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Quantitative biomedical annotation using medical subject heading over-representation profiles (MeSHOPs)

Overview of attention for article published in BMC Bioinformatics, January 2012
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About this Attention Score

  • In the top 25% of all research outputs scored by Altmetric
  • High Attention Score compared to outputs of the same age (92nd percentile)
  • High Attention Score compared to outputs of the same age and source (99th percentile)

Mentioned by

blogs
1 blog
twitter
9 tweeters

Citations

dimensions_citation
22 Dimensions

Readers on

mendeley
45 Mendeley
citeulike
3 CiteULike
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Title
Quantitative biomedical annotation using medical subject heading over-representation profiles (MeSHOPs)
Published in
BMC Bioinformatics, January 2012
DOI 10.1186/1471-2105-13-249
Pubmed ID
Authors

Warren A Cheung, BF Ouellette, Wyeth W Wasserman

Abstract

MEDLINE®/PubMed® indexes over 20 million biomedical articles, providing curated annotation of its contents using a controlled vocabulary known as Medical Subject Headings (MeSH). The MeSH vocabulary, developed over 50+ years, provides a broad coverage of topics across biomedical research. Distilling the essential biomedical themes for a topic of interest from the relevant literature is important to both understand the importance of related concepts and discover new relationships.

Twitter Demographics

The data shown below were collected from the profiles of 9 tweeters 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 45 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Portugal 1 2%
Germany 1 2%
Netherlands 1 2%
United Kingdom 1 2%
Canada 1 2%
Russia 1 2%
United States 1 2%
Unknown 38 84%

Demographic breakdown

Readers by professional status Count As %
Researcher 11 24%
Student > Ph. D. Student 10 22%
Professor > Associate Professor 5 11%
Student > Bachelor 5 11%
Student > Master 4 9%
Other 9 20%
Unknown 1 2%
Readers by discipline Count As %
Computer Science 15 33%
Agricultural and Biological Sciences 8 18%
Biochemistry, Genetics and Molecular Biology 5 11%
Engineering 4 9%
Social Sciences 3 7%
Other 8 18%
Unknown 2 4%

Attention Score in Context

This research output has an Altmetric Attention Score of 14. 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 07 May 2013.
All research outputs
#977,706
of 12,373,386 outputs
Outputs from BMC Bioinformatics
#354
of 4,588 outputs
Outputs of similar age
#10,042
of 128,341 outputs
Outputs of similar age from BMC Bioinformatics
#2
of 38 outputs
Altmetric has tracked 12,373,386 research outputs across all sources so far. Compared to these this one has done particularly well and is in the 92nd percentile: it's in the top 10% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 4,588 research outputs from this source. They receive a mean Attention Score of 4.9. This one has done particularly well, scoring higher than 92% of its peers.
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 128,341 tracked outputs that were published within six weeks on either side of this one in any source. This one has done particularly well, scoring higher than 92% of its contemporaries.
We're also able to compare this research output to 38 others from the same source and published within six weeks on either side of this one. This one has done particularly well, scoring higher than 99% of its contemporaries.