Mutation Rate Analysis using LSTM model

SARS-CoV-2, also known as COVID-19, is a novel coronavirus that has created a global epidemic. This highly infectious RNA virus posed a global danger. This virus has the ability to cause human mutations. Accurate mutation rate determination is required to understand the evolution of this virus and determine the danger of a new infectious illness. Based on patient data, this study looks at the mutation rate of the complete genome sequence. The data is analysed separately to look for nucleotide and codon mutations. To forecast the future mutation rate, a recurrent neural network (RNN) based Long Short-Term Memory (LSTM) model was utilised. In both the training and testing sets, this model has an extremely low error rate of about 1.03. 

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