Tuberculosis has been a global health concern for decades and the emergence of resistant strains and co-infection with HIV warrant newer approaches to identify anti-tubercular drugs and targets. The availability of many `omics'-scale datasets, together with the advances in computation and modelling have enabled the application of several systems-level modelling techniques in drug discovery. In this chapter, we focus on how systems-level modelling of Mycobacterium tuberculosis can provide us insights on various aspects of the pathogen, from metabolic pathways to protein--protein interaction networks, and how such models lend themselves to the identification of new and potentially improved drug targets. We present a brief overview of the modelling of mycobacterial metabolism, transcriptome and host-pathogen interactions, as well as how various models can be exploited for a rational identification of potential drug targets. Systems-level modelling and simulation of pathogenic organisms has an immense potential to impact most drug discovery programmes.
%0 Book Section
%1 Raman2011Systems
%A Raman, Karthik
%A Chandra, Nagasuma
%B Understanding the Dynamics of Biological Systems
%C New York, NY
%D 2011
%E Dubitzky, Werner
%E Southgate, Jennifer
%E Fuß, Hendrik
%I Springer New York
%K myown review systems\_biology tuberculosis
%P 83--110
%R 10.1007/978-1-4419-7964-3\_5
%T Systems Biology of Tuberculosis: Insights for Drug Discovery
%U http://dx.doi.org/10.1007/978-1-4419-7964-3\_5
%X Tuberculosis has been a global health concern for decades and the emergence of resistant strains and co-infection with HIV warrant newer approaches to identify anti-tubercular drugs and targets. The availability of many `omics'-scale datasets, together with the advances in computation and modelling have enabled the application of several systems-level modelling techniques in drug discovery. In this chapter, we focus on how systems-level modelling of Mycobacterium tuberculosis can provide us insights on various aspects of the pathogen, from metabolic pathways to protein--protein interaction networks, and how such models lend themselves to the identification of new and potentially improved drug targets. We present a brief overview of the modelling of mycobacterial metabolism, transcriptome and host-pathogen interactions, as well as how various models can be exploited for a rational identification of potential drug targets. Systems-level modelling and simulation of pathogenic organisms has an immense potential to impact most drug discovery programmes.
%& 5
%@ 978-1-4419-7963-6
@inbook{Raman2011Systems,
abstract = {Tuberculosis has been a global health concern for decades and the emergence of resistant strains and co-infection with {HIV} warrant newer approaches to identify anti-tubercular drugs and targets. The availability of many `omics'-scale datasets, together with the advances in computation and modelling have enabled the application of several systems-level modelling techniques in drug discovery. In this chapter, we focus on how systems-level modelling of Mycobacterium tuberculosis can provide us insights on various aspects of the pathogen, from metabolic pathways to protein--protein interaction networks, and how such models lend themselves to the identification of new and potentially improved drug targets. We present a brief overview of the modelling of mycobacterial metabolism, transcriptome and host-pathogen interactions, as well as how various models can be exploited for a rational identification of potential drug targets. Systems-level modelling and simulation of pathogenic organisms has an immense potential to impact most drug discovery programmes.},
added-at = {2018-12-02T16:09:07.000+0100},
address = {New York, NY},
author = {Raman, Karthik and Chandra, Nagasuma},
biburl = {https://www.bibsonomy.org/bibtex/221371d1c5f9b49639d6f1f73c86c5a24/karthikraman},
booktitle = {Understanding the Dynamics of Biological Systems},
chapter = 5,
citeulike-article-id = {8654877},
citeulike-linkout-0 = {http://dx.doi.org/10.1007/978-1-4419-7964-3\_5},
citeulike-linkout-1 = {http://www.springerlink.com/content/w823q330u8j22302},
doi = {10.1007/978-1-4419-7964-3\_5},
editor = {Dubitzky, Werner and Southgate, Jennifer and Fu{\ss}, Hendrik},
interhash = {4cb079c5956a461fca055a476ee79cbb},
intrahash = {21371d1c5f9b49639d6f1f73c86c5a24},
isbn = {978-1-4419-7963-6},
keywords = {myown review systems\_biology tuberculosis},
pages = {83--110},
posted-at = {2011-01-20 07:08:12},
priority = {2},
publisher = {Springer New York},
timestamp = {2019-02-10T16:15:28.000+0100},
title = {Systems Biology of Tuberculosis: Insights for Drug Discovery},
url = {http://dx.doi.org/10.1007/978-1-4419-7964-3\_5},
year = 2011
}