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Differential dependency network analysis to identify condition-specific topological changes in biological networks
Author(s) -
Bai Zhang,
Huai Li,
Rebecca B. Riggins,
Ming Zhan,
Jianhua Xuan,
Zhen Zhang,
Eric P. Hoffman,
Robert Clarke,
Yue Wang
Publication year - 2008
Publication title -
bioinformatics
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 3.599
H-Index - 390
eISSN - 1367-4811
pISSN - 1367-4803
DOI - 10.1093/bioinformatics/btn660
Subject(s) - gene regulatory network , biological network , computer science , dependency (uml) , network topology , network analysis , systems biology , computational biology , biology , gene , artificial intelligence , genetics , gene expression , quantum mechanics , operating system , physics
Significant efforts have been made to acquire data under different conditions and to construct static networks that can explain various gene regulation mechanisms. However, gene regulatory networks are dynamic and condition-specific; under different conditions, networks exhibit different regulation patterns accompanied by different transcriptional network topologies. Thus, an investigation on the topological changes in transcriptional networks can facilitate the understanding of cell development or provide novel insights into the pathophysiology of certain diseases, and help identify the key genetic players that could serve as biomarkers or drug targets.

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