Compound-protein interaction prediction by deep learning: Databases, descriptors and models.

Du, Bing-Xue; Qin, Yuan; Jiang, Yan-Feng; Xu, Yi; Yiu, Siu-Ming; Yu, Hui; Shi, Jian-Yu

Du, Bing-Xue; Qin, Yuan; Jiang, Yan-Feng; Xu, Yi; Yiu, Siu-Ming; Yu, Hui; Shi, Jian-Yu.

Afiliación

Du BX; School of Life Sciences, Northwestern Polytechnical University, Xi'an 710072, China.
Qin Y; School of Life Sciences, Northwestern Polytechnical University, Xi'an 710072, China.
Jiang YF; School of Life Sciences, Northwestern Polytechnical University, Xi'an 710072, China.
Xu Y; School of Life Sciences, Northwestern Polytechnical University, Xi'an 710072, China.
Yiu SM; Department of Computer Science, The University of Hong Kong, Hong Kong, China.
Yu H; School of Computer Science, Northwestern Polytechnical University, Xi'an 710072, China. Electronic address: huiyu@nwpu.edu.cn.
Shi JY; School of Life Sciences, Northwestern Polytechnical University, Xi'an 710072, China. Electronic address: jianyushi@nwpu.edu.cn.

Drug Discov Today ; 27(5): 1350-1366, 2022 05.

Article en En | MEDLINE | ID: mdl-35248748

Asunto(s)

Aprendizaje Profundo; Bases de Datos Factuales; Descubrimiento de Drogas/métodos; Proteínas/metabolismo

Palabras clave

Compoundprotein interaction; Deep learning; Drug discovery; Embedding; Representation

Texto completo

Añadir a Mi BVS

Imprimir

XML

PubMed Links

Buscar en Google

Texto completo: 1 Colección: 01-internacional Base de datos: MEDLINE Asunto principal: Aprendizaje Profundo Tipo de estudio: Prognostic_studies / Risk_factors_studies Idioma: En Revista: Drug Discov Today Asunto de la revista: FARMACOLOGIA / TERAPIA POR MEDICAMENTOS Año: 2022 Tipo del documento: Article País de afiliación: China Pais de publicación: Reino Unido

Texto completo

Añadir a Mi BVS

Imprimir

XML

PubMed Links

Buscar en Google