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GC-Content Normalization for RNA-Seq Data

Overview of attention for article published in BMC Bioinformatics, December 2011
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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 (95th percentile)
  • High Attention Score compared to outputs of the same age and source (96th percentile)

Mentioned by

blogs
1 blog
twitter
18 X users
patent
4 patents
wikipedia
1 Wikipedia page

Citations

dimensions_citation
701 Dimensions

Readers on

mendeley
1097 Mendeley
citeulike
28 CiteULike
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Title
GC-Content Normalization for RNA-Seq Data
Published in
BMC Bioinformatics, December 2011
DOI 10.1186/1471-2105-12-480
Pubmed ID
Authors

Davide Risso, Katja Schwartz, Gavin Sherlock, Sandrine Dudoit

X Demographics

X Demographics

The data shown below were collected from the profiles of 18 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 1,097 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
United States 23 2%
Germany 10 <1%
United Kingdom 9 <1%
France 4 <1%
Italy 3 <1%
Brazil 3 <1%
Japan 3 <1%
Sweden 2 <1%
Portugal 2 <1%
Other 20 2%
Unknown 1018 93%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 316 29%
Researcher 253 23%
Student > Master 103 9%
Student > Bachelor 83 8%
Student > Doctoral Student 53 5%
Other 158 14%
Unknown 131 12%
Readers by discipline Count As %
Agricultural and Biological Sciences 429 39%
Biochemistry, Genetics and Molecular Biology 258 24%
Computer Science 59 5%
Medicine and Dentistry 50 5%
Mathematics 40 4%
Other 109 10%
Unknown 152 14%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 26. 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 11 May 2023.
All research outputs
#1,516,466
of 26,017,215 outputs
Outputs from BMC Bioinformatics
#214
of 7,793 outputs
Outputs of similar age
#9,357
of 243,579 outputs
Outputs of similar age from BMC Bioinformatics
#4
of 102 outputs
Altmetric has tracked 26,017,215 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 7,793 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 97% 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 243,579 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 95% of its contemporaries.
We're also able to compare this research output to 102 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.