Aligning Biomolecular Networks Using Modular Graph Kernels

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...

• Type: Conference
• Year: 2009
• Where: WABI
• Authors: Fadi Towfic, M. Heather West Greenlee, Vasant Honavar
• Keywords: Algorithms, Biomolecular Network, Large Biomolecular Networks, Protein-protein Interaction Networks, WABI 2009