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Evaluation of statistical methods for normalization and differential expression in mRNA-Seq experiments

Overview of attention for article published in BMC Bioinformatics, February 2010
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About this Attention Score

  • In the top 5% 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 (97th percentile)

Mentioned by

blogs
2 blogs
twitter
6 X users
patent
6 patents
wikipedia
1 Wikipedia page
q&a
3 Q&A threads

Citations

dimensions_citation
1416 Dimensions

Readers on

mendeley
2703 Mendeley
citeulike
68 CiteULike
connotea
5 Connotea
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Title
Evaluation of statistical methods for normalization and differential expression in mRNA-Seq experiments
Published in
BMC Bioinformatics, February 2010
DOI 10.1186/1471-2105-11-94
Pubmed ID
Authors

James H Bullard, Elizabeth Purdom, Kasper D Hansen, Sandrine Dudoit

X Demographics

X Demographics

The data shown below were collected from the profiles of 6 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 2,703 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
United States 127 5%
Germany 30 1%
United Kingdom 30 1%
France 15 <1%
Brazil 12 <1%
Italy 10 <1%
Canada 10 <1%
Mexico 9 <1%
Spain 8 <1%
Other 68 3%
Unknown 2384 88%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 741 27%
Researcher 689 25%
Student > Master 300 11%
Student > Bachelor 177 7%
Student > Doctoral Student 143 5%
Other 435 16%
Unknown 218 8%
Readers by discipline Count As %
Agricultural and Biological Sciences 1417 52%
Biochemistry, Genetics and Molecular Biology 470 17%
Computer Science 145 5%
Medicine and Dentistry 88 3%
Mathematics 87 3%
Other 229 8%
Unknown 267 10%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 36. 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 August 2021.
All research outputs
#1,153,327
of 26,017,215 outputs
Outputs from BMC Bioinformatics
#106
of 7,793 outputs
Outputs of similar age
#3,660
of 106,963 outputs
Outputs of similar age from BMC Bioinformatics
#2
of 68 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 95th percentile: it's in the top 5% 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 98% 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 106,963 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 68 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 97% of its contemporaries.