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The anatomy of phenotype ontologies: principles, properties and applications


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Publication Date: 2017-04-06

Journal Title: Briefings in Bioinformatics

Publisher: Oxford University Press

Language: English

Type: Article

This Version: VoR

Metadata: Show full item record

Citation: Gkoutos, G., Schofield, P., & Hoehndorf, R. (2017). The anatomy of phenotype ontologies: principles, properties and applications. Briefings in Bioinformatics https://doi.org/10.1093/bib/bbx035

Abstract: The past decade has seen an explosion in the collection of genotype data in domains as diverse as medicine, ecology, livestock and plant breeding. Along with this comes the challenge of dealing with the related phenotype data, which is not only large but also highly multidimensional. Computational analysis of phenotypes has therefore become critical for our ability to understand the biological meaning of genomic data in the biological sciences. At the heart of computational phenotype analysis are the phenotype ontologies. A large number of these ontologies have been developed across many domains, and we are now at a point where the knowledge captured in the structure of these ontologies can be used for the integration and analysis of large interrelated data sets. The Phenotype And Trait Ontology framework provides a method for formal definitions of phenotypes and associated data sets and has proved to be key to our ability to develop methods for the integration and analysis of phenotype data. Here, we describe the development and products of the ontological approach to phenotype capture, the formal content of phenotype ontologies and how their content can be used computationally.

Keywords: phenotype, ontology, PATO, data integration, Semantic Web

Sponsorship: The National Science Foundation (IOS:1340112 to G.V.G.), the European Commission H2020 (grant agreement number 731075) to G.V.G. and the King Abdullah University of Science and Technology (to R.H.).

Identifiers:

External DOI: https://doi.org/10.1093/bib/bbx035

This record's URL: https://www.repository.cam.ac.uk/handle/1810/264437



Rights: Attribution 4.0 International

Licence URL: http://creativecommons.org/licenses/by/4.0/





Author: Gkoutos, GV Schofield, PNHoehndorf, R

Source: https://www.repository.cam.ac.uk/handle/1810/264437



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