Property Prediction Assessment
Toxicity Database System provides machine-learning based property prediction assessment for compounds without recorded toxicity information. The built-in models have passed 10-fold cross-validation and independent test-set validation, showing good robustness and generalization. Model prediction Accuracy exceeds 80%. This system supports risk prediction assessment for hepatotoxicity, nephrotoxicity, carcinogenicity, and mutagenicity.
Molecular Structure Preview
Supported Toxicity Endpoints:
Hepatotoxicity
Nephrotoxicity
Ames Mutagenicity
Human Carcinogenicity
Rat Carcinogenicity
Mouse Carcinogenicity
Rodent Carcinogenicity
Prediction Notes
📊 Prediction Metrics
- Accuracy: >80%
- Cross Validation: 10-fold
- Test Set Validation: Passed
🎯 Confidence Notes
- High Confidence: Highly reliable prediction
- Medium Confidence: Moderately reliable prediction
- Low Confidence: For reference only