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DeLIVR: a deep learning approach to IV regression for testing nonlinear causal effects in transcriptome-wide association studies.
He, Ruoyu; Liu, Mingyang; Lin, Zhaotong; Zhuang, Zhong; Shen, Xiaotong; Pan, Wei.
  • He R; Division of Biostatistics, School of Public Health, University of Minnesota, A460 Mayo Building, 420 Delaware Street SE, Minneapolis, MN 55455 and School of Statistics, University of Minnesota, 313 Ford Hall, 224 Church St SE, Minneapolis, MN 55455.
  • Liu M; Division of Biostatistics, School of Public Health, University of Minnesota, A460 Mayo Building, 420 Delaware Street SE, Minneapolis, MN 55455 and School of Statistics, University of Minnesota, 313 Ford Hall, 224 Church St SE, Minneapolis, MN 55455.
  • Lin Z; Division of Biostatistics, School of Public Health, University of Minnesota, A460 Mayo Building, 420 Delaware Street SE, Minneapolis, MN 55455 and School of Statistics, University of Minnesota, 313 Ford Hall, 224 Church St SE, Minneapolis, MN 55455.
  • Zhuang Z; Division of Biostatistics, School of Public Health, University of Minnesota, A460 Mayo Building, 420 Delaware Street SE, Minneapolis, MN 55455 and School of Statistics, University of Minnesota, 313 Ford Hall, 224 Church St SE, Minneapolis, MN 55455.
  • Shen X; Division of Biostatistics, School of Public Health, University of Minnesota, A460 Mayo Building, 420 Delaware Street SE, Minneapolis, MN 55455 and School of Statistics, University of Minnesota, 313 Ford Hall, 224 Church St SE, Minneapolis, MN 55455.
  • Pan W; Division of Biostatistics, School of Public Health, University of Minnesota, A460 Mayo Building, 420 Delaware Street SE, Minneapolis, MN 55455 and School of Statistics, University of Minnesota, 313 Ford Hall, 224 Church St SE, Minneapolis, MN 55455.
Biostatistics ; 25(2): 468-485, 2024 Apr 15.
Article en En | MEDLINE | ID: mdl-36610078
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Texto completo: 1 Banco de datos: MEDLINE Asunto principal: Transcriptoma / Aprendizaje Profundo Tipo de estudio: Prognostic_studies / Risk_factors_studies Límite: Humans Idioma: En Año: 2024 Tipo del documento: Article
Texto completo
Imprimir
XML
PubMed Links
Search on Google

Texto completo: 1 Banco de datos: MEDLINE Asunto principal: Transcriptoma / Aprendizaje Profundo Tipo de estudio: Prognostic_studies / Risk_factors_studies Límite: Humans Idioma: En Año: 2024 Tipo del documento: Article