Abstract
Heterogeneous DNA sequences can be partitioned into homogeneous domains that are comprised of the four nucleotides A, C, G, and T and the stop-codons. Recursively, we apply a new entropic segmentation method on DNA sequences using Jensen-Shannon and Jensen-Rényi divergences in order to find the borders between coding and noncoding DNA regions. We have chosen 12- and 18-symbol alphabets that capture (i) the differential nucleotide composition in codons, and (ii) the differential stop-codon composition along all the three phases in both strands of the DNA. The new segmentation method is based on the Jensen-Rényi divergence measure, nucleotide statistics, and stop-codon statistics in both DNA strands. The recursive segmentation process requires no prior training on known datasets. Consequently, for three entire genomes of bacteria, we find that the use of nucleotide composition, stop-codon composition, and Jensen-Rényi divergence improve the accuracy of finding the borders between coding and noncoding regions in DNA sequences.
Highlights
The computational identification of genes and coding regions in DNA sequences is a major goal and a long-lasting topic for molecular biology, especially for the human genome project [1, 2]
For three entire genomes of bacteria, we find that the use of nucleotide and stop-codon composition, and Jensen-Renyi divergence improve the accuracy of finding the borders between coding and noncoding regions in DNA sequences
In order to quantify the coincidence between cuts (CBC) obtained using the recursive segmentation algorithm and known borders between coding and noncoding regions, we use the following measure, introduced by Bernaola-Galvan et al [19]: CBC
Summary
The computational identification of genes and coding regions in DNA sequences is a major goal and a long-lasting topic for molecular biology, especially for the human genome project [1, 2]. Methods for reliable identification of genes in anonymous sequences of DNA can speed the process. There are two basic problems in gene finding: detection of protein-binding sites of the genes and detection of regions that code for proteins. These problems still are not satisfactorily solved, and the reliable detection of genes and coding regions in DNA sequences is critical for the success of the computational gene discovery from annotated genome sequences [4].
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