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Prediction of SNP interactions in complex diseases with mutual information and boolean algebra

  • Journal of The Korea Society of Computer and Information
  • Abbr : JKSCI
  • 2010, 15(11), pp.215-224
  • Publisher : The Korean Society Of Computer And Information
  • Research Area : Engineering > Computer Science

임상섭 1 Kyubum Wee 1

1아주대학교

Accredited

ABSTRACT

Most chronic diseases are complex diseases which are caused by interactions of several genes. Studies on finding SNPs and gene-gene interactions involved in the development of complex diseases can contribute to prevention and treatment of the diseases. Previous studies mostly concentrate on finding only the set of SNPs involved. In this study we suggest a way to see how these SNPs interact using boolean expressions. The proposed method consists of two stages. In the first stage we find the set of SNPs involved in the development of diseases using mutual information based on entropy. In the second stage we find the highest accuracy boolean expression that consists of the SNP set obtained in the first stage. We experimented with clinical data to demonstrate the effectiveness of the proposed method. We also compared the differences between our method and the previous results on the SNP associations studies.

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