Title :
Detection of period-3 behavior in genomic sequences using singular value decomposition
Author :
Akhtar, Mahmood ; Ambikairajah, Eliathamby ; Epps, Julien
Abstract :
Many digital signal processing techniques have been used to automatically distinguish the protein coding regions (exons) from non-coding regions (introns) in a DNA sequence. Recently, autoregressive (AR) technique has been used for the detection of 3-periodicty present in protein coding regions of genomic sequences. The sequence length, average spacing between coding regions, and average coding region length are the main factors that affect the performance of any prediction method. In this paper, we propose the use of singular value decomposition (SVD) method for the detection of period-3 behavior in DNA sequences. Results show that SVD method outperforms the AR technique.
Keywords :
DNA; biology computing; genetics; proteins; signal processing; singular value decomposition; DNA sequence; autoregressive technique; digital signal processing techniques; genomic sequences; noncoding regions; period-3 behavior detection; protein coding regions; singular value decomposition method; Australia; Bioinformatics; Communications technology; DNA; Digital filters; Digital signal processing; Genomics; Proteins; Sequences; Singular value decomposition;
Conference_Titel :
Emerging Technologies, 2005. Proceedings of the IEEE Symposium on
Print_ISBN :
0-7803-9247-7
DOI :
10.1109/ICET.2005.1558846