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X Demographics
Mendeley readers
Attention Score in Context
| Title |
DrugEx v2: de novo design of drug molecules by Pareto-based multi-objective reinforcement learning in polypharmacology
|
|---|---|
| Published in |
Journal of Cheminformatics, November 2021
|
| DOI | 10.1186/s13321-021-00561-9 |
| Pubmed ID | |
| Authors |
Xuhan Liu, Kai Ye, Herman W. T. van Vlijmen, Michael T. M. Emmerich, Adriaan P. IJzerman, Gerard J. P. van Westen |
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 % |
|---|---|---|
| Netherlands | 4 | 19% |
| Japan | 2 | 10% |
| Germany | 2 | 10% |
| United Kingdom | 1 | 5% |
| Sweden | 1 | 5% |
| Switzerland | 1 | 5% |
| Unknown | 10 | 48% |
Demographic breakdown
| Type | Count | As % |
|---|---|---|
| Members of the public | 12 | 57% |
| Scientists | 8 | 38% |
| Science communicators (journalists, bloggers, editors) | 1 | 5% |
Mendeley readers
The data shown below were compiled from readership statistics for 79 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Unknown | 79 | 100% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Researcher | 12 | 15% |
| Student > Master | 12 | 15% |
| Student > Bachelor | 10 | 13% |
| Student > Ph. D. Student | 9 | 11% |
| Other | 4 | 5% |
| Other | 9 | 11% |
| Unknown | 23 | 29% |
| Readers by discipline | Count | As % |
|---|---|---|
| Chemistry | 13 | 16% |
| Biochemistry, Genetics and Molecular Biology | 9 | 11% |
| Computer Science | 9 | 11% |
| Pharmacology, Toxicology and Pharmaceutical Science | 8 | 10% |
| Medicine and Dentistry | 3 | 4% |
| Other | 12 | 15% |
| Unknown | 25 | 32% |
Attention Score in Context
This research output has an Altmetric Attention Score of 12. 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 November 2021.
All research outputs
#2,999,716
of 25,155,561 outputs
Outputs from Journal of Cheminformatics
#271
of 946 outputs
Outputs of similar age
#63,682
of 430,370 outputs
Outputs of similar age from Journal of Cheminformatics
#8
of 26 outputs
Altmetric has tracked 25,155,561 research outputs across all sources so far. Compared to these this one has done well and is in the 88th percentile: it's in the top 25% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 946 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 gotten more attention than average, scoring higher than 71% 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 430,370 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 85% of its contemporaries.
We're also able to compare this research output to 26 others from the same source and published within six weeks on either side of this one. This one has gotten more attention than average, scoring higher than 73% of its contemporaries.