{"url":"/dataset/mutagenicity","name":"Mutagenicity","full_name":null,"description_markdown":"**Mutagenicity** is a chemical compound dataset of drugs, which can be categorized into two classes: mutagen and non-mutagen.\n\nSource: [Hierarchical Graph Pooling with Structure Learning](https://arxiv.org/abs/1911.05954)","description_withheld":null,"homepage":"https://ls11-www.cs.tu-dortmund.de/staff/morris/graphkerneldatasets","introduced_date":null,"introduced_date_note":null,"introduced_by":null,"license":null,"modalities":[{"name":"Graphs","url":"/datasets/modality/graphs"}],"tasks":[{"name":"Graph Classification","url":"/task/graph-classification","datasets_with_task":"/datasets/task/graph-classification"}],"languages":[],"variants":["Mutagenicity"],"data_loaders":[],"num_papers_in_archive":13,"source":{"archive":"pwc-archive (Hugging Face), CC BY-SA 4.0","snapshot":"2025-07-28"},"benchmarks":[{"leaderboard":"/sota/graph-classification-on-mutagenicity","task":"Graph Classification","dataset_variant":"Mutagenicity","rows":5,"metrics":["Accuracy"],"first_row_in_archive_order":{"model":"TREE-G","paper":"/paper/graph-trees-with-attention","metrics":{"Accuracy":"83"},"code_links":[{"title":"mayabechlerspeicher/tree-g","url":"https://github.com/mayabechlerspeicher/tree-g"}]},"note":"rows are the archive's own order at snapshot; nothing here re-ranks them"}],"papers_with_a_benchmark_row":[{"paper":"/paper/pre-training-graph-neural-networks-on","title":"Pre-training Graph Neural Networks on Molecules by Using Subgraph-Conditioned Graph Information Bottleneck","date":"2025-02-20","rows_on_this_dataset":1,"code_links":1,"syntology":null},{"paper":"/paper/graph-trees-with-attention","title":"TREE-G: Decision Trees Contesting Graph Neural Networks","date":"2022-07-06","rows_on_this_dataset":1,"code_links":1,"syntology":{"read_at":"2026-09-24T18:15:14+00:00","samples_harvested":10,"samples_ran":0,"samples_unverified":10,"pointer_only_for_licence":0,"claim":"Per-sample execution on synthesized fixtures; not a correctness claim."}},{"paper":"/paper/maximum-entropy-weighted-independent-set","title":"Maximum Entropy Weighted Independent Set Pooling for Graph Neural Networks","date":"2021-07-03","rows_on_this_dataset":1,"code_links":1,"syntology":{"read_at":"2026-09-24T18:15:14+00:00","samples_harvested":2,"samples_ran":2,"samples_unverified":0,"pointer_only_for_licence":2,"claim":"Per-sample execution on synthesized fixtures; not a correctness claim."}},{"paper":"/paper/hierarchical-graph-pooling-with-structure","title":"Hierarchical Graph Pooling with Structure Learning","date":"2019-11-14","rows_on_this_dataset":1,"code_links":3,"syntology":null},{"paper":"/paper/hierarchical-representation-learning-in-graph","title":"Hierarchical Representation Learning in Graph Neural Networks with Node Decimation Pooling","date":"2019-10-24","rows_on_this_dataset":1,"code_links":1,"syntology":{"read_at":"2026-09-24T18:15:14+00:00","samples_harvested":1,"samples_ran":1,"samples_unverified":0,"pointer_only_for_licence":1,"claim":"Per-sample execution on synthesized fixtures; not a correctness claim."}}],"syntology_totals":{"read_at":"2026-09-24T18:15:14+00:00","papers_with_samples":3,"samples_harvested":13,"samples_ran":3,"samples_unverified":10,"pointer_only_for_licence":3,"papers_with_no_sample_that_ran":1,"note":"the per-paper counts above, summed; not a rate"},"papers_note":"The archive never published its papers-using-dataset list; these are papers with a leaderboard row on this dataset's benchmarks."}