The anatomy of phenotype ontologies: principles, properties and applications

Georgios V. Gkoutos; Paul N Schofield; Robert Hoehndorf

doi:10.1093/bib/bbx035

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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Gkoutos, Georgios V. ; Schofield, Paul N ; Hoehndorf, Robert. / The anatomy of phenotype ontologies: principles, properties and applications. In: Briefings in Bioinformatics. 2018 ; Vol. 19, No. 5. pp. 1008-1021.

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@article{8bba09626eb9498f9061bf3382249f72,

title = "The anatomy of phenotype ontologies: principles, properties and applications",

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",

author = "Gkoutos, {Georgios V.} and Schofield, {Paul N} and Robert Hoehndorf",

year = "2018",

month = sep,

day = "28",

doi = "10.1093/bib/bbx035",

language = "English",

volume = "19",

pages = "1008--1021",

journal = "Briefings in Bioinformatics",

issn = "1467-5463",

publisher = "Oxford University Press",

number = "5",

}

RIS (suitable for import to EndNote) - Download

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