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Genomic Prediction Based on SNP Functional Annotation Using Imputed Whole-Genome Sequence Data in Korean Hanwoo Cattle.
Lopez, Bryan Irvine M; An, Narae; Srikanth, Krishnamoorthy; Lee, Seunghwan; Oh, Jae-Don; Shin, Dong-Hyun; Park, Woncheoul; Chai, Han-Ha; Park, Jong-Eun; Lim, Dajeong.
Afiliação
  • Lopez BIM; Division of Animal Genomics and Bioinformatics, National Institute of Animal Science, Rural Development Administration, Wanju, South Korea.
  • An N; Division of Animal Genomics and Bioinformatics, National Institute of Animal Science, Rural Development Administration, Wanju, South Korea.
  • Srikanth K; Division of Animal Genomics and Bioinformatics, National Institute of Animal Science, Rural Development Administration, Wanju, South Korea.
  • Lee S; Department of Animal Science and Biotechnology, Chungnam National University, Daejeon, South Korea.
  • Oh JD; Department of Animal Biotechnology, Chonbuk National University, Jeonju, South Korea.
  • Shin DH; Department of Agricultural Convergence Technology, Chonbuk National University, Jeonju, South Korea.
  • Park W; Division of Animal Genomics and Bioinformatics, National Institute of Animal Science, Rural Development Administration, Wanju, South Korea.
  • Chai HH; Division of Animal Genomics and Bioinformatics, National Institute of Animal Science, Rural Development Administration, Wanju, South Korea.
  • Park JE; Division of Animal Genomics and Bioinformatics, National Institute of Animal Science, Rural Development Administration, Wanju, South Korea.
  • Lim D; Division of Animal Genomics and Bioinformatics, National Institute of Animal Science, Rural Development Administration, Wanju, South Korea.
Front Genet ; 11: 603822, 2020.
Article em En | MEDLINE | ID: mdl-33552124
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Texto completo: 1 Bases de dados: MEDLINE Tipo de estudo: Prognostic_studies / Risk_factors_studies Idioma: En Revista: Front Genet Ano de publicação: 2020 Tipo de documento: Article País de afiliação: Coréia do Sul
Texto completo
Adicionar na Minha BVS
Imprimir
XML
PubMed Links
Buscar no Google

Texto completo: 1 Bases de dados: MEDLINE Tipo de estudo: Prognostic_studies / Risk_factors_studies Idioma: En Revista: Front Genet Ano de publicação: 2020 Tipo de documento: Article País de afiliação: Coréia do Sul