Statistics
1. Dataset description
The total number of compounds, including actives and inactives in the training and test sets for the respective models are provided in the table below.
2. Performance evaluation using MACCS fingerprints
To validate all the models in SuperCypPred webserver we have used preformance measures like accuracy, sensitivity, specificity, ROC-AUC and F measure for both 10 fold cross-validation and external validation.
Below, the preformance measures of the best performing model (sampling methods) using MACCS fingerprints for each CYP (both for cross-validation and external set) are reported.
3.Performance evaluation using Morgan fingerprints
To validate all the models in SuperCypPred web server we have used preformance measures like accuracy, sensitivity, specificity, ROC-AUC and F measure for both 10fold cross-validation and external validation.
Below, the preformance measures of the best performing model using Morgan fingerprints for each CYP (both for cross-validation and external set) are reported.
