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X Demographics
Mendeley readers
Attention Score in Context
| Title |
OntologyWidget – a reusable, embeddable widget for easily locating ontology terms
|
|---|---|
| Published in |
BMC Bioinformatics, September 2007
|
| DOI | 10.1186/1471-2105-8-338 |
| Pubmed ID | |
| Authors |
Catherine C Beauheim, Farrell Wymore, Michael Nitzberg, Zachariah K Zachariah, Heng Jin, JH Pate Skene, Catherine A Ball, Gavin Sherlock |
| Abstract |
Biomedical ontologies are being widely used to annotate biological data in a computer-accessible, consistent and well-defined manner. However, due to their size and complexity, annotating data with appropriate terms from an ontology is often challenging for experts and non-experts alike, because there exist few tools that allow one to quickly find relevant ontology terms to easily populate a web form. |
X Demographics
The data shown below were collected from the profile of 1 X user who shared this research output. Click here to find out more about how the information was compiled.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| India | 1 | 100% |
Demographic breakdown
| Type | Count | As % |
|---|---|---|
| Practitioners (doctors, other healthcare professionals) | 1 | 100% |
Mendeley readers
The data shown below were compiled from readership statistics for 39 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| United States | 3 | 8% |
| Mexico | 2 | 5% |
| Malaysia | 1 | 3% |
| Netherlands | 1 | 3% |
| United Kingdom | 1 | 3% |
| Germany | 1 | 3% |
| Switzerland | 1 | 3% |
| Iceland | 1 | 3% |
| Japan | 1 | 3% |
| Other | 1 | 3% |
| Unknown | 26 | 67% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Researcher | 17 | 44% |
| Student > Master | 6 | 15% |
| Student > Ph. D. Student | 4 | 10% |
| Student > Bachelor | 3 | 8% |
| Professor > Associate Professor | 3 | 8% |
| Other | 5 | 13% |
| Unknown | 1 | 3% |
| Readers by discipline | Count | As % |
|---|---|---|
| Agricultural and Biological Sciences | 13 | 33% |
| Medicine and Dentistry | 4 | 10% |
| Biochemistry, Genetics and Molecular Biology | 3 | 8% |
| Computer Science | 3 | 8% |
| Arts and Humanities | 3 | 8% |
| Other | 11 | 28% |
| Unknown | 2 | 5% |
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 17 January 2013.
All research outputs
#18,326,065
of 22,693,205 outputs
Outputs from BMC Bioinformatics
#6,289
of 7,254 outputs
Outputs of similar age
#64,792
of 69,829 outputs
Outputs of similar age from BMC Bioinformatics
#38
of 45 outputs
Altmetric has tracked 22,693,205 research outputs across all sources so far. This one is in the 11th percentile – i.e., 11% of other outputs scored the same or lower than it.
So far Altmetric has tracked 7,254 research outputs from this source. They typically receive a little more attention than average, with a mean Attention Score of 5.4. This one is in the 5th percentile – i.e., 5% 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 69,829 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 3rd percentile – i.e., 3% of its contemporaries scored the same or lower than it.
We're also able to compare this research output to 45 others from the same source and published within six weeks on either side of this one. This one is in the 4th percentile – i.e., 4% of its contemporaries scored the same or lower than it.