Welcome to CryoLike’s documentation!

Note

This documentation is still under construction. If you have any questions, please contact the authors.

CryoLike is a Python library for a fast and accurate algorithm for computing the likelihood of cryo-EM images given a cryo-EM map or an atomic model. The algorithm is described in this bioRxiv paper https://www.biorxiv.org/content/10.1101/2024.10.18.619077v1

Note

This project is under active development.

Documentation Contents:

• Mathematical Framework
• Installation
• First Steps
• Concepts
  • Parameter setup: Image Descriptor
  • Template Creation
  • Image Conversion
  • File formats for image conversion
  • Image-to-Structure Likelihood Computation
  • File and Directory Structure
• Examples
  • Parameter-setting example
  • Make templates from cryo-EM maps or atomic models
  • Convert Particles
  • Run likelihood
  • Combine likelihoods
• Tutorials
  • Full CryoLike pipeline from models and images to likelihood matrix
  • Converting particles from CryoSPARC file formats
  • Converting particles from STAR file formats
• CryoLike Python API
  • cryolike.file_conversions
  • cryolike.grids
  • cryolike.likelihoods
  • cryolike.metadata
  • cryolike.microscopy
  • cryolike.stacks
  • cryolike.util