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A universal protocol to generate consensus level genome sequences for foot-and-mouth disease virus and other positive-sense polyadenylated RNA viruses using the Illumina MiSeq

Overview of attention for article published in BMC Genomics, September 2014
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Title
A universal protocol to generate consensus level genome sequences for foot-and-mouth disease virus and other positive-sense polyadenylated RNA viruses using the Illumina MiSeq
Published in
BMC Genomics, September 2014
DOI 10.1186/1471-2164-15-828
Pubmed ID
Authors

Grace Logan, Graham L Freimanis, David J King, Begoña Valdazo-González, Katarzyna Bachanek-Bankowska, Nicholas D Sanderson, Nick J Knowles, Donald P King, Eleanor M Cottam

Abstract

Next-Generation Sequencing (NGS) is revolutionizing molecular epidemiology by providing new approaches to undertake whole genome sequencing (WGS) in diagnostic settings for a variety of human and veterinary pathogens. Previous sequencing protocols have been subject to biases such as those encountered during PCR amplification and cell culture, or are restricted by the need for large quantities of starting material. We describe here a simple and robust methodology for the generation of whole genome sequences on the Illumina MiSeq. This protocol is specific for foot-and-mouth disease virus (FMDV) or other polyadenylated RNA viruses and circumvents both the use of PCR and the requirement for large amounts of initial template.

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X Demographics

The data shown below were collected from the profiles of 3 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 110 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
France 1 <1%
Brazil 1 <1%
Sweden 1 <1%
United Kingdom 1 <1%
Belgium 1 <1%
United States 1 <1%
Unknown 104 95%

Demographic breakdown

Readers by professional status Count As %
Researcher 30 27%
Student > Ph. D. Student 21 19%
Student > Master 17 15%
Student > Doctoral Student 6 5%
Professor 5 5%
Other 15 14%
Unknown 16 15%
Readers by discipline Count As %
Agricultural and Biological Sciences 43 39%
Biochemistry, Genetics and Molecular Biology 16 15%
Veterinary Science and Veterinary Medicine 14 13%
Immunology and Microbiology 6 5%
Computer Science 2 2%
Other 10 9%
Unknown 19 17%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 1. 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 30 September 2014.
All research outputs
#15,306,466
of 22,764,165 outputs
Outputs from BMC Genomics
#6,678
of 10,638 outputs
Outputs of similar age
#146,728
of 252,706 outputs
Outputs of similar age from BMC Genomics
#117
of 200 outputs
Altmetric has tracked 22,764,165 research outputs across all sources so far. This one is in the 22nd percentile – i.e., 22% of other outputs scored the same or lower than it.
So far Altmetric has tracked 10,638 research outputs from this source. They receive a mean Attention Score of 4.7. This one is in the 29th percentile – i.e., 29% 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 252,706 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 32nd percentile – i.e., 32% of its contemporaries scored the same or lower than it.
We're also able to compare this research output to 200 others from the same source and published within six weeks on either side of this one. This one is in the 36th percentile – i.e., 36% of its contemporaries scored the same or lower than it.