Evidence map›Paper›PMID 22654893›Full record

ArticleFrontiers in genetics2012

Three ontologies to define phenotype measurement data.

Mary Shimoyama, Rajni Nigam, Leslie Sanders McIntosh, Rakesh Nagarajan, Treva Rice, D C Rao, Melinda R Dwinell

Abstract read
In one paragraph

Article in Frontiers in genetics, 2012. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 37 papers.

0numbers the graph read from it
0cells of the map it votes in
37citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

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.

2 · The registry

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.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

37 citing papers in PubMed.

  1. Article
  2. Mapping of EFO terms from the GWAS catalog data to multiple ontologies at the Rat Genome Database.Database : the journal of biological databases and curation · 2026
    Article
  3. The Immunopeptidomics Ontology (ImPO).Database : the journal of biological databases and curation · 2024
    Article
  4. Article
  5. The Ontology of Biological Attributes (OBA)-computational traits for the life sciences.Mammalian genome : official journal of the International Mammalian Genome Society · 2023
    Article
  6. Review
  7. Article
  8. Article
  9. Article
  10. Review
  11. Article
  12. Quantitative phenotype analysis to identify, validate and compare rat disease models.Database : the journal of biological databases and curation · 2019
    Article
  13. Ensembl 2018.Nucleic acids research · 2018
    Article
  14. Article
  15. Article
  16. Review
  17. Article
  18. Review
  19. Article
  20. The digital revolution in phenotyping.Briefings in bioinformatics · 2016
    Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

7 authors.

Mary ShimoyamaHuman and Molecular Genetics Center, Medical College of Wisconsin Milwaukee, WI, USA. shimoyama@mcw.edu
Rajni Nigam
Leslie Sanders McIntosh
Rakesh Nagarajan
Treva Rice
D C Rao
Melinda R Dwinell

Funding

RAT GENOME DATABASER01HL064541 · NHLBI · MEDICAL COLLEGE OF WISCONSIN · PI ANNE E. KWITEK · 1999 to 2026
$50.0M
Washington University Institute of Clinical and Translational SciencesUL1TR000448 · NCATS · WASHINGTON UNIVERSITY · PI EVANOFF, BRADLEY A · 2012 to 2016
$41.4M
Integration of phenotype data from multiple centers using ontologiesR01HL094271 · NHLBI · MEDICAL COLLEGE OF WISCONSIN · PI DWINELL, MELINDA R · 2010 to 2012
$1.1M
DEVELOPMENT OF DATA ONTOLOGIES FOR INTEGRATING MULTI-CENTER CARDIOVASCULAR STUDIER01HL094286 · NHLBI · WASHINGTON UNIVERSITY · PI NAGARAJAN, RAKESH, RAO, DABEERU C · 2009 to 2010
$963k
NCATS NIH HHS UL1 TR000448NHLBI NIH HHS R01 HL064541NHLBI NIH HHS R01 HL094271NHLBI NIH HHS R01 HL094286
6 · The paper itself

Abstract

backgroundThere is an increasing need to integrate phenotype measurement data across studies for both human studies and those involving model organisms. Current practices allow researchers to access only those data involved in a single experiment or multiple experiments utilizing the same protocol.

resultsThree ontologies were created: Clinical Measurement Ontology, Measurement Method Ontology and Experimental Condition Ontology. These ontologies provided the framework for integration of rat phenotype data from multiple studies into a single resource as well as facilitated data integration from multiple human epidemiological studies into a centralized repository.

conclusionAn ontology based framework for phenotype measurement data affords the ability to successfully integrate vital phenotype data into critical resources, regardless of underlying technological structures allowing the user to easily query and retrieve data from multiple studies.

Indexed as

ontologyphenotype

Identifiers

PMID22654893
PMCPMC3361058

What OpenQuestion holds

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LicenceCC BY-NC
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Registered trials

None linked

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.