Search results for "Bayesian probability"

showing 10 items of 217 documents

Dealing with physical barriers in bottlenose dolphin (Tursiops truncatus) distribution

2019

Abstract Worldwide, cetacean species have started to be protected, but they are still very vulnerable to accidental damage from an expanding range of human activities at sea. To properly manage these potential threats we need a detailed understanding of the seasonal distributions of these highly mobile populations. To achieve this goal, a growing effort has been underway to develop species distribution models (SDMs) that correctly describe and predict preferred species areas. However, accuracy is not always easy to achieve when physical barriers, such as islands, are present. Indeed, SDMs assume, if only implicitly, that the spatial effect is stationary, and that correlation is only depende…

0106 biological sciencesRange (biology)Bayesian probabilitySpecies distributionDistribution (economics)Sede Central IEO010603 evolutionary biology01 natural sciencesINLAPesqueríasArchipelago de La MaddalenaSPDEgeographyCetaceansgeography.geographical_feature_categorybiologybusiness.industry010604 marine biology & hydrobiologyEcological ModelingEnvironmental resource managementBottlenose dolphinbiology.organism_classificationPhysical BarrierHabitatArchipelagoHierarchical Bayesian spatial modelsbusinessEcological Modelling
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Bayesian Immature Survival Analysis of the Largest Colony of Common Murre (Uria aalge) in the Baltic Sea

2019

In long-lived species, such as seabirds, immature survival is the most important life history parameter after adult survival. The assessment of immature survival has often been difficult due to extended periods in which young birds remain unobservable at sea. This study presents results on survival of immature Common Murre (Uria aalge) obtained from an extensive mark-recapture study of a large colony at Stora Karlso in the Baltic Sea, Sweden. This colony, in contrast with other colonies, has the unique feature that many 1-year-old birds return to the colony (12%). Between 2006 and 2016, 28,930 chicks were marked at fledging, of which 5,493 individuals were later resighted in the colony. Ann…

0106 biological sciencesYounger ageBayesian probabilityFledgeZoologyBiologybiology.organism_classification010603 evolutionary biology01 natural sciences010605 ornithologyBaltic seaSurvival probabilityUria aalgeAnimal Science and ZoologyLife historySurvival analysisWaterbirds
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Fishery-dependent and -independent data lead to consistent estimations of essential habitats

2016

AbstractSpecies mapping is an essential tool for conservation programmes as it provides clear pictures of the distribution of marine resources. However, in fishery ecology, the amount of objective scientific information is limited and data may not always be directly comparable. Information about the distribution of marine species can be derived from two main sources: fishery-independent data (scientific surveys at sea) and fishery-dependent data (collection and sampling by observers in commercial vessels). The aim of this paper is to compare whether these two different sources produce similar, complementary, or different results. We compare them in the specific context of identifying the Es…

0106 biological scienceshttp://aims.fao.org/aos/agrovoc/c_28840Biodiversité et Ecologiehabitatmodélisation spatialehttp://aims.fao.org/aos/agrovoc/c_38371OceanographyGaleus melastomus01 natural sciencesRessource halieutiquehttp://aims.fao.org/aos/agrovoc/c_38127Scyliorhinus caniculamodèle hiérarchiqueSpatial statisticsEcologymodèle de distributionSampling (statistics)Contrast (statistics)Cross-validationModélisation et simulationGeographyHabitatGestion des pêchesModeling and Simulationhttp://aims.fao.org/aos/agrovoc/c_10566http://aims.fao.org/aos/agrovoc/c_3456http://aims.fao.org/aos/agrovoc/c_38117survey designMarine conservationSpecies Distribution ModelsEcology (disciplines)Bayesian probabilityEtmopterus spinaxenquête statistiqueDonnée sur les pêchesmodèle spatiotemporelSede Central IEOContext (language use)Aquatic ScienceDistribution des populationsBayesian hierarchical models010603 evolutionary biologyhttp://aims.fao.org/aos/agrovoc/c_24026elasmobranchsBiodiversity and Ecologyélasmobrancheétude comparativeBayesian hierarchical models;Cross-validation;Species Distribution Models;Spatial statistics;INLA;elasmobranchs ; survey designINLA14. Life underwaterspecies distribution modelsEcology Evolution Behavior and Systematicshttp://aims.fao.org/aos/agrovoc/c_6113collecte des donnéesÉcologie marinehttp://aims.fao.org/aos/agrovoc/c_29788http://aims.fao.org/aos/agrovoc/c_4609010604 marine biology & hydrobiologyGestion et conservation des pêchescross validation[INFO.INFO-MO]Computer Science [cs]/Modeling and Simulationmodèle bayésienFisheryM01 - Pêche et aquaculture - Considérations généraleshttp://aims.fao.org/aos/agrovoc/c_2a75d27eThéorie bayésienneM40 - Écologie aquatiqueSpatial ecologyhttp://aims.fao.org/aos/agrovoc/c_2942[SDE.BE]Environmental Sciences/Biodiversity and Ecologyvalidation croiséeElasmobranchii
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VARIABLE SELECTION FOR NOISY DATA APPLIED IN PROTEOMICS

2014

International audience; The paper proposes a variable selection method for pro-teomics. It aims at selecting, among a set of proteins, those (named biomarkers) which enable to discriminate between two groups of individuals (healthy and pathological). To this end, data is available for a cohort of individuals: the biological state and a measurement of concentrations for a list of proteins. The proposed approach is based on a Bayesian hierarchical model for the dependencies between biological and instrumental variables. The optimal selection function minimizes the Bayesian risk, that is to say the selected set of variables maximizes the posterior probability. The two main contributions are: (…

0209 industrial biotechnologybusiness.industryComputer scienceInstrumental variablePosterior probabilityBayesian probabilityPattern recognitionFeature selection02 engineering and technology[ SPI.SIGNAL ] Engineering Sciences [physics]/Signal and Image processingLogistic regression01 natural sciences010104 statistics & probability020901 industrial engineering & automationCohortProbability distributionBayesian hierarchical modelingArtificial intelligence0101 mathematicsbusiness[SPI.SIGNAL]Engineering Sciences [physics]/Signal and Image processingSelection (genetic algorithm)[SPI.SIGNAL] Engineering Sciences [physics]/Signal and Image processing
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Genome-scale analysis of evolutionary rate and selection in a fast-expanding Spanish cluster of HIV-1 subtype F1.

2018

Abstract This work is aimed at assessing the presence of positive selection and/or shifts of the evolutionary rate in a fast-expanding HIV-1 subtype F1 transmission cluster affecting men who have sex with men in Spain. We applied Bayesian coalescent phylogenetics and selection analyses to 23 full-coding region sequences from patients belonging to that cluster, along with other 19 F1 epidemiologically-unrelated sequences. A shift in the overall evolutionary rate of the virus, explained by positively selected sites in the cluster, was detected. We also found one substitution in Nef (H89F) that was specific to the cluster and experienced positive selection. These results suggest that fast tran…

0301 basic medicineMicrobiology (medical)GenotypeBayesian probabilityGenome scaleEpitopes T-LymphocyteHIV InfectionsGenome ViralBiologyDisease clusterMicrobiologyArticlelaw.inventionMen who have sex with menCoalescent theoryEvolution MolecularSubtype F103 medical and health sciencesSex FactorslawPhylogeneticsDatabases GeneticGeneticsHumansSelection GeneticSelectionMolecular BiologyAntigens ViralEcology Evolution Behavior and SystematicsSelection (genetic algorithm)PhylogenyRecombination GeneticGenomicsMen who have sex with men030104 developmental biologyInfectious DiseasesTransmission (mechanics)Evolutionary biologySpainHIV-1Transmission clusterInfection, genetics and evolution : journal of molecular epidemiology and evolutionary genetics in infectious diseases
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The best strategy for RAS wild-type metastatic colorectal cancer patients in first-line treatment: A classic and Bayesian meta-analysis

2018

Background: At present, there is uncertainty on the best systemic treatment in first-line setting for RAS wild-type (WT) metastatic colorectal cancer (mCRC) patients. Indeed, several chemotherapy and biologics combinations showed an improvement on survival. We performed a systematic review with a pair-wise and bayesan meta-analysis to rank the best strategy for these patients. Methods: A systematic literature search through March 2017 was performed to evaluate the association between several treatment combinations and overall survival (OS), progression-free survival (PFS), overall response rate (ORR) and toxicity rate (TR) in RAS WT mCRC patients. Data were extracted from studies and pooled…

0301 basic medicineOncologymedicine.medical_specialtyColorectal cancermedicine.medical_treatmentBayesian probabilitySidednessDisease-Free Survival03 medical and health sciences0302 clinical medicineInternal medicineAntineoplastic Combined Chemotherapy ProtocolsmedicineHumansIn patientMeta-analysiSystemic chemotherapyNeoplasm MetastasisRAS wild-typeChemotherapyVbusiness.industryMetastatic colorectal cancerWild typeBayes TheoremHematologymedicine.diseaseNeoadjuvant TherapyFirst line treatmentMeta-analysisSafety profileGenes ras030104 developmental biologyOncology030220 oncology & carcinogenesisMeta-analysisSystemic chemotherapy.Colorectal Neoplasmsbusiness
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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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Two-Stage Bayesian Approach for GWAS With Known Genealogy

2019

Genome-wide association studies (GWAS) aim to assess relationships between single nucleotide polymorphisms (SNPs) and diseases. They are one of the most popular problems in genetics, and have some peculiarities given the large number of SNPs compared to the number of subjects in the study. Individuals might not be independent, especially in animal breeding studies or genetic diseases in isolated populations with highly inbred individuals. We propose a family-based GWAS model in a two-stage approach comprising a dimension reduction and a subsequent model selection. The first stage, in which the genetic relatedness between the subjects is taken into account, selects the promising SNPs. The se…

0301 basic medicineStatistics and ProbabilityBayesian probabilityPopulationSingle-nucleotide polymorphismGenome-wide association studyComputational biologyEstadísticaBiologyKinship coefficientModel selection01 natural sciencesBeta-thalassemia010104 statistics & probability03 medical and health sciencesBeta-thalassemia disorderModelsRobust prior distributionRegularizationDiscrete Mathematics and Combinatorics0101 mathematicsStage (cooking)Genetic associationGenome-wide associationModel selectionVariable-selectionProbability and statisticsBayes factorRegressionBayes factor030104 developmental biologyPhenotypeStatistics Probability and UncertaintyGaussian Markov random field
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Prioritizing covariates in the planning of future studies in the meta-analytic framework

2016

Science can be seen as a sequential process where each new study augments evidence to the existing knowledge. To have the best prospects to make an impact in this process, a new study should be designed optimally taking into account the previous studies and other prior information. We propose a formal approach for the covariate prioritization, i.e., the decision about the covariates to be measured in a new study. The decision criteria can be based on conditional power, change of the p-value, change in lower confidence limit, Kullback-Leibler divergence, Bayes factors, Bayesian false discovery rate or difference between prior and posterior expectation. The criteria can be also used for decis…

0301 basic medicineStatistics and ProbabilityFalse discovery rateComputer scienceBayesian probabilityBayes factorGeneral MedicineMultiple-criteria decision analysis01 natural sciencesConfidence interval010104 statistics & probability03 medical and health sciences030104 developmental biologySample size determinationCovariateEconometrics0101 mathematicsStatistics Probability and UncertaintyDivergence (statistics)Biometrical Journal
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Kinematic Sub-Populations in Bull Spermatozoa: A Comparison of Classical and Bayesian Approaches

2020

The ejaculate is heterogenous and sperm sub-populations with different kinematic patterns can be identified in various species. Nevertheless, although these sub-populations are statistically well defined, the statistical differences are not always relevant. The aim of the present study was to characterize kinematic sub-populations in sperm from two bovine species, and diluted with different commercial extenders, and to determine the statistical relevance of sub-populations through Bayesian analysis. Semen from 10 bulls was evaluated after thawing. An ISAS&reg

0301 basic medicineendocrine systemMultivariate statisticsKinematicsCASABayesian probabilitySemenKinematicsBiologyArticleGeneral Biochemistry Genetics and Molecular Biologylaw.invention03 medical and health sciences0302 clinical medicinelawStatisticsbulllcsh:QH301-705.5030219 obstetrics & reproductive medicineGeneral Immunology and MicrobiologySub populationsurogenital systemExtenderMotilitySpermSpermatozoaBulls030104 developmental biologylcsh:Biology (General)ClusterPrincipal component analysisGeneral Agricultural and Biological Sciences
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