| Title |
Realistic in silico generation and augmentation of single-cell RNA-seq data using generative adversarial networks
|
|---|---|
| Published in |
Nature Communications, January 2020
|
| DOI | 10.1038/s41467-019-14018-z |
| Pubmed ID | |
| Authors |
Mohamed Marouf, Pierre Machart, Vikas Bansal, Christoph Kilian, Daniel S. Magruder, Christian F. Krebs, Stefan Bonn |
X Demographics
The data shown below were collected from the profiles of 26 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 States | 9 | 35% |
| Germany | 3 | 12% |
| United Kingdom | 2 | 8% |
| France | 2 | 8% |
| Sweden | 1 | 4% |
| China | 1 | 4% |
| Myanmar | 1 | 4% |
| Canada | 1 | 4% |
| India | 1 | 4% |
| Other | 1 | 4% |
| Unknown | 4 | 15% |
Demographic breakdown
| Type | Count | As % |
|---|---|---|
| Members of the public | 17 | 65% |
| Scientists | 7 | 27% |
| Practitioners (doctors, other healthcare professionals) | 2 | 8% |
Mendeley readers
The data shown below were compiled from readership statistics for 267 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Unknown | 267 | 100% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Student > Ph. D. Student | 56 | 21% |
| Researcher | 45 | 17% |
| Student > Master | 22 | 8% |
| Student > Bachelor | 15 | 6% |
| Other | 13 | 5% |
| Other | 29 | 11% |
| Unknown | 87 | 33% |
| Readers by discipline | Count | As % |
|---|---|---|
| Biochemistry, Genetics and Molecular Biology | 52 | 19% |
| Computer Science | 48 | 18% |
| Agricultural and Biological Sciences | 21 | 8% |
| Engineering | 10 | 4% |
| Medicine and Dentistry | 8 | 3% |
| Other | 35 | 13% |
| Unknown | 93 | 35% |
Attention Score in Context
This research output has an Altmetric Attention Score of 15. 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 January 2023.
All research outputs
#2,421,116
of 25,391,066 outputs
Outputs from Nature Communications
#28,713
of 56,503 outputs
Outputs of similar age
#55,772
of 472,802 outputs
Outputs of similar age from Nature Communications
#826
of 1,457 outputs
Altmetric has tracked 25,391,066 research outputs across all sources so far. Compared to these this one has done particularly well and is in the 90th percentile: it's in the top 10% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 56,503 research outputs from this source. They typically receive a lot more attention than average, with a mean Attention Score of 55.7. This one is in the 49th percentile – i.e., 49% of its peers scored the same or lower than it.
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 472,802 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 88% of its contemporaries.
We're also able to compare this research output to 1,457 others from the same source and published within six weeks on either side of this one. This one is in the 43rd percentile – i.e., 43% of its contemporaries scored the same or lower than it.