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Issue 7, 2013
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Social networks to biological networks: systems biology of Mycobacterium tuberculosis

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Abstract

Contextualizing relevant information to construct a network that represents a given biological process presents a fundamental challenge in the network science of biology. The quality of network for the organism of interest is critically dependent on the extent of functional annotation of its genome. Mostly the automated annotation pipelines do not account for unstructured information present in volumes of literature and hence large fraction of genome remains poorly annotated. However, if used, this information could substantially enhance the functional annotation of a genome, aiding the development of a more comprehensive network. Mining unstructured information buried in volumes of literature often requires manual intervention to a great extent and thus becomes a bottleneck for most of the automated pipelines. In this review, we discuss the potential of scientific social networking as a solution for systematic manual mining of data. Focusing on Mycobacterium tuberculosis, as a case study, we discuss our open innovative approach for the functional annotation of its genome. Furthermore, we highlight the strength of such collated structured data in the context of drug target prediction based on systems level analysis of pathogen.

Graphical abstract: Social networks to biological networks: systems biology of Mycobacterium tuberculosis

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Publication details

The article was received on 29 Nov 2012, accepted on 18 Mar 2013 and first published on 21 Mar 2013


Article type: Review Article
DOI: 10.1039/C3MB25546H
Citation: Mol. BioSyst., 2013,9, 1584-1593
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    Social networks to biological networks: systems biology of Mycobacterium tuberculosis

    R. Vashisht, A. Bhardwaj, OSDD Consortium and S. K. Brahmachari, Mol. BioSyst., 2013, 9, 1584
    DOI: 10.1039/C3MB25546H

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