Genomic Signal Processing Methods in DNA Mapping Schemes for Prediction of Exon in a Gene Using Digital Filters

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