GNN

A History of Graph Neural Networks in Drug Discovery

Graphs in drug discovery have gone from a quiet background tool to one of the main ways we think about molecules, proteins, and their interactions. This post walks through that story: how the field moved from fingerprints and QSAR to today’s 3D, attention-based graph neural networks operating directly on protein-ligand complexes.

Jun 8, 2026
Point Cloud Classification with Graph Neural Networks Using PyTorch Geometric

A beginner-friendly walkthrough of PyTorch Geometric's point cloud tutorial — covering the Data object, transforms, dynamic graph construction, PointNet++ message passing, and graph-level classification.

Apr 5, 2026
Getting Started with Graph Neural Networks for Protein–Ligand Complexes Using DGL

A practical, beginner-friendly introduction to the Deep Graph Library (DGL) and how to use it to featurize protein–ligand complexes for machine learning in drug discovery.

Apr 3, 2026