TITLE

Exploring biological interaction networks with tailored weighted quasi-bicliques

AUTHOR(S)
Wen-Chieh Chang; Vakati, Sudheer; Krause, Roland; Eulenstein, Oliver
PUB. DATE
January 2012
SOURCE
BMC Bioinformatics;2012, Vol. 13 Issue Suppl 10, p1
SOURCE TYPE
Academic Journal
DOC. TYPE
Article
ABSTRACT
Background: Biological networks provide fundamental insights into the functional characterization of genes and their products, the characterization of DNA-protein interactions, the identification of regulatory mechanisms, and other biological tasks. Due to the experimental and biological complexity, their computational exploitation faces many algorithmic challenges. Results: We introduce novel weighted quasi-biclique problems to identify functional modules in biological networks when represented by bipartite graphs. In difference to previous quasi-biclique problems, we include biological interaction levels by using edge-weighted quasi-bicliques. While we prove that our problems are NPhard, we also describe IP formulations to compute exact solutions for moderately sized networks. Conclusions: We verify the effectiveness of our IP solutions using both simulation and empirical data. The simulation shows high quasi-biclique recall rates, and the empirical data corroborate the abilities of our weighted quasi-bicliques in extracting features and recovering missing interactions from biological networks.
ACCESSION #
77916583

 

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