ULCYP: A Multi-task Model for Predicting P450 Inducers Based on Positive-Unlabeled Learning
Abstract
Inducer_Non-agonist_Dataset: Labeled collection of CYP inducers and non-agonists for calibration and validation. Positive-Unlabeled Dataset: Training data for the PU learning framework, containing positives and broad unlabeled metabolism-associated compounds. TestDataset.joblib: The serialized original test set ensuring model reproducibility. Chembl_inducer & Drugbank_inducer: The datasets that contain detailed sources of information. Model file
Fields of Study & Subjects
Computational Drug Discovery Methods
Pharmacogenetics and Drug Metabolism
Machine Learning in Materials Science
Publication details
- Journal / source
- Zenodo (CERN European Organization for Nuclear Research)
- Publication date
- 29 January 2026
- Document type
- Dataset