Quasi-bicliques: Complexity and Binding Pairs

Authors:
Xiaowen Liu;Jinyan Li;Lusheng Wang
Affiliations:
Department of Computer Science, City University of Hong Kong, Kowloon, Hong Kong, and Department of Computer Science, University of Western Ontario, Canada;School of Computer Engineering, Nanyang Technological University, Singapore 639798;Department of Computer Science, City University of Hong Kong, Kowloon, Hong Kong,
Venue:
COCOON '08 Proceedings of the 14th annual international conference on Computing and Combinatorics
Year:
2008

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Abstract

Protein-protein interactions (PPIs) are one of the most important mechanisms in cellular processes. To model protein interaction sites, recent studies have suggested to find interacting protein group pairs from large PPI networks at the first step, and then to search conserved motifs within the protein groups to form interacting motif pairs. To consider noise effect and incompleteness of biological data, we propose to use quasi-bicliquesfor finding interacting protein group pairs. We investigate two new problems which arise from finding interacting protein group pairs: the maximum vertex quasi-biclique problem and the maximum balanced quasi-biclique problem. We prove that both problems are NP-hard. This is a surprising result as the widely known maximum vertex biclique problem is polynomial time solvable [16]. We then propose a heuristic algorithm which uses the greedy method to find the quasi-bicliques from PPI networks. Our experiment results on real data show that this algorithm has a better performance than a benchmark algorithm for identifying highly matched BLOCKS and PRINTS motifs.