Clustering analysis for bacillus genus using fourier transform and self-organizing map

  • Authors:

  • Cheng-Chang Jeng;I-Ching Yang;Kun-Lin Hsieh;Chun-Nan Lin

  • Affiliations:

  • Systematic and Theoretical Science Research Group, National Taitung University, Taitung, Taiwan;Systematic and Theoretical Science Research Group, National Taitung University, Taitung, Taiwan;Systematic and Theoretical Science Research Group, National Taitung University, Taitung, Taiwan;Department of Management Information System, National Chung Cheng University, Min-Hsiung Chia-Yi, Taiwan

  • Venue:
  • ICONIP'06 Proceedings of the 13th international conference on Neural information processing - Volume Part III
  • Year:
  • 2006

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Abstract

Because the lengths of nucleotide sequences for microorganisms are various, it is difficult to directly compare the complete nucleotide sequences among microorganisms. In this study, we adopted a method that can convert DNA sequences of microorganisms into numerical form then applied Fourier transform to the numerical DNA sequences in order to investigate the distributions of nucleotides. Also, a visualization scheme for transformed DNA sequences was proposed to help visually categorize microorganisms. Furthermore, the well-known neural network technique Self-Organizing Map (SOM) was applied to the transformed DNA sequences to draw conclusions of taxonomic relationships among the bacteria of Bacillus genus. The results show that the relationships among the bacteria are corresponding to recent biological findings.