A Punctual Algorithm for Small Gene Prediction in DNA Sequences Using a Time-Frequency Approach based on the Z-Curve

Abstract

Identification of protein-coding regions in Deoxyribonucleic Acid (DNA) sequences because of their 3-base periodicity has been a challenging issue in bioinformatics. Many DSP (Digital Signal Processing) techniques have been applied for identification task and concentrated 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 periodicity components. In this paper, we investigate the location of exons in DNA strand using Variable Length Window approach based on z-curve. Z-curve is a unique 3-D curve to illustrate DNA's sequence which presents a complete description of DNA's sequence biological behavior. The proposed algorithm has a high accuracy and resolution due to applying Gaussian window with an adjustable length to identify and estimate exonic areas and non-coding regions are totally eliminated. In order to extract period-3 component we used a narrow-band band-pass filter with a central frequency of . The proposed algorithm was applied on some gene sequences existed in GenBank dataset and its results were compared by other existing methods at the nucleotide level. Simulation results show that our algorithm increases the accuracy of exon detection relative to other methods for exon prediction.