Identification of adaptor proteins by incorporating deep learning and PSSM profiles.

Gao, Wentao; Xu, Dali; Li, Hongfei; Du, Junping; Wang, Guohua; Li, Dan

Gao, Wentao; Xu, Dali; Li, Hongfei; Du, Junping; Wang, Guohua; Li, Dan.

Afiliación

Gao W; College of Information and Computer Engineering, Northeast Forestry University, Harbin 150000, China.
Xu D; College of Information and Computer Engineering, Northeast Forestry University, Harbin 150000, China.
Li H; College of Information and Computer Engineering, Northeast Forestry University, Harbin 150000, China.
Du J; Beijing Key Laboratory of Intelligent Telecommunication Software and Multimedia, School of Computer Science, Beijing University of Posts and Telecommunications, Beijing, 100876, China.
Wang G; College of Information and Computer Engineering, Northeast Forestry University, Harbin 150000, China. Electronic address: ghwang@nefu.edu.cn.
Li D; College of Information and Computer Engineering, Northeast Forestry University, Harbin 150000, China. Electronic address: ld725725@126.com.

Methods ; 209: 10-17, 2023 01.

Article en En | MEDLINE | ID: mdl-36427763

Asunto(s)

Aprendizaje Profundo; Posición Específica de Matrices de Puntuación; Redes Neurales de la Computación; Programas Informáticos; Proteínas Adaptadoras Transductoras de Señales; Algoritmos

Palabras clave

Adaptor proteins; Deep learning; PSSM; biLSTM

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Texto completo: 1 Colección: 01-internacional Base de datos: MEDLINE Asunto principal: Aprendizaje Profundo Tipo de estudio: Diagnostic_studies / Prognostic_studies Idioma: En Revista: Methods Asunto de la revista: BIOQUIMICA Año: 2023 Tipo del documento: Article País de afiliación: China Pais de publicación: Estados Unidos

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