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Annual International Conference on Research in Computational Molecular Biology

RECOMB 2005: Research in Computational Molecular Biology pp 48–65Cite as

Pairwise Local Alignment of Protein Interaction Networks Guided by Models of Evolution

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Part of the book series: Lecture Notes in Computer Science ((LNBI,volume 3500))

Abstract

With ever increasing amount of available data on protein-protein interaction (PPI) networks and research revealing that these networks evolve at a modular level, discovery of conserved patterns in these networks becomes an important problem. Recent algorithms on aligning PPI networks target simplified structures such as conserved pathways to render these problems computationally tractable. However, since conserved structures that are parts of functional modules and protein complexes generally correspond to dense subnets of the network, algorithms that are able to extract conserved patterns in terms of general graphs are necessary. With this motivation, we focus here on discovering protein sets that induce subnets that are highly conserved in the interactome of a pair of species. For this purpose, we develop a framework that formally defines the pairwise local alignment problem for PPI networks, models the problem as a graph optimization problem, and presents fast algorithms for this problem. In order to capture the underlying biological processes correctly, we base our framework on duplication/divergence models that focus on understanding the evolution of PPI networks. Experimental results from an implementation of the proposed framework show that our algorithm is able to discover conserved interaction patterns very effectively (in terms of accuracies and computational cost). While we focus on pairwise local alignment of PPI networks in this paper, the proposed algorithm can be easily adapted to finding matches for a subnet query in a database of PPI networks.

This research was supported in part by NIH Grant R01 GM068959-01 and NSF Grant CCR-0208709.

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Author information

Authors and Affiliations

  1. Dept. of Computer Sciences, Purdue University, West Lafayette, IN, 47907, USA

    Mehmet Koyutürk, Ananth Grama & Wojciech Szpankowski

Authors
  1. Mehmet Koyutürk
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  2. Ananth Grama
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  3. Wojciech Szpankowski
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Editor information

Editors and Affiliations

  1. Human Genome Center, Institute of Medical Science, University of Tokyo, 4-6-1 Shirokanedai, 108-8639, Minato-ku, Tokyo, Japan

    Satoru Miyano

  2. Broad Institute of MIT and Harvard, 320 Charles Street, 02141-2023, Cambridge, MA, USA

    Jill Mesirov

  3. Computational Genomics Laboratory, Department of Bioengineering, Boston University, 44 Cummington St., 02215, Boston, MA, USA

    Simon Kasif

  4. Center for Molecular Biology and Computer Sciecne Department, Brown University, 115 Waterman St., 02912, Providence, RI, USA

    Sorin Istrail

  5. University of California, San Diego, USA

    Pavel A. Pevzner

  6. Department of Molecular and Computational Biology, University of Southern California, 1050 Childs Way, 90089-2910, Los Angeles, CA, USA

    Michael Waterman

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© 2005 Springer-Verlag Berlin Heidelberg

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Koyutürk, M., Grama, A., Szpankowski, W. (2005). Pairwise Local Alignment of Protein Interaction Networks Guided by Models of Evolution. In: Miyano, S., Mesirov, J., Kasif, S., Istrail, S., Pevzner, P.A., Waterman, M. (eds) Research in Computational Molecular Biology. RECOMB 2005. Lecture Notes in Computer Science(), vol 3500. Springer, Berlin, Heidelberg. https://doi.org/10.1007/11415770_4

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  • DOI: https://doi.org/10.1007/11415770_4

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-25866-7

  • Online ISBN: 978-3-540-31950-4

  • eBook Packages: Computer ScienceComputer Science (R0)

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