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X Demographics
Mendeley readers
Attention Score in Context
Title |
Do count-based differential expression methods perform poorly when genes are expressed in only one condition?
|
---|---|
Published in |
Genome Biology, October 2015
|
DOI | 10.1186/s13059-015-0781-3 |
Pubmed ID | |
Authors |
Xiaobei Zhou, Mark D. Robinson |
Abstract |
A response to 'Comprehensive evaluation of differential gene expression analysis methods for RNA-seq data' by Rapaport F, Khanin R, Liang Y, Pirun M, Krek A, Zumbo P, Mason CE, Socci ND and Betel D in Genome Biology, 2013, 14:R95. |
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.
Geographical breakdown
Country | Count | As % |
---|---|---|
Australia | 5 | 28% |
United States | 4 | 22% |
Germany | 2 | 11% |
Spain | 2 | 11% |
United Kingdom | 1 | 6% |
Canada | 1 | 6% |
France | 1 | 6% |
Unknown | 2 | 11% |
Demographic breakdown
Type | Count | As % |
---|---|---|
Scientists | 16 | 89% |
Members of the public | 2 | 11% |
Mendeley readers
The data shown below were compiled from readership statistics for 75 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
Country | Count | As % |
---|---|---|
United States | 2 | 3% |
Germany | 1 | 1% |
United Kingdom | 1 | 1% |
Italy | 1 | 1% |
Taiwan | 1 | 1% |
Canada | 1 | 1% |
Unknown | 68 | 91% |
Demographic breakdown
Readers by professional status | Count | As % |
---|---|---|
Researcher | 25 | 33% |
Student > Ph. D. Student | 16 | 21% |
Student > Master | 8 | 11% |
Other | 7 | 9% |
Professor > Associate Professor | 4 | 5% |
Other | 12 | 16% |
Unknown | 3 | 4% |
Readers by discipline | Count | As % |
---|---|---|
Agricultural and Biological Sciences | 41 | 55% |
Biochemistry, Genetics and Molecular Biology | 16 | 21% |
Computer Science | 5 | 7% |
Mathematics | 2 | 3% |
Engineering | 2 | 3% |
Other | 3 | 4% |
Unknown | 6 | 8% |
Attention Score in Context
This research output has an Altmetric Attention Score of 9. 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 13 November 2015.
All research outputs
#4,127,714
of 25,374,647 outputs
Outputs from Genome Biology
#2,597
of 4,467 outputs
Outputs of similar age
#51,932
of 290,041 outputs
Outputs of similar age from Genome Biology
#59
of 84 outputs
Altmetric has tracked 25,374,647 research outputs across all sources so far. Compared to these this one has done well and is in the 83rd percentile: it's in the top 25% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 4,467 research outputs from this source. They typically receive a lot more attention than average, with a mean Attention Score of 27.6. This one is in the 41st percentile – i.e., 41% of its peers scored the same or lower than it.
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 290,041 tracked outputs that were published within six weeks on either side of this one in any source. This one has done well, scoring higher than 82% of its contemporaries.
We're also able to compare this research output to 84 others from the same source and published within six weeks on either side of this one. This one is in the 29th percentile – i.e., 29% of its contemporaries scored the same or lower than it.