ff_energy

Crates.ioff_energy
lib.rsff_energy
version0.3.0
created_at2025-10-01 11:06:08.822383+00
updated_at2026-01-14 08:15:17.966181+00
descriptionfuzzyfold's nearest neighbor free energy evaluations.
homepage
repositoryhttps://github.com/bad-ants-fleet/fuzzyfold
max_upload_size
id1862372
size3,093,751
Stefan Badelt (bad-ants-fleet)

documentation

https://docs.rs/ff_energy

README

The fuzzyfold workspace

License: MIT fuzzyfold ff_structure ff_energy ff_kinetics Contributions welcome

An open-source collection of nucleic acid folding algorithms.

Note: This is a very early stage, rapidly developing coding project. You are welcome to use it for research, but be prepared for frustration from drastic interface changes. You may use GitHub issues for suggestions, but you are also welcome to reach out directly at this point.

Current fuzzyfold software

  • ff-eval: Free-energy evaluation for secondary structures.
  • ff-trajectory: Single stochastic nucleic acid folding trajectories.
  • ff-timecourse: Stochastic nucleic acid secondary structure ensemble simulations.
  • ff-randseq: Generate a random sequence.
  • ff-locmin: Enumerate secondary structure neighborhoods.

(Other software is work in progress and not yet published to crates.io)

Current fuzzyfold crates

  • ff_structure: Nucleic acid secondary structure data structures.
  • ff_energy: Secondary structure free energy evaluation.
  • ff_kinetics: Stochastic folding kinetics for nucleic acids.

(Other crates are work in progress and not yet published to crates.io)

Developer notes

Thank you for considering contributing! The goal of the fuzzyfold workspace is to provide a coherent, well-documented ecosystem for RNA and DNA secondary-structure modeling, kinetic simulations, and analysis. Each crate focuses on a clearly separated aspect of the workflow: structure, energy evaluation, and/or kinetic modeling.

We welcome improvements of any kind, from bug fixes and performance enhancements to documentation, examples, and new features. Feel free to reach out with specific ideas.

For benchmarking of the stochastic simulation algorithm:

cargo bench --workspace

Git branches (work in progress)

  • main: well-structured, well-documented, high-coverage, publication-ready code.

  • development: well-integrated, some documentation, some coverage, experimental code.

  • dev_feature: early code/crate proposals.

Commit count: 108

cargo fmt