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Mendeley readers
Attention Score in Context
| 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 | 8 | 20% |
| Professor > Associate Professor | 6 | 15% |
| Other | 5 | 13% |
| Student > Ph. D. Student | 5 | 13% |
| Student > Postgraduate | 3 | 8% |
| Other | 9 | 23% |
| Unknown | 4 | 10% |
| Readers by discipline | Count | As % |
|---|---|---|
| Agricultural and Biological Sciences | 22 | 55% |
| Computer Science | 4 | 10% |
| Medicine and Dentistry | 3 | 8% |
| Biochemistry, Genetics and Molecular Biology | 2 | 5% |
| Mathematics | 1 | 3% |
| Other | 3 | 8% |
| Unknown | 5 | 13% |
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
#20,207,295
of 22,727,570 outputs
Outputs from Journal of Biomedical Semantics
#335
of 364 outputs
Outputs of similar age
#173,286
of 197,327 outputs
Outputs of similar age from Journal of Biomedical Semantics
#1
of 1 outputs
Altmetric has tracked 22,727,570 research outputs across all sources so far. This one is in the 1st percentile – i.e., 1% of other outputs scored the same or lower than it.
So far Altmetric has tracked 364 research outputs from this source. They receive a mean Attention Score of 4.6. This one is in the 1st percentile – i.e., 1% of its peers scored the same or lower than it.
Older research outputs will score higher simply because they've had more time to accumulate mentions. To account for age we can compare this Altmetric Attention Score to the 197,327 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 1st percentile – i.e., 1% of its contemporaries scored the same or lower than it.
We're also able to compare this research output to 1 others from the same source and published within six weeks on either side of this one. This one has scored higher than all of them