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

Background: Inferring drug-related side effects is beneficial for reducing drug development cost and time. Current computational prediction methods have concentrated on graph reasoning over heterogeneous graphs comprising the drug and side effect nodes. However, the various topologies and node attri...

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Detalles Bibliográficos
Autores principales: Xuan, Ping, Xu, Kai, Cui, Hui, Nakaguchi, Toshiya, Zhang, Tiangang
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Frontiers Media S.A. 2023
Materias:
Pharmacology
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10507253/
https://www.ncbi.nlm.nih.gov/pubmed/37731739
http://dx.doi.org/10.3389/fphar.2023.1257842

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10507253/
https://www.ncbi.nlm.nih.gov/pubmed/37731739
http://dx.doi.org/10.3389/fphar.2023.1257842

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