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Overview of attention for article published in BMC Bioinformatics, January 2004
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About this Attention Score

  • Good Attention Score compared to outputs of the same age (66th percentile)
  • Good Attention Score compared to outputs of the same age and source (69th percentile)

Mentioned by

patent
1 patent

Citations

dimensions_citation
195 Dimensions

Readers on

mendeley
191 Mendeley
citeulike
8 CiteULike
connotea
2 Connotea
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Title
Published in
BMC Bioinformatics, January 2004
DOI 10.1186/1471-2105-5-118
Pubmed ID
Authors

Carsten O Daub, Ralf Steuer, Joachim Selbig, Sebastian Kloska

Abstract

The information theoretic concept of mutual information provides a general framework to evaluate dependencies between variables. In the context of the clustering of genes with similar patterns of expression it has been suggested as a general quantity of similarity to extend commonly used linear measures. Since mutual information is defined in terms of discrete variables, its application to continuous data requires the use of binning procedures, which can lead to significant numerical errors for datasets of small or moderate size.

Mendeley readers

The data shown below were compiled from readership statistics for 191 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
United States 5 3%
Germany 2 1%
Belgium 2 1%
Finland 1 <1%
Norway 1 <1%
Italy 1 <1%
Hong Kong 1 <1%
Brazil 1 <1%
Israel 1 <1%
Other 10 5%
Unknown 166 87%

Demographic breakdown

Readers by professional status Count As %
Researcher 60 31%
Student > Ph. D. Student 48 25%
Student > Master 24 13%
Professor > Associate Professor 11 6%
Professor 10 5%
Other 26 14%
Unknown 12 6%
Readers by discipline Count As %
Agricultural and Biological Sciences 63 33%
Computer Science 35 18%
Engineering 23 12%
Biochemistry, Genetics and Molecular Biology 14 7%
Mathematics 12 6%
Other 25 13%
Unknown 19 10%

Attention Score in Context

This research output has an Altmetric Attention Score of 3. 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 10 December 2015.
All research outputs
#3,577,527
of 12,373,386 outputs
Outputs from BMC Bioinformatics
#1,717
of 4,576 outputs
Outputs of similar age
#78,161
of 265,107 outputs
Outputs of similar age from BMC Bioinformatics
#26
of 98 outputs
Altmetric has tracked 12,373,386 research outputs across all sources so far. This one is in the 49th percentile – i.e., 49% 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 has gotten more attention than average, scoring higher than 53% 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 265,107 tracked outputs that were published within six weeks on either side of this one in any source. This one has gotten more attention than average, scoring higher than 66% of its contemporaries.
We're also able to compare this research output to 98 others from the same source and published within six weeks on either side of this one. This one has gotten more attention than average, scoring higher than 69% of its contemporaries.