Unsupervised deep learning methods for biological image reconstruction and enhancement: An overview from a signal processing perspective

M Akçakaya, B Yaman, H Chung… - IEEE Signal Processing …, 2022 - ieeexplore.ieee.org
Recently, deep learning (DL) approaches have become the main research frontier for
biological image reconstruction and enhancement problems thanks to their high …

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 …

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 …

Emerging themes in CryoEM─ Single particle analysis image processing

JL Vilas, JM Carazo, COS Sorzano - Chemical Reviews, 2022 - ACS Publications
Cryo-electron microscopy (CryoEM) has become a vital technique in structural biology. It is
an interdisciplinary field that takes advantage of advances in biochemistry, physics, and …

DeepHEMNMA: ResNet-based hybrid analysis of continuous conformational heterogeneity in cryo-EM single particle images

I Hamitouche, S Jonic - Frontiers in Molecular Biosciences, 2022 - frontiersin.org
Single-particle cryo-electron microscopy (cryo-EM) is a technique for biomolecular structure
reconstruction from vitrified samples containing many copies of a biomolecular complex …

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 …

Deep generative modeling for volume reconstruction in cryo-electron microscopy

C Donnat, A Levy, F Poitevin, ED Zhong… - Journal of structural …, 2022 - Elsevier
Advances in cryo-electron microscopy (cryo-EM) for high-resolution imaging of biomolecules
in solution have provided new challenges and opportunities for algorithm development for …

Sensing theorems for unsupervised learning in linear inverse problems

J Tachella, D Chen, M Davies - Journal of Machine Learning Research, 2023 - jmlr.org
Solving an ill-posed linear inverse problem requires knowledge about the underlying signal
model. In many applications, this model is a priori unknown and has to be learned from data …

CryoPoseNet: End-to-end simultaneous learning of single-particle orientation and 3D map reconstruction from cryo-electron microscopy data

YSG Nashed, F Poitevin, H Gupta… - Proceedings of the …, 2021 - openaccess.thecvf.com
Cryogenic electron microscopy (cryo-EM) provides im-ages from different copies of the same
biomolecule in ar-bitrary orientations. Here, we present an end-to-end unsu-pervised …

Exploring the structural variability of dynamic biological complexes by single-particle cryo-electron microscopy

MC DiIorio, AW Kulczyk - Micromachines, 2022 - mdpi.com
Biological macromolecules and assemblies precisely rearrange their atomic 3D structures to
execute cellular functions. Understanding the mechanisms by which these molecular …