Protein Function Prediction

Protein function prediction aims to computationally determine a protein's biological role based on its sequence or structure. Current research heavily utilizes deep learning, employing architectures like graph neural networks, transformers, and convolutional neural networks to analyze protein sequences and structures, often integrating multiple data modalities (sequence, structure, expression levels) for improved accuracy. These advancements are crucial for accelerating drug discovery, understanding disease mechanisms, and enabling the design of novel proteins with specific functionalities. The field is also actively exploring methods to improve model interpretability and efficiency, and to leverage pre-trained models for enhanced performance with limited data.