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X Demographics
Mendeley readers
Attention Score in Context
Title |
Using sound to understand protein sequence data: new sonification algorithms for protein sequences and multiple sequence alignments
|
---|---|
Published in |
BMC Bioinformatics, September 2021
|
DOI | 10.1186/s12859-021-04362-7 |
Pubmed ID | |
Authors |
Edward J. Martin, Thomas R. Meagher, Daniel Barker |
X Demographics
The data shown below were collected from the profiles of 24 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 | 12 | 50% |
Ireland | 1 | 4% |
Australia | 1 | 4% |
Sweden | 1 | 4% |
France | 1 | 4% |
Unknown | 8 | 33% |
Demographic breakdown
Type | Count | As % |
---|---|---|
Members of the public | 13 | 54% |
Scientists | 11 | 46% |
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 % |
---|---|---|
Student > Ph. D. Student | 4 | 17% |
Student > Master | 3 | 13% |
Student > Bachelor | 2 | 9% |
Researcher | 2 | 9% |
Lecturer > Senior Lecturer | 1 | 4% |
Other | 1 | 4% |
Unknown | 10 | 43% |
Readers by discipline | Count | As % |
---|---|---|
Biochemistry, Genetics and Molecular Biology | 4 | 17% |
Agricultural and Biological Sciences | 2 | 9% |
Engineering | 2 | 9% |
Computer Science | 1 | 4% |
Chemical Engineering | 1 | 4% |
Other | 2 | 9% |
Unknown | 11 | 48% |
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 03 January 2024.
All research outputs
#2,044,790
of 25,628,260 outputs
Outputs from BMC Bioinformatics
#432
of 7,732 outputs
Outputs of similar age
#46,337
of 436,032 outputs
Outputs of similar age from BMC Bioinformatics
#7
of 150 outputs
Altmetric has tracked 25,628,260 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 7,732 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 436,032 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 96% of its contemporaries.