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X Demographics
Mendeley readers
Attention Score in Context
| Title |
scSemiAE: a deep model with semi-supervised learning for single-cell transcriptomics
|
|---|---|
| Published in |
BMC Bioinformatics, May 2022
|
| DOI | 10.1186/s12859-022-04703-0 |
| Pubmed ID | |
| Authors |
Jiayi Dong, Yin Zhang, Fei Wang |
X Demographics
The data shown below were collected from the profiles of 9 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 | 2 | 22% |
| India | 1 | 11% |
| Italy | 1 | 11% |
| Sweden | 1 | 11% |
| United Kingdom | 1 | 11% |
| Unknown | 3 | 33% |
Demographic breakdown
| Type | Count | As % |
|---|---|---|
| Members of the public | 5 | 56% |
| Scientists | 4 | 44% |
Mendeley readers
The data shown below were compiled from readership statistics for 20 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Unknown | 20 | 100% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Unspecified | 4 | 20% |
| Student > Ph. D. Student | 2 | 10% |
| Student > Bachelor | 1 | 5% |
| Professor | 1 | 5% |
| Student > Master | 1 | 5% |
| Other | 2 | 10% |
| Unknown | 9 | 45% |
| Readers by discipline | Count | As % |
|---|---|---|
| Unspecified | 4 | 20% |
| Computer Science | 3 | 15% |
| Mathematics | 1 | 5% |
| Agricultural and Biological Sciences | 1 | 5% |
| Unknown | 11 | 55% |
Attention Score in Context
This research output has an Altmetric Attention Score of 4. 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 11 May 2022.
All research outputs
#7,567,844
of 23,742,253 outputs
Outputs from BMC Bioinformatics
#2,925
of 7,429 outputs
Outputs of similar age
#149,424
of 444,767 outputs
Outputs of similar age from BMC Bioinformatics
#53
of 150 outputs
Altmetric has tracked 23,742,253 research outputs across all sources so far. This one has received more attention than most of these and is in the 67th percentile.
So far Altmetric has tracked 7,429 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 gotten more attention than average, scoring higher than 59% 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 444,767 tracked outputs that were published within six weeks on either side of this one in any source. This one has gotten more attention than average, scoring higher than 65% of its contemporaries.
We're also able to compare this research output to 150 others from the same source and published within six weeks on either side of this one. This one has gotten more attention than average, scoring higher than 63% of its contemporaries.