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X Demographics
Mendeley readers
Attention Score in Context
| Title |
A comparison of automatic cell identification methods for single-cell RNA sequencing data
|
|---|---|
| Published in |
Genome Biology, September 2019
|
| DOI | 10.1186/s13059-019-1795-z |
| Pubmed ID | |
| Authors |
Tamim Abdelaal, Lieke Michielsen, Davy Cats, Dylan Hoogduin, Hailiang Mei, Marcel J. T. Reinders, Ahmed Mahfouz |
X Demographics
The data shown below were collected from the profiles of 106 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 | 33 | 31% |
| United Kingdom | 12 | 11% |
| Australia | 9 | 8% |
| Germany | 5 | 5% |
| Netherlands | 4 | 4% |
| Japan | 2 | 2% |
| Spain | 2 | 2% |
| France | 2 | 2% |
| Norway | 1 | <1% |
| Other | 9 | 8% |
| Unknown | 27 | 25% |
Demographic breakdown
| Type | Count | As % |
|---|---|---|
| Scientists | 68 | 64% |
| Members of the public | 35 | 33% |
| Practitioners (doctors, other healthcare professionals) | 2 | 2% |
| Science communicators (journalists, bloggers, editors) | 1 | <1% |
Mendeley readers
The data shown below were compiled from readership statistics for 667 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Unknown | 667 | 100% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Researcher | 131 | 20% |
| Student > Ph. D. Student | 121 | 18% |
| Student > Master | 76 | 11% |
| Student > Bachelor | 53 | 8% |
| Other | 23 | 3% |
| Other | 70 | 10% |
| Unknown | 193 | 29% |
| Readers by discipline | Count | As % |
|---|---|---|
| Biochemistry, Genetics and Molecular Biology | 198 | 30% |
| Agricultural and Biological Sciences | 82 | 12% |
| Computer Science | 45 | 7% |
| Medicine and Dentistry | 26 | 4% |
| Immunology and Microbiology | 20 | 3% |
| Other | 84 | 13% |
| Unknown | 212 | 32% |
Attention Score in Context
This research output has an Altmetric Attention Score of 76. 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 23 June 2023.
All research outputs
#573,638
of 25,837,817 outputs
Outputs from Genome Biology
#340
of 4,506 outputs
Outputs of similar age
#11,971
of 353,748 outputs
Outputs of similar age from Genome Biology
#9
of 72 outputs
Altmetric has tracked 25,837,817 research outputs across all sources so far. Compared to these this one has done particularly well and is in the 97th percentile: it's in the top 5% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 4,506 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 92% 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 353,748 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 96% of its contemporaries.
We're also able to compare this research output to 72 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.