| --- |
| 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. |
