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Journal of Biomedicine and Biotechnology
Volume 2005 (2005), Issue 2, Pages 139-146
Research article

Protein Coding Sequence Identification by Simultaneously Characterizing the Periodic and Random Features of DNA Sequences

1Department of Electrical & Computer Engineering, University of Florida, Gainesville 32611-6200, FL, USA
2Department of Biomedical Engineering, Whitaker Institute, Johns Hopkins University, Baltimore 21205, MD, USA
3BioSieve, 1026 Springfield Drive, Campbell 95008, CA, USA
4National Center for Atmospheric Research, Boulder 80307-3000, CO, USA

Received 24 May 2004; Revised 30 August 2004; Accepted 3 September 2004

Copyright © 2005 Hindawi Publishing Corporation. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.


Most codon indices used today are based on highly biased nonrandom usage of codons in coding regions. The background of a coding or noncoding DNA sequence, however, is fairly random, and can be characterized as a random fractal. When a gene-finding algorithm incorporates multiple sources of information about coding regions, it becomes more successful. It is thus highly desirable to develop new and efficient codon indices by simultaneously characterizing the fractal and periodic features of a DNA sequence. In this paper, we describe a novel way of achieving this goal. The efficiency of the new codon index is evaluated by studying all of the 16 yeast chromosomes. In particular, we show that the method automatically and correctly identifies which of the three reading frames is the one that contains a gene.