Machine Learning Framework with Wilson Loop Perceptron for Measuring the Rate of Mutation Patterns between DNA and RNA Viruses
摘要
The Wilson loop is indicative of the pathway encompassed within the viral replication process, which carries the coherent gauge field behavior present in the genetic coding of the virus. We enhance the capabilities of the support spinor machine by integrating supplementary attributes through the incorporation of the knot and link characteristics of the Wilson loop, as derived from biological contexts. This framework was employed to get into more deeper understanding of the mutational dynamics within viral replication, with particular emphasis on the concurrent quantum genotyping transfer along the continuous gauge field’s geodesic evolutionary trajectory. This trajectory links the genetic code existing in viral RNA and protein. Furthermore, a comparative analysis was undertaken to quantifying the mutation patterns in the replication loop of the evolutionary pathway. This was achieved by utilizing the spectrum of tensor correlation between the Marburg virus and the Monkeypox virus. The computational results for the mutation rates of the Marburg virus,