You are seeing a free-to-access but limited selection of the activity Altmetric has collected about this research output.
Click here to find out more.
X Demographics
Mendeley readers
Attention Score in Context
| Title |
miRExpress: Analyzing high-throughput sequencing data for profiling microRNA expression
|
|---|---|
| Published in |
BMC Bioinformatics, October 2009
|
| DOI | 10.1186/1471-2105-10-328 |
| Pubmed ID | |
| Authors |
Wei-Chi Wang, Feng-Mao Lin, Wen-Chi Chang, Kuan-Yu Lin, Hsien-Da Huang, Na-Sheng Lin |
X Demographics
The data shown below were collected from the profile of 1 X user who shared this research output. Click here to find out more about how the information was compiled.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Spain | 1 | 100% |
Demographic breakdown
| Type | Count | As % |
|---|---|---|
| Members of the public | 1 | 100% |
Mendeley readers
The data shown below were compiled from readership statistics for 299 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| United States | 9 | 3% |
| Germany | 6 | 2% |
| Italy | 4 | 1% |
| China | 3 | 1% |
| United Kingdom | 3 | 1% |
| Uruguay | 2 | <1% |
| Brazil | 2 | <1% |
| Sweden | 2 | <1% |
| Canada | 2 | <1% |
| Other | 10 | 3% |
| Unknown | 256 | 86% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Researcher | 82 | 27% |
| Student > Ph. D. Student | 75 | 25% |
| Student > Master | 32 | 11% |
| Professor > Associate Professor | 20 | 7% |
| Professor | 14 | 5% |
| Other | 47 | 16% |
| Unknown | 29 | 10% |
| Readers by discipline | Count | As % |
|---|---|---|
| Agricultural and Biological Sciences | 164 | 55% |
| Biochemistry, Genetics and Molecular Biology | 51 | 17% |
| Computer Science | 22 | 7% |
| Medicine and Dentistry | 8 | 3% |
| Engineering | 6 | 2% |
| Other | 13 | 4% |
| Unknown | 35 | 12% |
Attention Score in Context
This research output has an Altmetric Attention Score of 11. 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 26 February 2018.
All research outputs
#3,313,257
of 26,017,215 outputs
Outputs from BMC Bioinformatics
#1,024
of 7,793 outputs
Outputs of similar age
#12,030
of 110,893 outputs
Outputs of similar age from BMC Bioinformatics
#7
of 65 outputs
Altmetric has tracked 26,017,215 research outputs across all sources so far. Compared to these this one has done well and is in the 87th percentile: it's in the top 25% 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 well, scoring higher than 86% 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 110,893 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 88% of its contemporaries.
We're also able to compare this research output to 65 others from the same source and published within six weeks on either side of this one. This one has done well, scoring higher than 89% of its contemporaries.