ArticleAMIA ... Annual Symposium proceedings. AMIA Symposium2012
An analysis of multi-type relational interactions in FMA using graph motifs with disjointness constraints.
Article in AMIA ... Annual Symposium proceedings. AMIA Symposium, 2012. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.
What it found
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
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Who cites it
5 citing papers in PubMed.
- Assessing the practice of biomedical ontology evaluation: Gaps and opportunities.Journal of biomedical informatics · 2018Review
- Biological Model Development as an Opportunity to Provide Content Auditing for the Foundational Model of Anatomy Ontology.AMIA ... Annual Symposium proceedings. AMIA Symposium · 2015Article
- MaPLE: A MapReduce Pipeline for Lattice-based Evaluation and Its Application to SNOMED CT.Proceedings : ... IEEE International Conference on Big Data. IEEE International Conference on Big Data · 2014Article
- An analysis of FMA using structural self-bisimilarity.Journal of biomedical informatics · 2013Article
- Dissecting the Ambiguity of FMA Concept Names Using Taxonomy and Partonomy Structural Information.AMIA Joint Summits on Translational Science proceedings. AMIA Joint Summits on Translational Science · 2013Article
Corrections and comments
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Authors and funding
6 authors.
Funding
Abstract
The interaction of multiple types of relationships among anatomical classes in the Foundational Model of Anatomy (FMA) can provide inferred information valuable for quality assurance. This paper introduces a method called Motif Checking (MOCH) to study the effects of such multi-relation type interactions for detecting logical inconsistencies as well as other anomalies represented by the motifs. MOCH represents patterns of multi-type interaction as small labeled (with multiple types of edges) sub-graph motifs, whose nodes represent class variables, and labeled edges represent relational types. By representing FMA as an RDF graph and motifs as SPARQL queries, fragments of FMA are automatically obtained as auditing candidates. Leveraging the scalability and reconfigurability of Semantic Web Technology, we performed exhaustive analyses of a variety of labeled sub-graph motifs. The quality assurance feature of MOCH comes from the distinct use of a subset of the edges of the graph motifs as constraints for disjointness, whereby bringing in rule-based flavor to the approach as well. With possible disjointness implied by antonyms, we performed manual inspection of the resulting FMA fragments and tracked down sources of abnormal inferred conclusions (logical inconsistencies), which are amendable for programmatic revision of the FMA. Our results demonstrate that MOCH provides a unique source of valuable information for quality assurance. Since our approach is general, it is applicable to any ontological system with an OWL representation.
Indexed as
Identifiers
23304382PMC3540524What OpenQuestion holds
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.