Code for ICLR 2024 (Spotlight) paper "MAPE-PPI: Towards Effective and Efficient Protein-Protein Interaction Prediction via Microenvironment-Aware Protein Embedding"

A Graph Neural Network Model for prediction of the effectiveness of a drug on a given cancer cell lines

Structured Multi-task Learning for Molecular Property Prediction, AISTATS'22 (https://proceedings.mlr.press/v151/liu22e.html)

Ensemble learning with graph neural networks for disease module discovery and classification

Python 3 library implementing a number of topological clustering techniques used on protein-protein interaction networks.

Embeddings to Network Alignment - align biological networks between two species

This study presents a deep learning-based framework for predicting PPIs between human and gut bacterial proteins using structural data.

Graph representation for system biology networks and the reduction of them for machine learning purposes

Splitpea Python package for building rewired protein-protein interaction networks from alternative splicing events

Evaluate a strategy for predicting cancer-related proteins in PPI networks.