Self-supervised learning for isotropic cryoET reconstruction

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.

A Modular Platform for Streamlining Automated Cryo-FIB Workflows

A Docker-based distribution of Appion-Protomo.

.MRC and .EM thumbnailer for GNOME

Scaling data analyses in cellular cryoET using comprehensive segmentation.

Subtomogram Averaging using Dynamo, imod, Relion and MatLab

This project builds machine learning models to automatically detect and classify protein complexes in cryo-electron tomography (cryoET) images, enabling scalable analysis of cellular structures and supporting advanced biological and medical research.

Docker environment for CryoET data analysis

Automated detection of protein complexes in cryo-electron tomography (cryoET) data. ML models identify five particle classes using a weighted F-β (β=4) metric focused on recall, especially for hard targets, helping reveal cellular “dark matter” and advance biological discovery.

Removing etomo skipped views from Warp xml files to improve the tomogram reconstruction.