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Avoiding hERG-liability in drug design via synergetic combinations of different (Q)SAR methodologies and data sources: a case study in an industrial setting

Overview of attention for article published in Journal of Cheminformatics, February 2019
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About this Attention Score

  • Good Attention Score compared to outputs of the same age (66th percentile)
  • Average Attention Score compared to outputs of the same age and source

Mentioned by

twitter
7 X users

Citations

dimensions_citation
15 Dimensions

Readers on

mendeley
33 Mendeley
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Title
Avoiding hERG-liability in drug design via synergetic combinations of different (Q)SAR methodologies and data sources: a case study in an industrial setting
Published in
Journal of Cheminformatics, February 2019
DOI 10.1186/s13321-019-0334-y
Pubmed ID
Authors

Thierry Hanser, Fabian P. Steinmetz, Jeffrey Plante, Friedrich Rippmann, Mireille Krier

X Demographics

X Demographics

The data shown below were collected from the profiles of 7 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 9 27%
Student > Ph. D. Student 5 15%
Student > Doctoral Student 3 9%
Student > Bachelor 3 9%
Lecturer 1 3%
Other 0 0%
Unknown 12 36%
Readers by discipline Count As %
Chemistry 7 21%
Biochemistry, Genetics and Molecular Biology 2 6%
Pharmacology, Toxicology and Pharmaceutical Science 2 6%
Business, Management and Accounting 1 3%
Agricultural and Biological Sciences 1 3%
Other 4 12%
Unknown 16 48%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 4. 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 24 February 2019.
All research outputs
#7,426,078
of 24,143,470 outputs
Outputs from Journal of Cheminformatics
#594
of 891 outputs
Outputs of similar age
#149,488
of 445,631 outputs
Outputs of similar age from Journal of Cheminformatics
#16
of 23 outputs
Altmetric has tracked 24,143,470 research outputs across all sources so far. This one has received more attention than most of these and is in the 69th percentile.
So far Altmetric has tracked 891 research outputs from this source. They typically receive a lot more attention than average, with a mean Attention Score of 10.7. This one is in the 32nd percentile – i.e., 32% of its peers scored the same or lower than it.
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 445,631 tracked outputs that were published within six weeks on either side of this one in any source. This one has gotten more attention than average, scoring higher than 66% of its contemporaries.
We're also able to compare this research output to 23 others from the same source and published within six weeks on either side of this one. This one is in the 34th percentile – i.e., 34% of its contemporaries scored the same or lower than it.