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X Demographics
Mendeley readers
Attention Score in Context
| Title |
PUResNet: prediction of protein-ligand binding sites using deep residual neural network
|
|---|---|
| Published in |
Journal of Cheminformatics, September 2021
|
| DOI | 10.1186/s13321-021-00547-7 |
| Pubmed ID | |
| Authors |
Jeevan Kandel, Hilal Tayara, Kil To Chong |
X Demographics
The data shown below were collected from the profiles of 32 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 States | 3 | 9% |
| Japan | 3 | 9% |
| India | 2 | 6% |
| United Kingdom | 2 | 6% |
| Thailand | 1 | 3% |
| China | 1 | 3% |
| South Africa | 1 | 3% |
| Belgium | 1 | 3% |
| Germany | 1 | 3% |
| Other | 5 | 16% |
| Unknown | 12 | 38% |
Demographic breakdown
| Type | Count | As % |
|---|---|---|
| Members of the public | 20 | 63% |
| Scientists | 11 | 34% |
| Science communicators (journalists, bloggers, editors) | 1 | 3% |
Mendeley readers
The data shown below were compiled from readership statistics for 91 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Unknown | 91 | 100% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Researcher | 12 | 13% |
| Student > Ph. D. Student | 11 | 12% |
| Student > Master | 8 | 9% |
| Student > Bachelor | 7 | 8% |
| Other | 5 | 5% |
| Other | 9 | 10% |
| Unknown | 39 | 43% |
| Readers by discipline | Count | As % |
|---|---|---|
| Biochemistry, Genetics and Molecular Biology | 13 | 14% |
| Chemistry | 9 | 10% |
| Pharmacology, Toxicology and Pharmaceutical Science | 8 | 9% |
| Computer Science | 7 | 8% |
| Agricultural and Biological Sciences | 5 | 5% |
| Other | 10 | 11% |
| Unknown | 39 | 43% |
Attention Score in Context
This research output has an Altmetric Attention Score of 16. 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 06 May 2022.
All research outputs
#2,336,634
of 25,635,728 outputs
Outputs from Journal of Cheminformatics
#196
of 979 outputs
Outputs of similar age
#53,017
of 434,944 outputs
Outputs of similar age from Journal of Cheminformatics
#6
of 28 outputs
Altmetric has tracked 25,635,728 research outputs across all sources so far. Compared to these this one has done particularly well and is in the 90th percentile: it's in the top 10% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 979 research outputs from this source. They typically receive more attention than average, with a mean Attention Score of 10.0. This one has done well, scoring higher than 79% 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 434,944 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 87% of its contemporaries.
We're also able to compare this research output to 28 others from the same source and published within six weeks on either side of this one. This one has done well, scoring higher than 78% of its contemporaries.