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Decode-seq: a practical approach to improve differential gene expression analysis

Overview of attention for article published in Genome Biology, March 2020
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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 (94th percentile)
  • High Attention Score compared to outputs of the same age and source (87th percentile)

Mentioned by

news
2 news outlets
blogs
2 blogs
twitter
51 X users

Citations

dimensions_citation
11 Dimensions

Readers on

mendeley
53 Mendeley
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Title
Decode-seq: a practical approach to improve differential gene expression analysis
Published in
Genome Biology, March 2020
DOI 10.1186/s13059-020-01966-9
Pubmed ID
Authors

Yingshu Li, Hang Yang, Hujun Zhang, Yongjie Liu, Hanqiao Shang, Herong Zhao, Ting Zhang, Qiang Tu

X Demographics

X Demographics

The data shown below were collected from the profiles of 51 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 53 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 53 100%

Demographic breakdown

Readers by professional status Count As %
Researcher 14 26%
Student > Ph. D. Student 8 15%
Student > Master 6 11%
Student > Bachelor 4 8%
Student > Doctoral Student 3 6%
Other 9 17%
Unknown 9 17%
Readers by discipline Count As %
Biochemistry, Genetics and Molecular Biology 20 38%
Agricultural and Biological Sciences 11 21%
Computer Science 2 4%
Neuroscience 2 4%
Chemical Engineering 1 2%
Other 4 8%
Unknown 13 25%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 53. 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 16 April 2020.
All research outputs
#782,384
of 24,998,746 outputs
Outputs from Genome Biology
#523
of 4,419 outputs
Outputs of similar age
#20,102
of 372,654 outputs
Outputs of similar age from Genome Biology
#11
of 79 outputs
Altmetric has tracked 24,998,746 research outputs across all sources so far. Compared to these this one has done particularly well and is in the 96th percentile: it's in the top 5% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 4,419 research outputs from this source. They typically receive a lot more attention than average, with a mean Attention Score of 27.6. This one has done well, scoring higher than 88% 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 372,654 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 79 others from the same source and published within six weeks on either side of this one. This one has done well, scoring higher than 87% of its contemporaries.