Non-parametric spectral estimation techniques for DNA sequence analysis and exon region prediction. (January 2019)

• Record Type: Journal Article
• Authors: Dessouky, Ahmed M.; Taha, Taha E.; Dessouky, Mohamed M.; Eltholth, Ashraf A.; Hassan, Emadeldeen; Abd El-Samie, Fathi E.
• Is Part Of: Computers & electrical engineering. Volume 73(2019)
• Page Start: 334
• Page End: 348
• Publication Date: 2019-01
• Subjects: Bioinformatics -- DNA -- Exon prediction -- Genomic signal processing -- Spectral estimation; Computer engineering -- Periodicals; Electrical engineering -- Periodicals; Electrical engineering -- Data processing -- Periodicals; Ordinateurs -- Conception et construction -- Périodiques; Électrotechnique -- Périodiques; Électrotechnique -- Informatique -- Périodiques; Computer engineering; Electrical engineering; Electrical engineering -- Data processing; Periodicals; Electronic journals; 621.302854
• DOI: 10.1016/j.compeleceng.2018.12.001
• Languages: English
• ISSNs: 0045-7906

Abstract

Abstract: Bioinformatics is the analysis of biological information using computers and statistical techniques. This paper presents non-parametric spectral estimation techniques based on the Discrete Fourier Transform (DFT) for the analysis of deoxyribonucleic acid (DNA) sequences. These techniques are efficient frequency-domain signal representation techniques, which improve the analysis of DNA sequences and enable the extraction of some desirable information that cannot be extracted from the time-domain representation of these sequences. The adopted techniques are the periodogram, average periodogram (Bartlett), modified average periodogram (Welch), and Blackman and Tukey spectral estimation techniques. The objective of these spectral estimation techniques is to investigate the locations of exons in DNA sequences for gene prediction. A comparison study is presented in this paper between the suggested spectral estimation techniques from the exon prediction perspective. The methods presented in this paper improve the detectability of peaks representing exon regions.