Genomics & Informatics

Korea Genome Organization (한국유전체학회)
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Implementation of a Particle Swarm Optimization-based Classification Algorithm for Analyzing DNA Chip Data

  • Han, Xiaoyue (Department of Computer Science and Engineering, Ewha Womans University) ;
  • Lee, Min-Soo (Department of Computer Science and Engineering, Ewha Womans University)
  • Accepted : 2011.06.04
  • Published : 2011.09.30
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Abstract

DNA chips are used for experiments on genes and provide useful information that could be further analyzed. Using the data extracted from the DNA chips to find useful patterns or information has become a very important issue. In this paper, we explain the application developed for classifying DNA chip data using a classification method based on the Particle Swarm Optimization (PSO) algorithm. Considering that DNA chip data is extremely large and has a fuzzy characteristic, an algorithm that imitates the ecosystem such as the PSO algorithm is suitable to be used for analyzing such data. The application enables researchers to customize the PSO algorithm parameters and see detail results of the classification rules.

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References

  1. Falco, I.D., Cioppa, A.D., and Tarantino, E. (2006). Evaluation of Particle Swarm Optimization Effectiveness in Classification. Fuzzy Logic and Applications 3849, 164-171. https://doi.org/10.1007/11676935_20
  2. Falco, I.D., Cioppa, A.D., and Tarantino, E. (2007). Facing classification problems with Particle Swarm Optimization. Appl. Soft. Comput. 7, 652-658. https://doi.org/10.1016/j.asoc.2005.09.004