Author

Huanghao Mai

Astera InstituteORCID 0000-0003-2278-0768Unclaimed ORCID profile · follow to get notified of new preprints

Biology Disciplines

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Signature Assays, Organisms & Methods

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Approach:deep learning· 2 Research Focus:protein structure prediction· 2 Assay:cryo-EM· 1 Research Focus:drug response / drug discovery· 1 Assay:protein structure· 1 Approach:statistical model· 1 Approach:transformer / foundation model· 1

Frequent Co-Authors

Ariana PeckiD· 1 shared Axel LevyiD· 1 shared Daniel F. RatneriD· 1 shared Frédéric PoiteviniD· 1 shared Gordon WetzsteiniD· 1 shared James M. HoltoniD· 1 shared Julien MarteliD· 1 shared Marcus D. CollinsiD· 1 shared

Activity by Year

2025-2026 · peak 1/yr

Co-Author Collaboration Network

10 top collaborators · 24 mutual co-author links

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1 shared paperBiophysics

Ariana PeckORCID

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2 papers

Recent·Most cited

BiophysicsbioRxivPreprintAug 27, 2026

WaterFlow: Prediction of Ordered Water Molecule Positions on Protein Structures

Vratin Srivastava, Huanghao Mai, Marcus D. Collins…·Stephanie A. M. Wankowicz

WaterFlow predicts ordered water molecule positions in protein structures with sub-angstrom accuracy, outperforming existing methods and improving drug design and crystallographic refinement.

DOI 10.64898/2026.08.26.747373

protein structuredeep learning

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BiophysicsbioRxivPreprintJul 27, 2025

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…·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.

DOI 10.1101/2025.07.27.666683

cryo-EMdeep learning

𝕏 PostBluesky