AIMC Topic: Cryoelectron Microscopy

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Amortized template matching of molecular conformations from cryoelectron microscopy images using simulation-based inference.

Proceedings of the National Academy of Sciences of the United States of America Jun 4, 2025
Characterizing the conformational ensemble of biomolecular systems is key to understand their functions. Cryoelectron microscopy (cryo-EM) captures two-dimensional snapshots of biomolecular ensembles, giving in principle access to thermodynamics. How...
Models, Molecular Bayes Theorem Molecular Conformation Cryoelectron Microscopy Neural Networks, Computer Deep Learning Computer Simulation Image Processing, Computer-Assisted
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Advancing Molecular Simulations: Merging Physical Models, Experiments, and AI to Tackle Multiscale Complexity.

The journal of physical chemistry letters Apr 3, 2025
Proteins and protein complexes form adaptable networks that regulate essential biochemical pathways and define cell phenotypes through dynamic mechanisms and interactions. Advances in structural biology and molecular simulations have revealed how pro...
Machine Learning Protein Conformation Cryoelectron Microscopy Proteins Molecular Dynamics Simulation
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A review of denoising methods in single-particle cryo-EM.

Micron (Oxford, England : 1993) Mar 29, 2025
Cryo-EM has become a vital technique for resolving macromolecular structures at near-atomic resolution, enabling the visualization of proteins and large molecular complexes. However, the images are often accompanied by extremely low SNR, which poses ...
Single Molecule Imaging Deep Learning Image Processing, Computer-Assisted Cryoelectron Microscopy Macromolecular Substances Proteins Imaging, Three-Dimensional Signal-To-Noise Ratio
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Fitting Atomic Structures into Cryo-EM Maps by Coupling Deep Learning-Enhanced Map Processing with Global-Local Optimization.

Journal of chemical information and modeling Mar 28, 2025
With the breakthroughs in protein structure prediction technology, constructing atomic structures from cryo-electron microscopy (cryo-EM) density maps through structural fitting has become increasingly critical. However, the accuracy of the construct...
Cryoelectron Microscopy Models, Molecular Protein Conformation Deep Learning Proteins
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FakET: Simulating cryo-electron tomograms with neural style transfer.

Structure (London, England : 1993) Feb 12, 2025
In cryo-electron microscopy, accurate particle localization and classification are imperative. Recent deep learning solutions, though successful, require extensive training datasets. The protracted generation time of physics-based models, often emplo...
Electron Microscope Tomography Algorithms Software Image Processing, Computer-Assisted Deep Learning Cryoelectron Microscopy
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Advancing structure modeling from cryo-EM maps with deep learning.

Biochemical Society transactions Feb 7, 2025
Cryo-electron microscopy (cryo-EM) has revolutionized structural biology by enabling the determination of biomolecular structures that are challenging to resolve using conventional methods. Interpreting a cryo-EM map requires accurate modeling of the...
Protein Conformation Cryoelectron Microscopy Proteins Models, Molecular Deep Learning
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AI-based methods for biomolecular structure modeling for Cryo-EM.

Current opinion in structural biology Jan 27, 2025
Cryo-electron microscopy (Cryo-EM) has revolutionized structural biology by enabling the determination of macromolecular structures that were challenging to study with conventional methods. Processing cryo-EM data involves several computational steps...
Cryoelectron Microscopy Models, Molecular Artificial Intelligence Macromolecular Substances Deep Learning
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Deciphering Protein Secondary Structures and Nucleic Acids in Cryo-EM Maps Using Deep Learning.

Journal of chemical information and modeling Jan 21, 2025
With the resolution revolution of cryo-electron microscopy (cryo-EM) and the rapid development of image processing technology, cryo-EM has become an indispensable experimental method for determining the three-dimensional structures of biological macr...
Deep Learning Proteins Models, Molecular Protein Structure, Secondary Nucleic Acids Cryoelectron Microscopy
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Overcoming the preferred-orientation problem in cryo-EM with self-supervised deep learning.

Nature methods Nov 18, 2024
While advances in single-particle cryo-EM have enabled the structural determination of macromolecular complexes at atomic resolution, particle orientation bias (the 'preferred' orientation problem) remains a complication for most specimens. Existing ...
Imaging, Three-Dimensional Image Processing, Computer-Assisted Software Algorithms Anisotropy Macromolecular Substances Deep Learning Ribosomes Cryoelectron Microscopy
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Deep Spatio-Temporal Network for Low-SNR Cryo-EM Movie Frame Enhancement.

IEEE/ACM transactions on computational biology and bioinformatics Oct 9, 2024
Cryo-EM in single particle analysis is known to have low SNR and requires to utilize several frames of the same particle sample to restore one high-quality image for visualizing that particle. However, the low SNR of cryo-EM movie and motion caused b...
Image Processing, Computer-Assisted Algorithms Cryoelectron Microscopy Signal-To-Noise Ratio Neural Networks, Computer Deep Learning
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