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ADMET property prediction via multi-task graph learning under adaptive auxiliary task selection
It is a critical step in lead optimization to evaluate the absorption, distribution, metabolism, excretion, and toxicity (ADMET) properties of drug-like compounds. Classical single-task learning (STL) has effectively predicted individual ADMET endpoints with abundant labels. Conversely, multi-task l...
| Autores principales: | , , , , |
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| Formato: | Online Artículo Texto |
| Lenguaje: | English |
| Publicado: |
Elsevier
2023
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| Materias: | |
| Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10654589/ https://www.ncbi.nlm.nih.gov/pubmed/38026198 http://dx.doi.org/10.1016/j.isci.2023.108285 |