Figure 1.

Workflow of the PhosphoPredict approach. Benchmark training/testing datasets were extracted from the Phospho.ELM database after removing sequence redundancy (70% sequence identity) using the CD-HIT program³⁹. After feature selection using mRMR and statistical analysis of over-represented and under-represented feature terms using hypergeometric tests, significant sequence, structural, and functional features were extracted and used as inputs to train RF classifiers. Classifier performance was assessed using randomized 5-fold cross-validation and independent tests.