Abstract
Genomic signal processing (GSP) is an engineering domain involved with the analysis of genomic data using digital signal processing (DSP) approaches after transformation of the sequence of genome to numerical sequence. One challenge of GSP is how to minimize the error of detection of the protein coding region in a specified deoxyribonucleic acid (DNA) sequence with a minimum processing time. Since the type of numerical representation of a DNA sequence extremely affects the prediction accuracy and precision. The impact of different DNA statistical representations on the identification of coding sequences (exons) was researched. In this study using the IIR inverse Chepyshev filter for twenty benchmark human genes. In order to accomplish this, the sensitivity, specificity, and correlation coefficient of the four most modern DNA numerical representation schemes GCC, FNO, atomic number, and 2-bit binary were measured and contrasted with those of EIIP, the most used technique for locating protein-coding regions.
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