Search results for "SIM"

showing 10 items of 10139 documents

SNVSniffer: an integrated caller for germline and somatic single-nucleotide and indel mutations

2016

Various approaches to calling single-nucleotide variants (SNVs) or insertion-or-deletion (indel) mutations have been developed based on next-generation sequencing (NGS). However, most of them are dedicated to a particular type of mutation, e.g. germline SNVs in normal cells, somatic SNVs in cancer/tumor cells, or indels only. In the literature, efficient and integrated callers for both germline and somatic SNVs/indels have not yet been extensively investigated. We present SNVSniffer, an efficient and integrated caller identifying both germline and somatic SNVs/indels from NGS data. In this algorithm, we propose the use of Bayesian probabilistic models to identify SNVs and investigate a mult…

0301 basic medicineSomatic cellBayesian probabilityBiologyPolymorphism Single NucleotideGermline03 medical and health sciencesGene FrequencyINDEL MutationStructural BiologyModelling and SimulationIndel callingGenetic variationHumansAlleleIndelMolecular BiologyOvarian NeoplasmsGeneticsResearchApplied MathematicsComputational BiologyHigh-Throughput Nucleotide SequencingSNP callingSomatic SNV callingCystadenocarcinoma SerousComputer Science ApplicationsGerm Cells030104 developmental biologyBayesian modelModeling and SimulationMutation (genetic algorithm)FemaleMultinomial distributionAlgorithmsBMC Systems Biology
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parSRA: A framework for the parallel execution of short read aligners on compute clusters

2018

The growth of next generation sequencing datasets poses as a challenge to the alignment of reads to reference genomes in terms of both accuracy and speed. In this work we present parSRA, a parallel framework to accelerate the execution of existing short read aligners on distributed-memory systems. parSRA can be used to parallelize a variety of short read alignment tools installed in the system without any modification to their source code. We show that our framework provides good scalability on a compute cluster for accelerating the popular BWA-MEM and Bowtie2 aligners. On average, it is able to accelerate sequence alignments on 16 64-core nodes (in total, 1024 cores) with speedup of 10.48 …

0301 basic medicineSource codeSpeedupGeneral Computer ScienceComputer sciencemedia_common.quotation_subjectParallel computingSupercomputerTheoretical Computer Science03 medical and health sciences030104 developmental biology0302 clinical medicine030220 oncology & carcinogenesisModeling and SimulationComputer clusterScalabilityFuse (electrical)Node (circuits)Partitioned global address spacemedia_commonJournal of Computational Science
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Targeting Bacterial Sortase A with Covalent Inhibitors: 27 New Starting Points for Structure-Based Hit-to-Lead Optimization.

2019

Because of its essential role as a bacterial virulence factor, enzyme sortase A (SrtA) has become an attractive target for the development of new antivirulence drugs against Gram-positive infections. Here we describe 27 compounds identified as covalent inhibitors of

0301 basic medicineStaphylococcus aureusMagnetic Resonance SpectroscopyAntivirulenceVirulence Factors030106 microbiologySmall Molecule Libraries03 medical and health sciencesMiceBacterial ProteinsCatalytic DomainDrug DiscoveryAnimalschemistry.chemical_classificationBinding SitesChemistryHit to leadFibroblastsAminoacyltransferasesAnti-Bacterial AgentsMolecular Docking SimulationCysteine Endopeptidases030104 developmental biologyInfectious DiseasesEnzymeBiochemistryCovalent bondSortase ABacterial virulenceNIH 3T3 CellsStructure basedACS infectious diseases
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Assessing statistical significance in multivariable genome wide association analysis

2016

Motivation: Although Genome Wide Association Studies (GWAS) genotype a very large number of single nucleotide polymorphisms (SNPs), the data are often analyzed one SNP at a time. The low predictive power of single SNPs, coupled with the high significance threshold needed to correct for multiple testing, greatly decreases the power of GWAS. Results: We propose a procedure in which all the SNPs are analyzed in a multiple generalized linear model, and we show its use for extremely high-dimensional datasets. Our method yields P-values for assessing significance of single SNPs or groups of SNPs while controlling for all other SNPs and the family wise error rate (FWER). Thus, our method tests whe…

0301 basic medicineStatistics and Probability1303 BiochemistryGenotypeOperations researchLibrary sciencePolymorphism Single NucleotideBiochemistryGerman03 medical and health sciences10007 Department of EconomicsPolitical scienceGenome-Wide Association Analysis1312 Molecular Biology1706 Computer Science ApplicationsCluster AnalysisHumansComputer Simulation2613 Statistics and ProbabilityMolecular BiologyEuropean researchGenetics and Population AnalysisComputational BiologyReproducibility of ResultsOriginal Paperslanguage.human_languageComputer Science Applications330 EconomicsComputational MathematicsPhenotype030104 developmental biologyComputational Theory and MathematicsLinear Modelslanguage2605 Computational MathematicsGenome-Wide Association Study1703 Computational Theory and Mathematics
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Stagewise pseudo-value regression for time-varying effects on the cumulative incidence

2015

In a competing risks setting, the cumulative incidence of an event of interest describes the absolute risk for this event as a function of time. For regression analysis, one can either choose to model all competing events by separate cause-specific hazard models or directly model the association between covariates and the cumulative incidence of one of the events. With a suitable link function, direct regression models allow for a straightforward interpretation of covariate effects on the cumulative incidence. In practice, where data can be right-censored, these regression models are implemented using a pseudo-value approach. For a grid of time points, the possibly unobserved binary event s…

0301 basic medicineStatistics and ProbabilityCarcinoma HepatocellularTime FactorsEpidemiologyComputer scienceFeature selectionBiostatistics01 natural sciences010104 statistics & probability03 medical and health sciencesRisk FactorsStatisticsCovariateEconometricsHumansComputer SimulationCumulative incidenceRegistries0101 mathematicsEvent (probability theory)Models StatisticalIncidenceLiver NeoplasmsAbsolute risk reductionRegression analysisRegression030104 developmental biologyRegression AnalysisJackknife resamplingAlgorithmsStatistics in Medicine
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Protein-protein interactions can be predicted using coiled coil co-evolution patterns

2016

AbstractProtein-protein interactions are sometimes mediated by coiled coil structures. The evolutionary conservation of interacting orthologs in different species, along with the presence or absence of coiled coils in them, may help in the prediction of interacting pairs. Here, we illustrate how the presence of coiled coils in a protein can be exploited as a potential indicator for its interaction with another protein with coiled coils. The prediction capability of our strategy improves when restricting our dataset to highly reliable, known protein-protein interactions. Our study of the co-evolution of coiled coils demonstrates that pairs of interacting proteins can be distinguished from no…

0301 basic medicineStatistics and ProbabilityComputational biologyCorrelated evolutionGeneral Biochemistry Genetics and Molecular BiologyProtein Structure SecondaryProtein–protein interactionConserved sequenceEvolution Molecular03 medical and health sciencesProtein-protein interactionModelling and SimulationImmunology and Microbiology(all)Coiled coilGeneticsCoiled coilPhysicsMedicine(all)030102 biochemistry & molecular biologyGeneral Immunology and MicrobiologyAgricultural and Biological Sciences(all)Models GeneticBiochemistry Genetics and Molecular Biology(all)Applied MathematicsA proteinProteinsGeneral Medicine030104 developmental biologyModeling and SimulationGeneral Agricultural and Biological SciencesJournal of Theoretical Biology
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Evidence for the implication of the histone code in building the genome structure

2018

International audience; Histones are punctuated with small chemical modifications that alter their interaction with DNA. One attractive hypothesis stipulates that certain combinations of these histone modifications may function, alone or together, as a part of a predictive histone code to provide ground rules for chromatin folding. We consider four features that relate histone modifications to chromatin folding: charge neutralisation, molecular specificity, robustness and evolvability. Next, we present evidence for the association among different histone modifications at various levels of chromatin organisation and show how these relationships relate to function such as transcription, repli…

0301 basic medicineStatistics and ProbabilityComputational biologyGeneral Biochemistry Genetics and Molecular BiologyHistones03 medical and health scienceschemistry.chemical_compoundTranscription (biology)AnimalsHumansHistone codeNucleosome[PHYS]Physics [physics]biologyGenome HumanApplied MathematicsRobustness (evolution)General MedicineChromatinChromatinHistone Code030104 developmental biologyHistonechemistryModeling and Simulationbiology.proteinHuman genomeDNABiosystems
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Gene-based and semantic structure of the Gene Ontology as a complex network

2012

The last decade has seen the advent and consolidation of ontology based tools for the identification and biological interpretation of classes of genes, such as the Gene Ontology. The information accumulated time-by-time and included in the GO is encoded in the definition of terms and in the setting up of semantic relations amongst terms. This approach might be usefully complemented by a bottom-up approach based on the knowledge of relationships amongst genes. To this end, we investigate the Gene Ontology from a complex network perspective. We consider the semantic network of terms naturally associated with the semantic relationships provided by the Gene Ontology consortium and a gene-based …

0301 basic medicineStatistics and ProbabilityFOS: Computer and information sciencesPhysics - Physics and SocietyComplex systemComputer scienceMolecular Networks (q-bio.MN)Complex systemFOS: Physical sciencesNetworkCondensed Matter PhysicPhysics and Society (physics.soc-ph)computer.software_genreQuantitative Biology - Quantitative MethodsStatistics - ApplicationsGeneSemantic network03 medical and health sciencesSemantic similarityQuantitative Biology - Molecular NetworksApplications (stat.AP)GeneQuantitative Methods (q-bio.QM)Community detectionGene ontologybusiness.industryOntologyOntology-based data integrationComplex networkCondensed Matter PhysicsBipartite system030104 developmental biologyBipartite system; Community detection; Complex systems; Genes; Networks; Ontology; Condensed Matter Physics; Statistics and ProbabilityFOS: Biological sciencesOntologyWeighted networkData miningArtificial intelligenceComputingMethodologies_GENERALbusinesscomputerNatural language processing
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L1-Penalized Censored Gaussian Graphical Model

2018

Graphical lasso is one of the most used estimators for inferring genetic networks. Despite its diffusion, there are several fields in applied research where the limits of detection of modern measurement technologies make the use of this estimator theoretically unfounded, even when the assumption of a multivariate Gaussian distribution is satisfied. Typical examples are data generated by polymerase chain reactions and flow cytometer. The combination of censoring and high-dimensionality make inference of the underlying genetic networks from these data very challenging. In this article, we propose an $\ell_1$-penalized Gaussian graphical model for censored data and derive two EM-like algorithm…

0301 basic medicineStatistics and ProbabilityFOS: Computer and information sciencesgraphical lassoComputer scienceGaussianNormal DistributionInferenceMultivariate normal distribution01 natural sciencesMethodology (stat.ME)010104 statistics & probability03 medical and health sciencessymbols.namesakeGraphical LassoExpectation–maximization algorithmHumansComputer SimulationGene Regulatory NetworksGraphical model0101 mathematicsStatistics - MethodologyEstimation theoryReverse Transcriptase Polymerase Chain ReactionEstimatorexpectation-maximization algorithmGeneral MedicineCensoring (statistics)High-dimensional datahigh-dimensional dataGaussian graphical model030104 developmental biologysymbolscensored dataCensored dataExpectation-Maximization algorithmStatistics Probability and UncertaintySettore SECS-S/01 - StatisticaAlgorithmAlgorithms
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Model selection for factorial Gaussian graphical models with an application to dynamic regulatory networks.

2016

Abstract Factorial Gaussian graphical Models (fGGMs) have recently been proposed for inferring dynamic gene regulatory networks from genomic high-throughput data. In the search for true regulatory relationships amongst the vast space of possible networks, these models allow the imposition of certain restrictions on the dynamic nature of these relationships, such as Markov dependencies of low order – some entries of the precision matrix are a priori zeros – or equal dependency strengths across time lags – some entries of the precision matrix are assumed to be equal. The precision matrix is then estimated by l 1-penalized maximum likelihood, imposing a further constraint on the absolute value…

0301 basic medicineStatistics and ProbabilityFactorialDependency (UML)Computer scienceGaussianNormal Distributionpenalized inferencesparse networkscomputer.software_genreMachine learning01 natural sciencesNormal distribution010104 statistics & probability03 medical and health sciencessymbols.namesakeSparse networksGeneticsComputer SimulationGene Regulatory NetworksGraphical model0101 mathematicsgene-regulatory systemMolecular BiologyProbabilityMarkov chainModels GeneticPenalized inferencebusiness.industryModel selectiongraphical modelGene-regulatory systemsComputational Mathematics030104 developmental biologysymbolsA priori and a posterioriData miningArtificial intelligenceGraphical modelsSettore SECS-S/01 - StatisticabusinesscomputerNeisseriaAlgorithmsStatistical applications in genetics and molecular biology
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