Learning Multi-Types of Neighbor Node Attributes and Semantics by Heterogeneous Graph Transformer and Multi-View Attention for Drug-Related Side-Effect Prediction

Since side-effects of drugs are one of the primary reasons for their failure in clinical trials, predicting their side-effects can help reduce drug development costs. We proposed a method based on heterogeneous graph transformer and capsule networks for side-effect-drug-association prediction (TCSD)...

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Detalles Bibliográficos
Autores principales: Xuan, Ping, Li, Peiru, Cui, Hui, Wang, Meng, Nakaguchi, Toshiya, Zhang, Tiangang
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2023
Materias:
Article
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10537290/
https://www.ncbi.nlm.nih.gov/pubmed/37764319
http://dx.doi.org/10.3390/molecules28186544

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10537290/
https://www.ncbi.nlm.nih.gov/pubmed/37764319
http://dx.doi.org/10.3390/molecules28186544

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