Author

Gordon Wetzstein

Stanford UniversityORCID 0000-0002-9243-6885Unclaimed ORCID profile · follow to get notified of new preprints

Biology Disciplines

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Signature Assays, Organisms & Methods

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Assay:cryo-EM· 2 Approach:deep learning· 2 Research Focus:protein structure prediction· 2 Approach:contrastive learning· 1 Approach:statistical model· 1

Frequent Co-Authors

Axel LevyiD· 2 shared Frédéric PoiteviniD· 2 shared Ariana PeckiD· 1 shared Daniel F. RatneriD· 1 shared Ellen D. ZhongiD· 1 shared Francesca ValleseiD· 1 shared Huanghao MaiiD· 1 shared J. Ryan FeathersiD· 1 shared

Activity by Year

2025-2025 · peak 2/yr

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10 top collaborators · 29 mutual co-author links

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2 shared papersBiophysics

Axel LevyORCID

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2 papers

Recent·Most cited

Unsupervised learning of structural variability in cryo-EM data using normal mode analysis of deformable atomic models

Youssef S. G. Nashed, Julien Martel, Ariana Peck, Axel Levy, Huanghao Mai, Gordon Wetzstein, Nina Miolane, Daniel F. Ratner, Frédéric Poitevin

The paper introduces an unsupervised method to analyze structural variability in cryo-EM data by deforming atomic models using normal mode analysis directly against 2D data, improving accuracy and interpretability.

bioRxiv · Jul 27, 2025 · PreprintBiophysics

CryoDRGN-AI: Neural ab initio reconstruction of challenging cryo-EM and cryo-ET datasets

Axel Levy, Rishwanth Raghu, J. Ryan Feathers, Michal R. Grzadkowski, Frédéric Poitevin, Jake D. Johnston, Francesca Vallese, Oliver B. Clarke, Gordon Wetzstein, Ellen D. Zhong

The paper introduces cryoDRGN-AI, a method for ab initio 3D reconstruction of cryo-EM and cryo-ET datasets, revealing new conformational states and unresolved motions.

Nature Methods · Jun 26, 2025Peer-reviewedBiophysics