Datasets:
Tasks:
Other
Multilinguality:
monolingual
Size Categories:
1K<n<10K
Language Creators:
machine-generated
Annotations Creators:
machine-generated
ArXiv:
License:
| annotations_creators: | |
| - machine-generated | |
| language_creators: | |
| - machine-generated | |
| license: | |
| - mit | |
| multilinguality: | |
| - monolingual | |
| pretty_name: tox21_srp53 | |
| size_categories: | |
| - 1K<n<10K | |
| source_datasets: [] | |
| tags: | |
| - bio | |
| - bio-chem | |
| - molnet | |
| - molecule-net | |
| - biophysics | |
| task_categories: | |
| - other | |
| task_ids: [] | |
| dataset_info: | |
| features: | |
| - name: smiles | |
| dtype: string | |
| - name: selfies | |
| dtype: string | |
| - name: target | |
| dtype: | |
| class_label: | |
| names: | |
| '0': '0' | |
| '1': '1' | |
| splits: | |
| - name: train | |
| num_bytes: 1055437 | |
| num_examples: 6264 | |
| - name: test | |
| num_bytes: 223704 | |
| num_examples: 784 | |
| - name: validation | |
| num_bytes: 224047 | |
| num_examples: 783 | |
| download_size: 451728 | |
| dataset_size: 1503188 | |
| # Dataset Card for tox21_srp53 | |
| ## Table of Contents | |
| - [Table of Contents](#table-of-contents) | |
| - [Dataset Description](#dataset-description) | |
| - [Dataset Summary](#dataset-summary) | |
| - [Supported Tasks and Leaderboards](#supported-tasks-and-leaderboards) | |
| - [Languages](#languages) | |
| - [Dataset Structure](#dataset-structure) | |
| - [Data Instances](#data-instances) | |
| - [Data Fields](#data-fields) | |
| - [Data Splits](#data-splits) | |
| - [Dataset Creation](#dataset-creation) | |
| - [Curation Rationale](#curation-rationale) | |
| - [Source Data](#source-data) | |
| - [Annotations](#annotations) | |
| - [Personal and Sensitive Information](#personal-and-sensitive-information) | |
| - [Considerations for Using the Data](#considerations-for-using-the-data) | |
| - [Social Impact of Dataset](#social-impact-of-dataset) | |
| - [Discussion of Biases](#discussion-of-biases) | |
| - [Other Known Limitations](#other-known-limitations) | |
| - [Additional Information](#additional-information) | |
| - [Dataset Curators](#dataset-curators) | |
| - [Licensing Information](#licensing-information) | |
| - [Citation Information](#citation-information) | |
| - [Contributions](#contributions) | |
| ## Dataset Description | |
| - **Homepage: https://moleculenet.org/** | |
| - **Repository: https://github.com/deepchem/deepchem/tree/master** | |
| - **Paper: https://arxiv.org/abs/1703.00564** | |
| ### Dataset Summary | |
| `tox21_srp53` is a dataset included in [MoleculeNet](https://moleculenet.org/). It is the p53 stress-response pathway activation (SR-p53) task from Tox21. | |
| ## Dataset Structure | |
| ### Data Fields | |
| Each split contains | |
| * `smiles`: the [SMILES](https://en.wikipedia.org/wiki/Simplified_molecular-input_line-entry_system) representation of a molecule | |
| * `selfies`: the [SELFIES](https://github.com/aspuru-guzik-group/selfies) representation of a molecule | |
| * `target`: clinical trial toxicity (or absence of toxicity) | |
| ### Data Splits | |
| The dataset is split into an 80/10/10 train/valid/test split using scaffold split. | |
| ### Source Data | |
| #### Initial Data Collection and Normalization | |
| Data was originially generated by the Pande Group at Standford | |
| ### Licensing Information | |
| This dataset was originally released under an MIT license | |
| ### Citation Information | |
| ``` | |
| @misc{https://doi.org/10.48550/arxiv.1703.00564, | |
| doi = {10.48550/ARXIV.1703.00564}, | |
| url = {https://arxiv.org/abs/1703.00564}, | |
| author = {Wu, Zhenqin and Ramsundar, Bharath and Feinberg, Evan N. and Gomes, Joseph and Geniesse, Caleb and Pappu, Aneesh S. and Leswing, Karl and Pande, Vijay}, | |
| keywords = {Machine Learning (cs.LG), Chemical Physics (physics.chem-ph), Machine Learning (stat.ML), FOS: Computer and information sciences, FOS: Computer and information sciences, FOS: Physical sciences, FOS: Physical sciences}, | |
| title = {MoleculeNet: A Benchmark for Molecular Machine Learning}, | |
| publisher = {arXiv}, | |
| year = {2017}, | |
| copyright = {arXiv.org perpetual, non-exclusive license} | |
| } | |
| ``` | |
| ### Contributions | |
| Thanks to [@zanussbaum](https://github.com/zanussbaum) for adding this dataset. |