Evidence map›Paper›PMID 23937709›Full record

ArticleJournal of biomedical semantics2013

The Vertebrate Trait Ontology: a controlled vocabulary for the annotation of trait data across species.

Carissa A Park, Susan M Bello, Cynthia L Smith, Zhi-Liang Hu, Diane H Munzenmaier, Rajni Nigam, Jennifer R Smith, Mary Shimoyama, Janan T Eppig, James M Reecy

Abstract read
In one paragraph

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 30 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
30citing papers in PubMed, 1 pooled it
–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

30 citing papers in PubMed, 1 synthesis or guideline pooled it.

  1. Mouse phenome database: curated data repository with interactive multi-population and multi-trait analyses.Mammalian genome : official journal of the International Mammalian Genome Society · 2023
    Pooled it
  2. Article
  3. 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
  4. Article
  5. Article
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  8. The Ontology of Biological Attributes (OBA)-computational traits for the life sciences.Mammalian genome : official journal of the International Mammalian Genome Society · 2023
    Article
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  10. Article
  11. Article
  12. Article
  13. Article
  14. Article
  15. Article
  16. Article
  17. Article
  18. Where to search top-K biomedical ontologies?Briefings in bioinformatics · 2019
    Review
  19. Data gaps and opportunities for comparative and conservation biology.Proceedings of the National Academy of Sciences of the United States of America · 2019
    Article
  20. 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

10 authors.

Carissa A ParkDepartment of Animal Science, Iowa State University, Ames, IA, USA. jreecy@iastate.edu.
Susan M Bello
Cynthia L Smith
Zhi-Liang Hu
Diane H Munzenmaier
Rajni Nigam
Jennifer R Smith
Mary Shimoyama
Janan T Eppig
James M Reecy

Funding

Mouse Genome DatabaseU41HG000330 · NHGRI · JACKSON LABORATORY · PI BLAKE, JUDITH A, BULT, CAROL J · 2011 to 2020
$45.5M
NHGRI NIH HHS U41 HG000330
6 · The paper itself

Abstract

backgroundThe use of ontologies to standardize biological data and facilitate comparisons among datasets has steadily grown as the complexity and amount of available data have increased. Despite the numerous ontologies available, one area currently lacking a robust ontology is the description of vertebrate traits. A trait is defined as any measurable or observable characteristic pertaining to an organism or any of its substructures. While there are several ontologies to describe entities and processes in phenotypes, diseases, and clinical measurements, one has not been developed for vertebrate traits; the Vertebrate Trait Ontology (VT) was created to fill this void. DESCRIPTION: Significant inconsistencies in trait nomenclature exist in the literature, and additional difficulties arise when trait data are compared across species. The VT is a unified trait vocabulary created to aid in the transfer of data within and between species and to facilitate investigation of the genetic basis of traits. Trait information provides a valuable link between the measurements that are used to assess the trait, the phenotypes related to the traits, and the diseases associated with one or more phenotypes. Because multiple clinical and morphological measurements are often used to assess a single trait, and a single measurement can be used to assess multiple physiological processes, providing investigators with standardized annotations for trait data will allow them to investigate connections among these data types.

conclusionsThe annotation of genomic data with ontology terms provides unique opportunities for data mining and analysis. Links between data in disparate databases can be identified and explored, a strategy that is particularly useful for cross-species comparisons or in situations involving inconsistent terminology. The VT provides a common basis for the description of traits in multiple vertebrate species. It is being used in the Rat Genome Database and Animal QTL Database for annotation of QTL data for rat, cattle, chicken, swine, sheep, and rainbow trout, and in the Mouse Phenome Database to annotate strain characterization data. In these databases, data are also cross-referenced to applicable terms from other ontologies, providing additional avenues for data mining and analysis. The ontology is available at http://bioportal.bioontology.org/ontologies/50138.

Identifiers

PMID23937709
PMCPMC3851175

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LicenceCC BY
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Registered trials

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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.