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About this Attention Score

  • Above-average Attention Score compared to outputs of the same age (52nd percentile)
  • Above-average Attention Score compared to outputs of the same age and source (53rd percentile)

Mentioned by

patent
1 patent

Readers on

mendeley
22 Mendeley
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Article details
Title
An NS5A single optimized method to determine genotype, subtype and resistance profiles of Hepatitis C strains
Published in
PLOS ONE, July 2017
DOI 10.1371/journal.pone.0179562
Pubmed ID
Authors
Abstract

The objective was to develop a method of HCV genome sequencing that allowed simultaneous genotyping and NS5A inhibitor resistance profiling. In order to validate the use of a unique RT-PCR for genotypes 1-5, 142 plasma samples from patients infected with HCV were analysed. The NS4B-NS5A partial region was successfully amplified and sequenced in all samples. In parallel, partial NS3 sequences were analyzed obtained for genotyping. Phylogenetic analysis showed concordance of genotypes and subtypes with a bootstrap >95% for each type cluster. NS5A resistance mutations were analyzed using the Geno2pheno [hcv] v0.92 tool and compared to the list of known Resistant Associated Substitutions recently published. In conclusion, this tool allows determination of HCV genotypes, subtypes and identification of NS5A resistance mutations. This single method can be used to detect pre-existing resistance mutations in NS5A before treatment and to check the emergence of resistant viruses while undergoing treatment in major HCV genotypes (G1-5) in the EU and the US.

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Mendeley demographics

Mendeley demographics

The data shown below were compiled from readership statistics for 22 Mendeley readers of this research output. Click here to see the associated Mendeley record.
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Geographical breakdown

Geographical breakdown
Country Count As %
Unknown 22 100%

Demographic breakdown

Readers by professional status
Readers by professional status Count As %
Student > Ph. D. Student 5 23%
Other 4 18%
Researcher 4 18%
Student > Bachelor 2 9%
Professor 2 9%
Other 1 5%
Unknown 4 18%
Readers by discipline
Readers by discipline Count As %
Biochemistry, Genetics and Molecular Biology 7 32%
Immunology and Microbiology 5 23%
Medicine and Dentistry 2 9%
Chemical Engineering 1 5%
Computer Science 1 5%
Other 1 5%
Unknown 5 23%
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 19 March 2020.
All research outputs
#8,951,298
of 26,397,269 outputs
Outputs from PLOS ONE
#122,490
of 229,745 outputs
Outputs of similar age
#128,222
of 330,518 outputs
Outputs of similar age from PLOS ONE
#1,741
of 4,027 outputs
Altmetric has tracked 26,397,269 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 229,745 research outputs from this source. They typically receive a lot more attention than average, with a mean Attention Score of 16.0. This one is in the 42nd percentile – i.e., 42% 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 330,518 tracked outputs that were published within six weeks on either side of this one in any source. This one has gotten more attention than average, scoring higher than 52% of its contemporaries.
We're also able to compare this research output to 4,027 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 53% of its contemporaries.