Before revision:  as a method to predict the stability/reactivity and risk of degradation of sequences of RNA.  Reasonably accurate results were able to be generated , with the Graph Convolutional Network being the best predictor of reactivity (RMSE = 0.249) while the Gated Recurrent Unit Network was the best at predicting risks of degradation under various circumstances (RMSE = 0.266)  . Results suggest feasibility of applying such methods in mRNA vaccine research in the near future.
After revision:  as a method to predict the stability/reactivity and risk of degradation of sequences of RNA. Reasonably accurate results were able to be generated , with the Graph Convolutional Network being the best predictor of reactivity (RMSE = 0.249) while the Gated Recurrent Unit Network was the best at predicting risks of degradation under various circumstances (RMSE = 0.266) . Overall, combining all target variables, the GRU performed the best with an accuracy value of 76\% . Results suggest feasibility of applying such methods in mRNA vaccine research in the near future.