❄️ diff-em: Differentiable Cryo-EM Fitting in JAX
diff-em provides high-performance, auto-differentiable kernels for fitting atomic structures into Cryo-EM density maps. Built on JAX, it enables gradient-based optimization of coordinates directly against 3D experimental data.
🎯 Features
- Gaussian Mixture Volumes: Represent atomic models as differentiable 3D density maps using sum-of-Gaussians (electrostatic potential approximation).
- Cross-Correlation Kernels: Differentiable computation of map-to-model correlation coefficients (CC) for structural refinement (Rossmann, 2000).
- Optimization Strategy: Compatible with multi-resolution fitting and neural density fields (Zhong et al., 2021).
- Hardware Acceleration: Optimized for GPU/TPU execution via XLA, enabling the fitting of large complexes in seconds.
📚 Tutorials
Experience diff-em directly in your browser:
Cryo-EM Density Fitting — Learn how to optimize atomic coordinates directly against 3D density maps using cross-correlation.
🏗️ Technical Architecture
- Backend: JAX (XLA-compiled).
- Physics: 3D Gaussian placement with B-factor smoothing.
- Optimization: Pure JAX implementation compatible with
optaxfor high-dimensional gradient descent.
🧪 Scientific Validation
- Density Parity: Simulated densities are verified against standard EM map generation tools (e.g.,
gemmiorChimeraX). - CC Gradient Stability: Verified numerically stable gradients for structural refinement in the presence of noise.
- Resolution Limits: Benchmarked against known high-resolution and low-resolution experimental maps.
🚀 Roadmap
- Differentiable 3D Gaussian density kernels.
- Cross-correlation (CC) loss functions.
- Integration with MRC map loaders.
- Automated multi-resolution refinement schedules.
🔗 Related Projects
diff-em is part of the differentiable biophysics ecosystem:
- diff-biophys — Core differentiable biophysics engine.
- diff-hdx — Differentiable HDX-MS prediction.
- synth-cryo-em — Cryo-EM simulation.
📖 Citation
@software{diff_em,
author = {Elkins, George},
title = {diff-em: Differentiable Cryo-EM map fitting in JAX},
year = {2026},
url = {https://github.com/elkins-lab/diff-em},
version = {0.1.2}
}
⚖️ License
MIT
Metadata
Release files for diff-em 0.1.2
For a detailed explanation of source distributions (sdists) and built distributions (wheels), please see the package formats documentation.
Source distribution (sdist)
| File | Size | Uploaded | Provenance | Actions |
|---|---|---|---|---|
| diff_em-0.1.2.tar.gz | 7.1 kB | With provenance | Details for diff_em-0.1.2.tar.gz |
Built distribution (wheel)
| File | Interpreter | ABI | Platform | Actions Reset |
|---|---|---|---|---|
| diff_em-0.1.2-py3-none-any.whl | Python 3 | none | any | Details for diff_em-0.1.2-py3-none-any.whl |
Total release size: 12.1 kB
Release files / diff_em-0.1.2.tar.gz
| Download URL | diff_em-0.1.2.tar.gz |
|---|---|
| Size | 7.1 kB |
| Tags | Source |
|
SHA-256 checksum How to use checksums |
e1503960b5a5adcf4b52aebb1608c558da3d3283a5dedb7c3bd5d5c0ef9e5b36
|
|
BLAKE2b-256 checksum How to use checksums |
70ea3d5c5e43143ceaa58788489b15df81040c8611bb9467c0e5f559e0f3a102
|
| Upload date | |
|
Uploaded using Trusted Publishing? What is trusted publishing? |
Yes |
| Uploaded via |
twine/6.1.0 CPython/3.13.12
|
Provenance
Provenance describes where a file came from. On PyPI, provenance is shared via attestations, which provide a verifiable record of the build or publishing details. View details, limitations and caveats.
PyPI Publish Attestation
PyPI verified that this artifact, at this checksum, originated from the publisher listed below.
Signed by GitHub Actions, verified by PyPI on Jun 30, 2026.
Transparency logRelease files / diff_em-0.1.2-py3-none-any.whl
| Download URL | diff_em-0.1.2-py3-none-any.whl |
|---|---|
| Size | 5.0 kB |
| Tags | Python 3 |
|
SHA-256 checksum How to use checksums |
e19c338d804e11661fdaa10b84fdbac1e4f4fd07de4ea77b53e6089f541b0fef
|
|
BLAKE2b-256 checksum How to use checksums |
b20a22fef75026907c031146967e26b5592cad78d69818a568492d8569968f05
|
| Upload date | |
|
Uploaded using Trusted Publishing? What is trusted publishing? |
Yes |
| Uploaded via |
twine/6.1.0 CPython/3.13.12
|
Provenance
Provenance describes where a file came from. On PyPI, provenance is shared via attestations, which provide a verifiable record of the build or publishing details. View details, limitations and caveats.
PyPI Publish Attestation
PyPI verified that this artifact, at this checksum, originated from the publisher listed below.
Signed by GitHub Actions, verified by PyPI on Jun 30, 2026.
Transparency logSecurity for diff-em 0.1.2
Provenance
Provenance describes where a file came from. On PyPI, provenance is shared via attestations, which provide a verifiable record of the build or publishing details. View details, limitations and caveats.
Full provenance
Both files in this release have been uploaded with provenance metadata.
Attestation for diff_em-0.1.2.tar.gz
PyPI Publish Attestation
PyPI verified that this artifact, at this checksum, originated from the publisher listed below.
Signed by GitHub Actions, verified by PyPI on Jun 30, 2026.
Transparency logA note on package security
PyPI is a repository for distributing packages, not a service for auditing them. While third-party security researchers and our staff do their best to detect and remove malicious packages, PyPI cannot guarantee the quality, security or suitability of any given package.
To learn more about protecting yourself from malicious actors, visit our package security documentation.