Deep-4mCGP: A Deep Learning Approach to Predict 4mC Sites in <i>Geobacter pickeringii</i> by Using Correlation-Based Feature Selection Technique.

Zulfiqar, Hasan; Huang, Qin-Lai; Lv, Hao; Sun, Zi-Jie; Dao, Fu-Ying; Lin, Hao

Deep-4mCGP: A Deep Learning Approach to Predict 4mC Sites in Geobacter pickeringii by Using Correlation-Based Feature Selection Technique.

Zulfiqar, Hasan; Huang, Qin-Lai; Lv, Hao; Sun, Zi-Jie; Dao, Fu-Ying; Lin, Hao.

Afiliação

Zulfiqar H; School of Life Science and Technology, Center for Informational Biology, University of Electronic Science and Technology of China, Chengdu 610054, China.
Huang QL; School of Life Science and Technology, Center for Informational Biology, University of Electronic Science and Technology of China, Chengdu 610054, China.
Lv H; School of Life Science and Technology, Center for Informational Biology, University of Electronic Science and Technology of China, Chengdu 610054, China.
Sun ZJ; School of Life Science and Technology, Center for Informational Biology, University of Electronic Science and Technology of China, Chengdu 610054, China.
Dao FY; School of Life Science and Technology, Center for Informational Biology, University of Electronic Science and Technology of China, Chengdu 610054, China.
Lin H; School of Life Science and Technology, Center for Informational Biology, University of Electronic Science and Technology of China, Chengdu 610054, China.

Int J Mol Sci ; 23(3)2022 Jan 23.

Article em En | MEDLINE | ID: mdl-35163174

Assuntos

Biologia Computacional/métodos; Epigênese Genética/genética; Geobacter/genética; Algoritmos; Citosina/metabolismo; DNA/genética; Metilação de DNA/genética; Aprendizado Profundo; Aprendizado de Máquina; Mutação/genética; Redes Neurais de Computação; Software

Palavras-chave

algorithm; alteration; deep learning; features vector; genomics

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Texto completo: 1 Base de dados: MEDLINE Assunto principal: Biologia Computacional / Geobacter / Epigênese Genética Tipo de estudo: Prognostic_studies / Risk_factors_studies Idioma: En Ano de publicação: 2022 Tipo de documento: Article

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