abstract

Enhancing Cryo-EM Particle Picking Through Consistency Model-based Latent Space Denoiser

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BCB '23: Proceedings of the 14th ACM International Conference on Bioinformatics, Computational Biology, and Health Informatics

Article No.: 72, Page 1

https://doi.org/10.1145/3584371.3613030

Published: 04 October 2023 Publication History

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Abstract

Particle picking, which aims to select randomly oriented macro-molecular particles in cryo-electron microscopy (cryo-EM) images, is the first critical step to ensuring accurate reconstruction of highresolution three-dimensional molecular structures from noisy cryo-EM images. To date, various deep-learning techniques have been introduced for particle picking in cryo-EM with promising results. In this work, we propose a combination of two generative models, spatial variational autoencoder and latent space consistency model, together with a latent space classifier model to facilitate cryo-EM particle picking by removing false positive picked particles.

References

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Tristan Bepler, Ellen Zhong, Kotaro Kelley, Edward Brignole, and Bonnie Berger. 2019. Explicitly disentangling image content from translation and rotation with spatial-VAE. Advances in Neural Information Processing Systems 32 (2019).

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Bonnie Berger Ellen D. Zhong, Tristan Bepler and Joseph H. Davis. 2021. CryoDRGN: reconstruction of heterogeneous cryo-EM structures using neural networks. Nature Methods 18 (Jan. 2021), 176--185. Issue 2.

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Yang Song, Prafulla Dhariwal, Mark Chen, and Ilya Sutskever. 2023. Consistency Models. arXiv preprint arXiv:2303.01469 (2023).

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Ellen D. Zhong, Adam Lerer, Joseph H. Davis, and Bonnie Berger. 2021. CryoDRGN2: Ab Initio Neural Reconstruction of 3D Protein Structures From Real Cryo-EM Images. In Proceedings of the IEEE/CVF International Conference on Computer Vision (ICCV). 4066--4075.

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Published In

BCB '23: Proceedings of the 14th ACM International Conference on Bioinformatics, Computational Biology, and Health Informatics

September 2023

626 pages

ISBN:9798400701269

DOI:10.1145/3584371

General Chairs:
May D. Wang
SGeorgia Institute of Technology
,
Byung-Jun Yoon

Permission to make digital or hard copies of part or all of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for third-party components of this work must be honored. For all other uses, contact the owner/author(s).

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Association for Computing Machinery

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Published: 04 October 2023

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Department of Energy (DOE)

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BCB '23

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SIGBio

BCB '23: 14th ACM International Conference on Bioinformatics, Computational Biology, and Health Informatics

September 3 - 6, 2023

TX, Houston, USA

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A Method for Fully Automated Particle Picking in Cryo-Electron Microscopy Based on a CNN

Automatic Detection of Beta-barrel from Medium Resolution Cryo-EM Density Maps

Particle Picking Method for Cryo Electron Tomography Image Based on Active Learning

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