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X Demographics
Mendeley readers
Attention Score in Context
| Title |
Automated Isoform Diversity Detector (AIDD): a pipeline for investigating transcriptome diversity of RNA-seq data
|
|---|---|
| Published in |
BMC Bioinformatics, December 2020
|
| DOI | 10.1186/s12859-020-03888-6 |
| Pubmed ID | |
| Authors |
Noel-Marie Plonski, Emily Johnson, Madeline Frederick, Heather Mercer, Gail Fraizer, Richard Meindl, Gemma Casadesus, Helen Piontkivska |
X Demographics
The data shown below were collected from the profiles of 12 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 Kingdom | 2 | 17% |
| United States | 1 | 8% |
| Sweden | 1 | 8% |
| Taiwan | 1 | 8% |
| Unknown | 7 | 58% |
Demographic breakdown
| Type | Count | As % |
|---|---|---|
| Members of the public | 7 | 58% |
| Scientists | 5 | 42% |
Mendeley readers
The data shown below were compiled from readership statistics for 29 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Unknown | 29 | 100% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Researcher | 6 | 21% |
| Student > Master | 5 | 17% |
| Student > Ph. D. Student | 4 | 14% |
| Student > Bachelor | 4 | 14% |
| Other | 1 | 3% |
| Other | 3 | 10% |
| Unknown | 6 | 21% |
| Readers by discipline | Count | As % |
|---|---|---|
| Biochemistry, Genetics and Molecular Biology | 4 | 14% |
| Neuroscience | 4 | 14% |
| Agricultural and Biological Sciences | 3 | 10% |
| Nursing and Health Professions | 2 | 7% |
| Medicine and Dentistry | 2 | 7% |
| Other | 6 | 21% |
| Unknown | 8 | 28% |
Attention Score in Context
This research output has an Altmetric Attention Score of 18. 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 13 January 2021.
All research outputs
#1,823,916
of 23,344,526 outputs
Outputs from BMC Bioinformatics
#424
of 7,388 outputs
Outputs of similar age
#51,624
of 503,448 outputs
Outputs of similar age from BMC Bioinformatics
#10
of 150 outputs
Altmetric has tracked 23,344,526 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 7,388 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 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 503,448 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 89% 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 done particularly well, scoring higher than 94% of its contemporaries.