ArticleBioData mining2016
FEDRR: fast, exhaustive detection of redundant hierarchical relations for quality improvement of large biomedical ontologies.
Article in BioData mining, 2016. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers.
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Who cites it
7 citing papers in PubMed.
- A review on Gene Ontology evaluations.Database : the journal of biological databases and curation · 2025Review
- An evidence-based lexical pattern approach for quality assurance of Gene Ontology relations.Briefings in bioinformatics · 2022Article
- A Comparison of Exhaustive and Non-lattice-based Methods for Auditing Hierarchical Relations in Gene Ontology.AMIA ... Annual Symposium proceedings. AMIA Symposium · 2021Article
- A review of auditing techniques for the Unified Medical Language System.Journal of the American Medical Informatics Association : JAMIA · 2020Review
- SSIF: Subsumption-based Sub-term Inference Framework to audit Gene Ontology.Bioinformatics (Oxford, England) · 2020Article
- Enumerating consistent sub-graphs of directed acyclic graphs: an insight into biomedical ontologies.Bioinformatics (Oxford, England) · 2018Article
- Spark-MCA: Large-scale, Exhaustive Formal Concept Analysis for Evaluating the Semantic Completeness of SNOMED CT.AMIA ... Annual Symposium proceedings. AMIA Symposium · 2017Article
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Authors and funding
3 authors.
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Abstract
backgroundRedundant hierarchical relations refer to such patterns as two paths from one concept to another, one with length one (direct) and the other with length greater than one (indirect). Each redundant relation represents a possibly unintended defect that needs to be corrected in the ontology quality assurance process. Detecting and eliminating redundant relations would help improve the results of all methods relying on the relevant ontological systems as knowledge source, such as the computation of semantic distance between concepts and for ontology matching and alignment.
resultsThis paper introduces a novel and scalable approach, called FEDRR - Fast, Exhaustive Detection of Redundant Relations - for quality assurance work during ontological evolution. FEDRR combines the algorithm ideas of Dynamic Programming with Topological Sort, for exhaustive mining of all redundant hierarchical relations in ontological hierarchies, in
conclusionsFEDRR provides a generally applicable, effective tool for systematic detecting redundant relations in large ontological systems for quality improvement.
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Registered trials
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.