An ontology for immune epitopes: application to the design of a broad scope database of immune reactivities
1 La Jolla Institute of Allergy and Immunology, 3030 Bunker Hill Street, Suite 326, San Diego, California, 92109, USA
2 Knowledge Systems, Artificial Intelligence Laboratory, Stanford University and McGuinness Associates, Stanford, CA 94305, USA
3 San Diego Supercomputer Center, P.O. Box 85608, San Diego, California 92186-5608, USA
Immunome Research 2005, 1:2 doi:10.1186/1745-7580-1-2Published: 20 September 2005
Epitopes can be defined as the molecular structures bound by specific receptors, which are recognized during immune responses. The Immune Epitope Database and Analysis Resource (IEDB) project will catalog and organize information regarding antibody and T cell epitopes from infectious pathogens, experimental antigens and self-antigens, with a priority on NIAID Category A-C pathogens (http://www2.niaid.nih.gov/Biodefense/bandc_priority.htm webcite) and emerging/re-emerging infectious diseases. Both intrinsic structural and phylogenetic features, as well as information relating to the interactions of the epitopes with the host's immune system will be catalogued.
To effectively represent and communicate the information related to immune epitopes, a formal ontology was developed. The semantics of the epitope domain and related concepts were captured as a hierarchy of classes, which represent the general and specialized relationships between the various concepts. A complete listing of classes and their properties can be found at http://www.immuneepitope.org/ontology/index.html webcite.
The IEDB's ontology is the first ontology specifically designed to capture both intrinsic chemical and biochemical information relating to immune epitopes with information relating to the interaction of these structures with molecules derived from the host immune system. We anticipate that the development of this type of ontology and associated databases will facilitate rigorous description of data related to immune epitopes, and might ultimately lead to completely new methods for describing and modeling immune responses.