An official Molecule Transformer Drug Target Interaction (MT-DTI) model

ANN4EEG is a convolutional neural network toolkit for EEG-mediated drug-target interaction prediction. This approach for drug-target interaction prediction can explain the mechanisms underlying complicated drug actions, as it allows the identification of similarities in the mechanisms of action and effects of psychotropic drugs.

Velodrome combines semi-supervised learning and out-of-distribution generalization (domain generalization) for drug response prediction and pharmacogenomics

Drug-Drug Interaction Prediction by Neural Network Using Integrated Similarity

A Deep Learning Toolkit for DTI, Drug Property, PPI, DDI, Protein Function Prediction (Bioinformatics)

Deep Learning based Drug Response Predication with public Omics datasets

TransformerCPI: Improving compound–protein interaction prediction by sequence-based deep learning with self-attention mechanism and label reversal experiments(BIOINFORMATICS 2020)

The Platform can predict whether the protien sequence and the drug SMILES will be interact with each other. Requires training before implementation