Pairwise Spectral Correlation of SARS-Corona Viruses

Abstract

A set of complete genome data of nine SARS-Corona type viruses are analyzed for identifying possible common features among their spectra. A novel isomorphic transform called ƒ??Discrete Rajan Transformƒ? introduced by Ms. PrashanthiGovindarajan in 2012 while she was in the Department of Electronics of Staffordshire University, United Kingdom, as an updated version of the homomorphic/isomorphic transform called ƒ??Rajan Transformƒ? is proposed here to perform spectral analysis of the virus genome data. The purpose of spectral analysis is to extract finer and hidden details pertaining to the evolutionary nature of SARS-Corona viruses.It was foundthat all SARS-Corona type viruses evolve by random mutation but with their basic structural genetic property maintained, in the system biological sense. This has already been verified by extracting common digital spatial patterns during a study on ƒ??Pairwise Spatial Correlation of SARS-Corona Virusesƒ?. However, the genetic functional properties of SARS-Corona type viruses are different for different strains. The scope of this paper is limited to the study of Rajan Transform based spectralcorrelation among the genome data under consideration. Every mutated virus strain contracted by an individual is likely to generate different strains, in vitro, depending on the health conditions of that individual. Our study has indicated this possibility.

Keywords

Artificial Intelligence Machine learning SARS-Corona Viruses Spectral Correlations

  • Research Identity (RIN)

  • License

  • Language & Pages

    English, 81-148

  • Classification

    J.3