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Deep learning-based phenotype imputation on population-scale biobank data increases genetic discoveries.
An, Ulzee; Pazokitoroudi, Ali; Alvarez, Marcus; Huang, Lianyun; Bacanu, Silviu; Schork, Andrew J; Kendler, Kenneth; Pajukanta, Päivi; Flint, Jonathan; Zaitlen, Noah; Cai, Na; Dahl, Andy; Sankararaman, Sriram.
Afiliación
  • An U; Computer Science Department, UCLA, Los Angeles, CA, USA. ulzee@cs.ucla.edu.
  • Pazokitoroudi A; Computer Science Department, UCLA, Los Angeles, CA, USA.
  • Alvarez M; Department of Human Genetics, David Geffen School of Medicine at UCLA, Los Angeles, CA, USA.
  • Huang L; Helmholtz Pioneer Campus, Helmholtz Zentrum München, Neuherberg, Germany.
  • Bacanu S; Computational Health Centre, Helmholtz Zentrum München, Neuherberg, Germany.
  • Schork AJ; School of Medicine, Technical University of Munich, Munich, Germany.
  • Kendler K; Virginia Institute for Psychiatric and Behavioral Genetics and Department of Psychiatry, Virginia Commonwealth University, Richmond, VA, USA.
  • Pajukanta P; Institute of Biological Psychiatry, Mental Health Center - Sct Hans, Copenhagen University Hospital, Copenhagen, Denmark.
  • Flint J; Neurogenomics Division, The Translational Genomics Research Institute (TGEN), Phoenix, AZ, USA.
  • Zaitlen N; Section for Geogenetics, GLOBE Institute, Faculty of Health and Medical Sciences, Copenhagen University, Copenhagen, Denmark.
  • Cai N; Virginia Institute for Psychiatric and Behavioral Genetics and Department of Psychiatry, Virginia Commonwealth University, Richmond, VA, USA.
  • Dahl A; Department of Human Genetics, David Geffen School of Medicine at UCLA, Los Angeles, CA, USA.
  • Sankararaman S; Institute for Precision Health, David Geffen School of Medicine at UCLA, Los Angeles, CA, USA.
Nat Genet ; 55(12): 2269-2276, 2023 Dec.
Article en En | MEDLINE | ID: mdl-37985819
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Texto completo: 1 Colección: 01-internacional Banco de datos: MEDLINE Asunto principal: Estudio de Asociación del Genoma Completo / Aprendizaje Profundo Límite: Humans Idioma: En Revista: Nat Genet Asunto de la revista: GENETICA MEDICA Año: 2023 Tipo del documento: Article País de afiliación: Estados Unidos
Texto completo
Imprimir
XML
PubMed Links
Buscar en Google

Texto completo: 1 Colección: 01-internacional Banco de datos: MEDLINE Asunto principal: Estudio de Asociación del Genoma Completo / Aprendizaje Profundo Límite: Humans Idioma: En Revista: Nat Genet Asunto de la revista: GENETICA MEDICA Año: 2023 Tipo del documento: Article País de afiliación: Estados Unidos