Cellular automata in protein coding region identification

Genes contain their information as a specific sequence of nucleotides or bases that are found in DNA molecules. These specific sequences of bases encode instructions on how to make proteins. But, the regions of these genes that code for proteins may occupy only a small region of the sequence. Identifying the coding region is of vital importance in understanding these genes. In this paper, we propose a cellular automata (CA) based pattern classifier to identify the coding region of a DNA sequence. CA is very simple, efficient, and produces more accurate classifier than that have previously been obtained for a range of different sequence lengths. Extensive experimental results establish that the proposed classifier is a cost-effective alternative in protein coding region identification problem.