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X Demographics
Mendeley readers
Attention Score in Context
| Title |
SMILES-based deep generative scaffold decorator for de-novo drug design
|
|---|---|
| Published in |
Journal of Cheminformatics, May 2020
|
| DOI | 10.1186/s13321-020-00441-8 |
| Pubmed ID | |
| Authors |
Josep Arús-Pous, Atanas Patronov, Esben Jannik Bjerrum, Christian Tyrchan, Jean-Louis Reymond, Hongming Chen, Ola Engkvist |
X Demographics
The data shown below were collected from the profiles of 28 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 | 2 | 7% |
| Japan | 2 | 7% |
| Switzerland | 2 | 7% |
| United Kingdom | 1 | 4% |
| Mexico | 1 | 4% |
| Sweden | 1 | 4% |
| India | 1 | 4% |
| Unknown | 18 | 64% |
Demographic breakdown
| Type | Count | As % |
|---|---|---|
| Members of the public | 15 | 54% |
| Scientists | 12 | 43% |
| Science communicators (journalists, bloggers, editors) | 1 | 4% |
Mendeley readers
The data shown below were compiled from readership statistics for 201 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Unknown | 201 | 100% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Researcher | 49 | 24% |
| Student > Ph. D. Student | 25 | 12% |
| Student > Master | 21 | 10% |
| Student > Bachelor | 15 | 7% |
| Other | 9 | 4% |
| Other | 21 | 10% |
| Unknown | 61 | 30% |
| Readers by discipline | Count | As % |
|---|---|---|
| Chemistry | 42 | 21% |
| Computer Science | 28 | 14% |
| Biochemistry, Genetics and Molecular Biology | 14 | 7% |
| Pharmacology, Toxicology and Pharmaceutical Science | 12 | 6% |
| Engineering | 8 | 4% |
| Other | 27 | 13% |
| Unknown | 70 | 35% |
Attention Score in Context
This research output has an Altmetric Attention Score of 26. 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 04 August 2022.
All research outputs
#1,377,755
of 24,143,470 outputs
Outputs from Journal of Cheminformatics
#91
of 891 outputs
Outputs of similar age
#38,972
of 400,168 outputs
Outputs of similar age from Journal of Cheminformatics
#3
of 20 outputs
Altmetric has tracked 24,143,470 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 891 research outputs from this source. They typically receive a lot more attention than average, with a mean Attention Score of 10.7. This one has done well, scoring higher than 89% 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 400,168 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 90% of its contemporaries.
We're also able to compare this research output to 20 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 90% of its contemporaries.