[Bioinformatics 2021] This is the repo for the paper `SumGNN: Multi-typed Drug Interaction Prediction via Efficient Knowledge Graph Summarization'.

Drug Similarity Integration Through Attentive Multi-view Graph Auto-Encoders (IJCAI 2018)

Emerging Drug Interaction Prediction Enabled by Flow-based Graph Neural Network with Biomedical Network. Nature Computational Science. 2023.

Bi-Level Graph Neural Networks for Drug-Drug Interaction Prediction. ICML 2020 Graph Representation Learning and Beyond (GRL+) Workshop

Drug-Drug Interaction Predicting by Neural Network Using Integrated Similarity

Drug-Drug Interaction Prediction on a Biomedical Literature Knowledge Graph

ISCMF: Integrated Similarity-Constrained Matrix Factorization for Drug-Drug Interaction Prediction

Novel deep learning model for more accurate prediction of drug-drug interaction effects

Towards Interpretable Drug-Drug Interaction Prediction: A Graph-Based Approach with Molecular and Network-Level Explanations

MVA-DDI: Interpretable attention network with multi-view learning for drug-drug interaction prediction (2023 BIBM)

Code for my Master thesis on "Intelligent Drug-Drug Interaction Extraction: A Natural Language Processing Approach to Biomedical Text Analysis".

Official Implementation of ADEP paper.

DrugDoseFinder: A Python tool that uses fuzzy name matching and RDF graphs to search for drugs and retrieve their dosage information. Designed for accurate querying and easy integration with personalized medical RDF datasets.

Graph Embedding Evaluation / Code and Datasets for "Graph Embedding on Biomedical Networks: Methods, Applications, and Evaluations"

Deep drug-drug interaction discovery and demystification (D4)

A DNN model for predicting adverse drug-drug and drug-food interactions (Top 7 in Northern Region, GDGoC Hackathon 2025)

PyTorch code for an effective way of making a Molecular Graph Dataset in Torch Geometric involving a pair of graphs from chemical SMILE strings

This is the repository for the AI4ALL Ignite Class 13B project on predicting adverse effects of drug interactions.

Scripts for the research paper "SF-Rx: A Multi-output Deep Neural Network-Based Framework Predicting Drug-Drug Interaction under Realistic Conditions for Safe Prescription"