SSM-DTA: Breaking the Barriers of Data Scarcity in Drug-Target Affinity Prediction (Briefings in Bioinformatics 2023)

DeepDrugDomain: A versatile Python toolkit for streamlined preprocessing and accurate prediction of drug-target interactions and binding affinities, leveraging deep learning for advancing computational drug discovery.

Implementation of GEFA: Early Fusion Approach in Drug-Target Affinity Prediction

DTITR: End-to-End Drug-Target Binding Affinity Prediction with Transformers

MLT-LE: predicting drug–target binding affinity with multi-task residual neural networks : https://arxiv.org/abs/2209.06274

Drug-target binding affinity counterfactual generation

Explainable Physicochemical Determinants of Protein–Ligand Binding via Non-Covalent Interactions

A Streamlit app for predicting drug-target binding affinity using a trained CNN model. Input SMILES strings and protein sequences for fast and accurate predictions.

Code for experimenting paper "SG-DTA: Stacked Graph Drug-Target binding Affinity prediction"

Undergraduate graduation project. A deep learning method for drug-target affinity prediction.

repository for "BASE: a web service for providing compound-protein binding affinity prediction datasets with reduced similarity bias"

Explainable AI framework for MGraphDTA drug-target affinity prediction model using SHAP, GNNExplainer, and Integrated Gradients

BASE: a web service for providing compound-protein binding affinity prediction datasets with reduced similarity bias

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