The One World Cryo-EM seminar series is a platform for discussion of algorithms, computational methods and mathematical problems in cryo-EM.

Online, Every Other Wednesday, at 8am PT / 11am ET/ 4pm BST / 5pm CET / 11pm China.

Registration has changed. For zoom links and announcements, please register to our mailing list. This is a read-only mailing list (users cannot post). Please use your institution/ company email – we approve registrations manually and this helps us know who you are . You may receive an email asking you to confirm your registration, it is important that you click the link, otherwise we will not see your request.

Organizers: Joakim Andén, Dorit Hanein, Roy R. Lederman and Steven J. Ludtke

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Next Talk

Quanquan Gu

Head of AI for Drug Design, ByteDance Research

Date and time: Mar 6th, 2024
Wednesday, at 8am PST / 11am EST / 4pm GMT / 5pm CET / 12am China

For the zoom and links, please join the One World Cryo-EM mailing list.

CryoSTAR: Leveraging Structural Prior and Constraints for Cryo-EM Heterogeneous Reconstruction

Resolving conformational heterogeneity in cryo-electron microscopy (cryo-EM) datasets remains a significant challenge in structural biology. Previous methods have often been restricted to working exclusively on volumetric densities, neglecting the potential of incorporating any pre-existing structural knowledge as prior or constraints. In this talk, I will present a novel methodology, cryoSTAR, that harnesses atomic model information as structural regularization to elucidate such heterogeneity. Our method uniquely outputs both coarse-grained models and density maps, showcasing the molecular conformational changes at different levels. Validated against four diverse experimental datasets, spanning large complexes, a membrane protein, and a small single-chain protein, our results consistently demonstrate an efficient and effective solution to conformational heterogeneity with minimal human bias. By integrating atomic model insights with cryo-EM data, cryoSTAR represents a meaningful step forward, paving the way for a deeper understanding of dynamic biological processes. This is joint work with Yilai Li, Yi Zhou, Jing Yuan and Fei Ye.

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Last Talk

Marc A. Gilles

Postdoctoral Research Associate, Program in Applied & Computational Mathematics, Princeton University

Date and time: Dec 6th, 2023
Wednesday, at 8am PST / 11am EST / 4pm GMT / 5pm CET / 12am China

For the zoom and links, please join the One World Cryo-EM mailing list.

A Bayesian Framework for Cryo-EM Heterogeneity Analysis using Regularized Covariance Estimation

Proteins and the complexes they form are central to nearly all cellular processes. Their flexibility, expressed through a continuum of states, provides a window into their biological functions. Cryogenic-electron microscopy (cryo-EM) is an ideal tool to study these dynamic states as it captures specimens in non-crystalline conditions and enables high-resolution reconstructions. However, analyzing the heterogeneous distribution of conformations from cryo-EM data is challenging. Current methods face issues such as a lack of explainability, overfitting caused by lack of regularization, and a large number of parameters to tune; problems exacerbated by the lack of proper metrics to evaluate or compare heterogeneous reconstructions. To address these challenges, we present RECOVAR, a white-box method based on principal component analysis (PCA) computed via regularized covariance estimation that can resolve intricate heterogeneity with similar expressive power to neural networks with significantly lower computational demands.