Computational prediction and interpretation of druggable proteins using a stacked ensemble-learning framework

Discovery of potential drugs requires rapid and precise identification of drug targets. Although traditional experimental methodologies can accurately identify drug targets, they are time-consuming and inappropriate for high-throughput screening. Computational approaches based on machine learning (M...

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Detalles Bibliográficos
Autores principales: Charoenkwan, Phasit, Schaduangrat, Nalini, Lio’, Pietro, Moni, Mohammad Ali, Shoombuatong, Watshara, Manavalan, Balachandran
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Elsevier 2022
Materias:
Article
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9421381/
https://www.ncbi.nlm.nih.gov/pubmed/36046193
http://dx.doi.org/10.1016/j.isci.2022.104883

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9421381/
https://www.ncbi.nlm.nih.gov/pubmed/36046193
http://dx.doi.org/10.1016/j.isci.2022.104883

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