Multiple Alignment of Biological Networks: A Flexible Approach

  • Yves-Pol Deniélou
  • Frédéric Boyer
  • Alain Viari
  • Marie-France Sagot
Part of the Lecture Notes in Computer Science book series (LNCS, volume 5577)


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.


multiple graph alignment biological network comparison protein-protein interactions 


Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.


  1. 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)CrossRefGoogle Scholar
  2. 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)CrossRefGoogle Scholar
  3. 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)CrossRefGoogle Scholar
  4. 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. 5.
    Dutkowsky, J., Tiuryn, J.: Identification of functional modules from conserved ancestral protein protein interactions. Bioinformatics 23(13) (2007)Google Scholar
  6. 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)CrossRefGoogle Scholar
  7. 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)CrossRefGoogle Scholar
  8. 8.
    Gai, A.T., Habib, M., Paul, C., Raffinot, M.: Identifying Common Connected Components of Graphs. Technical report, LIRMM (2003)Google Scholar
  9. 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)CrossRefGoogle Scholar
  10. 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)CrossRefGoogle Scholar
  11. 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)CrossRefGoogle Scholar
  12. 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)MathSciNetCrossRefGoogle Scholar
  13. 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)CrossRefGoogle Scholar
  14. 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. 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)CrossRefGoogle Scholar
  16. 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)CrossRefGoogle Scholar
  17. 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)CrossRefGoogle Scholar
  18. 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)CrossRefGoogle Scholar
  19. 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)CrossRefGoogle Scholar
  20. 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. 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)CrossRefGoogle Scholar

Copyright information

© Springer-Verlag Berlin Heidelberg 2009

Authors and Affiliations

  • Yves-Pol Deniélou
    • 1
  • Frédéric Boyer
    • 2
  • Alain Viari
    • 1
  • Marie-France Sagot
    • 1
  1. 1.projet BAMBOOINRIA Grenoble-Rhône-AlpesMontbonnot CedexFrance
  2. 2.CEA, iRTSV, Laboratoire Biologie, Informatique et MathématiquesGrenobleFrance

Personalised recommendations