# A complete data processing workflow for CryoET and subtomogram averaging

arXiv: https://arxiv.org/abs/1902.03978 · HTML: https://mlsanity.com/paper/1902.03978/

## Key facts

- Cited by 5 papers in the map (data through 14 Oct 2026).
- First posted on arXiv 11 Feb 2019.

## Built on by (most cited first, 5 of 5)

- [SparseAlign: A Super-Resolution Algorithm for Automatic Marker Localization and Deformation Estimation in Cryo-Electron Tomography](https://mlsanity.com/paper/2201.08706/) (2022)
- [DualContrast: Unsupervised Disentangling of Content and Transformations with Implicit Parameterization](https://mlsanity.com/paper/2405.16796/) (2024)
- [Solving ill-conditioned polynomial equations using score-based priors with application to multi-target detection](https://mlsanity.com/paper/2509.11397/) (2025)
- [Towards Foundation Models for Cryo-ET Subtomogram Analysis](https://mlsanity.com/paper/2509.24311/) (2025)
- [Unsupervised SE(3) Disentanglement for in situ Macromolecular Morphology Identification from Cryo-Electron Tomography](https://mlsanity.com/paper/2601.01364/) (2026)

## Abstract (arXiv)

Electron cryotomography (CryoET) is currently the only method capable of visualizing cells in 3D at nanometer resolutions. While modern instruments produce massive amounts of tomography data containing extremely rich structural information, the data processing is very labor intensive and results are often limited by the skills of the personnel rather than the data. We present an integrated workflow that covers the entire tomography data processing pipeline, from automated tilt series alignment to subnanometer resolution subtomogram averaging. This workflow greatly reduces human effort and increases throughput, and is capable of determining protein structures at state-of-the-art resolutions for both purified macromolecules and cells.