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X Demographics
Mendeley readers
Attention Score in Context
| Title |
Comparison of structure- and ligand-based scoring functions for deep generative models: a GPCR case study
|
|---|---|
| Published in |
Journal of Cheminformatics, May 2021
|
| DOI | 10.1186/s13321-021-00516-0 |
| Pubmed ID | |
| Authors |
Morgan Thomas, Robert T. Smith, Noel M. O’Boyle, Chris de Graaf, Andreas Bender |
X Demographics
The data shown below were collected from the profiles of 19 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 | 4 | 21% |
| Japan | 4 | 21% |
| France | 1 | 5% |
| Turkey | 1 | 5% |
| Unknown | 9 | 47% |
Demographic breakdown
| Type | Count | As % |
|---|---|---|
| Members of the public | 11 | 58% |
| Scientists | 7 | 37% |
| Science communicators (journalists, bloggers, editors) | 1 | 5% |
Mendeley readers
The data shown below were compiled from readership statistics for 135 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Unknown | 135 | 100% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Researcher | 30 | 22% |
| Student > Ph. D. Student | 15 | 11% |
| Student > Master | 14 | 10% |
| Student > Bachelor | 7 | 5% |
| Other | 6 | 4% |
| Other | 17 | 13% |
| Unknown | 46 | 34% |
| Readers by discipline | Count | As % |
|---|---|---|
| Chemistry | 24 | 18% |
| Pharmacology, Toxicology and Pharmaceutical Science | 11 | 8% |
| Computer Science | 9 | 7% |
| Biochemistry, Genetics and Molecular Biology | 8 | 6% |
| Agricultural and Biological Sciences | 5 | 4% |
| Other | 27 | 20% |
| Unknown | 51 | 38% |
Attention Score in Context
This research output has an Altmetric Attention Score of 27. 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 19 June 2023.
All research outputs
#1,322,530
of 24,169,085 outputs
Outputs from Journal of Cheminformatics
#76
of 890 outputs
Outputs of similar age
#34,853
of 431,465 outputs
Outputs of similar age from Journal of Cheminformatics
#3
of 16 outputs
Altmetric has tracked 24,169,085 research outputs across all sources so far. Compared to these this one has done particularly well and is in the 94th percentile: it's in the top 10% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 890 research outputs from this source. They typically receive a lot more attention than average, with a mean Attention Score of 10.5. This one has done particularly well, scoring higher than 91% 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 431,465 tracked outputs that were published within six weeks on either side of this one in any source. This one has done particularly well, scoring higher than 91% of its contemporaries.
We're also able to compare this research output to 16 others from the same source and published within six weeks on either side of this one. This one has done well, scoring higher than 87% of its contemporaries.