Skip to main content

Quantifying Systemic Evolutionary Changes by Color Coding Confidence-Scored PPI Networks

  • Conference paper
Algorithms in Bioinformatics (WABI 2009)

Part of the book series: Lecture Notes in Computer Science ((LNBI,volume 5724))

Included in the following conference series:

Abstract

A current major challenge in systems biology is to compute statistics on biomolecular network motifs, since this can reveal significant systemic differences between organisms. We extend the “color coding” technique to weighted edge networks and apply it to PPI networks where edges are weighted by probabilistic confidence scores, as provided by the STRING database. This is a substantial improvement over the previously available studies on, still heavily noisy, binary-edge-weight data. Following up on such a study, we compute the expected number of occurrences of non-induced subtrees with k ≤ 9 vertices. Beyond the previously reported differences between unicellular and multicellular organisms, we reveal major differences between prokaryotes and unicellular eukaryotes. This establishes, for the first time on a statistically sound data basis, that evolutionary distance can be monitored in terms of elevated systemic arrangements.

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

Access this chapter

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

Institutional subscriptions

Preview

Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.

References

  1. Alon, N., Dao, P., Hajirasouliha, I., Hormozdiari, F., Sahinalp, S.C.: Biomolecular network motif counting and discovery by color coding. Bioinformatics 24(Supp. 1), i241–i249 (2008)

    Article  Google Scholar 

  2. Alon, N., Gutner, S.: Balanced families of perfect hash functions and their applications. In: Arge, L., Cachin, C., Jurdziński, T., Tarlecki, A. (eds.) ICALP 2007. LNCS, vol. 4596, pp. 435–446. Springer, Heidelberg (2007)

    Chapter  Google Scholar 

  3. Alon, N., Yuster, R., Zwick, U.: Color-coding. J. ACM 42(4), 844–856 (1995)

    Article  Google Scholar 

  4. Arvind, V., Raman, V.: Approximation algorithms for some parameterized counting problems. In: Bose, P., Morin, P. (eds.) ISAAC 2002. LNCS, vol. 2518, pp. 453–464. Springer, Heidelberg (2002)

    Chapter  Google Scholar 

  5. Bjorklund, A., Husfeldt, T., Kaski, P., Koivisto, M.: The fast intersection transform with applications to counting paths (2008), http://arxiv.org/abs/0809.2489

  6. Ciriello, G., Guerra, C.: A review on models and algorithms for motif discovery in protein-protein interaction networks. Briefings in Functional Genomics and Proteomics (2008)

    Google Scholar 

  7. Colak, R., Hormozdiari, F., Moser, F., Schönhuth, A., Holman, J., Sahinalp, S.C., Ester, M.: Dense graphlet statistics of protein interaction and random networks. In: Proceedings of the Pacific Symposium on Biocomputing, vol. 14, pp. 178–189 (2009)

    Google Scholar 

  8. Dao, P., Schoenhuth, A., Hormozdiari, F., Hajirasouliha, I., Sahinalp, S.C., Ester, M.: Quantifying systemic evolutionary changes by color coding confidence-scored ppi networks. Supplementary Materials (2009), http://www.cs.sfu.ca/~pdao/personal/weightedmotifsup.pdf

  9. Dost, B., Shlomi, T., Gupta, N., Ruppin, E., Bafna, V., Sharan, R.: QNet: A tool for querying protein interaction networks. In: Speed, T., Huang, H. (eds.) RECOMB 2007. LNCS (LNBI), vol. 4453, pp. 1–15. Springer, Heidelberg (2007)

    Chapter  Google Scholar 

  10. Flum, J., Grohe, M.: The parameterized complexity of counting problems. SIAM J. Comput. 33, 892–922 (2004)

    Article  Google Scholar 

  11. Grochow, J.A., Kellis, M.: Network motif discovery using subgraph enumeration and symmetry-breaking. In: Speed, T., Huang, H. (eds.) RECOMB 2007. LNCS (LNBI), vol. 4453, pp. 92–106. Springer, Heidelberg (2007)

    Chapter  Google Scholar 

  12. Han, J., Dupuy, D., Bertin, N., Cusick, M., Vidal, M.: Effect of sampling on topology predictions of protein-protein interaction networks. Nature Biotech. 23, 839–844 (2005)

    Article  CAS  Google Scholar 

  13. Hormozdiari, F., Berenbrink, P., Przulj, N., Sahinalp, S.C.: Not all scale-free networks are born equal: The role of the seed graph in ppi network evolution. PLoS Comput. Biol. 3(7) (2007)

    Google Scholar 

  14. Huffner, F., Wernicke, S., Zichner, T.: Algorithm engineering for color coding with applications to signaling pathways. Algorithmica 52(2), 114–132 (2008)

    Article  Google Scholar 

  15. Jensen, L.J., Kuhn, M., Stark, M., Chaffron, S., Creevey, C., Muller, J., Doerke, T., Julien, P., Roth, A., Simonovic, M., Bork, P., von Mering, C.: String 8—a global view on proteins and their functional interactions in 630 organisms. Nucleic Acids Research 37(Database issue), D412–D416 (2009)

    Article  Google Scholar 

  16. Karp, R.M., Luby, M.: Monte-carlo algorithms for enumeration and reliability problems. In: FOCS, pp. 56–64 (1983)

    Google Scholar 

  17. Milo, R., Shen-Orr, S., Itzkovitz, S., Kashtan, N., Chklovskii, D., Alon, U.: Network motifs: simple building blocks of complex networks. Science 298(5594), 824–827 (2002)

    Article  CAS  PubMed  Google Scholar 

  18. University of Victoria. Combinatorial object server (since 1995), http://www.theory.csc.uvic.ca/~cos

  19. Przulj, N., Corneil, D.G., Jurisica, I.: Modeling interactome: scale-free or geometric? Bioinformatics 20(18), 3508–3515 (2004)

    Article  CAS  PubMed  Google Scholar 

  20. Scott, J., Ideker, T., Karp, R.M., Sharan, R.: Efficient algorithms for detecting signaling pathways in protein interaction networks. J. Comput. Biol. 13(2), 133–144 (2006)

    Article  CAS  PubMed  Google Scholar 

  21. Shlomi, T., Segal, D., Ruppin, E., Sharan, R.: Qpath: a method for querying pathways in a protein-protein interaction network. BMC Bioinformatics 7, 199 (2006)

    Article  PubMed  PubMed Central  Google Scholar 

  22. Ulitsky, I., Shamir, R.: Identifying functional modules using expression profiles and confidence-scored protein interactions. Bioinformatics (2009), doi:10.1093/bioinformatics/btp118

    Google Scholar 

  23. Vassilevska, V., Wiliams, R.: Finding, minimizing and counting weighted subgraphs. In: Proceedings of the Symposium of the Theory of Computing, STOC (to appear, 2009)

    Google Scholar 

  24. von Mering, C., Jensen, L.J.: News about the string and stitch databases (2008), http://string-stitch.blogspot.com/

  25. von Mering, C., Jensen, L.J., Snel, B., Hooper, S.D., Krupp, M., Foglierini, M., Jouffre, N., Huynen, M.A., Bork, P.: String: known and predicted protein-protein associations, integrated and transferred across organisms. Nucleic Acids Research 33(Database issue), D433–D437(2005)

    Article  Google Scholar 

  26. Zhu, X., Gerstein, M., Snyder, M.: Getting connected: analysis and principles of biological networks. Genes and Development 21, 1010–1024 (2007)

    Article  CAS  PubMed  Google Scholar 

Download references

Author information

Authors and Affiliations

Authors

Editor information

Editors and Affiliations

Rights and permissions

Reprints and permissions

Copyright information

© 2009 Springer-Verlag Berlin Heidelberg

About this paper

Cite this paper

Dao, P., Schönhuth, A., Hormozdiari, F., Hajirasouliha, I., Sahinalp, S.C., Ester, M. (2009). Quantifying Systemic Evolutionary Changes by Color Coding Confidence-Scored PPI Networks. In: Salzberg, S.L., Warnow, T. (eds) Algorithms in Bioinformatics. WABI 2009. Lecture Notes in Computer Science(), vol 5724. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-04241-6_4

Download citation

  • DOI: https://doi.org/10.1007/978-3-642-04241-6_4

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-642-04240-9

  • Online ISBN: 978-3-642-04241-6

  • eBook Packages: Computer ScienceComputer Science (R0)

Publish with us

Policies and ethics