Numerical representation of DNA sequences based on genetic code context and its applications in periodicity analysis of genomes

The indispensable prerequisites in characterizing information content of DNA molecules by computational methods are the numerical representations of symbolic DNA sequences. Current numerical representation methods for DNA sequences do not contain the genetic code context information, which may play an important role in defining protein coding regions. We propose a novel numerical representation of DNA sequences based on genetic code context within DNA sequences and explore the feasibility of applying this method to identify protein coding regions in genomes. Computational experiments indicate that incorporating genetic code information into numerical representations is a promising approach in which DNA sequences are uniquely represented and more information is represented so that digital processing tools can be applied to the periodicity analysis in DNA sequences effectively.

I. Introduction

WITH quickly growing volume of DNA sequence databases of human and model organisms since the Human Genome Program was completed, there is a strong demand to characterize the information in the sequences. Signal processing approaches have been attracting significant attentions in genomic DNA research and become increasingly important to elucidate genome structures because they may identify hidden periodicities and features which can not be revealed easily by conventional statistics methods [1]. Many attempts have been made in applying the proven digital processing techniques in image processing and speech recognition such as Fourier transform, wavelet analysis to the study of periodicities in DNA sequence [2], [3], [4].