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 |
Modeling and cleaning RNA-seq data significantly improve detection of differentially expressed genes
|
|---|---|
| Published in |
BMC Bioinformatics, November 2022
|
| DOI | 10.1186/s12859-022-05023-z |
| Pubmed ID | |
| Authors |
Igor V. Deyneko, Orkhan N. Mustafaev, Alexander А. Tyurin, Ksenya V. Zhukova, Alexander Varzari, Irina V. Goldenkova-Pavlova |
X Demographics
The data shown below were collected from the profiles of 19 X users who shared this research output. Click here to find out more about how the information was compiled.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| United Kingdom | 2 | 11% |
| Sweden | 2 | 11% |
| Finland | 1 | 5% |
| United States | 1 | 5% |
| China | 1 | 5% |
| Mexico | 1 | 5% |
| Germany | 1 | 5% |
| India | 1 | 5% |
| Korea, Republic of | 1 | 5% |
| Other | 2 | 11% |
| Unknown | 6 | 32% |
Demographic breakdown
| Type | Count | As % |
|---|---|---|
| Scientists | 9 | 47% |
| Members of the public | 9 | 47% |
| Science communicators (journalists, bloggers, editors) | 1 | 5% |
Mendeley readers
The data shown below were compiled from readership statistics for 28 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Unknown | 28 | 100% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Researcher | 4 | 14% |
| Student > Bachelor | 3 | 11% |
| Student > Ph. D. Student | 3 | 11% |
| Student > Master | 3 | 11% |
| Professor | 1 | 4% |
| Other | 2 | 7% |
| Unknown | 12 | 43% |
| Readers by discipline | Count | As % |
|---|---|---|
| Biochemistry, Genetics and Molecular Biology | 8 | 29% |
| Agricultural and Biological Sciences | 3 | 11% |
| Computer Science | 2 | 7% |
| Unknown | 15 | 54% |
Attention Score in Context
This research output has an Altmetric Attention Score of 9. 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 05 May 2023.
All research outputs
#4,080,302
of 25,163,238 outputs
Outputs from BMC Bioinformatics
#1,366
of 7,657 outputs
Outputs of similar age
#69,086
of 396,358 outputs
Outputs of similar age from BMC Bioinformatics
#21
of 157 outputs
Altmetric has tracked 25,163,238 research outputs across all sources so far. Compared to these this one has done well and is in the 83rd percentile: it's in the top 25% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 7,657 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 82% 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 396,358 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 82% of its contemporaries.
We're also able to compare this research output to 157 others from the same source and published within six weeks on either side of this one. This one has done well, scoring higher than 87% of its contemporaries.