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Twitter Demographics
Mendeley readers
Attention Score in Context
| Title |
CoGAPS 3: Bayesian non-negative matrix factorization for single-cell analysis with asynchronous updates and sparse data structures
|
|---|---|
| Published in |
BMC Bioinformatics, October 2020
|
| DOI | 10.1186/s12859-020-03796-9 |
| Pubmed ID | |
| Authors |
Thomas D. Sherman, Tiger Gao, Elana J. Fertig |
Twitter Demographics
The data shown below were collected from the profiles of 24 tweeters who shared this research output. Click here to find out more about how the information was compiled.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| United States | 8 | 33% |
| Australia | 3 | 13% |
| Norway | 2 | 8% |
| Sweden | 1 | 4% |
| United Kingdom | 1 | 4% |
| France | 1 | 4% |
| Italy | 1 | 4% |
| India | 1 | 4% |
| Korea, Republic of | 1 | 4% |
| Other | 0 | 0% |
| Unknown | 5 | 21% |
Demographic breakdown
| Type | Count | As % |
|---|---|---|
| Scientists | 15 | 63% |
| Members of the public | 8 | 33% |
| Science communicators (journalists, bloggers, editors) | 1 | 4% |
Mendeley readers
The data shown below were compiled from readership statistics for 39 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Unknown | 39 | 100% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Student > Ph. D. Student | 12 | 31% |
| Researcher | 4 | 10% |
| Student > Bachelor | 3 | 8% |
| Student > Master | 2 | 5% |
| Professor | 1 | 3% |
| Other | 2 | 5% |
| Unknown | 15 | 38% |
| Readers by discipline | Count | As % |
|---|---|---|
| Biochemistry, Genetics and Molecular Biology | 9 | 23% |
| Computer Science | 7 | 18% |
| Engineering | 2 | 5% |
| Immunology and Microbiology | 2 | 5% |
| Mathematics | 1 | 3% |
| Other | 3 | 8% |
| Unknown | 15 | 38% |
Attention Score in Context
This research output has an Altmetric Attention Score of 19. 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 November 2020.
All research outputs
#1,722,069
of 23,248,929 outputs
Outputs from BMC Bioinformatics
#381
of 7,362 outputs
Outputs of similar age
#47,710
of 415,857 outputs
Outputs of similar age from BMC Bioinformatics
#5
of 172 outputs
Altmetric has tracked 23,248,929 research outputs across all sources so far. Compared to these this one has done particularly well and is in the 92nd percentile: it's in the top 10% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 7,362 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 94% 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 415,857 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 88% of its contemporaries.
We're also able to compare this research output to 172 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 97% of its contemporaries.