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Multiple Alignment of Biological Networks: A Flexible Approach

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Part of the book series: Lecture Notes in Computer Science ((LNTCS,volume 5577))

Abstract

Recent experimental progress is once again producing a huge quantity of data in various areas of biology, in particular on protein interactions. In order to extract meaningful information from this data, researchers typically use a graph representation to which they apply network alignment tools. Because of the combinatorial difficulty of the network alignment problem, most of the algorithms developed so far are heuristics, and the exact ones are of no use in practice on large numbers of networks. In this paper, we propose a unified scheme on the question of network alignment and we present a new algorithm, C3Part-M, based on the work by Boyer et al. [2], that is much more efficient than the original one in the case of multiple networks. We compare it as concerns protein-protein interaction networks to a recently proposed alignment tool, NetworkBLAST-M [10], and show that we recover similar results, while using a different but exact approach.

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References

  1. Babu, M.M., Luscombe, N.M., Aravind, L., Gerstein, M., Teichmann, S.A.: Structure and evolution of transcriptional regulatory networks. Curr. Opin. Struct. Biol. 14(3), 283–291 (2004)

    Article  Google Scholar 

  2. Boyer, F., Morgat, A., Labarre, L., Pothier, J., Viari, A.: Syntons, metabolons and interactons: an exact graph-theoretical approach for exploring neighbourhood between genomic and functional data. Bioinformatics 21(23), 4209–4215 (2005)

    Article  Google Scholar 

  3. Cootes, A.P., Muggleton, S.H., Sternberg, M.J.: The identification of similarities between biological networks: Application to the metabolome and interactome. Journal of Molecular Biology 369(4), 1126–1139 (2007)

    Article  Google Scholar 

  4. Denielou, Y.-P., Boyer, F., Sagot, M.-F., Viari, A.: Recovering isofunctional genes: a synteny-based approach. In: JOBIM, pp. 11–16 (2008)

    Google Scholar 

  5. Dutkowsky, J., Tiuryn, J.: Identification of functional modules from conserved ancestral protein protein interactions. Bioinformatics 23(13) (2007)

    Google Scholar 

  6. Flannick, J.A., Novak, A.F., Do, C.B., Srinivasan, B.S., Batzoglou, S.: Automatic parameter learning for multiple network alignment. In: Vingron, M., Wong, L. (eds.) RECOMB 2008. LNCS (LNBI), vol. 4955, pp. 214–231. Springer, Heidelberg (2008)

    Chapter  Google Scholar 

  7. Flannick, J., Novak, A., Srinivasan, B.S., McAdams, H.H., Batzoglou, S.: Græmlin: general and robust alignment of multiple large interaction networks. Genome Res. 16(9), 1169–1181 (2006)

    Article  Google Scholar 

  8. Gai, A.T., Habib, M., Paul, C., Raffinot, M.: Identifying Common Connected Components of Graphs. Technical report, LIRMM (2003)

    Google Scholar 

  9. Habib, M., Paul, C., Raffinot, M.: Maximal Common Connected Sets of Interval Graphs. In: Sahinalp, S.C., Muthukrishnan, S.M., Dogrusoz, U. (eds.) CPM 2004. LNCS, vol. 3109, pp. 347–358. Springer, Heidelberg (2004)

    Chapter  Google Scholar 

  10. Kalaev, M., Bafna, V., Sharan, R.: Fast and accurate alignment of multiple protein networks. In: Vingron, M., Wong, L. (eds.) RECOMB 2008. LNCS (LNBI), vol. 4955, pp. 246–256. Springer, Heidelberg (2008)

    Chapter  Google Scholar 

  11. Kelley, B.P., Sharan, R., Karp, R.M., Sittler, T., Root, D.E., Stockwell, B.R., Ideker, T.: Conserved pathways within bacteria and yeast as revealed by global protein network alignment. Proc. Natl. Acad. Sci. USA 100(20), 11394–11399 (2003)

    Article  Google Scholar 

  12. Koyutürk, M., Kim, Y., Topkara, U., Subramaniam, S., Szpankowski, W., Grama, A.: Pairwise alignment of protein interaction networks. J. Comput. Biol. 13(2), 182–199 (2006)

    Article  MathSciNet  Google Scholar 

  13. Papin, J.A., Price, N.D., Wiback, S.J., Fell, D.A., Palsson, B.O.: Metabolic pathways in the post-genome era. Trends Biochem. Sci. 28(5), 250–258 (2003)

    Article  Google Scholar 

  14. Pasek, S., Bergeron, A., Risler, J.L., Louis, A., Ollivier, E., Raffinot, M.: Identification of genomic features using microsyntenies of domains: Domain teams. Genome Res (2005)

    Google Scholar 

  15. Sharan, R., Ideker, T., Kelley, B., Shamir, R., Karp, R.M.: Identification of protein complexes by comparative analysis of yeast and bacterial protein interaction data. J. Comput. Biol. 12(6), 835–846 (2005)

    Article  Google Scholar 

  16. Sharan, R., Suthram, S., Kelley, R.M., Kuhn, T., McCuine, S., Uetz, P., Sittler, T., Karp, R.M., Ideker, T.: From the cover: Conserved patterns of protein interaction in multiple species. Proc. Natl. Acad. Sci. USA 102(6), 1974–1979 (2005)

    Article  Google Scholar 

  17. Singh, R., Xu, J., Berger, B.: Pairwise global alignment of protein interaction networks by matching neighborhood topology. In: Speed, T., Huang, H. (eds.) RECOMB 2007. LNCS (LNBI), vol. 4453, pp. 16–31. Springer, Heidelberg (2007)

    Chapter  Google Scholar 

  18. Singh, R., Xu, J., Berger, B.: Global alignment of multiple protein interaction networks with application to functional orthology detection. Proceedings of the National Academy of Sciences 105(35), 12763–12768 (2008)

    Article  Google Scholar 

  19. Srinivasan, B.S., Novak, A.F., Flannick, J.A., Batzoglou, S., McAdams, H.H.: Integrated protein interaction networks for 11 microbes. In: Apostolico, A., Guerra, C., Istrail, S., Pevzner, P.A., Waterman, M. (eds.) RECOMB 2006. LNCS (LNBI), vol. 3909, pp. 1–14. Springer, Heidelberg (2006)

    Chapter  Google Scholar 

  20. Tian, W., Samatova, N.F.: Pairwise alignment of interaction networks by fast identification of maximal conserved patterns. In: PSB 2009, pp. 99–110 (2009)

    Google Scholar 

  21. Tucker, C.L., Gera, J.F., Uetz, P.: Towards an understanding of complex protein networks. Trends in Cell Biology 11(3), 102–106 (2001)

    Article  Google Scholar 

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Deniélou, YP., Boyer, F., Viari, A., Sagot, MF. (2009). Multiple Alignment of Biological Networks: A Flexible Approach. In: Kucherov, G., Ukkonen, E. (eds) Combinatorial Pattern Matching. CPM 2009. Lecture Notes in Computer Science, vol 5577. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-02441-2_23

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  • DOI: https://doi.org/10.1007/978-3-642-02441-2_23

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-642-02440-5

  • Online ISBN: 978-3-642-02441-2

  • eBook Packages: Computer ScienceComputer Science (R0)

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