An Non-Invasive Approach of Corona Genome Detection

Corona virus is formulated from large group of the viruses that causes illness range from common cold to more severe diseases. This virus has transmitted from animals to human beings. Millions of people throughout the world are affected to this deadly virus. So it is vital to detect this threatening virus. The Genomic Signal processing techniques is a constructive tool to detect infection as it deals with the advance research in the genetics. In this article we delineate the Genomic sequences of Corona Virus infected samples and convert the genomic data into digital signal and on applying Discrete Wavelet Transform and Fast Fourier Transform we performed mathematical modeling of the Corona-Virus gene so that it becomes effortless to predict the Corona-Virus Gene statistically. The motive of this research is to provide predicted results to drug designer for better response to this life threating Virus. We have tested these algorithms on most significant genes of the Corona Virus as well as Normal Cells of Homosapiens. The dataset of all the genomes are available on the National Center of Biotechnology Information (NCBI) website.