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X Demographics
Mendeley readers
Attention Score in Context
| Title |
Trade-off between conservation of biological variation and batch effect removal in deep generative modeling for single-cell transcriptomics
|
|---|---|
| Published in |
BMC Bioinformatics, November 2022
|
| DOI | 10.1186/s12859-022-05003-3 |
| Pubmed ID | |
| Authors |
Hui Li, Davis J. McCarthy, Heejung Shim, Susan Wei |
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 % |
|---|---|---|
| United States | 1 | 17% |
| Italy | 1 | 17% |
| Sweden | 1 | 17% |
| United Kingdom | 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 18 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Unknown | 18 | 100% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Unspecified | 3 | 17% |
| Other | 3 | 17% |
| Student > Ph. D. Student | 2 | 11% |
| Student > Bachelor | 2 | 11% |
| Student > Master | 1 | 6% |
| Other | 0 | 0% |
| Unknown | 7 | 39% |
| Readers by discipline | Count | As % |
|---|---|---|
| Unspecified | 3 | 17% |
| Environmental Science | 3 | 17% |
| Biochemistry, Genetics and Molecular Biology | 3 | 17% |
| Computer Science | 1 | 6% |
| Social Sciences | 1 | 6% |
| Other | 0 | 0% |
| Unknown | 7 | 39% |
Attention Score in Context
This research output has an Altmetric Attention Score of 2. 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 16 December 2022.
All research outputs
#14,714,578
of 23,862,416 outputs
Outputs from BMC Bioinformatics
#4,598
of 7,478 outputs
Outputs of similar age
#200,942
of 430,773 outputs
Outputs of similar age from BMC Bioinformatics
#97
of 170 outputs
Altmetric has tracked 23,862,416 research outputs across all sources so far. This one is in the 37th percentile – i.e., 37% of other outputs scored the same or lower than it.
So far Altmetric has tracked 7,478 research outputs from this source. They typically receive a little more attention than average, with a mean Attention Score of 5.5. This one is in the 35th percentile – i.e., 35% of its peers scored the same or lower than it.
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 430,773 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 51% of its contemporaries.
We're also able to compare this research output to 170 others from the same source and published within six weeks on either side of this one. This one is in the 37th percentile – i.e., 37% of its contemporaries scored the same or lower than it.