This is the Source Code and Data Repository of the SynGPS and BOYA Algorithms

1. Cite Us
2. Prerequisite
3. Installation
4. Case Study Reproduction
5. Post Publication Notes
6. For Contributors
7. License Related Section

Cite Us

Zahoránszky-Kőhalmi G, Walker B, Cole W, Miller N, Yang B, Vorontcov I, et al. Synthesis Route Identification and Prioritization in Reaction Knowledge Graphs. ChemRxiv. 2025; doi:10.26434/chemrxiv-2025-0s3jp This content is a preprint and has not been peer-reviewed.

Link to preprint

Prerequisite

Conda Python environment manager:

• For installation on your specific platform please refer to Conda official documentation.

Optional (not required, but nice to have):

• Git

Installation

Install SynGPS code as a Python package

The SynGPS code can be installed as a Python package using the following command:

pip install git+https://github.com/ncats/syngps.git

Clone this Git repository

git clone https://github.com/ncats/syngps

Enter into the subdirectory containing the source code.

cd syngps

If you want to utilize the publication branch of this repository, you can check out the publication branch using the following commands:

git fetch origin
git checkout -b publication origin/publication

To ensure you have the latest updates for this repository, you can use the following command:

git pull

Create the required Python environment via Conda

The conda environment for the SynGPS workflows can be created with the following commands:

cd workflows

conda env create -f environment.yml

Case Study Reproduction

The SynGPS library code required to reproduce the case studies is stored under subdirectory src. The workflows required to reproduce the case studies are stored under subdirectory workflows. The data required to reproduce the case studies is stored under subdirectory data.

Run the workflow in Jupyter Notebook in JupyterLab using the above created syngps Conda environment:

workflows/syngps_cs1.ipynb
workflows/case_study2.ipynb
workflows/use_case_3_syngps_from_file.ipynb

Post Publication Notes

To view the repository code at the time of publication view the publication branch.

For Contributors

We welcome contributions to the SynGPS and BOYA algorithms! Here's how you can contribute:

1. Create a Feature Branch:

   • Start by creating a personal feature branch (e.g., feat_new_1) from the feature branch.

2. Develop and Test:

   • Implement your feature or fix.
   • Ensure your code is thoroughly tested and works as expected.

3. Submit a Pull Request:

   • Once your code is complete and tested, create a pull request (PR) from your feature branch to the feature branch of the SynGPS repository.

4. Approval and Merge:

   • Approved features will be merged into the main branch.

Thank you for contributing to the SynGPS repository!

License Related Section

This repository contains source code, Jupyter notebook, data and results files which are organized into various subdirectories.

• Source code subdirectories

  src/

• Data and results subdirectory

  data/

• Worklows

  The workflow to reproduce Case Study 3 in the form of Jupyter Notebook can be found at workflows/use_case_3_syngps_from_file.ipynb.

• Source Code License of SynGPS Repository

  The applicable license to source code can be found under filename: src/LICENSE (license type: MIT License). This license is applicable to all files recursively in the source code subdirectories as defined above. The files src/NOTES list source code modules that were utilized and their respective licenses. These modules have their own licenses which might be different from the Source Code License of this repository, and they need to be respected accordingly.

• Data License of SynGPS Repository

  The applicable license to data and results can be found under: data/LICENSE that is a Creative Commons Attribution 4.0 International Public License. This license is applicable to all files recursively in the data and results subdirectory as defined above. The files listed in data/NOTES and plots/NOTES lists input files and resources utilized to perform the experiments and are considered as derivative work of those resources. These input files and resources have their own licenses which might be different from the Data License of this repository, and they need to be respected accordingly. In the same file we also list which results files can be considered as derivative works, and we also list the the respective ascendent data source(s).

• Jupyter Notebook License of SynGPS Repository

  Jupyter Notebboks are special in the sense that they are comprised of source code, but they can also contain embedded data and plot (graph) sections. This duality is resolved via dual-licensing as follows. The code sections of Jupter Notebooks fall under the same license as source codes, i.e. the MIT License src/LICENSEwhereas data and plot sections embedded into the Jupyter Notebooks fall under the same license as data and result files, i.e. Creative Commons Attribution 4.0 International Public License CC-BY 4.0 International License data/LICENSE. Remarks enclosed in the src/NOTES file are also valid for code section of the Jupyter Notebooks. Remarks enclosed in the data/NOTES files are also valid for the embedded data and plots of the Jupyter Notebook files.

• Links to licenses

  • MIT License: https://opensource.org/licenses/MIT

  • Creative Commons Attribution 4.0 International Public License (CC-BY 4.0 International): https://creativecommons.org/licenses/by/4.0/legalcode.txt

  • Creative Commons Attribution-ShareAlike 3.0 Unported License: https://creativecommons.org/licenses/by-sa/3.0/

  • GPL-2 License: https://www.gnu.org/licenses/old-licenses/gpl-2.0.en.html

  • GPL-3 License: https://www.gnu.org/licenses/gpl-3.0.en.html

  • Apache License 2.0: https://www.apache.org/licenses/LICENSE-2.0

  • 3-Clause BSD license: https://opensource.org/licenses/BSD-3-Clause, https://github.com/scikit-learn/scikit-learn/blob/master/COPYING