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Omics-driven investigation of the biology underlying intrinsic submaximal working capacity and its trainability.
Hota, Monalisa; Barber, Jacob L; Ruiz-Ramie, Jonathan J; Schwartz, Charles S; Lam, Do Thuy Uyen Ha; Rao, Prashant; Mi, Michael Y; Katz, Daniel H; Robbins, Jeremy M; Clish, Clary B; Gerszten, Robert E; Sarzynski, Mark A; Ghosh, Sujoy; Bouchard, Claude.
Afiliação
  • Hota M; Centre for Computational Biology, Duke-National University of Singapore Medical School, Singapore, Singapore.
  • Barber JL; Department of Exercise Science, Arnold School of Public Health, University of South Carolina, Columbia, South Carolina, United States.
  • Ruiz-Ramie JJ; Department of Exercise Science, Arnold School of Public Health, University of South Carolina, Columbia, South Carolina, United States.
  • Schwartz CS; Department of Kinesiology, Augusta University, Augusta, Georgia, United States.
  • Lam DTUH; Department of Exercise Science, Arnold School of Public Health, University of South Carolina, Columbia, South Carolina, United States.
  • Rao P; Centre for Computational Biology, Duke-National University of Singapore Medical School, Singapore, Singapore.
  • Mi MY; Division of Cardiovascular Medicine, Beth Israel Deaconess Medical Center, Boston, Massachusetts, United States.
  • Katz DH; Division of Cardiovascular Medicine, Beth Israel Deaconess Medical Center, Boston, Massachusetts, United States.
  • Robbins JM; Division of Cardiovascular Medicine, Beth Israel Deaconess Medical Center, Boston, Massachusetts, United States.
  • Clish CB; Division of Cardiovascular Medicine, Beth Israel Deaconess Medical Center, Boston, Massachusetts, United States.
  • Gerszten RE; Metabolomics Platform, Broad Institute, Boston, Massachusetts, United States.
  • Sarzynski MA; Division of Cardiovascular Medicine, Beth Israel Deaconess Medical Center, Boston, Massachusetts, United States.
  • Ghosh S; Department of Exercise Science, Arnold School of Public Health, University of South Carolina, Columbia, South Carolina, United States.
  • Bouchard C; Centre for Computational Biology, Duke-National University of Singapore Medical School, Singapore, Singapore.
Physiol Genomics ; 55(11): 517-543, 2023 Nov 01.
Article em En | MEDLINE | ID: mdl-37661925
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Texto completo: 1 Base de dados: MEDLINE Assunto principal: Exercício Físico / Estudo de Associação Genômica Ampla Limite: Animals / Humans Idioma: En Ano de publicação: 2023 Tipo de documento: Article
Texto completo
Imprimir
XML
PubMed Links
Buscar no Google

Texto completo: 1 Base de dados: MEDLINE Assunto principal: Exercício Físico / Estudo de Associação Genômica Ampla Limite: Animals / Humans Idioma: En Ano de publicação: 2023 Tipo de documento: Article