{"url":"/dataset/atc-graph","name":"ATC-GRAPH","full_name":null,"description_markdown":"ATC-GRAPH is the most extensive ATC benchmark dataset. All drugs in the benchmarks are linked to their Mol files instead of the SMILES sequences utilized in earlier benchmarks. This shift allows for more precise and detailed modeling and learning. In terms of scale, ATC-GRAPH surpasses Chen-2012 and ATC-SMILES by 36.78% and 16.85%, respectively. Significantly, ATC-GRAPH was curated through a cross-validation process involving multiple resources such as KEGG, PubChem, ChEMBL, ChemSpider, and ChemicalBook. This results in ATC-GRAPH being distinguished by its timeliness and comprehensive coverage across all five levels and drug genres.","description_withheld":null,"homepage":"https://github.com/lookwei/GraphATC","introduced_date":"2025-04-26","introduced_date_note":null,"introduced_by":{"paper":"/paper/graphatc-advancing-multilevel-and-multi-label","title":"GraphATC: advancing multilevel and multi-label anatomical therapeutic chemical classification via atom-level graph learning","first_author":"WengYu Zhang","url":null},"license":null,"modalities":[{"name":"Graphs","url":"/datasets/modality/graphs"},{"name":"Biomedical","url":"/datasets/modality/biomedical"}],"tasks":[{"name":"Drug ATC Classification","url":"/task/drug-atc-classification","datasets_with_task":"/datasets/task/drug-atc-classification"}],"languages":[{"name":"English","url":"/datasets/language/english"}],"variants":["ATC-GRAPH"],"data_loaders":[],"num_papers_in_archive":1,"source":{"archive":"pwc-archive (Hugging Face), CC BY-SA 4.0","snapshot":"2025-07-28"},"benchmarks":[{"leaderboard":"/sota/drug-atc-classification-on-atc-graph","task":"Drug ATC Classification","dataset_variant":"ATC-GRAPH","rows":2,"metrics":["Absolute False","Absolute True","Accuracy","Aiming","Coverage"],"first_row_in_archive_order":{"model":"GraphATC","paper":"/paper/graphatc-advancing-multilevel-and-multi-label","metrics":{"Absolute False":"0.0057","Absolute True":"0.9456","Accuracy":"0.9614","Aiming":"0.9694","Coverage":"0.9688"},"code_links":[{"title":"lookwei/GraphATC","url":"https://github.com/lookwei/GraphATC"}]},"note":"rows are the archive's own order at snapshot; nothing here re-ranks them"}],"papers_with_a_benchmark_row":[{"paper":"/paper/graphatc-advancing-multilevel-and-multi-label","title":"GraphATC: advancing multilevel and multi-label anatomical therapeutic chemical classification via atom-level graph learning","date":"2025-04-26","rows_on_this_dataset":2,"code_links":1,"syntology":null}],"syntology_totals":{"read_at":"2026-09-24T18:15:14+00:00","papers_with_samples":0,"samples_harvested":0,"samples_ran":0,"samples_unverified":0,"pointer_only_for_licence":0,"papers_with_no_sample_that_ran":0,"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."}