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OntologyWidget – a reusable, embeddable widget for easily locating ontology terms

Overview of attention for article published in BMC Bioinformatics, September 2007
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Mentioned by

twitter
1 tweeter

Citations

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2 Dimensions

Readers on

mendeley
38 Mendeley
citeulike
8 CiteULike
connotea
1 Connotea
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.

Twitter Demographics

The data shown below were collected from the profile of 1 tweeter who shared this research output. Click here to find out more about how the information was compiled.

Mendeley readers

The data shown below were compiled from readership statistics for 38 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%
United Kingdom 1 3%
Netherlands 1 3%
Malaysia 1 3%
Iceland 1 3%
Switzerland 1 3%
Japan 1 3%
Germany 1 3%
Other 1 3%
Unknown 25 66%

Demographic breakdown

Readers by professional status Count As %
Researcher 17 45%
Student > Master 6 16%
Student > Ph. D. Student 4 11%
Student > Bachelor 3 8%
Professor > Associate Professor 3 8%
Other 5 13%
Readers by discipline Count As %
Agricultural and Biological Sciences 13 34%
Medicine and Dentistry 4 11%
Chemistry 3 8%
Biochemistry, Genetics and Molecular Biology 3 8%
Computer Science 3 8%
Other 11 29%
Unknown 1 3%

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
#9,906,108
of 12,373,386 outputs
Outputs from BMC Bioinformatics
#3,815
of 4,576 outputs
Outputs of similar age
#183,123
of 260,821 outputs
Outputs of similar age from BMC Bioinformatics
#318
of 375 outputs
Altmetric has tracked 12,373,386 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 4,576 research outputs from this source. They receive a mean Attention Score of 4.9. This one is in the 7th percentile – i.e., 7% 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 260,821 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 15th percentile – i.e., 15% of its contemporaries scored the same or lower than it.
We're also able to compare this research output to 375 others from the same source and published within six weeks on either side of this one. This one is in the 6th percentile – i.e., 6% of its contemporaries scored the same or lower than it.