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Minimum InDel pattern analysis of the Zika virus

Overview of attention for article published in BMC Genomics, July 2018
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Title
Minimum InDel pattern analysis of the Zika virus
Published in
BMC Genomics, July 2018
DOI 10.1186/s12864-018-4935-z
Pubmed ID
Authors

Hyeji Lee, Mai Phuong Nguyen, Yunhee Choi, Yong-Hak Kim

Abstract

The Zika virus (ZIKV) can cause microcephaly and congenital abnormalities in the foetus. Recent studies have provided insights into the evolution of ZIKV from the current and previous outbreaks, but the types have not been determined. We analysed the insertions and deletions (InDels) in 212 ZIKV polyproteins and 5 Dengue virus (DENV) reference sequences. Spearman correlation tests for the minimum InDel (minInDel) patterns were used to assess the type of polyprotein. Using the minInDel frequencies calculated from polyproteins with 11 elements, likelihood estimation was conducted to correct the evolutionary distance. The minInDel-corrected tree topology clearly distinguished between the ZIKV types (I and II) with a unique minInDel character in the E protein. From the 10-year average genetic distance, the African and Asian lineages of ZIKV-II were estimated to have occurred ~ 270 years ago, which is unlikely for ZIKV-I. The minInDel pattern analysis showed that the minInDel in the E protein is targetable for the rapid detection and determination of the virus types.

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Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 25 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 25 100%

Demographic breakdown

Readers by professional status Count As %
Student > Master 7 28%
Researcher 6 24%
Student > Doctoral Student 3 12%
Student > Bachelor 2 8%
Professor 1 4%
Other 2 8%
Unknown 4 16%
Readers by discipline Count As %
Medicine and Dentistry 5 20%
Agricultural and Biological Sciences 4 16%
Biochemistry, Genetics and Molecular Biology 3 12%
Arts and Humanities 1 4%
Mathematics 1 4%
Other 2 8%
Unknown 9 36%
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 02 April 2021.
All research outputs
#13,385,033
of 23,096,849 outputs
Outputs from BMC Genomics
#4,800
of 10,705 outputs
Outputs of similar age
#164,090
of 327,048 outputs
Outputs of similar age from BMC Genomics
#79
of 203 outputs
Altmetric has tracked 23,096,849 research outputs across all sources so far. This one is in the 41st percentile – i.e., 41% of other outputs scored the same or lower than it.
So far Altmetric has tracked 10,705 research outputs from this source. They receive a mean Attention Score of 4.7. This one has gotten more attention than average, scoring higher than 53% 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 327,048 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 48th percentile – i.e., 48% of its contemporaries scored the same or lower than it.
We're also able to compare this research output to 203 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 59% of its contemporaries.