Self-supervised learning for isotropic cryoET reconstruction
-
Updated
Jun 21, 2024 - Python
Self-supervised learning for isotropic cryoET reconstruction
ArtiaX is an open-source extension of the molecular visualisation program ChimeraX.
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
A curated list of awesome computational cryo-ET methods.
TomoBEAR is a configurable and customizable modular pipeline for streamlined processing of cryo-electron tomographic data for subtomogram averaging.
Self-supervised deep learning for denoising and missing wedge reconstruction of cryo-ET tomograms
TomoNet is a GUI based pipeline package focusing on cryoET and STA data processing
Toolbox for post-correlation cryo-CLEM workflow developed at Chlanda Lab, Heidelberg University.
PyTorch implementation of "Open-set Recognition of Unseen Macromolecules in Cellular Electron Cryo-Tomograms by Soft Large Margin Centralized Cosine Loss"
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.
Denoising and segmentation networks for cryoET based on U-net architecture implemented in Pytorch
Cellular content mining and particle localization
Python scritps for rendering and distance analysis of proteins (proteasome) and segmentations (poly-GA aggregates) in Cryo-ET
A tool to normalize CryoET data by matching amplitude spectrums.
2D NN-based particle picking from sparse labels
Add a description, image, and links to the cryo-et topic page so that developers can more easily learn about it.
To associate your repository with the cryo-et topic, visit your repo's landing page and select "manage topics."