ModuleAlign: module-based global alignment of protein–protein interaction networks

• DOI: 10.1093/bioinformatics/btw447
• Publication Date: 2016-09-01T07:53:39Z
• Authors: Somaye Hashemifar; Jianzhu Ma; Hammad Naveed; Stefan Canzar; Jinbo Xu
• Keywords: Persistent Homology; Smith–Waterman algorithm; Homology; Multiple sequence alignment

As an increasing amount of protein-protein interaction (PPI) data becomes available, their computational interpretation has become important problem in bioinformatics. The alignment PPI networks from different species provides valuable information about conserved subnetworks, evolutionary pathways and functional orthologs. Although several methods have been proposed for global network alignment, there is a pressing need that produce more accurate alignments terms both topological consistency.In this work, we present novel algorithm, named ModuleAlign, which makes use local topology to define module-based homology score. Based on hierarchical clustering functionally coherent proteins involved the same module, ModuleAlign employs iterative scheme find between two networks. Evaluated diverse set benchmarks, outperforms state-of-the-art producing consistent alignments. By aligning Pathogen-Human networks, also detects human genes pathogens preferentially target cause pathogenesis.http://ttic.uchicago.edu/∼hashemifar/[e-mail] or j3xu.ttic.eduSupplementary are available at Bioinformatics online.