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Pattern-recognition techniques with haplotype analysis in pharmacogenomics.

Eugene Lin1, Yuchi Hwang, Kung-Hao Liang

  • 1Vita Genomics, Inc., Floor 7, Number 6, Section 1, Jung-Shing Road, Wugu Shiang, Taipei, Taiwan. eugene.lin@vitagenomics.com

Pharmacogenomics
|December 26, 2006
PubMed
Summary
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Selecting candidate single nucleotide polymorphisms (SNPs) is crucial for pharmacogenomic association studies. This review explores haplotype analysis and pattern recognition to efficiently identify SNPs linked to drug efficacy and adverse reactions.

Area of Science:

  • Pharmacogenomics
  • Genetics
  • Computational Biology

Background:

  • Single nucleotide polymorphisms (SNPs) are key in clinical association studies for drug efficacy.
  • Testing all common SNPs (millions) is highly inefficient for association studies.

Purpose of the Study:

  • To review methods for systematic SNP selection in pharmacogenomics.
  • To explore haplotype analysis and pattern recognition for identifying candidate SNPs.
  • To assess techniques for evaluating gene-epistasis and SNP associations with drug response.

Main Methods:

  • Surveying linkage disequilibrium methods to identify tag SNPs.
  • Investigating pattern-recognition algorithms and statistical analyses for SNP-based efficacy assessment.
  • Studying pattern-recognition approaches for evaluating gene-SNP epistasis.

Related Experiment Videos

Main Results:

  • Haplotypes can serve as genetic markers correlated with drug efficacy.
  • Pattern recognition and statistical analyses can assess drug efficacy based on multiple factors.
  • Epistasis among genes and SNPs can be evaluated using pattern-recognition approaches.

Conclusions:

  • Efficient SNP selection is vital for pharmacogenomic association studies.
  • Haplotype and pattern-recognition techniques offer systematic approaches to identify relevant SNPs.
  • These methods can aid in discovering genes/SNPs influencing therapeutic drug responses and adverse reactions.