Computational prediction and analysis of species-specific fungi phosphorylation via feature optimization strategy.

Cao, Man; Chen, Guodong; Yu, Jialin; Shi, Shaoping

Cao, Man; Chen, Guodong; Yu, Jialin; Shi, Shaoping.

Afiliação

Cao M; Department of Mathematics and Numerical Simulation and High-Performance Computing Laboratory, School of Sciences, Nanchang University, Nanchang, China.
Chen G; Department of Mathematics and Numerical Simulation and High-Performance Computing Laboratory, School of Sciences, Nanchang University, Nanchang, China.
Yu J; Department of Mathematics and Numerical Simulation and High-Performance Computing Laboratory, School of Sciences, Nanchang University, Nanchang, China.
Shi S; Department of Mathematics and Numerical Simulation and High-Performance Computing Laboratory, School of Sciences, Nanchang University, Nanchang, China.

Brief Bioinform ; 21(2): 595-608, 2020 03 23.

Article em En | MEDLINE | ID: mdl-30590490

Assuntos

Biologia Computacional/métodos; Fungos/metabolismo; Fungos/classificação; Fosforilação; Especificidade da Espécie

Palavras-chave

fungi; phosphorylation; random forest; two-step feature optimization

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Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Assunto principal: Biologia Computacional / Fungos Tipo de estudo: Prognostic_studies / Risk_factors_studies Idioma: En Ano de publicação: 2020 Tipo de documento: Article

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