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Utilizing genomic signatures to gain insights into the dynamics of SARS-CoV-2 through Machine and Deep Learning techniques

Overview of attention for article published in BMC Bioinformatics, March 2024
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About this Attention Score

  • Good Attention Score compared to outputs of the same age (68th percentile)
  • Above-average Attention Score compared to outputs of the same age and source (62nd percentile)

Mentioned by

twitter
4 X users

Readers on

mendeley
2 Mendeley
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Title
Utilizing genomic signatures to gain insights into the dynamics of SARS-CoV-2 through Machine and Deep Learning techniques
Published in
BMC Bioinformatics, March 2024
DOI 10.1186/s12859-024-05648-2
Pubmed ID
Authors

Ahmed M. A. Elsherbini, Amr Hassan Elkholy, Youssef M. Fadel, Gleb Goussarov, Ahmed Mohamed Elshal, Mohamed El-Hadidi, Mohamed Mysara

X Demographics

X Demographics

The data shown below were collected from the profiles of 4 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 2 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 2 100%

Demographic breakdown

Readers by professional status Count As %
Researcher 1 50%
Unspecified 1 50%
Readers by discipline Count As %
Unspecified 1 50%
Biochemistry, Genetics and Molecular Biology 1 50%
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 30 March 2024.
All research outputs
#8,516,283
of 25,601,426 outputs
Outputs from BMC Bioinformatics
#3,213
of 7,725 outputs
Outputs of similar age
#52,075
of 167,830 outputs
Outputs of similar age from BMC Bioinformatics
#17
of 43 outputs
Altmetric has tracked 25,601,426 research outputs across all sources so far. This one has received more attention than most of these and is in the 66th percentile.
So far Altmetric has tracked 7,725 research outputs from this source. They typically receive a little more attention than average, with a mean Attention Score of 5.5. This one has gotten more attention than average, scoring higher than 58% 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 167,830 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 68% of its contemporaries.
We're also able to compare this research output to 43 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 62% of its contemporaries.