Combining Metabolite-Based Pharmacophores with Bayesian Machine Learning Models for Mycobacterium tuberculosis Drug Discovery

Integrated computational approaches for Mycobacterium tuberculosis (Mtb) are useful to identify new molecules that could lead to future tuberculosis (TB) drugs. Our approach uses information derived from the TBCyc pathway and genome database, the Collaborative Drug Discovery TB database combined wit...

詳細記述

保存先:
書誌詳細
出版年:PLoS One
主要な著者: Ekins, Sean, Madrid, Peter B., Sarker, Malabika, Li, Shao-Gang, Mittal, Nisha, Kumar, Pradeep, Wang, Xin, Stratton, Thomas P., Zimmerman, Matthew, Talcott, Carolyn, Bourbon, Pauline, Travers, Mike, Yadav, Maneesh, Freundlich, Joel S.
フォーマット: Artigo
言語:Inglês
出版事項: Public Library of Science 2015
主題:
Research Article
オンライン･アクセス:https://ncbi.nlm.nih.gov/pmc/articles/PMC4627656/
https://ncbi.nlm.nih.gov/pubmed/26517557
https://ncbi.nlm.nih.govhttp://dx.doi.org/10.1371/journal.pone.0141076
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