NetGO 3.0: A Recent Protein Function Prediction Tool Based on Protein Language Model

In the field of bioinformatics, automated function prediction (AFP) for proteins is a significant issue. We propose a computational framework based on a protein language model to provide accurate functional predictions for proteins. By integrating multiple component methods, our approach effectively improves prediction performance. Additionally, we have developed a user-friendly online platform that allows users to obtain prediction results simply by submitting protein sequences, freely available at https://dmiip.sjtu.edu.cn/ng3.0/?returning=true . We provide a detailed guide on how to use the web server and correctly interpret the prediction results. Finally, through a practical example, we demonstrate the superior performance of NetGO 3.0 in predicting protein functions, further showcasing the potential of this framework for protein functional annotation.