title: Identification of exonic regions in DNA sequences using cross-correlation and noise suppression by discrete wavelet transform.
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.
authors: School of Engineering-Emerging Technologies, University of Tabriz, Tabriz 5166614761, Iran.
authors: Omid
authors: O
authors: Abbasi
authors: Ali
authors: A
authors: Rostami
authors: Ghader
authors: G
authors: Karimian
mesh_terms: D000465:Algorithms; D000818:Animals; D005091:Exons; D006801:Humans; D016366:Open Reading Frames; D017422:Sequence Analysis, DNA; D012815:Signal Processing, Computer-Assisted; D058067:Wavelet Analysis