Algorithm 447: efficient algorithms for graph manipulation
Communications of the ACM
Algorithm 457: finding all cliques of an undirected graph
Communications of the ACM
RECOMB '04 Proceedings of the eighth annual international conference on Resaerch in computational molecular biology
Functional topology in a network of protein interactions
Bioinformatics
Alignment of metabolic pathways
Bioinformatics
Dividing Protein Interaction Networks by Growing Orthologous Articulations
PRIB '08 Proceedings of the Third IAPR International Conference on Pattern Recognition in Bioinformatics
Fast Alignments of Metabolic Networks
BIBM '08 Proceedings of the 2008 IEEE International Conference on Bioinformatics and Biomedicine
Protein-Protein Interaction Network Alignment by Quantitative Simulation
BIBM '08 Proceedings of the 2008 IEEE International Conference on Bioinformatics and Biomedicine
Querying Protein-Protein Interaction Networks
ISBRA '09 Proceedings of the 5th International Symposium on Bioinformatics Research and Applications
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
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
Describing the orthology signal in a PPI network at a functional, complex level
ISBRA'11 Proceedings of the 7th international conference on Bioinformatics research and applications
Dense subgraph mining with a mixed graph model
Pattern Recognition Letters
| Hi-index | 0.10 |
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, that is, the comparison of networks across species for discovering conserved functional complexes. In this paper, we present an algorithm for dividing PPI networks, prior to their alignment, into small sub-graphs that are likely to cover conserved complexes. This allows one to perform network alignment in a modular fashion, by acting on pairs of resulting small sub-graphs from different species. The proposed dividing algorithm combines a graph-theoretical property (articulation) with a biological one (orthology). Extensive experiments on various PPI networks are conducted in order to assess how well the sub-graphs generated by this dividing algorithm cover protein functional complexes and whether the proposed pre-processing step can be used for enhancing the performance of network alignment algorithms. Source code of the dividing algorithm is available upon request for academic use.