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Learning Drug Functions from Chemical Structures with Convolutional Neural Networks and Random Forests
[Image: see text] Empirical testing of chemicals for drug efficacy costs many billions of dollars every year. The ability to predict the action of molecules in silico would greatly increase the speed and decrease the cost of prioritizing drug leads. Here, we asked whether drug function, defined as M...
| Autores principales: | , , , , |
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| Formato: | Online Artículo Texto |
| Lenguaje: | English |
| Publicado: |
American Chemical
Society
2019
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| Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6819987/ https://www.ncbi.nlm.nih.gov/pubmed/31518132 http://dx.doi.org/10.1021/acs.jcim.9b00236 |