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Mining large-scale response networks reveals `topmost activities' in Mycobacterium tuberculosis infection

Sambarey, Awanti and Prashanthi, Karyala and Chandra, Nagasuma (2013) Mining large-scale response networks reveals `topmost activities' in Mycobacterium tuberculosis infection. In: SCIENTIFIC REPORTS, 3 .

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Official URL: http://dx.doi.org/10.1038/srep02302

Abstract

Mycobacterium tuberculosis owes its high pathogenic potential to its ability to evade host immune responses and thrive inside the macrophage. The outcome of infection is largely determined by the cellular response comprising a multitude of molecular events. The complexity and inter-relatedness in the processes makes it essential to adopt systems approaches to study them. In this work, we construct a comprehensive network of infection-related processes in a human macrophage comprising 1888 proteins and 14,016 interactions. We then compute response networks based on available gene expression profiles corresponding to states of health, disease and drug treatment. We use a novel formulation for mining response networks that has led to identifying highest activities in the cell. Highest activity paths provide mechanistic insights into pathogenesis and response to treatment. The approach used here serves as a generic framework for mining dynamic changes in genome-scale protein interaction networks.

Item Type: Journal Article
Additional Information: Copyright of this article is belongs to NATURE PUBLISHING GROUP
Department/Centre: Division of Biological Sciences > Biochemistry
Division of Biological Sciences > Molecular Biophysics Unit
Depositing User: Id for Latest eprints
Date Deposited: 24 Sep 2013 07:28
Last Modified: 24 Sep 2013 07:28
URI: http://eprints.iisc.ac.in/id/eprint/47297

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