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- license: mit
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
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+ annotations_creators:
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+ - machine-generated
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+ language_creators:
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+ - machine-generated
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+ license:
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+ - mit
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+ multilinguality:
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+ - monolingual
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+ pretty_name: bbbp
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+ size_categories:
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+ - 1K<n<10K
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+ source_datasets: []
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+ tags:
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+ - bio
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+ - bio-chem
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+ - molnet
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+ - molecule-net
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+ - biophysics
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+ task_categories:
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+ - other
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+ task_ids: []
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  ---
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+
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+ # Dataset Card for bbbp
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+
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+ ## Table of Contents
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+ - [Table of Contents](#table-of-contents)
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+ - [Dataset Description](#dataset-description)
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+ - [Dataset Summary](#dataset-summary)
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+ - [Supported Tasks and Leaderboards](#supported-tasks-and-leaderboards)
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+ - [Languages](#languages)
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+ - [Dataset Structure](#dataset-structure)
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+ - [Data Instances](#data-instances)
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+ - [Data Fields](#data-fields)
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+ - [Data Splits](#data-splits)
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+ - [Dataset Creation](#dataset-creation)
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+ - [Curation Rationale](#curation-rationale)
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+ - [Source Data](#source-data)
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+ - [Annotations](#annotations)
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+ - [Personal and Sensitive Information](#personal-and-sensitive-information)
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+ - [Considerations for Using the Data](#considerations-for-using-the-data)
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+ - [Social Impact of Dataset](#social-impact-of-dataset)
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+ - [Discussion of Biases](#discussion-of-biases)
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+ - [Other Known Limitations](#other-known-limitations)
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+ - [Additional Information](#additional-information)
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+ - [Dataset Curators](#dataset-curators)
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+ - [Licensing Information](#licensing-information)
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+ - [Citation Information](#citation-information)
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+ - [Contributions](#contributions)
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+
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+ ## Dataset Description
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+
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+ - **Homepage: https://moleculenet.org/**
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+ - **Repository: https://github.com/deepchem/deepchem/tree/master**
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+ - **Paper: https://arxiv.org/abs/1703.00564**
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+
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+ ### Dataset Summary
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+
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+ `bbbp` is a dataset included in [MoleculeNet](https://moleculenet.org/). This dataset has binary labels of blood-brain barrier penetration(permeability).
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+
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+ ## Dataset Structure
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+
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+ ### Data Fields
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+
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+ Each split contains
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+
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+ * `smiles`: the [SMILES](https://en.wikipedia.org/wiki/Simplified_molecular-input_line-entry_system) representation of a molecule
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+ * `selfies`: the [SELFIES](https://github.com/aspuru-guzik-group/selfies) representation of a molecule
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+ * `target`: blood-brain barrier penetration(permeability)
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+
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+ ### Data Splits
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+
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+ The dataset is split into an 80/10/10 train/valid/test split using scaffold split.
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+
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+ ### Source Data
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+
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+ #### Initial Data Collection and Normalization
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+
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+ Data was originially generated by the Pande Group at Standford
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+
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+ ### Licensing Information
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+
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+ This dataset was originally released under an MIT license
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+
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+ ### Citation Information
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+
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+ ```
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+ @misc{https://doi.org/10.48550/arxiv.1703.00564,
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+ doi = {10.48550/ARXIV.1703.00564},
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+
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+ url = {https://arxiv.org/abs/1703.00564},
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+
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+ 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},
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+
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+ 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},
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+
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+ title = {MoleculeNet: A Benchmark for Molecular Machine Learning},
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+
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+ publisher = {arXiv},
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+
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+ year = {2017},
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+
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+ copyright = {arXiv.org perpetual, non-exclusive license}
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+ }
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+ ```
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+
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+ ### Contributions
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+
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+ Thanks to [@zanussbaum](https://github.com/zanussbaum) for adding this dataset.