Efficient Algorithms for Detecting Signaling Pathways in Protein Interaction Networks

  • Jacob Scott
  • Trey Ideker
  • Richard M. Karp
  • Roded Sharan
Part of the Lecture Notes in Computer Science book series (LNCS, volume 3500)


The interpretation of large-scale protein network data depends on our ability to identify significant sub-structures in the data, a computationally intensive task. Here we adapt and extend efficient techniques for finding paths in graphs to the problem of identifying pathways in protein interaction networks. We present linear-time algorithms for finding paths in networks under several biologically-motivated constraints. We apply our methodology to search for protein pathways in the yeast protein-protein interaction network. We demonstrate that our algorithm is capable of reconstructing known signaling pathways and identifying functionally enriched paths in an unsupervised manner. The algorithm is very efficient, computing optimal paths of length 8 within minutes and paths of length 10 in less than two hours.


Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.


  1. 1.
    Kelley, B., Sharan, R., Karp, R., et al.: Conserved pathways within bacteria and yeast as revealed by global protein network alignment. Proc. Natl. Acad. Sci. USA 100, 11394–11399 (2003)CrossRefGoogle Scholar
  2. 2.
    Steffen, M., Petti, A., Aach, J., D’haeseleer, P., Church, G.: Automated modelling of signal transduction networks. BMC Bioinformatics 3, 34–44 (2002)CrossRefGoogle Scholar
  3. 3.
    Alon, N., Yuster, R., Zwick, U.: Color-coding. J. ACM 42, 844–856 (1995)MATHCrossRefMathSciNetGoogle Scholar
  4. 4.
    Deng, M., Sun, F., Chen, T.: Assessment of the reliability of protein-protein interactions and protein function prediction. In: Proceedings of the Eighth Pacific Symposium on Biocomputing, pp. 140–151 (2003)Google Scholar
  5. 5.
    Bader, J., Chaudhuri, A., Rothberg, J., Chant, J.: Gaining confidence in high-throughput protein interaction networks. Nature Biotechnol., 78–85 (2004)Google Scholar
  6. 6.
    von Mering, C., et al.: Comparative assessment of large-scale data sets of protein-protein interactions. Nature 417, 399–403 (2002)CrossRefGoogle Scholar
  7. 7.
    Sharan, R., Suthram, S., Kelley, R., Kuhn, T., McCuine, S., Uetz, P., Sittler, T., Karp, R., Ideker, T.: Conserved patterns of protein interaction in multiple species. Proc. Natl. Acad. Sci. USA (2005) (in press)Google Scholar
  8. 8.
    Gollub, J., Ball, C., Binkley, G., Demeter, J., Finkelstein, D., Hebert, J., Hernandez-Boussard, T., Jin, H., Kaloper, M., Matese, J., et al.: The stanford microarray database: data access and quality assessment tools. Nucleic Acids Res. 31, 94–96 (2003)CrossRefGoogle Scholar
  9. 9.
    Goldberg, D., et al.: Assessing experimentally derived interactions in a small world. Proc. Natl. Acad. Sci. USA 100, 4372–4376 (2003)MATHCrossRefMathSciNetGoogle Scholar
  10. 10.
    Mewes, H., Amid, C., Arnold, R., Frishman, D., Guldener, U., Mannhaupt, G., Munsterkotter, M., Pagel, P., Strack, N., Stumpflen, V., et al.: MIPS: analysis and annotation of proteins from whole genomes. Nucleic Acids Res. 32, D41–D44 (2004)Google Scholar
  11. 11.
    The Gene Ontology Consortium: Gene ontology: Tool for the unification of biology. Nature Genetics 25, 25–29 (2000)Google Scholar
  12. 12.
    Xenarios, I., et al.: DIP, the database of interacting proteins: a research tool for studying cellular networks of protein interactions. Nucleic Acids Res. 30, 303–305 (2002)CrossRefGoogle Scholar
  13. 13.
    Roberts, C., et al.: Signaling and circuitry of multiple MAPK pathways revealed by a matrix of global gene expression profiles. Science 287, 873–880 (2000)CrossRefGoogle Scholar

Copyright information

© Springer-Verlag Berlin Heidelberg 2005

Authors and Affiliations

  • Jacob Scott
    • 1
  • Trey Ideker
    • 2
  • Richard M. Karp
    • 3
  • Roded Sharan
    • 4
  1. 1.Computer Science DivisionU. C. BerkeleyBerkeleyUSA
  2. 2.Dept. of BioengineeringU. C. San DiegoLa JollaUSA
  3. 3.International Computer Science InstituteBerkeleyUSA
  4. 4.School of Computer ScienceTel-Aviv UniversityTel-AvivIsrael

Personalised recommendations