Self-supervised learning for isotropic cryoET reconstruction
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Updated
Feb 13, 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
TomoNet is a GUI based pipeline package focusing on cryoET and STA data processing
ArtiaX is an open-source extension of the molecular visualisation program ChimeraX.
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.
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.
Python scritps for rendering and distance analysis of proteins (proteasome) and segmentations (poly-GA aggregates) in Cryo-ET
Python scripts to quantiatively describe Arp2/3 complex organization on travelling Actin Waves
Cellular content mining and particle localization
Python package for segmentation and analysis of Cryo-ET
A tool to normalize CryoET data by matching amplitude spectrums.
2D NN-based particle picking from sparse labels
Plugin to run MemBrain software within Scipion
Some scripts to facilitate subtomogram-averaging workflows.
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