A fast algorithm for exonic regions prediction in DNA sequences

The main purpose of this paper is to introduce a fast method for gene prediction in DNA sequences based on the period-3 property in exons. First, the symbolic DNA sequences were converted to digital signal using the electron ion interaction potential method. Then, to reduce the effect of background...

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Main Authors: Hamidreza Saberkari, Mousa Shamsi, Hamed Heravi, Mohammad Hossein Sedaaghi
Format: Article
Language:English
Published: Wolters Kluwer Medknow Publications 2013-01-01
Series:Journal of Medical Signals and Sensors
Subjects:
Online Access:http://www.jmss.mui.ac.ir/article.asp?issn=2228-7477;year=2013;volume=3;issue=3;spage=139;epage=149;aulast=Saberkari
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spelling doaj-e27a745f3307458c85b91f350ef0562f2020-11-25T00:01:59ZengWolters Kluwer Medknow PublicationsJournal of Medical Signals and Sensors2228-74772013-01-0133139149A fast algorithm for exonic regions prediction in DNA sequencesHamidreza SaberkariMousa ShamsiHamed HeraviMohammad Hossein SedaaghiThe main purpose of this paper is to introduce a fast method for gene prediction in DNA sequences based on the period-3 property in exons. First, the symbolic DNA sequences were converted to digital signal using the electron ion interaction potential method. Then, to reduce the effect of background noise in the period-3 spectrum, we used the discrete wavelet transform at three levels and applied it on the input digital signal. Finally, the Goertzel algorithm was used to extract period-3 components in the filtered DNA sequence. The proposed algorithm leads to decrease the computational complexity and hence, increases the speed of the process. Detection of small size exons in DNA sequences, exactly, is another advantage of the algorithm. The proposed algorithm ability in exon prediction was compared with several existing methods at the nucleotide level using: (i) specificity - sensitivity values; (ii) receiver operating curves (ROC); and (iii) area under ROC curve. Simulation results confirmed that the proposed method can be used as a promising tool for exon prediction in DNA sequences.http://www.jmss.mui.ac.ir/article.asp?issn=2228-7477;year=2013;volume=3;issue=3;spage=139;epage=149;aulast=SaberkariAlgorithmDNA sequencediscrete wavelet transformExonGoertzelprotein coding regionsignal processing
collection DOAJ
language English
format Article
sources DOAJ
author Hamidreza Saberkari
Mousa Shamsi
Hamed Heravi
Mohammad Hossein Sedaaghi
spellingShingle Hamidreza Saberkari
Mousa Shamsi
Hamed Heravi
Mohammad Hossein Sedaaghi
A fast algorithm for exonic regions prediction in DNA sequences
Journal of Medical Signals and Sensors
Algorithm
DNA sequence
discrete wavelet transform
Exon
Goertzel
protein coding region
signal processing
author_facet Hamidreza Saberkari
Mousa Shamsi
Hamed Heravi
Mohammad Hossein Sedaaghi
author_sort Hamidreza Saberkari
title A fast algorithm for exonic regions prediction in DNA sequences
title_short A fast algorithm for exonic regions prediction in DNA sequences
title_full A fast algorithm for exonic regions prediction in DNA sequences
title_fullStr A fast algorithm for exonic regions prediction in DNA sequences
title_full_unstemmed A fast algorithm for exonic regions prediction in DNA sequences
title_sort fast algorithm for exonic regions prediction in dna sequences
publisher Wolters Kluwer Medknow Publications
series Journal of Medical Signals and Sensors
issn 2228-7477
publishDate 2013-01-01
description The main purpose of this paper is to introduce a fast method for gene prediction in DNA sequences based on the period-3 property in exons. First, the symbolic DNA sequences were converted to digital signal using the electron ion interaction potential method. Then, to reduce the effect of background noise in the period-3 spectrum, we used the discrete wavelet transform at three levels and applied it on the input digital signal. Finally, the Goertzel algorithm was used to extract period-3 components in the filtered DNA sequence. The proposed algorithm leads to decrease the computational complexity and hence, increases the speed of the process. Detection of small size exons in DNA sequences, exactly, is another advantage of the algorithm. The proposed algorithm ability in exon prediction was compared with several existing methods at the nucleotide level using: (i) specificity - sensitivity values; (ii) receiver operating curves (ROC); and (iii) area under ROC curve. Simulation results confirmed that the proposed method can be used as a promising tool for exon prediction in DNA sequences.
topic Algorithm
DNA sequence
discrete wavelet transform
Exon
Goertzel
protein coding region
signal processing
url http://www.jmss.mui.ac.ir/article.asp?issn=2228-7477;year=2013;volume=3;issue=3;spage=139;epage=149;aulast=Saberkari
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