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A DSP Approach for Finding the Codon Bias in DNA Sequences

The detection of different forms of periodicities in DNA sequences has been an active area of research in recent years. Most of the signal processing based methods have primarily focussed on assigning numerical values to the symbolic DNA sequence and then applying spectral analysis tools such as the short-time discrete Fourier transform (ST-DFT) to locate these repeats. A key application of DNA periodicity finding has been in the identification of the protein coding regions in DNA sequences by tracking the so-called period-3 component using the DNA spectrum. The main problem with this gene detection approach is that it is successful for certain genes but does not work for others. An interesting open research problem is to therefore determine the underlying reasons behind this disparity in performance. This requires, in turn, a solid understanding of the working principles of the period-3 component and the DNA spectrum. In this paper, we present a DSP-based approach that provides a complete analysis of this phenomenon. Specifically, we derive a new DSP based model that 1) clearly explains the underlying mechanism of the period-3 component, 2) directly relates the identification of the period-3 component to the detection of nucleotide bias in the codon structure, and 3) completely characterizes the DNA spectrum by a set of numerical sequences termed the filtered polyphase sequences. Furthermore, by adhering to the specific structure of the derived model, we can show that standard signal processing tools such as digital filtering can substantially enhance the detection of the codon bias. Several performance measures of DNA periodicity detection are also proposed and experimental results are provided to illustrate the key findings of our work.