Skip to main content
SpringerLink
Log in
Book cover

International Symposium on Bioinformatics Research and Applications

ISBRA 2011: Bioinformatics Research and Applications pp 111–122Cite as

Algorithms to Detect Multiprotein Modularity Conserved during Evolution

  • Conference paper

Part of the book series: Lecture Notes in Computer Science ((LNBI,volume 6674))

Abstract

Detecting essential multiprotein modules that change infrequently during evolution is a challenging algorithmic task that is important for understanding the structure, function, and evolution of the biological cell. In this paper, we present a linear-time algorithm, Produles, that improves on the running time of previous algorithms. We present a biologically motivated graph theoretic set of algorithm goals complementary to previous evaluation measures, demonstrate that Produles attains these goals more comprehensively than previous algorithms, and exhibit certain recurrent anomalies in the performance of previous algorithms that are not detected by previous measures.

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

Chapter
USD   29.95
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
eBook
USD   39.99
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book
USD   54.99
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. Vidal, M.: Interactome modeling. FEBS Letters 579, 1834–1838 (2005)

    Article  Google Scholar 

  2. 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. 100(20), 11394–11399 (2003)

    Article  Google Scholar 

  3. Sharan, R., Suthram, S., Kelley, R.M., Kuhn, T., McCuine, S., Uetz, P., Sittler, T., Karp, R.M., Ideker, T.: Conserved patterns of protein interaction in multiple species. Proc. Natl. Acad. Sci. 102(6), 1947–1979 (2005)

    Article  Google Scholar 

  4. Koyutürk, M., Kim, Y., Topkara, U., Subramaniam, S., Szpankowski, W., Grama, A.: Pairwise alignment of protein interaction networks. Journal of Computational Biology 13(2), 182–199 (2006)

    Article  MathSciNet  Google Scholar 

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

    Article  Google Scholar 

  6. Narayanan, M., Karp, R.M.: Comparing protein interaction networks via a graph match-and-split algorithm. Journal of Computational Biology 14(7), 892–907 (2007)

    Article  Google Scholar 

  7. Beltrao, P., Serrano, L.: Specificity and evolvability in eukaryotic protein interaction networks. PLoS Computational Biology 3(2), e25 (2007)

    Article  Google Scholar 

  8. Altschul, S.F., Gish, W., Miller, W., Myers, E.W., Lipman, D.J.: Basic local alignment search tool. Journal of Molecular Biology 215(3), 403–410 (1990)

    Article  Google Scholar 

  9. Simon, H.A.: The structure of complexity in an evolving world: the role of near decomposability. In: Callebaut, W., Rasskin-Gutman, D. (eds.) Modularity: Understanding the Development and Evolution of Natural Complex Systems. Vienna Series in Theoretical Biology. MIT Press, Cambridge (2005)

    Google Scholar 

  10. Li, M., Wang, J., Chen, J., Pan, Y.: Hierarchical organization of functional modules in weighted protein interaction networks using clustering coefficient. In: Măndoiu, I., Narasimhan, G., Zhang, Y. (eds.) ISBRA 2009. LNCS (LNBI), vol. 5542, pp. 75–86. Springer, Heidelberg (2009)

    Chapter  Google Scholar 

  11. Andersen, R., Chung, F., Lang, K.: Local graph partitioning using PageRank vectors. In: 47th Annual IEEE Symposium on Foundations of Computer Science (FOCS 2006), pp. 475–486. IEEE Press, New York (2006)

    Chapter  Google Scholar 

  12. Voevodski, K., Teng, S., Xia, Y.: Finding local communities in protein networks. BMC Bioinformatics 10, 297 (2009)

    Article  Google Scholar 

  13. 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 

  14. Razick, S., Magklaras, G., Donaldson, I.M.: iRefIndex: a consolidated protein interaction database with provenance. BMC Bioinformatics 9, 405 (2008)

    Article  Google Scholar 

  15. Hodgkinson, L., Karp, R.M.: Algorithms to detect multi-protein modularity conserved during evolution. EECS Department, University of California, Berkeley, Technical Report UCB/EECS-2011-7 (2011)

    Google Scholar 

  16. Boyle, E.I., Weng, S., Gollub, J., Jin, H., Botstein, D., Cherry, J.M., Sherlock, G.: Go:termfinder—open source software for accessing gene ontology information and finding significantly enriched gene ontology terms associated with a list of genes. Bioinformatics 20(18), 3710–3715 (2004)

    Article  Google Scholar 

Download references

Author information

Authors and Affiliations

  1. Computer Science Division, University of California, Berkeley, USA

    Luqman Hodgkinson & Richard M. Karp

  2. Center for Computational Biology, University of California, Berkeley, USA

    Luqman Hodgkinson & Richard M. Karp

  3. International Computer Science Institute, USA

    Luqman Hodgkinson & Richard M. Karp

Authors
  1. Luqman Hodgkinson
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Richard M. Karp
    View author publications

    You can also search for this author in PubMed Google Scholar

Editor information

Editors and Affiliations

  1. Department of Computer Science and Engineering, Texas A&M University, 77843-3112, College Station, TX, USA

    Jianer Chen

  2. School of Information Science and Engineering, Central South University, 410083, Changsha, China

    Jianxin Wang

  3. Department of Computer Science, Georgia State University, 30303, Atlanta, GA, USA

    Alexander Zelikovsky

Rights and permissions

Reprints and permissions

Copyright information

© 2011 Springer-Verlag Berlin Heidelberg

About this paper

Cite this paper

Hodgkinson, L., Karp, R.M. (2011). Algorithms to Detect Multiprotein Modularity Conserved during Evolution. In: Chen, J., Wang, J., Zelikovsky, A. (eds) Bioinformatics Research and Applications. ISBRA 2011. Lecture Notes in Computer Science(), vol 6674. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-21260-4_14

Download citation

  • DOI: https://doi.org/10.1007/978-3-642-21260-4_14

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-642-21259-8

  • Online ISBN: 978-3-642-21260-4

  • eBook Packages: Computer ScienceComputer Science (R0)

Publish with us

Policies and ethics

Search

Navigation