cryoet

Self-supervised learning for isotropic cryoET reconstruction

A curated list of awesome computational cryo-ET methods.

IsoNet at higher resolution

🍦Icecream: a self-supervised framework for cryo-ET reconstruction

Definitions for a collaborative cryoET annotation tool.

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 tool for using surfaces to explore volumetric data in napari

A tool to support interactive machine learning for cryoET data

A Docker-based distribution of Appion-Protomo.

Scaling data analyses in cellular cryoET using comprehensive segmentation.

.MRC and .EM thumbnailer for GNOME

Album catalog of CellCanvas workflow solutions

A collaborative cryo-ET annotation tool

Napari plugin for CellCanvas interactive 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.

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

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.