ArticleJournal of biomedical semantics2012
Logical Gene Ontology Annotations (GOAL): exploring gene ontology annotations with OWL.
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.
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Who cites it
9 citing papers in PubMed.
- Article
- Formal axioms in biomedical ontologies improve analysis and interpretation of associated data.Bioinformatics (Oxford, England) · 2020Article
- Automated generation of gene summaries at the Alliance of Genome Resources.Database : the journal of biological databases and curation · 2020Article
- Aber-OWL: a framework for ontology-based data access in biology.BMC bioinformatics · 2015Article
- Thematic series on biomedical ontologies in JBMS: challenges and new directions.Journal of biomedical semantics · 2014Review
- Evaluation of research in biomedical ontologies.Briefings in bioinformatics · 2013Article
- OPPL-Galaxy, a Galaxy tool for enhancing ontology exploitation as part of bioinformatics workflows.Journal of biomedical semantics · 2013Article
- Article
- Selected papers from the 14th Annual Bio-Ontologies Special Interest Group Meeting.Journal of biomedical semantics · 2012Article
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3 authors.
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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.
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