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Overview of attention for article published in BMC Bioinformatics, January 2004
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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 (94th percentile)
  • High Attention Score compared to outputs of the same age and source (96th percentile)

Mentioned by

blogs
3 blogs

Citations

dimensions_citation
19 Dimensions

Readers on

mendeley
76 Mendeley
citeulike
19 CiteULike
connotea
5 Connotea
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Title
Published in
BMC Bioinformatics, January 2004
DOI 10.1186/1471-2105-5-146
Pubmed ID
Authors

Diane E. Oliver, Gaurav Bhalotia, Ariel S. Schwartz, Russ B. Altman, Marti A. Hearst

Abstract

Researchers who use MEDLINE for text mining, information extraction, or natural language processing may benefit from having a copy of MEDLINE that they can manage locally. The National Library of Medicine (NLM) distributes MEDLINE in eXtensible Markup Language (XML)-formatted text files, but it is difficult to query MEDLINE in that format. We have developed software tools to parse the MEDLINE data files and load their contents into a relational database. Although the task is conceptually straightforward, the size and scope of MEDLINE make the task nontrivial. Given the increasing importance of text analysis in biology and medicine, we believe a local installation of MEDLINE will provide helpful computing infrastructure for researchers.

Mendeley readers

The data shown below were compiled from readership statistics for 76 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
United States 9 12%
United Kingdom 4 5%
Mexico 3 4%
France 2 3%
Spain 2 3%
Tunisia 1 1%
Australia 1 1%
Italy 1 1%
Brazil 1 1%
Other 1 1%
Unknown 51 67%

Demographic breakdown

Readers by professional status Count As %
Researcher 29 38%
Student > Ph. D. Student 12 16%
Other 9 12%
Student > Master 5 7%
Professor > Associate Professor 5 7%
Other 13 17%
Unknown 3 4%
Readers by discipline Count As %
Agricultural and Biological Sciences 30 39%
Computer Science 18 24%
Medicine and Dentistry 11 14%
Biochemistry, Genetics and Molecular Biology 4 5%
Economics, Econometrics and Finance 2 3%
Other 8 11%
Unknown 3 4%

Attention Score in Context

This research output has an Altmetric Attention Score of 21. 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 15 August 2008.
All research outputs
#663,766
of 12,373,386 outputs
Outputs from BMC Bioinformatics
#169
of 4,576 outputs
Outputs of similar age
#646,253
of 11,793,654 outputs
Outputs of similar age from BMC Bioinformatics
#169
of 4,577 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 94th percentile: it's in the top 10% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 4,576 research outputs from this source. They receive a mean Attention Score of 4.9. This one has done particularly well, scoring higher than 96% 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 11,793,654 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 94% of its contemporaries.
We're also able to compare this research output to 4,577 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 96% of its contemporaries.