Readings for "A Unified View of Relational Deep Learning for Drug Pair Scoring." (IJCAI 2022)

Madrigal: Multimodal AI predicts clinical outcomes of drug combinations from preclinical data

An R package for Bayesian semi-parametric modelling of in-vitro drug combination experiments

Graph convolutional neural network for multirelational link prediction

This repository contains the graph neural networks built with PyTorch Geometric that are used in my bachelor thesis: "Drug-Drug GNN for Drug Combination Prediction and Explanations".

Code implementation of the paper "A Deep Neural Network for Predicting Synergistic Drug Combinations on Cancer"

Enhancing Drug Combination Safety: A Comprehensive Solution

A statistical framework for detecting significant drug combination synergies in cancer. By leveraging tissue-specific reference null distributions across multiple synergy metrics, we compute empirical p-values to standardize synergy detection, uncover novel interactions, and enable rigorous evaluation of drug combinations.

Code for Null Models used in Sinzger et al. (2019) Scientific Reports, 9, 3002

An R package for Bayesian semi-parametric modelling of in-vitro drug combination experiments