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X Demographics
Mendeley readers
Attention Score in Context
| Title |
EnClaSC: a novel ensemble approach for accurate and robust cell-type classification of single-cell transcriptomes
|
|---|---|
| Published in |
BMC Bioinformatics, September 2020
|
| DOI | 10.1186/s12859-020-03679-z |
| Pubmed ID | |
| Authors |
Xiaoyang Chen, Shengquan Chen, Rui Jiang |
X Demographics
The data shown below were collected from the profiles of 16 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 | 4 | 25% |
| Germany | 2 | 13% |
| Australia | 1 | 6% |
| Austria | 1 | 6% |
| Italy | 1 | 6% |
| Unknown | 7 | 44% |
Demographic breakdown
| Type | Count | As % |
|---|---|---|
| Members of the public | 13 | 81% |
| Scientists | 3 | 19% |
Mendeley readers
The data shown below were compiled from readership statistics for 21 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Unknown | 21 | 100% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Student > Bachelor | 4 | 19% |
| Student > Master | 3 | 14% |
| Student > Doctoral Student | 2 | 10% |
| Other | 1 | 5% |
| Lecturer | 1 | 5% |
| Other | 3 | 14% |
| Unknown | 7 | 33% |
| Readers by discipline | Count | As % |
|---|---|---|
| Biochemistry, Genetics and Molecular Biology | 6 | 29% |
| Computer Science | 5 | 24% |
| Unspecified | 1 | 5% |
| Veterinary Science and Veterinary Medicine | 1 | 5% |
| Medicine and Dentistry | 1 | 5% |
| Other | 0 | 0% |
| Unknown | 7 | 33% |
Attention Score in Context
This research output has an Altmetric Attention Score of 16. 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 13 October 2020.
All research outputs
#2,030,556
of 23,577,761 outputs
Outputs from BMC Bioinformatics
#503
of 7,418 outputs
Outputs of similar age
#55,650
of 409,175 outputs
Outputs of similar age from BMC Bioinformatics
#8
of 149 outputs
Altmetric has tracked 23,577,761 research outputs across all sources so far. Compared to these this one has done particularly well and is in the 91st percentile: it's in the top 10% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 7,418 research outputs from this source. They typically receive a little more attention than average, with a mean Attention Score of 5.4. This one has done particularly well, scoring higher than 93% 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 409,175 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 86% of its contemporaries.
We're also able to compare this research output to 149 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 94% of its contemporaries.