Uncovering structural ensembles from single-particle cryo-EM data using cryoDRGN

LF Kinman, BM Powell, ED Zhong, B Berger… - Nature protocols, 2023 - nature.com
Single-particle cryogenic electron microscopy (cryo-EM) has emerged as a powerful
technique to visualize the structural landscape sampled by a protein complex. However …

Conformational heterogeneity and probability distributions from single-particle cryo-electron microscopy

WS Tang, ED Zhong, SM Hanson, EH Thiede… - Current Opinion in …, 2023 - Elsevier
Single-particle cryo-electron microscopy (cryo-EM) is a technique that takes projection
images of biomolecules frozen at cryogenic temperatures. A major advantage of this …

CryoDRGN-ET: deep reconstructing generative networks for visualizing dynamic biomolecules inside cells

R Rangan, R Feathers, S Khavnekar, A Lerer… - Nature …, 2024 - nature.com
Advances in cryo-electron tomography (cryo-ET) have produced new opportunities to
visualize the structures of dynamic macromolecules in native cellular environments. While …

Methods for cryo-EM single particle reconstruction of macromolecules having continuous heterogeneity

B Toader, FJ Sigworth, RR Lederman - Journal of molecular biology, 2023 - Elsevier
Macromolecules change their shape (conformation) in the process of carrying out their
functions. The imaging by cryo-electron microscopy of rapidly-frozen, individual copies of …

MDSPACE: Extracting continuous conformational landscapes from Cryo-EM single particle datasets using 3D-to-2D flexible fitting based on molecular dynamics …

R Vuillemot, A Mirzaei, M Harastani… - Journal of Molecular …, 2023 - Elsevier
This article presents an original approach for extracting atomic-resolution landscapes of
continuous conformational variability of biomolecular complexes from cryo electron …

Generative Models for Inverse Imaging Problems: From mathematical foundations to physics-driven applications

Z Zhao, JC Ye, Y Bresler - IEEE Signal Processing Magazine, 2023 - ieeexplore.ieee.org
Physics-informed generative modeling for inverse problems in computational imaging is a
fast-growing field encompassing a variety of methods and applications. Here, we review a …