Relevant loci for milk production in dairy cattle, obtained by machine learning algorithms

Poster

Detalles Bibliográficos
Autores principales: Raschia, Maria Agustina, Ríos, Pablo J., Maizon, Daniel Omar, Demitrio, Daniel Arturo, Poli, Mario Andres
Formato: info:ar-repo/semantics/documento de conferencia
Lenguaje:Inglés
Publicado: Network of Women in Bioinformatics and Data Science 2022
Materias:
Acceso en línea:http://hdl.handle.net/20.500.12123/11715
_version_ 1855036623794733056
author Raschia, Maria Agustina
Ríos, Pablo J.
Maizon, Daniel Omar
Demitrio, Daniel Arturo
Poli, Mario Andres
author_browse Demitrio, Daniel Arturo
Maizon, Daniel Omar
Poli, Mario Andres
Raschia, Maria Agustina
Ríos, Pablo J.
author_facet Raschia, Maria Agustina
Ríos, Pablo J.
Maizon, Daniel Omar
Demitrio, Daniel Arturo
Poli, Mario Andres
author_sort Raschia, Maria Agustina
collection INTA Digital
description Poster
format info:ar-repo/semantics/documento de conferencia
id INTA11715
institution Instituto Nacional de Tecnología Agropecuaria (INTA -Argentina)
language Inglés
publishDate 2022
publishDateRange 2022
publishDateSort 2022
publisher Network of Women in Bioinformatics and Data Science
publisherStr Network of Women in Bioinformatics and Data Science
record_format dspace
spelling INTA117152022-04-25T10:31:08Z Relevant loci for milk production in dairy cattle, obtained by machine learning algorithms Raschia, Maria Agustina Ríos, Pablo J. Maizon, Daniel Omar Demitrio, Daniel Arturo Poli, Mario Andres Milk Production Dairy Cattle Machine Learning Algorithms Single Nucleotide Polymorphism Producción Lechera Ganado de Leche Aprendizaje Electrónico Algoritmos Polimorfismo de un Solo Nucleótido Poster 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 interest. Instituto de Genética Fil: Raschia, Maria Agustina. Instituto Nacional de Tecnología Agropecuaria (INTA). Instituto de Genética; Argentina Fil: Raschia, Maria Agustina. Universidad Nacional de La Plata. Facultad de Ciencias Médicas; Argentina Fil: Ríos, Pablo J. Universidad de Buenos Aires; Argentina Fil: Ríos, Pablo J. Universidad Nacional de La Plata. Facultad de Ciencias Exactas; Argentina Fil: Maizon, Daniel Omar. Instituto Nacional de Tecnología Agropecuaria (INTA). Estación Experimental Agropecuaria Anguil; Argentina Fil: Maizon, Daniel Omar. Universidad Nacional de La Pampa. Facultad de Agronomía; Argentina Fil: 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; Argentina Fil: Demitrio, Daniel Arturo. Universidad Nacional de La Plata. Facultad de Ciencias Exactas; Argentina Fil: Poli, Mario Andres. Instituto Nacional de Tecnología Agropecuaria (INTA). Instituto de Genética; Argentina Fil: Poli, Mario Andres. Universidad del Salvador. Facultad de Ciencias Agrarias y Veterinaria; Argentina 2022-04-25T10:22:28Z 2022-04-25T10:22:28Z 2021-09 info:ar-repo/semantics/documento de conferencia info:eu-repo/semantics/conferenceObject info:eu-repo/semantics/acceptedVersion http://hdl.handle.net/20.500.12123/11715 eng info: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. info:eu-repograntAgreement/INTA/2019-PT-E6-I513-001/2019-PT-E6-I513-001/AR./Plataforma de mejoramiento animal info:eu-repograntAgreement/INTA/2019-PT-E9-I180-001/2019-PT-E9-I180-001/AR./TICs y gestión de Big Data info:eu-repo/semantics/openAccess http://creativecommons.org/licenses/by-nc-sa/4.0/ Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International (CC BY-NC-SA 4.0) application/pdf Network of Women in Bioinformatics and Data Science 2nd Women in Bioinformatics & Data Science Latin America Conference, 22 al 24 de septiembre de 2021 (virtual)
spellingShingle Milk Production
Dairy Cattle
Machine Learning
Algorithms
Single Nucleotide Polymorphism
Producción Lechera
Ganado de Leche
Aprendizaje Electrónico
Algoritmos
Polimorfismo de un Solo Nucleótido
Raschia, Maria Agustina
Ríos, Pablo J.
Maizon, Daniel Omar
Demitrio, Daniel Arturo
Poli, Mario Andres
Relevant loci for milk production in dairy cattle, obtained by machine learning algorithms
title Relevant loci for milk production in dairy cattle, obtained by machine learning algorithms
title_full Relevant loci for milk production in dairy cattle, obtained by machine learning algorithms
title_fullStr Relevant loci for milk production in dairy cattle, obtained by machine learning algorithms
title_full_unstemmed Relevant loci for milk production in dairy cattle, obtained by machine learning algorithms
title_short Relevant loci for milk production in dairy cattle, obtained by machine learning algorithms
title_sort relevant loci for milk production in dairy cattle obtained by machine learning algorithms
topic Milk Production
Dairy Cattle
Machine Learning
Algorithms
Single Nucleotide Polymorphism
Producción Lechera
Ganado de Leche
Aprendizaje Electrónico
Algoritmos
Polimorfismo de un Solo Nucleótido
url http://hdl.handle.net/20.500.12123/11715
work_keys_str_mv AT raschiamariaagustina relevantlociformilkproductionindairycattleobtainedbymachinelearningalgorithms
AT riospabloj relevantlociformilkproductionindairycattleobtainedbymachinelearningalgorithms
AT maizondanielomar relevantlociformilkproductionindairycattleobtainedbymachinelearningalgorithms
AT demitriodanielarturo relevantlociformilkproductionindairycattleobtainedbymachinelearningalgorithms
AT polimarioandres relevantlociformilkproductionindairycattleobtainedbymachinelearningalgorithms