We are analyzing https://link.springer.com/article/10.1186/1471-2105-12-6.

Title:
Logical Development of the Cell Ontology | BMC Bioinformatics
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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Keywords {🔍}

cell, ontology, types, computable, definitions, classes, cells, ontologies, relationships, class, pubmed, article, type, figure, hematopoietic, isa, google, scholar, obo, defined, inferred, surface, protein, relationship, reasoners, markers, reasoner, biological, expression, owl, cas, masci, automated, natural, central, developsfrom, mature, gene, hemocl, oboedit, alphabeta, definition, capableof, authors, immune, hierarchy, complex, killer, receptor, mungall,

Topics {✒️}

net/viewvc/obo/obo/ontology/anatomy/cell_type anna maria masci gov/pubmed/20123131 http article download pdf medicine-clinical terms entity/quality-based logical definitions 2nd international conference mhc-ib protein complexes author information authors view held human-oriented textual definitions testing neural-immune interactions accommodate species-specific expression b-cell immunological synapse lymphocyte receptor complex species-specific cell types reflect species-specific differences cell receptor complex related subjects species-neutral cell type hidden cell-classes displaying obo-edit software tools owl-indexed knowledge bases formal textual definitions represent species-specific expression red zig-zag hematopoietic stem cell central nervous system human stem cells double-positive thymocyte class cd11b-negative dendritic cell varying standards snomed-ct ontology-based phenotype annotation amm contributed terms privacy choices/manage cookies hematopoietic stem cells full size image de la salle de-ac02-05ch11231 natural t-regulatory cell nucleate erythrocyte cell receptor genes species-specific differences human skeletal phenome authors’ original file uber anatomy ontology gene ontology consortium human cell markers complex biomedical ontologies

Questions {❓}

Curotto de Lafaille MA, Lafaille JJ: Natural and adaptive foxp3+ regulatory T cells: more of the same or a division of labor?
Godfrey DI, MacDonald HR, Kronenberg M, Smyth MJ, Van Kaer L: NKT cells: what's in a name?

Schema {🗺️}

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         description: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. 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. Use of computable definitions enhances the development of the CL and supports the interoperability of OBO ontologies.
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      headline:Logical Development of the Cell Ontology
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         Automate Reasoner
         Human Hematopoietic Stem Cell
         Nucleate Erythrocyte
         Cell Receptor Complex
         Bioinformatics
         Microarrays
         Computational Biology/Bioinformatics
         Computer Appl. in Life Sciences
         Algorithms
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               type:PostalAddress
            type:Organization
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            address:
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               type:PostalAddress
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      name:Mouse Genome Informatics, The Jackson Laboratory, Bar Harbor, USA
      name:Lawrence Berkeley National Laboratory, Berkeley, USA
      name:Mouse Genome Informatics, The Jackson Laboratory, Bar Harbor, USA
      name:Department of Neurology, University at Buffalo School of Medicine and Biomedical Sciences, Buffalo, USA

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