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Metagenomics for pathogen detection in public health

Overview of attention for article published in Genome Medicine, September 2013
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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 (88th percentile)
  • Above-average Attention Score compared to outputs of the same age and source (63rd percentile)

Mentioned by

twitter
11 X users
patent
1 patent
facebook
1 Facebook page
wikipedia
2 Wikipedia pages

Citations

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208 Dimensions

Readers on

mendeley
538 Mendeley
citeulike
2 CiteULike
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Title
Metagenomics for pathogen detection in public health
Published in
Genome Medicine, September 2013
DOI 10.1186/gm485
Pubmed ID
Authors

Ruth R Miller, Vincent Montoya, Jennifer L Gardy, David M Patrick, Patrick Tang

Abstract

Traditional pathogen detection methods in public health infectious disease surveillance rely upon the identification of agents that are already known to be associated with a particular clinical syndrome. The emerging field of metagenomics has the potential to revolutionize pathogen detection in public health laboratories by allowing the simultaneous detection of all microorganisms in a clinical sample, without a priori knowledge of their identities, through the use of next-generation DNA sequencing. A single metagenomics analysis has the potential to detect rare and novel pathogens, and to uncover the role of dysbiotic microbiomes in infectious and chronic human disease. Making use of advances in sequencing platforms and bioinformatics tools, recent studies have shown that metagenomics can even determine the whole-genome sequences of pathogens, allowing inferences about antibiotic resistance, virulence, evolution and transmission to be made. We are entering an era in which more novel infectious diseases will be identified through metagenomics-based methods than through traditional laboratory methods. The impetus is now on public health laboratories to integrate metagenomics techniques into their diagnostic arsenals.

X Demographics

X Demographics

The data shown below were collected from the profiles of 11 X users who shared this research output. Click here to find out more about how the information was compiled.
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Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 538 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Brazil 5 <1%
United States 4 <1%
United Kingdom 2 <1%
Turkey 1 <1%
South Africa 1 <1%
Portugal 1 <1%
Spain 1 <1%
Sweden 1 <1%
Unknown 522 97%

Demographic breakdown

Readers by professional status Count As %
Researcher 109 20%
Student > Ph. D. Student 83 15%
Student > Master 68 13%
Student > Bachelor 68 13%
Student > Doctoral Student 30 6%
Other 84 16%
Unknown 96 18%
Readers by discipline Count As %
Agricultural and Biological Sciences 158 29%
Biochemistry, Genetics and Molecular Biology 101 19%
Medicine and Dentistry 42 8%
Immunology and Microbiology 31 6%
Veterinary Science and Veterinary Medicine 15 3%
Other 68 13%
Unknown 123 23%
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 20 December 2023.
All research outputs
#2,861,994
of 26,101,087 outputs
Outputs from Genome Medicine
#643
of 1,631 outputs
Outputs of similar age
#24,258
of 215,148 outputs
Outputs of similar age from Genome Medicine
#8
of 22 outputs
Altmetric has tracked 26,101,087 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 1,631 research outputs from this source. They typically receive a lot more attention than average, with a mean Attention Score of 26.5. This one has gotten more attention than average, scoring higher than 60% 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 215,148 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 88% of its contemporaries.
We're also able to compare this research output to 22 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 63% of its contemporaries.