An improved ontological representation of dendritic cells as a paradigm for all cell types [electronic resource]
Saved in:
| Online Access: |
Full Text (via OSTI) |
|---|---|
| Format: | Electronic eBook |
| Language: | English |
| Published: |
Washington, D.C. : Oak Ridge, Tenn. :
United States. Department of Energy. Office of Science ; Distributed by the Office of Scientific and Technical Information, U.S. Department of Energy,
2009.
|
| Subjects: |
| Abstract: | Background: Recent increases in the volume and diversity of life science data and information andan increasing emphasis on data sharing and interoperability have resulted in the creation of a largenumber of biological ontologies, including the Cell Ontology (CL), designed to provide astandardized representation of cell types for data annotation. Ontologies have been shown to havesignificant benefits for computational analyses of large data sets and for automated reasoningapplications, leading to organized attempts to improve the structure and formal rigor of ontologiesto better support computation. Currently, the CL employs multiple is_a relations, defining celltypes in terms of histological, functional, and lineage properties, and the majority of definitions arewritten with sufficient generality to hold across multiple species. This approach limits the CL'sutility for computation and for cross-species data integration.Results: To enhance the CL's utility for computational analyses, we developed a method for theontological representation of cells and applied this method to develop a dendritic cell ontology(DC-CL). DC-CL subtypes are delineated on the basis of surface protein expression, systematicallyincluding both species-general and species-specific types and optimizing DC-CL for the analysis offlow cytometry data. We avoid multiple uses of is_a by linking DC-CL terms to terms in otherontologies via additional, formally defined relations such as has_function.Conclusion: This approach brings benefits in the form of increased accuracy, support forreasoning, and interoperability with other ontology resources. Accordingly, we propose ourmethod as a general strategy for the ontological representation of cells. DC-CL is available fromhttp://www.obofoundry.org. |
|---|---|
| Item Description: | Published through Scitech Connect. 01/01/2009. "Journal ID: ISSN 1471-2105." "Other: PII: 1471-2105-10-70." Masci, Anna ; Arighi, Cecilia N. ; Diehl, Alexander D. ; Lieberman, Anne E. ; Mungall, Chris ; Scheuermann, Richard H. ; Smith, Barry ; Cowell, Lindsay G. ; |
| Physical Description: | Size: Article No. 70 : digital, PDF file. |