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Quantifying Pairwise Chemical Similarity for Polymers

This repository supports the following manuscript.

Jiale Shi, Nathan J. Rebello, Dylan Walsh, Weizhong Zou, Michael E. Deagen, Bruno Salomao Leao, Debra J. Audus, Bradley D. Olsen, "Quantifying Pairwise Chemical Similarity for Polymers", Macromolecules. 2023. Link

In this work, we proposed a reliable method to quantitatively calculate the pairwise chemical similarity score for polymers, where the earth mover’s distance (EMD) is utilized to calculate the similarity of the repeat units and end groups, while the graph edit distance (GED) is used to calculate the similarity of the topology. These three values then are combined to yield an overall pairwise chemical similarity score for polymers.

The repository is intended for the following use cases:

  • Illustrate key ideas from the manuscript Method section including earth mover's distance and graph edit distance
  • Allow for full reproducibility of the data in the manuscript

Running the code

Running notebooks in Google Colab

If you are interested in running one or more notebooks in Google Colab, first click on the relevant links below.

Notebook for Main Text

Notebook for Supporting Information

Then open the colab badge Open In Colab in the notebook.

It will open a colab notebook. Then you can run the notebook as normal. All the required libraries and functions are present in the colab notebook.

Contact

Jiale Shi, PhD

Postdoctoral Associate

Department of Chemical Engineering

Massachusetts Institute of Technology (MIT)

Email: [email protected]

GithubID: shijiale0609

Please cite our work and star this repo if it helps your research

How to cite

@article{shi2023quantifying,
author = {Shi, Jiale and Rebello, Nathan J. and Walsh, Dylan and Zou, Weizhong and Deagen, Michael E. and Leao, Bruno Salomao and Audus, Debra J. and Olsen, Bradley D.},
title = {Quantifying Pairwise Similarity for Complex Polymers},
journal = {Macromolecules},
year = {2023},
doi = {10.1021/acs.macromol.3c00761},
URL = {https://doi.org/10.1021/acs.macromol.3c00761},
eprint = {https://doi.org/10.1021/acs.macromol.3c00761}
}