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Genetic polymorphisms of pharmacogenomic VIP variants in the Mongol of Northwestern China

Overview of attention for article published in BMC Genomic Data, May 2016
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Title
Genetic polymorphisms of pharmacogenomic VIP variants in the Mongol of Northwestern China
Published in
BMC Genomic Data, May 2016
DOI 10.1186/s12863-016-0379-0
Pubmed ID
Authors

Tianbo Jin, Xugang Shi, Li Wang, Huijuan Wang, Tian Feng, Longli Kang

Abstract

Within a population, the differences of pharmacogenomic variant frequencies may produce diversities in drug efficacy, safety, and the risk associated with adverse drug reactions. With the development of pharmacogenomics, widespread genetic research on drug metabolism has been conducted on major populations, but less is known about minorities. In this study, we recruited 100 unrelated, healthy Mongol adults from Xinjiang and genotyped 85 VIP variants from the PharmGKB database. We compared our data with eleven populations listed in 1000 genomes project and HapMap database. We used χ(2) tests to identify significantly different loci between these populations. We downloaded SNP allele frequencies from the ALlele FREquency Database to observe the global genetic variation distribution for these specific loci. And then we used Structure software to perform the genetic structure analysis of 12 populations. Our results demonstrated that different polymorphic allele frequencies exist between different nationalities,and indicated Mongol is most similar to Chinese populations, followed by JPT. This information on the Mongol population complements the existing pharmacogenomic data and provides a theoretical basis for screening and therapy in the different ethnic groups within Xinjiang.

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Mendeley readers

The data shown below were compiled from readership statistics for 8 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 8 100%

Demographic breakdown

Readers by professional status Count As %
Researcher 2 25%
Student > Master 2 25%
Student > Postgraduate 1 13%
Professor > Associate Professor 1 13%
Unknown 2 25%
Readers by discipline Count As %
Pharmacology, Toxicology and Pharmaceutical Science 2 25%
Biochemistry, Genetics and Molecular Biology 2 25%
Agricultural and Biological Sciences 1 13%
Unknown 3 38%
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 28 May 2016.
All research outputs
#22,758,309
of 25,373,627 outputs
Outputs from BMC Genomic Data
#1,008
of 1,204 outputs
Outputs of similar age
#308,461
of 352,953 outputs
Outputs of similar age from BMC Genomic Data
#35
of 45 outputs
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