metadata

license: unknown
task_categories:
  - tabular-classification
  - graph-ml
  - text-classification
tags:
  - chemistry
  - biology
  - medical
pretty_name: MoleculeNet BBBP
size_categories:
  - 1K<n<10K
configs:
  - config_name: default
    data_files:
      - split: train
        path: bbbp.csv

MoleculeNet BBBP

BBBP (Blood-Brain Barrier Penetration) dataset [1], part of MoleculeNet [2] benchmark. It is intended to be used through scikit-fingerprints library.

The task is to predict blood-brain barrier penetration (barrier permeability) of small drug-like molecules.

Characteristic	Description
Tasks	1
Task type	classification
Total samples	2039
Recommended split	scaffold
Recommended metric	AUROC

References

[1] Ines Filipa Martins et al. "A Bayesian Approach to in Silico Blood-Brain Barrier Penetration Modeling" J. Chem. Inf. Model. 2012, 52, 6, 1686–1697 https://pubs.acs.org/doi/10.1021/ci300124c

[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