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---
license: mit
task_categories:
- tabular-regression
- graph-ml
- text-classification
tags:
- chemistry
- biology
- medical
pretty_name: Biogen ADME Solubility
size_categories:
- 1K<n<10K
configs:
- config_name: default
data_files:
- split: train
path: solubility.csv
---
# Biogen ADME Solubility
Biogen_ADME_Solubility dataset from the Biogen ADME benchmark [[1]](#1). It is intended to be used through
[scikit-fingerprints](https://github.com/scikit-fingerprints/scikit-fingerprints) library.
The task is to predict log10 of aqueous solubility at pH 6.8 (in ug/mL) of molecules.
| **Characteristic** | **Description** |
|:------------------:|:-----------------:|
| Tasks | 1 |
| Task type | regression |
| Total samples | 2173 |
| Recommended split | time |
| Recommended metric | MAE |
## References
<a id="1">[1]</a>
Fang, Cheng, et al.
"Prospective Validation of Machine Learning Algorithms for Absorption, Distribution, Metabolism, and Excretion Prediction: An Industrial Perspective"
J. Chem. Inf. Model. 2023, 63, 11, 3263-3274
https://doi.org/10.1021/acs.jcim.3c00160