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Learning size-adaptive molecular substructures for explainable drug–drug interaction prediction by substructure-aware graph neural network
Drug–drug interactions (DDIs) can trigger unexpected pharmacological effects on the body, and the causal mechanisms are often unknown. Graph neural networks (GNNs) have been developed to better understand DDIs. However, identifying key substructures that contribute most to the DDI prediction is a ch...
| Autores principales: | , , , |
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| Formato: | Online Artículo Texto |
| Lenguaje: | English |
| Publicado: |
The Royal Society of Chemistry
2022
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| Materias: | |
| Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9337739/ https://www.ncbi.nlm.nih.gov/pubmed/35974769 http://dx.doi.org/10.1039/d2sc02023h |