Update README.md

README.md

@@ -1,3 +1,110 @@
 ---
-license: mit
+annotations_creators:
+- machine-generated
+language_creators:
+- machine-generated
+license:
+- mit
+multilinguality:
+- monolingual
+pretty_name: pcba_686978
+size_categories:
+- 100K<n<1M
+source_datasets: []
+tags:
+- bio
+- bio-chem
+- molnet
+- molecule-net
+- biophysics
+task_categories:
+- other
+task_ids: []
 ---
+
+# Dataset Card for pcba_686978
+
+## 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
+
+`pcba_686978` is a dataset included in [MoleculeNet](https://moleculenet.org/). PubChem BioAssay (PCBA) is a database consisting of biological activities of small molecules generated by high-throughput screening. We have chosen one of the larger tasks (ID 686978) as described in https://par.nsf.gov/servlets/purl/10168888.
+
+## 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`: the binary label binding results
+
+### 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.