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The mutation rate of mycobacterial repetitive unit loci in strains of M. tuberculosisfrom cynomolgus macaque infection

Overview of attention for article published in BMC Genomics, March 2013
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  • Good Attention Score compared to outputs of the same age (71st percentile)
  • Good Attention Score compared to outputs of the same age and source (70th percentile)

Mentioned by

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1 X user
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2 patents

Citations

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22 Dimensions

Readers on

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64 Mendeley
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Title
The mutation rate of mycobacterial repetitive unit loci in strains of M. tuberculosisfrom cynomolgus macaque infection
Published in
BMC Genomics, March 2013
DOI 10.1186/1471-2164-14-145
Pubmed ID
Authors

Mark N Ragheb, Christopher B Ford, Michael R Chase, Philana Ling Lin, JoAnne L Flynn, Sarah M Fortune

Abstract

Mycobacterial interspersed repetitive units (MIRUs) are minisatellites within the Mycobacterium tuberculosis (Mtb) genome. Copy number variation (CNV) in MIRU loci is used for epidemiological typing, making the rate of variation important for tracking the transmission of Mtb strains. In this study, we developed and assessed a whole-genome sequencing (WGS) approach to detect MIRU CNV in Mtb. We applied this methodology to a panel of Mtb strains isolated from the macaque model of tuberculosis (TB), the animal model that best mimics human disease. From these data, we have estimated the rate of MIRU variation in the host environment, providing a benchmark rate for future epidemiologic work.

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X Demographics

The data shown below were collected from the profile of 1 X user who shared this research output. Click here to find out more about how the information was compiled.
Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 64 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
United Kingdom 1 2%
Unknown 63 98%

Demographic breakdown

Readers by professional status Count As %
Researcher 18 28%
Student > Ph. D. Student 13 20%
Student > Master 8 13%
Student > Doctoral Student 5 8%
Professor 4 6%
Other 7 11%
Unknown 9 14%
Readers by discipline Count As %
Agricultural and Biological Sciences 22 34%
Biochemistry, Genetics and Molecular Biology 8 13%
Immunology and Microbiology 7 11%
Medicine and Dentistry 5 8%
Mathematics 3 5%
Other 7 11%
Unknown 12 19%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 4. 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 11 October 2023.
All research outputs
#6,389,271
of 22,701,287 outputs
Outputs from BMC Genomics
#2,869
of 10,622 outputs
Outputs of similar age
#53,550
of 194,741 outputs
Outputs of similar age from BMC Genomics
#39
of 132 outputs
Altmetric has tracked 22,701,287 research outputs across all sources so far. This one has received more attention than most of these and is in the 70th percentile.
So far Altmetric has tracked 10,622 research outputs from this source. They receive a mean Attention Score of 4.7. This one has gotten more attention than average, scoring higher than 71% 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 194,741 tracked outputs that were published within six weeks on either side of this one in any source. This one has gotten more attention than average, scoring higher than 71% of its contemporaries.
We're also able to compare this research output to 132 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 70% of its contemporaries.