Sign in
BiophysicsbioRxiv
Preprint

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.

PDFDOI

02 /Specification & Classification

Click any tag to browse matching papers

Reproducibility ledger

Nobody has reported trying to reproduce this paper yet. Did you replicate an experiment or run the code? Your report saves the next lab a week.

Sign in to file a reproducibility report.

Similarity Map
SelectedSame fieldCross-field
THISPunuru '26Yang '25Guo '26Schäfer '25Li '19Yee '23
79% semantic matchBioinformatics
Pranav Punuru, Thomas Klose, Daisuke Kihara·bioRxiv·Oct 30, 2026