| Title |
Randomized SMILES strings improve the quality of molecular generative models
|
|---|---|
| Published in |
Journal of Cheminformatics, November 2019
|
| DOI | 10.1186/s13321-019-0393-0 |
| Pubmed ID | |
| Authors |
Josep Arús-Pous, Simon Viet Johansson, Oleksii Prykhodko, Esben Jannik Bjerrum, Christian Tyrchan, Jean-Louis Reymond, Hongming Chen, Ola Engkvist |
X Demographics
The data shown below were collected from the profiles of 21 X users who shared this research output. Click here to find out more about how the information was compiled.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Switzerland | 3 | 14% |
| United States | 1 | 5% |
| Sweden | 1 | 5% |
| Japan | 1 | 5% |
| Korea, Republic of | 1 | 5% |
| India | 1 | 5% |
| Unknown | 13 | 62% |
Demographic breakdown
| Type | Count | As % |
|---|---|---|
| Scientists | 13 | 62% |
| Members of the public | 7 | 33% |
| Science communicators (journalists, bloggers, editors) | 1 | 5% |
Mendeley readers
The data shown below were compiled from readership statistics for 243 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Unknown | 243 | 100% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Researcher | 49 | 20% |
| Student > Ph. D. Student | 38 | 16% |
| Student > Master | 27 | 11% |
| Student > Bachelor | 23 | 9% |
| Other | 11 | 5% |
| Other | 16 | 7% |
| Unknown | 79 | 33% |
| Readers by discipline | Count | As % |
|---|---|---|
| Chemistry | 52 | 21% |
| Computer Science | 30 | 12% |
| Biochemistry, Genetics and Molecular Biology | 21 | 9% |
| Pharmacology, Toxicology and Pharmaceutical Science | 11 | 5% |
| Engineering | 8 | 3% |
| Other | 28 | 12% |
| Unknown | 93 | 38% |
Attention Score in Context
This research output has an Altmetric Attention Score of 41. 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 11 February 2023.
All research outputs
#1,021,300
of 26,017,215 outputs
Outputs from Journal of Cheminformatics
#29
of 984 outputs
Outputs of similar age
#24,288
of 480,630 outputs
Outputs of similar age from Journal of Cheminformatics
#1
of 19 outputs
Altmetric has tracked 26,017,215 research outputs across all sources so far. Compared to these this one has done particularly well and is in the 95th percentile: it's in the top 5% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 984 research outputs from this source. They typically receive a lot more attention than average, with a mean Attention Score of 10.2. This one has done particularly well, scoring higher than 97% 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 480,630 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 94% of its contemporaries.
We're also able to compare this research output to 19 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 94% of its contemporaries.