Segmentation of short human exons based on spectral features of double curves

Rong Jiang; Hong Yan

doi:10.1504/IJDMB.2008.016754

Segmentation of short human exons based on spectral features of double curves

Rong Jiang, Hong Yan

Research output: Journal Publications and Reviews › RGC 21 - Publication in refereed journal › peer-review

13 Citations (Scopus)

Abstract

This paper presents a new segmentation method based on spectral analysis to locate borders between short protein coding regions and non-coding regions. We formulate the innovative double curve representation of a DNA sequence and apply local three-codon measurement on the discrete Fourier spectral features at 1/3 frequency to identify short protein coding regions. The proposed spectral segmentation method based on double curves requires no prior knowledge of the DNA data. Our simulation results show that the proposed spectral method greatly improves the accuracy of identifying short coding regions in DNA sequences compared with the results obtained from the other methods that analyse DNA sequences directly. Copyright © 2008 Inderscience Enterprises Ltd.

Original language	English
Pages (from-to)	15-35
Journal	International Journal of Data Mining and Bioinformatics
Volume	2
Issue number	1
DOIs	https://doi.org/10.1504/IJDMB.2008.016754
Publication status	Published - Jan 2008

Research Keywords

Bioinformatics
Data mining
DNA sequence analysis
Double curves
Fourier spectrum
Gene identification
Short human exons
Spectral analysis
Triplets

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title = "Segmentation of short human exons based on spectral features of double curves",

abstract = "This paper presents a new segmentation method based on spectral analysis to locate borders between short protein coding regions and non-coding regions. We formulate the innovative double curve representation of a DNA sequence and apply local three-codon measurement on the discrete Fourier spectral features at 1/3 frequency to identify short protein coding regions. The proposed spectral segmentation method based on double curves requires no prior knowledge of the DNA data. Our simulation results show that the proposed spectral method greatly improves the accuracy of identifying short coding regions in DNA sequences compared with the results obtained from the other methods that analyse DNA sequences directly. Copyright {\textcopyright} 2008 Inderscience Enterprises Ltd.",

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author = "Rong Jiang and Hong Yan",

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language = "English",

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T1 - Segmentation of short human exons based on spectral features of double curves

AU - Jiang, Rong

AU - Yan, Hong

PY - 2008/1

Y1 - 2008/1

N2 - This paper presents a new segmentation method based on spectral analysis to locate borders between short protein coding regions and non-coding regions. We formulate the innovative double curve representation of a DNA sequence and apply local three-codon measurement on the discrete Fourier spectral features at 1/3 frequency to identify short protein coding regions. The proposed spectral segmentation method based on double curves requires no prior knowledge of the DNA data. Our simulation results show that the proposed spectral method greatly improves the accuracy of identifying short coding regions in DNA sequences compared with the results obtained from the other methods that analyse DNA sequences directly. Copyright © 2008 Inderscience Enterprises Ltd.

AB - This paper presents a new segmentation method based on spectral analysis to locate borders between short protein coding regions and non-coding regions. We formulate the innovative double curve representation of a DNA sequence and apply local three-codon measurement on the discrete Fourier spectral features at 1/3 frequency to identify short protein coding regions. The proposed spectral segmentation method based on double curves requires no prior knowledge of the DNA data. Our simulation results show that the proposed spectral method greatly improves the accuracy of identifying short coding regions in DNA sequences compared with the results obtained from the other methods that analyse DNA sequences directly. Copyright © 2008 Inderscience Enterprises Ltd.

KW - Bioinformatics

KW - Data mining

KW - DNA sequence analysis

KW - Double curves

KW - Fourier spectrum

KW - Gene identification

KW - Short human exons

KW - Spectral analysis

KW - Triplets

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U2 - 10.1504/IJDMB.2008.016754

DO - 10.1504/IJDMB.2008.016754

M3 - RGC 21 - Publication in refereed journal

C2 - 18399326

SN - 1748-5673

VL - 2

SP - 15

EP - 35

JO - International Journal of Data Mining and Bioinformatics

JF - International Journal of Data Mining and Bioinformatics

IS - 1

ER -

Segmentation of short human exons based on spectral features of double curves

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