COVID-19 mRNA Vaccine Degradation Prediction Using LR and LGBM Algorithms

Abstract The threatening Coronavirus which was assigned as the global pandemic concussed not only public health but society, economy and every walks of life. Some measurements are taken to stifle spread one best ways is carry out some precautions prevent contagion SARS-CoV-2 virus uninfected populaces. Injecting prevention vaccines precaution steps under grandiose blueprint. Among all vaccines, it found that mRNA vaccine shows no side effect with marvellous effectiveness most preferable candidates be considered. However, degradation had become its biggest drawback implemented. Hereby, this study held desideratum develop prediction models specifically predict rate for COVID-19. Two machine learning algorithms, are, Linear Regression (LR) Light Gradient Boosting Machine (LGBM) proposed development using Python language. Dataset comprises thousands RNA molecules holds rates at each position from Eterna platform extracted, pre-processed encoded label encoding before loaded into algorithms. results show LGBM (0.2447) performs better than LR (0.3957) when evaluated RMSE metric.