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Evaluation of deep and shallow learning methods in chemogenomics for the prediction of drugs specificity

Overview of attention for article published in Journal of Cheminformatics, February 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 (85th percentile)

Mentioned by

twitter
29 tweeters

Citations

dimensions_citation
12 Dimensions

Readers on

mendeley
46 Mendeley
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Title
Evaluation of deep and shallow learning methods in chemogenomics for the prediction of drugs specificity
Published in
Journal of Cheminformatics, February 2020
DOI 10.1186/s13321-020-0413-0
Authors

Benoit Playe, Veronique Stoven

Twitter Demographics

The data shown below were collected from the profiles of 29 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 46 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 46 100%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 11 24%
Researcher 10 22%
Student > Master 7 15%
Lecturer 4 9%
Professor 3 7%
Other 2 4%
Unknown 9 20%
Readers by discipline Count As %
Computer Science 7 15%
Chemistry 7 15%
Biochemistry, Genetics and Molecular Biology 6 13%
Engineering 4 9%
Agricultural and Biological Sciences 3 7%
Other 8 17%
Unknown 11 24%

Attention Score in Context

This research output has an Altmetric Attention Score of 13. 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 29 June 2021.
All research outputs
#1,925,101
of 19,268,016 outputs
Outputs from Journal of Cheminformatics
#203
of 729 outputs
Outputs of similar age
#50,617
of 353,346 outputs
Outputs of similar age from Journal of Cheminformatics
#1
of 1 outputs
Altmetric has tracked 19,268,016 research outputs across all sources so far. Compared to these this one has done particularly well and is in the 90th percentile: it's in the top 10% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 729 research outputs from this source. They typically receive a lot more attention than average, with a mean Attention Score of 10.5. This one has gotten more attention than average, scoring higher than 72% 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 353,346 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 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