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Deep learning of 2D-Restructured gene expression representations for improved low-sample therapeutic response prediction.
Cheng, Kai Ping; Shen, Wan Xiang; Jiang, Yu Yang; Chen, Yan; Chen, Yu Zong; Tan, Ying.
Afiliación
  • Cheng KP; The State Key Laboratory of Chemical Oncogenomics, Key Laboratory of Chemical Biology, Tsinghua Shenzhen International Graduate School, Tsinghua University, Shenzhen, 518055, PR China; Institute of Biomedical Health Technology and Engineering, Shenzhen Bay Laboratory, Shenzhen, 518132, PR China.
  • Shen WX; Bioinformatics and Drug Design Group, Department of Pharmacy, Center for Computational Science and Engineering, National University of Singapore, 117543, Singapore.
  • Jiang YY; School of Pharmaceutical Sciences, Tsinghua University, Beijing, 100084, PR China.
  • Chen Y; The State Key Laboratory of Chemical Oncogenomics, Key Laboratory of Chemical Biology, Tsinghua Shenzhen International Graduate School, Tsinghua University, Shenzhen, 518055, PR China.
  • Chen YZ; The State Key Laboratory of Chemical Oncogenomics, Key Laboratory of Chemical Biology, Tsinghua Shenzhen International Graduate School, Tsinghua University, Shenzhen, 518055, PR China; Institute of Biomedical Health Technology and Engineering, Shenzhen Bay Laboratory, Shenzhen, 518132, PR China. Ele
  • Tan Y; The State Key Laboratory of Chemical Oncogenomics, Key Laboratory of Chemical Biology, Tsinghua Shenzhen International Graduate School, Tsinghua University, Shenzhen, 518055, PR China; The Institute of Drug Discovery Technology, Ningbo University, Ningbo, 315211, PR China; Shenzhen Kivita Innovative
Comput Biol Med ; 164: 107245, 2023 09.
Article en En | MEDLINE | ID: mdl-37480677
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Texto completo: 1 Colección: 01-internacional Base de datos: MEDLINE Asunto principal: Aprendizaje Profundo Tipo de estudio: Prognostic_studies / Risk_factors_studies Límite: Humans Idioma: En Revista: Comput Biol Med Año: 2023 Tipo del documento: Article Pais de publicación: Estados Unidos
Texto completo
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Texto completo: 1 Colección: 01-internacional Base de datos: MEDLINE Asunto principal: Aprendizaje Profundo Tipo de estudio: Prognostic_studies / Risk_factors_studies Límite: Humans Idioma: En Revista: Comput Biol Med Año: 2023 Tipo del documento: Article Pais de publicación: Estados Unidos