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http://hdl.handle.net/10662/19309
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Campo DC | Valor | idioma |
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dc.contributor.author | González Velasco, Miguel | - |
dc.contributor.author | Gutiérrez Pérez, Cristina | - |
dc.contributor.author | Martínez Quintana, Rodrigo | - |
dc.date.accessioned | 2024-01-25T09:07:38Z | - |
dc.date.available | 2024-01-25T09:07:38Z | - |
dc.date.issued | 2021-04-01 | - |
dc.identifier.uri | http://hdl.handle.net/10662/19309 | - |
dc.description | This 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 license | es_ES |
dc.description.abstract | A 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.sponsorship | This 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.extent | 19 | es_ES |
dc.format.mimetype | application/pdf | en |
dc.language.iso | eng | es_ES |
dc.publisher | IEEE | es_ES |
dc.relation.replaces | https://arxiv.org/pdf/1801.09064.pdf | es_ES |
dc.rights | Attribution-NonCommercial 4.0 International | * |
dc.rights.uri | http://creativecommons.org/licenses/by-nc/4.0/ | * |
dc.subject | Y-linked genes | es_ES |
dc.subject | two-sex branching processes | es_ES |
dc.subject | Parametric Bayesian inference | es_ES |
dc.subject | approximate Bayesian computation | es_ES |
dc.subject | Genes ligados al Y | es_ES |
dc.subject | Inferencia bayesiana paramétrica | es_ES |
dc.subject | Procesos de ramificación de dos sexos | es_ES |
dc.subject | Cálculo bayesiano aproximado | es_ES |
dc.title | Bayesian Inference in Y-Linked Two-Sex Branching Processes with Mutations: ABC Approach | es_ES |
dc.type | article | es_ES |
dc.description.version | peerReviewed | es_ES |
europeana.type | TEXT | en_US |
dc.relation.projectID | This 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.accessRights | openAccess | es_ES |
dc.subject.unesco | 1209.13 Técnicas de Inferencia Estadística | es_ES |
dc.subject.unesco | 1208.08 Procesos Estocásticos | es_ES |
europeana.dataProvider | Universidad de Extremadura. España | es_ES |
dc.identifier.bibliographicCitation | Gonzalez, 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.2019.2921308 | es_ES |
dc.type.version | submittedVersion | es_ES |
dc.contributor.affiliation | Universidad de Extremadura. Departamento de Matemáticas | es_ES |
dc.relation.publisherversion | https://ieeexplore.ieee.org/document/8732353 | es_ES |
dc.identifier.doi | 10.1109/TCBB.2019.2921308 | - |
dc.identifier.publicationtitle | IEEE/ACM Transactions on Computational Biology and Bioinformatics | es_ES |
dc.identifier.publicationissue | 18 | es_ES |
dc.identifier.publicationfirstpage | 525 | es_ES |
dc.identifier.publicationlastpage | 538 | es_ES |
dc.identifier.publicationvolume | 2 | es_ES |
dc.identifier.orcid | 0000-0001-7481-6561 | es_ES |
dc.identifier.orcid | 0000-0003-1348-748X | es_ES |
dc.identifier.orcid | 0000-0003-1533-038X | es_ES |
Colección: | DMATE - Artículos |
Archivos
Archivo | Descripción | Tamaño | Formato | |
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1801.09064.pdf | 611,04 kB | Adobe PDF | Descargar |
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