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Short read sequence typing (SRST): multi-locus sequence types from short reads

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

  • In the top 5% of all research outputs scored by Altmetric
  • High Attention Score compared to outputs of the same age (96th percentile)
  • High Attention Score compared to outputs of the same age and source (97th percentile)

Mentioned by

blogs
3 blogs
twitter
7 X users
patent
2 patents
wikipedia
2 Wikipedia pages

Citations

dimensions_citation
83 Dimensions

Readers on

mendeley
159 Mendeley
citeulike
2 CiteULike
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Title
Short read sequence typing (SRST): multi-locus sequence types from short reads
Published in
BMC Genomics, July 2012
DOI 10.1186/1471-2164-13-338
Pubmed ID
Authors

Michael Inouye, Thomas C Conway, Justin Zobel, Kathryn E Holt

Abstract

Multi-locus sequence typing (MLST) has become the gold standard for population analyses of bacterial pathogens. This method focuses on the sequences of a small number of loci (usually seven) to divide the population and is simple, robust and facilitates comparison of results between laboratories and over time. Over the last decade, researchers and population health specialists have invested substantial effort in building up public MLST databases for nearly 100 different bacterial species, and these databases contain a wealth of important information linked to MLST sequence types such as time and place of isolation, host or niche, serotype and even clinical or drug resistance profiles. Recent advances in sequencing technology mean it is increasingly feasible to perform bacterial population analysis at the whole genome level. This offers massive gains in resolving power and genetic profiling compared to MLST, and will eventually replace MLST for bacterial typing and population analysis. However given the wealth of data currently available in MLST databases, it is crucial to maintain backwards compatibility with MLST schemes so that new genome analyses can be understood in their proper historical context.

X Demographics

X Demographics

The data shown below were collected from the profiles of 7 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 159 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
United States 6 4%
Australia 3 2%
Spain 3 2%
Denmark 2 1%
United Kingdom 1 <1%
Canada 1 <1%
Sweden 1 <1%
Belgium 1 <1%
Germany 1 <1%
Other 2 1%
Unknown 138 87%

Demographic breakdown

Readers by professional status Count As %
Researcher 47 30%
Student > Ph. D. Student 46 29%
Student > Master 16 10%
Professor > Associate Professor 8 5%
Student > Bachelor 7 4%
Other 22 14%
Unknown 13 8%
Readers by discipline Count As %
Agricultural and Biological Sciences 83 52%
Medicine and Dentistry 15 9%
Biochemistry, Genetics and Molecular Biology 14 9%
Immunology and Microbiology 6 4%
Business, Management and Accounting 4 3%
Other 15 9%
Unknown 22 14%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 35. 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 21 January 2021.
All research outputs
#1,159,040
of 25,711,518 outputs
Outputs from BMC Genomics
#163
of 11,306 outputs
Outputs of similar age
#6,284
of 179,453 outputs
Outputs of similar age from BMC Genomics
#4
of 170 outputs
Altmetric has tracked 25,711,518 research outputs across all sources so far. Compared to these this one has done particularly well and is in the 95th percentile: it's in the top 5% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 11,306 research outputs from this source. They receive a mean Attention Score of 4.8. This one has done particularly well, scoring higher than 98% 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 179,453 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 96% of its contemporaries.
We're also able to compare this research output to 170 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 97% of its contemporaries.