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📏 diff-fret: Differentiable FRET Modeling in JAX\n\n[![Tests](https://github.com/elkins/diff-fret/actions/workflows/test.yml/badge.svg)](https://github.com/elkins/diff-fret/actions/workflows/test.yml)\n[![License: MIT](https://img.shields.io/badge/License-MIT-yellow.svg)](https://opensource.org/licenses/MIT)\n[![JAX](https://img.shields.io/badge/backend-JAX-9cf.svg)](https://github.com/google/jax)\n\n**diff-fret** provides high-performance, auto-differentiable kernels for modeling Fluorescence Resonance Energy Transfer (FRET) observables from structural ensembles.\n\n---\n\n## 🎯 Features\n\n- **Differentiable Distance Distributions:** Compute donor-acceptor distance distributions ($P(r)$) from atomic coordinates.\n- **Förster Theory Integration:** Map distances to FRET efficiency ($E$) using parameterizable Förster distances ($R_0$).\n- **Orientation Uncertainty:** Calculate bounds for the orientation factor $\\kappa^2$ using fluorescence anisotropy (Dale, Eisinger, \u0026 Blumberg, 1979).\n- **Ensemble Averaging:** Native support for JAX `vmap` to average efficiency across conformational ensembles.\n- **Hardware Acceleration:** Optimized for GPU/TPU execution via XLA.\n\n---\n\n## 📚 Tutorials\n\nExperience **diff-fret** directly in your browser:\n\n- [![Open In Colab](https://colab.research.google.com/assets/colab-badge.svg)](https://colab.research.google.com/github/elkins/diff-fret/blob/main/examples/interactive_tutorials/fret_efficiency_tutorial.ipynb) **FRET Efficiency \u0026 Accessible Volumes** — Learn how to simulate Förster curves and perform AV simulations for flexible dyes.\n\n---\n\n## 🏗️ Technical Architecture\n\n- **Backend:** JAX (XLA-compiled).\n- **Kernels:** Vectorized distance and efficiency functions.\n- **Differentiability:** Support for gradient descent refinement of probe positions or protein conformations.\n\n---\n\n## 🚀 Roadmap\n\n- [x] Core Förster efficiency kernels.\n- [x] Ensemble averaging support.\n- [x] Orientation factor ($\\kappa^2$) modeling (Dale–Eisinger–Blumberg bounds).\n- [ ] Integration with dye rotamer libraries.\n\n---\n\n## 🚀 Installation\n\n```bash\npip install diff-fret\n```\n\n## 🧪 Scientific Validation\n\n- **Förster Limit:** Efficiency kernels are verified to match the $1/(1 + (r/R_0)^6)$ analytical solution.\n- **Auto-Diff Stability:** Reverse-mode gradients are tested for stability in the $r \\approx R_0$ region.\n- **Ensemble Benchmarks:** Average efficiency calculation validated against Monte Carlo simulations.\n\n---\n\n## 🔗 Related Projects\n\ndiff-fret is part of the **differentiable biophysics** ecosystem:\n\n- [diff-biophys](https://github.com/elkins/diff-biophys) — Core differentiable biophysics engine.\n- [diff-hdx](https://github.com/elkins/diff-hdx) — Differentiable HDX-MS prediction.\n- [diff-epr](https://github.com/elkins/diff-epr) — Differentiable EPR/DEER simulation.\n- [synth-dynamics](https://github.com/elkins/synth-dynamics) — Protein dynamics simulation.\n\n---\n\n## 📖 Citation\n\n```bibtex\n@software{diff_fret,\n  author  = {Elkins, George},\n  title   = {diff-fret: Differentiable FRET modeling in JAX},\n  year    = {2026},\n  url     = {https://github.com/elkins/diff-fret},\n  version = {0.1.0}\n}\n```\n\n## ⚖️ License\n\nMIT\n","project_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Felkins-lab%2Fdiff-fret","html_url":"https://awesome.ecosyste.ms/projects/github.com%2Felkins-lab%2Fdiff-fret","lists_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Felkins-lab%2Fdiff-fret/lists"}