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The anatomy of phenotype ontologies: principles, properties and applications.
Gkoutos, Georgios V; Schofield, Paul N; Hoehndorf, Robert.
Afiliación
  • Gkoutos GV; University of Birmingham Medical School.
  • Schofield PN; University of Cambridge.
  • Hoehndorf R; Computer, Electrical and Mathematical Sciences and Engineering Division, King Abdullah University of Science and Technology, King Abdullah University of Science and Technology, Thuwal.
Brief Bioinform ; 19(5): 1008-1021, 2018 09 28.
Article en En | MEDLINE | ID: mdl-28387809
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.
Asunto(s)

Texto completo: 1 Colección: 01-internacional Base de datos: MEDLINE Asunto principal: Fenotipo / Ontologías Biológicas Límite: Animals / Humans Idioma: En Revista: Brief Bioinform Asunto de la revista: BIOLOGIA / INFORMATICA MEDICA Año: 2018 Tipo del documento: Article

Texto completo: 1 Colección: 01-internacional Base de datos: MEDLINE Asunto principal: Fenotipo / Ontologías Biológicas Límite: Animals / Humans Idioma: En Revista: Brief Bioinform Asunto de la revista: BIOLOGIA / INFORMATICA MEDICA Año: 2018 Tipo del documento: Article
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