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X Demographics
Mendeley readers
Attention Score in Context
Title |
TSSAR: TSS annotation regime for dRNA-seq data
|
---|---|
Published in |
BMC Bioinformatics, March 2014
|
DOI | 10.1186/1471-2105-15-89 |
Pubmed ID | |
Authors |
Fabian Amman, Michael T Wolfinger, Ronny Lorenz, Ivo L Hofacker, Peter F Stadler, Sven Findeiß |
Abstract |
Differential RNA sequencing (dRNA-seq) is a high-throughput screening technique designed to examine the architecture of bacterial operons in general and the precise position of transcription start sites (TSS) in particular. Hitherto, dRNA-seq data were analyzed by visualizing the sequencing reads mapped to the reference genome and manually annotating reliable positions. This is very labor intensive and, due to the subjectivity, biased. |
X Demographics
The data shown below were collected from the profiles of 7 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 | 29% |
Austria | 1 | 14% |
Germany | 1 | 14% |
France | 1 | 14% |
Norway | 1 | 14% |
Unknown | 1 | 14% |
Demographic breakdown
Type | Count | As % |
---|---|---|
Scientists | 5 | 71% |
Members of the public | 2 | 29% |
Mendeley readers
The data shown below were compiled from readership statistics for 109 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
Country | Count | As % |
---|---|---|
Netherlands | 2 | 2% |
United States | 2 | 2% |
Germany | 1 | <1% |
Canada | 1 | <1% |
Austria | 1 | <1% |
Russia | 1 | <1% |
Denmark | 1 | <1% |
Unknown | 100 | 92% |
Demographic breakdown
Readers by professional status | Count | As % |
---|---|---|
Student > Ph. D. Student | 28 | 26% |
Researcher | 21 | 19% |
Student > Master | 19 | 17% |
Student > Bachelor | 13 | 12% |
Professor > Associate Professor | 5 | 5% |
Other | 15 | 14% |
Unknown | 8 | 7% |
Readers by discipline | Count | As % |
---|---|---|
Agricultural and Biological Sciences | 43 | 39% |
Biochemistry, Genetics and Molecular Biology | 27 | 25% |
Computer Science | 15 | 14% |
Immunology and Microbiology | 3 | 3% |
Engineering | 3 | 3% |
Other | 10 | 9% |
Unknown | 8 | 7% |
Attention Score in Context
This research output has an Altmetric Attention Score of 12. 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 June 2014.
All research outputs
#2,665,650
of 22,751,628 outputs
Outputs from BMC Bioinformatics
#869
of 7,268 outputs
Outputs of similar age
#28,115
of 224,538 outputs
Outputs of similar age from BMC Bioinformatics
#15
of 100 outputs
Altmetric has tracked 22,751,628 research outputs across all sources so far. Compared to these this one has done well and is in the 88th percentile: it's in the top 25% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 7,268 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 88% 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 224,538 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 87% of its contemporaries.
We're also able to compare this research output to 100 others from the same source and published within six weeks on either side of this one. This one has done well, scoring higher than 85% of its contemporaries.