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Normal modes analysis and surface electrostatics of haemagglutinin proteins as fingerprints for high pathogenic type A influenza viruses

Overview of attention for article published in BMC Bioinformatics, August 2020
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About this Attention Score

  • Average Attention Score compared to outputs of the same age

Mentioned by

twitter
3 tweeters
facebook
1 Facebook page

Citations

dimensions_citation
3 Dimensions

Readers on

mendeley
15 Mendeley
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Title
Normal modes analysis and surface electrostatics of haemagglutinin proteins as fingerprints for high pathogenic type A influenza viruses
Published in
BMC Bioinformatics, August 2020
DOI 10.1186/s12859-020-03563-w
Pubmed ID
Authors

Irene Righetto, Francesco Filippini

Twitter Demographics

The data shown below were collected from the profiles of 3 tweeters who shared this research output. Click here to find out more about how the information was compiled.

Mendeley readers

The data shown below were compiled from readership statistics for 15 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 15 100%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 3 20%
Other 2 13%
Student > Master 2 13%
Student > Doctoral Student 1 7%
Student > Postgraduate 1 7%
Other 2 13%
Unknown 4 27%
Readers by discipline Count As %
Biochemistry, Genetics and Molecular Biology 3 20%
Medicine and Dentistry 2 13%
Social Sciences 2 13%
Agricultural and Biological Sciences 1 7%
Veterinary Science and Veterinary Medicine 1 7%
Other 2 13%
Unknown 4 27%

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 02 August 2021.
All research outputs
#14,095,233
of 21,712,946 outputs
Outputs from BMC Bioinformatics
#4,863
of 7,013 outputs
Outputs of similar age
#188,910
of 317,177 outputs
Outputs of similar age from BMC Bioinformatics
#36
of 48 outputs
Altmetric has tracked 21,712,946 research outputs across all sources so far. This one is in the 33rd percentile – i.e., 33% of other outputs scored the same or lower than it.
So far Altmetric has tracked 7,013 research outputs from this source. They typically receive a little more attention than average, with a mean Attention Score of 5.4. This one is in the 26th percentile – i.e., 26% 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 317,177 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 37th percentile – i.e., 37% of its contemporaries scored the same or lower than it.
We're also able to compare this research output to 48 others from the same source and published within six weeks on either side of this one. This one is in the 22nd percentile – i.e., 22% of its contemporaries scored the same or lower than it.