Reference : Exploring biological interaction networks with tailored weighted quasi-bicliques.
Scientific journals : Article
Life sciences : Multidisciplinary, general & others
Exploring biological interaction networks with tailored weighted quasi-bicliques.
Chang, Wen-Chieh [> >]
Vakati, Sudheer [> >]
Krause, Roland mailto [University of Luxembourg > Luxembourg Centre for Systems Biomedicine (LCSB) > >]
Eulenstein, Oliver [> >]
BMC Bioinformatics
13 Suppl 10
Yes (verified by ORBilu)
[en] bioinformatics
[en] 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 NP-hard, 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.
Researchers ; Professionals

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