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Open Access Research article

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

Omid Abbasi1, Ali Rostami12 and Ghader Karimian3*

Author Affiliations

1 School of Engineering-Emerging Technologies, University of Tabriz, Tabriz 5166614761, Iran

2 Photonics and Nanocrystals Research Lab. (PNRL), Faculty of Electrical and Computer Engineering, University of Tabriz, Tabriz 5166614761, Iran

3 Faculty of Electrical and Computer Engineering, University of Tabriz, Tabriz 5166614761, Iran

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BMC Bioinformatics 2011, 12:430  doi:10.1186/1471-2105-12-430

Published: 3 November 2011

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.