Aligning biomolecular networks using modular graph kernels

Fadi Towfic, M. Heather West Greenlee, Vasant Honavar

Research output: Chapter in Book/Report/Conference proceedingConference contribution

18 Scopus citations


Comparative analysis of biomolecular networks constructed using measurements from different conditions, tissues, and organisms offer a powerful approach to understanding the structure, function, dynamics, and evolution of complex biological systems. We explore a class of algorithms for aligning large biomolecular networks by breaking down such networks into subgraphs and computing the alignment of the networks based on the alignment of their subgraphs. The resulting subnetworks are compared using graph kernels as scoring functions. We provide implementations of the resulting algorithms as part of BiNA, an open source biomolecular network alignment toolkit. Our experiments using Drosophila melanogaster, Saccharomyces cerevisiae, Mus musculus and Homo sapiens protein-protein interaction networks extracted from the DIP repository of protein-protein interaction data demonstrate that the performance of the proposed algorithms (as measured by % GO term enrichment of subnetworks identified by the alignment) is competitive with some of the state-of-the-art algorithms for pair-wise alignment of large protein-protein interaction networks. Our results also show that the inter-species similarity scores computed based on graph kernels can be used to cluster the species into a species tree that is consistent with the known phylogenetic relationships among the species.

Original languageEnglish (US)
Title of host publicationAlgorithms in Bioinformatics - 9th International Workshop, WABI 2009, Proceedings
Number of pages17
StatePublished - 2009
Event9th International Workshop on Algorithms in Bioinformatics, WABI 2009 - Philadelphia, PA, United States
Duration: Sep 12 2009Sep 13 2009

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume5724 LNBI
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349


Other9th International Workshop on Algorithms in Bioinformatics, WABI 2009
Country/TerritoryUnited States
CityPhiladelphia, PA

All Science Journal Classification (ASJC) codes

  • Theoretical Computer Science
  • General Computer Science


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