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Logical Development of the Cell Ontology

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...

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Autores principales: Meehan, Terrence F, Masci, Anna Maria, Abdulla, Amina, Cowell, Lindsay G, Blake, Judith A, Mungall, Christopher J, Diehl, Alexander D
Formato: Texto
Lenguaje:English
Publicado: BioMed Central 2011
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3024222/
https://www.ncbi.nlm.nih.gov/pubmed/21208450
http://dx.doi.org/10.1186/1471-2105-12-6
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author Meehan, Terrence F
Masci, Anna Maria
Abdulla, Amina
Cowell, Lindsay G
Blake, Judith A
Mungall, Christopher J
Diehl, Alexander D
author_facet Meehan, Terrence F
Masci, Anna Maria
Abdulla, Amina
Cowell, Lindsay G
Blake, Judith A
Mungall, Christopher J
Diehl, Alexander D
author_sort Meehan, Terrence F
collection PubMed
description 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.
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spelling pubmed-30242222011-01-21 Logical Development of the Cell Ontology Meehan, Terrence F Masci, Anna Maria Abdulla, Amina Cowell, Lindsay G Blake, Judith A Mungall, Christopher J Diehl, Alexander D BMC Bioinformatics Methodology Article 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. BioMed Central 2011-01-05 /pmc/articles/PMC3024222/ /pubmed/21208450 http://dx.doi.org/10.1186/1471-2105-12-6 Text en 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 (<url>http://creativecommons.org/licenses/by/2.0</url>), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
spellingShingle Methodology Article
Meehan, Terrence F
Masci, Anna Maria
Abdulla, Amina
Cowell, Lindsay G
Blake, Judith A
Mungall, Christopher J
Diehl, Alexander D
Logical Development of the Cell Ontology
title Logical Development of the Cell Ontology
title_full Logical Development of the Cell Ontology
title_fullStr Logical Development of the Cell Ontology
title_full_unstemmed Logical Development of the Cell Ontology
title_short Logical Development of the Cell Ontology
title_sort logical development of the cell ontology
topic Methodology Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3024222/
https://www.ncbi.nlm.nih.gov/pubmed/21208450
http://dx.doi.org/10.1186/1471-2105-12-6
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