Bioinformatics Advance Access originally published online on August 23, 2005
Bioinformatics 2005 21(20):3818-3823; doi:10.1093/bioinformatics/bti639
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Identification of coding and non-coding sequences using local Hölder exponent formalism
National Chemical Laboratory Pune 411008, India
*To whom correspondence should be addressed.
Motivation: Accurate prediction of genes in genomes has always been a challenging task for bioinformaticians and computational biologists. The discovery of existence of distinct scaling relations in coding and non-coding sequences has led to new perspectives in the understanding of the DNA sequences. This has motivated us to exploit the differences in the local singularity distributions for characterization and classification of coding and non-coding sequences.
Results: The local singularity density distribution in the coding and non-coding sequences of four genomes was first estimated using the wavelet transform modulus maxima methodology. Support vector machines classifier was then trained with the extracted features. The trained classifier is able to provide an average test accuracy of 97.7%. The local singularity features in a DNA sequence can be exploited for successful identification of coding and non-coding sequences.
Contact: Available on request from bd.kulkarni{at}ncl.res.in.
Received on March 30, 2005; revised on August 17, 2005; accepted on August 17, 2005
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