Cryo EM Data Collection

Cryo-EM data collection aims to optimize the acquisition of high-quality images for 3D structure determination of biomolecules, currently a labor-intensive and expensive process. Research focuses on automating this process through machine learning, employing techniques like reinforcement learning and convolutional neural networks to identify optimal imaging locations on cryo-EM grids and improve data acquisition efficiency. These advancements promise to significantly increase the throughput and accessibility of cryo-EM, accelerating biological research and structural discovery.