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X Demographics
Mendeley readers
Attention Score in Context
| Title |
Optimizing de novo transcriptome assembly from short-read RNA-Seq data: a comparative study
|
|---|---|
| Published in |
BMC Bioinformatics, December 2011
|
| DOI | 10.1186/1471-2105-12-s14-s2 |
| Pubmed ID | |
| Authors |
Qiong-Yi Zhao, Yi Wang, Yi-Meng Kong, Da Luo, Xuan Li, Pei Hao |
X Demographics
The data shown below were collected from the profiles of 14 X users who shared this research output. Click here to find out more about how the information was compiled.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Italy | 3 | 21% |
| United Kingdom | 2 | 14% |
| United States | 2 | 14% |
| France | 2 | 14% |
| Poland | 1 | 7% |
| Belgium | 1 | 7% |
| Unknown | 3 | 21% |
Demographic breakdown
| Type | Count | As % |
|---|---|---|
| Scientists | 10 | 71% |
| Members of the public | 4 | 29% |
Mendeley readers
The data shown below were compiled from readership statistics for 598 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| United States | 14 | 2% |
| Germany | 9 | 2% |
| Brazil | 4 | <1% |
| Spain | 3 | <1% |
| Australia | 3 | <1% |
| France | 3 | <1% |
| Mexico | 3 | <1% |
| Netherlands | 2 | <1% |
| Italy | 2 | <1% |
| Other | 23 | 4% |
| Unknown | 532 | 89% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Student > Ph. D. Student | 159 | 27% |
| Researcher | 140 | 23% |
| Student > Master | 82 | 14% |
| Student > Bachelor | 44 | 7% |
| Student > Doctoral Student | 31 | 5% |
| Other | 96 | 16% |
| Unknown | 46 | 8% |
| Readers by discipline | Count | As % |
|---|---|---|
| Agricultural and Biological Sciences | 344 | 58% |
| Biochemistry, Genetics and Molecular Biology | 102 | 17% |
| Computer Science | 35 | 6% |
| Environmental Science | 9 | 2% |
| Engineering | 7 | 1% |
| Other | 34 | 6% |
| Unknown | 67 | 11% |
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 02 September 2013.
All research outputs
#3,722,734
of 26,017,215 outputs
Outputs from BMC Bioinformatics
#1,237
of 7,793 outputs
Outputs of similar age
#27,811
of 255,464 outputs
Outputs of similar age from BMC Bioinformatics
#18
of 102 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 85th 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 83% 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 255,464 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 102 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.