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

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...

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Bibliographic Details
Main Authors: Sean Ekins, Peter B Madrid, Malabika Sarker, Shao-Gang Li, Nisha Mittal, Pradeep Kumar, Xin Wang, Thomas P Stratton, Matthew Zimmerman, Carolyn Talcott, Pauline Bourbon, Mike Travers, Maneesh Yadav, Joel S Freundlich
Format: Article
Language:English
Published: Public Library of Science (PLoS) 2015-01-01
Series:PLoS ONE
Online Access:http://europepmc.org/articles/PMC4627656?pdf=render

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http://europepmc.org/articles/PMC4627656?pdf=render

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