The anatomy of phenotype ontologies: principles, properties and applications
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The anatomy of phenotype ontologies: principles, properties and applications. / Gkoutos, Georgios V.; Schofield, Paul N; Hoehndorf, Robert.
In: Briefings in Bioinformatics, Vol. 19, No. 5, 28.09.2018, p. 1008-1021.Research output: Contribution to journal › Article › peer-review
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TY - JOUR
T1 - The anatomy of phenotype ontologies: principles, properties and applications
AU - Gkoutos, Georgios V.
AU - Schofield, Paul N
AU - Hoehndorf, Robert
PY - 2018/9/28
Y1 - 2018/9/28
N2 - 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
AB - 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
KW - phenotype
KW - ontology
KW - PATO
KW - data integration
KW - Semantic Web
U2 - 10.1093/bib/bbx035
DO - 10.1093/bib/bbx035
M3 - Article
VL - 19
SP - 1008
EP - 1021
JO - Briefings in Bioinformatics
JF - Briefings in Bioinformatics
SN - 1467-5463
IS - 5
ER -