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

 

Share

Read the Article

Courtesy of THE LIBRARY OF VIRGINIA

Sorry, but this item is not currently available from your library.

Try another library?
Sign out of this library

Other Topics