Bitter-RF: A random forest machine model for recognizing bitter peptides.

Zhang, Yu-Fei; Wang, Yu-Hao; Gu, Zhi-Feng; Pan, Xian-Run; Li, Jian; Ding, Hui; Zhang, Yang; Deng, Ke-Jun

Zhang, Yu-Fei; Wang, Yu-Hao; Gu, Zhi-Feng; Pan, Xian-Run; Li, Jian; Ding, Hui; Zhang, Yang; Deng, Ke-Jun.

Afiliação

Zhang YF; School of Life Science and Technology, Center for Informational Biology, University of Electronic Science and Technology of China, Chengdu, China.
Wang YH; School of Life Science and Technology, Center for Informational Biology, University of Electronic Science and Technology of China, Chengdu, China.
Gu ZF; School of Life Science and Technology, Center for Informational Biology, University of Electronic Science and Technology of China, Chengdu, China.
Pan XR; Innovative Institute of Chinese Medicine and Pharmacy, Academy for Interdiscipline, Chengdu University of Traditional Chinese Medicine, Chengdu, China.
Li J; School of Basic Medical Sciences, Chengdu University, Chengdu, China.
Ding H; School of Life Science and Technology, Center for Informational Biology, University of Electronic Science and Technology of China, Chengdu, China.
Zhang Y; Innovative Institute of Chinese Medicine and Pharmacy, Academy for Interdiscipline, Chengdu University of Traditional Chinese Medicine, Chengdu, China.
Deng KJ; School of Life Science and Technology, Center for Informational Biology, University of Electronic Science and Technology of China, Chengdu, China.

Front Med (Lausanne) ; 10: 1052923, 2023.

Article em En | MEDLINE | ID: mdl-36778738

Palavras-chave

bitter peptide; classification method; feature fusion; random forest; sequence information

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Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Tipo de estudo: Clinical_trials / Prognostic_studies Idioma: En Revista: Front Med (Lausanne) Ano de publicação: 2023 Tipo de documento: Article País de afiliação: China

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