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---
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]](#1), part of TDC [[2]](#2) benchmark. It is intended to be used through
[scikit-fingerprints](https://github.com/scikit-fingerprints/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
<a id="1">[1]</a>
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
<a id="2">[2]</a>
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 |