Self-supervised learning for isotropic cryoET reconstruction
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Updated
Jun 21, 2024 - Python
Self-supervised learning for isotropic cryoET reconstruction
Pipeline for the automatic detection and segmentation of particles and cellular structures in 3D Cryo-ET data, based on deep learning (convolutional neural networks).
cryo-ET particle picking by representation and metric learning
Self-supervised deep learning for denoising and missing wedge reconstruction of cryo-ET tomograms
TomoBEAR is a configurable and customizable modular pipeline for streamlined processing of cryo-electron tomographic data for subtomogram averaging.
ArtiaX is an open-source extension of the molecular visualisation program ChimeraX.
TomoNet is a GUI based pipeline package focusing on cryoET and STA data processing
Denoising and segmentation networks for cryoET based on U-net architecture implemented in Pytorch
A napari plugin for the DeepFinder library which includes display, annotation, target generation, segmentation and clustering functionalities. An orthoslice view has been added for an easier visualisation and annotation process.
A curated list of awesome computational cryo-ET methods.
PyTorch implementation of "Open-set Recognition of Unseen Macromolecules in Cellular Electron Cryo-Tomograms by Soft Large Margin Centralized Cosine Loss"
A pipeline to detect domains in cryo-EM density map by parsing domains from AlphaFold databases and fitting into the map for the best hits.
MemBrain : Membrane segmentation in 3D for cryo-ET (by @teamtomo)
Subtomogram averaging tutorials
Python scripts to quantiatively describe Arp2/3 complex organization on travelling Actin Waves
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