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Novel Computational Approach to Predict Off-Target Interactions for Small Molecules

Overview of attention for article published in Frontiers in Big Data, July 2019
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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 (86th percentile)

Mentioned by

news
1 news outlet
blogs
1 blog
twitter
2 X users
f1000
1 research highlight platform

Readers on

mendeley
135 Mendeley
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Title
Novel Computational Approach to Predict Off-Target Interactions for Small Molecules
Published in
Frontiers in Big Data, July 2019
DOI 10.3389/fdata.2019.00025
Pubmed ID
Authors

Mohan S. Rao, Rishi Gupta, Michael J. Liguori, Mufeng Hu, Xin Huang, Srinivasa R. Mantena, Scott W. Mittelstadt, Eric A. G. Blomme, Terry R. Van Vleet

Timeline

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X Demographics

X Demographics

The data shown below were collected from the profiles of 2 X users who shared this research output. Click here to find out more about how the information was compiled.
As of 1 July 2024, you may notice a temporary increase in the numbers of X profiles with Unknown location. Click here to learn more.
Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 135 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 135 100%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 20 15%
Researcher 20 15%
Student > Master 17 13%
Student > Bachelor 10 7%
Other 6 4%
Other 10 7%
Unknown 52 39%
Readers by discipline Count As %
Biochemistry, Genetics and Molecular Biology 25 19%
Pharmacology, Toxicology and Pharmaceutical Science 13 10%
Agricultural and Biological Sciences 12 9%
Chemistry 11 8%
Medicine and Dentistry 5 4%
Other 14 10%
Unknown 55 41%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 16. 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 08 February 2022.
All research outputs
#2,311,091
of 25,992,468 outputs
Outputs from Frontiers in Big Data
#1
of 1 outputs
Outputs of similar age
#45,004
of 346,019 outputs
Outputs of similar age from Frontiers in Big Data
#1
of 1 outputs
Altmetric has tracked 25,992,468 research outputs across all sources so far. Compared to these this one has done particularly well and is in the 91st percentile: it's in the top 10% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 1 research outputs from this source. They typically receive a lot more attention than average, with a mean Attention Score of 15.8. This one scored the same or higher as 0 of them.
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 346,019 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 86% of its contemporaries.
We're also able to compare this research output to 1 others from the same source and published within six weeks on either side of this one. This one has scored higher than all of them