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NGS data vectorization, clustering, and finding key codons in SARS-CoV-2 variations

Overview of attention for article published in BMC Bioinformatics, May 2022
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About this Attention Score

  • Above-average Attention Score compared to outputs of the same age (54th percentile)
  • Average Attention Score compared to outputs of the same age and source

Mentioned by

twitter
5 X users

Citations

dimensions_citation
2 Dimensions

Readers on

mendeley
20 Mendeley
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Title
NGS data vectorization, clustering, and finding key codons in SARS-CoV-2 variations
Published in
BMC Bioinformatics, May 2022
DOI 10.1186/s12859-022-04718-7
Pubmed ID
Authors

Juhyeon Kim, Saeyeon Cheon, Insung Ahn

X Demographics

X Demographics

The data shown below were collected from the profiles of 5 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 20 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 20 100%

Demographic breakdown

Readers by professional status Count As %
Student > Master 2 10%
Lecturer > Senior Lecturer 1 5%
Librarian 1 5%
Unspecified 1 5%
Professor 1 5%
Other 3 15%
Unknown 11 55%
Readers by discipline Count As %
Computer Science 3 15%
Biochemistry, Genetics and Molecular Biology 2 10%
Nursing and Health Professions 1 5%
Social Sciences 1 5%
Medicine and Dentistry 1 5%
Other 1 5%
Unknown 11 55%
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 18 May 2022.
All research outputs
#14,050,092
of 23,792,386 outputs
Outputs from BMC Bioinformatics
#4,283
of 7,439 outputs
Outputs of similar age
#190,278
of 443,481 outputs
Outputs of similar age from BMC Bioinformatics
#80
of 148 outputs
Altmetric has tracked 23,792,386 research outputs across all sources so far. This one is in the 39th percentile – i.e., 39% of other outputs scored the same or lower than it.
So far Altmetric has tracked 7,439 research outputs from this source. They typically receive a little more attention than average, with a mean Attention Score of 5.5. This one is in the 39th percentile – i.e., 39% of its peers scored the same or lower than it.
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 443,481 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 54% of its contemporaries.
We're also able to compare this research output to 148 others from the same source and published within six weeks on either side of this one. This one is in the 40th percentile – i.e., 40% of its contemporaries scored the same or lower than it.