INSERT INTO `papers` (`id`, `ano`, `journal`, `titulo`, `autores`, `afiliacao`, `pais`, `citacoes`, `palavra_chave`, `categorias`, `doi`, `pubmed`, `abstract`) VALUES
(84116, 2009, 'plos', 'Efficient network reconstruction from dynamical cascades identifies small-world topology of neuronal avalanches', 'Pajevic, Sinisa|Plenz, Dietmar', 'Division of Computational Bioscience, Mathematical and Statistical Computing Laboratory, Center for Information Technology, National Institutes of Health, Bethesda, Maryland, United States of America.|Division of Computational Bioscience, Mathematical and Statistical Computing Laboratory, Center for Information Technology, National Institutes of Health, Bethesda, Maryland, United States of America.', 'United States|United States', 73, 'Algorithms|Animals|Bayes Theorem|Cerebral Cortex|Computational Biology|Models, Neurological|Models, Statistical|Nerve Net|Neurons|Rats|Statistics, Nonparametric', 'Journal Article', '10.1371/journal.pcbi.1000271', '19180180', 'Cascading activity is commonly found in complex systems with directed interactions such as metabolic networks, neuronal networks, or disease spreading in social networks. Substantial insight into a systems organization can be obtained by reconstructing the underlying functional network architecture from the observed activity cascades. Here we focus on Bayesian approaches and reduce their computational demands by introducing the Iterative Bayesian (IB) and Posterior Weighted Averaging (PWA) methods. We introduce a special case of PWA, cast in nonparametric form, which we call the normalized count (NC) algorithm. NC efficiently reconstructs random and small-world functional network topologies and architectures from subcritical, critical, and supercritical cascading dynamics and yields significant improvements over commonly used correlation methods. With experimental data, NC identified a functional and structural small-world topology and its corresponding traffic in cortical networks with neuronal avalanche dynamics.'),
(84117, 2009, 'plos', 'Cohesive versus flexible evolution of functional modules in eukaryotes', 'Fokkens, Like|Snel, Berend', 'Theoretical Biology and Bioinformatics, Utrecht University, Utrecht, The Netherlands. l.fokkens@uu.nl|Theoretical Biology and Bioinformatics, Utrecht University, Utrecht, The Netherlands. l.fokkens@uu.nl', 'Netherlands|Netherlands', 11, 'Computational Biology|Databases, Protein|Eukaryotic Cells|Evolution, Molecular|Metabolic Networks and Pathways|Models, Genetic|Phylogeny|Proteins|Saccharomyces cerevisiae|Saccharomyces cerevisiae Proteins', 'Journal Article', '10.1371/journal.pcbi.1000276', '19180181', 'Although functionally related proteins can be reliably predicted from phylogenetic profiles, many functional modules do not seem to evolve cohesively according to case studies and systematic analyses in prokaryotes. In this study we quantify the extent of evolutionary cohesiveness of functional modules in eukaryotes and probe the biological and methodological factors influencing our estimates. We have collected various datasets of protein complexes and pathways in Saccheromyces cerevisiae. We define orthologous groups on 34 eukaryotic genomes and measure the extent of cohesive evolution of sets of orthologous groups of which members constitute a known complex or pathway. Within this framework it appears that most functional modules evolve flexibly rather than cohesively. Even after correcting for uncertain module definitions and potentially problematic orthologous groups, only 46% of pathways and complexes evolve more cohesively than random modules. This flexibility seems partly coupled to the nature of the functional module because biochemical pathways are generally more cohesively evolving than complexes.'),
(84118, 2009, 'plos', 'Precise regulation of gene expression dynamics favors complex promoter architectures', 'Müller, Dirk|Stelling, Jörg', 'Department of Biosystems Science and Engineering and Swiss Institute of Bioinformatics, ETH Zurich, Basel, Switzerland.|Department of Biosystems Science and Engineering and Swiss Institute of Bioinformatics, ETH Zurich, Basel, Switzerland.', 'Switzerland|Switzerland', 12, 'DNA, Fungal|Data Interpretation, Statistical|Fourier Analysis|Gene Expression Regulation, Fungal|Linear Models|Models, Genetic|Nonlinear Dynamics|Nucleic Acid Conformation|Promoter Regions, Genetic|Reproducibility of Results|Ribosomal Proteins|Saccharomyces cerevisiae|Saccharomyces cerevisiae Proteins|Transcription Factors', 'Journal Article', '10.1371/journal.pcbi.1000279', '19180182', 'Promoters process signals through recruitment of transcription factors and RNA polymerase, and dynamic changes in promoter activity constitute a major noise source in gene expression. However, it is barely understood how complex promoter architectures determine key features of promoter dynamics. Here, we employ prototypical promoters of yeast ribosomal protein genes as well as simplified versions thereof to analyze the relations among promoter design, complexity, and function. These promoters combine the action of a general regulatory factor with that of specific transcription factors, a common motif of many eukaryotic promoters. By comprehensively analyzing stationary and dynamic promoter properties, this model-based approach enables us to pinpoint the structural characteristics underlying the observed behavior. Functional tradeoffs impose constraints on the promoter architecture of ribosomal protein genes. We find that a stable scaffold in the natural design results in low transcriptional noise and strong co-regulation of target genes in the presence of gene silencing. This configuration also exhibits superior shut-off properties, and it can serve as a tunable switch in living cells. Model validation with independent experimental data suggests that the models are sufficiently realistic. When combined, our results offer a mechanistic explanation for why specific factors are associated with low protein noise in vivo. Many of these findings hold for a broad range of model parameters and likely apply to other eukaryotic promoters of similar structure.'),
(84119, 2009, 'plos', 'Prediction of protein-protein interaction sites in sequences and 3D structures by random forests', 'Sikixc4x87, Mile|Tomixc4x87, Sanja|Vlahovicek, Kristian', 'Department of Electronic Systems and Information Processing, Faculty of Electrical Engineering and Computing, University of Zagreb, Zagreb, Croatia. mile.sikic@fer.hr|Department of Electronic Systems and Information Processing, Faculty of Electrical Engineering and Computing, University of Zagreb, Zagreb, Croatia. mile.sikic@fer.hr|Department of Electronic Systems and Information Processing, Faculty of Electrical Engineering and Computing, University of Zagreb, Zagreb, Croatia. mile.sikic@fer.hr', 'Croatia|Croatia|Croatia', 126, 'Algorithms|Amino Acid Sequence|Area Under Curve|Artificial Intelligence|Databases, Protein|Entropy|Models, Molecular|Models, Statistical|Protein Conformation|Protein Interaction Domains and Motifs|Protein Interaction Mapping|Proteins|ROC Curve|Reproducibility of Results|raf Kinases|ras Proteins', 'Journal Article', '10.1371/journal.pcbi.1000278', '19180183', 'Identifying interaction sites in proteins provides important clues to the function of a protein and is becoming increasingly relevant in topics such as systems biology and drug discovery. Although there are numerous papers on the prediction of interaction sites using information derived from structure, there are only a few case reports on the prediction of interaction residues based solely on protein sequence. Here, a sliding window approach is combined with the Random Forests method to predict protein interaction sites using (i) a combination of sequence- and structure-derived parameters and (ii) sequence information alone. For sequence-based prediction we achieved a precision of 84% with a 26% recall and an F-measure of 40%. When combined with structural information, the prediction performance increases to a precision of 76% and a recall of 38% with an F-measure of 51%. We also present an attempt to rationalize the sliding window size and demonstrate that a nine-residue window is the most suitable for predictor construction. Finally, we demonstrate the applicability of our prediction methods by modeling the Ras-Raf complex using predicted interaction sites as target binding interfaces. Our results suggest that it is possible to predict protein interaction sites with quite a high accuracy using only sequence information.'),
(84120, 2009, 'plos', 'Social contact networks and disease eradicability under voluntary vaccination', 'Perisic, Ana|Bauch, Chris T', 'Department of Mathematics and Statistics, University of Guelph, Guelph, Ontario, Canada.|Department of Mathematics and Statistics, University of Guelph, Guelph, Ontario, Canada.', 'Canada|Canada', 106, 'Decision Theory|Disease Transmission, Infectious|Humans|Immunity, Herd|Immunization Programs|Interpersonal Relations|Logistic Models|Neural Networks (Computer)|Patient Compliance|Population Density|Refusal to Participate|Smallpox|Social Environment|Vaccination', 'Journal Article', '10.1371/journal.pcbi.1000280', '19197342', 'Certain theories suggest that it should be difficult or impossible to eradicate a vaccine-preventable disease under voluntary vaccination: Herd immunity implies that the individual incentive to vaccinate disappears at high coverage levels. Historically, there have been examples of declining coverage for vaccines, such as MMR vaccine and whole-cell pertussis vaccine, that are consistent with this theory. On the other hand, smallpox was globally eradicated by 1980 despite voluntary vaccination policies in many jurisdictions. Previous modeling studies of the interplay between disease dynamics and individual vaccinating behavior have assumed that infection is transmitted in a homogeneously mixing population. By comparison, here we simulate transmission of a vaccine-preventable SEIR infection through a random, static contact network. Individuals choose whether to vaccinate based on infection risks from neighbors, and based on vaccine risks. When neighborhood size is small, rational vaccinating behavior results in rapid containment of the infection through voluntary ring vaccination. As neighborhood size increases (while the average force of infection is held constant), a threshold is reached beyond which the infection can break through partially vaccinated rings, percolating through the whole population and resulting in considerable epidemic final sizes and a large number vaccinated. The former outcome represents convergence between individually and socially optimal outcomes, whereas the latter represents their divergence, as observed in most models of individual vaccinating behavior that assume homogeneous mixing. Similar effects are observed in an extended model using smallpox-specific natural history and transmissibility assumptions. This work illustrates the significant qualitative differences between behavior-infection dynamics in discrete contact-structured populations versus continuous unstructured populations. This work also shows how disease eradicability in populations where voluntary vaccination is the primary control mechanism may depend partly on whether the disease is transmissible only to a few close social contacts or to a larger subset of the population.'),
(84121, 2009, 'plos', 'Evidence for gene-specific rather than transcription rate-dependent histone H3 exchange in yeast coding regions', 'Gat-Viks, Irit|Vingron, Martin', 'Computational Molecular Biology Department, Max Planck Institute for Molecular Genetics, Berlin, Germany. gat-viks@molgen.mpg.de|Computational Molecular Biology Department, Max Planck Institute for Molecular Genetics, Berlin, Germany. gat-viks@molgen.mpg.de', 'Germany|Germany', 13, 'Cell Cycle Proteins|Chromatin Assembly and Disassembly|DNA Repair|DNA Replication|Epigenesis, Genetic|Genome, Fungal|Histones|Molecular Chaperones|Open Reading Frames|Protein Processing, Post-Translational|Saccharomyces cerevisiae|Saccharomyces cerevisiae Proteins|Transcription, Genetic', 'Journal Article', '10.1371/journal.pcbi.1000282', '19197343', 'In eukaryotic organisms, histones are dynamically exchanged independently of DNA replication. Recent reports show that different coding regions differ in their amount of replication-independent histone H3 exchange. The current paradigm is that this histone exchange variability among coding regions is a consequence of transcription rate. Here we put forward the idea that this variability might be also modulated in a gene-specific manner independently of transcription rate. To that end, we study transcription rate-independent replication-independent coding region histone H3 exchange. We term such events relative exchange. Our genome-wide analysis shows conclusively that in yeast, relative exchange is a novel consistent feature of coding regions. Outside of replication, each coding region has a characteristic pattern of histone H3 exchange that is either higher or lower than what was expected by its RNAPII transcription rate alone. Histone H3 exchange in coding regions might be a way to add or remove certain histone modifications that are important for transcription elongation. Therefore, our results that gene-specific coding region histone H3 exchange is decoupled from transcription rate might hint at a new epigenetic mechanism of transcription regulation.'),
(84122, 2009, 'plos', 'Computational fitness landscape for all gene-order permutations of an RNA virus', 'Lim, Kwang-il|Yin, John', 'Department of Chemical and Biological Engineering, University of Wisconsin Madison, Madison, WI, USA.|Department of Chemical and Biological Engineering, University of Wisconsin Madison, Madison, WI, USA.', 'United States|United States', 6, 'Animals|Cell Line|Cells|Computational Biology|Cricetinae|Gene Deletion|Gene Order|Genes, Essential|Host-Pathogen Interactions|Transcription, Genetic|Translocation, Genetic|Vesiculovirus|Virus Replication', 'Journal Article', '10.1371/journal.pcbi.1000283', '19197345', 'How does the growth of a virus depend on the linear arrangement of genes in its genome? Answering this question may enhance our basic understanding of virus evolution and advance applications of viruses as live attenuated vaccines, gene-therapy vectors, or anti-tumor therapeutics. We used a mathematical model for vesicular stomatitis virus (VSV), a prototype RNA virus that encodes five genes (N-P-M-G-L), to simulate the intracellular growth of all 120 possible gene-order variants. Simulated yields of virus infection varied by 6,000-fold and were found to be most sensitive to gene-order permutations that increased levels of the L gene transcript or reduced levels of the N gene transcript, the lowest and highest expressed genes of the wild-type virus, respectively. Effects of gene order on virus growth also depended upon the host-cell environment, reflecting different resources for protein synthesis and different cell susceptibilities to infection. Moreover, by computationally deleting intergenic attenuations, which define a key mechanism of transcriptional regulation in VSV, the variation in growth associated with the 120 gene-order variants was drastically narrowed from 6,000- to 20-fold, and many variants produced higher progeny yields than wild-type. These results suggest that regulation by intergenic attenuation preceded or co-evolved with the fixation of the wild type gene order in the evolution of VSV. In summary, our models have begun to reveal how gene functions, gene regulation, and genomic organization of viruses interact with their host environments to define processes of viral growth and evolution.'),
(84123, 2009, 'plos', 'Predicting peptide structures in native proteins from physical simulations of fragments', 'Voelz, Vincent A|Shell, M Scott|Dill, Ken A', 'Department of Chemistry, Stanford University, Stanford, CA, USA. vvoelz@stanford.edu|Department of Chemistry, Stanford University, Stanford, CA, USA. vvoelz@stanford.edu|Department of Chemistry, Stanford University, Stanford, CA, USA. vvoelz@stanford.edu', 'United States|United States|United States', 25, 'Artificial Intelligence|Bayes Theorem|Computer Simulation|Logistic Models|Models, Chemical|Models, Molecular|Protein Conformation|Protein Folding|Proteins|Proteomics|Solvents|Thermodynamics|Water|Weights and Measures', 'Journal Article', '10.1371/journal.pcbi.1000281', '19197352', 'It has long been proposed that much of the information encoding how a protein folds is contained locally in the peptide chain. Here we present a large-scale simulation study designed to examine the extent to which conformations of peptide fragments in water predict native conformations in proteins. We perform replica exchange molecular dynamics (REMD) simulations of 872 8-mer, 12-mer, and 16-mer peptide fragments from 13 proteins using the AMBER 96 force field and the OBC implicit solvent model. To analyze the simulations, we compute various contact-based metrics, such as contact probability, and then apply Bayesian classifier methods to infer which metastable contacts are likely to be native vs. non-native. We find that a simple measure, the observed contact probability, is largely more predictive of a peptides native structure in the protein than combinations of metrics or multi-body components. Our best classification model is a logistic regression model that can achieve up to 63% correct classifications for 8-mers, 71% for 12-mers, and 76% for 16-mers. We validate these results on fragments of a protein outside our training set. We conclude that local structure provides information to solve some but not all of the conformational search problem. These results help improve our understanding of folding mechanisms, and have implications for improving physics-based conformational sampling and structure prediction using all-atom molecular simulations.'),
(84124, 2009, 'plos', 'Stochastically gating ion channels enable patterned spike firing through activity-dependent modulation of spike probability', 'Dudman, Joshua T|Nolan, Matthew F', 'Janelia Farm Research Campus, Howard Hughes Medical Institute, Ashburn, Virginia, United States of America. dudmanj@janelia.hhmi.org|Janelia Farm Research Campus, Howard Hughes Medical Institute, Ashburn, Virginia, United States of America. dudmanj@janelia.hhmi.org', 'United States|United States', 26, 'Action Potentials|Animals|Cyclic Nucleotide-Gated Cation Channels|Entorhinal Cortex|Humans|Hyperpolarization-Activated Cyclic Nucleotide-Gated Channels|Ion Channel Gating|Ion Transport|Models, Neurological|Neural Conduction|Potassium Channels|Stochastic Processes|Synaptic Transmission', 'Journal Article', '10.1371/journal.pcbi.1000290', '19214199', 'The transformation of synaptic input into patterns of spike output is a fundamental operation that is determined by the particular complement of ion channels that a neuron expresses. Although it is well established that individual ion channel proteins make stochastic transitions between conducting and non-conducting states, most models of synaptic integration are deterministic, and relatively little is known about the functional consequences of interactions between stochastically gating ion channels. Here, we show that a model of stellate neurons from layer II of the medial entorhinal cortex implemented with either stochastic or deterministically gating ion channels can reproduce the resting membrane properties of stellate neurons, but only the stochastic version of the model can fully account for perithreshold membrane potential fluctuations and clustered patterns of spike output that are recorded from stellate neurons during depolarized states. We demonstrate that the stochastic model implements an example of a general mechanism for patterning of neuronal output through activity-dependent changes in the probability of spike firing. Unlike deterministic mechanisms that generate spike patterns through slow changes in the state of model parameters, this general stochastic mechanism does not require retention of information beyond the duration of a single spike and its associated afterhyperpolarization. Instead, clustered patterns of spikes emerge in the stochastic model of stellate neurons as a result of a transient increase in firing probability driven by activation of HCN channels during recovery from the spike afterhyperpolarization. Using this model, we infer conditions in which stochastic ion channel gating may influence firing patterns in vivo and predict consequences of modifications of HCN channel function for in vivo firing patterns.'),
(84125, 2009, 'plos', 'Statistical dynamics of flowing red blood cells by morphological image processing', 'Higgins, John M|Eddington, David T|Bhatia, Sangeeta N|Mahadevan, L', 'School of Engineering and Applied Sciences, Harvard University, Cambridge, Massachusetts, United States of America.|School of Engineering and Applied Sciences, Harvard University, Cambridge, Massachusetts, United States of America.|School of Engineering and Applied Sciences, Harvard University, Cambridge, Massachusetts, United States of America.|School of Engineering and Applied Sciences, Harvard University, Cambridge, Massachusetts, United States of America.', 'United States|United States|United States|United States', 43, 'Artificial Intelligence|Blood Flow Velocity|Blood Viscosity|Data Interpretation, Statistical|Erythrocyte Aggregation|Erythrocytes|Erythrocytes, Abnormal|Humans|Image Processing, Computer-Assisted|Microfluidics|Motion|Suspensions', 'Journal Article', '10.1371/journal.pcbi.1000288', '19214200', 'Blood is a dense suspension of soft non-Brownian cells of unique importance. Physiological blood flow involves complex interactions of blood cells with each other and with the environment due to the combined effects of varying cell concentration, cell morphology, cell rheology, and confinement. We analyze these interactions using computational morphological image analysis and machine learning algorithms to quantify the non-equilibrium fluctuations of cellular velocities in a minimal, quasi-two-dimensional microfluidic setting that enables high-resolution spatio-temporal measurements of blood cell flow. In particular, we measure the effective hydrodynamic diffusivity of blood cells and analyze its relationship to macroscopic properties such as bulk flow velocity and density. We also use the effective suspension temperature to distinguish the flow of normal red blood cells and pathological sickled red blood cells and suggest that this temperature may help to characterize the propensity for stasis in Virchows Triad of blood clotting and thrombosis.'),
(84126, 2009, 'plos', 'Can monkeys choose optimally when faced with noisy stimuli and unequal rewards?', 'Feng, Samuel|Holmes, Philip|Rorie, Alan|Newsome, William T', 'Program in Applied and Computational Mathematics, Princeton University, Princeton, New Jersey, United States of America.|Program in Applied and Computational Mathematics, Princeton University, Princeton, New Jersey, United States of America.|Program in Applied and Computational Mathematics, Princeton University, Princeton, New Jersey, United States of America.|Program in Applied and Computational Mathematics, Princeton University, Princeton, New Jersey, United States of America.', 'Jersey|Jersey|Jersey|Jersey', 0, 'Animals|Choice Behavior|Cues|Decision Theory|Higher Nervous Activity|Macaca mulatta|Male|Models, Psychological|Movement|Photic Stimulation|Psychometrics|Reward|Task Performance and Analysis', 'Journal Article', '10.1371/journal.pcbi.1000284', '19214201', 'We review the leaky competing accumulator model for two-alternative forced-choice decisions with cued responses, and propose extensions to account for the influence of unequal rewards. Assuming that stimulus information is integrated until the cue to respond arrives and that firing rates of stimulus-selective neurons remain well within physiological bounds, the model reduces to an Ornstein-Uhlenbeck (OU) process that yields explicit expressions for the psychometric function that describes accuracy. From these we compute strategies that optimize the rewards expected over blocks of trials administered with mixed difficulty and reward contingencies. The psychometric function is characterized by two parameters: its midpoint slope, which quantifies a subjects ability to extract signal from noise, and its shift, which measures the bias applied to account for unequal rewards. We fit these to data from two monkeys performing the moving dots task with mixed coherences and reward schedules. We find that their behaviors averaged over multiple sessions are close to optimal, with shifts erring in the direction of smaller penalties. We propose two methods for biasing the OU process to produce such shifts.'),
(84127, 2009, 'plos', 'A genome-scale metabolic reconstruction of Mycoplasma genitalium, iPS189', 'Suthers, Patrick F|Dasika, Madhukar S|Kumar, Vinay Satish|Denisov, Gennady|Glass, John I|Maranas, Costas D', 'Department of Chemical Engineering, The Pennsylvania State University, University Park, Pennsylvania, United States of America.|Department of Chemical Engineering, The Pennsylvania State University, University Park, Pennsylvania, United States of America.|Department of Chemical Engineering, The Pennsylvania State University, University Park, Pennsylvania, United States of America.|Department of Chemical Engineering, The Pennsylvania State University, University Park, Pennsylvania, United States of America.|Department of Chemical Engineering, The Pennsylvania State University, University Park, Pennsylvania, United States of America.|Department of Chemical Engineering, The Pennsylvania State University, University Park, Pennsylvania, United States of America.', 'United States|United States|United States|United States|United States|United States', 0, 'Genes, Essential|Genome, Bacterial|Metabolome|Metabolomics|Models, Biological|Mycoplasma genitalium|Nutrigenomics', 'Journal Article', '10.1371/journal.pcbi.1000285', '19214212', 'With a genome size of approximately 580 kb and approximately 480 protein coding regions, Mycoplasma genitalium is one of the smallest known self-replicating organisms and, additionally, has extremely fastidious nutrient requirements. The reduced genomic content of M. genitalium has led researchers to suggest that the molecular assembly contained in this organism may be a close approximation to the minimal set of genes required for bacterial growth. Here, we introduce a systematic approach for the construction and curation of a genome-scale in silico metabolic model for M. genitalium. Key challenges included estimation of biomass composition, handling of enzymes with broad specificities, and the lack of a defined medium. Computational tools were subsequently employed to identify and resolve connectivity gaps in the model as well as growth prediction inconsistencies with gene essentiality experimental data. The curated model, M. genitalium iPS189 (262 reactions, 274 metabolites), is 87% accurate in recapitulating in vivo gene essentiality results for M. genitalium. Approaches and tools described herein provide a roadmap for the automated construction of in silico metabolic models of other organisms.'),
(84128, 2009, 'plos', 'Accurate path integration in continuous attractor network models of grid cells', 'Burak, Yoram|Fiete, Ila R', 'Center for Brain Science, Harvard University, Cambridge, Massachusetts, United States of America. yburak@fas.harvard.edu|Center for Brain Science, Harvard University, Cambridge, Massachusetts, United States of America. yburak@fas.harvard.edu', 'United States|United States', 319, 'Action Potentials|Animals|Entorhinal Cortex|Models, Neurological|Motion Perception|Nerve Net|Neural Networks (Computer)|Neural Pathways|Nonlinear Dynamics|Rats|Space Perception|Systems Integration|Time Factors', 'Journal Article', '10.1371/journal.pcbi.1000291', '19229307', 'Grid cells in the rat entorhinal cortex display strikingly regular firing responses to the animals position in 2-D space and have been hypothesized to form the neural substrate for dead-reckoning. However, errors accumulate rapidly when velocity inputs are integrated in existing models of grid cell activity. To produce grid-cell-like responses, these models would require frequent resets triggered by external sensory cues. Such inadequacies, shared by various models, cast doubt on the dead-reckoning potential of the grid cell system. Here we focus on the question of accurate path integration, specifically in continuous attractor models of grid cell activity. We show, in contrast to previous models, that continuous attractor models can generate regular triangular grid responses, based on inputs that encode only the rats velocity and heading direction. We consider the role of the network boundary in the integration performance of the network and show that both periodic and aperiodic networks are capable of accurate path integration, despite important differences in their attractor manifolds. We quantify the rate at which errors in the velocity integration accumulate as a function of network size and intrinsic noise within the network. With a plausible range of parameters and the inclusion of spike variability, our model networks can accurately integrate velocity inputs over a maximum of approximately 10-100 meters and approximately 1-10 minutes. These findings form a proof-of-concept that continuous attractor dynamics may underlie velocity integration in the dorsolateral medial entorhinal cortex. The simulations also generate pertinent upper bounds on the accuracy of integration that may be achieved by continuous attractor dynamics in the grid cell network. We suggest experiments to test the continuous attractor model and differentiate it from models in which single cells establish their responses independently of each other.'),
(84129, 2009, 'plos', 'Conformational changes and slow dynamics through microsecond polarized atomistic molecular simulation of an integral Kv12 ion channel', 'Bjelkmar, Pär|Niemelä, Perttu S|Vattulainen, Ilpo|Lindahl, Erik', 'Center for Biomembrane Research & Stockholm Bioinformatics Center, Department of Biochemistry & Biophysics, Stockholm University, Stockholm, Sweden.|Center for Biomembrane Research & Stockholm Bioinformatics Center, Department of Biochemistry & Biophysics, Stockholm University, Stockholm, Sweden.|Center for Biomembrane Research & Stockholm Bioinformatics Center, Department of Biochemistry & Biophysics, Stockholm University, Stockholm, Sweden.|Center for Biomembrane Research & Stockholm Bioinformatics Center, Department of Biochemistry & Biophysics, Stockholm University, Stockholm, Sweden.', 'Sweden|Sweden|Sweden|Sweden', 92, 'Amino Acid Motifs|Computer Simulation|Energy Transfer|Hydrogen Bonding|Ion Channel Gating|Kv1.2 Potassium Channel|Membrane Lipids|Membrane Potentials|Models, Molecular|Static Electricity|Structure-Activity Relationship|Thermodynamics', 'Journal Article', '10.1371/journal.pcbi.1000289', '19229308', 'Structure and dynamics of voltage-gated ion channels, in particular the motion of the S4 helix, is a highly interesting and hotly debated topic in current membrane protein research. It has critical implications for insertion and stabilization of membrane proteins as well as for finding how transitions occur in membrane proteins-not to mention numerous applications in drug design. Here, we present a full 1 micros atomic-detail molecular dynamics simulation of an integral Kv1.2 ion channel, comprising 120,000 atoms. By applying 0.052 V/nm of hyperpolarization, we observe structural rearrangements, including up to 120 degrees rotation of the S4 segment, changes in hydrogen-bonding patterns, but only low amounts of translation. A smaller rotation ( approximately 35 degrees ) of the extracellular end of all S4 segments is present also in a reference 0.5 micros simulation without applied field, which indicates that the crystal structure might be slightly different from the natural state of the voltage sensor. The conformation change upon hyperpolarization is closely coupled to an increase in 3(10) helix contents in S4, starting from the intracellular side. This could support a model for transition from the crystal structure where the hyperpolarization destabilizes S4-lipid hydrogen bonds, which leads to the helix rotating to keep the arginine side chains away from the hydrophobic phase, and the driving force for final relaxation by downward translation is partly entropic, which would explain the slow process. The coordinates of the transmembrane part of the simulated channel actually stay closer to the recently determined higher-resolution Kv1.2 chimera channel than the starting structure for the entire second half of the simulation (0.5-1 micros). Together with lipids binding in matching positions and significant thinning of the membrane also observed in experiments, this provides additional support for the predictive power of microsecond-scale membrane protein simulations.'),
(84130, 2009, 'plos', 'The temporal winner-take-all readout', 'Shamir, Maoz', 'Department of Physiology and the Zlotowski Center for Neuroscience, Ben-Gurion University of the Negev, Beer-Sheva, Israel. shmaoz@bgu.ac.il', 'Israel', 0, 'Action Potentials|Models, Neurological|Models, Statistical|Nerve Net|Neural Networks (Computer)|Nonlinear Dynamics|Synaptic Transmission', 'Journal Article', '10.1371/journal.pcbi.1000286', '19229309', 'How can the central nervous system make accurate decisions about external stimuli at short times on the basis of the noisy responses of nerve cell populations? It has been suggested that spike time latency is the source of fast decisions. Here, we propose a simple and fast readout mechanism, the temporal Winner-Take-All (tWTA), and undertake a study of its accuracy. The tWTA is studied in the framework of a statistical model for the dynamic response of a nerve cell population to an external stimulus. Each cell is characterized by a preferred stimulus, a unique value of the external stimulus for which it responds fastest. The tWTA estimate for the stimulus is the preferred stimulus of the cell that fired the first spike in the entire population. We then pose the questions: How accurate is the tWTA readout? What are the parameters that govern this accuracy? What are the effects of noise correlations and baseline firing? We find that tWTA sensitivity to the stimulus grows algebraically fast with the number of cells in the population, N, in contrast to the logarithmic slow scaling of the conventional rate-WTA sensitivity with N. Noise correlations in first-spike times of different cells can limit the accuracy of the tWTA readout, even in the limit of large N, similar to the effect that has been observed in population coding theory. We show that baseline firing also has a detrimental effect on tWTA accuracy. We suggest a generalization of the tWTA, the n-tWTA, which estimates the stimulus by the identity of the group of cells firing the first n spikes and show how this simple generalization can overcome the detrimental effect of baseline firing. Thus, the tWTA can provide fast and accurate responses discriminating between a small number of alternatives. High accuracy in estimation of a continuous stimulus can be obtained using the n-tWTA.'),
(84131, 2009, 'plos', 'Identification of potential pathway mediation targets in Toll-like receptor signaling', 'Li, Fan|Thiele, Ines|Jamshidi, Neema|Palsson, Bernhard Ø', 'Department of Bioengineering, University of California San Diego, La Jolla, California, United States of America.|Department of Bioengineering, University of California San Diego, La Jolla, California, United States of America.|Department of Bioengineering, University of California San Diego, La Jolla, California, United States of America.|Department of Bioengineering, University of California San Diego, La Jolla, California, United States of America.', 'United States|United States|United States|United States', 0, 'Cell Compartmentation|Feedback, Physiological|Humans|Models, Biological|Phosphorylation|Proteome|Signal Transduction|Toll-Like Receptors', 'Journal Article', '10.1371/journal.pcbi.1000292', '19229310', 'Recent advances in reconstruction and analytical methods for signaling networks have spurred the development of large-scale models that incorporate fully functional and biologically relevant features. An extended reconstruction of the human Toll-like receptor signaling network is presented herein. This reconstruction contains an extensive complement of kinases, phosphatases, and other associated proteins that mediate the signaling cascade along with a delineation of their associated chemical reactions. A computational framework based on the methods of large-scale convex analysis was developed and applied to this network to characterize input-output relationships. The input-output relationships enabled significant modularization of the network into ten pathways. The analysis identified potential candidates for inhibitory mediation of TLR signaling with respect to their specificity and potency. Subsequently, we were able to identify eight novel inhibition targets through constraint-based modeling methods. The results of this study are expected to yield meaningful avenues for further research in the task of mediating the Toll-like receptor signaling network and its effects.'),
(84132, 2009, 'plos', 'Allosteric communication occurs via networks of tertiary and quaternary motions in proteins', 'Daily, Michael D|Gray, Jeffrey J', 'Program in Molecular & Computational Biophysics, Johns Hopkins University, Baltimore, Maryland, United States of America.|Program in Molecular & Computational Biophysics, Johns Hopkins University, Baltimore, Maryland, United States of America.', 'United States|United States', 76, 'Allosteric Regulation|Binding Sites|Databases, Protein|Models, Chemical|Models, Molecular|Motion|Nonlinear Dynamics|Protein Interaction Mapping|Protein Structure, Quaternary|Protein Structure, Tertiary|Proteins|Structure-Activity Relationship|Thermodynamics', 'Journal Article', '10.1371/journal.pcbi.1000293', '19229311', 'Allosteric proteins bind an effector molecule at one site resulting in a functional change at a second site. We hypothesize that allosteric communication in proteins relies upon networks of quaternary (collective, rigid-body) and tertiary (residue-residue contact) motions. We argue that cyclic topology of these networks is necessary for allosteric communication. An automated algorithm identifies rigid bodies from the displacement between the inactive and the active structures and constructs quaternary networks from these rigid bodies and the substrate and effector ligands. We then integrate quaternary networks with a coarse-grained representation of contact rearrangements to form global communication networks (GCNs). The GCN reveals allosteric communication among all substrate and effector sites in 15 of 18 multidomain and multimeric proteins, while tertiary and quaternary networks exhibit such communication in only 4 and 3 of these proteins, respectively. Furthermore, in 7 of the 15 proteins connected by the GCN, 50% or more of the substrate-effector paths via the GCN are interdependent paths that do not exist via either the tertiary or the quaternary network. Substrate-effector pathways typically are not linear but rather consist of polycyclic networks of rigid bodies and clusters of rearranging residue contacts. These results argue for broad applicability of allosteric communication based on structural changes and demonstrate the utility of the GCN. Global communication networks may inform a variety of experiments on allosteric proteins as well as the design of allostery into non-allosteric proteins.'),
(84133, 2009, 'plos', 'Signaling logic of activity-triggered dendritic protein synthesis: an mTOR gate but not a feedback switch', 'Jain, Pragati|Bhalla, Upinder S', 'National Centre for Biological Sciences, Tata Institute of Fundamental Research, Bangalore, India.|National Centre for Biological Sciences, Tata Institute of Fundamental Research, Bangalore, India.', 'India|India', 0, 'Animals|Brain-Derived Neurotrophic Factor|Calcium|Dendrites|Mice|Mice, Knockout|Mitogen-Activated Protein Kinases|Nerve Tissue Proteins|Protein Kinases|Signal Transduction|TOR Serine-Threonine Kinases', 'Journal Article', '10.1371/journal.pcbi.1000287', '19242559', 'Changes in synaptic efficacy are believed to form the cellular basis for memory. Protein synthesis in dendrites is needed to consolidate long-term synaptic changes. Many signals converge to regulate dendritic protein synthesis, including synaptic and cellular activity, and growth factors. The coordination of these multiple inputs is especially intriguing because the synthetic and control pathways themselves are among the synthesized proteins. We have modeled this system to study its molecular logic and to understand how runaway feedback is avoided. We show that growth factors such as brain-derived neurotrophic factor (BDNF) gate activity-triggered protein synthesis via mammalian target of rapamycin (mTOR). We also show that bistability is unlikely to arise from the major protein synthesis pathways in our model, even though these include several positive feedback loops. We propose that these gating and stability properties may serve to suppress runaway activation of the pathway, while preserving the key role of responsiveness to multiple sources of input.'),
(84134, 2009, 'plos', 'Agent-based model of therapeutic adipose-derived stromal cell trafficking during ischemia predicts ability to roll on P-selectin', 'Bailey, Alexander M|Lawrence, Michael B|Shang, Hulan|Katz, Adam J|Peirce, Shayn M', 'Department of Biomedical Engineering, University of Virginia, Charlottesville, Virginia, USA.|Department of Biomedical Engineering, University of Virginia, Charlottesville, Virginia, USA.|Department of Biomedical Engineering, University of Virginia, Charlottesville, Virginia, USA.|Department of Biomedical Engineering, University of Virginia, Charlottesville, Virginia, USA.|Department of Biomedical Engineering, University of Virginia, Charlottesville, Virginia, USA.', 'United States|United States|United States|United States|United States', 44, 'Adipose Tissue|Cell Movement|Cell Transplantation|Humans|Ischemia|Models, Biological|P-Selectin|Stromal Cells', 'Journal Article', '10.1371/journal.pcbi.1000294', '19247427', 'Intravenous delivery of human adipose-derived stromal cells (hASCs) is a promising option for the treatment of ischemia. After delivery, hASCs that reside and persist in the injured extravascular space have been shown to aid recovery of tissue perfusion and function, although low rates of incorporation currently limit the safety and efficacy of these therapies. We submit that a better understanding of the trafficking of therapeutic hASCs through the microcirculation is needed to address this and that selective control over their homing (organ- and injury-specific) may be possible by targeting bottlenecks in the homing process. This process, however, is incredibly complex, which merited the use of computational techniques to speed the rate of discovery. We developed a multicell agent-based model (ABM) of hASC trafficking during acute skeletal muscle ischemia, based on over 150 literature-based rules instituted in Netlogo and MatLab software programs. In silico, trafficking phenomena within cell populations emerged as a result of the dynamic interactions between adhesion molecule expression, chemokine secretion, integrin affinity states, hemodynamics and microvascular network architectures. As verification, the model reasonably reproduced key aspects of ischemia and trafficking behavior including increases in wall shear stress, upregulation of key cellular adhesion molecules expressed on injured endothelium, increased secretion of inflammatory chemokines and cytokines, quantified levels of monocyte extravasation in selectin knockouts, and circulating monocyte rolling distances. Successful ABM verification prompted us to conduct a series of systematic knockouts in silico aimed at identifying the most critical parameters mediating hASC trafficking. Simulations predicted the necessity of an unknown selectin-binding molecule to achieve hASC extravasation, in addition to any rolling behavior mediated by hASC surface expression of CD15s, CD34, CD62e, CD62p, or CD65. In vitro experiments confirmed this prediction, a subpopulation of hASCs slowly rolled on immobilized P-selectin at speeds as low as 2 microm/s. Thus, our work led to a fundamentally new understanding of hASC biology, which may have important therapeutic implications.'),
(84135, 2009, 'plos', 'Effects of ploidy and recombination on evolution of robustness in a model of the segment polarity network', 'Kim, Kerry J|Fernandes, Vilaiwan M', 'Center for Cell Dynamics, Friday Harbor Labs, University of Washington, Friday Harbor, Washington, USA. kjkim@u.washington.edu|Center for Cell Dynamics, Friday Harbor Labs, University of Washington, Friday Harbor, Washington, USA. kjkim@u.washington.edu', 'United States|United States', 0, 'Animals|Founder Effect|Genetics, Population|Mutation|Ploidies|Recombination, Genetic', 'Journal Article', '10.1371/journal.pcbi.1000296', '19247428', 'Many genetic networks are astonishingly robust to quantitative variation, allowing these networks to continue functioning in the face of mutation and environmental perturbation. However, the evolution of such robustness remains poorly understood for real genetic networks. Here we explore whether and how ploidy and recombination affect the evolution of robustness in a detailed computational model of the segment polarity network. We introduce a novel computational method that predicts the quantitative values of biochemical parameters from bit sequences representing genotype, allowing our model to bridge genotype to phenotype. Using this, we simulate 2,000 generations of evolution in a population of individuals under stabilizing and truncation selection, selecting for individuals that could sharpen the initial pattern of engrailed and wingless expression. Robustness was measured by simulating a mutation in the network and measuring the effect on the engrailed and wingless patterns, higher robustness corresponded to insensitivity of this pattern to perturbation. We compared robustness in diploid and haploid populations, with either asexual or sexual reproduction. In all cases, robustness increased, and the greatest increase was in diploid sexual populations, diploidy and sex synergized to evolve greater robustness than either acting alone. Diploidy conferred increased robustness by allowing most deleterious mutations to be rescued by a working allele. Sex (recombination) conferred a robustness advantage through survival of the compatible: those alleles that can work with a wide variety of genetically diverse partners persist, and this selects for robust alleles.');
INSERT INTO `papers` (`id`, `ano`, `journal`, `titulo`, `autores`, `afiliacao`, `pais`, `citacoes`, `palavra_chave`, `categorias`, `doi`, `pubmed`, `abstract`) VALUES
(84136, 2009, 'plos', 'Rapid sampling of molecular motions with prior information constraints', 'Raveh, Barak|Enosh, Angela|Schueler-Furman, Ora|Halperin, Dan', 'Department of Molecular Genetics and Biotechnology, Institute of Medical Research, Hadassah Medical School, The Hebrew University, Jerusalem, Israel.|Department of Molecular Genetics and Biotechnology, Institute of Medical Research, Hadassah Medical School, The Hebrew University, Jerusalem, Israel.|Department of Molecular Genetics and Biotechnology, Institute of Medical Research, Hadassah Medical School, The Hebrew University, Jerusalem, Israel.|Department of Molecular Genetics and Biotechnology, Institute of Medical Research, Hadassah Medical School, The Hebrew University, Jerusalem, Israel.', 'Israel|Israel|Israel|Israel', 55, 'Protein Conformation|Proteins|Software', 'Journal Article', '10.1371/journal.pcbi.1000295', '19247429', 'Proteins are active, flexible machines that perform a range of different functions. Innovative experimental approaches may now provide limited partial information about conformational changes along motion pathways of proteins. There is therefore a need for computational approaches that can efficiently incorporate prior information into motion prediction schemes. In this paper, we present PathRover, a general setup designed for the integration of prior information into the motion planning algorithm of rapidly exploring random trees (RRT). Each suggested motion pathway comprises a sequence of low-energy clash-free conformations that satisfy an arbitrary number of prior information constraints. These constraints can be derived from experimental data or from expert intuition about the motion. The incorporation of prior information is very straightforward and significantly narrows down the vast search in the typically high-dimensional conformational space, leading to dramatic reduction in running time. To allow the use of state-of-the-art energy functions and conformational sampling, we have integrated this framework into Rosetta, an accurate protocol for diverse types of structural modeling. The suggested framework can serve as an effective complementary tool for molecular dynamics, Normal Mode Analysis, and other prevalent techniques for predicting motion in proteins. We applied our framework to three different model systems. We show that a limited set of experimentally motivated constraints may effectively bias the simulations toward diverse predicates in an outright fashion, from distance constraints to enforcement of loop closure. In particular, our analysis sheds light on mechanisms of protein domain swapping and on the role of different residues in the motion.'),
(84137, 2009, 'plos', 'Steady-state kinetic modeling constrains cellular resting states and dynamic behavior', 'Purvis, Jeremy E|Radhakrishnan, Ravi|Diamond, Scott L', 'Institute for Medicine and Engineering, University of Pennsylvania, Philadelphia, Pennsylvania, United States of America.|Institute for Medicine and Engineering, University of Pennsylvania, Philadelphia, Pennsylvania, United States of America.|Institute for Medicine and Engineering, University of Pennsylvania, Philadelphia, Pennsylvania, United States of America.', 'United States|United States|United States', 15, 'Kinetics|Models, Biological', 'Journal Article', '10.1371/journal.pcbi.1000298', '19266013', 'A defining characteristic of living cells is the ability to respond dynamically to external stimuli while maintaining homeostasis under resting conditions. Capturing both of these features in a single kinetic model is difficult because the model must be able to reproduce both behaviors using the same set of molecular components. Here, we show how combining small, well-defined steady-state networks provides an efficient means of constructing large-scale kinetic models that exhibit realistic resting and dynamic behaviors. By requiring each kinetic module to be homeostatic (at steady state under resting conditions), the method proceeds by (i) computing steady-state solutions to a system of ordinary differential equations for each module, (ii) applying principal component analysis to each set of solutions to capture the steady-state solution space of each module network, and (iii) combining optimal search directions from all modules to form a global steady-state space that is searched for accurate simulation of the time-dependent behavior of the whole system upon perturbation. Importantly, this stepwise approach retains the nonlinear rate expressions that govern each reaction in the system and enforces constraints on the range of allowable concentration states for the full-scale model. These constraints not only reduce the computational cost of fitting experimental time-series data but can also provide insight into limitations on system concentrations and architecture. To demonstrate application of the method, we show how small kinetic perturbations in a modular model of platelet P2Y(1) signaling can cause widespread compensatory effects on cellular resting states.'),
(84138, 2009, 'plos', 'Alu exonization events reveal features required for precise recognition of exons by the splicing machinery', 'Schwartz, Schraga|Gal-Mark, Nurit|Kfir, Nir|Oren, Ram|Kim, Eddo|Ast, Gil', 'Department of Human Molecular Genetics and Biochemistry, Sackler Faculty of Medicine, Tel-Aviv University, Tel Aviv, Israel.|Department of Human Molecular Genetics and Biochemistry, Sackler Faculty of Medicine, Tel-Aviv University, Tel Aviv, Israel.|Department of Human Molecular Genetics and Biochemistry, Sackler Faculty of Medicine, Tel-Aviv University, Tel Aviv, Israel.|Department of Human Molecular Genetics and Biochemistry, Sackler Faculty of Medicine, Tel-Aviv University, Tel Aviv, Israel.|Department of Human Molecular Genetics and Biochemistry, Sackler Faculty of Medicine, Tel-Aviv University, Tel Aviv, Israel.|Department of Human Molecular Genetics and Biochemistry, Sackler Faculty of Medicine, Tel-Aviv University, Tel Aviv, Israel.', 'Israel|Israel|Israel|Israel|Israel|Israel', 0, 'Alu Elements|Enhancer Elements, Genetic|Exons|Introns|Nucleic Acid Conformation|RNA Splicing|Spliceosomes', 'Journal Article', '10.1371/journal.pcbi.1000300', '19266014', 'Despite decades of research, the question of how the mRNA splicing machinery precisely identifies short exonic islands within the vast intronic oceans remains to a large extent obscure. In this study, we analyzed Alu exonization events, aiming to understand the requirements for correct selection of exons. Comparison of exonizing Alus to their non-exonizing counterparts is informative because Alus in these two groups have retained high sequence similarity but are perceived differently by the splicing machinery. We identified and characterized numerous features used by the splicing machinery to discriminate between Alu exons and their non-exonizing counterparts. Of these, the most novel is secondary structure: Alu exons in general and their 5 splice sites (5ss) in particular are characterized by decreased stability of local secondary structures with respect to their non-exonizing counterparts. We detected numerous further differences between Alu exons and their non-exonizing counterparts, among others in terms of exon-intron architecture and strength of splicing signals, enhancers, and silencers. Support vector machine analysis revealed that these features allow a high level of discrimination (AUC = 0.91) between exonizing and non-exonizing Alus. Moreover, the computationally derived probabilities of exonization significantly correlated with the biological inclusion level of the Alu exons, and the model could also be extended to general datasets of constitutive and alternative exons. This indicates that the features detected and explored in this study provide the basis not only for precise exon selection but also for the fine-tuned regulation thereof, manifested in cases of alternative splicing.'),
(84139, 2009, 'plos', 'Understanding pitch perception as a hierarchical process with top-down modulation', 'Balaguer-Ballester, Emili|Clark, Nicholas R|Coath, Martin|Krumbholz, Katrin|Denham, Susan L', 'Centre for Theoretical and Computational Neuroscience, University of Plymouth, Plymouth, United Kingdom. emili.balaguer@zi-mannheim.de|Centre for Theoretical and Computational Neuroscience, University of Plymouth, Plymouth, United Kingdom. emili.balaguer@zi-mannheim.de|Centre for Theoretical and Computational Neuroscience, University of Plymouth, Plymouth, United Kingdom. emili.balaguer@zi-mannheim.de|Centre for Theoretical and Computational Neuroscience, University of Plymouth, Plymouth, United Kingdom. emili.balaguer@zi-mannheim.de|Centre for Theoretical and Computational Neuroscience, University of Plymouth, Plymouth, United Kingdom. emili.balaguer@zi-mannheim.de', 'United Kingdom|United Kingdom|United Kingdom|United Kingdom|United Kingdom', 0, 'Auditory Perception|Feedback|Humans|Models, Theoretical|Music|Speech', 'Journal Article', '10.1371/journal.pcbi.1000301', '19266015', 'Pitch is one of the most important features of natural sounds, underlying the perception of melody in music and prosody in speech. However, the temporal dynamics of pitch processing are still poorly understood. Previous studies suggest that the auditory system uses a wide range of time scales to integrate pitch-related information and that the effective integration time is both task- and stimulus-dependent. None of the existing models of pitch processing can account for such task- and stimulus-dependent variations in processing time scales. This study presents an idealized neurocomputational model, which provides a unified account of the multiple time scales observed in pitch perception. The model is evaluated using a range of perceptual studies, which have not previously been accounted for by a single model, and new results from a neurophysiological experiment. In contrast to other approaches, the current model contains a hierarchy of integration stages and uses feedback to adapt the effective time scales of processing at each stage in response to changes in the input stimulus. The model has features in common with a hierarchical generative process and suggests a key role for efferent connections from central to sub-cortical areas in controlling the temporal dynamics of pitch processing.'),
(84140, 2009, 'plos', 'The modulation transfer function for speech intelligibility', 'Elliott, Taffeta M|Theunissen, Frédéric E', 'Helen Wills Neuroscience Institute, University of California Berkeley, Berkeley, California, United States of America.|Helen Wills Neuroscience Institute, University of California Berkeley, Berkeley, California, United States of America.', 'United States|United States', 0, 'Auditory Perception|Female|Humans|Male|Speech', 'Journal Article', '10.1371/journal.pcbi.1000302', '19266016', 'We systematically determined which spectrotemporal modulations in speech are necessary for comprehension by human listeners. Speech comprehension has been shown to be robust to spectral and temporal degradations, but the specific relevance of particular degradations is arguable due to the complexity of the joint spectral and temporal information in the speech signal. We applied a novel modulation filtering technique to recorded sentences to restrict acoustic information quantitatively and to obtain a joint spectrotemporal modulation transfer function for speech comprehension, the speech MTF. For American English, the speech MTF showed the criticality of low modulation frequencies in both time and frequency. Comprehension was significantly impaired when temporal modulations <12 Hz or spectral modulations <4 cycles/kHz were removed. More specifically, the MTF was bandpass in temporal modulations and low-pass in spectral modulations: temporal modulations from 1 to 7 Hz and spectral modulations <1 cycles/kHz were the most important. We evaluated the importance of spectrotemporal modulations for vocal gender identification and found a different region of interest: removing spectral modulations between 3 and 7 cycles/kHz significantly increases gender misidentifications of female speakers. The determination of the speech MTF furnishes an additional method for producing speech signals with reduced bandwidth but high intelligibility. Such compression could be used for audio applications such as file compression or noise removal and for clinical applications such as signal processing for cochlear implants.'),
(84141, 2009, 'plos', 'Robustness in glyoxylate bypass regulation', 'Shinar, Guy|Rabinowitz, Joshua D|Alon, Uri', 'Department of Molecular Cell Biology and Physics of Complex Systems, Weizmann Institute of Science, Rehovot, Israel. guy.shinar@weizmann.ac.il|Department of Molecular Cell Biology and Physics of Complex Systems, Weizmann Institute of Science, Rehovot, Israel. guy.shinar@weizmann.ac.il|Department of Molecular Cell Biology and Physics of Complex Systems, Weizmann Institute of Science, Rehovot, Israel. guy.shinar@weizmann.ac.il', 'Israel|Israel|Israel', 40, 'Binding Sites|Escherichia coli|Glyoxylates|Isocitrate Dehydrogenase|Models, Biological|Phosphorylation', 'Journal Article', '10.1371/journal.pcbi.1000297', '19266029', 'The glyoxylate bypass allows Escherichia coli to grow on carbon sources with only two carbons by bypassing the loss of carbons as CO(2) in the tricarboxylic acid cycle. The flux toward this bypass is regulated by the phosphorylation of the enzyme isocitrate dehydrogenase (IDH) by a bifunctional kinase-phosphatase called IDHKP. In this system, IDH activity has been found to be remarkably robust with respect to wide variations in the total IDH protein concentration. Here, we examine possible mechanisms to explain this robustness. Explanations in which IDHKP works simultaneously as a first-order kinase and as a zero-order phosphatase with a single IDH binding site are found to be inconsistent with robustness. Instead, we suggest a robust mechanism where both substrates bind the bifunctional enzyme to form a ternary complex.'),
(84142, 2009, 'plos', 'Timing the emergence of resistance to anti-HIV drugs with large genetic barriers', 'Arora, Pankhuri|Dixit, Narendra M', 'Department of Chemical Engineering, Indian Institute of Science, Bangalore, India.|Department of Chemical Engineering, Indian Institute of Science, Bangalore, India.', 'India|India', 0, 'Anti-HIV Agents|Computer Simulation|Drug Resistance, Viral|Genetic Variation|Genome, Viral|HIV|Models, Genetic|Mutation|Time Factors|Virion|Virus Activation', 'Journal Article', '10.1371/journal.pcbi.1000305', '19282958', 'New antiretroviral drugs that offer large genetic barriers to resistance, such as the recently approved inhibitors of HIV-1 protease, tipranavir and darunavir, present promising weapons to avert the failure of current therapies for HIV infection. Optimal treatment strategies with the new drugs, however, are yet to be established. A key limitation is the poor understanding of the process by which HIV surmounts large genetic barriers to resistance. Extant models of HIV dynamics are predicated on the predominance of deterministic forces underlying the emergence of resistant genomes. In contrast, stochastic forces may dominate, especially when the genetic barrier is large, and delay the emergence of resistant genomes. We develop a mathematical model of HIV dynamics under the influence of an antiretroviral drug to predict the waiting time for the emergence of genomes that carry the requisite mutations to overcome the genetic barrier of the drug. We apply our model to describe the development of resistance to tipranavir in in vitro serial passage experiments. Model predictions of the times of emergence of different mutant genomes with increasing resistance to tipranavir are in quantitative agreement with experiments, indicating that our model captures the dynamics of the development of resistance to antiretroviral drugs accurately. Further, model predictions provide insights into the influence of underlying evolutionary processes such as recombination on the development of resistance, and suggest guidelines for drug design: drugs that offer large genetic barriers to resistance with resistance sites tightly localized on the viral genome and exhibiting positive epistatic interactions maximally inhibit the emergence of resistant genomes.'),
(84143, 2009, 'plos', 'Mechanism of action of cyclophilin a explored by metadynamics simulations', 'Leone, Vanessa|Lattanzi, Gianluca|Molteni, Carla|Carloni, Paolo', 'International School for Advanced Studies (SISSA), Trieste, Italy.|International School for Advanced Studies (SISSA), Trieste, Italy.|International School for Advanced Studies (SISSA), Trieste, Italy.|International School for Advanced Studies (SISSA), Trieste, Italy.', 'Italy|Italy|Italy|Italy', 38, 'Binding Sites|Capsid Proteins|Computer Simulation|Cyclophilin A|Enzyme Activation|HIV-1|Isomerism|Models, Chemical|Models, Molecular|Protein Binding|Water', 'Journal Article', '10.1371/journal.pcbi.1000309', '19282959', 'Trans/cis prolyl isomerisation is involved in several biological processes, including the development of numerous diseases. In the HIV-1 capsid protein (CA), such a process takes place in the uncoating and recruitment of the virion and is catalyzed by cyclophilin A (CypA). Here, we use metadynamics simulations to investigate the isomerization of CAs model substrate HAGPIA in water and in its target protein CypA. Our results allow us to propose a novel mechanistic hypothesis, which is finally consistent with all of the available molecular biology data.'),
(84144, 2009, 'plos', 'Mechanical network in titin immunoglobulin from force distribution analysis', 'Stacklies, Wolfram|Vega, M Cristina|Wilmanns, Matthias|Gräter, Frauke', 'CAS-MPG Partner Institute for Computational Biology, Shanghai, Peoples Republic of China.|CAS-MPG Partner Institute for Computational Biology, Shanghai, Peoples Republic of China.|CAS-MPG Partner Institute for Computational Biology, Shanghai, Peoples Republic of China.|CAS-MPG Partner Institute for Computational Biology, Shanghai, Peoples Republic of China.', 'China|China|China|China', 47, 'Computer Simulation|Connectin|Cytoskeletal Proteins|Elastic Modulus|Models, Chemical|Models, Molecular|Muscle Proteins|Protein Structure, Tertiary|Stress, Mechanical', 'Journal Article', '10.1371/journal.pcbi.1000306', '19282960', 'The role of mechanical force in cellular processes is increasingly revealed by single molecule experiments and simulations of force-induced transitions in proteins. How the applied force propagates within proteins determines their mechanical behavior yet remains largely unknown. We present a new method based on molecular dynamics simulations to disclose the distribution of strain in protein structures, here for the newly determined high-resolution crystal structure of I27, a titin immunoglobulin (IG) domain. We obtain a sparse, spatially connected, and highly anisotropic mechanical network. This allows us to detect load-bearing motifs composed of interstrand hydrogen bonds and hydrophobic core interactions, including parts distal to the site to which force was applied. The role of the force distribution pattern for mechanical stability is tested by in silico unfolding of I27 mutants. We then compare the observed force pattern to the sparse network of coevolved residues found in this family. We find a remarkable overlap, suggesting the force distribution to reflect constraints for the evolutionary design of mechanical resistance in the IG family. The force distribution analysis provides a molecular interpretation of coevolution and opens the road to the study of the mechanism of signal propagation in proteins in general.'),
(84145, 2009, 'plos', 'Cortical factor feedback model for cellular locomotion and cytofission', 'Nishimura, Shin I|Ueda, Masahiro|Sasai, Masaki', 'Department of Computational Science and Engineering, Nagoya University, Nagoya, Japan. shin@tbp.cse.nagoya-u.ac.jp|Department of Computational Science and Engineering, Nagoya University, Nagoya, Japan. shin@tbp.cse.nagoya-u.ac.jp|Department of Computational Science and Engineering, Nagoya University, Nagoya, Japan. shin@tbp.cse.nagoya-u.ac.jp', 'Japan|Japan|Japan', 37, 'Actins|Cell Division|Cell Movement|Cell Size|Computer Simulation|Feedback|Models, Biological|Models, Chemical|Models, Molecular|Molecular Motor Proteins', 'Journal Article', '10.1371/journal.pcbi.1000310', '19282961', 'Eukaryotic cells can move spontaneously without being guided by external cues. For such spontaneous movements, a variety of different modes have been observed, including the amoeboid-like locomotion with protrusion of multiple pseudopods, the keratocyte-like locomotion with a widely spread lamellipodium, cell division with two daughter cells crawling in opposite directions, and fragmentations of a cell to multiple pieces. Mutagenesis studies have revealed that cells exhibit these modes depending on which genes are deficient, suggesting that seemingly different modes are the manifestation of a common mechanism to regulate cell motion. In this paper, we propose a hypothesis that the positive feedback mechanism working through the inhomogeneous distribution of regulatory proteins underlies this variety of cell locomotion and cytofission. In this hypothesis, a set of regulatory proteins, which we call cortical factors, suppress actin polymerization. These suppressing factors are diluted at the extending front and accumulated at the retracting rear of cell, which establishes a cellular polarity and enhances the cell motility, leading to the further accumulation of cortical factors at the rear. Stochastic simulation of cell movement shows that the positive feedback mechanism of cortical factors stabilizes or destabilizes modes of movement and determines the cell migration pattern. The model predicts that the pattern is selected by changing the rate of formation of the actin-filament network or the threshold to initiate the network formation.'),
(84146, 2009, 'plos', 'Toward a detailed description of the thermally induced dynamics of the core promoter', 'Alexandrov, Boian S|Gelev, Vladimir|Yoo, Sang Wook|Bishop, Alan R|Rasmussen, Kim Ø|Usheva, Anny', 'Theoretical Division and Center for Nonlinear Studies, Los Alamos National Laboratory, Los Alamos, New Mexico, United States of America.|Theoretical Division and Center for Nonlinear Studies, Los Alamos National Laboratory, Los Alamos, New Mexico, United States of America.|Theoretical Division and Center for Nonlinear Studies, Los Alamos National Laboratory, Los Alamos, New Mexico, United States of America.|Theoretical Division and Center for Nonlinear Studies, Los Alamos National Laboratory, Los Alamos, New Mexico, United States of America.|Theoretical Division and Center for Nonlinear Studies, Los Alamos National Laboratory, Los Alamos, New Mexico, United States of America.|Theoretical Division and Center for Nonlinear Studies, Los Alamos National Laboratory, Los Alamos, New Mexico, United States of America.', 'Mexico|Mexico|Mexico|Mexico|Mexico|Mexico', 32, 'Base Sequence|Computer Simulation|DNA|DNA-Directed RNA Polymerases|Hot Temperature|Models, Chemical|Models, Genetic|Models, Molecular|Molecular Sequence Data|Promoter Regions, Genetic|Sequence Analysis, DNA', 'Journal Article', '10.1371/journal.pcbi.1000313', '19282962', 'Establishing the general and promoter-specific mechanistic features of gene transcription initiation requires improved understanding of the sequence-dependent structural/dynamic features of promoter DNA. Experimental data suggest that a spontaneous dsDNA strand separation at the transcriptional start site is likely to be a requirement for transcription initiation in several promoters. Here, we use Langevin molecular dynamic simulations based on the Peyrard-Bishop-Dauxois nonlinear model of DNA (PBD LMD) to analyze the strand separation (bubble) dynamics of 80-bp-long promoter DNA sequences. We derive three dynamic criteria, bubble probability, bubble lifetime, and average strand separation, to characterize bubble formation at the transcriptional start sites of eight mammalian gene promoters. We observe that the most stable dsDNA openings do not necessarily coincide with the most probable openings and the highest average strand displacement, underscoring the advantages of proper molecular dynamic simulations. The dynamic profiles of the tested mammalian promoters differ significantly in overall profile and bubble probability, but the transcriptional start site is often distinguished by large (longer than 10 bp) and long-lived transient openings in the double helix. In support of these results are our experimental transcription data demonstrating that an artificial bubble-containing DNA template is transcribed bidirectionally by human RNA polymerase alone in the absence of any other transcription factors.'),
(84147, 2009, 'plos', 'Probabilistic interaction network of evidence algorithm and its application to complete labeling of peak lists from protein NMR spectroscopy', 'Bahrami, Arash|Assadi, Amir H|Markley, John L|Eghbalnia, Hamid R', 'Biochemistry Department, National Magnetic Resonance Facility at Madison, University of Wisconsin Madison, Madison, Wisconsin, United States of America. arash@nmrfam.wisc.edu|Biochemistry Department, National Magnetic Resonance Facility at Madison, University of Wisconsin Madison, Madison, Wisconsin, United States of America. arash@nmrfam.wisc.edu|Biochemistry Department, National Magnetic Resonance Facility at Madison, University of Wisconsin Madison, Madison, Wisconsin, United States of America. arash@nmrfam.wisc.edu|Biochemistry Department, National Magnetic Resonance Facility at Madison, University of Wisconsin Madison, Madison, Wisconsin, United States of America. arash@nmrfam.wisc.edu', 'United States|United States|United States|United States', 145, 'Algorithms|Binding Sites|Data Interpretation, Statistical|Isotope Labeling|Magnetic Resonance Spectroscopy|Protein Binding|Protein Interaction Mapping|Proteins', 'Journal Article', '10.1371/journal.pcbi.1000307', '19282963', 'The process of assigning a finite set of tags or labels to a collection of observations, subject to side conditions, is notable for its computational complexity. This labeling paradigm is of theoretical and practical relevance to a wide range of biological applications, including the analysis of data from DNA microarrays, metabolomics experiments, and biomolecular nuclear magnetic resonance (NMR) spectroscopy. We present a novel algorithm, called Probabilistic Interaction Network of Evidence (PINE), that achieves robust, unsupervised probabilistic labeling of data. The computational core of PINE uses estimates of evidence derived from empirical distributions of previously observed data, along with consistency measures, to drive a fictitious system M with Hamiltonian H to a quasi-stationary state that produces probabilistic label assignments for relevant subsets of the data. We demonstrate the successful application of PINE to a key task in protein NMR spectroscopy: that of converting peak lists extracted from various NMR experiments into assignments associated with probabilities for their correctness. This application, called PINE-NMR, is available from a freely accessible computer server (http://pine.nmrfam.wisc.edu). The PINE-NMR server accepts as input the sequence of the protein plus user-specified combinations of data corresponding to an extensive list of NMR experiments, it provides as output a probabilistic assignment of NMR signals (chemical shifts) to sequence-specific backbone and aliphatic side chain atoms plus a probabilistic determination of the protein secondary structure. PINE-NMR can accommodate prior information about assignments or stable isotope labeling schemes. As part of the analysis, PINE-NMR identifies, verifies, and rectifies problems related to chemical shift referencing or erroneous input data. PINE-NMR achieves robust and consistent results that have been shown to be effective in subsequent steps of NMR structure determination.'),
(84148, 2009, 'plos', 'GrowMatch: an automated method for reconciling in silico/in vivo growth predictions', 'Kumar, Vinay Satish|Maranas, Costas D', 'Department of Industrial and Manufacturing Engineering, The Pennsylvania State University, University Park, Pennsylvania, United States of America.|Department of Industrial and Manufacturing Engineering, The Pennsylvania State University, University Park, Pennsylvania, United States of America.', 'United States|United States', 143, 'Algorithms|Cell Proliferation|Computer Simulation|Escherichia coli|Escherichia coli Proteins|Gene Expression Regulation, Bacterial|Models, Biological|Signal Transduction', 'Evaluation Studies', '10.1371/journal.pcbi.1000308', '19282964', 'Genome-scale metabolic reconstructions are typically validated by comparing in silico growth predictions across different mutants utilizing different carbon sources with in vivo growth data. This comparison results in two types of model-prediction inconsistencies, either the model predicts growth when no growth is observed in the experiment (GNG inconsistencies) or the model predicts no growth when the experiment reveals growth (NGG inconsistencies). Here we propose an optimization-based framework, GrowMatch, to automatically reconcile GNG predictions (by suppressing functionalities in the model) and NGG predictions (by adding functionalities to the model). We use GrowMatch to resolve inconsistencies between the predictions of the latest in silico Escherichia coli (iAF1260) model and the in vivo data available in the Keio collection and improved the consistency of in silico with in vivo predictions from 90.6% to 96.7%. Specifically, we were able to suggest consistency-restoring hypotheses for 56/72 GNG mutants and 13/38 NGG mutants. GrowMatch resolved 18 GNG inconsistencies by suggesting suppressions in the mutant metabolic networks. Fifteen inconsistencies were resolved by suppressing isozymes in the metabolic network, and the remaining 23 GNG mutants corresponding to blocked genes were resolved by suitably modifying the biomass equation of iAF1260. GrowMatch suggested consistency-restoring hypotheses for five NGG mutants by adding functionalities to the model whereas the remaining eight inconsistencies were resolved by pinpointing possible alternate genes that carry out the function of the deleted gene. For many cases, GrowMatch identified fairly nonintuitive model modification hypotheses that would have been difficult to pinpoint through inspection alone. In addition, GrowMatch can be used during the construction phase of new, as opposed to existing, genome-scale metabolic models, leading to more expedient and accurate reconstructions.'),
(84149, 2009, 'plos', 'Canalization of gene expression and domain shifts in the Drosophila blastoderm by dynamical attractors', '-', '-', '-', 139, 'Animals|Blastoderm|Body Patterning|Computer Simulation|Drosophila|Drosophila Proteins|Gene Expression Regulation, Developmental|Models, Biological|Transcription Factors', 'Journal Article', '10.1371/journal.pcbi.1000303', '19282965', 'The variation in the expression patterns of the gap genes in the blastoderm of the fruit fly Drosophila melanogaster reduces over time as a result of cross regulation between these genes, a fact that we have demonstrated in an accompanying article in PLoS Biology (see Manu et al., doi:10.1371/journal.pbio.1000049). This biologically essential process is an example of the phenomenon known as canalization. It has been suggested that the developmental trajectory of a wild-type organism is inherently stable, and that canalization is a manifestation of this property. Although the role of gap genes in the canalization process was established by correctly predicting the response of the system to particular perturbations, the stability of the developmental trajectory remains to be investigated. For many years, it has been speculated that stability against perturbations during development can be described by dynamical systems having attracting sets that drive reductions of volume in phase space. In this paper, we show that both the reduction in variability of gap gene expression as well as shifts in the position of posterior gap gene domains are the result of the actions of attractors in the gap gene dynamical system. Two biologically distinct dynamical regions exist in the early embryo, separated by a bifurcation at 53% egg length. In the anterior region, reduction in variation occurs because of stability induced by point attractors, while in the posterior, the stability of the developmental trajectory arises from a one-dimensional attracting manifold. This manifold also controls a previously characterized anterior shift of posterior region gap domains. Our analysis shows that the complex phenomena of canalization and pattern formation in the Drosophila blastoderm can be understood in terms of the qualitative features of the dynamical system. The result confirms the idea that attractors are important for developmental stability and shows a richer variety of dynamical attractors in developmental systems than has been previously recognized.'),
(84150, 2009, 'plos', 'Intrinsic disorder in protein interactions: insights from a comprehensive structural analysis', 'Fong, Jessica H|Shoemaker, Benjamin A|Garbuzynskiy, Sergiy O|Lobanov, Michail Y|Galzitskaya, Oxana V|Panchenko, Anna R', 'National Center for Biotechnology Information, National Institutes of Health, Bethesda, Maryland, United States of America.|National Center for Biotechnology Information, National Institutes of Health, Bethesda, Maryland, United States of America.|National Center for Biotechnology Information, National Institutes of Health, Bethesda, Maryland, United States of America.|National Center for Biotechnology Information, National Institutes of Health, Bethesda, Maryland, United States of America.|National Center for Biotechnology Information, National Institutes of Health, Bethesda, Maryland, United States of America.|National Center for Biotechnology Information, National Institutes of Health, Bethesda, Maryland, United States of America.', 'United States|United States|United States|United States|United States|United States', 82, 'Amino Acid Sequence|Binding Sites|Computer Simulation|Models, Chemical|Models, Molecular|Molecular Sequence Data|Protein Binding|Protein Interaction Mapping|Protein Structure, Tertiary|Proteins|Sequence Analysis, Protein', 'Journal Article', '10.1371/journal.pcbi.1000316', '19282967', 'We perform a large-scale study of intrinsically disordered regions in proteins and protein complexes using a non-redundant set of hundreds of different protein complexes. In accordance with the conventional view that folding and binding are coupled, in many of our cases the disorder-to-order transition occurs upon complex formation and can be localized to binding interfaces. Moreover, analysis of disorder in protein complexes depicts a significant fraction of intrinsically disordered regions, with up to one third of all residues being disordered. We find that the disorder in homodimers, especially in symmetrical homodimers, is significantly higher than in heterodimers and offer an explanation for this interesting phenomenon. We argue that the mechanisms of regulation of binding specificity through disordered regions in complexes can be as common as for unbound monomeric proteins. The fascinating diversity of roles of disordered regions in various biological processes and protein oligomeric forms shown in our study may be a subject of future endeavors in this area.'),
(84151, 2009, 'plos', 'Detection of alpha-rod protein repeats using a neural network and application to huntingtin', 'Palidwor, Gareth A|Shcherbinin, Sergey|Huska, Matthew R|Rasko, Tamas|Stelzl, Ulrich|Arumughan, Anup|Foulle, Raphaele|Porras, Pablo|Sanchez-Pulido, Luis|Wanker, Erich E|Andrade-Navarro, Miguel A', 'Ottawa Health Research Institute, Ottawa, Ontario, Canada.|Ottawa Health Research Institute, Ottawa, Ontario, Canada.|Ottawa Health Research Institute, Ottawa, Ontario, Canada.|Ottawa Health Research Institute, Ottawa, Ontario, Canada.|Ottawa Health Research Institute, Ottawa, Ontario, Canada.|Ottawa Health Research Institute, Ottawa, Ontario, Canada.|Ottawa Health Research Institute, Ottawa, Ontario, Canada.|Ottawa Health Research Institute, Ottawa, Ontario, Canada.|Ottawa Health Research Institute, Ottawa, Ontario, Canada.|Ottawa Health Research Institute, Ottawa, Ontario, Canada.|Ottawa Health Research Institute, Ottawa, Ontario, Canada.', 'Canada|Canada|Canada|Canada|Canada|Canada|Canada|Canada|Canada|Canada|Canada', 45, 'Algorithms|Amino Acid Sequence|Binding Sites|Computer Simulation|Huntingtin Protein|Models, Chemical|Models, Molecular|Molecular Sequence Data|Nerve Tissue Proteins|Neural Networks (Computer)|Nuclear Proteins|Pattern Recognition, Automated|Protein Binding|Repetitive Sequences, Amino Acid|Sequence Analysis, Protein', 'Journal Article', '10.1371/journal.pcbi.1000304', '19282972', 'A growing number of solved protein structures display an elongated structural domain, denoted here as alpha-rod, composed of stacked pairs of anti-parallel alpha-helices. Alpha-rods are flexible and expose a large surface, which makes them suitable for protein interaction. Although most likely originating by tandem duplication of a two-helix unit, their detection using sequence similarity between repeats is poor. Here, we show that alpha-rod repeats can be detected using a neural network. The network detects more repeats than are identified by domain databases using multiple profiles, with a low level of false positives (<10%). We identify alpha-rod repeats in approximately 0.4% of proteins in eukaryotic genomes. We then investigate the results for all human proteins, identifying alpha-rod repeats for the first time in six protein families, including proteins STAG1-3, SERAC1, and PSMD1-2 & 5. We also characterize a short version of these repeats in eight protein families of Archaeal, Bacterial, and Fungal species. Finally, we demonstrate the utility of these predictions in directing experimental work to demarcate three alpha-rods in huntingtin, a protein mutated in Huntingtons disease. Using yeast two hybrid analysis and an immunoprecipitation technique, we show that the huntingtin fragments containing alpha-rods associate with each other. This is the first definition of domains in huntingtin and the first validation of predicted interactions between fragments of huntingtin, which sets up directions toward functional characterization of this protein. An implementation of the repeat detection algorithm is available as a Web server with a simple graphical output: http://www.ogic.ca/projects/ard. This can be further visualized using BiasViz, a graphic tool for representation of multiple sequence alignments.'),
(84152, 2009, 'plos', 'Genome-scale reconstruction of Escherichia colis transcriptional and translational machinery: a knowledge base, its mathematical formulation, and its functional characterization', 'Thiele, Ines|Jamshidi, Neema|Fleming, Ronan M T|Palsson, Bernhard Ø', 'University of California San Diego, La Jolla, California, United States of America.|University of California San Diego, La Jolla, California, United States of America.|University of California San Diego, La Jolla, California, United States of America.|University of California San Diego, La Jolla, California, United States of America.', 'United States|United States|United States|United States', 119, 'Computer Simulation|Databases, Protein|Escherichia coli|Escherichia coli Proteins|Gene Expression Regulation, Bacterial|Genome, Bacterial|Models, Biological|Protein Modification, Translational|Transcription Factors|Transcription, Genetic', 'Journal Article', '10.1371/journal.pcbi.1000312', '19282977', 'Metabolic network reconstructions represent valuable scaffolds for -omics data integration and are used to computationally interrogate network properties. However, they do not explicitly account for the synthesis of macromolecules (i.e., proteins and RNA). Here, we present the first genome-scale, fine-grained reconstruction of Escherichia colis transcriptional and translational machinery, which produces 423 functional gene products in a sequence-specific manner and accounts for all necessary chemical transformations. Legacy data from over 500 publications and three databases were reviewed, and many pathways were considered, including stable RNA maturation and modification, protein complex formation, and iron-sulfur cluster biogenesis. This reconstruction represents the most comprehensive knowledge base for these important cellular functions in E. coli and is unique in its scope. Furthermore, it was converted into a mathematical model and used to: (1) quantitatively integrate gene expression data as reaction constraints and (2) compute functional network states, which were compared to reported experimental data. For example, the model predicted accurately the ribosome production, without any parameterization. Also, in silico rRNA operon deletion suggested that a high RNA polymerase density on the remaining rRNA operons is needed to reproduce the reported experimental ribosome numbers. Moreover, functional protein modules were determined, and many were found to contain gene products from multiple subsystems, highlighting the functional interaction of these proteins. This genome-scale reconstruction of E. colis transcriptional and translational machinery presents a milestone in systems biology because it will enable quantitative integration of -omics datasets and thus the study of the mechanistic principles underlying the genotype-phenotype relationship.'),
(84153, 2009, 'plos', 'Robust detection and genotyping of single feature polymorphisms from gene expression data', 'Wang, Minghui|Hu, Xiaohua|Li, Gang|Leach, Lindsey J|Potokina, Elena|Druka, Arnis|Waugh, Robbie|Kearsey, Michael J|Luo, Zewei', 'Laboratory of Population & Quantitative Genetics, The State Key Laboratory of Genetic Engineering, Institute of Biostatistics, School of Life Sciences, Fudan University, Shanghai, China.|Laboratory of Population & Quantitative Genetics, The State Key Laboratory of Genetic Engineering, Institute of Biostatistics, School of Life Sciences, Fudan University, Shanghai, China.|Laboratory of Population & Quantitative Genetics, The State Key Laboratory of Genetic Engineering, Institute of Biostatistics, School of Life Sciences, Fudan University, Shanghai, China.|Laboratory of Population & Quantitative Genetics, The State Key Laboratory of Genetic Engineering, Institute of Biostatistics, School of Life Sciences, Fudan University, Shanghai, China.|Laboratory of Population & Quantitative Genetics, The State Key Laboratory of Genetic Engineering, Institute of Biostatistics, School of Life Sciences, Fudan University, Shanghai, China.|Laboratory of Population & Quantitative Genetics, The State Key Laboratory of Genetic Engineering, Institute of Biostatistics, School of Life Sciences, Fudan University, Shanghai, China.|Laboratory of Population & Quantitative Genetics, The State Key Laboratory of Genetic Engineering, Institute of Biostatistics, School of Life Sciences, Fudan University, Shanghai, China.|Laboratory of Population & Quantitative Genetics, The State Key Laboratory of Genetic Engineering, Institute of Biostatistics, School of Life Sciences, Fudan University, Shanghai, China.|Laboratory of Population & Quantitative Genetics, The State Key Laboratory of Genetic Engineering, Institute of Biostatistics, School of Life Sciences, Fudan University, Shanghai, China.', 'China|China|China|China|China|China|China|China|China', 9, 'Algorithms|Base Sequence|Chromosome Mapping|Gene Expression Profiling|Molecular Sequence Data|Oligonucleotide Array Sequence Analysis|Polymorphism, Genetic|Sequence Analysis, DNA|Sequence Analysis, RNA', 'Journal Article', '10.1371/journal.pcbi.1000317', '19282978', 'It is well known that Affymetrix microarrays are widely used to predict genome-wide gene expression and genome-wide genetic polymorphisms from RNA and genomic DNA hybridization experiments, respectively. It has recently been proposed to integrate the two predictions by use of RNA microarray data only. Although the ability to detect single feature polymorphisms (SFPs) from RNA microarray data has many practical implications for genome study in both sequenced and unsequenced species, it raises enormous challenges for statistical modelling and analysis of microarray gene expression data for this objective. Several methods are proposed to predict SFPs from the gene expression profile. However, their performance is highly vulnerable to differential expression of genes. The SFPs thus predicted are eventually a reflection of differentially expressed genes rather than genuine sequence polymorphisms. To address the problem, we developed a novel statistical method to separate the binding affinity between a transcript and its targeting probe and the parameter measuring transcript abundance from perfect-match hybridization values of Affymetrix gene expression data. We implemented a Bayesian approach to detect SFPs and to genotype a segregating population at the detected SFPs. Based on analysis of three Affymetrix microarray datasets, we demonstrated that the present method confers a significantly improved robustness and accuracy in detecting the SFPs that carry genuine sequence polymorphisms when compared to its rivals in the literature. The method developed in this paper will provide experimental genomicists with advanced analytical tools for appropriate and efficient analysis of their microarray experiments and biostatisticians with insightful interpretation of Affymetrix microarray data.'),
(84154, 2009, 'plos', 'Sm/Lsm genes provide a glimpse into the early evolution of the spliceosome', 'Veretnik, Stella|Wills, Christopher|Youkharibache, Philippe|Valas, Ruben E|Bourne, Philip E', 'San Diego Supercomputer Center, University of California San Diego, La Jolla, California, United States of America. veretnik@sdsc.edu|San Diego Supercomputer Center, University of California San Diego, La Jolla, California, United States of America. veretnik@sdsc.edu|San Diego Supercomputer Center, University of California San Diego, La Jolla, California, United States of America. veretnik@sdsc.edu|San Diego Supercomputer Center, University of California San Diego, La Jolla, California, United States of America. veretnik@sdsc.edu|San Diego Supercomputer Center, University of California San Diego, La Jolla, California, United States of America. veretnik@sdsc.edu', 'United States|United States|United States|United States|United States', 23, 'Base Sequence|Evolution, Molecular|Genetic Variation|Models, Genetic|Molecular Sequence Data|Ribonucleoproteins, Small Nuclear|Sequence Analysis, DNA|Species Specificity|Spliceosomes', 'Journal Article', '10.1371/journal.pcbi.1000315', '19282982', 'The spliceosome, a sophisticated molecular machine involved in the removal of intervening sequences from the coding sections of eukaryotic genes, appeared and subsequently evolved rapidly during the early stages of eukaryotic evolution. The last eukaryotic common ancestor (LECA) had both complex spliceosomal machinery and some spliceosomal introns, yet little is known about the early stages of evolution of the spliceosomal apparatus. The Sm/Lsm family of proteins has been suggested as one of the earliest components of the emerging spliceosome and hence provides a first in-depth glimpse into the evolving spliceosomal apparatus. An analysis of 335 Sm and Sm-like genes from 80 species across all three kingdoms of life reveals two significant observations. First, the eukaryotic Sm/Lsm family underwent two rapid waves of duplication with subsequent divergence resulting in 14 distinct genes. Each wave resulted in a more sophisticated spliceosome, reflecting a possible jump in the complexity of the evolving eukaryotic cell. Second, an unusually high degree of conservation in intron positions is observed within individual orthologous Sm/Lsm genes and between some of the Sm/Lsm paralogs. This suggests that functional spliceosomal introns existed before the emergence of the complete Sm/Lsm family of proteins, hence, spliceosomal machinery with considerably fewer components than todays spliceosome was already functional.');
INSERT INTO `papers` (`id`, `ano`, `journal`, `titulo`, `autores`, `afiliacao`, `pais`, `citacoes`, `palavra_chave`, `categorias`, `doi`, `pubmed`, `abstract`) VALUES
(84155, 2009, 'plos', 'Alignment and prediction of cis-regulatory modules based on a probabilistic model of evolution', 'He, Xin|Ling, Xu|Sinha, Saurabh', 'Department of Computer Science, University of Illinois Urbana-Champaign, Urbana, IL, USA.|Department of Computer Science, University of Illinois Urbana-Champaign, Urbana, IL, USA.|Department of Computer Science, University of Illinois Urbana-Champaign, Urbana, IL, USA.', 'United States|United States|United States', 26, 'Binding Sites|DNA|Evolution, Molecular|Models, Genetic|Models, Statistical|Protein Binding|Regulatory Elements, Transcriptional|Sequence Alignment|Sequence Analysis, DNA|Transcription Factors', 'Journal Article', '10.1371/journal.pcbi.1000299', '19293946', 'Cross-species comparison has emerged as a powerful paradigm for predicting cis-regulatory modules (CRMs) and understanding their evolution. The comparison requires reliable sequence alignment, which remains a challenging task for less conserved noncoding sequences. Furthermore, the existing models of DNA sequence evolution generally do not explicitly treat the special properties of CRM sequences. To address these limitations, we propose a model of CRM evolution that captures different modes of evolution of functional transcription factor binding sites (TFBSs) and the background sequences. A particularly novel aspect of our work is a probabilistic model of gains and losses of TFBSs, a process being recognized as an important part of regulatory sequence evolution. We present a computational framework that uses this model to solve the problems of CRM alignment and prediction. Our alignment method is similar to existing methods of statistical alignment but uses the conserved binding sites to improve alignment. Our CRM prediction method deals with the inherent uncertainties of binding site annotations and sequence alignment in a probabilistic framework. In simulated as well as real data, we demonstrate that our program is able to improve both alignment and prediction of CRM sequences over several state-of-the-art methods. Finally, we used alignments produced by our program to study binding site conservation in genome-wide binding data of key transcription factors in the Drosophila blastoderm, with two intriguing results: (i) the factor-bound sequences are under strong evolutionary constraints even if their neighboring genes are not expressed in the blastoderm and (ii) binding sites in distal bound sequences (relative to transcription start sites) tend to be more conserved than those in proximal regions. Our approach is implemented as software, EMMA (Evolutionary Model-based cis-regulatory Module Analysis), ready to be applied in a broad biological context.'),
(84156, 2009, 'plos', 'Broadband criticality of human brain network synchronization', 'Kitzbichler, Manfred G|Smith, Marie L|Christensen, Søren R|Bullmore, Ed', 'Behavioural & Clinical Neurosciences Institute, Department of Experimental Psychology, University of Cambridge, Cambridge, United Kingdom.|Behavioural & Clinical Neurosciences Institute, Department of Experimental Psychology, University of Cambridge, Cambridge, United Kingdom.|Behavioural & Clinical Neurosciences Institute, Department of Experimental Psychology, University of Cambridge, Cambridge, United Kingdom.|Behavioural & Clinical Neurosciences Institute, Department of Experimental Psychology, University of Cambridge, Cambridge, United Kingdom.', 'United Kingdom|United Kingdom|United Kingdom|United Kingdom', 310, 'Action Potentials|Animals|Biological Clocks|Brain|Computer Simulation|Cortical Synchronization|Humans|Models, Neurological|Nerve Net|Neurons|Synaptic Transmission', 'Journal Article', '10.1371/journal.pcbi.1000314', '19300473', 'Self-organized criticality is an attractive model for human brain dynamics, but there has been little direct evidence for its existence in large-scale systems measured by neuroimaging. In general, critical systems are associated with fractal or power law scaling, long-range correlations in space and time, and rapid reconfiguration in response to external inputs. Here, we consider two measures of phase synchronization: the phase-lock interval, or duration of coupling between a pair of (neurophysiological) processes, and the lability of global synchronization of a (brain functional) network. Using computational simulations of two mechanistically distinct systems displaying complex dynamics, the Ising model and the Kuramoto model, we show that both synchronization metrics have power law probability distributions specifically when these systems are in a critical state. We then demonstrate power law scaling of both pairwise and global synchronization metrics in functional MRI and magnetoencephalographic data recorded from normal volunteers under resting conditions. These results strongly suggest that human brain functional systems exist in an endogenous state of dynamical criticality, characterized by a greater than random probability of both prolonged periods of phase-locking and occurrence of large rapid changes in the state of global synchronization, analogous to the neuronal avalanches previously described in cellular systems. Moreover, evidence for critical dynamics was identified consistently in neurophysiological systems operating at frequency intervals ranging from 0.05-0.11 to 62.5-125 Hz, confirming that criticality is a property of human brain functional network organization at all frequency intervals in the brains physiological bandwidth.'),
(84157, 2009, 'plos', 'Using network component analysis to dissect regulatory networks mediated by transcription factors in yeast', 'Ye, Chun|Galbraith, Simon J|Liao, James C|Eskin, Eleazar', 'Bioinformatics Program, University of California San Diego, La Jolla, California, United States of America. cye@bioinf.ucsd.edu|Bioinformatics Program, University of California San Diego, La Jolla, California, United States of America. cye@bioinf.ucsd.edu|Bioinformatics Program, University of California San Diego, La Jolla, California, United States of America. cye@bioinf.ucsd.edu|Bioinformatics Program, University of California San Diego, La Jolla, California, United States of America. cye@bioinf.ucsd.edu', 'United States|United States|United States|United States', 26, 'Algorithms|Base Sequence|DNA Mutational Analysis|Gene Expression Regulation, Fungal|Genetic Variation|Models, Genetic|Molecular Sequence Data|Polymorphism, Single Nucleotide|Principal Component Analysis|Saccharomyces cerevisiae|Saccharomyces cerevisiae Proteins|Sequence Analysis, DNA|Signal Transduction|Transcription Factors', 'Journal Article', '10.1371/journal.pcbi.1000311', '19300475', 'Understanding the relationship between genetic variation and gene expression is a central question in genetics. With the availability of data from high-throughput technologies such as ChIP-Chip, expression, and genotyping arrays, we can begin to not only identify associations but to understand how genetic variations perturb the underlying transcription regulatory networks to induce differential gene expression. In this study, we describe a simple model of transcription regulation where the expression of a gene is completely characterized by two properties: the concentrations and promoter affinities of active transcription factors. We devise a method that extends Network Component Analysis (NCA) to determine how genetic variations in the form of single nucleotide polymorphisms (SNPs) perturb these two properties. Applying our method to a segregating population of Saccharomyces cerevisiae, we found statistically significant examples of trans-acting SNPs located in regulatory hotspots that perturb transcription factor concentrations and affinities for target promoters to cause global differential expression and cis-acting genetic variations that perturb the promoter affinities of transcription factors on a single gene to cause local differential expression. Although many genetic variations linked to gene expressions have been identified, it is not clear how they perturb the underlying regulatory networks that govern gene expression. Our work begins to fill this void by showing that many genetic variations affect the concentrations of active transcription factors in a cell and their affinities for target promoters. Understanding the effects of these perturbations can help us to paint a more complete picture of the complex landscape of transcription regulation. The software package implementing the algorithms discussed in this work is available as a MATLAB package upon request.'),
(84158, 2009, 'plos', 'On the growth of scientific knowledge: yeast biology as a case study', 'He, Xionglei|Zhang, Jianzhi', 'State Key Laboratory of Biocontrol, School of Life Sciences, Sun Yat-sen University, Guangzhou, China. hexiongl@mail.sysu.edu.cn|State Key Laboratory of Biocontrol, School of Life Sciences, Sun Yat-sen University, Guangzhou, China. hexiongl@mail.sysu.edu.cn', 'China|China', 8, 'Bibliometrics|Biology|Databases, Protein|Gene Expression Profiling|Health Knowledge, Attitudes, Practice|Periodicals as Topic|Protein Interaction Mapping|Saccharomyces cerevisiae|Science', 'Journal Article', '10.1371/journal.pcbi.1000320', '19300476', 'The tempo and mode of human knowledge expansion is an enduring yet poorly understood topic. Through a temporal network analysis of three decades of discoveries of protein interactions and genetic interactions in bakers yeast, we show that the growth of scientific knowledge is exponential over time and that important subjects tend to be studied earlier. However, expansions of different domains of knowledge are highly heterogeneous and episodic such that the temporal turnover of knowledge hubs is much greater than expected by chance. Familiar subjects are preferentially studied over new subjects, leading to a reduced pace of innovation. While research is increasingly done in teams, the number of discoveries per researcher is greater in smaller teams. These findings reveal collective human behaviors in scientific research and help design better strategies in future knowledge exploration.'),
(84159, 2009, 'plos', 'Modeling signal propagation mechanisms and ligand-based conformational dynamics of the Hsp90 molecular chaperone full-length dimer', 'Morra, Giulia|Verkhivker, Gennady|Colombo, Giorgio', 'Istituto di Chimica del Riconoscimento Molecolare, Consiglio Nazionale delle Ricerche, Milano, Italy.|Istituto di Chimica del Riconoscimento Molecolare, Consiglio Nazionale delle Ricerche, Milano, Italy.|Istituto di Chimica del Riconoscimento Molecolare, Consiglio Nazionale delle Ricerche, Milano, Italy.', 'Italy|Italy|Italy', 104, 'Binding Sites|Computer Simulation|Dimerization|HSP90 Heat-Shock Proteins|Ligands|Models, Chemical|Models, Molecular|Molecular Chaperones|Protein Binding|Protein Conformation', 'Journal Article', '10.1371/journal.pcbi.1000323', '19300478', 'Hsp90 is a molecular chaperone essential for protein folding and activation in normal homeostasis and stress response. ATP binding and hydrolysis facilitate Hsp90 conformational changes required for client activation. Hsp90 plays an important role in disease states, particularly in cancer, where chaperoning of the mutated and overexpressed oncoproteins is important for function. Recent studies have illuminated mechanisms related to the chaperone function. However, an atomic resolution view of Hsp90 conformational dynamics, determined by the presence of different binding partners, is critical to define communication pathways between remote residues in different domains intimately affecting the chaperone cycle. Here, we present a computational analysis of signal propagation and long-range communication pathways in Hsp90. We carried out molecular dynamics simulations of the full-length Hsp90 dimer, combined with essential dynamics, correlation analysis, and a signal propagation model. All-atom MD simulations with timescales of 70 ns have been performed for complexes with the natural substrates ATP and ADP and for the unliganded dimer. We elucidate the mechanisms of signal propagation and determine hot spots involved in interdomain communication pathways from the nucleotide-binding site to the C-terminal domain interface. A comprehensive computational analysis of the Hsp90 communication pathways and dynamics at atomic resolution has revealed the role of the nucleotide in effecting conformational changes, elucidating the mechanisms of signal propagation. Functionally important residues and secondary structure elements emerge as effective mediators of communication between the nucleotide-binding site and the C-terminal interface. Furthermore, we show that specific interdomain signal propagation pathways may be activated as a function of the ligand. Our results support a conformational selection model of the Hsp90 mechanism, whereby the protein may exist in a dynamic equilibrium between different conformational states available on the energy landscape and binding of a specific partner can bias the equilibrium toward functionally relevant complexes.'),
(84160, 2009, 'plos', 'Computational model of the insect pheromone transduction cascade', 'Gu, Yuqiao|Lucas, Philippe|Rospars, Jean-Pierre', 'INRA, UMR 1272, Physiologie de lInsecte: Signalisation et Communication, Versailles, France.|INRA, UMR 1272, Physiologie de lInsecte: Signalisation et Communication, Versailles, France.|INRA, UMR 1272, Physiologie de lInsecte: Signalisation et Communication, Versailles, France.', 'France|France|France', 28, 'Action Potentials|Animals|Computer Simulation|Ion Channel Gating|Male|Models, Neurological|Moths|Olfactory Receptor Neurons|Pheromones|Receptors, Odorant|Receptors, Pheromone|Signal Transduction', 'Journal Article', '10.1371/journal.pcbi.1000321', '19300479', 'A biophysical model of receptor potential generation in the male moth olfactory receptor neuron is presented. It takes into account all pre-effector processes--the translocation of pheromone molecules from air to sensillum lymph, their deactivation and interaction with the receptors, and the G-protein and effector enzyme activation--and focuses on the main post-effector processes. These processes involve the production and degradation of second messengers (IP(3) and DAG), the opening and closing of a series of ionic channels (IP(3)-gated Ca(2+) channel, DAG-gated cationic channel, Ca(2+)-gated Cl(-) channel, and Ca(2+)- and voltage-gated K(+) channel), and Ca(2+) extrusion mechanisms. The whole network is regulated by modulators (protein kinase C and Ca(2+)-calmodulin) that exert feedback inhibition on the effector and channels. The evolution in time of these linked chemical species and currents and the resulting membrane potentials in response to single pulse stimulation of various intensities were simulated. The unknown parameter values were fitted by comparison to the amplitude and temporal characteristics (rising and falling times) of the experimentally measured receptor potential at various pheromone doses. The model obtained captures the main features of the dose-response curves: the wide dynamic range of six decades with the same amplitudes as the experimental data, the short rising time, and the long falling time. It also reproduces the second messenger kinetics. It suggests that the two main types of depolarizing ionic channels play different roles at low and high pheromone concentrations, the DAG-gated cationic channel plays the major role for depolarization at low concentrations, and the Ca(2+)-gated Cl(-) channel plays the major role for depolarization at middle and high concentrations. Several testable predictions are proposed, and future developments are discussed.'),
(84161, 2009, 'plos', 'Quantifying global tolerance of biochemical systems: design implications for moiety-transfer cycles', 'Coelho, Pedro M B M|Salvador, Armindo|Savageau, Michael A', 'Biological Chemistry Group, Chemistry Department, University of Coimbra, Coimbra, Portugal.|Biological Chemistry Group, Chemistry Department, University of Coimbra, Coimbra, Portugal.|Biological Chemistry Group, Chemistry Department, University of Coimbra, Coimbra, Portugal.', 'Portugal|Portugal|Portugal', 29, 'Algorithms|Computer Simulation|Gene Expression Regulation|Models, Biological|Proteome|Signal Transduction', 'Journal Article', '10.1371/journal.pcbi.1000319', '19300483', 'Robustness of organisms is widely observed although difficult to precisely characterize. Performance can remain nearly constant within some neighborhood of the normal operating regime, leading to homeostasis, but then abruptly break down with pathological consequences beyond this neighborhood. Currently, there is no generic approach to identifying boundaries where local performance deteriorates abruptly, and this has hampered understanding of the molecular basis of biological robustness. Here we introduce a generic approach for characterizing boundaries between operational regimes based on the piecewise power-law representation of the systems components. This conceptual framework allows us to define global tolerance as the ratio between the normal value of a parameter and the value at such a boundary. We illustrate the utility of this concept for a class of moiety-transfer cycles, which is a widespread module in biology. Our results show a region of best local performance surrounded by poor regions, also, selection for improved local performance often pushes the operating values away from regime boundaries, thus increasing global tolerance. These predictions agree with experimental data from the reduced nicotinamide adenine dinucleotide phosphate (NADPH) redox cycle of human erythrocytes.'),
(84162, 2009, 'plos', 'T-cell epitope prediction: rescaling can mask biological variation between MHC molecules', 'MacNamara, Aidan|Kadolsky, Ulrich|Bangham, Charles R M|Asquith, Becca', 'Department of Immunology, Imperial College School of Medicine, London, United Kingdom. aidan.macnamara@ic.ac.uk|Department of Immunology, Imperial College School of Medicine, London, United Kingdom. aidan.macnamara@ic.ac.uk|Department of Immunology, Imperial College School of Medicine, London, United Kingdom. aidan.macnamara@ic.ac.uk|Department of Immunology, Imperial College School of Medicine, London, United Kingdom. aidan.macnamara@ic.ac.uk', 'United Kingdom|United Kingdom|United Kingdom|United Kingdom', 27, 'Algorithms|Computer Simulation|Epitope Mapping|Epitopes, T-Lymphocyte|Major Histocompatibility Complex|Models, Chemical|Models, Molecular|Protein Interaction Mapping|T-Lymphocytes', 'Journal Article', '10.1371/journal.pcbi.1000327', '19300484', 'Theoretical methods for predicting CD8+ T-cell epitopes are an important tool in vaccine design and for enhancing our understanding of the cellular immune system. The most popular methods currently available produce binding affinity predictions across a range of MHC molecules. In comparing results between these MHC molecules, it is common practice to apply a normalization procedure known as rescaling, to correct for possible discrepancies between the allelic predictors. Using two of the most popular prediction software packages, NetCTL and NetMHC, we tested the hypothesis that rescaling removes genuine biological variation from the predicted affinities when comparing predictions across a number of MHC molecules. We found that removing the condition of rescaling improved the prediction softwares performance both qualitatively, in terms of ranking epitopes, and quantitatively, in the accuracy of their binding affinity predictions. We suggest that there is biologically significant variation among class 1 MHC molecules and find that retention of this variation leads to significantly more accurate epitope prediction.'),
(84163, 2009, 'plos', 'Accurate detection of recombinant breakpoints in whole-genome alignments', 'Westesson, Oscar|Holmes, Ian', 'Department of Bioengineering, University of California Berkeley, Berkeley, California, United States of America.|Department of Bioengineering, University of California Berkeley, Berkeley, California, United States of America.', 'United States|United States', 25, 'Algorithms|Base Sequence|Chromosome Mapping|Genome|Molecular Sequence Data|Recombination, Genetic|Reproducibility of Results|Sensitivity and Specificity|Sequence Alignment|Sequence Analysis, DNA', 'Evaluation Studies', '10.1371/journal.pcbi.1000318', '19300487', 'We propose a novel method for detecting sites of molecular recombination in multiple alignments. Our approach is a compromise between previous extremes of computationally prohibitive but mathematically rigorous methods and imprecise heuristic methods. Using a combined algorithm for estimating tree structure and hidden Markov model parameters, our program detects changes in phylogenetic tree topology over a multiple sequence alignment. We evaluate our method on benchmark datasets from previous studies on two recombinant pathogens, Neisseria and HIV-1, as well as simulated data. We show that we are not only able to detect recombinant regions of vastly different sizes but also the location of breakpoints with great accuracy. We show that our method does well inferring recombination breakpoints while at the same time maintaining practicality for larger datasets. In all cases, we confirm the breakpoint predictions of previous studies, and in many cases we offer novel predictions.'),
(84164, 2009, 'plos', 'Ras conformational switching: simulating nucleotide-dependent conformational transitions with accelerated molecular dynamics', 'Grant, Barry J|Gorfe, Alemayehu A|McCammon, J Andrew', 'Department of Chemistry and Biochemistry and Center for Theoretical Biological Physics, University of California San Diego, La Jolla, California, United States of America. bgrant@mccammon.ucsd.edu|Department of Chemistry and Biochemistry and Center for Theoretical Biological Physics, University of California San Diego, La Jolla, California, United States of America. bgrant@mccammon.ucsd.edu|Department of Chemistry and Biochemistry and Center for Theoretical Biological Physics, University of California San Diego, La Jolla, California, United States of America. bgrant@mccammon.ucsd.edu', 'United States|United States|United States', 0, 'Binding Sites|Computer Simulation|Enzyme Activation|Models, Chemical|Models, Molecular|Nucleotides|Protein Binding|Protein Conformation|ras Proteins', 'Journal Article', '10.1371/journal.pcbi.1000325', '19300489', 'Ras mediates signaling pathways controlling cell proliferation and development by cycling between GTP- and GDP-bound active and inactive conformational states. Understanding the complete reaction path of this conformational change and its intermediary structures is critical to understanding Ras signaling. We characterize nucleotide-dependent conformational transition using multiple-barrier-crossing accelerated molecular dynamics (aMD) simulations. These transitions, achieved for the first time for wild-type Ras, are impossible to observe with classical molecular dynamics (cMD) simulations due to the large energetic barrier between end states. Mapping the reaction path onto a conformer plot describing the distribution of the crystallographic structures enabled identification of highly populated intermediate structures. These structures have unique switch orientations (residues 25-40 and 57-75) intermediate between GTP and GDP states, or distinct loop3 (46-49), loop7 (105-110), and alpha5 C-terminus (159-166) conformations distal from the nucleotide-binding site. In addition, these barrier-crossing trajectories predict novel nucleotide-dependent correlated motions, including correlations of alpha2 (residues 66-74) with alpha3-loop7 (93-110), loop2 (26-37) with loop10 (145-151), and loop3 (46-49) with alpha5 (152-167). The interconversion between newly identified Ras conformations revealed by this study advances our mechanistic understanding of Ras function. In addition, the pattern of correlated motions provides new evidence for a dynamic linkage between the nucleotide-binding site and the membrane interacting C-terminus critical for the signaling function of Ras. Furthermore, normal mode analysis indicates that the dominant collective motion that occurs during nucleotide-dependent conformational exchange, and captured in aMD (but absent in cMD) simulations, is a low-frequency motion intrinsic to the structure.'),
(84165, 2009, 'plos', 'A systems approach uncovers restrictions for signal interactions regulating genome-wide responses to nutritional cues in Arabidopsis', 'Krouk, Gabriel|Tranchina, Daniel|Lejay, Laurence|Cruikshank, Alexis A|Shasha, Dennis|Coruzzi, Gloria M|Gutiérrez, Rodrigo A', 'Center for Genomics & Systems Biology, New York University, Department of Biology, New York, New York, United States of America.|Center for Genomics & Systems Biology, New York University, Department of Biology, New York, New York, United States of America.|Center for Genomics & Systems Biology, New York University, Department of Biology, New York, New York, United States of America.|Center for Genomics & Systems Biology, New York University, Department of Biology, New York, New York, United States of America.|Center for Genomics & Systems Biology, New York University, Department of Biology, New York, New York, United States of America.|Center for Genomics & Systems Biology, New York University, Department of Biology, New York, New York, United States of America.|Center for Genomics & Systems Biology, New York University, Department of Biology, New York, New York, United States of America.', 'United States|United States|United States|United States|United States|United States|United States', 0, 'Adaptation, Physiological|Arabidopsis|Arabidopsis Proteins|Computer Simulation|Cues|Gene Expression Regulation|Models, Biological|Plant Leaves|Plant Roots|Proteome|Signal Transduction', 'Journal Article', '10.1371/journal.pcbi.1000326', '19300494', 'As sessile organisms, plants must cope with multiple and combined variations of signals in their environment. However, very few reports have studied the genome-wide effects of systematic signal combinations on gene expression. Here, we evaluate a high level of signal integration, by modeling genome-wide expression patterns under a factorial combination of carbon (C), light (L), and nitrogen (N) as binary factors in two organs (O), roots and leaves. Signal management is different between C, N, and L and in shoots and roots. For example, L is the major factor controlling gene expression in leaves. However, in roots there is no obvious prominent signal, and signal interaction is stronger. The major signal interaction events detected genome wide in Arabidopsis roots are deciphered and summarized in a comprehensive conceptual model. Surprisingly, global analysis of gene expression in response to C, N, L, and O revealed that the number of genes controlled by a signal is proportional to the magnitude of the gene expression changes elicited by the signal. These results uncovered a strong constraining structure in plant cell signaling pathways, which prompted us to propose the existence of a code of signal integration.'),
(84166, 2009, 'plos', 'Positional information generated by spatially distributed signaling cascades', 'Muñoz-García, Javier|Neufeld, Zoltan|Kholodenko, Boris N', 'School of Mathematical Sciences and Complex Adaptive Systems Laboratory, University College Dublin, Dublin, Ireland.|School of Mathematical Sciences and Complex Adaptive Systems Laboratory, University College Dublin, Dublin, Ireland.|School of Mathematical Sciences and Complex Adaptive Systems Laboratory, University College Dublin, Dublin, Ireland.', 'Ireland|Ireland|Ireland', 0, 'Computer Simulation|Models, Biological|Multienzyme Complexes|Proteome|Signal Transduction|Subcellular Fractions', 'Journal Article', '10.1371/journal.pcbi.1000330', '19300504', 'The temporal and stationary behavior of protein modification cascades has been extensively studied, yet little is known about the spatial aspects of signal propagation. We have previously shown that the spatial separation of opposing enzymes, such as a kinase and a phosphatase, creates signaling activity gradients. Here we show under what conditions signals stall in the space or robustly propagate through spatially distributed signaling cascades. Robust signal propagation results in activity gradients with long plateaus, which abruptly decay at successive spatial locations. We derive an approximate analytical solution that relates the maximal amplitude and propagation length of each activation profile with the cascade level, protein diffusivity, and the ratio of the opposing enzyme activities. The control of the spatial signal propagation appears to be very different from the control of transient temporal responses for spatially homogenous cascades. For spatially distributed cascades where activating and deactivating enzymes operate far from saturation, the ratio of the opposing enzyme activities is shown to be a key parameter controlling signal propagation. The signaling gradients characteristic for robust signal propagation exemplify a pattern formation mechanism that generates precise spatial guidance for multiple cellular processes and conveys information about the cell size to the nucleus.'),
(84167, 2009, 'plos', 'Directing experimental biology: a case study in mitochondrial biogenesis', 'Hibbs, Matthew A|Myers, Chad L|Huttenhower, Curtis|Hess, David C|Li, Kai|Caudy, Amy A|Troyanskaya, Olga G', 'Lewis-Sigler Institute for Integrative Genomics, Princeton University, Carl Icahn Laboratory, Princeton, New Jersey, United States of America.|Lewis-Sigler Institute for Integrative Genomics, Princeton University, Carl Icahn Laboratory, Princeton, New Jersey, United States of America.|Lewis-Sigler Institute for Integrative Genomics, Princeton University, Carl Icahn Laboratory, Princeton, New Jersey, United States of America.|Lewis-Sigler Institute for Integrative Genomics, Princeton University, Carl Icahn Laboratory, Princeton, New Jersey, United States of America.|Lewis-Sigler Institute for Integrative Genomics, Princeton University, Carl Icahn Laboratory, Princeton, New Jersey, United States of America.|Lewis-Sigler Institute for Integrative Genomics, Princeton University, Carl Icahn Laboratory, Princeton, New Jersey, United States of America.|Lewis-Sigler Institute for Integrative Genomics, Princeton University, Carl Icahn Laboratory, Princeton, New Jersey, United States of America.', 'Jersey|Jersey|Jersey|Jersey|Jersey|Jersey|Jersey', 28, 'Biology|Computer Simulation|Mitochondria|Mitochondrial Proteins|Models, Biological|Research Design|Saccharomyces cerevisiae|Saccharomyces cerevisiae Proteins|Signal Transduction', 'Journal Article', '10.1371/journal.pcbi.1000322', '19300515', 'Computational approaches have promised to organize collections of functional genomics data into testable predictions of gene and protein involvement in biological processes and pathways. However, few such predictions have been experimentally validated on a large scale, leaving many bioinformatic methods unproven and underutilized in the biology community. Further, it remains unclear what biological concerns should be taken into account when using computational methods to drive real-world experimental efforts. To investigate these concerns and to establish the utility of computational predictions of gene function, we experimentally tested hundreds of predictions generated from an ensemble of three complementary methods for the process of mitochondrial organization and biogenesis in Saccharomyces cerevisiae. The biological data with respect to the mitochondria are presented in a companion manuscript published in PLoS Genetics (doi:10.1371/journal.pgen.1000407). Here we analyze and explore the results of this study that are broadly applicable for computationalists applying gene function prediction techniques, including a new experimental comparison with 48 genes representing the genomic background. Our study leads to several conclusions that are important to consider when driving laboratory investigations using computational prediction approaches. While most genes in yeast are already known to participate in at least one biological process, we confirm that genes with known functions can still be strong candidates for annotation of additional gene functions. We find that different analysis techniques and different underlying data can both greatly affect the types of functional predictions produced by computational methods. This diversity allows an ensemble of techniques to substantially broaden the biological scope and breadth of predictions. We also find that performing prediction and validation steps iteratively allows us to more completely characterize a biological area of interest. While this study focused on a specific functional area in yeast, many of these observations may be useful in the contexts of other processes and organisms.'),
(84168, 2009, 'plos', 'Accurate prediction of peptide binding sites on protein surfaces', 'Petsalaki, Evangelia|Stark, Alexander|García-Urdiales, Eduardo|Russell, Robert B', 'European Molecular Biology Laboratory, Heidelberg, Germany.|European Molecular Biology Laboratory, Heidelberg, Germany.|European Molecular Biology Laboratory, Heidelberg, Germany.|European Molecular Biology Laboratory, Heidelberg, Germany.', 'Germany|Germany|Germany|Germany', 116, 'Algorithms|Amino Acid Sequence|Binding Sites|Computer Simulation|Models, Chemical|Models, Molecular|Molecular Sequence Data|Peptides|Protein Binding|Protein Interaction Mapping|Proteins|Sensitivity and Specificity|Sequence Analysis, Protein|Surface Properties', 'Journal Article', '10.1371/journal.pcbi.1000335', '19325869', 'Many important protein-protein interactions are mediated by the binding of a short peptide stretch in one protein to a large globular segment in another. Recent efforts have provided hundreds of examples of new peptides binding to proteins for which a three-dimensional structure is available (either known experimentally or readily modeled) but where no structure of the protein-peptide complex is known. To address this gap, we present an approach that can accurately predict peptide binding sites on protein surfaces. For peptides known to bind a particular protein, the method predicts binding sites with great accuracy, and the specificity of the approach means that it can also be used to predict whether or not a putative or predicted peptide partner will bind. We used known protein-peptide complexes to derive preferences, in the form of spatial position specific scoring matrices, which describe the binding-site environment in globular proteins for each type of amino acid in bound peptides. We then scan the surface of a putative binding protein for sites for each of the amino acids present in a peptide partner and search for combinations of high-scoring amino acid sites that satisfy constraints deduced from the peptide sequence. The method performed well in a benchmark and largely agreed with experimental data mapping binding sites for several recently discovered interactions mediated by peptides, including RG-rich proteins with SMN domains, Epstein-Barr virus LMP1 with TRADD domains, DBC1 with Sir2, and the Ago hook with Argonaute PIWI domain. The method, and associated statistics, is an excellent tool for predicting and studying binding sites for newly discovered peptides mediating critical events in biology.'),
(84169, 2009, 'plos', 'I look in your eyes, honey: internal face features induce spatial frequency preference for human face processing', 'Keil, Matthias S', 'Basic Psychology Department, Faculty for Psychology, University of Barcelona, Barcelona, Spain. mats@cvc.uab.es', 'Spain', 0, 'Biomimetics|Computer Simulation|Face|Female|Humans|Male|Models, Biological|Models, Neurological|Nerve Net|Pattern Recognition, Visual|Visual Cortex', 'Journal Article', '10.1371/journal.pcbi.1000329', '19325870', 'Numerous psychophysical experiments found that humans preferably rely on a narrow band of spatial frequencies for recognition of face identity. A recently conducted theoretical study by the author suggests that this frequency preference reflects an adaptation of the brains face processing machinery to this specific stimulus class (i.e., faces). The purpose of the present study is to examine this property in greater detail and to specifically elucidate the implication of internal face features (i.e., eyes, mouth, and nose). To this end, I parameterized Gabor filters to match the spatial receptive field of contrast sensitive neurons in the primary visual cortex (simple and complex cells). Filter responses to a large number of face images were computed, aligned for internal face features, and response-equalized (whitened). The results demonstrate that the frequency preference is caused by internal face features. Thus, the psychophysically observed human frequency bias for face processing seems to be specifically caused by the intrinsic spatial frequency content of internal face features.'),
(84170, 2009, 'plos', 'Hypertrophy and/or Hyperplasia: Dynamics of Adipose Tissue Growth', 'Jo, Junghyo|Gavrilova, Oksana|Pack, Stephanie|Jou, William|Mullen, Shawn|Sumner, Anne E|Cushman, Samuel W|Periwal, Vipul', 'Laboratory of Biological Modeling, National Institute of Diabetes and Digestive and Kidney Diseases, National Institutes of Health, Bethedsa, Maryland, USA.|Laboratory of Biological Modeling, National Institute of Diabetes and Digestive and Kidney Diseases, National Institutes of Health, Bethedsa, Maryland, USA.|Laboratory of Biological Modeling, National Institute of Diabetes and Digestive and Kidney Diseases, National Institutes of Health, Bethedsa, Maryland, USA.|Laboratory of Biological Modeling, National Institute of Diabetes and Digestive and Kidney Diseases, National Institutes of Health, Bethedsa, Maryland, USA.|Laboratory of Biological Modeling, National Institute of Diabetes and Digestive and Kidney Diseases, National Institutes of Health, Bethedsa, Maryland, USA.|Laboratory of Biological Modeling, National Institute of Diabetes and Digestive and Kidney Diseases, National Institutes of Health, Bethedsa, Maryland, USA.|Laboratory of Biological Modeling, National Institute of Diabetes and Digestive and Kidney Diseases, National Institutes of Health, Bethedsa, Maryland, USA.|Laboratory of Biological Modeling, National Institute of Diabetes and Digestive and Kidney Diseases, National Institutes of Health, Bethedsa, Maryland, USA.', 'United States|United States|United States|United States|United States|United States|United States|United States', 0, 'Adipocytes|Adipose Tissue|Animals|Cell Enlargement|Cell Proliferation|Cell Size|Computer Simulation|Dietary Fats|Hyperplasia|Hypertrophy|Mice|Mice, Inbred C57BL|Models, Biological|Obesity', 'Journal Article', '10.1371/journal.pcbi.1000324', '19325873', 'Adipose tissue grows by two mechanisms: hyperplasia (cell number increase) and hypertrophy (cell size increase). Genetics and diet affect the relative contributions of these two mechanisms to the growth of adipose tissue in obesity. In this study, the size distributions of epididymal adipose cells from two mouse strains, obesity-resistant FVB/N and obesity-prone C57BL/6, were measured after 2, 4, and 12 weeks under regular and high-fat feeding conditions. The total cell number in the epididymal fat pad was estimated from the fat pad mass and the normalized cell-size distribution. The cell number and volume-weighted mean cell size increase as a function of fat pad mass. To address adipose tissue growth precisely, we developed a mathematical model describing the evolution of the adipose cell-size distributions as a function of the increasing fat pad mass, instead of the increasing chronological time. Our model describes the recruitment of new adipose cells and their subsequent development in different strains, and with different diet regimens, with common mechanisms, but with diet- and genetics-dependent model parameters. Compared to the FVB/N strain, the C57BL/6 strain has greater recruitment of small adipose cells. Hyperplasia is enhanced by high-fat diet in a strain-dependent way, suggesting a synergistic interaction between genetics and diet. Moreover, high-fat feeding increases the rate of adipose cell size growth, independent of strain, reflecting the increase in calories requiring storage. Additionally, high-fat diet leads to a dramatic spreading of the size distribution of adipose cells in both strains, this implies an increase in size fluctuations of adipose cells through lipid turnover.'),
(84171, 2009, 'plos', 'Biomedical discovery acceleration, with applications to craniofacial development', 'Leach, Sonia M|Tipney, Hannah|Feng, Weiguo|Baumgartner, William A|Kasliwal, Priyanka|Schuyler, Ronald P|Williams, Trevor|Spritz, Richard A|Hunter, Lawrence', 'Center for Computational Pharmacology, University of Colorado at Denver, Denver, Colorado, USA.|Center for Computational Pharmacology, University of Colorado at Denver, Denver, Colorado, USA.|Center for Computational Pharmacology, University of Colorado at Denver, Denver, Colorado, USA.|Center for Computational Pharmacology, University of Colorado at Denver, Denver, Colorado, USA.|Center for Computational Pharmacology, University of Colorado at Denver, Denver, Colorado, USA.|Center for Computational Pharmacology, University of Colorado at Denver, Denver, Colorado, USA.|Center for Computational Pharmacology, University of Colorado at Denver, Denver, Colorado, USA.|Center for Computational Pharmacology, University of Colorado at Denver, Denver, Colorado, USA.|Center for Computational Pharmacology, University of Colorado at Denver, Denver, Colorado, USA.', 'United States|United States|United States|United States|United States|United States|United States|United States|United States', 0, 'Animals|Artificial Intelligence|Database Management Systems|Databases, Protein|Facial Bones|Information Storage and Retrieval|Mice|Natural Language Processing|Periodicals as Topic|Proteome', 'Journal Article', '10.1371/journal.pcbi.1000215', '19325874', 'The profusion of high-throughput instruments and the explosion of new results in the scientific literature, particularly in molecular biomedicine, is both a blessing and a curse to the bench researcher. Even knowledgeable and experienced scientists can benefit from computational tools that help navigate this vast and rapidly evolving terrain. In this paper, we describe a novel computational approach to this challenge, a knowledge-based system that combines reading, reasoning, and reporting methods to facilitate analysis of experimental data. Reading methods extract information from external resources, either by parsing structured data or using biomedical language processing to extract information from unstructured data, and track knowledge provenance. Reasoning methods enrich the knowledge that results from reading by, for example, noting two genes that are annotated to the same ontology term or database entry. Reasoning is also used to combine all sources into a knowledge network that represents the integration of all sorts of relationships between a pair of genes, and to calculate a combined reliability score. Reporting methods combine the knowledge network with a congruent network constructed from experimental data and visualize the combined network in a tool that facilitates the knowledge-based analysis of that data. An implementation of this approach, called the Hanalyzer, is demonstrated on a large-scale gene expression array dataset relevant to craniofacial development. The use of the tool was critical in the creation of hypotheses regarding the roles of four genes never previously characterized as involved in craniofacial development, each of these hypotheses was validated by further experimental work.'),
(84172, 2009, 'plos', 'Estimation of thalamocortical and intracortical network models from joint thalamic single-electrode and cortical laminar-electrode recordings in the rat barrel system', 'Blomquist, Patrick|Devor, Anna|Indahl, Ulf G|Ulbert, Istvan|Einevoll, Gaute T|Dale, Anders M', 'Department of Mathematical Sciences and Technology and Center for Integrative Genetics, Norwegian University of Life Sciences, As, Norway.|Department of Mathematical Sciences and Technology and Center for Integrative Genetics, Norwegian University of Life Sciences, As, Norway.|Department of Mathematical Sciences and Technology and Center for Integrative Genetics, Norwegian University of Life Sciences, As, Norway.|Department of Mathematical Sciences and Technology and Center for Integrative Genetics, Norwegian University of Life Sciences, As, Norway.|Department of Mathematical Sciences and Technology and Center for Integrative Genetics, Norwegian University of Life Sciences, As, Norway.|Department of Mathematical Sciences and Technology and Center for Integrative Genetics, Norwegian University of Life Sciences, As, Norway.', 'Norway|Norway|Norway|Norway|Norway|Norway', 0, 'Afferent Pathways|Animals|Computer Simulation|Electroencephalography|Evoked Potentials, Somatosensory|Models, Neurological|Nerve Net|Rats|Somatosensory Cortex|Thalamus|Touch|Vibrissae', 'Journal Article', '10.1371/journal.pcbi.1000328', '19325875', 'A new method is presented for extraction of population firing-rate models for both thalamocortical and intracortical signal transfer based on stimulus-evoked data from simultaneous thalamic single-electrode and cortical recordings using linear (laminar) multielectrodes in the rat barrel system. Time-dependent population firing rates for granular (layer 4), supragranular (layer 2/3), and infragranular (layer 5) populations in a barrel column and the thalamic population in the homologous barreloid are extracted from the high-frequency portion (multi-unit activity, MUA) of the recorded extracellular signals. These extracted firing rates are in turn used to identify population firing-rate models formulated as integral equations with exponentially decaying coupling kernels, allowing for straightforward transformation to the more common firing-rate formulation in terms of differential equations. Optimal model structures and model parameters are identified by minimizing the deviation between model firing rates and the experimentally extracted population firing rates. For the thalamocortical transfer, the experimental data favor a model with fast feedforward excitation from thalamus to the layer-4 laminar population combined with a slower inhibitory process due to feedforward and/or recurrent connections and mixed linear-parabolic activation functions. The extracted firing rates of the various cortical laminar populations are found to exhibit strong temporal correlations for the present experimental paradigm, and simple feedforward population firing-rate models combined with linear or mixed linear-parabolic activation function are found to provide excellent fits to the data. The identified thalamocortical and intracortical network models are thus found to be qualitatively very different. While the thalamocortical circuit is optimally stimulated by rapid changes in the thalamic firing rate, the intracortical circuits are low-pass and respond most strongly to slowly varying inputs from the cortical layer-4 population.');
INSERT INTO `papers` (`id`, `ano`, `journal`, `titulo`, `autores`, `afiliacao`, `pais`, `citacoes`, `palavra_chave`, `categorias`, `doi`, `pubmed`, `abstract`) VALUES
(84173, 2009, 'plos', 'BETASCAN: probable beta-amyloids identified by pairwise probabilistic analysis', 'Bryan, Allen W|Menke, Matthew|Cowen, Lenore J|Lindquist, Susan L|Berger, Bonnie', 'Harvard/MIT Division of Health Science and Technology, Bioinformatics and Integrative Genomics, Cambridge, Massachusetts, USA.|Harvard/MIT Division of Health Science and Technology, Bioinformatics and Integrative Genomics, Cambridge, Massachusetts, USA.|Harvard/MIT Division of Health Science and Technology, Bioinformatics and Integrative Genomics, Cambridge, Massachusetts, USA.|Harvard/MIT Division of Health Science and Technology, Bioinformatics and Integrative Genomics, Cambridge, Massachusetts, USA.|Harvard/MIT Division of Health Science and Technology, Bioinformatics and Integrative Genomics, Cambridge, Massachusetts, USA.', 'United States|United States|United States|United States|United States', 73, 'Algorithms|Amino Acid Sequence|Amyloid beta-Peptides|Computer Simulation|Data Interpretation, Statistical|Molecular Sequence Data|Sequence Alignment|Sequence Analysis, Protein|Software', 'Journal Article', '10.1371/journal.pcbi.1000333', '19325876', 'Amyloids and prion proteins are clinically and biologically important beta-structures, whose supersecondary structures are difficult to determine by standard experimental or computational means. In addition, significant conformational heterogeneity is known or suspected to exist in many amyloid fibrils. Recent work has indicated the utility of pairwise probabilistic statistics in beta-structure prediction. We develop here a new strategy for beta-structure prediction, emphasizing the determination of beta-strands and pairs of beta-strands as fundamental units of beta-structure. Our program, BETASCAN, calculates likelihood scores for potential beta-strands and strand-pairs based on correlations observed in parallel beta-sheets. The program then determines the strands and pairs with the greatest local likelihood for all of the sequences potential beta-structures. BETASCAN suggests multiple alternate folding patterns and assigns relative a priori probabilities based solely on amino acid sequence, probability tables, and pre-chosen parameters. The algorithm compares favorably with the results of previous algorithms (BETAPRO, PASTA, SALSA, TANGO, and Zyggregator) in beta-structure prediction and amyloid propensity prediction. Accurate prediction is demonstrated for experimentally determined amyloid beta-structures, for a set of known beta-aggregates, and for the parallel beta-strands of beta-helices, amyloid-like globular proteins. BETASCAN is able both to detect beta-strands with higher sensitivity and to detect the edges of beta-strands in a richly beta-like sequence. For two proteins (Abeta and Het-s), there exist multiple sets of experimental data implying contradictory structures, BETASCAN is able to detect each competing structure as a potential structure variant. The ability to correlate multiple alternate beta-structures to experiment opens the possibility of computational investigation of prion strains and structural heterogeneity of amyloid. BETASCAN is publicly accessible on the Web at http://betascan.csail.mit.edu.'),
(84174, 2009, 'plos', 'Cross-over between discrete and continuous protein structure space: insights into automatic classification and networks of protein structures', 'Pascual-García, Alberto|Abia, David|Ortiz, Angel R|Bastolla, Ugo', 'Centro de Biología Molecular Severo Ochoa (CSIC-UAM), Cantoblanco, Madrid, Spain.|Centro de Biología Molecular Severo Ochoa (CSIC-UAM), Cantoblanco, Madrid, Spain.|Centro de Biología Molecular Severo Ochoa (CSIC-UAM), Cantoblanco, Madrid, Spain.|Centro de Biología Molecular Severo Ochoa (CSIC-UAM), Cantoblanco, Madrid, Spain.', 'Spain|Spain|Spain|Spain', 42, 'Algorithms|Amino Acid Sequence|Artificial Intelligence|Cluster Analysis|Computer Simulation|Models, Chemical|Molecular Sequence Data|Pattern Recognition, Automated|Proteins|Sequence Alignment|Sequence Analysis, Protein', 'Evaluation Studies', '10.1371/journal.pcbi.1000331', '19325884', 'Structural classifications of proteins assume the existence of the fold, which is an intrinsic equivalence class of protein domains. Here, we test in which conditions such an equivalence class is compatible with objective similarity measures. We base our analysis on the transitive property of the equivalence relationship, requiring that similarity of A with B and B with C implies that A and C are also similar. Divergent gene evolution leads us to expect that the transitive property should approximately hold. However, if protein domains are a combination of recurrent short polypeptide fragments, as proposed by several authors, then similarity of partial fragments may violate the transitive property, favouring the continuous view of the protein structure space. We propose a measure to quantify the violations of the transitive property when a clustering algorithm joins elements into clusters, and we find out that such violations present a well defined and detectable cross-over point, from an approximately transitive regime at high structure similarity to a regime with large transitivity violations and large differences in length at low similarity. We argue that protein structure space is discrete and hierarchic classification is justified up to this cross-over point, whereas at lower similarities the structure space is continuous and it should be represented as a network. We have tested the qualitative behaviour of this measure, varying all the choices involved in the automatic classification procedure, i.e., domain decomposition, alignment algorithm, similarity score, and clustering algorithm, and we have found out that this behaviour is quite robust. The final classification depends on the chosen algorithms. We used the values of the clustering coefficient and the transitivity violations to select the optimal choices among those that we tested. Interestingly, this criterion also favours the agreement between automatic and expert classifications. As a domain set, we have selected a consensus set of 2,890 domains decomposed very similarly in SCOP and CATH. As an alignment algorithm, we used a global version of MAMMOTH developed in our group, which is both rapid and accurate. As a similarity measure, we used the size-normalized contact overlap, and as a clustering algorithm, we used average linkage. The resulting automatic classification at the cross-over point was more consistent than expert ones with respect to the structure similarity measure, with 86% of the clusters corresponding to subsets of either SCOP or CATH superfamilies and fewer than 5% containing domains in distinct folds according to both SCOP and CATH. Almost 15% of SCOP superfamilies and 10% of CATH superfamilies were split, consistent with the notion of fold change in protein evolution. These results were qualitatively robust for all choices that we tested, although we did not try to use alignment algorithms developed by other groups. Folds defined in SCOP and CATH would be completely joined in the regime of large transitivity violations where clustering is more arbitrary. Consistently, the agreement between SCOP and CATH at fold level was lower than their agreement with the automatic classification obtained using as a clustering algorithm, respectively, average linkage (for SCOP) or single linkage (for CATH). The networks representing significant evolutionary and structural relationships between clusters beyond the cross-over point may allow us to perform evolutionary, structural, or functional analyses beyond the limits of classification schemes. These networks and the underlying clusters are available at http://ub.cbm.uam.es/research/ProtNet.php.'),
(84175, 2009, 'plos', 'A proposal for a coordinated effort for the determination of brainwide neuroanatomical connectivity in model organisms at a mesoscopic scale', 'Bohland, Jason W|Wu, Caizhi|Barbas, Helen|Bokil, Hemant|Bota, Mihail|Breiter, Hans C|Cline, Hollis T|Doyle, John C|Freed, Peter J|Greenspan, Ralph J|Haber, Suzanne N|Hawrylycz, Michael|Herrera, Daniel G|Hilgetag, Claus C|Huang, Z Josh|Jones, Allan|Jones, Edward G|Karten, Harvey J|Kleinfeld, David|Kötter, Rolf|Lester, Henry A|Lin, John M|Mensh, Brett D|Mikula, Shawn|Panksepp, Jaak|Price, Joseph L|Safdieh, Joseph|Saper, Clifford B|Schiff, Nicholas D|Schmahmann, Jeremy D|Stillman, Bruce W|Svoboda, Karel|Swanson, Larry W|Toga, Arthur W|Van Essen, David C|Watson, James D|Mitra, Partha P', 'Cold Spring Harbor Laboratory, Cold Spring Harbor, New York, USA. bohland@cshl.edu|Cold Spring Harbor Laboratory, Cold Spring Harbor, New York, USA. bohland@cshl.edu|Cold Spring Harbor Laboratory, Cold Spring Harbor, New York, USA. bohland@cshl.edu|Cold Spring Harbor Laboratory, Cold Spring Harbor, New York, USA. bohland@cshl.edu|Cold Spring Harbor Laboratory, Cold Spring Harbor, New York, USA. bohland@cshl.edu|Cold Spring Harbor Laboratory, Cold Spring Harbor, New York, USA. bohland@cshl.edu|Cold Spring Harbor Laboratory, Cold Spring Harbor, New York, USA. bohland@cshl.edu|Cold Spring Harbor Laboratory, Cold Spring Harbor, New York, USA. bohland@cshl.edu|Cold Spring Harbor Laboratory, Cold Spring Harbor, New York, USA. bohland@cshl.edu|Cold Spring Harbor Laboratory, Cold Spring Harbor, New York, USA. bohland@cshl.edu|Cold Spring Harbor Laboratory, Cold Spring Harbor, New York, USA. bohland@cshl.edu|Cold Spring Harbor Laboratory, Cold Spring Harbor, New York, USA. bohland@cshl.edu|Cold Spring Harbor Laboratory, Cold Spring Harbor, New York, USA. bohland@cshl.edu|Cold Spring Harbor Laboratory, Cold Spring Harbor, New York, USA. bohland@cshl.edu|Cold Spring Harbor Laboratory, Cold Spring Harbor, New York, USA. bohland@cshl.edu|Cold Spring Harbor Laboratory, Cold Spring Harbor, New York, USA. bohland@cshl.edu|Cold Spring Harbor Laboratory, Cold Spring Harbor, New York, USA. bohland@cshl.edu|Cold Spring Harbor Laboratory, Cold Spring Harbor, New York, USA. bohland@cshl.edu|Cold Spring Harbor Laboratory, Cold Spring Harbor, New York, USA. bohland@cshl.edu|Cold Spring Harbor Laboratory, Cold Spring Harbor, New York, USA. bohland@cshl.edu|Cold Spring Harbor Laboratory, Cold Spring Harbor, New York, USA. bohland@cshl.edu|Cold Spring Harbor Laboratory, Cold Spring Harbor, New York, USA. bohland@cshl.edu|Cold Spring Harbor Laboratory, Cold Spring Harbor, New York, USA. bohland@cshl.edu|Cold Spring Harbor Laboratory, Cold Spring Harbor, New York, USA. bohland@cshl.edu|Cold Spring Harbor Laboratory, Cold Spring Harbor, New York, USA. bohland@cshl.edu|Cold Spring Harbor Laboratory, Cold Spring Harbor, New York, USA. bohland@cshl.edu|Cold Spring Harbor Laboratory, Cold Spring Harbor, New York, USA. bohland@cshl.edu|Cold Spring Harbor Laboratory, Cold Spring Harbor, New York, USA. bohland@cshl.edu|Cold Spring Harbor Laboratory, Cold Spring Harbor, New York, USA. bohland@cshl.edu|Cold Spring Harbor Laboratory, Cold Spring Harbor, New York, USA. bohland@cshl.edu|Cold Spring Harbor Laboratory, Cold Spring Harbor, New York, USA. bohland@cshl.edu|Cold Spring Harbor Laboratory, Cold Spring Harbor, New York, USA. bohland@cshl.edu|Cold Spring Harbor Laboratory, Cold Spring Harbor, New York, USA. bohland@cshl.edu|Cold Spring Harbor Laboratory, Cold Spring Harbor, New York, USA. bohland@cshl.edu|Cold Spring Harbor Laboratory, Cold Spring Harbor, New York, USA. bohland@cshl.edu|Cold Spring Harbor Laboratory, Cold Spring Harbor, New York, USA. bohland@cshl.edu|Cold Spring Harbor Laboratory, Cold Spring Harbor, New York, USA. bohland@cshl.edu', 'United States|United States|United States|United States|United States|United States|United States|United States|United States|United States|United States|United States|United States|United States|United States|United States|United States|United States|Uni', 188, 'Animals|Brain|Databases, Factual|Humans|Macaca|Mice|Models, Neurological|Nerve Net|Neuroanatomy|Research Design', 'Journal Article', '10.1371/journal.pcbi.1000334', '19325892', 'In this era of complete genomes, our knowledge of neuroanatomical circuitry remains surprisingly sparse. Such knowledge is critical, however, for both basic and clinical research into brain function. Here we advocate for a concerted effort to fill this gap, through systematic, experimental mapping of neural circuits at a mesoscopic scale of resolution suitable for comprehensive, brainwide coverage, using injections of tracers or viral vectors. We detail the scientific and medical rationale and briefly review existing knowledge and experimental techniques. We define a set of desiderata, including brainwide coverage, validated and extensible experimental techniques suitable for standardization and automation, centralized, open-access data repository, compatibility with existing resources, and tractability with current informatics technology. We discuss a hypothetical but tractable plan for mouse, additional efforts for the macaque, and technique development for human. We estimate that the mouse connectivity project could be completed within five years with a comparatively modest budget.'),
(84176, 2009, 'plos', 'Fuzzy logic analysis of kinase pathway crosstalk in TNF/EGF/insulin-induced signaling', 'Aldridge, Bree B|Saez-Rodriguez, Julio|Muhlich, Jeremy L|Sorger, Peter K|Lauffenburger, Douglas A', 'Center for Cell Decision Processes, Cambridge, Massachusetts, United States of America.|Center for Cell Decision Processes, Cambridge, Massachusetts, United States of America.|Center for Cell Decision Processes, Cambridge, Massachusetts, United States of America.|Center for Cell Decision Processes, Cambridge, Massachusetts, United States of America.|Center for Cell Decision Processes, Cambridge, Massachusetts, United States of America.', 'United States|United States|United States|United States|United States', 0, 'Cell Line, Tumor|Colonic Neoplasms|Computer Simulation|Epidermal Growth Factor|Fuzzy Logic|Humans|Models, Biological|Phosphotransferases|Receptor, Insulin|Signal Transduction|Tumor Necrosis Factor-alpha', 'Journal Article', '10.1371/journal.pcbi.1000340', '19343194', 'When modeling cell signaling networks, a balance must be struck between mechanistic detail and ease of interpretation. In this paper we apply a fuzzy logic framework to the analysis of a large, systematic dataset describing the dynamics of cell signaling downstream of TNF, EGF, and insulin receptors in human colon carcinoma cells. Simulations based on fuzzy logic recapitulate most features of the data and generate several predictions involving pathway crosstalk and regulation. We uncover a relationship between MK2 and ERK pathways that might account for the previously identified pro-survival influence of MK2. We also find unexpected inhibition of IKK following EGF treatment, possibly due to down-regulation of autocrine signaling. More generally, fuzzy logic models are flexible, able to incorporate qualitative and noisy data, and powerful enough to produce quantitative predictions and new biological insights about the operation of signaling networks.'),
(84177, 2009, 'plos', 'Evolutionary epidemiology of drug-resistance in space', 'Débarre, Florence|Lenormand, Thomas|Gandon, Sylvain', 'Centre dEcologie Fonctionnelle et Evolutive, CNRS-UMR 5175, Montpellier, France. florence.debarre@cefe.cnrs.fr|Centre dEcologie Fonctionnelle et Evolutive, CNRS-UMR 5175, Montpellier, France. florence.debarre@cefe.cnrs.fr|Centre dEcologie Fonctionnelle et Evolutive, CNRS-UMR 5175, Montpellier, France. florence.debarre@cefe.cnrs.fr', 'France|France|France', 0, 'Biological Evolution|Computer Simulation|Disease Outbreaks|Drug Resistance|Host-Parasite Interactions|Humans|Models, Biological|Parasitic Diseases', 'Journal Article', '10.1371/journal.pcbi.1000337', '19343211', 'How can we optimize the use of drugs against parasites to limit the evolution of drug resistance? This question has been addressed by many theoretical studies focusing either on the mixing of various treatments, or their temporal alternation. Here we consider a different treatment strategy where the use of the drug may vary in space to prevent the rise of drug-resistance. We analyze epidemiological models where drug-resistant and drug-sensitive parasites compete in a one-dimensional spatially heterogeneous environment. Two different parasite life-cycles are considered: (i) direct transmission between hosts, and (ii) vector-borne transmission. In both cases we find a critical size of the treated area, under which the drug-resistant strain cannot persist. This critical size depends on the basic reproductive ratios of each strain in each environment, on the ranges of dispersal, and on the duration of an infection with drug-resistant parasites. We discuss optimal treatment strategies that limit disease prevalence and the evolution of drug-resistance.'),
(84178, 2009, 'plos', 'Natural image coding in V1: how much use is orientation selectivity?', 'Eichhorn, Jan|Sinz, Fabian|Bethge, Matthias', 'Max Planck Institute for Biological Cybernetics, Tübingen, Germany.|Max Planck Institute for Biological Cybernetics, Tübingen, Germany.|Max Planck Institute for Biological Cybernetics, Tübingen, Germany.', 'Germany|Germany|Germany', 32, 'Animals|Biomimetics|Computer Simulation|Form Perception|Humans|Image Interpretation, Computer-Assisted|Models, Neurological|Models, Statistical|Sensitivity and Specificity|Visual Cortex', 'Journal Article', '10.1371/journal.pcbi.1000336', '19343216', 'Orientation selectivity is the most striking feature of simple cell coding in V1 that has been shown to emerge from the reduction of higher-order correlations in natural images in a large variety of statistical image models. The most parsimonious one among these models is linear Independent Component Analysis (ICA), whereas second-order decorrelation transformations such as Principal Component Analysis (PCA) do not yield oriented filters. Because of this finding, it has been suggested that the emergence of orientation selectivity may be explained by higher-order redundancy reduction. To assess the tenability of this hypothesis, it is an important empirical question how much more redundancy can be removed with ICA in comparison to PCA or other second-order decorrelation methods. Although some previous studies have concluded that the amount of higher-order correlation in natural images is generally insignificant, other studies reported an extra gain for ICA of more than 100%. A consistent conclusion about the role of higher-order correlations in natural images can be reached only by the development of reliable quantitative evaluation methods. Here, we present a very careful and comprehensive analysis using three evaluation criteria related to redundancy reduction: In addition to the multi-information and the average log-loss, we compute complete rate-distortion curves for ICA in comparison with PCA. Without exception, we find that the advantage of the ICA filters is small. At the same time, we show that a simple spherically symmetric distribution with only two parameters can fit the data significantly better than the probabilistic model underlying ICA. This finding suggests that, although the amount of higher-order correlation in natural images can in fact be significant, the feature of orientation selectivity does not yield a large contribution to redundancy reduction within the linear filter bank models of V1 simple cells.'),
(84179, 2009, 'plos', 'Discovering cis-regulatory RNAs in Shewanella genomes by Support Vector Machines', 'Xu, Xing|Ji, Yongmei|Stormo, Gary D', 'Department of Genetics, Washington University School of Medicine, St. Louis, Missouri, United States of America.|Department of Genetics, Washington University School of Medicine, St. Louis, Missouri, United States of America.|Department of Genetics, Washington University School of Medicine, St. Louis, Missouri, United States of America.', 'United States|United States|United States', 13, 'Algorithms|Artificial Intelligence|Base Sequence|Chromosome Mapping|Genome, Bacterial|Molecular Sequence Data|Pattern Recognition, Automated|RNA, Bacterial|Regulatory Sequences, Ribonucleic Acid|Sequence Analysis, RNA|Shewanella', 'Journal Article', '10.1371/journal.pcbi.1000338', '19343219', 'An increasing number of cis-regulatory RNA elements have been found to regulate gene expression post-transcriptionally in various biological processes in bacterial systems. Effective computational tools for large-scale identification of novel regulatory RNAs are strongly desired to facilitate our exploration of gene regulation mechanisms and regulatory networks. We present a new computational program named RSSVM (RNA Sampler+Support Vector Machine), which employs Support Vector Machines (SVMs) for efficient identification of functional RNA motifs from random RNA secondary structures. RSSVM uses a set of distinctive features to represent the common RNA secondary structure and structural alignment predicted by RNA Sampler, a tool for accurate common RNA secondary structure prediction, and is trained with functional RNAs from a variety of bacterial RNA motif/gene families covering a wide range of sequence identities. When tested on a large number of known and random RNA motifs, RSSVM shows a significantly higher sensitivity than other leading RNA identification programs while maintaining the same false positive rate. RSSVM performs particularly well on sets with low sequence identities. The combination of RNA Sampler and RSSVM provides a new, fast, and efficient pipeline for large-scale discovery of regulatory RNA motifs. We applied RSSVM to multiple Shewanella genomes and identified putative regulatory RNA motifs in the 5 untranslated regions (UTRs) in S. oneidensis, an important bacterial organism with extraordinary respiratory and metal reducing abilities and great potential for bioremediation and alternative energy generation. From 1002 sets of 5-UTRs of orthologous operons, we identified 166 putative regulatory RNA motifs, including 17 of the 19 known RNA motifs from Rfam, an additional 21 RNA motifs that are supported by literature evidence, 72 RNA motifs overlapping predicted transcription terminators or attenuators, and other candidate regulatory RNA motifs. Our study provides a list of promising novel regulatory RNA motifs potentially involved in post-transcriptional gene regulation. Combined with the previous cis-regulatory DNA motif study in S. oneidensis, this genome-wide discovery of cis-regulatory RNA motifs may offer more comprehensive views of gene regulation at a different level in this organism. The RSSVM software, predictions, and analysis results on Shewanella genomes are available at http://ural.wustl.edu/resources.html#RSSVM.'),
(84180, 2009, 'plos', 'The homeostasis of Plasmodium falciparum-infected red blood cells', 'Mauritz, Jakob M A|Esposito, Alessandro|Ginsburg, Hagai|Kaminski, Clemens F|Tiffert, Teresa|Lew, Virgilio L', 'Department of Chemical Engineering and Biotechnology, University of Cambridge, Cambridge, United Kingdom.|Department of Chemical Engineering and Biotechnology, University of Cambridge, Cambridge, United Kingdom.|Department of Chemical Engineering and Biotechnology, University of Cambridge, Cambridge, United Kingdom.|Department of Chemical Engineering and Biotechnology, University of Cambridge, Cambridge, United Kingdom.|Department of Chemical Engineering and Biotechnology, University of Cambridge, Cambridge, United Kingdom.|Department of Chemical Engineering and Biotechnology, University of Cambridge, Cambridge, United Kingdom.', 'United Kingdom|United Kingdom|United Kingdom|United Kingdom|United Kingdom|United Kingdom', 0, 'Animals|Cells, Cultured|Computer Simulation|Erythrocytes|Homeostasis|Humans|Models, Biological|Plasmodium falciparum', 'Journal Article', '10.1371/journal.pcbi.1000339', '19343220', 'The asexual reproduction cycle of Plasmodium falciparum, the parasite responsible for severe malaria, occurs within red blood cells. A merozoite invades a red cell in the circulation, develops and multiplies, and after about 48 hours ruptures the host cell, releasing 15-32 merozoites ready to invade new red blood cells. During this cycle, the parasite increases the host cell permeability so much that when similar permeabilization was simulated on uninfected red cells, lysis occurred before approximately 48 h. So how could infected cells, with a growing parasite inside, prevent lysis before the parasite has completed its developmental cycle? A mathematical model of the homeostasis of infected red cells suggested that it is the wasteful consumption of host cell hemoglobin that prevents early lysis by the progressive reduction in the colloid-osmotic pressure within the host (the colloid-osmotic hypothesis). However, two critical model predictions, that infected cells would swell to near prelytic sphericity and that the hemoglobin concentration would become progressively reduced, remained controversial. In this paper, we are able for the first time to correlate model predictions with recent experimental data in the literature and explore the fine details of the homeostasis of infected red blood cells during five model-defined periods of parasite development. The conclusions suggest that infected red cells do reach proximity to lytic rupture regardless of their actual volume, thus requiring a progressive reduction in their hemoglobin concentration to prevent premature lysis.'),
(84181, 2009, 'plos', 'From nonspecific DNA-protein encounter complexes to the prediction of DNA-protein interactions', 'Gao, Mu|Skolnick, Jeffrey', 'Center for the Study of Systems Biology, School of Biology, Georgia Institute of Technology, Atlanta, Georgia, United States of America.|Center for the Study of Systems Biology, School of Biology, Georgia Institute of Technology, Atlanta, Georgia, United States of America.', 'Georgia|Georgia', 34, 'Amino Acid Sequence|Base Sequence|Binding Sites|Computer Simulation|DNA|DNA-Binding Proteins|Models, Chemical|Models, Molecular|Molecular Sequence Data|Protein Binding|Sequence Analysis', 'Journal Article', '10.1371/journal.pcbi.1000341', '19343221', 'DNA-protein interactions are involved in many essential biological activities. Because there is no simple mapping code between DNA base pairs and protein amino acids, the prediction of DNA-protein interactions is a challenging problem. Here, we present a novel computational approach for predicting DNA-binding protein residues and DNA-protein interaction modes without knowing its specific DNA target sequence. Given the structure of a DNA-binding protein, the method first generates an ensemble of complex structures obtained by rigid-body docking with a nonspecific canonical B-DNA. Representative models are subsequently selected through clustering and ranking by their DNA-protein interfacial energy. Analysis of these encounter complex models suggests that the recognition sites for specific DNA binding are usually favorable interaction sites for the nonspecific DNA probe and that nonspecific DNA-protein interaction modes exhibit some similarity to specific DNA-protein binding modes. Although the method requires as input the knowledge that the protein binds DNA, in benchmark tests, it achieves better performance in identifying DNA-binding sites than three previously established methods, which are based on sophisticated machine-learning techniques. We further apply our method to protein structures predicted through modeling and demonstrate that our method performs satisfactorily on protein models whose root-mean-square Calpha deviation from native is up to 5 A from their native structures. This study provides valuable structural insights into how a specific DNA-binding protein interacts with a nonspecific DNA sequence. The similarity between the specific DNA-protein interaction mode and nonspecific interaction modes may reflect an important sampling step in search of its specific DNA targets by a DNA-binding protein.'),
(84182, 2009, 'plos', 'Spontaneous local gamma oscillation selectively enhances neural network responsiveness', 'Paik, Se-Bum|Kumar, Tribhawan|Glaser, Donald A', 'Department of Physics, University of California Berkeley, Berkeley, California, United States of America. spaik@berkeley.edu|Department of Physics, University of California Berkeley, Berkeley, California, United States of America. spaik@berkeley.edu|Department of Physics, University of California Berkeley, Berkeley, California, United States of America. spaik@berkeley.edu', 'United States|United States|United States', 23, 'Action Potentials|Animals|Biological Clocks|Brain|Computer Simulation|Humans|Models, Neurological|Nerve Net|Neurons|Synaptic Transmission', 'Journal Article', '10.1371/journal.pcbi.1000342', '19343222', 'Synchronized oscillation is very commonly observed in many neuronal systems and might play an important role in the response properties of the system. We have studied how the spontaneous oscillatory activity affects the responsiveness of a neuronal network, using a neural network model of the visual cortex built from Hodgkin-Huxley type excitatory (E-) and inhibitory (I-) neurons. When the isotropic local E-I and I-E synaptic connections were sufficiently strong, the network commonly generated gamma frequency oscillatory firing patterns in response to random feed-forward (FF) input spikes. This spontaneous oscillatory network activity injects a periodic local current that could amplify a weak synaptic input and enhance the networks responsiveness. When E-E connections were added, we found that the strength of oscillation can be modulated by varying the FF input strength without any changes in single neuron properties or interneuron connectivity. The response modulation is proportional to the oscillation strength, which leads to self-regulation such that the cortical network selectively amplifies various FF inputs according to its strength, without requiring any adaptation mechanism. We show that this selective cortical amplification is controlled by E-E cell interactions. We also found that this response amplification is spatially localized, which suggests that the responsiveness modulation may also be spatially selective. This suggests a generalized mechanism by which neural oscillatory activity can enhance the selectivity of a neural network to FF inputs.'),
(84183, 2009, 'plos', 'Maximal extraction of biological information from genetic interaction data', 'Carter, Gregory W|Galas, David J|Galitski, Timothy', 'Institute for Systems Biology, Seattle, Washington, United States of America. gcarter@systemsbiology.org|Institute for Systems Biology, Seattle, Washington, United States of America. gcarter@systemsbiology.org|Institute for Systems Biology, Seattle, Washington, United States of America. gcarter@systemsbiology.org', 'United States|United States|United States', 0, 'Algorithms|Computer Simulation|Gene Expression Regulation|Information Storage and Retrieval|Models, Genetic|Protein Interaction Mapping|Proteome|Signal Transduction', 'Journal Article', '10.1371/journal.pcbi.1000347', '19343223', 'Extraction of all the biological information inherent in large-scale genetic interaction datasets remains a significant challenge for systems biology. The core problem is essentially that of classification of the relationships among phenotypes of mutant strains into biologically informative rules of gene interaction. Geneticists have determined such classifications based on insights from biological examples, but it is not clear that there is a systematic, unsupervised way to extract this information. In this paper we describe such a method that depends on maximizing a previously described context-dependent information measure to obtain maximally informative biological networks. We have successfully validated this method on two examples from yeast by demonstrating that more biological information is obtained when analysis is guided by this information measure. The context-dependent information measure is a function only of phenotype data and a set of interaction rules, involving no prior biological knowledge. Analysis of the resulting networks reveals that the most biologically informative networks are those with the greatest context-dependent information scores. We propose that these high-complexity networks reveal genetic architecture at a modular level, in contrast to classical genetic interaction rules that order genes in pathways. We suggest that our analysis represents a powerful, data-driven, and general approach to genetic interaction analysis, with particular potential in the study of mammalian systems in which interactions are complex and gene annotation data are sparse.'),
(84184, 2009, 'plos', 'Genome-wide functional divergence after the symbiosis of proteobacteria with insects unraveled through a novel computational approach', 'Toft, Christina|Williams, Tom A|Fares, Mario A', 'Department of Genetics, Trinity College Dublin, University of Dublin, Dublin, Ireland.|Department of Genetics, Trinity College Dublin, University of Dublin, Dublin, Ireland.|Department of Genetics, Trinity College Dublin, University of Dublin, Dublin, Ireland.', 'Ireland|Ireland|Ireland', 0, 'Animals|Ants|Aphids|Archaea|Chromosome Mapping|Genetic Variation|Genomic Islands|Selection, Genetic|Symbiosis', 'Journal Article', '10.1371/journal.pcbi.1000344', '19343224', 'Symbiosis has been among the most important evolutionary steps to generate biological complexity. The establishment of symbiosis required an intimate metabolic link between biological systems with different complexity levels. The strict endo-cellular symbiotic bacteria of insects are beautiful examples of the metabolic coupling between organisms belonging to different kingdoms, a eukaryote and a prokaryote. The host (eukaryote) provides the endosymbiont (prokaryote) with a stable cellular environment while the endosymbiont supplements the hosts diet with essential metabolites. For such communication to take place, endosymbionts genomes have suffered dramatic modifications and reconfigurations of proteins functions. Two of the main modifications, loss of genes redundant for endosymbiotic bacteria or the host and bacterial genome streamlining, have been extensively studied. However, no studies have accounted for possible functional shifts in the endosymbiotic proteomes. Here, we develop a simple method to screen genomes for evidence of functional divergence between two species clusters, and we apply it to identify functional shifts in the endosymbiotic proteomes. Despite the strong effects of genetic drift in the endosymbiotic systems, we unexpectedly identified genes to be under stronger selective constraints in endosymbionts of aphids and ants than in their free-living bacterial relatives. These genes are directly involved in supplementing the hosts diet with essential metabolites. A test of functional divergence supports a strong relationship between the endosymbiosis and the functional shifts of proteins involved in the metabolic communication with the insect host. The correlation between functional divergence in the endosymbiotic bacterium and the ecological requirements of the host uncovers their intimate biochemical and metabolic communication and provides insights on the role of symbiosis in generating species diversity.'),
(84185, 2009, 'plos', 'Probing the flexibility of large conformational changes in protein structures through local perturbations', 'Ho, Bosco K|Agard, David A', 'Howard Hughes Medical Institute and the Department of Biochemistry, University of California San Francisco, San Francisco, California, United States of America. boscoh@gmail.com|Howard Hughes Medical Institute and the Department of Biochemistry, University of California San Francisco, San Francisco, California, United States of America. boscoh@gmail.com', 'United States|United States', 0, 'Amino Acid Sequence|Computer Simulation|Models, Chemical|Models, Molecular|Molecular Sequence Data|Protein Conformation|Sequence Analysis, Protein|Triose-Phosphate Isomerase', 'Journal Article', '10.1371/journal.pcbi.1000343', '19343225', 'Protein conformational changes and dynamic behavior are fundamental for such processes as catalysis, regulation, and substrate recognition. Although protein dynamics have been successfully explored in computer simulation, there is an intermediate-scale of motions that has proven difficult to simulate - the motion of individual segments or domains that move independently of the body the protein. Here, we introduce a molecular-dynamics perturbation method, the Rotamerically Induced Perturbation (RIP), which can generate large, coherent motions of structural elements in picoseconds by applying large torsional perturbations to individual sidechains. Despite the large-scale motions, secondary structure elements remain intact without the need for applying backbone positional restraints. Owing to its computational efficiency, RIP can be applied to every residue in a protein, producing a global map of deformability. This map is remarkably sparse, with the dominant sites of deformation generally found on the protein surface. The global map can be used to identify loops and helices that are less tightly bound to the protein and thus are likely sites of dynamic modulation that may have important functional consequences. Additionally, they identify individual residues that have the potential to drive large-scale coherent conformational change. Applying RIP to two well-studied proteins, Dihdydrofolate Reductase and Triosephosphate Isomerase, which possess functionally-relevant mobile loops that fluctuate on the microsecond/millisecond timescale, the RIP deformation map identifies and recapitulates the flexibility of these elements. In contrast, the RIP deformation map of alpha-lytic protease, a kinetically stable protein, results in a map with no significant deformations. In the N-terminal domain of HSP90, the RIP deformation map clearly identifies the ligand-binding lid as a highly flexible region capable of large conformational changes. In the Estrogen Receptor ligand-binding domain, the RIP deformation map is quite sparse except for one large conformational change involving Helix-12, which is the structural element that allosterically links ligand binding to receptor activation. RIP analysis has the potential to discover sites of functional conformational changes and the linchpin residues critical in determining these conformational states.'),
(84186, 2009, 'plos', 'An analytically solvable model for rapid evolution of modular structure', 'Kashtan, Nadav|Mayo, Avi E|Kalisky, Tomer|Alon, Uri', 'Department of Molecular Cell Biology, Weizmann Institute of Science, Rehovot, Israel.|Department of Molecular Cell Biology, Weizmann Institute of Science, Rehovot, Israel.|Department of Molecular Cell Biology, Weizmann Institute of Science, Rehovot, Israel.|Department of Molecular Cell Biology, Weizmann Institute of Science, Rehovot, Israel.', 'Israel|Israel|Israel|Israel', 32, 'Bacterial Physiological Phenomena|Biological Evolution|Computer Simulation|Evolution, Molecular|Models, Genetic', 'Journal Article', '10.1371/journal.pcbi.1000355', '19360090', 'Biological systems often display modularity, in the sense that they can be decomposed into nearly independent subsystems. Recent studies have suggested that modular structure can spontaneously emerge if goals (environments) change over time, such that each new goal shares the same set of sub-problems with previous goals. Such modularly varying goals can also dramatically speed up evolution, relative to evolution under a constant goal. These studies were based on simulations of model systems, such as logic circuits and RNA structure, which are generally not easy to treat analytically. We present, here, a simple model for evolution under modularly varying goals that can be solved analytically. This model helps to understand some of the fundamental mechanisms that lead to rapid emergence of modular structure under modularly varying goals. In particular, the model suggests a mechanism for the dramatic speedup in evolution observed under such temporally varying goals.'),
(84187, 2009, 'plos', 'A dynamic network approach for the study of human phenotypes', 'Hidalgo, César A|Blumm, Nicholas|Barabási, Albert-László|Christakis, Nicholas A', 'Center for International Development and Harvard Kennedy School, Harvard University, Cambridge, Massachusetts, United States of America.|Center for International Development and Harvard Kennedy School, Harvard University, Cambridge, Massachusetts, United States of America.|Center for International Development and Harvard Kennedy School, Harvard University, Cambridge, Massachusetts, United States of America.|Center for International Development and Harvard Kennedy School, Harvard University, Cambridge, Massachusetts, United States of America.', 'United States|United States|United States|United States', 342, 'Algorithms|Comorbidity|Disease Susceptibility|Epidemiologic Measurements|Humans|Phenotype|Proportional Hazards Models|Risk Assessment|Risk Factors|United States', 'Journal Article', '10.1371/journal.pcbi.1000353', '19360091', 'The use of networks to integrate different genetic, proteomic, and metabolic datasets has been proposed as a viable path toward elucidating the origins of specific diseases. Here we introduce a new phenotypic database summarizing correlations obtained from the disease history of more than 30 million patients in a Phenotypic Disease Network (PDN). We present evidence that the structure of the PDN is relevant to the understanding of illness progression by showing that (1) patients develop diseases close in the network to those they already have, (2) the progression of disease along the links of the network is different for patients of different genders and ethnicities, (3) patients diagnosed with diseases which are more highly connected in the PDN tend to die sooner than those affected by less connected diseases, and (4) diseases that tend to be preceded by others in the PDN tend to be more connected than diseases that precede other illnesses, and are associated with higher degrees of mortality. Our findings show that disease progression can be represented and studied using network methods, offering the potential to enhance our understanding of the origin and evolution of human diseases. The dataset introduced here, released concurrently with this publication, represents the largest relational phenotypic resource publicly available to the research community.'),
(84188, 2009, 'plos', 'Predicting phenotypic diversity and the underlying quantitative molecular transitions', 'Giurumescu, Claudiu A|Sternberg, Paul W|Asthagiri, Anand R', 'Division of Chemistry and Chemical Engineering, California Institute of Technology, Pasadena, California, United States of America.|Division of Chemistry and Chemical Engineering, California Institute of Technology, Pasadena, California, United States of America.|Division of Chemistry and Chemical Engineering, California Institute of Technology, Pasadena, California, United States of America.', 'United States|United States|United States', 0, 'Animals|Caenorhabditis elegans|Caenorhabditis elegans Proteins|Computer Simulation|Female|Gene Expression Regulation, Developmental|Models, Biological|Phenotype|Signal Transduction|Species Specificity|Vulva', 'Journal Article', '10.1371/journal.pcbi.1000354', '19360093', 'During development, signaling networks control the formation of multicellular patterns. To what extent quantitative fluctuations in these complex networks may affect multicellular phenotype remains unclear. Here, we describe a computational approach to predict and analyze the phenotypic diversity that is accessible to a developmental signaling network. Applying this framework to vulval development in C. elegans, we demonstrate that quantitative changes in the regulatory network can render approximately 500 multicellular phenotypes. This phenotypic capacity is an order-of-magnitude below the theoretical upper limit for this system but yet is large enough to demonstrate that the system is not restricted to a select few outcomes. Using metrics to gauge the robustness of these phenotypes to parameter perturbations, we identify a select subset of novel phenotypes that are the most promising for experimental validation. In addition, our model calculations provide a layout of these phenotypes in network parameter space. Analyzing this landscape of multicellular phenotypes yielded two significant insights. First, we show that experimentally well-established mutant phenotypes may be rendered using non-canonical network perturbations. Second, we show that the predicted multicellular patterns include not only those observed in C. elegans, but also those occurring exclusively in other species of the Caenorhabditis genus. This result demonstrates that quantitative diversification of a common regulatory network is indeed demonstrably sufficient to generate the phenotypic differences observed across three major species within the Caenorhabditis genus. Using our computational framework, we systematically identify the quantitative changes that may have occurred in the regulatory network during the evolution of these species. Our model predictions show that significant phenotypic diversity may be sampled through quantitative variations in the regulatory network without overhauling the core network architecture. Furthermore, by comparing the predicted landscape of phenotypes to multicellular patterns that have been experimentally observed across multiple species, we systematically trace the quantitative regulatory changes that may have occurred during the evolution of the Caenorhabditis genus.'),
(84189, 2009, 'plos', 'Amyloidogenesis abolished by proline substitutions but enhanced by lipid binding', 'Jiang, Ping|Xu, Weixin|Mu, Yuguang', 'School of Biological Sciences, Nanyang Technological University, Singapore.|School of Biological Sciences, Nanyang Technological University, Singapore.|School of Biological Sciences, Nanyang Technological University, Singapore.', 'Singapore|Singapore|Singapore', 34, 'Amino Acid Substitution|Amyloid beta-Protein Precursor|Animals|Binding Sites|Computer Simulation|Lipids|Models, Chemical|Models, Molecular|Proline|Protein Binding|Rats', 'Journal Article', '10.1371/journal.pcbi.1000357', '19360098', 'The influence of lipid molecules on the aggregation of a highly amyloidogenic segment of human islet amyloid polypeptide, hIAPP20-29, and the corresponding sequence from rat has been studied by all-atom replica exchange molecular dynamics (REMD) simulations with explicit solvent model. hIAPP20-29 fragments aggregate into partially ordered beta-sheet oligomers and then undergo large conformational reorganization and convert into parallel/antiparallel beta-sheet oligomers in mixed in-register and out-of-register patterns. The hydrophobic interaction between lipid tails and residues at positions 23-25 is found to stabilize the ordered beta-sheet structure, indicating a catalysis role of lipid molecules in hIAPP20-29 self-assembly. The rat IAPP variants with three proline residues maintain unstructured micelle-like oligomers, which is consistent with non-amyloidogenic behavior observed in experimental studies. Our study provides the atomic resolution descriptions of the catalytic function of lipid molecules on the aggregation of IAPP peptides.');
INSERT INTO `papers` (`id`, `ano`, `journal`, `titulo`, `autores`, `afiliacao`, `pais`, `citacoes`, `palavra_chave`, `categorias`, `doi`, `pubmed`, `abstract`) VALUES
(84190, 2009, 'plos', 'Estimating the location and spatial extent of a covert anthrax release', 'Legrand, Judith|Egan, Joseph R|Hall, Ian M|Cauchemez, Simon|Leach, Steve|Ferguson, Neil M', 'MRC Centre for Outbreak Analysis and Modelling, Department of Infectious Diseases Epidemiology, Imperial College London, London, United Kingdom. jlegrand@imperial.ac.uk|MRC Centre for Outbreak Analysis and Modelling, Department of Infectious Diseases Epidemiology, Imperial College London, London, United Kingdom. jlegrand@imperial.ac.uk|MRC Centre for Outbreak Analysis and Modelling, Department of Infectious Diseases Epidemiology, Imperial College London, London, United Kingdom. jlegrand@imperial.ac.uk|MRC Centre for Outbreak Analysis and Modelling, Department of Infectious Diseases Epidemiology, Imperial College London, London, United Kingdom. jlegrand@imperial.ac.uk|MRC Centre for Outbreak Analysis and Modelling, Department of Infectious Diseases Epidemiology, Imperial College London, London, United Kingdom. jlegrand@imperial.ac.uk|MRC Centre for Outbreak Analysis and Modelling, Department of Infectious Diseases Epidemiology, Imperial College London, London, United Kingdom. jlegrand@imperial.ac.uk', 'United Kingdom|United Kingdom|United Kingdom|United Kingdom|United Kingdom|United Kingdom', 0, 'Aerosols|Algorithms|Anthrax|Bacillus anthracis|Bioterrorism|Computer Simulation|Disease Outbreaks|Humans|Markov Chains|Models, Biological|Models, Statistical|Public Health Practice|Spores, Bacterial|Topography, Medical', 'Journal Article', '10.1371/journal.pcbi.1000356', '19360099', 'Rapidly identifying the features of a covert release of an agent such as anthrax could help to inform the planning of public health mitigation strategies. Previous studies have sought to estimate the time and size of a bioterror attack based on the symptomatic onset dates of early cases. We extend the scope of these methods by proposing a method for characterizing the time, strength, and also the location of an aerosolized pathogen release. A back-calculation method is developed allowing the characterization of the release based on the data on the first few observed cases of the subsequent outbreak, meteorological data, population densities, and data on population travel patterns. We evaluate this method on small simulated anthrax outbreaks (about 25-35 cases) and show that it could date and localize a release after a few cases have been observed, although misspecifications of the spore dispersion model, or the within-host dynamics model, on which the method relies can bias the estimates. Our method could also provide an estimate of the outbreaks geographical extent and, as a consequence, could help to identify populations at risk and, therefore, requiring prophylactic treatment. Our analysis demonstrates that while estimates based on the first ten or 15 observed cases were more accurate and less sensitive to model misspecifications than those based on five cases, overall mortality is minimized by targeting prophylactic treatment early on the basis of estimates made using data on the first five cases. The method we propose could provide early estimates of the time, strength, and location of an aerosolized anthrax release and the geographical extent of the subsequent outbreak. In addition, estimates of release features could be used to parameterize more detailed models allowing the simulation of control strategies and intervention logistics.'),
(84191, 2009, 'plos', 'The role of environmental transmission in recurrent avian influenza epidemics', 'Breban, Romulus|Drake, John M|Stallknecht, David E|Rohani, Pejman', 'Odum School of Ecology, University of Georgia, Athens, Georgia, United States of America. breban@gmail.com|Odum School of Ecology, University of Georgia, Athens, Georgia, United States of America. breban@gmail.com|Odum School of Ecology, University of Georgia, Athens, Georgia, United States of America. breban@gmail.com|Odum School of Ecology, University of Georgia, Athens, Georgia, United States of America. breban@gmail.com', 'Georgia|Georgia|Georgia|Georgia', 0, 'Animals|Birds|Disease Outbreaks|Environmental Exposure|Influenza A virus|Influenza in Birds|Models, Biological', 'Journal Article', '10.1371/journal.pcbi.1000346', '19360126', 'Avian influenza virus (AIV) persists in North American wild waterfowl, exhibiting major outbreaks every 2-4 years. Attempts to explain the patterns of periodicity and persistence using simple direct transmission models are unsuccessful. Motivated by empirical evidence, we examine the contribution of an overlooked AIV transmission mode: environmental transmission. It is known that infectious birds shed large concentrations of virions in the environment, where virions may persist for a long time. We thus propose that, in addition to direct fecal/oral transmission, birds may become infected by ingesting virions that have long persisted in the environment. We design a new host-pathogen model that combines within-season transmission dynamics, between-season migration and reproduction, and environmental variation. Analysis of the model yields three major results. First, environmental transmission provides a persistence mechanism within small communities where epidemics cannot be sustained by direct transmission only (i.e., communities smaller than the critical community size). Second, environmental transmission offers a parsimonious explanation of the 2-4 year periodicity of avian influenza epidemics. Third, very low levels of environmental transmission (i.e., few cases per year) are sufficient for avian influenza to persist in populations where it would otherwise vanish.'),
(84192, 2009, 'plos', 'Statistical methods for detecting differentially abundant features in clinical metagenomic samples', 'White, James Robert|Nagarajan, Niranjan|Pop, Mihai', 'Applied Mathematics and Scientific Computation Program, Center for Bioinformatics and Computational Biology, University of Maryland, College Park, Maryland, United States of America.|Applied Mathematics and Scientific Computation Program, Center for Bioinformatics and Computational Biology, University of Maryland, College Park, Maryland, United States of America.|Applied Mathematics and Scientific Computation Program, Center for Bioinformatics and Computational Biology, University of Maryland, College Park, Maryland, United States of America.', 'United States|United States|United States', 808, 'Bacteria|Chromosome Mapping|DNA, Bacterial|Gene Expression Profiling|Humans|Intestines|Obesity', 'Journal Article', '10.1371/journal.pcbi.1000352', '19360128', 'Numerous studies are currently underway to characterize the microbial communities inhabiting our world. These studies aim to dramatically expand our understanding of the microbial biosphere and, more importantly, hope to reveal the secrets of the complex symbiotic relationship between us and our commensal bacterial microflora. An important prerequisite for such discoveries are computational tools that are able to rapidly and accurately compare large datasets generated from complex bacterial communities to identify features that distinguish them.We present a statistical method for comparing clinical metagenomic samples from two treatment populations on the basis of count data (e.g. as obtained through sequencing) to detect differentially abundant features. Our method, Metastats, employs the false discovery rate to improve specificity in high-complexity environments, and separately handles sparsely-sampled features using Fishers exact test. Under a variety of simulations, we show that Metastats performs well compared to previously used methods, and significantly outperforms other methods for features with sparse counts. We demonstrate the utility of our method on several datasets including a 16S rRNA survey of obese and lean human gut microbiomes, COG functional profiles of infant and mature gut microbiomes, and bacterial and viral metabolic subsystem data inferred from random sequencing of 85 metagenomes. The application of our method to the obesity dataset reveals differences between obese and lean subjects not reported in the original study. For the COG and subsystem datasets, we provide the first statistically rigorous assessment of the differences between these populations. The methods described in this paper are the first to address clinical metagenomic datasets comprising samples from multiple subjects. Our methods are robust across datasets of varied complexity and sampling level. While designed for metagenomic applications, our software can also be applied to digital gene expression studies (e.g. SAGE). A web server implementation of our methods and freely available source code can be found at http://metastats.cbcb.umd.edu/.'),
(84193, 2009, 'plos', 'Towards prediction of metabolic products of polyketide synthases: an in silico analysis', 'Yadav, Gitanjali|Gokhale, Rajesh S|Mohanty, Debasisa', 'National Institute of Immunology, New Delhi, India.|National Institute of Immunology, New Delhi, India.|National Institute of Immunology, New Delhi, India.', 'India|India|India', 0, 'Amino Acid Sequence|Computer Simulation|Enzyme Activation|Models, Biological|Models, Chemical|Molecular Sequence Data|Polyketide Synthases|Protein Interaction Mapping|Proteome|Sequence Analysis, Protein', 'Journal Article', '10.1371/journal.pcbi.1000351', '19360130', 'Sequence data arising from an increasing number of partial and complete genome projects is revealing the presence of the polyketide synthase (PKS) family of genes not only in microbes and fungi but also in plants and other eukaryotes. PKSs are huge multifunctional megasynthases that use a variety of biosynthetic paradigms to generate enormously diverse arrays of polyketide products that posses several pharmaceutically important properties. The remarkable conservation of these gene clusters across organisms offers abundant scope for obtaining novel insights into PKS biosynthetic code by computational analysis. We have carried out a comprehensive in silico analysis of modular and iterative gene clusters to test whether chemical structures of the secondary metabolites can be predicted from PKS protein sequences. Here, we report the success of our method and demonstrate the feasibility of deciphering the putative metabolic products of uncharacterized PKS clusters found in newly sequenced genomes. Profile Hidden Markov Model analysis has revealed distinct sequence features that can distinguish modular PKS proteins from their iterative counterparts. For iterative PKS proteins, structural models of iterative ketosynthase (KS) domains have revealed novel correlations between the size of the polyketide products and volume of the active site pocket. Furthermore, we have identified key residues in the substrate binding pocket that control the number of chain extensions in iterative PKSs. For modular PKS proteins, we describe for the first time an automated method based on crucial intermolecular contacts that can distinguish the correct biosynthetic order of substrate channeling from a large number of non-cognate combinatorial possibilities. Taken together, our in silico analysis provides valuable clues for formulating rules for predicting polyketide products of iterative as well as modular PKS clusters. These results have promising potential for discovery of novel natural products by genome mining and rational design of novel natural products.'),
(84194, 2009, 'plos', 'Dissociating variability and effort as determinants of coordination', 'OSullivan, Ian|Burdet, Etienne|Diedrichsen, Jörn', 'Wolfson Centre for Cognitive Neuroscience, School of Psychology, University of Wales, Bangor, United Kingdom.|Wolfson Centre for Cognitive Neuroscience, School of Psychology, University of Wales, Bangor, United Kingdom.|Wolfson Centre for Cognitive Neuroscience, School of Psychology, University of Wales, Bangor, United Kingdom.', 'United Kingdom|United Kingdom|United Kingdom', 0, 'Computer Simulation|Fingers|Humans|Models, Neurological|Motor Skills|Movement|Muscle Contraction|Muscle, Skeletal|Physical Exertion|Postural Balance|Task Performance and Analysis', 'Journal Article', '10.1371/journal.pcbi.1000345', '19360132', 'When coordinating movements, the nervous system often has to decide how to distribute work across a number of redundant effectors. Here, we show that humans solve this problem by trying to minimize both the variability of motor output and the effort involved. In previous studies that investigated the temporal shape of movements, these two selective pressures, despite having very different theoretical implications, could not be distinguished, because noise in the motor system increases with the motor commands, minimization of effort or variability leads to very similar predictions. When multiple effectors with different noise and effort characteristics have to be combined, however, these two cost terms can be dissociated. Here, we measure the importance of variability and effort in coordination by studying how humans share force production between two fingers. To capture variability, we identified the coefficient of variation of the index and little fingers. For effort, we used the sum of squared forces and the sum of squared forces normalized by the maximum strength of each effector. These terms were then used to predict the optimal force distribution for a task in which participants had to produce a target total force of 4-16 N, by pressing onto two isometric transducers using different combinations of fingers. By comparing the predicted distribution across fingers to the actual distribution chosen by participants, we were able to estimate the relative importance of variability and effort of 1:7, with the unnormalized effort being most important. Our results indicate that the nervous system uses multi-effector redundancy to minimize both the variability of the produced output and effort, although effort costs clearly outweighed variability costs.'),
(84195, 2009, 'plos', 'Adventures in semantic publishing: exemplar semantic enhancements of a research article', 'Shotton, David|Portwin, Katie|Klyne, Graham|Miles, Alistair', 'Image Bioinformatics Research Group, Department of Zoology, University of Oxford, Oxford, United Kingdom. david.shotton@zoo.ox.ac.uk|Image Bioinformatics Research Group, Department of Zoology, University of Oxford, Oxford, United Kingdom. david.shotton@zoo.ox.ac.uk|Image Bioinformatics Research Group, Department of Zoology, University of Oxford, Oxford, United Kingdom. david.shotton@zoo.ox.ac.uk|Image Bioinformatics Research Group, Department of Zoology, University of Oxford, Oxford, United Kingdom. david.shotton@zoo.ox.ac.uk', 'United Kingdom|United Kingdom|United Kingdom|United Kingdom', 108, 'Information Dissemination|Natural Language Processing|Periodicals as Topic|Publishing|Research Design|Semantics|Writing', 'Journal Article', '10.1371/journal.pcbi.1000361', '19381256', 'Scientific innovation depends on finding, integrating, and re-using the products of previous research. Here we explore how recent developments in Web technology, particularly those related to the publication of data and metadata, might assist that process by providing semantic enhancements to journal articles within the mainstream process of scholarly journal publishing. We exemplify this by describing semantic enhancements we have made to a recent biomedical research article taken from PLoS Neglected Tropical Diseases, providing enrichment to its content and increased access to datasets within it. These semantic enhancements include provision of live DOIs and hyperlinks, semantic markup of textual terms, with links to relevant third-party information resources, interactive figures, a re-orderable reference list, a document summary containing a study summary, a tag cloud, and a citation analysis, and two novel types of semantic enrichment: the first, a Supporting Claims Tooltip to permit Citations in Context, and the second, Tag Trees that bring together semantically related terms. In addition, we have published downloadable spreadsheets containing data from within tables and figures, have enriched these with provenance information, and have demonstrated various types of data fusion (mashups) with results from other research articles and with Google Maps. We have also published machine-readable RDF metadata both about the article and about the references it cites, for which we developed a Citation Typing Ontology, CiTO (http://purl.org/net/cito/). The enhanced article, which is available at http://dx.doi.org/10.1371/journal.pntd.0000228.x001, presents a compelling existence proof of the possibilities of semantic publication. We hope the showcase of examples and ideas it contains, described in this paper, will excite the imaginations of researchers and publishers, stimulating them to explore the possibilities of semantic publishing for their own research articles, and thereby break down present barriers to the discovery and re-use of information within traditional modes of scholarly communication.'),
(84196, 2009, 'plos', 'Inferring stabilizing mutations from protein phylogenies: application to influenza hemagglutinin', 'Bloom, Jesse D|Glassman, Matthew J', 'Division of Biology, California Institute of Technology, Pasadena, California, USA. jesse.bloom@gmail.com|Division of Biology, California Institute of Technology, Pasadena, California, USA. jesse.bloom@gmail.com', 'United States|United States', 44, 'Amino Acid Sequence|Base Sequence|Biological Evolution|DNA Mutational Analysis|Evolution, Molecular|Genomic Instability|Hemagglutinin Glycoproteins, Influenza Virus|Molecular Sequence Data|Mutation|Phylogeny|Sequence Analysis, Protein', 'Journal Article', '10.1371/journal.pcbi.1000349', '19381264', 'One selection pressure shaping sequence evolution is the requirement that a protein fold with sufficient stability to perform its biological functions. We present a conceptual framework that explains how this requirement causes the probability that a particular amino acid mutation is fixed during evolution to depend on its effect on protein stability. We mathematically formalize this framework to develop a Bayesian approach for inferring the stability effects of individual mutations from homologous protein sequences of known phylogeny. This approach is able to predict published experimentally measured mutational stability effects (DeltaDeltaG values) with an accuracy that exceeds both a state-of-the-art physicochemical modeling program and the sequence-based consensus approach. As a further test, we use our phylogenetic inference approach to predict stabilizing mutations to influenza hemagglutinin. We introduce these mutations into a temperature-sensitive influenza virus with a defect in its hemagglutinin gene and experimentally demonstrate that some of the mutations allow the virus to grow at higher temperatures. Our work therefore describes a powerful new approach for predicting stabilizing mutations that can be successfully applied even to large, complex proteins such as hemagglutinin. This approach also makes a mathematical link between phylogenetics and experimentally measurable protein properties, potentially paving the way for more accurate analyses of molecular evolution.'),
(84197, 2009, 'plos', 'Allosteric transitions of supramolecular systems explored by network models: application to chaperonin GroEL', 'Yang, Zheng|Májek, Peter|Bahar, Ivet', 'Department of Computational Biology, School of Medicine, University of Pittsburgh, Pittsburgh, Pennsylvania, USA.|Department of Computational Biology, School of Medicine, University of Pittsburgh, Pittsburgh, Pennsylvania, USA.|Department of Computational Biology, School of Medicine, University of Pittsburgh, Pittsburgh, Pennsylvania, USA.', 'United States|United States|United States', 110, 'Chaperonin 60|Computer Simulation|Isomerism|Models, Chemical|Models, Molecular|Multiprotein Complexes|Protein Conformation', 'Journal Article', '10.1371/journal.pcbi.1000360', '19381265', 'Identification of pathways involved in the structural transitions of biomolecular systems is often complicated by the transient nature of the conformations visited across energy barriers and the multiplicity of paths accessible in the multidimensional energy landscape. This task becomes even more challenging in exploring molecular systems on the order of megadaltons. Coarse-grained models that lend themselves to analytical solutions appear to be the only possible means of approaching such cases. Motivated by the utility of elastic network models for describing the collective dynamics of biomolecular systems and by the growing theoretical and experimental evidence in support of the intrinsic accessibility of functional substates, we introduce a new method, adaptive anisotropic network model (aANM), for exploring functional transitions. Application to bacterial chaperonin GroEL and comparisons with experimental data, results from action minimization algorithm, and previous simulations support the utility of aANM as a computationally efficient, yet physically plausible, tool for unraveling potential transition pathways sampled by large complexes/assemblies. An important outcome is the assessment of the critical inter-residue interactions formed/broken near the transition state(s), most of which involve conserved residues.'),
(84198, 2009, 'plos', 'Design principles for riboswitch function', 'Beisel, Chase L|Smolke, Christina D', 'Division of Chemistry and Chemical Engineering, California Institute of Technology, Pasadena, California, USA.|Division of Chemistry and Chemical Engineering, California Institute of Technology, Pasadena, California, USA.', 'United States|United States', 92, 'Base Sequence|Gene Expression Regulation|Models, Genetic|Molecular Sequence Data|RNA, Messenger|Regulatory Sequences, Ribonucleic Acid|Ribosomes', 'Journal Article', '10.1371/journal.pcbi.1000363', '19381267', 'Scientific and technological advances that enable the tuning of integrated regulatory components to match network and system requirements are critical to reliably control the function of biological systems. RNA provides a promising building block for the construction of tunable regulatory components based on its rich regulatory capacity and our current understanding of the sequence-function relationship. One prominent example of RNA-based regulatory components is riboswitches, genetic elements that mediate ligand control of gene expression through diverse regulatory mechanisms. While characterization of natural and synthetic riboswitches has revealed that riboswitch function can be modulated through sequence alteration, no quantitative frameworks exist to investigate or guide riboswitch tuning. Here, we combined mathematical modeling and experimental approaches to investigate the relationship between riboswitch function and performance. Model results demonstrated that the competition between reversible and irreversible rate constants dictates performance for different regulatory mechanisms. We also found that practical system restrictions, such as an upper limit on ligand concentration, can significantly alter the requirements for riboswitch performance, necessitating alternative tuning strategies. Previous experimental data for natural and synthetic riboswitches as well as experiments conducted in this work support model predictions. From our results, we developed a set of general design principles for synthetic riboswitches. Our results also provide a foundation from which to investigate how natural riboswitches are tuned to meet systems-level regulatory demands.'),
(84199, 2009, 'plos', 'A bipolar clamp mechanism for activation of Jak-family protein tyrosine kinases', 'Barua, Dipak|Faeder, James R|Haugh, Jason M', 'Department of Chemical and Biomolecular Engineering, North Carolina State University, Raleigh, North Carolina, USA.|Department of Chemical and Biomolecular Engineering, North Carolina State University, Raleigh, North Carolina, USA.|Department of Chemical and Biomolecular Engineering, North Carolina State University, Raleigh, North Carolina, USA.', 'United States|United States|United States', 13, 'Adaptor Proteins, Signal Transducing|Binding Sites|Computer Simulation|Enzyme Activation|Janus Kinases|Models, Biological|Models, Chemical|Phosphorylation|Protein Binding|Signal Transduction', 'Journal Article', '10.1371/journal.pcbi.1000364', '19381268', 'Most cell surface receptors for growth factors and cytokines dimerize in order to mediate signal transduction. For many such receptors, the Janus kinase (Jak) family of non-receptor protein tyrosine kinases are recruited in pairs and juxtaposed by dimerized receptor complexes in order to activate one another by trans-phosphorylation. An alternative mechanism for Jak trans-phosphorylation has been proposed in which the phosphorylated kinase interacts with the Src homology 2 (SH2) domain of SH2-B, a unique adaptor protein with the capacity to homo-dimerize. Building on a rule-based kinetic modeling approach that considers the concerted nature and combinatorial complexity of modular protein domain interactions, we examine these mechanisms in detail, focusing on the growth hormone (GH) receptor/Jak2/SH2-Bbeta system. The modeling results suggest that, whereas Jak2-(SH2-Bbeta)(2)-Jak2 heterotetramers are scarcely expected to affect Jak2 phosphorylation, SH2-Bbeta and dimerized receptors synergistically promote Jak2 trans-activation in the context of intracellular signaling. Analysis of the results revealed a unique mechanism whereby SH2-B and receptor dimers constitute a bipolar clamp that stabilizes the active configuration of two Jak2 molecules in the same macro-complex.'),
(84200, 2009, 'plos', 'Ten simple rules to combine teaching and research', 'Vicens, Quentin|Bourne, Philip E', 'Department of Chemical and Biomolecular Engineering, North Carolina State University, Raleigh, North Carolina, USA.|Department of Chemical and Biomolecular Engineering, North Carolina State University, Raleigh, North Carolina, USA.', 'United States|United States', 12, 'Algorithms|Models, Organizational|Organizational Objectives|Research|Teaching|United States|Universities', 'Editorial', '10.1371/journal.pcbi.1000358', '19390598', '-'),
(84201, 2009, 'plos', 'Webb Miller and Trey Ideker to receive top international bioinformatics awards for 2009 from the International Society for Computational Biology', 'Morrison McKay, B J|Sansom, Clare', 'International Society for Computational Biology, University of California San Diego, La Jolla, California, USA. bj@iscb.org|International Society for Computational Biology, University of California San Diego, La Jolla, California, USA. bj@iscb.org', 'United States|United States', 0, 'Awards and Prizes|Computational Biology|Internationality', 'Journal Article', '10.1371/journal.pcbi.1000375', '19390599', '-'),
(84202, 2009, 'plos', 'Divisive gain modulation with dynamic stimuli in integrate-and-fire neurons', 'Ly, Cheng|Doiron, Brent', 'Department of Mathematics, University of Pittsburgh, Pittsburgh, Pennsylvania, USA. chengly@math.pitt.edu|Department of Mathematics, University of Pittsburgh, Pittsburgh, Pennsylvania, USA. chengly@math.pitt.edu', 'United States|United States', 20, 'Action Potentials|Adaptation, Physiological|Animals|Differential Threshold|Humans|Models, Neurological|Nerve Net|Neuronal Plasticity|Neurons', 'Journal Article', '10.1371/journal.pcbi.1000365', '19390603', 'The modulation of the sensitivity, or gain, of neural responses to input is an important component of neural computation. It has been shown that divisive gain modulation of neural responses can result from a stochastic shunting from balanced (mixed excitation and inhibition) background activity. This gain control scheme was developed and explored with static inputs, where the membrane and spike train statistics were stationary in time. However, input statistics, such as the firing rates of pre-synaptic neurons, are often dynamic, varying on timescales comparable to typical membrane time constants. Using a population density approach for integrate-and-fire neurons with dynamic and temporally rich inputs, we find that the same fluctuation-induced divisive gain modulation is operative for dynamic inputs driving nonequilibrium responses. Moreover, the degree of divisive scaling of the dynamic response is quantitatively the same as the steady-state responses--thus, gain modulation via balanced conductance fluctuations generalizes in a straight-forward way to a dynamic setting.'),
(84203, 2009, 'plos', 'Polymorphism data can reveal the origin of species abundance statistics', 'Maruvka, Yosef E|Shnerb, Nadav M', 'Physics Department, Bar-Ilan University, Ramat-Gan, Israel. yosi.maruvka@gmail.com|Physics Department, Bar-Ilan University, Ramat-Gan, Israel. yosi.maruvka@gmail.com', 'Israel|Israel', 1, 'Animals|Biological Evolution|Evolution, Molecular|Genetic Variation|Genetics, Population|Humans|Models, Statistical|Origin of Life|Polymorphism, Single Nucleotide', 'Journal Article', '10.1371/journal.pcbi.1000359', '19390605', 'What is the underlying mechanism behind the fat-tailed statistics observed for species abundance distributions? The two main hypotheses in the field are the adaptive (niche) theories, where species abundance reflects its fitness, and the neutral theory that assumes demographic stochasticity as the main factor determining community structure. Both explanations suggest quite similar species-abundance distributions, but very different histories: niche scenarios assume that a species population in the past was similar to the observed one, while neutral scenarios are characterized by strongly fluctuating populations. Since the genetic variations within a population depend on its abundance in the past, we present here a way to discriminate between the theories using the genetic diversity of noncoding DNA. A statistical test, based on the Fu-Li method, has been developed and enables such a differentiation. We have analyzed the results gathered from individual-based simulation of both types of histories and obtained clear distinction between the Fu-Li statistics of the neutral scenario and that of the niche scenario. Our results suggest that data for 10-50 species, with approximately 30 sequenced individuals for each species, may allow one to distinguish between these two theories.'),
(84204, 2009, 'plos', 'Tumor-immune interaction, surgical treatment, and cancer recurrence in a mathematical model of melanoma', 'Eikenberry, Steffen|Thalhauser, Craig|Kuang, Yang', 'Department of Mathematics and Statistics, Arizona State University, Tempe, Arizona, USA. seikenbe@asu.edu|Department of Mathematics and Statistics, Arizona State University, Tempe, Arizona, USA. seikenbe@asu.edu|Department of Mathematics and Statistics, Arizona State University, Tempe, Arizona, USA. seikenbe@asu.edu', 'United States|United States|United States', 54, 'Computer Simulation|Humans|Immunity, Innate|Melanoma|Models, Immunological|Neoplasm Recurrence, Local|Treatment Outcome', 'Journal Article', '10.1371/journal.pcbi.1000362', '19390606', 'Malignant melanoma is a cancer of the skin arising in the melanocytes. We present a mathematical model of melanoma invasion into healthy tissue with an immune response. We use this model as a framework with which to investigate primary tumor invasion and treatment by surgical excision. We observe that the presence of immune cells can destroy tumors, hold them to minimal expansion, or, through the production of angiogenic factors, induce tumorigenic expansion. We also find that the tumor-immune system dynamic is critically important in determining the likelihood and extent of tumor regrowth following resection. We find that small metastatic lesions distal to the primary tumor mass can be held to a minimal size via the immune interaction with the larger primary tumor. Numerical experiments further suggest that metastatic disease is optimally suppressed by immune activation when the primary tumor is moderately, rather than minimally, metastatic. Furthermore, satellite lesions can become aggressively tumorigenic upon removal of the primary tumor and its associated immune tissue. This can lead to recurrence where total cancer mass increases more quickly than in primary tumor invasion, representing a clinically more dangerous disease state. These results are in line with clinical case studies involving resection of a primary melanoma followed by recurrence in local metastases.'),
(84205, 2009, 'plos', 'Mapping gene associations in human mitochondria using clinical disease phenotypes', 'Scharfe, Curt|Lu, Henry Horng-Shing|Neuenburg, Jutta K|Allen, Edward A|Li, Guan-Cheng|Klopstock, Thomas|Cowan, Tina M|Enns, Gregory M|Davis, Ronald W', 'Stanford Genome Technology Center, Stanford University, Palo Alto, California, USA. curts@stanford.edu|Stanford Genome Technology Center, Stanford University, Palo Alto, California, USA. curts@stanford.edu|Stanford Genome Technology Center, Stanford University, Palo Alto, California, USA. curts@stanford.edu|Stanford Genome Technology Center, Stanford University, Palo Alto, California, USA. curts@stanford.edu|Stanford Genome Technology Center, Stanford University, Palo Alto, California, USA. curts@stanford.edu|Stanford Genome Technology Center, Stanford University, Palo Alto, California, USA. curts@stanford.edu|Stanford Genome Technology Center, Stanford University, Palo Alto, California, USA. curts@stanford.edu|Stanford Genome Technology Center, Stanford University, Palo Alto, California, USA. curts@stanford.edu|Stanford Genome Technology Center, Stanford University, Palo Alto, California, USA. curts@stanford.edu', 'United States|United States|United States|United States|United States|United States|United States|United States|United States', 57, 'Chromosome Mapping|Computer Simulation|DNA, Mitochondrial|Genetic Predisposition to Disease|Humans|Mitochondrial Diseases|Models, Genetic|Quantitative Trait Loci', 'Journal Article', '10.1371/journal.pcbi.1000374', '19390613', 'Nuclear genes encode most mitochondrial proteins, and their mutations cause diverse and debilitating clinical disorders. To date, 1,200 of these mitochondrial genes have been recorded, while no standardized catalog exists of the associated clinical phenotypes. Such a catalog would be useful to develop methods to analyze human phenotypic data, to determine genotype-phenotype relations among many genes and diseases, and to support the clinical diagnosis of mitochondrial disorders. Here we establish a clinical phenotype catalog of 174 mitochondrial disease genes and study associations of diseases and genes. Phenotypic features such as clinical signs and symptoms were manually annotated from full-text medical articles and classified based on the hierarchical MeSH ontology. This classification of phenotypic features of each gene allowed for the comparison of diseases between different genes. In turn, we were then able to measure the phenotypic associations of disease genes for which we calculated a quantitative value that is based on their shared phenotypic features. The results showed that genes sharing more similar phenotypes have a stronger tendency for functional interactions, proving the usefulness of phenotype similarity values in disease gene network analysis. We then constructed a functional network of mitochondrial genes and discovered a higher connectivity for non-disease than for disease genes, and a tendency of disease genes to interact with each other. Utilizing these differences, we propose 168 candidate genes that resemble the characteristic interaction patterns of mitochondrial disease genes. Through their network associations, the candidates are further prioritized for the study of specific disorders such as optic neuropathies and Parkinson disease. Most mitochondrial disease phenotypes involve several clinical categories including neurologic, metabolic, and gastrointestinal disorders, which might indicate the effects of gene defects within the mitochondrial system. The accompanying knowledgebase (http://www.mitophenome.org/) supports the study of clinical diseases and associated genes.'),
(84206, 2009, 'plos', 'A structural model of the pore-forming region of the skeletal muscle ryanodine receptor (RyR1)', 'Ramachandran, Srinivas|Serohijos, Adrian W R|Xu, Le|Meissner, Gerhard|Dokholyan, Nikolay V', 'Department of Biochemistry and Biophysics, University of North Carolina Chapel Hill, Chapel Hill, North Carolina, USA.|Department of Biochemistry and Biophysics, University of North Carolina Chapel Hill, Chapel Hill, North Carolina, USA.|Department of Biochemistry and Biophysics, University of North Carolina Chapel Hill, Chapel Hill, North Carolina, USA.|Department of Biochemistry and Biophysics, University of North Carolina Chapel Hill, Chapel Hill, North Carolina, USA.|Department of Biochemistry and Biophysics, University of North Carolina Chapel Hill, Chapel Hill, North Carolina, USA.', 'United States|United States|United States|United States|United States', 25, 'Computer Simulation|Models, Chemical|Models, Molecular|Muscle, Skeletal|Porosity|Protein Conformation|Ryanodine Receptor Calcium Release Channel', 'Journal Article', '10.1371/journal.pcbi.1000367', '19390614', 'Ryanodine receptors (RyRs) are ion channels that regulate muscle contraction by releasing calcium ions from intracellular stores into the cytoplasm. Mutations in skeletal muscle RyR (RyR1) give rise to congenital diseases such as central core disease. The absence of high-resolution structures of RyR1 has limited our understanding of channel function and disease mechanisms at the molecular level. Here, we report a structural model of the pore-forming region of RyR1. Molecular dynamics simulations show high ion binding to putative pore residues D4899, E4900, D4938, and D4945, which are experimentally known to be critical for channel conductance and selectivity. We also observe preferential localization of Ca(2+) over K(+) in the selectivity filter of RyR1. Simulations of RyR1-D4899Q mutant show a loss of preference to Ca(2+) in the selectivity filter as seen experimentally. Electrophysiological experiments on a central core disease mutant, RyR1-G4898R, show constitutively open channels that conduct K(+) but not Ca(2+). Our simulations with G4898R likewise show a decrease in the preference of Ca(2+) over K(+) in the selectivity filter. Together, the computational and experimental results shed light on ion conductance and selectivity of RyR1 at an atomistic level.'),
(84207, 2009, 'plos', 'The role of the Frank-Starling law in the transduction of cellular work to whole organ pump function: a computational modeling analysis', 'Niederer, Steven A|Smith, Nicolas P', 'Computing Laboratory, University of Oxford, Oxford, United Kingdom. steven.niederer@comlab.ox.ac.uk|Computing Laboratory, University of Oxford, Oxford, United Kingdom. steven.niederer@comlab.ox.ac.uk', 'United Kingdom|United Kingdom', 50, 'Animals|Calcium|Computer Simulation|Energy Metabolism|Humans|Models, Cardiovascular|Myocardial Contraction|Myocytes, Cardiac|Rats|Signal Transduction|Ventricular Function', 'Journal Article', '10.1371/journal.pcbi.1000371', '19390615', 'We have developed a multi-scale biophysical electromechanics model of the rat left ventricle at room temperature. This model has been applied to investigate the relative roles of cellular scale length dependent regulators of tension generation on the transduction of work from the cell to whole organ pump function. Specifically, the role of the length dependent Ca(2+) sensitivity of tension (Ca(50)), filament overlap tension dependence, velocity dependence of tension, and tension dependent binding of Ca(2+) to Troponin C on metrics of efficient transduction of work and stress and strain homogeneity were predicted by performing simulations in the absence of each of these feedback mechanisms. The length dependent Ca(50) and the filament overlap, which make up the Frank-Starling Law, were found to be the two dominant regulators of the efficient transduction of work. Analyzing the fiber velocity field in the absence of the Frank-Starling mechanisms showed that the decreased efficiency in the transduction of work in the absence of filament overlap effects was caused by increased post systolic shortening, whereas the decreased efficiency in the absence of length dependent Ca(50) was caused by an inversion in the regional distribution of strain.'),
(84208, 2009, 'plos', 'Systems analysis of bioenergetics and growth of the extreme halophile Halobacterium salinarum', 'Gonzalez, Orland|Gronau, Susanne|Pfeiffer, Friedhelm|Mendoza, Eduardo|Zimmer, Ralf|Oesterhelt, Dieter', 'Department of Membrane Biochemistry, Max-Planck Institute for Biochemistry, Martinsried, Germany. gonzalez@biochem.mpg.de|Department of Membrane Biochemistry, Max-Planck Institute for Biochemistry, Martinsried, Germany. gonzalez@biochem.mpg.de|Department of Membrane Biochemistry, Max-Planck Institute for Biochemistry, Martinsried, Germany. gonzalez@biochem.mpg.de|Department of Membrane Biochemistry, Max-Planck Institute for Biochemistry, Martinsried, Germany. gonzalez@biochem.mpg.de|Department of Membrane Biochemistry, Max-Planck Institute for Biochemistry, Martinsried, Germany. gonzalez@biochem.mpg.de|Department of Membrane Biochemistry, Max-Planck Institute for Biochemistry, Martinsried, Germany. gonzalez@biochem.mpg.de', 'Germany|Germany|Germany|Germany|Germany|Germany', 30, 'Archaeal Proteins|Computer Simulation|Energy Metabolism|Halobacterium salinarum|Models, Biological|Systems Biology', 'Journal Article', '10.1371/journal.pcbi.1000332', '19401785', 'Halobacterium salinarum is a bioenergetically flexible, halophilic microorganism that can generate energy by respiration, photosynthesis, and the fermentation of arginine. In a previous study, using a genome-scale metabolic model, we have shown that the archaeon unexpectedly degrades essential amino acids under aerobic conditions, a behavior that can lead to the termination of growth earlier than necessary. Here, we further integratively investigate energy generation, nutrient utilization, and biomass production using an extended methodology that accounts for dynamically changing transport patterns, including those that arise from interactions among the supplied metabolites. Moreover, we widen the scope of our analysis to include phototrophic conditions to explore the interplay between different bioenergetic modes. Surprisingly, we found that cells also degrade essential amino acids even during phototropy, when energy should already be abundant. We also found that under both conditions considerable amounts of nutrients that were taken up were neither incorporated into the biomass nor used as respiratory substrates, implying the considerable production and accumulation of several metabolites in the medium. Some of these are likely the products of forms of overflow metabolism. In addition, our results also show that arginine fermentation, contrary to what is typically assumed, occurs simultaneously with respiration and photosynthesis and can contribute energy in levels that are comparable to the primary bioenergetic modes, if not more. These findings portray a picture that the organism takes an approach toward growth that favors the here and now, even at the cost of longer-term concerns. We believe that the seemingly greedy behavior exhibited actually consists of adaptations by the organism to its natural environments, where nutrients are not only irregularly available but may altogether be absent for extended periods that may span several years. Such a setting probably predisposed the cells to grow as much as possible when the conditions become favorable.'),
(84209, 2009, 'plos', 'Dating the age of the SIV lineages that gave rise to HIV-1 and HIV-2', 'Wertheim, Joel O|Worobey, Michael', 'Department of Ecology and Evolutionary Biology, University of Arizona, Tucson, AZ, USA. wertheim@email.arizona.edu|Department of Ecology and Evolutionary Biology, University of Arizona, Tucson, AZ, USA. wertheim@email.arizona.edu', 'United States|United States', 0, 'Animals|Cercocebus atys|Evolution, Molecular|Genes, env|Genes, gag|Genes, pol|HIV Infections|HIV-1|HIV-2|Humans|Models, Genetic|Pan troglodytes|Phylogeny|Sequence Alignment|Simian Acquired Immunodeficiency Syndrome|Simian Immunodeficiency Virus|Time', 'Journal Article', '10.1371/journal.pcbi.1000377', '19412344', 'Great strides have been made in understanding the evolutionary history of simian immunodeficiency virus (SIV) and the zoonoses that gave rise to HIV-1 and HIV-2. What remains unknown is how long these SIVs had been circulating in non-human primates before the transmissions to humans. Here, we use relaxed molecular clock dating techniques to estimate the time of most recent common ancestor for the SIVs infecting chimpanzees and sooty mangabeys, the reservoirs of HIV-1 and HIV-2, respectively. The date of the most recent common ancestor of SIV in chimpanzees is estimated to be 1492 (1266-1685), and the date in sooty mangabeys is estimated to be 1809 (1729-1875). Notably, we demonstrate that SIV sequences sampled from sooty mangabeys possess sufficient clock-like signal to calibrate a molecular clock, despite the differences in host biology and viral dynamics, the rate of evolution of SIV in sooty mangabeys is indistinguishable from that of its human counterpart, HIV-2. We also estimate the ages of the HIV-2 human-to-human transmissible lineages and provide the first age estimate for HIV-1 group N at 1963 (1948-1977). Comparisons between the SIV most recent common ancestor dates and those of the HIV lineages suggest a difference on the order of only hundreds of years. Our results suggest either that SIV is a surprisingly young lentiviral lineage or that SIV and, perhaps, HIV dating estimates are seriously compromised by unaccounted-for biases.'),
(84210, 2009, 'plos', 'Predictive feedback can account for biphasic responses in the lateral geniculate nucleus', 'Jehee, Janneke F M|Ballard, Dana H', 'Center for Visual Science and Department of Computer Science, University of Rochester, Rochester, NY, USA. janneke.jehee@vanderbilt.edu|Center for Visual Science and Department of Computer Science, University of Rochester, Rochester, NY, USA. janneke.jehee@vanderbilt.edu', 'United States|United States', 43, 'Algorithms|Animals|Artificial Intelligence|Brain|Cats|Computer Simulation|Feedback|Geniculate Bodies|Models, Neurological|Neurons|Visual Cortex', 'Journal Article', '10.1371/journal.pcbi.1000373', '19412529', 'Biphasic neural response properties, where the optimal stimulus for driving a neural response changes from one stimulus pattern to the opposite stimulus pattern over short periods of time, have been described in several visual areas, including lateral geniculate nucleus (LGN), primary visual cortex (V1), and middle temporal area (MT). We describe a hierarchical model of predictive coding and simulations that capture these temporal variations in neuronal response properties. We focus on the LGN-V1 circuit and find that after training on natural images the model exhibits the brains LGN-V1 connectivity structure, in which the structure of V1 receptive fields is linked to the spatial alignment and properties of center-surround cells in the LGN. In addition, the spatio-temporal response profile of LGN model neurons is biphasic in structure, resembling the biphasic response structure of neurons in cat LGN. Moreover, the model displays a specific pattern of influence of feedback, where LGN receptive fields that are aligned over a simple cell receptive field zone of the same polarity decrease their responses while neurons of opposite polarity increase their responses with feedback. This phase-reversed pattern of influence was recently observed in neurophysiology. These results corroborate the idea that predictive feedback is a general coding strategy in the brain.');
INSERT INTO `papers` (`id`, `ano`, `journal`, `titulo`, `autores`, `afiliacao`, `pais`, `citacoes`, `palavra_chave`, `categorias`, `doi`, `pubmed`, `abstract`) VALUES
(84211, 2009, 'plos', 'Prediction of protein binding regions in disordered proteins', 'Mészáros, Bálint|Simon, István|Dosztányi, Zsuzsanna', 'Institute of Enzymology, Biological Research Center, Hungarian Academy of Sciences, Budapest, Hungary.|Institute of Enzymology, Biological Research Center, Hungarian Academy of Sciences, Budapest, Hungary.|Institute of Enzymology, Biological Research Center, Hungarian Academy of Sciences, Budapest, Hungary.', 'Hungary|Hungary|Hungary', 365, 'Algorithms|Amino Acid Sequence|Databases, Protein|Humans|Pattern Recognition, Automated|Protein Binding|Protein Conformation|Protein Structure, Secondary|Proteins|Proteomics|ROC Curve|Thermodynamics|Tumor Suppressor Protein p53|Wiskott-Aldrich Syndrome Protein', 'Journal Article', '10.1371/journal.pcbi.1000376', '19412530', 'Many disordered proteins function via binding to a structured partner and undergo a disorder-to-order transition. The coupled folding and binding can confer several functional advantages such as the precise control of binding specificity without increased affinity. Additionally, the inherent flexibility allows the binding site to adopt various conformations and to bind to multiple partners. These features explain the prevalence of such binding elements in signaling and regulatory processes. In this work, we report ANCHOR, a method for the prediction of disordered binding regions. ANCHOR relies on the pairwise energy estimation approach that is the basis of IUPred, a previous general disorder prediction method. In order to predict disordered binding regions, we seek to identify segments that are in disordered regions, cannot form enough favorable intrachain interactions to fold on their own, and are likely to gain stabilizing energy by interacting with a globular protein partner. The performance of ANCHOR was found to be largely independent from the amino acid composition and adopted secondary structure. Longer binding sites generally were predicted to be segmented, in agreement with available experimentally characterized examples. Scanning several hundred proteomes showed that the occurrence of disordered binding sites increased with the complexity of the organisms even compared to disordered regions in general. Furthermore, the length distribution of binding sites was different from disordered protein regions in general and was dominated by shorter segments. These results underline the importance of disordered proteins and protein segments in establishing new binding regions. Due to their specific biophysical properties, disordered binding sites generally carry a robust sequence signal, and this signal is efficiently captured by our method. Through its generality, ANCHOR opens new ways to study the essential functional sites of disordered proteins.'),
(84212, 2009, 'plos', 'Representation of time-varying stimuli by a network exhibiting oscillations on a faster time scale', 'Shamir, Maoz|Ghitza, Oded|Epstein, Steven|Kopell, Nancy', 'Center for BioDynamics, Boston University, Boston, MA, USA. shmaoz@bgu.ac.il|Center for BioDynamics, Boston University, Boston, MA, USA. shmaoz@bgu.ac.il|Center for BioDynamics, Boston University, Boston, MA, USA. shmaoz@bgu.ac.il|Center for BioDynamics, Boston University, Boston, MA, USA. shmaoz@bgu.ac.il', 'United States|United States|United States|United States', 30, 'Algorithms|Computational Biology|Models, Neurological|Neural Networks (Computer)|Oscillometry|Speech|Time Factors', 'Journal Article', '10.1371/journal.pcbi.1000370', '19412531', 'Sensory processing is associated with gamma frequency oscillations (30-80 Hz) in sensory cortices. This raises the question whether gamma oscillations can be directly involved in the representation of time-varying stimuli, including stimuli whose time scale is longer than a gamma cycle. We are interested in the ability of the system to reliably distinguish different stimuli while being robust to stimulus variations such as uniform time-warp. We address this issue with a dynamical model of spiking neurons and study the response to an asymmetric sawtooth input current over a range of shape parameters. These parameters describe how fast the input current rises and falls in time. Our network consists of inhibitory and excitatory populations that are sufficient for generating oscillations in the gamma range. The oscillations period is about one-third of the stimulus duration. Embedded in this network is a subpopulation of excitatory cells that respond to the sawtooth stimulus and a subpopulation of cells that respond to an onset cue. The intrinsic gamma oscillations generate a temporally sparse code for the external stimuli. In this code, an excitatory cell may fire a single spike during a gamma cycle, depending on its tuning properties and on the temporal structure of the specific input, the identity of the stimulus is coded by the list of excitatory cells that fire during each cycle. We quantify the properties of this representation in a series of simulations and show that the sparseness of the code makes it robust to uniform warping of the time scale. We find that resetting of the oscillation phase at stimulus onset is important for a reliable representation of the stimulus and that there is a tradeoff between the resolution of the neural representation of the stimulus and robustness to time-warp.'),
(84213, 2009, 'plos', 'A differential wiring analysis of expression data correctly identifies the gene containing the causal mutation', 'Hudson, Nicholas J|Reverter, Antonio|Dalrymple, Brian P', 'Food Futures Flagship and Livestock Industries, Commonwealth Scientific and Industrial Research Organisation, Queensland Bioscience Precinct, St Lucia Brisbane, Queensland, Australia.|Food Futures Flagship and Livestock Industries, Commonwealth Scientific and Industrial Research Organisation, Queensland Bioscience Precinct, St Lucia Brisbane, Queensland, Australia.|Food Futures Flagship and Livestock Industries, Commonwealth Scientific and Industrial Research Organisation, Queensland Bioscience Precinct, St Lucia Brisbane, Queensland, Australia.', 'Australia|Australia|Australia', 135, 'Algorithms|Animals|Cattle|Cluster Analysis|Computer Simulation|Gene Expression Profiling|Gene Expression Regulation|Male|Models, Genetic|Mutation, Missense|Myostatin|Oligonucleotide Array Sequence Analysis|Phosphorylation|RNA Processing, Post-Transcriptional|Transcription Factors|Transcription, Genetic', 'Journal Article', '10.1371/journal.pcbi.1000382', '19412532', 'Transcription factor (TF) regulation is often post-translational. TF modifications such as reversible phosphorylation and missense mutations, which can act independent of TF expression level, are overlooked by differential expression analysis. Using bovine Piedmontese myostatin mutants as proof-of-concept, we propose a new algorithm that correctly identifies the gene containing the causal mutation from microarray data alone. The myostatin mutation releases the brakes on Piedmontese muscle growth by translating a dysfunctional protein. Compared to a less muscular non-mutant breed we find that myostatin is not differentially expressed at any of ten developmental time points. Despite this challenge, the algorithm identifies the myostatin smoking gun through a coordinated, simultaneous, weighted integration of three sources of microarray information: transcript abundance, differential expression, and differential wiring. By asking the novel question which regulator is cumulatively most differentially wired to the abundant most differentially expressed genes? it yields the correct answer, myostatin. Our new approach identifies causal regulatory changes by globally contrasting co-expression network dynamics. The entirely data-driven weighting procedure emphasises regulatory movement relative to the phenotypically relevant part of the network. In contrast to other published methods that compare co-expression networks, significance testing is not used to eliminate connections.'),
(84214, 2009, 'plos', 'Functional brain networks develop from a local to distributed organization', 'Fair, Damien A|Cohen, Alexander L|Power, Jonathan D|Dosenbach, Nico U F|Church, Jessica A|Miezin, Francis M|Schlaggar, Bradley L|Petersen, Steven E', 'Behavioral Neuroscience Department, Oregon Health and Science University, Portland, OR, USA. damien.fair@aya.yale.edu|Behavioral Neuroscience Department, Oregon Health and Science University, Portland, OR, USA. damien.fair@aya.yale.edu|Behavioral Neuroscience Department, Oregon Health and Science University, Portland, OR, USA. damien.fair@aya.yale.edu|Behavioral Neuroscience Department, Oregon Health and Science University, Portland, OR, USA. damien.fair@aya.yale.edu|Behavioral Neuroscience Department, Oregon Health and Science University, Portland, OR, USA. damien.fair@aya.yale.edu|Behavioral Neuroscience Department, Oregon Health and Science University, Portland, OR, USA. damien.fair@aya.yale.edu|Behavioral Neuroscience Department, Oregon Health and Science University, Portland, OR, USA. damien.fair@aya.yale.edu|Behavioral Neuroscience Department, Oregon Health and Science University, Portland, OR, USA. damien.fair@aya.yale.edu', 'United States|United States|United States|United States|United States|United States|United States|United States', 917, 'Adolescent|Adult|Brain|Child|Humans|Magnetic Resonance Imaging|Models, Neurological|Nerve Net|Neural Pathways', 'Journal Article', '10.1371/journal.pcbi.1000381', '19412534', 'The mature human brain is organized into a collection of specialized functional networks that flexibly interact to support various cognitive functions. Studies of development often attempt to identify the organizing principles that guide the maturation of these functional networks. In this report, we combine resting state functional connectivity MRI (rs-fcMRI), graph analysis, community detection, and spring-embedding visualization techniques to analyze four separate networks defined in earlier studies. As we have previously reported, we find, across development, a trend toward segregation (a general decrease in correlation strength) between regions close in anatomical space and integration (an increased correlation strength) between selected regions distant in space. The generalization of these earlier trends across multiple networks suggests that this is a general developmental principle for changes in functional connectivity that would extend to large-scale graph theoretic analyses of large-scale brain networks. Communities in children are predominantly arranged by anatomical proximity, while communities in adults predominantly reflect functional relationships, as defined from adult fMRI studies. In sum, over development, the organization of multiple functional networks shifts from a local anatomical emphasis in children to a more distributed architecture in young adults. We argue that this local to distributed developmental characterization has important implications for understanding the development of neural systems underlying cognition. Further, graph metrics (e.g., clustering coefficients and average path lengths) are similar in child and adult graphs, with both showing small-world-like properties, while community detection by modularity optimization reveals stable communities within the graphs that are clearly different between young children and young adults. These observations suggest that early school age children and adults both have relatively efficient systems that may solve similar information processing problems in divergent ways.'),
(84215, 2009, 'plos', 'Differential affinity and catalytic activity of CheZ in E coli chemotaxis', 'van Albada, Siebe B|Ten Wolde, Pieter Rein', 'FOM Institute for Atomic and Molecular Physics, Amsterdam, The Netherlands. siebevanalbada@gmail.com|FOM Institute for Atomic and Molecular Physics, Amsterdam, The Netherlands. siebevanalbada@gmail.com', 'Netherlands|Netherlands', 11, 'Algorithms|Bacterial Proteins|Chemotaxis|Escherichia coli|Escherichia coli Proteins|Histidine Kinase|Membrane Proteins|Methyl-Accepting Chemotaxis Proteins|Models, Biological|Protein Binding|Signal Transduction', 'Journal Article', '10.1371/journal.pcbi.1000378', '19424426', 'Push-pull networks, in which two antagonistic enzymes control the activity of a messenger protein, are ubiquitous in signal transduction pathways. A classical example is the chemotaxis system of the bacterium Escherichia coli, in which the kinase CheA and the phosphatase CheZ regulate the phosphorylation level of the messenger protein CheY. Recent experiments suggest that both the kinase and the phosphatase are localized at the receptor cluster, and Vaknin and Berg recently demonstrated that the spatial distribution of the phosphatase can markedly affect the dose-response curves. We argue, using mathematical modeling, that the canonical model of the chemotaxis network cannot explain the experimental observations of Vaknin and Berg. We present a new model, in which a small fraction of the phosphatase is localized at the receptor cluster, while the remainder freely diffuses in the cytoplasm, moreover, the phosphatase at the cluster has a higher binding affinity for the messenger protein and a higher catalytic activity than the phosphatase in the cytoplasm. This model is consistent with a large body of experimental data and can explain many of the experimental observations of Vaknin and Berg. More generally, the combination of differential affinity and catalytic activity provides a generic mechanism for amplifying signals that could be exploited in other two-component signaling systems. If this model is correct, then a number of recent modeling studies, which aim to explain the chemotactic gain in terms of the activity of the receptor cluster, should be reconsidered.'),
(84216, 2009, 'plos', 'A structure-based approach for detection of thiol oxidoreductases and their catalytic redox-active cysteine residues', 'Marino, Stefano M|Gladyshev, Vadim N', 'Department of Biochemistry and Redox Biology Center, University of Nebraska, Lincoln, Nebraska, USA.|Department of Biochemistry and Redox Biology Center, University of Nebraska, Lincoln, Nebraska, USA.', 'United States|United States', 20, 'Algorithms|Amino Acid Sequence|Catalytic Domain|Cysteine|Hydrogen-Ion Concentration|Models, Molecular|Oxidation-Reduction|Oxidoreductases|Protein Structure, Secondary|Saccharomyces cerevisiae Proteins|Sequence Analysis, Protein', 'Journal Article', '10.1371/journal.pcbi.1000383', '19424433', 'Cysteine (Cys) residues often play critical roles in proteins, for example, in the formation of structural disulfide bonds, metal binding, targeting proteins to the membranes, and various catalytic functions. However, the structural determinants for various Cys functions are not clear. Thiol oxidoreductases, which are enzymes containing catalytic redox-active Cys residues, have been extensively studied, but even for these proteins there is little understanding of what distinguishes their catalytic redox Cys from other Cys functions. Herein, we characterized thiol oxidoreductases at a structural level and developed an algorithm that can recognize these enzymes by (i) analyzing amino acid and secondary structure composition of the active site and its similarity to known active sites containing redox Cys and (ii) calculating accessibility, active site location, and reactivity of Cys. For proteins with known or modeled structures, this method can identify proteins with catalytic Cys residues and distinguish thiol oxidoreductases from the enzymes containing other catalytic Cys types. Furthermore, by applying this procedure to Saccharomyces cerevisiae proteins containing conserved Cys, we could identify the majority of known yeast thiol oxidoreductases. This study provides insights into the structural properties of catalytic redox-active Cys and should further help to recognize thiol oxidoreductases in protein sequence and structure databases.'),
(84217, 2009, 'plos', 'Pairwise maximum entropy models for studying large biological systems: when they can work and when they cant', 'Roudi, Yasser|Nirenberg, Sheila|Latham, Peter E', 'Gatsby Computational Neuroscience Unit, University College London, London, United Kingdom.|Gatsby Computational Neuroscience Unit, University College London, London, United Kingdom.|Gatsby Computational Neuroscience Unit, University College London, London, United Kingdom.', 'United Kingdom|United Kingdom|United Kingdom', 110, 'Algorithms|Computer Simulation|Entropy|Models, Biological|Models, Statistical|Systems Biology', 'Journal Article', '10.1371/journal.pcbi.1000380', '19424487', 'One of the most critical problems we face in the study of biological systems is building accurate statistical descriptions of them. This problem has been particularly challenging because biological systems typically contain large numbers of interacting elements, which precludes the use of standard brute force approaches. Recently, though, several groups have reported that there may be an alternate strategy. The reports show that reliable statistical models can be built without knowledge of all the interactions in a system, instead, pairwise interactions can suffice. These findings, however, are based on the analysis of small subsystems. Here, we ask whether the observations will generalize to systems of realistic size, that is, whether pairwise models will provide reliable descriptions of true biological systems. Our results show that, in most cases, they will not. The reason is that there is a crossover in the predictive power of pairwise models: If the size of the subsystem is below the crossover point, then the results have no predictive power for large systems. If the size is above the crossover point, then the results may have predictive power. This work thus provides a general framework for determining the extent to which pairwise models can be used to predict the behavior of large biological systems. Applied to neural data, the size of most systems studied so far is below the crossover point.'),
(84218, 2009, 'plos', 'Smoothing of, and parameter estimation from, noisy biophysical recordings', 'Huys, Quentin J M|Paninski, Liam', 'Gatsby Computational Neuroscience Unit, University College London, London, United Kingdom. qhuys@cantab.net|Gatsby Computational Neuroscience Unit, University College London, London, United Kingdom. qhuys@cantab.net', 'United Kingdom|United Kingdom', 61, 'Algorithms|Artificial Intelligence|Biophysical Phenomena|Cell Physiological Phenomena|Computational Biology|Computer Simulation|Electrophysiological Phenomena|Image Processing, Computer-Assisted|Models, Biological|Monte Carlo Method|Statistics, Nonparametric', 'Journal Article', '10.1371/journal.pcbi.1000379', '19424506', 'Biophysically detailed models of single cells are difficult to fit to real data. Recent advances in imaging techniques allow simultaneous access to various intracellular variables, and these data can be used to significantly facilitate the modelling task. These data, however, are noisy, and current approaches to building biophysically detailed models are not designed to deal with this. We extend previous techniques to take the noisy nature of the measurements into account. Sequential Monte Carlo (particle filtering) methods, in combination with a detailed biophysical description of a cell, are used for principled, model-based smoothing of noisy recording data. We also provide an alternative formulation of smoothing where the neural nonlinearities are estimated in a non-parametric manner. Biophysically important parameters of detailed models (such as channel densities, intercompartmental conductances, input resistances, and observation noise) are inferred automatically from noisy data via expectation-maximization. Overall, we find that model-based smoothing is a powerful, robust technique for smoothing of noisy biophysical data and for inference of biophysical parameters in the face of recording noise.'),
(84219, 2009, 'plos', 'Minimum criteria for DNA damage-induced phase advances in circadian rhythms', 'Hong, Christian I|Zámborszky, Judit|Csikász-Nagy, Attila', 'Department of Genetics, Dartmouth Medical School, Hanover, New Hampshire, USA.|Department of Genetics, Dartmouth Medical School, Hanover, New Hampshire, USA.|Department of Genetics, Dartmouth Medical School, Hanover, New Hampshire, USA.', 'United States|United States|United States', 11, 'Algorithms|Animals|Cell Cycle|Cell Cycle Proteins|Checkpoint Kinase 2|Circadian Rhythm|Computer Simulation|DNA Damage|Dexamethasone|Feedback, Physiological|Mammals|Models, Biological|Nuclear Proteins|Protein-Serine-Threonine Kinases|Radiation, Ionizing|Signal Transduction|Transcription Factors', 'Journal Article', '10.1371/journal.pcbi.1000384', '19424508', 'Robust oscillatory behaviors are common features of circadian and cell cycle rhythms. These cyclic processes, however, behave distinctively in terms of their periods and phases in response to external influences such as light, temperature, nutrients, etc. Nevertheless, several links have been found between these two oscillators. Cell division cycles gated by the circadian clock have been observed since the late 1950s. On the other hand, ionizing radiation (IR) treatments cause cells to undergo a DNA damage response, which leads to phase shifts (mostly advances) in circadian rhythms. Circadian gating of the cell cycle can be attributed to the cell cycle inhibitor kinase Wee1 (which is regulated by the heterodimeric circadian clock transcription factor, BMAL1/CLK), and possibly in conjunction with other cell cycle components that are known to be regulated by the circadian clock (i.e., c-Myc and cyclin D1). It has also been shown that DNA damage-induced activation of the cell cycle regulator, Chk2, leads to phosphorylation and destruction of a circadian clock component (i.e., PER1 in Mus or FRQ in Neurospora crassa). However, the molecular mechanism underlying how DNA damage causes predominantly phase advances in the circadian clock remains unknown. In order to address this question, we employ mathematical modeling to simulate different phase response curves (PRCs) from either dexamethasone (Dex) or IR treatment experiments. Dex is known to synchronize circadian rhythms in cell culture and may generate both phase advances and delays. We observe unique phase responses with minimum delays of the circadian clock upon DNA damage when two criteria are met: (1) existence of an autocatalytic positive feedback mechanism in addition to the time-delayed negative feedback loop in the clock system and (2) Chk2-dependent phosphorylation and degradation of PERs that are not bound to BMAL1/CLK.'),
(84220, 2009, 'plos', 'Drug discovery using chemical systems biology: identification of the protein-ligand binding network to explain the side effects of CETP inhibitors', 'Xie, Li|Li, Jerry|Xie, Lei|Bourne, Philip E', 'Skaggs School of Pharmacy and Pharmaceutical Sciences, University of California San Diego, La Jolla, California, USA. lxie@sdsc.edu|Skaggs School of Pharmacy and Pharmaceutical Sciences, University of California San Diego, La Jolla, California, USA. lxie@sdsc.edu|Skaggs School of Pharmacy and Pharmaceutical Sciences, University of California San Diego, La Jolla, California, USA. lxie@sdsc.edu|Skaggs School of Pharmacy and Pharmaceutical Sciences, University of California San Diego, La Jolla, California, USA. lxie@sdsc.edu', 'United States|United States|United States|United States', 206, 'Anticholesteremic Agents|Cell Proliferation|Cholesterol Ester Transfer Proteins|Cluster Analysis|Databases, Genetic|Drug Discovery|Gene Regulatory Networks|Inflammation|Ligands|Models, Biological|Models, Statistical|Protein Binding|Protein Interaction Domains and Motifs|Proteome|Receptors, Cytoplasmic and Nuclear|Renin-Angiotensin System|Systems Biology', 'Journal Article', '10.1371/journal.pcbi.1000387', '19436720', 'Systematic identification of protein-drug interaction networks is crucial to correlate complex modes of drug action to clinical indications. We introduce a novel computational strategy to identify protein-ligand binding profiles on a genome-wide scale and apply it to elucidating the molecular mechanisms associated with the adverse drug effects of Cholesteryl Ester Transfer Protein (CETP) inhibitors. CETP inhibitors are a new class of preventive therapies for the treatment of cardiovascular disease. However, clinical studies indicated that one CETP inhibitor, Torcetrapib, has deadly off-target effects as a result of hypertension, and hence it has been withdrawn from phase III clinical trials. We have identified a panel of off-targets for Torcetrapib and other CETP inhibitors from the human structural genome and map those targets to biological pathways via the literature. The predicted protein-ligand network is consistent with experimental results from multiple sources and reveals that the side-effect of CETP inhibitors is modulated through the combinatorial control of multiple interconnected pathways. Given that combinatorial control is a common phenomenon observed in many biological processes, our findings suggest that adverse drug effects might be minimized by fine-tuning multiple off-target interactions using single or multiple therapies. This work extends the scope of chemogenomics approaches and exemplifies the role that systems biology has in the future of drug discovery.'),
(84221, 2009, 'plos', 'Molecular mechanics of the alpha-actinin rod domain: bending, torsional, and extensional behavior', 'Golji, Javad|Collins, Robert|Mofrad, Mohammad R K', 'Molecular Cell Biomechanics Laboratory, University of California Berkeley, Berkeley, California, USA.|Molecular Cell Biomechanics Laboratory, University of California Berkeley, Berkeley, California, USA.|Molecular Cell Biomechanics Laboratory, University of California Berkeley, Berkeley, California, USA.', 'United States|United States|United States', 37, 'Actinin|Computer Simulation|Models, Molecular|Protein Conformation|Protein Multimerization|Protein Structure, Tertiary|Spectrin|Torsion, Mechanical', 'Journal Article', '10.1371/journal.pcbi.1000389', '19436721', 'alpha-Actinin is an actin crosslinking molecule that can serve as a scaffold and maintain dynamic actin filament networks. As a crosslinker in the stressed cytoskeleton, alpha-actinin can retain conformation, function, and strength. alpha-Actinin has an actin binding domain and a calmodulin homology domain separated by a long rod domain. Using molecular dynamics and normal mode analysis, we suggest that the alpha-actinin rod domain has flexible terminal regions which can twist and extend under mechanical stress, yet has a highly rigid interior region stabilized by aromatic packing within each spectrin repeat, by electrostatic interactions between the spectrin repeats, and by strong salt bridges between its two anti-parallel monomers. By exploring the natural vibrations of the alpha-actinin rod domain and by conducting bending molecular dynamics simulations we also predict that bending of the rod domain is possible with minimal force. We introduce computational methods for analyzing the torsional strain of molecules using rotating constraints. Molecular dynamics extension of the alpha-actinin rod is also performed, demonstrating transduction of the unfolding forces across salt bridges to the associated monomer of the alpha-actinin rod domain.'),
(84222, 2009, 'plos', 'SHRiMP: accurate mapping of short color-space reads', 'Rumble, Stephen M|Lacroute, Phil|Dalca, Adrian V|Fiume, Marc|Sidow, Arend|Brudno, Michael', 'Department of Computer Science, University of Toronto, Toronto, Ontario, Canada.|Department of Computer Science, University of Toronto, Toronto, Ontario, Canada.|Department of Computer Science, University of Toronto, Toronto, Ontario, Canada.|Department of Computer Science, University of Toronto, Toronto, Ontario, Canada.|Department of Computer Science, University of Toronto, Toronto, Ontario, Canada.|Department of Computer Science, University of Toronto, Toronto, Ontario, Canada.', 'Canada|Canada|Canada|Canada|Canada|Canada', 403, 'Algorithms|Animals|Chromosome Mapping|Computer Simulation|Models, Statistical|Reproducibility of Results|Sequence Alignment|Sequence Analysis, DNA|Software|Urochordata', 'Journal Article', '10.1371/journal.pcbi.1000386', '19461883', 'The development of Next Generation Sequencing technologies, capable of sequencing hundreds of millions of short reads (25-70 bp each) in a single run, is opening the door to population genomic studies of non-model species. In this paper we present SHRiMP - the SHort Read Mapping Package: a set of algorithms and methods to map short reads to a genome, even in the presence of a large amount of polymorphism. Our method is based upon a fast read mapping technique, separate thorough alignment methods for regular letter-space as well as AB SOLiD (color-space) reads, and a statistical model for false positive hits. We use SHRiMP to map reads from a newly sequenced Ciona savignyi individual to the reference genome. We demonstrate that SHRiMP can accurately map reads to this highly polymorphic genome, while confirming high heterozygosity of C. savignyi in this second individual. SHRiMP is freely available at http://compbio.cs.toronto.edu/shrimp.'),
(84223, 2009, 'plos', 'How to get the most out of your curation effort', 'Rzhetsky, Andrey|Shatkay, Hagit|Wilbur, W John', 'Department of Medicine, University of Chicago, Chicago, Illinois, USA.|Department of Medicine, University of Chicago, Chicago, Illinois, USA.|Department of Medicine, University of Chicago, Chicago, Illinois, USA.', 'United States|United States|United States', 26, 'Abstracting and Indexing as Topic|Computational Biology|Computer Simulation|Data Interpretation, Statistical|Database Management Systems|Databases, Factual|Models, Theoretical|Pattern Recognition, Automated|Terminology as Topic', 'Journal Article', '10.1371/journal.pcbi.1000391', '19461884', 'Large-scale annotation efforts typically involve several experts who may disagree with each other. We propose an approach for modeling disagreements among experts that allows providing each annotation with a confidence value (i.e., the posterior probability that it is correct). Our approach allows computing certainty-level for individual annotations, given annotator-specific parameters estimated from data. We developed two probabilistic models for performing this analysis, compared these models using computer simulation, and tested each models actual performance, based on a large data set generated by human annotators specifically for this study. We show that even in the worst-case scenario, when all annotators disagree, our approach allows us to significantly increase the probability of choosing the correct annotation. Along with this publication we make publicly available a corpus of 10,000 sentences annotated according to several cardinal dimensions that we have introduced in earlier work. The 10,000 sentences were all 3-fold annotated by a group of eight experts, while a 1,000-sentence subset was further 5-fold annotated by five new experts. While the presented data represent a specialized curation task, our modeling approach is general, most data annotation studies could benefit from our methodology.'),
(84224, 2009, 'plos', 'Computational models of the Notch network elucidate mechanisms of context-dependent signaling', 'Agrawal, Smita|Archer, Colin|Schaffer, David V', 'Department of Chemical Engineering, University of California Berkeley, Berkeley, California, United States of America.|Department of Chemical Engineering, University of California Berkeley, Berkeley, California, United States of America.|Department of Chemical Engineering, University of California Berkeley, Berkeley, California, United States of America.', 'United States|United States|United States', 53, 'Basic Helix-Loop-Helix Transcription Factors|Computational Biology|Computer Simulation|Gene Regulatory Networks|Homeodomain Proteins|Immunoglobulin J Recombination Signal Sequence-Binding Protein|Models, Genetic|Promoter Regions, Genetic|Receptor, Notch1|Repressor Proteins|Signal Transduction|Stochastic Processes|Transcription Factors|Transcription, Genetic', 'Journal Article', '10.1371/journal.pcbi.1000390', '19468305', 'The Notch signaling pathway controls numerous cell fate decisions during development and adulthood through diverse mechanisms. Thus, whereas it functions as an oscillator during somitogenesis, it can mediate an all-or-none cell fate switch to influence pattern formation in various tissues during development. Furthermore, while in some contexts continuous Notch signaling is required, in others a transient Notch signal is sufficient to influence cell fate decisions. However, the signaling mechanisms that underlie these diverse behaviors in different cellular contexts have not been understood. Notch1 along with two downstream transcription factors hes1 and RBP-Jk forms an intricate network of positive and negative feedback loops, and we have implemented a systems biology approach to computationally study this gene regulation network. Our results indicate that the system exhibits bistability and is capable of switching states at a critical level of Notch signaling initiated by its ligand Delta in a particular range of parameter values. In this mode, transient activation of Delta is also capable of inducing prolonged high expression of Hes1, mimicking the ON state depending on the intensity and duration of the signal. Furthermore, this system is highly sensitive to certain model parameters and can transition from functioning as a bistable switch to an oscillator by tuning a single parameter value. This parameter, the transcriptional repression constant of hes1, can thus qualitatively govern the behavior of the signaling network. In addition, we find that the system is able to dampen and reduce the effects of biological noise that arise from stochastic effects in gene expression for systems that respond quickly to Notch signaling.This work thus helps our understanding of an important cell fate control system and begins to elucidate how this context dependent signaling system can be modulated in different cellular settings to exhibit entirely different behaviors.'),
(84225, 2009, 'plos', 'Hypergraphs and cellular networks', 'Klamt, Steffen|Haus, Utz-Uwe|Theis, Fabian', 'Max Planck Institute for Dynamics of Complex Technical Systems, Magdeburg, Germany. klamt@mpi-magdeburg.mpg.de|Max Planck Institute for Dynamics of Complex Technical Systems, Magdeburg, Germany. klamt@mpi-magdeburg.mpg.de|Max Planck Institute for Dynamics of Complex Technical Systems, Magdeburg, Germany. klamt@mpi-magdeburg.mpg.de', 'Germany|Germany|Germany', 188, 'Algorithms|Computational Biology|Gene Regulatory Networks|Metabolic Networks and Pathways|Models, Biological|Models, Statistical|Signal Transduction', 'Journal Article', '10.1371/journal.pcbi.1000385', '19478865', '-'),
(84226, 2009, 'plos', 'BioLINK special interest group session on the future of scientific publishing', 'Markel, Scott', 'Accelrys, SciTegic R&D, San Diego, California, United States of America. smarkel@accelrys.com', 'United States', 1, 'Abstracting and Indexing as Topic|Computational Biology|Information Storage and Retrieval|Natural Language Processing|Periodicals as Topic|Publishing', 'Journal Article', '10.1371/journal.pcbi.1000398', '19478879', '-'),
(84227, 2009, 'plos', 'Structural adaptation and heterogeneity of normal and tumor microvascular networks', 'Pries, Axel R|Cornelissen, Annemiek J M|Sloot, Anoek A|Hinkeldey, Marlene|Dreher, Matthew R|Höpfner, Michael|Dewhirst, Mark W|Secomb, Timothy W', 'Department of Physiology, Charité, Berlin, Germany.|Department of Physiology, Charité, Berlin, Germany.|Department of Physiology, Charité, Berlin, Germany.|Department of Physiology, Charité, Berlin, Germany.|Department of Physiology, Charité, Berlin, Germany.|Department of Physiology, Charité, Berlin, Germany.|Department of Physiology, Charité, Berlin, Germany.|Department of Physiology, Charité, Berlin, Germany.', 'Germany|Germany|Germany|Germany|Germany|Germany|Germany|Germany', 108, 'Adaptation, Physiological|Animals|Computer Simulation|Hemodynamics|Mice|Mice, Nude|Microvessels|Models, Cardiovascular|Neoplasm Transplantation|Neoplasms|Neovascularization, Pathologic|Oxygen|Splanchnic Circulation', 'Journal Article', '10.1371/journal.pcbi.1000394', '19478883', 'Relative to normal tissues, tumor microcirculation exhibits high structural and functional heterogeneity leading to hypoxic regions and impairing treatment efficacy. Here, computational simulations of blood vessel structural adaptation are used to explore the hypothesis that abnormal adaptive responses to local hemodynamic and metabolic stimuli contribute to aberrant morphological and hemodynamic characteristics of tumor microcirculation. Topology, vascular diameter, length, and red blood cell velocity of normal mesenteric and tumor vascular networks were recorded by intravital microscopy. Computational models were used to estimate hemodynamics and oxygen distribution and to simulate vascular diameter adaptation in response to hemodynamic, metabolic and conducted stimuli. The assumed sensitivity to hemodynamic and conducted signals, the vascular growth tendency, and the random variability of vascular responses were altered to simulate normal and tumor adaptation modes. The heterogeneous properties of vascular networks were characterized by diameter mismatch at vascular branch points (d(3) (var)) and deficit of oxygen delivery relative to demand (O(2def)). In the tumor, d(3) (var) and O(2def) were higher (0.404 and 0.182) than in normal networks (0.278 and 0.099). Simulated remodeling of the tumor network with normal parameters gave low values (0.288 and 0.099). Conversely, normal networks attained tumor-like characteristics (0.41 and 0.179) upon adaptation with tumor parameters, including low conducted sensitivity, increased growth tendency, and elevated random biological variability. It is concluded that the deviant properties of tumor microcirculation may result largely from defective structural adaptation, including strongly reduced responses to conducted stimuli.'),
(84228, 2009, 'plos', 'A correspondence between solution-state dynamics of an individual protein and the sequence and conformational diversity of its family', 'Friedland, Gregory D|Lakomek, Nils-Alexander|Griesinger, Christian|Meiler, Jens|Kortemme, Tanja', 'Graduate Group in Biophysics, University of California San Francisco, San Francisco, California, United States of America.|Graduate Group in Biophysics, University of California San Francisco, San Francisco, California, United States of America.|Graduate Group in Biophysics, University of California San Francisco, San Francisco, California, United States of America.|Graduate Group in Biophysics, University of California San Francisco, San Francisco, California, United States of America.|Graduate Group in Biophysics, University of California San Francisco, San Francisco, California, United States of America.', 'United States|United States|United States|United States|United States', 58, 'Amino Acid Sequence|Computational Biology|Crystallography, X-Ray|Models, Molecular|Models, Statistical|Nuclear Magnetic Resonance, Biomolecular|Protein Conformation|Proteins|Reproducibility of Results|Sequence Alignment|Sequence Analysis, Protein|Temperature|Ubiquitin', 'Journal Article', '10.1371/journal.pcbi.1000393', '19478996', 'Conformational ensembles are increasingly recognized as a useful representation to describe fundamental relationships between protein structure, dynamics and function. Here we present an ensemble of ubiquitin in solution that is created by sampling conformational space without experimental information using Backrub motions inspired by alternative conformations observed in sub-Angstrom resolution crystal structures. Backrub-generated structures are then selected to produce an ensemble that optimizes agreement with nuclear magnetic resonance (NMR) Residual Dipolar Couplings (RDCs). Using this ensemble, we probe two proposed relationships between properties of protein ensembles: (i) a link between native-state dynamics and the conformational heterogeneity observed in crystal structures, and (ii) a relation between dynamics of an individual protein and the conformational variability explored by its natural family. We show that the Backrub motional mechanism can simultaneously explore protein native-state dynamics measured by RDCs, encompass the conformational variability present in ubiquitin complex structures and facilitate sampling of conformational and sequence variability matching those occurring in the ubiquitin protein family. Our results thus support an overall relation between protein dynamics and conformational changes enabling sequence changes in evolution. More practically, the presented method can be applied to improve protein design predictions by accounting for intrinsic native-state dynamics.'),
(84229, 2009, 'plos', 'Fast statistical alignment', 'Bradley, Robert K|Roberts, Adam|Smoot, Michael|Juvekar, Sudeep|Do, Jaeyoung|Dewey, Colin|Holmes, Ian|Pachter, Lior', 'Department of Mathematics, University of California Berkeley, Berkeley, California, United States of America. rbradley@berkeley.edu|Department of Mathematics, University of California Berkeley, Berkeley, California, United States of America. rbradley@berkeley.edu|Department of Mathematics, University of California Berkeley, Berkeley, California, United States of America. rbradley@berkeley.edu|Department of Mathematics, University of California Berkeley, Berkeley, California, United States of America. rbradley@berkeley.edu|Department of Mathematics, University of California Berkeley, Berkeley, California, United States of America. rbradley@berkeley.edu|Department of Mathematics, University of California Berkeley, Berkeley, California, United States of America. rbradley@berkeley.edu|Department of Mathematics, University of California Berkeley, Berkeley, California, United States of America. rbradley@berkeley.edu|Department of Mathematics, University of California Berkeley, Berkeley, California, United States of America. rbradley@berkeley.edu', 'United States|United States|United States|United States|United States|United States|United States|Un', 224, 'Algorithms|Amino Acid Sequence|Animals|Artificial Intelligence|Base Sequence|Data Interpretation, Statistical|Databases, Genetic|Humans|Markov Chains|Models, Genetic|Molecular Sequence Data|Sensitivity and Specificity|Sequence Alignment|Sequence Analysis|Software', 'Journal Article', '10.1371/journal.pcbi.1000392', '19478997', 'We describe a new program for the alignment of multiple biological sequences that is both statistically motivated and fast enough for problem sizes that arise in practice. Our Fast Statistical Alignment program is based on pair hidden Markov models which approximate an insertion/deletion process on a tree and uses a sequence annealing algorithm to combine the posterior probabilities estimated from these models into a multiple alignment. FSA uses its explicit statistical model to produce multiple alignments which are accompanied by estimates of the alignment accuracy and uncertainty for every column and character of the alignment--previously available only with alignment programs which use computationally-expensive Markov Chain Monte Carlo approaches--yet can align thousands of long sequences. Moreover, FSA utilizes an unsupervised query-specific learning procedure for parameter estimation which leads to improved accuracy on benchmark reference alignments in comparison to existing programs. The centroid alignment approach taken by FSA, in combination with its learning procedure, drastically reduces the amount of false-positive alignment on biological data in comparison to that given by other methods. The FSA program and a companion visualization tool for exploring uncertainty in alignments can be used via a web interface at http://orangutan.math.berkeley.edu/fsa/, and the source code is available at http://fsa.sourceforge.net/.'),
(84230, 2009, 'plos', 'Getting started in computational mass spectrometry-based proteomics', 'Vitek, Olga', 'Departments of Statistics and Computer Science, Purdue University, West Lafayette, Indiana, USA. ovitek@stat.purdue.edu', 'India', 12, 'Algorithms|Artificial Intelligence|Chromatography, Liquid|Data Interpretation, Statistical|Mass Spectrometry|Peptides|Proteins|Proteomics|Research Design', 'Journal Article', '10.1371/journal.pcbi.1000366', '19492072', '-'),
(84231, 2009, 'plos', 'Brain anatomical network and intelligence', 'Li, Yonghui|Liu, Yong|Li, Jun|Qin, Wen|Li, Kuncheng|Yu, Chunshui|Jiang, Tianzi', 'LIAMA Center for Computational Medicine, National Laboratory of Pattern Recognition, Institute of Automation, Chinese Academy of Sciences, Beijing, China.|LIAMA Center for Computational Medicine, National Laboratory of Pattern Recognition, Institute of Automation, Chinese Academy of Sciences, Beijing, China.|LIAMA Center for Computational Medicine, National Laboratory of Pattern Recognition, Institute of Automation, Chinese Academy of Sciences, Beijing, China.|LIAMA Center for Computational Medicine, National Laboratory of Pattern Recognition, Institute of Automation, Chinese Academy of Sciences, Beijing, China.|LIAMA Center for Computational Medicine, National Laboratory of Pattern Recognition, Institute of Automation, Chinese Academy of Sciences, Beijing, China.|LIAMA Center for Computational Medicine, National Laboratory of Pattern Recognition, Institute of Automation, Chinese Academy of Sciences, Beijing, China.|LIAMA Center for Computational Medicine, National Laboratory of Pattern Recognition, Institute of Automation, Chinese Academy of Sciences, Beijing, China.', 'China|China|China|China|China|China|China', 397, 'Adolescent|Adult|Brain|Brain Mapping|Cluster Analysis|Diffusion Magnetic Resonance Imaging|Female|Humans|Intelligence|Intelligence Tests|Male|Models, Neurological|Nerve Net|Neural Pathways', 'Journal Article', '10.1371/journal.pcbi.1000395', '19492086', 'Intuitively, higher intelligence might be assumed to correspond to more efficient information transfer in the brain, but no direct evidence has been reported from the perspective of brain networks. In this study, we performed extensive analyses to test the hypothesis that individual differences in intelligence are associated with brain structural organization, and in particular that higher scores on intelligence tests are related to greater global efficiency of the brain anatomical network. We constructed binary and weighted brain anatomical networks in each of 79 healthy young adults utilizing diffusion tensor tractography and calculated topological properties of the networks using a graph theoretical method. Based on their IQ test scores, all subjects were divided into general and high intelligence groups and significantly higher global efficiencies were found in the networks of the latter group. Moreover, we showed significant correlations between IQ scores and network properties across all subjects while controlling for age and gender. Specifically, higher intelligence scores corresponded to a shorter characteristic path length and a higher global efficiency of the networks, indicating a more efficient parallel information transfer in the brain. The results were consistently observed not only in the binary but also in the weighted networks, which together provide convergent evidence for our hypothesis. Our findings suggest that the efficiency of brain structural organization may be an important biological basis for intelligence.');
INSERT INTO `papers` (`id`, `ano`, `journal`, `titulo`, `autores`, `afiliacao`, `pais`, `citacoes`, `palavra_chave`, `categorias`, `doi`, `pubmed`, `abstract`) VALUES
(84232, 2009, 'plos', 'The effect of ongoing exposure dynamics in dose response relationships', 'Pujol, Josep M|Eisenberg, Joseph E|Haas, Charles N|Koopman, James S', 'Department of Epidemiology, University of Michigan, Ann Arbor, Michigan, United States of America. jmpujol@umich.edu|Department of Epidemiology, University of Michigan, Ann Arbor, Michigan, United States of America. jmpujol@umich.edu|Department of Epidemiology, University of Michigan, Ann Arbor, Michigan, United States of America. jmpujol@umich.edu|Department of Epidemiology, University of Michigan, Ann Arbor, Michigan, United States of America. jmpujol@umich.edu', 'United States|United States|United States|United States', 0, 'Adult|Algorithms|Animals|Computer Simulation|Cryptosporidiosis|Cryptosporidium parvum|Disease Transmission, Infectious|Female|Host-Pathogen Interactions|Humans|Infant|Male|Middle Aged|Models, Biological|Poliomyelitis|Poliovirus|Risk Assessment|Rotavirus|Rotavirus Infections|Time Factors|Young Adult', 'Journal Article', '10.1371/journal.pcbi.1000399', '19503605', 'Characterizing infectivity as a function of pathogen dose is integral to microbial risk assessment. Dose-response experiments usually administer doses to subjects at one time. Phenomenological models of the resulting data, such as the exponential and the Beta-Poisson models, ignore dose timing and assume independent risks from each pathogen. Real world exposure to pathogens, however, is a sequence of discrete events where concurrent or prior pathogen arrival affects the capacity of immune effectors to engage and kill newly arriving pathogens. We model immune effector and pathogen interactions during the period before infection becomes established in order to capture the dynamics generating dose timing effects. Model analysis reveals an inverse relationship between the time over which exposures accumulate and the risk of infection. Data from one time dose experiments will thus overestimate per pathogen infection risks of real world exposures. For instance, fitting our model to one time dosing data reveals a risk of 0.66 from 313 Cryptosporidium parvum pathogens. When the temporal exposure window is increased 100-fold using the same parameters fitted by our model to the one time dose data, the risk of infection is reduced to 0.09. Confirmation of this risk prediction requires data from experiments administering doses with different timings. Our model demonstrates that dose timing could markedly alter the risks generated by airborne versus fomite transmitted pathogens.'),
(84233, 2009, 'plos', 'The voice of bats: how greater mouse-eared bats recognize individuals based on their echolocation calls', 'Yovel, Yossi|Melcon, Mariana Laura|Franz, Matthias O|Denzinger, Annette|Schnitzler, Hans-Ulrich', 'Animal Physiology, Institute for Neurobiology, University of Tuebingen, Tuebingen, Germany. yossiyovel@hotmail.com|Animal Physiology, Institute for Neurobiology, University of Tuebingen, Tuebingen, Germany. yossiyovel@hotmail.com|Animal Physiology, Institute for Neurobiology, University of Tuebingen, Tuebingen, Germany. yossiyovel@hotmail.com|Animal Physiology, Institute for Neurobiology, University of Tuebingen, Tuebingen, Germany. yossiyovel@hotmail.com|Animal Physiology, Institute for Neurobiology, University of Tuebingen, Tuebingen, Germany. yossiyovel@hotmail.com', 'Germany|Germany|Germany|Germany|Germany', 63, 'Algorithms|Animals|Artificial Intelligence|Chiroptera|Data Interpretation, Statistical|Echolocation|Linear Models|Male|Models, Biological|Nonlinear Dynamics|Principal Component Analysis|Recognition (Psychology)', 'Journal Article', '10.1371/journal.pcbi.1000400', '19503606', 'Echolocating bats use the echoes from their echolocation calls to perceive their surroundings. The ability to use these continuously emitted calls, whose main function is not communication, for recognition of individual conspecifics might facilitate many of the social behaviours observed in bats. Several studies of individual-specific information in echolocation calls found some evidence for its existence but did not quantify or explain it. We used a direct paradigm to show that greater mouse-eared bats (Myotis myotis) can easily discriminate between individuals based on their echolocation calls and that they can generalize their knowledge to discriminate new individuals that they were not trained to recognize. We conclude that, despite their high variability, broadband bat-echolocation calls contain individual-specific information that is sufficient for recognition. An analysis of the call spectra showed that formant-related features are suitable cues for individual recognition. As a model for the bats decision strategy, we trained nonlinear statistical classifiers to reproduce the behaviour of the bats, namely to repeat correct and incorrect decisions of the bats. The comparison of the bats with the model strongly implies that the bats are using a prototype classification approach: they learn the average call characteristics of individuals and use them as a reference for classification.'),
(84234, 2009, 'plos', 'Functional states of the genome-scale Escherichia coli transcriptional regulatory system', 'Gianchandani, Erwin P|Joyce, Andrew R|Palsson, Bernhard Ø|Papin, Jason A', 'Department of Biomedical Engineering, University of Virginia, Charlottesville, Virginia, United States of America.|Department of Biomedical Engineering, University of Virginia, Charlottesville, Virginia, United States of America.|Department of Biomedical Engineering, University of Virginia, Charlottesville, Virginia, United States of America.|Department of Biomedical Engineering, University of Virginia, Charlottesville, Virginia, United States of America.', 'United States|United States|United States|United States', 33, 'Computational Biology|Computer Simulation|Escherichia coli|Gene Expression Profiling|Gene Regulatory Networks|Genome, Bacterial|Metabolic Networks and Pathways|Models, Biological|Monte Carlo Method|Reproducibility of Results|Signal Transduction|Transcription, Genetic', 'Journal Article', '10.1371/journal.pcbi.1000403', '19503608', 'A transcriptional regulatory network (TRN) constitutes the collection of regulatory rules that link environmental cues to the transcription state of a cells genome. We recently proposed a matrix formalism that quantitatively represents a system of such rules (a transcriptional regulatory system [TRS]) and allows systemic characterization of TRS properties. The matrix formalism not only allows the computation of the transcription state of the genome but also the fundamental characterization of the input-output mapping that it represents. Furthermore, a key advantage of this pseudo-stoichiometric matrix formalism is its ability to easily integrate with existing stoichiometric matrix representations of signaling and metabolic networks. Here we demonstrate for the first time how this matrix formalism is extendable to large-scale systems by applying it to the genome-scale Escherichia coli TRS. We analyze the fundamental subspaces of the regulatory network matrix (R) to describe intrinsic properties of the TRS. We further use Monte Carlo sampling to evaluate the E. coli transcription state across a subset of all possible environments, comparing our results to published gene expression data as validation. Finally, we present novel in silico findings for the E. coli TRS, including (1) a gene expression correlation matrix delineating functional motifs, (2) sets of gene ontologies for which regulatory rules governing gene transcription are poorly understood and which may direct further experimental characterization, and (3) the appearance of a distributed TRN structure, which is in stark contrast to the more hierarchical organization of metabolic networks.'),
(84235, 2009, 'plos', 'FINDSITE: a threading-based approach to ligand homology modeling', 'Brylinski, Michal|Skolnick, Jeffrey', 'Center for the Study of Systems Biology, School of Biology, Georgia Institute of Technology, Atlanta, Georgia, United States of America.|Center for the Study of Systems Biology, School of Biology, Georgia Institute of Technology, Atlanta, Georgia, United States of America.', 'Georgia|Georgia', 0, 'Algorithms|Bacterial Proteins|Binding Sites|Computational Biology|Conserved Sequence|Databases, Protein|Drug Discovery|Humans|Ligands|Matrix Metalloproteinase 8|Models, Molecular|Protein Binding|Protein Conformation|Proteins|Sequence Alignment|Structural Homology, Protein', 'Journal Article', '10.1371/journal.pcbi.1000405', '19503616', 'Ligand virtual screening is a widely used tool to assist in new pharmaceutical discovery. In practice, virtual screening approaches have a number of limitations, and the development of new methodologies is required. Previously, we showed that remotely related proteins identified by threading often share a common binding site occupied by chemically similar ligands. Here, we demonstrate that across an evolutionarily related, but distant family of proteins, the ligands that bind to the common binding site contain a set of strongly conserved anchor functional groups as well as a variable region that accounts for their binding specificity. Furthermore, the sequence and structure conservation of residues contacting the anchor functional groups is significantly higher than those contacting ligand variable regions. Exploiting these insights, we developed FINDSITE(LHM) that employs structural information extracted from weakly related proteins to perform rapid ligand docking by homology modeling. In large scale benchmarking, using the predicted anchor-binding mode and the crystal structure of the receptor, FINDSITE(LHM) outperforms classical docking approaches with an average ligand RMSD from native of approximately 2.5 A. For weakly homologous receptor protein models, using FINDSITE(LHM), the fraction of recovered binding residues and specific contacts is 0.66 (0.55) and 0.49 (0.38) for highly confident (all) targets, respectively. Finally, in virtual screening for HIV-1 protease inhibitors, using similarity to the ligand anchor region yields significantly improved enrichment factors. Thus, the rather accurate, computationally inexpensive FINDSITE(LHM) algorithm should be a useful approach to assist in the discovery of novel biopharmaceuticals.'),
(84236, 2009, 'plos', 'Recurrent network models for perfect temporal integration of fluctuating correlated inputs', 'Okamoto, Hiroshi|Fukai, Tomoki', 'Laboratory for Neural Circuit Theory, RIKEN Brain Science Institute, Wako, Saitama, Japan. hiroshi.okamoto@fujixerox.co.jp|Laboratory for Neural Circuit Theory, RIKEN Brain Science Institute, Wako, Saitama, Japan. hiroshi.okamoto@fujixerox.co.jp', 'Japan|Japan', 11, 'Action Potentials|Algorithms|Animals|Cerebral Cortex|Computer Simulation|Models, Neurological|Nerve Net|Neurons|Synapses|Synaptic Potentials|Time', 'Journal Article', '10.1371/journal.pcbi.1000404', '19503816', 'Temporal integration of input is essential to the accumulation of information in various cognitive and behavioral processes, and gradually increasing neuronal activity, typically occurring within a range of seconds, is considered to reflect such computation by the brain. Some psychological evidence suggests that temporal integration by the brain is nearly perfect, that is, the integration is non-leaky, and the output of a neural integrator is accurately proportional to the strength of input. Neural mechanisms of perfect temporal integration, however, remain largely unknown. Here, we propose a recurrent network model of cortical neurons that perfectly integrates partially correlated, irregular input spike trains. We demonstrate that the rate of this temporal integration changes proportionately to the probability of spike coincidences in synaptic inputs. We analytically prove that this highly accurate integration of synaptic inputs emerges from integration of the variance of the fluctuating synaptic inputs, when their mean component is kept constant. Highly irregular neuronal firing and spike coincidences are the major features of cortical activity, but they have been separately addressed so far. Our results suggest that the efficient protocol of information integration by cortical networks essentially requires both features and hence is heterotic.'),
(84237, 2009, 'plos', 'Information flow analysis of interactome networks', 'Missiuro, Patrycja Vasilyev|Liu, Kesheng|Zou, Lihua|Ross, Brian C|Zhao, Guoyan|Liu, Jun S|Ge, Hui', 'Whitehead Institute for Biomedical Research, Cambridge, Massachusetts, USA.|Whitehead Institute for Biomedical Research, Cambridge, Massachusetts, USA.|Whitehead Institute for Biomedical Research, Cambridge, Massachusetts, USA.|Whitehead Institute for Biomedical Research, Cambridge, Massachusetts, USA.|Whitehead Institute for Biomedical Research, Cambridge, Massachusetts, USA.|Whitehead Institute for Biomedical Research, Cambridge, Massachusetts, USA.|Whitehead Institute for Biomedical Research, Cambridge, Massachusetts, USA.', 'United States|United States|United States|United States|United States|United States|United States', 94, 'Animals|Caenorhabditis elegans|Caenorhabditis elegans Proteins|Computational Biology|Databases, Protein|Gene Expression|Gene Regulatory Networks|Information Theory|Models, Biological|Protein Interaction Mapping|RNA Interference|Saccharomyces cerevisiae|Saccharomyces cerevisiae Proteins', 'Journal Article', '10.1371/journal.pcbi.1000350', '19503817', 'Recent studies of cellular networks have revealed modular organizations of genes and proteins. For example, in interactome networks, a module refers to a group of interacting proteins that form molecular complexes and/or biochemical pathways and together mediate a biological process. However, it is still poorly understood how biological information is transmitted between different modules. We have developed information flow analysis, a new computational approach that identifies proteins central to the transmission of biological information throughout the network. In the information flow analysis, we represent an interactome network as an electrical circuit, where interactions are modeled as resistors and proteins as interconnecting junctions. Construing the propagation of biological signals as flow of electrical current, our method calculates an information flow score for every protein. Unlike previous metrics of network centrality such as degree or betweenness that only consider topological features, our approach incorporates confidence scores of protein-protein interactions and automatically considers all possible paths in a network when evaluating the importance of each protein. We apply our method to the interactome networks of Saccharomyces cerevisiae and Caenorhabditis elegans. We find that the likelihood of observing lethality and pleiotropy when a protein is eliminated is positively correlated with the proteins information flow score. Even among proteins of low degree or low betweenness, high information scores serve as a strong predictor of loss-of-function lethality or pleiotropy. The correlation between information flow scores and phenotypes supports our hypothesis that the proteins of high information flow reside in central positions in interactome networks. We also show that the ranks of information flow scores are more consistent than that of betweenness when a large amount of noisy data is added to an interactome. Finally, we combine gene expression data with interaction data in C. elegans and construct an interactome network for muscle-specific genes. We find that genes that rank high in terms of information flow in the muscle interactome network but not in the entire network tend to play important roles in muscle function. This framework for studying tissue-specific networks by the information flow model can be applied to other tissues and other organisms as well.'),
(84238, 2009, 'plos', 'Integrating statistical predictions and experimental verifications for enhancing protein-chemical interaction predictions in virtual screening', 'Nagamine, Nobuyoshi|Shirakawa, Takayuki|Minato, Yusuke|Torii, Kentaro|Kobayashi, Hiroki|Imoto, Masaya|Sakakibara, Yasubumi', 'Department of Biosciences and Informatics, Keio University, Yokohama, Japan.|Department of Biosciences and Informatics, Keio University, Yokohama, Japan.|Department of Biosciences and Informatics, Keio University, Yokohama, Japan.|Department of Biosciences and Informatics, Keio University, Yokohama, Japan.|Department of Biosciences and Informatics, Keio University, Yokohama, Japan.|Department of Biosciences and Informatics, Keio University, Yokohama, Japan.|Department of Biosciences and Informatics, Keio University, Yokohama, Japan.', 'Japan|Japan|Japan|Japan|Japan|Japan|Japan', 41, 'Algorithms|Amino Acid Sequence|Area Under Curve|Artificial Intelligence|Binding Sites|Computer Simulation|Databases, Protein|Drug Discovery|Feedback|Ligands|Models, Chemical|Models, Statistical|Protein Binding|Protein Interaction Domains and Motifs|Protein Interaction Mapping|Proteins|Receptors, Androgen|Reproducibility of Results|Sequence Analysis, Protein', 'Journal Article', '10.1371/journal.pcbi.1000397', '19503826', 'Predictions of interactions between target proteins and potential leads are of great benefit in the drug discovery process. We present a comprehensively applicable statistical prediction method for interactions between any proteins and chemical compounds, which requires only protein sequence data and chemical structure data and utilizes the statistical learning method of support vector machines. In order to realize reasonable comprehensive predictions which can involve many false positives, we propose two approaches for reduction of false positives: (i) efficient use of multiple statistical prediction models in the framework of two-layer SVM and (ii) reasonable design of the negative data to construct statistical prediction models. In two-layer SVM, outputs produced by the first-layer SVM models, which are constructed with different negative samples and reflect different aspects of classifications, are utilized as inputs to the second-layer SVM. In order to design negative data which produce fewer false positive predictions, we iteratively construct SVM models or classification boundaries from positive and tentative negative samples and select additional negative sample candidates according to pre-determined rules. Moreover, in order to fully utilize the advantages of statistical learning methods, we propose a strategy to effectively feedback experimental results to computational predictions with consideration of biological effects of interest. We show the usefulness of our approach in predicting potential ligands binding to human androgen receptors from more than 19 million chemical compounds and verifying these predictions by in vitro binding. Moreover, we utilize this experimental validation as feedback to enhance subsequent computational predictions, and experimentally validate these predictions again. This efficient procedure of the iteration of the in silico prediction and in vitro or in vivo experimental verifications with the sufficient feedback enabled us to identify novel ligand candidates which were distant from known ligands in the chemical space.'),
(84239, 2009, 'plos', 'SpaK/SpaR two-component system characterized by a structure-driven domain-fusion method and in vitro phosphorylation studies', 'Chakicherla, Anu|Ecale Zhou, Carol L|Dang, Martha Ligon|Rodriguez, Virginia|Hansen, J Norman|Zemla, Adam', 'Computing Applications and Research Department, Lawrence Livermore National Laboratory, Livermore, California, United States of America.|Computing Applications and Research Department, Lawrence Livermore National Laboratory, Livermore, California, United States of America.|Computing Applications and Research Department, Lawrence Livermore National Laboratory, Livermore, California, United States of America.|Computing Applications and Research Department, Lawrence Livermore National Laboratory, Livermore, California, United States of America.|Computing Applications and Research Department, Lawrence Livermore National Laboratory, Livermore, California, United States of America.|Computing Applications and Research Department, Lawrence Livermore National Laboratory, Livermore, California, United States of America.', 'United States|United States|United States|United States|United States|United States', 5, 'Bacillus subtilis|Bacterial Proteins|Computational Biology|DNA-Binding Proteins|Escherichia coli|Models, Chemical|Models, Molecular|Phosphorylation|Protein Conformation|Protein Interaction Domains and Motifs|Protein Interaction Mapping|Protein-Serine-Threonine Kinases|Recombinant Fusion Proteins|Reproducibility of Results|Structural Homology, Protein|Transcription Factors', 'Journal Article', '10.1371/journal.pcbi.1000401', '19503843', 'Here we introduce a quantitative structure-driven computational domain-fusion method, which we used to predict the structures of proteins believed to be involved in regulation of the subtilin pathway in Bacillus subtilis, and used to predict a protein-protein complex formed by interaction between the proteins. Homology modeling of SpaK and SpaR yielded preliminary structural models based on a best template for SpaK comprising a dimer of a histidine kinase, and for SpaR a response regulator protein. Our LGA code was used to identify multi-domain proteins with structure homology to both modeled structures, yielding a set of domain-fusion templates then used to model a hypothetical SpaK/SpaR complex. The models were used to identify putative functional residues and residues at the protein-protein interface, and bioinformatics was used to compare functionally and structurally relevant residues in corresponding positions among proteins with structural homology to the templates. Models of the complex were evaluated in light of known properties of the functional residues within two-component systems involving His-Asp phosphorelays. Based on this analysis, a phosphotransferase complexed with a beryllofluoride was selected as the optimal template for modeling a SpaK/SpaR complex conformation. In vitro phosphorylation studies performed using wild type and site-directed SpaK mutant proteins validated the predictions derived from application of the structure-driven domain-fusion method: SpaK was phosphorylated in the presence of (32)P-ATP and the phosphate moiety was subsequently transferred to SpaR, supporting the hypothesis that SpaK and SpaR function as sensor and response regulator, respectively, in a two-component signal transduction system, and furthermore suggesting that the structure-driven domain-fusion approach correctly predicted a physical interaction between SpaK and SpaR. Our domain-fusion algorithm leverages quantitative structure information and provides a tool for generation of hypotheses regarding protein function, which can then be tested using empirical methods.'),
(84240, 2009, 'plos', 'Modeling the impact of lesions in the human brain', 'Alstott, Jeffrey|Breakspear, Michael|Hagmann, Patric|Cammoun, Leila|Sporns, Olaf', 'Program in Cognitive Science, Indiana University, Bloomington, Indiana, USA.|Program in Cognitive Science, Indiana University, Bloomington, Indiana, USA.|Program in Cognitive Science, Indiana University, Bloomington, Indiana, USA.|Program in Cognitive Science, Indiana University, Bloomington, Indiana, USA.|Program in Cognitive Science, Indiana University, Bloomington, Indiana, USA.', 'India|India|India|India|India', 322, 'Algorithms|Brain Diseases|Brain Mapping|Cerebral Cortex|Computer Simulation|Humans|Models, Neurological|Nerve Net|Reproducibility of Results', 'Journal Article', '10.1371/journal.pcbi.1000408', '19521503', 'Lesions of anatomical brain networks result in functional disturbances of brain systems and behavior which depend sensitively, often unpredictably, on the lesion site. The availability of whole-brain maps of structural connections within the human cerebrum and our increased understanding of the physiology and large-scale dynamics of cortical networks allow us to investigate the functional consequences of focal brain lesions in a computational model. We simulate the dynamic effects of lesions placed in different regions of the cerebral cortex by recording changes in the pattern of endogenous (resting-state) neural activity. We find that lesions produce specific patterns of altered functional connectivity among distant regions of cortex, often affecting both cortical hemispheres. The magnitude of these dynamic effects depends on the lesion location and is partly predicted by structural network properties of the lesion site. In the model, lesions along the cortical midline and in the vicinity of the temporo-parietal junction result in large and widely distributed changes in functional connectivity, while lesions of primary sensory or motor regions remain more localized. The model suggests that dynamic lesion effects can be predicted on the basis of specific network measures of structural brain networks and that these effects may be related to known behavioral and cognitive consequences of brain lesions.'),
(84241, 2009, 'plos', 'Modeling and inferring cleavage patterns in proliferating epithelia', 'Patel, Ankit B|Gibson, William T|Gibson, Matthew C|Nagpal, Radhika', 'School of Engineering and Applied Science, Harvard University, Cambridge, Massachusetts, USA.|School of Engineering and Applied Science, Harvard University, Cambridge, Massachusetts, USA.|School of Engineering and Applied Science, Harvard University, Cambridge, Massachusetts, USA.|School of Engineering and Applied Science, Harvard University, Cambridge, Massachusetts, USA.', 'United States|United States|United States|United States', 34, 'Anagallis|Animals|Cell Division|Cell Shape|Computer Simulation|Cucumis|Drosophila melanogaster|Epithelial Cells|Epithelium|Models, Biological|Plant Epidermis|Wings, Animal', 'Journal Article', '10.1371/journal.pcbi.1000412', '19521504', 'The regulation of cleavage plane orientation is one of the key mechanisms driving epithelial morphogenesis. Still, many aspects of the relationship between local cleavage patterns and tissue-level properties remain poorly understood. Here we develop a topological model that simulates the dynamics of a 2D proliferating epithelium from generation to generation, enabling the exploration of a wide variety of biologically plausible cleavage patterns. We investigate a spectrum of models that incorporate the spatial impact of neighboring cells and the temporal influence of parent cells on the choice of cleavage plane. Our findings show that cleavage patterns generate signature equilibrium distributions of polygonal cell shapes. These signatures enable the inference of local cleavage parameters such as neighbor impact, maternal influence, and division symmetry from global observations of the distribution of cell shape. Applying these insights to the proliferating epithelia of five diverse organisms, we find that strong division symmetry and moderate neighbor/maternal influence are required to reproduce the predominance of hexagonal cells and low variability in cell shape seen empirically. Furthermore, we present two distinct cleavage pattern models, one stochastic and one deterministic, that can reproduce the empirical distribution of cell shapes. Although the proliferating epithelia of the five diverse organisms show a highly conserved cell shape distribution, there are multiple plausible cleavage patterns that can generate this distribution, and experimental evidence suggests that indeed plants and fruitflies use distinct division mechanisms.'),
(84242, 2009, 'plos', 'Integrated assessment of genomic correlates of protein evolutionary rate', 'Xia, Yu|Franzosa, Eric A|Gerstein, Mark B', 'Bioinformatics Program, Boston University, Boston, Massachusetts, USA. yuxia@bu.edu|Bioinformatics Program, Boston University, Boston, Massachusetts, USA. yuxia@bu.edu|Bioinformatics Program, Boston University, Boston, Massachusetts, USA. yuxia@bu.edu', 'United States|United States|United States', 0, 'Amino Acid Sequence|Amino Acids|Chemical Phenomena|Evolution, Molecular|Genome, Fungal|Genomics|Logistic Models|Models, Genetic|Models, Statistical|Protein Conformation|Saccharomyces cerevisiae Proteins', 'Journal Article', '10.1371/journal.pcbi.1000413', '19521505', 'Rates of evolution differ widely among proteins, but the causes and consequences of such differences remain under debate. With the advent of high-throughput functional genomics, it is now possible to rigorously assess the genomic correlates of protein evolutionary rate. However, dissecting the correlations among evolutionary rate and these genomic features remains a major challenge. Here, we use an integrated probabilistic modeling approach to study genomic correlates of protein evolutionary rate in Saccharomyces cerevisiae. We measure and rank degrees of association between (i) an approximate measure of protein evolutionary rate with high genome coverage, and (ii) a diverse list of protein properties (sequence, structural, functional, network, and phenotypic). We observe, among many statistically significant correlations, that slowly evolving proteins tend to be regulated by more transcription factors, deficient in predicted structural disorder, involved in characteristic biological functions (such as translation), biased in amino acid composition, and are generally more abundant, more essential, and enriched for interaction partners. Many of these results are in agreement with recent studies. In addition, we assess information contribution of different subsets of these protein properties in the task of predicting slowly evolving proteins. We employ a logistic regression model on binned data that is able to account for intercorrelation, non-linearity, and heterogeneity within features. Our model considers features both individually and in natural ensembles (meta-features) in order to assess joint information contribution and degree of contribution independence. Meta-features based on protein abundance and amino acid composition make strong, partially independent contributions to the task of predicting slowly evolving proteins, other meta-features make additional minor contributions. The combination of all meta-features yields predictions comparable to those based on paired species comparisons, and approaching the predictive limit of optimal lineage-insensitive features. Our integrated assessment framework can be readily extended to other correlational analyses at the genome scale.'),
(84243, 2009, 'plos', 'The dynamics of T-cell receptor repertoire diversity following thymus transplantation for DiGeorge anomaly', 'Ciupe, Stanca M|Devlin, Blythe H|Markert, M Louise|Kepler, Thomas B', 'Center for Computational Immunology, Department of Biostatistics and Bioinformatics, Duke University Medical Center, Durham, North Carolina, USA.|Center for Computational Immunology, Department of Biostatistics and Bioinformatics, Duke University Medical Center, Durham, North Carolina, USA.|Center for Computational Immunology, Department of Biostatistics and Bioinformatics, Duke University Medical Center, Durham, North Carolina, USA.|Center for Computational Immunology, Department of Biostatistics and Bioinformatics, Duke University Medical Center, Durham, North Carolina, USA.', 'United States|United States|United States|United States', 18, 'Algorithms|DiGeorge Syndrome|Homeostasis|Humans|Lymphocyte Count|Models, Immunological|Models, Statistical|Receptors, Antigen, T-Cell|T-Lymphocytes|Thymus Gland', 'Journal Article', '10.1371/journal.pcbi.1000396', '19521511', 'T cell populations are regulated both by signals specific to the T-cell receptor (TCR) and by signals and resources, such as cytokines and space, that act independently of TCR specificity. Although it has been demonstrated that disruption of either of these pathways has a profound effect on T-cell development, we do not yet have an understanding of the dynamical interactions of these pathways in their joint shaping of the T cell repertoire. Complete DiGeorge Anomaly is a developmental abnormality that results in the failure of the thymus to develop, absence of T cells, and profound immune deficiency. After receiving thymic tissue grafts, patients suffering from DiGeorge anomaly develop T cells derived from their own precursors but matured in the donor tissue. We followed three DiGeorge patients after thymus transplantation to utilize the remarkable opportunity these subjects provide to elucidate human T-cell developmental regulation. Our goal is the determination of the respective roles of TCR-specific vs. TCR-nonspecific regulatory signals in the growth of these emerging T-cell populations. During the course of the study, we measured peripheral blood T-cell concentrations, TCRbeta V gene-segment usage and CDR3-length spectratypes over two years or more for each of the subjects. We find, through statistical analysis based on a novel stochastic population-dynamic T-cell model, that the carrying capacity corresponding to TCR-specific resources is approximately 1000-fold larger than that of TCR-nonspecific resources, implying that the size of the peripheral T-cell pool at steady state is determined almost entirely by TCR-nonspecific mechanisms. Nevertheless, the diversity of the TCR repertoire depends crucially on TCR-specific regulation. The estimated strength of this TCR-specific regulation is sufficient to ensure rapid establishment of TCR repertoire diversity in the early phase of T cell population growth, and to maintain TCR repertoire diversity in the face of substantial clonal expansion-induced perturbation from the steady state.'),
(84244, 2009, 'plos', 'Spatio-temporal dynamics of yeast mitochondrial biogenesis: transcriptional and post-transcriptional mRNA oscillatory modules', 'Lelandais, Gaëlle|Saint-Georges, Yann|Geneix, Colette|Al-Shikhley, Liza|Dujardin, Geneviève|Jacq, Claude', 'Dynamique des Structures et Interactions des Macromolécules Biologiques (DSIMB), INSERM UMR-S 665, Université Paris Diderot, Paris, France. gaelle.lelandais@univ-paris-diderot.fr|Dynamique des Structures et Interactions des Macromolécules Biologiques (DSIMB), INSERM UMR-S 665, Université Paris Diderot, Paris, France. gaelle.lelandais@univ-paris-diderot.fr|Dynamique des Structures et Interactions des Macromolécules Biologiques (DSIMB), INSERM UMR-S 665, Université Paris Diderot, Paris, France. gaelle.lelandais@univ-paris-diderot.fr|Dynamique des Structures et Interactions des Macromolécules Biologiques (DSIMB), INSERM UMR-S 665, Université Paris Diderot, Paris, France. gaelle.lelandais@univ-paris-diderot.fr|Dynamique des Structures et Interactions des Macromolécules Biologiques (DSIMB), INSERM UMR-S 665, Université Paris Diderot, Paris, France. gaelle.lelandais@univ-paris-diderot.fr|Dynamique des Structures et Interactions des Macromolécules Biologiques (DSIMB), INSERM UMR-S 665, Université Paris Diderot, Paris, France. gaelle.lelandais@univ-paris-diderot.fr', 'France|France|France|France|France|France', 21, '3 Untranslated Regions|Algorithms|Cluster Analysis|Gene Expression Regulation, Fungal|Mitochondria|Mitochondrial Proteins|Models, Genetic|Oligonucleotide Array Sequence Analysis|Protein Biosynthesis|RNA, Fungal|RNA, Messenger|Regulatory Elements, Transcriptional|Regulon|Saccharomyces cerevisiae|Saccharomyces cerevisiae Proteins|Time Factors|Transcription Factors|Transcription, Genetic', 'Journal Article', '10.1371/journal.pcbi.1000409', '19521515', 'Examples of metabolic rhythms have recently emerged from studies of budding yeast. High density microarray analyses have produced a remarkably detailed picture of cycling gene expression that could be clustered according to metabolic functions. We developed a model-based approach for the decomposition of expression to analyze these data and to identify functional modules which, expressed sequentially and periodically, contribute to the complex and intricate mitochondrial architecture. This approach revealed that mitochondrial spatio-temporal modules are expressed during periodic spikes and specific cellular localizations, which cover the entire oscillatory period. For instance, assembly factors (32 genes) and translation regulators (47 genes) are expressed earlier than the components of the amino-acid synthesis pathways (31 genes). In addition, we could correlate the expression modules identified with particular post-transcriptional properties. Thus, mRNAs of modules expressed early are mostly translated in the vicinity of mitochondria under the control of the Puf3p mRNA-binding protein. This last spatio-temporal module concerns mostly mRNAs coding for basic elements of mitochondrial construction: assembly and regulatory factors. Prediction that unknown genes from this module code for important elements of mitochondrial biogenesis is supported by experimental evidence. More generally, these observations underscore the importance of post-transcriptional processes in mitochondrial biogenesis, highlighting close connections between nuclear transcription and cytoplasmic site-specific translation.'),
(84245, 2009, 'plos', 'Understanding the adaptive growth strategy of Lactobacillus plantarum by in silico optimisation', 'Teusink, Bas|Wiersma, Anne|Jacobs, Leo|Notebaart, Richard A|Smid, Eddy J', 'Top Institute Food and Nutrition (WCFS), Wageningen, The Netherlands. bas.teusink@falw.vu.nl|Top Institute Food and Nutrition (WCFS), Wageningen, The Netherlands. bas.teusink@falw.vu.nl|Top Institute Food and Nutrition (WCFS), Wageningen, The Netherlands. bas.teusink@falw.vu.nl|Top Institute Food and Nutrition (WCFS), Wageningen, The Netherlands. bas.teusink@falw.vu.nl|Top Institute Food and Nutrition (WCFS), Wageningen, The Netherlands. bas.teusink@falw.vu.nl', 'Netherlands|Netherlands|Netherlands|Netherlands|Netherlands', 0, 'Adaptation, Physiological|Algorithms|Bacterial Physiological Phenomena|Biomass|Computer Simulation|Fermentation|Glycerol|Lactic Acid|Lactobacillus plantarum|Metabolic Networks and Pathways|Models, Biological', 'Journal Article', '10.1371/journal.pcbi.1000410', '19521528', 'In the study of metabolic networks, optimization techniques are often used to predict flux distributions, and hence, metabolic phenotype. Flux balance analysis in particular has been successful in predicting metabolic phenotypes. However, an inherent limitation of a stoichiometric approach such as flux balance analysis is that it can predict only flux distributions that result in maximal yields. Hence, previous attempts to use FBA to predict metabolic fluxes in Lactobacillus plantarum failed, as this lactic acid bacterium produces lactate, even under glucose-limited chemostat conditions, where FBA predicted mixed acid fermentation as an alternative pathway leading to a higher yield. In this study we tested, however, whether long-term adaptation on an unusual and poor carbon source (for this bacterium) would select for mutants with optimal biomass yields. We have therefore adapted Lactobacillus plantarum to grow well on glycerol as its main growth substrate. After prolonged serial dilutions, the growth yield and corresponding fluxes were compared to in silico predictions. Surprisingly, the organism still produced mainly lactate, which was corroborated by FBA to indeed be optimal. To understand these results, constraint-based elementary flux mode analysis was developed that predicted 3 out of 2669 possible flux modes to be optimal under the experimental conditions. These optimal pathways corresponded very closely to the experimentally observed fluxes and explained lactate formation as the result of competition for oxygen by the other flux modes. Hence, these results provide thorough understanding of adaptive evolution, allowing in silico predictions of the resulting flux states, provided that the selective growth conditions favor yield optimization as the winning strategy.'),
(84246, 2009, 'plos', 'Directed mammalian gene regulatory networks using expression and comparative genomic hybridization microarray data from radiation hybrids', 'Ahn, Sangtae|Wang, Richard T|Park, Christopher C|Lin, Andy|Leahy, Richard M|Lange, Kenneth|Smith, Desmond J', 'Signal and Image Processing Institute, University of Southern California, Los Angeles, California, USA.|Signal and Image Processing Institute, University of Southern California, Los Angeles, California, USA.|Signal and Image Processing Institute, University of Southern California, Los Angeles, California, USA.|Signal and Image Processing Institute, University of Southern California, Los Angeles, California, USA.|Signal and Image Processing Institute, University of Southern California, Los Angeles, California, USA.|Signal and Image Processing Institute, University of Southern California, Los Angeles, California, USA.|Signal and Image Processing Institute, University of Southern California, Los Angeles, California, USA.', 'United States|United States|United States|United States|United States|United States|United States', 0, 'Animals|Comparative Genomic Hybridization|Cricetinae|Databases, Genetic|Gene Regulatory Networks|Mice|Models, Genetic|Models, Statistical|Oligonucleotide Array Sequence Analysis|Quantitative Trait Loci|Radiation Hybrid Mapping|Regression Analysis|Transcription Factors|Up-Regulation', 'Journal Article', '10.1371/journal.pcbi.1000407', '19521529', 'Meiotic mapping of quantitative trait loci regulating expression (eQTLs) has allowed the construction of gene networks. However, the limited mapping resolution of these studies has meant that genotype data are largely ignored, leading to undirected networks that fail to capture regulatory hierarchies. Here we use high resolution mapping of copy number eQTLs (ceQTLs) in a mouse-hamster radiation hybrid (RH) panel to construct directed genetic networks in the mammalian cell. The RH network covering 20,145 mouse genes had significant overlap with, and similar topological structures to, existing biological networks. Upregulated edges in the RH network had significantly more overlap than downregulated. This suggests repressive relationships between genes are missed by existing approaches, perhaps because the corresponding proteins are not present in the cell at the same time and therefore unlikely to interact. Gene essentiality was positively correlated with connectivity and betweenness centrality in the RH network, strengthening the centrality-lethality principle in mammals. Consistent with their regulatory role, transcription factors had significantly more outgoing edges (regulating) than incoming (regulated) in the RH network, a feature hidden by conventional undirected networks. Directed RH genetic networks thus showed concordance with pre-existing networks while also yielding information inaccessible to current undirected approaches.'),
(84247, 2009, 'plos', 'Active dendrites enhance neuronal dynamic range', 'Gollo, Leonardo L|Kinouchi, Osame|Copelli, Mauro', 'Laboratório de Física Teórica e Computacional, Departamento de Física, Universidade Federal de Pernambuco, Recife, Brazil. leonardo@ifisc.uib-csic.es|Laboratório de Física Teórica e Computacional, Departamento de Física, Universidade Federal de Pernambuco, Recife, Brazil. leonardo@ifisc.uib-csic.es|Laboratório de Física Teórica e Computacional, Departamento de Física, Universidade Federal de Pernambuco, Recife, Brazil. leonardo@ifisc.uib-csic.es', 'Brazil|Brazil|Brazil', 38, 'Animals|Computer Simulation|Dendrites|Electric Stimulation|Mice|Models, Neurological|Neurons|Retinal Ganglion Cells|Synapses', 'Journal Article', '10.1371/journal.pcbi.1000402', '19521531', 'Since the first experimental evidences of active conductances in dendrites, most neurons have been shown to exhibit dendritic excitability through the expression of a variety of voltage-gated ion channels. However, despite experimental and theoretical efforts undertaken in the past decades, the role of this excitability for some kind of dendritic computation has remained elusive. Here we show that, owing to very general properties of excitable media, the average output of a model of an active dendritic tree is a highly non-linear function of its afferent rate, attaining extremely large dynamic ranges (above 50 dB). Moreover, the model yields double-sigmoid response functions as experimentally observed in retinal ganglion cells. We claim that enhancement of dynamic range is the primary functional role of active dendritic conductances. We predict that neurons with larger dendritic trees should have larger dynamic range and that blocking of active conductances should lead to a decrease in dynamic range.'),
(84248, 2009, 'plos', 'Identification of yeast transcriptional regulation networks using multivariate random forests', 'Xiao, Yuanyuan|Segal, Mark R', 'Department of Epidemiology and Biostatistics, Center for Bioinformatics and Molecular Biostatistics, University of California, San Francisco, California, USA. Yuanyuan.Xiao@ucsf.edu|Department of Epidemiology and Biostatistics, Center for Bioinformatics and Molecular Biostatistics, University of California, San Francisco, California, USA. Yuanyuan.Xiao@ucsf.edu', 'United States|United States', 0, 'Algorithms|Artificial Intelligence|Cell Cycle|Cluster Analysis|Gene Expression Regulation, Fungal|Gene Regulatory Networks|Models, Genetic|Models, Statistical|Multivariate Analysis|Protein Binding|Protein Interaction Domains and Motifs|RNA, Fungal|RNA, Ribosomal|Reproducibility of Results|Saccharomyces cerevisiae|Saccharomyces cerevisiae Proteins|Stress, Physiological|Transcription Factors|Transcription, Genetic', 'Journal Article', '10.1371/journal.pcbi.1000414', '19543377', 'The recent availability of whole-genome scale data sets that investigate complementary and diverse aspects of transcriptional regulation has spawned an increased need for new and effective computational approaches to analyze and integrate these large scale assays. Here, we propose a novel algorithm, based on random forest methodology, to relate gene expression (as derived from expression microarrays) to sequence features residing in gene promoters (as derived from DNA motif data) and transcription factor binding to gene promoters (as derived from tiling microarrays). We extend the random forest approach to model a multivariate response as represented, for example, by time-course gene expression measures. An analysis of the multivariate random forest output reveals complex regulatory networks, which consist of cohesive, condition-dependent regulatory cliques. Each regulatory clique features homogeneous gene expression profiles and common motifs or synergistic motif groups. We apply our method to several yeast physiological processes: cell cycle, sporulation, and various stress conditions. Our technique displays excellent performance with regard to identifying known regulatory motifs, including high order interactions. In addition, we present evidence of the existence of an alternative MCB-binding pathway, which we confirm using data from two independent cell cycle studies and two other physioloigical processes. Finally, we have uncovered elaborate transcription regulation refinement mechanisms involving PAC and mRRPE motifs that govern essential rRNA processing. These include intriguing instances of differing motif dosages and differing combinatorial motif control that promote regulatory specificity in rRNA metabolism under differing physiological processes.');
INSERT INTO `papers` (`id`, `ano`, `journal`, `titulo`, `autores`, `afiliacao`, `pais`, `citacoes`, `palavra_chave`, `categorias`, `doi`, `pubmed`, `abstract`) VALUES
(84249, 2009, 'plos', 'A probabilistic model of RNA conformational space', 'Frellsen, Jes|Moltke, Ida|Thiim, Martin|Mardia, Kanti V|Ferkinghoff-Borg, Jesper|Hamelryck, Thomas', 'The Bioinformatics Center, Department of Biology, University of Copenhagen, Copenhagen, Denmark.|The Bioinformatics Center, Department of Biology, University of Copenhagen, Copenhagen, Denmark.|The Bioinformatics Center, Department of Biology, University of Copenhagen, Copenhagen, Denmark.|The Bioinformatics Center, Department of Biology, University of Copenhagen, Copenhagen, Denmark.|The Bioinformatics Center, Department of Biology, University of Copenhagen, Copenhagen, Denmark.|The Bioinformatics Center, Department of Biology, University of Copenhagen, Copenhagen, Denmark.', 'Denmark|Denmark|Denmark|Denmark|Denmark|Denmark', 64, 'Algorithms|Bayes Theorem|Computer Simulation|Databases, Nucleic Acid|Imaging, Three-Dimensional|Markov Chains|Models, Molecular|Models, Statistical|Monte Carlo Method|Nucleic Acid Conformation|RNA|Software', 'Journal Article', '10.1371/journal.pcbi.1000406', '19543381', 'The increasing importance of non-coding RNA in biology and medicine has led to a growing interest in the problem of RNA 3-D structure prediction. As is the case for proteins, RNA 3-D structure prediction methods require two key ingredients: an accurate energy function and a conformational sampling procedure. Both are only partly solved problems. Here, we focus on the problem of conformational sampling. The current state of the art solution is based on fragment assembly methods, which construct plausible conformations by stringing together short fragments obtained from experimental structures. However, the discrete nature of the fragments necessitates the use of carefully tuned, unphysical energy functions, and their non-probabilistic nature impairs unbiased sampling. We offer a solution to the sampling problem that removes these important limitations: a probabilistic model of RNA structure that allows efficient sampling of RNA conformations in continuous space, and with associated probabilities. We show that the model captures several key features of RNA structure, such as its rotameric nature and the distribution of the helix lengths. Furthermore, the model readily generates native-like 3-D conformations for 9 out of 10 test structures, solely using coarse-grained base-pairing information. In conclusion, the method provides a theoretical and practical solution for a major bottleneck on the way to routine prediction and simulation of RNA structure and dynamics in atomic detail.'),
(84250, 2009, 'plos', 'Taking the lag out of jet lag through model-based schedule design', 'Dean, Dennis A|Forger, Daniel B|Klerman, Elizabeth B', 'Division of Sleep Medicine, Brigham & Womens Hospital, Boston, Massachusetts, USA. ddean@rics.bwh.harvard.edu|Division of Sleep Medicine, Brigham & Womens Hospital, Boston, Massachusetts, USA. ddean@rics.bwh.harvard.edu|Division of Sleep Medicine, Brigham & Womens Hospital, Boston, Massachusetts, USA. ddean@rics.bwh.harvard.edu', 'United States|United States|United States', 31, 'Algorithms|Circadian Rhythm|Computer Simulation|Environment|Humans|Jet Lag Syndrome|Lighting|Models, Biological|Sleep|Software|Wakefulness', 'Journal Article', '10.1371/journal.pcbi.1000418', '19543382', 'Travel across multiple time zones results in desynchronization of environmental time cues and the sleep-wake schedule from their normal phase relationships with the endogenous circadian system. Circadian misalignment can result in poor neurobehavioral performance, decreased sleep efficiency, and inappropriately timed physiological signals including gastrointestinal activity and hormone release. Frequent and repeated transmeridian travel is associated with long-term cognitive deficits, and rodents experimentally exposed to repeated schedule shifts have increased death rates. One approach to reduce the short-term circadian, sleep-wake, and performance problems is to use mathematical models of the circadian pacemaker to design countermeasures that rapidly shift the circadian pacemaker to align with the new schedule. In this paper, the use of mathematical models to design sleep-wake and countermeasure schedules for improved performance is demonstrated. We present an approach to designing interventions that combines an algorithm for optimal placement of countermeasures with a novel mode of schedule representation. With these methods, rapid circadian resynchrony and the resulting improvement in neurobehavioral performance can be quickly achieved even after moderate to large shifts in the sleep-wake schedule. The key schedule design inputs are endogenous circadian period length, desired sleep-wake schedule, length of intervention, background light level, and countermeasure strength. The new schedule representation facilitates schedule design, simulation studies, and experiment design and significantly decreases the amount of time to design an appropriate intervention. The method presented in this paper has direct implications for designing jet lag, shift-work, and non-24-hour schedules, including scheduling for extreme environments, such as in space, undersea, or in polar regions.'),
(84251, 2009, 'plos', 'Global prediction of tissue-specific gene expression and context-dependent gene networks in Caenorhabditis elegans', 'Chikina, Maria D|Huttenhower, Curtis|Murphy, Coleen T|Troyanskaya, Olga G', 'Department of Molecular Biology, Princeton University, Princeton, New Jersey, USA.|Department of Molecular Biology, Princeton University, Princeton, New Jersey, USA.|Department of Molecular Biology, Princeton University, Princeton, New Jersey, USA.|Department of Molecular Biology, Princeton University, Princeton, New Jersey, USA.', 'Jersey|Jersey|Jersey|Jersey', 0, 'Algorithms|Animals|Artificial Intelligence|Base Sequence|Caenorhabditis elegans|Computer Simulation|Data Interpretation, Statistical|GATA Transcription Factors|Gene Expression Profiling|Gene Expression Regulation|Gene Regulatory Networks|Green Fluorescent Proteins|MicroRNAs|Models, Genetic|Oligonucleotide Array Sequence Analysis|Promoter Regions, Genetic|Reproducibility of Results|Sequence Homology, Nucleic Acid', 'Journal Article', '10.1371/journal.pcbi.1000417', '19543383', 'Tissue-specific gene expression plays a fundamental role in metazoan biology and is an important aspect of many complex diseases. Nevertheless, an organism-wide map of tissue-specific expression remains elusive due to difficulty in obtaining these data experimentally. Here, we leveraged existing whole-animal Caenorhabditis elegans microarray data representing diverse conditions and developmental stages to generate accurate predictions of tissue-specific gene expression and experimentally validated these predictions. These patterns of tissue-specific expression are more accurate than existing high-throughput experimental studies for nearly all tissues, they also complement existing experiments by addressing tissue-specific expression present at particular developmental stages and in small tissues. We used these predictions to address several experimentally challenging questions, including the identification of tissue-specific transcriptional motifs and the discovery of potential miRNA regulation specific to particular tissues. We also investigate the role of tissue context in gene function through tissue-specific functional interaction networks. To our knowledge, this is the first study producing high-accuracy predictions of tissue-specific expression and interactions for a metazoan organism based on whole-animal data.'),
(84252, 2009, 'plos', 'Establishing a successful bioinformatics core facility team', 'Lewitter, Fran|Rebhan, Michael', 'Bioinformatics and Research Computing, Whitehead Institute for Biomedical Research, Cambridge, Massachusetts, United States of America. lewitter@wi.mit.edu|Bioinformatics and Research Computing, Whitehead Institute for Biomedical Research, Cambridge, Massachusetts, United States of America. lewitter@wi.mit.edu', 'United States|United States', 0, 'Computational Biology|Humans', 'Journal Article', '10.1371/journal.pcbi.1000368', '19557124', '-'),
(84253, 2009, 'plos', 'Managing and analyzing next-generation sequence data', 'Richter, Brent G|Sexton, David P', 'Enterprise Research IS and Informatics, Brigham and Womens Hospital, Massachusetts General Hospital, and Partners Healthcare, Boston, Massachusetts, United States of America. brichter@partners.org|Enterprise Research IS and Informatics, Brigham and Womens Hospital, Massachusetts General Hospital, and Partners Healthcare, Boston, Massachusetts, United States of America. brichter@partners.org', 'United States|United States', 38, 'Computational Biology|Database Management Systems|Databases, Genetic|Sequence Analysis|Software|Workforce', 'Journal Article', '10.1371/journal.pcbi.1000369', '19557125', '-'),
(84254, 2009, 'plos', 'Maximum-likelihood model averaging to profile clustering of site types across discrete linear sequences', 'Zhang, Zhang|Townsend, Jeffrey P', 'Department of Ecology and Evolutionary Biology, Yale University, New Haven, Connecticut, United States of America.|Department of Ecology and Evolutionary Biology, Yale University, New Haven, Connecticut, United States of America.', 'United States|United States', 12, 'Alcohol Dehydrogenase|Algorithms|Amino Acid Sequence|Animals|Base Sequence|Cluster Analysis|Computational Biology|Computer Simulation|Drosophila|Drosophila Proteins|Likelihood Functions|Models, Genetic|Sequence Analysis', 'Journal Article', '10.1371/journal.pcbi.1000421', '19557160', 'A major analytical challenge in computational biology is the detection and description of clusters of specified site types, such as polymorphic or substituted sites within DNA or protein sequences. Progress has been stymied by a lack of suitable methods to detect clusters and to estimate the extent of clustering in discrete linear sequences, particularly when there is no a priori specification of cluster size or cluster count. Here we derive and demonstrate a maximum likelihood method of hierarchical clustering. Our method incorporates a tripartite divide-and-conquer strategy that models sequence heterogeneity, delineates clusters, and yields a profile of the level of clustering associated with each site. The clustering model may be evaluated via model selection using the Akaike Information Criterion, the corrected Akaike Information Criterion, and the Bayesian Information Criterion. Furthermore, model averaging using weighted model likelihoods may be applied to incorporate model uncertainty into the profile of heterogeneity across sites. We evaluated our method by examining its performance on a number of simulated datasets as well as on empirical polymorphism data from diverse natural alleles of the Drosophila alcohol dehydrogenase gene. Our method yielded greater power for the detection of clustered sites across a breadth of parameter ranges, and achieved better accuracy and precision of estimation of clusters, than did the existing empirical cumulative distribution function statistics.'),
(84255, 2009, 'plos', 'The need for centralization of computational biology resources', 'Lewitter, Fran|Rebhan, Michael|Richter, Brent|Sexton, David', 'Bioinformatics and Research Computing, Whitehead Institute for Biomedical Research, Cambridge, Massachusetts, United States of America. lewitter@wi.mit.edu|Bioinformatics and Research Computing, Whitehead Institute for Biomedical Research, Cambridge, Massachusetts, United States of America. lewitter@wi.mit.edu|Bioinformatics and Research Computing, Whitehead Institute for Biomedical Research, Cambridge, Massachusetts, United States of America. lewitter@wi.mit.edu|Bioinformatics and Research Computing, Whitehead Institute for Biomedical Research, Cambridge, Massachusetts, United States of America. lewitter@wi.mit.edu', 'United States|United States|United States|United States', 0, 'Computational Biology|Computer Communication Networks|Database Management Systems|Databases, Genetic', 'Editorial', '10.1371/journal.pcbi.1000372', '19557184', '-'),
(84256, 2009, 'plos', 'Exploring the free energy landscape: from dynamics to networks and back', 'Prada-Gracia, Diego|Gómez-Gardeñes, Jesús|Echenique, Pablo|Falo, Fernando', 'Departamento de Física de la Materia Condensada, Universidad de Zaragoza, Zaragoza, Spain.|Departamento de Física de la Materia Condensada, Universidad de Zaragoza, Zaragoza, Spain.|Departamento de Física de la Materia Condensada, Universidad de Zaragoza, Zaragoza, Spain.|Departamento de Física de la Materia Condensada, Universidad de Zaragoza, Zaragoza, Spain.', 'Spain|Spain|Spain|Spain', 75, 'Algorithms|Cluster Analysis|Dipeptides|Isomerism|Kinetics|Markov Chains|Models, Chemical|Polymers|Protein Conformation|Proteins|Thermodynamics', 'Journal Article', '10.1371/journal.pcbi.1000415', '19557191', 'Knowledge of the Free Energy Landscape topology is the essential key to understanding many biochemical processes. The determination of the conformers of a protein and their basins of attraction takes a central role for studying molecular isomerization reactions. In this work, we present a novel framework to unveil the features of a Free Energy Landscape answering questions such as how many meta-stable conformers there are, what the hierarchical relationship among them is, or what the structure and kinetics of the transition paths are. Exploring the landscape by molecular dynamics simulations, the microscopic data of the trajectory are encoded into a Conformational Markov Network. The structure of this graph reveals the regions of the conformational space corresponding to the basins of attraction. In addition, handling the Conformational Markov Network, relevant kinetic magnitudes as dwell times and rate constants, or hierarchical relationships among basins, completes the global picture of the landscape. We show the power of the analysis studying a toy model of a funnel-like potential and computing efficiently the conformers of a short peptide, dialanine, paving the way to a systematic study of the Free Energy Landscape in large peptides.'),
(84257, 2009, 'plos', 'Quantitative analysis of mechanisms that govern red blood cell age structure and dynamics during anaemia', 'Savill, Nicholas J|Chadwick, William|Reece, Sarah E', 'Centre for Infectious Diseases, Institute of Immunology and Infection Research, University of Edinburgh, Edinburgh, United Kingdom. nick.savill@ed.ac.uk|Centre for Infectious Diseases, Institute of Immunology and Infection Research, University of Edinburgh, Edinburgh, United Kingdom. nick.savill@ed.ac.uk|Centre for Infectious Diseases, Institute of Immunology and Infection Research, University of Edinburgh, Edinburgh, United Kingdom. nick.savill@ed.ac.uk', 'United Kingdom|United Kingdom|United Kingdom', 0, 'Anemia|Animals|Bayes Theorem|Bone Marrow Cells|Disease Models, Animal|Erythrocyte Aging|Erythrocyte Count|Erythrocytes|Erythropoietin|Feedback, Physiological|Markov Chains|Mice|Monte Carlo Method|Phenylhydrazines|Reticulocyte Count|Reticulocytes', 'Journal Article', '10.1371/journal.pcbi.1000416', '19557192', 'Mathematical modelling has proven an important tool in elucidating and quantifying mechanisms that govern the age structure and population dynamics of red blood cells (RBCs). Here we synthesise ideas from previous experimental data and the mathematical modelling literature with new data in order to test hypotheses and generate new predictions about these mechanisms. The result is a set of competing hypotheses about three intrinsic mechanisms: the feedback from circulating RBC concentration to production rate of immature RBCs (reticulocytes) in bone marrow, the release of reticulocytes from bone marrow into the circulation, and their subsequent ageing and clearance. In addition we examine two mechanisms specific to our experimental system: the effect of phenylhydrazine (PHZ) and blood sampling on RBC dynamics. We performed a set of experiments to quantify the dynamics of reticulocyte proportion, RBC concentration, and erythropoietin concentration in PHZ-induced anaemic mice. By quantifying experimental error we are able to fit and assess each hypothesis against our data and recover parameter estimates using Markov chain Monte Carlo based Bayesian inference. We find that, under normal conditions, about 3% of reticulocytes are released early from bone marrow and upon maturation all cells are released immediately. In the circulation, RBCs undergo random clearance but have a maximum lifespan of about 50 days. Under anaemic conditions reticulocyte production rate is linearly correlated with the difference between normal and anaemic RBC concentrations, and their release rate is exponentially correlated with the same. PHZ appears to age rather than kill RBCs, and younger RBCs are affected more than older RBCs. Blood sampling caused short aperiodic spikes in the proportion of reticulocytes which appear to have a different developmental pathway than normal reticulocytes. We also provide evidence of large diurnal oscillations in serum erythropoietin levels during anaemia.'),
(84258, 2009, 'plos', 'Optimal control predicts human performance on objects with internal degrees of freedom', 'Nagengast, Arne J|Braun, Daniel A|Wolpert, Daniel M', 'Department of Engineering, Computational and Biological Learning Lab, University of Cambridge, Cambridge, United Kingdom. an261@cam.ac.uk|Department of Engineering, Computational and Biological Learning Lab, University of Cambridge, Cambridge, United Kingdom. an261@cam.ac.uk|Department of Engineering, Computational and Biological Learning Lab, University of Cambridge, Cambridge, United Kingdom. an261@cam.ac.uk', 'United Kingdom|United Kingdom|United Kingdom', 76, 'Adult|Algorithms|Arm|Computer Simulation|Feedback|Female|Humans|Linear Models|Male|Models, Biological|Motor Skills|Nonlinear Dynamics|Robotics|Task Performance and Analysis|User-Computer Interface', 'Journal Article', '10.1371/journal.pcbi.1000419', '19557193', 'On a daily basis, humans interact with a vast range of objects and tools. A class of tasks, which can pose a serious challenge to our motor skills, are those that involve manipulating objects with internal degrees of freedom, such as when folding laundry or using a lasso. Here, we use the framework of optimal feedback control to make predictions of how humans should interact with such objects. We confirm the predictions experimentally in a two-dimensional object manipulation task, in which subjects learned to control six different objects with complex dynamics. We show that the non-intuitive behavior observed when controlling objects with internal degrees of freedom can be accounted for by a simple cost function representing a trade-off between effort and accuracy. In addition to using a simple linear, point-mass optimal control model, we also used an optimal control model, which considers the non-linear dynamics of the human arm. We find that the more realistic optimal control model captures aspects of the data that cannot be accounted for by the linear model or other previous theories of motor control. The results suggest that our everyday interactions with objects can be understood by optimality principles and advocate the use of more realistic optimal control models for the study of human motor neuroscience.'),
(84259, 2009, 'plos', 'What is stochastic resonance? Definitions, misconceptions, debates, and its relevance to biology', 'McDonnell, Mark D|Abbott, Derek', 'Institute for Telecommunications Research, University of South Australia, Mawson Lakes, South Australia, Australia. mark.mcdonnell@unisa.edu.au|Institute for Telecommunications Research, University of South Australia, Mawson Lakes, South Australia, Australia. mark.mcdonnell@unisa.edu.au', 'Australia|Australia', 406, 'Biomedical Engineering|Brain|Computational Biology|Models, Biological|Models, Neurological|Neurosciences|Signal Processing, Computer-Assisted|Stochastic Processes', 'Journal Article', '10.1371/journal.pcbi.1000348', '19562010', 'Stochastic resonance is said to be observed when increases in levels of unpredictable fluctuations--e.g., random noise--cause an increase in a metric of the quality of signal transmission or detection performance, rather than a decrease. This counterintuitive effect relies on system nonlinearities and on some parameter ranges being suboptimal. Stochastic resonance has been observed, quantified, and described in a plethora of physical and biological systems, including neurons. Being a topic of widespread multidisciplinary interest, the definition of stochastic resonance has evolved significantly over the last decade or so, leading to a number of debates, misunderstandings, and controversies. Perhaps the most important debate is whether the brain has evolved to utilize random noise in vivo, as part of the neural code. Surprisingly, this debate has been for the most part ignored by neuroscientists, despite much indirect evidence of a positive role for noise in the brain. We explore some of the reasons for this and argue why it would be more surprising if the brain did not exploit randomness provided by noise--via stochastic resonance or otherwise--than if it did. We also challenge neuroscientists and biologists, both computational and experimental, to embrace a very broad definition of stochastic resonance in terms of signal-processing noise benefits, and to devise experiments aimed at verifying that random variability can play a functional role in the brain, nervous system, or other areas of biology.'),
(84260, 2009, 'plos', 'Investigating the conformational stability of prion strains through a kinetic replication model', 'Zampieri, Mattia|Legname, Giuseppe|Altafini, Claudio', 'Functional Analysis Sector, International School for Advanced Studies, Trieste, Italy.|Functional Analysis Sector, International School for Advanced Studies, Trieste, Italy.|Functional Analysis Sector, International School for Advanced Studies, Trieste, Italy.', 'Italy|Italy|Italy', 0, 'Kinetics|Linear Models|Models, Chemical|Nonlinear Dynamics|PrPSc Proteins|Protein Conformation|Protein Multimerization|Protein Stability', 'Journal Article', '10.1371/journal.pcbi.1000420', '19578427', 'Prion proteins are known to misfold into a range of different aggregated forms, showing different phenotypic and pathological states. Understanding strain specificities is an important problem in the field of prion disease. Little is known about which PrP(Sc) structural properties and molecular mechanisms determine prion replication, disease progression and strain phenotype. The aim of this work is to investigate, through a mathematical model, how the structural stability of different aggregated forms can influence the kinetics of prion replication. The model-based results suggest that prion strains with different conformational stability undergoing in vivo replication are characterizable in primis by means of different rates of breakage. A further role seems to be played by the aggregation rate (i.e. the rate at which a prion fibril grows). The kinetic variability introduced in the model by these two parameters allows us to reproduce the different characteristic features of the various strains (e.g., fibrils mean length) and is coherent with all experimental observations concerning strain-specific behavior.'),
(84261, 2009, 'plos', 'Drug discovery using chemical systems biology: repositioning the safe medicine Comtan to treat multi-drug and extensively drug resistant tuberculosis', 'Kinnings, Sarah L|Liu, Nina|Buchmeier, Nancy|Tonge, Peter J|Xie, Lei|Bourne, Philip E', 'Department of Biology, University of York, York, UK.|Department of Biology, University of York, York, UK.|Department of Biology, University of York, York, UK.|Department of Biology, University of York, York, UK.|Department of Biology, University of York, York, UK.|Department of Biology, University of York, York, UK.', 'United Kingdom|United Kingdom|United Kingdom|United Kingdom|United Kingdom|United Kingdom', 0, 'Animals|Antitubercular Agents|Bacterial Proteins|Benzophenones|Catechol O-Methyltransferase|Catechol O-Methyltransferase Inhibitors|Catechols|Drug Discovery|Enzyme Inhibitors|Extensively Drug-Resistant Tuberculosis|Humans|Microbial Sensitivity Tests|Mycobacterium tuberculosis|Nitriles|Nitrophenols|Oxidoreductases|Rats|Systems Biology|Tolcapone|Tuberculosis, Multidrug-Resistant', 'Journal Article', '10.1371/journal.pcbi.1000423', '19578428', 'The rise of multi-drug resistant (MDR) and extensively drug resistant (XDR) tuberculosis around the world, including in industrialized nations, poses a great threat to human health and defines a need to develop new, effective and inexpensive anti-tubercular agents. Previously we developed a chemical systems biology approach to identify off-targets of major pharmaceuticals on a proteome-wide scale. In this paper we further demonstrate the value of this approach through the discovery that existing commercially available drugs, prescribed for the treatment of Parkinsons disease, have the potential to treat MDR and XDR tuberculosis. These drugs, entacapone and tolcapone, are predicted to bind to the enzyme InhA and directly inhibit substrate binding. The prediction is validated by in vitro and InhA kinetic assays using tablets of Comtan, whose active component is entacapone. The minimal inhibition concentration (MIC(99)) of entacapone for Mycobacterium tuberculosis (M.tuberculosis) is approximately 260.0 microM, well below the toxicity concentration determined by an in vitro cytotoxicity model using a human neuroblastoma cell line. Moreover, kinetic assays indicate that Comtan inhibits InhA activity by 47.0% at an entacapone concentration of approximately 80 microM. Thus the active component in Comtan represents a promising lead compound for developing a new class of anti-tubercular therapeutics with excellent safety profiles. More generally, the protocol described in this paper can be included in a drug discovery pipeline in an effort to discover novel drug leads with desired safety profiles, and therefore accelerate the development of new drugs.'),
(84262, 2009, 'plos', 'A compact representation of drawing movements with sequences of parabolic primitives', 'Polyakov, Felix|Drori, Rotem|Ben-Shaul, Yoram|Abeles, Moshe|Flash, Tamar', 'Department of Computer Science and Applied Mathematics, Weizmann Institute of Science, Rehovot, Israel. felix.polyakov@weizmann.ac.il|Department of Computer Science and Applied Mathematics, Weizmann Institute of Science, Rehovot, Israel. felix.polyakov@weizmann.ac.il|Department of Computer Science and Applied Mathematics, Weizmann Institute of Science, Rehovot, Israel. felix.polyakov@weizmann.ac.il|Department of Computer Science and Applied Mathematics, Weizmann Institute of Science, Rehovot, Israel. felix.polyakov@weizmann.ac.il|Department of Computer Science and Applied Mathematics, Weizmann Institute of Science, Rehovot, Israel. felix.polyakov@weizmann.ac.il', 'Israel|Israel|Israel|Israel|Israel', 0, 'Animals|Arm|Behavior, Animal|Computational Biology|Data Interpretation, Statistical|Female|Hand|Handwriting|Macaca fascicularis|Models, Biological|Motor Activity|Practice (Psychology)|Reward', 'Journal Article', '10.1371/journal.pcbi.1000427', '19578429', 'Some studies suggest that complex arm movements in humans and monkeys may optimize several objective functions, while others claim that arm movements satisfy geometric constraints and are composed of elementary components. However, the ability to unify different constraints has remained an open question. The criterion for a maximally smooth (minimizing jerk) motion is satisfied for parabolic trajectories having constant equi-affine speed, which thus comply with the geometric constraint known as the two-thirds power law. Here we empirically test the hypothesis that parabolic segments provide a compact representation of spontaneous drawing movements. Monkey scribblings performed during a period of practice were recorded. Practiced hand paths could be approximated well by relatively long parabolic segments. Following practice, the orientations and spatial locations of the fitted parabolic segments could be drawn from only 2-4 clusters, and there was less discrepancy between the fitted parabolic segments and the executed paths. This enabled us to show that well-practiced spontaneous scribbling movements can be represented as sequences (words) of a small number of elementary parabolic primitives (letters). A movement primitive can be defined as a movement entity that cannot be intentionally stopped before its completion. We found that in a well-trained monkey a movement was usually decelerated after receiving a reward, but it stopped only after the completion of a sequence composed of several parabolic segments. Piece-wise parabolic segments can be generated by applying affine geometric transformations to a single parabolic template. Thus, complex movements might be constructed by applying sequences of suitable geometric transformations to a few templates. Our findings therefore suggest that the motor system aims at achieving more parsimonious internal representations through practice, that parabolas serve as geometric primitives and that non-Euclidean variables are employed in internal movement representations (due to the special role of parabolas in equi-affine geometry).'),
(84263, 2009, 'plos', 'What a plant sounds like: the statistics of vegetation echoes as received by echolocating bats', 'Yovel, Yossi|Stilz, Peter|Franz, Matthias O|Boonman, Arjan|Schnitzler, Hans-Ulrich', 'Animal Physiology Department, University of Tuebingen, Tuebingen, Germany. yossiyovel@hotmail.com|Animal Physiology Department, University of Tuebingen, Tuebingen, Germany. yossiyovel@hotmail.com|Animal Physiology Department, University of Tuebingen, Tuebingen, Germany. yossiyovel@hotmail.com|Animal Physiology Department, University of Tuebingen, Tuebingen, Germany. yossiyovel@hotmail.com|Animal Physiology Department, University of Tuebingen, Tuebingen, Germany. yossiyovel@hotmail.com', 'Germany|Germany|Germany|Germany|Germany', 31, 'Acoustics|Animals|Chiroptera|Cluster Analysis|Echolocation|Infrared Rays|Models, Biological|Models, Statistical|Plant Leaves|Plant Physiological Phenomena|Poisson Distribution|Trees', 'Journal Article', '10.1371/journal.pcbi.1000429', '19578430', 'A critical step on the way to understanding a sensory system is the analysis of the input it receives. In this work we examine the statistics of natural complex echoes, focusing on vegetation echoes. Vegetation echoes constitute a major part of the sensory world of more than 800 species of echolocating bats and play an important role in several of their daily tasks. Our statistical analysis is based on a large collection of plant echoes acquired by a biomimetic sonar system. We explore the relation between the physical world (the structure of the plant) and the characteristics of its echo. Finally, we complete the story by analyzing the effect of the sensory processing of both the echolocation and the auditory systems on the echoes and interpret them in the light of information maximization. The echoes of all different plant species we examined share a surprisingly robust pattern that was also reproduced by a simple Poisson model of the spatial reflector arrangement. The fine differences observed between the echoes of different plant species can be explained by the spatial characteristics of the plants. The bats emitted signal enhances the most informative spatial frequency range where the species-specific information is large. The auditory system filtering affects the echoes in a similar way, thus enhancing the most informative spatial frequency range even more. These findings suggest how the bats sensory system could have evolved to deal with complex natural echoes.'),
(84264, 2009, 'plos', 'The Gene Ontologys Reference Genome Project: a unified framework for functional annotation across species', 'Reference Genome Group of the Gene Ontology Consortium', 'Animal Physiology Department, University of Tuebingen, Tuebingen, Germany. yossiyovel@hotmail.com', 'Germany', 118, 'Animals|Cluster Analysis|Database Management Systems|Databases, Genetic|Genomics|Humans|Vocabulary, Controlled', 'Journal Article', '10.1371/journal.pcbi.1000431', '19578431', 'The Gene Ontology (GO) is a collaborative effort that provides structured vocabularies for annotating the molecular function, biological role, and cellular location of gene products in a highly systematic way and in a species-neutral manner with the aim of unifying the representation of gene function across different organisms. Each contributing member of the GO Consortium independently associates GO terms to gene products from the organism(s) they are annotating. Here we introduce the Reference Genome project, which brings together those independent efforts into a unified framework based on the evolutionary relationships between genes in these different organisms. The Reference Genome project has two primary goals: to increase the depth and breadth of annotations for genes in each of the organisms in the project, and to create data sets and tools that enable other genome annotation efforts to infer GO annotations for homologous genes in their organisms. In addition, the project has several important incidental benefits, such as increasing annotation consistency across genome databases, and providing important improvements to the GOs logical structure and biological content.'),
(84265, 2009, 'plos', 'Predicting the distribution of spiral waves from cell properties in a developmental-path model of Dictyostelium pattern formation', 'Geberth, Daniel|Hütt, Marc-Thorsten', 'Computational Systems Biology, School of Engineering and Science, Jacobs University Bremen, Bremen, Germany. d.geberth@jacobs-university.de|Computational Systems Biology, School of Engineering and Science, Jacobs University Bremen, Bremen, Germany. d.geberth@jacobs-university.de', 'Germany|Germany', 12, 'Algorithms|Animals|Computational Biology|Cyclic AMP|Dictyostelium|Models, Biological|Models, Statistical|Phosphoric Diester Hydrolases', 'Journal Article', '10.1371/journal.pcbi.1000422', '19593362', 'The slime mold Dictyostelium discoideum is one of the model systems of biological pattern formation. One of the most successful answers to the challenge of establishing a spiral wave pattern in a colony of homogeneously distributed D. discoideum cells has been the suggestion of a developmental path the cells follow (Lauzeral and coworkers). This is a well-defined change in properties each cell undergoes on a longer time scale than the typical dynamics of the cell. Here we show that this concept leads to an inhomogeneous and systematic spatial distribution of spiral waves, which can be predicted from the distribution of cells on the developmental path. We propose specific experiments for checking whether such systematics are also found in data and thus, indirectly, provide evidence of a developmental path.'),
(84266, 2009, 'plos', 'An experimental and computational study of the effect of ActA polarity on the speed of Listeria monocytogenes actin-based motility', 'Rafelski, Susanne M|Alberts, Jonathan B|Odell, Garrett M', 'Center for Cell Dynamics, University of Washington, Friday Harbor, Washington, USA.|Center for Cell Dynamics, University of Washington, Friday Harbor, Washington, USA.|Center for Cell Dynamics, University of Washington, Friday Harbor, Washington, USA.', 'United States|United States|United States', 0, 'Actins|Bacterial Proteins|Cell Polarity|Computer Simulation|Friction|Listeria monocytogenes|Membrane Proteins|Models, Biological', 'Journal Article', '10.1371/journal.pcbi.1000434', '19593363', 'Listeria monocytogenes is a pathogenic bacterium that moves within infected cells and spreads directly between cells by harnessing the cells dendritic actin machinery. This motility is dependent on expression of a single bacterial surface protein, ActA, a constitutively active Arp2,3 activator, and has been widely studied as a biochemical and biophysical model system for actin-based motility. Dendritic actin network dynamics are important for cell processes including eukaryotic cell motility, cytokinesis, and endocytosis. Here we experimentally altered the degree of ActA polarity on a population of bacteria and made use of an ActA-RFP fusion to determine the relationship between ActA distribution and speed of bacterial motion. We found a positive linear relationship for both ActA intensity and polarity with speed. We explored the underlying mechanisms of this dependence with two distinctly different quantitative models: a detailed agent-based model in which each actin filament and branched network is explicitly simulated, and a three-state continuum model that describes a simplified relationship between bacterial speed and barbed-end actin populations. In silico bacterial motility required a cooperative restraining mechanism to reconstitute our observed speed-polarity relationship, suggesting that kinetic friction between actin filaments and the bacterial surface, a restraining force previously neglected in motility models, is important in determining the effect of ActA polarity on bacterial motility. The continuum model was less restrictive, requiring only a filament number-dependent restraining mechanism to reproduce our experimental observations. However, seemingly rational assumptions in the continuum model, e.g. an average propulsive force per filament, were invalidated by further analysis with the agent-based model. We found that the average contribution to motility from side-interacting filaments was actually a function of the ActA distribution. This ActA-dependence would be difficult to intuit but emerges naturally from the nanoscale interactions in the agent-based representation.'),
(84267, 2009, 'plos', 'Analysis of the free-energy surface of proteins from reversible folding simulations', 'Allen, Lucy R|Krivov, Sergei V|Paci, Emanuele', 'School of Physics & Astronomy, University of Leeds, Leeds, United Kingdom.|School of Physics & Astronomy, University of Leeds, Leeds, United Kingdom.|School of Physics & Astronomy, University of Leeds, Leeds, United Kingdom.', 'United Kingdom|United Kingdom|United Kingdom', 0, 'Computer Simulation|Models, Chemical|Models, Molecular|Protein Conformation|Protein Folding|Proteins|Thermodynamics', 'Journal Article', '10.1371/journal.pcbi.1000428', '19593364', 'Computer generated trajectories can, in principle, reveal the folding pathways of a protein at atomic resolution and possibly suggest general and simple rules for predicting the folded structure of a given sequence. While such reversible folding trajectories can only be determined ab initio using all-atom transferable force-fields for a few small proteins, they can be determined for a large number of proteins using coarse-grained and structure-based force-fields, in which a known folded structure is by construction the absolute energy and free-energy minimum. Here we use a model of the fast folding helical lambda-repressor protein to generate trajectories in which native and non-native states are in equilibrium and transitions are accurately sampled. Yet, representation of the free-energy surface, which underlies the thermodynamic and dynamic properties of the protein model, from such a trajectory remains a challenge. Projections over one or a small number of arbitrarily chosen progress variables often hide the most important features of such surfaces. The results unequivocally show that an unprojected representation of the free-energy surface provides important and unbiased information and allows a simple and meaningful description of many-dimensional, heterogeneous trajectories, providing new insight into the possible mechanisms of fast-folding proteins.'),
(84268, 2009, 'plos', 'Dynamic modeling of vaccinating behavior as a function of individual beliefs', 'Coelho, Flávio Codeço|Codeço, Claudia T', 'Theoretical Epidemiology Group, Instituto Gulbenkian de Ciência, Oeiras, Portugal. fcoelho@igc.gulbenkian.pt|Theoretical Epidemiology Group, Instituto Gulbenkian de Ciência, Oeiras, Portugal. fcoelho@igc.gulbenkian.pt', 'Portugal|Portugal', 0, 'Bayes Theorem|Behavior|Culture|Decision Support Techniques|Humans|Mass Media|Models, Psychological|Vaccination|Yellow Fever|Yellow Fever Vaccine', 'Journal Article', '10.1371/journal.pcbi.1000425', '19593365', 'Individual perception of vaccine safety is an important factor in determining a persons adherence to a vaccination program and its consequences for disease control. This perception, or belief, about the safety of a given vaccine is not a static parameter but a variable subject to environmental influence. To complicate matters, perception of risk (or safety) does not correspond to actual risk. In this paper we propose a way to include the dynamics of such beliefs into a realistic epidemiological model, yielding a more complete depiction of the mechanisms underlying the unraveling of vaccination campaigns. The methodology proposed is based on Bayesian inference and can be extended to model more complex belief systems associated with decision models. We found the method is able to produce behaviors which approximate what has been observed in real vaccine and disease scare situations. The framework presented comprises a set of useful tools for an adequate quantitative representation of a common yet complex public-health issue. These tools include representation of beliefs as Bayesian probabilities, usage of logarithmic pooling to combine probability distributions representing opinions, and usage of natural conjugate priors to efficiently compute the Bayesian posterior. This approach allowed a comprehensive treatment of the uncertainty regarding vaccination behavior in a realistic epidemiological model.'),
(84269, 2009, 'plos', 'Bistable perception modeled as competing stochastic integrations at two levels', 'Gigante, Guido|Mattia, Maurizio|Braun, Jochen|Del Giudice, Paolo', 'Wolf Soluzioni, Rome, Italy. guido.gigante@iss.infn.it|Wolf Soluzioni, Rome, Italy. guido.gigante@iss.infn.it|Wolf Soluzioni, Rome, Italy. guido.gigante@iss.infn.it|Wolf Soluzioni, Rome, Italy. guido.gigante@iss.infn.it', 'Italy|Italy|Italy|Italy', 57, 'Algorithms|Models, Neurological|Perception|Photic Stimulation|Stochastic Processes|Time Factors|Vision, Binocular', 'Journal Article', '10.1371/journal.pcbi.1000430', '19593372', 'We propose a novel explanation for bistable perception, namely, the collective dynamics of multiple neural populations that are individually meta-stable. Distributed representations of sensory input and of perceptual state build gradually through noise-driven transitions in these populations, until the competition between alternative representations is resolved by a threshold mechanism. The perpetual repetition of this collective race to threshold renders perception bistable. This collective dynamics - which is largely uncoupled from the time-scales that govern individual populations or neurons - explains many hitherto puzzling observations about bistable perception: the wide range of mean alternation rates exhibited by bistable phenomena, the consistent variability of successive dominance periods, and the stabilizing effect of past perceptual states. It also predicts a number of previously unsuspected relationships between observable quantities characterizing bistable perception. We conclude that bistable perception reflects the collective nature of neural decision making rather than properties of individual populations or neurons.'),
(84270, 2009, 'plos', 'Integrating sequencing technologies in personal genomics: optimal low cost reconstruction of structural variants', 'Du, Jiang|Bjornson, Robert D|Zhang, Zhengdong D|Kong, Yong|Snyder, Michael|Gerstein, Mark B', 'Department of Computer Science, Yale University, New Haven, Connecticut, USA.|Department of Computer Science, Yale University, New Haven, Connecticut, USA.|Department of Computer Science, Yale University, New Haven, Connecticut, USA.|Department of Computer Science, Yale University, New Haven, Connecticut, USA.|Department of Computer Science, Yale University, New Haven, Connecticut, USA.|Department of Computer Science, Yale University, New Haven, Connecticut, USA.', 'United States|United States|United States|United States|United States|United States', 10, 'Chromosome Mapping|Computer Simulation|Databases, Genetic|Genomics|Models, Genetic|Models, Statistical|Oligonucleotide Array Sequence Analysis|Sequence Analysis, DNA|Software', 'Journal Article', '10.1371/journal.pcbi.1000432', '19593373', 'The goal of human genome re-sequencing is obtaining an accurate assembly of an individuals genome. Recently, there has been great excitement in the development of many technologies for this (e.g. medium and short read sequencing from companies such as 454 and SOLiD, and high-density oligo-arrays from Affymetrix and NimbelGen), with even more expected to appear. The costs and sensitivities of these technologies differ considerably from each other. As an important goal of personal genomics is to reduce the cost of re-sequencing to an affordable point, it is worthwhile to consider optimally integrating technologies. Here, we build a simulation toolbox that will help us optimally combine different technologies for genome re-sequencing, especially in reconstructing large structural variants (SVs). SV reconstruction is considered the most challenging step in human genome re-sequencing. (It is sometimes even harder than de novo assembly of small genomes because of the duplications and repetitive sequences in the human genome.) To this end, we formulate canonical problems that are representative of issues in reconstruction and are of small enough scale to be computationally tractable and simulatable. Using semi-realistic simulations, we show how we can combine different technologies to optimally solve the assembly at low cost. With mapability maps, our simulations efficiently handle the inhomogeneous repeat-containing structure of the human genome and the computational complexity of practical assembly algorithms. They quantitatively show how combining different read lengths is more cost-effective than using one length, how an optimal mixed sequencing strategy for reconstructing large novel SVs usually also gives accurate detection of SNPs/indels, how paired-end reads can improve reconstruction efficiency, and how adding in arrays is more efficient than just sequencing for disentangling some complex SVs. Our strategy should facilitate the sequencing of human genomes at maximum accuracy and low cost.'),
(84271, 2009, 'plos', 'Computational fragment-based binding site identification by ligand competitive saturation', 'Guvench, Olgun|MacKerell, Alexander D', 'Department of Pharmaceutical Sciences, School of Pharmacy, University of Maryland Baltimore, Baltimore, Maryland, USA.|Department of Pharmaceutical Sciences, School of Pharmacy, University of Maryland Baltimore, Baltimore, Maryland, USA.', 'United States|United States', 0, 'Binding Sites|Binding, Competitive|Carbon|Computational Biology|Computer Simulation|Crystallography, X-Ray|DNA-Binding Proteins|Drug Discovery|Hydrogen Bonding|Ligands|Models, Molecular|Peptide Fragments|Protein Binding|Protein Conformation|Proto-Oncogene Proteins c-bcl-6|Reproducibility of Results|Thermodynamics', 'Journal Article', '10.1371/journal.pcbi.1000435', '19593374', 'Fragment-based drug discovery using NMR and x-ray crystallographic methods has proven utility but also non-trivial time, materials, and labor costs. Current computational fragment-based approaches circumvent these issues but suffer from limited representations of protein flexibility and solvation effects, leading to difficulties with rigorous ranking of fragment affinities. To overcome these limitations we describe an explicit solvent all-atom molecular dynamics methodology (SILCS: Site Identification by Ligand Competitive Saturation) that uses small aliphatic and aromatic molecules plus water molecules to map the affinity pattern of a protein for hydrophobic groups, aromatic groups, hydrogen bond donors, and hydrogen bond acceptors. By simultaneously incorporating ligands representative of all these functionalities, the method is an in silico free energy-based competition assay that generates three-dimensional probability maps of fragment binding (FragMaps) indicating favorable fragment:protein interactions. Applied to the two-fold symmetric oncoprotein BCL-6, the SILCS method yields two-fold symmetric FragMaps that recapitulate the crystallographic binding modes of the SMRT and BCOR peptides. These FragMaps account both for important sequence and structure differences in the C-terminal halves of the two peptides and also the high mobility of the BCL-6 His116 sidechain in the peptide-binding groove. Such SILCS FragMaps can be used to qualitatively inform the design of small-molecule inhibitors or as scoring grids for high-throughput in silico docking that incorporate both an atomic-level description of solvation and protein flexibility.');
INSERT INTO `papers` (`id`, `ano`, `journal`, `titulo`, `autores`, `afiliacao`, `pais`, `citacoes`, `palavra_chave`, `categorias`, `doi`, `pubmed`, `abstract`) VALUES
(84272, 2009, 'plos', 'Relating neuronal firing patterns to functional differentiation of cerebral cortex', 'Shinomoto, Shigeru|Kim, Hideaki|Shimokawa, Takeaki|Matsuno, Nanae|Funahashi, Shintaro|Shima, Keisetsu|Fujita, Ichiro|Tamura, Hiroshi|Doi, Taijiro|Kawano, Kenji|Inaba, Naoko|Fukushima, Kikuro|Kurkin, Sergei|Kurata, Kiyoshi|Taira, Masato|Tsutsui, Ken-Ichiro|Komatsu, Hidehiko|Ogawa, Tadashi|Koida, Kowa|Tanji, Jun|Toyama, Keisuke', 'Graduate School of Science, Kyoto University, Sakyo-ku, Kyoto, Japan. shinomoto@scphys.kyoto-u.ac.jp|Graduate School of Science, Kyoto University, Sakyo-ku, Kyoto, Japan. shinomoto@scphys.kyoto-u.ac.jp|Graduate School of Science, Kyoto University, Sakyo-ku, Kyoto, Japan. shinomoto@scphys.kyoto-u.ac.jp|Graduate School of Science, Kyoto University, Sakyo-ku, Kyoto, Japan. shinomoto@scphys.kyoto-u.ac.jp|Graduate School of Science, Kyoto University, Sakyo-ku, Kyoto, Japan. shinomoto@scphys.kyoto-u.ac.jp|Graduate School of Science, Kyoto University, Sakyo-ku, Kyoto, Japan. shinomoto@scphys.kyoto-u.ac.jp|Graduate School of Science, Kyoto University, Sakyo-ku, Kyoto, Japan. shinomoto@scphys.kyoto-u.ac.jp|Graduate School of Science, Kyoto University, Sakyo-ku, Kyoto, Japan. shinomoto@scphys.kyoto-u.ac.jp|Graduate School of Science, Kyoto University, Sakyo-ku, Kyoto, Japan. shinomoto@scphys.kyoto-u.ac.jp|Graduate School of Science, Kyoto University, Sakyo-ku, Kyoto, Japan. shinomoto@scphys.kyoto-u.ac.jp|Graduate School of Science, Kyoto University, Sakyo-ku, Kyoto, Japan. shinomoto@scphys.kyoto-u.ac.jp|Graduate School of Science, Kyoto University, Sakyo-ku, Kyoto, Japan. shinomoto@scphys.kyoto-u.ac.jp|Graduate School of Science, Kyoto University, Sakyo-ku, Kyoto, Japan. shinomoto@scphys.kyoto-u.ac.jp|Graduate School of Science, Kyoto University, Sakyo-ku, Kyoto, Japan. shinomoto@scphys.kyoto-u.ac.jp|Graduate School of Science, Kyoto University, Sakyo-ku, Kyoto, Japan. shinomoto@scphys.kyoto-u.ac.jp|Graduate School of Science, Kyoto University, Sakyo-ku, Kyoto, Japan. shinomoto@scphys.kyoto-u.ac.jp|Graduate School of Science, Kyoto University, Sakyo-ku, Kyoto, Japan. shinomoto@scphys.kyoto-u.ac.jp|Graduate School of Science, Kyoto University, Sakyo-ku, Kyoto, Japan. shinomoto@scphys.kyoto-u.ac.jp|Graduate School of Science, Kyoto University, Sakyo-ku, Kyoto, Japan. shinomoto@scphys.kyoto-u.ac.jp|Graduate School of Science, Kyoto University, Sakyo-ku, Kyoto, Japan. shinomoto@scphys.kyoto-u.ac.jp|Graduate School of Science, Kyoto University, Sakyo-ku, Kyoto, Japan. shinomoto@scphys.kyoto-u.ac.jp', 'Japan|Japan|Japan|Japan|Japan|Japan|Japan|Japan|Japan|Japan|Japan|Japan|Japan|Japan|Japan|Japan|Japa', 124, 'Action Potentials|Animals|Brain Mapping|Cerebral Cortex|Cluster Analysis|Haplorhini|Models, Neurological|Neurons|Regression Analysis', 'Journal Article', '10.1371/journal.pcbi.1000433', '19593378', 'It has been empirically established that the cerebral cortical areas defined by Brodmann one hundred years ago solely on the basis of cellular organization are closely correlated to their function, such as sensation, association, and motion. Cytoarchitectonically distinct cortical areas have different densities and types of neurons. Thus, signaling patterns may also vary among cytoarchitectonically unique cortical areas. To examine how neuronal signaling patterns are related to innate cortical functions, we detected intrinsic features of cortical firing by devising a metric that efficiently isolates non-Poisson irregular characteristics, independent of spike rate fluctuations that are caused extrinsically by ever-changing behavioral conditions. Using the new metric, we analyzed spike trains from over 1,000 neurons in 15 cortical areas sampled by eight independent neurophysiological laboratories. Analysis of firing-pattern dissimilarities across cortical areas revealed a gradient of firing regularity that corresponded closely to the functional category of the cortical area, neuronal spiking patterns are regular in motor areas, random in the visual areas, and bursty in the prefrontal area. Thus, signaling patterns may play an important role in function-specific cerebral cortical computation.'),
(84273, 2009, 'plos', 'Movement timing and invariance arise from several geometries', 'Bennequin, Daniel|Fuchs, Ronit|Berthoz, Alain|Flash, Tamar', 'Equipe Géométrie et Dynamique, Institut de Mathématiques de Jussieu, UMR 7586, Paris, France.|Equipe Géométrie et Dynamique, Institut de Mathématiques de Jussieu, UMR 7586, Paris, France.|Equipe Géométrie et Dynamique, Institut de Mathématiques de Jussieu, UMR 7586, Paris, France.|Equipe Géométrie et Dynamique, Institut de Mathématiques de Jussieu, UMR 7586, Paris, France.', 'France|France|France|France', 51, 'Algorithms|Data Interpretation, Statistical|Hand|Handwriting|Humans|Models, Biological|Movement|Perception|Regression Analysis|Time Factors|Walking', 'Journal Article', '10.1371/journal.pcbi.1000426', '19593380', 'Human movements show several prominent features, movement duration is nearly independent of movement size (the isochrony principle), instantaneous speed depends on movement curvature (captured by the 2/3 power law), and complex movements are composed of simpler elements (movement compositionality). No existing theory can successfully account for all of these features, and the nature of the underlying motion primitives is still unknown. Also unknown is how the brain selects movement duration. Here we present a new theory of movement timing based on geometrical invariance. We propose that movement duration and compositionality arise from cooperation among Euclidian, equi-affine and full affine geometries. Each geometry posses a canonical measure of distance along curves, an invariant arc-length parameter. We suggest that for continuous movements, the actual movement duration reflects a particular tensorial mixture of these canonical parameters. Near geometrical singularities, specific combinations are selected to compensate for time expansion or compression in individual parameters. The theory was mathematically formulated using Cartans moving frame method. Its predictions were tested on three data sets: drawings of elliptical curves, locomotion and drawing trajectories of complex figural forms (cloverleaves, lemniscates and limaçons, with varying ratios between the sizes of the large versus the small loops). Our theory accounted well for the kinematic and temporal features of these movements, in most cases better than the constrained Minimum Jerk model, even when taking into account the number of estimated free parameters. During both drawing and locomotion equi-affine geometry was the most dominant geometry, with affine geometry second most important during drawing, Euclidian geometry was second most important during locomotion. We further discuss the implications of this theory: the origin of the dominance of equi-affine geometry, the possibility that the brain uses different mixtures of these geometries to encode movement duration and speed, and the ontogeny of such representations.'),
(84274, 2009, 'plos', 'The natural statistics of audiovisual speech', 'Chandrasekaran, Chandramouli|Trubanova, Andrea|Stillittano, Sébastien|Caplier, Alice|Ghazanfar, Asif A', 'Neuroscience Institute, Princeton University, Princeton, New Jersey, USA.|Neuroscience Institute, Princeton University, Princeton, New Jersey, USA.|Neuroscience Institute, Princeton University, Princeton, New Jersey, USA.|Neuroscience Institute, Princeton University, Princeton, New Jersey, USA.|Neuroscience Institute, Princeton University, Princeton, New Jersey, USA.', 'Jersey|Jersey|Jersey|Jersey|Jersey', 0, 'Databases, Factual|Fourier Analysis|Humans|Image Processing, Computer-Assisted|Models, Statistical|Mouth|Signal Processing, Computer-Assisted|Speech|Speech Perception|Time Factors|Visual Perception|Voice', 'Journal Article', '10.1371/journal.pcbi.1000436', '19609344', 'Humans, like other animals, are exposed to a continuous stream of signals, which are dynamic, multimodal, extended, and time varying in nature. This complex input space must be transduced and sampled by our sensory systems and transmitted to the brain where it can guide the selection of appropriate actions. To simplify this process, its been suggested that the brain exploits statistical regularities in the stimulus space. Tests of this idea have largely been confined to unimodal signals and natural scenes. One important class of multisensory signals for which a quantitative input space characterization is unavailable is human speech. We do not understand what signals our brain has to actively piece together from an audiovisual speech stream to arrive at a percept versus what is already embedded in the signal structure of the stream itself. In essence, we do not have a clear understanding of the natural statistics of audiovisual speech. In the present study, we identified the following major statistical features of audiovisual speech. First, we observed robust correlations and close temporal correspondence between the area of the mouth opening and the acoustic envelope. Second, we found the strongest correlation between the area of the mouth opening and vocal tract resonances. Third, we observed that both area of the mouth opening and the voice envelope are temporally modulated in the 2-7 Hz frequency range. Finally, we show that the timing of mouth movements relative to the onset of the voice is consistently between 100 and 300 ms. We interpret these data in the context of recent neural theories of speech which suggest that speech communication is a reciprocally coupled, multisensory event, whereby the outputs of the signaler are matched to the neural processes of the receiver.'),
(84275, 2009, 'plos', 'Computational analysis of viscoelastic properties of crosslinked actin networks', 'Kim, Taeyoon|Hwang, Wonmuk|Lee, Hyungsuk|Kamm, Roger D', 'Department of Mechanical Engineering, Massachusetts Institute of Technology, Cambridge, Massachusetts, USA.|Department of Mechanical Engineering, Massachusetts Institute of Technology, Cambridge, Massachusetts, USA.|Department of Mechanical Engineering, Massachusetts Institute of Technology, Cambridge, Massachusetts, USA.|Department of Mechanical Engineering, Massachusetts Institute of Technology, Cambridge, Massachusetts, USA.', 'United States|United States|United States|United States', 111, 'Actins|Biomechanical Phenomena|Cytoskeleton|Elasticity|Models, Chemical|Models, Molecular|Rheology|Stress, Mechanical|Thermodynamics|Viscosity', 'Journal Article', '10.1371/journal.pcbi.1000439', '19609348', 'Mechanical force plays an important role in the physiology of eukaryotic cells whose dominant structural constituent is the actin cytoskeleton composed mainly of actin and actin crosslinking proteins (ACPs). Thus, knowledge of rheological properties of actin networks is crucial for understanding the mechanics and processes of cells. We used Brownian dynamics simulations to study the viscoelasticity of crosslinked actin networks. Two methods were employed, bulk rheology and segment-tracking rheology, where the former measures the stress in response to an applied shear strain, and the latter analyzes thermal fluctuations of individual actin segments of the network. It was demonstrated that the storage shear modulus (G) increases more by the addition of ACPs that form orthogonal crosslinks than by those that form parallel bundles. In networks with orthogonal crosslinks, as crosslink density increases, the power law exponent of G as a function of the oscillation frequency decreases from 0.75, which reflects the transverse thermal motion of actin filaments, to near zero at low frequency. Under increasing prestrain, the network becomes more elastic, and three regimes of behavior are observed, each dominated by different mechanisms: bending of actin filaments, bending of ACPs, and at the highest prestrain tested (55%), stretching of actin filaments and ACPs. In the last case, only a small portion of actin filaments connected via highly stressed ACPs support the strain. We thus introduce the concept of a supportive framework, as a subset of the full network, which is responsible for high elasticity. Notably, entropic effects due to thermal fluctuations appear to be important only at relatively low prestrains and when the average crosslinking distance is comparable to or greater than the persistence length of the filament. Taken together, our results suggest that viscoelasticity of the actin network is attributable to different mechanisms depending on the amount of prestrain.'),
(84276, 2009, 'plos', 'A neural computational model of incentive salience', 'Zhang, Jun|Berridge, Kent C|Tindell, Amy J|Smith, Kyle S|Aldridge, J Wayne', 'Department of Psychology, University of Michigan, Ann Arbor, Michigan, USA.|Department of Psychology, University of Michigan, Ann Arbor, Michigan, USA.|Department of Psychology, University of Michigan, Ann Arbor, Michigan, USA.|Department of Psychology, University of Michigan, Ann Arbor, Michigan, USA.|Department of Psychology, University of Michigan, Ann Arbor, Michigan, USA.', 'United States|United States|United States|United States|United States', 122, 'Algorithms|Animals|Appetite|Behavior, Animal|Brain|Conditioning, Classical|Dopamine|Learning|Limbic System|Models, Neurological|Motivation|Rats|Reward', 'Journal Article', '10.1371/journal.pcbi.1000437', '19609350', 'Incentive salience is a motivational property with magnet-like qualities. When attributed to reward-predicting stimuli (cues), incentive salience triggers a pulse of wanting and an individual is pulled toward the cues and reward. A key computational question is how incentive salience is generated during a cue re-encounter, which combines both learning and the state of limbic brain mechanisms. Learning processes, such as temporal-difference models, provide one way for stimuli to acquire cached predictive values of rewards. However, empirical data show that subsequent incentive values are also modulated on the fly by dynamic fluctuation in physiological states, altering cached values in ways requiring additional motivation mechanisms. Dynamic modulation of incentive salience for a Pavlovian conditioned stimulus (CS or cue) occurs during certain states, without necessarily requiring (re)learning about the cue. In some cases, dynamic modulation of cue value occurs during states that are quite novel, never having been experienced before, and even prior to experience of the associated unconditioned reward in the new state. Such cases can include novel drug-induced mesolimbic activation and addictive incentive-sensitization, as well as natural appetite states such as salt appetite. Dynamic enhancement specifically raises the incentive salience of an appropriate CS, without necessarily changing that of other CSs. Here we suggest a new computational model that modulates incentive salience by integrating changing physiological states with prior learning. We support the model with behavioral and neurobiological data from empirical tests that demonstrate dynamic elevations in cue-triggered motivation (involving natural salt appetite, and drug-induced intoxication and sensitization). Our data call for a dynamic model of incentive salience, such as presented here. Computational models can adequately capture fluctuations in cue-triggered wanting only by incorporating modulation of previously learned values by natural appetite and addiction-related states.'),
(84277, 2009, 'plos', 'PoreWalker: a novel tool for the identification and characterization of channels in transmembrane proteins from their three-dimensional structure', 'Pellegrini-Calace, Marialuisa|Maiwald, Tim|Thornton, Janet M', 'EMBL/EBI, The Wellcome Trust Genome Campus, Cambridge, United Kingdom. marial@ebi.ac.uk|EMBL/EBI, The Wellcome Trust Genome Campus, Cambridge, United Kingdom. marial@ebi.ac.uk|EMBL/EBI, The Wellcome Trust Genome Campus, Cambridge, United Kingdom. marial@ebi.ac.uk', 'United Kingdom|United Kingdom|United Kingdom', 0, 'Algorithms|Ion Channels|Membrane Proteins|Models, Chemical|Models, Molecular|Protein Conformation|Software', 'Journal Article', '10.1371/journal.pcbi.1000440', '19609355', 'Transmembrane channel proteins play pivotal roles in maintaining the homeostasis and responsiveness of cells and the cross-membrane electrochemical gradient by mediating the transport of ions and molecules through biological membranes. Therefore, computational methods which, given a set of 3D coordinates, can automatically identify and describe channels in transmembrane proteins are key tools to provide insights into how they function.Herein we present PoreWalker, a fully automated method, which detects and fully characterises channels in transmembrane proteins from their 3D structures. A stepwise procedure is followed in which the pore centre and pore axis are first identified and optimised using geometric criteria, and then the biggest and longest cavity through the channel is detected. Finally, pore features, including diameter profiles, pore-lining residues, size, shape and regularity of the pore are calculated, providing a quantitative and visual characterization of the channel. To illustrate the use of this tool, the method was applied to several structures of transmembrane channel proteins and was able to identify shape/size/residue features representative of specific channel families. The software is available as a web-based resource at http://www.ebi.ac.uk/thornton-srv/software/PoreWalker/.'),
(84278, 2009, 'plos', 'Identification of a topological characteristic responsible for the biological robustness of regulatory networks', 'Wu, Yangle|Zhang, Xiaomeng|Yu, Jianglei|Ouyang, Qi', 'Center for Theoretical Biology, Academy for Advanced Interdisciplinary Studies, Peking University, Beijing, Peoples Republic of China.|Center for Theoretical Biology, Academy for Advanced Interdisciplinary Studies, Peking University, Beijing, Peoples Republic of China.|Center for Theoretical Biology, Academy for Advanced Interdisciplinary Studies, Peking University, Beijing, Peoples Republic of China.|Center for Theoretical Biology, Academy for Advanced Interdisciplinary Studies, Peking University, Beijing, Peoples Republic of China.', 'China|China|China|China', 30, 'Algorithms|Cell Cycle|Models, Biological|Saccharomycetales|Schizosaccharomyces|Signal Transduction|Systems Biology|Thermodynamics', 'Journal Article', '10.1371/journal.pcbi.1000442', '19629157', 'Attribution of biological robustness to the specific structural properties of a regulatory network is an important yet unsolved problem in systems biology. It is widely believed that the topological characteristics of a biological control network largely determine its dynamic behavior, yet the actual mechanism is still poorly understood. Here, we define a novel structural feature of biological networks, termed regulation entropy, to quantitatively assess the influence of network topology on the robustness of the systems. Using the cell-cycle control networks of the budding yeast (Saccharomyces cerevisiae) and the fission yeast (Schizosaccharomyces pombe) as examples, we first demonstrate the correlation of this quantity with the dynamic stability of biological control networks, and then we establish a significant association between this quantity and the structural stability of the networks. And we further substantiate the generality of this approach with a broad spectrum of biological and random networks. We conclude that the regulation entropy is an effective order parameter in evaluating the robustness of biological control networks. Our work suggests a novel connection between the topological feature and the dynamic property of biological regulatory networks.'),
(84279, 2009, 'plos', 'Harvesting candidate genes responsible for serious adverse drug reactions from a chemical-protein interactome', 'Yang, Lun|Chen, Jian|He, Lin', 'Bio-X Center, Key Laboratory for the Genetics of Developmental and Neuropsychiatric Disorders (Ministry of Education), Shanghai Jiao Tong University, Shanghai, China. lunyang@gmail.com|Bio-X Center, Key Laboratory for the Genetics of Developmental and Neuropsychiatric Disorders (Ministry of Education), Shanghai Jiao Tong University, Shanghai, China. lunyang@gmail.com|Bio-X Center, Key Laboratory for the Genetics of Developmental and Neuropsychiatric Disorders (Ministry of Education), Shanghai Jiao Tong University, Shanghai, China. lunyang@gmail.com', 'China|China|China', 87, 'Cluster Analysis|Computational Biology|Computer Simulation|Databases, Protein|Drug-Related Side Effects and Adverse Reactions|Humans|Models, Biological|Models, Molecular|Pharmaceutical Preparations|Protein Binding|Protein Interaction Domains and Motifs|Proteins|Reproducibility of Results|Software|User-Computer Interface', 'Journal Article', '10.1371/journal.pcbi.1000441', '19629158', 'Identifying genetic factors responsible for serious adverse drug reaction (SADR) is of critical importance to personalized medicine. However, genome-wide association studies are hampered due to the lack of case-control samples, and the selection of candidate genes is limited by the lack of understanding of the underlying mechanisms of SADRs. We hypothesize that drugs causing the same type of SADR might share a common mechanism by targeting unexpectedly the same SADR-mediating protein. Hence we propose an approach of identifying the common SADR-targets through constructing and mining an in silico chemical-protein interactome (CPI), a matrix of binding strengths among 162 drug molecules known to cause at least one type of SADR and 845 proteins. Drugs sharing the same SADR outcome were also found to possess similarities in their CPI profiles towards this 845 protein set. This methodology identified the candidate gene of sulfonamide-induced toxic epidermal necrolysis (TEN): all nine sulfonamides that cause TEN were found to bind strongly to MHC I (Cw*4), whereas none of the 17 control drugs that do not cause TEN were found to bind to it. Through an insight into the CPI, we found the Y116S substitution of MHC I (B*5703) enhances the unexpected binding of abacavir to its antigen presentation groove, which explains why B*5701, not B*5703, is the risk allele of abacavir-induced hypersensitivity. In conclusion, SADR targets and the patient-specific off-targets could be identified through a systematic investigation of the CPI, generating important hypotheses for prospective experimental validation of the candidate genes.'),
(84280, 2009, 'plos', 'Identification of a kinase profile that predicts chromosome damage induced by small molecule kinase inhibitors', 'Olaharski, Andrew J|Gonzaludo, Nina|Bitter, Hans|Goldstein, David|Kirchner, Stephan|Uppal, Hirdesh|Kolaja, Kyle', 'Non Clinical Safety, Roche Palo Alto LLC, Palo Alto, California, United States of America. andrew.olaharski@roche.com|Non Clinical Safety, Roche Palo Alto LLC, Palo Alto, California, United States of America. andrew.olaharski@roche.com|Non Clinical Safety, Roche Palo Alto LLC, Palo Alto, California, United States of America. andrew.olaharski@roche.com|Non Clinical Safety, Roche Palo Alto LLC, Palo Alto, California, United States of America. andrew.olaharski@roche.com|Non Clinical Safety, Roche Palo Alto LLC, Palo Alto, California, United States of America. andrew.olaharski@roche.com|Non Clinical Safety, Roche Palo Alto LLC, Palo Alto, California, United States of America. andrew.olaharski@roche.com|Non Clinical Safety, Roche Palo Alto LLC, Palo Alto, California, United States of America. andrew.olaharski@roche.com', 'United States|United States|United States|United States|United States|United States|United States', 42, 'Algorithms|Animals|Artificial Intelligence|Cell Line, Tumor|Chromosomes|Cluster Analysis|DNA Damage|Drug Discovery|Mice|Models, Biological|Molecular Weight|Principal Component Analysis|Protein Binding|Protein Kinase Inhibitors|ROC Curve|Reproducibility of Results|Statistics, Nonparametric', 'Journal Article', '10.1371/journal.pcbi.1000446', '19629159', 'Kinases are heavily pursued pharmaceutical targets because of their mechanistic role in many diseases. Small molecule kinase inhibitors (SMKIs) are a compound class that includes marketed drugs and compounds in various stages of drug development. While effective, many SMKIs have been associated with toxicity including chromosomal damage. Screening for kinase-mediated toxicity as early as possible is crucial, as is a better understanding of how off-target kinase inhibition may give rise to chromosomal damage. To that end, we employed a competitive binding assay and an analytical method to predict the toxicity of SMKIs. Specifically, we developed a model based on the binding affinity of SMKIs to a panel of kinases to predict whether a compound tests positive for chromosome damage. As training data, we used the binding affinity of 113 SMKIs against a representative subset of all kinases (290 kinases), yielding a 113x290 data matrix. Additionally, these 113 SMKIs were tested for genotoxicity in an in vitro micronucleus test (MNT). Among a variety of models from our analytical toolbox, we selected using cross-validation a combination of feature selection and pattern recognition techniques: Kolmogorov-Smirnov/T-test hybrid as a univariate filter, followed by Random Forests for feature selection and Support Vector Machines (SVM) for pattern recognition. Feature selection identified 21 kinases predictive of MNT. Using the corresponding binding affinities, the SVM could accurately predict MNT results with 85% accuracy (68% sensitivity, 91% specificity). This indicates that kinase inhibition profiles are predictive of SMKI genotoxicity. While in vitro testing is required for regulatory review, our analysis identified a fast and cost-efficient method for screening out compounds earlier in drug development. Equally important, by identifying a panel of kinases predictive of genotoxicity, we provide medicinal chemists a set of kinases to avoid when designing compounds, thereby providing a basis for rational drug design away from genotoxicity.'),
(84281, 2009, 'plos', 'Stem cell proliferation and quiescence--two sides of the same coin', 'Glauche, Ingmar|Moore, Kateri|Thielecke, Lars|Horn, Katrin|Loeffler, Markus|Roeder, Ingo', 'Institute for Medical Informatics, Statistics and Epidemiology, University of Leipzig, Leipzig, Germany. ingmar.glauche@imise.uni-leipzig.de|Institute for Medical Informatics, Statistics and Epidemiology, University of Leipzig, Leipzig, Germany. ingmar.glauche@imise.uni-leipzig.de|Institute for Medical Informatics, Statistics and Epidemiology, University of Leipzig, Leipzig, Germany. ingmar.glauche@imise.uni-leipzig.de|Institute for Medical Informatics, Statistics and Epidemiology, University of Leipzig, Leipzig, Germany. ingmar.glauche@imise.uni-leipzig.de|Institute for Medical Informatics, Statistics and Epidemiology, University of Leipzig, Leipzig, Germany. ingmar.glauche@imise.uni-leipzig.de|Institute for Medical Informatics, Statistics and Epidemiology, University of Leipzig, Leipzig, Germany. ingmar.glauche@imise.uni-leipzig.de', 'Germany|Germany|Germany|Germany|Germany|Germany', 67, 'Animals|Bromodeoxyuridine|Cell Communication|Cell Cycle|Cell Growth Processes|Computer Simulation|Hematopoietic Stem Cells|Humans|Least-Squares Analysis|Models, Biological|Resting Phase, Cell Cycle|Systems Biology', 'Journal Article', '10.1371/journal.pcbi.1000447', '19629161', 'The kinetics of label uptake and dilution in dividing stem cells, e.g., using Bromodeoxyuridine (BrdU) as a labeling substance, are a common way to assess the cellular turnover of all hematopoietic stem cells (HSCs) in vivo. The assumption that HSCs form a homogeneous population of cells which regularly undergo cell division has recently been challenged by new experimental results. For a consistent functional explanation of heterogeneity among HSCs, we propose a concept in which stem cells flexibly and reversibly adapt their cycling state according to systemic needs. Applying a mathematical model analysis, we demonstrate that different experimentally observed label dilution kinetics are consistently explained by the proposed model. The dynamically stabilized equilibrium between quiescent and activated cells leads to a biphasic label dilution kinetic in which an initial and pronounced decline of label retaining cells is attributed to faster turnover of activated cells, whereas a secondary, decelerated decline results from the slow turnover of quiescent cells. These results, which support our previous model prediction of a reversible activation/deactivation of HSCs, are also consistent with recent findings that use GFP-conjugated histones as a label instead of BrdU. Based on our findings we interpret HSC organization as an adaptive and regulated process in which the slow activation of quiescent cells and their possible return into quiescence after division are sufficient to explain the simultaneous occurrence of self-renewal and differentiation. Furthermore, we suggest an experimental strategy which is suited to demonstrate that the repopulation ability among the population of label retaining cells changes during the course of dilution.'),
(84282, 2009, 'plos', 'Power efficiency of outer hair cell somatic electromotility', 'Rabbitt, Richard D|Clifford, Sarah|Breneman, Kathryn D|Farrell, Brenda|Brownell, William E', 'Department of Bioengineering, University of Utah, Salt Lake City, Utah, United States of America.|Department of Bioengineering, University of Utah, Salt Lake City, Utah, United States of America.|Department of Bioengineering, University of Utah, Salt Lake City, Utah, United States of America.|Department of Bioengineering, University of Utah, Salt Lake City, Utah, United States of America.|Department of Bioengineering, University of Utah, Salt Lake City, Utah, United States of America.', 'United States|United States|United States|United States|United States', 38, 'Animals|Cell Membrane|Electric Capacitance|Electric Impedance|Electrophysiological Phenomena|Guinea Pigs|Hair Cells, Auditory, Outer|Mechanotransduction, Cellular|Models, Biological|Motion|Nonlinear Dynamics|Patch-Clamp Techniques|Systems Biology|Thermodynamics', 'Journal Article', '10.1371/journal.pcbi.1000444', '19629162', 'Cochlear outer hair cells (OHCs) are fast biological motors that serve to enhance the vibration of the organ of Corti and increase the sensitivity of the inner ear to sound. Exactly how OHCs produce useful mechanical power at auditory frequencies, given their intrinsic biophysical properties, has been a subject of considerable debate. To address this we formulated a mathematical model of the OHC based on first principles and analyzed the power conversion efficiency in the frequency domain. The model includes a mixture-composite constitutive model of the active lateral wall and spatially distributed electro-mechanical fields. The analysis predicts that: 1) the peak power efficiency is likely to be tuned to a specific frequency, dependent upon OHC length, and this tuning may contribute to the place principle and frequency selectivity in the cochlea, 2) the OHC power output can be detuned and attenuated by increasing the basal conductance of the cell, a parameter likely controlled by the brain via the efferent system, and 3) power output efficiency is limited by mechanical properties of the load, thus suggesting that impedance of the organ of Corti may be matched regionally to the OHC. The high power efficiency, tuning, and efferent control of outer hair cells are the direct result of biophysical properties of the cells, thus providing the physical basis for the remarkable sensitivity and selectivity of hearing.'),
(84283, 2009, 'plos', 'Cooperativity dominates the genomic organization of p53-response elements: a mechanistic view', 'Pan, Yongping|Nussinov, Ruth', 'Basic Research Program, SAIC-Frederick, Inc, Center for Cancer Research Nanobiology Program, NCI-Frederick, Frederick, Maryland, United States of America.|Basic Research Program, SAIC-Frederick, Inc, Center for Cancer Research Nanobiology Program, NCI-Frederick, Frederick, Maryland, United States of America.', 'United States|United States', 17, 'Computer Simulation|DNA|Humans|Models, Genetic|Models, Molecular|Protein Interaction Domains and Motifs|Protein Multimerization|Response Elements|Systems Biology|Thermodynamics|Tumor Suppressor Protein p53', 'Journal Article', '10.1371/journal.pcbi.1000448', '19629163', 'p53-response elements (p53-REs) are organized as two repeats of a palindromic DNA segment spaced by 0 to 20 base pairs (bp). Several experiments indicate that in the vast majority of the human p53-REs there are no spacers between the two repeats, those with spacers, particularly with sizes beyond two nucleotides, are rare. This raises the question of what it indicates about the factors determining the p53-RE genomic organization. Clearly, given the double helical DNA conformation, the orientation of two p53 core domain dimers with respect to each other will vary depending on the spacer size: a small spacer of 0 to 2 bps will lead to the closest p53 dimer-dimer orientation, a 10-bp spacer will locate the p53 dimers on the same DNA face but necessitate DNA looping, while a 5-bp spacer will position the p53 dimers on opposite DNA faces. Here, via conformational analysis we show that when there are 0-2 bp spacers, p53-DNA binding is cooperative, however, cooperativity is greatly diminished when there are spacers with sizes beyond 2 bp. Cooperative binding is broadly recognized to be crucial for biological processes, including transcriptional regulation. Our results clearly indicate that cooperativity of the p53-DNA association dominates the genomic organization of the p53-REs, raising questions of the structural organization and functional roles of p53-REs with larger spacers. We further propose that a dynamic landscape scenario of p53 and p53-REs can better explain the selectivity of the degenerate p53-REs. Our conclusions bear on the evolutionary preference of the p53-RE organization and as such, are expected to have broad implications to other multimeric transcription factor response element organization.'),
(84284, 2009, 'plos', 'Topography of extracellular matrix mediates vascular morphogenesis and migration speeds in angiogenesis', 'Bauer, Amy L|Jackson, Trachette L|Jiang, Yi', 'Theoretical Division, Los Alamos National Laboratory, Los Alamos, New Mexico, United States of America.|Theoretical Division, Los Alamos National Laboratory, Los Alamos, New Mexico, United States of America.|Theoretical Division, Los Alamos National Laboratory, Los Alamos, New Mexico, United States of America.', 'Mexico|Mexico|Mexico', 122, 'Animals|Cell Adhesion|Cell Movement|Computer Simulation|Corneal Neovascularization|Extracellular Matrix|Limbus Corneae|Models, Biological|Neoplasm Transplantation|Neovascularization, Physiologic|Rabbits|Reproducibility of Results|Signal Transduction|Systems Biology|Vascular Endothelial Growth Factor A', 'Journal Article', '10.1371/journal.pcbi.1000445', '19629173', 'The extracellular matrix plays a critical role in orchestrating the events necessary for wound healing, muscle repair, morphogenesis, new blood vessel growth, and cancer invasion. In this study, we investigate the influence of extracellular matrix topography on the coordination of multi-cellular interactions in the context of angiogenesis. To do this, we validate our spatio-temporal mathematical model of angiogenesis against empirical data, and within this framework, we vary the density of the matrix fibers to simulate different tissue environments and to explore the possibility of manipulating the extracellular matrix to achieve pro- and anti-angiogenic effects. The model predicts specific ranges of matrix fiber densities that maximize sprout extension speed, induce branching, or interrupt normal angiogenesis, which are independently confirmed by experiment. We then explore matrix fiber alignment as a key factor contributing to peak sprout velocities and in mediating cell shape and orientation. We also quantify the effects of proteolytic matrix degradation by the tip cell on sprout velocity and demonstrate that degradation promotes sprout growth at high matrix densities, but has an inhibitory effect at lower densities. Our results are discussed in the context of ECM targeted pro- and anti-angiogenic therapies that can be tested empirically.'),
(84285, 2009, 'plos', 'Small RNAs originated from pseudogenes: cis- or trans-acting?', 'Guo, Xingyi|Zhang, Zhaolei|Gerstein, Mark B|Zheng, Deyou', 'Institute for Brain Disorders and Neural Regeneration, Department of Neurology, Albert Einstein College of Medicine, New York, New York, United States of America.|Institute for Brain Disorders and Neural Regeneration, Department of Neurology, Albert Einstein College of Medicine, New York, New York, United States of America.|Institute for Brain Disorders and Neural Regeneration, Department of Neurology, Albert Einstein College of Medicine, New York, New York, United States of America.|Institute for Brain Disorders and Neural Regeneration, Department of Neurology, Albert Einstein College of Medicine, New York, New York, United States of America.', 'United States|United States|United States|United States', 50, 'Base Sequence|Data Interpretation, Statistical|Gene Expression|Genes, Plant|Genome, Plant|Genomics|Nucleic Acid Conformation|Oryza|Plant Proteins|Pseudogenes|RNA Replicase|RNA, Plant|RNA, Small Interfering|Repetitive Sequences, Nucleic Acid|Ribonuclease III|Sequence Alignment|Transcription Factors', 'Journal Article', '10.1371/journal.pcbi.1000449', '19649160', 'Pseudogenes are significant components of eukaryotic genomes, and some have acquired novel regulatory roles. To date, no study has characterized rice pseudogenes systematically or addressed their impact on the structure and function of the rice genome. In this genome-wide study, we have identified 11,956 non-transposon-related rice pseudogenes, most of which are from gene duplications. About 12% of the rice protein-coding genes, half of which are in singleton families, have a pseudogene paralog. Interestingly, we found that 145 of these pseudogenes potentially gave rise to antisense small RNAs after examining approximately 1.5 million small RNAs from developing rice grains. The majority (>50%) of these antisense RNAs are 24-nucleotides long, a feature often seen in plant repeat-associated small interfering RNAs (siRNAs) produced by RNA-dependent RNA polymerase (RDR2) and Dicer-like protein 3 (DCL3), suggesting that some pseudogene-derived siRNAs may be implicated in repressing pseudogene transcription (i.e., cis-acting). Multiple lines of evidence, however, indicate that small RNAs from rice pseudogenes might also function as natural antisense siRNAs either by interacting with the complementary sense RNAs from functional parental genes (38 cases) or by forming double-strand RNAs with transcripts of adjacent paralogous pseudogenes (2 cases) (i.e., trans-acting). Further examinations of five additional small RNA libraries revealed that pseudogene-derived antisense siRNAs could be produced in specific rice developmental stages or physiological growth conditions, suggesting their potentially important roles in normal rice development. In summary, our results show that pseudogenes derived from protein-coding genes are prevalent in the rice genome, and a subset of them are strong candidates for producing small RNAs with novel regulatory roles. Our findings suggest that pseudogenes of exapted functions may be a phenomenon ubiquitous in eukaryotic organisms.'),
(84286, 2009, 'plos', 'A quick guide to organizing computational biology projects', 'Noble, William Stafford', 'Department of Genome Sciences, School of Medicine, University of Washington, Seattle, Washington, United States of America. william-noble@u.washington.edu', 'United States', 34, 'Computational Biology|Database Management Systems|Information Storage and Retrieval|Research Design', 'Journal Article', '10.1371/journal.pcbi.1000424', '19649301', '-'),
(84287, 2009, 'plos', 'Building disease-specific drug-protein connectivity maps from molecular interaction networks and PubMed abstracts', 'Li, Jiao|Zhu, Xiaoyan|Chen, Jake Yue', 'State Key Laboratory of Intelligent Technology and Systems, Tsinghua National Laboratory for Information Science and Technology, Department of Computer Science and Technology, Tsinghua University, Beijing, China.|State Key Laboratory of Intelligent Technology and Systems, Tsinghua National Laboratory for Information Science and Technology, Department of Computer Science and Technology, Tsinghua University, Beijing, China.|State Key Laboratory of Intelligent Technology and Systems, Tsinghua National Laboratory for Information Science and Technology, Department of Computer Science and Technology, Tsinghua University, Beijing, China.', 'China|China|China', 128, 'Algorithms|Alzheimer Disease|Animals|Cluster Analysis|Databases, Protein|Drug Therapy|Genes|Genomics|Humans|Pharmaceutical Preparations|Pharmacology|Proteins|PubMed|ROC Curve|Reproducibility of Results|Sensitivity and Specificity|Systems Biology', 'Journal Article', '10.1371/journal.pcbi.1000450', '19649302', 'The recently proposed concept of molecular connectivity maps enables researchers to integrate experimental measurements of genes, proteins, metabolites, and drug compounds under similar biological conditions. The study of these maps provides opportunities for future toxicogenomics and drug discovery applications. We developed a computational framework to build disease-specific drug-protein connectivity maps. We integrated gene/protein and drug connectivity information based on protein interaction networks and literature mining, without requiring gene expression profile information derived from drug perturbation experiments on disease samples. We described the development and application of this computational framework using Alzheimers Disease (AD) as a primary example in three steps. First, molecular interaction networks were incorporated to reduce bias and improve relevance of AD seed proteins. Second, PubMed abstracts were used to retrieve enriched drug terms that are indirectly associated with AD through molecular mechanistic studies. Third and lastly, a comprehensive AD connectivity map was created by relating enriched drugs and related proteins in literature. We showed that this molecular connectivity map development approach outperformed both curated drug target databases and conventional information retrieval systems. Our initial explorations of the AD connectivity map yielded a new hypothesis that diltiazem and quinidine may be investigated as candidate drugs for AD treatment. Molecular connectivity maps derived computationally can help study molecular signature differences between different classes of drugs in specific disease contexts. To achieve overall good data coverage and quality, a series of statistical methods have been developed to overcome high levels of data noise in biological networks and literature mining results. Further development of computational molecular connectivity maps to cover major disease areas will likely set up a new model for drug development, in which therapeutic/toxicological profiles of candidate drugs can be checked computationally before costly clinical trials begin.'),
(84288, 2009, 'plos', 'Getting started in text mining: part two', 'Rzhetsky, Andrey|Seringhaus, Michael|Gerstein, Mark B', 'University of Chicago, Chicago, Illinois, United States of America.|University of Chicago, Chicago, Illinois, United States of America.|University of Chicago, Chicago, Illinois, United States of America.', 'United States|United States|United States', 22, 'Artificial Intelligence|Database Management Systems|Databases, Bibliographic|Information Storage and Retrieval', 'Journal Article', '10.1371/journal.pcbi.1000411', '19649304', '-'),
(84289, 2009, 'plos', 'A three species model to simulate application of Hyperbaric Oxygen Therapy to chronic wounds', 'Flegg, Jennifer A|McElwain, Donald L S|Byrne, Helen M|Turner, Ian W', 'School of Mathematical Sciences, Queensland University of Technology, Brisbane, Queensland, Australia.|School of Mathematical Sciences, Queensland University of Technology, Brisbane, Queensland, Australia.|School of Mathematical Sciences, Queensland University of Technology, Brisbane, Queensland, Australia.|School of Mathematical Sciences, Queensland University of Technology, Brisbane, Queensland, Australia.', 'Australia|Australia|Australia|Australia', 36, 'Algorithms|Chronic Disease|Computer Simulation|Diabetic Foot|Humans|Hyperbaric Oxygenation|Models, Biological|Neovascularization, Physiologic|Wound Healing|Wounds and Injuries', 'Journal Article', '10.1371/journal.pcbi.1000451', '19649306', 'Chronic wounds are a significant socioeconomic problem for governments worldwide. Approximately 15% of people who suffer from diabetes will experience a lower-limb ulcer at some stage of their lives, and 24% of these wounds will ultimately result in amputation of the lower limb. Hyperbaric Oxygen Therapy (HBOT) has been shown to aid the healing of chronic wounds, however, the causal reasons for the improved healing remain unclear and hence current HBOT protocols remain empirical. Here we develop a three-species mathematical model of wound healing that is used to simulate the application of hyperbaric oxygen therapy in the treatment of wounds. Based on our modelling, we predict that intermittent HBOT will assist chronic wound healing while normobaric oxygen is ineffective in treating such wounds. Furthermore, treatment should continue until healing is complete, and HBOT will not stimulate healing under all circumstances, leading us to conclude that finding the right protocol for an individual patient is crucial if HBOT is to be effective. We provide constraints that depend on the model parameters for the range of HBOT protocols that will stimulate healing. More specifically, we predict that patients with a poor arterial supply of oxygen, high consumption of oxygen by the wound tissue, chronically hypoxic wounds, and/or a dysfunctional endothelial cell response to oxygen are at risk of nonresponsiveness to HBOT. The work of this paper can, in some way, highlight which patients are most likely to respond well to HBOT (for example, those with a good arterial supply), and thus has the potential to assist in improving both the success rate and hence the cost-effectiveness of this therapy.'),
(84290, 2009, 'plos', 'Semantic similarity in biomedical ontologies', 'Pesquita, Catia|Faria, Daniel|Falcão, André O|Lord, Phillip|Couto, Francisco M', 'LaSIGE, Faculty of Sciences, University of Lisboa, Lisboa, Portugal. cpesquita@xldb.di.fc.ul.pt|LaSIGE, Faculty of Sciences, University of Lisboa, Lisboa, Portugal. cpesquita@xldb.di.fc.ul.pt|LaSIGE, Faculty of Sciences, University of Lisboa, Lisboa, Portugal. cpesquita@xldb.di.fc.ul.pt|LaSIGE, Faculty of Sciences, University of Lisboa, Lisboa, Portugal. cpesquita@xldb.di.fc.ul.pt|LaSIGE, Faculty of Sciences, University of Lisboa, Lisboa, Portugal. cpesquita@xldb.di.fc.ul.pt', 'Portugal|Portugal|Portugal|Portugal|Portugal', 496, 'Algorithms|Biomedical Research|Classification|Computational Biology|Natural Language Processing|Semantics|Software|Terminology as Topic', 'Journal Article', '10.1371/journal.pcbi.1000443', '19649320', 'In recent years, ontologies have become a mainstream topic in biomedical research. When biological entities are described using a common schema, such as an ontology, they can be compared by means of their annotations. This type of comparison is called semantic similarity, since it assesses the degree of relatedness between two entities by the similarity in meaning of their annotations. The application of semantic similarity to biomedical ontologies is recent, nevertheless, several studies have been published in the last few years describing and evaluating diverse approaches. Semantic similarity has become a valuable tool for validating the results drawn from biomedical studies such as gene clustering, gene expression data analysis, prediction and validation of molecular interactions, and disease gene prioritization. We review semantic similarity measures applied to biomedical ontologies and propose their classification according to the strategies they employ: node-based versus edge-based and pairwise versus groupwise. We also present comparative assessment studies and discuss the implications of their results. We survey the existing implementations of semantic similarity measures, and we describe examples of applications to biomedical research. This will clarify how biomedical researchers can benefit from semantic similarity measures and help them choose the approach most suitable for their studies.Biomedical ontologies are evolving toward increased coverage, formality, and integration, and their use for annotation is increasingly becoming a focus of both effort by biomedical experts and application of automated annotation procedures to create corpora of higher quality and completeness than are currently available. Given that semantic similarity measures are directly dependent on these evolutions, we can expect to see them gaining more relevance and even becoming as essential as sequence similarity is today in biomedical research.');
