Python-based-polymer-unit-recognition-script-PURS-2.0

1.High throughput identification of polymer-units(repeating units) from SMILES codes of polymers

2.GNN models based on polymer-unit - Model acceleration and interpretative enhancement

Installation

1.Use only the recognition function

conda create -n PURS
conda activate PURS
pip install -r requirements.yml

2.Interpretable GNNS based on polymer-units--PU-gn-exp

gn-exp is developed as the baseline model.Please follow the link "https://github.com/baldassarreFe/graph-network-explainability" to install gn-exp first and then refer to Readme in the PU-gn-exp folder.

3.Prediction model based on polymer-unit--PU-MPNN

mol-MPNN is developed as the baseline model.Please follow the link "https://github.com/seokhokang/mol_mpnn" to install mol-MPNN first and then refer to Readme in the PU-MPNN folder.