Evaluating Scalable Supervised Learning for Synthesize-on-Demand Chemical Libraries

[Image: see text] Traditional small-molecule drug discovery is a time-consuming and costly endeavor. High-throughput chemical screening can only assess a tiny fraction of drug-like chemical space. The strong predictive power of modern machine-learning methods for virtual chemical screening enables t...

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Detalles Bibliográficos
Autores principales: Alnammi, Moayad, Liu, Shengchao, Ericksen, Spencer S., Ananiev, Gene E., Voter, Andrew F., Guo, Song, Keck, James L., Hoffmann, F. Michael, Wildman, Scott A., Gitter, Anthony
Formato: Online Artículo Texto
Lenguaje:English
Publicado: American Chemical Society 2023
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10538940/
https://www.ncbi.nlm.nih.gov/pubmed/37625010
http://dx.doi.org/10.1021/acs.jcim.3c00912

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10538940/
https://www.ncbi.nlm.nih.gov/pubmed/37625010
http://dx.doi.org/10.1021/acs.jcim.3c00912

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