↓ Skip to main content

Uncanny similarity of unique inserts in the 2019-nCoV spike protein to HIV-1 gp120 and Gag

Overview of attention for article published in bioRxiv, January 2020
Altmetric Badge

About this Attention Score

  • In the top 5% of all research outputs scored by Altmetric
  • One of the highest-scoring outputs from this source (#1 of 8,518)
  • High Attention Score compared to outputs of the same age (99th percentile)
  • High Attention Score compared to outputs of the same age and source (99th percentile)

Citations

dimensions_citation
126 Dimensions

Readers on

mendeley
233 Mendeley
You are seeing a free-to-access but limited selection of the activity Altmetric has collected about this research output. Click here to find out more.
Title
Uncanny similarity of unique inserts in the 2019-nCoV spike protein to HIV-1 gp120 and Gag
Published in
bioRxiv, January 2020
DOI 10.1101/2020.01.30.927871
Authors

Prashant Pradhan, Ashutosh Kumar Pandey, Akhilesh Mishra, Parul Gupta, Praveen Kumar Tripathi, Manoj Balakrishnan Menon, James Gomes, Perumal Vivekanandan, Bishwajit Kundu

X Demographics

X Demographics

The data shown below were collected from the profiles of 17,324 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 233 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 233 100%

Demographic breakdown

Readers by professional status Count As %
Researcher 40 17%
Student > Ph. D. Student 34 15%
Student > Bachelor 30 13%
Other 21 9%
Student > Master 20 9%
Other 40 17%
Unknown 48 21%
Readers by discipline Count As %
Biochemistry, Genetics and Molecular Biology 40 17%
Medicine and Dentistry 36 15%
Agricultural and Biological Sciences 20 9%
Computer Science 15 6%
Pharmacology, Toxicology and Pharmaceutical Science 10 4%
Other 50 21%
Unknown 62 27%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 14394. 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 July 2024.
All research outputs
#75
of 26,377,159 outputs
Outputs from bioRxiv
#1
of 8,518 outputs
Outputs of similar age
#3
of 480,058 outputs
Outputs of similar age from bioRxiv
#1
of 125 outputs
Altmetric has tracked 26,377,159 research outputs across all sources so far. Compared to these this one has done particularly well and is in the 99th percentile: it's in the top 5% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 8,518 research outputs from this source. They typically receive a lot more attention than average, with a mean Attention Score of 26.2. This one has done particularly well, scoring higher than 99% 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 480,058 tracked outputs that were published within six weeks on either side of this one in any source. This one has done particularly well, scoring higher than 99% of its contemporaries.
We're also able to compare this research output to 125 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 99% of its contemporaries.