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Datasets:
scikit-fingerprints
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TDC_caco2_wang

Tasks:
Tabular Classification
Graph Machine Learning
Text Classification
Modalities:
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Formats:
csv
Size:
< 1K
Tags:
chemistry
biology
medical
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TDC Caco-2 Wang

Caco-2 Wang dataset [1], part of TDC [2] benchmark. It is intended to be used through scikit-fingerprints library.

The task is to predict the rate at which drug passes through Caco-2 cells that serve as in vitro simulation of human intestinal tissue.

This dataset is a part of "absorption" subset of ADME tasks.

Characteristic Description
Tasks 1
Task type regression
Total samples 910
Recommended split scaffold
Recommended metric MAE

References

[1] Wang, NN, et al. "ADME Properties Evaluation in Drug Discovery: Prediction of Caco-2 Cell Permeability Using a Combination of NSGA-II and Boosting" Journal of Chemical Information and Modeling 2016 56 (4), 763-773 https://doi.org/10.1021/acs.jcim.5b00642

[2] Huang, Kexin, et al. "Therapeutics Data Commons: Machine Learning Datasets and Tasks for Drug Discovery and Development" Proceedings of Neural Information Processing Systems, NeurIPS Datasets and Benchmarks, 2021 https://openreview.net/forum?id=8nvgnORnoWr

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