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

Overview of attention for article published in Journal of Biomedical Semantics, August 2013
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Citations

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Title
The Vertebrate Trait Ontology: a controlled vocabulary for the annotation of trait data across species
Published in
Journal of Biomedical Semantics, August 2013
DOI 10.1186/2041-1480-4-13
Pubmed ID
Authors

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

The 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.

Mendeley readers

The data shown below were compiled from readership statistics for 40 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Netherlands 1 3%
Kenya 1 3%
Brazil 1 3%
Canada 1 3%
Mexico 1 3%
Russia 1 3%
United States 1 3%
Unknown 33 83%

Demographic breakdown

Readers by professional status Count As %
Researcher 9 23%
Other 5 13%
Student > Ph. D. Student 5 13%
Professor > Associate Professor 5 13%
Student > Postgraduate 3 8%
Other 9 23%
Unknown 4 10%
Readers by discipline Count As %
Agricultural and Biological Sciences 21 53%
Computer Science 5 13%
Biochemistry, Genetics and Molecular Biology 2 5%
Medicine and Dentistry 2 5%
Mathematics 1 3%
Other 3 8%
Unknown 6 15%

Attention Score in Context

This research output has an Altmetric Attention Score of 1. This is our high-level measure of the quality and quantity of online attention that it has received. This Attention Score, as well as the ranking and number of research outputs shown below, was calculated when the research output was last mentioned on 18 September 2015.
All research outputs
#15,484,648
of 17,520,445 outputs
Outputs from Journal of Biomedical Semantics
#338
of 358 outputs
Outputs of similar age
#166,441
of 194,582 outputs
Outputs of similar age from Journal of Biomedical Semantics
#17
of 17 outputs
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So far Altmetric has tracked 358 research outputs from this source. They receive a mean Attention Score of 4.5. This one is in the 1st percentile – i.e., 1% of its peers scored the same or lower than it.
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We're also able to compare this research output to 17 others from the same source and published within six weeks on either side of this one. This one is in the 1st percentile – i.e., 1% of its contemporaries scored the same or lower than it.