Sparse Fourier Backpropagation in Cryo-EM Reconstruction

This repository contains code for the paper: Sparse Fourier Backpropagation in Cryo-EM Reconstruction. Part of Advances in Neural Information Processing Systems 35 (NeurIPS 2022) Main Conference Track.

Setup a conda environment

You need to setup a Python environment with dependencies. We recommend installing via Miniconda3.

Once you have conda setup, you can install all the Python dependencies into a new environment by running:

conda env create -f environment.yml

You can then activate the conda environment by running:

conda activate sbackprop

Compile and Install CUDA code

Once inside the correct environment you can compile and install the CUDA dependencies by running:

python setup.py install

Running Training

You can then run training by running

python voxelium/vae_volume/train.py <input STAR-file> <logdir> --gpu 0

Use -h for more options.

Visualizing Results

You can then visualize the results using

python voxelium/vae_volume/volume_explorer.py <logdir>

Citation

@article{kimanius2022sparse,
  title={Sparse fourier backpropagation in cryo-em reconstruction},
  author={Kimanius, Dari and Jamali, Kiarash and Scheres, Sjors},
  journal={Advances in Neural Information Processing Systems},
  volume={35},
  pages={12395--12408},
  year={2022}
}