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X Demographics
Mendeley readers
Attention Score in Context
| Title |
BADGE: A novel Bayesian model for accurate abundance quantification and differential analysis of RNA-Seq data
|
|---|---|
| Published in |
BMC Bioinformatics, September 2014
|
| DOI | 10.1186/1471-2105-15-s9-s6 |
| Pubmed ID | |
| Authors |
Jinghua Gu, Xiao Wang, Leena Halakivi-Clarke, Robert Clarke, Jianhua Xuan |
X Demographics
The data shown below were collected from the profiles of 4 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 | 1 | 25% |
| United States | 1 | 25% |
| Unknown | 2 | 50% |
Demographic breakdown
| Type | Count | As % |
|---|---|---|
| Members of the public | 4 | 100% |
Mendeley readers
The data shown below were compiled from readership statistics for 52 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| United States | 3 | 6% |
| Russia | 1 | 2% |
| South Africa | 1 | 2% |
| Unknown | 47 | 90% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Researcher | 14 | 27% |
| Student > Ph. D. Student | 12 | 23% |
| Student > Master | 7 | 13% |
| Professor | 4 | 8% |
| Student > Bachelor | 3 | 6% |
| Other | 9 | 17% |
| Unknown | 3 | 6% |
| Readers by discipline | Count | As % |
|---|---|---|
| Agricultural and Biological Sciences | 33 | 63% |
| Biochemistry, Genetics and Molecular Biology | 7 | 13% |
| Computer Science | 2 | 4% |
| Medicine and Dentistry | 2 | 4% |
| Mathematics | 1 | 2% |
| Other | 1 | 2% |
| Unknown | 6 | 12% |
Attention Score in Context
This research output has an Altmetric Attention Score of 10. 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 03 October 2014.
All research outputs
#3,049,093
of 22,763,032 outputs
Outputs from BMC Bioinformatics
#1,072
of 7,273 outputs
Outputs of similar age
#33,711
of 238,994 outputs
Outputs of similar age from BMC Bioinformatics
#23
of 117 outputs
Altmetric has tracked 22,763,032 research outputs across all sources so far. Compared to these this one has done well and is in the 86th percentile: it's in the top 25% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 7,273 research outputs from this source. They typically receive a little more attention than average, with a mean Attention Score of 5.4. This one has done well, scoring higher than 85% 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 238,994 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 85% of its contemporaries.
We're also able to compare this research output to 117 others from the same source and published within six weeks on either side of this one. This one has done well, scoring higher than 80% of its contemporaries.