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Live Genomics for Pathogen Monitoring in Public Health

Overview of attention for article published in Pathogens, January 2014
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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 (92nd percentile)
  • High Attention Score compared to outputs of the same age and source (92nd percentile)

Mentioned by

blogs
1 blog
twitter
15 X users
facebook
1 Facebook page
googleplus
1 Google+ user

Citations

dimensions_citation
4 Dimensions

Readers on

mendeley
64 Mendeley
citeulike
1 CiteULike
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Title
Live Genomics for Pathogen Monitoring in Public Health
Published in
Pathogens, January 2014
DOI 10.3390/pathogens3010093
Pubmed ID
Authors

Giuseppe D’Auria, Maria Victoria Schneider, Andrés Moya

Abstract

Whole genome analysis based on next generation sequencing (NGS) now represents an affordable framework in public health systems. Robust analytical pipelines of genomic data provides in short laps of time (hours) information about taxonomy, comparative genomics (pan-genome) and single polymorphisms profiles. Pathogenic organisms of interest can be tracked at the genomic level, allowing monitoring at one-time several variables including: epidemiology, pathogenicity, resistance to antibiotics, virulence, persistence factors, mobile elements and adaptation features. Such information can be obtained not only at large spectra, but also at the "local" level, such as in the event of a recurrent or emergency outbreak. This paper reviews the state of the art in infection diagnostics in the context of modern NGS methodologies. We describe how actuation protocols in a public health environment will benefit from a "streaming approach" (pipeline). Such pipeline would NGS data quality assessment, data mining for comparative analysis, searching differential genetic features, such as virulence, resistance persistence factors and mutation profiles (SNPs and InDels) and formatted "comprehensible" results. Such analytical protocols will enable a quick response to the needs of locally circumscribed outbreaks, providing information on the causes of resistance and genetic tracking elements for rapid detection, and monitoring actuations for present and future occurrences.

X Demographics

X Demographics

The data shown below were collected from the profiles of 15 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 64 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
United States 3 5%
Australia 2 3%
Brazil 1 2%
Germany 1 2%
New Zealand 1 2%
United Kingdom 1 2%
Spain 1 2%
Argentina 1 2%
Unknown 53 83%

Demographic breakdown

Readers by professional status Count As %
Researcher 15 23%
Student > Ph. D. Student 12 19%
Professor 6 9%
Student > Master 5 8%
Other 4 6%
Other 13 20%
Unknown 9 14%
Readers by discipline Count As %
Agricultural and Biological Sciences 27 42%
Biochemistry, Genetics and Molecular Biology 7 11%
Medicine and Dentistry 6 9%
Computer Science 3 5%
Engineering 2 3%
Other 5 8%
Unknown 14 22%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 17. 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 09 December 2014.
All research outputs
#2,009,034
of 24,336,902 outputs
Outputs from Pathogens
#180
of 4,493 outputs
Outputs of similar age
#23,628
of 315,454 outputs
Outputs of similar age from Pathogens
#2
of 13 outputs
Altmetric has tracked 24,336,902 research outputs across all sources so far. Compared to these this one has done particularly well and is in the 91st percentile: it's in the top 10% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 4,493 research outputs from this source. They typically receive a little more attention than average, with a mean Attention Score of 6.7. This one has done particularly well, scoring higher than 96% 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 315,454 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 92% of its contemporaries.
We're also able to compare this research output to 13 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 92% of its contemporaries.