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 A new publication through collaborations between CIDR and ISB is now published in Nature Microbiology. Peterson et al., discusses how a network strategy predicts drug combinations with antagonistic interactions, potentially accelerating the discovery of new effective combination drug regimens for tuberculosis.

Eliza J. R. Peterson, Shuyi Ma, David R. Sherman & Nitin S. Baliga. Network analysis identifies Rv0324 and Rv0880 as regulators of bedaquiline tolerance in Mycobacterium tuberculosis.  Nature Microbiology

 06/06/2016 - 13:54   sturkarslan     news
Mycobacterium tuberculosis (MTB) causes ~12 million cases of active disease and 1.4 million deaths each year, and our tools to combat tuberculosis (TB) disease are universally outdated and overmatched. We anticipate that a systems-based analysis, with large-scale, multi-omics data collection and iterative cycles of modeling, prediction and testing, is the ideal means to detect patterns in the underlying complexity and define the critical regulatory components. This website serves as a portal for computational modeling program to generate an integrated, predictive gene regulatory network model of host/pathogen interactions.

The Omics for TB Disease Progression (OTB) program at the Center for Infectious Disease Research is pleased to announce a call for proposals for our Pilot Research Projects initiative in the coming year.  This program is an extension of our parent award from NIH/NIAID and provides an exciting opportunity to explore high-risk, innovative approaches related to tuberculosis research. 

 11/03/2015 - 10:20   sturkarslan     updates

We have made two new datasets available and integrated a new regulatory network visualization.

 07/07/2014 - 09:57   sturkarslan     updates