Create README.md

README.md

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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