Cryogenic Electron Microscopy (cryo-EM)
10 papers with code • 0 benchmarks • 0 datasets
Analysis of images and videos from transmission electron microscopes, including single-particle cryogenic electron microscopy and cryogenic electron tomography (cryo-ET). https://en.wikipedia.org/wiki/Cryogenic_electron_microscopy
Benchmarks
These leaderboards are used to track progress in Cryogenic Electron Microscopy (cryo-EM)
Most implemented papers
Reconstructing continuous distributions of 3D protein structure from cryo-EM images
Cryo-electron microscopy (cryo-EM) is a powerful technique for determining the structure of proteins and other macromolecular complexes at near-atomic resolution.
Cryo-CARE: Content-Aware Image Restoration for Cryo-Transmission Electron Microscopy Data
Cryo-transmission electron microscopy (cryo-TEM) could profoundly benefit from improved denoising methods, unfortunately it is one of the latter.
Cryo-EM reconstruction of continuous heterogeneity by Laplacian spectral volumes
An important challenge in cryo-EM is the reconstruction of non-rigid molecules with parts that move and deform.
Sequence-guided protein structure determination using graph convolutional and recurrent networks
leeneil/structure-generator
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Single particle, cryogenic electron microscopy (cryo-EM) experiments now routinely produce high-resolution data for large proteins and their complexes.
Deep manifold learning reveals hidden dynamics of proteasome autoregulation
The 2. 5-MDa 26S proteasome maintains proteostasis and regulates myriad cellular processes.
Learning to automate cryo-electron microscopy data collection with Ptolemy
Automating this is non-trivial: the images suffer from low signal-to-noise ratio and are affected by a range of experimental parameters that can differ for each collection session.
A Molecular Prior Distribution for Bayesian Inference Based on Wilson Statistics
Furthermore, it improves the resolution of estimates on the problems considered for a wide range of SNR and produces Fourier Shell Correlation curves that are insensitive to masking effects.
AlignOT: An optimal transport based algorithm for fast 3D alignment with applications to cryogenic electron microscopy density maps
Aligning electron density maps from Cryogenic electron microscopy (cryo-EM) is a first key step for studying multiple conformations of a biomolecule.
EMPOT: partial alignment of density maps and rigid body fitting using unbalanced Gromov-Wasserstein divergence
Aligning EM density maps and fitting atomic models are essential steps in single particle cryogenic electron microscopy (cryo-EM), with recent methods leveraging various algorithms and machine learning tools.
Moment-based metrics for molecules computable from cryo-EM images
Further, we introduce a metric between a stack of projection images and a molecular structure, which is invariant to rotations and reflections and does not require performing 3-D reconstruction.
