Skip to main content

Finding Exact and Maximum Occurrences of Protein Complexes in Protein-Protein Interaction Graphs

  • Conference paper

Part of the book series: Lecture Notes in Computer Science ((LNTCS,volume 3618))

Abstract

In the context of comparative analysis of protein-protein interaction graphs, we use a graph-based formalism to detect the preservation of a given protein complex G in the protein-protein interaction graph H of another species with respect to (w.r.t.) orthologous proteins. Two problems are considered: the Exact-(μ G , μ H )-Matching problem and the Max-(μ G , μ H ) problem, where μ G (resp. μ H ) denotes in both problems the maximum number of orthologous proteins in H (resp. G) of a protein in G (resp. H). Following [FLV04], the Exact-(μ G , μ H )-Matching problem asks for an injective homomorphism of G to H w.r.t. orthologous proteins. The optimization version is called the Max-(μ G , μ H )-Matching problem and is concerned with finding an injective mapping of a graph G to a graph H w.r.t. orthologous proteins that matches as many edges of G as possible. For both problems, the emphasis here is clearly on bounded degree graphs and extremal small values of parameters μ G and μ H .

This is a preview of subscription content, log in via an institution.

Buying options

Chapter
USD   29.95
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
eBook
USD   84.99
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book
USD   109.99
Price excludes VAT (USA)
  • Compact, lightweight edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info

Tax calculation will be finalised at checkout

Purchases are for personal use only

Learn about institutional subscriptions

Preview

Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.

References

  1. Ausiello, G., Crescenzi, P., Gambosi, G., Kann, V., Marchetti-Spaccamela, A., Protasi, M.: Complexity and Approximation: Combinatorial optimization problems and their approximability properties. Springer, Heidelberg (1999)

    MATH  Google Scholar 

  2. Akiyama, J., Exoo, G., Harary, F.: Covering and packing in graphs IV: Linear arboricity. Networks 11, 69–72 (1981)

    Article  MATH  MathSciNet  Google Scholar 

  3. Alber, J., Gramm, J., Guo, J., Niedermeier, R.: Towards optimally solving the LONGEST COMMON SUBSEQUENCE problem for sequences with nested arc annotations in linear time. In: Apostolico, A., Takeda, M. (eds.) CPM 2002. LNCS, vol. 2373, pp. 99–114. Springer, Heidelberg (2002)

    Chapter  Google Scholar 

  4. Alon, N.: The linear arboricity of graphs. Israel Journal of Mathematics 62(3), 311–325 (1988)

    Article  MATH  MathSciNet  Google Scholar 

  5. Alon, N., Spencer, J.H.: The probabilistic method. Wiley, Chichester (1992)

    MATH  Google Scholar 

  6. Bodlaender, H.L., Downey, R.G., Fellows, M.R., Hallett, M.T., Wareham, H.T.: Parameterized complexity analysis in computational biology. Computer Applications in the Biosciences 11, 49–57 (1995)

    Google Scholar 

  7. Berman, P., Karpinski, M.: On some tighter inapproximability results. In: Wiedermann, J., Van Emde Boas, P., Nielsen, M. (eds.) ICALP 1999. LNCS, vol. 1644, pp. 200–209. Springer, Heidelberg (1999)

    Chapter  Google Scholar 

  8. Downey, R., Fellows, M.: Parameterized complexity. Springer, Heidelberg (1999)

    Google Scholar 

  9. Fagnot, I., Lelandais, G., Vialette, S.: Bounded list injective homomorphism for comparative analysis of protein-protein interaction graphs. In: Proc. of the 1st Algorithms and Computational Methods for Biochemical and Evolutionary Networks (CompBioNets), pp. 45–70. KCL publications (2004)

    Google Scholar 

  10. Gavin, A.C., Boshe, M., et al.: Functional organization of the yeast proteome by systematic analysis of protein complexes. Nature 414(6868), 141–147 (2002)

    Article  Google Scholar 

  11. Gramm, J., Guo, J., Niedermeier, R.: Pattern matching for arc-annotated sequences. In: Agrawal, M., Seth, A.K. (eds.) FSTTCS 2002. LNCS, vol. 2556, pp. 182–193. Springer, Heidelberg (2002)

    Chapter  Google Scholar 

  12. Garey, M.R., Johnson, D.S.: Computers and intractability: a guide to the theory of NP-completeness. W.H. Freeman, San Franciso (1979)

    MATH  Google Scholar 

  13. Ho, Y., al, A.G.e.: Systematic identification of protein complexes in Saccharomyces cerevisae by mass spectrometry. Nature 415(6868), 180–183 (2002)

    Article  Google Scholar 

  14. 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. PNAS 100(20), 11394–11399 (2003)

    Article  Google Scholar 

  15. Micali, S., Vazirani, V.V.: An \({O(\sqrt{|V|}|E|)}\) algorithm for finding maximum matching in general graphs. In: Proc. of the 21st Annual Symposium on Foundation of Computer Science (FOCS), pp. 17–27. IEEE, Los Alamitos (1980)

    Google Scholar 

  16. Pereira-Leal, J.B., Enright, A.J., Ouzounis, C.A.: Detection of functional modules from protein interaction networks. Proteins 54(1), 49–57 (2004)

    Article  Google Scholar 

  17. Pellegrini, M., Marcotte, E.M., Thompson, M.J., Eisenberg, D., Yeates, T.O.: Assigning protein functions by comparative genome analysis: protein phylogenetic profiles. PNAS 96(8), 4285–4288 (1999)

    Article  Google Scholar 

  18. 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. In: Proc. of the 8th annual international conference on Computational molecular biology (RECOMB 2004), pp. 282–289. ACM Press, New York (2004)

    Google Scholar 

  19. Sharan, R., Suthram, S., Kelley, R.M., Kuhn, T., McCuin, S., Uetz, P., Sittler, T., Karp, R., Ideker, T.: Conserved patterns of protein interaction in multiple species. PNAS 102(6), 1974–1979 (2005)

    Article  Google Scholar 

  20. Titz, B., Schlesner, M., Uetz, P.: What do we learn from high-throughput protein interaction data? Expert Review of Anticancer Therapy 1(1), 111–121 (2004)

    Google Scholar 

  21. Uetz, P., Giot, L., et al.: A comprehensive analysis of protein-protein interactions in Saccharomyces cerevisae. Nature 403(6770), 623–627 (2000)

    Article  Google Scholar 

Download references

Author information

Authors and Affiliations

Authors

Editor information

Editors and Affiliations

Rights and permissions

Reprints and permissions

Copyright information

© 2005 Springer-Verlag Berlin Heidelberg

About this paper

Cite this paper

Fertin, G., Rizzi, R., Vialette, S. (2005). Finding Exact and Maximum Occurrences of Protein Complexes in Protein-Protein Interaction Graphs. In: Jȩdrzejowicz, J., Szepietowski, A. (eds) Mathematical Foundations of Computer Science 2005. MFCS 2005. Lecture Notes in Computer Science, vol 3618. Springer, Berlin, Heidelberg. https://doi.org/10.1007/11549345_29

Download citation

  • DOI: https://doi.org/10.1007/11549345_29

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-28702-5

  • Online ISBN: 978-3-540-31867-5

  • eBook Packages: Computer ScienceComputer Science (R0)

Publish with us

Policies and ethics