Identificador persistente para citar o vincular este elemento: http://hdl.handle.net/10662/19309
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dc.contributor.authorGonzález Velasco, Miguel-
dc.contributor.authorGutiérrez Pérez, Cristina-
dc.contributor.authorMartínez Quintana, Rodrigo-
dc.date.accessioned2024-01-25T09:07:38Z-
dc.date.available2024-01-25T09:07:38Z-
dc.date.issued2021-04-01-
dc.identifier.urihttp://hdl.handle.net/10662/19309-
dc.descriptionThis is a preprint version localated at https://arxiv.org/pdf/1801.09064.pdf of an article published by IEEE in IEEE/ACM Transactions on Computational Biology and Bioinformatics on 1 April 2021, available at: https://doi.org/10.1109/TCBB.2019.2921308 It is deposited under the terms of the Creative Common BY-NC licensees_ES
dc.description.abstractA Y-linked two-sex branching process with mutations and blind choice of males is a suitable model for analyzing the evolution of the number of carriers of an allele and its mutations of a Y-linked gene. Considering a two-sex monogamous population, in this model each female chooses her partner from among the male population without caring about his type (i.e., the allele he carries). In this work, we deal with the problem of estimating the main parameters of such model developing the Bayesian inference in a parametric framework. Firstly, we consider, as sample scheme, the observation of the total number of females and males up to some generation as well as the number of males of each genotype at last generation. Later, we introduce the information of the mutated males only in the last generation obtaining in this way a second sample scheme. For both samples, we apply the Approximate Bayesian Computation (ABC) methodology to approximate the posterior distributions of the main parameters of this model. The accuracy of the procedure based on these samples is illustrated and discussed by way of simulated examples.es_ES
dc.description.sponsorshipThis research was supported by Grant MTM2015-70522-P (MINECO/FEDER, UE) and Grant IB16- 103 (Junta de Extremadura / Fondo Europeo de Desarrollo Regional, UE).es_ES
dc.format.extent19es_ES
dc.format.mimetypeapplication/pdfen
dc.language.isoenges_ES
dc.publisherIEEEes_ES
dc.relation.replaceshttps://arxiv.org/pdf/1801.09064.pdfes_ES
dc.rightsAttribution-NonCommercial 4.0 International*
dc.rights.urihttp://creativecommons.org/licenses/by-nc/4.0/*
dc.subjectY-linked geneses_ES
dc.subjecttwo-sex branching processeses_ES
dc.subjectParametric Bayesian inferencees_ES
dc.subjectapproximate Bayesian computationes_ES
dc.subjectGenes ligados al Yes_ES
dc.subjectInferencia bayesiana paramétricaes_ES
dc.subjectProcesos de ramificación de dos sexoses_ES
dc.subjectCálculo bayesiano aproximadoes_ES
dc.titleBayesian Inference in Y-Linked Two-Sex Branching Processes with Mutations: ABC Approaches_ES
dc.typearticlees_ES
dc.description.versionpeerReviewedes_ES
europeana.typeTEXTen_US
dc.relation.projectIDThis research was supported by Grant number MTM2015- 70522-P (MINECO/FEDER, UE) and Grant IB16103 (Junta de Extremadura / Fondo Europeo de Desarrollo Regional, UE).es_ES
dc.rights.accessRightsopenAccesses_ES
dc.subject.unesco1209.13 Técnicas de Inferencia Estadísticaes_ES
dc.subject.unesco1208.08 Procesos Estocásticoses_ES
europeana.dataProviderUniversidad de Extremadura. Españaes_ES
dc.identifier.bibliographicCitationGonzalez, M., Gutierrez, C., & Martinez, R. (2021). Bayesian Inference in Y-Linked Two-Sex Branching Processes with Mutations: ABC Approach. IEEE/ACM transactions on computational biology and bioinformatics, 18(2), 525–538. https://doi.org/10.1109/TCBB.2019.2921308es_ES
dc.type.versionsubmittedVersiones_ES
dc.contributor.affiliationUniversidad de Extremadura. Departamento de Matemáticases_ES
dc.relation.publisherversionhttps://ieeexplore.ieee.org/document/8732353es_ES
dc.identifier.doi10.1109/TCBB.2019.2921308-
dc.identifier.publicationtitleIEEE/ACM Transactions on Computational Biology and Bioinformaticses_ES
dc.identifier.publicationissue18es_ES
dc.identifier.publicationfirstpage525es_ES
dc.identifier.publicationlastpage538es_ES
dc.identifier.publicationvolume2es_ES
dc.identifier.orcid0000-0001-7481-6561es_ES
dc.identifier.orcid0000-0003-1348-748Xes_ES
dc.identifier.orcid0000-0003-1533-038Xes_ES
Colección:DMATE - Artículos

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