Identify RNA-associated subcellular localizations based on multi-label learning using Chou's 5-steps rule.

Wang, Hao; Ding, Yijie; Tang, Jijun; Zou, Quan; Guo, Fei

Wang, Hao; Ding, Yijie; Tang, Jijun; Zou, Quan; Guo, Fei.

Afiliação

Wang H; School of Computer Science and Technology, College of Intelligence and Computing, Tianjin University, Tianjin, China.
Ding Y; School of Electronic and Information Engineering, Suzhou University of Science and Technology, Suzhou, China.
Tang J; School of Computer Science and Technology, College of Intelligence and Computing, Tianjin University, Tianjin, China.
Zou Q; School of Computational Science and Engineering, University of South Carolina, Columbia, 29208, SC, US.
Guo F; Institute of Fundamental and Frontier Sciences, University of Electronic Science and Technology of China, Chengdu, Sichuan, China.

BMC Genomics ; 22(1): 56, 2021 Jan 15.

Article em En | MEDLINE | ID: mdl-33451286

Assuntos

Biologia Computacional; Proteínas; Bases de Dados de Proteínas; Humanos; RNA/genética; Máquina de Vetores de Suporte

Palavras-chave

Hilbert-Schmidt independence criterion; Multi-label classification; Multiple kernel learning; RNA subcellular localization; Web server

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Texto completo: 1 Base de dados: MEDLINE Assunto principal: Proteínas / Biologia Computacional Tipo de estudo: Prognostic_studies / Risk_factors_studies Limite: Humans Idioma: En Ano de publicação: 2021 Tipo de documento: Article

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