Paper Info
Title
A fast iterative-clique percolation method for identifying functional modules in protein interaction networks
Abstract
Accumulating evidence suggests that biological systems are composed of interacting, separable, functional modules-groups of vertices within which connections are dense but between which they are sparse. Identifying these modules is likely through capturing the biologically meaningful interactions. In recent years, many algorithms have been developed for detecting such structures. These algorithms, however, are computationally demanding, which limits their applications. In this paper, we propose a fast iterative-clique percolation method (ICPM) for identifying overlapping functional modules in protein-protein interaction (PPI) networks. Our method is based on clique percolation method (CPM), and it not only considers the degree of nodes to minimize the search space (the vertices in k-cliques must have the degree of k − 1 at least), but also converts k-cliques to (k − 1)-cliques. It finds k-cliques by appending one node to (k − 1)-cliques. By testing our method on PPI networks, our analysis of the yeast PPI network suggests that most of these modules have well-supported biological significance.
Year
DOI
Venue
2009
10.1007/s11704-009-0048-9
Frontiers of Computer Science in China
Keywords
DocType
Volume
iterative-clique percolation method (ICPM),clique percolation method (CPM),functional modules,protein-protein interaction (PPI)
Journal
3
Issue
ISSN
Citations 
3
16737466
2
PageRank 
References 
Authors
0.37
6
2
Name
Order
Citations
PageRank
Peng Gang Sun1997.76
Lin Gao213729.86