Short Exon detection in DNA sequences based on multifeature spectral analysis

Authors:
Nancy Yu Song;Hong Yan
Affiliations:
Department of Electronic Engineering, City University of Hong Kong, Kowloon, Hong Kong;Department of Electronic Engineering, City University of Hong Kong, Kowloon, Hong Kong
Venue:
EURASIP Journal on Advances in Signal Processing - Special issue on recent advances in theory and methods for nonstationary signal analysis
Year:
2011

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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.