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Machine Learning From Molecular Dynamics Trajectories to Predict Caspase-8 Inhibitors Against Alzheimer’s Disease

Overview of attention for article published in Frontiers in Pharmacology, 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 (85th percentile)
  • High Attention Score compared to outputs of the same age and source (90th percentile)

Mentioned by

news
1 news outlet
twitter
8 X users
reddit
1 Redditor

Citations

dimensions_citation
40 Dimensions

Readers on

mendeley
98 Mendeley
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Title
Machine Learning From Molecular Dynamics Trajectories to Predict Caspase-8 Inhibitors Against Alzheimer’s Disease
Published in
Frontiers in Pharmacology, July 2019
DOI 10.3389/fphar.2019.00780
Pubmed ID
Authors

Salma Jamal, Abhinav Grover, Sonam Grover

X Demographics

X Demographics

The data shown below were collected from the profiles of 8 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 98 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 98 100%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 32 33%
Student > Master 10 10%
Student > Bachelor 6 6%
Student > Doctoral Student 6 6%
Researcher 6 6%
Other 12 12%
Unknown 26 27%
Readers by discipline Count As %
Biochemistry, Genetics and Molecular Biology 14 14%
Chemistry 10 10%
Pharmacology, Toxicology and Pharmaceutical Science 10 10%
Engineering 9 9%
Neuroscience 4 4%
Other 19 19%
Unknown 32 33%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 14. 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 02 August 2019.
All research outputs
#2,256,254
of 23,152,542 outputs
Outputs from Frontiers in Pharmacology
#865
of 16,541 outputs
Outputs of similar age
#49,451
of 346,549 outputs
Outputs of similar age from Frontiers in Pharmacology
#30
of 302 outputs
Altmetric has tracked 23,152,542 research outputs across all sources so far. Compared to these this one has done particularly well and is in the 90th percentile: it's in the top 10% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 16,541 research outputs from this source. They typically receive a little more attention than average, with a mean Attention Score of 5.0. This one has done particularly well, scoring higher than 94% 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 346,549 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 85% of its contemporaries.
We're also able to compare this research output to 302 others from the same source and published within six weeks on either side of this one. This one has done particularly well, scoring higher than 90% of its contemporaries.