MoseDTI

The official implementation of AAAI25 paper "Blend the Separated: Mixture of Synergistic Experts for Data-Scarcity Drug-Target Interaction Prediction".

Read the paper

Usage

1. Unzip the esm.tar.gz to your anaconda envs directory and activate the esm environment.
2. Execute the split_data.py to split the data as cross-validation splits.
3. Train model from a pretrained KGE model:

   python kge/std_main.py --dataset ago_10shots_0 --device 0 --load_kge_model 2024-04-28_10_01_40.24__kgeSLHstd_main.py--save--dataset__a-10--device__6--gate__kge.pth
   

   You can also train the KGE model yourself without the --load_kge_model argument. You can also save the intermediate models with the --save and load them with the --load* arguments.

If there are any issues or cooperation intentions, please contact [email protected].