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X Demographics
Mendeley readers
Attention Score in Context
Title |
AMPlify: attentive deep learning model for discovery of novel antimicrobial peptides effective against WHO priority pathogens
|
---|---|
Published in |
BMC Genomics, January 2022
|
DOI | 10.1186/s12864-022-08310-4 |
Pubmed ID | |
Authors |
Chenkai Li, Darcy Sutherland, S. Austin Hammond, Chen Yang, Figali Taho, Lauren Bergman, Simon Houston, René L. Warren, Titus Wong, Linda M. N. Hoang, Caroline E. Cameron, Caren C. Helbing, Inanc Birol |
X Demographics
The data shown below were collected from the profile of 1 X user who shared this research output. Click here to find out more about how the information was compiled.
Geographical breakdown
Country | Count | As % |
---|---|---|
Unknown | 1 | 100% |
Demographic breakdown
Type | Count | As % |
---|---|---|
Members of the public | 1 | 100% |
Mendeley readers
The data shown below were compiled from readership statistics for 116 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
Country | Count | As % |
---|---|---|
Unknown | 116 | 100% |
Demographic breakdown
Readers by professional status | Count | As % |
---|---|---|
Researcher | 16 | 14% |
Student > Ph. D. Student | 14 | 12% |
Student > Master | 12 | 10% |
Student > Bachelor | 9 | 8% |
Student > Doctoral Student | 6 | 5% |
Other | 12 | 10% |
Unknown | 47 | 41% |
Readers by discipline | Count | As % |
---|---|---|
Biochemistry, Genetics and Molecular Biology | 27 | 23% |
Agricultural and Biological Sciences | 11 | 9% |
Computer Science | 8 | 7% |
Engineering | 4 | 3% |
Immunology and Microbiology | 3 | 3% |
Other | 15 | 13% |
Unknown | 48 | 41% |
Attention Score in Context
This research output has an Altmetric Attention Score of 1. 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 27 January 2022.
All research outputs
#15,478,452
of 23,001,641 outputs
Outputs from BMC Genomics
#6,724
of 10,692 outputs
Outputs of similar age
#280,645
of 502,330 outputs
Outputs of similar age from BMC Genomics
#117
of 185 outputs
Altmetric has tracked 23,001,641 research outputs across all sources so far. This one is in the 22nd percentile – i.e., 22% of other outputs scored the same or lower than it.
So far Altmetric has tracked 10,692 research outputs from this source. They receive a mean Attention Score of 4.7. This one is in the 28th percentile – i.e., 28% of its peers scored the same or lower than it.
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 502,330 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 31st percentile – i.e., 31% of its contemporaries scored the same or lower than it.
We're also able to compare this research output to 185 others from the same source and published within six weeks on either side of this one. This one is in the 22nd percentile – i.e., 22% of its contemporaries scored the same or lower than it.