| Title |
Performance evaluation of lossy quality compression algorithms for RNA-seq data
|
|---|---|
| Published in |
BMC Bioinformatics, July 2020
|
| DOI | 10.1186/s12859-020-03658-4 |
| Pubmed ID | |
| Authors |
Rongshan Yu, Wenxian Yang, Shun Wang |
X Demographics
The data shown below were collected from the profiles of 6 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 | 17% |
| United Kingdom | 1 | 17% |
| Unknown | 4 | 67% |
Demographic breakdown
| Type | Count | As % |
|---|---|---|
| Members of the public | 5 | 83% |
| Scientists | 1 | 17% |
Mendeley readers
The data shown below were compiled from readership statistics for 17 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Unknown | 17 | 100% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Researcher | 4 | 24% |
| Student > Bachelor | 2 | 12% |
| Professor | 2 | 12% |
| Student > Master | 2 | 12% |
| Other | 1 | 6% |
| Other | 1 | 6% |
| Unknown | 5 | 29% |
| Readers by discipline | Count | As % |
|---|---|---|
| Computer Science | 4 | 24% |
| Biochemistry, Genetics and Molecular Biology | 3 | 18% |
| Environmental Science | 1 | 6% |
| Medicine and Dentistry | 1 | 6% |
| Engineering | 1 | 6% |
| Other | 0 | 0% |
| Unknown | 7 | 41% |
Attention Score in Context
This research output has an Altmetric Attention Score of 7. 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 28 April 2023.
All research outputs
#5,283,313
of 25,738,558 outputs
Outputs from BMC Bioinformatics
#1,816
of 7,739 outputs
Outputs of similar age
#122,477
of 431,323 outputs
Outputs of similar age from BMC Bioinformatics
#46
of 120 outputs
Altmetric has tracked 25,738,558 research outputs across all sources so far. Compared to these this one has done well and is in the 79th percentile: it's in the top 25% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 7,739 research outputs from this source. They typically receive a little more attention than average, with a mean Attention Score of 5.5. This one has done well, scoring higher than 76% 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 431,323 tracked outputs that were published within six weeks on either side of this one in any source. This one has gotten more attention than average, scoring higher than 71% of its contemporaries.
We're also able to compare this research output to 120 others from the same source and published within six weeks on either side of this one. This one has gotten more attention than average, scoring higher than 61% of its contemporaries.