Metadata-Version: 2.1
Name: regdiffusion
Version: 0.0.4
Summary: Gene Regulatory Networks Inference using diffusion model
Author-email: Hao Zhu <haozhu233@gmail.com>, Donna Slonim <donna.slonim@tufts.edu>
Maintainer-email: Hao Zhu <haozhu233@gmail.com>
Description-Content-Type: text/markdown
Classifier: License :: OSI Approved :: Apache Software License
Requires-Dist: numpy>=1.16.5
Requires-Dist: pandas>=1.1.1
Requires-Dist: torch
Requires-Dist: tqdm
Requires-Dist: scanpy
Requires-Dist: scikit-learn
Requires-Dist: h5py
Project-URL: Home, https://github.com/TuftsBCB/RegDiffusion

# RegDiffusion: Probabilistic Diffusion-Based Neural Inference of Gene Regulatory Networks

Diffusion model has been widely used in generative AI, especially in the vision domain. In our paper, we proposed RegDiffusion, a diffusion based model for GRN inference. Compared with previous model, RegDiffusion completes inference within a fraction of time and yield better benchmarking results.

```
From Noise to Knowledge: Probabilistic Diffusion-Based Neural Inference of Gene Regulatory Networks
Hao Zhu, Donna K. Slonim
bioRxiv 2023.11.05.565675; doi: https://doi.org/10.1101/2023.11.05.565675
```

## Installation

RegDiffusion is on pypi.

```
pip install regdiffusion
```

Check out the [example notebook](https://github.com/TuftsBCB/RegDiffusion/blob/master/example.ipynb) for a quick tour of how to use RegDiffusion for your research!


