license: unknown
task_categories:
- tabular-classification
- graph-ml
- text-classification
tags:
- chemistry
- biology
- medical
pretty_name: TDC Caco-2 Wang
size_categories:
- n<1K
configs:
- config_name: default
data_files:
- split: train
path: tdc_caco2_wang.csv
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