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X Demographics
Mendeley readers
Attention Score in Context
| Title |
NPEBseq: nonparametric empirical bayesian-based procedure for differential expression analysis of RNA-seq data
|
|---|---|
| Published in |
BMC Bioinformatics, August 2013
|
| DOI | 10.1186/1471-2105-14-262 |
| Pubmed ID | |
| Authors |
Yingtao Bi, Ramana V Davuluri |
X Demographics
The data shown below were collected from the profiles of 10 X users who shared this research output. Click here to find out more about how the information was compiled.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| India | 2 | 20% |
| United States | 1 | 10% |
| Germany | 1 | 10% |
| France | 1 | 10% |
| Unknown | 5 | 50% |
Demographic breakdown
| Type | Count | As % |
|---|---|---|
| Scientists | 5 | 50% |
| Members of the public | 5 | 50% |
Mendeley readers
The data shown below were compiled from readership statistics for 223 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| United States | 5 | 2% |
| United Kingdom | 4 | 2% |
| Brazil | 2 | <1% |
| Germany | 2 | <1% |
| France | 1 | <1% |
| Sweden | 1 | <1% |
| Netherlands | 1 | <1% |
| South Africa | 1 | <1% |
| Denmark | 1 | <1% |
| Other | 1 | <1% |
| Unknown | 204 | 91% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Researcher | 62 | 28% |
| Student > Ph. D. Student | 61 | 27% |
| Student > Master | 30 | 13% |
| Professor > Associate Professor | 12 | 5% |
| Student > Doctoral Student | 11 | 5% |
| Other | 35 | 16% |
| Unknown | 12 | 5% |
| Readers by discipline | Count | As % |
|---|---|---|
| Agricultural and Biological Sciences | 119 | 53% |
| Biochemistry, Genetics and Molecular Biology | 39 | 17% |
| Computer Science | 13 | 6% |
| Mathematics | 5 | 2% |
| Chemistry | 5 | 2% |
| Other | 19 | 9% |
| Unknown | 23 | 10% |
Attention Score in Context
This research output has an Altmetric Attention Score of 20. 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 23 June 2014.
All research outputs
#1,714,990
of 24,086,561 outputs
Outputs from BMC Bioinformatics
#342
of 7,498 outputs
Outputs of similar age
#15,257
of 204,812 outputs
Outputs of similar age from BMC Bioinformatics
#7
of 86 outputs
Altmetric has tracked 24,086,561 research outputs across all sources so far. Compared to these this one has done particularly well and is in the 92nd percentile: it's in the top 10% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 7,498 research outputs from this source. They typically receive a little more attention than average, with a mean Attention Score of 5.5. This one has done particularly well, scoring higher than 95% 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 204,812 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 92% of its contemporaries.
We're also able to compare this research output to 86 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 93% of its contemporaries.