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High resolution clustering of Salmonella enterica serovar Montevideo strains using a next-generation sequencing approach

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 (91st percentile)
  • High Attention Score compared to outputs of the same age and source (95th percentile)

Mentioned by

policy
3 policy sources
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2 X users
patent
1 patent

Citations

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131 Dimensions

Readers on

mendeley
133 Mendeley
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1 CiteULike
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Title
High resolution clustering of Salmonella enterica serovar Montevideo strains using a next-generation sequencing approach
Published in
BMC Genomics, January 2012
DOI 10.1186/1471-2164-13-32
Pubmed ID
Authors

Marc W Allard, Yan Luo, Errol Strain, Cong Li, Christine E Keys, Insook Son, Robert Stones, Steven M Musser, Eric W Brown

Abstract

Next-Generation Sequencing (NGS) is increasingly being used as a molecular epidemiologic tool for discerning ancestry and traceback of the most complicated, difficult to resolve bacterial pathogens. Making a linkage between possible food sources and clinical isolates requires distinguishing the suspected pathogen from an environmental background and placing the variation observed into the wider context of variation occurring within a serovar and among other closely related foodborne pathogens. Equally important is the need to validate these high resolution molecular tools for use in molecular epidemiologic traceback. Such efforts include the examination of strain cluster stability as well as the cumulative genetic effects of sub-culturing on these clusters. Numerous isolates of S. Montevideo were shot-gun sequenced including diverse lineage representatives as well as numerous replicate clones to determine how much variability is due to bias, sequencing error, and or the culturing of isolates. All new draft genomes were compared to 34 S. Montevideo isolates previously published during an NGS-based molecular epidemiological case study.

X Demographics

X Demographics

The data shown below were collected from the profiles of 2 X users 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 133 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
United States 3 2%
Brazil 3 2%
Sweden 2 2%
Denmark 2 2%
Uruguay 1 <1%
Australia 1 <1%
Unknown 121 91%

Demographic breakdown

Readers by professional status Count As %
Researcher 33 25%
Student > Ph. D. Student 30 23%
Student > Master 19 14%
Student > Doctoral Student 9 7%
Student > Bachelor 7 5%
Other 18 14%
Unknown 17 13%
Readers by discipline Count As %
Agricultural and Biological Sciences 70 53%
Biochemistry, Genetics and Molecular Biology 15 11%
Immunology and Microbiology 8 6%
Veterinary Science and Veterinary Medicine 6 5%
Computer Science 3 2%
Other 10 8%
Unknown 21 16%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 13. 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 23 October 2023.
All research outputs
#2,702,603
of 25,698,912 outputs
Outputs from BMC Genomics
#769
of 11,305 outputs
Outputs of similar age
#19,962
of 252,848 outputs
Outputs of similar age from BMC Genomics
#5
of 118 outputs
Altmetric has tracked 25,698,912 research outputs across all sources so far. Compared to these this one has done well and is in the 89th percentile: it's in the top 25% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 11,305 research outputs from this source. They receive a mean Attention Score of 4.8. This one has done particularly well, scoring higher than 93% 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 252,848 tracked outputs that were published within six weeks on either side of this one in any source. This one has done particularly well, scoring higher than 91% of its contemporaries.
We're also able to compare this research output to 118 others from the same source and published within six weeks on either side of this one. This one has done particularly well, scoring higher than 95% of its contemporaries.