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Predicting the Extension of Biomedical Ontologies

Developing and extending a biomedical ontology is a very demanding task that can never be considered complete given our ever-evolving understanding of the life sciences. Extension in particular can benefit from the automation of some of its steps, thus releasing experts to focus on harder tasks. Her...

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Detalles Bibliográficos
Autores principales: Pesquita, Catia, Couto, Francisco M.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Public Library of Science 2012
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3441454/
https://www.ncbi.nlm.nih.gov/pubmed/23028267
http://dx.doi.org/10.1371/journal.pcbi.1002630
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author Pesquita, Catia
Couto, Francisco M.
author_facet Pesquita, Catia
Couto, Francisco M.
author_sort Pesquita, Catia
collection PubMed
description Developing and extending a biomedical ontology is a very demanding task that can never be considered complete given our ever-evolving understanding of the life sciences. Extension in particular can benefit from the automation of some of its steps, thus releasing experts to focus on harder tasks. Here we present a strategy to support the automation of change capturing within ontology extension where the need for new concepts or relations is identified. Our strategy is based on predicting areas of an ontology that will undergo extension in a future version by applying supervised learning over features of previous ontology versions. We used the Gene Ontology as our test bed and obtained encouraging results with average f-measure reaching 0.79 for a subset of biological process terms. Our strategy was also able to outperform state of the art change capturing methods. In addition we have identified several issues concerning prediction of ontology evolution, and have delineated a general framework for ontology extension prediction. Our strategy can be applied to any biomedical ontology with versioning, to help focus either manual or semi-automated extension methods on areas of the ontology that need extension.
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spelling pubmed-34414542012-10-01 Predicting the Extension of Biomedical Ontologies Pesquita, Catia Couto, Francisco M. PLoS Comput Biol Research Article Developing and extending a biomedical ontology is a very demanding task that can never be considered complete given our ever-evolving understanding of the life sciences. Extension in particular can benefit from the automation of some of its steps, thus releasing experts to focus on harder tasks. Here we present a strategy to support the automation of change capturing within ontology extension where the need for new concepts or relations is identified. Our strategy is based on predicting areas of an ontology that will undergo extension in a future version by applying supervised learning over features of previous ontology versions. We used the Gene Ontology as our test bed and obtained encouraging results with average f-measure reaching 0.79 for a subset of biological process terms. Our strategy was also able to outperform state of the art change capturing methods. In addition we have identified several issues concerning prediction of ontology evolution, and have delineated a general framework for ontology extension prediction. Our strategy can be applied to any biomedical ontology with versioning, to help focus either manual or semi-automated extension methods on areas of the ontology that need extension. Public Library of Science 2012-09-13 /pmc/articles/PMC3441454/ /pubmed/23028267 http://dx.doi.org/10.1371/journal.pcbi.1002630 Text en © 2012 Pesquita, Couto http://creativecommons.org/licenses/by/4.0/ This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are properly credited.
spellingShingle Research Article
Pesquita, Catia
Couto, Francisco M.
Predicting the Extension of Biomedical Ontologies
title Predicting the Extension of Biomedical Ontologies
title_full Predicting the Extension of Biomedical Ontologies
title_fullStr Predicting the Extension of Biomedical Ontologies
title_full_unstemmed Predicting the Extension of Biomedical Ontologies
title_short Predicting the Extension of Biomedical Ontologies
title_sort predicting the extension of biomedical ontologies
topic Research Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3441454/
https://www.ncbi.nlm.nih.gov/pubmed/23028267
http://dx.doi.org/10.1371/journal.pcbi.1002630
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