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Identification of OBO nonalignments and its implications for OBO enrichment

Motivation: Existing projects that focus on the semiautomatic addition of links between existing terms in the Open Biomedical Ontologies can take advantage of reasoners that can make new inferences between terms that are based on the added formal definitions and that reflect nonalignments between th...

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Detalles Bibliográficos
Autores principales: Bada, Michael, Hunter, Lawrence
Formato: Texto
Lenguaje:English
Publicado: Oxford University Press 2008
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC2427163/
https://www.ncbi.nlm.nih.gov/pubmed/18463117
http://dx.doi.org/10.1093/bioinformatics/btn194
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author Bada, Michael
Hunter, Lawrence
author_facet Bada, Michael
Hunter, Lawrence
author_sort Bada, Michael
collection PubMed
description Motivation: Existing projects that focus on the semiautomatic addition of links between existing terms in the Open Biomedical Ontologies can take advantage of reasoners that can make new inferences between terms that are based on the added formal definitions and that reflect nonalignments between the linked terms. However, these projects require that these definitions be necessary and sufficient, a strong requirement that often does not hold. If such definitions cannot be added, the reasoners cannot point to the nonalignments through the suggestion of new inferences. Results: We describe a methodology by which we have identified over 1900 instances of nonredundant nonalignments between terms from the Gene Ontology (GO) biological process (BP), cellular component (CC) and molecular function (MF) ontologies, Chemical Entities of Biological Interest (ChEBI) and the Cell Type Ontology (CL). Many of the 39.8% of these nonalignments whose object terms are more atomic than the subject terms are not currently examined in other ontology-enrichment projects due to the fact that the necessary and sufficient conditions required for the inferences are not currently examined. Analysis of the ratios of nonalignments to assertions from which the nonalignments were identified suggests that BP–MF, BP–BP, BP–CL and CC–CC terms are relatively well-aligned, while ChEBI–MF, BP–ChEBI and CC–MF terms are relatively not aligned well. We propose four ways to resolve an identified nonalignment and recommend an analogous implementation of our methodology in ontology-enrichment tools to identify types of nonalignments that are currently not detected. Availability: The nonalignments discussed in this article may be viewed at http://compbio.uchsc.edu/Hunter_lab/Bada/nonalignments_2008_03_06.html. Code for the generation of these nonalignments is available upon request. Contact: mike.bada@uchsc.edu
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spelling pubmed-24271632009-02-25 Identification of OBO nonalignments and its implications for OBO enrichment Bada, Michael Hunter, Lawrence Bioinformatics Original Papers Motivation: Existing projects that focus on the semiautomatic addition of links between existing terms in the Open Biomedical Ontologies can take advantage of reasoners that can make new inferences between terms that are based on the added formal definitions and that reflect nonalignments between the linked terms. However, these projects require that these definitions be necessary and sufficient, a strong requirement that often does not hold. If such definitions cannot be added, the reasoners cannot point to the nonalignments through the suggestion of new inferences. Results: We describe a methodology by which we have identified over 1900 instances of nonredundant nonalignments between terms from the Gene Ontology (GO) biological process (BP), cellular component (CC) and molecular function (MF) ontologies, Chemical Entities of Biological Interest (ChEBI) and the Cell Type Ontology (CL). Many of the 39.8% of these nonalignments whose object terms are more atomic than the subject terms are not currently examined in other ontology-enrichment projects due to the fact that the necessary and sufficient conditions required for the inferences are not currently examined. Analysis of the ratios of nonalignments to assertions from which the nonalignments were identified suggests that BP–MF, BP–BP, BP–CL and CC–CC terms are relatively well-aligned, while ChEBI–MF, BP–ChEBI and CC–MF terms are relatively not aligned well. We propose four ways to resolve an identified nonalignment and recommend an analogous implementation of our methodology in ontology-enrichment tools to identify types of nonalignments that are currently not detected. Availability: The nonalignments discussed in this article may be viewed at http://compbio.uchsc.edu/Hunter_lab/Bada/nonalignments_2008_03_06.html. Code for the generation of these nonalignments is available upon request. Contact: mike.bada@uchsc.edu Oxford University Press 2008-06-15 2008-05-07 /pmc/articles/PMC2427163/ /pubmed/18463117 http://dx.doi.org/10.1093/bioinformatics/btn194 Text en © 2008 The Author(s) http://creativecommons.org/licenses/by-nc/2.0/uk/ This is an Open Access article distributed under the terms of the Creative Commons Attribution Non-Commercial License (http://creativecommons.org/licenses/by-nc/2.0/uk/) which permits unrestricted non-commercial use, distribution, and reproduction in any medium, provided the original work is properly cited.
spellingShingle Original Papers
Bada, Michael
Hunter, Lawrence
Identification of OBO nonalignments and its implications for OBO enrichment
title Identification of OBO nonalignments and its implications for OBO enrichment
title_full Identification of OBO nonalignments and its implications for OBO enrichment
title_fullStr Identification of OBO nonalignments and its implications for OBO enrichment
title_full_unstemmed Identification of OBO nonalignments and its implications for OBO enrichment
title_short Identification of OBO nonalignments and its implications for OBO enrichment
title_sort identification of obo nonalignments and its implications for obo enrichment
topic Original Papers
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC2427163/
https://www.ncbi.nlm.nih.gov/pubmed/18463117
http://dx.doi.org/10.1093/bioinformatics/btn194
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