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

Drug target identification is a crucial step in drug development. Here, the authors introduce a Bayesian machine learning framework that integrates multiple data types to predict the targets of small molecules, enabling identification of a new set of microtubule inhibitors and the target of the anti...

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Autores principales: Neel S. Madhukar, Prashant K. Khade, Linda Huang, Kaitlyn Gayvert, Giuseppe Galletti, Martin Stogniew, Joshua E. Allen, Paraskevi Giannakakou, Olivier Elemento
Formato: article
Lenguaje:EN
Publicado: Nature Portfolio 2019
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Acceso en línea:https://doaj.org/article/fd2f68d27a0449ed8826ad49e3a65d1c
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