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.
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.
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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
Grenon P, Smith B et al (2004) Biodynamic ontology: Applying BFO in the biomedical domain. Stud Health Technol Inform 102:20–38PubMedGoogle Scholar
Peters B, Sidney J et al (2005) The immune epitope database and analysis resource: From vision to blueprint. PLoS Biol 3(3):e91CrossRefPubMedGoogle Scholar
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