Complexity Estimation of Genetic Sequences Using Information-Theoretic and Frequency Analysis Methods
Volume 21, Issue 1 (2010), pp. 13–30
Pub. online: 1 January 2010
Type: Research Article
Received
1 January 2009
1 January 2009
Accepted
1 February 2009
1 February 2009
Published
1 January 2010
1 January 2010
Abstract
The genetic information in cells is stored in DNA sequences, represented by a string of four letters, each corresponding to a definite type of nucleotides. Genomic DNA sequences are very abundant in periodic patterns, which play important biological roles. The complexity of genetic sequences can be estimated using the information-theoretic methods. Low complexity regions are of particular interest to genome researchers, because they indicate to sequence repeats and patterns. In this paper, the complexity of genetic sequences is estimated using Shannon entropy, Rényi entropy and relative Kolmogorov complexity. The structural complexity based on periodicities is analyzed using the autocorrelation function and time delayed mutual information. As a case study, we analyze human 22nd chromosome and identify 3 and 49 bp periodicities.