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Combining structural and bioactivity-based fingerprints improves prediction performance and scaffold hopping capability

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

  • Above-average Attention Score compared to outputs of the same age (62nd percentile)
  • Average Attention Score compared to outputs of the same age and source

Mentioned by

twitter
6 tweeters

Citations

dimensions_citation
22 Dimensions

Readers on

mendeley
69 Mendeley
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Title
Combining structural and bioactivity-based fingerprints improves prediction performance and scaffold hopping capability
Published in
Journal of Cheminformatics, August 2019
DOI 10.1186/s13321-019-0376-1
Authors

Oliver Laufkötter, Noé Sturm, Jürgen Bajorath, Hongming Chen, Ola Engkvist

Twitter Demographics

The data shown below were collected from the profiles of 6 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 69 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 69 100%

Demographic breakdown

Readers by professional status Count As %
Researcher 20 29%
Student > Ph. D. Student 13 19%
Student > Master 10 14%
Lecturer 3 4%
Student > Doctoral Student 3 4%
Other 5 7%
Unknown 15 22%
Readers by discipline Count As %
Chemistry 14 20%
Biochemistry, Genetics and Molecular Biology 12 17%
Computer Science 8 12%
Agricultural and Biological Sciences 5 7%
Pharmacology, Toxicology and Pharmaceutical Science 4 6%
Other 6 9%
Unknown 20 29%

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 12 August 2019.
All research outputs
#7,349,621
of 23,342,092 outputs
Outputs from Journal of Cheminformatics
#593
of 862 outputs
Outputs of similar age
#128,801
of 345,652 outputs
Outputs of similar age from Journal of Cheminformatics
#12
of 18 outputs
Altmetric has tracked 23,342,092 research outputs across all sources so far. This one has received more attention than most of these and is in the 68th percentile.
So far Altmetric has tracked 862 research outputs from this source. They typically receive a lot more attention than average, with a mean Attention Score of 11.0. This one is in the 30th percentile – i.e., 30% 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 345,652 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 62% 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 is in the 38th percentile – i.e., 38% of its contemporaries scored the same or lower than it.