DRSN4mCPred: accurately predicting sites of DNA N4-methylcytosine using deep residual shrinkage network for diagnosis and treatment of gastrointestinal cancer in the precision medicine era.

Yu, Xia; Ren, Jia; Cui, Yani; Zeng, Rao; Long, Haixia; Ma, Cuihua

Yu, Xia; Ren, Jia; Cui, Yani; Zeng, Rao; Long, Haixia; Ma, Cuihua.

Afiliación

Yu X; School of Information and Communication Engineering, Hainan University, Haikou, Hainan, China.
Ren J; School of Information Science and Technology, Hainan Normal University, Haikou, Hainan, China.
Cui Y; Industrial Design School, Shandong University of ART and Design, Jinan, Shandong, China.
Zeng R; School of Information and Communication Engineering, Hainan University, Haikou, Hainan, China.
Long H; School of Information Science and Technology, Hainan Normal University, Haikou, Hainan, China.
Ma C; School of Information Science and Technology, Hainan Normal University, Haikou, Hainan, China.

Front Med (Lausanne) ; 10: 1187430, 2023.

Article en En | MEDLINE | ID: mdl-37215722

Palabras clave

DNA N4-methylcytosine; deep learning; deep residual shrinkage network; multi-scale channel attention; site prediction

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Texto completo: 1 Colección: 01-internacional Base de datos: MEDLINE Tipo de estudio: Diagnostic_studies / Prognostic_studies / Risk_factors_studies Idioma: En Revista: Front Med (Lausanne) Año: 2023 Tipo del documento: Article País de afiliación: China

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