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X Demographics
Mendeley readers
Attention Score in Context
| Title |
A de novo molecular generation method using latent vector based generative adversarial network
|
|---|---|
| Published in |
Journal of Cheminformatics, December 2019
|
| DOI | 10.1186/s13321-019-0397-9 |
| Pubmed ID | |
| Authors |
Oleksii Prykhodko, Simon Viet Johansson, Panagiotis-Christos Kotsias, Josep Arús-Pous, Esben Jannik Bjerrum, Ola Engkvist, Hongming Chen |
X Demographics
The data shown below were collected from the profiles of 18 X users who shared this research output. Click here to find out more about how the information was compiled.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Japan | 1 | 6% |
| United Kingdom | 1 | 6% |
| United States | 1 | 6% |
| Israel | 1 | 6% |
| India | 1 | 6% |
| Sweden | 1 | 6% |
| Unknown | 12 | 67% |
Demographic breakdown
| Type | Count | As % |
|---|---|---|
| Scientists | 10 | 56% |
| Members of the public | 7 | 39% |
| Science communicators (journalists, bloggers, editors) | 1 | 6% |
Mendeley readers
The data shown below were compiled from readership statistics for 279 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Unknown | 279 | 100% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Student > Ph. D. Student | 45 | 16% |
| Researcher | 44 | 16% |
| Student > Master | 34 | 12% |
| Student > Bachelor | 15 | 5% |
| Other | 8 | 3% |
| Other | 27 | 10% |
| Unknown | 106 | 38% |
| Readers by discipline | Count | As % |
|---|---|---|
| Chemistry | 44 | 16% |
| Computer Science | 38 | 14% |
| Biochemistry, Genetics and Molecular Biology | 19 | 7% |
| Pharmacology, Toxicology and Pharmaceutical Science | 11 | 4% |
| Engineering | 10 | 4% |
| Other | 32 | 11% |
| Unknown | 125 | 45% |
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 31 July 2020.
All research outputs
#2,277,806
of 25,713,737 outputs
Outputs from Journal of Cheminformatics
#190
of 981 outputs
Outputs of similar age
#53,264
of 479,546 outputs
Outputs of similar age from Journal of Cheminformatics
#4
of 20 outputs
Altmetric has tracked 25,713,737 research outputs across all sources so far. Compared to these this one has done particularly well and is in the 91st percentile: it's in the top 10% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 981 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 80% 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 479,546 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 88% 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 well, scoring higher than 80% of its contemporaries.