cryoAgent: An agentic workflow for robust and adaptive end-to-end cryo-EM image processing
Daoyi LiiD, 杨少迪, Taining PeiiD, Chen Qi, 肖茜, Tongxin NiuiD, Yan Zhang, Yun ZhuiD, Fei SuniD
Abstract
Cryo-electron microscopy (cryo-EM) is the mainstream method for structure determination, yet current automated workflows remain rigid and require expert intervention for failure recovery, heterogeneity analysis, and optimization. We present cryoAgent, an agentic workflow for autonomous cryo-EM image processing with adaptive tool use to address these challenges. cryoAgent improves reconstruction quality across diverse datasets, identifies a previously unreported structural state, advancing scalable and discovery-oriented structural biology.
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