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Bioinformatics Advance Access published online on August 23, 2005
Bioinformatics, doi:10.1093/bioinformatics/bti639
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© The Author (2005). Published by Oxford University Press. All rights reserved. For Permissions, please email: journals.permissions@oupjournals.org
Received March 30, 2005
Revised August 17, 2005
Accepted August 17, 2005

Article

Identification of coding and noncoding sequences using local Hölder exponent formalism

Onkar C. Kulkarni 1, R. Vigneshwar 1, Valadi K. Jayaraman 1, and Bhaskar D. Kulkarni 1*

1 National Chemical Laboratory, Pune-411008, India

* To whom correspondence should be addressed.
Bhaskar D. Kulkarni, E-mail: bd.kulkarni{at}ncl.res.in


  Abstract

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 noncoding 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 noncoding sequences.

Results: The local singularity density distribution in the coding and noncoding sequences of four genomes was first estimated using the wavelet transform modulus maxima methodology (WTMM). Support vector Machines (SVM) 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 noncoding sequences.


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