Enabling data-limited chemical bioactivity predictions through deep neural network transfer learning.

Liu, Ruifeng; Laxminarayan, Srinivas; Reifman, Jaques; Wallqvist, Anders

Liu, Ruifeng; Laxminarayan, Srinivas; Reifman, Jaques; Wallqvist, Anders.

Afiliación

Liu R; Department of Defense Biotechnology High Performance Computing Software Applications Institute, Telemedicine and Advanced Technology Research Center, U.S. Army Medical Research and Development Command, FCMR-TT, 504 Scott Street, Fort Detrick, MD, 21702-5012, USA.
Laxminarayan S; The Henry M. Jackson Foundation for the Advancement of Military Medicine, Inc., Bethesda, MD, USA.
Reifman J; Department of Defense Biotechnology High Performance Computing Software Applications Institute, Telemedicine and Advanced Technology Research Center, U.S. Army Medical Research and Development Command, FCMR-TT, 504 Scott Street, Fort Detrick, MD, 21702-5012, USA.
Wallqvist A; The Henry M. Jackson Foundation for the Advancement of Military Medicine, Inc., Bethesda, MD, USA.

J Comput Aided Mol Des ; 36(12): 867-878, 2022 12.

Article en En | MEDLINE | ID: mdl-36272041

Asunto(s)

Aprendizaje Automático; Redes Neurales de la Computación

Palabras clave

Deep neural networks; Machine learning; QSAR; Transfer learning

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Texto completo: 1 Banco de datos: MEDLINE Asunto principal: Redes Neurales de la Computación / Aprendizaje Automático Tipo de estudio: Prognostic_studies / Risk_factors_studies Idioma: En Revista: J Comput Aided Mol Des Asunto de la revista: BIOLOGIA MOLECULAR / ENGENHARIA BIOMEDICA Año: 2022 Tipo del documento: Article País de afiliación: Estados Unidos

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