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 |
DeepImpute: an accurate, fast, and scalable deep neural network method to impute single-cell RNA-seq data
|
---|---|
Published in |
Genome Biology, October 2019
|
DOI | 10.1186/s13059-019-1837-6 |
Pubmed ID | |
Authors |
Cédric Arisdakessian, Olivier Poirion, Breck Yunits, Xun Zhu, Lana X. Garmire |
X Demographics
The data shown below were collected from the profiles of 79 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 | 20 | 25% |
Japan | 6 | 8% |
Mexico | 2 | 3% |
China | 2 | 3% |
Australia | 2 | 3% |
Germany | 2 | 3% |
Canada | 2 | 3% |
Nigeria | 1 | 1% |
Côte d'Ivoire | 1 | 1% |
Other | 10 | 13% |
Unknown | 31 | 39% |
Demographic breakdown
Type | Count | As % |
---|---|---|
Members of the public | 54 | 68% |
Scientists | 23 | 29% |
Practitioners (doctors, other healthcare professionals) | 1 | 1% |
Science communicators (journalists, bloggers, editors) | 1 | 1% |
Mendeley readers
The data shown below were compiled from readership statistics for 263 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
Country | Count | As % |
---|---|---|
Unknown | 263 | 100% |
Demographic breakdown
Readers by professional status | Count | As % |
---|---|---|
Student > Ph. D. Student | 57 | 22% |
Researcher | 32 | 12% |
Student > Bachelor | 18 | 7% |
Student > Master | 16 | 6% |
Student > Doctoral Student | 13 | 5% |
Other | 35 | 13% |
Unknown | 92 | 35% |
Readers by discipline | Count | As % |
---|---|---|
Biochemistry, Genetics and Molecular Biology | 54 | 21% |
Computer Science | 41 | 16% |
Agricultural and Biological Sciences | 24 | 9% |
Engineering | 8 | 3% |
Mathematics | 7 | 3% |
Other | 29 | 11% |
Unknown | 100 | 38% |
Attention Score in Context
This research output has an Altmetric Attention Score of 53. 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 12 May 2020.
All research outputs
#794,811
of 25,387,668 outputs
Outputs from Genome Biology
#529
of 4,470 outputs
Outputs of similar age
#17,654
of 371,035 outputs
Outputs of similar age from Genome Biology
#15
of 73 outputs
Altmetric has tracked 25,387,668 research outputs across all sources so far. Compared to these this one has done particularly well and is in the 96th percentile: it's in the top 5% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 4,470 research outputs from this source. They typically receive a lot more attention than average, with a mean Attention Score of 27.6. 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 371,035 tracked outputs that were published within six weeks on either side of this one in any source. This one has done particularly well, scoring higher than 95% of its contemporaries.
We're also able to compare this research output to 73 others from the same source and published within six weeks on either side of this one. This one has done well, scoring higher than 79% of its contemporaries.