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Metagenomic identification of viral pathogens

Overview of attention for article published in Trends in Biotechnology, February 2013
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Mentioned by

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7 X users

Citations

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73 Dimensions

Readers on

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277 Mendeley
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Title
Metagenomic identification of viral pathogens
Published in
Trends in Biotechnology, February 2013
DOI 10.1016/j.tibtech.2013.01.016
Pubmed ID
Authors

Kyle Bibby

Abstract

The target-independent identification of viral pathogens using 'shotgun' metagenomic sequencing is an emerging approach with potentially wide applications in clinical diagnostics, public health monitoring, and viral discovery. In this approach, all viral nucleic acids present in a sample are sequenced in a random, shotgun manner. Pathogens are then identified without the prerequisite of searching for a specific viral pathogen. In this opinion article, I discuss the current state and future research directions for this emerging and disruptive technology. With further technical developments, viral metagenomics has the potential to be deployed as a powerful and widely adopted tool, transforming the way that viral disease is researched, monitored, and treated.

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 277 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
United States 6 2%
Brazil 5 2%
United Kingdom 3 1%
South Africa 2 <1%
Sweden 2 <1%
Portugal 1 <1%
Israel 1 <1%
Australia 1 <1%
Switzerland 1 <1%
Other 7 3%
Unknown 248 90%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 59 21%
Researcher 52 19%
Student > Master 38 14%
Student > Bachelor 36 13%
Professor > Associate Professor 15 5%
Other 45 16%
Unknown 32 12%
Readers by discipline Count As %
Agricultural and Biological Sciences 120 43%
Biochemistry, Genetics and Molecular Biology 37 13%
Immunology and Microbiology 18 6%
Medicine and Dentistry 15 5%
Environmental Science 11 4%
Other 32 12%
Unknown 44 16%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 3. 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 17 October 2020.
All research outputs
#8,535,472
of 25,374,917 outputs
Outputs from Trends in Biotechnology
#1,754
of 2,856 outputs
Outputs of similar age
#91,108
of 296,603 outputs
Outputs of similar age from Trends in Biotechnology
#20
of 29 outputs
Altmetric has tracked 25,374,917 research outputs across all sources so far. This one is in the 43rd percentile – i.e., 43% of other outputs scored the same or lower than it.
So far Altmetric has tracked 2,856 research outputs from this source. They typically receive more attention than average, with a mean Attention Score of 9.5. This one is in the 17th percentile – i.e., 17% of its peers scored the same or lower than it.
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 296,603 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 44th percentile – i.e., 44% of its contemporaries scored the same or lower than it.
We're also able to compare this research output to 29 others from the same source and published within six weeks on either side of this one. This one is in the 31st percentile – i.e., 31% of its contemporaries scored the same or lower than it.