Molecular Networks

DataFunSummit

Nov 26, 2021 · Artificial Intelligence

Graph Machine Learning for Molecular Networks: Challenges, Methods, and Applications in Biomedicine

This talk by a Stanford PhD student explores how graph neural networks can be adapted for molecular and biomedical networks, discusses the limitations of standard GNNs, introduces novel methods such as SkipGNN and G‑Meta, and demonstrates their use for drug‑drug interaction prediction, hypothesis generation, and treatment discovery with few‑shot learning.