In current scenario, genomic analysis using signal processing has generated much interest over researchers. Human genome project and the existing genome data bases have attracted computer engineers to develop computational methods for the analysis of genomic data. The major goals of functional genomics are to use genomic signals to categorize disease on a molecular level and to screen for genes that resolve specific disease and model their activity in such a way that normal and abnormal behavior can be differentiated. Cancer is a category of diseases caused by genetic and epigenetic changes. Cancer results from mutations of sequences of genes like oncogenes or tumor suppressor genes or both. In this paper, a method to analyze De-oxy ribonucleic acid (DNA) sequences using signal processing techniques to classify whether it is normal or mutated is proposed. Here, entropy of the DNA sequence is used as marker for classification. For the analysis, reference data are taken from National Center for Biotechnology information (NCBI). Various evaluation parameters used in the literature are determined are found out and compared. The results proved that our method is better in terms of accuracy, specificity and sensitivity and error rates. © Research India Publications.