CryoRL: Reinforcement Learning Enables Efficient Cryo-EM Data Collection. (arXiv:2204.07543v1 [cs.LG])

Single-particle cryo-electron microscopy (cryo-EM) has become one of the
mainstream structural biology techniques because of its ability to determine
high-resolution structures of dynamic bio-molecules. However, cryo-EM data
acquisition remains expensive and labor-intensive, requiring substantial
expertise. Structural biologists need a more efficient and objective method to
collect the best data in a limited time frame. We formulate the cryo-EM data
collection task as an optimization problem in this work. The goal is to
maximize the total number of good images taken …

arxiv cryo-em data data collection learning reinforcement reinforcement learning