Code for the models in the paper: Predicting Aqueous Solubility of Organic Molecules Using Deep Learning Models with Varied Molecular Representations (https://pubs.acs.org/doi/full/10.1021/acsomega.2c00642)
- Download data from https://figshare.com/s/542fb80e65742746603c and save it as data.csv in the ./data folder
- Generate Pybel coordinates and MDM features by running create_data.py at the ./data folder
- To train MDM, GNN, SMI and SCH models run train.py at ./mdm, ./gnn, ./smi and ./sch folderes respectively.
- To make predictions use predict.ipynb files at each model folders.
Best models used to obtain the results in the paper are included in each model folders (mdm_paper.h5, gnn_paper.pt, smi_paper.h5, sch_paper.pt)
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