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X Demographics
Mendeley readers
Attention Score in Context
| Title |
Transcript mapping based on dRNA-seq data
|
|---|---|
| Published in |
BMC Bioinformatics, April 2014
|
| DOI | 10.1186/1471-2105-15-122 |
| Pubmed ID | |
| Authors |
Thorsten Bischler, Matthias Kopf, Björn Voß |
| Abstract |
RNA-seq and its variant differential RNA-seq (dRNA-seq) are today routine methods for transcriptome analysis in bacteria. While expression profiling and transcriptional start site prediction are standard tasks today, the problem of identifying transcriptional units in a genome-wide fashion is still not solved for prokaryotic systems. |
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 % |
|---|---|---|
| France | 1 | 25% |
| India | 1 | 25% |
| Norway | 1 | 25% |
| Unknown | 1 | 25% |
Demographic breakdown
| Type | Count | As % |
|---|---|---|
| Scientists | 2 | 50% |
| Members of the public | 2 | 50% |
Mendeley readers
The data shown below were compiled from readership statistics for 44 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| United States | 1 | 2% |
| Germany | 1 | 2% |
| Brazil | 1 | 2% |
| Unknown | 41 | 93% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Student > Ph. D. Student | 11 | 25% |
| Researcher | 8 | 18% |
| Student > Master | 6 | 14% |
| Professor | 3 | 7% |
| Student > Postgraduate | 3 | 7% |
| Other | 9 | 20% |
| Unknown | 4 | 9% |
| Readers by discipline | Count | As % |
|---|---|---|
| Agricultural and Biological Sciences | 21 | 48% |
| Biochemistry, Genetics and Molecular Biology | 7 | 16% |
| Computer Science | 4 | 9% |
| Medicine and Dentistry | 3 | 7% |
| Mathematics | 1 | 2% |
| Other | 2 | 5% |
| Unknown | 6 | 14% |
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 19 May 2014.
All research outputs
#3,047,910
of 22,754,104 outputs
Outputs from BMC Bioinformatics
#1,074
of 7,269 outputs
Outputs of similar age
#31,920
of 227,503 outputs
Outputs of similar age from BMC Bioinformatics
#24
of 136 outputs
Altmetric has tracked 22,754,104 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 7,269 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 227,503 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 136 others from the same source and published within six weeks on either side of this one. This one has done well, scoring higher than 82% of its contemporaries.