A Novel Circular Mapping Technique for Spectral Classification of Exons and Introns in Human DNA Sequences

Abstract

Signals that represent information may be classified into two forms: numeric and symbolic. Symbolic signals such as DNA symbolic sequences cannot be directly processed with digital signal processing (DSP) techniques. The only way to apply DSP in genomic field is the mapping of DNA symbolic sequences to numerical sequences. Hence, biological properties are reflected in a numerical domain. This opens a field to present a set of tools for solving genomic problems. In literature many techniques have been developed for numerical representation of DNA sequences. The main drawback of these techniques is that each nucleotide is represented by a numerical value depending on nucleotide type only ignoring its position in codon and DNA sequence. In this paper a new approach for DNA symbolic to numeric representation called Circular Mapping (CM) is introduced. It's based on graphical representation of DNA sequence that maps each nucleotide by a complex numerical value depending not only on nucleotide type but also on its position in codons. The main applications of this method are the gene prediction that aims to locate the protein-coding regions and the classification of exons and introns in DNA sequences. The proposed approach showed significant improvement in exons and introns classification as compared with the existing techniques. The efficiency of this method in classification depends on the right choice of the mapping angle () as indicated by the power spectral analysis results over the sequences of the human genome (GRch37/hg19).

A novel genome analysis method with the entropy-based numerical technique using pretrained convolutional neural networks

“…These RNAs are named as mRNA. While mRNA is extracted, the noncoding parts of a DNA sequence are called introns, the coding parts of DNA are called exons [6][7][8][9]. Classification of the DNA sequence, which belong to a gene, as exons and introns is quite classification of DNA sequences as exon and intron, it can be known where the stem cells will be transformed into organs, tissues, and cells, under which conditions the cells will be reproduced or killed.…”

Locating All Common Subsequences in Two DNA Sequences

“…BLAST: (Basic Local Alignment Search Tool) [4] is an example of a larger scale. Most of these algorithms uses SmithWaterman algorithm for performing sequence alignment [6][7][8][9][10][21][22][23][24][25]. This algorithm which is also used in crimes' forensic investigation does not use full DNA to DNA sequence comparison.…”