INSERT INTO `papers` (`id`, `ano`, `journal`, `titulo`, `autores`, `afiliacao`, `pais`, `citacoes`, `palavra_chave`, `categorias`, `doi`, `pubmed`, `abstract`) VALUES
(83930, 2008, 'plos', 'How to record a million synaptic weights in a hippocampal slice', 'Bhalla, Upinder S', 'National Centre for Biological Sciences, Tata Institute of Fundamental Research, Bangalore, India. bhalla@ncbs.res.in', 'India', 5, 'Action Potentials|Animals|Brain Mapping|Computer Simulation|Hippocampus|Humans|Models, Neurological|Nerve Net|Neurons|Synapses|Synaptic Transmission', 'Journal Article', '10.1371/journal.pcbi.1000098', '18566658', 'A key step toward understanding the function of a brain circuit is to find its wiring diagram. New methods for optical stimulation and optical recording of neurons make it possible to map circuit connectivity on a very large scale. However, single synapses produce small responses that are difficult to measure on a large scale. Here I analyze how single synaptic responses may be detectable using relatively coarse readouts such as optical recording of somatic calcium. I model a network consisting of 10,000 input axons and 100 CA1 pyramidal neurons, each represented using 19 compartments with voltage-gated channels and calcium dynamics. As single synaptic inputs cannot produce a measurable somatic calcium response, I stimulate many inputs as a baseline to elicit somatic action potentials leading to a strong calcium signal. I compare statistics of responses with or without a single axonal input riding on this baseline. Through simulations I show that a single additional input shifts the distribution of the number of output action potentials. Stochastic resonance due to probabilistic synaptic release makes this shift easier to detect. With approximately 80 stimulus repetitions this approach can resolve up to 35% of individual activated synapses even in the presence of 20% recording noise. While the technique is applicable using conventional electrical stimulation and extracellular recording, optical methods promise much greater scaling, since the number of synapses scales as the product of the number of inputs and outputs. I extrapolate from current high-speed optical stimulation and recording methods, and show that this approach may scale up to the order of a million synapses in a single two-hour slice-recording experiment.'),
(83931, 2008, 'plos', 'Dynamics and potential impact of the immune response to chronic myelogenous leukemia', 'Kim, Peter S|Lee, Peter P|Levy, Doron', 'Laboratoire des Signaux et Systèmes, Ecole Supérieure dElectricité, Gif-sur-Yvette, France.|Laboratoire des Signaux et Systèmes, Ecole Supérieure dElectricité, Gif-sur-Yvette, France.|Laboratoire des Signaux et Systèmes, Ecole Supérieure dElectricité, Gif-sur-Yvette, France.', 'France|France|France', 70, 'Benzamides|Computer Simulation|Humans|Imatinib Mesylate|Immunity, Innate|Leukemia, Myelogenous, Chronic, BCR-ABL Positive|Models, Immunological|Piperazines|Pyrimidines|T-Lymphocytes', 'Journal Article', '10.1371/journal.pcbi.1000095', '18566683', 'Recent mathematical models have been developed to study the dynamics of chronic myelogenous leukemia (CML) under imatinib treatment. None of these models incorporates the anti-leukemia immune response. Recent experimental data show that imatinib treatment may promote the development of anti-leukemia immune responses as patients enter remission. Using these experimental data we develop a mathematical model to gain insights into the dynamics and potential impact of the resulting anti-leukemia immune response on CML. We model the immune response using a system of delay differential equations, where the delay term accounts for the duration of cell division. The mathematical model suggests that anti-leukemia T cell responses may play a critical role in maintaining CML patients in remission under imatinib therapy. Furthermore, it proposes a novel concept of an optimal load zone for leukemic cells in which the anti-leukemia immune response is most effective. Imatinib therapy may drive leukemic cell populations to enter and fall below this optimal load zone too rapidly to sustain the anti-leukemia T cell response. As a potential therapeutic strategy, the model shows that vaccination approaches in combination with imatinib therapy may optimally sustain the anti-leukemia T cell response to potentially eradicate residual leukemic cells for a durable cure of CML. The approach presented in this paper accounts for the role of the anti-leukemia specific immune response in the dynamics of CML. By combining experimental data and mathematical models, we demonstrate that persistence of anti-leukemia T cells even at low levels seems to prevent the leukemia from relapsing (for at least 50 months). As a consequence, we hypothesize that anti-leukemia T cell responses may help maintain remission under imatinib therapy. The mathematical model together with the new experimental data imply that there may be a feasible, low-risk, clinical approach to enhancing the effects of imatinib treatment.'),
(83932, 2008, 'plos', 'Ten simple rules for organizing a scientific meeting', 'Corpas, Manuel|Gehlenborg, Nils|Janga, Sarath Chandra|Bourne, Philip E', 'European Bioinformatics Institute, Wellcome Trust Genome Campus, Hinxton, Cambridge, United Kingdom.|European Bioinformatics Institute, Wellcome Trust Genome Campus, Hinxton, Cambridge, United Kingdom.|European Bioinformatics Institute, Wellcome Trust Genome Campus, Hinxton, Cambridge, United Kingdom.|European Bioinformatics Institute, Wellcome Trust Genome Campus, Hinxton, Cambridge, United Kingdom.', 'United Kingdom|United Kingdom|United Kingdom|United Kingdom', 11, 'Congresses as Topic|Group Processes|Science|Societies, Scientific', 'Journal Article', '10.1371/journal.pcbi.1000080', '18584020', '-'),
(83933, 2008, 'plos', 'Regulation of signal duration and the statistical dynamics of kinase activation by scaffold proteins', 'Locasale, Jason W|Chakraborty, Arup K', 'Department of Biological Engineering, Massachusetts Institute of Technology, Cambridge, Massachusetts, USA.|Department of Biological Engineering, Massachusetts Institute of Technology, Cambridge, Massachusetts, USA.', 'United States|United States', 15, 'Computer Simulation|Cytoskeletal Proteins|Enzyme Activation|Extracellular Matrix Proteins|Gene Expression Regulation, Enzymologic|MAP Kinase Signaling System|Models, Biological|Models, Statistical|Phosphotransferases', 'Journal Article', '10.1371/journal.pcbi.1000099', '18584022', 'Scaffolding proteins that direct the assembly of multiple kinases into a spatially localized signaling complex are often essential for the maintenance of an appropriate biological response. Although scaffolds are widely believed to have dramatic effects on the dynamics of signal propagation, the mechanisms that underlie these consequences are not well understood. Here, Monte Carlo simulations of a model kinase cascade are used to investigate how the temporal characteristics of signaling cascades can be influenced by the presence of scaffold proteins. Specifically, we examine the effects of spatially localizing kinase components on a scaffold on signaling dynamics. The simulations indicate that a major effect that scaffolds exert on the dynamics of cell signaling is to control how the activation of protein kinases is distributed over time. Scaffolds can influence the timing of kinase activation by allowing for kinases to become activated over a broad range of times, thus allowing for signaling at both early and late times. Scaffold concentrations that result in optimal signal amplitude also result in the broadest distributions of times over which kinases are activated. These calculations provide insights into one mechanism that describes how the duration of a signal can potentially be regulated in a scaffold mediated protein kinase cascade. Our results illustrate another complexity in the broad array of control properties that emerge from the physical effects of spatially localizing components of kinase cascades on scaffold proteins.'),
(83934, 2008, 'plos', 'ISMB 2008 Toronto', 'Linial, Michal|Mesirov, Jill P|Morrison McKay, B J|Rost, Burkhard', 'International Society for Computational Biology, University of California San Diego, La Jolla, California, USA.|International Society for Computational Biology, University of California San Diego, La Jolla, California, USA.|International Society for Computational Biology, University of California San Diego, La Jolla, California, USA.|International Society for Computational Biology, University of California San Diego, La Jolla, California, USA.', 'United States|United States|United States|United States', 0, 'International Agencies|Molecular Biology|Systems Biology', 'Journal Article', '10.1371/journal.pcbi.1000094', '18584023', '-'),
(83935, 2008, 'plos', 'How to advance open international scientific exchange', 'Bryant, Barbara', 'Millennium Pharmaceuticals, Cambridge, Massachusetts, USA. barb.bryant@gmail.com', 'United States', 1, 'Information Dissemination|International Cooperation|Science', 'Journal Article', '10.1371/journal.pcbi.1000097', '18584025', '-'),
(83936, 2008, 'plos', 'Network analysis of intrinsic functional brain connectivity in Alzheimers disease', 'Supekar, Kaustubh|Menon, Vinod|Rubin, Daniel|Musen, Mark|Greicius, Michael D', 'Graduate Program in Biomedical Informatics, Stanford University School of Medicine, Stanford, California, USA.|Graduate Program in Biomedical Informatics, Stanford University School of Medicine, Stanford, California, USA.|Graduate Program in Biomedical Informatics, Stanford University School of Medicine, Stanford, California, USA.|Graduate Program in Biomedical Informatics, Stanford University School of Medicine, Stanford, California, USA.|Graduate Program in Biomedical Informatics, Stanford University School of Medicine, Stanford, California, USA.', 'United States|United States|United States|United States|United States', 758, 'Adult|Aged|Alzheimer Disease|Brain|Brain Mapping|Computer Simulation|Female|Humans|Magnetic Resonance Imaging|Male|Middle Aged|Models, Neurological|Nerve Net|Neural Pathways', 'Journal Article', '10.1371/journal.pcbi.1000100', '18584043', 'Functional brain networks detected in task-free (resting-state) functional magnetic resonance imaging (fMRI) have a small-world architecture that reflects a robust functional organization of the brain. Here, we examined whether this functional organization is disrupted in Alzheimers disease (AD). Task-free fMRI data from 21 AD subjects and 18 age-matched controls were obtained. Wavelet analysis was applied to the fMRI data to compute frequency-dependent correlation matrices. Correlation matrices were thresholded to create 90-node undirected-graphs of functional brain networks. Small-world metrics (characteristic path length and clustering coefficient) were computed using graph analytical methods. In the low frequency interval 0.01 to 0.05 Hz, functional brain networks in controls showed small-world organization of brain activity, characterized by a high clustering coefficient and a low characteristic path length. In contrast, functional brain networks in AD showed loss of small-world properties, characterized by a significantly lower clustering coefficient (p<0.01), indicative of disrupted local connectivity. Clustering coefficients for the left and right hippocampus were significantly lower (p<0.01) in the AD group compared to the control group. Furthermore, the clustering coefficient distinguished AD participants from the controls with a sensitivity of 72% and specificity of 78%. Our study provides new evidence that there is disrupted organization of functional brain networks in AD. Small-world metrics can characterize the functional organization of the brain in AD, and our findings further suggest that these network measures may be useful as an imaging-based biomarker to distinguish AD from healthy aging.'),
(83937, 2008, 'plos', 'Local function conservation in sequence and structure space', 'Weinhold, Nils|Sander, Oliver|Domingues, Francisco S|Lengauer, Thomas|Sommer, Ingolf', 'Max Planck Institute for Informatics, Saarbrücken, Germany.|Max Planck Institute for Informatics, Saarbrücken, Germany.|Max Planck Institute for Informatics, Saarbrücken, Germany.|Max Planck Institute for Informatics, Saarbrücken, Germany.|Max Planck Institute for Informatics, Saarbrücken, Germany.', 'Germany|Germany|Germany|Germany|Germany', 10, 'Amino Acid Sequence|Artificial Intelligence|Computational Biology|Data Interpretation, Statistical|Databases, Protein|Evolution, Molecular|Models, Molecular|Pattern Recognition, Automated|Protein Conformation|Proteins|Sequence Alignment|Sequence Analysis, Protein|Structural Homology, Protein|Structure-Activity Relationship', 'Journal Article', '10.1371/journal.pcbi.1000105', '18604264', 'We assess the variability of protein function in protein sequence and structure space. Various regions in this space exhibit considerable difference in the local conservation of molecular function. We analyze and capture local function conservation by means of logistic curves. Based on this analysis, we propose a method for predicting molecular function of a query protein with known structure but unknown function. The prediction method is rigorously assessed and compared with a previously published function predictor. Furthermore, we apply the method to 500 functionally unannotated PDB structures and discuss selected examples. The proposed approach provides a simple yet consistent statistical model for the complex relations between protein sequence, structure, and function. The GOdot method is available online (http://godot.bioinf.mpi-inf.mpg.de).'),
(83938, 2008, 'plos', 'Increased brain signal variability accompanies lower behavioral variability in development', 'McIntosh, Anthony Randal|Kovacevic, Natasa|Itier, Roxane J', 'Rotman Research Institute of Baycrest Centre, University of Toronto, Toronto, Ontario, Canada. rmcintosh@rotman-baycrest.on.ca|Rotman Research Institute of Baycrest Centre, University of Toronto, Toronto, Ontario, Canada. rmcintosh@rotman-baycrest.on.ca|Rotman Research Institute of Baycrest Centre, University of Toronto, Toronto, Ontario, Canada. rmcintosh@rotman-baycrest.on.ca', 'Canada|Canada|Canada', 226, 'Adolescent|Adult|Behavior|Brain|Brain Mapping|Child|Electroencephalography|Evoked Potentials, Visual|Human Development|Humans|Nerve Net|Reaction Time|Recognition (Psychology)', 'Journal Article', '10.1371/journal.pcbi.1000106', '18604265', 'As the brain matures, its responses become optimized. Behavioral measures show this through improved accuracy and decreased trial-to-trial variability. The question remains whether the supporting brain dynamics show a similar decrease in variability. We examined the relation between variability in single trial evoked electrical activity of the brain (measured with EEG) and performance of a face memory task in children (8-15 y) and young adults (20-33 y). Behaviorally, children showed slower, more variable response times (RT), and less accurate recognition than adults. However, brain signal variability increased with age, and showed strong negative correlations with intrasubject RT variability and positive correlations with accuracy. Thus, maturation appears to lead to a brain with greater functional variability, which is indicative of enhanced neural complexity. This variability may reflect a broader repertoire of metastable brain states and more fluid transitions among them that enable optimum responses. Our results suggest that the moment-to-moment variability in brain activity may be a critical index of the cognitive capacity of the brain.'),
(83939, 2008, 'plos', 'Quantitative predictions of peptide binding to any HLA-DR molecule of known sequence: NetMHCIIpan', 'Nielsen, Morten|Lundegaard, Claus|Blicher, Thomas|Peters, Bjoern|Sette, Alessandro|Justesen, Sune|Buus, Søren|Lund, Ole', 'Center for Biological Sequence Analysis, Department of Systems Biology, Technical University of Denmark, Lyngby, Denmark. mniel@cbs.dtu.dk|Center for Biological Sequence Analysis, Department of Systems Biology, Technical University of Denmark, Lyngby, Denmark. mniel@cbs.dtu.dk|Center for Biological Sequence Analysis, Department of Systems Biology, Technical University of Denmark, Lyngby, Denmark. mniel@cbs.dtu.dk|Center for Biological Sequence Analysis, Department of Systems Biology, Technical University of Denmark, Lyngby, Denmark. mniel@cbs.dtu.dk|Center for Biological Sequence Analysis, Department of Systems Biology, Technical University of Denmark, Lyngby, Denmark. mniel@cbs.dtu.dk|Center for Biological Sequence Analysis, Department of Systems Biology, Technical University of Denmark, Lyngby, Denmark. mniel@cbs.dtu.dk|Center for Biological Sequence Analysis, Department of Systems Biology, Technical University of Denmark, Lyngby, Denmark. mniel@cbs.dtu.dk|Center for Biological Sequence Analysis, Department of Systems Biology, Technical University of Denmark, Lyngby, Denmark. mniel@cbs.dtu.dk', 'Denmark|Denmark|Denmark|Denmark|Denmark|Denmark|Denmark|Denmark', 176, 'Algorithms|Alleles|Amino Acid Sequence|Binding Sites|Databases, Protein|HLA-DR Antigens|Humans|Major Histocompatibility Complex|Molecular Sequence Data|Predictive Value of Tests|Protein Binding|Protein Interaction Mapping|Reproducibility of Results|Sequence Alignment|Sequence Analysis, Protein', 'Journal Article', '10.1371/journal.pcbi.1000107', '18604266', 'CD4 positive T helper cells control many aspects of specific immunity. These cells are specific for peptides derived from protein antigens and presented by molecules of the extremely polymorphic major histocompatibility complex (MHC) class II system. The identification of peptides that bind to MHC class II molecules is therefore of pivotal importance for rational discovery of immune epitopes. HLA-DR is a prominent example of a human MHC class II. Here, we present a method, NetMHCIIpan, that allows for pan-specific predictions of peptide binding to any HLA-DR molecule of known sequence. The method is derived from a large compilation of quantitative HLA-DR binding events covering 14 of the more than 500 known HLA-DR alleles. Taking both peptide and HLA sequence information into account, the method can generalize and predict peptide binding also for HLA-DR molecules where experimental data is absent. Validation of the method includes identification of endogenously derived HLA class II ligands, cross-validation, leave-one-molecule-out, and binding motif identification for hitherto uncharacterized HLA-DR molecules. The validation shows that the method can successfully predict binding for HLA-DR molecules-even in the absence of specific data for the particular molecule in question. Moreover, when compared to TEPITOPE, currently the only other publicly available prediction method aiming at providing broad HLA-DR allelic coverage, NetMHCIIpan performs equivalently for alleles included in the training of TEPITOPE while outperforming TEPITOPE on novel alleles. We propose that the method can be used to identify those hitherto uncharacterized alleles, which should be addressed experimentally in future updates of the method to cover the polymorphism of HLA-DR most efficiently. We thus conclude that the presented method meets the challenge of keeping up with the MHC polymorphism discovery rate and that it can be used to sample the MHC space, enabling a highly efficient iterative process for improving MHC class II binding predictions.'),
(83940, 2008, 'plos', 'Kinetic modeling of the assembly, dynamic steady state, and contraction of the FtsZ ring in prokaryotic cytokinesis', 'Surovtsev, Ivan V|Morgan, Jeffrey J|Lindahl, Paul A', 'Departments of Chemistry and Biochemistry and Biophysics, Texas A&M University, College Station, Texas, United States of America.|Departments of Chemistry and Biochemistry and Biophysics, Texas A&M University, College Station, Texas, United States of America.|Departments of Chemistry and Biochemistry and Biophysics, Texas A&M University, College Station, Texas, United States of America.', 'United States|United States|United States', 34, 'Bacterial Proteins|Computer Simulation|Cytokinesis|Cytoskeletal Proteins|Dimerization|Energy Transfer|GTP-Binding Proteins|Kinetics|Models, Chemical|Protein Binding|Systems Biology|Thermodynamics', 'Journal Article', '10.1371/journal.pcbi.1000102', '18604268', 'Cytokinesis in prokaryotes involves the assembly of a polymeric ring composed of FtsZ protein monomeric units. The Z ring forms at the division plane and is attached to the membrane. After assembly, it maintains a stable yet dynamic steady state. Once induced, the ring contracts and the membrane constricts. In this work, we present a computational deterministic biochemical model exhibiting this behavior. The model is based on biochemical features of FtsZ known from in vitro studies, and it quantitatively reproduces relevant in vitro data. An essential part of the model is a consideration of interfacial reactions involving the cytosol volume, where monomeric FtsZ is dispersed, and the membrane surface in the cells mid-zone where the ring is assembled. This approach allows the same chemical model to simulate either in vitro or in vivo conditions by adjusting only two geometrical parameters. The model includes minimal reactions, components, and assumptions, yet is able to reproduce sought-after in vivo behavior, including the rapid assembly of the ring via FtsZ-polymerization, the formation of a dynamic steady state in which GTP hydrolysis leads to the exchange of monomeric subunits between cytoplasm and the ring, and finally the induced contraction of the ring. The model gives a quantitative estimate for coupling between the rate of GTP hydrolysis and of FtsZ subunit turnover between the assembled ring and the cytoplasmic pool as observed. Membrane constriction is chemically driven by the strong tendency of GTP-bound FtsZ to self-assembly. The model suggests a possible mechanism of membrane contraction without a motor protein. The portion of the free energy of GTP hydrolysis released in cyclization is indirectly used in this energetically unfavorable process. The model provides a limit to the mechanistic complexity required to mimic ring behavior, and it highlights the importance of parallel in vitro and in vivo modeling.'),
(83941, 2008, 'plos', 'Unraveling protein networks with power graph analysis', 'Royer, Loïc|Reimann, Matthias|Andreopoulos, Bill|Schroeder, Michael', 'Biotechnology Center, Technische Universität Dresden, Dresden, Germany.|Biotechnology Center, Technische Universität Dresden, Dresden, Germany.|Biotechnology Center, Technische Universität Dresden, Dresden, Germany.|Biotechnology Center, Technische Universität Dresden, Dresden, Germany.', 'Germany|Germany|Germany|Germany', 93, 'Amino Acid Motifs|Animals|Binding Sites|Casein Kinase II|Catalytic Domain|Cluster Analysis|Computational Biology|Computer Simulation|Data Compression|Evolution, Molecular|Humans|Models, Biological|Neural Networks (Computer)|Protein Binding|Protein Interaction Mapping|Protein Tyrosine Phosphatase, Non-Receptor Type 22|Proteins|Sequence Analysis, Protein|Structural Homology, Protein|Transcription Factors|src Homology Domains', 'Journal Article', '10.1371/journal.pcbi.1000108', '18617988', 'Networks play a crucial role in computational biology, yet their analysis and representation is still an open problem. Power Graph Analysis is a lossless transformation of biological networks into a compact, less redundant representation, exploiting the abundance of cliques and bicliques as elementary topological motifs. We demonstrate with five examples the advantages of Power Graph Analysis. Investigating protein-protein interaction networks, we show how the catalytic subunits of the casein kinase II complex are distinguishable from the regulatory subunits, how interaction profiles and sequence phylogeny of SH3 domains correlate, and how false positive interactions among high-throughput interactions are spotted. Additionally, we demonstrate the generality of Power Graph Analysis by applying it to two other types of networks. We show how power graphs induce a clustering of both transcription factors and target genes in bipartite transcription networks, and how the erosion of a phosphatase domain in type 22 non-receptor tyrosine phosphatases is detected. We apply Power Graph Analysis to high-throughput protein interaction networks and show that up to 85% (56% on average) of the information is redundant. Experimental networks are more compressible than rewired ones of same degree distribution, indicating that experimental networks are rich in cliques and bicliques. Power Graphs are a novel representation of networks, which reduces network complexity by explicitly representing re-occurring network motifs. Power Graphs compress up to 85% of the edges in protein interaction networks and are applicable to all types of networks such as protein interactions, regulatory networks, or homology networks.'),
(83942, 2008, 'plos', 'Evolution of evolvability in gene regulatory networks', 'Crombach, Anton|Hogeweg, Paulien', 'Theoretical Biology and Bioinformatics Group, Utrecht University, The Netherlands. a.b.m.crombach@uu.nl|Theoretical Biology and Bioinformatics Group, Utrecht University, The Netherlands. a.b.m.crombach@uu.nl', 'Netherlands|Netherlands', 131, 'Adaptation, Biological|Computer Simulation|Evolution, Molecular|Gene Expression Regulation|Gene Regulatory Networks|Genotype|Models, Genetic|Mutation|Neural Networks (Computer)|Phenotype', 'Journal Article', '10.1371/journal.pcbi.1000112', '18617989', 'Gene regulatory networks are perhaps the most important organizational level in the cell where signals from the cell state and the outside environment are integrated in terms of activation and inhibition of genes. For the last decade, the study of such networks has been fueled by large-scale experiments and renewed attention from the theoretical field. Different models have been proposed to, for instance, investigate expression dynamics, explain the network topology we observe in bacteria and yeast, and for the analysis of evolvability and robustness of such networks. Yet how these gene regulatory networks evolve and become evolvable remains an open question. An individual-oriented evolutionary model is used to shed light on this matter. Each individual has a genome from which its gene regulatory network is derived. Mutations, such as gene duplications and deletions, alter the genome, while the resulting network determines the gene expression pattern and hence fitness. With this protocol we let a population of individuals evolve under Darwinian selection in an environment that changes through time. Our work demonstrates that long-term evolution of complex gene regulatory networks in a changing environment can lead to a striking increase in the efficiency of generating beneficial mutations. We show that the population evolves towards genotype-phenotype mappings that allow for an orchestrated network-wide change in the gene expression pattern, requiring only a few specific gene indels. The genes involved are hubs of the networks, or directly influencing the hubs. Moreover, throughout the evolutionary trajectory the networks maintain their mutational robustness. In other words, evolution in an alternating environment leads to a network that is sensitive to a small class of beneficial mutations, while the majority of mutations remain neutral: an example of evolution of evolvability.'),
(83943, 2008, 'plos', 'Active nuclear receptors exhibit highly correlated AF-2 domain motions', 'Teotico, Denise G|Frazier, Monica L|Ding, Feng|Dokholyan, Nikolay V|Temple, Brenda R S|Redinbo, Matthew R', 'Department of Chemistry, University of North Carolina at Chapel Hill, Chapel Hill, North Carolina, USA.|Department of Chemistry, University of North Carolina at Chapel Hill, Chapel Hill, North Carolina, USA.|Department of Chemistry, University of North Carolina at Chapel Hill, Chapel Hill, North Carolina, USA.|Department of Chemistry, University of North Carolina at Chapel Hill, Chapel Hill, North Carolina, USA.|Department of Chemistry, University of North Carolina at Chapel Hill, Chapel Hill, North Carolina, USA.|Department of Chemistry, University of North Carolina at Chapel Hill, Chapel Hill, North Carolina, USA.', 'United States|United States|United States|United States|United States|United States', 0, 'Amino Acid Sequence|Binding Sites|Conserved Sequence|Dimerization|Energy Transfer|Humans|Models, Molecular|Motion|Nuclear Proteins|Pregnane X Receptor|Protein Binding|Protein Interaction Domains and Motifs|Receptors, Cytoplasmic and Nuclear|Receptors, Steroid|Retinoid X Receptors', 'Journal Article', '10.1371/journal.pcbi.1000111', '18617990', 'Nuclear receptor ligand binding domains (LBDs) convert ligand binding events into changes in gene expression by recruiting transcriptional coregulators to a conserved activation function-2 (AF-2) surface. While most nuclear receptor LBDs form homo- or heterodimers, the human nuclear receptor pregnane X receptor (PXR) forms a unique and essential homodimer and is proposed to assemble into a functional heterotetramer with the retinoid X receptor (RXR). How the homodimer interface, which is located 30 A from the AF-2, would affect function at this critical surface has remained unclear. By using 20- to 30-ns molecular dynamics simulations on PXR in various oligomerization states, we observed a remarkably high degree of correlated motion in the PXR-RXR heterotetramer, most notably in the four helices that create the AF-2 domain. The function of such correlation may be to create active-capable receptor complexes that are ready to bind to transcriptional coactivators. Indeed, we found in additional simulations that active-capable receptor complexes involving other orphan or steroid nuclear receptors also exhibit highly correlated AF-2 domain motions. We further propose a mechanism for the transmission of long-range motions through the nuclear receptor LBD to the AF-2 surface. Taken together, our findings indicate that long-range motions within the LBD scaffold are critical to nuclear receptor function by promoting a mobile AF-2 state ready to bind coactivators.'),
(83944, 2008, 'plos', 'The generation of promoter-mediated transcriptional noise in bacteria', 'Mitarai, Namiko|Dodd, Ian B|Crooks, Michael T|Sneppen, Kim', 'Department of Physics, Kyushu University, Fukuoka, Japan.|Department of Physics, Kyushu University, Fukuoka, Japan.|Department of Physics, Kyushu University, Fukuoka, Japan.|Department of Physics, Kyushu University, Fukuoka, Japan.', 'Japan|Japan|Japan|Japan', 37, 'DNA, Superhelical|DNA-Directed RNA Polymerases|Escherichia coli|Gene Expression Regulation, Bacterial|Kinetics|Models, Genetic|Promoter Regions, Genetic|Transcription Factors|Transcription, Genetic', 'Journal Article', '10.1371/journal.pcbi.1000109', '18617999', 'Noise in the expression of a gene produces fluctuations in the concentration of the gene product. These fluctuations can interfere with optimal function or can be exploited to generate beneficial diversity between cells, gene expression noise is therefore expected to be subject to evolutionary pressure. Shifts between modes of high and low rates of transcription initiation at a promoter appear to contribute to this noise both in eukaryotes and prokaryotes. However, models invoked for eukaryotic promoter noise such as stable activation scaffolds or persistent nucleosome alterations seem unlikely to apply to prokaryotic promoters. We consider the relative importance of the steps required for transcription initiation. The 3-step transcription initiation model of McClure is extended into a mathematical model that can be used to predict consequences of additional promoter properties. We show in principle that the transcriptional bursting observed at an E. coli promoter by Golding et al. (2005) can be explained by stimulation of initiation by the negative supercoiling behind a transcribing RNA polymerase (RNAP) or by the formation of moribund or dead-end RNAP-promoter complexes. Both mechanisms are tunable by the alteration of promoter kinetics and therefore allow the optimization of promoter mediated noise.'),
(83945, 2008, 'plos', 'Dynamics of immune escape during HIV/SIV infection', 'Althaus, Christian L|De Boer, Rob J', 'Theoretical Biology, Utrecht University, The Netherlands. c.l.althaus@uu.nl|Theoretical Biology, Utrecht University, The Netherlands. c.l.althaus@uu.nl', 'Netherlands|Netherlands', 0, 'Animals|Antigens, Viral|Cytotoxicity, Immunologic|Epitopes, T-Lymphocyte|HIV|HIV Antigens|HIV Infections|Humans|Immunodominant Epitopes|Kinetics|Models, Immunological|Mutation|Simian Acquired Immunodeficiency Syndrome|Simian Immunodeficiency Virus|Virus Replication', 'Journal Article', '10.1371/journal.pcbi.1000103', '18636096', 'Several studies have shown that cytotoxic T lymphocytes (CTLs) play an important role in controlling HIV/SIV infection. Notably, the observation of escape mutants suggests a selective pressure induced by the CTL response. However, it remains difficult to assess the definite role of the cellular immune response. We devise a computational model of HIV/SIV infection having a broad cellular immune response targeting different viral epitopes. The CTL clones are stimulated by viral antigen and interact with the virus population through cytotoxic killing of infected cells. Consequently, the virus population reacts through the acquisition of CTL escape mutations. Our model provides realistic virus dynamics and describes several experimental observations. We postulate that inter-clonal competition and immunodominance may be critical factors determining the sequential emergence of escapes. We show that even though the total killing induced by the CTL response can be high, escape rates against a single CTL clone are often slow and difficult to estimate from infrequent sequence measurements. Finally, our simulations show that a higher degree of immunodominance leads to more frequent escape with a reduced control of viral replication but a substantially impaired replicative capacity of the virus. This result suggests two strategies for vaccine design: Vaccines inducing a broad CTL response should decrease the viral load, whereas vaccines stimulating a narrow but dominant CTL response are likely to induce escape but may dramatically reduce the replicative capacity of the virus.'),
(83946, 2008, 'plos', 'The ascent of the abundant: how mutational networks constrain evolution', 'Cowperthwaite, Matthew C|Economo, Evan P|Harcombe, William R|Miller, Eric L|Meyers, Lauren Ancel', 'Institute for Cellular and Molecular Biology, University of Texas at Austin, Austin, Texas, USA. mattccowp@mac.com|Institute for Cellular and Molecular Biology, University of Texas at Austin, Austin, Texas, USA. mattccowp@mac.com|Institute for Cellular and Molecular Biology, University of Texas at Austin, Austin, Texas, USA. mattccowp@mac.com|Institute for Cellular and Molecular Biology, University of Texas at Austin, Austin, Texas, USA. mattccowp@mac.com|Institute for Cellular and Molecular Biology, University of Texas at Austin, Austin, Texas, USA. mattccowp@mac.com', 'United States|United States|United States|United States|United States', 59, 'Computer Simulation|Epistasis, Genetic|Evolution, Molecular|Genotype|Models, Genetic|Mutation|Nucleic Acid Conformation|Phenotype|RNA|Selection, Genetic', 'Journal Article', '10.1371/journal.pcbi.1000110', '18636097', 'Evolution by natural selection is fundamentally shaped by the fitness landscapes in which it occurs. Yet fitness landscapes are vast and complex, and thus we know relatively little about the long-range constraints they impose on evolutionary dynamics. Here, we exhaustively survey the structural landscapes of RNA molecules of lengths 12 to 18 nucleotides, and develop a network model to describe the relationship between sequence and structure. We find that phenotype abundance--the number of genotypes producing a particular phenotype--varies in a predictable manner and critically influences evolutionary dynamics. A study of naturally occurring functional RNA molecules using a new structural statistic suggests that these molecules are biased toward abundant phenotypes. This supports an ascent of the abundant hypothesis, in which evolution yields abundant phenotypes even when they are not the most fit.'),
(83947, 2008, 'plos', 'Emergent synchronous bursting of oxytocin neuronal network', 'Rossoni, Enrico|Feng, Jianfeng|Tirozzi, Brunello|Brown, David|Leng, Gareth|Moos, Françoise', 'Department of Computer Science, University of Warwick, Coventry, United Kingdom.|Department of Computer Science, University of Warwick, Coventry, United Kingdom.|Department of Computer Science, University of Warwick, Coventry, United Kingdom.|Department of Computer Science, University of Warwick, Coventry, United Kingdom.|Department of Computer Science, University of Warwick, Coventry, United Kingdom.|Department of Computer Science, University of Warwick, Coventry, United Kingdom.', 'United Kingdom|United Kingdom|United Kingdom|United Kingdom|United Kingdom|United Kingdom', 0, 'Animals|Dendrites|Feedback|Female|Humans|Membrane Potentials|Milk Ejection|Models, Neurological|Nerve Net|Neural Pathways|Neurons, Efferent|Oxytocin|Paracrine Communication|Pituitary Gland|Reflex|Synaptic Transmission|Systems Biology', 'Journal Article', '10.1371/journal.pcbi.1000123', '18636098', 'When young suckle, they are rewarded intermittently with a let-down of milk that results from reflex secretion of the hormone oxytocin, without oxytocin, newly born young will die unless they are fostered. Oxytocin is made by magnocellular hypothalamic neurons, and is secreted from their nerve endings in the pituitary in response to action potentials (spikes) that are generated in the cell bodies and which are propagated down their axons to the nerve endings. Normally, oxytocin cells discharge asynchronously at 1-3 spikes/s, but during suckling, every 5 min or so, each discharges a brief, intense burst of spikes that release a pulse of oxytocin into the circulation. This reflex was the first, and is perhaps the best, example of a physiological role for peptide-mediated communication within the brain: it is coordinated by the release of oxytocin from the dendrites of oxytocin cells, it can be facilitated by injection of tiny amounts of oxytocin into the hypothalamus, and it can be blocked by injection of tiny amounts of oxytocin antagonist. Here we show how synchronized bursting can arise in a neuronal network model that incorporates basic observations of the physiology of oxytocin cells. In our model, bursting is an emergent behaviour of a complex system, involving both positive and negative feedbacks, between many sparsely connected cells. The oxytocin cells are regulated by independent afferent inputs, but they interact by local release of oxytocin and endocannabinoids. Oxytocin released from the dendrites of these cells has a positive-feedback effect, while endocannabinoids have an inhibitory effect by suppressing the afferent input to the cells.'),
(83948, 2008, 'plos', 'Memory switches in chemical reaction space', 'Ramakrishnan, Naren|Bhalla, Upinder S', 'Department of Computer Science, Virginia Tech, Blacksburg, Virginia, USA.|Department of Computer Science, Virginia Tech, Blacksburg, Virginia, USA.', 'United States|United States', 0, 'Biochemistry|Computational Biology|Energy Transfer|Feedback, Physiological|Kinetics|Models, Chemical|Signal Transduction|Systems Biology', 'Journal Article', '10.1371/journal.pcbi.1000122', '18636099', 'Just as complex electronic circuits are built from simple Boolean gates, diverse biological functions, including signal transduction, differentiation, and stress response, frequently use biochemical switches as a functional module. A relatively small number of such switches have been described in the literature, and these exhibit considerable diversity in chemical topology. We asked if biochemical switches are indeed rare and if there are common chemical motifs and family relationships among such switches. We performed a systematic exploration of chemical reaction space by generating all possible stoichiometrically valid chemical configurations up to 3 molecules and 6 reactions and up to 4 molecules and 3 reactions. We used Monte Carlo sampling of parameter space for each such configuration to generate specific models and checked each model for switching properties. We found nearly 4,500 reaction topologies, or about 10% of our tested configurations, that demonstrate switching behavior. Commonly accepted topological features such as feedback were poor predictors of bistability, and we identified new reaction motifs that were likely to be found in switches. Furthermore, the discovered switches were related in that most of the larger configurations were derived from smaller ones by addition of one or more reactions. To explore even larger configurations, we developed two tools: the bistabilizer, which converts almost-bistable systems into bistable ones, and frequent motif mining, which helps rank untested configurations. Both of these tools increased the coverage of our library of bistable systems. Thus, our systematic exploration of chemical reaction space has produced a valuable resource for investigating the key signaling motif of bistability.'),
(83949, 2008, 'plos', 'Intrinsic gain modulation and adaptive neural coding', 'Hong, Sungho|Lundstrom, Brian Nils|Fairhall, Adrienne L', 'Physiology and Biophysics Department, University of Washington, Seattle, Washington, USA. shhong@oist.jp|Physiology and Biophysics Department, University of Washington, Seattle, Washington, USA. shhong@oist.jp|Physiology and Biophysics Department, University of Washington, Seattle, Washington, USA. shhong@oist.jp', 'United States|United States|United States', 0, 'Action Potentials|Adaptation, Physiological|Animals|Humans|Linear Models|Models, Neurological|Neural Networks (Computer)|Neuronal Plasticity|Neurons|Nonlinear Dynamics|Synaptic Transmission|Time Factors', 'Journal Article', '10.1371/journal.pcbi.1000119', '18636100', 'In many cases, the computation of a neural system can be reduced to a receptive field, or a set of linear filters, and a thresholding function, or gain curve, which determines the firing probability, this is known as a linear/nonlinear model. In some forms of sensory adaptation, these linear filters and gain curve adjust very rapidly to changes in the variance of a randomly varying driving input. An apparently similar but previously unrelated issue is the observation of gain control by background noise in cortical neurons: the slope of the firing rate versus current (f-I) curve changes with the variance of background random input. Here, we show a direct correspondence between these two observations by relating variance-dependent changes in the gain of f-I curves to characteristics of the changing empirical linear/nonlinear model obtained by sampling. In the case that the underlying system is fixed, we derive relationships relating the change of the gain with respect to both mean and variance with the receptive fields derived from reverse correlation on a white noise stimulus. Using two conductance-based model neurons that display distinct gain modulation properties through a simple change in parameters, we show that coding properties of both these models quantitatively satisfy the predicted relationships. Our results describe how both variance-dependent gain modulation and adaptive neural computation result from intrinsic nonlinearity.'),
(83950, 2008, 'plos', 'Computational biology resources lack persistence and usability', 'Veretnik, Stella|Fink, J Lynn|Bourne, Philip E', 'San Diego Supercomputer Center, University of California San Diego, La Jolla, California, USA.|San Diego Supercomputer Center, University of California San Diego, La Jolla, California, USA.|San Diego Supercomputer Center, University of California San Diego, La Jolla, California, USA.', 'United States|United States|United States', 19, 'Computational Biology|Diffusion of Innovation|Humans|Information Dissemination|Internet|Software', 'Journal Article', '10.1371/journal.pcbi.1000136', '18636105', '-'),
(83951, 2008, 'plos', 'Similarity queries for temporal toxicogenomic expression profiles', 'Smith, Adam A|Vollrath, Aaron|Bradfield, Christopher A|Craven, Mark', 'Department of Computer Science, University of Wisconsin, Madison, Wisconsin, USA. aasmith@cs.wisc.edu|Department of Computer Science, University of Wisconsin, Madison, Wisconsin, USA. aasmith@cs.wisc.edu|Department of Computer Science, University of Wisconsin, Madison, Wisconsin, USA. aasmith@cs.wisc.edu|Department of Computer Science, University of Wisconsin, Madison, Wisconsin, USA. aasmith@cs.wisc.edu', 'United States|United States|United States|United States', 11, 'Animals|Databases, Genetic|Drug-Related Side Effects and Adverse Reactions|Gene Expression Profiling|Liver|Mice|Pattern Recognition, Automated|Sequence Alignment|Time Factors|Toxicogenetics', 'Journal Article', '10.1371/journal.pcbi.1000116', '18636114', 'We present an approach for answering similarity queries about gene expression time series that is motivated by the task of characterizing the potential toxicity of various chemicals. Our approach involves two key aspects. First, our method employs a novel alignment algorithm based on time warping. Our time warping algorithm has several advantages over previous approaches. It allows the user to impose fairly strong biases on the form that the alignments can take, and it permits a type of local alignment in which the entirety of only one series has to be aligned. Second, our method employs a relaxed spline interpolation to predict expression responses for unmeasured time points, such that the spline does not necessarily exactly fit every observed point. We evaluate our approach using expression time series from the Edge toxicology database. Our experiments show the value of using spline representations for sparse time series. More significantly, they show that our time warping method provides more accurate alignments and classifications than previous standard alignment methods for time series.'),
(83952, 2008, 'plos', 'Decoding of superimposed traces produced by direct sequencing of heterozygous indels', 'Dmitriev, Dmitry A|Rakitov, Roman A', 'Illinois Natural History Survey, Champaign, Illinois, USA. dmitriev@inhs.uiuc.edu|Illinois Natural History Survey, Champaign, Illinois, USA. dmitriev@inhs.uiuc.edu', 'United States|United States', 87, 'Computational Biology|Heterozygote|Humans|INDEL Mutation|Molecular Sequence Data|Sequence Alignment|Sequence Analysis, DNA|Sequence Homology, Nucleic Acid|Software', 'Journal Article', '10.1371/journal.pcbi.1000113', '18654614', 'Direct Sanger sequencing of a diploid template containing a heterozygous insertion or deletion results in a difficult-to-interpret mixed trace formed by two allelic traces superimposed onto each other. Existing computational methods for deconvolution of such traces require knowledge of a reference sequence or the availability of both direct and reverse mixed sequences of the same template. We describe a simple yet accurate method, which uses dynamic programming optimization to predict superimposed allelic sequences solely from a string of letters representing peaks within an individual mixed trace. We used the method to decode 104 human traces (mean length 294 bp) containing heterozygous indels 5 to 30 bp with a mean of 99.1% bases per allelic sequence reconstructed correctly and unambiguously. Simulations with artificial sequences have demonstrated that the method yields accurate reconstructions when (1) the allelic sequences forming the mixed trace are sufficiently similar, (2) the analyzed fragment is significantly longer than the indel, and (3) multiple indels, if present, are well-spaced. Because these conditions occur in most encountered DNA sequences, the method is widely applicable. It is available as a free Web application Indelligent at http://ctap.inhs.uiuc.edu/dmitriev/indel.asp.');
INSERT INTO `papers` (`id`, `ano`, `journal`, `titulo`, `autores`, `afiliacao`, `pais`, `citacoes`, `palavra_chave`, `categorias`, `doi`, `pubmed`, `abstract`) VALUES
(83953, 2008, 'plos', 'Predicting and validating protein interactions using network structure', 'Chen, Pao-Yang|Deane, Charlotte M|Reinert, Gesine', 'Department of Statistics, University of Oxford, Oxford, United Kingdom. pchen@stats.ox.ac.uk|Department of Statistics, University of Oxford, Oxford, United Kingdom. pchen@stats.ox.ac.uk|Department of Statistics, University of Oxford, Oxford, United Kingdom. pchen@stats.ox.ac.uk', 'United Kingdom|United Kingdom|United Kingdom', 0, 'Amino Acid Sequence|Animals|Computational Biology|Databases, Protein|Humans|Neural Networks (Computer)|Predictive Value of Tests|Protein Interaction Mapping|Proteins|Structural Homology, Protein|Structure-Activity Relationship|Systems Integration', 'Journal Article', '10.1371/journal.pcbi.1000118', '18654616', 'Protein interactions play a vital part in the function of a cell. As experimental techniques for detection and validation of protein interactions are time consuming, there is a need for computational methods for this task. Protein interactions appear to form a network with a relatively high degree of local clustering. In this paper we exploit this clustering by suggesting a score based on triplets of observed protein interactions. The score utilises both protein characteristics and network properties. Our score based on triplets is shown to complement existing techniques for predicting protein interactions, outperforming them on data sets which display a high degree of clustering. The predicted interactions score highly against test measures for accuracy. Compared to a similar score derived from pairwise interactions only, the triplet score displays higher sensitivity and specificity. By looking at specific examples, we show how an experimental set of interactions can be enriched and validated. As part of this work we also examine the effect of different prior databases upon the accuracy of prediction and find that the interactions from the same kingdom give better results than from across kingdoms, suggesting that there may be fundamental differences between the networks. These results all emphasize that network structure is important and helps in the accurate prediction of protein interactions. The protein interaction data set and the program used in our analysis, and a list of predictions and validations, are available at http://www.stats.ox.ac.uk/bioinfo/resources/PredictingInteractions.'),
(83954, 2008, 'plos', 'Isolation-by-distance and outbreeding depression are sufficient to drive parapatric speciation in the absence of environmental influences', 'Hoelzer, Guy A|Drewes, Rich|Meier, Jeffrey|Doursat, René', 'Department of Biology, University of Nevada, Reno, Nevada, USA. hoelzer@unr.edu|Department of Biology, University of Nevada, Reno, Nevada, USA. hoelzer@unr.edu|Department of Biology, University of Nevada, Reno, Nevada, USA. hoelzer@unr.edu|Department of Biology, University of Nevada, Reno, Nevada, USA. hoelzer@unr.edu', 'United States|United States|United States|United States', 39, 'Animals|Ecosystem|Genetic Speciation|Genetic Variation|Genetics, Population|Geography|Humans|Models, Genetic|Phylogeny|Population Dynamics|Reproduction|Selection, Genetic', 'Journal Article', '10.1371/journal.pcbi.1000126', '18654617', 'A commonly held view in evolutionary biology is that speciation (the emergence of genetically distinct and reproductively incompatible subpopulations) is driven by external environmental constraints, such as localized barriers to dispersal or habitat-based variation in selection pressures. We have developed a spatially explicit model of a biological population to study the emergence of spatial and temporal patterns of genetic diversity in the absence of predetermined subpopulation boundaries. We propose a 2-D cellular automata model showing that an initially homogeneous population might spontaneously subdivide into reproductively incompatible species through sheer isolation-by-distance when the viability of offspring decreases as the genomes of parental gametes become increasingly different. This simple implementation of the Dobzhansky-Muller model provides the basis for assessing the process and completion of speciation, which is deemed to occur when there is complete postzygotic isolation between two subpopulations. The model shows an inherent tendency toward spatial self-organization, as has been the case with other spatially explicit models of evolution. A well-mixed version of the model exhibits a relatively stable and unimodal distribution of genetic differences as has been shown with previous models. A much more interesting pattern of temporal waves, however, emerges when the dispersal of individuals is limited to short distances. Each wave represents a subset of comparisons between members of emergent subpopulations diverging from one another, and a subset of these divergences proceeds to the point of speciation. The long-term persistence of diverging subpopulations is the essence of speciation in biological populations, so the rhythmic diversity waves that we have observed suggest an inherent disposition for a population experiencing isolation-by-distance to generate new species.'),
(83955, 2008, 'plos', 'Optimal compensation for temporal uncertainty in movement planning', 'Hudson, Todd E|Maloney, Laurence T|Landy, Michael S', 'Department of Psychology and Center for Neural Science, New York University, New York, New York, USA. hudson@cns.nyu.edu|Department of Psychology and Center for Neural Science, New York University, New York, New York, USA. hudson@cns.nyu.edu|Department of Psychology and Center for Neural Science, New York University, New York, New York, USA. hudson@cns.nyu.edu', 'United States|United States|United States', 59, 'Arm|Biomechanical Phenomena|Feedback, Psychological|Hand|Humans|Models, Biological|Motor Activity|Movement|Orientation|Proprioception|Psychomotor Performance|Reaction Time|Reference Values|Reward|Time Factors', 'Journal Article', '10.1371/journal.pcbi.1000130', '18654619', 'Motor control requires the generation of a precise temporal sequence of control signals sent to the skeletal musculature. We describe an experiment that, for good performance, requires human subjects to plan movements taking into account uncertainty in their movement duration and the increase in that uncertainty with increasing movement duration. We do this by rewarding movements performed within a specified time window, and penalizing slower movements in some conditions and faster movements in others. Our results indicate that subjects compensated for their natural duration-dependent temporal uncertainty as well as an overall increase in temporal uncertainty that was imposed experimentally. Their compensation for temporal uncertainty, both the natural duration-dependent and imposed overall components, was nearly optimal in the sense of maximizing expected gain in the task. The motor system is able to model its temporal uncertainty and compensate for that uncertainty so as to optimize the consequences of movement.'),
(83956, 2008, 'plos', 'Outlook on Thailands genomics and computational biology research and development', 'Tongsima, Wannipha|Tongsima, Sissades|Palittapongarnpim, Prasit', 'National Science and Technology Development Agency (NSTDA), Pathumtani, Thailand.|National Science and Technology Development Agency (NSTDA), Pathumtani, Thailand.|National Science and Technology Development Agency (NSTDA), Pathumtani, Thailand.', 'Thailand|Thailand|Thailand', 0, 'Animals|Computational Biology|Databases, Genetic|Drug Design|Genomics|Humans|Proteomics|Research|Systems Biology|Thailand', 'Journal Article', '10.1371/journal.pcbi.1000115', '18654621', '-'),
(83957, 2008, 'plos', 'Prediction by graph theoretic measures of structural effects in proteins arising from non-synonymous single nucleotide polymorphisms', 'Cheng, Tammy M K|Lu, Yu-En|Vendruscolo, Michele|Lio, Pietro|Blundell, Tom L', 'Department of Biochemistry, University of Cambridge, Cambridge, United Kingdom. tammy@cryst.bioc.cam.ac.uk|Department of Biochemistry, University of Cambridge, Cambridge, United Kingdom. tammy@cryst.bioc.cam.ac.uk|Department of Biochemistry, University of Cambridge, Cambridge, United Kingdom. tammy@cryst.bioc.cam.ac.uk|Department of Biochemistry, University of Cambridge, Cambridge, United Kingdom. tammy@cryst.bioc.cam.ac.uk|Department of Biochemistry, University of Cambridge, Cambridge, United Kingdom. tammy@cryst.bioc.cam.ac.uk', 'United Kingdom|United Kingdom|United Kingdom|United Kingdom|United Kingdom', 39, 'Artificial Intelligence|Computational Biology|DNA Mutational Analysis|Genetic Predisposition to Disease|Humans|Models, Genetic|Models, Molecular|Neural Networks (Computer)|Polymorphism, Single Nucleotide|Predictive Value of Tests|Protein Conformation|Protein Interaction Mapping|Proteins|Sequence Alignment|Sequence Analysis, Protein|Thermodynamics', 'Journal Article', '10.1371/journal.pcbi.1000135', '18654622', 'Recent analyses of human genome sequences have given rise to impressive advances in identifying non-synonymous single nucleotide polymorphisms (nsSNPs). By contrast, the annotation of nsSNPs and their links to diseases are progressing at a much slower pace. Many of the current approaches to analysing disease-associated nsSNPs use primarily sequence and evolutionary information, while structural information is relatively less exploited. In order to explore the potential of such information, we developed a structure-based approach, Bongo (Bonds ON Graph), to predict structural effects of nsSNPs. Bongo considers protein structures as residue-residue interaction networks and applies graph theoretical measures to identify the residues that are critical for maintaining structural stability by assessing the consequences on the interaction network of single point mutations. Our results show that Bongo is able to identify mutations that cause both local and global structural effects, with a remarkably low false positive rate. Application of the Bongo method to the prediction of 506 disease-associated nsSNPs resulted in a performance (positive predictive value, PPV, 78.5%) similar to that of PolyPhen (PPV, 77.2%) and PANTHER (PPV, 72.2%). As the Bongo method is solely structure-based, our results indicate that the structural changes resulting from nsSNPs are closely associated to their pathological consequences.'),
(83958, 2008, 'plos', 'Nonnegative matrix factorization: an analytical and interpretive tool in computational biology', 'Devarajan, Karthik', 'Division of Population Science, Fox Chase Cancer Center, Philadelphia, Pennsylvania, USA. karthik.devarajan@fccc.edu', 'United States', 208, 'Artificial Intelligence|Computational Biology|Gene Expression Profiling|Oligonucleotide Array Sequence Analysis|Pattern Recognition, Automated|Systems Integration', 'Journal Article', '10.1371/journal.pcbi.1000029', '18654623', 'In the last decade, advances in high-throughput technologies such as DNA microarrays have made it possible to simultaneously measure the expression levels of tens of thousands of genes and proteins. This has resulted in large amounts of biological data requiring analysis and interpretation. Nonnegative matrix factorization (NMF) was introduced as an unsupervised, parts-based learning paradigm involving the decomposition of a nonnegative matrix V into two nonnegative matrices, W and H, via a multiplicative updates algorithm. In the context of a pxn gene expression matrix V consisting of observations on p genes from n samples, each column of W defines a metagene, and each column of H represents the metagene expression pattern of the corresponding sample. NMF has been primarily applied in an unsupervised setting in image and natural language processing. More recently, it has been successfully utilized in a variety of applications in computational biology. Examples include molecular pattern discovery, class comparison and prediction, cross-platform and cross-species analysis, functional characterization of genes and biomedical informatics. In this paper, we review this method as a data analytical and interpretive tool in computational biology with an emphasis on these applications.'),
(83959, 2008, 'plos', 'Innate visual learning through spontaneous activity patterns', 'Albert, Mark V|Schnabel, Adam|Field, David J', 'Field of Computational Biology, Cornell University, Ithaca, New York, United States of America.|Field of Computational Biology, Cornell University, Ithaca, New York, United States of America.|Field of Computational Biology, Cornell University, Ithaca, New York, United States of America.', 'United States|United States|United States', 22, 'Action Potentials|Animals|Developmental Biology|Evoked Potentials, Visual|Fetal Organ Maturity|Geniculate Bodies|Humans|Information Theory|Learning|Models, Neurological|Nerve Net|Neuronal Plasticity|Neurons|Pattern Recognition, Visual|Photic Stimulation|Retinal Ganglion Cells|Stochastic Processes|Synaptic Transmission|Visual Cortex|Visual Fields|Visual Pathways', 'Journal Article', '10.1371/journal.pcbi.1000137', '18670593', 'Patterns of spontaneous activity in the developing retina, LGN, and cortex are necessary for the proper development of visual cortex. With these patterns intact, the primary visual cortices of many newborn animals develop properties similar to those of the adult cortex but without the training benefit of visual experience. Previous models have demonstrated how V1 responses can be initialized through mechanisms specific to development and prior to visual experience, such as using axonal guidance cues or relying on simple, pairwise correlations on spontaneous activity with additional developmental constraints. We argue that these spontaneous patterns may be better understood as part of an innate learning strategy, which learns similarly on activity both before and during visual experience. With an abstraction of spontaneous activity models, we show how the visual system may be able to bootstrap an efficient code for its natural environment prior to external visual experience, and we continue the same refinement strategy upon natural experience. The patterns are generated through simple, local interactions and contain the same relevant statistical properties of retinal waves and hypothesized waves in the LGN and V1. An efficient encoding of these patterns resembles a sparse coding of natural images by producing neurons with localized, oriented, bandpass structure-the same code found in early visual cortical cells. We address the relevance of higher-order statistical properties of spontaneous activity, how this relates to a system that may adapt similarly on activity prior to and during natural experience, and how these concepts ultimately relate to an efficient coding of our natural world.'),
(83960, 2008, 'plos', 'Identification and rational redesign of peptide ligands to CRIP1, a novel biomarker for cancers', 'Hao, Jihua|Serohijos, Adrian W R|Newton, Gail|Tassone, Gina|Wang, Zuncai|Sgroi, Dennis C|Dokholyan, Nikolay V|Basilion, James P', 'Department of Radiology, Case Western Reserve University, Cleveland, Ohio, United States of America.|Department of Radiology, Case Western Reserve University, Cleveland, Ohio, United States of America.|Department of Radiology, Case Western Reserve University, Cleveland, Ohio, United States of America.|Department of Radiology, Case Western Reserve University, Cleveland, Ohio, United States of America.|Department of Radiology, Case Western Reserve University, Cleveland, Ohio, United States of America.|Department of Radiology, Case Western Reserve University, Cleveland, Ohio, United States of America.|Department of Radiology, Case Western Reserve University, Cleveland, Ohio, United States of America.|Department of Radiology, Case Western Reserve University, Cleveland, Ohio, United States of America.', 'United States|United States|United States|United States|United States|United States|United States|Un', 0, 'Amino Acid Motifs|Binding, Competitive|Carrier Proteins|Coliphages|Computational Biology|Humans|LIM Domain Proteins|Ligands|Models, Molecular|Peptide Library|Peptides|Protein Binding|Thermodynamics', 'Journal Article', '10.1371/journal.pcbi.1000138', '18670594', 'Cysteine-rich intestinal protein 1 (CRIP1) has been identified as a novel marker for early detection of cancers. Here we report on the use of phage display in combination with molecular modeling to identify a high-affinity ligand for CRIP1. Panning experiments using a circularized C7C phage library yielded several consensus sequences with modest binding affinities to purified CRIP1. Two sequence motifs, A1 and B5, having the highest affinities for CRIP1, were chosen for further study. With peptide structure information and the NMR structure of CRIP1, the higher-affinity A1 peptide was computationally redesigned, yielding a novel peptide, A1M, whose affinity was predicted to be much improved. Synthesis of the peptide and saturation and competitive binding studies demonstrated approximately a 10-28-fold improvement in the affinity of A1M compared to that of either A1 or B5 peptide. These techniques have broad application to the design of novel ligand peptides.'),
(83961, 2008, 'plos', 'Evolutionarily conserved substrate substructures for automated annotation of enzyme superfamilies', 'Chiang, Ranyee A|Sali, Andrej|Babbitt, Patricia C', 'Department of Biopharmaceutical Sciences, California Institute for Quantitative Biosciences, University of California at San Francisco, San Francisco, California, United States of America.|Department of Biopharmaceutical Sciences, California Institute for Quantitative Biosciences, University of California at San Francisco, San Francisco, California, United States of America.|Department of Biopharmaceutical Sciences, California Institute for Quantitative Biosciences, University of California at San Francisco, San Francisco, California, United States of America.', 'United States|United States|United States', 15, 'Amino Acid Sequence|Animals|Catalysis|Cluster Analysis|Computational Biology|Conserved Sequence|Databases, Protein|Enzymes|Evolution, Molecular|Humans|Pattern Recognition, Automated|Protein Binding|Protein Interaction Domains and Motifs|Sequence Alignment|Structural Homology, Protein|Structure-Activity Relationship|Substrate Specificity', 'Journal Article', '10.1371/journal.pcbi.1000142', '18670595', 'The evolution of enzymes affects how well a species can adapt to new environmental conditions. During enzyme evolution, certain aspects of molecular function are conserved while other aspects can vary. Aspects of function that are more difficult to change or that need to be reused in multiple contexts are often conserved, while those that vary may indicate functions that are more easily changed or that are no longer required. In analogy to the study of conservation patterns in enzyme sequences and structures, we have examined the patterns of conservation and variation in enzyme function by analyzing graph isomorphisms among enzyme substrates of a large number of enzyme superfamilies. This systematic analysis of substrate substructures establishes the conservation patterns that typify individual superfamilies. Specifically, we determined the chemical substructures that are conserved among all known substrates of a superfamily and the substructures that are reacting in these substrates and then examined the relationship between the two. Across the 42 superfamilies that were analyzed, substantial variation was found in how much of the conserved substructure is reacting, suggesting that superfamilies may not be easily grouped into discrete and separable categories. Instead, our results suggest that many superfamilies may need to be treated individually for analyses of evolution, function prediction, and guiding enzyme engineering strategies. Annotating superfamilies with these conserved and reacting substructure patterns provides information that is orthogonal to information provided by studies of conservation in superfamily sequences and structures, thereby improving the precision with which we can predict the functions of enzymes of unknown function and direct studies in enzyme engineering. Because the method is automated, it is suitable for large-scale characterization and comparison of fundamental functional capabilities of both characterized and uncharacterized enzyme superfamilies.'),
(83962, 2008, 'plos', 'Embedding mRNA stability in correlation analysis of time-series gene expression data', 'Farina, Lorenzo|De Santis, Alberto|Salvucci, Samanta|Morelli, Giorgio|Ruberti, Ida', 'Dipartimento di Informatica e Sistemistica Antonio Ruberti, Sapienza Università di Roma, Rome, Italy. lorenzo.farina@uniroma1.it|Dipartimento di Informatica e Sistemistica Antonio Ruberti, Sapienza Università di Roma, Rome, Italy. lorenzo.farina@uniroma1.it|Dipartimento di Informatica e Sistemistica Antonio Ruberti, Sapienza Università di Roma, Rome, Italy. lorenzo.farina@uniroma1.it|Dipartimento di Informatica e Sistemistica Antonio Ruberti, Sapienza Università di Roma, Rome, Italy. lorenzo.farina@uniroma1.it|Dipartimento di Informatica e Sistemistica Antonio Ruberti, Sapienza Università di Roma, Rome, Italy. lorenzo.farina@uniroma1.it', 'Italy|Italy|Italy|Italy|Italy', 0, 'Artificial Intelligence|Cell Cycle|Databases, Genetic|Gene Expression|Gene Expression Profiling|Genes, Fungal|Oligonucleotide Array Sequence Analysis|Pattern Recognition, Automated|Predictive Value of Tests|RNA Stability|Saccharomyces cerevisiae|Time Factors', 'Journal Article', '10.1371/journal.pcbi.1000141', '18670596', 'Current methods for the identification of putatively co-regulated genes directly from gene expression time profiles are based on the similarity of the time profile. Such association metrics, despite their central role in gene network inference and machine learning, have largely ignored the impact of dynamics or variation in mRNA stability. Here we introduce a simple, but powerful, new similarity metric called lead-lag R(2) that successfully accounts for the properties of gene dynamics, including varying mRNA degradation and delays. Using yeast cell-cycle time-series gene expression data, we demonstrate that the predictive power of lead-lag R(2) for the identification of co-regulated genes is significantly higher than that of standard similarity measures, thus allowing the selection of a large number of entirely new putatively co-regulated genes. Furthermore, the lead-lag metric can also be used to uncover the relationship between gene expression time-series and the dynamics of formation of multiple protein complexes. Remarkably, we found a high lead-lag R(2) value among genes coding for a transient complex.'),
(83963, 2008, 'plos', 'Why do hubs in the yeast protein interaction network tend to be essential: reexamining the connection between the network topology and essentiality', 'Zotenko, Elena|Mestre, Julian|OLeary, Dianne P|Przytycka, Teresa M', 'Max-Planck Institute for Informatics, Saarbruecken, Germany.|Max-Planck Institute for Informatics, Saarbruecken, Germany.|Max-Planck Institute for Informatics, Saarbruecken, Germany.|Max-Planck Institute for Informatics, Saarbruecken, Germany.', 'Germany|Germany|Germany|Germany', 271, 'Genes, Essential|Genes, Fungal|Neural Networks (Computer)|Protein Interaction Mapping|Saccharomyces cerevisiae|Saccharomyces cerevisiae Proteins', 'Journal Article', '10.1371/journal.pcbi.1000140', '18670624', 'The centrality-lethality rule, which notes that high-degree nodes in a protein interaction network tend to correspond to proteins that are essential, suggests that the topological prominence of a protein in a protein interaction network may be a good predictor of its biological importance. Even though the correlation between degree and essentiality was confirmed by many independent studies, the reason for this correlation remains illusive. Several hypotheses about putative connections between essentiality of hubs and the topology of protein-protein interaction networks have been proposed, but as we demonstrate, these explanations are not supported by the properties of protein interaction networks. To identify the main topological determinant of essentiality and to provide a biological explanation for the connection between the network topology and essentiality, we performed a rigorous analysis of six variants of the genomewide protein interaction network for Saccharomyces cerevisiae obtained using different techniques. We demonstrated that the majority of hubs are essential due to their involvement in Essential Complex Biological Modules, a group of densely connected proteins with shared biological function that are enriched in essential proteins. Moreover, we rejected two previously proposed explanations for the centrality-lethality rule, one relating the essentiality of hubs to their role in the overall network connectivity and another relying on the recently published essential protein interactions model.'),
(83964, 2008, 'plos', 'Modeling the violation of reward maximization and invariance in reinforcement schedules', 'La Camera, Giancarlo|Richmond, Barry J', 'Laboratory of Neuropsychology, National Institute of Mental Health, National Institutes of Health, Department of Health and Human Services, Bethesda, Maryland, United States of America.|Laboratory of Neuropsychology, National Institute of Mental Health, National Institutes of Health, Department of Health and Human Services, Bethesda, Maryland, United States of America.', 'United States|United States', 0, 'Animals|Behavior, Animal|Choice Behavior|Conditioning (Psychology)|Cues|Discrimination Learning|Humans|Markov Chains|Models, Psychological|Motivation|Neural Networks (Computer)|Personal Satisfaction|Probability Learning|Reinforcement Schedule|Reward', 'Journal Article', '10.1371/journal.pcbi.1000131', '18688266', 'It is often assumed that animals and people adjust their behavior to maximize reward acquisition. In visually cued reinforcement schedules, monkeys make errors in trials that are not immediately rewarded, despite having to repeat error trials. Here we show that error rates are typically smaller in trials equally distant from reward but belonging to longer schedules (referred to as schedule length effect). This violates the principles of reward maximization and invariance and cannot be predicted by the standard methods of Reinforcement Learning, such as the method of temporal differences. We develop a heuristic model that accounts for all of the properties of the behavior in the reinforcement schedule task but whose predictions are not different from those of the standard temporal difference model in choice tasks. In the modification of temporal difference learning introduced here, the effect of schedule length emerges spontaneously from the sensitivity to the immediately preceding trial. We also introduce a policy for general Markov Decision Processes, where the decision made at each node is conditioned on the motivation to perform an instrumental action, and show that the application of our model to the reinforcement schedule task and the choice task are special cases of this general theoretical framework. Within this framework, Reinforcement Learning can approach contextual learning with the mixture of empirical findings and principled assumptions that seem to coexist in the best descriptions of animal behavior. As examples, we discuss two phenomena observed in humans that often derive from the violation of the principle of invariance: framing, wherein equivalent options are treated differently depending on the context in which they are presented, and the sunk cost effect, the greater tendency to continue an endeavor once an investment in money, effort, or time has been made. The schedule length effect might be a manifestation of these phenomena in monkeys.'),
(83965, 2008, 'plos', 'Retroviral integration process in the human genome: is it really non-random? A new statistical approach', 'Ambrosi, Alessandro|Cattoglio, Claudia|Di Serio, Clelia', 'University Centre for Statistics in the Biomedical Sciences, Università Vita-Salute San Raffaele, Milan Italy.|University Centre for Statistics in the Biomedical Sciences, Università Vita-Salute San Raffaele, Milan Italy.|University Centre for Statistics in the Biomedical Sciences, Università Vita-Salute San Raffaele, Milan Italy.', 'Italy|Italy|Italy', 0, 'DNA, Viral|Genetic Vectors|Genome, Human|Hematopoietic Stem Cells|Humans|Moloney murine leukemia virus|Sequence Analysis, Protein|Statistical Distributions|Stochastic Processes|Transcription Initiation Site|Virus Integration', 'Journal Article', '10.1371/journal.pcbi.1000144', '18688267', 'Retroviral vectors are widely used in gene therapy to introduce therapeutic genes into patients cells, since, once delivered to the nucleus, the genes of interest are stably inserted (integrated) into the target cell genome. There is now compelling evidence that integration of retroviral vectors follows non-random patterns in mammalian genome, with a preference for active genes and regulatory regions. In particular, Moloney Leukemia Virus (MLV)-derived vectors show a tendency to integrate in the proximity of the transcription start site (TSS) of genes, occasionally resulting in the deregulation of gene expression and, where proto-oncogenes are targeted, in tumor initiation. This has drawn the attention of the scientific community to the molecular determinants of the retroviral integration process as well as to statistical methods to evaluate the genome-wide distribution of integration sites. In recent approaches, the observed distribution of MLV integration distances (IDs) from the TSS of the nearest gene is assumed to be non-random by empirical comparison with a random distribution generated by computational simulation procedures. To provide a statistical procedure to test the randomness of the retroviral insertion pattern, we propose a probability model (Beta distribution) based on IDs between two consecutive genes. We apply the procedure to a set of 595 unique MLV insertion sites retrieved from human hematopoietic stem/progenitor cells. The statistical goodness of fit test shows the suitability of this distribution to the observed data. Our statistical analysis confirms the preference of MLV-based vectors to integrate in promoter-proximal regions.'),
(83966, 2008, 'plos', 'A general definition and nomenclature for alternative splicing events', 'Sammeth, Michael|Foissac, Sylvain|Guigó, Roderic', 'Centre de Regulació Genòmica, Barcelona, Spain. micha@sammeth.net|Centre de Regulació Genòmica, Barcelona, Spain. micha@sammeth.net|Centre de Regulació Genòmica, Barcelona, Spain. micha@sammeth.net', 'Spain|Spain|Spain', 131, 'Alternative Splicing|Animals|Bees|Caenorhabditis elegans|Cattle|Chickens|Cluster Analysis|Databases, Genetic|Dogs|Drosophila melanogaster|Gene Expression Profiling|Genomics|Humans|Mice|Pan troglodytes|RNA Splice Sites|Rats|Sequence Analysis, RNA|Software|Species Specificity|Terminology as Topic|Xenopus|Zebrafish', 'Journal Article', '10.1371/journal.pcbi.1000147', '18688268', 'Understanding the molecular mechanisms responsible for the regulation of the transcriptome present in eukaryotic cells is one of the most challenging tasks in the postgenomic era. In this regard, alternative splicing (AS) is a key phenomenon contributing to the production of different mature transcripts from the same primary RNA sequence. As a plethora of different transcript forms is available in databases, a first step to uncover the biology that drives AS is to identify the different types of reflected splicing variation. In this work, we present a general definition of the AS event along with a notation system that involves the relative positions of the splice sites. This nomenclature univocally and dynamically assigns a specific AS code to every possible pattern of splicing variation. On the basis of this definition and the corresponding codes, we have developed a computational tool (AStalavista) that automatically characterizes the complete landscape of AS events in a given transcript annotation of a genome, thus providing a platform to investigate the transcriptome diversity across genes, chromosomes, and species. Our analysis reveals that a substantial part--in human more than a quarter-of the observed splicing variations are ignored in common classification pipelines. We have used AStalavista to investigate and to compare the AS landscape of different reference annotation sets in human and in other metazoan species and found that proportions of AS events change substantially depending on the annotation protocol, species-specific attributes, and coding constraints acting on the transcripts. The AStalavista system therefore provides a general framework to conduct specific studies investigating the occurrence, impact, and regulation of AS.'),
(83967, 2008, 'plos', 'Intramolecular cohesion of coils mediated by phenylalanine--glycine motifs in the natively unfolded domain of a nucleoporin', 'Krishnan, V V|Lau, Edmond Y|Yamada, Justin|Denning, Daniel P|Patel, Samir S|Colvin, Michael E|Rexach, Michael F', 'Department of Applied Science, University of California Davis, Davis, California, United States of America.|Department of Applied Science, University of California Davis, Davis, California, United States of America.|Department of Applied Science, University of California Davis, Davis, California, United States of America.|Department of Applied Science, University of California Davis, Davis, California, United States of America.|Department of Applied Science, University of California Davis, Davis, California, United States of America.|Department of Applied Science, University of California Davis, Davis, California, United States of America.|Department of Applied Science, University of California Davis, Davis, California, United States of America.', 'United States|United States|United States|United States|United States|United States|United States', 0, 'Active Transport, Cell Nucleus|Amino Acid Motifs|Glycine|Models, Molecular|Molecular Weight|Nuclear Pore|Nuclear Pore Complex Proteins|Phenylalanine|Protein Binding|Protein Folding|Protein Interaction Domains and Motifs|Protein Structure, Quaternary|Repetitive Sequences, Amino Acid|Saccharomyces cerevisiae|Saccharomyces cerevisiae Proteins|Thermodynamics', 'Journal Article', '10.1371/journal.pcbi.1000145', '18688269', 'The nuclear pore complex (NPC) provides the sole aqueous conduit for macromolecular exchange between the nucleus and the cytoplasm of cells. Its diffusion conduit contains a size-selective gate formed by a family of NPC proteins that feature large, natively unfolded domains with phenylalanine-glycine repeats (FG domains). These domains of nucleoporins play key roles in establishing the NPC permeability barrier, but little is known about their dynamic structure. Here we used molecular modeling and biophysical techniques to characterize the dynamic ensemble of structures of a representative FG domain from the yeast nucleoporin Nup116. The results showed that its FG motifs function as intramolecular cohesion elements that impart order to the FG domain and compact its ensemble of structures into native premolten globular configurations. At the NPC, the FG motifs of nucleoporins may exert this cohesive effect intermolecularly as well as intramolecularly to form a malleable yet cohesive quaternary structure composed of highly flexible polypeptide chains. Dynamic shifts in the equilibrium or competition between intra- and intermolecular FG motif interactions could facilitate the rapid and reversible structural transitions at the NPC conduit needed to accommodate passing karyopherin-cargo complexes of various shapes and sizes while simultaneously maintaining a size-selective gate against protein diffusion.'),
(83968, 2008, 'plos', 'Efficient algorithms for probing the RNA mutation landscape', 'Waldispühl, Jérôme|Devadas, Srinivas|Berger, Bonnie|Clote, Peter', 'Department of Mathematics, Massachusetts Institute of Technology, Cambridge, Massachusetts, United States of America.|Department of Mathematics, Massachusetts Institute of Technology, Cambridge, Massachusetts, United States of America.|Department of Mathematics, Massachusetts Institute of Technology, Cambridge, Massachusetts, United States of America.|Department of Mathematics, Massachusetts Institute of Technology, Cambridge, Massachusetts, United States of America.', 'United States|United States|United States|United States', 34, 'Algorithms|Cluster Analysis|Computational Biology|Evolution, Molecular|HIV|Hepacivirus|Humans|Mutagenesis|Mutation|Nucleic Acid Conformation|RNA|Replicon|Response Elements|Software|Thermodynamics', 'Journal Article', '10.1371/journal.pcbi.1000124', '18688270', 'The diversity and importance of the role played by RNAs in the regulation and development of the cell are now well-known and well-documented. This broad range of functions is achieved through specific structures that have been (presumably) optimized through evolution. State-of-the-art methods, such as McCaskills algorithm, use a statistical mechanics framework based on the computation of the partition function over the canonical ensemble of all possible secondary structures on a given sequence. Although secondary structure predictions from thermodynamics-based algorithms are not as accurate as methods employing comparative genomics, the former methods are the only available tools to investigate novel RNAs, such as the many RNAs of unknown function recently reported by the ENCODE consortium. In this paper, we generalize the McCaskill partition function algorithm to sum over the grand canonical ensemble of all secondary structures of all mutants of the given sequence. Specifically, our new program, RNAmutants, simultaneously computes for each integer k the minimum free energy structure MFE(k) and the partition function Z(k) over all secondary structures of all k-point mutants, even allowing the user to specify certain positions required not to mutate and certain positions required to base-pair or remain unpaired. This technically important extension allows us to study the resilience of an RNA molecule to pointwise mutations. By computing the mutation profile of a sequence, a novel graphical representation of the mutational tendency of nucleotide positions, we analyze the deleterious nature of mutating specific nucleotide positions or groups of positions. We have successfully applied RNAmutants to investigate deleterious mutations (mutations that radically modify the secondary structure) in the Hepatitis C virus cis-acting replication element and to evaluate the evolutionary pressure applied on different regions of the HIV trans-activation response element. In particular, we show qualitative agreement between published Hepatitis C and HIV experimental mutagenesis studies and our analysis of deleterious mutations using RNAmutants. Our work also predicts other deleterious mutations, which could be verified experimentally. Finally, we provide evidence that the 3 UTR of the GB RNA virus C has been optimized to preserve evolutionarily conserved stem regions from a deleterious effect of pointwise mutations. We hope that there will be long-term potential applications of RNAmutants in de novo RNA design and drug design against RNA viruses. This work also suggests potential applications for large-scale exploration of the RNA sequence-structure network. Binary distributions are available at http://RNAmutants.csail.mit.edu/.'),
(83969, 2008, 'plos', 'Geometric interpretation of gene coexpression network analysis', 'Horvath, Steve|Dong, Jun', 'Department of Human Genetics, David Geffen School of Medicine, University of California, Los Angeles, California, United States of America.|Department of Human Genetics, David Geffen School of Medicine, University of California, Los Angeles, California, United States of America.', 'United States|United States', 410, 'Algorithms|Animals|Cluster Analysis|Fuzzy Logic|Gene Expression Profiling|Genes, Fungal|Humans|Interdisciplinary Communication|Mice|Neural Networks (Computer)|Oligonucleotide Array Sequence Analysis|Systems Biology|Terminology as Topic', 'Journal Article', '10.1371/journal.pcbi.1000117', '18704157', 'THE MERGING OF NETWORK THEORY AND MICROARRAY DATA ANALYSIS TECHNIQUES HAS SPAWNED A NEW FIELD: gene coexpression network analysis. While network methods are increasingly used in biology, the network vocabulary of computational biologists tends to be far more limited than that of, say, social network theorists. Here we review and propose several potentially useful network concepts. We take advantage of the relationship between network theory and the field of microarray data analysis to clarify the meaning of and the relationship among network concepts in gene coexpression networks. Network theory offers a wealth of intuitive concepts for describing the pairwise relationships among genes, which are depicted in cluster trees and heat maps. Conversely, microarray data analysis techniques (singular value decomposition, tests of differential expression) can also be used to address difficult problems in network theory. We describe conditions when a close relationship exists between network analysis and microarray data analysis techniques, and provide a rough dictionary for translating between the two fields. Using the angular interpretation of correlations, we provide a geometric interpretation of network theoretic concepts and derive unexpected relationships among them. We use the singular value decomposition of module expression data to characterize approximately factorizable gene coexpression networks, i.e., adjacency matrices that factor into node specific contributions. High and low level views of coexpression networks allow us to study the relationships among modules and among module genes, respectively. We characterize coexpression networks where hub genes are significant with respect to a microarray sample trait and show that the network concept of intramodular connectivity can be interpreted as a fuzzy measure of module membership. We illustrate our results using human, mouse, and yeast microarray gene expression data. The unification of coexpression network methods with traditional data mining methods can inform the application and development of systems biologic methods.'),
(83970, 2008, 'plos', 'A novel three-phase model of brain tissue microstructure', 'Gevertz, Jana L|Torquato, Salvatore', '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', 39, 'Animals|Brain|Diffusion|Extracellular Space|Factor Analysis, Statistical|Humans|Imaging, Three-Dimensional|Models, Anatomic|Models, Neurological|Monte Carlo Method', 'Journal Article', '10.1371/journal.pcbi.1000152', '18704170', 'We propose a novel biologically constrained three-phase model of the brain microstructure. Designing a realistic model is tantamount to a packing problem, and for this reason, a number of techniques from the theory of random heterogeneous materials can be brought to bear on this problem. Our analysis strongly suggests that previously developed two-phase models in which cells are packed in the extracellular space are insufficient representations of the brain microstructure. These models either do not preserve realistic geometric and topological features of brain tissue or preserve these properties while overestimating the brains effective diffusivity, an average measure of the underlying microstructure. In light of the highly connected nature of three-dimensional space, which limits the minimum diffusivity of biologically constrained two-phase models, we explore the previously proposed hypothesis that the extracellular matrix is an important factor that contributes to the diffusivity of brain tissue. Using accurate first-passage-time techniques, we support this hypothesis by showing that the incorporation of the extracellular matrix as the third phase of a biologically constrained model gives the reduction in the diffusion coefficient necessary for the three-phase model to be a valid representation of the brain microstructure.'),
(83971, 2008, 'plos', 'Allosteric communication in myosin V: from small conformational changes to large directed movements', 'Cecchini, M|Houdusse, A|Karplus, M', 'Laboratoire de Chimie Biophysique, Université Louis Pasteur, ISIS, Strasbourg, France.|Laboratoire de Chimie Biophysique, Université Louis Pasteur, ISIS, Strasbourg, France.|Laboratoire de Chimie Biophysique, Université Louis Pasteur, ISIS, Strasbourg, France.', 'France|France|France', 0, 'Actins|Actomyosin|Adenosine Triphosphate|Allosteric Regulation|Animals|Binding Sites|Energy Transfer|Humans|Hydrolysis|Models, Molecular|Motion|Movement|Muscle Contraction|Myosin Heavy Chains|Myosin Subfragments|Myosin Type V|Protein Binding|Protein Conformation|Structure-Activity Relationship', 'Journal Article', '10.1371/journal.pcbi.1000129', '18704171', 'The rigor to post-rigor transition in myosin, a consequence of ATP binding, plays an essential role in the Lymn-Taylor functional cycle because it results in the dissociation of the actomyosin complex after the powerstroke. On the basis of the X-ray structures of myosin V, we have developed a new normal mode superposition model for the transition path between the two states. Rigid-body motions of the various subdomains and specific residues at the subdomain interfaces are key elements in the transition. The allosteric communication between the nucleotide binding site and the U50/L50 cleft is shown to result from local changes due to ATP binding, which induce large amplitude motions that are encoded in the structure of the protein. The triggering event is the change in the interaction of switch I and the P-loop, which is stabilized by ATP binding. The motion of switch I, which is a relatively rigid element of the U50 subdomain, leads directly to a partial opening of the U50/L50 cleft, the latter is expected to weaken the binding of myosin to actin. The calculated transition path demonstrates the nature of the subdomain coupling and offers an explanation for the mutual exclusion of ATP and actin binding. The mechanism of the uncoupling of the converter from the motor head, an essential part of the transition, is elucidated. The origin of the partial untwisting of the central beta-sheet in the rigor to post-rigor transition is described.'),
(83972, 2008, 'plos', 'Protein complex evolution does not involve extensive network rewiring', 'van Dam, Teunis J P|Snel, Berend', 'Theoretical Biology and Bioinformatics Group, Department of Biology, Utrecht University, Utrecht, The Netherlands.|Theoretical Biology and Bioinformatics Group, Department of Biology, Utrecht University, Utrecht, The Netherlands.', 'Netherlands|Netherlands', 33, 'Animals|Chromatography, Affinity|Drosophila melanogaster|Evolution, Molecular|Humans|Proteins|Saccharomyces cerevisiae|Tandem Mass Spectrometry', 'Journal Article', '10.1371/journal.pcbi.1000132', '18711636', 'The formation of proteins into stable protein complexes plays a fundamental role in the operation of the cell. The study of the degree of evolutionary conservation of protein complexes between species and the evolution of protein-protein interactions has been hampered by lack of comprehensive coverage of the high-throughput (HTP) technologies that measure the interactome. We show that new high-throughput datasets on protein co-purification in yeast have a substantially lower false negative rate than previous datasets when compared to known complexes. These datasets are therefore more suitable to estimate the conservation of protein complex membership than hitherto possible. We perform comparative genomics between curated protein complexes from human and the HTP data in Saccharomyces cerevisiae to study the evolution of co-complex memberships. This analysis revealed that out of the 5,960 protein pairs that are part of the same complex in human, 2,216 are absent because both proteins lack an ortholog in S. cerevisiae, while for 1,828 the co-complex membership is disrupted because one of the two proteins lacks an ortholog. For the remaining 1,916 protein pairs, only 10% were never co-purified in the large-scale experiments. This implies a conservation level of co-complex membership of 90% when the genes coding for the protein pairs that participate in the same protein complex are also conserved. We conclude that the evolutionary dynamics of protein complexes are, by and large, not the result of network rewiring (i.e. acquisition or loss of co-complex memberships), but mainly due to genomic acquisition or loss of genes coding for subunits. We thus reveal evidence for the tight interrelation of genomic and network evolution.');
INSERT INTO `papers` (`id`, `ano`, `journal`, `titulo`, `autores`, `afiliacao`, `pais`, `citacoes`, `palavra_chave`, `categorias`, `doi`, `pubmed`, `abstract`) VALUES
(83973, 2008, 'plos', 'The spatiotemporal pattern of Src activation at lipid rafts revealed by diffusion-corrected FRET imaging', 'Lu, Shaoying|Ouyang, Mingxing|Seong, Jihye|Zhang, Jin|Chien, Shu|Wang, Yingxiao', 'Department of Bioengineering, University of Illinois at Urbana-Champaign, Urbana, Illinois, USA.|Department of Bioengineering, University of Illinois at Urbana-Champaign, Urbana, Illinois, USA.|Department of Bioengineering, University of Illinois at Urbana-Champaign, Urbana, Illinois, USA.|Department of Bioengineering, University of Illinois at Urbana-Champaign, Urbana, Illinois, USA.|Department of Bioengineering, University of Illinois at Urbana-Champaign, Urbana, Illinois, USA.|Department of Bioengineering, University of Illinois at Urbana-Champaign, Urbana, Illinois, USA.', 'United States|United States|United States|United States|United States|United States', 0, 'Biosensing Techniques|Computer Simulation|Diffusion|Fluorescence Resonance Energy Transfer|Lipids|Proto-Oncogene Proteins pp60(c-src)', 'Journal Article', '10.1371/journal.pcbi.1000127', '18711637', 'Genetically encoded biosensors based on fluorescence resonance energy transfer (FRET) have been widely applied to visualize the molecular activity in live cells with high spatiotemporal resolution. However, the rapid diffusion of biosensor proteins hinders a precise reconstruction of the actual molecular activation map. Based on fluorescence recovery after photobleaching (FRAP) experiments, we have developed a finite element (FE) method to analyze, simulate, and subtract the diffusion effect of mobile biosensors. This method has been applied to analyze the mobility of Src FRET biosensors engineered to reside at different subcompartments in live cells. The results indicate that the Src biosensor located in the cytoplasm moves 4-8 folds faster (0.93+/-0.06 microm(2)/sec) than those anchored on different compartments in plasma membrane (at lipid raft: 0.11+/-0.01 microm(2)/sec and outside: 0.18+/-0.02 microm(2)/sec). The mobility of biosensor at lipid rafts is slower than that outside of lipid rafts and is dominated by two-dimensional diffusion. When this diffusion effect was subtracted from the FRET ratio images, high Src activity at lipid rafts was observed at clustered regions proximal to the cell periphery, which remained relatively stationary upon epidermal growth factor (EGF) stimulation. This result suggests that EGF induced a Src activation at lipid rafts with well-coordinated spatiotemporal patterns. Our FE-based method also provides an integrated platform of image analysis for studying molecular mobility and reconstructing the spatiotemporal activation maps of signaling molecules in live cells.'),
(83974, 2008, 'plos', 'Using expression profiles of Caenorhabditis elegans neurons to identify genes that mediate synaptic connectivity', 'Baruch, Leehod|Itzkovitz, Shalev|Golan-Mashiach, Michal|Shapiro, Ehud|Segal, Eran', 'Department of Computer Science and Applied Mathematics, Weizmann Institute of Science, Rehovot, Israel.|Department of Computer Science and Applied Mathematics, Weizmann Institute of Science, Rehovot, Israel.|Department of Computer Science and Applied Mathematics, Weizmann Institute of Science, Rehovot, Israel.|Department of Computer Science and Applied Mathematics, Weizmann Institute of Science, Rehovot, Israel.|Department of Computer Science and Applied Mathematics, Weizmann Institute of Science, Rehovot, Israel.', 'Israel|Israel|Israel|Israel|Israel', 0, 'Animals|Caenorhabditis elegans|Gene Expression Profiling|Neurons|Synaptic Transmission', 'Journal Article', '10.1371/journal.pcbi.1000120', '18711638', 'Synaptic wiring of neurons in Caenorhabditis elegans is largely invariable between animals. It has been suggested that this feature stems from genetically encoded molecular markers that guide the neurons in the final stage of synaptic formation. Identifying these markers and unraveling the logic by which they direct synapse formation is a key challenge. Here, we address this task by constructing a probabilistic model that attempts to explain the neuronal connectivity diagram of C. elegans as a function of the expression patterns of its neurons. By only considering neuron pairs that are known to be connected by chemical or electrical synapses, we focus on the final stage of synapse formation, in which neurons identify their designated partners. Our results show that for many neurons the neuronal expression map of C. elegans can be used to accurately predict the subset of adjacent neurons that will be chosen as its postsynaptic partners. Notably, these predictions can be achieved using the expression patterns of only a small number of specific genes that interact in a combinatorial fashion.'),
(83975, 2008, 'plos', 'Classifying RNA-binding proteins based on electrostatic properties', 'Shazman, Shula|Mandel-Gutfreund, Yael', 'Faculty of Biology, Technion-Israel Institute of Technology, Haifa, Israel.|Faculty of Biology, Technion-Israel Institute of Technology, Haifa, Israel.', 'Israel|Israel', 54, 'Amino Acid Sequence|Animals|Artificial Intelligence|Binding Sites|Computational Biology|DNA-Binding Proteins|Databases, Protein|Humans|Pattern Recognition, Automated|Protein Interaction Domains and Motifs|RNA, Messenger|RNA, Ribosomal|RNA, Transfer|RNA-Binding Proteins|Sequence Analysis, Protein|Static Electricity|Structure-Activity Relationship', 'Journal Article', '10.1371/journal.pcbi.1000146', '18716674', 'Protein structure can provide new insight into the biological function of a protein and can enable the design of better experiments to learn its biological roles. Moreover, deciphering the interactions of a protein with other molecules can contribute to the understanding of the proteins function within cellular processes. In this study, we apply a machine learning approach for classifying RNA-binding proteins based on their three-dimensional structures. The method is based on characterizing unique properties of electrostatic patches on the protein surface. Using an ensemble of general protein features and specific properties extracted from the electrostatic patches, we have trained a support vector machine (SVM) to distinguish RNA-binding proteins from other positively charged proteins that do not bind nucleic acids. Specifically, the method was applied on proteins possessing the RNA recognition motif (RRM) and successfully classified RNA-binding proteins from RRM domains involved in protein-protein interactions. Overall the method achieves 88% accuracy in classifying RNA-binding proteins, yet it cannot distinguish RNA from DNA binding proteins. Nevertheless, by applying a multiclass SVM approach we were able to classify the RNA-binding proteins based on their RNA targets, specifically, whether they bind a ribosomal RNA (rRNA), a transfer RNA (tRNA), or messenger RNA (mRNA). Finally, we present here an innovative approach that does not rely on sequence or structural homology and could be applied to identify novel RNA-binding proteins with unique folds and/or binding motifs.'),
(83976, 2008, 'plos', 'Regulatory control and the costs and benefits of biochemical noise', 'Txc4x83nase-Nicola, Sorin|ten Wolde, Pieter Rein', 'Foundation for Fundamental Research on Matter (FOM), Institute for Atomic and Molecular Physics, Amsterdam, The Netherlands.|Foundation for Fundamental Research on Matter (FOM), Institute for Atomic and Molecular Physics, Amsterdam, The Netherlands.', 'Netherlands|Netherlands', 42, 'Cell Proliferation|Gene Expression Regulation|Gene Regulatory Networks|Models, Biological|Protein Biosynthesis|Proteins|Reference Values|Statistical Distributions', 'Journal Article', '10.1371/journal.pcbi.1000125', '18716677', 'Experiments in recent years have vividly demonstrated that gene expression can be highly stochastic. How protein concentration fluctuations affect the growth rate of a population of cells is, however, a wide-open question. We present a mathematical model that makes it possible to quantify the effect of protein concentration fluctuations on the growth rate of a population of genetically identical cells. The model predicts that the populations growth rate depends on how the growth rate of a single cell varies with protein concentration, the variance of the protein concentration fluctuations, and the correlation time of these fluctuations. The model also predicts that when the average concentration of a protein is close to the value that maximizes the growth rate, fluctuations in its concentration always reduce the growth rate. However, when the average protein concentration deviates sufficiently from the optimal level, fluctuations can enhance the growth rate of the population, even when the growth rate of a cell depends linearly on the protein concentration. The model also shows that the ensemble or population average of a quantity, such as the average protein expression level or its variance, is in general not equal to its time average as obtained from tracing a single cell and its descendants. We apply our model to perform a cost-benefit analysis of gene regulatory control. Our analysis predicts that the optimal expression level of a gene regulatory protein is determined by the trade-off between the cost of synthesizing the regulatory protein and the benefit of minimizing the fluctuations in the expression of its target gene. We discuss possible experiments that could test our predictions.'),
(83977, 2008, 'plos', 'Coordinate regulation of G protein signaling via dynamic interactions of receptor and GAP', 'Turcotte, Marc|Tang, Wei|Ross, Elliott M', 'Department of Pharmacology, University of Texas Southwestern Medical Center, Dallas, Texas, USA.|Department of Pharmacology, University of Texas Southwestern Medical Center, Dallas, Texas, USA.|Department of Pharmacology, University of Texas Southwestern Medical Center, Dallas, Texas, USA.', 'United States|United States|United States', 0, 'Binding, Competitive|Enzyme Activation|Enzyme Inhibitors|GTP-Binding Proteins|GTPase-Activating Proteins|Guanosine Diphosphate|Guanosine Triphosphate|Hydrolysis|Kinetics|Least-Squares Analysis|Models, Biological|Phospholipase C beta|Protein Binding|Receptors, G-Protein-Coupled|Signal Transduction|Systems Biology|Unilamellar Liposomes|Up-Regulation', 'Journal Article', '10.1371/journal.pcbi.1000148', '18716678', 'Signal output from receptor-G-protein-effector modules is a dynamic function of the nucleotide exchange activity of the receptor, the GTPase-accelerating activity of GTPase-activating proteins (GAPs), and their interactions. GAPs may inhibit steady-state signaling but may also accelerate deactivation upon removal of stimulus without significantly inhibiting output when the receptor is active. Further, some effectors (e.g., phospholipase C-beta) are themselves GAPs, and it is unclear how such effectors can be stimulated by G proteins at the same time as they accelerate G protein deactivation. The multiple combinations of protein-protein associations and interacting regulatory effects that allow such complex behaviors in this system do not permit the usual simplifying assumptions of traditional enzyme kinetics and are uniquely subject to systems-level analysis. We developed a kinetic model for G protein signaling that permits analysis of both interactive and independent G protein binding and regulation by receptor and GAP. We evaluated parameters of the model (all forward and reverse rate constants) by global least-squares fitting to a diverse set of steady-state GTPase measurements in an m1 muscarinic receptor-G(q)-phospholipase C-beta1 module in which GTPase activities were varied by approximately 10(4)-fold. We provide multiple tests to validate the fitted parameter set, which is consistent with results from the few previous pre-steady-state kinetic measurements. Results indicate that (1) GAP potentiates the GDP/GTP exchange activity of the receptor, an activity never before reported, (2) exchange activity of the receptor is biased toward replacement of GDP by GTP, (3) receptor and GAP bind G protein with negative cooperativity when G protein is bound to either GTP or GDP, promoting rapid GAP binding and dissociation, (4) GAP indirectly stabilizes the continuous binding of receptor to G protein during steady-state GTPase hydrolysis, thus further enhancing receptor activity, and (5) receptor accelerates GDP/GTP exchange primarily by opening an otherwise closed nucleotide binding site on the G protein but has minimal effect on affinity (K(assoc) = k(assoc)/k(dissoc)) of G protein for nucleotide. Model-based simulation explains how GAP activity can accelerate deactivation >10-fold upon removal of agonist but still allow high signal output while the receptor is active. Analysis of GTPase flux through distinct reaction pathways and consequent accumulation of specific GTPase cycle intermediates indicate that, in the presence of a GAP, the receptor remains bound to G protein throughout the GTPase cycle and that GAP binds primarily during the GTP-bound phase. The analysis explains these behaviors and relates them to the specific regulatory phenomena described above. The work also demonstrates the applicability of appropriately data-constrained system-level analysis to signaling networks of this scale.'),
(83978, 2008, 'plos', 'Host control of malaria infections: constraints on immune and erythropoeitic response kinetics', 'McQueen, Philip G|McKenzie, F Ellis', 'Mathematical and Statistical Computing Laboratory, Division of Computational Bioscience, Center for Information Technology, National Institutes of Health, Bethesda, Maryland, United States of America. mcqueenp@mail.nih.gov|Mathematical and Statistical Computing Laboratory, Division of Computational Bioscience, Center for Information Technology, National Institutes of Health, Bethesda, Maryland, United States of America. mcqueenp@mail.nih.gov', 'United States|United States', 29, 'Anemia|Animals|Antibodies, Protozoan|Antigens, Protozoan|Erythrocyte Count|Erythrocytes|Erythropoiesis|Host-Parasite Interactions|Humans|Immunity, Innate|Kinetics|Malaria|Models, Immunological|Parasitemia|Plasmodium falciparum|Plasmodium vivax|Schizonts', 'Journal Article', '10.1371/journal.pcbi.1000149', '18725923', 'The two main agents of human malaria, Plasmodium vivax and Plasmodium falciparum, can induce severe anemia and provoke strong, complex immune reactions. Which dynamical behaviors of host immune and erythropoietic responses would foster control of infection, and which would lead to runaway parasitemia and/or severe anemia? To answer these questions, we developed differential equation models of interacting parasite and red blood cell (RBC) populations modulated by host immune and erythropoietic responses. The model immune responses incorporate both a rapidly responding innate component and a slower-responding, long-term antibody component, with several parasite developmental stages considered as targets for each type of immune response. We found that simulated infections with the highest parasitemia tended to be those with ineffective innate immunity even if antibodies were present. We also compared infections with dyserythropoiesis (reduced RBC production during infection) to those with compensatory erythropoiesis (boosted RBC production) or a fixed basal RBC production rate. Dyserythropoiesis tended to reduce parasitemia slightly but at a cost to the host of aggravating anemia. On the other hand, compensatory erythropoiesis tended to reduce the severity of anemia but with enhanced parasitemia if the innate response was ineffective. For both parasite species, sharp transitions between the schizont and the merozoite stages of development (i.e., with standard deviation in intra-RBC development time <or=2.4 h) were associated with lower parasitemia and less severe anemia. Thus tight synchronization in asexual parasite development might help control parasitemia. Finally, our simulations suggest that P. vivax can induce severe anemia as readily as P. falciparum for the same type of immune response, though P. vivax attacks a much smaller subset of RBCs. Since most P. vivax infections are nonlethal (if debilitating) clinically, this suggests that P. falciparum adaptations for countering or evading immune responses are more effective than those of P. vivax.'),
(83979, 2008, 'plos', 'The effect of a DeltaK280 mutation on the unfolded state of a microtubule-binding repeat in Tau', 'Huang, Austin|Stultz, Collin M', 'Department of Electrical Engineering and Computer Science, Harvard-MIT Division of Health Sciences and Technology, Research Laboratory of Electronics, Massachusetts Institute of Technology, Cambridge, Massachusetts, United States of America.|Department of Electrical Engineering and Computer Science, Harvard-MIT Division of Health Sciences and Technology, Research Laboratory of Electronics, Massachusetts Institute of Technology, Cambridge, Massachusetts, United States of America.', 'United States|United States', 37, 'Amino Acid Motifs|Dimerization|Humans|Lysine|Microtubules|Models, Molecular|Mutation|Protein Binding|Protein Folding|Protein Interaction Domains and Motifs|Repetitive Sequences, Amino Acid|Systems Integration|Thermodynamics|tau Proteins', 'Journal Article', '10.1371/journal.pcbi.1000155', '18725924', 'Tau is a natively unfolded protein that forms intracellular aggregates in the brains of patients with Alzheimers disease. To decipher the mechanism underlying the formation of tau aggregates, we developed a novel approach for constructing models of natively unfolded proteins. The method, energy-minima mapping and weighting (EMW), samples local energy minima of subsequences within a natively unfolded protein and then constructs ensembles from these energetically favorable conformations that are consistent with a given set of experimental data. A unique feature of the method is that it does not strive to generate a single ensemble that represents the unfolded state. Instead we construct a number of candidate ensembles, each of which agrees with a given set of experimental constraints, and focus our analysis on local structural features that are present in all of the independently generated ensembles. Using EMW we generated ensembles that are consistent with chemical shift measurements obtained on tau constructs. Thirty models were constructed for the second microtubule binding repeat (MTBR2) in wild-type (WT) tau and a DeltaK280 mutant, which is found in some forms of frontotemporal dementia. By focusing on structural features that are preserved across all ensembles, we find that the aggregation-initiating sequence, PHF6*, prefers an extended conformation in both the WT and DeltaK280 sequences. In addition, we find that residue K280 can adopt a loop/turn conformation in WT MTBR2 and that deletion of this residue, which can adopt nonextended states, leads to an increase in locally extended conformations near the C-terminus of PHF6*. As an increased preference for extended states near the C-terminus of PHF6* may facilitate the propagation of beta-structure downstream from PHF6*, these results explain how a deletion at position 280 can promote the formation of tau aggregates.'),
(83980, 2008, 'plos', 'Modeling ChIP sequencing in silico with applications', 'Zhang, Zhengdong D|Rozowsky, Joel|Snyder, Michael|Chang, Joseph|Gerstein, Mark', 'Department of Molecular Biophysics and Biochemistry, Yale University, New Haven, Connecticut, United States of America.|Department of Molecular Biophysics and Biochemistry, Yale University, New Haven, Connecticut, United States of America.|Department of Molecular Biophysics and Biochemistry, Yale University, New Haven, Connecticut, United States of America.|Department of Molecular Biophysics and Biochemistry, Yale University, New Haven, Connecticut, United States of America.|Department of Molecular Biophysics and Biochemistry, Yale University, New Haven, Connecticut, United States of America.', 'United States|United States|United States|United States|United States', 49, 'Base Sequence|Binding Sites|Chromatin Immunoprecipitation|Cluster Analysis|Computational Biology|Computer Simulation|DNA|DNA-Binding Proteins|Genome, Human|Genomics|Humans|Oligonucleotide Array Sequence Analysis|Sequence Analysis, DNA|Statistical Distributions|Transcription Factors', 'Journal Article', '10.1371/journal.pcbi.1000158', '18725927', 'ChIP sequencing (ChIP-seq) is a new method for genomewide mapping of protein binding sites on DNA. It has generated much excitement in functional genomics. To score data and determine adequate sequencing depth, both the genomic background and the binding sites must be properly modeled. To develop a computational foundation to tackle these issues, we first performed a study to characterize the observed statistical nature of this new type of high-throughput data. By linking sequence tags into clusters, we show that there are two components to the distribution of tag counts observed in a number of recent experiments: an initial power-law distribution and a subsequent long right tail. Then we develop in silico ChIP-seq, a computational method to simulate the experimental outcome by placing tags onto the genome according to particular assumed distributions for the actual binding sites and for the background genomic sequence. In contrast to current assumptions, our results show that both the background and the binding sites need to have a markedly nonuniform distribution in order to correctly model the observed ChIP-seq data, with, for instance, the background tag counts modeled by a gamma distribution. On the basis of these results, we extend an existing scoring approach by using a more realistic genomic-background model. This enables us to identify transcription-factor binding sites in ChIP-seq data in a statistically rigorous fashion.'),
(83981, 2008, 'plos', 'Structure and dynamics of interphase chromosomes', 'Rosa, Angelo|Everaers, Ralf', 'Max-Planck-Institut für Physik Komplexer Systeme, Dresden, Germany. anrosa@unizar.es|Max-Planck-Institut für Physik Komplexer Systeme, Dresden, Germany. anrosa@unizar.es', 'Germany|Germany', 274, 'Animals|Chromatin|Chromosome Banding|Chromosomes|Drosophila|Humans|Interphase|Models, Genetic|Molecular Weight|Nuclear Matrix|Phase Transition|Polymers|Saccharomycetales|Thermodynamics', 'Journal Article', '10.1371/journal.pcbi.1000153', '18725929', 'During interphase chromosomes decondense, but fluorescent in situ hybridization experiments reveal the existence of distinct territories occupied by individual chromosomes inside the nuclei of most eukaryotic cells. We use computer simulations to show that the existence and stability of territories is a kinetic effect that can be explained without invoking an underlying nuclear scaffold or protein-mediated interactions between DNA sequences. In particular, we show that the experimentally observed territory shapes and spatial distances between marked chromosome sites for human, Drosophila, and budding yeast chromosomes can be reproduced by a parameter-free minimal model of decondensing chromosomes. Our results suggest that the observed interphase structure and dynamics are due to generic polymer effects: confined Brownian motion conserving the local topological state of long chain molecules and segregation of mutually unentangled chains due to topological constraints.'),
(83982, 2008, 'plos', 'Predicting human nucleosome occupancy from primary sequence', 'Gupta, Shobhit|Dennis, Jonathan|Thurman, Robert E|Kingston, Robert|Stamatoyannopoulos, John A|Noble, William Stafford', 'Department of Genome Sciences, University of Washington, Seattle, Washington, United States of America.|Department of Genome Sciences, University of Washington, Seattle, Washington, United States of America.|Department of Genome Sciences, University of Washington, Seattle, Washington, United States of America.|Department of Genome Sciences, University of Washington, Seattle, Washington, United States of America.|Department of Genome Sciences, University of Washington, Seattle, Washington, United States of America.|Department of Genome Sciences, University of Washington, Seattle, Washington, United States of America.', 'United States|United States|United States|United States|United States|United States', 84, 'Base Sequence|DNA Footprinting|Genome, Human|Humans|Models, Molecular|Nucleic Acid Conformation|Nucleosomes|Pattern Recognition, Automated|Saccharomyces cerevisiae|Software', 'Journal Article', '10.1371/journal.pcbi.1000134', '18725940', 'Nucleosomes are the fundamental repeating unit of chromatin and comprise the structural building blocks of the living eukaryotic genome. Micrococcal nuclease (MNase) has long been used to delineate nucleosomal organization. Microarray-based nucleosome mapping experiments in yeast chromatin have revealed regularly-spaced translational phasing of nucleosomes. These data have been used to train computational models of sequence-directed nuclesosome positioning, which have identified ubiquitous strong intrinsic nucleosome positioning signals. Here, we successfully apply this approach to nucleosome positioning experiments from human chromatin. The predictions made by the human-trained and yeast-trained models are strongly correlated, suggesting a shared mechanism for sequence-based determination of nucleosome occupancy. In addition, we observed striking complementarity between classifiers trained on experimental data from weakly versus heavily digested MNase samples. In the former case, the resulting model accurately identifies nucleosome-forming sequences, in the latter, the classifier excels at identifying nucleosome-free regions. Using this model we are able to identify several characteristics of nucleosome-forming and nucleosome-disfavoring sequences. First, by combining results from each classifier applied de novo across the human ENCODE regions, the classifier reveals distinct sequence composition and periodicity features of nucleosome-forming and nucleosome-disfavoring sequences. Short runs of dinucleotide repeat appear as a hallmark of nucleosome-disfavoring sequences, while nucleosome-forming sequences contain short periodic runs of GC base pairs. Second, we show that nucleosome phasing is most frequently predicted flanking nucleosome-free regions. The results suggest that the major mechanism of nucleosome positioning in vivo is boundary-event-driven and affirm the classical statistical positioning theory of nucleosome organization.'),
(83983, 2008, 'plos', 'Falling towards forgetfulness: synaptic decay prevents spontaneous recovery of memory', 'Stone, James V|Jupp, Peter E', 'Psychology Department, Sheffield University, Sheffield, United Kingdom. j.v.stone@sheffield.ac.uk|Psychology Department, Sheffield University, Sheffield, United Kingdom. j.v.stone@sheffield.ac.uk', 'United Kingdom|United Kingdom', 1, 'Association|Biological Evolution|Conditioning (Psychology)|Cues|Generalization, Stimulus|Humans|Memory|Models, Neurological|Neural Networks (Computer)|Neuronal Plasticity|Synaptic Transmission|Systems Theory', 'Journal Article', '10.1371/journal.pcbi.1000143', '18725945', 'Long after a new language has been learned and forgotten, relearning a few words seems to trigger the recall of other words. This free-lunch learning (FLL) effect has been demonstrated both in humans and in neural network models. Specifically, previous work proved that linear networks that learn a set of associations, then partially forget them all, and finally relearn some of the associations, show improved performance on the remaining (i.e., nonrelearned) associations. Here, we prove that relearning forgotten associations decreases performance on nonrelearned associations, an effect we call negative free-lunch learning. The difference between free-lunch learning and the negative free-lunch learning presented here is due to the particular method used to induce forgetting. Specifically, if forgetting is induced by isotropic drifting of weight vectors (i.e., by adding isotropic noise), then free-lunch learning is observed. However, as proved here, if forgetting is induced by weight values that simply decay or fall towards zero, then negative free-lunch learning is observed. From a biological perspective, and assuming that nervous systems are analogous to the networks used here, this suggests that evolution may have selected physiological mechanisms that involve forgetting using a form of synaptic drift rather than synaptic decay, because synaptic drift, but not synaptic decay, yields free-lunch learning.'),
(83984, 2008, 'plos', 'A feature-based approach to modeling protein-DNA interactions', 'Sharon, Eilon|Lubliner, Shai|Segal, Eran', 'Department of Computer Science and Applied Mathematics, Weizmann Institute of Science, Rehovot, Israel.|Department of Computer Science and Applied Mathematics, Weizmann Institute of Science, Rehovot, Israel.|Department of Computer Science and Applied Mathematics, Weizmann Institute of Science, Rehovot, Israel.', 'Israel|Israel|Israel', 68, 'Animals|Artificial Intelligence|Base Sequence|Binding Sites|CCCTC-Binding Factor|Chromatin Immunoprecipitation|DNA|DNA-Binding Proteins|Databases, Genetic|Humans|Mice|Models, Chemical|Models, Genetic|Repressor Proteins|Sequence Analysis, DNA|Software|Transcription Factors', 'Journal Article', '10.1371/journal.pcbi.1000154', '18725950', 'Transcription factor (TF) binding to its DNA target site is a fundamental regulatory interaction. The most common model used to represent TF binding specificities is a position specific scoring matrix (PSSM), which assumes independence between binding positions. However, in many cases, this simplifying assumption does not hold. Here, we present feature motif models (FMMs), a novel probabilistic method for modeling TF-DNA interactions, based on log-linear models. Our approach uses sequence features to represent TF binding specificities, where each feature may span multiple positions. We develop the mathematical formulation of our model and devise an algorithm for learning its structural features from binding site data. We also developed a discriminative motif finder, which discovers de novo FMMs that are enriched in target sets of sequences compared to background sets. We evaluate our approach on synthetic data and on the widely used TF chromatin immunoprecipitation (ChIP) dataset of Harbison et al. We then apply our algorithm to high-throughput TF ChIP data from mouse and human, reveal sequence features that are present in the binding specificities of mouse and human TFs, and show that FMMs explain TF binding significantly better than PSSMs. Our FMM learning and motif finder software are available at http://genie.weizmann.ac.il/.'),
(83985, 2008, 'plos', 'Self containment, a property of modular RNA structures, distinguishes microRNAs', 'Lee, Miler T|Kim, Junhyong', 'Genomics and Computational Biology Program, University of Pennsylvania School of Medicine, Philadelphia, Pennsylvania, United States of America.|Genomics and Computational Biology Program, University of Pennsylvania School of Medicine, Philadelphia, Pennsylvania, United States of America.', 'United States|United States', 0, 'Animals|Base Sequence|Chromosome Mapping|Computational Biology|Conserved Sequence|Databases, Genetic|Evolution, Molecular|Humans|MicroRNAs|Nucleic Acid Conformation|Nucleic Acid Hybridization|Thermodynamics', 'Journal Article', '10.1371/journal.pcbi.1000150', '18725951', 'RNA molecules will tend to adopt a folded conformation through the pairing of bases on a single strand, the resulting so-called secondary structure is critical to the function of many types of RNA. The secondary structure of a particular substring of functional RNA may depend on its surrounding sequence. Yet, some RNAs such as microRNAs retain their specific structures during biogenesis, which involves extraction of the substructure from a larger structural context, while other functional RNAs may be composed of a fusion of independent substructures. Such observations raise the question of whether particular functional RNA substructures may be selected for invariance of secondary structure to their surrounding nucleotide context. We define the property of self containment to be the tendency for an RNA sequence to robustly adopt the same optimal secondary structure regardless of whether it exists in isolation or is a substring of a longer sequence of arbitrary nucleotide content. We measured degree of self containment using a scoring method we call the self-containment index and found that miRNA stem loops exhibit high self containment, consistent with the requirement for structural invariance imposed by the miRNA biogenesis pathway, while most other structured RNAs do not. Further analysis revealed a trend toward higher self containment among clustered and conserved miRNAs, suggesting that high self containment may be a characteristic of novel miRNAs acquiring new genomic contexts. We found that miRNAs display significantly enhanced self containment compared to other functional RNAs, but we also found a trend toward natural selection for self containment in most functional RNA classes. We suggest that self containment arises out of selection for robustness against perturbations, invariance during biogenesis, and modular composition of structural function. Analysis of self containment will be important for both annotation and design of functional RNAs. A Python implementation and Web interface to calculate the self-containment index are available at http://kim.bio.upenn.edu/software/.'),
(83986, 2008, 'plos', 'Mean-fields and neural masses', 'Friston, Karl', 'Genomics and Computational Biology Program, University of Pennsylvania School of Medicine, Philadelphia, Pennsylvania, United States of America.', 'United States', 4, 'Biomedical Research|Computational Biology|Models, Neurological|Nerve Net|Terminology as Topic|Thermodynamics', 'Comment', '10.1371/journal.pcbi.1000081', '18769501', '-'),
(83987, 2008, 'plos', 'Genome-scale computational biology and bioinformatics in Australia', 'Ragan, Mark A|Littlejohn, Tim|Ross, Bruce', 'Australian Research Council Centre of Excellence in Bioinformatics, Institute for Molecular Bioscience, The University of Queensland, Brisbane, Australia. m.ragan@imb.uq.edu.au|Australian Research Council Centre of Excellence in Bioinformatics, Institute for Molecular Bioscience, The University of Queensland, Brisbane, Australia. m.ragan@imb.uq.edu.au|Australian Research Council Centre of Excellence in Bioinformatics, Institute for Molecular Bioscience, The University of Queensland, Brisbane, Australia. m.ragan@imb.uq.edu.au', 'Australia|Australia|Australia', 0, 'Australia|Cell Proliferation|Computational Biology|Diffusion of Innovation|Genomics|Research Support as Topic', 'Journal Article', '10.1371/journal.pcbi.1000068', '18769502', '-'),
(83988, 2008, 'plos', 'Stroke rehabilitation reaches a threshold', 'Han, Cheol E|Arbib, Michael A|Schweighofer, Nicolas', 'Department of Computer Science, University of Southern California, Los Angeles, California, United States of America.|Department of Computer Science, University of Southern California, Los Angeles, California, United States of America.|Department of Computer Science, University of Southern California, Los Angeles, California, United States of America.', 'United States|United States|United States', 95, 'Activities of Daily Living|Animals|Arm|Decision Making|Differential Threshold|Feedback, Psychological|Functional Laterality|Hand|Hemiplegia|Humans|Learning|Models, Neurological|Motion Therapy, Continuous Passive|Motivation|Motor Activity|Motor Skills|Nerve Net|Neuronal Plasticity|Nonlinear Dynamics|Practice (Psychology)|Recovery of Function|Reinforcement (Psychology)|Stroke|Stroke Rehabilitation', 'Journal Article', '10.1371/journal.pcbi.1000133', '18769588', 'Motor training with the upper limb affected by stroke partially reverses the loss of cortical representation after lesion and has been proposed to increase spontaneous arm use. Moreover, repeated attempts to use the affected hand in daily activities create a form of practice that can potentially lead to further improvement in motor performance. We thus hypothesized that if motor retraining after stroke increases spontaneous arm use sufficiently, then the patient will enter a virtuous circle in which spontaneous arm use and motor performance reinforce each other. In contrast, if the dose of therapy is not sufficient to bring spontaneous use above threshold, then performance will not increase and the patient will further develop compensatory strategies with the less affected hand. To refine this hypothesis, we developed a computational model of bilateral hand use in arm reaching to study the interactions between adaptive decision making and motor relearning after motor cortex lesion. The model contains a left and a right motor cortex, each controlling the opposite arm, and a single action choice module. The action choice module learns, via reinforcement learning, the value of using each arm for reaching in specific directions. Each motor cortex uses a neural population code to specify the initial direction along which the contralateral hand moves towards a target. The motor cortex learns to minimize directional errors and to maximize neuronal activity for each movement. The derived learning rule accounts for the reversal of the loss of cortical representation after rehabilitation and the increase of this loss after stroke with insufficient rehabilitation. Further, our model exhibits nonlinear and bistable behavior: if natural recovery, motor training, or both, brings performance above a certain threshold, then training can be stopped, as the repeated spontaneous arm use provides a form of motor learning that further bootstraps performance and spontaneous use. Below this threshold, motor training is in vain: there is little spontaneous arm use after training, the model exhibits learned nonuse, and compensatory movements with the less affected hand are reinforced. By exploring the nonlinear dynamics of stroke recovery using a biologically plausible neural model that accounts for reversal of the loss of motor cortex representation following rehabilitation or the lack thereof, respectively, we can explain previously hard to reconcile data on spontaneous arm use in stroke recovery. Further, our threshold prediction could be tested with an adaptive train-wait-train paradigm: if spontaneous arm use has increased in the wait period, then the threshold has been reached, and rehabilitation can be stopped. If spontaneous arm use is still low or has decreased, then another bout of rehabilitation is to be provided.'),
(83989, 2008, 'plos', 'Probing the extent of randomness in protein interaction networks', 'Ivanic, Joseph|Wallqvist, Anders|Reifman, Jaques', 'Biotechnology HPC Software Applications Institute, Telemedicine and Advanced Technology Research Center, US Army Medical Research and Materiel Command, Ft Detrick, Maryland, United States of America.|Biotechnology HPC Software Applications Institute, Telemedicine and Advanced Technology Research Center, US Army Medical Research and Materiel Command, Ft Detrick, Maryland, United States of America.|Biotechnology HPC Software Applications Institute, Telemedicine and Advanced Technology Research Center, US Army Medical Research and Materiel Command, Ft Detrick, Maryland, United States of America.', 'United States|United States|United States', 11, 'Molecular Probes|Protein Binding|Proteins', 'Journal Article', '10.1371/journal.pcbi.1000114', '18769589', 'Protein-protein interaction (PPI) networks are commonly explored for the identification of distinctive biological traits, such as pathways, modules, and functional motifs. In this respect, understanding the underlying network structure is vital to assess the significance of any discovered features. We recently demonstrated that PPI networks show degree-weighted behavior, whereby the probability of interaction between two proteins is generally proportional to the product of their numbers of interacting partners or degrees. It was surmised that degree-weighted behavior is a characteristic of randomness. We expand upon these findings by developing a random, degree-weighted, network model and show that eight PPI networks determined from single high-throughput (HT) experiments have global and local properties that are consistent with this model. The apparent random connectivity in HT PPI networks is counter-intuitive with respect to their observed degree distributions, however, we resolve this discrepancy by introducing a non-network-based model for the evolution of protein degrees or binding affinities. This mechanism is based on duplication and random mutation, for which the degree distribution converges to a steady state that is identical to one obtained by averaging over the eight HT PPI networks. The results imply that the degrees and connectivities incorporated in HT PPI networks are characteristic of unbiased interactions between proteins that have varying individual binding affinities. These findings corroborate the observation that curated and high-confidence PPI networks are distinct from HT PPI networks and not consistent with a random connectivity. These results provide an avenue to discern indiscriminate organizations in biological networks and suggest caution in the analysis of curated and high-confidence networks.'),
(83990, 2008, 'plos', 'Cooperative transition between open and closed conformations in potassium channels', 'Haliloglu, Turkan|Ben-Tal, Nir', 'Polymer Research Center, Bogazici University, Bebek-Istanbul, Turkey. turkan@prc.boun.edu.tr|Polymer Research Center, Bogazici University, Bebek-Istanbul, Turkey. turkan@prc.boun.edu.tr', 'Turkey|Turkey', 0, 'Alanine|Bacterial Proteins|Computer Simulation|Crystallography, X-Ray|Energy Transfer|Ion Channel Gating|Methanobacterium|Models, Chemical|Models, Molecular|Motion|Mutagenesis, Site-Directed|Potassium Channels|Potassium Channels, Calcium-Activated|Potassium Channels, Inwardly Rectifying|Protein Interaction Domains and Motifs|Protein Structure, Secondary|Protein Subunits|Streptomyces lividans|Structure-Activity Relationship', 'Journal Article', '10.1371/journal.pcbi.1000164', '18769593', 'Potassium (K+) ion channels switch between open and closed conformations. The nature of this important transition was revealed by comparing the X-ray crystal structures of the MthK channel from Methanobacterium thermoautotrophicum, obtained in its open conformation, and the KcsA channel from Streptomyces lividans, obtained in its closed conformation. We analyzed the dynamic characteristics and energetics of these homotetrameric structures in order to study the role of the intersubunit cooperativity in this transition. For this, elastic models and in silico alanine-scanning mutagenesis were used, respectively. Reassuringly, the calculations manifested motion from the open (closed) towards the closed (open) conformation. The calculations also revealed a network of dynamically and energetically coupled residues. Interestingly, the network suggests coupling between the selectivity filter and the gate, which are located at the two ends of the channel pore. Coupling between these two regions was not observed in calculations that were conducted with the monomer, which emphasizes the importance of the intersubunit interactions within the tetrameric structure for the cooperative gating behavior of the channel.'),
(83991, 2008, 'plos', 'Getting started in computational immunology', 'Kleinstein, Steven H', 'Interdepartmental Program in Computational Biology and Bioinformatics, and Department of Pathology, Yale University School of Medicine, New Haven, Connecticut, United States of America. steven.kleinstein@yale.edu', 'United States', 0, 'Adaptation, Biological|Animals|Antibody Affinity|B-Lymphocytes|Computational Biology|Germ-Line Mutation|Humans|Mutagenesis|Recombination, Genetic', 'Journal Article', '10.1371/journal.pcbi.1000128', '18769677', '-'),
(83992, 2008, 'plos', 'The dynamic brain: from spiking neurons to neural masses and cortical fields', 'Deco, Gustavo|Jirsa, Viktor K|Robinson, Peter A|Breakspear, Michael|Friston, Karl', 'Institució Catalana de Recerca i Estudis Avançats (ICREA), Universitat Pompeu Fabra, Department of Technology, Computational Neuroscience, Barcelona, Spain. Gustavo.Deco@upf.edu|Institució Catalana de Recerca i Estudis Avançats (ICREA), Universitat Pompeu Fabra, Department of Technology, Computational Neuroscience, Barcelona, Spain. Gustavo.Deco@upf.edu|Institució Catalana de Recerca i Estudis Avançats (ICREA), Universitat Pompeu Fabra, Department of Technology, Computational Neuroscience, Barcelona, Spain. Gustavo.Deco@upf.edu|Institució Catalana de Recerca i Estudis Avançats (ICREA), Universitat Pompeu Fabra, Department of Technology, Computational Neuroscience, Barcelona, Spain. Gustavo.Deco@upf.edu|Institució Catalana de Recerca i Estudis Avançats (ICREA), Universitat Pompeu Fabra, Department of Technology, Computational Neuroscience, Barcelona, Spain. Gustavo.Deco@upf.edu', 'Spain|Spain|Spain|Spain|Spain', 524, 'Animals|Biomedical Research|Cerebral Cortex|Computational Biology|Electrophysiology|Empirical Research|Humans|Models, Neurological|Nerve Net|Neurons|Nonlinear Dynamics|Terminology as Topic|Thermodynamics', 'Journal Article', '10.1371/journal.pcbi.1000092', '18769680', 'The cortex is a complex system, characterized by its dynamics and architecture, which underlie many functions such as action, perception, learning, language, and cognition. Its structural architecture has been studied for more than a hundred years, however, its dynamics have been addressed much less thoroughly. In this paper, we review and integrate, in a unifying framework, a variety of computational approaches that have been used to characterize the dynamics of the cortex, as evidenced at different levels of measurement. Computational models at different space-time scales help us understand the fundamental mechanisms that underpin neural processes and relate these processes to neuroscience data. Modeling at the single neuron level is necessary because this is the level at which information is exchanged between the computing elements of the brain, the neurons. Mesoscopic models tell us how neural elements interact to yield emergent behavior at the level of microcolumns and cortical columns. Macroscopic models can inform us about whole brain dynamics and interactions between large-scale neural systems such as cortical regions, the thalamus, and brain stem. Each level of description relates uniquely to neuroscience data, from single-unit recordings, through local field potentials to functional magnetic resonance imaging (fMRI), electroencephalogram (EEG), and magnetoencephalogram (MEG). Models of the cortex can establish which types of large-scale neuronal networks can perform computations and characterize their emergent properties. Mean-field and related formulations of dynamics also play an essential and complementary role as forward models that can be inverted given empirical data. This makes dynamic models critical in integrating theory and experiments. We argue that elaborating principled and informed models is a prerequisite for grounding empirical neuroscience in a cogent theoretical framework, commensurate with the achievements in the physical sciences.');
INSERT INTO `papers` (`id`, `ano`, `journal`, `titulo`, `autores`, `afiliacao`, `pais`, `citacoes`, `palavra_chave`, `categorias`, `doi`, `pubmed`, `abstract`) VALUES
(83993, 2008, 'plos', 'Noise reduction by diffusional dissipation in a minimal quorum sensing motif', 'Tanouchi, Yu|Tu, Dennis|Kim, Jungsang|You, Lingchong', 'Department of Biomedical Engineering, Duke University, Durham, North Carolina, United States of America.|Department of Biomedical Engineering, Duke University, Durham, North Carolina, United States of America.|Department of Biomedical Engineering, Duke University, Durham, North Carolina, United States of America.|Department of Biomedical Engineering, Duke University, Durham, North Carolina, United States of America.', 'United States|United States|United States|United States', 0, 'Diffusion|Down-Regulation|Feedback, Physiological|Gene Expression|Gene Expression Regulation, Bacterial|Gram-Negative Bacteria|Kinetics|Models, Biological|Quorum Sensing|Regulatory Elements, Transcriptional|Stochastic Processes', 'Journal Article', '10.1371/journal.pcbi.1000167', '18769706', 'Cellular interactions are subject to random fluctuations (noise) in quantities of interacting molecules. Noise presents a major challenge for the robust function of natural and engineered cellular networks. Past studies have analyzed how noise is regulated at the intracellular level. Cell-cell communication, however, may provide a complementary strategy to achieve robust gene expression by enabling the coupling of a cell with its environment and other cells. To gain insight into this issue, we have examined noise regulation by quorum sensing (QS), a mechanism by which many bacteria communicate through production and sensing of small diffusible signals. Using a stochastic model, we analyze a minimal QS motif in Gram-negative bacteria. Our analysis shows that diffusion of the QS signal, together with fast turnover of its transcriptional regulator, attenuates low-frequency components of extrinsic noise. We term this unique mechanism diffusional dissipation to emphasize the importance of fast signal turnover (or dissipation) by diffusion. We further show that this noise attenuation is a property of a more generic regulatory motif, of which QS is an implementation. Our results suggest that, in a QS system, an unstable transcriptional regulator may be favored for regulating expression of costly proteins that generate public goods.'),
(83994, 2008, 'plos', 'Combining structural connectivity and response latencies to model the structure of the visual system', 'Capalbo, Michael|Postma, Eric|Goebel, Rainer', 'Department of Cognitive Neuroscience, University of Maastricht, Maastricht, The Netherlands. M.Capalbo@psychology.unimaas.nl|Department of Cognitive Neuroscience, University of Maastricht, Maastricht, The Netherlands. M.Capalbo@psychology.unimaas.nl|Department of Cognitive Neuroscience, University of Maastricht, Maastricht, The Netherlands. M.Capalbo@psychology.unimaas.nl', 'Netherlands|Netherlands|Netherlands', 13, 'Animals|Basal Ganglia|Databases, Factual|Electrophysiology|Macaca|Models, Neurological|Nerve Net|Reaction Time|Signal Transduction|Systems Biology|Time Factors|Visual Cortex|Visual Pathways', 'Journal Article', '10.1371/journal.pcbi.1000159', '18769707', 'Several approaches exist to ascertain the connectivity of the brain, and these approaches lead to markedly different topologies, often incompatible with each other. Specifically, recent single-cell recording results seem incompatible with current structural connectivity models. We present a novel method that combines anatomical and temporal constraints to generate biologically plausible connectivity patterns of the visual system of the macaque monkey. Our method takes structural connectivity data from the CoCoMac database and recent single-cell recording data as input and employs an optimization technique to arrive at a new connectivity pattern of the visual system that is in agreement with both types of experimental data. The new connectivity pattern yields a revised model that has fewer levels than current models. In addition, it introduces subcortical-cortical connections. We show that these connections are essential for explaining latency data, are consistent with our current knowledge of the structural connectivity of the visual system, and might explain recent functional imaging results in humans. Furthermore we show that the revised model is not underconstrained like previous models and can be extended to include newer data and other kinds of data. We conclude that the revised model of the connectivity of the visual system reflects current knowledge on the structure and function of the visual system and addresses some of the limitations of previous models.'),
(83995, 2008, 'plos', 'Inference of protein complex activities from chemical-genetic profile and its applications: predicting drug-target pathways', 'Han, Sangjo|Kim, Dongsup', 'Department of Bio and Brain Engineering, KAIST, Daejeon, South Korea.|Department of Bio and Brain Engineering, KAIST, Daejeon, South Korea.', '-|-', 0, 'Bayes Theorem|Biological Factors|Biotechnology|Drug Design|Drug Evaluation, Preclinical|Fungal Proteins|Gene Deletion|Genome, Fungal|Multiprotein Complexes|Organisms, Genetically Modified|Pharmaceutical Preparations|Pharmacogenetics|Phenotype|Phosphatidylinositol 3-Kinases|Protein Interaction Mapping|Saccharomyces cerevisiae|Saccharomyces cerevisiae Proteins|Sirolimus', 'Journal Article', '10.1371/journal.pcbi.1000162', '18769708', 'The chemical-genetic profile can be defined as quantitative values of deletion strains growth defects under exposure to chemicals. In yeast, the compendium of chemical-genetic profiles of genomewide deletion strains under many different chemicals has been used for identifying direct target proteins and a common mode-of-action of those chemicals. In the previous study, valuable biological information such as protein-protein and genetic interactions has not been fully utilized. In our study, we integrated this compendium and biological interactions into the comprehensive collection of approximately 490 protein complexes of yeast for model-based prediction of a drugs target proteins and similar drugs. We assumed that those protein complexes (PCs) were functional units for yeast cell growth and regarded them as hidden factors and developed the PC-based Bayesian factor model that relates the chemical-genetic profile at the level of organism phenotypes to the hidden activities of PCs at the molecular level. The inferred PC activities provided the predictive power of a common mode-of-action of drugs as well as grouping of PCs with similar functions. In addition, our PC-based model allowed us to develop a new effective method to predict a drugs target pathway, by which we were able to highlight the target-protein, TOR1, of rapamycin. Our study is the first approach to model phenotypes of systematic deletion strains in terms of protein complexes. We believe that our PC-based approach can provide an appropriate framework for combining and modeling several types of chemical-genetic profiles including interspecies. Such efforts will contribute to predicting more precisely relevant pathways including target proteins that interact directly with bioactive compounds.'),
(83996, 2008, 'plos', 'Biophysical parameters modification could overcome essential hearing gaps', 'Kern, A|Heid, C|Steeb, W-H|Stoop, N|Stoop, R', 'Institute of Neuroinformatics, University and Swiss Federal Institute of Technology Zurich, Zürich, Switzerland.|Institute of Neuroinformatics, University and Swiss Federal Institute of Technology Zurich, Zürich, Switzerland.|Institute of Neuroinformatics, University and Swiss Federal Institute of Technology Zurich, Zürich, Switzerland.|Institute of Neuroinformatics, University and Swiss Federal Institute of Technology Zurich, Zürich, Switzerland.|Institute of Neuroinformatics, University and Swiss Federal Institute of Technology Zurich, Zürich, Switzerland.', 'Switzerland|Switzerland|Switzerland|Switzerland|Switzerland', 0, 'Acoustic Stimulation|Animals|Auditory Pathways|Auditory Perception|Auditory Threshold|Cochlea|Energy Transfer|Hearing Disorders|Humans|Models, Biological|Signal Transduction', 'Journal Article', '10.1371/journal.pcbi.1000161', '18769713', 'A majority of hearing defects are due to malfunction of the outer hair cells (OHCs), those cells within the mammalian hearing sensor (the cochlea) that provide an active amplification of the incoming signal. Malformation of the hearing sensor, ototoxic drugs, acoustical trauma, infections, or the effect of aging affect often a whole frequency interval, which leads to a substantial loss of speech intelligibility. Using an energy-based biophysical model of the passive cochlea, we obtain an explicit description of the dependence of the tonotopic map on the biophysical parameters of the cochlea. Our findings indicate the possibility that by suitable local modifications of the biophysical parameters by microsurgery, even very salient gaps of the tonotopic map could be bridged.'),
(83997, 2008, 'plos', 'Network inference algorithms elucidate Nrf2 regulation of mouse lung oxidative stress', 'Taylor, Ronald C|Acquaah-Mensah, George|Singhal, Mudita|Malhotra, Deepti|Biswal, Shyam', 'Computational Biology and Bioinformatics Group, Pacific Northwest National Laboratory, U.S. Department of Energy, Richland, Washington, United States of America. ronald.taylor24@gmail.com|Computational Biology and Bioinformatics Group, Pacific Northwest National Laboratory, U.S. Department of Energy, Richland, Washington, United States of America. ronald.taylor24@gmail.com|Computational Biology and Bioinformatics Group, Pacific Northwest National Laboratory, U.S. Department of Energy, Richland, Washington, United States of America. ronald.taylor24@gmail.com|Computational Biology and Bioinformatics Group, Pacific Northwest National Laboratory, U.S. Department of Energy, Richland, Washington, United States of America. ronald.taylor24@gmail.com|Computational Biology and Bioinformatics Group, Pacific Northwest National Laboratory, U.S. Department of Energy, Richland, Washington, United States of America. ronald.taylor24@gmail.com', 'United States|United States|United States|United States|United States', 0, 'Algorithms|Animals|Artificial Intelligence|Gene Expression Profiling|Gene Regulatory Networks|Guanine Nucleotide Exchange Factors|Lung|Mice|Mice, Knockout|NF-E2-Related Factor 2|Oligonucleotide Array Sequence Analysis|Oxidative Stress|Oxidoreductases Acting on Sulfur Group Donors|Promoter Regions, Genetic|Signal Transduction|Smoking|Software|Transcription, Genetic', 'Journal Article', '10.1371/journal.pcbi.1000166', '18769717', 'A variety of cardiovascular, neurological, and neoplastic conditions have been associated with oxidative stress, i.e., conditions under which levels of reactive oxygen species (ROS) are elevated over significant periods. Nuclear factor erythroid 2-related factor (Nrf2) regulates the transcription of several gene products involved in the protective response to oxidative stress. The transcriptional regulatory and signaling relationships linking gene products involved in the response to oxidative stress are, currently, only partially resolved. Microarray data constitute RNA abundance measures representing gene expression patterns. In some cases, these patterns can identify the molecular interactions of gene products. They can be, in effect, proxies for protein-protein and protein-DNA interactions. Traditional techniques used for clustering coregulated genes on high-throughput gene arrays are rarely capable of distinguishing between direct transcriptional regulatory interactions and indirect ones. In this study, newly developed information-theoretic algorithms that employ the concept of mutual information were used: the Algorithm for the Reconstruction of Accurate Cellular Networks (ARACNE), and Context Likelihood of Relatedness (CLR). These algorithms captured dependencies in the gene expression profiles of the mouse lung, allowing the regulatory effect of Nrf2 in response to oxidative stress to be determined more precisely. In addition, a characterization of promoter sequences of Nrf2 regulatory targets was conducted using a Support Vector Machine classification algorithm to corroborate ARACNE and CLR predictions. Inferred networks were analyzed, compared, and integrated using the Collective Analysis of Biological Interaction Networks (CABIN) plug-in of Cytoscape. Using the two network inference algorithms and one machine learning algorithm, a number of both previously known and novel targets of Nrf2 transcriptional activation were identified. Genes predicted as novel Nrf2 targets include Atf1, Srxn1, Prnp, Sod2, Als2, Nfkbib, and Ppp1r15b. Furthermore, microarray and quantitative RT-PCR experiments following cigarette-smoke-induced oxidative stress in Nrf2(+/+) and Nrf2(-/-) mouse lung affirmed many of the predictions made. Several new potential feed-forward regulatory loops involving Nrf2, Nqo1, Srxn1, Prdx1, Als2, Atf1, Sod1, and Park7 were predicted. This work shows the promise of network inference algorithms operating on high-throughput gene expression data in identifying transcriptional regulatory and other signaling relationships implicated in mammalian disease.'),
(83998, 2008, 'plos', 'Nonlinear muscles, passive viscoelasticity and body taper conspire to create neuromechanical phase lags in anguilliform swimmers', 'McMillen, T|Williams, T|Holmes, P', 'Department of Mathematics, California State University Fullerton, Fullerton, California, United States of America. tmcmillen@fullerton.edu|Department of Mathematics, California State University Fullerton, Fullerton, California, United States of America. tmcmillen@fullerton.edu|Department of Mathematics, California State University Fullerton, Fullerton, California, United States of America. tmcmillen@fullerton.edu', 'United States|United States|United States', 41, 'Animals|Calcium Signaling|Connective Tissue|Elasticity|Electromyography|Energy Transfer|Lampreys|Models, Biological|Muscle Contraction|Muscle Fibers, Skeletal|Muscle, Skeletal|Nonlinear Dynamics|Swimming|Systems Biology|Time Factors|Viscosity', 'Journal Article', '10.1371/journal.pcbi.1000157', '18769734', 'Locomotion provides superb examples of cooperation among neuromuscular systems, environmental reaction forces, and sensory feedback. As part of a program to understand the neuromechanics of locomotion, here we construct a model of anguilliform (eel-like) swimming in slender fishes. Building on a continuum mechanical representation of the body as an viscoelastic rod, actuated by a traveling wave of preferred curvature and subject to hydrodynamic reaction forces, we incorporate a new version of a calcium release and muscle force model, fitted to data from the lamprey Ichthyomyzon unicuspis, that interactively generates the curvature wave. We use the model to investigate the source of the difference in speeds observed between electromyographic waves of muscle activation and mechanical waves of body curvature, concluding that it is due to a combination of passive viscoelastic and geometric properties of the body and active muscle properties. Moreover, we find that nonlinear force dependence on muscle length and shortening velocity may reduce the work done by the swimming muscles in steady swimming.'),
(83999, 2008, 'plos', 'PhyloGibbs-MP: module prediction and discriminative motif-finding by Gibbs sampling', 'Siddharthan, Rahul', 'The Institute of Mathematical Sciences, Chennai, India. rsidd@imsc.res.in', 'India', 0, 'Animals|Binding Sites|Consensus Sequence|DNA|DNA-Binding Proteins|Drosophila melanogaster|Gene Expression Regulation|Genomics|Nucleic Acid Conformation|Phylogeny|Regulatory Elements, Transcriptional|Saccharomyces cerevisiae|Sequence Homology, Nucleic Acid|Software|Structure-Activity Relationship|Transcription Factors', 'Journal Article', '10.1371/journal.pcbi.1000156', '18769735', 'PhyloGibbs, our recent Gibbs-sampling motif-finder, takes phylogeny into account in detecting binding sites for transcription factors in DNA and assigns posterior probabilities to its predictions obtained by sampling the entire configuration space. Here, in an extension called PhyloGibbs-MP, we widen the scope of the program, addressing two major problems in computational regulatory genomics. First, PhyloGibbs-MP can localise predictions to small, undetermined regions of a large input sequence, thus effectively predicting cis-regulatory modules (CRMs) ab initio while simultaneously predicting binding sites in those modules-tasks that are usually done by two separate programs. PhyloGibbs-MPs performance at such ab initio CRM prediction is comparable with or superior to dedicated module-prediction software that use prior knowledge of previously characterised transcription factors. Second, PhyloGibbs-MP can predict motifs that differentiate between two (or more) different groups of regulatory regions, that is, motifs that occur preferentially in one group over the others. While other discriminative motif-finders have been published in the literature, PhyloGibbs-MPs implementation has some unique features and flexibility. Benchmarks on synthetic and actual genomic data show that this algorithm is successful at enhancing predictions of differentiating sites and suppressing predictions of common sites and compares with or outperforms other discriminative motif-finders on actual genomic data. Additional enhancements include significant performance and speed improvements, the ability to use informative priors on known transcription factors, and the ability to output annotations in a format that can be visualised with the Generic Genome Browser. In stand-alone motif-finding, PhyloGibbs-MP remains competitive, outperforming PhyloGibbs-1.0 and other programs on benchmark data.'),
(84000, 2008, 'plos', 'Rhythm generation through period concatenation in rat somatosensory cortex', 'Kramer, Mark A|Roopun, Anita K|Carracedo, Lucy M|Traub, Roger D|Whittington, Miles A|Kopell, Nancy J', 'Department of Mathematics and Statistics, Boston University, Boston, Massachusetts, United States of America. mak@bu.edu|Department of Mathematics and Statistics, Boston University, Boston, Massachusetts, United States of America. mak@bu.edu|Department of Mathematics and Statistics, Boston University, Boston, Massachusetts, United States of America. mak@bu.edu|Department of Mathematics and Statistics, Boston University, Boston, Massachusetts, United States of America. mak@bu.edu|Department of Mathematics and Statistics, Boston University, Boston, Massachusetts, United States of America. mak@bu.edu|Department of Mathematics and Statistics, Boston University, Boston, Massachusetts, United States of America. mak@bu.edu', 'United States|United States|United States|United States|United States|United States', 71, 'Animals|Computational Biology|Electrophysiology|Excitatory Amino Acid Agonists|In Vitro Techniques|Kainic Acid|Male|Models, Neurological|Models, Statistical|Periodicity|Rats|Rats, Wistar|Receptors, N-Methyl-D-Aspartate|Somatosensory Cortex|Time Factors', 'Journal Article', '10.1371/journal.pcbi.1000169', '18773075', 'Rhythmic voltage oscillations resulting from the summed activity of neuronal populations occur in many nervous systems. Contemporary observations suggest that coexistent oscillations interact and, in time, may switch in dominance. We recently reported an example of these interactions recorded from in vitro preparations of rat somatosensory cortex. We found that following an initial interval of coexistent gamma ( approximately 25 ms period) and beta2 ( approximately 40 ms period) rhythms in the superficial and deep cortical layers, respectively, a transition to a synchronous beta1 ( approximately 65 ms period) rhythm in all cortical layers occurred. We proposed that the switch to beta1 activity resulted from the novel mechanism of period concatenation of the faster rhythms: gamma period (25 ms)+beta2 period (40 ms) = beta1 period (65 ms). In this article, we investigate in greater detail the fundamental mechanisms of the beta1 rhythm. To do so we describe additional in vitro experiments that constrain a biologically realistic, yet simplified, computational model of the activity. We use the model to suggest that the dynamic building blocks (or motifs) of the gamma and beta2 rhythms combine to produce a beta1 oscillation that exhibits cross-frequency interactions. Through the combined approach of in vitro experiments and mathematical modeling we isolate the specific components that promote or destroy each rhythm. We propose that mechanisms vital to establishing the beta1 oscillation include strengthened connections between a population of deep layer intrinsically bursting cells and a transition from antidromic to orthodromic spike generation in these cells. We conclude that neural activity in the superficial and deep cortical layers may temporally combine to generate a slower oscillation.'),
(84001, 2008, 'plos', 'Insights into protein-DNA interactions through structure network analysis', 'Sathyapriya, R|Vijayabaskar, M S|Vishveshwara, Saraswathi', 'Molecular Biophysics Unit, Indian Institute of Science, Bangalore, India.|Molecular Biophysics Unit, Indian Institute of Science, Bangalore, India.|Molecular Biophysics Unit, Indian Institute of Science, Bangalore, India.', 'India|India|India', 0, 'Binding Sites|Computational Biology|Computer Graphics|Computer Simulation|DNA|DNA-Binding Proteins|Databases, Nucleic Acid|Databases, Protein|Macromolecular Substances|Models, Molecular|Molecular Structure|Nucleic Acid Conformation|Protein Conformation|Protein Structure, Secondary|Proteins', 'Journal Article', '10.1371/journal.pcbi.1000170', '18773096', 'Protein-DNA interactions are crucial for many cellular processes. Now with the increased availability of structures of protein-DNA complexes, gaining deeper insights into the nature of protein-DNA interactions has become possible. Earlier, investigations have characterized the interface properties by considering pairwise interactions. However, the information communicated along the interfaces is rarely a pairwise phenomenon, and we feel that a global picture can be obtained by considering a protein-DNA complex as a network of noncovalently interacting systems. Furthermore, most of the earlier investigations have been carried out from the protein point of view (protein-centric), and the present network approach aims to combine both the protein-centric and the DNA-centric points of view. Part of the study involves the development of methodology to investigate protein-DNA graphs/networks with the development of key parameters. A network representation provides a holistic view of the interacting surface and has been reported here for the first time. The second part of the study involves the analyses of these graphs in terms of clusters of interacting residues and the identification of highly connected residues (hubs) along the protein-DNA interface. A predominance of deoxyribose-amino acid clusters in beta-sheet proteins, distinction of the interface clusters in helix-turn-helix, and the zipper-type proteins would not have been possible by conventional pairwise interaction analysis. Additionally, we propose a potential classification scheme for a set of protein-DNA complexes on the basis of the protein-DNA interface clusters. This provides a general idea of how the proteins interact with the different components of DNA in different complexes. Thus, we believe that the present graph-based method provides a deeper insight into the analysis of the protein-DNA recognition mechanisms by throwing more light on the nature and the specificity of these interactions.'),
(84002, 2008, 'plos', 'Top-down analysis of temporal hierarchy in biochemical reaction networks', '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.', 'United States|United States', 46, 'Algorithms|Biochemical Phenomena|Biochemistry|Computational Biology|Computer Simulation|Erythrocytes|Folic Acid|Glycolysis|Humans|Kinetics|Metabolic Networks and Pathways|Models, Biological|Saccharomyces cerevisiae|Thermodynamics', 'Journal Article', '10.1371/journal.pcbi.1000177', '18787685', 'The study of dynamic functions of large-scale biological networks has intensified in recent years. A critical component in developing an understanding of such dynamics involves the study of their hierarchical organization. We investigate the temporal hierarchy in biochemical reaction networks focusing on: (1) the elucidation of the existence of pools (i.e., aggregate variables) formed from component concentrations and (2) the determination of their composition and interactions over different time scales. To date the identification of such pools without prior knowledge of their composition has been a challenge. A new approach is developed for the algorithmic identification of pool formation using correlations between elements of the modal matrix that correspond to a pair of concentrations and how such correlations form over the hierarchy of time scales. The analysis elucidates a temporal hierarchy of events that range from chemical equilibration events to the formation of physiologically meaningful pools, culminating in a network-scale (dynamic) structure-(physiological) function relationship. This method is validated on a model of human red blood cell metabolism and further applied to kinetic models of yeast glycolysis and human folate metabolism, enabling the simplification of these models. The understanding of temporal hierarchy and the formation of dynamic aggregates on different time scales is foundational to the study of network dynamics and has relevance in multiple areas ranging from bacterial strain design and metabolic engineering to the understanding of disease processes in humans.'),
(84003, 2008, 'plos', 'Sizing up allometric scaling theory', 'Savage, Van M|Deeds, Eric J|Fontana, Walter', 'Department of Systems Biology, Harvard Medical School, Boston, Massachusetts, United States of America.|Department of Systems Biology, Harvard Medical School, Boston, Massachusetts, United States of America.|Department of Systems Biology, Harvard Medical School, Boston, Massachusetts, United States of America.', 'United States|United States|United States', 142, 'Animals|Blood Flow Velocity|Body Size|Capillaries|Computational Biology|Computer Simulation|Databases, Factual|Mammals|Mathematics|Metabolism|Models, Biological|Oxygen', 'Journal Article', '10.1371/journal.pcbi.1000171', '18787686', 'Metabolic rate, heart rate, lifespan, and many other physiological properties vary with body mass in systematic and interrelated ways. Present empirical data suggest that these scaling relationships take the form of power laws with exponents that are simple multiples of one quarter. A compelling explanation of this observation was put forward a decade ago by West, Brown, and Enquist (WBE). Their framework elucidates the link between metabolic rate and body mass by focusing on the dynamics and structure of resource distribution networks-the cardiovascular system in the case of mammals. Within this framework the WBE model is based on eight assumptions from which it derives the well-known observed scaling exponent of 3/4. In this paper we clarify that this result only holds in the limit of infinite network size (body mass) and that the actual exponent predicted by the model depends on the sizes of the organisms being studied. Failure to clarify and to explore the nature of this approximation has led to debates about the WBE model that were at cross purposes. We compute analytical expressions for the finite-size corrections to the 3/4 exponent, resulting in a spectrum of scaling exponents as a function of absolute network size. When accounting for these corrections over a size range spanning the eight orders of magnitude observed in mammals, the WBE model predicts a scaling exponent of 0.81, seemingly at odds with data. We then proceed to study the sensitivity of the scaling exponent with respect to variations in several assumptions that underlie the WBE model, always in the context of finite-size corrections. Here too, the trends we derive from the model seem at odds with trends detectable in empirical data. Our work illustrates the utility of the WBE framework in reasoning about allometric scaling, while at the same time suggesting that the current canonical model may need amendments to bring its predictions fully in line with available datasets.'),
(84004, 2008, 'plos', 'Identifying cognate binding pairs among a large set of paralogs: the case of PE/PPE proteins of Mycobacterium tuberculosis', 'Riley, Robert|Pellegrini, Matteo|Eisenberg, David', 'Department of Human Genetics, David Geffen School of Medicine, University of California Los Angeles, Los Angeles, California, United States of America.|Department of Human Genetics, David Geffen School of Medicine, University of California Los Angeles, Los Angeles, California, United States of America.|Department of Human Genetics, David Geffen School of Medicine, University of California Los Angeles, Los Angeles, California, United States of America.', 'United States|United States|United States', 0, 'Bacterial Proteins|Binding Sites|Computational Biology|Computer Simulation|Escherichia coli|Evolution, Molecular|Gene Expression|Genome, Bacterial|Models, Genetic|Multiprotein Complexes|Mycobacterium tuberculosis|Operon|Phylogeny|Protein Binding|Protein Interaction Domains and Motifs|Protein Interaction Mapping|RNA, Bacterial|RNA, Messenger', 'Journal Article', '10.1371/journal.pcbi.1000174', '18787688', 'We consider the problem of how to detect cognate pairs of proteins that bind when each belongs to a large family of paralogs. To illustrate the problem, we have undertaken a genomewide analysis of interactions of members of the PE and PPE protein families of Mycobacterium tuberculosis. Our computational method uses structural information, operon organization, and protein coevolution to infer the interaction of PE and PPE proteins. Some 289 PE/PPE complexes were predicted out of a possible 5,590 PE/PPE pairs genomewide. Thirty-five of these predicted complexes were also found to have correlated mRNA expression, providing additional evidence for these interactions. We show that our method is applicable to other protein families, by analyzing interactions of the Esx family of proteins. Our resulting set of predictions is a starting point for genomewide experimental interaction screens of the PE and PPE families, and our method may be generally useful for detecting interactions of proteins within families having many paralogs.'),
(84005, 2008, 'plos', 'Identifying the important HIV-1 recombination breakpoints', 'Archer, John|Pinney, John W|Fan, Jun|Simon-Loriere, Etienne|Arts, Eric J|Negroni, Matteo|Robertson, David L', 'Faculty of Life Sciences, University of Manchester, Manchester, United Kingdom.|Faculty of Life Sciences, University of Manchester, Manchester, United Kingdom.|Faculty of Life Sciences, University of Manchester, Manchester, United Kingdom.|Faculty of Life Sciences, University of Manchester, Manchester, United Kingdom.|Faculty of Life Sciences, University of Manchester, Manchester, United Kingdom.|Faculty of Life Sciences, University of Manchester, Manchester, United Kingdom.|Faculty of Life Sciences, University of Manchester, Manchester, United Kingdom.', 'United Kingdom|United Kingdom|United Kingdom|United Kingdom|United Kingdom|United Kingdom|United Kin', 0, 'Computational Biology|Evolution, Molecular|Genes, env|Genetic Variation|Genome, Viral|HIV Infections|HIV-1|Humans|Models, Genetic|Models, Statistical|RNA, Viral|Recombination, Genetic', 'Journal Article', '10.1371/journal.pcbi.1000178', '18787691', 'Recombinant HIV-1 genomes contribute significantly to the diversity of variants within the HIV/AIDS pandemic. It is assumed that some of these mosaic genomes may have novel properties that have led to their prevalence, particularly in the case of the circulating recombinant forms (CRFs). In regions of the HIV-1 genome where recombination has a tendency to convey a selective advantage to the virus, we predict that the distribution of breakpoints--the identifiable boundaries that delimit the mosaic structure--will deviate from the underlying null distribution. To test this hypothesis, we generate a probabilistic model of HIV-1 copy-choice recombination and compare the predicted breakpoint distribution to the distribution from the HIV/AIDS pandemic. Across much of the HIV-1 genome, we find that the observed frequencies of inter-subtype recombination are predicted accurately by our model. This observation strongly indicates that in these regions a probabilistic model, dependent on local sequence identity, is sufficient to explain breakpoint locations. In regions where there is a significant over- (either side of the env gene) or under- (short regions within gag, pol, and most of env) representation of breakpoints, we infer natural selection to be influencing the recombination pattern. The paucity of recombination breakpoints within most of the envelope gene indicates that recombinants generated in this region are less likely to be successful. The breakpoints at a higher frequency than predicted by our model are approximately at either side of env, indicating increased selection for these recombinants as a consequence of this region, or at least part of it, having a tendency to be recombined as an entire unit. Our findings thus provide the first clear indication of the existence of a specific portion of the genome that deviates from a probabilistic null model for recombination. This suggests that, despite the wide diversity of recombinant forms seen in the viral population, only a minority of recombination events appear to be of significance to the evolution of HIV-1.'),
(84006, 2008, 'plos', 'Preferentially quantized linker DNA lengths in Saccharomyces cerevisiae', 'Wang, Ji-Ping|Fondufe-Mittendorf, Yvonne|Xi, Liqun|Tsai, Guei-Feng|Segal, Eran|Widom, Jonathan', 'Department of Statistics, Northwestern University, Evanston, Illinois, United States of America. jzwang@northwestern.edu|Department of Statistics, Northwestern University, Evanston, Illinois, United States of America. jzwang@northwestern.edu|Department of Statistics, Northwestern University, Evanston, Illinois, United States of America. jzwang@northwestern.edu|Department of Statistics, Northwestern University, Evanston, Illinois, United States of America. jzwang@northwestern.edu|Department of Statistics, Northwestern University, Evanston, Illinois, United States of America. jzwang@northwestern.edu|Department of Statistics, Northwestern University, Evanston, Illinois, United States of America. jzwang@northwestern.edu', 'United States|United States|United States|United States|United States|United States', 0, 'Chromatin|Computational Biology|DNA, Fungal|Fourier Analysis|Genome, Fungal|Markov Chains|Models, Genetic|Nucleosomes|Saccharomyces cerevisiae|Sequence Alignment', 'Journal Article', '10.1371/journal.pcbi.1000175', '18787693', 'The exact lengths of linker DNAs connecting adjacent nucleosomes specify the intrinsic three-dimensional structures of eukaryotic chromatin fibers. Some studies suggest that linker DNA lengths preferentially occur at certain quantized values, differing one from another by integral multiples of the DNA helical repeat, approximately 10 bp, however, studies in the literature are inconsistent. Here, we investigate linker DNA length distributions in the yeast Saccharomyces cerevisiae genome, using two novel methods: a Fourier analysis of genomic dinucleotide periodicities adjacent to experimentally mapped nucleosomes and a duration hidden Markov model applied to experimentally defined dinucleosomes. Both methods reveal that linker DNA lengths in yeast are preferentially periodic at the DNA helical repeat ( approximately 10 bp), obeying the forms 10n+5 bp (integer n). This 10 bp periodicity implies an ordered superhelical intrinsic structure for the average chromatin fiber in yeast.'),
(84007, 2008, 'plos', 'Probabilistic phylogenetic inference with insertions and deletions', 'Rivas, Elena|Eddy, Sean R', 'Janelia Farm Research Campus, Howard Hughes Medical Institute, Ashburn, Virginia, United States of America. rivase@janelia.hhmi.org|Janelia Farm Research Campus, Howard Hughes Medical Institute, Ashburn, Virginia, United States of America. rivase@janelia.hhmi.org', 'United States|United States', 41, 'Algorithms|Computational Biology|Computer Simulation|DNA|Evolution, Molecular|Markov Chains|Models, Genetic|Models, Statistical|Mutagenesis, Insertional|Phylogeny|Poisson Distribution|RNA, Ribosomal|Sequence Alignment|Sequence Deletion|Software', 'Comparative Study', '10.1371/journal.pcbi.1000172', '18787703', 'A fundamental task in sequence analysis is to calculate the probability of a multiple alignment given a phylogenetic tree relating the sequences and an evolutionary model describing how sequences change over time. However, the most widely used phylogenetic models only account for residue substitution events. We describe a probabilistic model of a multiple sequence alignment that accounts for insertion and deletion events in addition to substitutions, given a phylogenetic tree, using a rate matrix augmented by the gap character. Starting from a continuous Markov process, we construct a non-reversible generative (birth-death) evolutionary model for insertions and deletions. The model assumes that insertion and deletion events occur one residue at a time. We apply this model to phylogenetic tree inference by extending the program dnaml in phylip. Using standard benchmarking methods on simulated data and a new concordance test benchmark on real ribosomal RNA alignments, we show that the extended program dnamlepsilon improves accuracy relative to the usual approach of ignoring gaps, while retaining the computational efficiency of the Felsenstein peeling algorithm.'),
(84008, 2008, 'plos', 'ISCB honors David Haussler and Aviv Regev', 'Sansom, Clare|Morrison McKay, B J', 'Birkbeck College, London, United Kingdom.|Birkbeck College, London, United Kingdom.', 'United Kingdom|United Kingdom', 0, 'Awards and Prizes|Computational Biology|History, 21st Century', 'Biography', '10.1371/journal.pcbi.1000101', '18795145', '-'),
(84009, 2008, 'plos', 'Circadian phase resetting via single and multiple control targets', 'Bagheri, Neda|Stelling, Jörg|Doyle, Francis J', 'Department of Electrical and Computer Engineering, University of California Santa Barbara, Santa Barbara, California, USA.|Department of Electrical and Computer Engineering, University of California Santa Barbara, Santa Barbara, California, USA.|Department of Electrical and Computer Engineering, University of California Santa Barbara, Santa Barbara, California, USA.', 'United States|United States|United States', 40, 'Algorithms|Animals|Circadian Rhythm|Drosophila melanogaster|Light', 'Journal Article', '10.1371/journal.pcbi.1000104', '18795146', 'Circadian entrainment is necessary for rhythmic physiological functions to be appropriately timed over the 24-hour day. Disruption of circadian rhythms has been associated with sleep and neuro-behavioral impairments as well as cancer. To date, light is widely accepted to be the most powerful circadian synchronizer, motivating its use as a key control input for phase resetting. Through sensitivity analysis, we identify additional control targets whose individual and simultaneous manipulation (via a model predictive control algorithm) out-perform the open-loop light-based phase recovery dynamics by nearly 3-fold. We further demonstrate the robustness of phase resetting by synchronizing short- and long-period mutant phenotypes to the 24-hour environment, the control algorithm is robust in the presence of model mismatch. These studies prove the efficacy and immediate application of model predictive control in experimental studies and medicine. In particular, maintaining proper circadian regulation may significantly decrease the chance of acquiring chronic illness.'),
(84010, 2008, 'plos', 'A model of stimulus-specific neural assemblies in the insect antennal lobe', 'Martinez, Dominique|Montejo, Noelia', 'LORIA, Campus Scientifique, Vandoeuvre-lès-Nancy, France. dominique.martinez@loria.fr|LORIA, Campus Scientifique, Vandoeuvre-lès-Nancy, France. dominique.martinez@loria.fr', 'France|France', 14, 'Animals|Association|Feedback|Insecta|Kinetics|Models, Neurological|Nerve Net|Neural Inhibition|Olfactory Pathways|Olfactory Receptor Neurons|Pattern Recognition, Physiological|Smell|Synaptic Transmission|Systems Biology|Time Factors|gamma-Aminobutyric Acid', 'Journal Article', '10.1371/journal.pcbi.1000139', '18795147', 'It has been proposed that synchronized neural assemblies in the antennal lobe of insects encode the identity of olfactory stimuli. In response to an odor, some projection neurons exhibit synchronous firing, phase-locked to the oscillations of the field potential, whereas others do not. Experimental data indicate that neural synchronization and field oscillations are induced by fast GABA(A)-type inhibition, but it remains unclear how desynchronization occurs. We hypothesize that slow inhibition plays a key role in desynchronizing projection neurons. Because synaptic noise is believed to be the dominant factor that limits neuronal reliability, we consider a computational model of the antennal lobe in which a population of oscillatory neurons interact through unreliable GABA(A) and GABA(B) inhibitory synapses. From theoretical analysis and extensive computer simulations, we show that transmission failures at slow GABA(B) synapses make the neural response unpredictable. Depending on the balance between GABA(A) and GABA(B) inputs, particular neurons may either synchronize or desynchronize. These findings suggest a wiring scheme that triggers stimulus-specific synchronized assemblies. Inhibitory connections are set by Hebbian learning and selectively activated by stimulus patterns to form a spiking associative memory whose storage capacity is comparable to that of classical binary-coded models. We conclude that fast inhibition acts in concert with slow inhibition to reformat the glomerular input into odor-specific synchronized neural assemblies.'),
(84011, 2008, 'plos', 'Modeling recursive RNA interference', 'Marshall, Wallace F', 'Department of Biochemistry and Biophysics, Integrative Program in Quantitative Biology, University of California San Francisco, San Francisco, California, United States of America. wmarshall@biochem.ucsf.edu', 'United States', 7, 'Computational Biology|Genes, Reporter|Genetic Techniques|Models, Genetic|Nucleic Acid Amplification Techniques|RNA Interference|RNA Replicase|RNA, Small Interfering|Ribonuclease III|Transfection', 'Journal Article', '10.1371/journal.pcbi.1000183', '18802453', 'An important application of the RNA interference (RNAi) pathway is its use as a small RNA-based regulatory system commonly exploited to suppress expression of target genes to test their function in vivo. In several published experiments, RNAi has been used to inactivate components of the RNAi pathway itself, a procedure termed recursive RNAi in this report. The theoretical basis of recursive RNAi is unclear since the procedure could potentially be self-defeating, and in practice the effectiveness of recursive RNAi in published experiments is highly variable. A mathematical model for recursive RNAi was developed and used to investigate the range of conditions under which the procedure should be effective. The model predicts that the effectiveness of recursive RNAi is strongly dependent on the efficacy of RNAi at knocking down target gene expression. This efficacy is known to vary highly between different cell types, and comparison of the model predictions to published experimental data suggests that variation in RNAi efficacy may be the main cause of discrepancies between published recursive RNAi experiments in different organisms. The model suggests potential ways to optimize the effectiveness of recursive RNAi both for screening of RNAi components as well as for improved temporal control of gene expression in switch off-switch on experiments.'),
(84012, 2008, 'plos', 'Contact-inhibited chemotaxis in de novo and sprouting blood-vessel growth', 'Merks, Roeland M H|Perryn, Erica D|Shirinifard, Abbas|Glazier, James A', 'VIB Department of Plant Systems Biology, Ghent, Belgium. post@roelandmerks.nl|VIB Department of Plant Systems Biology, Ghent, Belgium. post@roelandmerks.nl|VIB Department of Plant Systems Biology, Ghent, Belgium. post@roelandmerks.nl|VIB Department of Plant Systems Biology, Ghent, Belgium. post@roelandmerks.nl', 'Belgium|Belgium|Belgium|Belgium', 143, 'Animals|Blood Vessels|Cell Aggregation|Chemotactic Factors|Chemotaxis|Computational Biology|Computer Simulation|Contact Inhibition|Endothelial Cells|Mice|Models, Biological|Neovascularization, Pathologic|Neovascularization, Physiologic|Pseudopodia', 'Journal Article', '10.1371/journal.pcbi.1000163', '18802455', 'Blood vessels form either when dispersed endothelial cells (the cells lining the inner walls of fully formed blood vessels) organize into a vessel network (vasculogenesis), or by sprouting or splitting of existing blood vessels (angiogenesis). Although they are closely related biologically, no current model explains both phenomena with a single biophysical mechanism. Most computational models describe sprouting at the level of the blood vessel, ignoring how cell behavior drives branch splitting during sprouting. We present a cell-based, Glazier-Graner-Hogeweg model (also called Cellular Potts Model) simulation of the initial patterning before the vascular cords form lumens, based on plausible behaviors of endothelial cells. The endothelial cells secrete a chemoattractant, which attracts other endothelial cells. As in the classic Keller-Segel model, chemotaxis by itself causes cells to aggregate into isolated clusters. However, including experimentally observed VE-cadherin-mediated contact inhibition of chemotaxis in the simulation causes randomly distributed cells to organize into networks and cell aggregates to sprout, reproducing aspects of both de novo and sprouting blood-vessel growth. We discuss two branching instabilities responsible for our results. Cells at the surfaces of cell clusters attempting to migrate to the centers of the clusters produce a buckling instability. In a model variant that eliminates the surface-normal force, a dissipative mechanism drives sprouting, with the secreted chemical acting both as a chemoattractant and as an inhibitor of pseudopod extension. Both mechanisms would also apply if force transmission through the extracellular matrix rather than chemical signaling mediated cell-cell interactions. The branching instabilities responsible for our results, which result from contact inhibition of chemotaxis, are both generic developmental mechanisms and interesting examples of unusual patterning instabilities.'),
(84013, 2008, 'plos', 'Advanced genomic data mining', 'Fernández-Suárez, Xosé M|Birney, Ewan', 'European Bioinformatics Institute, Ensembl Group, Wellcome Trust Genome Campus, Hinxton, Cambridge, United Kingdom. xose@ebi.ac.uk|European Bioinformatics Institute, Ensembl Group, Wellcome Trust Genome Campus, Hinxton, Cambridge, United Kingdom. xose@ebi.ac.uk', 'United Kingdom|United Kingdom', 8, 'Computational Biology|Data Interpretation, Statistical|Databases, Factual|Databases, Genetic|Genomics|Internet|Software|User-Computer Interface', 'Journal Article', '10.1371/journal.pcbi.1000121', '18818719', '-'),
(84014, 2008, 'plos', 'Structure-guided comparative analysis of proteins: principles, tools, and applications for predicting function', 'Mazumder, Raja|Vasudevan, Sona', 'Department of Biochemistry and Molecular and Cellular Biology, Georgetown University Medical Center, Washington, D.C. USA.|Department of Biochemistry and Molecular and Cellular Biology, Georgetown University Medical Center, Washington, D.C. USA.', 'United States|United States', 6, 'Computational Biology|Databases, Protein|Molecular Structure|Phylogeny|Protein Conformation|Proteins|Proteomics|Sequence Alignment', 'Comparative Study', '10.1371/journal.pcbi.1000151', '18818720', '-');
INSERT INTO `papers` (`id`, `ano`, `journal`, `titulo`, `autores`, `afiliacao`, `pais`, `citacoes`, `palavra_chave`, `categorias`, `doi`, `pubmed`, `abstract`) VALUES
(84015, 2008, 'plos', 'Structural biology by NMR: structure, dynamics, and interactions', 'Markwick, Phineus R L|Malliavin, Thérèse|Nilges, Michael', 'Département de Biologie Structurale et Chimie, Institut Pasteur, Unité de Bio-Informatique Structurale, CNRS URA 2185, Paris, France.|Département de Biologie Structurale et Chimie, Institut Pasteur, Unité de Bio-Informatique Structurale, CNRS URA 2185, Paris, France.|Département de Biologie Structurale et Chimie, Institut Pasteur, Unité de Bio-Informatique Structurale, CNRS URA 2185, Paris, France.', 'France|France|France', 69, 'Computational Biology|Data Interpretation, Statistical|Macromolecular Substances|Models, Chemical|Models, Molecular|Molecular Biology|Molecular Conformation|Molecular Structure|Nuclear Magnetic Resonance, Biomolecular|Proteins|Thermodynamics', 'Journal Article', '10.1371/journal.pcbi.1000168', '18818721', 'The function of bio-macromolecules is determined by both their 3D structure and conformational dynamics. These molecules are inherently flexible systems displaying a broad range of dynamics on time-scales from picoseconds to seconds. Nuclear Magnetic Resonance (NMR) spectroscopy has emerged as the method of choice for studying both protein structure and dynamics in solution. Typically, NMR experiments are sensitive both to structural features and to dynamics, and hence the measured data contain information on both. Despite major progress in both experimental approaches and computational methods, obtaining a consistent view of structure and dynamics from experimental NMR data remains a challenge. Molecular dynamics simulations have emerged as an indispensable tool in the analysis of NMR data.'),
(84016, 2008, 'plos', 'Protein meta-functional signatures from combining sequence, structure, evolution, and amino acid property information', 'Wang, Kai|Horst, Jeremy A|Cheng, Gong|Nickle, David C|Samudrala, Ram', 'Department of Microbiology, Computational Genomics Group, University of Washington, Seattle, Washington, United States of America.|Department of Microbiology, Computational Genomics Group, University of Washington, Seattle, Washington, United States of America.|Department of Microbiology, Computational Genomics Group, University of Washington, Seattle, Washington, United States of America.|Department of Microbiology, Computational Genomics Group, University of Washington, Seattle, Washington, United States of America.|Department of Microbiology, Computational Genomics Group, University of Washington, Seattle, Washington, United States of America.', 'United States|United States|United States|United States|United States', 30, 'Amino Acid Sequence|Amino Acids|Bacterial Proteins|Binding Sites|Cellulose 1,4-beta-Cellobiosidase|Computational Biology|Computer Simulation|Conserved Sequence|Databases, Protein|Evolution, Molecular|Internet|Models, Chemical|Models, Genetic|Models, Molecular|Molecular Structure|Mutagenesis, Site-Directed|Ornithine Decarboxylase|Protein Interaction Domains and Motifs|Protein Structure, Tertiary|Proteins|Regression Analysis|Sequence Alignment|Thermodynamics', 'Journal Article', '10.1371/journal.pcbi.1000181', '18818722', 'Protein function is mediated by different amino acid residues, both their positions and types, in a protein sequence. Some amino acids are responsible for the stability or overall shape of the protein, playing an indirect role in protein function. Others play a functionally important role as part of active or binding sites of the protein. For a given protein sequence, the residues and their degree of functional importance can be thought of as a signature representing the function of the protein. We have developed a combination of knowledge- and biophysics-based function prediction approaches to elucidate the relationships between the structural and the functional roles of individual residues and positions. Such a meta-functional signature (MFS), which is a collection of continuous values representing the functional significance of each residue in a protein, may be used to study proteins of known function in greater detail and to aid in experimental characterization of proteins of unknown function. We demonstrate the superior performance of MFS in predicting protein functional sites and also present four real-world examples to apply MFS in a wide range of settings to elucidate protein sequence-structure-function relationships. Our results indicate that the MFS approach, which can combine multiple sources of information and also give biological interpretation to each component, greatly facilitates the understanding and characterization of protein function.'),
(84017, 2008, 'plos', 'Adaptation and selective information transmission in the cricket auditory neuron AN2', 'Wimmer, Klaus|Hildebrandt, K Jannis|Hennig, R Matthias|Obermayer, Klaus', 'School of Computer Science and Electrical Engineering, Technische Universität Berlin, Berlin, Germany. klaus@cs.tu-berlin.de|School of Computer Science and Electrical Engineering, Technische Universität Berlin, Berlin, Germany. klaus@cs.tu-berlin.de|School of Computer Science and Electrical Engineering, Technische Universität Berlin, Berlin, Germany. klaus@cs.tu-berlin.de|School of Computer Science and Electrical Engineering, Technische Universität Berlin, Berlin, Germany. klaus@cs.tu-berlin.de', 'Germany|Germany|Germany|Germany', 11, 'Acoustic Stimulation|Adaptation, Physiological|Animals|Auditory Pathways|Bayes Theorem|Computational Biology|Evoked Potentials, Auditory|Gryllidae|Models, Neurological|Neurons, Afferent|Synaptic Transmission', 'Journal Article', '10.1371/journal.pcbi.1000182', '18818723', 'Sensory systems adapt their neural code to changes in the sensory environment, often on multiple time scales. Here, we report a new form of adaptation in a first-order auditory interneuron (AN2) of crickets. We characterize the response of the AN2 neuron to amplitude-modulated sound stimuli and find that adaptation shifts the stimulus-response curves toward higher stimulus intensities, with a time constant of 1.5 s for adaptation and recovery. The spike responses were thus reduced for low-intensity sounds. We then address the question whether adaptation leads to an improvement of the signals representation and compare the experimental results with the predictions of two competing hypotheses: infomax, which predicts that information conveyed about the entire signal range should be maximized, and selective coding, which predicts that foreground signals should be enhanced while background signals should be selectively suppressed. We test how adaptation changes the input-response curve when presenting signals with two or three peaks in their amplitude distributions, for which selective coding and infomax predict conflicting changes. By means of Bayesian data analysis, we quantify the shifts of the measured response curves and also find a slight reduction of their slopes. These decreases in slopes are smaller, and the absolute response thresholds are higher than those predicted by infomax. Most remarkably, and in contrast to the infomax principle, adaptation actually reduces the amount of encoded information when considering the whole range of input signals. The response curve changes are also not consistent with the selective coding hypothesis, because the amount of information conveyed about the loudest part of the signal does not increase as predicted but remains nearly constant. Less information is transmitted about signals with lower intensity.'),
(84018, 2008, 'plos', 'Natural selection fails to optimize mutation rates for long-term adaptation on rugged fitness landscapes', 'Clune, Jeff|Misevic, Dusan|Ofria, Charles|Lenski, Richard E|Elena, Santiago F|Sanjuán, Rafael', 'Department of Computer Science and Engineering, Michigan State University, East Lansing, Michigan, United States of America. jclune@msu.edu|Department of Computer Science and Engineering, Michigan State University, East Lansing, Michigan, United States of America. jclune@msu.edu|Department of Computer Science and Engineering, Michigan State University, East Lansing, Michigan, United States of America. jclune@msu.edu|Department of Computer Science and Engineering, Michigan State University, East Lansing, Michigan, United States of America. jclune@msu.edu|Department of Computer Science and Engineering, Michigan State University, East Lansing, Michigan, United States of America. jclune@msu.edu|Department of Computer Science and Engineering, Michigan State University, East Lansing, Michigan, United States of America. jclune@msu.edu', 'United States|United States|United States|United States|United States|United States', 71, 'Adaptation, Physiological|Biological Evolution|Computational Biology|Computer Simulation|Models, Genetic|Mutation|Selection, Genetic|Time Factors', 'Journal Article', '10.1371/journal.pcbi.1000187', '18818724', 'The rate of mutation is central to evolution. Mutations are required for adaptation, yet most mutations with phenotypic effects are deleterious. As a consequence, the mutation rate that maximizes adaptation will be some intermediate value. Here, we used digital organisms to investigate the ability of natural selection to adjust and optimize mutation rates. We assessed the optimal mutation rate by empirically determining what mutation rate produced the highest rate of adaptation. Then, we allowed mutation rates to evolve, and we evaluated the proximity to the optimum. Although we chose conditions favorable for mutation rate optimization, the evolved rates were invariably far below the optimum across a wide range of experimental parameter settings. We hypothesized that the reason that mutation rates evolved to be suboptimal was the ruggedness of fitness landscapes. To test this hypothesis, we created a simplified landscape without any fitness valleys and found that, in such conditions, populations evolved near-optimal mutation rates. In contrast, when fitness valleys were added to this simple landscape, the ability of evolving populations to find the optimal mutation rate was lost. We conclude that rugged fitness landscapes can prevent the evolution of mutation rates that are optimal for long-term adaptation. This finding has important implications for applied evolutionary research in both biological and computational realms.'),
(84019, 2008, 'plos', 'A genomewide functional network for the laboratory mouse', 'Guan, Yuanfang|Myers, Chad L|Lu, Rong|Lemischka, Ihor R|Bult, Carol J|Troyanskaya, Olga G', 'Lewis-Sigler Institute for Integrative Genomics, Carl Icahn Laboratory, Princeton University, Princeton, New Jersey, United States of America.|Lewis-Sigler Institute for Integrative Genomics, Carl Icahn Laboratory, Princeton University, Princeton, New Jersey, United States of America.|Lewis-Sigler Institute for Integrative Genomics, Carl Icahn Laboratory, Princeton University, Princeton, New Jersey, United States of America.|Lewis-Sigler Institute for Integrative Genomics, Carl Icahn Laboratory, Princeton University, Princeton, New Jersey, United States of America.|Lewis-Sigler Institute for Integrative Genomics, Carl Icahn Laboratory, Princeton University, Princeton, New Jersey, United States of America.|Lewis-Sigler Institute for Integrative Genomics, Carl Icahn Laboratory, Princeton University, Princeton, New Jersey, United States of America.', 'Jersey|Jersey|Jersey|Jersey|Jersey|Jersey', 87, 'Animals|Bayes Theorem|Cell Differentiation|Cluster Analysis|Computational Biology|Database Management Systems|Databases, Genetic|Down-Regulation|Gene Regulatory Networks|Genomics|Homeodomain Proteins|Internet|MAP Kinase Signaling System|Mice|Mice, Knockout|Models, Statistical|Nanog Homeobox Protein|Phenotype|Proteomics|Saccharomyces cerevisiae|Species Specificity|User-Computer Interface', 'Comparative Study', '10.1371/journal.pcbi.1000165', '18818725', 'Establishing a functional network is invaluable to our understanding of gene function, pathways, and systems-level properties of an organism and can be a powerful resource in directing targeted experiments. In this study, we present a functional network for the laboratory mouse based on a Bayesian integration of diverse genetic and functional genomic data. The resulting network includes probabilistic functional linkages among 20,581 protein-coding genes. We show that this network can accurately predict novel functional assignments and network components and present experimental evidence for predictions related to Nanog homeobox (Nanog), a critical gene in mouse embryonic stem cell pluripotency. An analysis of the global topology of the mouse functional network reveals multiple biologically relevant systems-level features of the mouse proteome. Specifically, we identify the clustering coefficient as a critical characteristic of central modulators that affect diverse pathways as well as genes associated with different phenotype traits and diseases. In addition, a cross-species comparison of functional interactomes on a genomic scale revealed distinct functional characteristics of conserved neighborhoods as compared to subnetworks specific to higher organisms. Thus, our global functional network for the laboratory mouse provides the community with a key resource for discovering protein functions and novel pathway components as well as a tool for exploring systems-level topological and evolutionary features of cellular interactomes. To facilitate exploration of this network by the biomedical research community, we illustrate its application in function and disease gene discovery through an interactive, Web-based, publicly available interface at http://mouseNET.princeton.edu.'),
(84020, 2008, 'plos', 'Spatial bistability generates hunchback expression sharpness in the Drosophila embryo', 'Lopes, Francisco J P|Vieira, Fernando M C|Holloway, David M|Bisch, Paulo M|Spirov, Alexander V', 'Department of Applied Mathematics, Stony Brook University, Stony Brook, New York, United States of America. fjplopes@gmail.com|Department of Applied Mathematics, Stony Brook University, Stony Brook, New York, United States of America. fjplopes@gmail.com|Department of Applied Mathematics, Stony Brook University, Stony Brook, New York, United States of America. fjplopes@gmail.com|Department of Applied Mathematics, Stony Brook University, Stony Brook, New York, United States of America. fjplopes@gmail.com|Department of Applied Mathematics, Stony Brook University, Stony Brook, New York, United States of America. fjplopes@gmail.com', 'United States|United States|United States|United States|United States', 44, 'Animals|Binding Sites|Body Patterning|Computational Biology|DNA-Binding Proteins|Drosophila Proteins|Drosophila melanogaster|Female|Gene Expression Regulation, Developmental|Gene Regulatory Networks|Genes, Insect|Genotype|Homeodomain Proteins|Models, Genetic|Mutation|Trans-Activators|Transcription Factors|Transcription, Genetic', 'Journal Article', '10.1371/journal.pcbi.1000184', '18818726', 'During embryonic development, the positional information provided by concentration gradients of maternal factors directs pattern formation by providing spatially dependent cues for gene expression. In the fruit fly, Drosophila melanogaster, a classic example of this is the sharp on-off activation of the hunchback (hb) gene at midembryo, in response to local concentrations of the smooth anterior-posterior Bicoid (Bcd) gradient. The regulatory region for hb contains multiple binding sites for the Bcd protein as well as multiple binding sites for the Hb protein. Some previous studies have suggested that Bcd is sufficient for properly sharpened Hb expression, yet other evidence suggests a need for additional regulation. We experimentally quantified the dynamics of hb gene expression in flies that were wild-type, were mutant for hb self-regulation or Bcd binding, or contained an artificial promoter construct consisting of six Bcd and two Hb sites. In addition to these experiments, we developed a reaction-diffusion model of hb transcription, with Bcd cooperative binding and hb self-regulation, and used Zero Eigenvalue Analysis to look for multiple stationary states in the reaction network. Our model reproduces the hb developmental dynamics and correctly predicts the mutant patterns. Analysis of our model indicates that the Hb sharpness can be produced by spatial bistability, in which hb self-regulation produces two stable levels of expression. In the absence of self-regulation, the bistable behavior vanishes and Hb sharpness is disrupted. Bcd cooperative binding affects the position where bistability occurs but is not itself sufficient for a sharp Hb pattern. Our results show that the control of Hb sharpness and positioning, by hb self-regulation and Bcd cooperativity, respectively, are separate processes that can be altered independently. Our model, which matches the changes in Hb position and sharpness observed in different experiments, provides a theoretical framework for understanding the data and in particular indicates that spatial bistability can play a central role in threshold-dependent reading mechanisms of positional information.'),
(84021, 2008, 'plos', 'A dual receptor crosstalk model of G-protein-coupled signal transduction', 'Flaherty, Patrick|Radhakrishnan, Mala L|Dinh, Tuan|Rebres, Robert A|Roach, Tamara I|Jordan, Michael I|Arkin, Adam P', 'Department of Electrical Engineering and Computer Sciences, University of California Berkeley, Berkeley, California, United States of America.|Department of Electrical Engineering and Computer Sciences, University of California Berkeley, Berkeley, California, United States of America.|Department of Electrical Engineering and Computer Sciences, University of California Berkeley, Berkeley, California, United States of America.|Department of Electrical Engineering and Computer Sciences, University of California Berkeley, Berkeley, California, United States of America.|Department of Electrical Engineering and Computer Sciences, University of California Berkeley, Berkeley, California, United States of America.|Department of Electrical Engineering and Computer Sciences, University of California Berkeley, Berkeley, California, United States of America.|Department of Electrical Engineering and Computer Sciences, University of California Berkeley, Berkeley, California, United States of America.', 'United States|United States|United States|United States|United States|United States|United States', 0, 'Animals|Calcium Signaling|Cell Line|Complement C5a|Computational Biology|Feedback, Physiological|GTP-Binding Protein alpha Subunits, Gi-Go|GTP-Binding Protein alpha Subunits, Gq-G11|Ligands|Macrophages|Mice|Models, Biological|RNA Interference|Receptor Cross-Talk|Receptors, G-Protein-Coupled|Signal Transduction|Uridine Diphosphate', 'Journal Article', '10.1371/journal.pcbi.1000185', '18818727', 'Macrophage cells that are stimulated by two different ligands that bind to G-protein-coupled receptors (GPCRs) usually respond as if the stimulus effects are additive, but for a minority of ligand combinations the response is synergistic. The G-protein-coupled receptor system integrates signaling cues from the environment to actuate cell morphology, gene expression, ion homeostasis, and other physiological states. We analyze the effects of the two signaling molecules complement factors 5a (C5a) and uridine diphosphate (UDP) on the intracellular second messenger calcium to elucidate the principles that govern the processing of multiple signals by GPCRs. We have developed a formal hypothesis, in the form of a kinetic model, for the mechanism of action of this GPCR signal transduction system using data obtained from RAW264.7 macrophage cells. Bayesian statistical methods are employed to represent uncertainty in both data and model parameters and formally tie the model to experimental data. When the model is also used as a tool in the design of experiments, it predicts a synergistic region in the calcium peak height dose response that results when cells are simultaneously stimulated by C5a and UDP. An analysis of the model reveals a potential mechanism for crosstalk between the Galphai-coupled C5a receptor and the Galphaq-coupled UDP receptor signaling systems that results in synergistic calcium release.'),
(84022, 2008, 'plos', 'Gene-boosted assembly of a novel bacterial genome from very short reads', 'Salzberg, Steven L|Sommer, Daniel D|Puiu, Daniela|Lee, Vincent T', 'Center for Bioinformatics and Computational Biology, University of Maryland, College Park, Maryland, United States of America. salzberg@umd.edu|Center for Bioinformatics and Computational Biology, University of Maryland, College Park, Maryland, United States of America. salzberg@umd.edu|Center for Bioinformatics and Computational Biology, University of Maryland, College Park, Maryland, United States of America. salzberg@umd.edu|Center for Bioinformatics and Computational Biology, University of Maryland, College Park, Maryland, United States of America. salzberg@umd.edu', 'United States|United States|United States|United States', 0, 'Bacteria|Computational Biology|DNA, Bacterial|Genetic Engineering|Genetic Techniques|Genome, Bacterial|Humans|Models, Genetic|Pseudomonas aeruginosa', 'Journal Article', '10.1371/journal.pcbi.1000186', '18818729', 'Recent improvements in technology have made DNA sequencing dramatically faster and more efficient than ever before. The new technologies produce highly accurate sequences, but one drawback is that the most efficient technology produces the shortest read lengths. Short-read sequencing has been applied successfully to resequence the human genome and those of other species but not to whole-genome sequencing of novel organisms. Here we describe the sequencing and assembly of a novel clinical isolate of Pseudomonas aeruginosa, strain PAb1, using very short read technology. From 8,627,900 reads, each 33 nucleotides in length, we assembled the genome into one scaffold of 76 ordered contiguous sequences containing 6,290,005 nucleotides, including one contig spanning 512,638 nucleotides, plus an additional 436 unordered contigs containing 416,897 nucleotides. Our method includes a novel gene-boosting algorithm that uses amino acid sequences from predicted proteins to build a better assembly. This study demonstrates the feasibility of very short read sequencing for the sequencing of bacterial genomes, particularly those for which a related species has been sequenced previously, and expands the potential application of this new technology to most known prokaryotic species.'),
(84023, 2008, 'plos', 'Organization of excitable dynamics in hierarchical biological networks', 'Müller-Linow, Mark|Hilgetag, Claus C|Hütt, Marc-Thorsten', 'Department of Biology, Bioinformatics Group, Darmstadt University of Technology, Darmstadt, Germany. mamuelow@web.de|Department of Biology, Bioinformatics Group, Darmstadt University of Technology, Darmstadt, Germany. mamuelow@web.de|Department of Biology, Bioinformatics Group, Darmstadt University of Technology, Darmstadt, Germany. mamuelow@web.de', 'Germany|Germany|Germany', 96, 'Animals|Caenorhabditis elegans|Cats|Computational Biology|Computer Graphics|Computer Simulation|Metabolic Networks and Pathways|Models, Biological|Models, Neurological|Nerve Net|Neural Networks (Computer)', 'Journal Article', '10.1371/journal.pcbi.1000190', '18818769', 'This study investigates the contributions of network topology features to the dynamic behavior of hierarchically organized excitable networks. Representatives of different types of hierarchical networks as well as two biological neural networks are explored with a three-state model of node activation for systematically varying levels of random background network stimulation. The results demonstrate that two principal topological aspects of hierarchical networks, node centrality and network modularity, correlate with the network activity patterns at different levels of spontaneous network activation. The approach also shows that the dynamic behavior of the cerebral cortical systems network in the cat is dominated by the networks modular organization, while the activation behavior of the cellular neuronal network of Caenorhabditis elegans is strongly influenced by hub nodes. These findings indicate the interaction of multiple topological features and dynamic states in the function of complex biological networks.'),
(84024, 2008, 'plos', 'Discarding functional residues from the substitution table improves predictions of active sites within three-dimensional structures', 'Gong, Sungsam|Blundell, Tom L', 'Department of Biochemistry, Biocomputing Group, University of Cambridge, Cambridge, United Kingdom.|Department of Biochemistry, Biocomputing Group, University of Cambridge, Cambridge, United Kingdom.', 'United Kingdom|United Kingdom', 16, 'Amino Acid Substitution|Binding Sites|Catalytic Domain|Computational Biology|Conserved Sequence|Databases, Protein|Enzymes|Ligands|Nucleic Acids|Protein Interaction Mapping|Proteins|Sequence Alignment|Software', 'Journal Article', '10.1371/journal.pcbi.1000179', '18833291', 'Substitutions of individual amino acids in proteins may be under very different evolutionary restraints depending on their structural and functional roles. The Environment Specific Substitution Table (ESST) describes the pattern of substitutions in terms of amino acid location within elements of secondary structure, solvent accessibility, and the existence of hydrogen bonds between side chains and neighbouring amino acid residues. Clearly amino acids that have very different local environments in their functional state compared to those in the protein analysed will give rise to inconsistencies in the calculation of amino acid substitution tables. Here, we describe how the calculation of ESSTs can be improved by discarding the functional residues from the calculation of substitution tables. Four categories of functions are examined in this study: protein-protein interactions, protein-nucleic acid interactions, protein-ligand interactions, and catalytic activity of enzymes. Their contributions to residue conservation are measured and investigated. We test our new ESSTs using the program CRESCENDO, designed to predict functional residues by exploiting knowledge of amino acid substitutions, and compare the benchmark results with proteins whose functions have been defined experimentally. The new methodology increases the Z-score by 98% at the active site residues and finds 16% more active sites compared with the old ESST. We also find that discarding amino acids responsible for protein-protein interactions helps in the prediction of those residues although they are not as conserved as the residues of active sites. Our methodology can make the substitution tables better reflect and describe the substitution patterns of amino acids that are under structural restraints only.'),
(84025, 2008, 'plos', 'Removal of AU bias from microarray mRNA expression data enhances computational identification of active microRNAs', 'Elkon, Ran|Agami, Reuven', 'Division of Gene Regulation, The Netherlands Cancer Institute, Amsterdam, The Netherlands.|Division of Gene Regulation, The Netherlands Cancer Institute, Amsterdam, The Netherlands.', 'Netherlands|Netherlands', 6, '3 Untranslated Regions|Animals|Base Composition|Bias|Computational Biology|Databases, Nucleic Acid|Gene Expression Profiling|Hematopoiesis|Hematopoietic Stem Cells|Humans|Mice|MicroRNAs|Multipotent Stem Cells|Oligonucleotide Array Sequence Analysis|RNA, Messenger|T-Lymphocyte Subsets', 'Journal Article', '10.1371/journal.pcbi.1000189', '18833292', 'Elucidation of regulatory roles played by microRNAs (miRs) in various biological networks is one of the greatest challenges of present molecular and computational biology. The integrated analysis of gene expression data and 3-UTR sequences holds great promise for being an effective means to systematically delineate active miRs in different biological processes. Applying such an integrated analysis, we uncovered a striking relationship between 3-UTR AU content and gene response in numerous microarray datasets. We show that this relationship is secondary to a general bias that links gene response and probe AU content and reflects the fact that in the majority of current arrays probes are selected from target transcript 3-UTRs. Therefore, removal of this bias, which is in order in any analysis of microarray datasets, is of crucial importance when integrating expression data and 3-UTR sequences to identify regulatory elements embedded in this region. We developed visualization and normalization schemes for the detection and removal of such AU biases and demonstrate that their application to microarray data significantly enhances the computational identification of active miRs. Our results substantiate that, after removal of AU biases, mRNA expression profiles contain ample information which allows in silico detection of miRs that are active in physiological conditions.'),
(84026, 2008, 'plos', 'Impact of limited solvent capacity on metabolic rate, enzyme activities, and metabolite concentrations of S cerevisiae glycolysis', 'Vazquez, Alexei|de Menezes, Marcio A|Barabási, Albert-László|Oltvai, Zoltan N', 'The Simons Center for Systems Biology, Institute for Advanced Study, Princeton, New Jersey, United States of America. vazquez@ias.edu|The Simons Center for Systems Biology, Institute for Advanced Study, Princeton, New Jersey, United States of America. vazquez@ias.edu|The Simons Center for Systems Biology, Institute for Advanced Study, Princeton, New Jersey, United States of America. vazquez@ias.edu|The Simons Center for Systems Biology, Institute for Advanced Study, Princeton, New Jersey, United States of America. vazquez@ias.edu', 'Jersey|Jersey|Jersey|Jersey', 11, 'Computational Biology|Cytoplasm|Glycolysis|Kinetics|Models, Biological|Multiprotein Complexes|Saccharomyces cerevisiae|Solvents', 'Journal Article', '10.1371/journal.pcbi.1000195', '18846199', 'The cells cytoplasm is crowded by its various molecular components, resulting in a limited solvent capacity for the allocation of new proteins, thus constraining various cellular processes such as metabolism. Here we study the impact of the limited solvent capacity constraint on the metabolic rate, enzyme activities, and metabolite concentrations using a computational model of Saccharomyces cerevisiae glycolysis as a case study. We show that given the limited solvent capacity constraint, the optimal enzyme activities and the metabolite concentrations necessary to achieve a maximum rate of glycolysis are in agreement with their experimentally measured values. Furthermore, the predicted maximum glycolytic rate determined by the solvent capacity constraint is close to that measured in vivo. These results indicate that the limited solvent capacity is a relevant constraint acting on S. cerevisiae at physiological growth conditions, and that a full kinetic model together with the limited solvent capacity constraint can be used to predict both metabolite concentrations and enzyme activities in vivo.'),
(84027, 2008, 'plos', 'Protein docking by the underestimation of free energy funnels in the space of encounter complexes', 'Shen, Yang|Paschalidis, Ioannis Ch|Vakili, Pirooz|Vajda, Sandor', 'Department of Biomedical Engineering, BioMolecular Engineering Research Center, Boston University, Boston, Massachusetts, United States of America.|Department of Biomedical Engineering, BioMolecular Engineering Research Center, Boston University, Boston, Massachusetts, United States of America.|Department of Biomedical Engineering, BioMolecular Engineering Research Center, Boston University, Boston, Massachusetts, United States of America.|Department of Biomedical Engineering, BioMolecular Engineering Research Center, Boston University, Boston, Massachusetts, United States of America.', 'United States|United States|United States|United States', 36, 'Algorithms|Computational Biology|Models, Chemical|Multiprotein Complexes|Protein Binding|Protein Interaction Domains and Motifs|Protein Interaction Mapping|Proteins|Software|Thermodynamics', 'Journal Article', '10.1371/journal.pcbi.1000191', '18846200', 'Similarly to protein folding, the association of two proteins is driven by a free energy funnel, determined by favorable interactions in some neighborhood of the native state. We describe a docking method based on stochastic global minimization of funnel-shaped energy functions in the space of rigid body motions (SE(3)) while accounting for flexibility of the interface side chains. The method, called semi-definite programming-based underestimation (SDU), employs a general quadratic function to underestimate a set of local energy minima and uses the resulting underestimator to bias further sampling. While SDU effectively minimizes functions with funnel-shaped basins, its application to docking in the rotational and translational space SE(3) is not straightforward due to the geometry of that space. We introduce a strategy that uses separate independent variables for side-chain optimization, center-to-center distance of the two proteins, and five angular descriptors of the relative orientations of the molecules. The removal of the center-to-center distance turns out to vastly improve the efficiency of the search, because the five-dimensional space now exhibits a well-behaved energy surface suitable for underestimation. This algorithm explores the free energy surface spanned by encounter complexes that correspond to local free energy minima and shows similarity to the model of macromolecular association that proceeds through a series of collisions. Results for standard protein docking benchmarks establish that in this space the free energy landscape is a funnel in a reasonably broad neighborhood of the native state and that the SDU strategy can generate docking predictions with less than 5 A ligand interface C(alpha) root-mean-square deviation while achieving an approximately 20-fold efficiency gain compared to Monte Carlo methods.'),
(84028, 2008, 'plos', 'Nonidentifiability of the source of intrinsic noise in gene expression from single-burst data', 'Ingram, Piers J|Stumpf, Michael P H|Stark, Jaroslav', 'Department of Mathematics, Imperial College London, London, United Kingdom. piers.ingram@imperial.ac.uk|Department of Mathematics, Imperial College London, London, United Kingdom. piers.ingram@imperial.ac.uk|Department of Mathematics, Imperial College London, London, United Kingdom. piers.ingram@imperial.ac.uk', 'United Kingdom|United Kingdom|United Kingdom', 25, 'Computational Biology|Data Interpretation, Statistical|Gene Expression|Gene Expression Profiling|Models, Genetic|Models, Statistical|Proteins|RNA, Messenger', 'Journal Article', '10.1371/journal.pcbi.1000192', '18846201', 'Over the last few years, experimental data on the fluctuations in gene activity between individual cells and within the same cell over time have confirmed that gene expression is a noisy process. This variation is in part due to the small number of molecules taking part in some of the key reactions that are involved in gene expression. One of the consequences of this is that protein production often occurs in bursts, each due to a single promoter or transcription factor binding event. Recently, the distribution of the number of proteins produced in such bursts has been experimentally measured, offering a unique opportunity to study the relative importance of different sources of noise in gene expression. Here, we provide a derivation of the theoretical probability distribution of these bursts for a wide variety of different models of gene expression. We show that there is a good fit between our theoretical distribution and that obtained from two different published experimental datasets. We then prove that, irrespective of the details of the model, the burst size distribution is always geometric and hence determined by a single parameter. Many different combinations of the biochemical rates for the constituent reactions of both transcription and translation will therefore lead to the same experimentally observed burst size distribution. It is thus impossible to identify different sources of fluctuations purely from protein burst size data or to use such data to estimate all of the model parameters. We explore methods of inferring these values when additional types of experimental data are available.'),
(84029, 2008, 'plos', 'Dose-to-duration encoding and signaling beyond saturation in intracellular signaling networks', 'Behar, Marcelo|Hao, Nan|Dohlman, Henrik G|Elston, Timothy C', 'Department of Physics, University of North Carolina Chapel Hill, Chapel Hill, North Carolina, United States of America.|Department of Physics, University of North Carolina Chapel Hill, Chapel Hill, North Carolina, United States of America.|Department of Physics, University of North Carolina Chapel Hill, Chapel Hill, North Carolina, United States of America.|Department of Physics, University of North Carolina Chapel Hill, Chapel Hill, North Carolina, United States of America.', 'United States|United States|United States|United States', 43, 'Computational Biology|Dose-Response Relationship, Drug|Feedback, Physiological|Models, Biological|Pheromones|Receptors, Cell Surface|Receptors, Pheromone|Saccharomyces cerevisiae|Saccharomyces cerevisiae Proteins|Signal Transduction|Time Factors', 'Journal Article', '10.1371/journal.pcbi.1000197', '18846202', 'The cellular response elicited by an environmental cue typically varies with the strength of the stimulus. For example, in the yeast Saccharomyces cerevisiae, the concentration of mating pheromone determines whether cells undergo vegetative growth, chemotropic growth, or mating. This implies that the signaling pathways responsible for detecting the stimulus and initiating a response must transmit quantitative information about the intensity of the signal. Our previous experimental results suggest that yeast encode pheromone concentration as the duration of the transmitted signal. Here we use mathematical modeling to analyze possible biochemical mechanisms for performing this dose-to-duration conversion. We demonstrate that modulation of signal duration increases the range of stimulus concentrations for which dose-dependent responses are possible, this increased dynamic range produces the counterintuitive result of signaling beyond saturation in which dose-dependent responses are still possible after apparent saturation of the receptors. We propose a mechanism for dose-to-duration encoding in the yeast pheromone pathway that is consistent with current experimental observations. Most previous investigations of information processing by signaling pathways have focused on amplitude encoding without considering temporal aspects of signal transduction. Here we demonstrate that dose-to-duration encoding provides cells with an alternative mechanism for processing and transmitting quantitative information about their surrounding environment. The ability of signaling pathways to convert stimulus strength into signal duration results directly from the nonlinear nature of these systems and emphasizes the importance of considering the dynamic properties of signaling pathways when characterizing their behavior. Understanding how signaling pathways encode and transmit quantitative information about the external environment will not only deepen our understanding of these systems but also provide insight into how to reestablish proper function of pathways that have become dysregulated by disease.'),
(84030, 2008, 'plos', 'A learning theory for reward-modulated spike-timing-dependent plasticity with application to biofeedback', 'Legenstein, Robert|Pecevski, Dejan|Maass, Wolfgang', 'Institute for Theoretical Computer Science, Graz University of Technology, Graz, Austria.|Institute for Theoretical Computer Science, Graz University of Technology, Graz, Austria.|Institute for Theoretical Computer Science, Graz University of Technology, Graz, Austria.', 'Austria|Austria|Austria', 129, 'Action Potentials|Animals|Biofeedback, Psychology|Computational Biology|Computer Simulation|Haplorhini|Learning|Models, Neurological|Nerve Net|Neural Networks (Computer)|Neuronal Plasticity|Neurosciences|Pattern Recognition, Physiological|Reward', 'Journal Article', '10.1371/journal.pcbi.1000180', '18846203', 'Reward-modulated spike-timing-dependent plasticity (STDP) has recently emerged as a candidate for a learning rule that could explain how behaviorally relevant adaptive changes in complex networks of spiking neurons could be achieved in a self-organizing manner through local synaptic plasticity. However, the capabilities and limitations of this learning rule could so far only be tested through computer simulations. This article provides tools for an analytic treatment of reward-modulated STDP, which allows us to predict under which conditions reward-modulated STDP will achieve a desired learning effect. These analytical results imply that neurons can learn through reward-modulated STDP to classify not only spatial but also temporal firing patterns of presynaptic neurons. They also can learn to respond to specific presynaptic firing patterns with particular spike patterns. Finally, the resulting learning theory predicts that even difficult credit-assignment problems, where it is very hard to tell which synaptic weights should be modified in order to increase the global reward for the system, can be solved in a self-organizing manner through reward-modulated STDP. This yields an explanation for a fundamental experimental result on biofeedback in monkeys by Fetz and Baker. In this experiment monkeys were rewarded for increasing the firing rate of a particular neuron in the cortex and were able to solve this extremely difficult credit assignment problem. Our model for this experiment relies on a combination of reward-modulated STDP with variable spontaneous firing activity. Hence it also provides a possible functional explanation for trial-to-trial variability, which is characteristic for cortical networks of neurons but has no analogue in currently existing artificial computing systems. In addition our model demonstrates that reward-modulated STDP can be applied to all synapses in a large recurrent neural network without endangering the stability of the network dynamics.'),
(84031, 2008, 'plos', 'Analysis of gene regulatory networks in the mammalian circadian rhythm', 'Yan, Jun|Wang, Haifang|Liu, Yuting|Shao, Chunxuan', 'CAS-MPG Partner Institute for Computational Biology, Shanghai Institutes of Biological Sciences, Shanghai, China. junyan@picb.ac.cn|CAS-MPG Partner Institute for Computational Biology, Shanghai Institutes of Biological Sciences, Shanghai, China. junyan@picb.ac.cn|CAS-MPG Partner Institute for Computational Biology, Shanghai Institutes of Biological Sciences, Shanghai, China. junyan@picb.ac.cn|CAS-MPG Partner Institute for Computational Biology, Shanghai Institutes of Biological Sciences, Shanghai, China. junyan@picb.ac.cn', 'China|China|China|China', 180, 'Animals|Circadian Rhythm|Computational Biology|Databases, Genetic|Gene Regulatory Networks|Humans|Macaca mulatta|Mammals|Mice|Mice, Knockout|Mice, Mutant Strains|Oligonucleotide Array Sequence Analysis|Promoter Regions, Genetic|Rats|Species Specificity|Tissue Distribution', 'Comparative Study', '10.1371/journal.pcbi.1000193', '18846204', 'Circadian rhythm is fundamental in regulating a wide range of cellular, metabolic, physiological, and behavioral activities in mammals. Although a small number of key circadian genes have been identified through extensive molecular and genetic studies in the past, the existence of other key circadian genes and how they drive the genomewide circadian oscillation of gene expression in different tissues still remains unknown. Here we try to address these questions by integrating all available circadian microarray data in mammals. We identified 41 common circadian genes that showed circadian oscillation in a wide range of mouse tissues with a remarkable consistency of circadian phases across tissues. Comparisons across mouse, rat, rhesus macaque, and human showed that the circadian phases of known key circadian genes were delayed for 4-5 hours in rat compared to mouse and 8-12 hours in macaque and human compared to mouse. A systematic gene regulatory network for the mouse circadian rhythm was constructed after incorporating promoter analysis and transcription factor knockout or mutant microarray data. We observed the significant association of cis-regulatory elements: EBOX, DBOX, RRE, and HSE with the different phases of circadian oscillating genes. The analysis of the network structure revealed the paths through which light, food, and heat can entrain the circadian clock and identified that NR3C1 and FKBP/HSP90 complexes are central to the control of circadian genes through diverse environmental signals. Our study improves our understanding of the structure, design principle, and evolution of gene regulatory networks involved in the mammalian circadian rhythm.'),
(84032, 2008, 'plos', 'Biophysical basis for three distinct dynamical mechanisms of action potential initiation', 'Prescott, Steven A|De Koninck, Yves|Sejnowski, Terrence J', 'Computational Neurobiology Laboratory, Salk Institute, La Jolla, California, United States of America. prescott@neurobio.pitt.edu|Computational Neurobiology Laboratory, Salk Institute, La Jolla, California, United States of America. prescott@neurobio.pitt.edu|Computational Neurobiology Laboratory, Salk Institute, La Jolla, California, United States of America. prescott@neurobio.pitt.edu', 'United States|United States|United States', 142, 'Action Potentials|Animals|Biophysical Phenomena|Biophysics|Computational Biology|Electrophysiology|In Vitro Techniques|Male|Models, Neurological|Neurons, Afferent|Rats|Rats, Sprague-Dawley|Spinal Nerves', 'Journal Article', '10.1371/journal.pcbi.1000198', '18846205', 'Transduction of graded synaptic input into trains of all-or-none action potentials (spikes) is a crucial step in neural coding. Hodgkin identified three classes of neurons with qualitatively different analog-to-digital transduction properties. Despite widespread use of this classification scheme, a generalizable explanation of its biophysical basis has not been described. We recorded from spinal sensory neurons representing each class and reproduced their transduction properties in a minimal model. With phase plane and bifurcation analysis, each class of excitability was shown to derive from distinct spike initiating dynamics. Excitability could be converted between all three classes by varying single parameters, moreover, several parameters, when varied one at a time, had functionally equivalent effects on excitability. From this, we conclude that the spike-initiating dynamics associated with each of Hodgkins classes represent different outcomes in a nonlinear competition between oppositely directed, kinetically mismatched currents. Class 1 excitability occurs through a saddle node on invariant circle bifurcation when net current at perithreshold potentials is inward (depolarizing) at steady state. Class 2 excitability occurs through a Hopf bifurcation when, despite net current being outward (hyperpolarizing) at steady state, spike initiation occurs because inward current activates faster than outward current. Class 3 excitability occurs through a quasi-separatrix crossing when fast-activating inward current overpowers slow-activating outward current during a stimulus transient, although slow-activating outward current dominates during constant stimulation. Experiments confirmed that different classes of spinal lamina I neurons express the subthreshold currents predicted by our simulations and, further, that those currents are necessary for the excitability in each cell class. Thus, our results demonstrate that all three classes of excitability arise from a continuum in the direction and magnitude of subthreshold currents. Through detailed analysis of the spike-initiating process, we have explained a fundamental link between biophysical properties and qualitative differences in how neurons encode sensory input.');
INSERT INTO `papers` (`id`, `ano`, `journal`, `titulo`, `autores`, `afiliacao`, `pais`, `citacoes`, `palavra_chave`, `categorias`, `doi`, `pubmed`, `abstract`) VALUES
(84033, 2008, 'plos', 'Noise during rest enables the exploration of the brains dynamic repertoire', 'Ghosh, Anandamohan|Rho, Y|McIntosh, A R|Kötter, R|Jirsa, V K', 'Theoretical Neuroscience Group, Institut des Sciences du Mouvement, Marseille, France. Anandamohan.GHOSH@univmed.fr|Theoretical Neuroscience Group, Institut des Sciences du Mouvement, Marseille, France. Anandamohan.GHOSH@univmed.fr|Theoretical Neuroscience Group, Institut des Sciences du Mouvement, Marseille, France. Anandamohan.GHOSH@univmed.fr|Theoretical Neuroscience Group, Institut des Sciences du Mouvement, Marseille, France. Anandamohan.GHOSH@univmed.fr|Theoretical Neuroscience Group, Institut des Sciences du Mouvement, Marseille, France. Anandamohan.GHOSH@univmed.fr', 'France|France|France|France|France', 311, 'Animals|Brain|Computational Biology|Electroencephalography|Humans|Macaca|Models, Neurological|Nerve Net|Noise|Rest', 'Journal Article', '10.1371/journal.pcbi.1000196', '18846206', 'Traditionally brain function is studied through measuring physiological responses in controlled sensory, motor, and cognitive paradigms. However, even at rest, in the absence of overt goal-directed behavior, collections of cortical regions consistently show temporally coherent activity. In humans, these resting state networks have been shown to greatly overlap with functional architectures present during consciously directed activity, which motivates the interpretation of rest activity as day dreaming, free association, stream of consciousness, and inner rehearsal. In monkeys, it has been shown though that similar coherent fluctuations are present during deep anesthesia when there is no consciousness. Here, we show that comparable resting state networks emerge from a stability analysis of the network dynamics using biologically realistic primate brain connectivity, although anatomical information alone does not identify the network. We specifically demonstrate that noise and time delays via propagation along connecting fibres are essential for the emergence of the coherent fluctuations of the default network. The spatiotemporal network dynamics evolves on multiple temporal scales and displays the intermittent neuroelectric oscillations in the fast frequency regimes, 1-100 Hz, commonly observed in electroencephalographic and magnetoencephalographic recordings, as well as the hemodynamic oscillations in the ultraslow regimes, <0.1 Hz, observed in functional magnetic resonance imaging. The combination of anatomical structure and time delays creates a space-time structure in which the neural noise enables the brain to explore various functional configurations representing its dynamic repertoire.'),
(84034, 2008, 'plos', 'Aggregation propensity of the human proteome', 'Monsellier, Elodie|Ramazzotti, Matteo|Taddei, Niccolò|Chiti, Fabrizio', 'Dipartimento di Scienze Biochimiche, Università degli studi di Firenze, Florence, Italy.|Dipartimento di Scienze Biochimiche, Università degli studi di Firenze, Florence, Italy.|Dipartimento di Scienze Biochimiche, Università degli studi di Firenze, Florence, Italy.|Dipartimento di Scienze Biochimiche, Università degli studi di Firenze, Florence, Italy.', 'Italy|Italy|Italy|Italy', 56, 'Algorithms|Amyloid|Computational Biology|Databases, Protein|Humans|Multiprotein Complexes|Protein Folding|Protein Interaction Mapping|Proteome|Proteomics|Subcellular Fractions', 'Journal Article', '10.1371/journal.pcbi.1000199', '18927604', 'Formation of amyloid-like fibrils is involved in numerous human protein deposition diseases, but is also an intrinsic property of polypeptide chains in general. Progress achieved recently now allows the aggregation propensity of proteins to be analyzed over large scales. In this work we used a previously developed predictive algorithm to analyze the propensity of the 34,180 protein sequences of the human proteome to form amyloid-like fibrils. We show that long proteins have, on average, less intense aggregation peaks than short ones. Human proteins involved in protein deposition diseases do not differ extensively from the rest of the proteome, further demonstrating the generality of protein aggregation. We were also able to reproduce some of the results obtained with other algorithms, demonstrating that they do not depend on the type of computational tool employed. For example, proteins with different subcellular localizations were found to have different aggregation propensities, in relation to the various efficiencies of quality control mechanisms. Membrane proteins, intrinsically disordered proteins, and folded proteins were confirmed to have very different aggregation propensities, as a consequence of their different structures and cellular microenvironments. In addition, gatekeeper residues at strategic positions of the sequences were found to protect human proteins from aggregation. The results of these comparative analyses highlight the existence of intimate links between the propensity of proteins to form aggregates with beta-structure and their biology. In particular, they emphasize the existence of a negative selection pressure that finely modulates protein sequences in order to adapt their aggregation propensity to their biological context.'),
(84035, 2008, 'plos', 'ChromaSig: a probabilistic approach to finding common chromatin signatures in the human genome', 'Hon, Gary|Ren, Bing|Wang, Wei', 'Bioinformatics Program, University of California San Diego, La Jolla, California, United States of America.|Bioinformatics Program, University of California San Diego, La Jolla, California, United States of America.|Bioinformatics Program, University of California San Diego, La Jolla, California, United States of America.', 'United States|United States|United States', 108, 'Artificial Intelligence|Chromatin|Chromatin Immunoprecipitation|Computational Biology|Enhancer Elements, Genetic|Genome, Human|HeLa Cells|Histones|Humans|Models, Genetic|Models, Statistical|Oligonucleotide Array Sequence Analysis|Promoter Regions, Genetic|Protein Processing, Post-Translational|Transcription Initiation Site', 'Journal Article', '10.1371/journal.pcbi.1000201', '18927605', 'Computational methods to identify functional genomic elements using genetic information have been very successful in determining gene structure and in identifying a handful of cis-regulatory elements. But the vast majority of regulatory elements have yet to be discovered, and it has become increasingly apparent that their discovery will not come from using genetic information alone. Recently, high-throughput technologies have enabled the creation of information-rich epigenetic maps, most notably for histone modifications. However, tools that search for functional elements using this epigenetic information have been lacking. Here, we describe an unsupervised learning method called ChromaSig to find, in an unbiased fashion, commonly occurring chromatin signatures in both tiling microarray and sequencing data. Applying this algorithm to nine chromatin marks across a 1% sampling of the human genome in HeLa cells, we recover eight clusters of distinct chromatin signatures, five of which correspond to known patterns associated with transcriptional promoters and enhancers. Interestingly, we observe that the distinct chromatin signatures found at enhancers mark distinct functional classes of enhancers in terms of transcription factor and coactivator binding. In addition, we identify three clusters of novel chromatin signatures that contain evolutionarily conserved sequences and potential cis-regulatory elements. Applying ChromaSig to a panel of 21 chromatin marks mapped genomewide by ChIP-Seq reveals 16 classes of genomic elements marked by distinct chromatin signatures. Interestingly, four classes containing enrichment for repressive histone modifications appear to be locally heterochromatic sites and are enriched in quickly evolving regions of the genome. The utility of this approach in uncovering novel, functionally significant genomic elements will aid future efforts of genome annotation via chromatin modifications.'),
(84036, 2008, 'plos', 'Fusion and fission of genes define a metric between fungal genomes', 'Durrens, Pascal|Nikolski, Macha|Sherman, David', 'MAGNOME Team, INRIA Centre de Recherche Bordeaux- Sud-Ouest, Laboratoire Bordelais de Recherche en Informatique, UMR 5800 CNRS, Domaine Universitaire, Talence Cedex, France. pascal.durrens@labri.fr|MAGNOME Team, INRIA Centre de Recherche Bordeaux- Sud-Ouest, Laboratoire Bordelais de Recherche en Informatique, UMR 5800 CNRS, Domaine Universitaire, Talence Cedex, France. pascal.durrens@labri.fr|MAGNOME Team, INRIA Centre de Recherche Bordeaux- Sud-Ouest, Laboratoire Bordelais de Recherche en Informatique, UMR 5800 CNRS, Domaine Universitaire, Talence Cedex, France. pascal.durrens@labri.fr', 'France|France|France', 17, 'Base Sequence|Computational Biology|DNA|Evolution, Molecular|Fungi|Gene Fusion|Genes, Fungal|Genetic Code|Genome, Fungal|Models, Genetic|Multigene Family|Neural Networks (Computer)|Phylogeny|Proteins|Species Specificity', 'Journal Article', '10.1371/journal.pcbi.1000200', '18949021', 'Gene fusion and fission events are key mechanisms in the evolution of gene architecture, whose effects are visible in protein architecture when they occur in coding sequences. Until now, the detection of fusion and fission events has been performed at the level of protein sequences with a post facto removal of supernumerary links due to paralogy, and often did not include looking for events defined only in single genomes. We propose a method for the detection of these events, defined on groups of paralogs to compensate for the gene redundancy of eukaryotic genomes, and apply it to the proteomes of 12 fungal species. We collected an inventory of 1,680 elementary fusion and fission events. In half the cases, both composite and element genes are found in the same species. Per-species counts of events correlate with the species genome size, suggesting a random mechanism of occurrence. Some biological functions of the genes involved in fusion and fission events are slightly over- or under-represented. As already noted in previous studies, the genes involved in an event tend to belong to the same functional category. We inferred the position of each event in the evolution tree of the 12 fungal species. The event localization counts for all the segments of the tree provide a metric that depicts the recombinational phylogeny among fungi. A possible interpretation of this metric as distance in adaptation space is proposed.'),
(84037, 2008, 'plos', 'Organization of physical interactomes as uncovered by network schemas', 'Banks, Eric|Nabieva, Elena|Chazelle, Bernard|Singh, Mona', 'Department of Computer Science & Lewis-Sigler Institute for Integrative Genomics, Princeton University, Princeton, New Jersey, United States of America.|Department of Computer Science & Lewis-Sigler Institute for Integrative Genomics, Princeton University, Princeton, New Jersey, United States of America.|Department of Computer Science & Lewis-Sigler Institute for Integrative Genomics, Princeton University, Princeton, New Jersey, United States of America.|Department of Computer Science & Lewis-Sigler Institute for Integrative Genomics, Princeton University, Princeton, New Jersey, United States of America.', 'Jersey|Jersey|Jersey|Jersey', 11, 'Animals|Carrier Proteins|Computational Biology|Databases, Protein|Humans|Intracellular Signaling Peptides and Proteins|Models, Biological|Neural Networks (Computer)|Pattern Recognition, Automated|Protein Interaction Domains and Motifs|Protein Interaction Mapping|Proteomics|Saccharomyces cerevisiae|Saccharomyces cerevisiae Proteins', 'Journal Article', '10.1371/journal.pcbi.1000203', '18949022', 'Large-scale protein-protein interaction networks provide new opportunities for understanding cellular organization and functioning. We introduce network schemas to elucidate shared mechanisms within interactomes. Network schemas specify descriptions of proteins and the topology of interactions among them. We develop algorithms for systematically uncovering recurring, over-represented schemas in physical interaction networks. We apply our methods to the S. cerevisiae interactome, focusing on schemas consisting of proteins described via sequence motifs and molecular function annotations and interacting with one another in one of four basic network topologies. We identify hundreds of recurring and over-represented network schemas of various complexity, and demonstrate via graph-theoretic representations how more complex schemas are organized in terms of their lower-order constituents. The uncovered schemas span a wide range of cellular activities, with many signaling and transport related higher-order schemas. We establish the functional importance of the schemas by showing that they correspond to functionally cohesive sets of proteins, are enriched in the frequency with which they have instances in the H. sapiens interactome, and are useful for predicting protein function. Our findings suggest that network schemas are a powerful paradigm for organizing, interrogating, and annotating cellular networks.'),
(84038, 2008, 'plos', 'The inactivation principle: mathematical solutions minimizing the absolute work and biological implications for the planning of arm movements', 'Berret, Bastien|Darlot, Christian|Jean, Frédéric|Pozzo, Thierry|Papaxanthis, Charalambos|Gauthier, Jean Paul', 'Université de Bourgogne, INSERM U887 Motricité-Plasticité, Dijon, France. bastien.berret@u-bourgogne.fr|Université de Bourgogne, INSERM U887 Motricité-Plasticité, Dijon, France. bastien.berret@u-bourgogne.fr|Université de Bourgogne, INSERM U887 Motricité-Plasticité, Dijon, France. bastien.berret@u-bourgogne.fr|Université de Bourgogne, INSERM U887 Motricité-Plasticité, Dijon, France. bastien.berret@u-bourgogne.fr|Université de Bourgogne, INSERM U887 Motricité-Plasticité, Dijon, France. bastien.berret@u-bourgogne.fr|Université de Bourgogne, INSERM U887 Motricité-Plasticité, Dijon, France. bastien.berret@u-bourgogne.fr', 'France|France|France|France|France|France', 79, 'Adult|Arm|Biomechanical Phenomena|Feedback|Gravitation|Humans|Joints|Male|Models, Biological|Movement|Muscle Contraction|Physical Exertion|Postural Balance|Psychomotor Performance|Range of Motion, Articular', 'Journal Article', '10.1371/journal.pcbi.1000194', '18949023', 'An important question in the literature focusing on motor control is to determine which laws drive biological limb movements. This question has prompted numerous investigations analyzing arm movements in both humans and monkeys. Many theories assume that among all possible movements the one actually performed satisfies an optimality criterion. In the framework of optimal control theory, a first approach is to choose a cost function and test whether the proposed model fits with experimental data. A second approach (generally considered as the more difficult) is to infer the cost function from behavioral data. The cost proposed here includes a term called the absolute work of forces, reflecting the mechanical energy expenditure. Contrary to most investigations studying optimality principles of arm movements, this model has the particularity of using a cost function that is not smooth. First, a mathematical theory related to both direct and inverse optimal control approaches is presented. The first theoretical result is the Inactivation Principle, according to which minimizing a term similar to the absolute work implies simultaneous inactivation of agonistic and antagonistic muscles acting on a single joint, near the time of peak velocity. The second theoretical result is that, conversely, the presence of non-smoothness in the cost function is a necessary condition for the existence of such inactivation. Second, during an experimental study, participants were asked to perform fast vertical arm movements with one, two, and three degrees of freedom. Observed trajectories, velocity profiles, and final postures were accurately simulated by the model. In accordance, electromyographic signals showed brief simultaneous inactivation of opposing muscles during movements. Thus, assuming that human movements are optimal with respect to a certain integral cost, the minimization of an absolute-work-like cost is supported by experimental observations. Such types of optimality criteria may be applied to a large range of biological movements.'),
(84039, 2008, 'plos', 'An end to endless forms: epistasis, phenotype distribution bias, and nonuniform evolution', 'Borenstein, Elhanan|Krakauer, David C', 'Department of Biological Sciences, Stanford University, Stanford, California, United States of America. ebo@stanford.edu|Department of Biological Sciences, Stanford University, Stanford, California, United States of America. ebo@stanford.edu', 'United States|United States', 30, 'Animals|Anthropology, Physical|Biological Evolution|Epistasis, Genetic|Gene Regulatory Networks|Genotype|Growth and Development|Humans|Models, Genetic|Mutation|Phenotype|Physiology, Comparative', 'Journal Article', '10.1371/journal.pcbi.1000202', '18949026', 'Studies of the evolution of development characterize the way in which gene regulatory dynamics during ontogeny constructs and channels phenotypic variation. These studies have identified a number of evolutionary regularities: (1) phenotypes occupy only a small subspace of possible phenotypes, (2) the influence of mutation is not uniform and is often canalized, and (3) a great deal of morphological variation evolved early in the history of multicellular life. An important implication of these studies is that diversity is largely the outcome of the evolution of gene regulation rather than the emergence of new, structural genes. Using a simple model that considers a generic property of developmental maps-the interaction between multiple genetic elements and the nonlinearity of gene interaction in shaping phenotypic traits-we are able to recover many of these empirical regularities. We show that visible phenotypes represent only a small fraction of possibilities. Epistasis ensures that phenotypes are highly clustered in morphospace and that the most frequent phenotypes are the most similar. We perform phylogenetic analyses on an evolving, developmental model and find that species become more alike through time, whereas higher-level grades have a tendency to diverge. Ancestral phenotypes, produced by early developmental programs with a low level of gene interaction, are found to span a significantly greater volume of the total phenotypic space than derived taxa. We suggest that early and late evolution have a different character that we classify into micro- and macroevolutionary configurations. These findings complement the view of development as a key component in the production of endless forms and highlight the crucial role of development in constraining biotic diversity and evolutionary trajectories.'),
(84040, 2008, 'plos', 'The rough guide to in silico function prediction, or how to use sequence and structure information to predict protein function', 'Punta, Marco|Ofran, Yanay', 'Department of Biochemistry and Molecular Biophysics, Columbia University, New York, NY, USA.|Department of Biochemistry and Molecular Biophysics, Columbia University, New York, NY, USA.', 'United States|United States', 74, 'Computational Biology|Databases, Protein|Forecasting|Proteins|Structure-Activity Relationship', 'Journal Article', '10.1371/journal.pcbi.1000160', '18974821', '-'),
(84041, 2008, 'plos', 'Support vector machines and kernels for computational biology', 'Ben-Hur, Asa|Ong, Cheng Soon|Sonnenburg, Sören|Schölkopf, Bernhard|Rätsch, Gunnar', 'Department of Computer Science, Colorado State University, Fort Collins, CO, USA.|Department of Computer Science, Colorado State University, Fort Collins, CO, USA.|Department of Computer Science, Colorado State University, Fort Collins, CO, USA.|Department of Computer Science, Colorado State University, Fort Collins, CO, USA.|Department of Computer Science, Colorado State University, Fort Collins, CO, USA.', 'United States|United States|United States|United States|United States', 352, 'Artificial Intelligence|Computational Biology|Decision Support Techniques|Information Storage and Retrieval|Pattern Recognition, Automated|Software|Statistics as Topic', 'Journal Article', '10.1371/journal.pcbi.1000173', '18974822', '-'),
(84042, 2008, 'plos', 'Genome-scale reconstruction and analysis of the Pseudomonas putida KT2440 metabolic network facilitates applications in biotechnology', 'Puchaxc5x82ka, Jacek|Oberhardt, Matthew A|Godinho, Miguel|Bielecka, Agata|Regenhardt, Daniela|Timmis, Kenneth N|Papin, Jason A|Martins dos Santos, Vxc3xadtor A P', 'Synthetic and Systems Biology Group, Helmholtz Center for Infection Research (HZI), Braunschweig, Germany.|Synthetic and Systems Biology Group, Helmholtz Center for Infection Research (HZI), Braunschweig, Germany.|Synthetic and Systems Biology Group, Helmholtz Center for Infection Research (HZI), Braunschweig, Germany.|Synthetic and Systems Biology Group, Helmholtz Center for Infection Research (HZI), Braunschweig, Germany.|Synthetic and Systems Biology Group, Helmholtz Center for Infection Research (HZI), Braunschweig, Germany.|Synthetic and Systems Biology Group, Helmholtz Center for Infection Research (HZI), Braunschweig, Germany.|Synthetic and Systems Biology Group, Helmholtz Center for Infection Research (HZI), Braunschweig, Germany.|Synthetic and Systems Biology Group, Helmholtz Center for Infection Research (HZI), Braunschweig, Germany.', 'Germany|Germany|Germany|Germany|Germany|Germany|Germany|Germany', 183, 'Biocatalysis|Biomass|Biotechnology|Databases, Genetic|Genome, Bacterial|Genomics|Metabolic Networks and Pathways|Models, Biological|Mutagenesis, Site-Directed|Polyhydroxyalkanoates|Pseudomonas putida|Systems Biology', 'Journal Article', '10.1371/journal.pcbi.1000210', '18974823', 'A cornerstone of biotechnology is the use of microorganisms for the efficient production of chemicals and the elimination of harmful waste. Pseudomonas putida is an archetype of such microbes due to its metabolic versatility, stress resistance, amenability to genetic modifications, and vast potential for environmental and industrial applications. To address both the elucidation of the metabolic wiring in P. putida and its uses in biocatalysis, in particular for the production of non-growth-related biochemicals, we developed and present here a genome-scale constraint-based model of the metabolism of P. putida KT2440. Network reconstruction and flux balance analysis (FBA) enabled definition of the structure of the metabolic network, identification of knowledge gaps, and pin-pointing of essential metabolic functions, facilitating thereby the refinement of gene annotations. FBA and flux variability analysis were used to analyze the properties, potential, and limits of the model. These analyses allowed identification, under various conditions, of key features of metabolism such as growth yield, resource distribution, network robustness, and gene essentiality. The model was validated with data from continuous cell cultures, high-throughput phenotyping data, (13)C-measurement of internal flux distributions, and specifically generated knock-out mutants. Auxotrophy was correctly predicted in 75% of the cases. These systematic analyses revealed that the metabolic network structure is the main factor determining the accuracy of predictions, whereas biomass composition has negligible influence. Finally, we drew on the model to devise metabolic engineering strategies to improve production of polyhydroxyalkanoates, a class of biotechnologically useful compounds whose synthesis is not coupled to cell survival. The solidly validated model yields valuable insights into genotype-phenotype relationships and provides a sound framework to explore this versatile bacterium and to capitalize on its vast biotechnological potential.'),
(84043, 2008, 'plos', 'The effects of NR2 subunit-dependent NMDA receptor kinetics on synaptic transmission and CaMKII activation', 'Santucci, David M|Raghavachari, Sridhar', 'Department of Neurobiology, Duke University Medical Center, Durham, NC, USA.|Department of Neurobiology, Duke University Medical Center, Durham, NC, USA.', 'United States|United States', 38, 'Animals|Calcium Signaling|Calcium-Calmodulin-Dependent Protein Kinase Type 2|Glutamic Acid|Hippocampus|Ion Channel Gating|Kinetics|Long-Term Potentiation|Membrane Potentials|Models, Biological|Protein Isoforms|Protein Subunits|Rats|Receptors, N-Methyl-D-Aspartate|Structure-Activity Relationship|Synapses|Synaptic Transmission', 'Journal Article', '10.1371/journal.pcbi.1000208', '18974824', 'N-Methyl-D-aspartic acid (NMDA) receptors are widely expressed in the brain and are critical for many forms of synaptic plasticity. Subtypes of the NMDA receptor NR2 subunit are differentially expressed during development, in the forebrain, the NR2B receptor is dominant early in development, and later both NR2A and NR2B are expressed. In heterologous expression systems, NR2A-containing receptors open more reliably and show much faster opening and closing kinetics than do NR2B-containing receptors. However, conflicting data, showing similar open probabilities, exist for receptors expressed in neurons. Similarly, studies of synaptic plasticity have produced divergent results, with some showing that only NR2A-containing receptors can drive long-term potentiation and others showing that either subtype is capable of driving potentiation. In order to address these conflicting results as well as open questions about the number and location of functional receptors in the synapse, we constructed a Monte Carlo model of glutamate release, diffusion, and binding to NMDA receptors and of receptor opening and closing as well as a model of the activation of calcium-calmodulin kinase II, an enzyme critical for induction of synaptic plasticity, by NMDA receptor-mediated calcium influx. Our results suggest that the conflicting data concerning receptor open probabilities can be resolved, with NR2A- and NR2B-containing receptors having very different opening probabilities. They also support the conclusion that receptors containing either subtype can drive long-term potentiation. We also are able to estimate the number of functional receptors at a synapse from experimental data. Finally, in our models, the opening of NR2B-containing receptors is highly dependent on the location of the receptor relative to the site of glutamate release whereas the opening of NR2A-containing receptors is not. These results help to clarify the previous findings and suggest future experiments to address open questions concerning NMDA receptor function.'),
(84044, 2008, 'plos', 'Flux-based transport enhancement as a plausible unifying mechanism for auxin transport in meristem development', 'Stoma, Szymon|Lucas, Mikael|Chopard, Jérôme|Schaedel, Marianne|Traas, Jan|Godin, Christophe', 'Virtual Plants Project-Team, UMR DAP, INRIA, Montpellier, France.|Virtual Plants Project-Team, UMR DAP, INRIA, Montpellier, France.|Virtual Plants Project-Team, UMR DAP, INRIA, Montpellier, France.|Virtual Plants Project-Team, UMR DAP, INRIA, Montpellier, France.|Virtual Plants Project-Team, UMR DAP, INRIA, Montpellier, France.|Virtual Plants Project-Team, UMR DAP, INRIA, Montpellier, France.', 'France|France|France|France|France|France', 120, 'Cell Polarity|Facilitated Diffusion|Indoleacetic Acids|Membrane Transport Proteins|Meristem|Models, Biological|Plant Physiological Phenomena|Protein Transport|Signal Transduction', 'Journal Article', '10.1371/journal.pcbi.1000207', '18974825', 'Plants continuously generate new organs through the activity of populations of stem cells called meristems. The shoot apical meristem initiates leaves, flowers, and lateral meristems in highly ordered, spiralled, or whorled patterns via a process called phyllotaxis. It is commonly accepted that the active transport of the plant hormone auxin plays a major role in this process. Current hypotheses propose that cellular hormone transporters of the PIN family would create local auxin maxima at precise positions, which in turn would lead to organ initiation. To explain how auxin transporters could create hormone fluxes to distinct regions within the plant, different concepts have been proposed. A major hypothesis, canalization, proposes that the auxin transporters act by amplifying and stabilizing existing fluxes, which could be initiated, for example, by local diffusion. This convincingly explains the organised auxin fluxes during vein formation, but for the shoot apical meristem a second hypothesis was proposed, where the hormone would be systematically transported towards the areas with the highest concentrations. This implies the coexistence of two radically different mechanisms for PIN allocation in the membrane, one based on flux sensing and the other on local concentration sensing. Because these patterning processes require the interaction of hundreds of cells, it is impossible to estimate on a purely intuitive basis if a particular scenario is plausible or not. Therefore, computational modelling provides a powerful means to test this type of complex hypothesis. Here, using a dedicated computer simulation tool, we show that a flux-based polarization hypothesis is able to explain auxin transport at the shoot meristem as well, thus providing a unifying concept for the control of auxin distribution in the plant. Further experiments are now required to distinguish between flux-based polarization and other hypotheses.'),
(84045, 2008, 'plos', 'Cell groups reveal structure of stimulus space', 'Curto, Carina|Itskov, Vladimir', 'Center for Molecular and Behavioral Neuroscience, Rutgers, The State University of New Jersey, Newark, NJ, USA.|Center for Molecular and Behavioral Neuroscience, Rutgers, The State University of New Jersey, Newark, NJ, USA.', 'Jersey|Jersey', 0, 'Action Potentials|Animals|Conditioning, Classical|Conditioning, Operant|Generalization, Stimulus|Hippocampus|Models, Neurological|Nerve Net|Neurons|Orientation|Pattern Recognition, Physiological|Set (Psychology)|Space Perception', 'Journal Article', '10.1371/journal.pcbi.1000205', '18974826', 'An important task of the brain is to represent the outside world. It is unclear how the brain may do this, however, as it can only rely on neural responses and has no independent access to external stimuli in order to decode what those responses mean. We investigate what can be learned about a space of stimuli using only the action potentials (spikes) of cells with stereotyped -- but unknown -- receptive fields. Using hippocampal place cells as a model system, we show that one can (1) extract global features of the environment and (2) construct an accurate representation of space, up to an overall scale factor, that can be used to track the animals position. Unlike previous approaches to reconstructing position from place cell activity, this information is derived without knowing place fields or any other functions relating neural responses to position. We find that simply knowing which groups of cells fire together reveals a surprising amount of structure in the underlying stimulus space, this may enable the brain to construct its own internal representations.'),
(84046, 2008, 'plos', 'Defrosting the digital library: bibliographic tools for the next generation web', 'Hull, Duncan|Pettifer, Steve R|Kell, Douglas B', 'School of Chemistry, The University of Manchester, Manchester, UK. duncan.hull@cs.man.ac.uk|School of Chemistry, The University of Manchester, Manchester, UK. duncan.hull@cs.man.ac.uk|School of Chemistry, The University of Manchester, Manchester, UK. duncan.hull@cs.man.ac.uk', 'United Kingdom|United Kingdom|United Kingdom', 0, 'Database Management Systems|Databases, Bibliographic|Humans|Internet|Libraries, Digital|Library Automation|Library Collection Development', 'Journal Article', '10.1371/journal.pcbi.1000204', '18974831', 'Many scientists now manage the bulk of their bibliographic information electronically, thereby organizing their publications and citation material from digital libraries. However, a library has been described as thought in cold storage, and unfortunately many digital libraries can be cold, impersonal, isolated, and inaccessible places. In this Review, we discuss the current chilly state of digital libraries for the computational biologist, including PubMed, IEEE Xplore, the ACM digital library, ISI Web of Knowledge, Scopus, Citeseer, arXiv, DBLP, and Google Scholar. We illustrate the current process of using these libraries with a typical workflow, and highlight problems with managing data and metadata using URIs. We then examine a range of new applications such as Zotero, Mendeley, Mekentosj Papers, MyNCBI, CiteULike, Connotea, and HubMed that exploit the Web to make these digital libraries more personal, sociable, integrated, and accessible places. We conclude with how these applications may begin to help achieve a digital defrost, and discuss some of the issues that will help or hinder this in terms of making libraries on the Web warmer places in the future, becoming resources that are considerably more useful to both humans and machines.'),
(84047, 2008, 'plos', 'Facilitated variation: how evolution learns from past environments to generalize to new environments', 'Parter, Merav|Kashtan, Nadav|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.', 'Israel|Israel|Israel', 0, 'Adaptation, Biological|Animals|Biological Evolution|Environment|Genetics, Population|Humans|Models, Genetic|Mutation|Nerve Net|Nucleic Acid Conformation|Phenotype|RNA|Selection, Genetic', 'Journal Article', '10.1371/journal.pcbi.1000206', '18989390', 'One of the striking features of evolution is the appearance of novel structures in organisms. Recently, Kirschner and Gerhart have integrated discoveries in evolution, genetics, and developmental biology to form a theory of facilitated variation (FV). The key observation is that organisms are designed such that random genetic changes are channeled in phenotypic directions that are potentially useful. An open question is how FV spontaneously emerges during evolution. Here, we address this by means of computer simulations of two well-studied model systems, logic circuits and RNA secondary structure. We find that evolution of FV is enhanced in environments that change from time to time in a systematic way: the varying environments are made of the same set of subgoals but in different combinations. We find that organisms that evolve under such varying goals not only remember their history but also generalize to future environments, exhibiting high adaptability to novel goals. Rapid adaptation is seen to goals composed of the same subgoals in novel combinations, and to goals where one of the subgoals was never seen in the history of the organism. The mechanisms for such enhanced generation of novelty (generalization) are analyzed, as is the way that organisms store information in their genomes about their past environments. Elements of facilitated variation theory, such as weak regulatory linkage, modularity, and reduced pleiotropy of mutations, evolve spontaneously under these conditions. Thus, environments that change in a systematic, modular fashion seem to promote facilitated variation and allow evolution to generalize to novel conditions.'),
(84048, 2008, 'plos', 'Hierarchical models in the brain', 'Friston, Karl', 'The Wellcome Trust Centre of Neuroimaging, University College London, London, United Kingdom. k.friston@fil.ion.ucl.ac.uk', 'United Kingdom', 0, 'Algorithms|Animals|Brain|Humans|Linear Models|Mental Processes|Models, Neurological|Nerve Net|Neural Networks (Computer)|Nonlinear Dynamics|Probability', 'Journal Article', '10.1371/journal.pcbi.1000211', '18989391', 'This paper describes a general model that subsumes many parametric models for continuous data. The model comprises hidden layers of state-space or dynamic causal models, arranged so that the output of one provides input to another. The ensuing hierarchy furnishes a model for many types of data, of arbitrary complexity. Special cases range from the general linear model for static data to generalised convolution models, with system noise, for nonlinear time-series analysis. Crucially, all of these models can be inverted using exactly the same scheme, namely, dynamic expectation maximization. This means that a single model and optimisation scheme can be used to invert a wide range of models. We present the model and a brief review of its inversion to disclose the relationships among, apparently, diverse generative models of empirical data. We then show that this inversion can be formulated as a simple neural network and may provide a useful metaphor for inference and learning in the brain.'),
(84049, 2008, 'plos', 'A model of brain circulation and metabolism: NIRS signal changes during physiological challenges', 'Banaji, Murad|Mallet, Alfred|Elwell, Clare E|Nicholls, Peter|Cooper, Chris E', 'Department of Biological Sciences, University of Essex, Colchester, United Kingdom. m.banaji@ucl.ac.uk|Department of Biological Sciences, University of Essex, Colchester, United Kingdom. m.banaji@ucl.ac.uk|Department of Biological Sciences, University of Essex, Colchester, United Kingdom. m.banaji@ucl.ac.uk|Department of Biological Sciences, University of Essex, Colchester, United Kingdom. m.banaji@ucl.ac.uk|Department of Biological Sciences, University of Essex, Colchester, United Kingdom. m.banaji@ucl.ac.uk', 'United Kingdom|United Kingdom|United Kingdom|United Kingdom|United Kingdom', 61, 'Animals|Brain|Cerebrovascular Circulation|Electron Transport Complex IV|Energy Metabolism|Hemodynamics|Humans|Models, Biological|Oxidation-Reduction|Oxygen|Oxygen Consumption|Spectroscopy, Near-Infrared|Systems Biology|Thermodynamics', 'Journal Article', '10.1371/journal.pcbi.1000212', '18989392', 'We construct a model of brain circulation and energy metabolism. The model is designed to explain experimental data and predict the response of the circulation and metabolism to a variety of stimuli, in particular, changes in arterial blood pressure, CO(2) levels, O(2) levels, and functional activation. Significant model outputs are predictions about blood flow, metabolic rate, and quantities measurable noninvasively using near-infrared spectroscopy (NIRS), including cerebral blood volume and oxygenation and the redox state of the Cu(A) centre in cytochrome c oxidase. These quantities are now frequently measured in clinical settings, however the relationship between the measurements and the underlying physiological events is in general complex. We anticipate that the model will play an important role in helping to understand the NIRS signals, in particular, the cytochrome signal, which has been hard to interpret. A range of model simulations are presented, and model outputs are compared to published data obtained from both in vivo and in vitro settings. The comparisons are encouraging, showing that the model is able to reproduce observed behaviour in response to various stimuli.'),
(84050, 2008, 'plos', 'Transmembrane topology and signal peptide prediction using dynamic bayesian networks', 'Reynolds, Sheila M|Käll, Lukas|Riffle, Michael E|Bilmes, Jeff A|Noble, William Stafford', 'Department of Electrical Engineering, University of Washington, Seattle, Washington, United States of America.|Department of Electrical Engineering, University of Washington, Seattle, Washington, United States of America.|Department of Electrical Engineering, University of Washington, Seattle, Washington, United States of America.|Department of Electrical Engineering, University of Washington, Seattle, Washington, United States of America.|Department of Electrical Engineering, University of Washington, Seattle, Washington, United States of America.', 'United States|United States|United States|United States|United States', 0, 'Artificial Intelligence|Bayes Theorem|Computational Biology|Fungal Proteins|Markov Chains|Membrane Proteins|Models, Molecular|Neural Networks (Computer)|Protein Conformation|Protein Sorting Signals|Reproducibility of Results|Yeasts', 'Journal Article', '10.1371/journal.pcbi.1000213', '18989393', 'Hidden Markov models (HMMs) have been successfully applied to the tasks of transmembrane protein topology prediction and signal peptide prediction. In this paper we expand upon this work by making use of the more powerful class of dynamic Bayesian networks (DBNs). Our model, Philius, is inspired by a previously published HMM, Phobius, and combines a signal peptide submodel with a transmembrane submodel. We introduce a two-stage DBN decoder that combines the power of posterior decoding with the grammar constraints of Viterbi-style decoding. Philius also provides protein type, segment, and topology confidence metrics to aid in the interpretation of the predictions. We report a relative improvement of 13% over Phobius in full-topology prediction accuracy on transmembrane proteins, and a sensitivity and specificity of 0.96 in detecting signal peptides. We also show that our confidence metrics correlate well with the observed precision. In addition, we have made predictions on all 6.3 million proteins in the Yeast Resource Center (YRC) database. This large-scale study provides an overall picture of the relative numbers of proteins that include a signal-peptide and/or one or more transmembrane segments as well as a valuable resource for the scientific community. All DBNs are implemented using the Graphical Models Toolkit. Source code for the models described here is available at http://noble.gs.washington.edu/proj/philius. A Philius Web server is available at http://www.yeastrc.org/philius, and the predictions on the YRC database are available at http://www.yeastrc.org/pdr.'),
(84051, 2008, 'plos', 'Evolutionary modeling of rate shifts reveals specificity determinants in HIV-1 subtypes', 'Penn, Osnat|Stern, Adi|Rubinstein, Nimrod D|Dutheil, Julien|Bacharach, Eran|Galtier, Nicolas|Pupko, Tal', 'Department of Cell Research and Immunology, George S Wise Faculty of Life Sciences, Tel Aviv University, Tel Aviv, Israel.|Department of Cell Research and Immunology, George S Wise Faculty of Life Sciences, Tel Aviv University, Tel Aviv, Israel.|Department of Cell Research and Immunology, George S Wise Faculty of Life Sciences, Tel Aviv University, Tel Aviv, Israel.|Department of Cell Research and Immunology, George S Wise Faculty of Life Sciences, Tel Aviv University, Tel Aviv, Israel.|Department of Cell Research and Immunology, George S Wise Faculty of Life Sciences, Tel Aviv University, Tel Aviv, Israel.|Department of Cell Research and Immunology, George S Wise Faculty of Life Sciences, Tel Aviv University, Tel Aviv, Israel.|Department of Cell Research and Immunology, George S Wise Faculty of Life Sciences, Tel Aviv University, Tel Aviv, Israel.', 'Israel|Israel|Israel|Israel|Israel|Israel|Israel', 22, 'Adaptation, Biological|Amino Acid Sequence|Bayes Theorem|Drug Resistance, Multiple, Viral|Evolution, Molecular|Genetic Speciation|Geography|HIV Infections|HIV-1|Humans|Models, Biological|Phylogeny|Proteomics|Time Factors|Virus Internalization', 'Journal Article', '10.1371/journal.pcbi.1000214', '18989394', 'A hallmark of the human immunodeficiency virus 1 (HIV-1) is its rapid rate of evolution within and among its various subtypes. Two complementary hypotheses are suggested to explain the sequence variability among HIV-1 subtypes. The first suggests that the functional constraints at each site remain the same across all subtypes, and the differences among subtypes are a direct reflection of random substitutions, which have occurred during the time elapsed since their divergence. The alternative hypothesis suggests that the functional constraints themselves have evolved, and thus sequence differences among subtypes in some sites reflect shifts in function. To determine the contribution of each of these two alternatives to HIV-1 subtype evolution, we have developed a novel Bayesian method for testing and detecting site-specific rate shifts. The RAte Shift EstimatoR (RASER) method determines whether or not site-specific functional shifts characterize the evolution of a protein and, if so, points to the specific sites and lineages in which these shifts have most likely occurred. Applying RASER to a dataset composed of large samples of HIV-1 sequences from different group M subtypes, we reveal rampant evolutionary shifts throughout the HIV-1 proteome. Most of these rate shifts have occurred during the divergence of the major subtypes, establishing that subtype divergence occurred together with functional diversification. We report further evidence for the emergence of a new sub-subtype, characterized by abundant rate-shifting sites. When focusing on the rate-shifting sites detected, we find that many are associated with known function relating to viral life cycle and drug resistance. Finally, we discuss mechanisms of covariation of rate-shifting sites.'),
(84052, 2008, 'plos', 'Distinct modes of regulation by chromatin encoded through nucleosome positioning signals', 'Field, Yair|Kaplan, Noam|Fondufe-Mittendorf, Yvonne|Moore, Irene K|Sharon, Eilon|Lubling, Yaniv|Widom, Jonathan|Segal, Eran', 'Department of Computer Science and Applied Mathematics, Weizmann Institute of Science, Rehovot, Israel.|Department of Computer Science and Applied Mathematics, Weizmann Institute of Science, Rehovot, Israel.|Department of Computer Science and Applied Mathematics, Weizmann Institute of Science, Rehovot, Israel.|Department of Computer Science and Applied Mathematics, Weizmann Institute of Science, Rehovot, Israel.|Department of Computer Science and Applied Mathematics, Weizmann Institute of Science, Rehovot, Israel.|Department of Computer Science and Applied Mathematics, Weizmann Institute of Science, Rehovot, Israel.|Department of Computer Science and Applied Mathematics, Weizmann Institute of Science, Rehovot, Israel.|Department of Computer Science and Applied Mathematics, Weizmann Institute of Science, Rehovot, Israel.', 'Israel|Israel|Israel|Israel|Israel|Israel|Israel|Israel', 314, 'Animals|Base Sequence|Binding Sites|Chromatin Assembly and Disassembly|DNA, Fungal|Drosophila melanogaster|Gene Expression Regulation, Fungal|HeLa Cells|Humans|Locus Control Region|Nucleosomes|Saccharomyces cerevisiae|Transcription Factors|Transcription, Genetic', 'Journal Article', '10.1371/journal.pcbi.1000216', '18989395', 'The detailed positions of nucleosomes profoundly impact gene regulation and are partly encoded by the genomic DNA sequence. However, less is known about the functional consequences of this encoding. Here, we address this question using a genome-wide map of approximately 380,000 yeast nucleosomes that we sequenced in their entirety. Utilizing the high resolution of our map, we refine our understanding of how nucleosome organizations are encoded by the DNA sequence and demonstrate that the genomic sequence is highly predictive of the in vivo nucleosome organization, even across new nucleosome-bound sequences that we isolated from fly and human. We find that Poly(dA:dT) tracts are an important component of these nucleosome positioning signals and that their nucleosome-disfavoring action results in large nucleosome depletion over them and over their flanking regions and enhances the accessibility of transcription factors to their cognate sites. Our results suggest that the yeast genome may utilize these nucleosome positioning signals to regulate gene expression with different transcriptional noise and activation kinetics and DNA replication with different origin efficiency. These distinct functions may be achieved by encoding both relatively closed (nucleosome-covered) chromatin organizations over some factor binding sites, where factors must compete with nucleosomes for DNA access, and relatively open (nucleosome-depleted) organizations over other factor sites, where factors bind without competition.');
INSERT INTO `papers` (`id`, `ano`, `journal`, `titulo`, `autores`, `afiliacao`, `pais`, `citacoes`, `palavra_chave`, `categorias`, `doi`, `pubmed`, `abstract`) VALUES
(84053, 2008, 'plos', 'Inferring pathway activity toward precise disease classification', 'Lee, Eunjung|Chuang, Han-Yu|Kim, Jong-Won|Ideker, Trey|Lee, Doheon', 'Department of Bio and Brain Engineering, KAIST, Daejeon, South Korea.|Department of Bio and Brain Engineering, KAIST, Daejeon, South Korea.|Department of Bio and Brain Engineering, KAIST, Daejeon, South Korea.|Department of Bio and Brain Engineering, KAIST, Daejeon, South Korea.|Department of Bio and Brain Engineering, KAIST, Daejeon, South Korea.', '-|-|-|-|-', 0, 'Artificial Intelligence|Biomarkers, Tumor|Diagnostic Techniques and Procedures|Gene Expression|Gene Expression Profiling|HeLa Cells|Humans|Neoplasms|Pattern Recognition, Automated|Prognosis|Signal Transduction|Systems Integration', 'Journal Article', '10.1371/journal.pcbi.1000217', '18989396', 'The advent of microarray technology has made it possible to classify disease states based on gene expression profiles of patients. Typically, marker genes are selected by measuring the power of their expression profiles to discriminate among patients of different disease states. However, expression-based classification can be challenging in complex diseases due to factors such as cellular heterogeneity within a tissue sample and genetic heterogeneity across patients. A promising technique for coping with these challenges is to incorporate pathway information into the disease classification procedure in order to classify disease based on the activity of entire signaling pathways or protein complexes rather than on the expression levels of individual genes or proteins. We propose a new classification method based on pathway activities inferred for each patient. For each pathway, an activity level is summarized from the gene expression levels of its condition-responsive genes (CORGs), defined as the subset of genes in the pathway whose combined expression delivers optimal discriminative power for the disease phenotype. We show that classifiers using pathway activity achieve better performance than classifiers based on individual gene expression, for both simple and complex case-control studies including differentiation of perturbed from non-perturbed cells and subtyping of several different kinds of cancer. Moreover, the new method outperforms several previous approaches that use a static (i.e., non-conditional) definition of pathways. Within a pathway, the identified CORGs may facilitate the development of better diagnostic markers and the discovery of core alterations in human disease.'),
(84054, 2008, 'plos', 'Genome-wide analysis of human disease alleles reveals that their locations are correlated in paralogous proteins', 'Yandell, Mark|Moore, Barry|Salas, Fidel|Mungall, Chris|MacBride, Andrew|White, Charles|Reese, Martin G', 'Eccles Institute of Human Genetics, University of Utah and School of Medicine, Salt Lake City, Utah, United States of America. myandell@genetics.utah.edu|Eccles Institute of Human Genetics, University of Utah and School of Medicine, Salt Lake City, Utah, United States of America. myandell@genetics.utah.edu|Eccles Institute of Human Genetics, University of Utah and School of Medicine, Salt Lake City, Utah, United States of America. myandell@genetics.utah.edu|Eccles Institute of Human Genetics, University of Utah and School of Medicine, Salt Lake City, Utah, United States of America. myandell@genetics.utah.edu|Eccles Institute of Human Genetics, University of Utah and School of Medicine, Salt Lake City, Utah, United States of America. myandell@genetics.utah.edu|Eccles Institute of Human Genetics, University of Utah and School of Medicine, Salt Lake City, Utah, United States of America. myandell@genetics.utah.edu|Eccles Institute of Human Genetics, University of Utah and School of Medicine, Salt Lake City, Utah, United States of America. myandell@genetics.utah.edu', 'United States|United States|United States|United States|United States|United States|United States', 0, 'Alleles|Amino Acid Sequence|Chromosome Mapping|Clinical Laboratory Techniques|Computational Biology|Databases, Genetic|Disease|Evolution, Molecular|Gene Frequency|Genetic Markers|Genetic Speciation|Genome, Human|Humans|Linkage Disequilibrium|Phenotype|Polymorphism, Single Nucleotide|Proteins|Sequence Alignment', 'Journal Article', '10.1371/journal.pcbi.1000218', '18989397', 'The millions of mutations and polymorphisms that occur in human populations are potential predictors of disease, of our reactions to drugs, of predisposition to microbial infections, and of age-related conditions such as impaired brain and cardiovascular functions. However, predicting the phenotypic consequences and eventual clinical significance of a sequence variant is not an easy task. Computational approaches have found perturbation of conserved amino acids to be a useful criterion for identifying variants likely to have phenotypic consequences. To our knowledge, however, no study to date has explored the potential of variants that occur at homologous positions within paralogous human proteins as a means of identifying polymorphisms with likely phenotypic consequences. In order to investigate the potential of this approach, we have assembled a unique collection of known disease-causing variants from OMIM and the Human Genome Mutation Database (HGMD) and used them to identify and characterize pairs of sequence variants that occur at homologous positions within paralogous human proteins. Our analyses demonstrate that the locations of variants are correlated in paralogous proteins. Moreover, if one member of a variant-pair is disease-causing, its partner is likely to be disease-causing as well. Thus, information about variant-pairs can be used to identify potentially disease-causing variants, extend existing procedures for polymorphism prioritization, and provide a suite of candidates for further diagnostic and therapeutic purposes.'),
(84055, 2008, 'plos', 'Emergence of functional hierarchy in a multiple timescale neural network model: a humanoid robot experiment', 'Yamashita, Yuichi|Tani, Jun', 'Laboratory for Behavior and Dynamic Cognition, RIKEN Brain Science Institute, Wako-shi, Saitama, Japan. yamay@brain.riken.jp|Laboratory for Behavior and Dynamic Cognition, RIKEN Brain Science Institute, Wako-shi, Saitama, Japan. yamay@brain.riken.jp', 'Japan|Japan', 276, 'Generalization, Stimulus|Higher Nervous Activity|Humans|Models, Neurological|Nerve Net|Neural Networks (Computer)|Neuronal Plasticity|Neurons|Psychomotor Performance|Robotics|Synapses|Systems Biology|Time Factors', 'Journal Article', '10.1371/journal.pcbi.1000220', '18989398', 'It is generally thought that skilled behavior in human beings results from a functional hierarchy of the motor control system, within which reusable motor primitives are flexibly integrated into various sensori-motor sequence patterns. The underlying neural mechanisms governing the way in which continuous sensori-motor flows are segmented into primitives and the way in which series of primitives are integrated into various behavior sequences have, however, not yet been clarified. In earlier studies, this functional hierarchy has been realized through the use of explicit hierarchical structure, with local modules representing motor primitives in the lower level and a higher module representing sequences of primitives switched via additional mechanisms such as gate-selecting. When sequences contain similarities and overlap, however, a conflict arises in such earlier models between generalization and segmentation, induced by this separated modular structure. To address this issue, we propose a different type of neural network model. The current model neither makes use of separate local modules to represent primitives nor introduces explicit hierarchical structure. Rather than forcing architectural hierarchy onto the system, functional hierarchy emerges through a form of self-organization that is based on two distinct types of neurons, each with different time properties (multiple timescales). Through the introduction of multiple timescales, continuous sequences of behavior are segmented into reusable primitives, and the primitives, in turn, are flexibly integrated into novel sequences. In experiments, the proposed network model, coordinating the physical body of a humanoid robot through high-dimensional sensori-motor control, also successfully situated itself within a physical environment. Our results suggest that it is not only the spatial connections between neurons but also the timescales of neural activity that act as important mechanisms leading to functional hierarchy in neural systems.'),
(84056, 2008, 'plos', 'Cavities and atomic packing in protein structures and interfaces', 'Sonavane, Shrihari|Chakrabarti, Pinak', 'Department of Biochemistry, Bose Institute, Calcutta, India.|Department of Biochemistry, Bose Institute, Calcutta, India.', 'India|India', 0, 'Bacillus|Computational Biology|Dimerization|Hydrogen Bonding|Ligands|Models, Molecular|Molecular Conformation|Protein Binding|Protein Conformation|Protein Structure, Secondary|Protein Structure, Tertiary|Proteins|Solvents|Water', 'Journal Article', '10.1371/journal.pcbi.1000188', '19005575', 'A comparative analysis of cavities enclosed in a tertiary structure of proteins and interfaces formed by the interaction of two protein subunits in obligate and non-obligate categories (represented by homodimeric molecules and heterocomplexes, respectively) is presented. The total volume of cavities increases with the size of the protein (or the interface), though the exact relationship may vary in different cases. Likewise, for individual cavities also there is quantitative dependence of the volume on the number of atoms (or residues) lining the cavity. The larger cavities tend to be less spherical, solvated, and the interfaces are enriched in these. On average 15 A(3) of cavity volume is found to accommodate single water, with another 40-45 A(3) needed for each additional solvent molecule. Polar atoms/residues have a higher propensity to line solvated cavities. Relative to the frequency of occurrence in the whole structure (or interface), residues in beta-strands are found more often lining the cavities, and those in turn and loop the least. Any depression in one chain not complemented by a protrusion in the other results in a cavity in the protein-protein interface. Through the use of the Voronoi volume, the packing of residues involved in protein-protein interaction has been compared to that in the protein interior. For a comparable number of atoms the interface has about twice the number of cavities relative to the tertiary structure.'),
(84057, 2008, 'plos', 'A hierarchy of time-scales and the brain', 'Kiebel, Stefan J|Daunizeau, Jean|Friston, Karl J', 'Wellcome Trust Centre for Neuroimaging, University College London, London, United Kingdom. skiebel@fil.ion.ucl.ac.uk|Wellcome Trust Centre for Neuroimaging, University College London, London, United Kingdom. skiebel@fil.ion.ucl.ac.uk|Wellcome Trust Centre for Neuroimaging, University College London, London, United Kingdom. skiebel@fil.ion.ucl.ac.uk', 'United Kingdom|United Kingdom|United Kingdom', 305, 'Animals|Brain|Computer Simulation|Models, Neurological|Vocalization, Animal', 'Journal Article', '10.1371/journal.pcbi.1000209', '19008936', 'In this paper, we suggest that cortical anatomy recapitulates the temporal hierarchy that is inherent in the dynamics of environmental states. Many aspects of brain function can be understood in terms of a hierarchy of temporal scales at which representations of the environment evolve. The lowest level of this hierarchy corresponds to fast fluctuations associated with sensory processing, whereas the highest levels encode slow contextual changes in the environment, under which faster representations unfold. First, we describe a mathematical model that exploits the temporal structure of fast sensory input to track the slower trajectories of their underlying causes. This model of sensory encoding or perceptual inference establishes a proof of concept that slowly changing neuronal states can encode the paths or trajectories of faster sensory states. We then review empirical evidence that suggests that a temporal hierarchy is recapitulated in the macroscopic organization of the cortex. This anatomic-temporal hierarchy provides a comprehensive framework for understanding cortical function: the specific time-scale that engages a cortical area can be inferred by its location along a rostro-caudal gradient, which reflects the anatomical distance from primary sensory areas. This is most evident in the prefrontal cortex, where complex functions can be explained as operations on representations of the environment that change slowly. The framework provides predictions about, and principled constraints on, cortical structure-function relationships, which can be tested by manipulating the time-scales of sensory input.'),
(84058, 2008, 'plos', 'Polar or apolar--the role of polarity for urea-induced protein denaturation', 'Stumpe, Martin C|Grubmüller, Helmut', 'Department of Theoretical and Computational Biophysics, Max-Planck-Institute for Biophysical Chemistry, Göttingen, Germany.|Department of Theoretical and Computational Biophysics, Max-Planck-Institute for Biophysical Chemistry, Göttingen, Germany.', 'Germany|Germany', 0, 'Amino Acids|Computer Simulation|Protein Conformation|Protein Denaturation|Protein Folding|Proteins|Solvents|Surface Properties|Urea|Water', 'Journal Article', '10.1371/journal.pcbi.1000221', '19008937', 'Urea-induced protein denaturation is widely used to study protein folding and stability, however, the molecular mechanism and driving forces of this process are not yet fully understood. In particular, it is unclear whether either hydrophobic or polar interactions between urea molecules and residues at the protein surface drive denaturation. To address this question, here, many molecular dynamics simulations totalling ca. 7 micros of the CI2 protein in aqueous solution served to perform a computational thought experiment, in which we varied the polarity of urea. For apolar driving forces, hypopolar urea should show increased denaturation power, for polar driving forces, hyperpolar urea should be the stronger denaturant. Indeed, protein unfolding was observed in all simulations with decreased urea polarity. Hyperpolar urea, in contrast, turned out to stabilize the native state. Moreover, the differential interaction preferences between urea and the 20 amino acids turned out to be enhanced for hypopolar urea and suppressed (or even inverted) for hyperpolar urea. These results strongly suggest that apolar urea-protein interactions, and not polar interactions, are the dominant driving force for denaturation. Further, the observed interactions provide a detailed picture of the underlying molecular driving forces. Our simulations finally allowed characterization of CI2 unfolding pathways. Unfolding proceeds sequentially with alternating loss of secondary or tertiary structure. After the transition state, unfolding pathways show large structural heterogeneity.'),
(84059, 2008, 'plos', 'A generic mechanism of emergence of amyloid protofilaments from disordered oligomeric aggregates', 'Auer, Stefan|Meersman, Filip|Dobson, Christopher M|Vendruscolo, Michele', 'Centre for Self Organising Molecular Systems, University of Leeds, Leeds, United Kingdom. s.auer@leeds.ac.uk|Centre for Self Organising Molecular Systems, University of Leeds, Leeds, United Kingdom. s.auer@leeds.ac.uk|Centre for Self Organising Molecular Systems, University of Leeds, Leeds, United Kingdom. s.auer@leeds.ac.uk|Centre for Self Organising Molecular Systems, University of Leeds, Leeds, United Kingdom. s.auer@leeds.ac.uk', 'United Kingdom|United Kingdom|United Kingdom|United Kingdom', 0, 'Amyloid|Computer Simulation|Models, Molecular|Peptides|Protein Structure, Quaternary|Protein Structure, Secondary', 'Journal Article', '10.1371/journal.pcbi.1000222', '19008938', 'The presence of oligomeric aggregates, which is often observed during the process of amyloid formation, has recently attracted much attention because it has been associated with a range of neurodegenerative conditions including Alzheimers and Parkinsons diseases. We provide a description of a sequence-indepedent mechanism by which polypeptide chains aggregate by forming metastable oligomeric intermediate states prior to converting into fibrillar structures. Our results illustrate that the formation of ordered arrays of hydrogen bonds drives the formation of beta-sheets within the disordered oligomeric aggregates that form early under the effect of hydrophobic forces. Individual beta-sheets initially form with random orientations and subsequently tend to align into protofilaments as their lengths increase. Our results suggest that amyloid aggregation represents an example of the Ostwald step rule of first-order phase transitions by showing that ordered cross-beta structures emerge preferentially from disordered compact dynamical intermediate assemblies.'),
(84060, 2008, 'plos', 'A predictive model of the oxygen and heme regulatory network in yeast', 'Kundaje, Anshul|Xin, Xiantong|Lan, Changgui|Lianoglou, Steve|Zhou, Mei|Zhang, Li|Leslie, Christina', 'Department of Computer Science, Columbia University, New York, New York, United States of America.|Department of Computer Science, Columbia University, New York, New York, United States of America.|Department of Computer Science, Columbia University, New York, New York, United States of America.|Department of Computer Science, Columbia University, New York, New York, United States of America.|Department of Computer Science, Columbia University, New York, New York, United States of America.|Department of Computer Science, Columbia University, New York, New York, United States of America.|Department of Computer Science, Columbia University, New York, New York, United States of America.', 'United States|United States|United States|United States|United States|United States|United States', 36, 'Algorithms|Computational Biology|Databases, Nucleic Acid|Down-Regulation|Gene Expression Profiling|Gene Regulatory Networks|Heme|Hot Temperature|Models, Biological|Multigene Family|Oxygen|Saccharomyces cerevisiae|Up-Regulation', 'Journal Article', '10.1371/journal.pcbi.1000224', '19008939', 'Deciphering gene regulatory mechanisms through the analysis of high-throughput expression data is a challenging computational problem. Previous computational studies have used large expression datasets in order to resolve fine patterns of coexpression, producing clusters or modules of potentially coregulated genes. These methods typically examine promoter sequence information, such as DNA motifs or transcription factor occupancy data, in a separate step after clustering. We needed an alternative and more integrative approach to study the oxygen regulatory network in Saccharomyces cerevisiae using a small dataset of perturbation experiments. Mechanisms of oxygen sensing and regulation underlie many physiological and pathological processes, and only a handful of oxygen regulators have been identified in previous studies. We used a new machine learning algorithm called MEDUSA to uncover detailed information about the oxygen regulatory network using genome-wide expression changes in response to perturbations in the levels of oxygen, heme, Hap1, and Co2+. MEDUSA integrates mRNA expression, promoter sequence, and ChIP-chip occupancy data to learn a model that accurately predicts the differential expression of target genes in held-out data. We used a novel margin-based score to extract significant condition-specific regulators and assemble a global map of the oxygen sensing and regulatory network. This network includes both known oxygen and heme regulators, such as Hap1, Mga2, Hap4, and Upc2, as well as many new candidate regulators. MEDUSA also identified many DNA motifs that are consistent with previous experimentally identified transcription factor binding sites. Because MEDUSAs regulatory program associates regulators to target genes through their promoter sequences, we directly tested the predicted regulators for OLE1, a gene specifically induced under hypoxia, by experimental analysis of the activity of its promoter. In each case, deletion of the candidate regulator resulted in the predicted effect on promoter activity, confirming that several novel regulators identified by MEDUSA are indeed involved in oxygen regulation. MEDUSA can reveal important information from a small dataset and generate testable hypotheses for further experimental analysis. Supplemental data are included.'),
(84061, 2008, 'plos', 'Quantification of local morphodynamics and local GTPase activity by edge evolution tracking', 'Tsukada, Yuki|Aoki, Kazuhiro|Nakamura, Takeshi|Sakumura, Yuichi|Matsuda, Michiyuki|Ishii, Shin', 'Laboratory for Systems Biology, Graduate School of Information Science, Nara Institute of Science and Technology, Nara, Japan.|Laboratory for Systems Biology, Graduate School of Information Science, Nara Institute of Science and Technology, Nara, Japan.|Laboratory for Systems Biology, Graduate School of Information Science, Nara Institute of Science and Technology, Nara, Japan.|Laboratory for Systems Biology, Graduate School of Information Science, Nara Institute of Science and Technology, Nara, Japan.|Laboratory for Systems Biology, Graduate School of Information Science, Nara Institute of Science and Technology, Nara, Japan.|Laboratory for Systems Biology, Graduate School of Information Science, Nara Institute of Science and Technology, Nara, Japan.', 'Japan|Japan|Japan|Japan|Japan|Japan', 0, 'Animals|Biomarkers|Cell Line|Cell Shape|Computational Biology|Cytoskeleton|GTP Phosphohydrolases|Humans|Mutation|Neurites|Rats', 'Journal Article', '10.1371/journal.pcbi.1000223', '19008941', 'Advances in time-lapse fluorescence microscopy have enabled us to directly observe dynamic cellular phenomena. Although the techniques themselves have promoted the understanding of dynamic cellular functions, the vast number of images acquired has generated a need for automated processing tools to extract statistical information. A problem underlying the analysis of time-lapse cell images is the lack of rigorous methods to extract morphodynamic properties. Here, we propose an algorithm called edge evolution tracking (EET) to quantify the relationship between local morphological changes and local fluorescence intensities around a cell edge using time-lapse microscopy images. This algorithm enables us to trace the local edge extension and contraction by defining subdivided edges and their corresponding positions in successive frames. Thus, this algorithm enables the investigation of cross-correlations between local morphological changes and local intensity of fluorescent signals by considering the time shifts. By applying EET to fluorescence resonance energy transfer images of the Rho-family GTPases Rac1, Cdc42, and RhoA, we examined the cross-correlation between the local area difference and GTPase activity. The calculated correlations changed with time-shifts as expected, but surprisingly, the peak of the correlation coefficients appeared with a 6-8 min time shift of morphological changes and preceded the Rac1 or Cdc42 activities. Our method enables the quantification of the dynamics of local morphological change and local protein activity and statistical investigation of the relationship between them by considering time shifts in the relationship. Thus, this algorithm extends the value of time-lapse imaging data to better understand dynamics of cellular function.'),
(84062, 2008, 'plos', 'A low dimensional description of globally coupled heterogeneous neural networks of excitatory and inhibitory neurons', 'Stefanescu, Roxana A|Jirsa, Viktor K', 'Department of Physics, Florida Atlantic University, Boca Raton, Florida, United States of America.|Department of Physics, Florida Atlantic University, Boca Raton, Florida, United States of America.', 'United States|United States', 80, 'Computational Biology|Models, Neurological|Nerve Net|Neurons', 'Journal Article', '10.1371/journal.pcbi.1000219', '19008942', 'Neural networks consisting of globally coupled excitatory and inhibitory nonidentical neurons may exhibit a complex dynamic behavior including synchronization, multiclustered solutions in phase space, and oscillator death. We investigate the conditions under which these behaviors occur in a multidimensional parametric space defined by the connectivity strengths and dispersion of the neuronal membrane excitability. Using mode decomposition techniques, we further derive analytically a low dimensional description of the neural population dynamics and show that the various dynamic behaviors of the entire network can be well reproduced by this reduced system. Examples of networks of FitzHugh-Nagumo and Hindmarsh-Rose neurons are discussed in detail.'),
(84063, 2008, 'plos', 'Erratum', 'Punta, Marco|Ofran, Yanay', 'Department of Physics, Florida Atlantic University, Boca Raton, Florida, United States of America.|Department of Physics, Florida Atlantic University, Boca Raton, Florida, United States of America.', 'United States|United States', 0, '-', 'Journal Article', '10.1371/annotation/3d8d748f-d1be-4ba9-84b3-23d2a582338b', '19015738', '[This corrects the article on p. e1000160 in vol. 4, PMID: 18974821.].'),
(84064, 2008, 'plos', 'Structural and thermodynamic approach to peptide immunogenicity', 'Camacho, Carlos J|Katsumata, Yasuhiro|Ascherman, Dana P', 'Department of Computational Biology, University of Pittsburgh, Pittsburgh, Pennsylvania, United States of America. ccamacho@pitt.edu|Department of Computational Biology, University of Pittsburgh, Pittsburgh, Pennsylvania, United States of America. ccamacho@pitt.edu|Department of Computational Biology, University of Pittsburgh, Pittsburgh, Pennsylvania, United States of America. ccamacho@pitt.edu', 'United States|United States|United States', 24, 'Amino Acid Motifs|Animals|Antibody Formation|Antigens|B-Lymphocytes|Computer Simulation|Enzyme-Linked Immunosorbent Assay|Epitopes, B-Lymphocyte|Histidine-tRNA Ligase|Mice|Models, Molecular|Peptides|Protein Interaction Domains and Motifs|Protein Stability|Protein Structure, Tertiary|Thermodynamics', 'Journal Article', '10.1371/journal.pcbi.1000231', '19023401', 'In the conventional paradigm of humoral immunity, B cells recognize their cognate antigen target in its native form. However, it is well known that relatively unstable peptides bearing only partial structural resemblance to the native protein can trigger antibodies recognizing higher-order structures found in the native protein. On the basis of sound thermodynamic principles, this work reveals that stability of immunogenic proteinlike motifs is a critical parameter rationalizing the diverse humoral immune responses induced by different linear peptide epitopes. In this paradigm, peptides with a minimal amount of stability (DeltaG(x)<0 kcal/mol) around a proteinlike motif (x) are capable of inducing antibodies with similar affinity for both peptide and native protein, more weakly stable peptides (DeltaG(x)>0 kcal/mol) trigger antibodies recognizing full protein but not peptide, and unstable peptides (DeltaG(x)>8 kcal/mol) fail to generate antibodies against either peptide or protein. Immunization experiments involving peptides derived from the autoantigen histidyl-tRNA synthetase verify that selected peptides with varying relative stabilities predicted by molecular dynamics simulations induce antibody responses consistent with this theory. Collectively, these studies provide insight pertinent to the structural basis of immunogenicity and, at the same time, validate this form of thermodynamic and molecular modeling as an approach to probe the development/evolution of humoral immune responses.'),
(84065, 2008, 'plos', 'Neutrality and robustness in evo-devo: emergence of lateral inhibition', 'Munteanu, Andreea|Solé, Ricard V', 'ICREA-Complex Systems Lab, Universitat Pompeu Fabra PRBB-GRIB, Barcelona, Spain.|ICREA-Complex Systems Lab, Universitat Pompeu Fabra PRBB-GRIB, Barcelona, Spain.', 'Spain|Spain', 0, 'Algorithms|Biological Evolution|Chromosome Mapping|Developmental Biology|Evolution, Molecular|Gene Expression Profiling|Gene Regulatory Networks|Genotype|Humans|Models, Genetic|Phenotype', 'Journal Article', '10.1371/journal.pcbi.1000226', '19023404', 'Embryonic development is defined by the hierarchical dynamical process that translates genetic information (genotype) into a spatial gene expression pattern (phenotype) providing the positional information for the correct unfolding of the organism. The nature and evolutionary implications of genotype-phenotype mapping still remain key topics in evolutionary developmental biology (evo-devo). We have explored here issues of neutrality, robustness, and diversity in evo-devo by means of a simple model of gene regulatory networks. The small size of the system allowed an exhaustive analysis of the entire fitness landscape and the extent of its neutrality. This analysis shows that evolution leads to a class of robust genetic networks with an expression pattern characteristic of lateral inhibition. This class is a repertoire of distinct implementations of this key developmental process, the diversity of which provides valuable clues about its underlying causal principles.'),
(84066, 2008, 'plos', 'Phylogenetic dependency networks: inferring patterns of CTL escape and codon covariation in HIV-1 Gag', 'Carlson, Jonathan M|Brumme, Zabrina L|Rousseau, Christine M|Brumme, Chanson J|Matthews, Philippa|Kadie, Carl|Mullins, James I|Walker, Bruce D|Harrigan, P Richard|Goulder, Philip J R|Heckerman, David', 'eScience Group, Microsoft Research, Redmond, Washington, United States of America. carlson@microsoft.com|eScience Group, Microsoft Research, Redmond, Washington, United States of America. carlson@microsoft.com|eScience Group, Microsoft Research, Redmond, Washington, United States of America. carlson@microsoft.com|eScience Group, Microsoft Research, Redmond, Washington, United States of America. carlson@microsoft.com|eScience Group, Microsoft Research, Redmond, Washington, United States of America. carlson@microsoft.com|eScience Group, Microsoft Research, Redmond, Washington, United States of America. carlson@microsoft.com|eScience Group, Microsoft Research, Redmond, Washington, United States of America. carlson@microsoft.com|eScience Group, Microsoft Research, Redmond, Washington, United States of America. carlson@microsoft.com|eScience Group, Microsoft Research, Redmond, Washington, United States of America. carlson@microsoft.com|eScience Group, Microsoft Research, Redmond, Washington, United States of America. carlson@microsoft.com|eScience Group, Microsoft Research, Redmond, Washington, United States of America. carlson@microsoft.com', 'United States|United States|United States|United States|United States|United States|United States|Un', 90, 'Algorithms|Analysis of Variance|Codon|Computer Simulation|Databases, Nucleic Acid|Decision Trees|Evolution, Molecular|Genes, gag|Genetic Variation|HIV|HIV Core Protein p24|HIV Infections|HLA Antigens|Humans|Linkage Disequilibrium|Mutation|Peptide Fragments|Phylogeny|Selection, Genetic|T-Lymphocytes, Cytotoxic|env Gene Products, Human Immunodeficiency Virus', 'Journal Article', '10.1371/journal.pcbi.1000225', '19023406', 'HIV avoids elimination by cytotoxic T-lymphocytes (CTLs) through the evolution of escape mutations. Although there is mounting evidence that these escape pathways are broadly consistent among individuals with similar human leukocyte antigen (HLA) class I alleles, previous population-based studies have been limited by the inability to simultaneously account for HIV codon covariation, linkage disequilibrium among HLA alleles, and the confounding effects of HIV phylogeny when attempting to identify HLA-associated viral evolution. We have developed a statistical model of evolution, called a phylogenetic dependency network, that accounts for these three sources of confounding and identifies the primary sources of selection pressure acting on each HIV codon. Using synthetic data, we demonstrate the utility of this approach for identifying sites of HLA-mediated selection pressure and codon evolution as well as the deleterious effects of failing to account for all three sources of confounding. We then apply our approach to a large, clinically-derived dataset of Gag p17 and p24 sequences from a multicenter cohort of 1144 HIV-infected individuals from British Columbia, Canada (predominantly HIV-1 clade B) and Durban, South Africa (predominantly HIV-1 clade C). The resulting phylogenetic dependency network is dense, containing 149 associations between HLA alleles and HIV codons and 1386 associations among HIV codons. These associations include the complete reconstruction of several recently defined escape and compensatory mutation pathways and agree with emerging data on patterns of epitope targeting. The phylogenetic dependency network adds to the growing body of literature suggesting that sites of escape, order of escape, and compensatory mutations are largely consistent even across different clades, although we also identify several differences between clades. As recent case studies have demonstrated, understanding both the complexity and the consistency of immune escape has important implications for CTL-based vaccine design. Phylogenetic dependency networks represent a major step toward systematically expanding our understanding of CTL escape to diverse populations and whole viral genes.'),
(84067, 2008, 'plos', 'Order-based representation in random networks of cortical neurons', 'Shahaf, Goded|Eytan, Danny|Gal, Asaf|Kermany, Einat|Lyakhov, Vladimir|Zrenner, Christoph|Marom, Shimon', 'Technion-Israel Institute of Technology, Haifa, Israel.|Technion-Israel Institute of Technology, Haifa, Israel.|Technion-Israel Institute of Technology, Haifa, Israel.|Technion-Israel Institute of Technology, Haifa, Israel.|Technion-Israel Institute of Technology, Haifa, Israel.|Technion-Israel Institute of Technology, Haifa, Israel.|Technion-Israel Institute of Technology, Haifa, Israel.', 'Israel|Israel|Israel|Israel|Israel|Israel|Israel', 0, 'Action Potentials|Algorithms|Animals|Animals, Newborn|Cerebral Cortex|Computational Biology|Electrodes|Microtechnology|Models, Neurological|Nerve Net|Neural Pathways|Neurobiology|Neurons|Rats|Rats, Sprague-Dawley|Synaptic Potentials', 'Journal Article', '10.1371/journal.pcbi.1000228', '19023409', 'The wide range of time scales involved in neural excitability and synaptic transmission might lead to ongoing change in the temporal structure of responses to recurring stimulus presentations on a trial-to-trial basis. This is probably the most severe biophysical constraint on putative time-based primitives of stimulus representation in neuronal networks. Here we show that in spontaneously developing large-scale random networks of cortical neurons in vitro the order in which neurons are recruited following each stimulus is a naturally emerging representation primitive that is invariant to significant temporal changes in spike times. With a relatively small number of randomly sampled neurons, the information about stimulus position is fully retrievable from the recruitment order. The effective connectivity that makes order-based representation invariant to time warping is characterized by the existence of stations through which activity is required to pass in order to propagate further into the network. This study uncovers a simple invariant in a noisy biological network in vitro, its applicability under in vivo constraints remains to be seen.'),
(84068, 2008, 'plos', 'Behavioral sequence analysis reveals a novel role for beta2* nicotinic receptors in exploration', 'Maubourguet, Nicolas|Lesne, Annick|Changeux, Jean-Pierre|Maskos, Uwe|Faure, Philippe', 'Unité Neurobiologie Intégrative des Systèmes Cholinergiques, Institut Pasteur, Paris, France.|Unité Neurobiologie Intégrative des Systèmes Cholinergiques, Institut Pasteur, Paris, France.|Unité Neurobiologie Intégrative des Systèmes Cholinergiques, Institut Pasteur, Paris, France.|Unité Neurobiologie Intégrative des Systèmes Cholinergiques, Institut Pasteur, Paris, France.|Unité Neurobiologie Intégrative des Systèmes Cholinergiques, Institut Pasteur, Paris, France.', 'France|France|France|France|France', 28, 'Animals|Behavior, Animal|Exploratory Behavior|Hyperkinesis|Markov Chains|Mice|Mice, Knockout|Receptors, Nicotinic|Statistics, Nonparametric', 'Journal Article', '10.1371/journal.pcbi.1000229', '19023420', 'Nicotinic acetylcholine receptors (nAChRs) are widely expressed throughout the central nervous system and modulate neuronal function in most mammalian brain structures. The contribution of defined nAChR subunits to a specific behavior is thus difficult to assess. Mice deleted for beta2-containing nAChRs (beta2-/-) have been shown to be hyperactive in an open-field paradigm, without determining the origin of this hyperactivity. We here develop a quantitative description of mouse behavior in the open field based upon first order Markov and variable length Markov chain analysis focusing on the time-organized sequence that behaviors are composed of. This description reveals that this hyperactivity is the consequence of the absence of specific inactive states or stops. These stops are associated with a scanning of the environment in wild-type mice (WT), and they affect the way that animals organize their sequence of behaviors when compared with stops without scanning. They characterize a specific decision moment that is reduced in beta2-/- mutant mice, suggesting an important role of beta2-nAChRs in the strategy used by animals to explore an environment and collect information in order to organize their behavior. This integrated analysis of the displacement of an animal in a simple environment offers new insights, specifically into the contribution of nAChRs to higher brain functions and more generally into the principles that organize sequences of behaviors in animals.'),
(84069, 2008, 'plos', 'Differentiating protein-coding and noncoding RNA: challenges and ambiguities', 'Dinger, Marcel E|Pang, Ken C|Mercer, Tim R|Mattick, John S', 'ARC Special Research Centre for Functional and Applied Genomics, Institute for Molecular Bioscience, University of Queensland, St Lucia, Australia.|ARC Special Research Centre for Functional and Applied Genomics, Institute for Molecular Bioscience, University of Queensland, St Lucia, Australia.|ARC Special Research Centre for Functional and Applied Genomics, Institute for Molecular Bioscience, University of Queensland, St Lucia, Australia.|ARC Special Research Centre for Functional and Applied Genomics, Institute for Molecular Bioscience, University of Queensland, St Lucia, Australia.', 'Australia|Australia|Australia|Australia', 307, 'Computational Biology|Gene Expression Profiling|Genomics|Open Reading Frames|RNA, Messenger|RNA, Untranslated|Transcription, Genetic', 'Journal Article', '10.1371/journal.pcbi.1000176', '19043537', 'The assumption that RNA can be readily classified into either protein-coding or non-protein-coding categories has pervaded biology for close to 50 years. Until recently, discrimination between these two categories was relatively straightforward: most transcripts were clearly identifiable as protein-coding messenger RNAs (mRNAs), and readily distinguished from the small number of well-characterized non-protein-coding RNAs (ncRNAs), such as transfer, ribosomal, and spliceosomal RNAs. Recent genome-wide studies have revealed the existence of thousands of noncoding transcripts, whose function and significance are unclear. The discovery of this hidden transcriptome and the implicit challenge it presents to our understanding of the expression and regulation of genetic information has made the need to distinguish between mRNAs and ncRNAs both more pressing and more complicated. In this Review, we consider the diverse strategies employed to discriminate between protein-coding and noncoding transcripts and the fundamental difficulties that are inherent in what may superficially appear to be a simple problem. Misannotations can also run in both directions: some ncRNAs may actually encode peptides, and some of those currently thought to do so may not. Moreover, recent studies have shown that some RNAs can function both as mRNAs and intrinsically as functional ncRNAs, which may be a relatively widespread phenomenon. We conclude that it is difficult to annotate an RNA unequivocally as protein-coding or noncoding, with overlapping protein-coding and noncoding transcripts further confounding this distinction. In addition, the finding that some transcripts can function both intrinsically at the RNA level and to encode proteins suggests a false dichotomy between mRNAs and ncRNAs. Therefore, the functionality of any transcript at the RNA level should not be discounted.'),
(84070, 2008, 'plos', 'Optimal learning rules for discrete synapses', 'Barrett, Adam B|van Rossum, M C W', 'Institute for Adaptive and Neural Computation, University of Edinburgh, Edinburgh, United Kingdom. abarrett@inf.ed.ac.uk|Institute for Adaptive and Neural Computation, University of Edinburgh, Edinburgh, United Kingdom. abarrett@inf.ed.ac.uk', 'United Kingdom|United Kingdom', 0, 'Algorithms|Learning|Memory|Models, Neurological|Nerve Net|Neural Networks (Computer)|Neuronal Plasticity|Neurons|Synapses|Synaptic Transmission', 'Journal Article', '10.1371/journal.pcbi.1000230', '19043540', 'There is evidence that biological synapses have a limited number of discrete weight states. Memory storage with such synapses behaves quite differently from synapses with unbounded, continuous weights, as old memories are automatically overwritten by new memories. Consequently, there has been substantial discussion about how this affects learning and storage capacity. In this paper, we calculate the storage capacity of discrete, bounded synapses in terms of Shannon information. We use this to optimize the learning rules and investigate how the maximum information capacity depends on the number of synapses, the number of synaptic states, and the coding sparseness. Below a certain critical number of synapses per neuron (comparable to numbers found in biology), we find that storage is similar to unbounded, continuous synapses. Hence, discrete synapses do not necessarily have lower storage capacity.'),
(84071, 2008, 'plos', 'A methodological framework for the reconstruction of contiguous regions of ancestral genomes and its application to mammalian genomes', 'Chauve, Cedric|Tannier, Eric', 'Department of Mathematics, Simon Fraser University, Burnaby, British Columbia, Canada.|Department of Mathematics, Simon Fraser University, Burnaby, British Columbia, Canada.', 'Canada|Canada', 0, 'Animals|Computational Biology|Cytogenetics|Evolution, Molecular|Genetic Markers|Genome|Genome, Human|Genomics|Humans|Mammals|Models, Genetic|Phylogeny|Synteny', 'Journal Article', '10.1371/journal.pcbi.1000234', '19043541', 'The reconstruction of ancestral genome architectures and gene orders from homologies between extant species is a long-standing problem, considered by both cytogeneticists and bioinformaticians. A comparison of the two approaches was recently investigated and discussed in a series of papers, sometimes with diverging points of view regarding the performance of these two approaches. We describe a general methodological framework for reconstructing ancestral genome segments from conserved syntenies in extant genomes. We show that this problem, from a computational point of view, is naturally related to physical mapping of chromosomes and benefits from using combinatorial tools developed in this scope. We develop this framework into a new reconstruction method considering conserved gene clusters with similar gene content, mimicking principles used in most cytogenetic studies, although on a different kind of data. We implement and apply it to datasets of mammalian genomes. We perform intensive theoretical and experimental comparisons with other bioinformatics methods for ancestral genome segments reconstruction. We show that the method that we propose is stable and reliable: it gives convergent results using several kinds of data at different levels of resolution, and all predicted ancestral regions are well supported. The results come eventually very close to cytogenetics studies. It suggests that the comparison of methods for ancestral genome reconstruction should include the algorithmic aspects of the methods as well as the disciplinary differences in data acquisition.'),
(84072, 2008, 'plos', 'Dynamic changes in protein functional linkage networks revealed by integration with gene expression data', 'Hegde, Shubhada R|Manimaran, Palanisamy|Mande, Shekhar C', 'Centre for DNA Fingerprinting and Diagnostics, Nacharam, Hyderabad, India.|Centre for DNA Fingerprinting and Diagnostics, Nacharam, Hyderabad, India.|Centre for DNA Fingerprinting and Diagnostics, Nacharam, Hyderabad, India.', 'India|India|India', 29, 'Algorithms|Computational Biology|Computer Simulation|Databases, Genetic|Escherichia coli|Escherichia coli Proteins|Gene Expression|Gene Regulatory Networks|Oligonucleotide Array Sequence Analysis|Protein Binding|Protein Interaction Mapping|Ultraviolet Rays', 'Journal Article', '10.1371/journal.pcbi.1000237', '19043542', 'Response of cells to changing environmental conditions is governed by the dynamics of intricate biomolecular interactions. It may be reasonable to assume, proteins being the dominant macromolecules that carry out routine cellular functions, that understanding the dynamics of protein:protein interactions might yield useful insights into the cellular responses. The large-scale protein interaction data sets are, however, unable to capture the changes in the profile of protein:protein interactions. In order to understand how these interactions change dynamically, we have constructed conditional protein linkages for Escherichia coli by integrating functional linkages and gene expression information. As a case study, we have chosen to analyze UV exposure in wild-type and SOS deficient E. coli at 20 minutes post irradiation. The conditional networks exhibit similar topological properties. Although the global topological properties of the networks are similar, many subtle local changes are observed, which are suggestive of the cellular response to the perturbations. Some such changes correspond to differences in the path lengths among the nodes of carbohydrate metabolism correlating with its loss in efficiency in the UV treated cells. Similarly, expression of hubs under unique conditions reflects the importance of these genes. Various centrality measures applied to the networks indicate increased importance for replication, repair, and other stress proteins for the cells under UV treatment, as anticipated. We thus propose a novel approach for studying an organism at the systems level by integrating genome-wide functional linkages and the gene expression data.'),
(84073, 2008, 'plos', 'Multistable decision switches for flexible control of epigenetic differentiation', 'Guantes, Raúl|Poyatos, Juan F', 'Department of Condensed Matter Physics, Facultad de Ciencias C-XVI, Universidad Autónoma de Madrid, Madrid, Spain.|Department of Condensed Matter Physics, Facultad de Ciencias C-XVI, Universidad Autónoma de Madrid, Madrid, Spain.', 'Spain|Spain', 0, 'Algorithms|Computational Biology|Epigenesis, Genetic|Gene Regulatory Networks|Homeostasis|Models, Biological|Phenotype|Signal Transduction', 'Journal Article', '10.1371/journal.pcbi.1000235', '19043543', 'It is now recognized that molecular circuits with positive feedback can induce two different gene expression states (bistability) under the very same cellular conditions. Whether, and how, cells make use of the coexistence of a larger number of stable states (multistability) is however largely unknown. Here, we first examine how autoregulation, a common attribute of genetic master regulators, facilitates multistability in two-component circuits. A systematic exploration of these modules parameter space reveals two classes of molecular switches, involving transitions in bistable (progression switches) or multistable (decision switches) regimes. We demonstrate the potential of decision switches for multifaceted stimulus processing, including strength, duration, and flexible discrimination. These tasks enhance response specificity, help to store short-term memories of recent signaling events, stabilize transient gene expression, and enable stochastic fate commitment. The relevance of these circuits is further supported by biological data, because we find them in numerous developmental scenarios. Indeed, many of the presented information-processing features of decision switches could ultimately demonstrate a more flexible control of epigenetic differentiation.');
INSERT INTO `papers` (`id`, `ano`, `journal`, `titulo`, `autores`, `afiliacao`, `pais`, `citacoes`, `palavra_chave`, `categorias`, `doi`, `pubmed`, `abstract`) VALUES
(84074, 2008, 'plos', 'PSICIC: noise and asymmetry in bacterial division revealed by computational image analysis at sub-pixel resolution', 'Guberman, Jonathan M|Fay, Allison|Dworkin, Jonathan|Wingreen, Ned S|Gitai, Zemer', 'Department of Molecular Biology, Princeton University, Princeton, New Jersey, United States of America.|Department of Molecular Biology, Princeton University, Princeton, New Jersey, United States of America.|Department of Molecular Biology, Princeton University, Princeton, New Jersey, United States of America.|Department of Molecular Biology, Princeton University, Princeton, New Jersey, United States of America.|Department of Molecular Biology, Princeton University, Princeton, New Jersey, United States of America.', 'Jersey|Jersey|Jersey|Jersey|Jersey', 75, 'Algorithms|Bacillus subtilis|Bacteria|Cell Division|Escherichia coli|Image Processing, Computer-Assisted|Microscopy|Molecular Sequence Data|Software', 'Journal Article', '10.1371/journal.pcbi.1000233', '19043544', 'Live-cell imaging by light microscopy has demonstrated that all cells are spatially and temporally organized. Quantitative, computational image analysis is an important part of cellular imaging, providing both enriched information about individual cell properties and the ability to analyze large datasets. However, such studies are often limited by the small size and variable shape of objects of interest. Here, we address two outstanding problems in bacterial cell division by developing a generally applicable, standardized, and modular software suite termed Projected System of Internal Coordinates from Interpolated Contours (PSICIC) that solves common problems in image quantitation. PSICIC implements interpolated-contour analysis for accurate and precise determination of cell borders and automatically generates internal coordinate systems that are superimposable regardless of cell geometry. We have used PSICIC to establish that the cell-fate determinant, SpoIIE, is asymmetrically localized during Bacillus subtilis sporulation, thereby demonstrating the ability of PSICIC to discern protein localization features at sub-pixel scales. We also used PSICIC to examine the accuracy of cell division in Esherichia coli and found a new role for the Min system in regulating division-site placement throughout the cell length, but only prior to the initiation of cell constriction. These results extend our understanding of the regulation of both asymmetry and accuracy in bacterial division while demonstrating the general applicability of PSICIC as a computational approach for quantitative, high-throughput analysis of cellular images.'),
(84075, 2008, 'plos', 'Analyzing ChIP-chip data using bioconductor', 'Toedling, Joern|Huber, Wolfgang', 'EMBL European Bioinformatics Institute, Wellcome Trust Genome Campus, Hinxton, United Kingdom. toedling@ebi.ac.uk|EMBL European Bioinformatics Institute, Wellcome Trust Genome Campus, Hinxton, United Kingdom. toedling@ebi.ac.uk', 'United Kingdom|United Kingdom', 0, 'Chromatin Immunoprecipitation|Computational Biology|Databases, Genetic|Oligonucleotide Array Sequence Analysis|Software', 'Journal Article', '10.1371/journal.pcbi.1000227', '19043553', '-'),
(84076, 2008, 'plos', 'Age-dependent evolution of the yeast protein interaction network suggests a limited role of gene duplication and divergence', 'Kim, Wan Kyu|Marcotte, Edward M', 'Center for Systems and Synthetic Biology, Institute for Cellular and Molecular Biology, University of Texas at Austin, Austin, Texas, United States of America.|Center for Systems and Synthetic Biology, Institute for Cellular and Molecular Biology, University of Texas at Austin, Austin, Texas, United States of America.', 'United States|United States', 65, 'Evolution, Molecular|Fungal Proteins|Gene Duplication|Gene Frequency|Genes, Fungal|Genetic Variation|Metabolic Networks and Pathways|Models, Genetic|Multiprotein Complexes|Protein Binding|Protein Interaction Mapping|Protein Multimerization', 'Journal Article', '10.1371/journal.pcbi.1000232', '19043579', 'Proteins interact in complex protein-protein interaction (PPI) networks whose topological properties-such as scale-free topology, hierarchical modularity, and dissortativity-have suggested models of network evolution. Currently preferred models invoke preferential attachment or gene duplication and divergence to produce networks whose topology matches that observed for real PPIs, thus supporting these as likely models for network evolution. Here, we show that the interaction density and homodimeric frequency are highly protein age-dependent in real PPI networks in a manner which does not agree with these canonical models. In light of these results, we propose an alternative stochastic model, which adds each protein sequentially to a growing network in a manner analogous to protein crystal growth (CG) in solution. The key ideas are (1) interaction probability increases with availability of unoccupied interaction surface, thus following an anti-preferential attachment rule, (2) as a network grows, highly connected sub-networks emerge into protein modules or complexes, and (3) once a new protein is committed to a module, further connections tend to be localized within that module. The CG model produces PPI networks consistent in both topology and age distributions with real PPI networks and is well supported by the spatial arrangement of protein complexes of known 3-D structure, suggesting a plausible physical mechanism for network evolution.'),
(84077, 2008, 'plos', 'Spontaneous reaction silencing in metabolic optimization', 'Nishikawa, Takashi|Gulbahce, Natali|Motter, Adilson E', 'Division of Mathematics and Computer Science, Clarkson University, Potsdam, New York, United States of America.|Division of Mathematics and Computer Science, Clarkson University, Potsdam, New York, United States of America.|Division of Mathematics and Computer Science, Clarkson University, Potsdam, New York, United States of America.', 'United States|United States|United States', 33, 'Algorithms|Bacteria|Biochemical Phenomena|Biological Evolution|Computational Biology|Computer Simulation|Environment|Escherichia coli|Metabolic Networks and Pathways|Models, Biological', 'Journal Article', '10.1371/journal.pcbi.1000236', '19057639', 'Metabolic reactions of single-cell organisms are routinely observed to become dispensable or even incapable of carrying activity under certain circumstances. Yet, the mechanisms as well as the range of conditions and phenotypes associated with this behavior remain very poorly understood. Here we predict computationally and analytically that any organism evolving to maximize growth rate, ATP production, or any other linear function of metabolic fluxes tends to significantly reduce the number of active metabolic reactions compared to typical nonoptimal states. The reduced number appears to be constant across the microbial species studied and just slightly larger than the minimum number required for the organism to grow at all. We show that this massive spontaneous reaction silencing is triggered by the irreversibility of a large fraction of the metabolic reactions and propagates through the network as a cascade of inactivity. Our results help explain existing experimental data on intracellular flux measurements and the usage of latent pathways, shedding new light on microbial evolution, robustness, and versatility for the execution of specific biochemical tasks. In particular, the identification of optimal reaction activity provides rigorous ground for an intriguing knockout-based method recently proposed for the synthetic recovery of metabolic function.'),
(84078, 2008, 'plos', 'Formation and growth of oligomers: a Monte Carlo study of an amyloid tau fragment', 'Li, Da-Wei|Mohanty, Sandipan|Irbäck, Anders|Huo, Shuanghong', 'Gustaf H Carlson School of Chemistry and Biochemistry, Clark University, Worcester, Massachusetts, United States of America.|Gustaf H Carlson School of Chemistry and Biochemistry, Clark University, Worcester, Massachusetts, United States of America.|Gustaf H Carlson School of Chemistry and Biochemistry, Clark University, Worcester, Massachusetts, United States of America.|Gustaf H Carlson School of Chemistry and Biochemistry, Clark University, Worcester, Massachusetts, United States of America.', 'United States|United States|United States|United States', 72, 'Algorithms|Alzheimer Disease|Amyloid beta-Peptides|Computer Simulation|Hydrogen Bonding|Hydrophobic and Hydrophilic Interactions|Models, Molecular|Monte Carlo Method|Oligopeptides|Protein Structure, Quaternary|tau Proteins', 'Journal Article', '10.1371/journal.pcbi.1000238', '19057640', 'Small oligomers formed early in the process of amyloid fibril formation may be the major toxic species in Alzheimers disease. We investigate the early stages of amyloid aggregation for the tau fragment AcPHF6 (Ac-VQIVYK-NH2) using an implicit solvent all-atom model and extensive Monte Carlo simulations of 12, 24, and 36 chains. A variety of small metastable aggregates form and dissolve until an aggregate of a critical size and conformation arises. However, the stable oligomers, which are beta-sheet-rich and feature many hydrophobic contacts, are not always growth-ready. The simulations indicate instead that these supercritical oligomers spend a lengthy period in equilibrium in which considerable reorganization takes place accompanied by exchange of chains with the solution. Growth competence of the stable oligomers correlates with the alignment of the strands in the beta-sheets. The larger aggregates seen in our simulations are all composed of two twisted beta-sheets, packed against each other with hydrophobic side chains at the sheet-sheet interface. These beta-sandwiches show similarities with the proposed steric zipper structure for PHF6 fibrils but have a mixed parallel/antiparallel beta-strand organization as opposed to the parallel organization found in experiments on fibrils. Interestingly, we find that the fraction of parallel beta-sheet structure increases with aggregate size. We speculate that the reorganization of the beta-sheets into parallel ones is an important rate-limiting step in the formation of PHF6 fibrils.'),
(84079, 2008, 'plos', 'Encoding of naturalistic stimuli by local field potential spectra in networks of excitatory and inhibitory neurons', 'Mazzoni, Alberto|Panzeri, Stefano|Logothetis, Nikos K|Brunel, Nicolas', 'Division of Statistical Physics, Institute for Scientific Interchange, Turin, Italy. alb.mazzoni@gmail.com|Division of Statistical Physics, Institute for Scientific Interchange, Turin, Italy. alb.mazzoni@gmail.com|Division of Statistical Physics, Institute for Scientific Interchange, Turin, Italy. alb.mazzoni@gmail.com|Division of Statistical Physics, Institute for Scientific Interchange, Turin, Italy. alb.mazzoni@gmail.com', 'Italy|Italy|Italy|Italy', 146, 'Action Potentials|Animals|Biological Clocks|Computer Simulation|Evoked Potentials, Visual|Humans|Models, Neurological|Nerve Net|Neurons|Visual Cortex', 'Journal Article', '10.1371/journal.pcbi.1000239', '19079571', 'Recordings of local field potentials (LFPs) reveal that the sensory cortex displays rhythmic activity and fluctuations over a wide range of frequencies and amplitudes. Yet, the role of this kind of activity in encoding sensory information remains largely unknown. To understand the rules of translation between the structure of sensory stimuli and the fluctuations of cortical responses, we simulated a sparsely connected network of excitatory and inhibitory neurons modeling a local cortical population, and we determined how the LFPs generated by the network encode information about input stimuli. We first considered simple static and periodic stimuli and then naturalistic input stimuli based on electrophysiological recordings from the thalamus of anesthetized monkeys watching natural movie scenes. We found that the simulated network produced stimulus-related LFP changes that were in striking agreement with the LFPs obtained from the primary visual cortex. Moreover, our results demonstrate that the network encoded static input spike rates into gamma-range oscillations generated by inhibitory-excitatory neural interactions and encoded slow dynamic features of the input into slow LFP fluctuations mediated by stimulus-neural interactions. The model cortical network processed dynamic stimuli with naturalistic temporal structure by using low and high response frequencies as independent communication channels, again in agreement with recent reports from visual cortex responses to naturalistic movies. One potential function of this frequency decomposition into independent information channels operated by the cortical network may be that of enhancing the capacity of the cortical column to encode our complex sensory environment.'),
(84080, 2008, 'plos', 'Dynamic correlation between intrahost HIV-1 quasispecies evolution and disease progression', 'Lee, Ha Youn|Perelson, Alan S|Park, Su-Chan|Leitner, Thomas', 'Department of Biostatistics and Computational Biology, University of Rochester Medical Center, NY, USA. hayoun@bst.rochester.edu|Department of Biostatistics and Computational Biology, University of Rochester Medical Center, NY, USA. hayoun@bst.rochester.edu|Department of Biostatistics and Computational Biology, University of Rochester Medical Center, NY, USA. hayoun@bst.rochester.edu|Department of Biostatistics and Computational Biology, University of Rochester Medical Center, NY, USA. hayoun@bst.rochester.edu', 'United States|United States|United States|United States', 54, 'Biological Evolution|Computer Simulation|HIV Infections|HIV-1|Humans|Models, Genetic|Mutation|Species Specificity|Statistics as Topic', 'Journal Article', '10.1371/journal.pcbi.1000240', '19079613', 'Quantifying the dynamics of intrahost HIV-1 sequence evolution is one means of uncovering information about the interaction between HIV-1 and the host immune system. In the chronic phase of infection, common dynamics of sequence divergence and diversity have been reported. We developed an HIV-1 sequence evolution model that simulated the effects of mutation and fitness of sequence variants. The amount of evolution was described by the distance from the founder strain, and fitness was described by the number of offspring a parent sequence produces. Analysis of the model suggested that the previously observed saturation of divergence and decrease of diversity in later stages of infection can be explained by a decrease in the proportion of offspring that are mutants as the distance from the founder strain increases rather than due to an increase of viral fitness. The prediction of the model was examined by performing phylogenetic analysis to estimate the change in the rate of evolution during infection. In agreement with our modeling, in 13 out of 15 patients (followed for 3-12 years) we found that the rate of intrahost HIV-1 evolution was not constant but rather slowed down at a rate correlated with the rate of CD4+ T-cell decline. The correlation between the dynamics of the evolutionary rate and the rate of CD4+ T-cell decline, coupled with our HIV-1 sequence evolution model, explains previously conflicting observations of the relationships between the rate of HIV-1 quasispecies evolution and disease progression.'),
(84081, 2008, 'plos', 'Disordered flanks prevent peptide aggregation', 'Abeln, Sanne|Frenkel, Daan', 'FOM Institute for Atomic and Molecular Physics, Amsterdam, The Netherlands. s.abeln@amolf.nl|FOM Institute for Atomic and Molecular Physics, Amsterdam, The Netherlands. s.abeln@amolf.nl', 'Netherlands|Netherlands', 45, 'Binding Sites|Computer Simulation|Models, Chemical|Models, Molecular|Multiprotein Complexes|Peptides|Protein Binding|Protein Conformation', 'Journal Article', '10.1371/journal.pcbi.1000241', '19096500', 'Natively unstructured or disordered regions appear to be abundant in eukaryotic proteins. Many such regions have been found alongside small linear binding motifs. We report a Monte Carlo study that aims to elucidate the role of disordered regions adjacent to such binding motifs. The coarse-grained simulations show that small hydrophobic peptides without disordered flanks tend to aggregate under conditions where peptides embedded in unstructured peptide sequences are stable as monomers or as part of small micelle-like clusters. Surprisingly, the binding free energy of the motif is barely decreased by the presence of disordered flanking regions, although it is sensitive to the loss of entropy of the motif itself upon binding. This latter effect allows for reversible binding of the signalling motif to the substrate. The work provides insights into a mechanism that prevents the aggregation of signalling peptides, distinct from the general mechanism of protein folding, and provides a testable hypothesis to explain the abundance of disordered regions in proteins.'),
(84082, 2008, 'plos', 'Malleable machines in transcription regulation: the mediator complex', 'Tóth-Petróczy, Agnes|Oldfield, Christopher J|Simon, István|Takagi, Yuichiro|Dunker, A Keith|Uversky, Vladimir N|Fuxreiter, Monika', '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.|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.|Institute of Enzymology, Biological Research Center, Hungarian Academy of Sciences, Budapest, Hungary.', 'Hungary|Hungary|Hungary|Hungary|Hungary|Hungary|Hungary', 80, 'Computer Simulation|Gene Expression Regulation|Models, Genetic|Trans-Activators|Transcription Factors|Transcriptional Activation', 'Journal Article', '10.1371/journal.pcbi.1000243', '19096501', 'The Mediator complex provides an interface between gene-specific regulatory proteins and the general transcription machinery including RNA polymerase II (RNAP II). The complex has a modular architecture (Head, Middle, and Tail) and cryoelectron microscopy analysis suggested that it undergoes dramatic conformational changes upon interactions with activators and RNAP II. These rearrangements have been proposed to play a role in the assembly of the preinitiation complex and also to contribute to the regulatory mechanism of Mediator. In analogy to many regulatory and transcriptional proteins, we reasoned that Mediator might also utilize intrinsically disordered regions (IDRs) to facilitate structural transitions and transmit transcriptional signals. Indeed, a high prevalence of IDRs was found in various subunits of Mediator from both Saccharomyces cerevisiae and Homo sapiens, especially in the Tail and the Middle modules. The level of disorder increases from yeast to man, although in both organisms it significantly exceeds that of multiprotein complexes of a similar size. IDRs can contribute to Mediators function in three different ways: they can individually serve as target sites for multiple partners having distinctive structures, they can act as malleable linkers connecting globular domains that impart modular functionality on the complex, and they can also facilitate assembly and disassembly of complexes in response to regulatory signals. Short segments of IDRs, termed molecular recognition features (MoRFs) distinguished by a high protein-protein interaction propensity, were identified in 16 and 19 subunits of the yeast and human Mediator, respectively. In Saccharomyces cerevisiae, the functional roles of 11 MoRFs have been experimentally verified, and those in the Med8/Med18/Med20 and Med7/Med21 complexes were structurally confirmed. Although the Saccharomyces cerevisiae and Homo sapiens Mediator sequences are only weakly conserved, the arrangements of the disordered regions and their embedded interaction sites are quite similar in the two organisms. All of these data suggest an integral role for intrinsic disorder in Mediators function.'),
(84083, 2008, 'plos', 'Dependence of bacterial chemotaxis on gradient shape and adaptation rate', 'Vladimirov, Nikita|Løvdok, Linda|Lebiedz, Dirk|Sourjik, Victor', 'Interdisziplinäres Zentrum für Wissenschaftliches Rechnen, University of Heidelberg, Heidelberg, Germany. nikita.vladimirov@gmail.com|Interdisziplinäres Zentrum für Wissenschaftliches Rechnen, University of Heidelberg, Heidelberg, Germany. nikita.vladimirov@gmail.com|Interdisziplinäres Zentrum für Wissenschaftliches Rechnen, University of Heidelberg, Heidelberg, Germany. nikita.vladimirov@gmail.com|Interdisziplinäres Zentrum für Wissenschaftliches Rechnen, University of Heidelberg, Heidelberg, Germany. nikita.vladimirov@gmail.com', 'Germany|Germany|Germany|Germany', 76, 'Adaptation, Physiological|Cell Culture Techniques|Chemotaxis|Computer Simulation|Escherichia coli|Models, Biological', 'Journal Article', '10.1371/journal.pcbi.1000242', '19096502', 'Simulation of cellular behavior on multiple scales requires models that are sufficiently detailed to capture central intracellular processes but at the same time enable the simulation of entire cell populations in a computationally cheap way. In this paper we present RapidCell, a hybrid model of chemotactic Escherichia coli that combines the Monod-Wyman-Changeux signal processing by mixed chemoreceptor clusters, the adaptation dynamics described by ordinary differential equations, and a detailed model of cell tumbling. Our model dramatically reduces computational costs and allows the highly efficient simulation of E. coli chemotaxis. We use the model to investigate chemotaxis in different gradients, and suggest a new, constant-activity type of gradient to systematically study chemotactic behavior of virtual bacteria. Using the unique properties of this gradient, we show that optimal chemotaxis is observed in a narrow range of CheA kinase activity, where concentration of the response regulator CheY-P falls into the operating range of flagellar motors. Our simulations also confirm that the CheB phosphorylation feedback improves chemotactic efficiency by shifting the average CheY-P concentration to fit the motor operating range. Our results suggest that in liquid media the variability in adaptation times among cells may be evolutionary favorable to ensure coexistence of subpopulations that will be optimally tactic in different gradients. However, in a porous medium (agar) such variability appears to be less important, because agar structure poses mainly negative selection against subpopulations with low levels of adaptation enzymes. RapidCell is available from the authors upon request.'),
(84084, 2008, 'plos', 'Association rate constants of ras-effector interactions are evolutionarily conserved', 'Kiel, Christina|Aydin, Dorothee|Serrano, Luis', 'EMBL-CRG Systems Biology Unit, Centre de Regulacio Genomica, Barcelona, Spain. christina.kiel@crg.es|EMBL-CRG Systems Biology Unit, Centre de Regulacio Genomica, Barcelona, Spain. christina.kiel@crg.es|EMBL-CRG Systems Biology Unit, Centre de Regulacio Genomica, Barcelona, Spain. christina.kiel@crg.es', 'Spain|Spain|Spain', 14, 'Binding Sites|Computer Simulation|Conserved Sequence|Evolution, Molecular|Models, Chemical|Models, Genetic|Protein Binding|Protein Interaction Mapping|Signal Transduction|ras Proteins', 'Journal Article', '10.1371/journal.pcbi.1000245', '19096503', 'Evolutionary conservation of protein interaction properties has been shown to be a valuable indication for functional importance. Here we use homology interface modeling of 10 Ras-effector complexes by selecting ortholog proteins from 12 organisms representing the major eukaryotic branches, except plants. We find that with increasing divergence time the sequence similarity decreases with respect to the human protein, but the affinities and association rate constants are conserved as predicted by the protein design algorithm, FoldX. In parallel we have done computer simulations on a minimal network based on Ras-effector interactions, and our results indicate that in the absence of negative feedback, changes in kinetics that result in similar binding constants have strong consequences on network behavior. This, together with the previous results, suggests an important biological role, not only for equilibrium binding constants but also for kinetics in signaling processes involving Ras-effector interactions. Our findings are important to take into consideration in system biology approaches and simulations of biological networks.'),
(84085, 2008, 'plos', 'I am not a scientist, I am a number', 'Bourne, Philip E|Fink, J Lynn', 'Skaggs School of Pharmacy and Pharmaceutical Sciences, University of California San Diego, La Jolla, CA, USA. bourne@sdsc.edu|Skaggs School of Pharmacy and Pharmaceutical Sciences, University of California San Diego, La Jolla, CA, USA. bourne@sdsc.edu', 'United States|United States', 11, 'Algorithms|Authorship|Bibliometrics|Journal Impact Factor|Peer Review|Publishing|Records|Science|United States', 'Journal Article', '10.1371/journal.pcbi.1000247', '19112480', '-'),
(84086, 2008, 'plos', 'The morphological identity of insect dendrites', 'Cuntz, Hermann|Forstner, Friedrich|Haag, Juergen|Borst, Alexander', 'Wolfson Institute for Biomedical Research and Department of Physiology, University College London, London, UK. h.cuntz@ucl.ac.uk|Wolfson Institute for Biomedical Research and Department of Physiology, University College London, London, UK. h.cuntz@ucl.ac.uk|Wolfson Institute for Biomedical Research and Department of Physiology, University College London, London, UK. h.cuntz@ucl.ac.uk|Wolfson Institute for Biomedical Research and Department of Physiology, University College London, London, UK. h.cuntz@ucl.ac.uk', 'United Kingdom|United Kingdom|United Kingdom|United Kingdom', 53, 'Animals|Computer Simulation|Dendrites|Diptera|Models, Anatomic|Models, Neurological|Sensory Receptor Cells', 'Journal Article', '10.1371/journal.pcbi.1000251', '19112481', 'Dendrite morphology, a neurons anatomical fingerprint, is a neuroscientists asset in unveiling organizational principles in the brain. However, the genetic program encoding the morphological identity of a single dendrite remains a mystery. In order to obtain a formal understanding of dendritic branching, we studied distributions of morphological parameters in a group of four individually identifiable neurons of the fly visual system. We found that parameters relating to the branching topology were similar throughout all cells. Only parameters relating to the area covered by the dendrite were cell type specific. With these areas, artificial dendrites were grown based on optimization principles minimizing the amount of wiring and maximizing synaptic democracy. Although the same branching rule was used for all cells, this yielded dendritic structures virtually indistinguishable from their real counterparts. From these principles we derived a fully-automated model-based neuron reconstruction procedure validating the artificial branching rule. In conclusion, we suggest that the genetic program implementing neuronal branching could be constant in all cells whereas the one responsible for the dendrite spanning field should be cell specific.'),
(84087, 2008, 'plos', 'A mathematical framework for the selection of an optimal set of peptides for epitope-based vaccines', 'Toussaint, Nora C|Dönnes, Pierre|Kohlbacher, Oliver', 'Simulation of Biological Systems, Center for Bioinformatics, Eberhard Karls University Tübingen, Tübingen, Germany. toussaint@informatik.uni-tuebingen.de|Simulation of Biological Systems, Center for Bioinformatics, Eberhard Karls University Tübingen, Tübingen, Germany. toussaint@informatik.uni-tuebingen.de|Simulation of Biological Systems, Center for Bioinformatics, Eberhard Karls University Tübingen, Tübingen, Germany. toussaint@informatik.uni-tuebingen.de', 'Germany|Germany|Germany', 23, 'Algorithms|Amino Acid Sequence|Computer Simulation|Epitope Mapping|Models, Immunological|Molecular Sequence Data|Sequence Analysis, Protein|Vaccines, Subunit', 'Journal Article', '10.1371/journal.pcbi.1000246', '19112482', 'Epitope-based vaccines (EVs) have a wide range of applications: from therapeutic to prophylactic approaches, from infectious diseases to cancer. The development of an EV is based on the knowledge of target-specific antigens from which immunogenic peptides, so-called epitopes, are derived. Such epitopes form the key components of the EV. Due to regulatory, economic, and practical concerns the number of epitopes that can be included in an EV is limited. Furthermore, as the major histocompatibility complex (MHC) binding these epitopes is highly polymorphic, every patient possesses a set of MHC class I and class II molecules of differing specificities. A peptide combination effective for one person can thus be completely ineffective for another. This renders the optimal selection of these epitopes an important and interesting optimization problem. In this work we present a mathematical framework based on integer linear programming (ILP) that allows the formulation of various flavors of the vaccine design problem and the efficient identification of optimal sets of epitopes. Out of a user-defined set of predicted or experimentally determined epitopes, the framework selects the set with the maximum likelihood of eliciting a broad and potent immune response. Our ILP approach allows an elegant and flexible formulation of numerous variants of the EV design problem. In order to demonstrate this, we show how common immunological requirements for a good EV (e.g., coverage of epitopes from each antigen, coverage of all MHC alleles in a set, or avoidance of epitopes with high mutation rates) can be translated into constraints or modifications of the objective function within the ILP framework. An implementation of the algorithm outperforms a simple greedy strategy as well as a previously suggested evolutionary algorithm and has runtimes on the order of seconds for typical problem sizes.'),
(84088, 2008, 'plos', 'Search algorithms as a framework for the optimization of drug combinations', 'Calzolari, Diego|Bruschi, Stefania|Coquin, Laurence|Schofield, Jennifer|Feala, Jacob D|Reed, John C|McCulloch, Andrew D|Paternostro, Giovanni', 'Burnham Institute for Medical Research, La Jolla, CA, USA.|Burnham Institute for Medical Research, La Jolla, CA, USA.|Burnham Institute for Medical Research, La Jolla, CA, USA.|Burnham Institute for Medical Research, La Jolla, CA, USA.|Burnham Institute for Medical Research, La Jolla, CA, USA.|Burnham Institute for Medical Research, La Jolla, CA, USA.|Burnham Institute for Medical Research, La Jolla, CA, USA.|Burnham Institute for Medical Research, La Jolla, CA, USA.', 'United States|United States|United States|United States|United States|United States|United States|United States', 62, 'Algorithms|Decision Support Techniques|Dose-Response Relationship, Drug|Drug Therapy, Combination|Drug Therapy, Computer-Assisted|Pharmaceutical Preparations', 'Journal Article', '10.1371/journal.pcbi.1000249', '19112483', 'Combination therapies are often needed for effective clinical outcomes in the management of complex diseases, but presently they are generally based on empirical clinical experience. Here we suggest a novel application of search algorithms -- originally developed for digital communication -- modified to optimize combinations of therapeutic interventions. In biological experiments measuring the restoration of the decline with age in heart function and exercise capacity in Drosophila melanogaster, we found that search algorithms correctly identified optimal combinations of four drugs using only one-third of the tests performed in a fully factorial search. In experiments identifying combinations of three doses of up to six drugs for selective killing of human cancer cells, search algorithms resulted in a highly significant enrichment of selective combinations compared with random searches. In simulations using a network model of cell death, we found that the search algorithms identified the optimal combinations of 6-9 interventions in 80-90% of tests, compared with 15-30% for an equivalent random search. These findings suggest that modified search algorithms from information theory have the potential to enhance the discovery of novel therapeutic drug combinations. This report also helps to frame a biomedical problem that will benefit from an interdisciplinary effort and suggests a general strategy for its solution.'),
(84089, 2008, 'plos', 'Mechanics and dynamics of X-chromosome pairing at X inactivation', 'Scialdone, Antonio|Nicodemi, Mario', 'Dipartimento di Scienze Fisiche, Università di Napoli Federico II, Naples, Italy.|Dipartimento di Scienze Fisiche, Università di Napoli Federico II, Naples, Italy.', 'Italy|Italy', 15, 'Chromosome Mapping|Chromosome Pairing|Chromosomes, Human, X|Computer Simulation|Humans|Models, Genetic|Models, Statistical|Sequence Analysis, DNA|X Chromosome Inactivation', 'Journal Article', '10.1371/journal.pcbi.1000244', '19112484', 'At the onset of X-chromosome inactivation, the vital process whereby female mammalian cells equalize X products with respect to males, the X chromosomes are colocalized along their Xic (X-inactivation center) regions. The mechanism inducing recognition and pairing of the Xs remains, though, elusive. Starting from recent discoveries on the molecular factors and on the DNA sequences (the so-called pairing sites) involved, we dissect the mechanical basis of Xic colocalization by using a statistical physics model. We show that soluble DNA-specific binding molecules, such as those experimentally identified, can be indeed sufficient to induce the spontaneous colocalization of the homologous chromosomes but only when their concentration, or chemical affinity, rises above a threshold value as a consequence of a thermodynamic phase transition. We derive the likelihood of pairing and its probability distribution. Chromosome dynamics has two stages: an initial independent Brownian diffusion followed, after a characteristic time scale, by recognition and pairing. Finally, we investigate the effects of DNA deletion/insertions in the region of pairing sites and compare model predictions to available experimental data.'),
(84090, 2008, 'plos', 'Identification of mechanosensitive genes during embryonic bone formation', 'Nowlan, Niamh C|Prendergast, Patrick J|Murphy, Paula', 'Department of Zoology, School of Natural Sciences, Trinity College Dublin, Dublin, Ireland. nowlann@tcd.ie|Department of Zoology, School of Natural Sciences, Trinity College Dublin, Dublin, Ireland. nowlann@tcd.ie|Department of Zoology, School of Natural Sciences, Trinity College Dublin, Dublin, Ireland. nowlann@tcd.ie', 'Ireland|Ireland|Ireland', 44, 'Animals|Bone Development|Bone and Bones|Collagen Type X|Gene Expression Profiling|Hedgehog Proteins|Humans|Mechanotransduction, Cellular|Signal Transduction', 'Journal Article', '10.1371/journal.pcbi.1000250', '19112485', 'Although it is known that mechanical forces are needed for normal bone development, the current understanding of how biophysical stimuli are interpreted by and integrated with genetic regulatory mechanisms is limited. Mechanical forces are thought to be mediated in cells by mechanosensitive genes, but it is a challenge to demonstrate that the genetic regulation of the biological system is dependant on particular mechanical forces in vivo. We propose a new means of selecting candidate mechanosensitive genes by comparing in vivo gene expression patterns with patterns of biophysical stimuli, computed using finite element analysis. In this study, finite element analyses of the avian embryonic limb were performed using anatomically realistic rudiment and muscle morphologies, and patterns of biophysical stimuli were compared with the expression patterns of four candidate mechanosensitive genes integral to bone development. The expression patterns of two genes, Collagen X (ColX) and Indian hedgehog (Ihh), were shown to colocalise with biophysical stimuli induced by embryonic muscle contractions, identifying them as potentially being involved in the mechanoregulation of bone formation. An altered mechanical environment was induced in the embryonic chick, where a neuromuscular blocking agent was administered in ovo to modify skeletal muscle contractions. Finite element analyses predicted dramatic changes in levels and patterns of biophysical stimuli, and a number of immobilised specimens exhibited differences in ColX and Ihh expression. The results obtained indicate that computationally derived patterns of biophysical stimuli can be used to inform a directed search for genes that may play a mechanoregulatory role in particular in vivo events or processes. Furthermore, the experimental data demonstrate that ColX and Ihh are involved in mechanoregulatory pathways and may be key mediators in translating information from the mechanical environment to the molecular regulation of bone formation in the embryo.'),
(84091, 2008, 'plos', 'Tag-trigger-consolidation: a model of early and late long-term-potentiation and depression', 'Clopath, Claudia|Ziegler, Lorric|Vasilaki, Eleni|Büsing, Lars|Gerstner, Wulfram', 'Laboratory of Computational Neuroscience, Brain-Mind Institute and School of Computer and Communication Sciences, Ecole Polytechnique Fédérale de Lausanne, Lausanne, Switzerland.|Laboratory of Computational Neuroscience, Brain-Mind Institute and School of Computer and Communication Sciences, Ecole Polytechnique Fédérale de Lausanne, Lausanne, Switzerland.|Laboratory of Computational Neuroscience, Brain-Mind Institute and School of Computer and Communication Sciences, Ecole Polytechnique Fédérale de Lausanne, Lausanne, Switzerland.|Laboratory of Computational Neuroscience, Brain-Mind Institute and School of Computer and Communication Sciences, Ecole Polytechnique Fédérale de Lausanne, Lausanne, Switzerland.|Laboratory of Computational Neuroscience, Brain-Mind Institute and School of Computer and Communication Sciences, Ecole Polytechnique Fédérale de Lausanne, Lausanne, Switzerland.', 'Switzerland|Switzerland|Switzerland|Switzerland|Switzerland', 78, 'Animals|Computer Simulation|Humans|Long-Term Potentiation|Long-Term Synaptic Depression|Models, Neurological|Nerve Net|Neuronal Plasticity|Synaptic Transmission', 'Journal Article', '10.1371/journal.pcbi.1000248', '19112486', 'Changes in synaptic efficacies need to be long-lasting in order to serve as a substrate for memory. Experimentally, synaptic plasticity exhibits phases covering the induction of long-term potentiation and depression (LTP/LTD) during the early phase of synaptic plasticity, the setting of synaptic tags, a trigger process for protein synthesis, and a slow transition leading to synaptic consolidation during the late phase of synaptic plasticity. We present a mathematical model that describes these different phases of synaptic plasticity. The model explains a large body of experimental data on synaptic tagging and capture, cross-tagging, and the late phases of LTP and LTD. Moreover, the model accounts for the dependence of LTP and LTD induction on voltage and presynaptic stimulation frequency. The stabilization of potentiated synapses during the transition from early to late LTP occurs by protein synthesis dynamics that are shared by groups of synapses. The functional consequence of this shared process is that previously stabilized patterns of strong or weak synapses onto the same postsynaptic neuron are well protected against later changes induced by LTP/LTD protocols at individual synapses.'),
(84092, 2008, 'plos', 'A common cortical circuit mechanism for perceptual categorical discrimination and veridical judgment', 'Liu, Feng|Wang, Xiao-Jing', 'Department of Physics, Nanjing University, Nanjing, PR China.|Department of Physics, Nanjing University, Nanjing, PR China.', 'China|China', 21, 'Animals|Cerebral Cortex|Choice Behavior|Computer Simulation|Decision Making|Discrimination Learning|Haplorhini|Models, Neurological|Nerve Net|Visual Perception', 'Journal Article', '10.1371/journal.pcbi.1000253', '19112487', 'Perception involves two types of decisions about the sensory world: identification of stimulus features as analog quantities, or discrimination of the same stimulus features among a set of discrete alternatives. Veridical judgment and categorical discrimination have traditionally been conceptualized as two distinct computational problems. Here, we found that these two types of decision making can be subserved by a shared cortical circuit mechanism. We used a continuous recurrent network model to simulate two monkey experiments in which subjects were required to make either a two-alternative forced choice or a veridical judgment about the direction of random-dot motion. The model network is endowed with a continuum of bell-shaped population activity patterns, each representing a possible motion direction. Slow recurrent excitation underlies accumulation of sensory evidence, and its interplay with strong recurrent inhibition leads to decision behaviors. The model reproduced the monkeys performance as well as single-neuron activity in the categorical discrimination task. Furthermore, we examined how direction identification is determined by a combination of sensory stimulation and microstimulation. Using a population-vector measure, we found that direction judgments instantiate winner-take-all (with the population vector coinciding with either the coherent motion direction or the electrically elicited motion direction) when two stimuli are far apart, or vector averaging (with the population vector falling between the two directions) when two stimuli are close to each other. Interestingly, for a broad range of intermediate angular distances between the two stimuli, the network displays a mixed strategy in the sense that direction estimates are stochastically produced by winner-take-all on some trials and by vector averaging on the other trials, a model prediction that is experimentally testable. This work thus lends support to a common neurodynamic framework for both veridical judgment and categorical discrimination in perceptual decision making.'),
(84093, 2008, 'plos', 'Game theory of mind', 'Yoshida, Wako|Dolan, Ray J|Friston, Karl J', 'The Wellcome Trust Centre for Neuroimaging, University College London, UK. w.yoshida@fil.ion.ucl.ac.uk|The Wellcome Trust Centre for Neuroimaging, University College London, UK. w.yoshida@fil.ion.ucl.ac.uk|The Wellcome Trust Centre for Neuroimaging, University College London, UK. w.yoshida@fil.ion.ucl.ac.uk', 'United Kingdom|United Kingdom|United Kingdom', 123, 'Animals|Cognition|Computer Simulation|Decision Making|Game Theory|Humans|Models, Biological|Predatory Behavior|Reward', 'Journal Article', '10.1371/journal.pcbi.1000254', '19112488', 'This paper introduces a model of theory of mind, namely, how we represent the intentions and goals of others to optimise our mutual interactions. We draw on ideas from optimum control and game theory to provide a game theory of mind. First, we consider the representations of goals in terms of value functions that are prescribed by utility or rewards. Critically, the joint value functions and ensuing behaviour are optimised recursively, under the assumption that I represent your value function, your representation of mine, your representation of my representation of yours, and so on ad infinitum. However, if we assume that the degree of recursion is bounded, then players need to estimate the opponents degree of recursion (i.e., sophistication) to respond optimally. This induces a problem of inferring the opponents sophistication, given behavioural exchanges. We show it is possible to deduce whether players make inferences about each other and quantify their sophistication on the basis of choices in sequential games. This rests on comparing generative models of choices with, and without, inference. Model comparison is demonstrated using simulated and real data from a stag-hunt. Finally, we note that exactly the same sophisticated behaviour can be achieved by optimising the utility function itself (through prosocial utility), producing unsophisticated but apparently altruistic agents. This may be relevant ethologically in hierarchal game theory and coevolution.'),
(84094, 2009, 'plos', 'Questioning the ubiquity of neofunctionalization', 'Gibson, Todd A|Goldberg, Debra S', 'Computational Bioscience Program, University of Colorado Denver, Aurora, Colorado, United States of America. Todd.Gibson@ucdenver.edu|Computational Bioscience Program, University of Colorado Denver, Aurora, Colorado, United States of America. Todd.Gibson@ucdenver.edu', 'United States|United States', 26, 'Computer Simulation|Evolution, Molecular|Gene Duplication|Genetic Variation|Models, Genetic|Protein Interaction Mapping|Proteins|Signal Transduction', 'Journal Article', '10.1371/journal.pcbi.1000252', '19119408', 'Gene duplication provides much of the raw material from which functional diversity evolves. Two evolutionary mechanisms have been proposed that generate functional diversity: neofunctionalization, the de novo acquisition of function by one duplicate, and subfunctionalization, the partitioning of ancestral functions between gene duplicates. With protein interactions as a surrogate for protein functions, evidence of prodigious neofunctionalization and subfunctionalization has been identified in analyses of empirical protein interactions and evolutionary models of protein interactions. However, we have identified three phenomena that have contributed to neofunctionalization being erroneously identified as a significant factor in protein interaction network evolution. First, self-interacting proteins are underreported in interaction data due to biological artifacts and design limitations in the two most common high-throughput protein interaction assays. Second, evolutionary inferences have been drawn from paralog analysis without consideration for concurrent and subsequent duplication events. Third, the theoretical model of prodigious neofunctionalization is unable to reproduce empirical network clustering and relies on untenable parameter requirements. In light of these findings, we believe that protein interaction evolution is more persuasively characterized by subfunctionalization and self-interactions.'),
(84095, 2009, 'plos', 'Polyamine sharing between tubulin dimers favours microtubule nucleation and elongation via facilitated diffusion', 'Mechulam, Alain|Chernov, Konstantin G|Mucher, Elodie|Hamon, Loic|Curmi, Patrick A|Pastré, David', 'Laboratoire Structure-Activité des Biomolécules Normales et Pathologiques, Université Evry-Val dEssonne, Evry, France.|Laboratoire Structure-Activité des Biomolécules Normales et Pathologiques, Université Evry-Val dEssonne, Evry, France.|Laboratoire Structure-Activité des Biomolécules Normales et Pathologiques, Université Evry-Val dEssonne, Evry, France.|Laboratoire Structure-Activité des Biomolécules Normales et Pathologiques, Université Evry-Val dEssonne, Evry, France.|Laboratoire Structure-Activité des Biomolécules Normales et Pathologiques, Université Evry-Val dEssonne, Evry, France.|Laboratoire Structure-Activité des Biomolécules Normales et Pathologiques, Université Evry-Val dEssonne, Evry, France.', 'France|France|France|France|France|France', 23, 'Binding Sites|Computer Simulation|Diffusion|Dimerization|Microtubules|Models, Chemical|Models, Molecular|Polyamines|Protein Binding|Protein Conformation|Tubulin', 'Journal Article', '10.1371/journal.pcbi.1000255', '19119409', 'We suggest for the first time that the action of multivalent cations on microtubule dynamics can result from facilitated diffusion of GTP-tubulin to the microtubule ends. Facilitated diffusion can promote microtubule assembly, because, upon encountering a growing nucleus or the microtubule wall, random GTP-tubulin sliding on their surfaces will increase the probability of association to the target sites (nucleation sites or MT ends). This is an original explanation for understanding the apparent discrepancy between the high rate of microtubule elongation and the low rate of tubulin association at the microtubule ends in the viscous cytoplasm. The mechanism of facilitated diffusion requires an attraction force between two tubulins, which can result from the sharing of multivalent counterions. Natural polyamines (putrescine, spermidine, and spermine) are present in all living cells and are potent agents to trigger tubulin self-attraction. By using an analytical model, we analyze the implication of facilitated diffusion mediated by polyamines on nucleation and elongation of microtubules. In vitro experiments using pure tubulin indicate that the promotion of microtubule assembly by polyamines is typical of facilitated diffusion. The results presented here show that polyamines can be of particular importance for the regulation of the microtubule network in vivo and provide the basis for further investigations into the effects of facilitated diffusion on cytoskeleton dynamics.');
INSERT INTO `papers` (`id`, `ano`, `journal`, `titulo`, `autores`, `afiliacao`, `pais`, `citacoes`, `palavra_chave`, `categorias`, `doi`, `pubmed`, `abstract`) VALUES
(84096, 2009, 'plos', 'Shape, size, and robustness: feasible regions in the parameter space of biochemical networks', 'Dayarian, Adel|Chaves, Madalena|Sontag, Eduardo D|Sengupta, Anirvan M', 'Department of Physics and Astronomy, Rutgers University, Piscataway, New Jersey, United States of America.|Department of Physics and Astronomy, Rutgers University, Piscataway, New Jersey, United States of America.|Department of Physics and Astronomy, Rutgers University, Piscataway, New Jersey, United States of America.|Department of Physics and Astronomy, Rutgers University, Piscataway, New Jersey, United States of America.', 'Jersey|Jersey|Jersey|Jersey', 31, 'Algorithms|Computer Simulation|Feasibility Studies|Gene Expression Regulation|Metabolome|Models, Biological|Proteome|Signal Transduction', 'Journal Article', '10.1371/journal.pcbi.1000256', '19119410', 'The concept of robustness of regulatory networks has received much attention in the last decade. One measure of robustness has been associated with the volume of the feasible region, namely, the region in the parameter space in which the system is functional. In this paper, we show that, in addition to volume, the geometry of this region has important consequences for the robustness and the fragility of a network. We develop an approximation within which we could algebraically specify the feasible region. We analyze the segment polarity gene network to illustrate our approach. The study of random walks in the parameter space and how they exit the feasible region provide us with a rich perspective on the different modes of failure of this network model. In particular, we found that, between two alternative ways of activating Wingless, one is more robust than the other. Our method provides a more complete measure of robustness to parameter variation. As a general modeling strategy, our approach is an interesting alternative to Boolean representation of biochemical networks.'),
(84097, 2009, 'plos', 'Predicting cellular growth from gene expression signatures', 'Airoldi, Edoardo M|Huttenhower, Curtis|Gresham, David|Lu, Charles|Caudy, Amy A|Dunham, Maitreya J|Broach, James R|Botstein, David|Troyanskaya, Olga G', 'Lewis-Sigler Institute for Integrative Genomics, Carl Icahn Laboratory, Princeton University, Princeton, New Jersey, United States of America.|Lewis-Sigler Institute for Integrative Genomics, Carl Icahn Laboratory, Princeton University, Princeton, New Jersey, United States of America.|Lewis-Sigler Institute for Integrative Genomics, Carl Icahn Laboratory, Princeton University, Princeton, New Jersey, United States of America.|Lewis-Sigler Institute for Integrative Genomics, Carl Icahn Laboratory, Princeton University, Princeton, New Jersey, United States of America.|Lewis-Sigler Institute for Integrative Genomics, Carl Icahn Laboratory, Princeton University, Princeton, New Jersey, United States of America.|Lewis-Sigler Institute for Integrative Genomics, Carl Icahn Laboratory, Princeton University, Princeton, New Jersey, United States of America.|Lewis-Sigler Institute for Integrative Genomics, Carl Icahn Laboratory, Princeton University, Princeton, New Jersey, United States of America.|Lewis-Sigler Institute for Integrative Genomics, Carl Icahn Laboratory, Princeton University, Princeton, New Jersey, United States of America.|Lewis-Sigler Institute for Integrative Genomics, Carl Icahn Laboratory, Princeton University, Princeton, New Jersey, United States of America.', 'Jersey|Jersey|Jersey|Jersey|Jersey|Jersey|Jersey|Jersey|Jersey', 72, 'Algorithms|Cell Proliferation|Computer Simulation|Gene Expression Profiling|Models, Biological|Proteome|Saccharomyces cerevisiae|Saccharomyces cerevisiae Proteins', 'Journal Article', '10.1371/journal.pcbi.1000257', '19119411', 'Maintaining balanced growth in a changing environment is a fundamental systems-level challenge for cellular physiology, particularly in microorganisms. While the complete set of regulatory and functional pathways supporting growth and cellular proliferation are not yet known, portions of them are well understood. In particular, cellular proliferation is governed by mechanisms that are highly conserved from unicellular to multicellular organisms, and the disruption of these processes in metazoans is a major factor in the development of cancer. In this paper, we develop statistical methodology to identify quantitative aspects of the regulatory mechanisms underlying cellular proliferation in Saccharomyces cerevisiae. We find that the expression levels of a small set of genes can be exploited to predict the instantaneous growth rate of any cellular culture with high accuracy. The predictions obtained in this fashion are robust to changing biological conditions, experimental methods, and technological platforms. The proposed model is also effective in predicting growth rates for the related yeast Saccharomyces bayanus and the highly diverged yeast Schizosaccharomyces pombe, suggesting that the underlying regulatory signature is conserved across a wide range of unicellular evolution. We investigate the biological significance of the gene expression signature that the predictions are based upon from multiple perspectives: by perturbing the regulatory network through the Ras/PKA pathway, observing strong upregulation of growth rate even in the absence of appropriate nutrients, and discovering putative transcription factor binding sites, observing enrichment in growth-correlated genes. More broadly, the proposed methodology enables biological insights about growth at an instantaneous time scale, inaccessible by direct experimental methods. Data and tools enabling others to apply our methods are available at http://function.princeton.edu/growthrate.'),
(84098, 2009, 'plos', 'Deterministic mechanical model of T-killer cell polarization reproduces the wandering of aim between simultaneously engaged targets', 'Kim, Mun Ju|Maly, Ivan V', 'Department of Computational Biology, University of Pittsburgh School of Medicine, Pittsburgh, Pennsylvania, United States of America.|Department of Computational Biology, University of Pittsburgh School of Medicine, Pittsburgh, Pennsylvania, United States of America.', 'United States|United States', 16, 'Animals|Cell Compartmentation|Cell Polarity|Centrosome|Cytoplasmic Streaming|Humans|Intercellular Junctions|Lymphocyte Activation|Microtubules|Models, Biological|Molecular Motor Proteins|Natural Killer T-Cells', 'Journal Article', '10.1371/journal.pcbi.1000260', '19132078', 'T-killer cells of the immune system eliminate virus-infected and tumorous cells through direct cell-cell interactions. Reorientation of the killing apparatus inside the T cell to the T-cell interface with the target cell ensures specificity of the immune response. The killing apparatus can also oscillate next to the cell-cell interface. When two target cells are engaged by the T cell simultaneously, the killing apparatus can oscillate between the two interface areas. This oscillation is one of the most striking examples of cell movements that give the microscopist an unmechanistic impression of the cells fidgety indecision. We have constructed a three-dimensional, numerical biomechanical model of the molecular-motor-driven microtubule cytoskeleton that positions the killing apparatus. The model demonstrates that the cortical pulling mechanism is indeed capable of orienting the killing apparatus into the functional position under a range of conditions. The model also predicts experimentally testable limitations of this commonly hypothesized mechanism of T-cell polarization. After the reorientation, the numerical solution exhibits complex, multidirectional, multiperiodic, and sustained oscillations in the absence of any external guidance or stochasticity. These computational results demonstrate that the strikingly animate wandering of aim in T-killer cells has a purely mechanical and deterministic explanation.'),
(84099, 2009, 'plos', 'An analysis of enzyme kinetics data for mitochondrial DNA strand termination by nucleoside reverse transcription inhibitors', 'Wendelsdorf, Katherine V|Song, Zhuo|Cao, Yang|Samuels, David C', 'Virginia Bioinformatics Institute, Virginia Polytechnic Institute and State University, Virginia, United States of America.|Virginia Bioinformatics Institute, Virginia Polytechnic Institute and State University, Virginia, United States of America.|Virginia Bioinformatics Institute, Virginia Polytechnic Institute and State University, Virginia, United States of America.|Virginia Bioinformatics Institute, Virginia Polytechnic Institute and State University, Virginia, United States of America.', 'United States|United States|United States|United States', 0, 'Base Sequence|DNA Replication|DNA, Mitochondrial|DNA-Directed DNA Polymerase|Deoxyribonucleotides|Dose-Response Relationship, Drug|Humans|Kinetics|Models, Biological|Nucleic Acid Synthesis Inhibitors|Nucleosides|Reverse Transcriptase Inhibitors|Zidovudine', 'Journal Article', '10.1371/journal.pcbi.1000261', '19132079', 'Nucleoside analogs used in antiretroviral treatment have been associated with mitochondrial toxicity. The polymerase-gamma hypothesis states that this toxicity stems from the analogs inhibition of the mitochondrial DNA polymerase (polymerase-gamma) leading to mitochondrial DNA (mtDNA) depletion. We have constructed a computational model of the interaction of polymerase-gamma with activated nucleoside and nucleotide analog drugs, based on experimentally measured reaction rates and base excision rates, together with the mtDNA genome size, the human mtDNA sequence, and mitochondrial dNTP concentrations. The model predicts an approximately 1000-fold difference in the activated drug concentration required for a 50% probability of mtDNA strand termination between the activated di-deoxy analogs d4T, ddC, and ddI (activated to ddA) and the activated forms of the analogs 3TC, TDF, AZT, FTC, and ABC. These predictions are supported by experimental and clinical data showing significantly greater mtDNA depletion in cell culture and patient samples caused by the di-deoxy analog drugs. For zidovudine (AZT) we calculated a very low mtDNA replication termination probability, in contrast to its reported mitochondrial toxicity in vitro and clinically. Therefore AZT mitochondrial toxicity is likely due to a mechanism that does not involve strand termination of mtDNA replication.'),
(84100, 2009, 'plos', 'Evolutionary sequence modeling for discovery of peptide hormones', 'Sonmez, Kemal|Zaveri, Naunihal T|Kerman, Ilan A|Burke, Sharon|Neal, Charles R|Xie, Xinmin|Watson, Stanley J|Toll, Lawrence', 'SRI International, Menlo Park, California, United States of America.|SRI International, Menlo Park, California, United States of America.|SRI International, Menlo Park, California, United States of America.|SRI International, Menlo Park, California, United States of America.|SRI International, Menlo Park, California, United States of America.|SRI International, Menlo Park, California, United States of America.|SRI International, Menlo Park, California, United States of America.|SRI International, Menlo Park, California, United States of America.', 'United States|United States|United States|United States|United States|United States|United States|Un', 57, 'Amino Acid Sequence|Animals|Binding Sites|Brain|Brain Chemistry|Computational Biology|Conserved Sequence|Databases, Protein|Evolution, Molecular|Genome|Humans|Ligands|Markov Chains|Mice|Models, Statistical|Pattern Recognition, Automated|Peptide Hormones|Receptors, G-Protein-Coupled|Sequence Alignment|Sequence Analysis, Protein|Sequence Homology, Amino Acid|Species Specificity', 'Journal Article', '10.1371/journal.pcbi.1000258', '19132080', 'There are currently a large number of orphan G-protein-coupled receptors (GPCRs) whose endogenous ligands (peptide hormones) are unknown. Identification of these peptide hormones is a difficult and important problem. We describe a computational framework that models spatial structure along the genomic sequence simultaneously with the temporal evolutionary path structure across species and show how such models can be used to discover new functional molecules, in particular peptide hormones, via cross-genomic sequence comparisons. The computational framework incorporates a priori high-level knowledge of structural and evolutionary constraints into a hierarchical grammar of evolutionary probabilistic models. This computational method was used for identifying novel prohormones and the processed peptide sites by producing sequence alignments across many species at the functional-element level. Experimental results with an initial implementation of the algorithm were used to identify potential prohormones by comparing the human and non-human proteins in the Swiss-Prot database of known annotated proteins. In this proof of concept, we identified 45 out of 54 prohormones with only 44 false positives. The comparison of known and hypothetical human and mouse proteins resulted in the identification of a novel putative prohormone with at least four potential neuropeptides. Finally, in order to validate the computational methodology, we present the basic molecular biological characterization of the novel putative peptide hormone, including its identification and regional localization in the brain. This species comparison, HMM-based computational approach succeeded in identifying a previously undiscovered neuropeptide from whole genome protein sequences. This novel putative peptide hormone is found in discreet brain regions as well as other organs. The success of this approach will have a great impact on our understanding of GPCRs and associated pathways and help to identify new targets for drug development.'),
(84101, 2009, 'plos', 'State based model of long-term potentiation and synaptic tagging and capture', 'Barrett, Adam B|Billings, Guy O|Morris, Richard G M|van Rossum, Mark C W', 'Institute for Adaptive and Neural Computation, University of Edinburgh, Edinburgh, United Kingdom. abarrett@inf.ed.ac.uk|Institute for Adaptive and Neural Computation, University of Edinburgh, Edinburgh, United Kingdom. abarrett@inf.ed.ac.uk|Institute for Adaptive and Neural Computation, University of Edinburgh, Edinburgh, United Kingdom. abarrett@inf.ed.ac.uk|Institute for Adaptive and Neural Computation, University of Edinburgh, Edinburgh, United Kingdom. abarrett@inf.ed.ac.uk', 'United Kingdom|United Kingdom|United Kingdom|United Kingdom', 0, 'Animals|Electric Stimulation|Evoked Potentials|Hippocampus|Humans|Long-Term Potentiation|Memory|Models, Neurological|Nerve Net|Nerve Tissue Proteins|Neurons|Stochastic Processes|Synapses|Synaptic Transmission', 'Journal Article', '10.1371/journal.pcbi.1000259', '19148264', 'Recent data indicate that plasticity protocols have not only synapse-specific but also more widespread effects. In particular, in synaptic tagging and capture (STC), tagged synapses can capture plasticity-related proteins, synthesized in response to strong stimulation of other synapses. This leads to long-lasting modification of only weakly stimulated synapses. Here we present a biophysical model of synaptic plasticity in the hippocampus that incorporates several key results from experiments on STC. The model specifies a set of physical states in which a synapse can exist, together with transition rates that are affected by high- and low-frequency stimulation protocols. In contrast to most standard plasticity models, the model exhibits both early- and late-phase LTP/D, de-potentiation, and STC. As such, it provides a useful starting point for further theoretical work on the role of STC in learning and memory.'),
(84102, 2009, 'plos', 'Action potential initiation in the hodgkin-huxley model', 'Colwell, Lucy J|Brenner, Michael P', 'School of Engineering and Applied Science, Harvard University, Cambridge, Massachusetts, United States of America. lcolwell@fas.harvard.edu|School of Engineering and Applied Science, Harvard University, Cambridge, Massachusetts, United States of America. lcolwell@fas.harvard.edu', 'United States|United States', 20, 'Action Potentials|Animals|Cats|Cerebral Cortex|Electrophysiology|Ion Channel Gating|Models, Neurological|Models, Statistical|Neural Conduction|Neurons|Quantum Theory|Synaptic Potentials', 'Journal Article', '10.1371/journal.pcbi.1000265', '19148265', 'A recent paper of B. Naundorf et al. described an intriguing negative correlation between variability of the onset potential at which an action potential occurs (the onset span) and the rapidity of action potential initiation (the onset rapidity). This correlation was demonstrated in numerical simulations of the Hodgkin-Huxley model. Due to this antagonism, it is argued that Hodgkin-Huxley-type models are unable to explain action potential initiation observed in cortical neurons in vivo or in vitro. Here we apply a method from theoretical physics to derive an analytical characterization of this problem. We analytically compute the probability distribution of onset potentials and analytically derive the inverse relationship between onset span and onset rapidity. We find that the relationship between onset span and onset rapidity depends on the level of synaptic background activity. Hence we are able to elucidate the regions of parameter space for which the Hodgkin-Huxley model is able to accurately describe the behavior of this system.'),
(84103, 2009, 'plos', 'Developmental robustness by obligate interaction of class B floral homeotic genes and proteins', 'Lenser, Thorsten|Theissen, Günter|Dittrich, Peter', 'Department of Computer Science, Friedrich Schiller University, Jena, Germany. thlenser@inf.uni-jena.de|Department of Computer Science, Friedrich Schiller University, Jena, Germany. thlenser@inf.uni-jena.de|Department of Computer Science, Friedrich Schiller University, Jena, Germany. thlenser@inf.uni-jena.de', 'Germany|Germany|Germany', 0, 'Evolution, Molecular|Flowers|Gene Expression Regulation, Developmental|Gene Expression Regulation, Plant|Gene Regulatory Networks|Genes, Homeobox|Genes, Plant|MADS Domain Proteins|Magnoliopsida|Models, Genetic|Phylogeny|Plant Proteins|Protein Multimerization|Stochastic Processes', 'Journal Article', '10.1371/journal.pcbi.1000264', '19148269', 'DEF-like and GLO-like class B floral homeotic genes encode closely related MADS-domain transcription factors that act as developmental switches involved in specifying the identity of petals and stamens during flower development. Class B gene function requires transcriptional upregulation by an autoregulatory loop that depends on obligate heterodimerization of DEF-like and GLO-like proteins. Because switch-like behavior of gene expression can be displayed by single genes already, the functional relevance of this complex circuitry has remained enigmatic. On the basis of a stochastic in silico model of class B gene and protein interactions, we suggest that obligate heterodimerization of class B floral homeotic proteins is not simply the result of neutral drift but enhanced the robustness of cell-fate organ identity decisions in the presence of stochastic noise. This finding strongly corroborates the view that the appearance of this regulatory mechanism during angiosperm phylogeny led to a canalization of flower development and evolution.'),
(84104, 2009, 'plos', 'Partial order optimum likelihood (POOL): maximum likelihood prediction of protein active site residues using 3D Structure and sequence properties', 'Tong, Wenxu|Wei, Ying|Murga, Leonel F|Ondrechen, Mary Jo|Williams, Ronald J', 'College of Computer and Information Science, Northeastern University, Boston, Massachusetts, United States of America.|College of Computer and Information Science, Northeastern University, Boston, Massachusetts, United States of America.|College of Computer and Information Science, Northeastern University, Boston, Massachusetts, United States of America.|College of Computer and Information Science, Northeastern University, Boston, Massachusetts, United States of America.|College of Computer and Information Science, Northeastern University, Boston, Massachusetts, United States of America.', 'United States|United States|United States|United States|United States', 42, 'Amino Acid Sequence|Animals|Catalytic Domain|Conserved Sequence|Genomics|Humans|Likelihood Functions|Models, Chemical|Models, Molecular|Protein Folding|Protein Structure, Secondary|Proteins|ROC Curve|Sequence Alignment|Sequence Analysis, Protein|Static Electricity|Structure-Activity Relationship|Thermodynamics', 'Journal Article', '10.1371/journal.pcbi.1000266', '19148270', 'A new monotonicity-constrained maximum likelihood approach, called Partial Order Optimum Likelihood (POOL), is presented and applied to the problem of functional site prediction in protein 3D structures, an important current challenge in genomics. The input consists of electrostatic and geometric properties derived from the 3D structure of the query protein alone. Sequence-based conservation information, where available, may also be incorporated. Electrostatics features from THEMATICS are combined with multidimensional isotonic regression to form maximum likelihood estimates of probabilities that specific residues belong to an active site. This allows likelihood ranking of all ionizable residues in a given protein based on THEMATICS features. The corresponding ROC curves and statistical significance tests demonstrate that this method outperforms prior THEMATICS-based methods, which in turn have been shown previously to outperform other 3D-structure-based methods for identifying active site residues. Then it is shown that the addition of one simple geometric property, the size rank of the cleft in which a given residue is contained, yields improved performance. Extension of the method to include predictions of non-ionizable residues is achieved through the introduction of environment variables. This extension results in even better performance than THEMATICS alone and constitutes to date the best functional site predictor based on 3D structure only, achieving nearly the same level of performance as methods that use both 3D structure and sequence alignment data. Finally, the method also easily incorporates such sequence alignment data, and when this information is included, the resulting method is shown to outperform the best current methods using any combination of sequence alignments and 3D structures. Included is an analysis demonstrating that when THEMATICS features, cleft size rank, and alignment-based conservation scores are used individually or in combination THEMATICS features represent the single most important component of such classifiers.'),
(84105, 2009, 'plos', 'Phylogenetic and functional assessment of orthologs inference projects and methods', 'Altenhoff, Adrian M|Dessimoz, Christophe', 'Institute of Computational Science, ETH Zurich, and Swiss Institute of Bioinformatics, Zürich, Switzerland. adrian.altenhoff@inf.ethz.ch|Institute of Computational Science, ETH Zurich, and Swiss Institute of Bioinformatics, Zürich, Switzerland. adrian.altenhoff@inf.ethz.ch', 'Switzerland|Switzerland', 0, 'Animals|Databases, Genetic|Genetic Speciation|Genomics|Humans|Models, Genetic|Phylogeny|Physiology, Comparative|Sensitivity and Specificity|Species Specificity', 'Journal Article', '10.1371/journal.pcbi.1000262', '19148271', 'Accurate genome-wide identification of orthologs is a central problem in comparative genomics, a fact reflected by the numerous orthology identification projects developed in recent years. However, only a few reports have compared their accuracy, and indeed, several recent efforts have not yet been systematically evaluated. Furthermore, orthology is typically only assessed in terms of function conservation, despite the phylogeny-based original definition of Fitch. We collected and mapped the results of nine leading orthology projects and methods (COG, KOG, Inparanoid, OrthoMCL, Ensembl Compara, Homologene, RoundUp, EggNOG, and OMA) and two standard methods (bidirectional best-hit and reciprocal smallest distance). We systematically compared their predictions with respect to both phylogeny and function, using six different tests. This required the mapping of millions of sequences, the handling of hundreds of millions of predicted pairs of orthologs, and the computation of tens of thousands of trees. In phylogenetic analysis or in functional analysis where high specificity is required, we find that OMA and Homologene perform best. At lower functional specificity but higher coverage level, OrthoMCL outperforms Ensembl Compara, and to a lesser extent Inparanoid. Lastly, the large coverage of the recent EggNOG can be of interest to build broad functional grouping, but the method is not specific enough for phylogenetic or detailed function analyses. In terms of general methodology, we observe that the more sophisticated tree reconstruction/reconciliation approach of Ensembl Compara was at times outperformed by pairwise comparison approaches, even in phylogenetic tests. Furthermore, we show that standard bidirectional best-hit often outperforms projects with more complex algorithms. First, the present study provides guidance for the broad community of orthology data users as to which database best suits their needs. Second, it introduces new methodology to verify orthology. And third, it sets performance standards for current and future approaches.'),
(84106, 2009, 'plos', 'Astrocytic mechanisms explaining neural-activity-induced shrinkage of extraneuronal space', 'Østby, Ivar|Øyehaug, Leiv|Einevoll, Gaute T|Nagelhus, Erlend A|Plahte, Erik|Zeuthen, Thomas|Lloyd, Catherine M|Ottersen, Ole P|Omholt, Stig W', 'Centre for Integrative Genetics, Norwegian University of Life Sciences, As, Norway.|Centre for Integrative Genetics, Norwegian University of Life Sciences, As, Norway.|Centre for Integrative Genetics, Norwegian University of Life Sciences, As, Norway.|Centre for Integrative Genetics, Norwegian University of Life Sciences, As, Norway.|Centre for Integrative Genetics, Norwegian University of Life Sciences, As, Norway.|Centre for Integrative Genetics, Norwegian University of Life Sciences, As, Norway.|Centre for Integrative Genetics, Norwegian University of Life Sciences, As, Norway.|Centre for Integrative Genetics, Norwegian University of Life Sciences, As, Norway.|Centre for Integrative Genetics, Norwegian University of Life Sciences, As, Norway.', 'Norway|Norway|Norway|Norway|Norway|Norway|Norway|Norway|Norway', 72, 'Animals|Astrocytes|Bicarbonates|Chlorides|Extracellular Space|Humans|Ion Transport|Membrane Potentials|Models, Biological|Neurons|Osmosis|Paracrine Communication|Potassium|Sodium|Sodium-Potassium-Exchanging ATPase|Systems Biology', 'Journal Article', '10.1371/journal.pcbi.1000272', '19165313', 'Neuronal stimulation causes approximately 30% shrinkage of the extracellular space (ECS) between neurons and surrounding astrocytes in grey and white matter under experimental conditions. Despite its possible implications for a proper understanding of basic aspects of potassium clearance and astrocyte function, the phenomenon remains unexplained. Here we present a dynamic model that accounts for current experimental data related to the shrinkage phenomenon in wild-type as well as in gene knockout individuals. We find that neuronal release of potassium and uptake of sodium during stimulation, astrocyte uptake of potassium, sodium, and chloride in passive channels, action of the Na/K/ATPase pump, and osmotically driven transport of water through the astrocyte membrane together seem sufficient for generating ECS shrinkage as such. However, when taking into account ECS and astrocyte ion concentrations observed in connection with neuronal stimulation, the actions of the Na(+)/K(+)/Cl(-) (NKCC1) and the Na(+)/HCO(3) (-) (NBC) cotransporters appear to be critical determinants for achieving observed quantitative levels of ECS shrinkage. Considering the current state of knowledge, the model framework appears sufficiently detailed and constrained to guide future key experiments and pave the way for more comprehensive astroglia-neuron interaction models for normal as well as pathophysiological situations.'),
(84107, 2009, 'plos', 'Model-based therapeutic correction of hypothalamic-pituitary-adrenal axis dysfunction', 'Ben-Zvi, Amos|Vernon, Suzanne D|Broderick, Gordon', 'Department of Chemical and Materials Engineering, University of Alberta, Edmonton, Alberta, Canada.|Department of Chemical and Materials Engineering, University of Alberta, Edmonton, Alberta, Canada.|Department of Chemical and Materials Engineering, University of Alberta, Edmonton, Alberta, Canada.', 'Canada|Canada|Canada', 37, 'Adrenal Insufficiency|Adrenocorticotropic Hormone|Dose-Response Relationship, Drug|Fatigue Syndrome, Chronic|Feedback, Physiological|Humans|Hydrocortisone|Hypothalamo-Hypophyseal System|Models, Biological|Pituitary-Adrenal System|Receptors, Glucocorticoid|Systems Biology|Transcortin', 'Journal Article', '10.1371/journal.pcbi.1000273', '19165314', 'The hypothalamic-pituitary-adrenal (HPA) axis is a major system maintaining body homeostasis by regulating the neuroendocrine and sympathetic nervous systems as well modulating immune function. Recent work has shown that the complex dynamics of this system accommodate several stable steady states, one of which corresponds to the hypocortisol state observed in patients with chronic fatigue syndrome (CFS). At present these dynamics are not formally considered in the development of treatment strategies. Here we use model-based predictive control (MPC) methodology to estimate robust treatment courses for displacing the HPA axis from an abnormal hypocortisol steady state back to a healthy cortisol level. This approach was applied to a recent model of HPA axis dynamics incorporating glucocorticoid receptor kinetics. A candidate treatment that displays robust properties in the face of significant biological variability and measurement uncertainty requires that cortisol be further suppressed for a short period until adrenocorticotropic hormone levels exceed 30% of baseline. Treatment may then be discontinued, and the HPA axis will naturally progress to a stable attractor defined by normal hormone levels. Suppression of biologically available cortisol may be achieved through the use of binding proteins such as CBG and certain metabolizing enzymes, thus offering possible avenues for deployment in a clinical setting. Treatment strategies can therefore be designed that maximally exploit system dynamics to provide a robust response to treatment and ensure a positive outcome over a wide range of conditions. Perhaps most importantly, a treatment course involving further reduction in cortisol, even transient, is quite counterintuitive and challenges the conventional strategy of supplementing cortisol levels, an approach based on steady-state reasoning.'),
(84108, 2009, 'plos', 'Joint evolutionary trees: a large-scale method to predict protein interfaces based on sequence sampling', 'Engelen, Stefan|Trojan, Ladislas A|Sacquin-Mora, Sophie|Lavery, Richard|Carbone, Alessandra', 'Génomique Analytique, Université Pierre et Marie Curie-Paris 6, UMR S511, Paris, France.|Génomique Analytique, Université Pierre et Marie Curie-Paris 6, UMR S511, Paris, France.|Génomique Analytique, Université Pierre et Marie Curie-Paris 6, UMR S511, Paris, France.|Génomique Analytique, Université Pierre et Marie Curie-Paris 6, UMR S511, Paris, France.|Génomique Analytique, Université Pierre et Marie Curie-Paris 6, UMR S511, Paris, France.', 'France|France|France|France|France', 54, 'Binding Sites|Cluster Analysis|Computational Biology|Conserved Sequence|Databases, Protein|Evolution, Molecular|Models, Chemical|Models, Molecular|Neural Networks (Computer)|Phylogeny|Protein Binding|Protein Conformation|Protein Interaction Mapping|Proteins|Sequence Analysis, Protein|Sequence Homology, Amino Acid|Structure-Activity Relationship', 'Journal Article', '10.1371/journal.pcbi.1000267', '19165315', 'The Joint Evolutionary Trees (JET) method detects protein interfaces, the core residues involved in the folding process, and residues susceptible to site-directed mutagenesis and relevant to molecular recognition. The approach, based on the Evolutionary Trace (ET) method, introduces a novel way to treat evolutionary information. Families of homologous sequences are analyzed through a Gibbs-like sampling of distance trees to reduce effects of erroneous multiple alignment and impacts of weakly homologous sequences on distance tree construction. The sampling method makes sequence analysis more sensitive to functional and structural importance of individual residues by avoiding effects of the overrepresentation of highly homologous sequences and improves computational efficiency. A carefully designed clustering method is parametrized on the target structure to detect and extend patches on protein surfaces into predicted interaction sites. Clustering takes into account residues physical-chemical properties as well as conservation. Large-scale application of JET requires the system to be adjustable for different datasets and to guarantee predictions even if the signal is low. Flexibility was achieved by a careful treatment of the number of retrieved sequences, the amino acid distance between sequences, and the selective thresholds for cluster identification. An iterative version of JET (iJET) that guarantees finding the most likely interface residues is proposed as the appropriate tool for large-scale predictions. Tests are carried out on the Huang database of 62 heterodimer, homodimer, and transient complexes and on 265 interfaces belonging to signal transduction proteins, enzymes, inhibitors, antibodies, antigens, and others. A specific set of proteins chosen for their special functional and structural properties illustrate JET behavior on a large variety of interactions covering proteins, ligands, DNA, and RNA. JET is compared at a large scale to ET and to Consurf, Rate4Site, siteFiNDER|3D, and SCORECONS on specific structures. A significant improvement in performance and computational efficiency is shown.'),
(84109, 2009, 'plos', 'Computational modeling of the hematopoietic erythroid-myeloid switch reveals insights into cooperativity, priming, and irreversibility', 'Chickarmane, Vijay|Enver, Tariq|Peterson, Carsten', 'Division of Biology, California Institute of Technology, Pasadena, California, United States of America.|Division of Biology, California Institute of Technology, Pasadena, California, United States of America.|Division of Biology, California Institute of Technology, Pasadena, California, United States of America.', 'United States|United States|United States', 0, 'Animals|CCAAT-Enhancer-Binding Protein-alpha|Cell Differentiation|Cell Lineage|Erythroid Precursor Cells|Feedback, Physiological|GATA1 Transcription Factor|Gene Expression Regulation, Developmental|Gene Regulatory Networks|Hematopoiesis|Homeodomain Proteins|Humans|Models, Genetic|Nuclear Proteins|Proto-Oncogene Proteins|Systems Biology|Trans-Activators|Transcription, Genetic|Transcriptional Activation', 'Journal Article', '10.1371/journal.pcbi.1000268', '19165316', 'Hematopoietic stem cell lineage choices are decided by genetic networks that are turned ON/OFF in a switch-like manner. However, prior to lineage commitment, genes are primed at low expression levels. Understanding the underlying molecular circuitry in terms of how it governs both a primed state and, at the other extreme, a committed state is of relevance not only to hematopoiesis but also to developmental systems in general. We develop a computational model for the hematopoietic erythroid-myeloid lineage decision, which is determined by a genetic switch involving the genes PU.1 and GATA-1. Dynamical models based upon known interactions between these master genes, such as mutual antagonism and autoregulation, fail to make the system bistable, a desired feature for robust lineage determination. We therefore suggest a new mechanism involving a cofactor that is regulated as well as recruited by one of the master genes to bind to the antagonistic partner that is necessary for bistability and hence switch-like behavior. An interesting fallout from this architecture is that suppression of the cofactor through external means can lead to a loss of cooperativity, and hence to a primed state for PU.1 and GATA-1. The PU.1-GATA-1 switch also interacts with another mutually antagonistic pair, C/EBPalpha-FOG-1. The latter pair inherits the state of its upstream master genes and further reinforces the decision due to several feedback loops, thereby leading to irreversible commitment. The genetic switch, which handles the erythroid-myeloid lineage decision, is an example of a network that implements both a primed and a committed state by regulating cooperativity through recruitment of cofactors. Perturbing the feedback between the master regulators and downstream targets suggests potential reprogramming strategies. The approach points to a framework for lineage commitment studies in general and could aid the search for lineage-determining genes.'),
(84110, 2009, 'plos', 'A primer on regression methods for decoding cis-regulatory logic', 'Das, Debopriya|Pellegrini, Matteo|Gray, Joe W', 'Life Sciences Division, Ernest O Lawrence Berkeley National Laboratory, Berkeley, California, United States of America. ddas@potternexus.lbl.gov|Life Sciences Division, Ernest O Lawrence Berkeley National Laboratory, Berkeley, California, United States of America. ddas@potternexus.lbl.gov|Life Sciences Division, Ernest O Lawrence Berkeley National Laboratory, Berkeley, California, United States of America. ddas@potternexus.lbl.gov', 'United States|United States|United States', 13, 'Algorithms|Computational Biology|Gene Expression Regulation|Genomics|Least-Squares Analysis|Models, Genetic|Models, Statistical|Nonlinear Dynamics|Regression Analysis|Regulatory Elements, Transcriptional|Transcription Factors', 'Journal Article', '10.1371/journal.pcbi.1000269', '19180174', '-'),
(84111, 2009, 'plos', 'Microblogging the ISMB: a new approach to conference reporting', 'Saunders, Neil|Beltrão, Pedro|Jensen, Lars|Jurczak, Daniel|Krause, Roland|Kuhn, Michael|Wu, Shirley', 'School of Molecular and Microbial Sciences, University of Queensland, St Lucia, Brisbane, Queensland, Australia. n.saunders@uq.edu.au|School of Molecular and Microbial Sciences, University of Queensland, St Lucia, Brisbane, Queensland, Australia. n.saunders@uq.edu.au|School of Molecular and Microbial Sciences, University of Queensland, St Lucia, Brisbane, Queensland, Australia. n.saunders@uq.edu.au|School of Molecular and Microbial Sciences, University of Queensland, St Lucia, Brisbane, Queensland, Australia. n.saunders@uq.edu.au|School of Molecular and Microbial Sciences, University of Queensland, St Lucia, Brisbane, Queensland, Australia. n.saunders@uq.edu.au|School of Molecular and Microbial Sciences, University of Queensland, St Lucia, Brisbane, Queensland, Australia. n.saunders@uq.edu.au|School of Molecular and Microbial Sciences, University of Queensland, St Lucia, Brisbane, Queensland, Australia. n.saunders@uq.edu.au', 'Australia|Australia|Australia|Australia|Australia|Australia|Australia', 12, 'Computational Biology|Congresses as Topic|Internet|Systems Biology', 'Journal Article', '10.1371/journal.pcbi.1000263', '19180175', '-'),
(84112, 2009, 'plos', 'A Review of 2008 for PLoS Computational Biology', 'Browne, Evie|Dickin, Rosemary|Bourne, Philip E', 'School of Molecular and Microbial Sciences, University of Queensland, St Lucia, Brisbane, Queensland, Australia. n.saunders@uq.edu.au|School of Molecular and Microbial Sciences, University of Queensland, St Lucia, Brisbane, Queensland, Australia. n.saunders@uq.edu.au|School of Molecular and Microbial Sciences, University of Queensland, St Lucia, Brisbane, Queensland, Australia. n.saunders@uq.edu.au', 'Australia|Australia|Australia', 0, 'Computational Biology|Editorial Policies|Peer Review, Research|Periodicals as Topic', 'Editorial', '10.1371/journal.pcbi.1000275', '19180176', '-'),
(84113, 2009, 'plos', 'A factor graph nested effects model to identify networks from genetic perturbations', 'Vaske, Charles J|House, Carrie|Luu, Truong|Frank, Bryan|Yeang, Chen-Hsiang|Lee, Norman H|Stuart, Joshua M', 'Biomolecular Engineering Department, University of California Santa Cruz, Santa Cruz, California, United States of America.|Biomolecular Engineering Department, University of California Santa Cruz, Santa Cruz, California, United States of America.|Biomolecular Engineering Department, University of California Santa Cruz, Santa Cruz, California, United States of America.|Biomolecular Engineering Department, University of California Santa Cruz, Santa Cruz, California, United States of America.|Biomolecular Engineering Department, University of California Santa Cruz, Santa Cruz, California, United States of America.|Biomolecular Engineering Department, University of California Santa Cruz, Santa Cruz, California, United States of America.|Biomolecular Engineering Department, University of California Santa Cruz, Santa Cruz, California, United States of America.', 'United States|United States|United States|United States|United States|United States|United States', 29, 'Algorithms|Colonic Neoplasms|Computational Biology|Computer Simulation|Data Interpretation, Statistical|Gene Expression Regulation|Gene Expression Regulation, Neoplastic|Gene Regulatory Networks|Gene Silencing|HT29 Cells|Humans|Models, Genetic|Neoplasm Invasiveness|Normal Distribution|Oligonucleotide Array Sequence Analysis|Saccharomyces cerevisiae|Signal Transduction', 'Journal Article', '10.1371/journal.pcbi.1000274', '19180177', 'Complex phenotypes such as the transformation of a normal population of cells into cancerous tissue result from a series of molecular triggers gone awry. We describe a method that searches for a genetic network consistent with expression changes observed under the knock-down of a set of genes that share a common role in the cell, such as a disease phenotype. The method extends the Nested Effects Model of Markowetz et al. (2005) by using a probabilistic factor graph to search for a network representing interactions among these silenced genes. The method also expands the network by attaching new genes at specific downstream points, providing candidates for subsequent perturbations to further characterize the pathway. We investigated an extension provided by the factor graph approach in which the model distinguishes between inhibitory and stimulatory interactions. We found that the extension yielded significant improvements in recovering the structure of simulated and Saccharomyces cerevisae networks. We applied the approach to discover a signaling network among genes involved in a human colon cancer cell invasiveness pathway. The method predicts several genes with new roles in the invasiveness process. We knocked down two genes identified by our approach and found that both knock-downs produce loss of invasive potential in a colon cancer cell line. Nested effects models may be a powerful tool for inferring regulatory connections and genes that operate in normal and disease-related processes.'),
(84114, 2009, 'plos', 'Poisson-Nernst-Planck models of nonequilibrium ion electrodiffusion through a protegrin transmembrane pore', 'Bolintineanu, Dan S|Sayyed-Ahmad, Abdallah|Davis, H Ted|Kaznessis, Yiannis N', 'Department of Chemical Engineering and Materials Science, University of Minnesota, Minneapolis, Minnesota, United States of America.|Department of Chemical Engineering and Materials Science, University of Minnesota, Minneapolis, Minnesota, United States of America.|Department of Chemical Engineering and Materials Science, University of Minnesota, Minneapolis, Minnesota, United States of America.|Department of Chemical Engineering and Materials Science, University of Minnesota, Minneapolis, Minnesota, United States of America.', 'United States|United States|United States|United States', 37, 'Algorithms|Antimicrobial Cationic Peptides|Arginine|Chlorides|Computational Biology|Computer Simulation|Diffusion|Electric Conductivity|Ions|Models, Molecular|Poisson Distribution|Potassium', 'Journal Article', '10.1371/journal.pcbi.1000277', '19180178', 'Protegrin peptides are potent antimicrobial agents believed to act against a variety of pathogens by forming nonselective transmembrane pores in the bacterial cell membrane. We have employed 3D Poisson-Nernst-Planck (PNP) calculations to determine the steady-state ion conduction characteristics of such pores at applied voltages in the range of -100 to +100 mV in 0.1 M KCl bath solutions. We have tested a variety of pore structures extracted from molecular dynamics (MD) simulations based on an experimentally proposed octomeric pore structure. The computed single-channel conductance values were in the range of 290-680 pS. Better agreement with the experimental range of 40-360 pS was obtained using structures from the last 40 ns of the MD simulation, where conductance values range from 280 to 430 pS. We observed no significant variation of the conductance with applied voltage in any of the structures that we tested, suggesting that the voltage dependence observed experimentally is a result of voltage-dependent channel formation rather than an inherent feature of the open pore structure. We have found the pore to be highly selective for anions, with anionic to cationic current ratios (I(Cl-)/I(K+)) on the order of 10(3). This is consistent with the highly cationic nature of the pore but surprisingly in disagreement with the experimental finding of only slight anionic selectivity. We have additionally tested the sensitivity of our PNP model to several parameters and found the ion diffusion coefficients to have a significant influence on conductance characteristics. The best agreement with experimental data was obtained using a diffusion coefficient for each ion set to 10% of the bulk literature value everywhere inside the channel, a scaling used by several other studies employing PNP calculations. Overall, this work presents a useful link between previous work focused on the structure of protegrin pores and experimental efforts aimed at investigating their conductance characteristics.'),
(84115, 2009, 'plos', 'Coordinated concentration changes of transcripts and metabolites in Saccharomyces cerevisiae', 'Bradley, Patrick H|Brauer, Matthew J|Rabinowitz, Joshua D|Troyanskaya, Olga G', 'Lewis-Sigler Institute for Integrative Genomics, Princeton University, Princeton, New Jersey, United States of America.|Lewis-Sigler Institute for Integrative Genomics, Princeton University, Princeton, New Jersey, United States of America.|Lewis-Sigler Institute for Integrative Genomics, Princeton University, Princeton, New Jersey, United States of America.|Lewis-Sigler Institute for Integrative Genomics, Princeton University, Princeton, New Jersey, United States of America.', 'Jersey|Jersey|Jersey|Jersey', 78, 'Algorithms|Bayes Theorem|Biosynthetic Pathways|Carbon|Chromatography, Liquid|Gene Expression Profiling|Gene Expression Regulation|Genes, Fungal|Genomics|Glycogenolysis|Glycolysis|Metabolomics|Nitrogen|Saccharomyces cerevisiae|Statistics, Nonparametric|Tandem Mass Spectrometry|Transcription, Genetic', 'Journal Article', '10.1371/journal.pcbi.1000270', '19180179', 'Metabolite concentrations can regulate gene expression, which can in turn regulate metabolic activity. The extent to which functionally related transcripts and metabolites show similar patterns of concentration changes, however, remains unestablished. We measure and analyze the metabolomic and transcriptional responses of Saccharomyces cerevisiae to carbon and nitrogen starvation. Our analysis demonstrates that transcripts and metabolites show coordinated response dynamics. Furthermore, metabolites and gene products whose concentration profiles are alike tend to participate in related biological processes. To identify specific, functionally related genes and metabolites, we develop an approach based on Bayesian integration of the joint metabolomic and transcriptomic data. This algorithm finds interactions by evaluating transcript-metabolite correlations in light of the experimental context in which they occur and the class of metabolite involved. It effectively predicts known enzymatic and regulatory relationships, including a gene-metabolite interaction central to the glycolytic-gluconeogenetic switch. This work provides quantitative evidence that functionally related metabolites and transcripts show coherent patterns of behavior on the genome scale and lays the groundwork for building gene-metabolite interaction networks directly from systems-level data.');
