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Incorporating structural similarity into a scoring function to enhance the prediction of binding affinities

Overview of attention for article published in Journal of Cheminformatics, February 2021
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About this Attention Score

  • Above-average Attention Score compared to outputs of the same age (56th percentile)

Mentioned by

twitter
7 X users

Citations

dimensions_citation
1 Dimensions

Readers on

mendeley
24 Mendeley
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Title
Incorporating structural similarity into a scoring function to enhance the prediction of binding affinities
Published in
Journal of Cheminformatics, February 2021
DOI 10.1186/s13321-021-00493-4
Pubmed ID
Authors

Beihong Ji, Xibing He, Yuzhao Zhang, Jingchen Zhai, Viet Hoang Man, Shuhan Liu, Junmei Wang

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 24 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 24 100%

Demographic breakdown

Readers by professional status Count As %
Researcher 6 25%
Student > Ph. D. Student 6 25%
Student > Bachelor 3 13%
Professor > Associate Professor 2 8%
Student > Master 1 4%
Other 1 4%
Unknown 5 21%
Readers by discipline Count As %
Biochemistry, Genetics and Molecular Biology 5 21%
Chemistry 4 17%
Pharmacology, Toxicology and Pharmaceutical Science 3 13%
Computer Science 2 8%
Agricultural and Biological Sciences 2 8%
Other 3 13%
Unknown 5 21%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 3. 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 18 February 2021.
All research outputs
#8,031,401
of 24,143,470 outputs
Outputs from Journal of Cheminformatics
#630
of 891 outputs
Outputs of similar age
#214,455
of 555,854 outputs
Outputs of similar age from Journal of Cheminformatics
#24
of 28 outputs
Altmetric has tracked 24,143,470 research outputs across all sources so far. This one is in the 44th percentile – i.e., 44% of other outputs scored the same or lower than it.
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 27th percentile – i.e., 27% 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 555,854 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 56% of its contemporaries.
We're also able to compare this research output to 28 others from the same source and published within six weeks on either side of this one. This one is in the 17th percentile – i.e., 17% of its contemporaries scored the same or lower than it.