Identification of Unique Genomic Signatures in Viral Immunogenic Syndrome (VIS) Using FIMAR and FCSM Methods for Development of Effective Diagnostic and Therapeutic Strategies

The "Viral Immunogenic Syndrome" (VIS) incorporates the concepts of "viral" and "immunogenic" to emphasise the pathogenic character of the illness and the immunological response it generates, as well as the word "syndrome" to describe the broad set of symptoms and consequences.Our research focused on analyzing the COVID-19 genome sequence using a proposed framework to improve computation time and model efficiency.We also aimed to identify frequent patterns, missing indices, and variations in the genome sequence while comparing performance with varying minimum support using existing and proposed models.We used FCSM to classify COVID-19 genomic sequences and detect variations while calculating computation time.Additionally, we proposed a novel framework utilizing FIMAR to identify nucleotide sequences and compute consecutive sets, resulting in a more efficient and accurate approach to analyzing COVID-19 genome than existing methods.Our study shows that the proposed framework with FIMAR and FCSM algorithms is 94.34% more efficient than the existing system for computing the COVID-19 genome sequence.We also identified 0.2% and 1.61% genomic variation in the USA and China datasets, respectively, which the existing system failed to detect.Additionally, we conducted a comparative study using an Apriori and FIMAR methods to identify frequent patterns.In this work, we also present an analysis of the nucleotide substitution rate at each isolation step.