ELECTRA-DTA: a new compound-protein binding affinity prediction model based on the contextualized sequence encoding.

Wang, Junjie; Wen, NaiFeng; Wang, Chunyu; Zhao, Lingling; Cheng, Liang

Wang, Junjie; Wen, NaiFeng; Wang, Chunyu; Zhao, Lingling; Cheng, Liang.

Afiliación

Wang J; Department of Medical Informatics, School of Biomedical Engineering and Informatics, Nanjing Medical University, Nanjing, People's Republic of China.
Wen N; School of Mechanical and Electrical Engineering, Dalian Minzu University, Dalian, People's Republic of China.
Wang C; Faculty of Computing, Harbin Institute of Technology, Harbin, People's Republic of China.
Zhao L; Faculty of Computing, Harbin Institute of Technology, Harbin, People's Republic of China. zhaoll@hit.edu.cn.
Cheng L; NHC and CAMS Key Laboratory of Molecular Probe and Targeted Theranostics, Harbin Medical University, Harbin, People's Republic of China. liangcheng@hrbmu.edu.cn.

J Cheminform ; 14(1): 14, 2022 Mar 15.

Article en En | MEDLINE | ID: mdl-35292100

Palabras clave

Deep learning; Drug-target affinity prediction; ELECTRA; Representative learning

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Texto completo: 1 Colección: 01-internacional Banco de datos: MEDLINE Tipo de estudio: Prognostic_studies / Risk_factors_studies Idioma: En Revista: J Cheminform Año: 2022 Tipo del documento: Article

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