RISK Network Publication

Caution

This repository is designed to work with risk-network==0.0.11, the version submitted for publication. To ensure compatibility with these notebooks and figures, please run:

pip install risk-network==0.0.11

This repository provides Jupyter notebooks and datasets necessary to reproduce all figures from the RISK and SAFE analyses described in:

Horecka et al., "RISK: a next-generation tool for biological network annotation and visualization", Bioinformatics, 2025.
DOI: 10.1234/zenodo.xxxxxxx

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Documentation

Full documentation (with examples and usage guidance) is available at https://riskportal.github.io/network-tutorial/.

Repository Structure

This repository contains the notebooks and data needed to reproduce figures from the RISK and SAFE analyses. The full RISK source code is available at riskportal/network.

risk_network/

Jupyter notebooks and processed datasets for RISK-based clustering, annotation, and visualization:

• fig_1_supp_fig_3_6_7_8.ipynb – Yeast PPI network analysis, RISK workflow overview, GO BP enrichment, and comparison to SAFE
• supp_fig_1_4.ipynb – GI network analysis (RISK) and side-by-side comparison with SAFE
• supp_fig_2_5.ipynb – RISK analysis of the full yeast PPI network and comparative clustering (RISK vs SAFE)
• supp_fig_9.ipynb – RISK analysis of a high-energy physics citation network (non-biological validation)
• supp_fig_10.ipynb, supp_fig_10.py – Benchmarking: execution time and memory usage for RISK (vs SAFE) using synthetic networks

safe_network/

Jupyter notebooks and datasets for SAFE-based overrepresentation analysis and benchmarking:

• supp_fig_3_4_5.ipynb – SAFE-based annotation and domain export for GI and PPI networks, including pruned/full networks
• supp_fig_10.ipynb, supp_fig_10.py – Benchmarking: execution time and memory usage for SAFE (vs RISK) on synthetic networks
• safepy/ – Lightweight Python implementation of SAFE, includes core logic and utilities

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Installation

To run the notebooks locally, follow these steps:

Step 1: Install Python 3.8+

Download and install Python 3.8 or higher from the official website.

💡 Windows Tip: Check the box for Add Python to PATH during install. If you missed it, this guide can help.

Step 2: Create a Virtual Environment

• Windows

python -m venv risk-env
risk-env\Scripts\activate

• macOS/Linux

python3 -m venv risk-env
source risk-env/bin/activate

Step 3: Install Jupyter and Dependencies

pip install -r requirements.txt
pip install jupyter

Step 4: Clone This Repository

git clone https://github.com/riskportal/network-publication.git
cd network-publication

Step 5: Launch Jupyter Notebook

jupyter notebook

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Figure Reproduction

Use the following notebooks to regenerate all manuscript figures:

RISK Figures

• fig_1_supp_fig_3_6_7_8.ipynb – Yeast PPI network annotation and layout
• supp_fig_1_4.ipynb – GI network module analysis
• supp_fig_2_5.ipynb – PPI comparisons (RISK vs SAFE)
• supp_fig_9.ipynb – Citation network validation
• supp_fig_10.ipynb – Benchmarking RISK vs SAFE

SAFE Figures

• supp_fig_3_4_5.ipynb – SAFE-based GO BP overrepresentation (GI and PPI)
• supp_fig_10.ipynb – Benchmarking SAFE (comparative execution time, memory usage)

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Citation

If you use RISK or SAFE benchmarking in your research, please reference the following:

Horecka et al., "RISK: a next-generation tool for biological network annotation and visualization", 2025.
DOI: 10.1234/zenodo.xxxxxxx

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License

This repository is distributed under the GNU General Public License v3.0.