QSAR Toxicity Dataset with Molecular Descriptors

A quantitative structure-activity relationship dataset for predicting chemical toxicity, featuring molecular descriptors. It is hosted on OpenML and categorized for QSAR and toxicology applications. The original creator and specific temporal coverage are not provided.

Use Cases

• Predict chemical toxicity endpoints from molecular descriptor features using regression or classification models.
• Train machine learning models to identify structural features correlated with toxicological activity.
• Benchmark QSAR model performance for toxicity prediction against established datasets.
• Analyze relationships between specific molecular descriptors and toxicological outcomes.

Strengths

• Dataset is structured for quantitative structure-activity relationship modeling, a standard approach in computational toxicology.
• Categorized with specific platform tags including Qsar, Molecular Descriptors, and Toxicology, indicating a clear domain focus.

Limitations

• The total number of chemical compounds, rows, and specific descriptor columns is unknown.
• The absence of sample data, column names, and license information limits immediate usability and reproducibility.

Provenance

Source

OpenML