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Abstract
Background: Extensive genetic research focused on identifyng associations between single nucleotide polymorphism (SNP) markers located all over the genome and milk traits were conducted for different dairy cattle breeds. Most published genome-wide association studies (GWAS) were performed fitting linear, multivariate and Bayesian linear mixed models. Machine learning (ML) methods have been shown to be efficient in identifying SNP underlying a trait of [ver mas...]
dc.contributor.authorRaschia, Maria Agustina
dc.contributor.authorRíos, Pablo J.
dc.contributor.authorMaizon, Daniel Omar
dc.contributor.authorDemitrio, Daniel Arturo
dc.contributor.authorPoli, Mario Andres
dc.date.accessioned2022-04-25T10:22:28Z
dc.date.available2022-04-25T10:22:28Z
dc.date.issued2021-09
dc.identifier.urihttp://hdl.handle.net/20.500.12123/11715
dc.descriptionPoster
dc.description.abstractBackground: Extensive genetic research focused on identifyng associations between single nucleotide polymorphism (SNP) markers located all over the genome and milk traits were conducted for different dairy cattle breeds. Most published genome-wide association studies (GWAS) were performed fitting linear, multivariate and Bayesian linear mixed models. Machine learning (ML) methods have been shown to be efficient in identifying SNP underlying a trait of interest.eng
dc.formatapplication/pdfes_AR
dc.language.isoenges_AR
dc.publisherNetwork of Women in Bioinformatics and Data Science
dc.relationinfo:eu-repograntAgreement/INTA/2019-PE-E6-I145-001/2019-PE-E6-I145-001/AR./Mejora genética objetiva para aumentar la eficiencia de los sistemas de producción animal.es_AR
dc.relationinfo:eu-repograntAgreement/INTA/2019-PT-E6-I513-001/2019-PT-E6-I513-001/AR./Plataforma de mejoramiento animales_AR
dc.relationinfo:eu-repograntAgreement/INTA/2019-PT-E9-I180-001/2019-PT-E9-I180-001/AR./TICs y gestión de Big Dataes_AR
dc.rightsinfo:eu-repo/semantics/openAccesses_AR
dc.rights.urihttp://creativecommons.org/licenses/by-nc-sa/4.0/
dc.source2nd Women in Bioinformatics & Data Science Latin America Conference, 22 al 24 de septiembre de 2021 (virtual)es_AR
dc.subjectMilk Productioneng
dc.subjectProducción Lecheraes_AR
dc.subjectDairy Cattleeng
dc.subjectGanado de Lechees_AR
dc.subjectMachine Learningeng
dc.subjectAprendizaje Electrónicoes_AR
dc.subjectAlgorithmseng
dc.subjectAlgoritmoses_AR
dc.subjectSingle Nucleotide Polymorphismeng
dc.subjectPolimorfismo de un Solo Nucleótidoes_AR
dc.titleRelevant loci for milk production in dairy cattle, obtained by machine learning algorithmses_AR
dc.typeinfo:ar-repo/semantics/documento de conferenciaes_AR
dc.typeinfo:eu-repo/semantics/conferenceObjectes_AR
dc.typeinfo:eu-repo/semantics/acceptedVersiones_AR
dc.rights.licenseCreative Commons Attribution-NonCommercial-ShareAlike 4.0 International (CC BY-NC-SA 4.0)
dc.description.origenInstituto de Genéticaes_AR
dc.description.filFil: Raschia, Maria Agustina. Instituto Nacional de Tecnología Agropecuaria (INTA). Instituto de Genética; Argentinaes_AR
dc.description.filFil: Raschia, Maria Agustina. Universidad Nacional de La Plata. Facultad de Ciencias Médicas; Argentinaes_AR
dc.description.filFil: Ríos, Pablo J. Universidad de Buenos Aires; Argentinaes_AR
dc.description.filFil: Ríos, Pablo J. Universidad Nacional de La Plata. Facultad de Ciencias Exactas; Argentinaes_AR
dc.description.filFil: Maizon, Daniel Omar. Instituto Nacional de Tecnología Agropecuaria (INTA). Estación Experimental Agropecuaria Anguil; Argentinaes_AR
dc.description.filFil: Maizon, Daniel Omar. Universidad Nacional de La Pampa. Facultad de Agronomía; Argentinaes_AR
dc.description.filFil: Demitrio, Daniel Arturo. Instituto Nacional de Tecnología Agropecuaria (INTA). Dirección General de Sistemas de Información, Comunicación y Procesos. Gerencia de Informática y Gestión de la Información; Argentinaes_AR
dc.description.filFil: Demitrio, Daniel Arturo. Universidad Nacional de La Plata. Facultad de Ciencias Exactas; Argentinaes_AR
dc.description.filFil: Poli, Mario Andres. Instituto Nacional de Tecnología Agropecuaria (INTA). Instituto de Genética; Argentinaes_AR
dc.description.filFil: Poli, Mario Andres. Universidad del Salvador. Facultad de Ciencias Agrarias y Veterinaria; Argentinaes_AR
dc.subtypeponencia


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