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GSVA: gene set variation analysis for microarray and RNA-Seq data

Overview of attention for article published in BMC Bioinformatics, January 2013
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About this Attention Score

  • In the top 5% of all research outputs scored by Altmetric
  • Among the highest-scoring outputs from this source (#23 of 7,763)
  • High Attention Score compared to outputs of the same age (98th percentile)
  • High Attention Score compared to outputs of the same age and source (99th percentile)

Mentioned by

news
5 news outlets
blogs
4 blogs
twitter
14 X users
patent
42 patents
wikipedia
1 Wikipedia page

Citations

dimensions_citation
8044 Dimensions

Readers on

mendeley
1996 Mendeley
citeulike
9 CiteULike
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Title
GSVA: gene set variation analysis for microarray and RNA-Seq data
Published in
BMC Bioinformatics, January 2013
DOI 10.1186/1471-2105-14-7
Pubmed ID
Authors

Sonja Hänzelmann, Robert Castelo, Justin Guinney

X Demographics

X Demographics

The data shown below were collected from the profiles of 14 X users who shared this research output. Click here to find out more about how the information was compiled.
Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 1,996 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
United States 12 <1%
Spain 6 <1%
United Kingdom 6 <1%
Germany 3 <1%
Australia 3 <1%
Brazil 2 <1%
Sweden 2 <1%
Netherlands 1 <1%
India 1 <1%
Other 6 <1%
Unknown 1954 98%

Demographic breakdown

Readers by professional status Count As %
Researcher 428 21%
Student > Ph. D. Student 393 20%
Student > Master 180 9%
Student > Bachelor 127 6%
Student > Doctoral Student 102 5%
Other 254 13%
Unknown 512 26%
Readers by discipline Count As %
Biochemistry, Genetics and Molecular Biology 476 24%
Agricultural and Biological Sciences 336 17%
Medicine and Dentistry 213 11%
Computer Science 101 5%
Immunology and Microbiology 73 4%
Other 215 11%
Unknown 582 29%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 82. 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 31 January 2024.
All research outputs
#528,175
of 25,837,817 outputs
Outputs from BMC Bioinformatics
#23
of 7,763 outputs
Outputs of similar age
#3,833
of 296,777 outputs
Outputs of similar age from BMC Bioinformatics
#1
of 137 outputs
Altmetric has tracked 25,837,817 research outputs across all sources so far. Compared to these this one has done particularly well and is in the 97th percentile: it's in the top 5% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 7,763 research outputs from this source. They typically receive a little more attention than average, with a mean Attention Score of 5.6. This one has done particularly well, scoring higher than 99% 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 296,777 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 98% of its contemporaries.
We're also able to compare this research output to 137 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.