ArticleJournal of biomedical semantics2013
The clinical measurement, measurement method and experimental condition ontologies: expansion, improvements and new applications.
Article in Journal of biomedical semantics, 2013. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 26 papers, 1 of them a synthesis that pooled it.
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
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
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Who cites it
26 citing papers in PubMed, 1 synthesis or guideline pooled it.
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- Generating Clinical-Grade Gene-Disease Validity Classifications Through the ClinGen Data Platforms.Annual review of biomedical data science · 2024Review
- The Ontology of Biological Attributes (OBA)-computational traits for the life sciences.Mammalian genome : official journal of the International Mammalian Genome Society · 2023Article
- Rare disease research resources at the Rat Genome Database.Genetics · 2023Article
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- A combinatorial approach implementing new database structures to facilitate practical data curation management of QTL, association, correlation and heritability data on trait variants.Database : the journal of biological databases and curation · 2023Article
- The Ontology of Biological Attributes (OBA) - Computational Traits for the Life Sciences.bioRxiv : the preprint server for biology · 2023Article
- Ontologies for increasing the FAIRness of plant research data.Frontiers in plant science · 2023Review
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- Providing Adverse Outcome Pathways from the AOP-Wiki in a Semantic Web Format to Increase Usability and Accessibility of the Content.Applied in vitro toxicology · 2022Article
- The AOP-DB RDF: Applying FAIR Principles to the Semantic Integration of AOP Data Using the Research Description Framework.Frontiers in toxicology · 2022Article
- Modelling kidney disease using ontology: insights from the Kidney Precision Medicine Project.Nature reviews. Nephrology · 2020Review
- Building a livestock genetic and genomic information knowledgebase through integrative developments of Animal QTLdb and CorrDB.Nucleic acids research · 2019Article
- Quantitative phenotype analysis to identify, validate and compare rat disease models.Database : the journal of biological databases and curation · 2019Article
- Integrated curation and data mining for disease and phenotype models at the Rat Genome Database.Database : the journal of biological databases and curation · 2019Article
- Ensembl variation resources.Database : the journal of biological databases and curation · 2018Article
- Rat Genome and Model Resources.ILAR journal · 2017Review
- Comprehensive coverage of cardiovascular disease data in the disease portals at the Rat Genome Database.Physiological genomics · 2016Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
14 authors.
Funding
Abstract
backgroundThe Clinical Measurement Ontology (CMO), Measurement Method Ontology (MMO), and Experimental Condition Ontology (XCO) were originally developed at the Rat Genome Database (RGD) to standardize quantitative rat phenotype data in order to integrate results from multiple studies into the PhenoMiner database and data mining tool. These ontologies provide the framework for presenting what was measured, how it was measured, and under what conditions it was measured.
resultsThere has been a continuing expansion of subdomains in each ontology with a parallel 2-3 fold increase in the total number of terms, substantially increasing the size and improving the scope of the ontologies. The proportion of terms with textual definitions has increased from ~60% to over 80% with greater synchronization of format and content throughout the three ontologies. Representation of definition source Uniform Resource Identifiers (URI) has been standardized, including the removal of all non-URI characters, and systematic versioning of all ontology files has been implemented. The continued expansion and success of these ontologies has facilitated the integration of more than 60,000 records into the RGD PhenoMiner database. In addition, new applications of these ontologies, such as annotation of Quantitative Trait Loci (QTL), have been added at the sites actively using them, including RGD and the Animal QTL Database.
conclusionsThe improvements to these three ontologies have been substantial, and development is ongoing. New terms and expansions to the ontologies continue to be added as a result of active curation efforts at RGD and the Animal QTL database. Use of these vocabularies to standardize data representation for quantitative phenotypes and quantitative trait loci across databases for multiple species has demonstrated their utility for integrating diverse data types from multiple sources. These ontologies are freely available for download and use from the NCBO BioPortal website at http://bioportal.bioontology.org/ontologies/1583 (CMO), http://bioportal.bioontology.org/ontologies/1584 (MMO), and http://bioportal.bioontology.org/ontologies/1585 (XCO), or from the RGD ftp site at ftp://rgd.mcw.edu/pub/ontology/.
Identifiers
What 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.