Evidence map›Paper›PMID 22541594›Full record

ArticleJournal of biomedical semantics2012

Logical Gene Ontology Annotations (GOAL): exploring gene ontology annotations with OWL.

Simon Jupp, Robert Stevens, Robert Hoehndorf

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In one paragraph

Article in Journal of biomedical semantics, 2012. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 9 papers.

0numbers the graph read from it
0cells of the map it votes in
9citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

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3 · Its place in the literature

Who cites it

9 citing papers in PubMed.

  1. Article
  2. Article
  3. Automated generation of gene summaries at the Alliance of Genome Resources.Database : the journal of biological databases and curation · 2020
    Article
  4. Article
  5. Review
  6. Evaluation of research in biomedical ontologies.Briefings in bioinformatics · 2013
    Article
  7. Article
  8. Article
  9. Article
4 · The record

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5 · Who and what money

Authors and funding

3 authors.

Simon JuppEuropean Bioinformatics Institute, Wellcome Trust Genome Campus, Cambridge, CB10 1SD, UK. jupp@ebi.ac.uk.
Robert Stevens
Robert Hoehndorf

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

motivationOntologies such as the Gene Ontology (GO) and their use in annotations make cross species comparisons of genes possible, along with a wide range of other analytical activities. The bio-ontologies community, in particular the Open Biomedical Ontologies (OBO) community, have provided many other ontologies and an increasingly large volume of annotations of gene products that can be exploited in query and analysis. As many annotations with different ontologies centre upon gene products, there is a possibility to explore gene products through multiple ontological perspectives at the same time. Questions could be asked that link a gene product's function, process, cellular location, phenotype and disease. Current tools, such as AmiGO, allow exploration of genes based on their GO annotations, but not through multiple ontological perspectives. In addition, the semantics of these ontology's representations should be able to, through automated reasoning, afford richer query opportunities of the gene product annotations than is currently possible.

resultsTo do this multi-perspective, richer querying of gene product annotations, we have created the Logical Gene Ontology, or GOAL ontology, in OWL that combines the Gene Ontology, Human Disease Ontology and the Mammalian Phenotype Ontology, together with classes that represent the annotations with these ontologies for mouse gene products. Each mouse gene product is represented as a class, with the appropriate relationships to the GO aspects, phenotype and disease with which it has been annotated. We then use defined classes to query these protein classes through automated reasoning, and to build a complex hierarchy of gene products. We have presented this through a Web interface that allows arbitrary queries to be constructed and the results displayed.

conclusionThis standard use of OWL affords a rich interaction with Gene Ontology, Human Disease Ontology and Mammalian Phenotype Ontology annotations for the mouse, to give a fine partitioning of the gene products in the GOAL ontology. OWL in combination with automated reasoning can be effectively used to query across ontologies to ask biologically rich questions. We have demonstrated that automated reasoning can be used to deliver practical on-line querying support for the ontology annotations available for the mouse. AVAILABILITY: The GOAL Web page is to be found at http://owl.cs.manchester.ac.uk/goal.

Identifiers

PMID22541594
PMCPMC3337258

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.