license: unknown
task_categories:
- tabular-classification
- graph-ml
- text-classification
tags:
- chemistry
- biology
- medical
pretty_name: MoleculeNet PCBA
size_categories:
- 100K<n<1M
configs:
- config_name: default
data_files:
- split: train
path: pcba.csv
MoleculeNet PCBA
PCBA (PubChem BioAssay) dataset [1], part of MoleculeNet [2] benchmark. It is intended to be used through scikit-fingerprints library.
The task is to predict biological activity against 128 bioassays, generated by high-throughput screening (HTS). All tasks are binary active/non-active.
Note that targets have missing values. Algorithms should be evaluated only on present labels. For training data, you may want to impute them, e.g. with zeros.
| Characteristic | Description |
|---|---|
| Tasks | 128 |
| Task type | multitask classification |
| Total samples | 437929 |
| Recommended split | scaffold |
| Recommended metric | AUPRC, AUROC |
References
[1] Ramsundar, Bharath, et al. "Massively multitask networks for drug discovery" arXiv:1502.02072 (2015) https://arxiv.org/abs/1502.02072
[2] Wu, Zhenqin, et al. "MoleculeNet: a benchmark for molecular machine learning." Chemical Science 9.2 (2018): 513-530 https://pubs.rsc.org/en/content/articlelanding/2018/sc/c7sc02664a