Identification of exonic regions in DNA sequences using cross-correlation and noise suppression by discrete wavelet transform

Author:

Abbasi Omid,Rostami Ali,Karimian Ghader

Abstract

Abstract Background The identification of protein coding regions (exons) in DNA sequences using signal processing techniques is an important component of bioinformatics and biological signal processing. In this paper, a new method is presented for the identification of exonic regions in DNA sequences. This method is based on the cross-correlation technique that can identify periodic regions in DNA sequences. Results The method reduces the dependency of window length on identification accuracy. The proposed algorithm is applied to different eukaryotic datasets and the output results are compared with those of other established methods. The proposed method increased the accuracy of exon detection by 4% to 41% relative to the most common digital signal processing methods for exon prediction. Conclusions We demonstrated that periodic signals can be estimated using cross-correlation. In addition, discrete wavelet transform (DWT) can minimise noise while maintaining the signal. The proposed algorithm, which combines cross-correlation and DWT, significantly increases the accuracy of exonic region identification.

Publisher

Springer Science and Business Media LLC

Subject

Applied Mathematics,Computer Science Applications,Molecular Biology,Biochemistry,Structural Biology

Reference22 articles.

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3. Eskesen ST, Eskesen FN, Kinghom B, Ruvinsky A: Periodicity of DNA in exons. BMC Molecular Biology 2004.

4. Chang CQ, Fung PCW, Hung YS: Improved Gene Prediction by Resampling-based Spectral Analysis of DNA Sequence. In Proceedings of the 5th International Conference on Information Technology and Application in Biomedicine: 30–31 May 2008. Shenzhen, China; 2008.

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