ArticleBMC bioinformatics2011
Improving ontologies by automatic reasoning and evaluation of logical definitions.
Article in BMC bioinformatics, 2011. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 21 papers.
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Who cites it
21 citing papers in PubMed.
- Integrating Heterogeneous Real-World Cancer Data for Semantic Interoperability in Oncology and Medical Imaging: Development and Validation of the Cancer Image Europe Hyperontology.Journal of medical Internet research · 2026Article
- Dynamic Retrieval Augmented Generation of Ontologies using Artificial Intelligence (DRAGON-AI).Journal of biomedical semantics · 2024Article
- An ontological framework for organising and describing behaviours: The Human Behaviour Ontology.Wellcome open research · 2024Article
- octoFLUshow: an Interactive Tool Describing Spatial and Temporal Trends in the Genetic Diversity of Influenza A Virus in U.S. Swine.Microbiology resource announcements · 2021Article
- Semantic characterization of adverse outcome pathways.Aquatic toxicology (Amsterdam, Netherlands) · 2020Article
- Expansion of the Human Phenotype Ontology (HPO) knowledge base and resources.Nucleic acids research · 2019Article
- The Human Phenotype Ontology: Semantic Unification of Common and Rare Disease.American journal of human genetics · 2015Article
- Aber-OWL: a framework for ontology-based data access in biology.BMC bioinformatics · 2015Article
- Linking gene expression to phenotypes via pathway information.Journal of biomedical semantics · 2015Article
- Clinical interpretation of CNVs with cross-species phenotype data.Journal of medical genetics · 2014Article
- Phevor combines multiple biomedical ontologies for accurate identification of disease-causing alleles in single individuals and small nuclear families.American journal of human genetics · 2014Article
- The Human Phenotype Ontology project: linking molecular biology and disease through phenotype data.Nucleic acids research · 2014Article
- Evaluation of research in biomedical ontologies.Briefings in bioinformatics · 2013Article
- The Drosophila phenotype ontology.Journal of biomedical semantics · 2013Article
- Automatically transforming pre- to post-composed phenotypes: EQ-lising HPO and MP.Journal of biomedical semantics · 2013Article
- Phenotypic overlap in the contribution of individual genes to CNV pathogenicity revealed by cross-species computational analysis of single-gene mutations in humans, mice and zebrafish.Disease models & mechanisms · 2013Article
- Article
- Construction and accessibility of a cross-species phenotype ontology along with gene annotations for biomedical research.F1000Research · 2013Article
- Toward knowledge support for analysis and interpretation of complex traits.Genome biology · 2013Review
- The Mammalian Phenotype Ontology as a unifying standard for experimental and high-throughput phenotyping data.Mammalian genome : official journal of the International Mammalian Genome Society · 2012Article
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8 authors.
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Abstract
backgroundOntologies are widely used to represent knowledge in biomedicine. Systematic approaches for detecting errors and disagreements are needed for large ontologies with hundreds or thousands of terms and semantic relationships. A recent approach of defining terms using logical definitions is now increasingly being adopted as a method for quality control as well as for facilitating interoperability and data integration.
resultsWe show how automated reasoning over logical definitions of ontology terms can be used to improve ontology structure. We provide the Java software package GULO (Getting an Understanding of LOgical definitions), which allows fast and easy evaluation for any kind of logically decomposed ontology by generating a composite OWL ontology from appropriate subsets of the referenced ontologies and comparing the inferred relationships with the relationships asserted in the target ontology. As a case study we show how to use GULO to evaluate the logical definitions that have been developed for the Mammalian Phenotype Ontology (MPO).
conclusionsLogical definitions of terms from biomedical ontologies represent an important resource for error and disagreement detection. GULO gives ontology curators a fast and simple tool for validation of their work.
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