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Ontology Development for the Immune Epitope Database

  • Jason A. Greenbaum
  • Randi Vita
  • Laura M. Zarebski
  • Alessandro Sette
  • Bjoern Peters
Chapter
Part of the Immunomics Reviews: book series (IMMUN, volume 3)

Abstract

A key challenge in bioinformatics today is ensuring that biological data can be unequivocally communicated between experimentalists and bioinformaticians. Enabling such communication is not trivial, as every scientific field develops its own jargon with implicit understandings that can easily escape an outsider. We describe here our approach to enforce an explicit and exact data representation for the Immune Epitope Database (IEDB Peters et al. 2005) through the use of a formal ontology.

Being the first database of its scale in the immune epitope domain, it was necessary for the IEDB to devise an adequate data structure at the outset of the project with the goal that it should be capable of capturing the context of immune recognition. Early on, it became readily apparent that an unambiguous description of the information being captured is imperative for consistent curation across journal articles and among curators. Accordingly, an initial ontology was developed (Sathiamurthy et al. 2005) based upon consultations with domain experts and guidance from expert ontologists. The structure devised from this ontology proved capable of dealing with a great deal of immunological data over time.

Keywords

ELISPOT Assay Major Histocompatibility Complex Molecule Ontology Development Formal Ontology Immunization Protocol 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

References

  1. Ashburner M, Ball CA et al (2000) Gene ontology: Tool for the unification of biology. The Gene Ontology Consortium. Nat Genet 25(1):25–29CrossRefPubMedGoogle Scholar
  2. Grenon P, Smith B et al (2004) Biodynamic ontology: Applying BFO in the biomedical domain. Stud Health Technol Inform 102:20–38PubMedGoogle Scholar
  3. Peters B, Sidney J et al (2005) The immune epitope database and analysis resource: From vision to blueprint. PLoS Biol 3(3):e91CrossRefPubMedGoogle Scholar
  4. Rosse C, Mejino JL Jr (2003) A reference ontology for biomedical informatics: The Foundational Model of Anatomy. J Biomed Inform 36(6):478–500CrossRefPubMedGoogle Scholar
  5. Salimi N, Vita R (2006) The biocurator: Connecting and enhancing scientific data. PLoS Comput Biol 2(10):e125CrossRefPubMedGoogle Scholar
  6. Sathiamurthy M, Peters B et al (2005) An ontology for immune epitopes: Application to the design of a broad scope database of immune reactivities. Immunome Res 1(1):2CrossRefPubMedGoogle Scholar
  7. Smith B, Ashburner M et al (2007) The OBO Foundry: Coordinated evolution of ontologies to support biomedical data integration. Nat Biotechnol 25(11):1251–1255CrossRefPubMedGoogle Scholar
  8. Vita R, Vaughan K et al (2006) Curation of complex, context-dependent immunological data. BMC Bioinform 7:341CrossRefGoogle Scholar
  9. Whetzel PL, Brinkman RR et al (2006a) Development of FuGO: An ontology for functional genomics investigations. Omics 10(2):199–204CrossRefPubMedGoogle Scholar
  10. Whetzel PL, Parkinson H et al (2006b) The MGED Ontology: A resource for semantics-based description of microarray experiments. Bioinformatics 22(7):866–873CrossRefPubMedGoogle Scholar

Copyright information

© Springer Science+Business Media, LLC 2009

Authors and Affiliations

  • Jason A. Greenbaum
  • Randi Vita
  • Laura M. Zarebski
  • Alessandro Sette
  • Bjoern Peters
    • 1
  1. 1.La Jolla Institute for Allergy and ImmunologyLa JollaUSA

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