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Finding Relevant SNP Sets and Predicting Risk to Disease Using Simulated Annealing

  • Journal of Knowledge Information Technology and Systems
  • Abbr : JKITS
  • 2010, 5(3), pp.99-106
  • Publisher : Korea Knowledge Information Technology Society
  • Research Area : Interdisciplinary Studies > Interdisciplinary Research
  • Published : June 30, 2010

김동회 1 엄상용 1 Jin Kim 1

1한림대학교

Candidate

ABSTRACT

We applied simulated annealing algorithm and decision tree to find SNP sets relevant to a disease and predict the disease risk. For time complexity problem of SA, we construct an initial SNP set by fast heuristic algorithm and applied efficient transition rules to obtain new SNP sets. The experiment results show that we can obtain new SNP sets with the improved prediction performance compared to others by traditional feature selection algorithms.

Citation status

* References for papers published after 2023 are currently being built.

This paper was written with support from the National Research Foundation of Korea.