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Aligning Biomolecular Networks Using Modular Graph Kernels

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Algorithms in Bioinformatics (WABI 2009)

Part of the book series: Lecture Notes in Computer Science ((LNBI,volume 5724))

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Abstract

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.

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Author information

Authors and Affiliations

  1. Bioinformatics and Computational Biology Graduate Program, USA

    Fadi Towfic, M. Heather West Greenlee & Vasant Honavar

  2. Department of Computer Science, USA

    Fadi Towfic & Vasant Honavar

  3. Department of Biomedical Sciences, Iowa State University, Ames, IA, USA

    M. Heather West Greenlee

Authors
  1. Fadi Towfic
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  2. M. Heather West Greenlee
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  3. Vasant Honavar
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Editor information

Editors and Affiliations

  1. Center for Bioinformatics and Computational Biology, and Department of Computer Science, University of Maryland, MD, College Park, USA

    Steven L. Salzberg

  2. Department of Computer Sciences, The University of Texas at Austin, TX, USA

    Tandy Warnow

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© 2009 Springer-Verlag Berlin Heidelberg

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Towfic, F., Greenlee, M.H.W., Honavar, V. (2009). Aligning Biomolecular Networks Using Modular Graph Kernels. In: Salzberg, S.L., Warnow, T. (eds) Algorithms in Bioinformatics. WABI 2009. Lecture Notes in Computer Science(), vol 5724. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-04241-6_29

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  • DOI: https://doi.org/10.1007/978-3-642-04241-6_29

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-642-04240-9

  • Online ISBN: 978-3-642-04241-6

  • eBook Packages: Computer ScienceComputer Science (R0)

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