Abstract

Abstract

Background: The Cell Ontology (CL) is an ontology for the representation of in vivo cell types. As biological ontologies such as the CL grow in complexity, they become increasingly difficult to use and maintain. By making the information in the ontology computable, we can use automated reasoners to detect errors and assist with classification. Here we report on the generation of computable definitions for the hematopoietic cell types in the CL.

Results: Computable definitions for over 340 CL classes have been created using a genus-differentia approach. These define cell types according to multiple axes of classification such as the protein complexes found on the surface of a cell type, the biological processes participated in by a cell type, or the phenotypic characteristics associated with a cell type. We employed automated reasoners to verify the ontology and to reveal mistakes in manual curation. The implementation of this process exposed areas in the ontology where new cell type classes were needed to accommodate species-specific expression of cellular markers. Our use of reasoners also inferred new relationships within the CL, and between the CL and the contributing ontologies. This restructured ontology can be used to identify immune cells by flow cytometry, supports sophisticated biological queries involving cells, and helps generate new hypotheses about cell function based on similarities to other cell types.

Conclusion: Use of computable definitions enhances the development of the CL and supports the interoperability of OBO ontologies.

Details

Title
Logical Development of the Cell Ontology
Author
Meehan, Terrence F; Masci, Anna Maria; Abdulla, Amina; Cowell, Lindsay G; Blake, Judith A; Mungall, Christopher J; Diehl, Alexander D
Pages
6
Publication year
2011
Publication date
2011
Publisher
Springer Nature B.V.
e-ISSN
14712105
Source type
Scholarly Journal
Language of publication
English
ProQuest document ID
901905063
Copyright
© 2011 Meehan et al; licensee BioMed Central Ltd. This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/2.0>), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.