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VNTR analysis of selected outbreaks of Burkholderia pseudomallei in Australia

Overview of attention for article published in Infection, Genetics & Evolution, July 2007
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Citations

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Readers on

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24 Mendeley
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Title
VNTR analysis of selected outbreaks of Burkholderia pseudomallei in Australia
Published in
Infection, Genetics & Evolution, July 2007
DOI 10.1016/j.meegid.2006.12.002
Pubmed ID
Authors

Talima Pearson, Jana M. U’Ren, James M. Schupp, Gerard J. Allan, Peter G. Foster, Mark J. Mayo, Daniel Gal, Jodie Low Choy, Rebecca Leadem Daugherty, Sergey Kachur, Christine L. Clark Friedman, Benjamin Leadem, Shalamar Georgia, Heidie Hornstra, Amy J. Vogler, David M. Wagner, Paul Keim, Bart J. Currie

Abstract

Molecular typing methods for Burkholderia pseudomallei have been successful at assigning isolates into epidemiologically related groups, but have not been able to detect differences and define evolutionary patterns within groups. Our variable number tandem repeat (VNTR) analysis of a set of 121 Australian B. pseudomallei isolates, 104 of which were associated with nine epidemiological groups, provides fine scale differentiation even among very closely related isolates. We used a Bayesian model based upon mutation accumulation patterns to define the close phylogenetic relationships within these epidemiological groups. Our results reveal that genetic diversity can exist within a very small geographic area, and that low levels of diversity can exist even within a single infection. These methods provide the ability to generate robust evolutionary hypotheses that enable tracking of B. pseudomallei in forensic and epidemiological outbreaks at fine phylogenetic scales.

Mendeley readers

The data shown below were compiled from readership statistics for 24 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Malaysia 1 4%
Hungary 1 4%
Netherlands 1 4%
Unknown 21 88%

Demographic breakdown

Readers by professional status Count As %
Researcher 6 25%
Student > Master 5 21%
Unspecified 3 13%
Student > Ph. D. Student 3 13%
Other 2 8%
Other 5 21%
Readers by discipline Count As %
Agricultural and Biological Sciences 9 38%
Biochemistry, Genetics and Molecular Biology 5 21%
Unspecified 3 13%
Medicine and Dentistry 2 8%
Immunology and Microbiology 1 4%
Other 4 17%

Attention Score in Context

This research output has an Altmetric Attention Score of 1. 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 06 March 2007.
All research outputs
#7,686,722
of 12,302,784 outputs
Outputs from Infection, Genetics & Evolution
#820
of 1,845 outputs
Outputs of similar age
#46,302
of 74,465 outputs
Outputs of similar age from Infection, Genetics & Evolution
#7
of 9 outputs
Altmetric has tracked 12,302,784 research outputs across all sources so far. This one is in the 23rd percentile – i.e., 23% of other outputs scored the same or lower than it.
So far Altmetric has tracked 1,845 research outputs from this source. They receive a mean Attention Score of 2.4. This one is in the 47th percentile – i.e., 47% 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 74,465 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 24th percentile – i.e., 24% of its contemporaries scored the same or lower than it.
We're also able to compare this research output to 9 others from the same source and published within six weeks on either side of this one. This one has scored higher than 2 of them.