https://github.com/adicksonlab/wepy-analysis
Analysis tools for wepy simulations
https://github.com/adicksonlab/wepy-analysis
Last synced: 28 days ago
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Analysis tools for wepy simulations
- Host: GitHub
- URL: https://github.com/adicksonlab/wepy-analysis
- Owner: ADicksonLab
- License: mit
- Created: 2025-06-13T17:47:10.000Z (8 months ago)
- Default Branch: main
- Last Pushed: 2025-07-31T14:50:18.000Z (7 months ago)
- Last Synced: 2025-09-08T23:58:06.167Z (5 months ago)
- Language: Python
- Size: 59.6 KB
- Stars: 1
- Watchers: 0
- Forks: 1
- Open Issues: 0
-
Metadata Files:
- Readme: README.md
- License: LICENSE
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README
# WepyAnalysis
WepyAnalysis is a modular toolkit for analyzing data generated from Weighted Ensemble (WE) simulations using the [Wepy](https://github.com/ADicksonLab/wepy) framework.
The codebase is organized into five main components:
- `featurization/`: Tools for extracting structural features from WE data
- `dataset/`: Code for generating datasets from WE data
- `msm/`: Building Markov State Models (MSMs) and performing kinetic analysis
- `example/`: Example scripts for running simulations with Wepy and building MSMs
This repository is under active development and intended for researchers working with WE data, especially those using the Wepy framework.
## Installation
We recommend installing WepyAnalysis with a Python package manager such as conda or mamba. The package is tested and fully compatible with ```Python 3.12```, and we strongly encourage using ```python>=3.10``` for compatibility.
```
conda create -n wepy-analysis python=3.12
conda activate wepy-analysis
```
Once your python environment is ready, `wepy-analysis` can be installed with `pip` as follows:
```
pip install git+https://github.com/ADicksonLab/wepy-analysis
```
which will also install all dependencies. The installation procedure takes less than a minute to complete at a local desktop.
## Dependencies:
```
Wepy (https://github.com/ADicksonLab/wepy) >= 1.2
geomm (https://github.com/ADicksonLab/geomm) >= 0.3
csnanalysis (https://github.com/ADicksonLab/CSNAnalysis) >= 0.6.0
numpy >= 2.3.1
scipy >= 1.16.0
h5py >= 3.14.0
mdtraj >= 1.11.0
scikit-learn >= 1.7.0
deeptime >= 0.4.5
```
## More Information
- Example dataset files can be found at current [Zenodo DOI](https://zenodo.org/records/15361245)
- This repository is a part of the preprint ["Determinants of Improved CGRP Peptide Binding Kinetics Revealed by Enhanced Molecular Simulations"](https://www.biorxiv.org/content/10.1101/2025.06.13.659569v1) and can be used to build MSMs explained in the paper.