ALDPI: adaptively learning importance of multi-scale topologies and multi-modality similarities for drug-protein interaction prediction.

Hu, Kaimiao; Cui, Hui; Zhang, Tiangang; Sun, Chang; Xuan, Ping

Hu, Kaimiao; Cui, Hui; Zhang, Tiangang; Sun, Chang; Xuan, Ping.

Afiliação

Hu K; School of Computer Science and Technology, Heilongjiang University, Harbin 150080, China.
Cui H; Department of Computer Science and Information Technology, La Trobe University, Melbourne 3083, Australia.
Zhang T; School of Mathematical Science, Heilongjiang University, Harbin 150080, China.
Sun C; College of Computer Science, Nankai University, Tianjin 300071, China.
Xuan P; School of Computer Science and Technology, Heilongjiang University, Harbin 150080, China.

Brief Bioinform ; 23(2)2022 03 10.

Article em En | MEDLINE | ID: mdl-35108362

Assuntos

Algoritmos; Redes Neurais de Computação; Desenvolvimento de Medicamentos/métodos; Interações Medicamentosas; Proteínas

Palavras-chave

drugprotein interaction prediction; drugprotein heterogeneous graph; multi-modality similarities; multi-scale neighbor topologies; neighbor topology-level attention

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Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Assunto principal: Algoritmos / Redes Neurais de Computação Tipo de estudo: Prognostic_studies / Risk_factors_studies Idioma: En Ano de publicação: 2022 Tipo de documento: Article

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