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X Demographics
Mendeley readers
Attention Score in Context
| Title |
Autoencoder-based cluster ensembles for single-cell RNA-seq data analysis
|
|---|---|
| Published in |
BMC Bioinformatics, December 2019
|
| DOI | 10.1186/s12859-019-3179-5 |
| Pubmed ID | |
| Authors |
Thomas A. Geddes, Taiyun Kim, Lihao Nan, James G. Burchfield, Jean Y. H. Yang, Dacheng Tao, Pengyi Yang |
X Demographics
The data shown below were collected from the profiles of 6 X users who shared this research output. Click here to find out more about how the information was compiled.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Australia | 3 | 50% |
| Austria | 1 | 17% |
| Unknown | 2 | 33% |
Demographic breakdown
| Type | Count | As % |
|---|---|---|
| Members of the public | 5 | 83% |
| Scientists | 1 | 17% |
Mendeley readers
The data shown below were compiled from readership statistics for 98 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Unknown | 98 | 100% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Researcher | 18 | 18% |
| Student > Ph. D. Student | 15 | 15% |
| Student > Bachelor | 14 | 14% |
| Student > Master | 12 | 12% |
| Other | 3 | 3% |
| Other | 9 | 9% |
| Unknown | 27 | 28% |
| Readers by discipline | Count | As % |
|---|---|---|
| Biochemistry, Genetics and Molecular Biology | 23 | 23% |
| Computer Science | 19 | 19% |
| Agricultural and Biological Sciences | 9 | 9% |
| Engineering | 4 | 4% |
| Mathematics | 3 | 3% |
| Other | 10 | 10% |
| Unknown | 30 | 31% |
Attention Score in Context
This research output has an Altmetric Attention Score of 12. 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 27 June 2021.
All research outputs
#2,808,363
of 23,577,761 outputs
Outputs from BMC Bioinformatics
#900
of 7,418 outputs
Outputs of similar age
#67,574
of 460,385 outputs
Outputs of similar age from BMC Bioinformatics
#23
of 215 outputs
Altmetric has tracked 23,577,761 research outputs across all sources so far. Compared to these this one has done well and is in the 88th percentile: it's in the top 25% 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 well, scoring higher than 87% 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 460,385 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 85% of its contemporaries.
We're also able to compare this research output to 215 others from the same source and published within six weeks on either side of this one. This one has done well, scoring higher than 89% of its contemporaries.