Graph generative and adversarial strategy-enhanced node feature learning and self-calibrated pairwise attribute encoding for prediction of drug-related side effects.

Xuan, Ping; Xu, Kai; Cui, Hui; Nakaguchi, Toshiya; Zhang, Tiangang

Xuan, Ping; Xu, Kai; Cui, Hui; Nakaguchi, Toshiya; Zhang, Tiangang.

Afiliación

Xuan P; Department of Computer Science, School of Engineering, Shantou University, Shantou, China.
Xu K; School of Computer Science and Technology, Heilongjiang University, Harbin, China.
Cui H; Department of Computer Science and Information Technology, La Trobe University, Melbourne, VI, Australia.
Nakaguchi T; Center for Frontier Medical Engineering, Chiba University, Chiba, Japan.
Zhang T; School of Computer Science and Technology, Heilongjiang University, Harbin, China.

Front Pharmacol ; 14: 1257842, 2023.

Article en En | MEDLINE | ID: mdl-37731739

Palabras clave

graph convolutional autoencoder; graph generative and adversarial strategy; representation-level attention; self-calibrated pairwise attributes; topologies and attributes from heterogeneous graphs

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Texto completo: 1 Colección: 01-internacional Base de datos: MEDLINE Tipo de estudio: Prognostic_studies / Risk_factors_studies Idioma: En Revista: Front Pharmacol Año: 2023 Tipo del documento: Article País de afiliación: China Pais de publicación: Suiza

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