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arXiv · 2512.06332

CryoHype: Reconstructing a thousand cryo-EM structures with transformer-based hypernetworks

Jeffrey Gu·Minkyu Jeon·Ambri Ma·Serena Yeung-Levy·Ellen D. Zhong
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Abstract

Cryo-electron microscopy (cryo-EM) is an indispensable technique for determining the 3D structures of dynamic biomolecular complexes. While typically applied to image a single molecular species, cryo-EM has the potential for structure determination of many targets simultaneously in a high-throughput fashion. However, existing methods typically focus on modeling conformational heterogeneity within a single or a few structures and are not designed to resolve compositional heterogeneity arising from mixtures of many distinct molecular species. To address this challenge, we propose CryoHype, a transformer-based hypernetwork for cryo-EM reconstruction that dynamically adjusts the weights of an implicit neural representation. Using CryoHype, we achieve state-of-the-art results on a challenging benchmark dataset containing 100 structures. We further demonstrate that CryoHype scales to the reconstruction of 1,000 distinct structures from unlabeled cryo-EM images in the fixed-pose setting.

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Jeffrey Gu, Minkyu Jeon, Ambri Ma, Serena Yeung-Levy, Ellen D. Zhong. 2025-12-06. CryoHype: Reconstructing a thousand cryo-EM structures with transformer-based hypernetworks. https://arxiv.org/abs/2512.06332

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