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Non-parametric spectral estimation techniques for DNA sequence analysis and exon region prediction
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2019 (English)In: Computers & electrical engineering, ISSN 0045-7906, E-ISSN 1879-0755, Vol. 73, p. 334-348Article in journal (Refereed) Published
Abstract [en]

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.

Place, publisher, year, edition, pages
Elsevier, 2019. Vol. 73, p. 334-348
Keywords [en]
Bioinformatics, DNA, Exon prediction, Genomic signal processing, Spectral estimation
National Category
Computer Sciences Bioinformatics (Computational Biology)
Identifiers
URN: urn:nbn:se:umu:diva-156897DOI: 10.1016/j.compeleceng.2018.12.001ISI: 000458593900026OAI: oai:DiVA.org:umu-156897DiVA, id: diva2:1295060
Available from: 2019-03-09 Created: 2019-03-09 Last updated: 2019-03-09Bibliographically approved

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Hassan, Emadeldeen

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  • asciidoc
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