Deep learning

In recent years, deep learning has emerged as a powerful tool for protein structure prediction. Deep learning algorithms, such as convolutional neural networks (CNNs) and recurrent neural networks (RNNs), can learn complex patterns and relationships from large datasets of protein sequences and structures. These algorithms have shown promising results in predicting protein secondary structures, contact maps, and even 3D coordinates.