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X Demographics
Mendeley readers
Attention Score in Context
| Title |
A sparse Bayesian factor model for the construction of gene co-expression networks from single-cell RNA sequencing count data
|
|---|---|
| Published in |
BMC Bioinformatics, August 2020
|
| DOI | 10.1186/s12859-020-03707-y |
| Pubmed ID | |
| Authors |
Michael Sekula, Jeremy Gaskins, Susmita Datta |
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% |
| United Kingdom | 1 | 17% |
| Unknown | 3 | 50% |
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 23 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Unknown | 23 | 100% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Researcher | 6 | 26% |
| Student > Master | 5 | 22% |
| Student > Ph. D. Student | 3 | 13% |
| Student > Bachelor | 2 | 9% |
| Other | 1 | 4% |
| Other | 2 | 9% |
| Unknown | 4 | 17% |
| Readers by discipline | Count | As % |
|---|---|---|
| Biochemistry, Genetics and Molecular Biology | 9 | 39% |
| Agricultural and Biological Sciences | 5 | 22% |
| Computer Science | 3 | 13% |
| Mathematics | 1 | 4% |
| Neuroscience | 1 | 4% |
| Other | 0 | 0% |
| Unknown | 4 | 17% |
Attention Score in Context
This research output has an Altmetric Attention Score of 11. 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 18 September 2020.
All research outputs
#3,325,849
of 24,998,746 outputs
Outputs from BMC Bioinformatics
#1,084
of 7,630 outputs
Outputs of similar age
#81,823
of 406,451 outputs
Outputs of similar age from BMC Bioinformatics
#27
of 146 outputs
Altmetric has tracked 24,998,746 research outputs across all sources so far. Compared to these this one has done well and is in the 86th percentile: it's in the top 25% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 7,630 research outputs from this source. They typically receive a little more attention than average, with a mean Attention Score of 5.5. This one has done well, scoring higher than 85% 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 406,451 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 79% of its contemporaries.
We're also able to compare this research output to 146 others from the same source and published within six weeks on either side of this one. This one has done well, scoring higher than 82% of its contemporaries.