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Deep Learning Algorithms Achieved Satisfactory Predictions When Trained on a Novel Collection of Anticoronavirus Molecules

Overview of attention for article published in Frontiers in Genetics, November 2021
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  • Average Attention Score compared to outputs of the same age
  • Good Attention Score compared to outputs of the same age and source (70th percentile)

Mentioned by

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3 X users

Citations

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8 Dimensions

Readers on

mendeley
32 Mendeley
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Title
Deep Learning Algorithms Achieved Satisfactory Predictions When Trained on a Novel Collection of Anticoronavirus Molecules
Published in
Frontiers in Genetics, November 2021
DOI 10.3389/fgene.2021.744170
Pubmed ID
Authors

Emna Harigua-Souiai, Mohamed Mahmoud Heinhane, Yosser Zina Abdelkrim, Oussama Souiai, Ines Abdeljaoued-Tej, Ikram Guizani

Timeline

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X Demographics

X Demographics

The data shown below were collected from the profiles of 3 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 32 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 32 100%

Demographic breakdown

Readers by professional status Count As %
Unspecified 6 19%
Student > Doctoral Student 3 9%
Student > Bachelor 2 6%
Student > Ph. D. Student 2 6%
Student > Master 2 6%
Other 7 22%
Unknown 10 31%
Readers by discipline Count As %
Unspecified 6 19%
Computer Science 5 16%
Biochemistry, Genetics and Molecular Biology 4 13%
Medicine and Dentistry 2 6%
Pharmacology, Toxicology and Pharmaceutical Science 2 6%
Other 3 9%
Unknown 10 31%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 2. 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 01 December 2021.
All research outputs
#15,030,956
of 23,885,338 outputs
Outputs from Frontiers in Genetics
#4,173
of 12,835 outputs
Outputs of similar age
#251,455
of 505,943 outputs
Outputs of similar age from Frontiers in Genetics
#208
of 761 outputs
Altmetric has tracked 23,885,338 research outputs across all sources so far. This one is in the 34th percentile – i.e., 34% of other outputs scored the same or lower than it.
So far Altmetric has tracked 12,835 research outputs from this source. They receive a mean Attention Score of 3.7. This one has gotten more attention than average, scoring higher than 63% 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 505,943 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 47th percentile – i.e., 47% of its contemporaries scored the same or lower than it.
We're also able to compare this research output to 761 others from the same source and published within six weeks on either side of this one. This one has gotten more attention than average, scoring higher than 70% of its contemporaries.