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Automated Reasoning
Biological Process
Flow Cytometry
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Type Classes
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Logical Development of the Cell Ontology
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Logical Development of the Cell Ontology
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Terrence F. Meehan
,
Anna Maria Masci
,
Amina Abdulla
,
Lindsay G. Cowell
,
Judith A. Blake
,
Christopher J. Mungall
,
Alexander D. Diehl
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.
Journal:
BMC Bioinformatics
, vol. 12, no. 1, pp. 6-12, 2011
DOI:
10.1186/1471-2105-12-6
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References
(29)
The OBO Foundry: coordinated evolution of ontologies to support biomedical data integration
(
Citations: 274
)
Barry Smith
,
Michael Ashburner
,
Cornelius Rosse
,
Jonathan Bard
,
William Bug
,
Werner Ceusters
,
Louis J Goldberg
,
Karen Eilbeck
,
Christopher J Mungall
,
Philippe Rocca-Serra
,
Susanna-Assunta Sansone
,
Nigam Shah
http://academic.research.microsoft.com/io.ashx?type=5&id=4553939&selfId1=0&selfId2=0&maxNumber=12&query=
Journal:
Nature Biotechnology - NAT BIOTECHNOL
, vol. 25, no. 11, pp. 1251-1255, 2007
An ontology for cell types
(
Citations: 103
)
J Bard
,
Sy Rhee
,
M Ashburner
Published in 2005.
Modularisation of domain ontologies implemented in description logics and related formalisms including OWL
(
Citations: 94
)
Alan L. Rector
Conference:
International Conference on Knowledge Capture - K-CAP
, pp. 121-128, 2003
Defaults, Context, and Knowledge: Alternatives for OWL-Indexed Knowledge Bases
(
Citations: 19
)
Alan L. Rector
Conference:
Pacific Symposium on Biocomputing
, pp. 226-237, 2004
Extension and Integration of the Gene Ontology (GO): Combining GO Vocabularies With External Vocabularies
(
Citations: 30
)
D. P. Hill
Journal:
Genome Research - GENOME RES
, vol. 12, no. 12, pp. 1982-1991, 2002