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X Demographics
Mendeley readers
Attention Score in Context
| Title |
Knowledge-primed neural networks enable biologically interpretable deep learning on single-cell sequencing data
|
|---|---|
| Published in |
Genome Biology, August 2020
|
| DOI | 10.1186/s13059-020-02100-5 |
| Pubmed ID | |
| Authors |
Nikolaus Fortelny, Christoph Bock |
X Demographics
The data shown below were collected from the profiles of 93 X users who shared this research output. Click here to find out more about how the information was compiled.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Austria | 13 | 14% |
| United States | 9 | 10% |
| India | 6 | 6% |
| Germany | 5 | 5% |
| Brazil | 3 | 3% |
| Belgium | 2 | 2% |
| Switzerland | 2 | 2% |
| Netherlands | 2 | 2% |
| Italy | 2 | 2% |
| Other | 14 | 15% |
| Unknown | 35 | 38% |
Demographic breakdown
| Type | Count | As % |
|---|---|---|
| Members of the public | 64 | 69% |
| Scientists | 27 | 29% |
| Science communicators (journalists, bloggers, editors) | 2 | 2% |
Mendeley readers
The data shown below were compiled from readership statistics for 251 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Unknown | 251 | 100% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Student > Ph. D. Student | 54 | 22% |
| Researcher | 37 | 15% |
| Student > Master | 29 | 12% |
| Student > Bachelor | 21 | 8% |
| Student > Doctoral Student | 7 | 3% |
| Other | 25 | 10% |
| Unknown | 78 | 31% |
| Readers by discipline | Count | As % |
|---|---|---|
| Biochemistry, Genetics and Molecular Biology | 59 | 24% |
| Agricultural and Biological Sciences | 33 | 13% |
| Computer Science | 29 | 12% |
| Engineering | 13 | 5% |
| Medicine and Dentistry | 5 | 2% |
| Other | 28 | 11% |
| Unknown | 84 | 33% |
Attention Score in Context
This research output has an Altmetric Attention Score of 103. 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 25 January 2022.
All research outputs
#415,675
of 25,661,882 outputs
Outputs from Genome Biology
#217
of 4,498 outputs
Outputs of similar age
#12,711
of 427,458 outputs
Outputs of similar age from Genome Biology
#7
of 102 outputs
Altmetric has tracked 25,661,882 research outputs across all sources so far. Compared to these this one has done particularly well and is in the 98th percentile: it's in the top 5% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 4,498 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 particularly well, scoring higher than 95% 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 427,458 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 97% 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 particularly well, scoring higher than 93% of its contemporaries.