A better way for exon identification in DNA splicing

Abstract

The strands of chromosomes are supposed to be split into genic and intergenic regions. Gene identification is an optimization problem in Eukaryotic DNA splicing. An optimal solution is essential which may help in better protein translation. We have proposed a novel approach for gene identification by employing discrete wavelet transforms for noise reduction in DNA sequences and introducing a new indicator sequence for better signal generation. Wavelet transforms greatly reduced the background noise and visible peaks of genic regions were found in power spectral estimation. The comparative analysis of proposed and existing approaches showed significant results for novel approach over prevailing solutions over dataset Yersinia pestis (ACCESSION: NC_004088, 4000 bp, four genes and exons from location 5000 bp to 8999 bp). Similar outperformace was observed over many other datasets.