Random-forest model for drug–target interaction prediction via Kullbeck–Leibler divergence

Virtual screening has significantly improved the success rate of early stage drug discovery. Recent virtual screening methods have improved owing to advances in machine learning and chemical information. Among these advances, the creative extraction of drug features is important for predicting drug–...

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Detalles Bibliográficos
Autores principales: Ahn, Sangjin, Lee, Si Eun, Kim, Mi-hyun
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Springer International Publishing 2022
Materias:
Research
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9531514/
https://www.ncbi.nlm.nih.gov/pubmed/36192818
http://dx.doi.org/10.1186/s13321-022-00644-1

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9531514/
https://www.ncbi.nlm.nih.gov/pubmed/36192818
http://dx.doi.org/10.1186/s13321-022-00644-1

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