An application of information theory for DNA structure

In this study, first the definitions of the concepts of entropy and information which express the measurement of the indeterminacy existing in a probabilistic system are addressed. The features of these two concepts and their variety are presented in detail, and the relation and differences between these two are touched upon. For both concepts, applications had been conducted on DNA structures belonging to human genome taken from the NCBI (National Center for Biotechnology information) website.The results on the relative entropy (Kullback-Leibler divergence) and Bhattacharyya distance values calculated from the probability distributions, formed by taking the bases of the regions that encode proteins (exon) and that do not encode proteins (intron) of the DNA structures of the eukaryote cells, and the results on the similarity of the probability distribution of these two structures were presented contrastively. A similar study is conducted for the splice site regions where exons and introns separated, and an alternative way is proposed for estimating this region. Also, via the probability distributions of the amino acids, the Entropy, Kullback-Leibler distance and Mutual Information values is calculated and interpreted.