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The Transcriptional Regulatory Network of Mycobacterium tuberculosis
Author(s) -
Joaquín Sanz,
Jorge Navarro,
Ainhoa Arbués,
Carlos Martı́n,
Pedro C. Marijuán,
Yamir Moreno
Publication year - 2011
Publication title -
plos one
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.99
H-Index - 332
ISSN - 1932-6203
DOI - 10.1371/journal.pone.0022178
Subject(s) - computational biology , gene regulatory network , mycobacterium tuberculosis , function (biology) , systems biology , context (archaeology) , transcriptional regulation , data science , regulation of gene expression , network analysis , biology , interaction network , computer science , gene , genetics , tuberculosis , gene expression , medicine , paleontology , physics , pathology , quantum mechanics
Under the perspectives of network science and systems biology, the characterization of transcriptional regulatory (TR) networks beyond the context of model organisms offers a versatile tool whose potential remains yet mainly unexplored. In this work, we present an updated version of the TR network of Mycobacterium tuberculosis ( M.tb ), which incorporates newly characterized transcriptional regulations coming from 31 recent, different experimental works available in the literature. As a result of the incorporation of these data, the new network doubles the size of previous data collections, incorporating more than a third of the entire genome of the bacterium. We also present an exhaustive topological analysis of the new assembled network, focusing on the statistical characterization of motifs significances and the comparison with other model organisms. The expanded M.tb transcriptional regulatory network, considering its volume and completeness, constitutes an important resource for diverse tasks such as dynamic modeling of gene expression and signaling processes, computational reliability determination or protein function prediction, being the latter of particular relevance, given that the function of only a small percent of the proteins of M.tb is known.

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