You are seeing a free-to-access but limited selection of the activity Altmetric has collected about this research output.
Click here to find out more.
X Demographics
Mendeley readers
Attention Score in Context
| Title |
A multivariate Poisson-log normal mixture model for clustering transcriptome sequencing data
|
|---|---|
| Published in |
BMC Bioinformatics, July 2019
|
| DOI | 10.1186/s12859-019-2916-0 |
| Pubmed ID | |
| Authors |
Anjali Silva, Steven J. Rothstein, Paul D. McNicholas, Sanjeena Subedi |
X Demographics
The data shown below were collected from the profiles of 8 X users who shared this research output. Click here to find out more about how the information was compiled.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Canada | 3 | 38% |
| United Kingdom | 1 | 13% |
| Unknown | 4 | 50% |
Demographic breakdown
| Type | Count | As % |
|---|---|---|
| Members of the public | 5 | 63% |
| Scientists | 2 | 25% |
| Science communicators (journalists, bloggers, editors) | 1 | 13% |
Mendeley readers
The data shown below were compiled from readership statistics for 36 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Unknown | 36 | 100% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Student > Ph. D. Student | 9 | 25% |
| Student > Doctoral Student | 3 | 8% |
| Researcher | 3 | 8% |
| Student > Master | 2 | 6% |
| Professor | 2 | 6% |
| Other | 3 | 8% |
| Unknown | 14 | 39% |
| Readers by discipline | Count | As % |
|---|---|---|
| Biochemistry, Genetics and Molecular Biology | 5 | 14% |
| Computer Science | 5 | 14% |
| Mathematics | 4 | 11% |
| Decision Sciences | 2 | 6% |
| Agricultural and Biological Sciences | 1 | 3% |
| Other | 3 | 8% |
| Unknown | 16 | 44% |
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 30 June 2020.
All research outputs
#2,975,960
of 25,481,734 outputs
Outputs from BMC Bioinformatics
#855
of 7,708 outputs
Outputs of similar age
#58,927
of 359,592 outputs
Outputs of similar age from BMC Bioinformatics
#25
of 151 outputs
Altmetric has tracked 25,481,734 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 7,708 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 88% 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 359,592 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 83% of its contemporaries.
We're also able to compare this research output to 151 others from the same source and published within six weeks on either side of this one. This one has done well, scoring higher than 84% of its contemporaries.