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Codon usage bias and the evolution of influenza A viruses. Codon Usage Biases of Influenza Virus

Overview of attention for article published in BMC Evolutionary Biology, January 2010
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About this Attention Score

  • In the top 25% of all research outputs scored by Altmetric
  • Good Attention Score compared to outputs of the same age (78th percentile)
  • Above-average Attention Score compared to outputs of the same age and source (64th percentile)

Mentioned by

twitter
8 tweeters
patent
1 patent
facebook
1 Facebook page

Citations

dimensions_citation
149 Dimensions

Readers on

mendeley
164 Mendeley
citeulike
1 CiteULike
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Title
Codon usage bias and the evolution of influenza A viruses. Codon Usage Biases of Influenza Virus
Published in
BMC Evolutionary Biology, January 2010
DOI 10.1186/1471-2148-10-253
Pubmed ID
Authors

Emily HM Wong, David K Smith, Raul Rabadan, Malik Peiris, Leo LM Poon

Twitter Demographics

The data shown below were collected from the profiles of 8 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 164 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Germany 3 2%
United States 3 2%
United Kingdom 2 1%
Netherlands 2 1%
Argentina 1 <1%
Denmark 1 <1%
Brazil 1 <1%
Unknown 151 92%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 48 29%
Student > Master 24 15%
Researcher 22 13%
Student > Bachelor 17 10%
Student > Doctoral Student 10 6%
Other 29 18%
Unknown 14 9%
Readers by discipline Count As %
Agricultural and Biological Sciences 79 48%
Biochemistry, Genetics and Molecular Biology 30 18%
Immunology and Microbiology 6 4%
Medicine and Dentistry 6 4%
Computer Science 4 2%
Other 17 10%
Unknown 22 13%

Attention Score in Context

This research output has an Altmetric Attention Score of 9. 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 January 2020.
All research outputs
#2,387,326
of 15,508,924 outputs
Outputs from BMC Evolutionary Biology
#747
of 2,698 outputs
Outputs of similar age
#83,629
of 383,934 outputs
Outputs of similar age from BMC Evolutionary Biology
#74
of 206 outputs
Altmetric has tracked 15,508,924 research outputs across all sources so far. Compared to these this one has done well and is in the 84th percentile: it's in the top 25% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 2,698 research outputs from this source. They typically receive a lot more attention than average, with a mean Attention Score of 10.6. This one has gotten more attention than average, scoring higher than 72% 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 383,934 tracked outputs that were published within six weeks on either side of this one in any source. This one has done well, scoring higher than 78% of its contemporaries.
We're also able to compare this research output to 206 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 64% of its contemporaries.