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Building attention and edge message passing neural networks for bioactivity and physical–chemical property prediction

Overview of attention for article published in Journal of Cheminformatics, January 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)
  • Good Attention Score compared to outputs of the same age and source (74th percentile)

Mentioned by

blogs
1 blog
twitter
13 tweeters
patent
1 patent

Citations

dimensions_citation
71 Dimensions

Readers on

mendeley
133 Mendeley
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Title
Building attention and edge message passing neural networks for bioactivity and physical–chemical property prediction
Published in
Journal of Cheminformatics, January 2020
DOI 10.1186/s13321-019-0407-y
Pubmed ID
Authors

M. Withnall, E. Lindelöf, O. Engkvist, H. Chen

Twitter Demographics

The data shown below were collected from the profiles of 13 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 133 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 133 100%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 26 20%
Researcher 22 17%
Student > Master 18 14%
Student > Bachelor 9 7%
Other 6 5%
Other 13 10%
Unknown 39 29%
Readers by discipline Count As %
Chemistry 26 20%
Computer Science 25 19%
Engineering 7 5%
Agricultural and Biological Sciences 6 5%
Biochemistry, Genetics and Molecular Biology 5 4%
Other 19 14%
Unknown 45 34%

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 16 September 2021.
All research outputs
#1,828,206
of 22,039,250 outputs
Outputs from Journal of Cheminformatics
#174
of 807 outputs
Outputs of similar age
#53,541
of 428,976 outputs
Outputs of similar age from Journal of Cheminformatics
#21
of 78 outputs
Altmetric has tracked 22,039,250 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 807 research outputs from this source. They typically receive a lot more attention than average, with a mean Attention Score of 11.1. This one has done well, scoring higher than 78% 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 428,976 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 78 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 74% of its contemporaries.