Multi-scale parametric spectral analysis for exon detection in DNA sequences based on forward-backward linear prediction and singular value decomposition of the double-base curves


Beyond Bioinformatics

Title

Authors

Miew Keen Choong^1,* and Hong Yan^{1,
2}

Affiliation

¹School of Electrical and Information Engineering, University of Sydney, NSW 2006; ²Department of Electronic Engineering, City University of Hong Kong, Kowloon, Hong Kong

miewkeen@ee.usyd.edu.au; * Corresponding author

Article Type

Prediction Model

Date

received September 20, 2007; accepted October 19, 2007; published February 12, 2008

Abstract

This paper presents a new method for exon detection in DNA sequences based on multi-scale parametric spectral analysis. A forward-backward linear prediction (FBLP) with the singular value decomposition (SVD) algorithm FBLP-SVD is applied to the double-base curves (DB-curves) of a DNA sequence using a variable moving window sizes to estimate the signal spectrum at multiple scales. Simulations are done on short human genes in the range of 11bp to 2032bp and the results show that our proposed method out-performs the classical Fourier transform method. The multi-scale approach is shown to be more effective than using a single scale with a fixed window size. In addition, our method is flexible as it requires no training data.

Keywords

spectral estimation; autoregressive model; double-base curve; DNA sequence analysis; gene identification

Citation

Choong & Yan, Bioinformation 2(7): 273-278 (2008)

Edited by

P. Kangueane

ISSN

0973-2063

Publisher

Biomedical Informatics Publishing Group

Copyright

Publisher

Copyright Transfer Agreement

The authors of published articles in Bioinformation automatically transfer the copyright to the publisher upon formal acceptance. However, the authors reserve right to use the information contained in the article for non commercial purposes.

License

This is an open-access article, which permits unrestricted use, distribution, and reproduction in any medium, for non-commercial purposes, provided the original author and source are credited.