 Tomato yellow leaf curl virus, TYLCV, a virus that causes severe damage to tomato crops, has been a global threat since its discovery in 1931. In recent years, three new strains have been identified in South Korea, but their function remains unknown. To address this issue, a team of scientists developed an integrated computational framework for accurately identifying the severity of symptoms caused by TYLCV. This framework included extracting various features from the virus sequences, testing multiple classifiers, and combining the best performing models into a single prediction model. The resulting model, called IMLTYLCV, was used to predict the severity of symptoms caused by the three new strains. The results showed that two of the strains were severe while the third was mild. Additionally, the team tested the accuracy of the model by conducting blind prediction tests and found that the model correctly predicted the severity of symptoms caused by the three strains. Finally, they validated the model by conducting virus challenge experiments on tomato plants. These experiments confirmed that the model could accurately identify the severity of symptoms caused by the three strains. This article was authored by Natanon Bupi, Vinoth Kumar Sangaraju, Lutifon, and others. We are article.tv, links in the description below.