{"url":"/dataset/atom3d","name":"ATOM3D","full_name":null,"description_markdown":"**ATOM3D** is a unified collection of datasets concerning the three-dimensional structure of biomolecules, including proteins, small molecules, and nucleic acids. These datasets are specifically designed to provide a benchmark for machine learning methods which operate on 3D molecular structure, and represent a variety of important structural, functional, and engineering tasks. All datasets are provided in a standardized format along with a Python package containing processing code, utilities, models, and dataloaders for common machine learning frameworks such as PyTorch. ATOM3D is designed to be a living database, where datasets are updated and tasks are added as the field progresses.\r\n\r\nDescription from: [https://www.atom3d.ai/](https://www.atom3d.ai/)","description_withheld":null,"homepage":"https://www.atom3d.ai/","introduced_date":"2020-12-07","introduced_date_note":null,"introduced_by":{"paper":"/paper/atom3d-tasks-on-molecules-in-three-dimensions-1","title":"ATOM3D: Tasks On Molecules in Three Dimensions","first_author":"Raphael J. L. Townshend","url":null},"license":null,"modalities":[{"name":"Biomedical","url":"/datasets/modality/biomedical"}],"tasks":[{"name":"Atom3D benchmark","url":"/task/atom3d-benchmark","datasets_with_task":"/datasets/task/atom3d-benchmark"}],"languages":[],"variants":["ATOM3D"],"data_loaders":[],"num_papers_in_archive":23,"source":{"archive":"pwc-archive (Hugging Face), CC BY-SA 4.0","snapshot":"2025-07-28"},"benchmarks":[],"papers_with_a_benchmark_row":[],"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."}