Author

Daniel F. Ratner

SLAC National Accelerator LaboratoryORCID 0000-0002-5747-7323Unclaimed 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· 1 Approach:deep learning· 1 Research Focus:protein structure prediction· 1 Approach:statistical model· 1

Frequent Co-Authors

Ariana PeckiD· 1 shared Axel LevyiD· 1 shared Frédéric PoiteviniD· 1 shared Gordon WetzsteiniD· 1 shared Huanghao MaiiD· 1 shared Julien MarteliD· 1 shared Nina MiolaneiD· 1 shared Youssef S. G. NashediD· 1 shared

Activity by Year

2025-2025 · peak 1/yr

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8 top collaborators · 28 mutual co-author links

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1 shared paperBiophysics

Ariana PeckORCID

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1 paper

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