Negative Selection Algorithm for DNA Pattern Classification

  • Lee, Dong-Wook (School of Electrical and Electronic Engineering, Chung-Ang University) ;
  • Sim, Kwee-Bo (School of Electrical and Electronic Engineering, Chung-Ang University)
  • Published : 2004.08.25

Abstract

We propose a pattern classification algorithm using self-nonself discrimination principle of immune cells and apply it to DNA pattern classification problem. Pattern classification problem in bioinformatics is very important and frequent one. In this paper, we propose a classification algorithm based on the negative selection of the immune system to classify DNA patterns. The negative selection is the process to determine an antigenic receptor that recognize antigens, nonself cells. The immune cells use this antigen receptor to judge whether a self or not. If one composes ${\eta}$ groups of antigenic receptor for ${\eta}$ different patterns, these receptor groups can classify into ${\eta}$ patterns. We propose a pattern classification algorithm based on the negative selection in nucleotide base level and amino acid level. Also to show the validity of our algorithm, experimental results of RNA group classification are presented.