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Estimating variation within the genes and inferring the phylogeny of 186 sequenced diverse Escherichia coli genomes

Overview of attention for article published in BMC Genomics, January 2012
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About this Attention Score

  • In the top 25% of all research outputs scored by Altmetric
  • High Attention Score compared to outputs of the same age (86th percentile)

Mentioned by

twitter
15 tweeters

Citations

dimensions_citation
109 Dimensions

Readers on

mendeley
225 Mendeley
citeulike
2 CiteULike
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Title
Estimating variation within the genes and inferring the phylogeny of 186 sequenced diverse Escherichia coli genomes
Published in
BMC Genomics, January 2012
DOI 10.1186/1471-2164-13-577
Pubmed ID
Authors

Rolf S Kaas, Carsten Friis, David W Ussery, Frank M Aarestrup

Abstract

Escherichia coli exists in commensal and pathogenic forms. By measuring the variation of individual genes across more than a hundred sequenced genomes, gene variation can be studied in detail, including the number of mutations found for any given gene. This knowledge will be useful for creating better phylogenies, for determination of molecular clocks and for improved typing techniques.

Twitter Demographics

The data shown below were collected from the profiles of 15 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 225 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
United States 6 3%
Denmark 6 3%
Sweden 2 <1%
South Africa 1 <1%
Australia 1 <1%
France 1 <1%
Ireland 1 <1%
India 1 <1%
Czechia 1 <1%
Other 5 2%
Unknown 200 89%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 70 31%
Researcher 48 21%
Student > Master 27 12%
Student > Bachelor 18 8%
Student > Doctoral Student 16 7%
Other 32 14%
Unknown 14 6%
Readers by discipline Count As %
Agricultural and Biological Sciences 108 48%
Biochemistry, Genetics and Molecular Biology 42 19%
Immunology and Microbiology 15 7%
Medicine and Dentistry 14 6%
Computer Science 8 4%
Other 18 8%
Unknown 20 9%

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 14 April 2018.
All research outputs
#1,806,068
of 12,880,184 outputs
Outputs from BMC Genomics
#969
of 7,563 outputs
Outputs of similar age
#19,650
of 145,318 outputs
Outputs of similar age from BMC Genomics
#1
of 4 outputs
Altmetric has tracked 12,880,184 research outputs across all sources so far. Compared to these this one has done well and is in the 85th percentile: it's in the top 25% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 7,563 research outputs from this source. They receive a mean Attention Score of 4.3. This one has done well, scoring higher than 87% 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 145,318 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 86% of its contemporaries.
We're also able to compare this research output to 4 others from the same source and published within six weeks on either side of this one. This one has scored higher than all of them