This article is part of the supplement: Proceedings of the Bio-Ontologies Special Interest Group Meeting 2009: Knowledge in Biology

Open Access Proceedings

Modeling biomedical experimental processes with OBI

Ryan R Brinkman1, Mélanie Courtot1, Dirk Derom2, Jennifer M Fostel3, Yongqun He4, Phillip Lord5, James Malone6, Helen Parkinson6, Bjoern Peters7, Philippe Rocca-Serra6, Alan Ruttenberg8, Susanna-Assunta Sansone6, Larisa N Soldatova9*, Christian J Stoeckert10, Jessica A Turner11, Jie Zheng10 and the OBI consortium

Author Affiliations

1 British Columbia Cancer Agency, Vancouver, Canada

2 Victoria University of Wellington, New Zealand

3 Global Health Sector, SRA International, Inc, Durham, NC, USA

4 University of Michigan Medical School, Ann Arbor, USA

5 School of Computing Science, Newcastle University, UK

6 The European Bioinformatics Institute, Cambridge, UK

7 La Jolla Institute for Allergy and Immunology, La Jolla, CA, USA

8 Science Commons, Cambridge, MA, USA

9 Aberystwyth University, Wales, UK

10 Center for Bioinformatics, Department of Genetics, University of Pennsylvania School of Medicine, Philadelphia, PA, USA

11 Department of Psychiatry and Human Behavior, University of California, Irvine, CA, USA

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Journal of Biomedical Semantics 2010, 1(Suppl 1):S7  doi:10.1186/2041-1480-1-S1-S7

Published: 22 June 2010

Abstract

Background

Experimental descriptions are typically stored as free text without using standardized terminology, creating challenges in comparison, reproduction and analysis. These difficulties impose limitations on data exchange and information retrieval.

Results

The Ontology for Biomedical Investigations (OBI), developed as a global, cross-community effort, provides a resource that represents biomedical investigations in an explicit and integrative framework. Here we detail three real-world applications of OBI, provide detailed modeling information and explain how to use OBI.

Conclusion

We demonstrate how OBI can be applied to different biomedical investigations to both facilitate interpretation of the experimental process and increase the computational processing and integration within the Semantic Web. The logical definitions of the entities involved allow computers to unambiguously understand and integrate different biological experimental processes and their relevant components.

Availability

OBI is available at http://purl.obolibrary.org/obo/obi/2009-11-02/obi.owl webcite