Year: 2012
Type: book-chapter
Abstract: Will-be-set-by-IN-TECH(possible interaction sites) by multiple sequence alignments within each protein group.Thus, those conserved motifs can be paired with motifs identified from other protein groups to model protein interaction sites.One of the novel aspects of the algorithm in (Li et al., 2006) is that it combines two types of data: the PPI data and the associated sequence data for modeling binding motif pairs.Each protein in the above PPI networks is represented by a vertex and every interaction between two proteins is represented by an edge.Discovering complete bipartite subgraphs in PPI networks can thus be formulated as the following biclique problem: Given a graph, the biclique problem is to find a subgraph which is bipartite and complete.The objective is to maximize the number of vertices or edges in the bipartite complete subgraph.We note that the maximum vertex biclique problem is polynomial time solvable (Yannakakis, 1981).This problem is also equivalent to the maximum independent set problem on bipartite graphs which is known to be solvable by a minimum cut algorithm.However, the maximum vertex balanced biclique problem is NP-hard (Garey & Johnson, 1979).The maximum edge biclique problem is proved to be NP-hard as well (Peeters, 2003).In this paper, we consider incompleteness of biological data, as the interaction data of PPI networks is usually not fully available.On the other hand, within an interacting protein group pair, some proteins in one group may only interact with a proportion of the proteins in the other group.Therefore, many subgraphs formed by interacting protein group pairs are not perfect bicliques.They are more often near complete bipartite subgraphs.Therefore, methods of finding bicliques may miss many useful interacting protein group pairs.To deal with this problem, we use quasi-bicliques instead of bicliques to find interacting protein group pairs.With the quasi-biclique, even though some interactions are missing in a protein interaction subnetwork, we can still find the two interacting protein groups.In this paper, we introduce and investigate the maximum vertex quasi-biclique problem.We show that the problem is NP-hard.We also propose approximation and heuristic algorithms for finding large quasi-bicliques in PPI networks.The applications for finding protein-protein binding sites are illustrated.
Source: IntechOpen eBooks
DOI: 10.5772/38293
Author: Lusheng Wang
Institution: City University of Hong Kong
Language: English
Subfield: Molecular Biology
Domain: Life Sciences
Open Access status: hybrid
OpenAlex ID: W1525652667