Efficient algorithms for finding maximum matching in graphs
ACM Computing Surveys (CSUR)
Uniform Techniques for Deriving Similarities of Objects and Subschemes in Heterogeneous Databases
IEEE Transactions on Knowledge and Data Engineering
PIVOT: Protein Interacions VisualizatiOn Tool
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
BioTRON: a biological workflow management system
Proceedings of the 2011 ACM Symposium on Applied Computing
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We describe a method to search for similarities across protein-protein interaction networks of different organisms. The technique core consists in computing a maximum weight matching of bipartite graphs resulting from comparing the neighbourhoods of proteins belonging to different networks. Both quantitative and reliability information are exploited. We tested the method on the networks of S. cerevisiae, D. melanogaster and C. elegans. The experiments showed that the technique is able to detect functional orthologs when the sole sequence similarity does not prove itself sufficient. They also demonstrated the capability of our approach in discovering common biological processes involving uncharacterised proteins.