Tox21

The Tox21 dataset is a benchmark that contains data on various toxicological endpoints used to evaluate the predictive performance of models in assessing molecular toxicity.

Papers using Tox21 (9)

What Molecular Structure Cannot Tell Us: A Taxonomy of Explainability Gaps in GNN-Based Drug Toxicity Prediction2026Combining Deep Learning and Explainable AI for Toxicity Prediction of Chemical Compounds2025 · 1 citesDo Larger Models Really Win in Drug Discovery? A Benchmark Assessment of Model Scaling in AI-Driven Molecular Property and Activity Prediction2026Budget-Sensitive Discovery Scoring: A Formally Verified Framework for Evaluating AI-Guided Scientific Selection2026Task-Specific Sparse Feature Masks for Molecular Toxicity Prediction with Chemical Language Models2025Measuring AI Progress in Drug Discovery: A Reproducible Leaderboard for the Tox21 Challenge2025MolKD: Distilling Cross-Modal Knowledge in Chemical Reactions for Molecular Property Prediction2023 · 3 citesStructure to Property: Chemical Element Embeddings and a Deep Learning Approach for Accurate Prediction of Chemical Properties2023 · 3 citesShape is (almost) all!: Persistent homology features (PHFs) are an information rich input for efficient molecular machine learning2023