Learning spatial structures of proteins improves protein-protein interaction prediction.

Song, Bosheng; Luo, Xiaoyan; Luo, Xiaoli; Liu, Yuansheng; Niu, Zhangming; Zeng, Xiangxiang

Song, Bosheng; Luo, Xiaoyan; Luo, Xiaoli; Liu, Yuansheng; Niu, Zhangming; Zeng, Xiangxiang.

Afiliação

Song B; College of Computer Science and Electronic Engineering, Hunan University, Changsha, 410012, Hunan, China.
Luo X; College of Computer Science and Electronic Engineering, Hunan University, Changsha, 410012, Hunan, China.
Luo X; MindRank AI ltd., Hangzhou, 311113, Zhejiang, China.
Liu Y; College of Computer Science and Electronic Engineering, Hunan University, Changsha, 410012, Hunan, China.
Niu Z; BioMap, Haidian, 100089, Beijing, China.
Zeng X; College of Computer Science and Electronic Engineering, Hunan University, Changsha, 410012, Hunan, China.

Brief Bioinform ; 23(2)2022 03 10.

Article em En | MEDLINE | ID: mdl-35018418

Assuntos

Aprendizado de Máquina; Proteínas; Sequência de Aminoácidos; Proteínas/metabolismo

Palavras-chave

graph neural network; multi-dimension feature confusion; protein representation learning; proteinprotein interaction

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Texto completo: 1 Base de dados: MEDLINE Assunto principal: Proteínas / Aprendizado de Máquina Tipo de estudo: Prognostic_studies / Risk_factors_studies Idioma: En Revista: Brief Bioinform Assunto da revista: BIOLOGIA / INFORMATICA MEDICA Ano de publicação: 2022 Tipo de documento: Article País de afiliação: China

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