Fig. 1: A random forest model for predicting biallelic TP53 samples from gene expression profile.

A Data composition for model training and validation. B Receiver operating characteristic (ROC) curves. C Precision–recall curves. D Fivefold cross-validation results measure the performance of the models with various sets of differentially expressed genes.