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Identification of novel inhibitors for SARS-CoV-2 as therapeutic options using machine learning-based virtual screening, molecular docking and MD simulation

Overview of attention for article published in Frontiers in Molecular Biosciences, March 2023
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About this Attention Score

  • Good Attention Score compared to outputs of the same age (66th percentile)
  • High Attention Score compared to outputs of the same age and source (81st percentile)

Mentioned by

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6 X users

Readers on

mendeley
24 Mendeley
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Title
Identification of novel inhibitors for SARS-CoV-2 as therapeutic options using machine learning-based virtual screening, molecular docking and MD simulation
Published in
Frontiers in Molecular Biosciences, March 2023
DOI 10.3389/fmolb.2023.1060076
Pubmed ID
Authors

Abdus Samad, Amar Ajmal, Arif Mahmood, Beenish Khurshid, Ping Li, Syed Mansoor Jan, Ashfaq Ur Rehman, Pei He, Ashraf N. Abdalla, Muhammad Umair, Junjian Hu, Abdul Wadood

Timeline

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X Demographics

X Demographics

The data shown below were collected from the profiles of 6 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 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 %
Lecturer 3 13%
Researcher 2 8%
Student > Postgraduate 2 8%
Student > Bachelor 1 4%
Professor 1 4%
Other 5 21%
Unknown 10 42%
Readers by discipline Count As %
Biochemistry, Genetics and Molecular Biology 4 17%
Chemistry 4 17%
Agricultural and Biological Sciences 2 8%
Nursing and Health Professions 1 4%
Unspecified 1 4%
Other 2 8%
Unknown 10 42%
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 26 March 2023.
All research outputs
#8,039,503
of 25,584,565 outputs
Outputs from Frontiers in Molecular Biosciences
#818
of 4,750 outputs
Outputs of similar age
#141,619
of 425,487 outputs
Outputs of similar age from Frontiers in Molecular Biosciences
#45
of 243 outputs
Altmetric has tracked 25,584,565 research outputs across all sources so far. This one has received more attention than most of these and is in the 67th percentile.
So far Altmetric has tracked 4,750 research outputs from this source. They receive a mean Attention Score of 3.5. This one has done well, scoring higher than 82% 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 425,487 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 243 others from the same source and published within six weeks on either side of this one. This one has done well, scoring higher than 81% of its contemporaries.