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Updated: Jun 23, 2026

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Published on: December 9, 2015
Predicting potentially functional SNPs in drug-response genes
Grace S Y Pang1, Jingbo Wang, Zihua Wang
1Division of Medical Sciences, National Cancer Center, Level 6, Lab 5, 11 Hospital Drive, Singapore 169610, Singapore.
Identifying functional single nucleotide polymorphisms (SNPs) is crucial for understanding drug response variations. In silico methods offer an economical approach to filter these important SNPs for further experimental validation.
Area of Science:
- Genetics
- Pharmacogenomics
- Bioinformatics
Background:
- Single nucleotide polymorphisms (SNPs) significantly influence individual drug response.
- Over 14 million polymorphisms exist in the human genome, but not all are functional.
- Experimental validation of every SNP is impractical and costly.
Purpose of the Study:
- To address the challenge of identifying functional SNPs within the vast human genome.
- To present in silico methods as an economical and efficient approach for SNP filtering.
- To enable prioritization of SNPs for experimental drug-response studies.
Main Methods:
- Utilizing in silico (bioinformatic) approaches to analyze SNPs.
- Filtering potentially functional SNPs within drug-response genes.
- Prioritizing SNPs for subsequent experimental evaluation.
Main Results:
- In silico methods provide an economical and less labor-intensive way to identify functional SNPs.
- Bioinformatic analysis helps filter a large number of SNPs down to a manageable set.
- This approach allows for focused experimental validation of high-priority SNPs.
Conclusions:
- In silico methods are powerful tools for discovering functional SNPs relevant to drug response.
- Economical bioinformatic filtering accelerates the identification of SNPs impacting drug-response genes.
- This strategy aids researchers in prioritizing experimental studies and understanding SNP mechanisms.
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