Cryo EM

Cryo-electron microscopy (cryo-EM) is a powerful technique for determining the 3D structures of biomolecules at near-atomic resolution, primarily by reconstructing 3D structures from noisy 2D projection images. Current research heavily utilizes deep learning, employing architectures like generative adversarial networks (GANs), diffusion models, transformers, and autoencoders to address challenges such as image denoising, pose estimation, heterogeneous reconstruction (handling multiple conformations), and automated model building. These advancements significantly improve the accuracy, speed, and efficiency of cryo-EM data analysis, leading to a deeper understanding of biological structures and functions.