An Optimization to Protein Coding Regions Identification in Eukaryotes

Identification of coding regions in DNA sequences is an important and challenging optimization problem in bioinformatics. Several approaches have been proposed but none is currently satisfactory. Here, the authors propose an optimization methodology to identify protein coding regions in Eukaryotes. Noise reduction in DNA signal indirectly overcomes spectral leakage phenomenon. The proposed methodology fragments this optimization in two classes as opposed to the usual optimization methods that rely on statistical and digital signal processing. Compact DNA signal with minimal spectral leakage is obtained in class one by using a new indicator sequence while class two addresses the 1/f background noise reduction employing wavelet transforms. Significant improvement in coding regions identification was observed over many real datasets, which were obtained from the national center for bioinformatics. Quantitatively, the authors monitored a gain of 80.5% in coding identification with the Complex method, 42.5% with the Binary method, and 15% with the EIIP indicator sequence method over Mus Musculus Domesticus (House rat), NCBI Accession number: NC_006914, Length of gene: 7700 bp with number of coding regions: 4. Continuous improvement in significance with dyadic wavelet transforms will be observed as a future expectation.