↓ Skip to main content

Precise genotyping and recombination detection of Enterovirus

Overview of attention for article published in BMC Genomics, December 2015
Altmetric Badge

Mentioned by

twitter
1 X user

Citations

dimensions_citation
10 Dimensions

Readers on

mendeley
27 Mendeley
You are seeing a free-to-access but limited selection of the activity Altmetric has collected about this research output. Click here to find out more.
Title
Precise genotyping and recombination detection of Enterovirus
Published in
BMC Genomics, December 2015
DOI 10.1186/1471-2164-16-s12-s8
Pubmed ID
Authors

Chieh-Hua Lin, Yu-Bin Wang, Shu-Hwa Chen, Chao Agnes Hsiung, Chung-Yen Lin

Abstract

Enteroviruses (EV) with different genotypes cause diverse infectious diseases in humans and mammals. A correct EV typing result is crucial for effective medical treatment and disease control; however, the emergence of novel viral strains has impaired the performance of available diagnostic tools. Here, we present a web-based tool, named EVIDENCE (EnteroVirus In DEep conception, http://symbiont.iis.sinica.edu.tw/evidence), for EV genotyping and recombination detection. We introduce the idea of using mixed-ranking scores to evaluate the fitness of prototypes based on relatedness and on the genome regions of interest. Using phylogenetic methods, the most possible genotype is determined based on the closest neighbor among the selected references. To detect possible recombination events, EVIDENCE calculates the sequence distance and phylogenetic relationship among sequences of all sliding windows scanning over the whole genome. Detected recombination events are plotted in an interactive figure for viewing of fine details. In addition, all EV sequences available in GenBank were collected and revised using the latest classification and nomenclature of EV in EVIDENCE. These sequences are built into the database and are retrieved in an indexed catalog, or can be searched for by keywords or by sequence similarity. EVIDENCE is the first web-based tool containing pipelines for genotyping and recombination detection, with updated, built-in, and complete reference sequences to improve sensitivity and specificity. The use of EVIDENCE can accelerate genotype identification, aiding clinical diagnosis and enhancing our understanding of EV evolution.

X Demographics

X Demographics

The data shown below were collected from the profile of 1 X user 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 27 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 27 100%

Demographic breakdown

Readers by professional status Count As %
Student > Bachelor 4 15%
Student > Master 3 11%
Researcher 3 11%
Other 2 7%
Student > Ph. D. Student 2 7%
Other 5 19%
Unknown 8 30%
Readers by discipline Count As %
Biochemistry, Genetics and Molecular Biology 5 19%
Agricultural and Biological Sciences 4 15%
Computer Science 3 11%
Engineering 2 7%
Veterinary Science and Veterinary Medicine 1 4%
Other 3 11%
Unknown 9 33%
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 19 December 2015.
All research outputs
#20,298,249
of 22,835,198 outputs
Outputs from BMC Genomics
#9,281
of 10,655 outputs
Outputs of similar age
#326,292
of 389,036 outputs
Outputs of similar age from BMC Genomics
#325
of 342 outputs
Altmetric has tracked 22,835,198 research outputs across all sources so far. This one is in the 1st percentile – i.e., 1% of other outputs scored the same or lower than it.
So far Altmetric has tracked 10,655 research outputs from this source. They receive a mean Attention Score of 4.7. This one is in the 1st percentile – i.e., 1% 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 389,036 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 1st percentile – i.e., 1% of its contemporaries scored the same or lower than it.
We're also able to compare this research output to 342 others from the same source and published within six weeks on either side of this one. This one is in the 1st percentile – i.e., 1% of its contemporaries scored the same or lower than it.