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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 (84th percentile)
  • Average Attention Score compared to outputs of the same age and source

Mentioned by

twitter
23 X users

Citations

dimensions_citation
28 Dimensions

Readers on

mendeley
78 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
Pubmed ID
Authors

Benoit Playe, Veronique Stoven

X Demographics

X Demographics

The data shown below were collected from the profiles of 23 X users who shared this research output. Click here to find out more about how the information was compiled.
Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 78 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 78 100%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 14 18%
Researcher 11 14%
Student > Master 8 10%
Professor 6 8%
Lecturer 3 4%
Other 7 9%
Unknown 29 37%
Readers by discipline Count As %
Biochemistry, Genetics and Molecular Biology 10 13%
Computer Science 9 12%
Engineering 6 8%
Chemistry 6 8%
Pharmacology, Toxicology and Pharmaceutical Science 4 5%
Other 11 14%
Unknown 32 41%
Attention Score in Context

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 23 February 2020.
All research outputs
#3,046,537
of 24,903,209 outputs
Outputs from Journal of Cheminformatics
#285
of 934 outputs
Outputs of similar age
#71,103
of 468,180 outputs
Outputs of similar age from Journal of Cheminformatics
#10
of 18 outputs
Altmetric has tracked 24,903,209 research outputs across all sources so far. Compared to these this one has done well and is in the 87th percentile: it's in the top 25% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 934 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 69% 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 468,180 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 84% of its contemporaries.
We're also able to compare this research output to 18 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 50% of its contemporaries.