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synth-cryo-em

A lightweight Pythonic utility to convert atomic models into synthetic 3D Cryo-EM maps.

Overview

synth-cryo-em is designed to bridge the gap between atomic coordinates (PDB/CIF) and realistic density maps used in Cryo-Electron Microscopy. It simulates the physical processes of image formation, including resolution effects, Contrast Transfer Function (CTF), and noise.

Why use synth-cryo-em?

  • ML Training: Generate thousands of labeled synthetic maps for training denoisers, pickers, and segmentors.
  • Education: Visualize how experimental parameters like resolution and defocus affect the resulting 3D density.
  • Validation: Test the robustness of structural biology algorithms against varied noise and resolution levels.

Scientific Basis

For details on the physical models and mathematical formulas used in this project, see our Scientific Foundations page.