A Bayesian machine learning approach for drug target identification using diverse data types

Drug target identification is a crucial step in development, yet is also among the most complex. To address this, we develop BANDIT, a Bayesian machine-learning approach that integrates multiple data types to predict drug binding targets. Integrating public data, BANDIT benchmarked a ~90% accuracy o...

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Detalles Bibliográficos
Autores principales: Madhukar, Neel S., Khade, Prashant K., Huang, Linda, Gayvert, Kaitlyn, Galletti, Giuseppe, Stogniew, Martin, Allen, Joshua E., Giannakakou, Paraskevi, Elemento, Olivier
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Nature Publishing Group UK 2019
Materias:
Article
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6863850/
https://www.ncbi.nlm.nih.gov/pubmed/31745082
http://dx.doi.org/10.1038/s41467-019-12928-6

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6863850/
https://www.ncbi.nlm.nih.gov/pubmed/31745082
http://dx.doi.org/10.1038/s41467-019-12928-6

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