Abstract
Single nucleotide polymorphisms (SNPs) are the commonest genetic variant in the human genome and have been associated with inter-individual differences in drug response. Finding the causative SNPs underlying variations in drug response has been a cornerstone of personalized medicine. However, as there are over 19 million SNPs, the task of finding causative SNPs underlying differences in drug response using in vitro and in vivo methods can be intimidating.
SNP related web resources can be invaluable in the search for SNPs relevant to drug response phenotypes as they represent relatively cheaper yet efficient ways of prioritizing relevant SNPs for further study. These resources serve as repositories of SNP information or contain in silico tools that can predict the functionality of a SNP. More sophisticated resources integrate the information repository function with the predictive function to create a one stop SNP resource for researchers. SNP related web resources can also aid researchers in planning and analyzing different types of genetic association studies by aiding in selecting SNPs for genotyping in these studies.
The focus of this mini review is to outline the SNP related web resources that are available to researchers and how these resources may aid researchers studying SNP-drug response phenotype associations.
Through efficient utilization of SNP related web resources, researchers will hopefully be able accelerate the pace of SNP related research in pharmacogenomics by identifying high risk SNP variants contributing to drug response as well as developing novel therapeutic targets based on understanding how SNPs alter drug response pathways.
Keywords: Candidate gene study, drug response, genome wide study, single nucleotide polymorphisms, web based resources.
Current Drug Metabolism
Title:SNP Web Resources and Their Potential Applications in Personalized Medicine
Volume: 13 Issue: 7
Author(s): Jingbo Wang, Grace S.Y. Pang, Samuel S. Chong and Caroline G.L. Lee
Affiliation:
Keywords: Candidate gene study, drug response, genome wide study, single nucleotide polymorphisms, web based resources.
Abstract: Single nucleotide polymorphisms (SNPs) are the commonest genetic variant in the human genome and have been associated with inter-individual differences in drug response. Finding the causative SNPs underlying variations in drug response has been a cornerstone of personalized medicine. However, as there are over 19 million SNPs, the task of finding causative SNPs underlying differences in drug response using in vitro and in vivo methods can be intimidating.
SNP related web resources can be invaluable in the search for SNPs relevant to drug response phenotypes as they represent relatively cheaper yet efficient ways of prioritizing relevant SNPs for further study. These resources serve as repositories of SNP information or contain in silico tools that can predict the functionality of a SNP. More sophisticated resources integrate the information repository function with the predictive function to create a one stop SNP resource for researchers. SNP related web resources can also aid researchers in planning and analyzing different types of genetic association studies by aiding in selecting SNPs for genotyping in these studies.
The focus of this mini review is to outline the SNP related web resources that are available to researchers and how these resources may aid researchers studying SNP-drug response phenotype associations.
Through efficient utilization of SNP related web resources, researchers will hopefully be able accelerate the pace of SNP related research in pharmacogenomics by identifying high risk SNP variants contributing to drug response as well as developing novel therapeutic targets based on understanding how SNPs alter drug response pathways.
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Cite this article as:
Wang Jingbo, S.Y. Pang Grace, S. Chong Samuel and G.L. Lee Caroline, SNP Web Resources and Their Potential Applications in Personalized Medicine, Current Drug Metabolism 2012; 13 (7) . https://dx.doi.org/10.2174/138920012802138552
DOI https://dx.doi.org/10.2174/138920012802138552 |
Print ISSN 1389-2002 |
Publisher Name Bentham Science Publisher |
Online ISSN 1875-5453 |
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