Algorithm 447: efficient algorithms for graph manipulation
Communications of the ACM
Functional topology in a network of protein interactions
Bioinformatics
Pairwise global alignment of protein interaction networks by matching neighborhood topology
RECOMB'07 Proceedings of the 11th annual international conference on Research in computational molecular biology
Divide, align and full-search for discovering conserved protein complexes
EvoBIO'08 Proceedings of the 6th European conference on Evolutionary computation, machine learning and data mining in bioinformatics
Multilevel algorithms for partitioning power-law graphs
IPDPS'06 Proceedings of the 20th international conference on Parallel and distributed processing
Improving functional modularity in protein-protein interactions graphs using hub-induced subgraphs
PKDD'06 Proceedings of the 10th European conference on Principle and Practice of Knowledge Discovery in Databases
Pairwise local alignment of protein interaction networks guided by models of evolution
RECOMB'05 Proceedings of the 9th Annual international conference on Research in Computational Molecular Biology
Dividing protein interaction networks for modular network comparative analysis
Pattern Recognition Letters
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The increasing growth of data on protein-protein interaction (PPI) networks has boosted research on their comparative analysis. In particular, recent studies proposed models and algorithms for performing network alignment, the comparison of networks across species for discovering conserved modules. Common approaches for this task construct a merged representation of the considered networks, called alignment graph, and search the alignment graph for conserved networks of interest using greedy techniques. In this paper we propose a modular approach to this task. First, each network to be compared is divided into small subnets which are likely to contain conserved modules. To this aim, we develop an algorithm for dividing PPI networks that combines a graph theoretical property(articulation) with a biological one (orthology). Next, network alignment is performed on pairs of resulting subnets from different species. We tackle this task by means of a state-of-the-art alignment graph model for constructing alignment graphs, and an exact algorithm for searching in the alignment graph. Results of experiments show the ability of this approach to discover accurate conserved modules, and substantiate the importance of the notions of orthology and articulation for performing comparative network analysis in a modular fashion.