Densest subgraph-based methods for protein-protein interaction hot spot prediction.

Li, Ruiming; Lee, Jung-Yu; Yang, Jinn-Moon; Akutsu, Tatsuya

Li, Ruiming; Lee, Jung-Yu; Yang, Jinn-Moon; Akutsu, Tatsuya.

Afiliação

Li R; Bioinformatics Center, Institute for Chemical Research, Kyoto University, Uji, 611-0011, Kyoto, Japan. lrming1993@gmail.com.
Lee JY; Institute of Bioinformatics and Systems Biology, National Yang Ming Chiao Tung University, Hsinchu, 300, Taiwan.
Yang JM; Institute of Bioinformatics and Systems Biology, National Yang Ming Chiao Tung University, Hsinchu, 300, Taiwan.
Akutsu T; Department of Biological Science and Technology, National Yang Ming Chiao Tung University, Hsinchu, 300, Taiwan.

BMC Bioinformatics ; 23(1): 451, 2022 Oct 31.

Article em En | MEDLINE | ID: mdl-36316653

Assuntos

Mapeamento de Interação de Proteínas; Proteínas; Bases de Dados de Proteínas; Proteínas/química; Sítios de Ligação; Ligação Proteica; Mapeamento de Interação de Proteínas/métodos

Palavras-chave

Bioinformatics; Densest subgraph; Graph theory; Hot spot; Linear programming; Network analysis; Protein-protein interaction; Residue interaction

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Texto completo: 1 Base de dados: MEDLINE Assunto principal: Proteínas / Mapeamento de Interação de Proteínas Tipo de estudo: Prognostic_studies / Risk_factors_studies Idioma: En Ano de publicação: 2022 Tipo de documento: Article

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