Self-supervised learning for isotropic cryoET reconstruction

A curated list of awesome computational cryo-ET methods.

Self-supervised deep learning for denoising and missing wedge reconstruction of cryo-ET tomograms

deep structural disentanglement

cryo-ET particle picking by representation and metric learning

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).

Python tool for visualising and interacting with cryo-ET and subtomogram averaging data.

TomoBEAR is a configurable and customizable modular pipeline for streamlined processing of cryo-electron tomographic data for subtomogram averaging.

TomoNet is a GUI based pipeline package focusing on cryoET and STA data processing

IsoNet at higher resolution

Two-Dimensional Template Matching implemented in Python

Cryo-EM/ET image analysis

Cellular content mining and particle localization

structural heterogeneity analysis for cryo-ET subtomogram

Prompt-based segmentation and fine-tuning for data-efficient and flexible particle picking in cryo-ET tomograms

Web-interface for nextPYP

F2FD-TTT: Test-time training with self-supervised Fourier-to-Fourier denoising for membrane segmentation in cryo-ET tomograms

Search for Protein 3D Coordinates in CryoET Tomograms

PyTorch implementation of "Open-set Recognition of Unseen Macromolecules in Cellular Electron Cryo-Tomograms by Soft Large Margin Centralized Cosine Loss"