiology, Rhodes University, Grahamstown, South Africa.|South African National Bioinformatics Institute/Medical Research Council of South Africa Bioinformatics Unit, University of the Western Cape, Bellville, South Africa.', 'South Africa|South Africa|South Africa|South Africa|South Africa|South Africa|South Africa|South Afr', 5, 'Biotechnology|Computational Biology|History, 20th Century|History, 21st Century|Humans|South Africa', 'Historical Article', '10.1371/journal.pcbi.1004395', '26845152', 'Bioinformatics is now a critical skill in many research and commercial environments as biological data are increasing in both size and complexity. South African researchers recognized this need in the mid-1990s and responded by working with the government as well as international bodies to develop initiatives to build bioinformatics capacity in the country. Significant injections of support from these bodies provided a springboard for the establishment of computational biology units at multiple universities throughout the country, which took on teaching, basic research and support roles. Several challenges were encountered, for example with unreliability of funding, lack of skills, and lack of infrastructure. However, the bioinformatics community worked together to overcome these, and South Africa is now arguably the leading country in bioinformatics on the African continent. Here we discuss how the discipline developed in the country, highlighting the challenges, successes, and lessons learnt. ');
INSERT INTO `papers` (`id`, `ano`, `journal`, `titulo`, `autores`, `afiliacao`, `pais`, `citacoes`, `palavra_chave`, `categorias`, `doi`, `pubmed`, `abstract`) VALUES
(87649, 2016, 'plos', 'Unbiased Rare Event Sampling in Spatial Stochastic Systems Biology Models Using a Weighted Ensemble of Trajectories', 'Donovan, Rory M|Tapia, Jose-Juan|Sullivan, Devin P|Faeder, James R|Murphy, Robert F|Dittrich, Markus|Zuckerman, Daniel M', 'Joint CMU-Pitt Ph.D. Program in Computational Biology, Pittsburgh, Pennsylvania, United States of America.|Joint CMU-Pitt Ph.D. Program in Computational Biology, Pittsburgh, Pennsylvania, United States of America.|Joint CMU-Pitt Ph.D. Program in Computational Biology, Pittsburgh, Pennsylvania, United States of America.|Department of Computational and Systems Biology, School of Medicine, University of Pittsburgh, Pittsburgh, Pennsylvania, United States of America.|Computational Biology Department, School of Computer Science, Carnegie Mellon University, 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 Computational and Systems Biology, School of Medicine, University of Pittsburgh, Pittsburgh, Pennsylvania, United States of America.', 'United States|United States|United States|United States|United States|United States|United States', 11, 'Algorithms|Animals|Anura|Models, Biological|Neuromuscular Junction|Stochastic Processes|Systems Biology', 'Journal Article', '10.1371/journal.pcbi.1004611', '26845334', 'The long-term goal of connecting scales in biological simulation can be facilitated by scale-agnostic methods. We demonstrate that the weighted ensemble (WE) strategy, initially developed for molecular simulations, applies effectively to spatially resolved cell-scale simulations. The WE approach runs an ensemble of parallel trajectories with assigned weights and uses a statistical resampling strategy of replicating and pruning trajectories to focus computational effort on difficult-to-sample regions. The method can also generate unbiased estimates of non-equilibrium and equilibrium observables, sometimes with significantly less aggregate computing time than would be possible using standard parallelization. Here, we use WE to orchestrate particle-based kinetic Monte Carlo simulations, which include spatial geometry (e.g., of organelles, plasma membrane) and biochemical interactions among mobile molecular species. We study a series of models exhibiting spatial, temporal and biochemical complexity and show that although WE has important limitations, it can achieve performance significantly exceeding standard parallel simulation--by orders of magnitude for some observables.'),
(87650, 2016, 'plos', 'Persistent Chaos of Measles Epidemics in the Prevaccination United States Caused by a Small Change in Seasonal Transmission Patterns', 'Dalziel, Benjamin D|Bjørnstad, Ottar N|van Panhuis, Willem G|Burke, Donald S|Metcalf, C Jessica E|Grenfell, Bryan T', 'Department of Ecology and Evolutionary Biology and Woodrow Wilson School of Public and International Affairs, Princeton University, Princeton, New Jersey, United States of America.|Department of Biology, Pennsylvania State University, University Park, Pennsylvania, United States of America.|Department of Epidemiology, University of Pittsburgh, Pittsburgh, Pennsylvania, United States of America.|Graduate School of Public Health, University of Pittsburgh, Pittsburgh, Pennsylvania, United States of America.|Department of Ecology and Evolutionary Biology and Woodrow Wilson School of Public and International Affairs, Princeton University, Princeton, New Jersey, United States of America.|Department of Ecology and Evolutionary Biology and Woodrow Wilson School of Public and International Affairs, Princeton University, Princeton, New Jersey, United States of America.', 'Jersey|United States|United States|United States|Jersey|Jersey', 19, 'Computational Biology|Epidemics|Humans|Mass Vaccination|Measles|Measles Vaccine|Models, Biological|Stochastic Processes|United Kingdom|United States', 'Journal Article', '10.1371/journal.pcbi.1004655', '26845437', 'Epidemics of infectious diseases often occur in predictable limit cycles. Theory suggests these cycles can be disrupted by high amplitude seasonal fluctuations in transmission rates, resulting in deterministic chaos. However, persistent deterministic chaos has never been observed, in part because sufficiently large oscillations in transmission rates are uncommon. Where they do occur, the resulting deep epidemic troughs break the chain of transmission, leading to epidemic extinction, even in large cities. Here we demonstrate a new path to locally persistent chaotic epidemics via subtle shifts in seasonal patterns of transmission, rather than through high-amplitude fluctuations in transmission rates. We base our analysis on a comparison of measles incidence in 80 major cities in the prevaccination era United States and United Kingdom. Unlike the regular limit cycles seen in the UK, measles cycles in US cities consistently exhibit spontaneous shifts in epidemic periodicity resulting in chaotic patterns. We show that these patterns were driven by small systematic differences between countries in the duration of the summer period of low transmission. This example demonstrates empirically that small perturbations in disease transmission patterns can fundamentally alter the regularity and spatiotemporal coherence of epidemics. '),
(87651, 2016, 'plos', 'Ensemble Tractography', 'Takemura, Hiromasa|Caiafa, Cesar F|Wandell, Brian A|Pestilli, Franco', 'Center for Information and Neural Networks (CiNet), National Institute of Information and Communications Technology, and Osaka University, Suita, Japan.|Instituto Argentino de Radioastronomía (IAR)-CCT La Plata-CONICET, Villa Elisa, Buenos Aires, Argentina.|Department of Psychology, Stanford University, Stanford, California, United States of America.|Department of Psychological and Brain Sciences, Indiana University, Bloomington, Indiana, United States of America.', 'Japan|Argentina|United States|India', 40, 'Adult|Brain|Computational Biology|Connectome|Diffusion Tensor Imaging|Humans|Magnetic Resonance Imaging|Male|Nerve Net', 'Journal Article', '10.1371/journal.pcbi.1004692', '26845558', 'Tractography uses diffusion MRI to estimate the trajectory and cortical projection zones of white matter fascicles in the living human brain. There are many different tractography algorithms and each requires the user to set several parameters, such as curvature threshold. Choosing a single algorithm with specific parameters poses two challenges. First, different algorithms and parameter values produce different results. Second, the optimal choice of algorithm and parameter value may differ between different white matter regions or different fascicles, subjects, and acquisition parameters. We propose using ensemble methods to reduce algorithm and parameter dependencies. To do so we separate the processes of fascicle generation and evaluation. Specifically, we analyze the value of creating optimized connectomes by systematically combining candidate streamlines from an ensemble of algorithms (deterministic and probabilistic) and systematically varying parameters (curvature and stopping criterion). The ensemble approach leads to optimized connectomes that provide better cross-validated prediction error of the diffusion MRI data than optimized connectomes generated using a single-algorithm or parameter set. Furthermore, the ensemble approach produces connectomes that contain both short- and long-range fascicles, whereas single-parameter connectomes are biased towards one or the other. In summary, a systematic ensemble tractography approach can produce connectomes that are superior to standard single parameter estimates both for predicting the diffusion measurements and estimating white matter fascicles. '),
(87652, 2016, 'plos', 'Erosion of Conserved Binding Sites in Personal Genomes Points to Medical Histories', 'Guturu, Harendra|Chinchali, Sandeep|Clarke, Shoa L|Bejerano, Gill', 'Department of Electrical Engineering, Stanford University, Stanford, California, United States of America.|Department of Electrical Engineering, Stanford University, Stanford, California, United States of America.|Department of Genetics, Stanford University, Stanford, California, United States of America.|Department of Pediatrics (Genetics), Stanford University, Stanford, California, United States of America.', 'United States|United States|United States|United States', 4, 'Binding Sites|Genome, Human|Genomics|HLA-DQ beta-Chains|Humans|Linkage Disequilibrium|Models, Genetic|Models, Statistical|Mutation|Narcolepsy|Precision Medicine', 'Journal Article', '10.1371/journal.pcbi.1004711', '26845687', 'Although many human diseases have a genetic component involving many loci, the majority of studies are statistically underpowered to isolate the many contributing variants, raising the question of the existence of alternate processes to identify disease mutations. To address this question, we collect ancestral transcription factor binding sites disrupted by an individuals variants and then look for their most significant congregation next to a group of functionally related genes. Strikingly, when the method is applied to five different full human genomes, the top enriched function for each is invariably reflective of their very different medical histories. For example, our method implicates abnormal cardiac output for a patient with a longstanding family history of heart disease, decreased circulating sodium level for an individual with hypertension, and other biologically appealing links for medical histories spanning narcolepsy to axonal neuropathy. Our results suggest that erosion of gene regulation by mutation load significantly contributes to observed heritable phenotypes that manifest in the medical history. The test we developed exposes a hitherto hidden layer of personal variants that promise to shed new light on human disease penetrance, expressivity and the sensitivity with which we can detect them. '),
(87653, 2016, 'plos', 'Computational Cancer Biology: An Evolutionary Perspective', 'Beerenwinkel, Niko|Greenman, Chris D|Lagergren, Jens', 'Department of Biosystems Science and Engineering, ETH Zurich, Basel, Switzerland.|School of Computing Sciences, University of East Anglia, Norwich, United Kingdom.|Science for Life Laboratory, School of Computer Science and Communication, Swedish E-Science Research Center, KTH Royal Institute of Technology, Solna, Sweden.', 'Switzerland|United Kingdom|Sweden', 22, 'Computational Biology|Disease Progression|Evolution, Molecular|Genome, Human|High-Throughput Nucleotide Sequencing|Humans|Neoplasms', 'Journal Article', '10.1371/journal.pcbi.1004717', '26845763', '-'),
(87654, 2016, 'plos', 'What Population Reveals about Individual Cell Identity: Single-Cell Parameter Estimation of Models of Gene Expression in Yeast', 'Llamosi, Artémis|Gonzalez-Vargas, Andres M|Versari, Cristian|Cinquemani, Eugenio|Ferrari-Trecate, Giancarlo|Hersen, Pascal|Batt, Gregory', 'Inria Saclay - Ile-de-France, Palaiseau, France.|Dipartimento di Ingegneria Industriale e dellInformazione, Università degli Studi di Pavia, Pavia, Italy.|Laboratoire dInformatique Fondamentale de Lille, UMR 8022, Université de Lille 1 & CNRS, Villeneuve dAscq Cedex, France.|INRIA Grenoble - Rhône-Alpes, Montbonnot, France.|Dipartimento di Ingegneria Industriale e dellInformazione, Università degli Studi di Pavia, Pavia, Italy.|Laboratoire Matière et Systèmes Complexes, UMR 7057, Université Paris Diderot & CNRS, Paris, France.|Inria Saclay - Ile-de-France, Palaiseau, France.', 'France|Italy|France|France|Italy|France|France', 32, 'Computational Biology|Gene Expression|Microfluidic Analytical Techniques|Models, Biological|Saccharomyces cerevisiae|Single-Cell Analysis', 'Journal Article', '10.1371/journal.pcbi.1004706', '26859137', 'Significant cell-to-cell heterogeneity is ubiquitously observed in isogenic cell populations. Consequently, parameters of models of intracellular processes, usually fitted to population-averaged data, should rather be fitted to individual cells to obtain a population of models of similar but non-identical individuals. Here, we propose a quantitative modeling framework that attributes specific parameter values to single cells for a standard model of gene expression. We combine high quality single-cell measurements of the response of yeast cells to repeated hyperosmotic shocks and state-of-the-art statistical inference approaches for mixed-effects models to infer multidimensional parameter distributions describing the population, and then derive specific parameters for individual cells. The analysis of single-cell parameters shows that single-cell identity (e.g. gene expression dynamics, cell size, growth rate, mother-daughter relationships) is, at least partially, captured by the parameter values of gene expression models (e.g. rates of transcription, translation and degradation). Our approach shows how to use the rich information contained into longitudinal single-cell data to infer parameters that can faithfully represent single-cell identity. '),
(87655, 2016, 'plos', 'Robust Unidirectional Airflow through Avian Lungs: New Insights from a Piecewise Linear Mathematical Model', 'Harvey, Emily P|Ben-Tal, Alona', 'Institute of Natural and Mathematical Sciences, Massey University Albany, Auckland, New Zealand.|Institute of Natural and Mathematical Sciences, Massey University Albany, Auckland, New Zealand.', 'New Zealand|New Zealand', 4, 'Animals|Biomechanical Phenomena|Birds|Computational Biology|Lung|Models, Biological|Respiratory Physiological Phenomena', 'Journal Article', '10.1371/journal.pcbi.1004637', '26862752', 'Avian lungs are remarkably different from mammalian lungs in that air flows unidirectionally through rigid tubes in which gas exchange occurs. Experimental observations have been able to determine the pattern of gas flow in the respiratory system, but understanding how the flow pattern is generated and determining the factors contributing to the observed dynamics remains elusive. It has been hypothesized that the unidirectional flow is due to aerodynamic valving during inspiration and expiration, resulting from the anatomical structure and the fluid dynamics involved, however, theoretical studies to back up this hypothesis are lacking. We have constructed a novel mathematical model of the airflow in the avian respiratory system that can produce unidirectional flow which is robust to changes in model parameters, breathing frequency and breathing amplitude. The model consists of two piecewise linear ordinary differential equations with lumped parameters and discontinuous, flow-dependent resistances that mimic the experimental observations. Using dynamical systems techniques and numerical analysis, we show that unidirectional flow can be produced by either effective inspiratory or effective expiratory valving, but that both inspiratory and expiratory valving are required to produce the high efficiencies of flows observed in avian lungs. We further show that the efficacy of the inspiratory and expiratory valving depends on airsac compliances and airflow resistances that may not be located in the immediate area of the valving. Our model provides additional novel insights, for example, we show that physiologically realistic resistance values lead to efficiencies that are close to maximum, and that when the relative lumped compliances of the caudal and cranial airsacs vary, it affects the timing of the airflow across the gas exchange area. These and other insights obtained by our study significantly enhance our understanding of the operation of the avian respiratory system. '),
(87656, 2016, 'plos', 'Plasticity-Driven Self-Organization under Topological Constraints Accounts for Non-random Features of Cortical Synaptic Wiring', 'Miner, Daniel|Triesch, Jochen', 'Frankfurt Institute for Advanced Studies, Frankfurt am Main, Germany.|Frankfurt Institute for Advanced Studies, Frankfurt am Main, Germany.', 'Germany|Germany', 24, 'Cerebral Cortex|Computer Simulation|Humans|Models, Neurological|Nerve Net|Neuronal Plasticity|Synapses', 'Journal Article', '10.1371/journal.pcbi.1004759', '26866369', 'Understanding the structure and dynamics of cortical connectivity is vital to understanding cortical function. Experimental data strongly suggest that local recurrent connectivity in the cortex is significantly non-random, exhibiting, for example, above-chance bidirectionality and an overrepresentation of certain triangular motifs. Additional evidence suggests a significant distance dependency to connectivity over a local scale of a few hundred microns, and particular patterns of synaptic turnover dynamics, including a heavy-tailed distribution of synaptic efficacies, a power law distribution of synaptic lifetimes, and a tendency for stronger synapses to be more stable over time. Understanding how many of these non-random features simultaneously arise would provide valuable insights into the development and function of the cortex. While previous work has modeled some of the individual features of local cortical wiring, there is no model that begins to comprehensively account for all of them. We present a spiking network model of a rodent Layer 5 cortical slice which, via the interactions of a few simple biologically motivated intrinsic, synaptic, and structural plasticity mechanisms, qualitatively reproduces these non-random effects when combined with simple topological constraints. Our model suggests that mechanisms of self-organization arising from a small number of plasticity rules provide a parsimonious explanation for numerous experimentally observed non-random features of recurrent cortical wiring. Interestingly, similar mechanisms have been shown to endow recurrent networks with powerful learning abilities, suggesting that these mechanism are central to understanding both structure and function of cortical synaptic wiring. '),
(87657, 2016, 'plos', 'Inferring Growth Control Mechanisms in Growing Multi-cellular Spheroids of NSCLC Cells from Spatial-Temporal Image Data', 'Jagiella, Nick|Müller, Benedikt|Müller, Margareta|Vignon-Clementel, Irene E|Drasdo, Dirk', 'Institute for Computational Biology, Helmholtz Zentrum München, Neuherberg, Germany.|Institute for Pathology Heidelberg (iPH), Heidelberg University Hospital, Heidelberg, Germany.|Faculty of Medical and Life Sciences, Furtwangen University, Furtwangen, Germany.|INRIA Paris, Centre de recherche Inria de Paris, Paris, France.|INRIA Paris, Centre de recherche Inria de Paris, Paris, France.', 'Germany|Germany|Germany|France|France', 34, 'Algorithms|Carcinoma, Non-Small-Cell Lung|Cell Line, Tumor|Cell Proliferation|Computational Biology|Humans|Image Processing, Computer-Assisted|In Situ Nick-End Labeling|Models, Biological|Spheroids, Cellular|Tumor Cells, Cultured', 'Journal Article', '10.1371/journal.pcbi.1004412', '26866479', 'We develop a quantitative single cell-based mathematical model for multi-cellular tumor spheroids (MCTS) of SK-MES-1 cells, a non-small cell lung cancer (NSCLC) cell line, growing under various nutrient conditions: we confront the simulations performed with this model with data on the growth kinetics and spatial labeling patterns for cell proliferation, extracellular matrix (ECM), cell distribution and cell death. We start with a simple model capturing part of the experimental observations. We then show, by performing a sensitivity analysis at each development stage of the model that its complexity needs to be stepwise increased to account for further experimental growth conditions. We thus ultimately arrive at a model that mimics the MCTS growth under multiple conditions to a great extent. Interestingly, the final model, is a minimal model capable of explaining all data simultaneously in the sense, that the number of mechanisms it contains is sufficient to explain the data and missing out any of its mechanisms did not permit fit between all data and the model within physiological parameter ranges. Nevertheless, compared to earlier models it is quite complex i.e., it includes a wide range of mechanisms discussed in biological literature. In this model, the cells lacking oxygen switch from aerobe to anaerobe glycolysis and produce lactate. Too high concentrations of lactate or too low concentrations of ATP promote cell death. Only if the extracellular matrix density overcomes a certain threshold, cells are able to enter the cell cycle. Dying cells produce a diffusive growth inhibitor. Missing out the spatial information would not permit to infer the mechanisms at work. Our findings suggest that this iterative data integration together with intermediate model sensitivity analysis at each model development stage, provide a promising strategy to infer predictive yet minimal (in the above sense) quantitative models of tumor growth, as prospectively of other tissue organization processes. Importantly, calibrating the model with two nutriment-rich growth conditions, the outcome for two nutriment-poor growth conditions could be predicted. As the final model is however quite complex, incorporating many mechanisms, space, time, and stochastic processes, parameter identification is a challenge. This calls for more efficient strategies of imaging and image analysis, as well as of parameter identification in stochastic agent-based simulations. '),
(87658, 2016, 'plos', 'Non-monotonic Temporal-Weighting Indicates a Dynamically Modulated Evidence-Integration Mechanism', 'Bronfman, Zohar Z|Brezis, Noam|Usher, Marius', 'School of Psychology, Tel-Aviv University, Tel-Aviv, Israel.|School of Psychology, Tel-Aviv University, Tel-Aviv, Israel.|School of Psychology, Tel-Aviv University, Tel-Aviv, Israel.', 'Israel|Israel|Israel', 11, 'Choice Behavior|Computational Biology|Decision Making|Humans|Models, Biological|Task Performance and Analysis', 'Journal Article', '10.1371/journal.pcbi.1004667', '26866598', 'Perceptual decisions are thought to be mediated by a mechanism of sequential sampling and integration of noisy evidence whose temporal weighting profile affects the decision quality. To examine temporal weighting, participants were presented with two brightness-fluctuating disks for 1, 2 or 3 seconds and were requested to choose the overall brighter disk at the end of each trial. By employing a signal-perturbation method, which deploys across trials a set of systematically controlled temporal dispersions of the same overall signal, we were able to quantify the participants temporal weighting profile. Results indicate that, for intervals of 1 or 2 sec, participants exhibit a primacy-bias. However, for longer stimuli (3-sec) the temporal weighting profile is non-monotonic, with concurrent primacy and recency, which is inconsistent with the predictions of previously suggested computational models of perceptual decision-making (drift-diffusion and Ornstein-Uhlenbeck processes). We propose a novel, dynamic variant of the leaky-competing accumulator model as a potential account for this finding, and we discuss potential neural mechanisms. '),
(87659, 2016, 'plos', 'Using an Insect Mushroom Body Circuit to Encode Route Memory in Complex Natural Environments', 'Ardin, Paul|Peng, Fei|Mangan, Michael|Lagogiannis, Konstantinos|Webb, Barbara', 'School of Informatics, University of Edinburgh, Edinburgh, United Kingdom.|Biological and Experimental Psychology, School of Biological and Chemical Sciences, Queen Mary University of London, London, United Kingdom.|School of Informatics, University of Edinburgh, Edinburgh, United Kingdom.|School of Informatics, University of Edinburgh, Edinburgh, United Kingdom.|School of Informatics, University of Edinburgh, Edinburgh, United Kingdom.', 'United Kingdom|United Kingdom|United Kingdom|United Kingdom|United Kingdom', 58, 'Action Potentials|Algorithms|Animals|Ants|Computational Biology|Memory|Models, Neurological|Mushroom Bodies|Neurons', 'Journal Article', '10.1371/journal.pcbi.1004683', '26866692', 'Ants, like many other animals, use visual memory to follow extended routes through complex environments, but it is unknown how their small brains implement this capability. The mushroom body neuropils have been identified as a crucial memory circuit in the insect brain, but their function has mostly been explored for simple olfactory association tasks. We show that a spiking neural model of this circuit originally developed to describe fruitfly (Drosophila melanogaster) olfactory association, can also account for the ability of desert ants (Cataglyphis velox) to rapidly learn visual routes through complex natural environments. We further demonstrate that abstracting the key computational principles of this circuit, which include one-shot learning of sparse codes, enables the theoretical storage capacity of the ant mushroom body to be estimated at hundreds of independent images. '),
(87660, 2016, 'plos', 'On the Origins and Control of Community Types in the Human Microbiome', 'Gibson, Travis E|Bashan, Amir|Cao, Hong-Tai|Weiss, Scott T|Liu, Yang-Yu', 'Channing Division of Network Medicine, Brigham and Womens Hospital, Harvard Medical School, Boston, Massachusetts, United States of America.|Channing Division of Network Medicine, Brigham and Womens Hospital, Harvard Medical School, Boston, Massachusetts, United States of America.|Channing Division of Network Medicine, Brigham and Womens Hospital, Harvard Medical School, Boston, Massachusetts, United States of America.|Channing Division of Network Medicine, Brigham and Womens Hospital, Harvard Medical School, Boston, Massachusetts, United States of America.|Channing Division of Network Medicine, Brigham and Womens Hospital, Harvard Medical School, Boston, Massachusetts, United States of America.', 'United States|United States|United States|United States|United States', 32, 'Algorithms|Cluster Analysis|Computational Biology|Humans|Microbiota|Models, Biological', 'Journal Article', '10.1371/journal.pcbi.1004688', '26866806', 'Microbiome-based stratification of healthy individuals into compositional categories, referred to as enterotypes or community types, holds promise for drastically improving personalized medicine. Despite this potential, the existence of community types and the degree of their distinctness have been highly debated. Here we adopted a dynamic systems approach and found that heterogeneity in the interspecific interactions or the presence of strongly interacting species is sufficient to explain community types, independent of the topology of the underlying ecological network. By controlling the presence or absence of these strongly interacting species we can steer the microbial ecosystem to any desired community type. This open-loop control strategy still holds even when the community types are not distinct but appear as dense regions within a continuous gradient. This finding can be used to develop viable therapeutic strategies for shifting the microbial composition to a healthy configuration. '),
(87661, 2016, 'plos', 'Radial Frequency Analysis of Contour Shapes in the Visual Cortex', 'Salmela, Viljami R|Henriksson, Linda|Vanni, Simo', 'Institute of Behavioural Sciences, Division of Cognitive and Neuropsychology, University of Helsinki, Helsinki, Finland.|Advanced Magnetic Imaging Centre, Aalto NeuroImaging, Aalto University School of Science, Espoo, Finland.|Advanced Magnetic Imaging Centre, Aalto NeuroImaging, Aalto University School of Science, Espoo, Finland.', 'Finland|Finland|Finland', 1, 'Computational Biology|Female|Form Perception|Humans|Magnetic Resonance Imaging|Male|Pattern Recognition, Visual|Psychophysics|Visual Cortex', 'Journal Article', '10.1371/journal.pcbi.1004719', '26866917', 'Cumulative psychophysical evidence suggests that the shape of closed contours is analysed by means of their radial frequency components (RFC). However, neurophysiological evidence for RFC-based representations is still missing. We investigated the representation of radial frequency in the human visual cortex with functional magnetic resonance imaging. We parametrically varied the radial frequency, amplitude and local curvature of contour shapes. The stimuli evoked clear responses across visual areas in the univariate analysis, but the response magnitude did not depend on radial frequency or local curvature. Searchlight-based, multivariate representational similarity analysis revealed RFC specific response patterns in areas V2d, V3d, V3AB, and IPS0. Interestingly, RFC-specific representations were not found in hV4 or LO, traditionally associated with visual shape analysis. The modulation amplitude of the shapes did not affect the responses in any visual area. Local curvature, SF-spectrum and contrast energy related representations were found across visual areas but without similar specificity for visual area that was found for RFC. The results suggest that the radial frequency of a closed contour is one of the cortical shape analysis dimensions, represented in the early and mid-level visual areas. '),
(87662, 2016, 'plos', 'Muscle Synergies Heavily Influence the Neural Control of Arm Endpoint Stiffness and Energy Consumption', 'Inouye, Joshua M|Valero-Cuevas, Francisco J', 'Department of Biomedical Engineering, University of Virginia, Charlottesville, Virginia, United States of America.|Department of Biomedical Engineering, University of Southern California, Los Angeles, California, United States of America.', 'United States|United States', 0, 'Arm|Computational Biology|Energy Metabolism|Hand|Humans|Models, Neurological|Muscle, Skeletal|Musculoskeletal Physiological Phenomena|Task Performance and Analysis', 'Journal Article', '10.1371/journal.pcbi.1004737', '26867014', 'Much debate has arisen from research on muscle synergies with respect to both limb impedance control and energy consumption. Studies of limb impedance control in the context of reaching movements and postural tasks have produced divergent findings, and this study explores whether the use of synergies by the central nervous system (CNS) can resolve these findings and also provide insights on mechanisms of energy consumption. In this study, we phrase these debates at the conceptual level of interactions between neural degrees of freedom and tasks constraints. This allows us to examine the ability of experimentally-observed synergies--correlated muscle activations--to control both energy consumption and the stiffness component of limb endpoint impedance. In our nominal 6-muscle planar arm model, muscle synergies and the desired size, shape, and orientation of endpoint stiffness ellipses, are expressed as linear constraints that define the set of feasible muscle activation patterns. Quadratic programming allows us to predict whether and how energy consumption can be minimized throughout the workspace of the limb given those linear constraints. We show that the presence of synergies drastically decreases the ability of the CNS to vary the properties of the endpoint stiffness and can even preclude the ability to minimize energy. Furthermore, the capacity to minimize energy consumption--when available--can be greatly affected by arm posture. Our computational approach helps reconcile divergent findings and conclusions about task-specific regulation of endpoint stiffness and energy consumption in the context of synergies. But more generally, these results provide further evidence that the benefits and disadvantages of muscle synergies go hand-in-hand with the structure of feasible muscle activation patterns afforded by the mechanics of the limb and task constraints. These insights will help design experiments to elucidate the interplay between synergies and the mechanisms of learning, plasticity, versatility and pathology in neuromuscular systems.'),
(87663, 2016, 'plos', 'Practical Approaches for Detecting Selection in Microbial Genomes', 'Hedge, Jessica|Wilson, Daniel J', 'Nuffield Department of Medicine, University of Oxford, John Radcliffe Hospital, Oxford, United Kingdom.|Nuffield Department of Medicine, University of Oxford, John Radcliffe Hospital, Oxford, United Kingdom.', 'United Kingdom|United Kingdom', 9, 'Computational Biology|Evolution, Molecular|Genome, Microbial|Molecular Sequence Annotation|Phylogeny|Selection, Genetic', 'Journal Article', '10.1371/journal.pcbi.1004739', '26867134', 'Microbial genome evolution is shaped by a variety of selective pressures. Understanding how these processes occur can help to address important problems in microbiology by explaining observed differences in phenotypes, including virulence and resistance to antibiotics. Greater access to whole-genome sequencing provides microbiologists with the opportunity to perform large-scale analyses of selection in novel settings, such as within individual hosts. This tutorial aims to guide researchers through the fundamentals underpinning popular methods for measuring selection in pathogens. These methods are transferable to a wide variety of organisms, and the exercises provided are designed for researchers with any level of programming experience. '),
(87664, 2016, 'plos', 'Ten Simple Rules for Selecting a Bio-ontology', 'Malone, James|Stevens, Robert|Jupp, Simon|Hancocks, Tom|Parkinson, Helen|Brooksbank, Cath', 'European Bioinformatics Institute (EMBL-EBI), Cambridge, United Kingdom.|School of Computer Science, University of Manchester, Manchester, United Kingdom.|European Bioinformatics Institute (EMBL-EBI), Cambridge, United Kingdom.|European Bioinformatics Institute (EMBL-EBI), Cambridge, United Kingdom.|European Bioinformatics Institute (EMBL-EBI), Cambridge, United Kingdom.|European Bioinformatics Institute (EMBL-EBI), Cambridge, United Kingdom.', 'United Kingdom|United Kingdom|United Kingdom|United Kingdom|United Kingdom|United Kingdom', 0, 'Biological Ontologies|Computational Biology|Databases, Factual|Humans', 'Editorial', '10.1371/journal.pcbi.1004743', '26867217', '-'),
(87665, 2016, 'plos', 'Developing a Physiologically-Based Pharmacokinetic Model Knowledgebase in Support of Provisional Model Construction', 'Lu, Jingtao|Goldsmith, Michael-Rock|Grulke, Christopher M|Chang, Daniel T|Brooks, Raina D|Leonard, Jeremy A|Phillips, Martin B|Hypes, Ethan D|Fair, Matthew J|Tornero-Velez, Rogelio|Johnson, Jeffre|Dary, Curtis C|Tan, Yu-Mei', 'Oak Ridge Institute for Science and Education, Oak Ridge, Tennessee, United States of America.|National Exposure Research Laboratory, US-Environmental Protection Agency, Research Triangle Park, North Carolina, United States of America.|National Exposure Research Laboratory, US-Environmental Protection Agency, Research Triangle Park, North Carolina, United States of America.|National Exposure Research Laboratory, US-Environmental Protection Agency, Research Triangle Park, North Carolina, United States of America.|National Exposure Research Laboratory, US-Environmental Protection Agency, Research Triangle Park, North Carolina, United States of America.|Oak Ridge Institute for Science and Education, Oak Ridge, Tennessee, United States of America.|Oak Ridge Institute for Science and Education, Oak Ridge, Tennessee, United States of America.|National Exposure Research Laboratory, US-Environmental Protection Agency, Research Triangle Park, North Carolina, United States of America.|National Exposure Research Laboratory, US-Environmental Protection Agency, Research Triangle Park, North Carolina, United States of America.|National Exposure Research Laboratory, US-Environmental Protection Agency, Research Triangle Park, North Carolina, United States of America.|National Exposure Research Laboratory, US-Environmental Protection Agency, Las Vegas, Nevada, United States of America.|National Exposure Research Laboratory, US-Environmental Protection Agency, Las Vegas, Nevada, United States of America.|National Exposure Research Laboratory, US-Environmental Protection Agency, Research Triangle Park, North Carolina, United States of America.', 'United States|United States|United States|United States|United States|United States|United States|Un', 0, 'Animals|Computational Biology|Humans|Knowledge Bases|Mice|Models, Biological|Pharmaceutical Preparations|Pharmacokinetics|Rats|Swine', 'Journal Article', '10.1371/journal.pcbi.1004495', '26871706', 'Developing physiologically-based pharmacokinetic (PBPK) models for chemicals can be resource-intensive, as neither chemical-specific parameters nor in vivo pharmacokinetic data are easily available for model construction. Previously developed, well-parameterized, and thoroughly-vetted models can be a great resource for the construction of models pertaining to new chemicals. A PBPK knowledgebase was compiled and developed from existing PBPK-related articles and used to develop new models. From 2,039 PBPK-related articles published between 1977 and 2013, 307 unique chemicals were identified for use as the basis of our knowledgebase. Keywords related to species, gender, developmental stages, and organs were analyzed from the articles within the PBPK knowledgebase. A correlation matrix of the 307 chemicals in the PBPK knowledgebase was calculated based on pharmacokinetic-relevant molecular descriptors. Chemicals in the PBPK knowledgebase were ranked based on their correlation toward ethylbenzene and gefitinib. Next, multiple chemicals were selected to represent exact matches, close analogues, or non-analogues of the target case study chemicals. Parameters, equations, or experimental data relevant to existing models for these chemicals and their analogues were used to construct new models, and model predictions were compared to observed values. This compiled knowledgebase provides a chemical structure-based approach for identifying PBPK models relevant to other chemical entities. Using suitable correlation metrics, we demonstrated that models of chemical analogues in the PBPK knowledgebase can guide the construction of PBPK models for other chemicals. '),
(87666, 2016, 'plos', 'Structural and Functional Characterization of a Caenorhabditis elegans Genetic Interaction Network within Pathways', 'Boucher, Benjamin|Lee, Anna Y|Hallett, Michael|Jenna, Sarah', 'Department of Chemistry, Université du Québec à Montréal, Montréal, Québec, Canada.|McGill Centre for Bioinformatics, McGill University, Montréal, Québec, Canada.|McGill Centre for Bioinformatics, McGill University, Montréal, Québec, Canada.|Department of Chemistry, Université du Québec à Montréal, Montréal, Québec, Canada.', 'Canada|Canada|Canada|Canada', 2, 'Animals|Caenorhabditis elegans|Caenorhabditis elegans Proteins|Computational Biology|Gene Regulatory Networks|Models, Biological|Protein Interaction Maps', 'Journal Article', '10.1371/journal.pcbi.1004738', '26871911', 'A genetic interaction (GI) is defined when the mutation of one gene modifies the phenotypic expression associated with the mutation of a second gene. Genome-wide efforts to map GIs in yeast revealed structural and functional properties of a GI network. This provided insights into the mechanisms underlying the robustness of yeast to genetic and environmental insults, and also into the link existing between genotype and phenotype. While a significant conservation of GIs and GI network structure has been reported between distant yeast species, such a conservation is not clear between unicellular and multicellular organisms. Structural and functional characterization of a GI network in these latter organisms is consequently of high interest. In this study, we present an in-depth characterization of ~1.5K GIs in the nematode Caenorhabditis elegans. We identify and characterize six distinct classes of GIs by examining a wide-range of structural and functional properties of genes and network, including co-expression, phenotypical manifestations, relationship with protein-protein interaction dense subnetworks (PDS) and pathways, molecular and biological functions, gene essentiality and pleiotropy. Our study shows that GI classes link genes within pathways and display distinctive properties, specifically towards PDS. It suggests a model in which pathways are composed of PDS-centric and PDS-independent GIs coordinating molecular machines through two specific classes of GIs involving pleiotropic and non-pleiotropic connectors. Our study provides the first in-depth characterization of a GI network within pathways of a multicellular organism. It also suggests a model to understand better how GIs control system robustness and evolution. '),
(87667, 2016, 'plos', 'FastGGM: An Efficient Algorithm for the Inference of Gaussian Graphical Model in Biological Networks', 'Wang, Ting|Ren, Zhao|Ding, Ying|Fang, Zhou|Sun, Zhe|MacDonald, Matthew L|Sweet, Robert A|Wang, Jieru|Chen, Wei', 'Division of Pulmonary Medicine, Allergy and Immunology, Department of Pediatrics, Childrens Hospital of Pittsburgh of UPMC, University of Pittsburgh, Pittsburgh, Pennsylvania, United States of America.|Department of Statistics, University of Pittsburgh, Pittsburgh, Pennsylvania, United States of America.|Department of Biostatistics, University of Pittsburgh Graduate School of Public Health, Pittsburgh, Pennsylvania, United States of America.|Department of Biostatistics, University of Pittsburgh Graduate School of Public Health, Pittsburgh, Pennsylvania, United States of America.|Department of Biostatistics, University of Pittsburgh Graduate School of Public Health, Pittsburgh, Pennsylvania, United States of America.|Department of Psychiatry, University of Pittsburgh, Pittsburgh, Pennsylvania, United States of America.|Department of Psychiatry, University of Pittsburgh, Pittsburgh, Pennsylvania, United States of America.|Division of Pulmonary Medicine, Allergy and Immunology, Department of Pediatrics, Childrens Hospital of Pittsburgh of UPMC, University of Pittsburgh, Pittsburgh, Pennsylvania, United States of America.|Division of Pulmonary Medicine, Allergy and Immunology, Department of Pediatrics, Childrens Hospital of Pittsburgh of UPMC, University of Pittsburgh, Pittsburgh, Pennsylvania, United States of America.', 'United States|United States|United States|United States|United States|United States|United States|Un', 17, 'Algorithms|Asthma|Child|Cluster Analysis|Computational Biology|Computer Simulation|Gene Expression Profiling|Gene Regulatory Networks|Humans|Models, Biological|Normal Distribution', 'Journal Article', '10.1371/journal.pcbi.1004755', '26872036', 'Biological networks provide additional information for the analysis of human diseases, beyond the traditional analysis that focuses on single variables. Gaussian graphical model (GGM), a probability model that characterizes the conditional dependence structure of a set of random variables by a graph, has wide applications in the analysis of biological networks, such as inferring interaction or comparing differential networks. However, existing approaches are either not statistically rigorous or are inefficient for high-dimensional data that include tens of thousands of variables for making inference. In this study, we propose an efficient algorithm to implement the estimation of GGM and obtain p-value and confidence interval for each edge in the graph, based on a recent proposal by Ren et al., 2015. Through simulation studies, we demonstrate that the algorithm is faster by several orders of magnitude than the current implemented algorithm for Ren et al. without losing any accuracy. Then, we apply our algorithm to two real data sets: transcriptomic data from a study of childhood asthma and proteomic data from a study of Alzheimers disease. We estimate the global gene or protein interaction networks for the disease and healthy samples. The resulting networks reveal interesting interactions and the differential networks between cases and controls show functional relevance to the diseases. In conclusion, we provide a computationally fast algorithm to implement a statistically sound procedure for constructing Gaussian graphical model and making inference with high-dimensional biological data. The algorithm has been implemented in an R package named FastGGM. '),
(87668, 2016, 'plos', 'Neighborhood Regularized Logistic Matrix Factorization for Drug-Target Interaction Prediction', 'Liu, Yong|Wu, Min|Miao, Chunyan|Zhao, Peilin|Li, Xiao-Li', 'Joint NTU-UBC Research Centre of Excellence in Active Living for the Elderly (LILY), and School of Computer Engineering, Nanyang Technological University, Singapore.|Institute for Infocomm Research (I2R), Agency for Science, Technology and Research (A*STAR), Singapore.|Joint NTU-UBC Research Centre of Excellence in Active Living for the Elderly (LILY), and School of Computer Engineering, Nanyang Technological University, Singapore.|Institute for Infocomm Research (I2R), Agency for Science, Technology and Research (A*STAR), Singapore.|Institute for Infocomm Research (I2R), Agency for Science, Technology and Research (A*STAR), Singapore.', 'Singapore|Singapore|Singapore|Singapore|Singapore', 0, 'Algorithms|Computational Biology|Drug Discovery|Ligands|Pharmaceutical Preparations|Proteins', 'Journal Article', '10.1371/journal.pcbi.1004760', '26872142', 'In pharmaceutical sciences, a crucial step of the drug discovery process is the identification of drug-target interactions. However, only a small portion of the drug-target interactions have been experimentally validated, as the experimental validation is laborious and costly. To improve the drug discovery efficiency, there is a great need for the development of accurate computational approaches that can predict potential drug-target interactions to direct the experimental verification. In this paper, we propose a novel drug-target interaction prediction algorithm, namely neighborhood regularized logistic matrix factorization (NRLMF). Specifically, the proposed NRLMF method focuses on modeling the probability that a drug would interact with a target by logistic matrix factorization, where the properties of drugs and targets are represented by drug-specific and target-specific latent vectors, respectively. Moreover, NRLMF assigns higher importance levels to positive observations (i.e., the observed interacting drug-target pairs) than negative observations (i.e., the unknown pairs). Because the positive observations are already experimentally verified, they are usually more trustworthy. Furthermore, the local structure of the drug-target interaction data has also been exploited via neighborhood regularization to achieve better prediction accuracy. We conducted extensive experiments over four benchmark datasets, and NRLMF demonstrated its effectiveness compared with five state-of-the-art approaches. '),
(87669, 2016, 'plos', 'Optimal Information Representation and Criticality in an Adaptive Sensory Recurrent Neuronal Network', 'Shriki, Oren|Yellin, Dovi', 'Department of Cognitive and Brain Sciences, Ben-Gurion University of the Negev, Beer-Sheva, Israel.|Department of Neurobiology, Weizmann Institute of Science, Rehovot, Israel.', 'Israel|Israel', 0, 'Computational Biology|Humans|Models, Neurological|Nerve Net|Visual Cortex', 'Journal Article', '10.1371/journal.pcbi.1004698', '26882372', 'Recurrent connections play an important role in cortical function, yet their exact contribution to the network computation remains unknown. The principles guiding the long-term evolution of these connections are poorly understood as well. Therefore, gaining insight into their computational role and into the mechanism shaping their pattern would be of great importance. To that end, we studied the learning dynamics and emergent recurrent connectivity in a sensory network model based on a first-principle information theoretic approach. As a test case, we applied this framework to a model of a hypercolumn in the visual cortex and found that the evolved connections between orientation columns have a Mexican hat profile, consistent with empirical data and previous modeling work. Furthermore, we found that optimal information representation is achieved when the network operates near a critical point in its dynamics. Neuronal networks working near such a phase transition are most sensitive to their inputs and are thus optimal in terms of information representation. Nevertheless, a mild change in the pattern of interactions may cause such networks to undergo a transition into a different regime of behavior in which the network activity is dominated by its internal recurrent dynamics and does not reflect the objective input. We discuss several mechanisms by which the pattern of interactions can be driven into this supercritical regime and relate them to various neurological and neuropsychiatric phenomena. '),
(87670, 2016, 'plos', 'Correction: Membrane Partitioning of Anionic, Ligand-Coated Nanoparticles Is Accompanied by Ligand Snorkeling, Local Disordering, and Cholesterol Depletion', 'PLOS Computational Biology Staff', 'Department of Neurobiology, Weizmann Institute of Science, Rehovot, Israel.', 'Israel', 0, '-', 'Published Erratum', '10.1371/journal.pcbi.1004769', '26886168', '-');
