Skip to main content

Short Exon Detection in DNA Sequences Based on Multifeature Spectral Analysis

Abstract

This paper presents a new technique for the detection of short exons in DNA sequences. In this method, we analyze four DNA structural properties, which include the DNA bending stiffness, disrupt energy, free energy, and propeller twist, using the autoregressive (AR) model. The linear prediction matrices for the four features are combined to find the same set of linear prediction coefficients, from which we estimate the spectrum of the DNA sequence and detect exons based on the 1/3 frequency component. To overcome the nonstationarity of DNA sequences, we use moving windows of different sizes in the AR model. Experiments on the human genome show that our multi-feature based method is superior in performance to existing exon detection algorithms.

Publisher note

To access the full article, please see PDF.

Author information

Affiliations

Authors

Corresponding author

Correspondence to Nancy Yu Song.

Rights and permissions

Open Access This article is distributed under the terms of the Creative Commons Attribution 2.0 International License (https://creativecommons.org/licenses/by/2.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

Reprints and Permissions

About this article

Cite this article

Song, N.Y., Yan, H. Short Exon Detection in DNA Sequences Based on Multifeature Spectral Analysis. EURASIP J. Adv. Signal Process. 2011, 780794 (2011). https://doi.org/10.1155/2011/780794

Download citation

Keywords

  • Free Energy
  • Human Genome
  • Spectral Analysis
  • Quantum Information
  • Detection Algorithm
\