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EvoMol: a flexible and interpretable evolutionary algorithm for unbiased de novo molecular generation

Overview of attention for article published in Journal of Cheminformatics, September 2020
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About this Attention Score

  • In the top 25% of all research outputs scored by Altmetric
  • High Attention Score compared to outputs of the same age (87th percentile)

Mentioned by

twitter
28 tweeters

Citations

dimensions_citation
2 Dimensions

Readers on

mendeley
37 Mendeley
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Title
EvoMol: a flexible and interpretable evolutionary algorithm for unbiased de novo molecular generation
Published in
Journal of Cheminformatics, September 2020
DOI 10.1186/s13321-020-00458-z
Authors

Jules Leguy, Thomas Cauchy, Marta Glavatskikh, Béatrice Duval, Benoit Da Mota

Twitter Demographics

The data shown below were collected from the profiles of 28 tweeters who shared this research output. Click here to find out more about how the information was compiled.

Mendeley readers

The data shown below were compiled from readership statistics for 37 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 37 100%

Demographic breakdown

Readers by professional status Count As %
Researcher 15 41%
Student > Ph. D. Student 8 22%
Other 5 14%
Student > Master 3 8%
Unspecified 1 3%
Other 2 5%
Unknown 3 8%
Readers by discipline Count As %
Chemistry 14 38%
Chemical Engineering 4 11%
Biochemistry, Genetics and Molecular Biology 3 8%
Engineering 3 8%
Pharmacology, Toxicology and Pharmaceutical Science 2 5%
Other 6 16%
Unknown 5 14%

Attention Score in Context

This research output has an Altmetric Attention Score of 17. 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 09 October 2020.
All research outputs
#1,317,459
of 17,389,828 outputs
Outputs from Journal of Cheminformatics
#127
of 672 outputs
Outputs of similar age
#39,650
of 315,779 outputs
Outputs of similar age from Journal of Cheminformatics
#1
of 1 outputs
Altmetric has tracked 17,389,828 research outputs across all sources so far. Compared to these this one has done particularly well and is in the 92nd percentile: it's in the top 10% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 672 research outputs from this source. They typically receive a lot more attention than average, with a mean Attention Score of 10.1. This one has done well, scoring higher than 81% 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 315,779 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 87% of its contemporaries.
We're also able to compare this research output to 1 others from the same source and published within six weeks on either side of this one. This one has scored higher than all of them