Authors: Nancy Yu Song; Hong Yan
Addresses: Department of Electronic Engineering, City University of Hong Kong, Kowloon, Hong Kong ' Department of Electronic Engineering, City University of Hong Kong, Kowloon, Hong Kong; School of Electrical and Information Engineering, University of Sydney, NSW 2006, Australia
Abstract: This paper presents two new approaches for short gene recognition in DNA sequences. Three of fourteen DNA structural features are selected based on their classification power by a modified auto-regressive model method. Experiments on human genome show that the method is superior to existing exon detection algorithms. However, this method requires computing time. To overcome this problem, the DNA structural features are mapped to a set of new values. The three signals generated by the mapped feature values are normalised and averaged before their power spectral density is estimated. The computational complexity is reduced substantially using the feature mapping method.
Keywords: short gene recognition; exon detection; AR model; autoregressive model; spectral estimation; spectral analysis; DNA structural features; feature selection; feature mapping; DNA sequences; modelling; bioinformatics; power spectral density.
International Journal of Data Mining and Bioinformatics, 2012 Vol.6 No.6, pp.675 - 691
Received: 11 Apr 2011
Accepted: 11 Apr 2011
Published online: 12 Nov 2012 *