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Off-targetP ML: an open source machine learning framework for off-target panel safety assessment of small molecules

Overview of attention for article published in Journal of Cheminformatics, May 2022
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About this Attention Score

  • In the top 25% of all research outputs scored by Altmetric
  • Good Attention Score compared to outputs of the same age (78th percentile)
  • Average Attention Score compared to outputs of the same age and source

Mentioned by

twitter
14 X users

Citations

dimensions_citation
6 Dimensions

Readers on

mendeley
33 Mendeley
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Title
Off-targetP ML: an open source machine learning framework for off-target panel safety assessment of small molecules
Published in
Journal of Cheminformatics, May 2022
DOI 10.1186/s13321-022-00603-w
Pubmed ID
Authors

Doha Naga, Wolfgang Muster, Eunice Musvasva, Gerhard F. Ecker

X Demographics

X Demographics

The data shown below were collected from the profiles of 14 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 33 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 33 100%

Demographic breakdown

Readers by professional status Count As %
Researcher 5 15%
Student > Ph. D. Student 4 12%
Student > Bachelor 3 9%
Professor 3 9%
Professor > Associate Professor 2 6%
Other 3 9%
Unknown 13 39%
Readers by discipline Count As %
Pharmacology, Toxicology and Pharmaceutical Science 6 18%
Chemistry 4 12%
Biochemistry, Genetics and Molecular Biology 3 9%
Engineering 3 9%
Business, Management and Accounting 2 6%
Other 3 9%
Unknown 12 36%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 8. 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 13 May 2022.
All research outputs
#4,248,596
of 24,079,942 outputs
Outputs from Journal of Cheminformatics
#399
of 886 outputs
Outputs of similar age
#90,340
of 429,974 outputs
Outputs of similar age from Journal of Cheminformatics
#12
of 22 outputs
Altmetric has tracked 24,079,942 research outputs across all sources so far. Compared to these this one has done well and is in the 82nd percentile: it's in the top 25% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 886 research outputs from this source. They typically receive a lot more attention than average, with a mean Attention Score of 10.6. This one has gotten more attention than average, scoring higher than 55% 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 429,974 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 78% of its contemporaries.
We're also able to compare this research output to 22 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.