Applications, Representation, and Management of Signaling Pathway Information: Introduction to the SigPath Project

  • Eliza Chan
  • Fabien Campagne


This chapter reviews current approaches for managing signaling pathway information. After a brief introduction to signaling pathways and their computational uses in support of biomedical research, the chapter covers the data representation paradigms currently used to store and compute information about signaling pathways. File formats, ontologies, and databases are considered and compared. The chapter includes a description of the SigPath project, which is an information management system for signaling pathway information.

Key Words

Information management signaling pathways ontology database information management system 


Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.


  1. 1.
    Max M, Shanker YG, Huang L, et al. Tas1r3, encoding a new candidate taste receptor, is allelic to the sweet responsiveness locus Sac. Nat Genet 2001;28(1):58–63.PubMedCrossRefGoogle Scholar
  2. 2.
    Cooper KE. Some historical perspectives on thermoregulation. J Appl Physiol 2002;92(4):1717–1724.PubMedGoogle Scholar
  3. 3.
    Stewart S, Guan KL. The dominant negative Ras mutant, N17Ras, can inhibit signaling independently of blocking Ras activation. J Biol Chem 2000; 275(12):8854–8862.PubMedCrossRefGoogle Scholar
  4. 4.
    Davis R, Szolovits P. What is Knowledge Representation? AI Magazine 1993;14(1):17–33.Google Scholar
  5. 5.
    Zeeberg BR, Feng W, Wang G, et al. GoMiner: a resource for biological interpretation of genomic and proteomic data. Genome Biol 2003;4(4): R28.PubMedCrossRefGoogle Scholar
  6. 6.
    Dennis G, Jr., Sherman BT, Hosack DA, et al. DAVID: Database for Annotation, Visualization, and Integrated Discovery. Genome Biol 2003;4(5):P3.PubMedCrossRefGoogle Scholar
  7. 7.
    Hosack DA, Dennis G, Jr., Sherman BT, Lane HC, Lempicki RA. Identifying biological themes within lists of genes with EASE. Genome Biol 2003;4(10): R70.PubMedCrossRefGoogle Scholar
  8. 8.
    Ford G, Xu Z, Gates A, Jiang J, Ford BD. Expression Analysis Systematic Explorer (EASE) analysis reveals differential gene expression in permanent and transient focal stroke rat models. Brain Res 2006;1071(1):226–236.PubMedCrossRefGoogle Scholar
  9. 9.
    Shen-Orr SS, Milo R, Mangan S, Alon U. Network motifs in the transcriptional regulation network of Escherichia coli. Nat Genet 2002;31(1):64–8.PubMedCrossRefGoogle Scholar
  10. 10.
    Artzy-Randrup Y, Fleishman SJ, Ben-Tal N, Stone L. Comment on “Network motifs: simple building blocks of complex networks” and “Superfamilies of evolved and designed networks.” Science 2004;305(5687):1107PubMedCrossRefGoogle Scholar
  11. 11.
    Albert R. Scale-free networks in cell biology. J Cell Sci 2005;118 (Pt 21): 4947–4957.PubMedCrossRefGoogle Scholar
  12. 12.
    Ma’ayan A, Jenkins SL, Neves S, et al. Formation of regulatory patterns during signal propagation in a Mammalian cellular network. Science 2005; 309(5737):1078–1083.CrossRefGoogle Scholar
  13. 13.
    Neves SR, Iyengar R. Modeling of signaling networks. Bioessays 2002; 24(12):1110–1117.PubMedCrossRefGoogle Scholar
  14. 14.
    von Dassow G, Meir E, Munro EM, Odell GM. The segment polarity network is a robust developmental module. Nature 2000;406(6792):188–192.CrossRefGoogle Scholar
  15. 15.
    Alon U, Surette MG, Barkai N, Leibler S. Robustness in bacterial chemotaxis. Nature 1999;397(6715):168–171.PubMedCrossRefGoogle Scholar
  16. 16.
    Urban S, Lee JR, Freeman M. A family of Rhomboid intramembrane proteases activates all Drosophila membrane-tethered EGF ligands. EMBO J 2002;21(16):4277–4286.PubMedCrossRefGoogle Scholar
  17. 17.
    Jenssen TK, Laegreid A, Komorowski J, Hovig E. A literature network of human genes for high-throughput analysis of gene expression. Nat Genet 2001;28(1):21–28.PubMedCrossRefGoogle Scholar
  18. 18.
    Friedman C, Kra P, Yu H, et al. GENIES: a natural-language processing system for the extraction of molecular pathways from journal articles. Bioinformatics 2001;17Suppl 1:S74–S82.PubMedGoogle Scholar
  19. 19.
    Shi L, Campagne F. Building a protein name dictionary from full text: a machine learning term extraction approach. BMC Bioinformatics 2005; 6(1):88.PubMedCrossRefGoogle Scholar
  20. 20.
    Peri S, Navarro JD, Amanchy R, et al. Development of human protein reference database as an initial platform for approaching systems biology in humans. Genome Res 2003;13(10):2363–2371.PubMedCrossRefGoogle Scholar
  21. 21.
    Mishra GR, Suresh M, Kumaran K, et al. Human protein reference database-2006 update. Nucleic Acids Res 2006;34 (Database issue):D411–D414.PubMedCrossRefGoogle Scholar
  22. 22.
    Kohn KW. Molecular interaction map of the mammalian cell cycle control and DNA repair systems. Mol Biol Cell 1999;10(8):2703–2734.PubMedGoogle Scholar
  23. 23.
    Kitano H, Funahashi A, Matsuoka Y, Oda K. Using process diagrams for the graphical representation of biological networks. Nat Biotechnol 2005;23(8):961–966.PubMedCrossRefGoogle Scholar
  24. 24.
    Cooper K, Torczon L. Engineering a Compiler. San Francisco: Morgan Kaufmann Publishers; 2004.Google Scholar
  25. 25.
    Hermjakob H, Montecchi-Palazzi L, Bader G, et al. The HUPO PSI’s molecular interaction format-a community standard for the representation of protein interaction data. Nat Biotechnol 2004;22(2):177–183.PubMedCrossRefGoogle Scholar
  26. 26.
    Lloyd CM, Halstead MD, Nielsen PF. CellML: its future, present and past. Prog Biophys Mol Biol 2004;85(2–3):433–450.Google Scholar
  27. 27.
    Finney A, Hucka M. Systems biology markup language: Level 2 and beyond. Biochem Soc Trans 2003;31 (Pt 6):1472–1473.PubMedGoogle Scholar
  28. 28.
    Gruber TR. A Translation Approach to Portable Ontology Specification. Knowledge Acquisition 1993;5:199–220.CrossRefGoogle Scholar
  29. 29.
    Harris MA, Clark J, Ireland A, et al. The Gene Ontology (GO) database and informatics resource. Nucleic Acids Res 2004;32 (Database issue):D258–D261.PubMedCrossRefGoogle Scholar
  30. 30.
    Keseler IM, Collado-Vides J, Gama-Castro S, et al. EcoCyc: a comprehensive database resource for Escherichia coli. Nucleic Acids Res 2005;33 Database Issue:D334–D337.PubMedCrossRefGoogle Scholar
  31. 31.
    Eilbeck K, Lewis SE, Mungall CJ, et al. The Sequence Ontology: a tool for the unification of genome annotations. Genome Biol 2005;6(5): R44.PubMedCrossRefGoogle Scholar
  32. 32.
    Noy NF, McGuinness DL. Ontology Development 101: A Guide to Creating Your First Ontology; 2001. Report No.: TR #SMI-2001-0880.Google Scholar
  33. 33.
    Skrabanek L, Campagne F. TissueInfo: high-throughput identification of tissue expression profiles and specificity. Nucleic Acids Res 2001;29(21): E102–E102.PubMedCrossRefGoogle Scholar
  34. 34.
    Campagne F, Neves S, Chang CW, et al. Quantitative information management for the biochemical computation of cellular networks. Sci STKE 2004;2004(248):l11.Google Scholar
  35. 35.
    Resource Description Framework (RDF) Schema Specification 1.0, Candidate recommendation, World Wide Web Consortium (Mar. 2000). URL 2000. (Accessed at Scholar
  36. 36.
    Dean M, Connolly D, van Harmelen F, et al. OWL web ontology language 1.0 reference, 2002.Google Scholar
  37. 37.
    Noy NF, Crubezy M, Fergerson RW, et al. Protege-2000: an open-source ontology-development and knowledge-acquisition environment. AMIA Annu Symp Proc 2003:953.Google Scholar
  38. 38.
    Stromback L, Lambrix P. Representations of molecular pathways: an evaluation of SBML, PSI MI and BioPAX. Bioinformatics 2005;21(24):4401–7.PubMedCrossRefGoogle Scholar
  39. 39.
    Srdanovic M, Schenk U, Schwieger M, Campagne F. Critical evaluation of the JDO API for the persistence and portability requirements of complex biological databases. BMC Bioinformatics 2005;6(1):5.PubMedCrossRefGoogle Scholar
  40. 40.
    Slepchenko BM, Schaff JC, Macara I, Loew LM. Quantitative cell biology with the Virtual Cell. Trends Cell Biol 2003;13(11):570–576.PubMedCrossRefGoogle Scholar
  41. 41.
    Le Novere N, Bornstein B, Broicher A, et al. BioModels Database: a free, centralized database of curated, published, quantitative kinetic models of biochemical and cellular systems. Nucleic Acids Res 2006;34 (Database issue): D689–D691.PubMedCrossRefGoogle Scholar
  42. 42.
    Vayttaden SJ, Bhalla US. Developing complex signaling models using GENESIS/Kinetikit. Sci STKE 2004;2004(219):pl4.PubMedCrossRefGoogle Scholar
  43. 43.
    Bhalla US. Use of Kinetikit and GENESIS for modeling signaling pathways. Methods Enzymol 2002;345:3–23.PubMedGoogle Scholar

Copyright information

© Humana Press Inc. 2007

Authors and Affiliations

  • Eliza Chan
    • 1
  • Fabien Campagne
    • 1
  1. 1.Institute for Computational Biomedicine and Department of Physiology and BiophysicsWeill Medical College of Cornell UniversityNew YorkUSA

Personalised recommendations